Bioinformatics of Human Diseases

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: closed (10 September 2024) | Viewed by 6612

Special Issue Editor

Department of Population Health Sciences, Augusta University, Augusta, GA 30912-4900, USA
Interests: statistial genetics; genomics; bioinformatics; population genetics; data science
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Special Issue Information

Dear Colleagues,

Bioinformatics is the scientific discipline that involves the use of computers to collect, store and analyze information about biological data, including DNA and amino acid sequences or annotations about sequences. Bioinformatics is an important discipline for life science research today. The goal of this research branch is to reveal the complexity of genome information structure and the fundamental laws of genetic language, and to clarify the structure, function, interaction and relationship between human proteins and various human diseases, seeking for a variety of therapeutic and preventive measures.

Given the significant potential of bioinformatics to understand human disease, this Special Issue invites researchers to publish their work on bioinformatics analysis methods for disease identification, classification, diagnosis and prognosis that address the current advances in bioinformatics relating human diseases. If you would like more information about the Special Issue, please feel free to contact us.

Dr. Hongyan Xu
Guest Editor

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Keywords

  • bioinformatics
  • human disease
  • sequencing
  • gene expression analysis
  • analysis methods
  • proteomics analysis
  • metabolomics analysis
  • microbiome analysis

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Published Papers (5 papers)

