Big Data in Healthcare, Bioinformatics and Precision Medicine

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Applied Sciences applsci	2.5	5.3	2011	17.8 Days	CHF 2400
Biology biology	3.6	5.7	2012	16.1 Days	CHF 2700
Genes genes	2.8	5.2	2010	16.3 Days	CHF 2600
Journal of Personalized Medicine jpm	3.0	4.1	2011	16.7 Days	CHF 2600
Cancers cancers	4.5	8.0	2009	16.3 Days	CHF 2900

16 pages, 317 KiB

Open AccessArticle

LIFEHOUSE’s Functional Nutrition Examination (Physical Exam, Anthropometrics, and Selected Biomarkers) Informs Personalized Wellness Interventions

by Michael Stone, Dan Lukaczer, Christopher R. D’Adamo, Nicole Dotson, Andrey Volkov, Deanna Minich, Dina Metti, Michelle Leary, Monique Class, Malisa Carullo, Erik Lundquist, Brent Eck, Jose Ordovas, Joseph Lamb and Jeffrey Bland

J. Pers. Med. 2023, 13(4), 594; https://doi.org/10.3390/jpm13040594 - 28 Mar 2023

Viewed by 3350

Abstract

Each individual has a unique and interacting set of genetic, lifestyle, and environmental factors that are reflected in their physical exam and laboratory biomarkers and significantly impact their experience of health. Patterns of nutrient deficiency signs and biomarker levels below health-promoting thresholds have [...] Read more.

Each individual has a unique and interacting set of genetic, lifestyle, and environmental factors that are reflected in their physical exam and laboratory biomarkers and significantly impact their experience of health. Patterns of nutrient deficiency signs and biomarker levels below health-promoting thresholds have been identified in national nutrition surveys. However, identifying these patterns remains a challenge in clinical medicine for many reasons, including clinician training and education, clinical time restraints, and the belief that these signs are both rare and recognizable only in cases of severe nutritional deficiencies. With an increased interest in prevention and limited resources for comprehensive diagnostic evaluations, a functional nutrition evaluation may augment patient-centered screening evaluations and personalized wellness programs. During LIFEHOUSE, we have documented physical exam, anthropometric, and biomarker findings that may increase the recognition of these wellness-challenging patterns in a population of 369 adult employees working in two occupational areas: administrative/sales and manufacturing/warehouse. Distinct and significant physical exam differences and constellations of biomarker abnormalities were identified. We present these patterns of physical exam findings, anthropometrics, and advanced biomarkers to assist clinicians in diagnostic and therapeutic interventions that may stem the loss of function that precedes the development of the non-communicable chronic diseases of aging. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

17 pages, 3781 KiB

Open AccessArticle

Use of Sample Entropy to Assess Sub-Maximal Physical Load for Avoiding Exercise-Induced Cardiac Fatigue

by Yu-Han Lai, Po-Hsun Huang and Tzu-Chien Hsiao

Appl. Sci. 2023, 13(6), 3813; https://doi.org/10.3390/app13063813 - 16 Mar 2023

Cited by 2 | Viewed by 1768

Abstract

Sub-maximal physical load (sub-max) training is optimal for athletes. However, few methods can directly assess whether training is sub-max. Therefore, this study aimed to identify metrics that could assess sub-max training by predicting maximal physical load, helping athletes to avoid the risks associated [...] Read more.

Sub-maximal physical load (sub-max) training is optimal for athletes. However, few methods can directly assess whether training is sub-max. Therefore, this study aimed to identify metrics that could assess sub-max training by predicting maximal physical load, helping athletes to avoid the risks associated with maximal training. Physiological data were collected from 30 participants in a bicycle incremental exercise experiment, including the R-R interval (RR), stroke volume (SV), breath-to-breath interval (BB), and breathing rate (BR). Sample Entropy (SampEn) analysis was used to assess the complexity of the physiological data. BR increased with exercise time but could not be used to identify the sub-max stage; however, SampEn BB could effectively identify the sub-max stage (p < 0.05), as could the novel indicators SampEn SV and cardiac output (p < 0.01). This study also identified the threshold value of each SampEn value in sub-max, which can be used as a sports science indicator to assess the load of athletes. The results suggest that SampEn-based indicators can be used to assess sub-max and maximal physical load. These findings can be used as a guide for quantitative exercise healthcare. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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15 pages, 6592 KiB

Open AccessArticle

Immunocyte Infiltration Analysis and Immunohistochemistry Identify EVL as a Potential Prognostic Biomarker for Pancreatic Cancer

by Yan Du, Lin Zhu, Xin Li, Huaqing Shi, Wenkai Jiang and Wence Zhou

J. Pers. Med. 2023, 13(3), 433; https://doi.org/10.3390/jpm13030433 - 28 Feb 2023

Viewed by 1913

Abstract

Ena-VASP-like (EVL), a member of the Enabled/vasodilator stimulated phosphoprotein family, is functionally expressed in various cancers. This study explored the prognostic value and potential mechanism of EVL in pancreatic cancer (PC). RNA-seq obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus [...] Read more.

Ena-VASP-like (EVL), a member of the Enabled/vasodilator stimulated phosphoprotein family, is functionally expressed in various cancers. This study explored the prognostic value and potential mechanism of EVL in pancreatic cancer (PC). RNA-seq obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used to evaluate EVL expression differences, and clinical samples were collected for validation. The prognostic value of EVL was evaluated by survival data obtained from TCGA and clinical samples. The biological pathways involved in EVL were evaluated by functional enrichment analysis such as GO, KEGG, and GSEA. We used immune infiltration analysis to estimate the correlation between EVL and tumor-infiltrating immune cells (TICs). The expression of EVL is down-regulated in PC tissues, which is an independent factor affecting survival time. Survival analysis suggested EVL-high expression was associated with good prognosis in PC patients. The results of the enrichment analysis suggested that the biological function of EVL was closely related to the immune mechanism. Tumor immune infiltration analysis showed that high expression of EVL was accompanied by high levels of immune infiltration. Furthermore, EVL was strongly correlated with the content of immune cells such as CD8+ T cells, B cells, regulatory T cells, CD4+ Tem cells, and follicular Th cells. EVL is a potential independent prognostic marker and immunotherapy target for PC. Mechanistically, EVL may affect the prognosis by extensively promoting immune cell infiltration, including strengthening the anti-tumor immune response of CD8+ T cells. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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10 pages, 262 KiB

Open AccessArticle

Clinical Evolution of Acute Vestibular Syndrome: Longitudinal Retrospective Analysis of Epidemiological Data and Prognostic Factors for Recovery

by Pasqualina M. Picciotti, Roberta Anzivino, Jacopo Galli, Francesco Franceschi, Guido Conti, Benedetta Simeoni and Marcello Covino

J. Pers. Med. 2023, 13(3), 407; https://doi.org/10.3390/jpm13030407 - 24 Feb 2023

Viewed by 1616

Abstract

We evaluated the clinical features of patients admitted to the ED with acute vertigo, verifying symptoms after one month and one year to establish epidemiological factors and predictors of resolution. We reviewed 233 records of patients admitted to ED for acute vertigo (125 [...] Read more.

We evaluated the clinical features of patients admitted to the ED with acute vertigo, verifying symptoms after one month and one year to establish epidemiological factors and predictors of resolution. We reviewed 233 records of patients admitted to ED for acute vertigo (125 F and 85 M, mean age 56.12 years). We analyzed the correlation between time of resolution (at one month and one year) and symptoms duration (subjective and/or objective vertigo, instability, cervical pain, audiological, neurological, and neurovegetative symptoms), comorbidities, and therapies, the result of the clinical and instrumental vestibular examination. Resolution of acute vertigo occurred in 81.1%, while persistence of vertigo one year after ED access was reported in 18.8%. There were 135 patients who recovered in one month. The presence of instability, auditory and neurovegetative symptoms, and neck pain represents a significant factor for recovery within one year. Age over 65 and a history of hypertension are associated with a worst recovery. Patients with spontaneous Nystagmus or positive HIT showed a significant difference in symptoms recovery within one month and one year. Presence of positional Nystagmus represents a positive prognostic factor. Our findings emphasize the importance of clinical evaluation of the acute vertigo, helping the clinicians to define central or peripheral diagnosis and predict the resolution of vertigo. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

17 pages, 7087 KiB

Open AccessArticle

Comprehensive Analysis of Necroptosis Landscape in Skin Cutaneous Melanoma for Appealing its Implications in Prognosis Estimation and Microenvironment Status

by Xiaoying Cao, Jiaming He, An Chen, Jianhua Ran, Jing Li, Dilong Chen and Hengshu Zhang

J. Pers. Med. 2023, 13(2), 245; https://doi.org/10.3390/jpm13020245 - 29 Jan 2023

Cited by 1 | Viewed by 2498

Abstract

Purpose: Due to poor prognosis and immunotherapy failure of skin cutaneous melanoma (SKCM), this study sought to find necroptosis-related biomarkers to predict prognosis and improve the situation with predicted immunotherapy drugs. Experimental Design: The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression Program [...] Read more.

Purpose: Due to poor prognosis and immunotherapy failure of skin cutaneous melanoma (SKCM), this study sought to find necroptosis-related biomarkers to predict prognosis and improve the situation with predicted immunotherapy drugs. Experimental Design: The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression Program (GTEx) database were utilized to recognize the differential necroptosis-related genes (NRGs). Univariate Cox (uni-Cox) and least absolute shrinkage and selection operator (LASSO) Cox analysis were utilized for prognostic signature establishment. The signature was verified in the internal cohort. To assess the signature’s prediction performance, the area under the curve (AUC) of receiver operating characteristic (ROC) curves, Kaplan-Meier (K-M) analyses, multivariate Cox (multi-Cox) regression, nomogram, and calibration curves were performed. The molecular and immunological aspects were also reviewed using single-sample gene set enrichment analysis (ssGSEA). Cluster analysis was performed to identify the different types of SKCM. Finally, the expression of the signature gene was verified by immunohistochemical staining. Results: On basis of the 67 NRGs, 4 necroptosis-related genes (FASLG, PLK1, EGFR, and TNFRSF21) were constructed to predict SKCM prognosis. The area’s 1-, 3-, and 5-year OS under the AUC curve was 0.673, 0.649, and 0.677, respectively. High-risk individuals had significantly lower overall survival (OS) compared to low-risk patients. Immunological status and tumor cell infiltration in high-risk groups were significantly lower, indicating an immune system that was suppressed. In addition, hot and cold tumors could be obtained by cluster analysis, which is helpful for accurate treatment. Cluster 1 was considered a hot tumor and more susceptible to immunotherapy. Immunohistochemical results were consistent with positive and negative regulation of coefficients in signature. Conclusion: The results of this finding supported that NRGs could predict prognosis and help make a distinction between the cold and hot tumors for improving personalized therapy for SKCM. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 943 KiB

Open AccessArticle

Marital Status of Never Married with Rey Auditory Verbal Learning Test Cognition Performance Is Associated with Mild Cognitive Impairment

by Yohn Jairo Parra Bautista, Samia S. Messeha, Carlos Theran, Richard Aló, Clement Yedjou, Victor Adankai, Samuel Babatunde and on behalf of the Alzheimer’s Disease Prediction of Longitudinal Evolution (TADPOLE)

Appl. Sci. 2023, 13(3), 1656; https://doi.org/10.3390/app13031656 - 28 Jan 2023

Cited by 3 | Viewed by 2267

Abstract

A small number of robust studies have explored the association between cognitive tests and marital status levels of mild cognitive impairment (MCI) patients using the TADPOLE dataset. Rey Auditory Verbal Learning Test (RAVLT) cognition performance combined with marital status levels is associated with [...] Read more.

A small number of robust studies have explored the association between cognitive tests and marital status levels of mild cognitive impairment (MCI) patients using the TADPOLE dataset. Rey Auditory Verbal Learning Test (RAVLT) cognition performance combined with marital status levels is associated with increased odds of MCI than either RAVLT in isolation. The cross-sectional association between RAVLT performance in immediate response, learning, forgetting, and perception of forgetting with marital status and MCI was evaluated using TADPOLE data. We included participants with MCI and normal cognition in our study. Based on our logistic regression model, four RAVLT subgroups are associated with MCI (low and high response performance, immediate response with learning, immediate response with learning and forgetting, immediate response with learning, forgetting, and perception of forgetting). We adjusted models for sex, age, race, marital status, education, ethnicity, APOE4 genotype, hippocampus, whole brain, ventricles, and ICV. A mean age of 77/67 years was observed in the sample (n = 6560), 44% of participants were females, and 58% had mild cognitive impairment. Subgroups whose ages are 61 to 70 (OR 0.26, 95% CI 0.15–0.45) and older (OR 0.07, 95% CI 0.04–0.12), as well as race: black/African American (OR 0.13, 95% CI 0.03–0.52), multiple races (OR 0.05, 95% CI 0.01–0.24), and never married (OR 0.2, 95% CI 0.12–0.34) were negatively associated with immediate response and forgetting subgroup tests. There is a need for studies that evaluate other cognitive tests in the TADPOLE dataset with missing data as a predictive tool that aligns with the factors associated with MCI. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 1829 KiB

Open AccessCommunication

GDReBase: A Knowledge Base for Relations between Human Gut Microbes and Diseases Based on Deep Learning

by Haolei Xu, Xin Li, Xiaolong Dai, Chunhao Liu, Dongxiao Wang, Chenghao Zheng, Kaihua Liu, Sitong Liu, Yufei Zeng, Ziyang Song, Shanzhu Cui and Yongdong Xu

Appl. Sci. 2023, 13(3), 1614; https://doi.org/10.3390/app13031614 - 27 Jan 2023

Viewed by 2237

Abstract

Gut microbes play a prominent role in many aspects of human health, as seen through the increasing number of related studies. The accumulation of intestinal-flora-related studies enables us to better understand the various relationships between human gut microbes and other factors that affect [...] Read more.

Gut microbes play a prominent role in many aspects of human health, as seen through the increasing number of related studies. The accumulation of intestinal-flora-related studies enables us to better understand the various relationships between human gut microbes and other factors that affect the human body. However, the existing database does not meet the requirements of scientists to browse or retrieve the latest and most comprehensive published data. Thus, a knowledge base containing data related to gut microbes with updates occurring in real time would be highly valuable. We present a knowledge base of consistently curated relationships between human gut microbes and disease. By continuously and automatically collecting papers published in mainstream journals and using deep learning and NLP methods for entity relationship identification, GDReBase has now integrated 3674 diseases, 687 microbes, 7068 relationships, and 13,553 pieces of evidence from 518,286 papers, a figure that will continue to grow. GDReBase is a convenient and comprehensive resource for gut microbiology research and can be accessed free of charge. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 694 KiB

Open AccessArticle

Carbohydrate, Lipid, and Apolipoprotein Biomarkers in Blood and Risk of Thyroid Cancer: Findings from the AMORIS Cohort

by Xue Xiao, Yi Huang, Fetemeh Sadeghi, Maria Feychting, Niklas Hammar, Fang Fang, Zhe Zhang and Qianwei Liu

Cancers 2023, 15(2), 520; https://doi.org/10.3390/cancers15020520 - 14 Jan 2023

Cited by 6 | Viewed by 2367

Abstract

Background: Previous studies have examined the link between blood metabolic biomarkers and risk of thyroid cancer, with inconclusive results. We performed a cohort study based on the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort, including 561,388 individuals undergoing health examinations during 1985–1996 with a [...] Read more.

Background: Previous studies have examined the link between blood metabolic biomarkers and risk of thyroid cancer, with inconclusive results. We performed a cohort study based on the Swedish Apolipoprotein-Related Mortality Risk (AMORIS) Cohort, including 561,388 individuals undergoing health examinations during 1985–1996 with a follow-up of >30 years. Methods: Newly diagnosed cases of thyroid cancer were identified from the Swedish Cancer Register. We assessed the associations of nine blood biomarkers of carbohydrate, lipid, and apolipoprotein metabolism measured at the time of health examinations with the subsequent risk of thyroid cancer and demonstrated the temporal trend of these biomarkers during the 30 years before diagnosis of thyroid cancer. Results: After multivariable adjustment, there was a lower risk of thyroid cancer, per standard deviation increase in total cholesterol (TC; HR 0.91; 95%CI 0.82–0.99) and HDL-C (HR 0.86; 95%CI 0.75–0.99). During the 20 to 30 years before diagnosis, patients with thyroid cancer, as a group, demonstrated constantly lower levels of TC and HDL-C, compared to controls. Further, patients with thyroid cancer demonstrated declining levels of these biomarkers during the ten years before diagnosis, whereas controls demonstrated stable or increasing levels. Conclusions: Taken together, we found blood levels of TC and HDL-C to be associated with the risk of thyroid cancer and that there was a declining level of metabolic biomarkers during the 10 years before diagnosis of thyroid cancer. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 373 KiB

Open AccessArticle

Support Interval for Two-Sample Summary Data-Based Mendelian Randomization

by Kai Wang

Genes 2023, 14(1), 211; https://doi.org/10.3390/genes14010211 - 13 Jan 2023

Cited by 2 | Viewed by 2254

Abstract

The summary-data-based Mendelian randomization (SMR) method is gaining popularity in estimating the causal effect of an exposure on an outcome. In practice, the instrument SNP is often selected from the genome-wide association study (GWAS) on the exposure but no correction is made for [...] Read more.

The summary-data-based Mendelian randomization (SMR) method is gaining popularity in estimating the causal effect of an exposure on an outcome. In practice, the instrument SNP is often selected from the genome-wide association study (GWAS) on the exposure but no correction is made for such selection in downstream analysis, leading to a biased estimate of the effect size and invalid inference. We address this issue by using the likelihood derived from the sampling distribution of the estimated SNP effects in the exposure GWAS and the outcome GWAS. This likelihood takes into account how the instrument SNPs are selected. Since the effective sample size is 1, the asymptotic theory does not apply. We use a support for a profile likelihood as an interval estimate of the causal effect. Simulation studies indicate that this support has robust coverage while the confidence interval implied by the SMR method has lower-than-nominal coverage. Furthermore, the variance of the two-stage least squares estimate of the causal effect is shown to be the same as the variance used for SMR for one-sample data when there is no selection. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)
(This article belongs to the Section Bioinformatics)

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23 pages, 8357 KiB

Open AccessArticle

Multiomics Analysis Reveals Cuproptosis-Related Signature for Evaluating Prognosis and Immunotherapy Efficacy in Colorectal Cancer

by Rong He, Heping Zhang, Huaxin Zhao, Xiaolan Yin, Jingyi Lu, Cheng Gu, Jie Gao and Qing Xu

Cancers 2023, 15(2), 387; https://doi.org/10.3390/cancers15020387 - 6 Jan 2023

Cited by 11 | Viewed by 3468

Abstract

Cuproptosis is a copper-induced form of mitochondrial cell death which is engaged in the proliferation and migration of a variety of tumors. Nevertheless, the role of cuproptosis in tumor microenvironment (TME) remodeling and antitumor therapy is still poorly understood. We characterized two diverse [...] Read more.

Cuproptosis is a copper-induced form of mitochondrial cell death which is engaged in the proliferation and migration of a variety of tumors. Nevertheless, the role of cuproptosis in tumor microenvironment (TME) remodeling and antitumor therapy is still poorly understood. We characterized two diverse cuproptosis-associated molecular isoforms in CRC which exhibit distinct prognostic and TME characteristics. Subsequently, we constructed a cuproptosis-associated prognostic model containing five genes and divided the patients into a high CPS-score group and a low CPS-score group. Univariate and multivariate Cox analyses showed that the CPS score could be used as an independent prognostic factor. The nomogram, and its consequent calibration curves, indicated that this prognostic signature had good predictive power for CRC. The analysis of single-cell sequencing data showed the significant expression of HES4 and SPHK1 in various immune and stromal (including fibroblasts) cells. Further studies showed that tumor mutational burden (TMB), high microsatellite instability (MSI-H) ratio, immune checkpoint blockade (ICB), and human leukocyte antigen (HLA) gene expression all positively correlated with the CPS score, predicting a better reaction to immunotherapy in high CPS-core patients. The CPS score constructed from cuproptosis subtypes can be used as a predictive tool to evaluate the prognosis of CRC patients and their response to immunotherapy. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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9 pages, 635 KiB

Open AccessArticle

Oral Health and Risk of Retinal Vascular Occlusions: A Nationwide Cohort Study

by Yoonkyung Chang, Sung-Hee Kim, Jimin Jeon, Tae-Jin Song and Jinkwon Kim

J. Pers. Med. 2023, 13(1), 121; https://doi.org/10.3390/jpm13010121 - 5 Jan 2023

Cited by 3 | Viewed by 1771

Abstract

Retinal vascular occlusions are a common cause of visual loss. The association between oral health and the risk of retinal vascular occlusions remains unknown. We investigated whether oral health was associated with the risk of retinal vascular occlusions. We conducted a retrospective cohort [...] Read more.

Retinal vascular occlusions are a common cause of visual loss. The association between oral health and the risk of retinal vascular occlusions remains unknown. We investigated whether oral health was associated with the risk of retinal vascular occlusions. We conducted a retrospective cohort study including 138,484 participants who completed a national health screening program with an oral health examination from the National Health Insurance Service-National Health Screening Cohort (NHIS-HEALS) 2002–2015. Oral health markers, such as the presence of periodontitis, tooth loss, and dental caries, and the frequency of daily tooth brushing, were evaluated. The primary outcome was the occurrence of retinal vascular occlusions up to December 2015. In total, 2533 participants developed retinal vascular occlusions (215 with retinal artery occlusion, 1686 with retinal vein occlusion, 632 with unspecified retinal vascular occlusion). In the multivariable Cox regression analysis, periodontitis was an independent risk factor for retinal vascular occlusions (adjusted hazard ratio: 1.18; 95% confidence interval: 1.02–1.36; p = 0.024). Frequent tooth brushing was negatively associated with the risk of retinal vascular occlusions (adjusted hazard ratio: 0.89; 95% confidence interval: 0.80–0.98; p = 0.022). Improving oral hygiene may contribute to the attenuation of the risk of retinal vascular occlusions. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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15 pages, 1964 KiB

Open AccessArticle

Web-Based Dynamic Nomograms for Predicting Overall Survival and Cancer-Specific Survival in Breast Cancer Patients with Lung Metastases

by Kangtao Wang, Yuqiang Li, Dan Wang and Zhongyi Zhou

J. Pers. Med. 2023, 13(1), 43; https://doi.org/10.3390/jpm13010043 - 26 Dec 2022

Cited by 5 | Viewed by 2345

Abstract

Background: 60–70% of patients who die from breast cancer have lung metastases. However, there is a lack of readily available tools for accurate risk stratification in patients with breast cancer lung metastases (BCLM). Therefore, a web-based dynamic nomogram was developed for BCLM to [...] Read more.

Background: 60–70% of patients who die from breast cancer have lung metastases. However, there is a lack of readily available tools for accurate risk stratification in patients with breast cancer lung metastases (BCLM). Therefore, a web-based dynamic nomogram was developed for BCLM to quickly, accurately, and intuitively assess overall and cancer-specific survival rates. Methods: Patients diagnosed with BCLM between 2004 and 2016 were extracted from the Surveillance, Epidemiology, and Final Results (SEER) database. After excluding incomplete data, all patients were randomly assigned to training and validation cohorts (2:1). Patients’ basic clinical information, detailed pathological staging and treatment information, and sociological information were included in further analysis. Nomograms were constructed following the evaluations of the Cox regression model and verified using the concordance index (C-index), calibration curves, time-dependent receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Web-based dynamic nomograms were published online. Results: 3916 breast cancer patients with lung metastases were identified from the SEER database. Based on multivariate Cox regression analysis, overall survival (OS) and cancer-specific survival (CSS) are significantly correlated with 13 variables: age, marital status, race, grade, T stage, surgery, chemotherapy, bone metastatic, brain metastatic, liver metastatic, estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2). These are included in the construction of the nomogram of OS and CSS. The time-dependent receiver operating characteristic curve, decision curve analysis, consistency index, and calibration curve prove the distinct advantages of the nomogram. Conclusions: Our web-based dynamic nomogram effectively integrates patient molecular subtype and sociodemographic characteristics with clinical characteristics and guidance and can be easily used. ER-Negative should receive attention in diagnosing and treating BCLM. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 4757 KiB

Open AccessArticle

Identification of Potential microRNA Panels for Male Non-Small Cell Lung Cancer Identification Using Microarray Datasets and Bioinformatics Methods

by Antonia Haranguș, Raduly Lajos, Livia Budisan, Oana Zanoaga, Cristina Ciocan, Cecilia Bica, Radu Pirlog, Ioan Simon, Marioara Simon, Cornelia Braicu and Ioana Berindan-Neagoe

J. Pers. Med. 2022, 12(12), 2056; https://doi.org/10.3390/jpm12122056 - 13 Dec 2022

Cited by 7 | Viewed by 2301

Abstract

Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We [...] Read more.

Background: Non-small cell lung cancer (NSCLC) is still one of the types of cancer with the highest death rates. MicroRNAs (miRNAs) play essential roles in NSCLC development. This study evaluates miRNA expression patterns and specific mechanisms in male patients with NSCLC. Methods: We report an integrated microarray analysis of miRNAs for eight matched samples of males with NSCLC compared to the study of public datasets of males with NSCLC from TCGA, followed by qRT-PCR validation. Results: For the TCGA dataset, we identified 385 overexpressed and 75 underexpressed miRNAs. Our cohort identified 54 overexpressed and 77 underexpressed miRNAs, considering a fold-change (FC) of ±1.5 and p < 0.05 as the cutoff value. The common miRNA signature consisted of eight overexpressed and nine underexpressed miRNAs. Validation was performed using qRT-PCR on the tissue samples for miR-183-3p and miR-34c-5p and on plasma samples for miR-34c-5p. We also created mRNA-miRNA regulatory networks to identify critical molecules, revealing NSCLC signaling pathways related to underexpressed and overexpressed transcripts. The genes targeted by these transcripts were correlated with overall survival. Conclusions: miRNAs and some of their target genes could play essential roles in investigating the mechanisms involved in NSCLC evolution and provide opportunities to identify potential therapeutic targets. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 885 KiB

Open AccessArticle

A Body Shape Index (ABSI) as a Variant of Conicity Index Not Affected by the Obesity Paradox: A Cross-Sectional Study Using Arterial Stiffness Parameter

by Daiji Nagayama, Kentaro Fujishiro, Yasuhiro Watanabe, Takashi Yamaguchi, Kenji Suzuki, Atsuhito Saiki and Kohji Shirai

J. Pers. Med. 2022, 12(12), 2014; https://doi.org/10.3390/jpm12122014 - 5 Dec 2022

Cited by 12 | Viewed by 2471

Abstract

A body shape index (ABSI) is an abdominal obesity index developed based on epidemiological statistics and designed to correlate minimally with body mass index (BMI). We examined the approximation between ABSI and other abdominal obesity indices based on biophysical concepts. The cross-sectional data [...] Read more.

