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A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Omics/Informatics".

Deadline for manuscript submissions: closed (10 July 2023) | Viewed by 26416

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Special Issue Editors

Prof. Dr. Chia-Hsiang Chen

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Guest Editor

1. Department of Psychiatry, Chang Gung Memorial Hospital-Linkou, Taoyuan 333, Taiwan
2. Department and Institute of Biomedical Sciences, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
Interests: etiology, pathogenesis, and treatment of major psychiatric disorders

Prof. Dr. Yu-Shu Huang

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Guest Editor

1. Department of Child Psychiatry, Sleep Center, Chang Gung Memorial Hospital-Linkou, Taoyuan 333, Taiwan
2. School of Medicine, College of Medicine, Chang Gung University, Taoyuan 333, Taiwan
Interests: etiology, pathogenesis, and treatment of major pediatric psychiatric disorders and sleep medicine

Special Issue Information

Dear Colleagues,

In the 21st century, medicine has advanced to the era of precision medicine. The goals of precision medicine are to find the patient-specific etiology, understand the unique pathophysiology, and tailor treatment for every patient. Psychiatry is no exception. Every psychiatric patient is unique in the context of their biopsychosocial and spiritual perspectives. As the Russian novelist Leo Tolstoy wrote in his novel Anna Karenina, “All happy families are alike, each unhappy family is unhappy in its own way.” Precision medicine is most suitable and desirable in the field of psychiatry. The recent advances in genomics, functional genomics, pharmacogenomics, brain imaging, electrophysiology, stem cell biology, and genome editing, to name a few, have greatly facilitated advances in the etiological diagnosis, pathogenesis elucidation, treatment regimen optimization, and new therapy development of psychiatric disorders. This new frontier of precision psychiatry comes with many challenges, and it is also a daring adventure involving insightful and surprising discoveries. In this Special Issue, we will showcase some exciting and excellent research findings that move psychiatry to the area of precision psychiatry. We sincerely invite you to contribute your important research findings to this Special Issue.

Prof. Dr. Chia-Hsiang Chen
Prof. Dr. Yu-Shu Huang
Guest Editors

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Keywords

precision medicine
psychiatry
personalized medicine
genomics
functional genomics

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Published Papers (10 papers)

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Research

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9 pages, 1104 KiB

Open AccessArticle

Validity of Diagnostic Support Model for Attention Deficit Hyperactivity Disorder: A Machine Learning Approach

by Kuo-Chung Chu, Hsin-Jou Huang and Yu-Shu Huang

J. Pers. Med. 2023, 13(11), 1525; https://doi.org/10.3390/jpm13111525 - 24 Oct 2023

Cited by 1 | Viewed by 1597

Abstract

An accurate and early diagnosis of attention deficit hyperactivity disorder can improve health outcomes and prevent unnecessary medical expenses. This study developed a diagnostic support model using a machine learning approach to effectively screen individuals for attention deficit hyperactivity disorder. Three models were developed: a logistic regression model, a classification and regression tree (CART), and a neural network. The models were assessed by using a receiver operating characteristic analysis. In total, 74 participants were enrolled into the disorder group, while 21 participants were enrolled in the control group. The sensitivity and specificity of each model, indicating the rate of true positive and true negative results, respectively, were assessed. The CART model demonstrated a superior performance compared to the other two models, with region values of receiver operating characteristic analyses in the following order: CART (0.848) > logistic regression model (0.826) > neural network (0.67). The sensitivity and specificity of the CART model were 78.8% and 50%, respectively. This model can be applied to other neuroscience research fields, including the diagnoses of autism spectrum disorder, Tourette syndrome, and dementia. This will enhance the effect and practical value of our research. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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10 pages, 276 KiB

Open AccessArticle

Metabolic Hormones in Schizophrenia Patients with Antipsychotic-Induced Metabolic Syndrome

by Anastasiia S. Boiko, Irina A. Mednova, Elena G. Kornetova, Anastasiia A. Goncharova, Arkadiy V. Semke, Nikolay A. Bokhan and Svetlana A. Ivanova

