Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank.
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ABSTRACT:
SUBMITTER: Warland A
PROVIDER: S-EPMC7156345 | biostudies-literature | 2020 Apr
REPOSITORIES: biostudies-literature
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Schizophrenia-associated genomic copy number variants and subcortical brain volumes in the UK Biobank.
Warland Anthony A Kendall Kimberley M KM Rees Elliott E Kirov George G Caseras Xavier X
Molecular psychiatry 20190124 4
Schizophrenia is a highly heritable disorder for which anatomical brain alterations have been repeatedly reported in clinical samples. Unaffected at-risk groups have also been studied in an attempt to identify brain changes that do not reflect reverse causation or treatment effects. However, no robust associations have been observed between neuroanatomical phenotypes and known genetic risk factors for schizophrenia. We tested subcortical brain volume differences between 49 unaffected participant ...[more]
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Project description:ObjectivesCopy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs) including autism (ASD) and schizophrenia (SZ). Overall, little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, we investigated gross volume, and vertex level thickness and surface maps of subcortical structures in 11 different CNVs and 6 different NPDs.MethodsSubcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (at the following loci: 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2) and 782 controls (Male/Female: 727/730; age-range: 6-80 years) as well as ENIGMA summary-statistics for ASD, SZ, ADHD, Obsessive-Compulsive-Disorder, Bipolar-Disorder, and Major-Depression.ResultsNine of the 11 CNVs affected volume of at least one subcortical structure. The hippocampus and amygdala were affected by five CNVs. Effect sizes of CNVs on subcortical volume, thickness and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and SZ. Shape analyses were able to identify subregional alterations that were averaged out in volume analyses. We identified a common latent dimension - characterized by opposing effects on basal ganglia and limbic structures - across CNVs and across NPDs.ConclusionOur findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions. We also observed distinct effects with some CNVs clustering with adult conditions while others clustered with ASD. This large cross-CNV and NPDs analysis provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD, as well as why a single CNV increases the risk for a diverse set of NPDs.
| S-EPMC9980268 | biostudies-literature
Project description:ObjectiveCopy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs), including autism (ASD) and schizophrenia. Little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, the authors investigated gross volume, vertex-level thickness, and surface maps of subcortical structures in 11 CNVs and six NPDs.MethodsSubcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (CNVs at 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2; age range, 6-80 years; 340 males) and 782 control subjects (age range, 6-80 years; 387 males) as well as ENIGMA summary statistics for ASD, schizophrenia, attention deficit hyperactivity disorder, obsessive-compulsive disorder, bipolar disorder, and major depression.ResultsAll CNVs showed alterations in at least one subcortical measure. Each structure was affected by at least two CNVs, and the hippocampus and amygdala were affected by five. Shape analyses detected subregional alterations that were averaged out in volume analyses. A common latent dimension was identified, characterized by opposing effects on the hippocampus/amygdala and putamen/pallidum, across CNVs and across NPDs. Effect sizes of CNVs on subcortical volume, thickness, and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and schizophrenia.ConclusionsThe findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions, as well distinct effects, with some CNVs clustering with adult-onset conditions and others with ASD. These findings provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD and why a single CNV increases the risk for a diverse set of NPDs.
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Project description:BackgroundSchizophrenia is a highly heritable disorder with undetermined neurobiological causes. Understanding the impact on brain anatomy of carrying genetic risk for the disorder will contribute to uncovering its neurobiological underpinnings.AimsTo examine the effect of rare copy number variants (CNVs) associated with schizophrenia on brain cortical anatomy in a sample of unaffected participants from the UK Biobank.MethodWe used regression analyses to compare cortical thickness and surface area (total and across gyri) between 120 unaffected carriers of rare CNVs associated with schizophrenia and 16 670 participants without any pathogenic CNV. A measure of cortical thickness and surface area covariance across gyri was also compared between groups.ResultsCarrier status was associated with reduced surface area (β = -0.020 mm2, P < 0.001) and less robustly with increased cortical thickness (β = 0.015 mm, P = 0.035), and with increased covariance in thickness (carriers z = 0.31 v. non-carriers z = 0.22, P < 0.0005). Associations were mainly present in frontal and parietal areas and driven by a limited number of rare risk alleles included in our analyses (mainly 15q11.2 deletion for surface area and 16p13.11 duplication for thickness covariance).ConclusionsResults for surface area conformed with previous clinical findings, supporting surface area reductions as an indicator of genetic liability for schizophrenia. Results for cortical thickness, though, argued against its validity as a potential risk marker. Increased structural thickness covariance across gyri also appears related to risk for schizophrenia. The heterogeneity found across the effects of rare risk alleles suggests potential different neurobiological gateways into schizophrenia's phenotype.