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Research

14 pages, 2082 KiB  
Article
Dynamics of SARS-CoV-2 Spike RBD Protein Mutation and Pathogenicity Consequences in Indonesian Circulating Variants in 2020–2022
by Nabiel Muhammad Haykal, Fadilah Fadilah, Beti Ernawati Dewi, Linda Erlina, Aisyah Fitriannisa Prawiningrum and Badriul Hegar
Genes 2024, 15(11), 1468; https://doi.org/10.3390/genes15111468 - 14 Nov 2024
Viewed by 569
Abstract
Background: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This [...] Read more.
Background: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This research analyzes the mutation trend in various RBD samples from Indonesia published in the Global Initiative on Sharing All Influenza Data (GISAID) database using genomic profiling. Method: Patients in Indonesia infected with SARS-CoV-2, whose samples have been published in genomic databases, were selected for this research. The collected data were processed for analysis following several bioinformatics protocols: visualization into phylogenetic trees, 3D rendering, and the assessment of mutational impact. Results: In Indonesia, there are 25 unique SARS-CoV-2 clades and 318 unique SARS-CoV-2 RBD mutations from the earliest COVID-19 sample to samples collected in 2022, with T478K being the most prevalent RBD mutation and 22B being the most abundant clade. The Omicron variant has a lower docking score, higher protein destabilization, and higher KD than the Delta variant and the original virus. Conclusions: The study findings reveal a decreasing trend in virus pathogenicity as a potential trade-off to increase transmissibility via mutations in RBD over the years. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
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24 pages, 3052 KiB  
Article
Comparison of B-Cell Lupus and Lymphoma Using a Novel Immune Imbalance Transcriptomics Algorithm Reveals Potential Therapeutic Targets
by Naomi Rapier-Sharman, Sehi Kim, Madelyn Mudrow, Michael T. Told, Lane Fischer, Liesl Fawson, Joseph Parry, Brian D. Poole, Kim L. O’Neill, Stephen R. Piccolo and Brett E. Pickett
Genes 2024, 15(9), 1215; https://doi.org/10.3390/genes15091215 - 17 Sep 2024
Viewed by 1202
Abstract
Background/Objectives: Systemic lupus erythematosus (lupus) and B-cell lymphoma (lymphoma) co-occur at higher-than-expected rates and primarily depend on B cells for their pathology. These observations implicate shared inflammation-related B cell molecular mechanisms as a potential cause of co-occurrence. Methods: We consequently implemented a novel [...] Read more.
Background/Objectives: Systemic lupus erythematosus (lupus) and B-cell lymphoma (lymphoma) co-occur at higher-than-expected rates and primarily depend on B cells for their pathology. These observations implicate shared inflammation-related B cell molecular mechanisms as a potential cause of co-occurrence. Methods: We consequently implemented a novel Immune Imbalance Transcriptomics (IIT) algorithm and applied IIT to lupus, lymphoma, and healthy B cell RNA-sequencing (RNA-seq) data to find shared and contrasting mechanisms that are potential therapeutic targets. Results: We observed 7143 significantly dysregulated genes in both lupus and lymphoma. Of those genes, we found 5137 to have a significant immune imbalance, defined as a significant dysregulation by both diseases, as analyzed by IIT. Gene Ontology (GO) term and pathway enrichment of the IIT genes yielded immune-related “Neutrophil Degranulation” and “Adaptive Immune System”, which validates that the IIT algorithm isolates biologically relevant genes in immunity and inflammation. We found that 344 IIT gene products are known targets for established and/or repurposed drugs. Among our results, we found 48 known and 296 novel lupus targets, along with 151 known and 193 novel lymphoma targets. Known disease drug targets in our IIT results further validate that IIT isolates genes with disease-relevant mechanisms. Conclusions: We anticipate the IIT algorithm, together with the shared and contrasting gene mechanisms uncovered here, will contribute to the development of immune-related therapeutic options for lupus and lymphoma patients. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
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15 pages, 2577 KiB  
Article
In Silico Exploration of AHR-HIF Pathway Interplay: Implications for Therapeutic Targeting in ccRCC
by Francesco Gregoris, Giovanni Minervini and Silvio C. E. Tosatto
Genes 2024, 15(9), 1167; https://doi.org/10.3390/genes15091167 - 5 Sep 2024
Viewed by 885
Abstract
The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel–Lindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF [...] Read more.
The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel–Lindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF activation and uncontrolled angiogenesis, increasing the risk of developing clear cell renal cell carcinoma (ccRCC). HIF hyperactivation can sequester HIF-1β, preventing the aryl hydrocarbon receptor (AHR) from correctly activating gene expression in response to endogenous and exogenous ligands such as TCDD (dioxins). In this study, we used protein–protein interaction networks and gene expression profiling to characterize the impact of VHL loss on AHR activity. Our findings reveal specific expression patterns of AHR interactors following exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and in ccRCC. We identified several AHR interactors significantly associated with poor survival rates in ccRCC patients. Notably, the upregulation of the androgen receptor (AR) and retinoblastoma-associated protein (RB1) by TCDD, coupled with their respective downregulation in ccRCC and association with poor survival rates, suggests novel therapeutic targets. The strategic activation of the AHR via selective AHR modulators (SAhRMs) could stimulate its anticancer activity, specifically targeting RB1 and AR to reduce cell cycle progression and metastasis formation in ccRCC. Our study provides comprehensive insights into the complex interplay between the AHR and HIF pathways in ccRCC pathogenesis, offering novel strategies for targeted therapeutic interventions. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
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14 pages, 4342 KiB  
Article
Identification of Autophagy-Related Biomarkers and Diagnostic Model in Alzheimer’s Disease
by Wei Xu, Xi Su, Jing Qin, Ye Jin, Ning Zhang and Shasha Huang
Genes 2024, 15(8), 1027; https://doi.org/10.3390/genes15081027 - 5 Aug 2024
Viewed by 1352
Abstract
Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease. Its accurate pathogenic mechanisms are incompletely clarified, and effective therapeutic treatments are still inadequate. Autophagy is closely associated with AD and plays multiple roles in eliminating harmful aggregated proteins and maintaining cell homeostasis. This [...] Read more.
Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease. Its accurate pathogenic mechanisms are incompletely clarified, and effective therapeutic treatments are still inadequate. Autophagy is closely associated with AD and plays multiple roles in eliminating harmful aggregated proteins and maintaining cell homeostasis. This study identified 1191 differentially expressed genes (DEGs) based on the GSE5281 dataset from the GEO database, intersected them with 325 autophagy-related genes from GeneCards, and screened 26 differentially expressed autophagy-related genes (DEAGs). Subsequently, GO and KEGG enrichment analysis was performed and indicated that these DEAGs were primarily involved in autophagy–lysosomal biological process. Further, eight hub genes were determined by PPI construction, and experimental validation was performed by qRT-PCR on a SH-SY5Y cell model. Finally, three hub genes (TFEB, TOMM20, GABARAPL1) were confirmed to have potential application for biomarkers. A multigenic prediction model with good predictability (AUC = 0.871) was constructed in GSE5281 and validated in the GSE132903 dataset. Hub gene-targeted miRNAs closely associated with AD were also retrieved through the miRDB and HDMM database, predicting potential therapeutic agents for AD. This study provides new insights into autophagy-related genes in brain tissues of AD patients and offers more candidate biomarkers for AD mechanistic research as well as clinical diagnosis. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
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16 pages, 451 KiB  
Article
Investigating the Influence of ANTXR2 Gene Mutations on Protective Antigen Binding for Heightened Anthrax Resistance
by Chamalapura Ashwathama Archana, Yamini Sri Sekar, Kuralayanapalya Puttahonnappa Suresh, Saravanan Subramaniam, Ningegowda Sagar, Swati Rani, Jayashree Anandakumar, Rajan Kumar Pandey, Nagendra Nath Barman and Sharanagouda S. Patil
Genes 2024, 15(4), 426; https://doi.org/10.3390/genes15040426 - 28 Mar 2024
Cited by 2 | Viewed by 1974
Abstract
Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin [...] Read more.
Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin Receptor-2 (ANTXR2) gene acts as membrane receptor and facilitates the entry of the anthrax toxin into host cells. Additionally, mutations in the ANTXR2 gene have been linked to various autoimmune diseases, including Hyaline Fibromatosis Syndrome (HFS), Ankylosing Spondylitis (AS), Juvenile Hyaline Fibromatosis (JHF), and Infantile Systemic Hyalinosis (ISH). This study delves into the genetic landscape of ANTXR2, aiming to comprehend its associations with diverse disorders, elucidate the impacts of its mutations, and pinpoint minimal non-pathogenic mutations capable of reducing the binding affinity of the ANTXR2 gene with the protective antigen. Recognizing the pivotal role of single-nucleotide polymorphisms (SNPs) in shaping genetic diversity, we conducted computational analyses to discern highly deleterious and tolerated non-synonymous SNPs (nsSNPs) in the ANTXR2 gene. The Mutpred2 server determined that the Arg465Trp alteration in the ANTXR2 gene leads to altered DNA binding (p = 0.22) with a probability of a deleterious mutation of 0.808; notably, among the identified deleterious SNPs, rs368288611 (Arg465Trp) stands out due to its significant impact on altering the DNA-binding ability of ANTXR2. We propose these SNPs as potential candidates for hypertension linked to the ANTXR2 gene, which is implicated in blood pressure regulation. Noteworthy among the tolerated substitutions is rs200536829 (Ala33Ser), recognized as less pathogenic; this highlights its potential as a valuable biomarker, potentially reducing side effects on the host while also reducing binding with the protective antigen protein. Investigating these SNPs holds the potential to correlate with several autoimmune disorders and mitigate the impact of anthrax disease in humans. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
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