J. Pers. Med. 2022, 12(10), 1655; https://doi.org/10.3390/jpm12101655 - 5 Oct 2022

Cited by 3 | Viewed by 1666

Abstract

Metabolic syndrome (MetS) is a common complication of schizophrenia that is quite exacerbated by long-term use of (atypical) antipsychotics. The mechanism of MetS has neuronal, neuroendocrine, and neuroimmunological components and shows some overlap with those of aspects of schizophrenia. We examined 195 patients with schizophrenia (90 with and 105 without MetS) for the association of serum levels of ghrelin, insulin, and leptin with metabolic abnormalities. Serum glucose levels and lipid profiles were routinely measured with colorimetric enzymatic methods and hormone levels with multiplex analyzers. Leptin levels were highly significantly increased (p < 0.001) in people with MetS (9.966 [5.882; 21.496] vs. 6.35 [2.005; 11.753], Me [Q1; Q3]) and ghrelin levels were actually significantly decreased (p = 0.045). Insulin levels did not differ significantly between those with and without MetS (p = 0.162). In Spearman’s correlation analysis between the hormone levels, body characteristics, and biochemical parameters, significant correlations were seen somewhat more often in people without MetS than in those with MetS and also less often for ghrelin than for the other hormones. We conclude that evidence exists for a role in the development of MetS especially for leptin, but that less is supporting a role for ghrelin. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

10 pages, 1118 KiB

Open AccessArticle

Cytokine Levels and Neuropsychological Function among Patients with Attention-Deficit/Hyperactivity Disorder and Atopic Diseases

by Shung-Jie Chang, Ho-Chang Kuo, Wen-Jiun Chou, Ching-Shu Tsai, Sheng-Yu Lee and Liang-Jen Wang

J. Pers. Med. 2022, 12(7), 1155; https://doi.org/10.3390/jpm12071155 - 17 Jul 2022

Cited by 9 | Viewed by 2032

Abstract

Since atopic disease and inflammatory cytokines are both involved in attention deficit hyperactivity disorder (ADHD), in this study, we examined the relationship among cytokine levels, neuropsychological function, and behavioral manifestations in patients with ADHD and atopic diseases. Participants were categorized into individuals with ADHD and atopic disease (n = 41), those with ADHD without allergy (n = 74), individuals without ADHD but with allergy (n = 23), and those without ADHD or allergy (n = 49). We used the Swanson, Nolan, and Pelham IV Scale (SNAP-IV), Conners’ Continuous Performance Test (Conners CPT), and Conners’ Continuous Auditory Test of Attention (CATA) to assess patients’ behavioral symptoms, visual attention, and auditory attention, respectively. Participants’ IFN-γ, IL-1B, IL-6, IL-10, IL-13, IL-17, MCP-1, and TNF-α plasma levels were assessed using multiplex assays. We found that the prevalence rates of atopic diseases (asthma, allergic rhinitis, or atopic dermatitis) were similar between individuals with ADHD and those without ADHD. ADHD behavioral symptoms (SNAP-IV), CPT omission scores, and CATA detectability scores demonstrated significant differences between individuals with ADHD and those without ADHD, regardless of atopic diseases. However, plasma levels of cytokines (TNF-α, IFN-γ, and IL-17) were negatively correlated with inattention symptoms. This study demonstrates a potential relationship between cytokine levels and neuropsychological function among patients with ADHD and atopic diseases. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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13 pages, 2088 KiB

Open AccessArticle

Two Genetic Mechanisms in Two Siblings with Intellectual Disability, Autism Spectrum Disorder, and Psychosis

