Project # | Submitter name | Affiliation | Conference | Title of abstract | Abstract |
2 | Marieke Klein | Department of Psychiatry, University of California San Diego, 92093 La Jolla, CA, USA | WCPG 2020 | Analysis of genomic copy number variation across psychiatric disorders | Copy number variants (CNVs) have been identified as a major risk factor in neuropsychiatric disorders and are implicated across many neurodevelopmental disorders, partially contributing to their shared genetic etiology. The pleiotropic effects of CNVs in which specific risk alleles may increase risk for multiple disorders have previously been demonstrated. This study set out to determine associations of 93 known pathogenic CNVs across multiple psychiatric and developmental disorders, and to characterize the range of psychiatric risk associated with each CNV. CNVs were called in the PGC-Autism, PGC-Bipolar, PGC-Schizophrenia and a large cohort of (mostly pediatric) subjects ascertained through clinical genetic testing (CLIN; mostly developmental delay). In total, we analysed data from 307,236 individuals who passed CNV quality control, including 15,016 patients with autism spectrum disorder (ASD), 27,372 patients with bipolar disorder (BD), 35,609 patients with schizophrenia (SZ), 115,850 control samples, and 113,389 individuals from two clinical genetics datasets (referred to as CLIN). We analysed 93 pathogenic CNVs, including both their reciprocal deletions and duplications, for association with the different psychiatric disorders. We compared effect sizes across diagnostic categories and performed cluster analyses to determine genetic relationships between disorders and to determine whether CNVs can be clustered into distinct groups based on their trait associations. Overall reciprocal deletions and duplications had divergent effects across diagnostic categories, as effect sizes for “developmental delay” (ASD and CLIN) were significantly positively correlated, whereas we observed significant “mirror” effects for SZ, i.e. higher effect sizes for deletions were correlated with lower effect sizes for duplications and vice versa. Clustering of diagnostic categories across CNVs revealed that disorders clustered according to period of onset with pediatric disorders (ASD and CLIN) being highly correlated and adolescent/adult-onset disorders (BP and SZ) being correlated. We identified groups of CNVs which tend to cluster into groups based on phenotype association, with one subgroup being predominantly “CLIN” and other groupings that differ from each other based on their combination of psychiatric associations; for example some with a predominant ASD, some with predominant SZ and others with differing combinations. Most distinct patterns were seen for loci where risk is primarily associated with adult psychiatric disorders and we identified one cluster to be significantly different from others (p < 0.009). The significant cluster included the 1q21.1, 2q11.2 and 2q13 loci and showed larger effects in BD and SZ. These results suggest that specific CNV alleles have distinct psychiatric risk profiles, and further suggest that a psychiatric profile may be attributable to the functions or expression of the underlying genes in the brain. Our ongoing studies will test for enrichment of biological processes or spatial and temporal brain expression of genes within each cluster to better understand the biological mechanisms within the CNV groups. In addition, we will expand the range of cognitive and neuropsychiatric traits through inclusion of additional disorders and disorder related phenotypes. |
2 | Marieke Klein | Department of Psychiatry, University of California San Diego, 92093 La Jolla, CA, USA | ASHG 2020 | Analysis of genomic copy number variation across psychiatric disorders | Copy number variants (CNVs) have been identified as a major risk factor in neuropsychiatric disorders and are implicated across many psychiatric disorders, partially contributing to their shared genetic etiology. Pleiotropic effects of CNVs in which specific risk alleles may increase risk for multiple disorders were previously shown. Here, we determine associations of 93 pathogenic CNVs across psychiatric disorders, and characterize the range of psychiatric risk associated with each CNV. CNVs were called in PGC-Autism, PGC-Bipolar, PGC-Schizophrenia data and two cohorts of (mostly pediatric) subjects ascertained through clinical genetic testing (mainly for neurodevelopmental disorders). We analysed data from 307,236 individuals, including 15,016 patients with autism (ASD), 27,372 patients with bipolar disorder (BD), 35,609 patients with schizophrenia (SZ), 115,850 control samples, and 113,389 individuals from two clinical genetics datasets (CLIN). We