A body shape index (ABSI) is an abdominal obesity index developed based on epidemiological statistics and designed to correlate minimally with body mass index (BMI). We examined the approximation between ABSI and other abdominal obesity indices based on biophysical concepts. The cross-sectional data from 62,514 Japanese urban residents were analyzed. Body adiposity indices comprising BMI, waist circumference (WC), ABSI, conicity index (CI), waist-to-height ratio (WHtR), and WC/BMI ratio were examined. ABSI and CI more strongly correlated with age and arterial stiffness assessed by cardio-ankle vascular index (CAVI) compared to the other indices. The discriminative power for high CAVI (≥9.0) was the strongest for ABSI followed by CI and other indices, in that order. The range and distribution of WC corresponding to the cutoff of ABSI (0.0801), or CI (1.23) seemed reasonable. The correlation between ABSI and CI was the strongest compared to any other combination of indices. CI correlated moderately with BMI, whereas ABSI correlated minimally with BMI. ABSI correlates strongly and approximates closely with CI. Hence, ABSI may be considered to reflect the degree of body shape change from cylindricity to conicity and is currently the only abdominal obesity index not affected by the obesity paradox. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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10 pages, 926 KiB

Open AccessArticle

Acute Pancreatitis Increases the Risk of Gastrointestinal Cancer in Type 2 Diabetic Patients: A Korean Nationwide Cohort Study

by Jin Ho Choi, Woo Hyun Paik, Dong Kee Jang, Min Kyu Kim, Ji Kon Ryu, Yong-Tae Kim, Kyungdo Han and Sang Hyub Lee

Cancers 2022, 14(22), 5696; https://doi.org/10.3390/cancers14225696 - 20 Nov 2022

Cited by 1 | Viewed by 2261

Abstract

The association between acute pancreatitis (AP) and gastrointestinal cancers in diabetic patients is currently not well understood. The study aim was to investigate the association between AP and gastrointestinal cancers in diabetic patients. Data from the Korean National Health Insurance Service database were [...] Read more.

The association between acute pancreatitis (AP) and gastrointestinal cancers in diabetic patients is currently not well understood. The study aim was to investigate the association between AP and gastrointestinal cancers in diabetic patients. Data from the Korean National Health Insurance Service database were analyzed. Participants with diabetes who underwent a health examination between 2009 and 2012 were followed up till December 2018. The primary outcome was the occurrence of gastrointestinal cancer. A total of 2,263,184 patients were included in the final analysis. Patients with a history of AP (n = 2390) were found to have a significantly higher risk of gastrointestinal cancer, except for esophageal cancer, as follows: gastric cancer (aHR = 1.637, 95% CI: 1.323–2.025), colorectal cancer (aHR = 2.183, 95% CI: 1.899–2.51), liver cancer (aHR = 2.216, 95% CI: 1.874–2.621), pancreatic cancer (aHR = 4.558, 95% CI: 4.078–5.095), bile duct cancer (aHR = 3.996, 95% CI: 3.091–5.269), and gallbladder cancer (aHR = 2.445, 95% CI: 1.459–4.099). The history of AP is associated with the increased risk of gastrointestinal cancer in diabetic patients. It is necessary to investigate the history of AP and more actively recommend screening for gastrointestinal cancers in such patients. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 5685 KiB

Open AccessArticle

Identification and Validation of UPF1 as a Novel Prognostic Biomarker in Renal Clear Cell Carcinoma

by Chun Wu, Hongmu Li, Wuguang Chang, Leqi Zhong, Lin Zhang, Zhesheng Wen and Shijuan Mai

Genes 2022, 13(11), 2166; https://doi.org/10.3390/genes13112166 - 20 Nov 2022

Viewed by 3188

Abstract

Background: Up frameshift protein 1 (UPF1) is a key component of nonsense-mediated mRNA decay (NMD) of mRNA containing premature termination codons (PTCs). The dysregulation of UPF1 has been reported in various cancers. However, the expression profile of UPF1 and its clinical significance in [...] Read more.

Background: Up frameshift protein 1 (UPF1) is a key component of nonsense-mediated mRNA decay (NMD) of mRNA containing premature termination codons (PTCs). The dysregulation of UPF1 has been reported in various cancers. However, the expression profile of UPF1 and its clinical significance in clear cell renal cell carcinoma (ccRCC) remains unclear. Methods: In order to detect UPF1 expression in ccRCC and its relationship with the clinical features of ccRCC, bulk RNA sequencing data were analyzed from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and ArrayExpress databases. The impact of UPF1 on the immune microenvironment of ccRCC was evaluated by multiple immune scoring algorithms to identify the cell groups that typically express UPF1 using ccRCC single cell sequencing (scRNA) data. In addition, genes co-expressed with UPF1 were identified by the weighted gene correlation network analysis (WGCNA), followed by KEGG and Reactome enrichment analysis. A series of functional experiments were performed to assess the roles of UPF1 in renal cancer cells. Finally, pan-cancer analysis of UPF1 was also performed. Results: Compared with normal tissues, the expression levels of UPF1 mRNA and protein in tumor tissues of ccRCC patients decreased significantly. In addition, patients with low expression of UPF1 had a worse prognosis. Analysis of the immune microenvironment indicated that UPF1 immune cell infiltration was closely related and the ccRCC scRNA-seq data identified that UPF1 was mainly expressed in macrophages. WGCNA analysis suggested that the functions of co-expressed genes are mainly enriched in cell proliferation and cellular processes. Experimental tests showed that knockdown of UPF1 can promote the invasion, migration and proliferation of ccRCC cells. Lastly, pan-cancer analysis revealed that UPF1 disorders were closely associated with various cancer outcomes. Conclusions: UPF1 may play a tumor suppressive role in ccRCC and modulate the immune microenvironment. The loss of UPF1 can predict the prognosis of ccRCC, making it a promising biomarker and providing a new reference for prevention and treatment. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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8 pages, 417 KiB

Open AccessArticle

Comparison of Glucose Lowering Efficacy of Human GLP-1 Agonist in Taiwan Type 2 Diabetes Patients after Switching from DPP-4 Inhibitor Use or Non-Use

by Chia-Jen Tsai and Cheng-Feng Tsao

J. Pers. Med. 2022, 12(11), 1915; https://doi.org/10.3390/jpm12111915 - 16 Nov 2022

Cited by 2 | Viewed by 2057

Abstract

To determine the efficacy of glucose control in type 2 diabetes patients who switch from dipeptidyl peptidase-4 (DPP-4) inhibitors use or non-use to GLP-1 receptor agonists (GLP-1 RAs). We conducted a cohort study using data from the Chang Gung Research Database. Patients aged [...] Read more.

To determine the efficacy of glucose control in type 2 diabetes patients who switch from dipeptidyl peptidase-4 (DPP-4) inhibitors use or non-use to GLP-1 receptor agonists (GLP-1 RAs). We conducted a cohort study using data from the Chang Gung Research Database. Patients aged ≥18 years using newly initiated GLP-1 RAs between 1 January 2009, and 31 December 2016, were included. Cox proportional hazards models were used to adjust for treatment selection bias. The primary outcome was changes in the glycated hemoglobin (HbA1c) level. The HbA1c level fell substantially after initiating GLP-1 RAs in DPP-4 inhibitor users and nonusers. A mean HbA1c reduction of −0.42% was found in patients who received DPP-4 inhibitors. Those who were DPP-4 inhibitor nonusers had a reduction in HbA1c of −0.99%. The degree of reduction in HbA1c was significantly greater in patients who were DPP-4 inhibitor nonusers (p value < 0.01), compared to the DPP-4 inhibitor users. In routine care, DPP-4 inhibitor nonusers had better efficacy in glucose control than DPP-4 inhibitor users after switching to a GLP-1 agonist. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 1485 KiB

Open AccessCase Report

Ehlers-Danlos: A Literature Review and Case Report in a Colombian Woman with Multiple Comorbidities

by María José Fajardo-Jiménez, Johanna A. Tejada-Moreno, Alejandro Mejía-García, Andrés Villegas-Lanau, Wildeman Zapata-Builes, Jorge E. Restrepo, Gina P. Cuartas and Juan C. Hernandez

Genes 2022, 13(11), 2118; https://doi.org/10.3390/genes13112118 - 15 Nov 2022

Cited by 3 | Viewed by 3517

Abstract

Ehlers-Danlos syndromes (EDS) are a heterogeneous group of genetically transmitted connective tissue disorders that directly affect collagen synthesis, with a broad range of symptoms. Case presentation: This study presents a clinical case of a Colombian woman with myopathic EDS and multiple comorbidities taking [...] Read more.

Ehlers-Danlos syndromes (EDS) are a heterogeneous group of genetically transmitted connective tissue disorders that directly affect collagen synthesis, with a broad range of symptoms. Case presentation: This study presents a clinical case of a Colombian woman with myopathic EDS and multiple comorbidities taking 40 years of medical history to make the right diagnosis. This article also presents a review of the current literature on EDS, not only to remind the syndrome but also to help the clinician correctly identify symptoms of this diverse syndrome. Conclusion: A multidisciplinary approach to the diagnosis of the patient, including clinical and molecular analysis, and neuropsychological and psychological assessment, is important to improve the treatment choice and the outcome prediction of the patients. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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21 pages, 9281 KiB

Open AccessArticle

Bi-EB: Empirical Bayesian Biclustering for Multi-Omics Data Integration Pattern Identification among Species

by Aida Yazdanparast, Lang Li, Chi Zhang and Lijun Cheng

Genes 2022, 13(11), 1982; https://doi.org/10.3390/genes13111982 - 30 Oct 2022

Cited by 3 | Viewed by 2138

Abstract

Although several biclustering algorithms have been studied, few are used for cross-pattern identification across species using multi-omics data mining. A fast empirical Bayesian biclustering (Bi-EB) algorithm is developed to detect the patterns shared from both integrated omics data and between species. The Bi-EB [...] Read more.

Although several biclustering algorithms have been studied, few are used for cross-pattern identification across species using multi-omics data mining. A fast empirical Bayesian biclustering (Bi-EB) algorithm is developed to detect the patterns shared from both integrated omics data and between species. The Bi-EB algorithm addresses the clinical critical translational question using the bioinformatics strategy, which addresses how modules of genotype variation associated with phenotype from cancer cell screening data can be identified and how these findings can be directly translated to a cancer patient subpopulation. Empirical Bayesian probabilistic interpretation and ratio strategy are proposed in Bi-EB for the first time to detect the pairwise regulation patterns among species and variations in multiple omics on a gene level, such as proteins and mRNA. An expectation–maximization (EM) optimal algorithm is used to extract the foreground co-current variations out of its background noise data by adjusting parameters with bicluster membership probability threshold Ac; and the bicluster average probability p. Three simulation experiments and two real biology mRNA and protein data analyses conducted on the well-known Cancer Genomics Atlas (TCGA) and The Cancer Cell Line Encyclopedia (CCLE) verify that the proposed Bi-EB algorithm can significantly improve the clustering recovery and relevance accuracy, outperforming the other seven biclustering methods—Cheng and Church (CC), xMOTIFs, BiMax, Plaid, Spectral, FABIA, and QUBIC—with a recovery score of 0.98 and a relevance score of 0.99. At the same time, the Bi-EB algorithm is used to determine shared the causality patterns of mRNA to the protein between patients and cancer cells in TCGA and CCLE breast cancer. The clinically well-known treatment target protein module estrogen receptor (ER), ER (p118), AR, BCL2, cyclin E1, and IGFBP2 are identified in accordance with their mRNA expression variations in the luminal-like subtype. Ten genes, including CCNB1, CDH1, KDR, RAB25, PRKCA, etc., found which can maintain the high accordance of mRNA–protein for both breast cancer patients and cell lines in basal-like subtypes for the first time. Bi-EB provides a useful biclustering analysis tool to discover the cross patterns hidden both in multiple data matrixes (omics) and species. The implementation of the Bi-EB method in the clinical setting will have a direct impact on administrating translational research based on the cancer cell screening guidance. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 3538 KiB

Open AccessArticle

Gene Regulatory Network Characterization of Gastric Cancer’s Histological Subtypes: Distinctive Biological and Clinically Relevant Master Regulators

by Sabino Russi, Luigi Marano, Simona Laurino, Giovanni Calice, Dario Scala, Graziella Marino, Alessandro Sgambato, Pellegrino Mazzone, Ludovico Carbone, Giuliana Napolitano, Franco Roviello, Geppino Falco and Pietro Zoppoli

Cancers 2022, 14(19), 4961; https://doi.org/10.3390/cancers14194961 - 10 Oct 2022

Cited by 5 | Viewed by 2758

Abstract

Gastric cancer (GC) molecular heterogeneity represents a major determinant for clinical outcomes, and although new molecular classifications have been introduced, they are not easy to translate from bench to bedside. We explored the data from GC public databases by performing differential gene expression [...] Read more.

Gastric cancer (GC) molecular heterogeneity represents a major determinant for clinical outcomes, and although new molecular classifications have been introduced, they are not easy to translate from bench to bedside. We explored the data from GC public databases by performing differential gene expression analysis (DEGs) and gene network reconstruction to identify master regulators (MRs), as well as a gene set analysis (GSA) to reveal their biological features. Moreover, we evaluated the association of MRs with clinicopathological parameters. According to the GSA, the Diffuse group was characterized by an epithelial-mesenchymal transition (EMT) and inflammatory response, while the Intestinal group was associated with a cell cycle and drug resistance pathways. In particular, the regulons of Diffuse MRs, such as Vgll3 and Ciita, overlapped with the EMT and interferon-gamma response, while the regulons Top2a and Foxm1 were shared with the cell cycle pathways in the Intestinal group. We also found a strict association between MR activity and several clinicopathological features, such as survival. Our approach led to the identification of genes and pathways differentially regulated in the Intestinal and Diffuse GC histotypes, highlighting biologically interesting MRs and subnetworks associated with clinical features and prognosis, suggesting putative actionable candidates. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 2766 KiB

Open AccessArticle

Bioinformatics and Experimental Analyses Reveal MAP4K4 as a Potential Marker for Gastric Cancer

by Junping Zhang, Xiaoping Cai, Weifeng Cui and Zheng Wei

Genes 2022, 13(10), 1786; https://doi.org/10.3390/genes13101786 - 3 Oct 2022

Cited by 2 | Viewed by 2712

Abstract

Background: Gastric cancer remains the most prevalent and highly lethal disease worldwide. MAP4K4, a member of Ste20, plays an important role in various pathologies, including cancer. However, its role in gastric cancer is not yet fully elucidated. Therefore, this study aims to determine [...] Read more.

Background: Gastric cancer remains the most prevalent and highly lethal disease worldwide. MAP4K4, a member of Ste20, plays an important role in various pathologies, including cancer. However, its role in gastric cancer is not yet fully elucidated. Therefore, this study aims to determine the tumor-promoting role of MAP4K4 in gastric cancer and whether it can be used as a new and reliable biomarker to predict the prognosis of gastric cancer. For this purpose, we divide the samples into high- and low-expression groups according to the expression level of MAP4K4. The association of MAP4K4 expression with prognosis is assessed using the Kaplan–Meier survival analysis. Furthermore, immune infiltration analysis using ESTIMATE is conducted to evaluate the tumor immune scores of the samples. Results: The findings reveal a significantly higher expression of MAP4K4 in tumor samples than in adjacent samples. The high-expression group was significantly enriched in tumor-related pathways, such as the PI3K-Akt signaling pathway. In addition, immune infiltration analysis revealed a positive correlation between immune scores and MAP4K4 expression. We also observed that miRNAs, such as miR-192-3p (R = −0.317, p-value 3.111 × 10⁻⁹), miR-33b-5p (R= −0.238, p-value 1.166 × 10⁻⁵), and miR-582-3p (R = −0.214, p-value 8.430 × 10⁻⁵), had potential negative regulatory effects on MAP4K4. Moreover, we identified several transcription factors, ubiquitinated proteins, and interacting proteins that might regulate MAP4K4. The relationship between MAP4K4 and DNA methylation was also identified. Finally, we verified the high expression of MAP4K4 and its effect on promoting cancer. Conclusion: MAP4K4 might be closely related to gastric cancer’s progression, invasion, and metastasis. Its high expression negatively impacts the prognosis of gastric cancer patients. This suggests MAP4K4 as an important prognostic factor for gastric cancer and could be regarded as a new potential prognostic detection and therapeutic target. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 662 KiB

Open AccessArticle

Association between A Family History of Colorectal Cancer and the Risk of Colorectal Cancer: A Nationwide Population-Based Study

by Yoon Suk Jung, Huiyeon Song, Mai Thi Xuan Tran, Boyoung Park and Chang Mo Moon

J. Pers. Med. 2022, 12(10), 1566; https://doi.org/10.3390/jpm12101566 - 23 Sep 2022

Cited by 1 | Viewed by 1857

Abstract

Large-scale Asian studies on this topic are lacking. We evaluated the CRC risk associated with family history in the Korean population. We analyzed the data of participants aged ≥40 years who underwent national cancer screening between 2013 and 2014. During a mean follow-up [...] Read more.

Large-scale Asian studies on this topic are lacking. We evaluated the CRC risk associated with family history in the Korean population. We analyzed the data of participants aged ≥40 years who underwent national cancer screening between 2013 and 2014. During a mean follow-up of 4.7 ± 0.8 years, 0.43% of the 292,467 participants with family history and 0.28% of the 1,169,868 participants without family history developed CRC. Participants with a family history in any FDR, parents only, and siblings only had a higher risk of CRC than those without family history; adjusted hazard ratios (HRs) were 1.53, 1.46, and 1.61, respectively. Participants with a family history comprising both parents and siblings had an even higher risk of CRC than those without a family history (HR, 2.34). The HRs for CRC in the 40–49, 50–59, 60–69, 70–79, and ≥80 age groups with family history were 1.72, 1.74, 1.50, 1.30, and 0.78, respectively (p < 0.001). A family history of CRC in any FDR and both parents and siblings was associated with an approximately 1.5- and 2.3-fold increased risk of CRC. The effect of family history was relatively greater in the younger than the older age group. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 771 KiB

Open AccessArticle

CNVs Associated with Different Clinical Phenotypes of Psoriasis and Anti-TNF-Induced Palmoplantar Pustulosis

by Alejandra Reolid, Antonio Sahuquillo-Torralba, Ancor Sanz-García, Rafael Botella-Estrada, Ester Muñoz-Aceituno, Mar Llamas-Velasco, Jorge García-Martínez, Esteban Daudén, Francisco Abad-Santos and María C. Ovejero-Benito

J. Pers. Med. 2022, 12(9), 1452; https://doi.org/10.3390/jpm12091452 - 4 Sep 2022

Cited by 1 | Viewed by 2351

Abstract

Background: Psoriasis can present different phenotypes and could affect diverse body areas. In contrast to the high effectiveness of biological drugs in the treatment of trunk and extremities plaque psoriasis, in palmoplantar phenotypes and in plaque scalp psoriasis, these same drugs usually have [...] Read more.

Background: Psoriasis can present different phenotypes and could affect diverse body areas. In contrast to the high effectiveness of biological drugs in the treatment of trunk and extremities plaque psoriasis, in palmoplantar phenotypes and in plaque scalp psoriasis, these same drugs usually have reduced efficacy. Anti-TNF drugs could induce the appearance of palmoplantar pustulosis (PPP) in patients with other inflammatory diseases. The objective of this study is to identify if there are DNA Copy Number Variations (CNVs) associated with these different clinical phenotypes, which could justify the differences found in clinical practice. Moreover, we intend to elucidate if anti-TNF-induced PPP has a similar genetic background to idiopathic PPP. Methods: Skin samples were collected from 39 patients with different patterns of psoriasis and six patients with anti-TNF-induced PPP. The CNVs were obtained from methylation array data (Illumina Infinium Human Methylation) using the conumee R package. Results: No significant CNVs were found between the different phenotypes and the locations of psoriasis compared. Nevertheless, we found two significant bins harboring five different genes associated with anti-TNF-induced PPP in patients with a different background other than psoriasis. Conclusions: Our results may help to predict which patients could develop anti-TNF-induced PPP. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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2 pages, 187 KiB

Open AccessEditorial

Is Radiomics Growing towards Clinical Practice?

by Marco Aiello

J. Pers. Med. 2022, 12(9), 1373; https://doi.org/10.3390/jpm12091373 - 25 Aug 2022

Cited by 4 | Viewed by 1309

Abstract

A recent article [...] Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

20 pages, 5108 KiB

Open AccessArticle

Innovative Hybrid-Alignment Annotation Method for Bioinformatics Identification and Functional Verification of a Novel Nitric Oxide Synthase in Trichomonas vaginalis

by Hung-Che Lin, Hao-Ai Shui, Kuo-Yang Huang, Wei-Zhi Lin, Hsin-Yi Chang, Hwei-Jen Lee, Ying-Chih Lin, Yuahn-Sieh Huang, Guan-Ru Chen, Ya-Ting Yang, Hsiu-Lin Liu, Yi-Syuan Wu, Chia-Shiang Cheng, Ching-Lung Ko, Yu-Tien Chang, Jih-Chin Lee, Chen-Shien Lin, Chih-Hung Wang and Chi-Ming Chu

Biology 2022, 11(8), 1210; https://doi.org/10.3390/biology11081210 - 12 Aug 2022

Viewed by 2821

Abstract

Both the annotation and identification of genes in pathogenic parasites are still challenging. Although, as a survival factor, nitric oxide (NO) has been proven to be synthesized in Trichomonas vaginalis (TV), nitric oxide synthase (NOS) has not yet been annotated in the TV [...] Read more.

Both the annotation and identification of genes in pathogenic parasites are still challenging. Although, as a survival factor, nitric oxide (NO) has been proven to be synthesized in Trichomonas vaginalis (TV), nitric oxide synthase (NOS) has not yet been annotated in the TV genome. We developed a witness-to-suspect strategy to identify incorrectly annotated genes in TV via the Smith–Waterman and Needleman–Wunsch algorithms through in-depth and repeated alignment of whole coding sequences of TV against thousands of sequences of known proteins from other organisms. A novel NOS of TV (TV NOS), which was annotated as hydrogenase in the NCBI database, was successfully identified; this TV NOS had a high witness-to-suspect ratio and contained all the NOS cofactor-binding motifs (NADPH, tetrahydrobiopterin (BH4), heme and flavin adenine dinucleotide (FAD) motifs). To confirm this identification, we performed in silico modeling of the protein structure and cofactor docking, cloned the gene, expressed and purified the protein, performed mass spectrometry analysis, and ultimately performed an assay to measure enzymatic activity. Our data showed that although the predicted structure of the TV NOS protein was not similar to the structure of NOSs of other species, all cofactor-binding motifs could interact with their ligands with high affinities. We clearly showed that the purified protein had high enzymatic activity for generating NO in vitro. This study provides an innovative approach to identify incorrectly annotated genes in TV and highlights a novel NOS that might serve as a virulence factor of TV. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 1668 KiB

Open AccessArticle

Synergistic Effect of Motivation for the Elderly and Support for Going out

by Yumi Mashimo, Saki Tsuchihashi, Kenta Tsutsui, Tomoyuki Arai, Yoshitaka Tsuji, Toshiaki Numai, Kazuo Kameda, Kyoko Nishizawa, Mami Kovacs, Shukichi Tanaka, Hiroki Watanabe, Yasushi Naruse, Mitsuyo Ohmura, Noriyuki Ishida, Toshiki Iwasaki, Gaku Hiruma, Naoki Miyazaki, Ryo Takemura, Kengo Nagashima, Yasunori Sato, Yui Ohtsu, Takashi Nakano, Naomi Aida, Isao Iizuka, Hiromi Kato, Yoshiki Kobayashi and Takaaki Senbonmatsu Show full author list Hide full author list

J. Pers. Med. 2022, 12(8), 1257; https://doi.org/10.3390/jpm12081257 - 30 Jul 2022

Cited by 3 | Viewed by 2317

Abstract

Maintaining a social environment that enables going out freely is important for older people and aids the prevention of frailty syndrome. However, losing a driver’s license can increase the long-term care needs of older people. Therefore, outing support systems are important. However, the [...] Read more.

Maintaining a social environment that enables going out freely is important for older people and aids the prevention of frailty syndrome. However, losing a driver’s license can increase the long-term care needs of older people. Therefore, outing support systems are important. However, the utilization rate of these systems is currently relatively low. We conducted a demonstration experiment among older people aged 70 years and over, living in Iruma City, Saitama Japan, by implementing the Choisoko outing support system developed by Aisin Co., Ltd., in conjunction with an approach for improving motivation. Using this system, elderly people were able to go shopping freely whenever they chose, without a driver’s license. Participants in the demonstration experiment exhibited higher Functional Independence Measure scores after the intervention, irrespective of whether or not they used the Choisoko system. The number of uses per person increased over time, and the subjective well-being of Choisoko users improved. However, few male participants engaged with the system. Although improving motivation is important for inducing positive behaviors and enabling the elderly to go out, motivation-improving factors differ between men and women. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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9 pages, 1199 KiB

Open AccessArticle

Risk of Tuberculosis Caused by Fluticasone Propionate versus Budesonide in Chronic Obstructive Pulmonary Disease: A Nationwide Population-Based Study

by Iseul Yu, Sunmin Park, Se Hwa Hong, Min-Seok Chang, Seok Jeong Lee, Suk Joong Yong, Won-Yeon Lee, Sang-Ha Kim and Ji-Ho Lee

J. Pers. Med. 2022, 12(7), 1189; https://doi.org/10.3390/jpm12071189 - 21 Jul 2022

Cited by 3 | Viewed by 2172

Abstract

Background: In chronic obstructive pulmonary disease (COPD), inhaled corticosteroids (ICSs) are recommended for use by patients with frequent exacerbations and blood eosinophilia. However, ICSs are often inappropriately prescribed and overused. COPD studies have reported an increased risk of tuberculosis among ICS users. This [...] Read more.