by Yu-Shu Huang, Ting-Hsuan Fang, Belle Kung and Chia-Hsiang Chen

J. Pers. Med. 2022, 12(6), 1013; https://doi.org/10.3390/jpm12061013 - 20 Jun 2022

Cited by 10 | Viewed by 2963

Abstract

Intellectual disability (ID) and autism spectrum disorder (ASD) are complex neurodevelopmental disorders with high heritability. To search for the genetic deficits in two siblings affected with ID and ASD in a family, we first performed a genome-wide copy number variation (CNV) analysis using chromosomal microarray analysis (CMA). We found a 3.7 Mb microdeletion at 22q13.3 in the younger sister. This de novo microdeletion resulted in the haploinsufficiency of SHANK3 and several nearby genes involved in neurodevelopment disorders. Hence, she was diagnosed with Phelan–McDermid syndrome (PMS, OMIM#606232). We further performed whole-genome sequencing (WGS) analysis in this family. We did not detect pathogenic mutations with significant impacts on the phenotypes of the elder brother. Instead, we identified several rare, likely pathogenic variants in seven genes implicated in neurodevelopmental disorders: KLHL17, TDO2, TRRAP, EIF3F, ATP10A, DICER1, and CDH15. These variants were transmitted from his unaffected parents, indicating these variants have only moderate clinical effects. We propose that these variants worked together and led to the clinical phenotypes in the elder brother. We also suggest that the combination of multiple genes with moderate effects is part of the genetic mechanism of neurodevelopmental disorders. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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15 pages, 2094 KiB

Open AccessArticle

Ultrarare Loss-of-Function Mutations in the Genes Encoding the Ionotropic Glutamate Receptors of Kainate Subtypes Associated with Schizophrenia Disrupt the Interaction with PSD95

by Tsung-Ming Hu, Chia-Liang Wu, Shih-Hsin Hsu, Hsin-Yao Tsai, Fu-Yu Cheng and Min-Chih Cheng

J. Pers. Med. 2022, 12(5), 783; https://doi.org/10.3390/jpm12050783 - 12 May 2022

Cited by 8 | Viewed by 2496

Abstract

Schizophrenia is a complex mental disorder with a genetic component. The GRIK gene family encodes ionotropic glutamate receptors of the kainate subtype, which are considered candidate genes for schizophrenia. We screened for rare and pathogenic mutations in the protein-coding sequences of the GRIK gene family in 516 unrelated patients with schizophrenia using the ion semiconductor sequencing method. We identified 44 protein-altered variants, and in silico analysis indicated that 36 of these mutations were rare and damaging or pathological based on putative protein function. Notably, we identified four truncating mutations, including two frameshift deletion mutations (GRIK1^p.Phe24fs and GRIK1^p.Thr882fs) and two nonsense mutations (GRIK2^p.Arg300Ter and GRIK4^p.Gln342Ter) in four unrelated patients with schizophrenia. They exhibited minor allele frequencies of less than 0.01% and were absent in 1517 healthy controls from Taiwan Biobank. Functional analysis identified these four truncating mutants as loss-of-function (LoF) mutants in HEK-293 cells. We also showed that three mutations (GRIK1^p.Phe24fs, GRIK1^p.Thr882fs, and GRIK2^p.Arg300Ter) weakened the interaction with the PSD95 protein. The results suggest that the GRIK gene family harbors ultrarare LoF mutations in some patients with schizophrenia. The identification of proteins that interact with the kainate receptors will be essential to determine kainate receptor-mediated signaling in the brain. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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12 pages, 931 KiB

Open AccessArticle

Antidepressant Treatment and Manic Switch in Bipolar I Disorder: A Clinical and Molecular Genetic Study

by Chih-Ken Chen, Lawrence Shih-Hsin Wu, Ming-Chyi Huang, Chian-Jue Kuo and Andrew Tai-Ann Cheng

J. Pers. Med. 2022, 12(4), 615; https://doi.org/10.3390/jpm12040615 - 11 Apr 2022

Cited by 8 | Viewed by 4079

Abstract

Affective switch is an important clinical issue when treating bipolar disorder. Though commonly seen in clinical practice, the benefits of prescribing antidepressants for bipolar depression are still controversial. To date, there have been few genetic studies and no genome-wide association study (GWAS), focusing on manic switch following bipolar depression. This study aims to investigate the effects of individual genomics and antidepressant medication on the risk of manic switch in bipolar I disorder (BPI). A total of 1004 patients with BPI who had at least one depressive episode with complete data on antidepressant treatment and outcome were included. Clinical assessment of mania and depression was performed by trained psychiatric nurses and psychiatrists using the Chinese version of the Schedules for Clinical Assessment in Neuropsychiatry (SCAN), and the diagnosis of BPI was made according to DSM-IV criteria. Manic switch was defined as a manic episode occurring within eight weeks of remission from an acute depressive episode. The age at first depressive episode of the study patients was 30.7 years (SD 12.5) and 56% of all patients were female. GWAS was carried out in a discovery group of 746 patients, followed by replication in an independent group of 255 patients. The top SNP rs10262219 on chromosome 7 showed the strongest allelic association with manic switch (p = 2.21 × 10⁻⁷) in GWAS, which was however not significantly replicated. Antidepressant treatment significantly (odds ratio 1.7; 95% CI 1.3–2.2; p < 0.001) increased the risk of manic switch. In logistic regression analysis, the CC genotype of rs10262219 (odds ratio 3.0; 95% CI 1.7–5.2) and antidepressant treatment (odds ratio 2.3; 95% CI 1.4–3.7) significantly increased the risk of manic switch with a joint effect (odds ratio 5.9; 95% CI 3.7–9.4). In conclusion, antidepressant medication and rs10262219 variants jointly increased the risk of manic switch after bipolar depression. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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23 pages, 9081 KiB

