Psychiatric Genetics最新文献

Objective: Schizophrenia (SCZ) is a debilitating disease with a complex genetic cause in which age at onset may reflect genetic vulnerability. Though there has been some association between genetic polymorphisms and age of onset, there has been little exploration of the role of epigenetic processes. We sought to explore the influence of DNA methylation, a key epigenetic mechanism, and its association with the age of onset of illness.

Methods: One hundred thirty-eight participants aged 18-75 years and previously diagnosed with SCZ spectrum disorders by the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders (SCID DSM-5) were recruited. Venous blood was collected and genome-wide DNA methylation was quantified using the Illumina Infinium HumanMethylation450 BeadChip array. Individual CpG sites and regions of differential methylation were explored by the age of onset; covariates included age, sex, as well as white blood cell composition.

Results: Binary grouping (early vs. late onset) revealed four intergenic CpG sites on chromosome 2 that were above the expected P-value threshold, with hypermethylation of the CpG site cg10392614 most strongly associated with early-onset SCZ. The four most strongly associated CpG sites, including cg 10392614, were intergenic. Continuous analysis revealed the top CpG site to be cg11723066 , which is linked to the JAM3 gene, with hypomethylation associated with earlier onset; however, results were below the expected P-value threshold.

Conclusion: Studies on DNA methylation in the first-episode psychosis population may help further our understanding of the role of epigenetics in the age of onset of SCZ.

A considerable group of patients suffering from mental health disorders do not respond adequately to pharmacological treatment. For the purposes of precision and personalized medicine, pharmacogenomics has been developed as a valuable and promising tool. The technology of identifying single nucleotide polymorphisms and genotyping supplies clinicians, and therefore their patients, with the opportunity of avoiding long-lasting 'trial and error' periods, reducing the risk of manifesting disturbing adverse effects during treatment. Consequently, better adherence to treatment and clinical response can be achieved, contributing to personalized treatment planning, according to a person's genetic profile and needs. In the present report, we present a case of an individual diagnosed with bipolar affective disorder type I, who showed resistance to pharmacological treatment and underwent through pharmacogenomic investigations, in order to identify the appropriate medication for the best possible clinical response.

Introduction: The distribution pattern and knowledge structure of psychiatric genomics were surveyed based on literature dealing with both psychiatry and genomics/genetics. Coword analysis and bibliographic coupling of the records retrieved from Scopus and PubMed for 2016-2020 revealed the subsurface research aspects.

Method: The data were analyzed using coword analysis and clustering methods using Sci2 and VOSviewer.

Result: Analysis of ~3800 records showed that psychiatric genomics is, as expectedly, covered largely under biomedical subjects with a visible interest in other disciplines such as humanities and ethics. A coword analysis was done for all the years, followed by a year-wise analysis based on the keywords, and then a bibliographic coupling based on the cited references. This led to the generation of different clusters of prevalent research areas. The centrality values described the position of each component.

Discussion: 'Schizophrenia', 'depression', 'pharmacogenomics', and 'immunopathogenesis' were the research topics of overarching interest. 'Gut-brain axis' and 'gene-environment interaction' were the emerging topics, whereas certain topics such as 'child and adolescent psychiatry' remained priorities when compared to earlier studies. The keywords and research focus were diverse. They ranged from genetics to transcriptomics and epigenetics to proteomics of psychiatric disorders. We found a stagnation of science communication in the field with only 0.2% of the articles from the entire corpus relevant to it. The research categories identified in this study reflect the current publication and research trends in psychiatric genomics.