Background: In chronic obstructive pulmonary disease (COPD), inhaled corticosteroids (ICSs) are recommended for use by patients with frequent exacerbations and blood eosinophilia. However, ICSs are often inappropriately prescribed and overused. COPD studies have reported an increased risk of tuberculosis among ICS users. This study aimed to compare the risk of tuberculosis according to the different ICS components. Methods: This study was conducted using a nationwide, population-based cohort. Patients newly diagnosed with COPD between 2005 and 2018, and treated with either fluticasone propionate or budesonide, were selected. The patients were followed up until the development of tuberculosis. Results: After propensity score matching, 16,514 fluticasone propionate and 16,514 budesonide users were identified. The incidence rate of tuberculosis per 100,000 person-years was 274.73 for fluticasone propionate and 214.18 for budesonide. The hazard ratio of tuberculosis in fluticasone propionate compared with budesonide was 1.28 (95% confidence interval 1.05–1.60). The risk of tuberculosis for fluticasone propionate increased with higher ICS cumulative doses: 1.01 (0.69–1.48), 1.16 (0.74–1.81), 1.25 (0.79–1.97), and 1.82 (1.27–2.62) from the lowest to highest quartiles, respectively. Conclusion: Fluticasone propionate is associated with a higher risk of tuberculosis than budesonide. ICS components can differently affect the risk of tuberculosis in patients with COPD. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 551 KiB

Open AccessPerspective

Stem Cell Theory of Cancer: Implications for Translational Research from Bedside to Bench

by Shi-Ming Tu, Sunny R. Singh, Konstantinos Arnaoutakis, Sindhu Malapati, Sajjad A. Bhatti, Aron Y. Joon, Omar T. Atiq and Louis L. Pisters

Cancers 2022, 14(14), 3345; https://doi.org/10.3390/cancers14143345 - 9 Jul 2022

Cited by 4 | Viewed by 2037

Abstract

A stem cell theory of cancer considers genetic makeup in the proper cellular context. It is a unified theory of cancer that unites the genome with the epigenome, links the intracellular with the extracellular, and connects the cellular constituents and compartments with the [...] Read more.

A stem cell theory of cancer considers genetic makeup in the proper cellular context. It is a unified theory of cancer that unites the genome with the epigenome, links the intracellular with the extracellular, and connects the cellular constituents and compartments with the microenvironment. Although it allies with genomic medicine, it is better aligned with integrated medicine. In this perspective, we focus on translational research in cancer care. We expose some intrinsic fallacies in translational research when it relates to the basic principles of the scientific method in the care of patients with genomic medicine versus integrated medicine. We postulate that genomic medicine may be at the root of many failed efforts in drug development and data reproducibility. We propose an alternate heuristic approach that may expedite the development of safe and effective treatments and minimize the generation of unproductive pharmaceutical products and nonreproducible experimental results. Importantly, a heuristic approach emphasizes the role of a pertinent scientific theory and distinguishes therapy development from drug development, such that we discover not only useful drugs but also better ways to use them in order to optimize patient care and maximize clinical outcomes. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 2449 KiB

Open AccessArticle

Revisiting the Risk Factors for Endometriosis: A Machine Learning Approach

by Ido Blass, Tali Sahar, Adi Shraibman, Dan Ofer, Nadav Rappoport and Michal Linial

J. Pers. Med. 2022, 12(7), 1114; https://doi.org/10.3390/jpm12071114 - 7 Jul 2022

Cited by 12 | Viewed by 4789

Abstract

Endometriosis is a condition characterized by implants of endometrial tissues into extrauterine sites, mostly within the pelvic peritoneum. The prevalence of endometriosis is under-diagnosed and is estimated to account for 5–10% of all women of reproductive age. The goal of this study was [...] Read more.

Endometriosis is a condition characterized by implants of endometrial tissues into extrauterine sites, mostly within the pelvic peritoneum. The prevalence of endometriosis is under-diagnosed and is estimated to account for 5–10% of all women of reproductive age. The goal of this study was to develop a model for endometriosis based on the UK-biobank (UKB) and re-assess the contribution of known risk factors to endometriosis. We partitioned the data into those diagnosed with endometriosis (5924; ICD-10: N80) and a control group (142,723). We included over 1000 variables from the UKB covering personal information about female health, lifestyle, self-reported data, genetic variants, and medical history prior to endometriosis diagnosis. We applied machine learning algorithms to train an endometriosis prediction model. The optimal prediction was achieved with the gradient boosting algorithms of CatBoost for the data-combined model with an area under the ROC curve (ROC-AUC) of 0.81. The same results were obtained for women from a mixed ethnicity population of the UKB (7112; ICD-10: N80). We discovered that, prior to being diagnosed with endometriosis, affected women had significantly more ICD-10 diagnoses than the average unaffected woman. We used SHAP, an explainable AI tool, to estimate the marginal impact of a feature, given all other features. The informative features ranked by SHAP values included irritable bowel syndrome (IBS) and the length of the menstrual cycle. We conclude that the rich population-based retrospective data from the UKB are valuable for developing unified machine learning endometriosis models despite the limitations of missing data, noisy medical input, and participant age. The informative features of the model may improve clinical utility for endometriosis diagnosis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 1192 KiB

Open AccessArticle

Head and Neck Cancer Types and Risks of Cervical–Cranial Vascular Complications within 5 Years after Radiation Therapy

by Chi-Hung Liu, Bing-Shen Huang, Chien-Yu Lin, Chih-Hua Yeh, Tsong-Hai Lee, Hsiu-Chuan Wu, Chien-Hung Chang, Ting-Yu Chang, Kuo-Lun Huang, Jian-Lin Jiang, Joseph Tung-Chieh Chang and Yeu-Jhy Chang

J. Pers. Med. 2022, 12(7), 1060; https://doi.org/10.3390/jpm12071060 - 29 Jun 2022

Cited by 3 | Viewed by 2292

Abstract

Background and purpose: to investigate the frequency of cervical–cranial vascular complications soon after radiation therapy (RT) and identify differences among patients with various types of head and neck cancer (HNC). Methods: We enrolled 496 patients with HNC who had received their final RT [...] Read more.

Background and purpose: to investigate the frequency of cervical–cranial vascular complications soon after radiation therapy (RT) and identify differences among patients with various types of head and neck cancer (HNC). Methods: We enrolled 496 patients with HNC who had received their final RT dose in our hospital. These patients underwent carotid duplex ultrasound (CDU) for monitoring significant carotid artery stenosis (CAS). Brain imaging were reviewed to detect vertebral, intracranial artery stenosis, or preexisted CAS before RT. Primary outcome was significant CAS at the internal or common carotid artery within first 5 years after RT. We categorized the patients into nasopharyngeal carcinoma (NPC) and non-NPC groups and compared the cumulative occurrence of significant CAS between the groups using Kaplan–Meier and Cox-regression analyses. Results: Compared to the NPC group, the non-NPC group had a higher frequency of significant CAS (12.7% vs. 2.0%) and were more commonly associated with significant CAS after adjusting the covariates (Adjusted hazard ratio: 0.17, 95% confident interval: 0.05–0.57) during the follow-up period. All the non-NPC subtypes (oral cancer/oropharyngeal, hypopharyngeal, and laryngeal cancers) were associated with higher risks of significant CAS than the NPC group (p < 0.001 respectively). Conclusion: Significant CAS was more frequently noted within 5 years of RT among the patients with non-NPC HNC than among the patients with NPC. Scheduled carotid artery surveillance and vascular risk monitoring should be commenced earlier for patients with non-NPC HNC. By contrast, vascular surveillance could be deferred to 5 years after RT completion in NPC patients. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 3694 KiB

Open AccessArticle

Characterization of the Oncogenic Potential of Eukaryotic Initiation Factor 4A1 in Lung Adenocarcinoma via Cell Cycle Regulation and Immune Microenvironment Reprogramming

by Kuan-Li Wu, Yung-Chi Huang, Yu-Yuan Wu, Chao-Yuan Chang, Yung-Yun Chang, Hung-Hsing Chiang, Lian-Xiu Liu, Ying-Ming Tsai and Jen-Yu Hung

Biology 2022, 11(7), 975; https://doi.org/10.3390/biology11070975 - 28 Jun 2022

Cited by 3 | Viewed by 2291

Abstract

Lung adenocarcinoma (LUAD) is a common type of lung cancer. Although the diagnosis and treatment of LUAD have significantly improved in recent decades, the survival for advanced LUAD is still poor. It is necessary to identify more targets for developing potential agents against [...] Read more.

Lung adenocarcinoma (LUAD) is a common type of lung cancer. Although the diagnosis and treatment of LUAD have significantly improved in recent decades, the survival for advanced LUAD is still poor. It is necessary to identify more targets for developing potential agents against LUAD. This study explored the dysregulation of translation initiation factors, specifically eukaryotic initiation factors 4A1 (EIF4A1) and EIF4A2, in developing LUAD, as well as their underlying mechanisms. We found that the expression of EIF4A1, but not EIF4A2, was higher in tumor tissue and associated with poor clinical outcomes in LUAD patients. Elevated expression of EIF4H with poor prognosis may potentiate the oncogenic role of EIF4A1. Functional enrichment analysis revealed that upregulation of EIF4A1 was related to cell cycle regulation and DNA repair. The oncogenic effect of EIF4A1 was further elucidated by Gene Set Variation Analysis (GSVA). The GSVA score of the gene set positively correlated with EIF4A1 was higher in tumors and significantly associated with worse survival. In the meantime, gene set enrichment analysis (GSEA) also indicated that elevated EIF4A1 expression in LUAD patients was associated with a decreased infiltration score for immune cells by reducing anticancer immune cell types and recruiting immunosuppressive cells. Consistent with the results, the GSVA score of genes whose expression was negatively correlated with EIF4A1 was lower in the tumor tissue of LUAD cases with worse clinical outcomes and was strongly associated with the disequilibrium of anti-cancer immunity by recruiting anticancer immune cells. Based on the results from the present study, we hypothesize that the dysregulation of EIF4A1 might be involved in the pathophysiology of LUAD development by promoting cancer growth and changing the tumor immune microenvironment. This can be used to develop potential diagnostic biomarkers or therapeutic targets for LUAD. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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10 pages, 1244 KiB

Open AccessArticle

Development of Machine Learning Models Predicting Estimated Blood Loss during Liver Transplant Surgery

by Sujung Park, Kyemyung Park, Jae Geun Lee, Tae Yang Choi, Sungtaik Heo, Bon-Nyeo Koo and Dongwoo Chae

J. Pers. Med. 2022, 12(7), 1028; https://doi.org/10.3390/jpm12071028 - 23 Jun 2022

Cited by 2 | Viewed by 2417

Abstract

The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning [...] Read more.

The incidence of major hemorrhage and transfusion during liver transplantation has decreased significantly over the past decade, but major bleeding remains a common expectation. Massive intraoperative hemorrhage during liver transplantation can lead to mortality or reoperation. This study aimed to develop machine learning models for the prediction of massive hemorrhage and a scoring system which is applicable to new patients. Data were retrospectively collected from patients aged >18 years who had undergone liver transplantation. These data included emergency information, donor information, demographic data, preoperative laboratory data, the etiology of hepatic failure, the Model for End-stage Liver Disease (MELD) score, surgical history, antiplatelet therapy, continuous renal replacement therapy (CRRT), the preoperative dose of vasopressor, and the estimated blood loss (EBL) during surgery. The logistic regression model was one of the best-performing machine learning models. The most important factors for the prediction of massive hemorrhage were the disease etiology, activated partial thromboplastin time (aPTT), operation duration, body temperature, MELD score, mean arterial pressure, serum creatinine, and pulse pressure. The risk-scoring system was developed using the odds ratios of these factors from the logistic model. The risk-scoring system showed good prediction performance and calibration (AUROC: 0.775, AUPR: 0.753). Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 9746 KiB

Open AccessArticle

Characterization of Immune-Based Molecular Subtypes and Prognostic Model in Prostate Adenocarcinoma

by Li Guo, Yihao Kang, Daoliang Xia, Yujie Ren, Xueni Yang, Yangyang Xiang, Lihua Tang, Dekang Ren, Jiafeng Yu, Jun Wang and Tingming Liang

Genes 2022, 13(6), 1087; https://doi.org/10.3390/genes13061087 - 18 Jun 2022

Viewed by 2428

Abstract

Prostate adenocarcinoma (PRAD), also named prostate cancer, the most common visceral malignancy, is diagnosed in male individuals. Herein, in order to obtain immune-based subtypes, we performed an integrative analysis to characterize molecular subtypes based on immune-related genes, and further discuss the potential features [...] Read more.

Prostate adenocarcinoma (PRAD), also named prostate cancer, the most common visceral malignancy, is diagnosed in male individuals. Herein, in order to obtain immune-based subtypes, we performed an integrative analysis to characterize molecular subtypes based on immune-related genes, and further discuss the potential features and differences between identified subtypes. Simultaneously, we also construct an immune-based risk model to assess cancer prognosis. Our findings showed that the two subtypes, C1 and C2, could be characterized, and the two subtypes showed different characteristics that could clearly describe the heterogeneity of immune microenvironments. The C2 subtype presented a better survival rate than that in the C1 subtype. Further, we constructed an immune-based prognostic model based on four screened abnormally expressed genes, and they were selected as predictors of the robust prognostic model (AUC = 0.968). Our studies provide reference for characterization of molecular subtypes and immunotherapeutic agents against prostate cancer, and the developed robust and useful immune-based prognostic model can contribute to cancer prognosis and provide reference for the individualized treatment plan and health resource utilization. These findings further promote the development and application of precision medicine in prostate cancer. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 1462 KiB

Open AccessArticle

Potential Cancer Risk in Patients with Rheumatoid Arthritis: A Longitudinal Korean Population-Based Analysis

by Hyo Geun Choi, Ho Suk Kang, Hyun Lim, Joo-Hee Kim, Ji Hee Kim, Seong-Jin Cho, Eun Sook Nam, Kyueng-Whan Min, Ha Young Park, Nan Young Kim and Mi Jung Kwon

J. Pers. Med. 2022, 12(6), 965; https://doi.org/10.3390/jpm12060965 - 13 Jun 2022

Cited by 9 | Viewed by 2818

Abstract

The potential link between rheumatoid arthritis (RA) and cancer incidence needs to be validated due to inconsistent results between Asian and Western countries. We explored the long-term association of RA with the overall and organ-specific cancer incidence using nationwide population data. This longitudinal [...] Read more.

The potential link between rheumatoid arthritis (RA) and cancer incidence needs to be validated due to inconsistent results between Asian and Western countries. We explored the long-term association of RA with the overall and organ-specific cancer incidence using nationwide population data. This longitudinal follow-up study (2002–2015) included 3070 patients with RA and 12,280 controls (1:4 propensity score-matched for sex, age, residence, and income) from the Korean National Health Insurance Service-Health Screening Cohort database. A Cox proportional hazard model estimated the hazard ratio for malignancy following adjusting for covariates. Despite the similar overall cancer incidence between RA and control groups, differences in the incidence of organ-specific cancers were noted: the RA group had a 1.63-fold greater likelihood for lung cancer (95% confidence interval 1.11–2.40). In the sex-stratified subgroup analyses, the male RA patients exhibited higher odds of lung and thyroid cancer but a lower probability for colorectal cancer; no such associations were detected in either female patients with RA or age subgroups. In summary, the higher likelihood for lung cancer in Korean RA patients, especially thyroid and lung cancer in male RA patients, seems to be characteristic, which needs to be carefully monitored. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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37 pages, 6815 KiB

Open AccessArticle

Bioinformatic Prioritization and Functional Annotation of GWAS-Based Candidate Genes for Primary Open-Angle Glaucoma

by Nigus G. Asefa, Zoha Kamali, Satyajit Pereira, Ahmad Vaez, Nomdo Jansonius, Arthur A. Bergen and Harold Snieder

Genes 2022, 13(6), 1055; https://doi.org/10.3390/genes13061055 - 13 Jun 2022

Cited by 14 | Viewed by 4172

Abstract

Background: Primary open-angle glaucoma (POAG) is the most prevalent glaucoma subtype, but its exact etiology is still unknown. In this study, we aimed to prioritize the most likely ‘causal’ genes and identify functional characteristics and underlying biological pathways of POAG candidate genes. Methods: [...] Read more.

Background: Primary open-angle glaucoma (POAG) is the most prevalent glaucoma subtype, but its exact etiology is still unknown. In this study, we aimed to prioritize the most likely ‘causal’ genes and identify functional characteristics and underlying biological pathways of POAG candidate genes. Methods: We used the results of a large POAG genome-wide association analysis study from GERA and UK Biobank cohorts. First, we performed systematic gene-prioritization analyses based on: (i) nearest genes; (ii) nonsynonymous single-nucleotide polymorphisms; (iii) co-regulation analysis; (iv) transcriptome-wide association studies; and (v) epigenomic data. Next, we performed functional enrichment analyses to find overrepresented functional pathways and tissues. Results: We identified 142 prioritized genes, of which 64 were novel for POAG. BICC1, AFAP1, and ABCA1 were the most highly prioritized genes based on four or more lines of evidence. The most significant pathways were related to extracellular matrix turnover, transforming growth factor-β, blood vessel development, and retinoic acid receptor signaling. Ocular tissues such as sclera and trabecular meshwork showed enrichment in prioritized gene expression (>1.5 fold). We found pleiotropy of POAG with intraocular pressure and optic-disc parameters, as well as genetic correlation with hypertension and diabetes-related eye disease. Conclusions: Our findings contribute to a better understanding of the molecular mechanisms underlying glaucoma pathogenesis and have prioritized many novel candidate genes for functional follow-up studies. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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16 pages, 2961 KiB

Open AccessArticle

Bioinformatics and Experimental Analyses Reveal NFIC as an Upstream Transcriptional Regulator for Ischemic Cardiomyopathy

by Yang Ye, Qiao Jin, Qian Gong, Aoqi Li, Minghao Sun, Sibo Jiang, Yulan Jin, Zhe Zhang, Jin He and Lenan Zhuang

Genes 2022, 13(6), 1051; https://doi.org/10.3390/genes13061051 - 13 Jun 2022

Cited by 5 | Viewed by 3158

Abstract

Ischemic cardiomyopathy (ICM) caused by coronary artery disease always leads to myocardial infarction and heart failure. Identification of novel transcriptional regulators in ICM is an effective method to establish new diagnostic and therapeutic strategies. In this study, we used two RNA-seq datasets and [...] Read more.

Ischemic cardiomyopathy (ICM) caused by coronary artery disease always leads to myocardial infarction and heart failure. Identification of novel transcriptional regulators in ICM is an effective method to establish new diagnostic and therapeutic strategies. In this study, we used two RNA-seq datasets and one microarray dataset from different studies, including 25 ICM and 21 non-failing control (NF) samples of human left ventricle tissues for further analysis. In total, 208 differentially expressed genes (DEGs) were found by combining two RNA-seq datasets with batch effects removed. GO and KEGG analyses of DEGs indicated that the response to wounding, positive regulation of smooth muscle contraction, chromatin, PI3K-Akt signaling pathway, and transporters pathways are involved in ICM. Simple Enrichment Analysis found that NFIC-binding motifs are enriched in promoter regions of downregulated genes. The Gene Importance Calculator further proved that NFIC is vital. NFIC and its downstream genes were verified in the validating microarray dataset. Meanwhile, in rat cardiomyocyte cell line H9C2 cells, two genes (Tspan1 and Hopx) were confirmed, which decreased significantly along with knocking down Nfic expression. In conclusion, NFIC participates in the ICM process by regulating TSPAN1 and HOPX. NFIC and its downstream genes may be marker genes and potential diagnostic and therapeutic targets for ICM. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 1723 KiB

Open AccessArticle

PhenGenVar: A User-Friendly Genetic Variant Detection and Visualization Tool for Precision Medicine

by JaeMoon Shin, Junbeom Jeon, Dawoon Jung, Kiyong Kim, Yun Joong Kim, Dong-Hoon Jeong and JeeHee Yoon

J. Pers. Med. 2022, 12(6), 959; https://doi.org/10.3390/jpm12060959 - 12 Jun 2022

Cited by 4 | Viewed by 3044

Abstract

Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, [...] Read more.

Precision medicine has been revolutionized by the advent of high-throughput next-generation sequencing (NGS) technology and development of various bioinformatic analysis tools for large-scale NGS big data. At the population level, biomedical studies have identified human diseases and phenotype-associated genetic variations using NGS technology, such as whole-genome sequencing, exome sequencing, and gene panel sequencing. Furthermore, patients’ genetic variations related to a specific phenotype can also be identified by analyzing their genomic information. These breakthroughs paved the way for the clinical diagnosis and precise treatment of patients’ diseases. Although many bioinformatics tools have been developed to analyze the genetic variations from the individual patient’s NGS data, it is still challenging to develop user-friendly programs for clinical physicians who do not have bioinformatics programing skills to diagnose a patient’s disease using the genomic data. In response to this demand, we developed a Phenotype to Genotype Variation program (PhenGenVar), which is a user-friendly interface for monitoring the variations in a gene of interest for molecular diagnosis. This allows for flexible filtering and browsing of variants of the disease and phenotype-associated genes. To test this program, we analyzed the whole-genome sequencing data of an anonymous person from the 1000 human genome project data. As a result, we were able to identify several genomic variations, including single-nucleotide polymorphism, insertions, and deletions in specific gene regions. Therefore, PhenGenVar can be used to diagnose a patient’s disease. PhenGenVar is freely accessible and is available at our website. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 1294 KiB

Open AccessArticle

Development of a Machine Learning Model to Predict Non-Durable Response to Anti-TNF Therapy in Crohn’s Disease Using Transcriptome Imputed from Genotypes

by Soo Kyung Park, Yea Bean Kim, Sangsoo Kim, Chil Woo Lee, Chang Hwan Choi, Sang-Bum Kang, Tae Oh Kim, Ki Bae Bang, Jaeyoung Chun, Jae Myung Cha, Jong Pil Im, Min Suk Kim, Kwang Sung Ahn, Seon-Young Kim and Dong Il Park

J. Pers. Med. 2022, 12(6), 947; https://doi.org/10.3390/jpm12060947 - 9 Jun 2022

Cited by 5 | Viewed by 2747

Abstract

Almost half of patients show no primary or secondary response to monoclonal anti-tumor necrosis factor α (anti-TNF) antibody treatment for inflammatory bowel disease (IBD). Thus, the exact mechanisms of a non-durable response (NDR) remain inadequately defined. We used our genome-wide genotype data to [...] Read more.

Almost half of patients show no primary or secondary response to monoclonal anti-tumor necrosis factor α (anti-TNF) antibody treatment for inflammatory bowel disease (IBD). Thus, the exact mechanisms of a non-durable response (NDR) remain inadequately defined. We used our genome-wide genotype data to impute expression values as features in training machine learning models to predict a NDR. Blood samples from various IBD cohorts were used for genotyping with the Korea Biobank Array. A total of 234 patients with Crohn’s disease (CD) who received their first anti-TNF therapy were enrolled. The expression profiles of 6294 genes in whole-blood tissue imputed from the genotype data were combined with clinical parameters to train a logistic model to predict the NDR. The top two and three most significant features were genetic features (DPY19L3, GSTT1, and NUCB1), not clinical features. The logistic regression of the NDR vs. DR status in our cohort by the imputed expression levels showed that the β coefficients were positive for DPY19L3 and GSTT1, and negative for NUCB1, concordant with the known eQTL information. Machine learning models using imputed gene expression features effectively predicted NDR to anti-TNF agents in patients with CD. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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10 pages, 592 KiB

Open AccessArticle

Risk of Infertility in Males with Obstructive Sleep Apnea: A Nationwide, Population-Based, Nested Case-Control Study

by Pin-Yao Lin, Hua Ting, Yen-Ting Lu, Jing-Yang Huang, Tsung-Hsien Lee, Maw-Sheng Lee and James Cheng-Chung Wei

J. Pers. Med. 2022, 12(6), 933; https://doi.org/10.3390/jpm12060933 - 5 Jun 2022

Cited by 3 | Viewed by 2828

Abstract

Obstructive sleep apnea (OSA) yields intermittent hypoxia, hypercapnia, and sleep fragmentation. OSA is associated with chronic medical conditions such as cardiovascular diseases, metabolic syndrome, and neurocognitive dysfunction. However, the risk of infertility in OSA remains unclear due to limited data and lack of [...] Read more.

Obstructive sleep apnea (OSA) yields intermittent hypoxia, hypercapnia, and sleep fragmentation. OSA is associated with chronic medical conditions such as cardiovascular diseases, metabolic syndrome, and neurocognitive dysfunction. However, the risk of infertility in OSA remains unclear due to limited data and lack of long-term population-based studies. The study aims to assess the risk of infertility in obstructive sleep apnea (OSA) by means of a population-based cohort study. The data was utilized from the Taiwan National Health Insurance Research Database (NHIRD) to conduct a population-based cohort study (1997–2013). Compared with the Non-OSA group, the male with OSA and surgery group has the OR (odds ratio) of infertility of 2.70 (95% CI, 1.46–4.98, p = 0.0015), but no significance exists in females with OSA. When the data was stratified according to age and gender, some associations in the specific subgroups were significant. Respectively, males aged 20–35 years old and aged 35–50 years old with a history of OSA and surgery both had a positive association with infertility. (aOR: 3.19; 95% CI, 1.18–8.66, p = 0.0227; aOR: 2.57; 95% CI, 1.18–5.62 p = 0.0176). Male patients with OSA suffer from reduced fertility, but no significant difference was noted in females with OSA. The identification of OSA as a risk factor for male infertility will aid clinicians to optimize long-term medical care. Furthermore, more studies will be encouraged to clarify the effect of OSA on female fertility. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 4313 KiB

Open AccessArticle

The Therapeutic Potential of ADAMTS8 in Lung Adenocarcinoma without Targetable Therapy

by Hsiao-Chen Lee, Chao-Yuan Chang, Kuan-Li Wu, Hung-Hsing Chiang, Yung-Yun Chang, Lian-Xiu Liu, Yung-Chi Huang, Jen-Yu Hung, Ya-Ling Hsu, Yu-Yuan Wu and Ying-Ming Tsai

J. Pers. Med. 2022, 12(6), 902; https://doi.org/10.3390/jpm12060902 - 30 May 2022

Cited by 5 | Viewed by 2611

Abstract

Lung cancer is well known for its high mortality worldwide. The treatment for advanced lung cancer needs more attention to improve its survival time. A disintegrin and metallopeptidase with thrombospondin motifs 8 (ADAMTS8) has been linked to several cancer types. However, its role [...] Read more.