Open AccessArticle

Long-Lasting Exendin-4-Loaded PLGA Nanoparticles Ameliorate Cerebral Ischemia/Reperfusion Damage in Diabetic Rats

by Cheng-Hsun Chung, Shiu-Dong Chung, Yu-Hsuan Cheng, Chun-Pai Yang and Chiang-Ting Chien

J. Pers. Med. 2022, 12(3), 390; https://doi.org/10.3390/jpm12030390 - 3 Mar 2022

Cited by 6 | Viewed by 3090

Abstract

Exendin-4 (Ex-4) is an incretin mimetic agent approved for diabetes treatment and neuronal protection. However, the required frequent injections restrict its clinical application. We prepared Ex-4-loaded poly(d,l-lactide-co-glycolide) nanoparticles (PEx-4) and investigated their effect on cerebral ischemia/reperfusion (IR) injury associated with micturition center damage-induced cystopathy in diabetic rats. Using ten minutes of bilateral carotid artery occlusion combined with hemorrhage-induced hypotension of the IR model in streptozotocin-induced type 1 diabetic (T1DM) Wistar rats, we compared the effects of Ex-4 and PEx-4 on prefrontal cortex edema, voiding function and oxidative stress including cerebral spinal fluid (CSF) reference H₂O₂ (RH₂O₂) and HOCl (RHOCl) levels, endoplasmic reticulum (ER) stress, apoptosis, autophagy and pyroptosis signaling in brain and bladder by Western blot and immunohistochemistry. Single injection of PEx-4 displayed higher CSF antioxidant activity and a long-lasting hypoglycemic effect compared to Ex-4 in rats. T1DM and IR primarily enhanced CSF RH₂O₂, and pIRE-1/caspase-12/pJNK/CHOP-mediated ER stress, caspase-3/PARP-mediated apoptosis, Beclin-1/LC3B-mediated autophagy and caspase-1/IL-1β-mediated pyroptosis signaling in the damaged brains. Our data further evidenced that PEx-4 were more efficient than Ex-4 in attenuating IR-evoked prefrontal cortex edema, the impairment in micturition center and the enhanced level of CSF RH₂O₂ and HOCl, ER stress, apoptosis, autophagy and pyroptosis parameters in the damaged brains, but had less of an effect on IR-induced voiding dysfunction in bladders of T1DM rats. In summary, PEx-4 with stronger antioxidant activity and long-lasting bioavailability may efficiently confer therapeutic efficacy to ameliorate IR-evoked brain damage through the inhibitory action on oxidative stress, ER stress, apoptosis, autophagy and pyroptosis signaling in diabetic rats. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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Review

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11 pages, 276 KiB

Open AccessReview

Racial/Ethnic Differences in the Pharmacokinetics of Antipsychotics: Focusing on East Asians