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Project description:Research has shown differences in subcortical brain volumes between participants with schizophrenia and healthy controls. However, none of these differences have been found to associate with schizophrenia polygenic risk. Here, in a large sample (n = 14,701) of unaffected participants from the UK Biobank, we test whether schizophrenia polygenic risk scores (PRS) limited to specific gene-sets predict subcortical brain volumes. We compare associations with schizophrenia PRS at the whole genome level ('genomic', including all SNPs associated with the disorder at a p-value threshold < 0.05) with 'genic' PRS (based on SNPs in the vicinity of known genes), 'intergenic' PRS (based on the remaining SNPs), and genic PRS limited to SNPs within 7 gene-sets previously found to be enriched for genetic association with schizophrenia ('abnormal behaviour,' 'abnormal long-term potentiation,' 'abnormal nervous system electrophysiology,' 'FMRP targets,' '5HT2C channels,' 'CaV2 channels' and 'loss-of-function intolerant genes'). We observe a negative association between the 'abnormal behaviour' gene-set PRS and volume of the right thalamus that survived correction for multiple testing (ß = -0.031, pFDR = 0.005) and was robust to different schizophrenia PRS p-value thresholds. In contrast, the only association with genomic PRS surviving correction for multiple testing was for right pallidum, which was observed using a schizophrenia PRS p-value threshold < 0.01 (ß = -0.032, p = 0.0003, pFDR = 0.02), but not when using other PRS P-value thresholds. We conclude that schizophrenia PRS limited to functional gene sets may provide a better means of capturing differences in subcortical brain volume than whole genome PRS approaches.
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Project description:Large copy-number variants (CNVs) are strongly associated with both developmental delay and cancer, but the type of disease depends strongly on when and where the mutation occurred, i.e., germline versus somatic. We used microarray data from UK Biobank to investigate the prevalence and penetrance of large autosomal CNVs and chromosomal aneuploidies using a standard CNV detection algorithm not designed for detecting mosaic variants. We found 160 individuals that carry >10 Mb copy number changes, including 56 with whole chromosome aneuploidies. Nineteen (12%) individuals had a diagnosis of Down syndrome or other developmental disorder, while 84 (52.5%) individuals had a diagnosis of hematological malignancies or chronic myeloproliferative disorders. Notably, there was no evidence of mosaicism in the blood for many of these large CNVs, so they could easily be mistaken for germline alleles even when caused by somatic mutations. We therefore suggest that somatic mutations associated with blood cancers may result in false estimates of rare variant penetrance from population biobanks.
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Project description:Large-scale genomic studies have made major progress in identifying genetic risk variants for schizophrenia. A key finding from these studies is that there is an increased burden of genomic copy number variants (CNVs) in schizophrenia cases compared with controls. The mechanism through which these CNVs confer risk for the symptoms of schizophrenia, however, remains unclear. One possibility is that schizophrenia risk CNVs impact basic associative learning processes, abnormalities of which have long been associated with the disorder. To investigate whether genes in schizophrenia CNVs impact on specific phases of associative learning we combined human genetics with experimental gene expression studies in animals. In a sample of 11 917 schizophrenia cases and 16 416 controls, we investigated whether CNVs from patients with schizophrenia are enriched for genes expressed during the consolidation, retrieval or extinction of associative memories. We show that CNVs from cases are enriched for genes expressed during fear extinction in the hippocampus, but not genes expressed following consolidation or retrieval. These results suggest that CNVs act to impair inhibitory learning in schizophrenia, potentially contributing to the development of core symptoms of the disorder.
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Project description:Large rare copy number variants (CNVs) have been recognized as significant genetic risk factors for the development of schizophrenia (SCZ). However, due to their low frequency (1?150 to 1?1000) among patients, large sample sizes are needed to detect an association between specific CNVs and SCZ. So far, the majority of genome-wide CNV analyses have focused on reporting only CNVs that reached a significant P-value within the study cohort and merely confirmed the frequency of already-established risk-carrying CNVs. As a result, CNVs with a very low frequency that might be relevant for SCZ susceptibility are lost for secondary analyses. In this study, we provide a concise collection of high-quality CNVs in a large German sample consisting of 1,637 patients with SCZ or schizoaffective disorder and 1,627 controls. All individuals were genotyped on Illumina's BeadChips and putative CNVs were identified using QuantiSNP and PennCNV. Only those CNVs that were detected by both programs and spanned ?30 consecutive SNPs were included in the data collection and downstream analyses (2,366 CNVs, 0.73 CNVs per individual). The genome-wide analysis did not reveal a specific association between a previously unknown CNV and SCZ. However, the group of CNVs previously reported to be associated with SCZ was more frequent in our patients than in the controls. The publication of our dataset will serve as a unique, easily accessible, high-quality CNV data collection for other research groups. The dataset could be useful for the identification of new disease-relevant CNVs that are currently overlooked due to their very low frequency and lack of power for their detection in individual studies.
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