Lung cancer is well known for its high mortality worldwide. The treatment for advanced lung cancer needs more attention to improve its survival time. A disintegrin and metallopeptidase with thrombospondin motifs 8 (ADAMTS8) has been linked to several cancer types. However, its role in lung cancer is worthy of deep investigation to promote novel drug development. This study took advantage of RNA-seq and bioinformatics to verify the role that ADAMTS8 plays in lung cancer. The functional assays suggested that ADAMTS8 mediates invasion and metastasis when expressed at a low level, contributing to poor overall survival (OS). The expression of ADAMTS8 was under the regulation of GATA Binding Protein 1 (GATA1) and executed its pathologic role through Thrombospondin Type 1 Domain Containing 1 (THSD1) and ADAMTS Like 2 (ADAMTSL2). To define the impact of ADAMTS8 in the lung cancer treatment strategy, this study further grouped lung cancer patients in the TCGA database into mutated epidermal growth factor receptor (EGFR)/wild-type EGFR and programmed death ligand 1 (PD-L1) high/low groups. Importantly, the expression of ADAMTS8 was correlated positively with the recruitment of anticancer NKT cells and negatively with the infiltration of immunosuppressive Treg and exhausted T cells. The results indicated that lung cancer patients with higher ADAMTS8 levels among wild-type EGFR or low PD-L1 groups survive longer than those with lower levels do. This study indicates that ADAMTS8 might be a treatment option for patients with lung adenocarcinoma who lack efficient targeted or immunotherapies. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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16 pages, 3109 KiB

Open AccessEditor’s ChoiceArticle

MDMF: Predicting miRNA–Disease Association Based on Matrix Factorization with Disease Similarity Constraint

by Jihwan Ha

J. Pers. Med. 2022, 12(6), 885; https://doi.org/10.3390/jpm12060885 - 27 May 2022

Cited by 23 | Viewed by 2795

Abstract

MicroRNAs (miRNAs) have drawn enormous attention owing to their significant roles in various biological processes, as well as in the pathogenesis of human diseases. Therefore, predicting miRNA–disease associations is a pivotal task for the early diagnosis and better understanding of disease pathogenesis. To [...] Read more.

MicroRNAs (miRNAs) have drawn enormous attention owing to their significant roles in various biological processes, as well as in the pathogenesis of human diseases. Therefore, predicting miRNA–disease associations is a pivotal task for the early diagnosis and better understanding of disease pathogenesis. To date, numerous computational frameworks have been proposed to identify potential miRNA–disease associations without escalating the costs and time required for clinical experiments. In this regard, I propose a novel computational framework (MDMF) for identifying potential miRNA–disease associations using matrix factorization with a disease similarity constraint. To evaluate the performance of MDMF, I calculated the area under the ROC curve (AUCs) in the framework of global and local leave-one-out cross-validation (LOOCV). In conclusion, MDMF achieved reliable AUC values of 0.9147 and 0.8905 for global and local LOOCV, respectively, which was a significant improvement upon the previous methods. Additionally, case studies were conducted on two major human cancers (breast cancer and lung cancer) to validate the effectiveness of MDMF. Comprehensive experimental results demonstrate that MDMF not only discovers miRNA–disease associations efficiently but also deciphers the underlying roles of miRNAs in the pathogenesis of diseases at a system level. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 1083 KiB

Open AccessArticle

Advanced Molecular Characterisation in Relapsed and Refractory Paediatric Acute Leukaemia, the Key for Personalised Medicine

by Víctor Galán-Gómez, Nerea Matamala, Beatriz Ruz-Caracuel, Paula Valle-Simón, Bárbara Ochoa-Fernández, Pilar Guerra-García, Alicia Pernas-Sánchez, Jordi Minguillón, Berta González, Isabel Martínez-Romera, Sonsoles San Román-Pacheco, Pablo Estival-Monteliú, Adrián Ibáñez-Navarro, Antonio Pérez-Martínez and Adela Escudero-López

J. Pers. Med. 2022, 12(6), 881; https://doi.org/10.3390/jpm12060881 - 27 May 2022

Viewed by 2677

Abstract

Relapsed and refractory (R/r) disease in paediatric acute leukaemia remains the first reason for treatment failure. Advances in molecular characterisation can ameliorate the identification of genetic biomarkers treatment strategies for this disease, especially in high-risk patients. The purpose of this study was to [...] Read more.

Relapsed and refractory (R/r) disease in paediatric acute leukaemia remains the first reason for treatment failure. Advances in molecular characterisation can ameliorate the identification of genetic biomarkers treatment strategies for this disease, especially in high-risk patients. The purpose of this study was to analyse a cohort of R/r children diagnosed with acute lymphoblastic (ALL) or myeloid (AML) leukaemia in order to offer them a targeted treatment if available. Advanced molecular characterisation of 26 patients diagnosed with R/r disease was performed using NGS, MLPA, and RT-qPCR. The clinical relevance of the identified alterations was discussed in a multidisciplinary molecular tumour board (MTB). A total of 18 (69.2%) patients were diagnosed with B-ALL, 4 (15.4%) with T-ALL, 3 (11.5%) with AML and 1 patient (3.8%) with a mixed-phenotype acute leukaemia (MPL). Most of the patients had relapsed disease (88%) at the time of sample collection. A total of 17 patients (65.4%) were found to be carriers of a druggable molecular alteration, 8 of whom (47%) received targeted therapy, 7 (87.5%) of them in addition to hematopoietic stem cell transplantation (HSCT). Treatment response and disease control were achieved in 4 patients (50%). In conclusion, advanced molecular characterisation and MTB can improve treatment and outcome in paediatric R/r acute leukaemias. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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19 pages, 4993 KiB

Open AccessArticle

The French Early Breast Cancer Cohort (FRESH): A Resource for Breast Cancer Research and Evaluations of Oncology Practices Based on the French National Healthcare System Database (SNDS)

by Elise Dumas, Lucie Laot, Florence Coussy, Beatriz Grandal Rejo, Eric Daoud, Enora Laas, Amyn Kassara, Alena Majdling, Rayan Kabirian, Floriane Jochum, Paul Gougis, Sophie Michel, Sophie Houzard, Christine Le Bihan-Benjamin, Philippe-Jean Bousquet, Judicaël Hotton, Chloé-Agathe Azencott, Fabien Reyal and Anne-Sophie Hamy

Cancers 2022, 14(11), 2671; https://doi.org/10.3390/cancers14112671 - 27 May 2022

Cited by 11 | Viewed by 4150

Abstract

Background: Breast cancer (BC) is the most frequent cancer and the leading cause of cancer-related death in women. The French National Cancer Institute has created a national cancer cohort to promote cancer research and improve our understanding of cancer using the National Health [...] Read more.

Background: Breast cancer (BC) is the most frequent cancer and the leading cause of cancer-related death in women. The French National Cancer Institute has created a national cancer cohort to promote cancer research and improve our understanding of cancer using the National Health Data System (SNDS) and amalgamating all cancer sites. So far, no detailed separate data are available for early BC. Objectives: To describe the creation of the French Early Breast Cancer Cohort (FRESH). Methods: All French women aged 18 years or over, with early-stage BC newly diagnosed between 1 January 2011 and 31 December 2017, treated by surgery, and registered in the general health insurance coverage plan were included in the cohort. Patients with suspected locoregional or distant metastases at diagnosis were excluded. BC treatments (surgery, chemotherapy, targeted therapy, radiotherapy, and endocrine therapy), and diagnostic procedures (biopsy, cytology, and imaging) were extracted from hospital discharge reports, outpatient care notes, or pharmacy drug delivery data. The BC subtype was inferred from the treatments received. Results: We included 235,368 patients with early BC in the cohort (median age: 60 years). The BC subtype distribution was as follows: luminal (80.2%), triple-negative (TNBC, 9.5%); HER2⁺ (10.3%), or unidentifiable (n = 44,388, 18.9% of the cohort). Most patients underwent radiotherapy (n = 200,685, 85.3%) and endocrine therapy (n = 165,655, 70.4%), and 38.3% (n = 90,252) received chemotherapy. Treatments and care pathways are described. Conclusions: The FRESH Cohort is an unprecedented population-based resource facilitating future large-scale real-life studies aiming to improve care pathways and quality of care for BC patients. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 2660 KiB

Open AccessArticle

Loss of CHGA Protein as a Potential Biomarker for Colon Cancer Diagnosis: A Study on Biomarker Discovery by Machine Learning and Confirmation by Immunohistochemistry in Colorectal Cancer Tissue Microarrays

by Xueli Zhang, Hong Zhang, Chuanwen Fan, Camilla Hildesjö, Bairong Shen and Xiao-Feng Sun

Cancers 2022, 14(11), 2664; https://doi.org/10.3390/cancers14112664 - 27 May 2022

Cited by 8 | Viewed by 3325

Abstract

Background. The incidence of colorectal cancers has been constantly increasing. Although the mortality has slightly decreased, it is far from satisfaction. Precise early diagnosis for colorectal cancer has been a great challenge in order to improve patient survival. Patients and Methods. We started [...] Read more.

Background. The incidence of colorectal cancers has been constantly increasing. Although the mortality has slightly decreased, it is far from satisfaction. Precise early diagnosis for colorectal cancer has been a great challenge in order to improve patient survival. Patients and Methods. We started with searching for protein biomarkers based on our colorectal cancer biomarker database (CBD), finding differential expressed genes (GEGs) and non-DEGs from RNA sequencing (RNA-seq) data, and further predicted new biomarkers of protein–protein interaction (PPI) networks by machine learning (ML) methods. The best-selected biomarker was further verified by a receiver operating characteristic (ROC) test from microarray and RNA-seq data, biological network, and functional analysis, and immunohistochemistry in the tissue arrays from 198 specimens. Results. There were twelve proteins (MYO5A, CHGA, MAPK13, VDAC1, CCNA2, YWHAZ, CDK5, GNB3, CAMK2G, MAPK10, SDC2, and ADCY5) which were predicted by ML as colon cancer candidate diagnosis biomarkers. These predicted biomarkers showed close relationships with reported biomarkers of the PPI network and shared some pathways. An ROC test showed the CHGA protein with the best diagnostic accuracy (AUC = 0.9 in microarray data and 0.995 in RNA-seq data) among these candidate protein biomarkers. Furthermore, immunohistochemistry examination on our colon cancer tissue microarray samples further confirmed our bioinformatical prediction, indicating that CHGA may be used as a potential biomarker for early diagnosis of colon cancer patients. Conclusions. CHGA could be a potential candidate biomarker for diagnosing earlier colon cancer in the patients. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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21 pages, 6794 KiB

Open AccessArticle

Construction and Validation of a Tumor Microenvironment-Based Scoring System to Evaluate Prognosis and Response to Immune Checkpoint Inhibitor Therapy in Lung Adenocarcinoma Patients

by Pinzheng Huang, Linfeng Xu, Mingming Jin, Lixi Li, Yizhong Ke, Min Zhang, Kairui Zhang, Kongyao Lu and Gang Huang

Genes 2022, 13(6), 951; https://doi.org/10.3390/genes13060951 - 26 May 2022

Cited by 3 | Viewed by 3202

Abstract

Background: Lung cancer is among the most dangerous malignant tumors to human health. Lung adenocarcinoma (LUAD) accounts for about 40% of all lung cancers. Accumulating evidence suggests that the tumor microenvironment (TME) is a crucial regulator of carcinogenesis and therapeutic efficacy in LUAD. [...] Read more.

Background: Lung cancer is among the most dangerous malignant tumors to human health. Lung adenocarcinoma (LUAD) accounts for about 40% of all lung cancers. Accumulating evidence suggests that the tumor microenvironment (TME) is a crucial regulator of carcinogenesis and therapeutic efficacy in LUAD. However, the impact of tumor microenvironment-related signatures (TMERSs) representing the TME characteristics on the prognosis and therapeutic outcome of LUAD patients remains to be further explored. Materials and methods: Gene expression files and clinical information of 1630 LUAD samples and 275 samples with immunotherapy information from different databases such as The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Cancer Research Institute (CRI) iAtlas were downloaded and analyzed. Three hundred tumor microenvironment-related signatures (TMERS) based on a comprehensive collection of marker genes were quantified by single sample gene set enrichment analysis (ssGSEA), and then eight significant signatures were selected to construct the tumor microenvironment-related signature score (TMERSscore) by performing Least Absolute Shrinkage and Selection Operator (LASSO)-Cox analysis. Results: In this study, we constructed a TME-based prognostic stratification model for patients with LUAD and validated it in several external datasets. Furthermore, the TMERSscore was found to be positively correlated with tumor malignancy and a high TMERSscore predicted a poor prognosis. Moreover, the TMERSscore of responders treated with Immune Checkpoint Inhibitor (ICI) therapies was significantly lower than that of non-responders, and the TMERSscore was positively correlated with the tumor immune dysfunction and exclusion (TIDE) score, implying that a low TMERSscore predicts a better response to ICI treatment and may provide independent and incremental predictive value over current biomarkers. Conclusions: Overall, we constructed a TMERSscore that can be used for LUAD patient prognosis stratification as well as ICI therapeutic efficacy evaluation, supportive results from independent external validation sets showed its robustness and effectiveness. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 4332 KiB

Open AccessArticle

DNA Hypermethylation and a Specific Methylation Spectrum on the X Chromosome in Turner Syndrome as Determined by Nanopore Sequencing

by Xin Fan, Beibei Zhang, Lijun Fan, Jiajia Chen, Chang Su, Bingyan Cao, Liya Wei, Miao Qin and Chunxiu Gong

J. Pers. Med. 2022, 12(6), 872; https://doi.org/10.3390/jpm12060872 - 26 May 2022

Viewed by 2811

Abstract

The molecular genetic mechanism of Turner syndrome (TS) still leaves much to be discovered. Methods: TS (45X0) patients and age-matched controls (46XX and 46XY) were selected. The nanopore sequencing combined with trio-whole exome sequencing (trio-WES) were used for the first time to investigate [...] Read more.

The molecular genetic mechanism of Turner syndrome (TS) still leaves much to be discovered. Methods: TS (45X0) patients and age-matched controls (46XX and 46XY) were selected. The nanopore sequencing combined with trio-whole exome sequencing (trio-WES) were used for the first time to investigate TS. Results: Thirteen TS (45X0) patients and eight controls were enrolled. Trio-WES analysis did not find any pathogenetic or likely pathogenic variants except X chromosome (chrX) deletion. The average methylation levels and patterns of chrX in 45X0 and 46XY were similar, and significantly higher than in 46XX (p = 2.22 × 10⁻¹⁶). Both hyper-methylation and hypo-methylation were detected in the CpG island (CGI), CGI_shore, promoter, genebody, and PAR1-region, while in the transposon element inactivation regions of the chrX and hypermethylation were predominant. A total of 125 differentially methylated genes were identified in 45X0 compared to 46XX, including 8 and 117 hypermethylated and hypomethylated genes, respectively, with the enrichment terms of mitophagy, regulation of DNA-binding transcription factor activity, etc. Conclusions: The results suggest that the methylation profile in patients with TS might be determined by the number of X chromosomes; the patterns of methylation in TS were precisely associated with the maintenance of genomic stability and improvement of gene expression. Differentially methylated genes/pathways might reveal the potential epigenetic modulation and lead to better understanding of TS. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 1710 KiB

Open AccessArticle

Distinct Phenotypes of Kidney Transplant Recipients in the United States with Limited Functional Status as Identified through Machine Learning Consensus Clustering

by Charat Thongprayoon, Caroline C. Jadlowiec, Wisit Kaewput, Pradeep Vaitla, Shennen A. Mao, Michael A. Mao, Napat Leeaphorn, Fawad Qureshi, Pattharawin Pattharanitima, Fahad Qureshi, Prakrati C. Acharya, Pitchaphon Nissaisorakarn, Matthew Cooper and Wisit Cheungpasitporn

J. Pers. Med. 2022, 12(6), 859; https://doi.org/10.3390/jpm12060859 - 25 May 2022

Cited by 2 | Viewed by 2539

Abstract

Background: There have been concerns regarding increased perioperative mortality, length of hospital stay, and rates of graft loss in kidney transplant recipients with functional limitations. The application of machine learning consensus clustering approach may provide a novel understanding of unique phenotypes of functionally [...] Read more.

Background: There have been concerns regarding increased perioperative mortality, length of hospital stay, and rates of graft loss in kidney transplant recipients with functional limitations. The application of machine learning consensus clustering approach may provide a novel understanding of unique phenotypes of functionally limited kidney transplant recipients with distinct outcomes in order to identify strategies to improve outcomes. Methods: Consensus cluster analysis was performed based on recipient-, donor-, and transplant-related characteristics in 3205 functionally limited kidney transplant recipients (Karnofsky Performance Scale (KPS) < 40% at transplant) in the OPTN/UNOS database from 2010 to 2019. Each cluster’s key characteristics were identified using the standardized mean difference. Posttransplant outcomes, including death-censored graft failure, patient death, and acute allograft rejection were compared among the clusters Results: Consensus cluster analysis identified two distinct clusters that best represented the clinical characteristics of kidney transplant recipients with limited functional status prior to transplant. Cluster 1 patients were older in age and were more likely to receive deceased donor kidney transplant with a higher number of HLA mismatches. In contrast, cluster 2 patients were younger, had shorter dialysis duration, were more likely to be retransplants, and were more likely to receive living donor kidney transplants from HLA mismatched donors. As such, cluster 2 recipients had a higher PRA, less cold ischemia time, and lower proportion of machine-perfused kidneys. Despite having a low KPS, 5-year patient survival was 79.1 and 83.9% for clusters 1 and 2; 5-year death-censored graft survival was 86.9 and 91.9%. Cluster 1 had lower death-censored graft survival and patient survival but higher acute rejection, compared to cluster 2. Conclusion: Our study used an unsupervised machine learning approach to characterize kidney transplant recipients with limited functional status into two clinically distinct clusters with differing posttransplant outcomes. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 1009 KiB

Open AccessArticle

Risk Factors of Incident Lung Cancer in Patients with Non-Cystic Fibrosis Bronchiectasis: A Korean Population-Based Study

by Youlim Kim, Kyungdo Han, Juhwan Yoo, Hyung Koo Kang, Tai Sun Park, Dong Won Park, Ji Young Hong, Ji-Yong Moon, Sang-Heon Kim, Tae Hyung Kim, Kwang Ha Yoo, Jang Won Sohn, Ho Joo Yoon, Hayoung Choi and Hyun Lee

Cancers 2022, 14(11), 2604; https://doi.org/10.3390/cancers14112604 - 25 May 2022

Cited by 5 | Viewed by 2636

Abstract

Background: Patients with non-cystic fibrosis bronchiectasis have an increased risk of lung cancer, followed by higher mortality in this population. Because the risk factors of lung cancer have not been well identified, this study aimed to investigate the risk factors of lung cancer [...] Read more.

Background: Patients with non-cystic fibrosis bronchiectasis have an increased risk of lung cancer, followed by higher mortality in this population. Because the risk factors of lung cancer have not been well identified, this study aimed to investigate the risk factors of lung cancer in individuals with newly diagnosed bronchiectasis. Methods: This cohort study using the Korean National Health Insurance Service database identified 7425 individuals with incident bronchiectasis among those who participated in the health screening exam in 2009. The cohort was followed from baseline to the date of incident: lung cancer, death, or until the end of the study period. We investigated the risk factors of lung cancer in participants with bronchiectasis using the Cox–proportional hazard models. Results: During median 8.3 years of follow-up duration, 1.9% (138/7425) developed lung cancer. In multivariable analyses, significant factors associated with increased risk of incident lung cancer included: males (adjusted hazard ratio [HR] = 3.54, 95% confidence interval [CI] = 2.17–5.79) than females, the overweight (adjusted HR = 1.55, 95% CI = 1.03–2.35) than the normal weight, current smokers (adjusted HR = 3.10, 95% CI = 2.00–4.79) than never smokers, participants living in the rural area (adjusted HR = 2.54, 95% CI = 1.68–3.85) than those living in the metropolitan area. Among comorbidities, chronic obstructive pulmonary disease was associated with an increased risk of lung cancer (adjusted HR = 1.46, 95% CI = 1.01–2.13) in participants with bronchiectasis. In contrast, mild alcohol consumption was associated with reduced risk of lung cancer (adjusted HR = 0.47, 95% CI = 0.29–0.74) in those with bronchiectasis. Conclusion: This Korean population-based study showed that males, current smoking, overweight, living in rural areas, and comorbid chronic obstructive pulmonary disease are associated with increased risk of lung cancer in individuals with bronchiectasis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 2916 KiB

Open AccessArticle

Reassessment of Reliability and Reproducibility for Triple-Negative Breast Cancer Subtyping

by Xinjian Yu, Yongjing Liu and Ming Chen

Cancers 2022, 14(11), 2571; https://doi.org/10.3390/cancers14112571 - 24 May 2022

Cited by 4 | Viewed by 2871

Abstract

Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no [...] Read more.

Triple-negative breast cancer (TNBC) is a heterogeneous disease with diverse, often poor prognoses and treatment responses. In order to identify targetable biomarkers and guide personalized care, scientists have developed multiple molecular classification systems for TNBC based on transcriptomic profiling. However, there is no consensus on the molecular subtypes of TNBC, likely due to discrepancies in technical and computational methods used by different research groups. Here, we reassessed the major steps for TNBC subtyping, validated the reproducibility of established TNBC subtypes, and identified two more subtypes with a larger sample size. By comparing results from different workflows, we demonstrated the limitations of formalin-fixed, paraffin-embedded samples, as well as batch effect removal across microarray platforms. We also refined the usage of computational tools for TNBC subtyping. Furthermore, we integrated high-quality multi-institutional TNBC datasets (discovery set: n = 457; validation set: n = 165). Performing unsupervised clustering on the discovery and validation sets independently, we validated four previously discovered subtypes: luminal androgen receptor, mesenchymal, immunomodulatory, and basal-like immunosuppressed. Additionally, we identified two potential intermediate states of TNBC tumors based on their resemblance with more than one well-characterized subtype. In summary, we addressed the issues and limitations of previous TNBC subtyping through comprehensive analyses. Our results promote the rational design of future subtyping studies and provide new insights into TNBC patient stratification. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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22 pages, 3533 KiB

Open AccessArticle

Gene Expression Monotonicity across Bladder Cancer Stages Informs on the Molecular Pathogenesis and Identifies a Prognostic Eight-Gene Signature

by Rafael Stroggilos, Maria Frantzi, Jerome Zoidakis, Marika Mokou, Napoleon Moulavasilis, Emmanouil Mavrogeorgis, Anna Melidi, Manousos Makridakis, Konstantinos Stravodimos, Maria G. Roubelakis, Harald Mischak and Antonia Vlahou

Cancers 2022, 14(10), 2542; https://doi.org/10.3390/cancers14102542 - 21 May 2022

Cited by 3 | Viewed by 3828

Abstract

Despite advancements in molecular classification, tumor stage and grade still remain the most relevant prognosticators used by clinicians to decide on patient management. Here, we leverage publicly available data to characterize bladder cancer (BLCA)’s stage biology based on increased sample sizes, identify potential [...] Read more.

Despite advancements in molecular classification, tumor stage and grade still remain the most relevant prognosticators used by clinicians to decide on patient management. Here, we leverage publicly available data to characterize bladder cancer (BLCA)’s stage biology based on increased sample sizes, identify potential therapeutic targets, and extract putative biomarkers. A total of 1135 primary BLCA transcriptomes from 12 microarray studies were compiled in a meta-cohort and analyzed for monotonal alterations in pathway activities, gene expression, and co-expression patterns with increasing stage (Ta–T1–T2–T3–T4), starting from the non-malignant tumor-adjacent urothelium. The TCGA-2017 and IMvigor-210 RNA-Seq data were used to validate our findings. Wnt, MTORC1 signaling, and MYC activity were monotonically increased with increasing stage, while an opposite trend was detected for the catabolism of fatty acids, circadian clock genes, and the metabolism of heme. Co-expression network analysis highlighted stage- and cell-type-specific genes of potentially synergistic therapeutic value. An eight-gene signature, consisting of the genes AKAP7, ANLN, CBX7, CDC14B, ENO1, GTPBP4, MED19, and ZFP2, had independent prognostic value in both the discovery and validation sets. This novel eight-gene signature may increase the granularity of current risk-to-progression estimators. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 1890 KiB

Open AccessEditor’s ChoiceArticle

Sex Differences in the Prevalence of Head and Neck Cancers: A 10-Year Follow-Up Study of 10 Million Healthy People

by Jun-Ook Park, Inn-Chul Nam, Choung-Soo Kim, Sung-Joon Park, Dong-Hyun Lee, Hyun-Bum Kim, Kyung-Do Han and Young-Hoon Joo

Cancers 2022, 14(10), 2521; https://doi.org/10.3390/cancers14102521 - 20 May 2022

Cited by 46 | Viewed by 3985

Abstract

Background: Descriptive epidemiologists have repeatedly reported that males are more susceptible to head and neck cancers. However, most published data are those of cross-sectional studies, and no population-based cohort study has yet been published. The aim of this study was to compare the [...] Read more.