Sex can influence almost all aspects of schizophrenia. However, the molecular mechanisms underlying sex differences in schizophrenia remain poorly understood. In this project, the dataset GSE107638 containing neuronal RNA-seq data and age/sex information of individuals with or without schizophrenia were retrieved. Schizophrenia samples were divided into young male (M-1), young female (F-1), middle-aged and elderly male (M-2) and middle-aged and elderly female (F-2) groups. Next, green/yellow/turquoise modules related to the M-2 trait and turquoise module correlated with the F-2 trait were identified by weighted correlation network analysis (WGCNA) analysis (soft thresholding power: 13; min module size: 200). Crucial genes in the M-2 green, M-2 turquoise and F-2 turquoise modules were identified by WGCNA, gene significance/module membership, and protein-protein interaction (PPI) analysis. Moreover, 2067 and 934 differentially expressed genes (|log2 fold-change| ≥0.58 and P-value < 0.05) in M-2 and F-2 schizophrenia subgroups versus same-age and same-sex counterparts were identified, respectively. Additionally, 82 core genes in the M-2 turquoise module and 4 hub genes in the F-2 turquoise module were differentially expressed in M-2 and F-2 schizophrenia subgroups versus their counterparts, respectively. Among the 82 hub genes, 15 genes were found to be correlated with neuronal development by the Kyoto Encyclopedia of Genes and Genomes enrichment analysis. Also, 2 potential PPI networks related to neuronal development were identified. Taken together, multiple potential hub genes and 2 potential neurobiological networks related to schizophrenia sex differences and disease progression were identified among middle-aged and elderly schizophrenia populations.

Coffin-Lowry syndrome (CLS) is a rare X-linked disorder that, usually affects males, presenting with intellectual disability, short stature, growth retardation, short hands, hyperextensible fingers and progressive kyphoscoliosis. Due to skewed X chromosome inactivation, the clinical presentations of the affected females vary greatly and clinical manifestations could range from mild intellectual disability to typical features of CLS in males. Here, we reported two different novel RPS6KA3 gene mutations in two unrelated CLS patients and also described concomitant compulsive eyebrow-pulling behavior in one of these cases for the first time in the literature.

Background: Schizophrenia is a chronic brain disorder. Previously, the Schizophrenia Exome Sequencing Meta-analysis consortium identified 10 highest risk genes related to schizophrenia. This study aimed to analyze the relationship between the 10 highest risk genes identified by the SCHEMA and schizophrenia in a Chinese population.

Methods: A total of 225 variants in 10 genes were screened in a Chinese population of 6836 using a customized array. All variants were annotated through the Variant Effect Predictor tool, and the functional impacts of missense variants were assessed based on sorting intolerant from tolerant and PolyPhen-2 scores. The SHEsisPlus tool was used to analyze the association between risk genes and schizophrenia at the locus and gene levels.

Results: At the locus level, no missense variants significantly related to schizophrenia were found, but we detected three missense variants that appeared only in cases, including TRIO p. Arg1185Gln, RB1CC1 p. Arg1514Cys, and HERC1 p. Val4517Leu. At the gene level, five genes (TRIO, RB1CC1, HERC1, GRIN2A, and CACAN1G) with more than one variant analyzed were kept for the gene-level association analysis. Only the association between RB1CC1 and schizophrenia reached a significant level (OR = 1.634; 95% CI, 1.062-2.516; P = 0.025).

Conclusion: In this study, we determined that RB1CC1 might be a risk gene for schizophrenia in the Chinese population. Our results provide new evidence for recognizing the correlation of these risk genes with the Chinese schizophrenia population.

Objective: Clozapine response varies widely from person to person, which may be due to inter-individual genetic variability. This umbrella review aims to summarize the current evidence on associations between pharmacodynamic genes and response to clozapine treatment.

Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis methodology, a systematic literature search was conducted in the PubMed and EMBASE databases from inception to November 2021 to identify systematic reviews and meta-analyses of studies that examined genetic determinants of clozapine response. The quality of the reviews was assessed with the AMSTAR-2 tool.

Results: From a total of 128 records, 10 studies representing nine systematic reviews and one meta-analysis met our inclusion criteria. The overall quality of the included studies was poor. All systematic reviews concluded that the results of primary studies were largely negative or conflicting. Most evidence was found for an association with clozapine response and rs6313 and rs6314 within HTR2A and rs1062613 within HTR3A in the serotonergic system.

Conclusions: Conclusive evidence for associations between genetic variants and clozapine response is still lacking. Hypothesis-generating genetic studies in large, well-characterized study populations are urgently needed to obtain more consistent and clinically informative results. Future studies may also include multi-omics approaches to identify novel genetic determinants associated with clozapine response.

Introduction: The complex structure of the chromosome 2q12.3-q13 region provides a high chance of recombination events between various low copy repeats (LCRs). Copy number variants (CNV) in this region are present in both healthy populations and individuals affected with developmental delay, autism and congenital anomalies. Variable expressivity, reduced penetrance and limited characterization of the affected genes have complicated the classification of the CNVs clinical significance.

