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Analysis of copy number variations in brain DNA from patients with schizophrenia and other psychiatric disorders.

ABSTRACT: BACKGROUND:Clinical studies have identified several regions of the genome with copy number variations (CNVs) associated with diverse neurodevelopmental behavioral disorders. METHODS:We analyzed 1 million (M) single nucleotide polymorphism genotype arrays for evidence of previously reported recurrent CNVs and enriched genome-wide CNV burden in DNA from 600 brains, including 441 individuals with various psychiatric diagnoses. We explored gene expression in the dorsolateral prefrontal cortex in selected cases with CNVs and in other subjects with Illumina BeadArrays (568 subjects in total) and additionally in 66-92 subjects with quantitative real-time polymerase chain reaction. RESULTS:The CNVs in previously reported genomic regions were identified in 4 of 193 patients with the diagnosis of schizophrenia (1q21.1, 11q25, 15q11.2, 22q11), 4 of 238 patients with mood disorders (11q25, 15q11.2, 22q11), and 1 of 10 patients with autism (2p16.3). No evidence of increased genome-wide CNV burden was observed in cases with schizophrenia or mood disorders, although the study is underpowered to observe rare events. Messenger RNA expression patterns suggested incomplete molecular penetrance of observed CNVs. CONCLUSIONS:Our data confirm in brain DNA the presence of certain recurrent CNVs in a small percentage of patients with psychiatric diagnoses.

SUBMITTER: Ye T

PROVIDER: S-EPMC3456994 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Analysis of copy number variations in brain DNA from patients with schizophrenia and other psychiatric disorders.

Ye Tianzhang T Lipska Barbara K BK Tao Ran R Hyde Thomas M TM Wang Liqin L Li Chao C Choi Kwang H KH Straub Richard E RE Kleinman Joel E JE Weinberger Daniel R DR

Biological psychiatry 20120715 8

<h4>Background</h4>Clinical studies have identified several regions of the genome with copy number variations (CNVs) associated with diverse neurodevelopmental behavioral disorders.<h4>Methods</h4>We analyzed 1 million (M) single nucleotide polymorphism genotype arrays for evidence of previously reported recurrent CNVs and enriched genome-wide CNV burden in DNA from 600 brains, including 441 individuals with various psychiatric diagnoses. We explored gene expression in the dorsolateral prefronta ...[more]

PMID: 22795968

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Project description:Schizophrenia is a common mental disorder with high heritability and strong genetic heterogeneity. Common disease-common variants hypothesis predicts that schizophrenia is attributable in part to common genetic variants. However, recent studies have clearly demonstrated that copy number variations (CNVs) also play pivotal roles in schizophrenia susceptibility and explain a proportion of missing heritability. Though numerous CNVs have been identified, many of the regions affected by CNVs show poor overlapping among different studies, and it is not known whether the genes disrupted by CNVs contribute to the risk of schizophrenia. By using cumulative scoring, we systematically prioritized the genes affected by CNVs in schizophrenia. We identified 8 top genes that are frequently disrupted by CNVs, including NRXN1, CHRNA7, BCL9, CYFIP1, GJA8, NDE1, SNAP29, and GJA5. Integration of genes affected by CNVs with known schizophrenia susceptibility genes (from previous genetic linkage and association studies) reveals that many genes disrupted by CNVs are also associated with schizophrenia. Further protein-protein interaction (PPI) analysis indicates that protein products of genes affected by CNVs frequently interact with known schizophrenia-associated proteins. Finally, systematic integration of CNVs prioritization data with genetic association and PPI data identifies key schizophrenia candidate genes. Our results provide a global overview of genes impacted by CNVs in schizophrenia and reveal a densely interconnected molecular network of de novo CNVs in schizophrenia. Though the prioritized top genes represent promising schizophrenia risk genes, further work with different prioritization methods and independent samples is needed to confirm these findings. Nevertheless, the identified key candidate genes may have important roles in the pathogenesis of schizophrenia, and further functional characterization of these genes may provide pivotal targets for future therapeutics and diagnostics.

Project description:ImportanceRecurrent copy number variants (rCNVs) have been associated with increased risk of psychiatric disorders in case-control studies, but their population-level impact is unknown.ObjectiveTo provide unbiased population-based estimates of prevalence and risk associated with psychiatric disorders for rCNVs and to compare risks across outcomes, rCNV dosage type (deletions or duplications), and locus features.Design, setting, and participantsThis genetic association study is an analysis of data from the Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH) case-cohort sample of individuals born in Denmark in 1981-2008 and followed up until 2015, including (1) all individuals (n = 92 531) with a hospital discharge diagnosis of attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder, major depressive disorder (MDD), or schizophrenia spectrum disorder (SSD) and (2) a subcohort (n = 50 625) randomly drawn from the source population. Data were analyzed from January 2021 to August 2023.ExposuresCarrier status of deletions and duplications at 27 autosomal rCNV loci was determined from neonatal blood samples genotyped on single-nucleotide variant microarrays.Main outcomes and measuresPopulation-based rCNV prevalence was estimated with a survey model using finite population correction to account for oversampling of cases. Hazard ratio (HR) estimates and 95% CIs for psychiatric disorders were derived using weighted Cox proportional hazard models. Risks were compared across outcomes, dosage type, and locus features using generalized estimating equation models.ResultsA total of 3547 rCNVs were identified in 64 735 individuals assigned male at birth (53.8%) and 55 512 individuals assigned female at birth (46.2%) whose age at the end of follow-up ranged from 7.0 to 34.7 years (mean, 21.8 years). Most observed increases in rCNV-associated risk for ADHD, ASD, or SSD were moderate, and risk estimates were highly correlated across these disorders. Notable exceptions included high ASD-associated risk observed for Prader-Willi/Angelman syndrome duplications (HR, 20.8; 95% CI, 7.9-55). No rCNV was associated with increased MDD risk. Also, rCNV-associated risk was positively correlated with locus size and gene constraint but not with dosage type. Comparison with published case-control and community-based studies revealed a higher prevalence of deletions and lower associated increase in risk for several rCNVs in iPSYCH2015.Conclusions and relevanceThis study found that several rCNVs were more prevalent and conferred less risk of psychiatric disorders than estimated previously. Most case-control studies overestimate rCNV-associated risk of psychiatric disorders, likely because of selection bias. In an era where genetics is increasingly being clinically applied, these results highlight the importance of population-based risk estimates for genetics-based predictions.

Dataset Information

Analysis of copy number variations in brain DNA from patients with schizophrenia and other psychiatric disorders.

Publications

Analysis of copy number variations in brain DNA from patients with schizophrenia and other psychiatric disorders.

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