Background: Descriptive epidemiologists have repeatedly reported that males are more susceptible to head and neck cancers. However, most published data are those of cross-sectional studies, and no population-based cohort study has yet been published. The aim of this study was to compare the prevalence of head and neck cancers in healthy males with females. Methods: A retrospective cohort study using the Korean National Health Insurance Service database on 9,598,085 individuals who underwent regular health checkups from 1 January to 31 December 2009. We sought head and neck cancers developed during the 10-year follow-up. Results: A total of 10,732 (incidence rate (IR) per 1000 person-years 0.25) individuals were newly diagnosed with head and neck cancer among the 9,598,085 individuals during the 10-year follow-up. The IR was 0.19 in males (8500 affected) and 0.06 in females (2232 affected). Notably, the male–female ratio increased with age below 70 years but decreased thereafter. The male–female difference was most apparent for laryngeal cancer; the male IR was 11-fold higher in the 40 s and 20-fold higher in the 60 s, followed by hypopharyngeal cancer (6.8- and 24.2-fold). Males smoked more and drank more alcohol than females (p < 0.0001 *, p < 0.0001 *). When never-smokers/-drinkers (only) were compared, males remained at a 2.9-fold higher risk of head and neck cancer than females. The hazard ratios for head and neck cancers in males tended to increase in the lower part of the upper aerodigestive tract: larynx (13.9) > hypopharynx (10.9) > oropharynx (4.4) > nasopharynx (2.9) > sinonasal region (1.8) > oral (1.6). Only the salivary gland cancer incidence did not differ between the sexes; the gland is not in the upper aerodigestive tract. Conclusion: Males are much more susceptible to head and neck cancers than females regardless of whether they drink alcohol or smoke tobacco. Sex differences in the incidence of head and neck cancer are most evident in the 60 s in the lower part of the upper aerodigestive tract, such as the larynx and hypopharynx. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 339 KiB

Open AccessArticle

Deep Splicer: A CNN Model for Splice Site Prediction in Genetic Sequences

by Elisa Fernandez-Castillo, Liliana Ibeth Barbosa-Santillán, Luis Falcon-Morales and Juan Jaime Sánchez-Escobar

Genes 2022, 13(5), 907; https://doi.org/10.3390/genes13050907 - 19 May 2022

Cited by 7 | Viewed by 3244

Abstract

Many living organisms have DNA in their cells that is responsible for their biological features. DNA is an organic molecule of two complementary strands of four different nucleotides wound up in a double helix. These nucleotides are adenine (A), thymine (T), guanine (G), [...] Read more.

Many living organisms have DNA in their cells that is responsible for their biological features. DNA is an organic molecule of two complementary strands of four different nucleotides wound up in a double helix. These nucleotides are adenine (A), thymine (T), guanine (G), and cytosine (C). Genes are DNA sequences containing the information to synthesize proteins. The genes of higher eukaryotic organisms contain coding sequences, known as exons and non-coding sequences, known as introns, which are removed on splice sites after the DNA is transcribed into RNA. Genome annotation is the process of identifying the location of coding regions and determining their function. This process is fundamental for understanding gene structure; however, it is time-consuming and expensive when done by biochemical methods. With technological advances, splice site detection can be done computationally. Although various software tools have been developed to predict splice sites, they need to improve accuracy and reduce false-positive rates. The main goal of this research was to generate Deep Splicer, a deep learning model to identify splice sites in the genomes of humans and other species. This model has good performance metrics and a lower false-positive rate than the currently existing tools. Deep Splicer achieved an accuracy between 93.55% and 99.66% on the genetic sequences of different organisms, while Splice2Deep, another splice site detection tool, had an accuracy between 90.52% and 98.08%. Splice2Deep surpassed Deep Splicer on the accuracy obtained after evaluating C. elegans genomic sequences (97.88% vs. 93.62%) and A. thaliana (95.40% vs. 94.93%); however, Deep Splicer’s accuracy was better for H. sapiens (98.94% vs. 97.15%) and D. melanogaster (97.14% vs. 92.30%). The rate of false positives was 0.11% for human genetic sequences and 0.25% for other species’ genetic sequences. Another splice prediction tool, Splice Finder, had between 1% and 3% of false positives for human sequences, while other species’ sequences had around 4% and 10%. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 1341 KiB

Open AccessArticle

Radioactive Iodine Treatment for Thyroid Cancer Patients Increases the Risk of Long-Term Gastrointestinal Disorders: A Nationwide Population-Based Cohort Analysis

by Yueh Lee, Chi-Hsiang Chung, Li-Fan Lin, Chuang-Hsin Chiu, Yi-Feng Chen, Chao-Feng Chang, Cheng-Yi Cheng and Wu-Chien Chien

Cancers 2022, 14(10), 2505; https://doi.org/10.3390/cancers14102505 - 19 May 2022

Cited by 3 | Viewed by 3526

Abstract

(1) Background: The study aimed to investigate the association between radioactive iodine (RAI) treatment and long-term gastrointestinal disorders including ulcers, atrophic gastritis, and secondary malignant neoplasm of the stomach in patients with thyroid cancer. (2) Methods: The data of the study were extracted [...] Read more.

(1) Background: The study aimed to investigate the association between radioactive iodine (RAI) treatment and long-term gastrointestinal disorders including ulcers, atrophic gastritis, and secondary malignant neoplasm of the stomach in patients with thyroid cancer. (2) Methods: The data of the study were extracted from the National Health Insurance Database (NHIRD) of Taiwan between 2000 to 2015. Patients of ages older than 20 with thyroid cancer after thyroidectomy were included and divided into groups with RAI (study cohort) and without RAI (comparison cohort). Multivariate Cox proportional hazards regression analysis and the Kaplan–Meier method were used for statistical analysis. (3) Results: A total of 7250 (with RAI: 5800, without RAI: 1450) patients were included. The Kaplan-Meier analysis revealed a significantly higher cumulative risk for overall gastrointestinal disorders in the group with RAI (log-rank p = 0.034). The risk for gastrointestinal disorders was higher when receiving a cumulative RAI dose higher than 1.11 GBq in the Cox regression analysis. In the subgroup analysis, the risks of gastric and duodenal ulcers are significantly higher in the group with RAI treatment. (4) Conclusions: This study revealed that RAI was associated with an increased risk for long-term gastrointestinal disorders, specifically gastric and duodenal ulcers, in thyroid cancer, especially when the cumulative dose exceeds 1.11 GBq. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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17 pages, 4884 KiB

Open AccessArticle

Physiologically-Based Pharmacokinetics Modeling for Hydroxychloroquine as a Treatment for Malaria and Optimized Dosing Regimens for Different Populations

by Jingchen Zhai, Beihong Ji, Lianjin Cai, Shuhan Liu, Yuchen Sun and Junmei Wang

J. Pers. Med. 2022, 12(5), 796; https://doi.org/10.3390/jpm12050796 - 14 May 2022

Cited by 5 | Viewed by 3098

Abstract

Malaria is a severe parasite infectious disease with high fatality. As one of the approved treatments of this disease, hydroxychloroquine (HCQ) lacks clinical administration guidelines for patients with special health conditions and co-morbidities. This may result in improper dosing for different populations and [...] Read more.

Malaria is a severe parasite infectious disease with high fatality. As one of the approved treatments of this disease, hydroxychloroquine (HCQ) lacks clinical administration guidelines for patients with special health conditions and co-morbidities. This may result in improper dosing for different populations and lead them to suffer from severe side effects. One of the most important toxicities of HCQ overdose is cardiotoxicity. In this study, we built and validated a physiologically based pharmacokinetic modeling (PBPK) model for HCQ. With the full-PBPK model, we predicted the pharmacokinetic (PK) profile for malaria patients without other co-morbidities under the HCQ dosing regimen suggested by Food and Drug Administration (FDA) guidance. The PK profiles for different special populations were also predicted and compared to the normal population. Moreover, we proposed a series of adjusted dosing regimens for different populations with special health conditions and predicted the concentration-time (C-T) curve of the drug plasma concentration in these populations which include the pregnant population, elderly population, RA patients, and renal impairment populations. The recommended special population-dependent dosage regimens can maintain the similar drug levels observed in the virtual healthy population under the original dosing regimen provided by FDA. Last, we developed mathematic formulas for predicting dosage based on a patient’s body measurements and two indexes of renal function (glomerular filtration rate and serum creatine level) for the pediatric and morbidly obese populations. Those formulas can facilitate personalized treatment of this disease. We hope to provide some advice to clinical practice when taking HCQ as a treatment for malaria patients with special health conditions or co-morbidities so that they will not suffer from severe side effects due to higher drug plasma concentration, especially cardiotoxicity. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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7 pages, 582 KiB

Open AccessReview

An Umbrella Review of the Evidence of Sex Determination Procedures in Forensic Dentistry

by João Albernaz Neves, Nathalie Antunes-Ferreira, Vanessa Machado, João Botelho, Luís Proença, Alexandre Quintas, Ana Sintra Delgado and José João Mendes

J. Pers. Med. 2022, 12(5), 787; https://doi.org/10.3390/jpm12050787 - 13 May 2022

Cited by 7 | Viewed by 2765

Abstract

Sex determination in forensic dentistry is a major step towards postmortem profiling. The most widely recognized method is DNA, yet its application in the dental field of forensic sciences is still impractical. Depending on the conditions of the remains, teeth are often the [...] Read more.

Sex determination in forensic dentistry is a major step towards postmortem profiling. The most widely recognized method is DNA, yet its application in the dental field of forensic sciences is still impractical. Depending on the conditions of the remains, teeth are often the only surviving organ. Some systematic reviews (SRs) have been recently produced; hence this umbrella review critically assesses their level of evidence and provides an overall comprehensive view. An electronic database search was conducted in four databases (PubMed, Cochrane, Web of Science, and LILACS) and three grey search engines up to December 2021, focusing on SRs of sex determination through forensic dentistry procedures. The methodological quality of the SRs was analyzed using the measurement tool to assess SRs criteria (AMSTAR2). Five SRs were included, two of critically low quality and three of low quality. The SRs posited that canines are the most dimorphic teeth; oral tissue remnants are a rich source for sex determination by DNA tracing; and artificial intelligence tools demonstrate high potential in forensic dentistry. The quality of evidence on sex determination using dental approaches was rated as low. Well-designed clinical trials and high standard systematic reviews are essential to corroborate the accuracy of the different procedures of sex determination in forensic dentistry. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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16 pages, 7751 KiB

Open AccessEditor’s ChoiceArticle

A Novel Cuproptosis-Related Prognostic Gene Signature and Validation of Differential Expression in Clear Cell Renal Cell Carcinoma

by Zilong Bian, Rong Fan and Lingmin Xie

Genes 2022, 13(5), 851; https://doi.org/10.3390/genes13050851 - 10 May 2022

Cited by 197 | Viewed by 16471

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cell carcinoma, which is characterized by metabolic reprogramming. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical impacts [...] Read more.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal cell carcinoma, which is characterized by metabolic reprogramming. Cuproptosis, a novel form of cell death, is highly linked to mitochondrial metabolism and mediated by protein lipoylation. However, the clinical impacts of cuproptosis-related genes (CRGs) in ccRCC largely remain unclear. In the current study, we systematically evaluated the genetic alterations of cuproptosis-related genes in ccRCC. Our results revealed that CDKN2A, DLAT, DLD, FDX1, GLS, PDHA1 and PDHB exhibited differential expression between ccRCC and normal tissues (|log₂(fold change)| > 2/3 and p < 0.05). Utilizing an iterative sure independence screening (SIS) method, we separately constructed the prognostic signature of CRGs for predicting the overall survival (OS) and progression-free survival (PFS) in ccRCC patients. The prognostic score of CRGs yielded an area under the curve (AUC) of 0.658 and 0.682 for the prediction of 5-year OS and PFS, respectively. In the Kaplan−Meier survival analysis of OS, a higher risk score of cuproptosis-related gene signature was significantly correlated with worse overall survival (HR = 2.72 (2.01–3.68), log-rank p = 1.76 × 10⁻⁷). Patients with a higher risk had a significantly shorter PFS (HR = 2.83 (2.08–3.85), log-rank p = 3.66 × 10⁻⁷). Two independent validation datasets (GSE40435 (N = 101), GSE53757 (N = 72)) were collected for meta-analysis, suggesting that CDKN2A (log₂(fold change) = 1.46, 95%CI: 1.75–2.35) showed significantly higher expression in ccRCC tissues while DLAT (log₂(fold change) = −0.54, 95%CI: −0.93–−0.15) and FDX1 (log₂(fold change) = −1.01, 95%CI: −1.61–−0.42) were lowly expressed. The expression of CDKN2A and FDX1 in ccRCC was also significantly associated with immune infiltration levels and programmed cell death protein 1 (PD-1) expression (CDKN2A: r = 0.24, p = 2.14 × 10⁻⁸; FDX1: r = −0.17, p = 1.37 × 10⁻⁴). In conclusion, the cuproptosis-related gene signature could serve as a potential prognostic predictor for ccRCC patients and may offer novel insights into the cancer treatment. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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28 pages, 5633 KiB

Open AccessArticle

A Novel Patient Similarity Network (PSN) Framework Based on Multi-Model Deep Learning for Precision Medicine

by Alramzana Nujum Navaz, Hadeel T. El-Kassabi, Mohamed Adel Serhani, Abderrahim Oulhaj and Khaled Khalil

J. Pers. Med. 2022, 12(5), 768; https://doi.org/10.3390/jpm12050768 - 10 May 2022

Cited by 8 | Viewed by 3671

Abstract

Precision medicine can be defined as the comparison of a new patient with existing patients that have similar characteristics and can be referred to as patient similarity. Several deep learning models have been used to build and apply patient similarity networks (PSNs). However, [...] Read more.

Precision medicine can be defined as the comparison of a new patient with existing patients that have similar characteristics and can be referred to as patient similarity. Several deep learning models have been used to build and apply patient similarity networks (PSNs). However, the challenges related to data heterogeneity and dimensionality make it difficult to use a single model to reduce data dimensionality and capture the features of diverse data types. In this paper, we propose a multi-model PSN that considers heterogeneous static and dynamic data. The combination of deep learning models and PSN allows ample clinical evidence and information extraction against which similar patients can be compared. We use the bidirectional encoder representations from transformers (BERT) to analyze the contextual data and generate word embedding, where semantic features are captured using a convolutional neural network (CNN). Dynamic data are analyzed using a long-short-term-memory (LSTM)-based autoencoder, which reduces data dimensionality and preserves the temporal features of the data. We propose a data fusion approach combining temporal and clinical narrative data to estimate patient similarity. The experiments we conducted proved that our model provides a higher classification accuracy in determining various patient health outcomes when compared with other traditional classification algorithms. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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24 pages, 1189 KiB

Open AccessArticle

A Data Science Approach for the Identification of Molecular Signatures of Aggressive Cancers

by Adriano Barbosa-Silva, Milena Magalhães, Gilberto Ferreira Da Silva, Fabricio Alves Barbosa Da Silva, Flávia Raquel Gonçalves Carneiro and Nicolas Carels

Cancers 2022, 14(9), 2325; https://doi.org/10.3390/cancers14092325 - 7 May 2022

Cited by 4 | Viewed by 4427

Abstract

The main hallmarks of cancer include sustaining proliferative signaling and resisting cell death. We analyzed the genes of the WNT pathway and seven cross-linked pathways that may explain the differences in aggressiveness among cancer types. We divided six cancer types (liver, lung, stomach, [...] Read more.

The main hallmarks of cancer include sustaining proliferative signaling and resisting cell death. We analyzed the genes of the WNT pathway and seven cross-linked pathways that may explain the differences in aggressiveness among cancer types. We divided six cancer types (liver, lung, stomach, kidney, prostate, and thyroid) into classes of high (H) and low (L) aggressiveness considering the TCGA data, and their correlations between Shannon entropy and 5-year overall survival (OS). Then, we used principal component analysis (PCA), a random forest classifier (RFC), and protein–protein interactions (PPI) to find the genes that correlated with aggressiveness. Using PCA, we found GRB2, CTNNB1, SKP1, CSNK2A1, PRKDC, HDAC1, YWHAZ, YWHAB, and PSMD2. Except for PSMD2, the RFC analysis showed a different list, which was CAD, PSMD14, APH1A, PSMD2, SHC1, TMEFF2, PSMD11, H2AFZ, PSMB5, and NOTCH1. Both methods use different algorithmic approaches and have different purposes, which explains the discrepancy between the two gene lists. The key genes of aggressiveness found by PCA were those that maximized the separation of H and L classes according to its third component, which represented 19% of the total variance. By contrast, RFC classified whether the RNA-seq of a tumor sample was of the H or L type. Interestingly, PPIs showed that the genes of PCA and RFC lists were connected neighbors in the PPI signaling network of WNT and cross-linked pathways. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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20 pages, 3532 KiB

Open AccessSystematic Review

The Effect of Probiotics on Intestinal Tight Junction Protein Expression in Animal Models: A Meta-Analysis

by Sung-Il Ahn, Sangbuem Cho, Eunjeong Jeon, Myungsun Park, Byungho Chae, Isaac Celestin Poaty Ditengou, Jr. and Nag-Jin Choi

Appl. Sci. 2022, 12(9), 4680; https://doi.org/10.3390/app12094680 - 6 May 2022

Cited by 6 | Viewed by 2836

Abstract

This study investigates the effect of probiotics supplementation on tight junction protein (TJP) expression in animal models by meta-analysis. We estimated the effect of probiotics administration in an animal inflammatory bowel disease model based on 47 collected articles from the databases, including Sciencedirect, [...] Read more.

This study investigates the effect of probiotics supplementation on tight junction protein (TJP) expression in animal models by meta-analysis. We estimated the effect of probiotics administration in an animal inflammatory bowel disease model based on 47 collected articles from the databases, including Sciencedirect, Pubmed, Scopus, and Google Scholar. The effect size was analyzed with the standardized mean difference, and the heterogeneity of the effect sizes was assessed using Cochran’s Q test. To explain the heterogeneity, moderate analyses, such as meta-ANOVA and meta-regression, were performed using the mixed effects model. Finally, publication bias was assessed using Egger’s linear regression test. Among the evaluated items, zonula occluden (ZO)-1 showed the highest Q statistics value, and the effect sizes of all items were positive with high significance (p < 0.0001). The I² value of all items reflected high heterogeneity (in excess of 80%). From the results of the meta-ANOVA, the factors of the heterogeneity found in the probiotics strains were investigated. Lactobacillus reuteri was identified as having the greatest effect on claudin and ZO-1 expression. The publication bias was detected by the Egger’s linear regression test, though it revealed that the occludin and ZO-1 had larger sample sizes than the claudin. In sum, this meta-analysis reveals that probiotics are effective at improving TJP expression in a gut environment of inflammatory bowel disease (IBD)-induced animal model. Our findings will interest IBD patients, as they suggest an area warranting future study. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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8 pages, 416 KiB

Open AccessArticle

Secondary Treatment for Men with Localized Prostate Cancer: A Pooled Analysis of PRIAS and ERSPC-Rotterdam Data within the PIONEER Data Platform

by Katharina Beyer, Vera Straten, Sebastiaan Remmers, Steven MacLennan, Sara MacLennan, Giorgio Gandaglia, Peter-Paul M. Willemse, Ronald Herrera, Muhammad Imran Omar, Beth Russell, Johannes Huber, Markus Kreuz, Alex Asiimwe, Tom Abbott, Alberto Briganti, Mieke Van Hemelrijck, Monique J. Roobol, The PRIAS Consortium, The ERSPC Rotterdam Study Group and The PIONEER Consortium

J. Pers. Med. 2022, 12(5), 751; https://doi.org/10.3390/jpm12050751 - 5 May 2022

Cited by 1 | Viewed by 2592

Abstract

Introduction: Treatment choice for localized prostate cancer is complicated, as each treatment option comes with various pros and cons. It is well established that active surveillance (AS), may be ended with a change to curative treatment at the time of disease progression, but [...] Read more.

Introduction: Treatment choice for localized prostate cancer is complicated, as each treatment option comes with various pros and cons. It is well established that active surveillance (AS), may be ended with a change to curative treatment at the time of disease progression, but it is less clear whether secondary treatment after initial curative treatment is required. As part of the PIONEER project, we quantified the probabilities of treatment change. Methods: A cohort study based on PRIAS and ERSPC-Rotterdam data was conducted. Patients were followed up for 10 years or until the 31st of December 2017. The primary outcome was the incidence of treatment change following initial treatment (i.e., a change to curative treatment following AS or secondary treatment after initial RP/RT). Results: Over a period of 1 to 5 years after initial treatment, the cumulative incidence of treatment change ranged from 3.8% to 42.8% for AS, from 7.6% to 12.1% for radical prostatectomy (RP) and from no change to 5.3% for radiation therapy (RT). While the possibility of treatment change in AS is known, the numbers within a five-year period were substantial. For RP and RT, the rate of change to secondary treatment was lower, but still non-neglectable, with 5 (10)-year incidences up to 12% (20%) and 5% (16%), respectively. Conclusion: This is one of the first studies comparing the incidence of guideline-recommended treatment changes in men receiving different primary treatments (i.e., AS, RT, or RP) for localized prostate cancer (PCa). Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 2224 KiB

Open AccessArticle

Osteosarcoma-Specific Genes as a Diagnostic Tool and Clinical Predictor of Tumor Progression

by Pattaralawan Sittiju, Parunya Chaiyawat, Dumnoensun Pruksakorn, Jeerawan Klangjorhor, Weerinrada Wongrin, Phichayut Phinyo, Rawikant Kamolphiwong, Areerak Phanphaisarn, Pimpisa Teeyakasem, Prachya Kongtawelert and Peraphan Pothacharoen

Biology 2022, 11(5), 698; https://doi.org/10.3390/biology11050698 - 1 May 2022

Cited by 8 | Viewed by 3631

Abstract

A liquid biopsy is currently an interesting tool for measuring tumor material with the advantage of being non-invasive. The overexpression of vimentin and ezrin genes was associated with epithelial-mesenchymal transition (EMT), a key process in metastasis and progression in osteosarcoma (OS). In this [...] Read more.

A liquid biopsy is currently an interesting tool for measuring tumor material with the advantage of being non-invasive. The overexpression of vimentin and ezrin genes was associated with epithelial-mesenchymal transition (EMT), a key process in metastasis and progression in osteosarcoma (OS). In this study, we identified other OS-specific genes by calculating differential gene expression using the Gene Expression Omnibus (GEO) database, confirmed by using quantitative reverse transcription-PCR (qRT-PCR) to detect OS-specific genes, including VIM and ezrin in the buffy coat, which were obtained from the whole blood of OS patients and healthy donors. Furthermore, the diagnostic model for OS detection was generated by utilizing binary logistic regression with a multivariable fractional polynomial (MFP) algorithm. The model incorporating VIM, ezrin, and COL5A2 genes exhibited outstanding discriminative ability, as determined by the receiver operating characteristic curve (AUC = 0.9805, 95% CI 0.9603, 1.000). At the probability cut-off value of 0.3366, the sensitivity and the specificity of the model for detecting OS were 98.63% (95% CI 90.5, 99.7) and 94.94% (95% CI 87.5, 98.6), respectively. Bioinformatic analysis and qRT-PCR, in our study, identified three candidate genes that are potential diagnostic and prognostic genes for OS. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 1025 KiB

Open AccessArticle

Optimal Timing of Cholecystectomy in Secondary Choledocholithiasis Patients Who Underwent Preoperative Endoscopic Retrograde Cholangiopancreatography

by Shang-Lin Ye, Sheng-Der Hsu, Wu-Chien Chien and Chi-Hsiang Chung

Appl. Sci. 2022, 12(9), 4574; https://doi.org/10.3390/app12094574 - 30 Apr 2022

Cited by 1 | Viewed by 2589

Abstract

Secondary choledocholithiasis occurs when stones leave the gallbladder. After therapeutic endoscopic retrograde cholangiopancreatography (ERCP) with stone removal, cholecystectomy should be performed to prevent recurrence. However, the optimal timing for cholecystectomy in secondary choledocholithiasis patients is unclear. The aim of this study was to [...] Read more.

Secondary choledocholithiasis occurs when stones leave the gallbladder. After therapeutic endoscopic retrograde cholangiopancreatography (ERCP) with stone removal, cholecystectomy should be performed to prevent recurrence. However, the optimal timing for cholecystectomy in secondary choledocholithiasis patients is unclear. The aim of this study was to determine the optimal timing for laparoscopic cholecystectomy in patients with secondary choledocholithiasis. In total, 22,996 patients in the Taiwan National Health Insurance Research Database (NHIRD) who underwent laparoscopic cholecystectomy for acute cholecystitis from 1998–2015 were divided into three groups according to whether they underwent surgery as an inpatient (early cholecystectomy (ELC)), within 2 months of admission (intermediate cholecystectomy (ILC)), or 2 months after admission (delayed cholecystectomy (DLC)). The primary outcomes included the recurrence, complication, and mortality rates. After adjusting for confounders, according to the 2013 Tokyo guidelines (cut-off at 2013), a subgroup analysis showed that, compared to the ELC group, the ILC group had lower recurrence, complication, and mortality rates, whereas the DLC group exhibited statistically significantly higher recurrence and mortality rates. In conclusion, the optimal timing of cholecystectomy in secondary choledocholithiasis patients after preoperative ERCP is within 2 months (ILC) after hospital admission. Moreover, ELC is associated with a measurable risk of complications. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 775 KiB

Open AccessArticle

Development and Assessment of the Validity and Reliability of the Short-Form Life Satisfaction Index (LSI-SF) among the Elderly Population

by Pei-Shan Li, Chia-Jung Hsieh, Eva Berthy Tallutondok, Ya-Ling Shih and Chieh-Yu Liu

J. Pers. Med. 2022, 12(5), 709; https://doi.org/10.3390/jpm12050709 - 28 Apr 2022

Cited by 5 | Viewed by 2579

Abstract

Background: Elderly care should focus on not only prolonging life but also satisfaction with elderly life. Our study investigated the reliability and validity of the Short-Form Life Satisfaction Index (LSI-SF). Method: Data were drawn from the 2015 Taiwan Longitudinal Study on Aging. Internal [...] Read more.