Methods: Chromosomal microarray analysis data were reviewed for 10 298 patients with neurodevelopmental disorders referred to the UPMC Medical Genetics and Genomics Laboratories. A genotype-phenotype correlation was performed among the patients harboring the 2q12.3-q13 CNVs with overlapping genomic intervals.

Results: We identified 17 (1 in ~600) individuals with rare CNVs in the 2q12.3-q13 region, including nine patients with deletions, seven individuals with duplications and one patient who had both a deletion and a duplication. Likely pathogenic CNVs with the breakpoints between LCRs encompassing the potential dosage-sensitive genes BCL2L11, BUB1, FBLN7 and TMEM87B were the most common. CNVs were also observed between LCRs surrounding the RANBP2 and LIMS1 genes.

Conclusion: Our study provides evidence for pathogenic CNV hotspots within the chromosome 2q12.3-q13 region. We suggest CNV classification based on the affected interval and the involvement of potential dosage-sensitive genes in these patients.

Objectives: We aimed to identify differentially methylated genes and related signaling pathways in autism spectrum disorder (ASD).

Methods: First, the DNA methylation profile in the brain samples (GSE131706 and GSE80017) and peripheral blood samples (GSE109905) was downloaded from the Gene Expression Omnibus database (GEO) dataset, followed by identification of differentially methylated genes and functional analysis. Second, the GSE109905 data set was used to further validate the methylation state and test the ability to diagnose disease of identified differentially methylated genes. Third, expression measurement of selected differentially methylated genes was performed in whole blood from an independent sample. Finally, protein-protein interaction (PPI) network of core differentially methylated genes was constructed.

Results: Totally, 74 differentially methylated genes were identified in ASD, including 38 hypermethylated genes and 36 hypomethylated genes. 15 differentially methylated genes were further identified after validation in the GSE109905 data set. Among these, major histocompatibility complex (HLA)-DQA1 was involved in the molecular function of myosin heavy chain class II receptor activity; HLA-DRB5 was involved in the signaling pathways of cell adhesion molecules, Epstein-Barr virus infection and antigen processing and presentation. In the PPI analysis, the interaction pairs of HLA-DQA1 and HLA-DRB5, FMN2 and ACTR3, and CALCOCO2 and BAZ2B were identified. Interestingly, FMN2, BAZ2B, HLA-DRB5, CALCOCO2 and DUSP22 had a potential diagnostic value for patients with ASD. The expression result of four differentially methylated genes (HLA-DRB5, NTM, IL16 and COL5A3) in the independent sample was consistent with the integrated analysis.

Conclusions: Identified differentially methylated genes and enriched signaling pathway could be associated with ASD.

Objective: T helper 17 (Th17) pathway has been reported to be abnormal in schizophrenia; however, it is not known whether variation within genes of this pathway has any impact on schizophrenia. Herein, the impact of genetic variations and gene-gene interactions of Th17 pathway-related genes on the risk, psychopathology, and brain volume was examined in schizophrenia patients.

Methods: Functional polymorphisms within interleukin 6 ( IL6 )(rs1800795 and rs1800797), IL10 (rs1800872 and rs1800896), IL17A (rs2275913 and rs8193036), IL22 (rs2227484 and rs2227485), IL23R (rs1884444), and IL27 (rs153109 and rs181206) genes were studied in 224 schizophrenia patients and 226 healthy controls. These variants were correlated with the brain morphometry, analyzed using MRI in a subset of patients ( n = 117) and controls ( n = 137).

Results: Patients carrying CC genotype of rs2227484 of IL22 gene had significantly higher apathy total score [ F (1,183) = 5.60; P = 0.019; partial ɳ 2 = 0.030]. Significant epistatic interactions between IL6 (rs1800797) and IL17A (rs2275913) genes were observed in schizophrenia patients. GG genotype of rs2275913 of IL17A gene was associated with reduced right middle occipital gyrus volume in schizophrenia patients ( T = 4.56; P < 0.001).

Conclusion: Interactions between genes of Th17 pathway impact the risk for schizophrenia. The variants of Th17 pathway-related genes seem to have a determining effect on psychopathology and brain morphometric changes in schizophrenia.