analysed 93 pathogenic CNVs, including reciprocal deletions and duplications, for association with different psychiatric disorders. We compared effect sizes across diagnostic categories and performed cluster analyses to determine genetic relationships between disorders and to determine whether CNVs can be clustered into distinct groups based on their trait associations. Clustering of diagnostic categories across CNVs revealed that disorders clustered according to period of onset with pediatric disorders (ASD and CLIN) being highly correlated and adult-onset disorders (BP and SZ) being correlated. Overall reciprocal deletions and duplications had divergent effects across diagnostic categories, suggesting that CNVs have “mirror” effects on psychiatric traits, as it has been previously documented for anthropometric traits such as head size. Groups of CNVs tend to cluster into groups based on phenotype association, with one subgroup being predominantly “CLIN” and other groupings that differ from each other based on their combination of psychiatric associations; for example some with a predominant ASD, predominant SZ or with differing combinations. This suggests that specific CNV alleles have distinct psychiatric risk profiles and such profiles may be attributable to function or expression of underlying genes in the brain. Ongoing studies will test for enrichment of biological processes or spatial-temporal brain expression of genes within each cluster to better understand the biological mechanisms within the CNV groups. In addition, we will expand the range of cognitive and neuropsychiatric traits through inclusion of additional disorders and disorder related phenotypes. |
2 | Marieke Klein | Department of Psychiatry, University of California San Diego, 92093 La Jolla, CA, USA | ESHG 2021 | Analysis of genomic copy number variation across psychiatric disorders | Background: Copy number variants (CNVs) are major risk factors in neuropsychiatric disorders and are partially contributing to their shared genetic etiology. Here, we determine associations of pathogenic CNVs across five psychiatric disorders and investigate the modifying role of common genetic variants in CNV carriers. Methods: Harmonized CNV calling and quality control was performed for data from 262,190 individuals, including patients with Attention-Deficit/Hyperactivity Disorder (ADHD, N=5,364), autism (ASD, N=15,030), bipolar disorder (BD, N=25,766), schizophrenia (SZ, N=32,635), control samples (N=70,006), and 113,389 individuals from clinical genetics datasets (CLIN, predominantly developmental delay). We analyzed 42 multi-genic pathogenic CNVs, including reciprocal deletions and duplications, for association with different psychiatric disorders. Results: Disorders clustered according to period of onset with pediatric disorders (ASD and CLIN) being highly correlated and adult-onset disorders (BP and SZ) being correlated. Groups of CNVs tend to cluster based on phenotype associations, with the most distinct CNV cluster showing larger effects in ADHD, BD and SZ. Overall, reciprocal deletions and duplications had divergent effects across diagnostic categories, suggesting that CNVs have “mirror” effects on psychiatric traits, such as CLIN and SZ. Polygenic risk scores (PRS) and CNV genotype (16p11.2 locus) showed combined effects on dimensional traits. Conclusions: Specific CNV alleles have distinct psychiatric risk profiles and that may be attributable to function or expression of underlying genes in the brain. PRS contributed to the variable phenotypic expressivity in CNV carriers. We will expand the range of cognitive and neuropsychiatric traits through inclusion of additional disorders and disorder-related phenotypes. |
2 | Marieke Klein | Department of Psychiatry, University of California San Diego, 92093 La Jolla, CA, USA | SOBP 2021 | Analysis of genomic copy number variation and their interaction with polygenic risk scores across psychiatric disorders | Background: Copy number variants (CNVs) are major risk factors in neuropsychiatric disorders and are partially contributing to their shared genetic etiology. Here, we determine associations of pathogenic CNVs across five psychiatric disorders and investigate the modifying role of common genetic variants in CNV carriers. Methods: Harmonized CNV calling and quality control was performed for data from 262,190 individuals, including patients with Attention-Deficit/Hyperactivity Disorder (ADHD, N=5,364), autism (ASD, N=15,030), bipolar disorder (BD, N=25,766), schizophrenia (SZ, N=32,635), control samples (N=70,006), and 113,389 individuals from clinical genetics datasets (CLIN, predominantly developmental delay). We analyzed 42 multi-genic pathogenic CNVs, including reciprocal deletions and