Background: Elderly care should focus on not only prolonging life but also satisfaction with elderly life. Our study investigated the reliability and validity of the Short-Form Life Satisfaction Index (LSI-SF). Method: Data were drawn from the 2015 Taiwan Longitudinal Study on Aging. Internal consistency reliability was used to confirm that the items measured the targeted characteristics. Construct validity was established by confirmatory factor analysis (CFA). Criterion-related validity was examined with the WHO-5 Well-Being Index as an indicator of quality of life. Known-group validity was determined from the difference between frailty stage and quality of life. Results: The high consistency reliability supported the reliability of the LSI-SF. Rigorous CFA validated the construct validity of the LSI-SF. Perfect convergent and discriminant validity supported the validity of the LSI-SF. In addition, there was a significant correlation between the LSI-SF and the WHO-5 Well-Being Index. The LSI-SF appears to be a reliable measure of quality of life in the elderly. We found that frailty status was associated with lower life satisfaction, which supported the known-group validity. Life satisfaction was highest in the non-frailty stage and lowest in the frailty stage. Conclusions: The LSI-SF appears to be a valid and reliable measure of satisfaction with elderly life. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 619 KiB

Open AccessArticle

Role of Metformin in Morbidity and Mortality Associated with Urinary Tract Infections in Patients with Type 2 Diabetes

by Fu-Shun Yen, James Cheng-Chung Wei, Ying-Hsiu Shih, Wei-Lin Pan, Chih-Cheng Hsu and Chii-Min Hwu

J. Pers. Med. 2022, 12(5), 702; https://doi.org/10.3390/jpm12050702 - 28 Apr 2022

Cited by 3 | Viewed by 2422

Abstract

We conducted this study to compare the morbidity and mortality associated with UTI and sepsis, between metformin users and nonusers in patients with diabetes. As such, 40,774 propensity score-matched metformin users and nonusers were identified from Taiwan’s National Health Insurance Research Database, between [...] Read more.

We conducted this study to compare the morbidity and mortality associated with UTI and sepsis, between metformin users and nonusers in patients with diabetes. As such, 40,774 propensity score-matched metformin users and nonusers were identified from Taiwan’s National Health Insurance Research Database, between 1 January 2000 and 31 December 2017. We adopted the Cox proportional hazards model with robust standard error estimates for comparing the risks of UTI, sepsis, and death due to UTI or sepsis, in patients with T2DM. Compared with the nonuse of metformin, the aHRs (95% CI) for metformin use in UTI, recurrent UTI, sepsis, and death due to UTI or sepsis were 1.06 (0.98, 1.15), 1.08 (0.97, 1.2), 1.01 (0.97, 1.06), and 0.58 (0.42, 0.8), respectively. The cumulative incidence of death due to UTI or sepsis was significantly lower in metformin users than in nonusers (p = 0.002). A longer cumulative duration of metformin use had a lower aHR in the risk of death due to UTI or sepsis than metformin nonuse. In patients with T2DM, metformin use showed no significant differences in the risks of UTI, recurrent UTI, or sepsis. However, it was associated with a lower risk of death due to UTI or sepsis than metformin nonuse. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 536 KiB

Open AccessEditor’s ChoiceArticle

Human Papillomavirus Infection and the Risk of Erectile Dysfunction: A Nationwide Population-Based Matched Cohort Study

by Sin-Ei Juang, Kevin Sheng-Kai Ma, Pei-En Kao, James Cheng-Chung Wei, Hei-Tung Yip, Mei-Chia Chou, Yao-Min Hung and Ning-Chien Chin

J. Pers. Med. 2022, 12(5), 699; https://doi.org/10.3390/jpm12050699 - 27 Apr 2022

Cited by 13 | Viewed by 3650

Abstract

Background: Male patients with genital warts are known for higher rates of sexual dysfunction. This study was conducted to investigate whether human papillomaviruses (HPV) infection is associated with an increased risk of erectile dysfunction (ED). Methods: Patients aged over 18 with HPV infection [...] Read more.

Background: Male patients with genital warts are known for higher rates of sexual dysfunction. This study was conducted to investigate whether human papillomaviruses (HPV) infection is associated with an increased risk of erectile dysfunction (ED). Methods: Patients aged over 18 with HPV infection (n = 13,296) and propensity score-matched controls (n = 53,184) were recruited from the Longitudinal Health Insurance Database (LHID). The primary endpoint was the diagnosis of ED. Chi-square tests were used to analyze the distribution of demographic characteristics. The Cox proportional hazards regression was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the development of ED in both groups, after adjusting for sex, age, relevant comorbidities, co-medication, and surgery. Results: ED developed in 181 patients of the study group. The incidence density of ED was 2.53 per 1000 person-years for the HPV group and 1.51 per 1000 person-years for the non-HPV group, with an adjusted HR (95% CI) of 1.63 (1.37–1.94). In stratification analysis, adjusted HR of diabetes-, chronic obstructive pulmonary disease (COPD-), and stroke-subgroup were 2.39, 2.51, and 4.82, with significant p values for interaction, respectively. Sensitivity analysis yields consistent findings. Conclusions: The patients with HPV infection had a higher risk of subsequent ED in comparison to the non-HPV controls. The mechanism behind such association and its possible role in ED prevention deserves further study in the future. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 4761 KiB

Open AccessEditor’s ChoiceArticle

A Risk Model of Eight Immune-Related Genes Predicting Prognostic Response to Immune Therapies for Gastric Cancer

by Miao Yu, Yi Zhang, Rongchen Mao, Chao Zhu, Ruixue Zhao and Lai Jin

Genes 2022, 13(5), 720; https://doi.org/10.3390/genes13050720 - 20 Apr 2022

Cited by 4 | Viewed by 3982

Abstract

Immune checkpoint inhibitor (ICI) treatment is considered as an innovative approach for cancers. Since not every patient responded well to ICI therapy, it is imperative to screen out novel signatures to predict prognosis. Based on 407 gastric cancer (GC) samples retrieved from The [...] Read more.

Immune checkpoint inhibitor (ICI) treatment is considered as an innovative approach for cancers. Since not every patient responded well to ICI therapy, it is imperative to screen out novel signatures to predict prognosis. Based on 407 gastric cancer (GC) samples retrieved from The Cancer Genome Atlas (TCGA), 36 immune-related hub genes were identified by weighted gene co-expression network analysis (WGCNA), and eight of them (RNASE2, CGB5, INHBE, DUSP1, APOA1, CD36, PTGER3, CTLA4) were used to formulate the Cox regression model. The obtained risk score was proven to be significantly correlated with overall survival (OS), consistent with the consequence of the Gene Expression Omnibus (GEO) cohort (n = 433). Then, the relationship between the risk score and clinical, molecular and immune characteristics was further investigated. Results showed that the low-risk subgroup exhibited higher mutation rate, more M1 macrophages, CD8⁺ and CD4⁺ T cells infiltrating, more active MHC-I, and bias to “IFN-γ Dominant” immune type, which is consistent with our current understanding of tumor prognostic risk. Furthermore, it is suggested that our model can accurately predict 1-, 2-, and 3-year OS of GC patients, and that it was superior to other canonical models, such as TIDE and TIS. Thus, these eight genes are probably considered as potential signatures to predict prognosis and to distinguish patient benefit from ICI, serving as a guiding individualized immunotherapy. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 1874 KiB

Open AccessArticle

Effects of Multi-Omics Characteristics on Identification of Driver Genes Using Machine Learning Algorithms

by Feng Li, Xin Chu, Lingyun Dai, Juan Wang, Jinxing Liu and Junliang Shang

Genes 2022, 13(5), 716; https://doi.org/10.3390/genes13050716 - 19 Apr 2022

Cited by 4 | Viewed by 2690

Abstract

Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging task. Most studies have detected cancer drivers with mutated traits, while few studies consider multiple omics characteristics as important factors. In this [...] Read more.

Cancer is a complex disease caused by genomic and epigenetic alterations; hence, identifying meaningful cancer drivers is an important and challenging task. Most studies have detected cancer drivers with mutated traits, while few studies consider multiple omics characteristics as important factors. In this study, we present a framework to analyze the effects of multi-omics characteristics on the identification of driver genes. We utilize four machine learning algorithms within this framework to detect cancer driver genes in pan-cancer data, including 75 characteristics among 19,636 genes. The 75 features are divided into four types and analyzed using Kullback–Leibler divergence based on CGC genes and non-CGC genes. We detect cancer driver genes in two different ways. One is to detect driver genes from a single feature type, while the other is from the top N features. The first analysis denotes that the mutational features are the best characteristics. The second analysis reveals that the top 45 features are the most effective feature combinations and superior to the mutational features. The top 45 features not only contain mutational features but also three other types of features. Therefore, our study extends the detection of cancer driver genes and provides a more comprehensive understanding of cancer mechanisms. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 1115 KiB

Open AccessArticle

Update on the Phenotypic and Genotypic Spectrum of KIF11-Related Retinopathy

by You Wang, Zhaotian Zhang, Li Huang, Limei Sun, Songshan Li, Ting Zhang and Xiaoyan Ding

Genes 2022, 13(4), 713; https://doi.org/10.3390/genes13040713 - 18 Apr 2022

Cited by 12 | Viewed by 3098

Abstract

Background: This study aimed to report the frequency of KIF11-mutations in a large familial exudative vitreoretinopathy (FEVR) population, extend the clinical spectrum of KIF11-associated retinopathy and compare KIF11-associated retinopathy to FEVR with mutations in other genes. Methods: Genetic data collected [...] Read more.

Background: This study aimed to report the frequency of KIF11-mutations in a large familial exudative vitreoretinopathy (FEVR) population, extend the clinical spectrum of KIF11-associated retinopathy and compare KIF11-associated retinopathy to FEVR with mutations in other genes. Methods: Genetic data collected from 696 FEVR families were reviewed. The ocular phenotypes in patients with KIF11 mutations were analyzed and compared with those of FEVR patients with mutations in other genes (FZD4, TSPAN12, LRP5, NDP and JAG1). Results: In a cohort of 696 FEVR families, disease-causing KIF11 mutations were identified in 3.6% of families (25/696). Among 25 KIF11 mutations, 80% (20/25) carried variants of loss of function and 48% (12/25) of variants were de novo. The phenotypes were variable. Compared with FEVR with disease-causing mutations in other genes, chorioretinal dysplasia was observed in 44.2% (31/70) of eyes with KIF11-associated retinopathy and in only 1.3% (1/70) of eyes with FEVR with mutations in other genes (p < 0.01). Increase and straightening of peripheral vessels (ISPV) was observed in 17.1% (12/70) of eyes with KIF11-associated retinopathy, and in 50% (39/78) of eyes with FEVR with mutations in other genes (p < 0.01). Conclusions: The frequency of the KIF11 mutation in FEVR was 3.6% in our database. The manifestation of KIF11-associated retinopathy was variable and different from the phenotype in FEVR caused by other genes. Chorioretinal dysplasia, instead of retinal folds, was the dominant phenotype in KIF11-associated retinopathy. ISPV was rare in KIF11-associated retinopathy. Moreover, our study revealed that most pathogenic KIF11 mutations were de novo. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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22 pages, 7790 KiB

Open AccessArticle

Deciphering of Adult Glioma Vulnerabilities through Expression Pattern Analysis of GABA, Glutamate and Calcium Neurotransmitter Genes

by Hoang Dong Nguyen, Phedias Diamandis, Michelle S. Scott and Maxime Richer

J. Pers. Med. 2022, 12(4), 633; https://doi.org/10.3390/jpm12040633 - 14 Apr 2022

Viewed by 2611

Abstract

Adult infiltrating gliomas are highly aggressive tumors of the central nervous system with a dismal prognosis despite intensive multimodal therapy (chemotherapy and/or radiotherapy). In this study, we studied the expression, methylation and interacting miRNA profiles of GABA-, glutamate- and calcium-related genes in 661 [...] Read more.

Adult infiltrating gliomas are highly aggressive tumors of the central nervous system with a dismal prognosis despite intensive multimodal therapy (chemotherapy and/or radiotherapy). In this study, we studied the expression, methylation and interacting miRNA profiles of GABA-, glutamate- and calcium-related genes in 661 adult infiltrating gliomas available through the TCGA database. Neurotransmitter-based unsupervised clustering identified three established glioma molecular subgroups that parallel major World Health Organization glioma subclasses (IDH-wildtype astrocytomas, IDH-mutant astrocytomas, IDH-mutant oligodendroglioma). In addition, this analysis also defined a novel, neurotransmitter-related glioma subgroup (NT-1), mostly comprised of IDH-mutated gliomas and characterized by the overexpression of neurotransmitter-related genes. Lower expression of neurotransmission-related genes was correlated with increased aggressivity in hypomethylated IDH-wildtype tumors. There were also significant differences in the composition of the tumor inflammatory microenvironment between neurotransmission-based tumor categories, with lower estimated pools of M2-phenotype macrophages in NT-1 gliomas. This multi-omics analysis of the neurotransmission expression landscape of TCGA gliomas—which highlights the existence of neurotransmission-based glioma categories with different expression, epigenetic and inflammatory profiles—supports the existence of operational neurotransmitter signaling pathways in adult gliomas. These findings could shed new light on potential vulnerabilities to exploit in future glioma-targeting drug therapies. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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9 pages, 595 KiB

Open AccessArticle

Association of Permanent Vascular Access Dysfunction with Subsequent Risk of Cardiovascular Disease: A Population-Based Cohort Study

by Tung-Wei Hung, Sheng-Wen Wu, Jeng-Yuan Chiou, Yu-Hsun Wang, Yu-Chan Liao and Cheng-Chung Wei

J. Pers. Med. 2022, 12(4), 598; https://doi.org/10.3390/jpm12040598 - 8 Apr 2022

Cited by 2 | Viewed by 2270

Abstract

A functional permanent vascular access (VA) is required to perform a successful hemodialysis procedure. Hemodialysis VA dysfunction is a major cause of morbidity and hospitalization in the hemodialysis population. Cardiovascular disease (CVD) is the leading cause of death in patients receiving chronic hemodialysis. [...] Read more.

A functional permanent vascular access (VA) is required to perform a successful hemodialysis procedure. Hemodialysis VA dysfunction is a major cause of morbidity and hospitalization in the hemodialysis population. Cardiovascular disease (CVD) is the leading cause of death in patients receiving chronic hemodialysis. Information about CVD associated with hemodialysis VA dysfunction is unclear. We analyzed the association between dialysis VA dysfunction and the risk of developing CVD in hemodialysis patients. This nationwide population-based cohort study was conducted using data from the National Health Insurance Research Database in Taiwan. One million subjects were sampled from 23 million beneficiaries and data was collected from 2000 to 2013. Patients with end-stage renal disease who had received permanent VA construction and hemodialysis and were aged at least 20 years old from 2000 to 2007 were included in the study population. The primary outcome was CVD, as defined by ICD-9-CM codes 410–414 and 430–437. A total of 197 individuals with permanent VA dysfunction were selected as the test group, and 100 individuals with non-permanent VA dysfunction were selected as the control group. Compared with the control group, the adjusted hazard ratio of CVD for the VA dysfunction group was 3.05 (95% CI: 1.14–8.20). A Kaplan–Meier analysis revealed that the cumulative incidence of CVD was higher in the permanent VA dysfunction group than in the comparison group. Permanent VA dysfunction is significantly associated with an increased risk of subsequent CVD. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 646 KiB

Open AccessArticle

Rhythm Control Better Prevents Dementia than Rate Control Strategies in Patients with Atrial Fibrillation—A Nationwide Cohort Study

by Jiunn-Cherng Lin, Cheng-Hung Li, Yun-Yu Chen, Chi-Jen Weng, Yu-Shan Chien, Shang-Ju Wu, Chu-Pin Lo, Hui-Chun Tien, Ching-Heng Lin, Jin-Long Huang, Yenn-Jiang Lin, Yu-Cheng Hsieh and Shih-Ann Chen

J. Pers. Med. 2022, 12(4), 572; https://doi.org/10.3390/jpm12040572 - 3 Apr 2022

Cited by 12 | Viewed by 2708

Abstract

Background: Atrial fibrillation (AF) increases the risk of dementia. Whether the pharmacological rhythm control of AF can reduce the risk of dementia compared to the rate control strategy remains unclear. We hypothesize that the rhythm control strategy is better than the rate control [...] Read more.

Background: Atrial fibrillation (AF) increases the risk of dementia. Whether the pharmacological rhythm control of AF can reduce the risk of dementia compared to the rate control strategy remains unclear. We hypothesize that the rhythm control strategy is better than the rate control strategy in preventing dementia. Methods: AF patients aged ≥65 years were identified from the Taiwan National Health Insurance Database. Patients receiving anti-arrhythmic drugs at a cumulative defined daily dose (cDDD) of >30 within the first year of enrollment constituted the rhythm control group. Patients who used rate control medications for a cDDD of >30 constituted the rate control group. A multivariate Cox hazards regression model was used to determine the hazard ratio (HR) for dementia. Results: A total of 3382 AF patients (698 in the rhythm control group; 2684 in the rate control group) were analyzed. During a 4.86 ± 3.38 year follow-up period, 414 dementia events occurred. The rhythm control group had a lower rate of dementia than the rate control group (adjust HR: 0.75, p = 0.031). The rhythm control strategy reduced the risk of dementia particularly in those receiving aspirin (p = 0.03). Conclusions: In patients with AF, pharmacological rhythm control was associated with a lower risk of dementia than rate control over a long-term follow-up period, particularly in patients receiving aspirin treatment. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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37 pages, 6640 KiB

Open AccessArticle

Decision Theory versus Conventional Statistics for Personalized Therapy of Breast Cancer

by Michael Kenn, Rudolf Karch, Dan Cacsire Castillo-Tong, Christian F. Singer, Heinz Koelbl and Wolfgang Schreiner

J. Pers. Med. 2022, 12(4), 570; https://doi.org/10.3390/jpm12040570 - 2 Apr 2022

Cited by 2 | Viewed by 2856

Abstract

Estrogen and progesterone receptors being present or not represents one of the most important biomarkers for therapy selection in breast cancer patients. Conventional measurement by immunohistochemistry (IHC) involves errors, and numerous attempts have been made to increase precision by additional information from gene [...] Read more.

Estrogen and progesterone receptors being present or not represents one of the most important biomarkers for therapy selection in breast cancer patients. Conventional measurement by immunohistochemistry (IHC) involves errors, and numerous attempts have been made to increase precision by additional information from gene expression. This raises the question of how to fuse information, in particular, if there is disagreement. It is the primary domain of Dempster–Shafer decision theory (DST) to deal with contradicting evidence on the same item (here: receptor status), obtained through different techniques. DST is widely used in technical settings, such as self-driving cars and aviation, and is also promising to deliver significant advantages in medicine. Using data from breast cancer patients already presented in previous work, we focus on comparing DST with classical statistics in this work, to pave the way for its application in medicine. First, we explain how DST not only considers probabilities (a single number per sample), but also incorporates uncertainty in a concept of ‘evidence’ (two numbers per sample). This allows for very powerful displays of patient data in so-called ternary plots, a novel and crucial advantage for medical interpretation. Results are obtained according to conventional statistics (ODDS) and, in parallel, according to DST. Agreement and differences are evaluated, and the particular merits of DST discussed. The presented application demonstrates how decision theory introduces new levels of confidence in diagnoses derived from medical data. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 1391 KiB

Open AccessArticle

Incident Rheumatoid Arthritis Following Statin Use: From the View of a National Cohort Study in Korea

by Mi Jung Kwon, Joo-Hee Kim, Ji Hee Kim, Hye-Rim Park, Nan Young Kim, Sangkyoon Hong and Hyo Geun Choi

J. Pers. Med. 2022, 12(4), 559; https://doi.org/10.3390/jpm12040559 - 1 Apr 2022

Cited by 7 | Viewed by 2435

Abstract

Safety issues regarding the potential risk of statins and incident rheumatoid arthritis (RA) have been raised, but the existing data are largely based on Caucasian populations, and continue to have biases and require further validation in Asian populations. Here, we aimed to verify [...] Read more.

Safety issues regarding the potential risk of statins and incident rheumatoid arthritis (RA) have been raised, but the existing data are largely based on Caucasian populations, and continue to have biases and require further validation in Asian populations. Here, we aimed to verify the risk of RA depending on the duration of previous statin use and statin types using a large-scale, nationwide database. This study enrolled 3149 patients with RA and 12,596 matched non-RA participants from the national health insurance database (2002–2015), and investigated their statin prescription histories for two years before the index date. Propensity score overlap-weighted logistic regression was applied after adjusting for multiple covariates. The prior use of any statins and, specifically, the long-term use of lipophilic statins (>365 days) were related to a lower likelihood of developing RA ((odds ratio (OR) = 0.73; 95% confidence intervals (CI) = 0.63–0.85, p < 0.001) and (OR = 0.71; 95% CI = 0.61–0.84, p < 0.001), respectively). Subgroup analyses supported these preventive effects on RA in those with dyslipidemia, independent of sex, age, smoking, alcohol use, hypertension, and hyperglycemia. Hydrophilic statin use or short-term use showed no such associations. Our study suggests that prior statin use, especially long-term lipophilic statin use, appears to confer preventive benefits against RA. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 2540 KiB

Open AccessArticle

CT Reconstruction Kernels and the Effect of Pre- and Post-Processing on the Reproducibility of Handcrafted Radiomic Features

by Turkey Refaee, Zohaib Salahuddin, Yousif Widaatalla, Sergey Primakov, Henry C. Woodruff, Roland Hustinx, Felix M. Mottaghy, Abdalla Ibrahim and Philippe Lambin

J. Pers. Med. 2022, 12(4), 553; https://doi.org/10.3390/jpm12040553 - 31 Mar 2022

Cited by 7 | Viewed by 4453

Abstract

Handcrafted radiomics features (HRFs) are quantitative features extracted from medical images to decode biological information to improve clinical decision making. Despite the potential of the field, limitations have been identified. The most important identified limitation, currently, is the sensitivity of HRF to variations [...] Read more.

Handcrafted radiomics features (HRFs) are quantitative features extracted from medical images to decode biological information to improve clinical decision making. Despite the potential of the field, limitations have been identified. The most important identified limitation, currently, is the sensitivity of HRF to variations in image acquisition and reconstruction parameters. In this study, we investigated the use of Reconstruction Kernel Normalization (RKN) and ComBat harmonization to improve the reproducibility of HRFs across scans acquired with different reconstruction kernels. A set of phantom scans (n = 28) acquired on five different scanner models was analyzed. HRFs were extracted from the original scans, and scans were harmonized using the RKN method. ComBat harmonization was applied on both sets of HRFs. The reproducibility of HRFs was assessed using the concordance correlation coefficient. The difference in the number of reproducible HRFs in each scenario was assessed using McNemar’s test. The majority of HRFs were found to be sensitive to variations in the reconstruction kernels, and only six HRFs were found to be robust with respect to variations in reconstruction kernels. The use of RKN resulted in a significant increment in the number of reproducible HRFs in 19 out of the 67 investigated scenarios (28.4%), while the ComBat technique resulted in a significant increment in 36 (53.7%) scenarios. The combination of methods resulted in a significant increment in 53 (79.1%) scenarios compared to the HRFs extracted from original images. Since the benefit of applying the harmonization methods depended on the data being harmonized, reproducibility analysis is recommended before performing radiomics analysis. For future radiomics studies incorporating images acquired with similar image acquisition and reconstruction parameters, except for the reconstruction kernels, we recommend the systematic use of the pre- and post-processing approaches (respectively, RKN and ComBat). Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 443 KiB

Open AccessReview

Update on Multiple Sclerosis Molecular Biomarkers to Monitor Treatment Effects

by Viviana Nociti, Marina Romozzi and Massimiliano Mirabella

J. Pers. Med. 2022, 12(4), 549; https://doi.org/10.3390/jpm12040549 - 31 Mar 2022

Cited by 7 | Viewed by 4231

Abstract

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system characterized by broad inter- and intraindividual heterogeneity. The relapse rate, disability progression, and lesion load assessed through MRI are used to detect disease activity and response to treatment. Although [...] Read more.

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease of the central nervous system characterized by broad inter- and intraindividual heterogeneity. The relapse rate, disability progression, and lesion load assessed through MRI are used to detect disease activity and response to treatment. Although it is possible to standardize these characteristics in larger patient groups, so far, this has been difficult to achieve in individual patients. Easily detectable molecular biomarkers can be powerful tools, permitting a tailored therapy approach for MS patients. However, only a few molecular biomarkers have been routinely used in clinical practice as the validation process, and their transfer into clinical practice takes a long time. This review describes the characteristics of an ideal MS biomarker, the challenges of establishing new biomarkers, and promising molecular biomarkers from blood or CSF samples used to monitor MS treatment effects in clinical practice. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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9 pages, 561 KiB

Open AccessArticle

Pooled Analysis of Complications with Transvenous ICD Compared to Subcutaneous ICD in Patients with Catecholaminergic Polymorphic Ventricular Arrhythmia

by Henrik Eckert, Ibrahim El-Battrawy, Michael Veith, Gretje Roterberg, Jacqueline Kowitz, Siegfried Lang, Xiaobo Zhou, Ibrahim Akin, Andreas Mügge and Assem Aweimer

J. Pers. Med. 2022, 12(4), 536; https://doi.org/10.3390/jpm12040536 - 28 Mar 2022

Cited by 9 | Viewed by 2696

Abstract

Background: Catecholaminergic polymorphic ventricular tachycardia (CPVT) is associated with arrhythmic events which may lead to sudden cardiac death (SCD). A leading therapy for CPVT besides medical treatment with beta-blockers is the use of an implantable cardioverter-defibrillator (ICD). For this paper we compared data [...] Read more.

Background: Catecholaminergic polymorphic ventricular tachycardia (CPVT) is associated with arrhythmic events which may lead to sudden cardiac death (SCD). A leading therapy for CPVT besides medical treatment with beta-blockers is the use of an implantable cardioverter-defibrillator (ICD). For this paper we compared data from a pooled analysis to get further evidence about the complications of transvenous and subcutaneous ICDs. Methods: We gathered data from a search of PubMed, Web of Science, Cochrane Library and Cinahl. For our analysis, we chose 30 studies with a total number of 784 patients. We compared the data regarding complications caused by different ICD device types. Results: During a mean follow up of 38.9 months for the patients with ICD implantation (n = 337), data showed a complication rate of 101 (30%). A total of 330 (98%) of them received a transvenous-ICD (T-ICD) and 7 (2%) a subcutaneous-ICD (S-ICD). A total of 97 (29.4%) of the T-ICD patients and 4 (57.1%) of the S-ICD patients had at least one complication. Of the 234 complications that occurred in T-ICD patients 152 (65%) were inappropriate shocks due to supraventricular arrhythmias, T/R-wave oversensing or electrode defect, 26 (11.1%) lead fracture/failure, 1 (0.4%) electrode defect, 46 were (19.7%) events of electrical storms, 1 (0.4%) thromboembolic event, 2 (0.8%) cases of endocarditis and 6 (2.6%) infections of the ICD-pocket. Ten (100%) of the complications for the four patients with the S-ICD were an event of an inappropriate shock due to supraventricular arrhythmias, T/R-wave oversensing or electrode defect. Conclusion: Subcutaneous ICDs (S-ICD) show a certain advantage over T-ICDs regarding lead-related complications. Nevertheless, they still show problems with inappropriate shocks and other ICD related complications. Therefore, a case-by-case decision is advised, but the continuous improvement of S-ICD might make it an overall advantageous therapy option in the future. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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21 pages, 3884 KiB

Open AccessArticle

Association of Elevated Expression Levels of COL4A1 in Stromal Cells with an Immunosuppressive Tumor Microenvironment in Low-Grade Glioma, Pancreatic Adenocarcinoma, Skin Cutaneous Melanoma, and Stomach Adenocarcinoma

by Hyo-Jae Shin, Minchan Gil and Im-Soon Lee

J. Pers. Med. 2022, 12(4), 534; https://doi.org/10.3390/jpm12040534 - 28 Mar 2022

Cited by 5 | Viewed by 3570

Abstract

Aberrant expression of collagen type IV alpha chain 1 (COL4A1) can influence tumor cell behavior. To examine the association of COL4A1 expression in the tumor microenvironment (TME) with tumor progression, we performed bioinformatics analyses of The Cancer Genome Atlas RNA sequencing [...] Read more.

