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Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants.

ABSTRACT: Genome-wide association studies (GWAS) have found widespread evidence of pleiotropy, but characterization of global patterns of pleiotropy remain highly incomplete due to insufficient power of current approaches. We develop fastASSET, a method that allows efficient detection of variant-level pleiotropic association across many traits. We analyze GWAS summary statistics of 116 complex traits of diverse types collected from the GRASP repository and large GWAS Consortia. We identify 2293 independent loci and find that the lead variants in nearly all these loci (~99%) to be associated with ≥2 traits (median = 6). We observe that degree of pleiotropy estimated from our study predicts that observed in the UK Biobank for a much larger number of traits (K = 4114) (correlation = 0.43, p-value <2.2×10-16 ). Follow-up analyzes of 21 trait-specific variants indicate their link to the expression in trait-related tissues for a small number of genes involved in relevant biological processes. Our findings provide deeper insight into the nature of pleiotropy and leads to identification of highly trait-specific susceptibility variants.

SUBMITTER: Qi G

PROVIDER: S-EPMC11324957 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature

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Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants.

Qi Guanghao G Chhetri Surya B SB Ray Debashree D Dutta Diptavo D Battle Alexis A Bhattacharjee Samsiddhi S Chatterjee Nilanjan N

Nature communications 20240814 1

Genome-wide association studies (GWAS) have found widespread evidence of pleiotropy, but characterization of global patterns of pleiotropy remain highly incomplete due to insufficient power of current approaches. We develop fastASSET, a method that allows efficient detection of variant-level pleiotropic association across many traits. We analyze GWAS summary statistics of 116 complex traits of diverse types collected from the GRASP repository and large GWAS Consortia. We identify 2293 independen ...[more]

PMID: 39143063

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Project description:IntroductionObservational studies have reported that patients with Alzheimer's disease (AD) have a greater burden of comorbidities typically associated with stress-related psychiatric disorders. However, the contribution of hereditary factors to this comorbidity remains unclear. We evaluated phenotypic associations using observational data from the UK Biobank.MethodOur study focused on investigating the shared risk variants and genetic etiology underlying AD and three stress-related psychiatric disorders: post-traumatic stress disorder, anxiety disorder, and major depressive disorder. By leveraging summary statistics from genome-wide association studies, we investigated global genetic correlations using linkage disequilibrium score regression, genetic covariance analysis, and high-definition likelihood. Genome-wide cross-trait analysis with association analysis based on subsets and cross-phenotype association were performed to discover genome-wide significant risk variants shared between AD and the three stress-related psychiatric disorders.ResultsA significant positive genetic correlation was observed between AD and major depressive disorder using linkage disequilibrium score regression (rg = 0.231; P = 0.018), genetic covariance analysis (rg = 0.138; P < 0.001), and high-definition likelihood (rg = 0.188; P < 0.001). Association analysis based on subsets and cross-phenotype association revealed thirteen risk variants in six genes shared between AD and post-traumatic stress disorder; seven risk variants in four genes shared between AD and anxiety disorder; and 23 risk variants in four genes shared between AD and major depressive disorder. Functional annotation and gene-set enrichment analysis indicated that 12 genes for comorbidity shared between patients with AD and all three stress-related psychiatric disorders were enriched in the spleen, pancreas, and whole blood.ConclusionThese results advance our knowledge of the shared genetic origins of comorbidities and pave the way for advancements in the diagnosis, management, and prevention of stress-related AD.

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Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants.

Publications

Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants.

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