duplications, for association with different psychiatric disorders. Results: Disorders clustered according to period of onset with pediatric disorders (ASD and CLIN) being highly correlated and adult-onset disorders (BP and SZ) being correlated. Groups of CNVs tend to cluster based on phenotype associations, with the most distinct CNV cluster showing larger effects in ADHD, BD and SZ. Overall, reciprocal deletions and duplications had divergent effects across diagnostic categories, suggesting that CNVs have “mirror” effects on psychiatric traits, such as CLIN and SZ. Polygenic risk scores (PRS) and CNV genotype (16p11.2 locus) showed combined effects on dimensional traits. Conclusions: Specific CNV alleles have distinct psychiatric risk profiles and that may be attributable to function or expression of underlying genes in the brain. PRS contributed to the variable phenotypic expressivity in CNV carriers. We will expand the range of cognitive and neuropsychiatric traits through inclusion of additional disorders and disorder-related phenotypes. |
2 | Marieke Klein | Department of Psychiatry, University of California San Diego, 92093 La Jolla, CA, USA | WCPG 2021 | Analysis of genomic copy number variation and their interaction with polygenic risk scores across psychiatric disorders | Copy number variants (CNVs) are major risk factors in neuropsychiatric disorders and are partially contributing to their shared genetic etiology. This project aims to achieve clarity on how CNVs contribute to psychiatric traits and how the diagnoses are shaped by a combination of CNVs and common polygenic factors. Here, we determine associations of pathogenic CNVs across psychiatric disorders and investigate the modifying role of common genetic variants on clinical and dimensional traits in CNV carriers. Harmonized CNV calling and quality control was performed for data from 579,488 individuals, including patients with Attention-Deficit/Hyperactivity Disorder (ADHD, N=4,488), autism (ASD, N=15,906), bipolar disorder (BD, N=23,596), post-traumatic-stress disorder (PTSD, N=11,070), schizophrenia (SZ, N=31,686), control samples (N=107,355), 117,491 individuals from clinical genetics datasets (CLIN, predominantly developmental delay) and UK Biobank (UKBB; N=267,896). We analyzed 42 multi-genic pathogenic CNVs, including reciprocal deletions and duplications, for association with different psychiatric disorders. We compared effect sizes across diagnostic categories and performed cluster analyses to determine genetic relationships between disorders and to determine whether CNVs can be clustered into distinct groups based on their trait associations. Next, we analyzed the combined effects of CNVs and polygenic risk scores (PRS) on psychiatric diagnoses and dimensional phenotypes. Disorders clustered according to period of onset with pediatric disorders (ASD and CLIN) being highly correlated and adult-onset disorders (BP and SZ) being correlated. Groups of CNVs tend to cluster based on phenotype associations, with the most distinct CNV cluster showing larger effects in ADHD, BD and SZ. Genotype-phenotype correlations of individual CNVs show that phenotype correlations differ from one locus to the next. Overall reciprocal deletions and duplications had divergent effects across diagnostic categories, as effect sizes for “developmental delay” (ASD and CLIN) risk are not allele-specific (deletions and duplication are positively correlated), whereas for SZ risk this is allele-specific (effect sizes for the deletion alleles are anticorrelated with effect sizes for the duplication). This means that SZ risk is not simply correlated with the overall cognitive impairment. We find significant evidence of genetic interactions of CNV genotype and polygenic load on case status. These results suggest that the modifying effects of polygenic risk (i.e., PRS-trait correlations) may differ between clinical/genetic subtypes. These interactions are further characterized by using dimensional phenotype data of UKBB. Our results suggest that specific CNV alleles have distinct psychiatric risk profiles and that such profiles may be attributable to function or expression of underlying genes in the brain. Our ongoing studies will test for enrichment of biological processes or spatial and temporal brain expression of genes within each cluster to better understand the biological mechanisms within the CNV groups. PRS contributed to the variable phenotypic expressivity in CNV carriers and we observed that PRS effects can differ by CNV genotype. In addition, we will expand the range of cognitive and neuropsychiatric traits through inclusion of additional disorders and disorder-related phenotypes. |
Conference AbstractsSarah McGaughey2022-07-21T16:30:07-04:00