Aberrant expression of collagen type IV alpha chain 1 (COL4A1) can influence tumor cell behavior. To examine the association of COL4A1 expression in the tumor microenvironment (TME) with tumor progression, we performed bioinformatics analyses of The Cancer Genome Atlas RNA sequencing and RNA microarray datasets available in public databases and identified upregulated COL4A1 expression in most examined tumor types compared to their normal counterparts. The elevated expression of COL4A1 was correlated with low survival rates of patients with low-grade glioma, pancreatic adenocarcinoma, skin cutaneous melanoma, and stomach adenocarcinoma, thus suggesting its potential use as a biomarker for the poor prognosis of these tumors. However, COL4A1 was mostly expressed in adjacent stromal cells, such as cancer-associated fibroblasts (CAFs) and endothelial cells. Additionally, COL4A1 expression was highly correlated with the signatures of CAFs and endothelial cells in all four tumor types. The expression of marker genes for the infiltration of pro-tumoral immune cells, such as Treg, M2, and TAM, and those of immunosuppressive cytokines exhibited very strong positive correlations with COL4A1 expression. Collectively, our data suggest that COL4A1 overexpression in stromal cells may be a potential regulator of tumor-supporting TME composition associated with poor prognosis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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27 pages, 5234 KiB

Open AccessArticle

In Silico Bioinformatics Followed by Molecular Validation Using Archival FFPE Tissue Biopsies Identifies a Panel of Transcripts Associated with Severe Asthma and Lung Cancer

by Laila Salameh, Poorna Manasa Bhamidimarri, Narjes Saheb Sharif-Askari, Youssef Dairi, Sarah Musa Hammoudeh, Amena Mahdami, Mouza Alsharhan, Syed Hammad Tirmazy, Surendra Singh Rawat, Hauke Busch, Qutayba Hamid, Saba Al Heialy, Rifat Hamoudi and Bassam Mahboub

Cancers 2022, 14(7), 1663; https://doi.org/10.3390/cancers14071663 - 25 Mar 2022

Cited by 3 | Viewed by 4372

Abstract

Severe asthma and lung cancer are both heterogeneous pathological diseases affecting the lung tissue. Whilst there are a few studies that suggest an association between asthma and lung cancer, to the best of our knowledge, this is the first study to identify common [...] Read more.

Severe asthma and lung cancer are both heterogeneous pathological diseases affecting the lung tissue. Whilst there are a few studies that suggest an association between asthma and lung cancer, to the best of our knowledge, this is the first study to identify common genes involved in both severe asthma and lung cancer. Publicly available transcriptomic data for 23 epithelial brushings from severe asthmatics and 55 samples of formalin-fixed paraffin-embedded (FFPE) lung cancer tissue at relatively early stages were analyzed by absolute gene set enrichment analysis (GSEA) in comparison to 37 healthy bronchial tissue samples. The key pathways enriched in asthmatic patients included adhesion, extracellular matrix, and epithelial cell proliferation, which contribute to tissue remodeling. In the lung cancer dataset, the main pathways identified were receptor tyrosine kinase signaling, wound healing, and growth factor response, representing the early cancer pathways. Analysis of the enriched genes derived from the pathway analysis identified seven genes expressed in both the asthma and lung cancer sets: BCL3, POSTN, PPARD, STAT1, MYC, CD44, and FOSB. The differential expression of these genes was validated in vitro in the cell lines retrieved from different lung cancer and severe asthma patients using real-time PCR. The effect of the expression of the seven genes identified in the study on the overall survival of lung cancer patients (n = 1925) was assessed using a Kaplan–Meier plot. In vivo validation performed in the archival biopsies obtained from patients diagnosed with both the disease conditions provided interesting insights into the pathogenesis of severe asthma and lung cancer, as indicated by the differential expression pattern of the seven transcripts in the mixed group as compared to the asthmatics and lung cancer samples alone. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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19 pages, 798 KiB

Open AccessArticle

DeepBiomarker: Identifying Important Lab Tests from Electronic Medical Records for the Prediction of Suicide-Related Events among PTSD Patients

by Oshin Miranda, Peihao Fan, Xiguang Qi, Zeshui Yu, Jian Ying, Haohan Wang, David A. Brent, Jonathan C. Silverstein, Yu Chen and Lirong Wang

J. Pers. Med. 2022, 12(4), 524; https://doi.org/10.3390/jpm12040524 - 24 Mar 2022

Cited by 8 | Viewed by 4059

Abstract

Identifying patients with high risk of suicide is critical for suicide prevention. We examined lab tests together with medication use and diagnosis from electronic medical records (EMR) data for prediction of suicide-related events (SREs; suicidal ideations, attempts and deaths) in post-traumatic stress disorder [...] Read more.

Identifying patients with high risk of suicide is critical for suicide prevention. We examined lab tests together with medication use and diagnosis from electronic medical records (EMR) data for prediction of suicide-related events (SREs; suicidal ideations, attempts and deaths) in post-traumatic stress disorder (PTSD) patients, a population with a high risk of suicide. We developed DeepBiomarker, a deep-learning model through augmenting the data, including lab tests, and integrating contribution analysis for key factor identification. We applied DeepBiomarker to analyze EMR data of 38,807 PTSD patients from the University of Pittsburgh Medical Center. Our model predicted whether a patient would have an SRE within the following 3 months with an area under curve score of 0.930. Through contribution analysis, we identified important lab tests for suicide prediction. These identified factors imply that the regulation of the immune system, respiratory system, cardiovascular system, and gut microbiome were involved in shaping the pathophysiological pathways promoting depression and suicidal risks in PTSD patients. Our results showed that abnormal lab tests combined with medication use and diagnosis could facilitate predicting SRE risk. Moreover, this may imply beneficial effects for suicide prevention by treating comorbidities associated with these biomarkers. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 870 KiB

Open AccessArticle

Inherited and De Novo Variation in Lithuanian Genomes: Introduction to the Analysis of the Generational Shift

by Alina Urnikyte, Laura Pranckeniene, Ingrida Domarkiene, Svetlana Dauengauer-Kirliene, Alma Molyte, Ausra Matuleviciene, Ingrida Pilypiene and Vaidutis Kučinskas

Genes 2022, 13(4), 569; https://doi.org/10.3390/genes13040569 - 23 Mar 2022

Cited by 3 | Viewed by 2833

Abstract

Most genetic variants are rare and specific to the population, highlighting the importance of characterizing local population genetic diversity. Many countries have initiated population-based whole-genome sequencing (WGS) studies. Genomic variation within Lithuanian families are not available in the public databases. Here, we describe [...] Read more.

Most genetic variants are rare and specific to the population, highlighting the importance of characterizing local population genetic diversity. Many countries have initiated population-based whole-genome sequencing (WGS) studies. Genomic variation within Lithuanian families are not available in the public databases. Here, we describe initial findings of a high-coverage (an average of 36.27×) whole genome sequencing for 25 trios of the Lithuanian population. Each genome on average carried approximately 4,701,473 (±28,255) variants, where 80.6% (3,787,626) were single nucleotide polymorphisms (SNPs), and the rest 19.4% were indels. An average of 12.45% was novel according to dbSNP (build 150). The WGS structural variation (SV) analysis identified on average 9133 (±85.10) SVs, of which 95.85% were novel. De novo single nucleotide variation (SNV) analysis identified 4417 variants, where 1.1% de novo SNVs were exonic, 43.9% intronic, 51.9% intergenic, and the rest 3.13% in UTR or downstream sequence. Three potential pathogenic de novo variants in the ZSWIM8, CDC42EP1, and RELA genes were identified. Our findings provide useful information on local human population genomic variation, especially for de novo variants, and will be a valuable resource for further genetic studies, and medical implications. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 259 KiB

Open AccessArticle

Sex Differences in Clinical Characteristics and Outcomes of Patients with SARS-CoV-2-Infection Admitted to Intensive Care Units in Austria

by Alexandra Kautzky-Willer, Michaela Kaleta, Simon D. Lindner, Michael Leutner, Stefan Thurner and Peter Klimek

J. Pers. Med. 2022, 12(4), 517; https://doi.org/10.3390/jpm12040517 - 23 Mar 2022

Cited by 3 | Viewed by 2600

Abstract

Importance: A male predominance is reported in hospitalised patients with COVID-19 alongside a higher mortality rate in men compared to women. Objective: To assess if the reported sex bias in the COVID-19 pandemic is validated by analysis of a subset of patients with [...] Read more.

Importance: A male predominance is reported in hospitalised patients with COVID-19 alongside a higher mortality rate in men compared to women. Objective: To assess if the reported sex bias in the COVID-19 pandemic is validated by analysis of a subset of patients with severe disease. Design: A nationwide retrospective cohort study was performed using the Austrian National COVID Database. We performed a sex-specific Lasso regression to select the covariates best explaining the outcomes of mechanical ventilation and death using variables known before ICU admission. We use logistic regression to construct a sex-specific “risk score” for the outcomes using these variables. Setting: We studied the characteristics and outcomes of patients admitted to intensive care units (ICUs) in Austria. Participants: 5118 patients admitted to the ICU in Austria with a COVID-19 diagnosis in 03/2020–03/2021. Exposures: Demographic and clinical characteristics, vital signs and laboratory tests, comorbidities, and management of patients admitted to ICUs were analysed for possible sex differences. Main outcomes and measures: The aim was to define risk scores for mechanical ventilation and mortality for each sex to provide better sex-sensitive management and outcomes in the future. Results: We found balanced accuracies between 55% and 65% to predict the outcomes. Regarding outcome death, we found that the risk score for pre-ICU variables increases with age, renal insufficiency (f: OR 1.7(2), m: 1.9(2)) and decreases with observance as admission cause (f: OR 0.33(5), m: 0.36(5)). Additionally, the risk score for females also includes respiratory insufficiency (OR 2.4(4)) while heart failure for males only (OR 1.5(1)). Conclusions and relevance: Better knowledge of how sex influences COVID-19 outcomes at ICUs will have important implications for the ongoing pandemic’s clinical care and management strategies. Identifying sex-specific features in individuals with COVID-19 and fatal consequences might inform preventive strategies and public health services. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

16 pages, 4186 KiB

Open AccessArticle

Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients

by Sergey G. Shcherbak, Anton I. Changalidi, Yury A. Barbitoff, Anna Yu. Anisenkova, Sergei V. Mosenko, Zakhar P. Asaulenko, Victoria V. Tsay, Dmitrii E. Polev, Roman S. Kalinin, Yuri A. Eismont, Andrey S. Glotov, Evgeny Y. Garbuzov, Alexander N. Chernov, Olga A. Klitsenko, Mikhail O. Ushakov, Anton E. Shikov, Stanislav P. Urazov, Vladislav S. Baranov and Oleg S. Glotov

Genes 2022, 13(3), 534; https://doi.org/10.3390/genes13030534 - 17 Mar 2022

Cited by 5 | Viewed by 3772

Abstract

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an [...] Read more.

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an analysis might be complicated in cohorts of limited size and/or in case of limited breadth of genome coverage. In this work, we tried to circumvent these challenges by searching for candidate genes and genetic variants associated with a variety of quantitative and binary traits in a cohort of 840 COVID-19 patients from Russia. While we found no gene- or pathway-level associations with the disease severity and outcome, we discovered eleven independent candidate loci associated with quantitative traits in COVID-19 patients. Out of these, the most significant associations correspond to rs1651553 in MYH14p = 1.4 × 10⁻⁷), rs11243705 in SETX (p = 8.2 × 10⁻⁶), and rs16885 in ATXN1 (p = 1.3 × 10⁻⁵). One of the identified variants, rs33985936 in SCN11A, was successfully replicated in an independent study, and three of the variants were found to be associated with blood-related quantitative traits according to the UK Biobank data (rs33985936 in SCN11A, rs16885 in ATXN1, and rs4747194 in CDH23). Moreover, we show that a risk score based on these variants can predict the severity and outcome of hospitalization in our cohort of patients. Given these findings, we believe that our work may serve as proof-of-concept study demonstrating the utility of quantitative traits and extensive phenotyping for identification of genetic risk factors of severe COVID-19. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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15 pages, 2878 KiB

Open AccessArticle

De Novo Transcriptome Analysis Reveals Putative Genes Involved in Anthraquinone Biosynthesis in Rubia yunnanensis

by Rongfei Zhang, Yuanyuan Miao, Lingyun Chen, Shanyong Yi and Ninghua Tan

Genes 2022, 13(3), 521; https://doi.org/10.3390/genes13030521 - 16 Mar 2022

Cited by 9 | Viewed by 2835

Abstract

Rubia yunnanensis Diels (R. yunnanensis), a Chinese perennial plant, is well-known for its medicinal values such as rheumatism, contusion, and anemia. It is rich in bioactive anthraquinones, but the biosynthetic pathways of anthraquinones in R. yunnanensis remain unknown. To investigate genes [...] Read more.

Rubia yunnanensis Diels (R. yunnanensis), a Chinese perennial plant, is well-known for its medicinal values such as rheumatism, contusion, and anemia. It is rich in bioactive anthraquinones, but the biosynthetic pathways of anthraquinones in R. yunnanensis remain unknown. To investigate genes involved in anthraquinone biosynthesis in R. yunnanensis, we generated a de novo transcriptome of R. yunnanensis using the Illumina HiSeq 2500 sequencing platform. A total of 636,198 transcripts were obtained, in which 140,078 transcripts were successfully annotated. A differential gene expression analysis identified 15 putative genes involved in anthraquinone biosynthesis. Additionally, the hairy roots of R. yunnanensis were treated with 200 µM Methyl Jasmonate (MeJA). The contents of six bioactive anthraquinones and gene expression levels of 15 putative genes were measured using ultra performance liquid chromatography coupled with mass spectrometry (UPLC-MS/MS) and real-time quantitative polymerase chain reaction (RT-qPCR), respectively. The results showed that the expressions levels for 11 of the 15 genes and the contents of two of six anthraquinones significantly increased by MeJA treatment. Pearson’s correlation analyses indicated that the expressions of 4 of the 15 putative genes were positively correlated with the contents of rubiquinone (Q3) and rubiquinone-3-O-β-d-xylopranosyl-(1→6)-β-d-glucopyranoside (Q20). This study reported the first de novo transcriptome of R. yunnanensis and shed light on the anthraquinone biosynthesis and genetic information for R. yunnanensis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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9 pages, 803 KiB

Open AccessArticle

Association between Spinal Cord Injury and Alcohol Dependence: A Population-Based Retrospective Cohort Study

by Ching-Hui Chuang, Po-Cheng Chen, Chyi-Huey Bai, Yi-Lin Wu, Ming-Chao Tsai and Chieh-Yu Li

J. Pers. Med. 2022, 12(3), 473; https://doi.org/10.3390/jpm12030473 - 16 Mar 2022

Cited by 3 | Viewed by 2472

Abstract

Spinal cord injury (SCI) is a devastating disorder. Alcohol abuse has been recognized as hindering SCI patients from rehabilitation, thus leading to longer length of days and poorer prognosis. This article aimed to investigate the association between spinal cord injury (SCI) and alcohol [...] Read more.

Spinal cord injury (SCI) is a devastating disorder. Alcohol abuse has been recognized as hindering SCI patients from rehabilitation, thus leading to longer length of days and poorer prognosis. This article aimed to investigate the association between spinal cord injury (SCI) and alcohol dependence. Data were derived from the National Health Insurance Research Database (NHIRD). The incidence of alcohol dependence between SCI and non-SCI groups was compared. Other possible risk factors were also analyzed. Patients (N = 5670) with SCI from 2000 to 2009 were initially assessed for eligibility. After propensity score matching, 5639 first-time SCI survivors were included. The Cox proportional hazard regression model was used to assess differences in the incidence of alcohol dependence syndrome. Based on the adjusted hazard ratios (HR), the SCI group had a higher hazard for alcohol dependence syndrome compared to the non-SCI group (adjusted HR: 1.39, 95% CI: 1.03~1.86, p = 0.0305). The injury level did not have an impact on the incidence of alcohol dependence syndrome. A higher incidence of alcohol dependence syndrome was related to male patients, lower insurance levels, higher Deyo’s CCI, and psychiatric OPD times. A lower incidence of alcohol dependence syndrome was related to elder age. The incidence of alcohol dependence increased after the occurrence of SCI and was also related to age, sex, monthly income, comorbidities, and psychiatric problems. The injury level did not affect the incidence of alcohol dependence after SCI. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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19 pages, 4352 KiB

Open AccessArticle

RNA-Seq Reveals Differentially Expressed Genes Associated with High Fiber Quality in Abaca (Musa textilis Nee)

by Nelzo C. Ereful, Antonio G. Lalusin and Antonio C. Laurena

Genes 2022, 13(3), 519; https://doi.org/10.3390/genes13030519 - 15 Mar 2022

Cited by 4 | Viewed by 4240

Abstract

Despite the importance of and current demand for abaca (Musa textilis Nee) fiber, there has been limited study that capitalizes on RNA-seq to identify candidate genes associated with high fiber quality and bunchy top virus (AbBTV) resistance. Three varieties (Abuab, Inosa, and [...] Read more.

Despite the importance of and current demand for abaca (Musa textilis Nee) fiber, there has been limited study that capitalizes on RNA-seq to identify candidate genes associated with high fiber quality and bunchy top virus (AbBTV) resistance. Three varieties (Abuab, Inosa, and Tangongon), one wild banana variety (Musa balbisiana Colla) Pacol, and two developed backcrosses (Abuab × Pacol BC₂ and BC₃) were grown at the Institute of Plant Breeding (IPB), Laguna, Philippines. The pseudostems of 3-month-old suckers of each genotype were sampled for RNA-seq. Datasets were analyzed for differential expression (DE) implementing various model frameworks, including pairwise, genotypic and non-DE models. Results indicate that Abuab and BC₃ induce the highest proportion (70%) of abaca-specific genes. Gene ontology (GO) enrichment analysis showed several genes associated with cellulose synthase activity, callose synthase, ß-glucosidase activity, glucan biosynthetic process, etc. KEGG pathway analysis showed several genes encoding for enzymes involved in the lignin biosynthetic pathway. Analysis using genotypic DE (GDE) between abaca bunchy top virus (AbBTV)-resistant and -susceptible groups revealed genes such as pathogenesis-related protein and NBS-LRR. As the genotypes were not infected with the pathogen, these genes are yet to be confirmed for their roles in disease resistance and are an interesting subject for further investigation. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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18 pages, 2681 KiB

Open AccessArticle

Screening the Significant Hub Genes by Comparing Tumor Cells, Normoxic and Hypoxic Glioblastoma Stem-like Cell Lines Using Co-Expression Analysis in Glioblastoma

by Emine Güven, Muhammad Afzal and Imran Kazmi

Genes 2022, 13(3), 518; https://doi.org/10.3390/genes13030518 - 15 Mar 2022

Cited by 3 | Viewed by 3114

Abstract

Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, [...] Read more.

Glioblastoma multiforme (GBM) is categorized by rapid malignant cellular growth in the central nervous system (CNS) tumors. It is one of the most prevailing primary brain tumors, particularly in human male adults. Even though the combination therapy comprises surgery, chemotherapy, and adjuvant therapies, the survival rate is on average 14.6 months. Glioma stem cells (GSCs) have key roles in tumorigenesis, progression, and counteracting chemotherapy and radiotherapy. In our study, firstly, the gene expression dataset GSE45117 was retrieved and differentially expressed genes (DEGs) were spotted. The co-expression network analysis was employed on DEGs to find the significant modules. The most significant module resulting from co-expression analysis was the turquoise module. The turquoise module related to the tumor cells, hypoxia, normoxic treatments of glioblastoma tumor (GBT), and GSCs were screened. Sixty-one common genes in the turquoise module were selected generated through the co-expression analysis and protein–protein interaction (PPI) network. Moreover, the GO and KEGG pathway enrichment results were studied. Twenty common hub genes were screened by the NetworkAnalyst web instrument constructed on the PPI network through the STRING database. After survival analysis via the Kaplan–Meier (KM) plotter from The Cancer Genome Atlas (TCGA) database, we identified the five most significant hub genes strongly related to the progression of GBM. We further observed these five most significant hub genes also up-regulated in another GBM gene expression dataset. The protein–protein interaction (PPI) network of the turquoise module genes was constructed and a KEGG pathway enrichments study of the turquoise module genes was performed. The VEGF signaling pathway was emphasized because of the strong link with GBM. A gene–disease association network was further constructed to demonstrate the information of the progression of GBM and other related brain neoplasms. All hub genes assessed through this study would be potential markers for the prognosis and diagnosis of GBM. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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21 pages, 3749 KiB

Open AccessArticle

Next-Generation Sequencing in Lung Cancer Patients: A Comparative Approach in NSCLC and SCLC Mutational Landscapes

by Cecilia Pop-Bica, Cristina Alexandra Ciocan, Cornelia Braicu, Antonia Haranguș, Marioara Simon, Andreea Nutu, Laura Ancuta Pop, Ondrej Slaby, Atanas G. Atanasov, Radu Pirlog, Nadim Al Hajjar and Ioana Berindan-Neagoe

J. Pers. Med. 2022, 12(3), 453; https://doi.org/10.3390/jpm12030453 - 13 Mar 2022

Cited by 9 | Viewed by 4417

Abstract

Background: Lung cancer remains one of the most diagnosed malignancies, being the second most diagnosed cancer, while still being the leading cause of cancer-related deaths. Late diagnosis remains a problem, alongside the high mutational burden encountered in lung cancer. Methods: We assessed the [...] Read more.

Background: Lung cancer remains one of the most diagnosed malignancies, being the second most diagnosed cancer, while still being the leading cause of cancer-related deaths. Late diagnosis remains a problem, alongside the high mutational burden encountered in lung cancer. Methods: We assessed the genetic profile of cancer genes in lung cancer using The Cancer Genome Atlas (TCGA) datasets for mutations and validated the results in a separate cohort of 32 lung cancer patients using tumor tissue and whole blood samples for next-generation sequencing (NGS) experiments. Another separate cohort of 32 patients was analyzed to validate some of the molecular alterations depicted in the NGS experiment. Results: In the TCGA analysis, we identified the most commonly mutated genes in each lung cancer dataset, with differences among the three histotypes analyzed. NGS analysis revealed TP53, CSF1R, PIK3CA, FLT3, ERBB4, and KDR as being the genes most frequently mutated. We validated the c.1621A>C mutation in KIT. The correlation analysis indicated negative correlation between adenocarcinoma and altered PIK3CA (r = −0.50918; p = 0.0029). TCGA survival analysis indicated that NRAS and IDH2 (LUAD), STK11 and TP53 (LUSC), and T53 (SCLC) alterations are correlated with the survival of patients. Conclusions: The study revealed differences in the mutational landscape of lung cancer histotypes. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 3948 KiB

Open AccessFeature PaperArticle

Gene Network Analysis for Osteoporosis, Sarcopenia, Diabetes, and Obesity in Human Mesenchymal Stromal Cells

by Yilan Jin, Dowan Kim, Yong Jun Choi, Insun Song and Yoon-Sok Chung

Genes 2022, 13(3), 459; https://doi.org/10.3390/genes13030459 - 3 Mar 2022

Cited by 3 | Viewed by 3176

Abstract

The systemic gene interactions that occur during osteoporosis and their underlying mechanisms remain to be determined. To this end, mesenchymal stromal cells (MSCs) were analyzed from bone marrow samples collected from healthy individuals (n = 5) and patients with osteoporosis (n [...] Read more.

The systemic gene interactions that occur during osteoporosis and their underlying mechanisms remain to be determined. To this end, mesenchymal stromal cells (MSCs) were analyzed from bone marrow samples collected from healthy individuals (n = 5) and patients with osteoporosis (n = 5). A total of 120 osteoporosis-related genes were identified using RNA-sequencing (RNA-seq) and Ingenuity Pathway Analysis (IPA) software. In order to analyze these genes, we constructed a heatmap of one-way hierarchical clustering and grouped the gene expression patterns of the samples. The MSCs from one control participant showed a similar expression pattern to that observed in the MSCs of three patients with osteoporosis, suggesting that the differentiating genes might be important genetic determinants of osteoporosis. Then, we selected the top 38 genes based on fold change and expression, excluding osteoporosis-related genes from the control participant. We identified a network among the top 38 genes related to osteoblast and osteoclast differentiation, bone remodeling, osteoporosis, and sarcopenia using the Molecule Activity Predictor program. Among them, 25 genes were essential systemic genes involved in osteoporosis. Furthermore, we identified 24 genes also associated with diabetes and obesity, among which 10 genes were involved in a network related to bone and energy metabolism. The study findings may have implications for the treatment and prevention of osteoporosis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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11 pages, 1342 KiB

Open AccessArticle

Association of Metabolic Parameter Variability with Esophageal Cancer Risk: A Nationwide Population-Based Study

by Ji Eun Lee, Kyungdo Han, Juhwan Yoo, Yohwan Yeo, In Young Cho, Belong Cho, Hyuktae Kwon, Dong Wook Shin, Jong Ho Cho and Yong-Moon Park

J. Pers. Med. 2022, 12(3), 375; https://doi.org/10.3390/jpm12030375 - 1 Mar 2022

Cited by 3 | Viewed by 3396

Abstract

Introduction: Certain metabolic parameters increase the risk of esophageal cancer. This study investigated the association between the variability in metabolic parameters and esophageal cancer incidence using large nationally representative data. Methods: Using the health checkup and claims data provided by the Korean National [...] Read more.