by Shih-Ku Lin

J. Pers. Med. 2022, 12(9), 1362; https://doi.org/10.3390/jpm12091362 - 24 Aug 2022

Cited by 15 | Viewed by 3692

Abstract

Empirical clinical studies have suggested that East Asian patients may require lower dosages of psychotropic drugs, such as antipsychotics, lithium, and antidepressants, than non-Asians. Both the pharmacokinetic and pharmacodynamic properties of a drug can affect the clinical response of an illness. The levels of antipsychotics used for the treatment of schizophrenia may affect patient clinical responses; several factors can affect these levels, including patient medication adherence, body weight (BW) or body mass index, smoking habits, and sex. The cytochrome P450 (CYP) system is a major factor affecting the blood levels of antipsychotics because many antipsychotics are metabolized by this system. There were notable genetic differences between people of different races. In this study, we determined the racial or ethnic differences in the metabolic patterns of some selected antipsychotics by reviewing therapeutic drug monitoring studies in East Asian populations. The plasma concentrations of haloperidol, clozapine, quetiapine, aripiprazole, and lurasidone, which are metabolized by specific CYP enzymes, were determined to be higher, under the same daily dose, in East Asian populations than in Western populations. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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12 pages, 1377 KiB

Open AccessBrief Report

Deep Clinical Phenotyping of Schizophrenia Spectrum Disorders Using Data-Driven Methods: Marching towards Precision Psychiatry

by Tesfa Dejenie Habtewold, Jiasi Hao, Edith J. Liemburg, Nalan Baştürk, Richard Bruggeman and Behrooz Z. Alizadeh

J. Pers. Med. 2023, 13(6), 954; https://doi.org/10.3390/jpm13060954 - 5 Jun 2023

Cited by 1 | Viewed by 2164

Abstract

Heterogeneity is the main challenge in the traditional classification of mental disorders, including schizophrenia spectrum disorders (SSD). This can be partly attributed to the absence of objective diagnostic criteria and the multidimensional nature of symptoms and their associated factors. This article provides an overview of findings from the Genetic Risk and Outcome of Psychosis (GROUP) cohort study on the deep clinical phenotyping of schizophrenia spectrum disorders targeting positive and negative symptoms, cognitive impairments and psychosocial functioning. Three to four latent subtypes of positive and negative symptoms were identified in patients, siblings and controls, whereas four to six latent cognitive subtypes were identified. Five latent subtypes of psychosocial function—multidimensional social inclusion and premorbid adjustment—were also identified in patients. We discovered that the identified subtypes had mixed profiles and exhibited stable, deteriorating, relapsing and ameliorating longitudinal courses over time. Baseline positive and negative symptoms, premorbid adjustment, psychotic-like experiences, health-related quality of life and PRS_SCZ were found to be the strong predictors of the identified subtypes. Our findings are comprehensive, novel and of clinical interest for precisely identifying high-risk population groups, patients with good or poor disease prognosis and the selection of optimal intervention, ultimately fostering precision psychiatry by tackling diagnostic and treatment selection challenges pertaining to heterogeneity. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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12 pages, 1139 KiB

Open AccessPerspective

Proof of Concept of the Contribution of the Interaction between Trait-like and State-like Effects in Identifying Individual-Specific Mechanisms of Action in Biological Psychiatry

by Sigal Zilcha-Mano, Nili Solomonov, Jonathan E. Posner, Steven P. Roose and Bret R. Rutherford

J. Pers. Med. 2022, 12(8), 1197; https://doi.org/10.3390/jpm12081197 - 23 Jul 2022

Cited by 4 | Viewed by 1409

Abstract

Background: Identifying individual-specific mechanisms of action may facilitate progress toward precision medicine. Most studies seeking to identify mechanisms of action collapse together two distinct components: pre-treatment trait-like characteristics differentiating between individuals and state-like characteristics changing within each individual over the course of treatment. We suggest a conceptual framework highlighting the importance of studying interactions between trait-like and state-like components in the development of moderated mediation models that can guide personalized targeted interventions. Methods: To facilitate implementation of this framework, two empirical demonstrations are presented from a recent clinical trial and neuroimaging study. The first examines limbic reactivity during an emotional face task; the second concerns striatal activation in a monetary reward task. Results: In both tasks, considering the interaction between trait-like and state-like components predicted treatment outcome more robustly than did the trait-like or state-like components examined individually. Conclusions: These findings suggest that the extent to which state-like modulation of neural activations can serve as a potential treatment target depends on the pre-treatment, trait-like levels of activation in these regions. Thus, the interaction between trait-like and state-like components can serve as a promising path to the development of personalized interventions within a precision medicine framework in which mechanisms of action are individual-specific. Full article

(This article belongs to the Special Issue Recent Advances in Precision Psychiatry)

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