Introduction: Certain metabolic parameters increase the risk of esophageal cancer. This study investigated the association between the variability in metabolic parameters and esophageal cancer incidence using large nationally representative data. Methods: Using the health checkup and claims data provided by the Korean National Health Insurance Service (NHIS), we included 8,376,233 subjects who underwent NHIS-provided health checkups between 2009 and 2010 (index year) and two or more health checkups within five years before the index year. Hazard ratios (HRs) and 95% confidence intervals (CIs) for esophageal cancer were obtained using Cox proportional hazards models according to the quartiles of variability of each metabolic parameter: fasting blood glucose (FBG), weight, systolic blood pressure (SBP), and total cholesterol (TC) as well as a cumulative number of high-variability parameters. Results: A total of 6,455 cases of esophageal cancer occurred during a mean (±SD) follow-up of 8.8 (±1.1) years. The following metabolic parameters were used, with an adjusted HR and 95% CI: FBG (1.11, 1.03–1.18), weight (1.15, 1.07–1.23), SBP (1.08, 1.01–1.16), and TC (1.23, 1.15–1.32). The risk of esophageal cancer was higher in the highest quartile of variability than the lower quartiles. The risk of esophageal cancer gradually increased with a greater number of high-variability parameters: 1.08 (1.02–1.15), 1.22 (1.14–1.31), and 1.33 (1.21–1.46) for 1, 2, and 3–4 high-variability parameters (vs. none). Conclusions: A high variability of metabolic parameters was associated with an increased esophageal cancer risk. Further studies are needed to replicate our findings in other populations. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 3407 KiB

Open AccessArticle

Identification of Immune Markers in Dilated Cardiomyopathies with Heart Failure by Integrated Weighted Gene Coexpression Network Analysis

by Xuehua Wang, Hongquan Guan, Wei Liu, Huili Li, Jiaxing Ding, Yu Feng and Zhijian Chen

Genes 2022, 13(3), 393; https://doi.org/10.3390/genes13030393 - 22 Feb 2022

Cited by 4 | Viewed by 3469

Abstract

Dilated cardiomyopathy (DCM), a heterogeneous cardiomyopathy, is a major cause of heart failure and heart transplant. Currently, immunotherapy is believed to be an effective treatment method for DCM. However, individual differences are so obvious that the clinical effect is not satisfactory. In order [...] Read more.

Dilated cardiomyopathy (DCM), a heterogeneous cardiomyopathy, is a major cause of heart failure and heart transplant. Currently, immunotherapy is believed to be an effective treatment method for DCM. However, individual differences are so obvious that the clinical effect is not satisfactory. In order to find immune-related biomarkers of DCM to guide treatment and improve clinical efficacy, we downloaded a GSE120895 dataset from the Gene Expression Omnibus (GEO) database using CIBERSORT and WGCNA algorithms in RStudio and visualizing the protein–protein interaction (PPI) network for key modules by Cytoscape, and finally obtained six hub genes. A GSE17800 dataset was downloaded from the GEO dataset to verify the diagnostic values of hub genes, MYG1, FLOT1, and ATG13, which were excellent. Our study revealed unpublished potential immune mechanisms, biomarkers, and therapeutic targets of DCM. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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15 pages, 25040 KiB

Open AccessArticle

Large-Scale Meta-Longitudinal Microbiome Data with a Known Batch Factor

by Vera-Khlara S. Oh and Robert W. Li

Genes 2022, 13(3), 392; https://doi.org/10.3390/genes13030392 - 22 Feb 2022

Cited by 1 | Viewed by 2584

Abstract

Data contamination in meta-approaches where multiple biological samples are combined considerably affects the results of subsequent downstream analyses, such as differential abundance tests comparing multiple groups at a fixed time point. Little has been thoroughly investigated regarding the impact of the lurking variable [...] Read more.

Data contamination in meta-approaches where multiple biological samples are combined considerably affects the results of subsequent downstream analyses, such as differential abundance tests comparing multiple groups at a fixed time point. Little has been thoroughly investigated regarding the impact of the lurking variable of various batch sources, such as different days or different laboratories, in more complicated time series experimental designs, for instance, repeatedly measured longitudinal data and metadata. We highlight that the influence of batch factors is significant on subsequent downstream analyses, including longitudinal differential abundance tests, by performing a case study of microbiome time course data with two treatment groups and a simulation study of mimic microbiome longitudinal counts. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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10 pages, 4787 KiB

Open AccessArticle

Automatic Microaneurysms Detection for Early Diagnosis of Diabetic Retinopathy Using Improved Discrete Particle Swarm Optimization

by Usharani Bhimavarapu and Gopi Battineni

J. Pers. Med. 2022, 12(2), 317; https://doi.org/10.3390/jpm12020317 - 20 Feb 2022

Cited by 18 | Viewed by 2582

Abstract

Diabetic retinopathy (DR) is one of the most important microvascular complications associated with diabetes mellitus. The early signs of DR are microaneurysms, which can lead to complete vision loss. The detection of DR at an early stage can help to avoid non-reversible blindness. [...] Read more.

Diabetic retinopathy (DR) is one of the most important microvascular complications associated with diabetes mellitus. The early signs of DR are microaneurysms, which can lead to complete vision loss. The detection of DR at an early stage can help to avoid non-reversible blindness. To do this, we incorporated fuzzy logic techniques into digital image processing to conduct effective detection. The digital fundus images were segmented using particle swarm optimization to identify microaneurysms. The particle swarm optimization clustering combined the membership functions by grouping the high similarity data into clusters. Model testing was conducted on the publicly available dataset called DIARETDB0, and image segmentation was done by probability-based (PBPSO) clustering algorithms. Different fuzzy models were applied and the outcomes were compared with our probability discrete particle swarm optimization algorithm. The results revealed that the proposed PSO algorithm achieved an accuracy of 99.9% in the early detection of DR. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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10 pages, 258 KiB

Open AccessArticle

Association between Hyperosmolar Hyperglycemic State and Venous Thromboembolism in Diabetes Patients: A Nationwide Analysis in Taiwan

by Wei-Ting Wei, Shu-Man Lin, Jin-Yi Hsu, Ying-Ying Wu, Ching-Hui Loh, Huei-Kai Huang and Peter Pin-Sung Liu

J. Pers. Med. 2022, 12(2), 302; https://doi.org/10.3390/jpm12020302 - 17 Feb 2022

Cited by 3 | Viewed by 2507

Abstract

Background: Previous studies in Western countries have shown that a hyperosmolar hyperglycemic state (HHS) is associated with an increased risk of venous thromboembolism (VTE); in these cases, prophylactic anticoagulant treatment is suggested. However, the association between HHS and VTE in Asian populations remains [...] Read more.

Background: Previous studies in Western countries have shown that a hyperosmolar hyperglycemic state (HHS) is associated with an increased risk of venous thromboembolism (VTE); in these cases, prophylactic anticoagulant treatment is suggested. However, the association between HHS and VTE in Asian populations remains undetermined. Therefore, we aimed to evaluate whether HHS is associated with an increased risk of VTE in diabetic Taiwanese patients. Methods: This nationwide, population-based, retrospective cohort study was conducted using the Taiwan National Health Insurance Research Database. We enrolled a total of 4,723,607 admission records of patients with diabetes diagnosed with one or more of seven common diseases (pneumonia, urinary tract infection, sepsis, heart disease, stroke, malignancy, and respiratory tract disease) between 2001 and 2018 in Taiwan. The patients were divided into two groups based on the presence (n = 46,000) or absence (n = 4,677,607) of HHS. We estimated the adjusted odds ratio (aOR) for developing VTE within 90 days after the index hospitalization using multivariable logistic regression with generalized estimating equations accounting for repeated measures. Results: Overall, patients admitted with HHS had a similar risk of VTE compared with those admitted without HHS (408/46,000 vs. 39,345/4,677,607; aOR = 1.06, 95% CI: 0.97–1.17, p = 0.190). A similar non-significant association between HHS and VTE was found regardless of age and sex subgroups. Conclusions: There was no significant association between HHS and overall VTE risk in patients with diabetes in Taiwan. The results of our study may not support the use of prophylactic anticoagulant therapy in diabetic Taiwanese patients with HHS. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

18 pages, 3310 KiB

Open AccessArticle

Prediction Model for Pancreatic Cancer—A Population-Based Study from NHIRD

by Hsiu-An Lee, Kuan-Wen Chen and Chien-Yeh Hsu

Cancers 2022, 14(4), 882; https://doi.org/10.3390/cancers14040882 - 10 Feb 2022

Cited by 18 | Viewed by 3744

Abstract

(1) Background: Cancer has been the leading cause of death in Taiwan for 39 years, and among them, pancreatic cancer has been ranked seventh in the top ten cancer mortality rates for the past three years. While the incidence rate of pancreatic cancer [...] Read more.

(1) Background: Cancer has been the leading cause of death in Taiwan for 39 years, and among them, pancreatic cancer has been ranked seventh in the top ten cancer mortality rates for the past three years. While the incidence rate of pancreatic cancer is ranked at the bottom of the top 10 cancers, the survival rate is very low. Pancreatic cancer is one of the more difficult cancers to detect early due to the lack of early diagnostic tools. Early screening is important for the treatment of pancreatic cancer. Only a few studies have designed predictive models for pancreatic cancer. (2) Methods: The Taiwan Health Insurance Database was used in this study, covering over 99% of the population in Taiwan. The subset sample was not significantly different from the original NHIRD sample. A machine learning approach was used to develop a predictive model for pancreatic cancer disease. Four models, including logistic regression, deep neural networks, ensemble learning, and voting ensemble were used in this study. The ROC curve and a confusion matrix were used to evaluate the accuracy of the pancreatic cancer prediction models. (3) Results: The AUC of the LR model was higher than the other three models in the external testing set for all three of the factor combinations. Sensitivity was best measured by the stacking model for the first factor combinations, and specificity was best measured by the DNN model for the second factor combination. The result of the model that used only nine factors (third factor combinations) was equal to the other two factor combinations. The AUC of the previous models for the early assessment of pancreatic cancer ranged from approximately 0.57 to 0.71. The AUC of this study was higher than that of previous studies and ranged from 0.71 to 0.76, which provides higher accuracy. (4) Conclusions: This study compared the performances of LR, DNN, stacking, and voting models for pancreatic cancer prediction and constructed a pancreatic cancer prediction model with accuracy higher than that of previous studies. This predictive model will improve awareness of the risk of pancreatic cancer and give patients with pancreatic cancer a simpler tool for early screening in the golden period when the disease can still be eradicated. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 2612 KiB

Open AccessArticle

Improving the Process of Shared Decision-Making by Integrating Online Structured Information and Self-Assessment Tools

by Pei-Jung Hsu, Chia-Ying Wu, Lu-Cheng Kuo, Ming-Yuan Chen, Yu-Ling Chen, Szu-Fen Huang, Pao-Yu Chuang, Jih-Shuin Jerng and Shey-Ying Chen

J. Pers. Med. 2022, 12(2), 256; https://doi.org/10.3390/jpm12020256 - 10 Feb 2022

Cited by 3 | Viewed by 3240

Abstract

The integration of face-to-face communication and online processes to provide access to information and self-assessment tools may improve shared decision-making (SDM) processes. We aimed to assess the effectiveness of implementing an online SDM process with topics and content developed through a participatory design [...] Read more.

The integration of face-to-face communication and online processes to provide access to information and self-assessment tools may improve shared decision-making (SDM) processes. We aimed to assess the effectiveness of implementing an online SDM process with topics and content developed through a participatory design approach. We analyzed the triggered and completed SDM cases with responses from participants at a medical center in Taiwan. Data were retrieved from the Research Electronic Data Capture (REDCap) database of the hospital for analysis. Each team developed web-based patient decision aids (PDA) with empirical evidence in a multi-digitized manner, allowing patients to scan QR codes on a leaflet using their mobile phones and then read the PDA content online. From July 2019 to December 2020, 48 web-based SDM topics were implemented in the 24 clinical departments of this hospital. The results showed that using the REDCap system improved SDM efficiency and quality. Implementing an online SDM process integrated with face-to-face communication enhanced the practice and effectiveness of SDM, possibly through the flexibility of accessing information, self-assessment, and feedback evaluation. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 3587 KiB

Open AccessArticle

Efficacy of Ventilation Tube Insertion with Palatal Repair for Otitis Media in Cleft Palate: Meta-Analysis and Trial Sequential Analysis

by Feng-Liang Chang, Chih-Hao Chen, Hsiu-Lien Cheng, Chun-Yu Chang, Jing-Li Leong, Yen-Ting Chang, Yen-Fu Cheng and Wen-Huei Liao

J. Pers. Med. 2022, 12(2), 255; https://doi.org/10.3390/jpm12020255 - 10 Feb 2022

Cited by 1 | Viewed by 3403

Abstract

Cleft palate is the most common congenital facial deformity and may result in multiple sequelae and disabilities. One common comorbidity is refractory otitis media with effusion (OME), as patients with cleft palate have impaired eustachian tube function with alteration of the nearby muscular [...] Read more.

Cleft palate is the most common congenital facial deformity and may result in multiple sequelae and disabilities. One common comorbidity is refractory otitis media with effusion (OME), as patients with cleft palate have impaired eustachian tube function with alteration of the nearby muscular structures. Ventilation tube insertion (VTI) is regarded as an effective mean to address OME in addition to palatal repair surgery. However, controversy regarding the efficacy of VTI and the timing of VTI remains. We aimed to assess the efficacy of VTI with palatal repair for cleft palate on OME development via a meta-analysis with systematic review and trial sequential analysis (TSA). Studies including patients with cleft palate who underwent palatal repair with or without VTI were considered eligible. After searching the Cochrane Library, PubMed, EMBASE, Web of Science, Scopus and China National Knowledge Infrastructure (CNKI) from inception through 5 September 2021, 9 studies involving 929 patients were included. Overall, a significantly higher OME-free rate was noted in those who underwent VTI and palatal repair than in those who underwent palatal repair alone (OR, 2.73; 95% CI, 1.37 to 5.42; p = 0.004; I² = 84%). Subgroup analysis revealed that the OME-free rate remained higher in the concurrent VTI group (OR, 3.29; 95% CI, 1.64 to 6.59; p < 0.001; I² = 81%). TSA indicated that all the analyses provided conclusive results by meeting the required information size and Z-value. The meta-analysis indicated that VTI is an effective procedure to prevent OME in patients with cleft palate and that VTI is beneficial when performed concurrently with palatal repair surgery. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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15 pages, 3470 KiB

Open AccessArticle

Systemic Periodontal Risk Score Using an Innovative Machine Learning Strategy: An Observational Study

by Paul Monsarrat, David Bernard, Mathieu Marty, Chiara Cecchin-Albertoni, Emmanuel Doumard, Laure Gez, Julien Aligon, Jean-Noël Vergnes, Louis Casteilla and Philippe Kemoun

J. Pers. Med. 2022, 12(2), 217; https://doi.org/10.3390/jpm12020217 - 4 Feb 2022

Cited by 6 | Viewed by 3513

Abstract

Early diagnosis is crucial for individuals who are susceptible to tooth-supporting tissue diseases (e.g., periodontitis) that may lead to tooth loss, so as to prevent systemic implications and maintain quality of life. The aim of this study was to propose a personalized explainable [...] Read more.

Early diagnosis is crucial for individuals who are susceptible to tooth-supporting tissue diseases (e.g., periodontitis) that may lead to tooth loss, so as to prevent systemic implications and maintain quality of life. The aim of this study was to propose a personalized explainable machine learning algorithm, solely based on non-invasive predictors that can easily be collected in a clinic, to identify subjects at risk of developing periodontal diseases. To this end, the individual data and periodontal health of 532 subjects was assessed. A machine learning pipeline combining a feature selection step, multilayer perceptron, and SHapley Additive exPlanations (SHAP) explainability, was used to build the algorithm. The prediction scores for healthy periodontium and periodontitis gave final F1-scores of 0.74 and 0.68, respectively, while gingival inflammation was harder to predict (F1-score of 0.32). Age, body mass index, smoking habits, systemic pathologies, diet, alcohol, educational level, and hormonal status were found to be the most contributive variables for periodontal health prediction. The algorithm clearly shows different risk profiles before and after 35 years of age and suggests transition ages in the predisposition to developing gingival inflammation or periodontitis. This innovative approach to systemic periodontal disease risk profiles, combining both ML and up-to-date explainability algorithms, paves the way for new periodontal health prediction strategies. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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12 pages, 1936 KiB

Open AccessArticle

Investigation of the Genetic Architecture of Pigs Subjected to Breeding Intensification

by Anatoly Kolosov, Lyubov Getmantseva, Maria Kolosova, Timofey Romanets, Nekruz Bakoev, Elena Romanets, Ilona Bakoeva, Olga Kostyunina, Yuri Prytkov, Olga Tretiakova and Siroj Bakoev

Genes 2022, 13(2), 197; https://doi.org/10.3390/genes13020197 - 22 Jan 2022

Cited by 1 | Viewed by 3344

Abstract

Pigs are strategically important animals for the agricultural industry. An assessment of genetic differentiation between pigs, undergone and not undergone to selection intensification, is of particular interest. Our research was conducted on two groups of Large White pigs grown on the same farm [...] Read more.

Pigs are strategically important animals for the agricultural industry. An assessment of genetic differentiation between pigs, undergone and not undergone to selection intensification, is of particular interest. Our research was conducted on two groups of Large White pigs grown on the same farm but in different years. A total of 165 samples were selected with 78 LW_А (n = 78, the Russian selection) and LW_B (n = 87, a commercial livestock). For genotyping, we used GeneSeek^® GGP Porcine HD Genomic Profiler v1 (Illumina Inc, San Diego, CA, USA). To define breeding characteristics of selection, we used smoothing FST and segment identification of HBD (Homozygous-by-Descent). The results of smoothing FST showed 20 areas of a genome with strong ejection regions of the genome located on all chromosomes except SSC2, SSC3, and SSC8. The average realized autozygosity in Large White pigs of native selection was in (LW_A)—0.21, in LW_В—0.29. LW_А showed 13,338 HBD segments, 171 per one animal, and LW_B—15,747 HBD segments, 181 per one animal. The ejections found by the smoothing FST method were partially localized in the HBD regions. In these areas, the genes ((NCBP1, PLPPR1, GRIN3A, NBEA, TRPC4, HS6ST3, NALCN, SMG6, TTC3, KCNJ6, IKZF2, OBSL1, CARD10, ETV6, VWF, CCND2, TSPAN9, CDH13, CEP128, SERPINA11, PIK3CG, COG5, BCAP29, SLC26A4) were defined. The revealed genes can be of special interest for further studying their influence on an organism of an animal since they can act as candidate genes for selection-significant traits. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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21 pages, 7663 KiB

Open AccessArticle

PeMNet for Pectoral Muscle Segmentation

by Xiang Yu, Shui-Hua Wang, Juan Manuel Górriz, Xian-Wei Jiang, David S. Guttery and Yu-Dong Zhang

Biology 2022, 11(1), 134; https://doi.org/10.3390/biology11010134 - 14 Jan 2022

Cited by 6 | Viewed by 3504

Abstract

As an important imaging modality, mammography is considered to be the global gold standard for early detection of breast cancer. Computer-Aided (CAD) systems have played a crucial role in facilitating quicker diagnostic procedures, which otherwise could take weeks if only radiologists were involved. [...] Read more.

As an important imaging modality, mammography is considered to be the global gold standard for early detection of breast cancer. Computer-Aided (CAD) systems have played a crucial role in facilitating quicker diagnostic procedures, which otherwise could take weeks if only radiologists were involved. In some of these CAD systems, breast pectoral segmentation is required for breast region partition from breast pectoral muscle for specific analysis tasks. Therefore, accurate and efficient breast pectoral muscle segmentation frameworks are in high demand. Here, we proposed a novel deep learning framework, which we code-named PeMNet, for breast pectoral muscle segmentation in mammography images. In the proposed PeMNet, we integrated a novel attention module called the Global Channel Attention Module (GCAM), which can effectively improve the segmentation performance of Deeplabv3+ using minimal parameter overheads. In GCAM, channel attention maps (CAMs) are first extracted by concatenating feature maps after paralleled global average pooling and global maximum pooling operation. CAMs are then refined and scaled up by multi-layer perceptron (MLP) for elementwise multiplication with CAMs in next feature level. By iteratively repeating this procedure, the global CAMs (GCAMs) are then formed and multiplied elementwise with final feature maps to lead to final segmentation. By doing so, CAMs in early stages of a deep convolution network can be effectively passed on to later stages of the network and therefore leads to better information usage. The experiments on a merged dataset derived from two datasets, INbreast and OPTIMAM, showed that PeMNet greatly outperformed state-of-the-art methods by achieving an IoU of

97.46 %

, global pixel accuracy of

99.48 %

, Dice similarity coefficient of

96.30 %

, and Jaccard of

93.33 %

, respectively. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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14 pages, 2795 KiB

Open AccessArticle

In Silico Research of New Therapeutics Rotenoids Derivatives against Leishmania amazonensis Infection

by Adrián Vicente-Barrueco, Ángel Carlos Román, Trinidad Ruiz-Téllez and Francisco Centeno

Biology 2022, 11(1), 133; https://doi.org/10.3390/biology11010133 - 14 Jan 2022

Cited by 1 | Viewed by 3340

Abstract

Yearly, 1,500,000 cases of leishmaniasis are diagnosed, causing thousands of deaths. To advance in its therapy, we present an interdisciplinary protocol that unifies ethnobotanical knowledge of natural compounds and the latest bioinformatics advances to respond to an orphan disease such as leishmaniasis and [...] Read more.

Yearly, 1,500,000 cases of leishmaniasis are diagnosed, causing thousands of deaths. To advance in its therapy, we present an interdisciplinary protocol that unifies ethnobotanical knowledge of natural compounds and the latest bioinformatics advances to respond to an orphan disease such as leishmaniasis and specifically the one caused by Leishmania amazonensis. The use of ethnobotanical information serves as a basis for the development of new drugs, a field in which computer-aided drug design (CADD) has been a revolution. Taking this information from Amazonian communities, located in the area with a high prevalence of this disease, a protocol has been designed to verify new leads. Moreover, a method has been developed that allows the evaluation of lead molecules, and the improvement of their affinity and specificity against therapeutic targets. Through this approach, deguelin has been identified as a good lead to treat the infection due to its potential as an ornithine decarboxylase (ODC) inhibitor, a key enzyme in Leishmania development. Using an in silico-generated combinatorial library followed by docking approaches, we have found deguelin derivatives with better affinity and specificity against ODC than the original compound, suggesting that this approach could be adapted for developing new drugs against leishmaniasis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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13 pages, 1503 KiB

Open AccessArticle

CGENet: A Deep Graph Model for COVID-19 Detection Based on Chest CT

by Si-Yuan Lu, Zheng Zhang, Yu-Dong Zhang and Shui-Hua Wang

Biology 2022, 11(1), 33; https://doi.org/10.3390/biology11010033 - 27 Dec 2021

Cited by 31 | Viewed by 3182

Abstract

Accurate and timely diagnosis of COVID-19 is indispensable to control its spread. This study proposes a novel explainable COVID-19 diagnosis system called CGENet based on graph embedding and an extreme learning machine for chest CT images. We put forward an optimal backbone selection [...] Read more.

Accurate and timely diagnosis of COVID-19 is indispensable to control its spread. This study proposes a novel explainable COVID-19 diagnosis system called CGENet based on graph embedding and an extreme learning machine for chest CT images. We put forward an optimal backbone selection algorithm to select the best backbone for the CGENet based on transfer learning. Then, we introduced graph theory into the ResNet-18 based on the k-nearest neighbors. Finally, an extreme learning machine was trained as the classifier of the CGENet. The proposed CGENet was evaluated on a large publicly-available COVID-19 dataset and produced an average accuracy of 97.78% based on 5-fold cross-validation. In addition, we utilized the Grad-CAM maps to present a visual explanation of the CGENet based on COVID-19 samples. In all, the proposed CGENet can be an effective and efficient tool to assist COVID-19 diagnosis. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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44 pages, 1807 KiB

Open AccessSystematic Review

A Survey of Computer-Aided Tumor Diagnosis Based on Convolutional Neural Network

by Yan Yan, Xu-Jing Yao, Shui-Hua Wang and Yu-Dong Zhang

Biology 2021, 10(11), 1084; https://doi.org/10.3390/biology10111084 - 22 Oct 2021

Cited by 28 | Viewed by 3640

Abstract

Tumors are new tissues that are harmful to human health. The malignant tumor is one of the main diseases that seriously affect human health and threaten human life. For cancer treatment, early detection of pathological features is essential to reduce cancer mortality effectively. [...] Read more.

Tumors are new tissues that are harmful to human health. The malignant tumor is one of the main diseases that seriously affect human health and threaten human life. For cancer treatment, early detection of pathological features is essential to reduce cancer mortality effectively. Traditional diagnostic methods include routine laboratory tests of the patient’s secretions, and serum, immune and genetic tests. At present, the commonly used clinical imaging examinations include X-ray, CT, MRI, SPECT scan, etc. With the emergence of new problems of radiation noise reduction, medical image noise reduction technology is more and more investigated by researchers. At the same time, doctors often need to rely on clinical experience and academic background knowledge in the follow-up diagnosis of lesions. However, it is challenging to promote clinical diagnosis technology. Therefore, due to the medical needs, research on medical imaging technology and computer-aided diagnosis appears. The advantages of a convolutional neural network in tumor diagnosis are increasingly obvious. The research on computer-aided diagnosis based on medical images of tumors has become a sharper focus in the industry. Neural networks have been commonly used to research intelligent methods to assist medical image diagnosis and have made significant progress. This paper introduces the traditional methods of computer-aided diagnosis of tumors. It introduces the segmentation and classification of tumor images as well as the diagnosis methods based on CNN to help doctors determine tumors. It provides a reference for developing a CNN computer-aided system based on tumor detection research in the future. Full article

(This article belongs to the Topic Big Data in Healthcare, Bioinformatics and Precision Medicine)

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