Identification of genetic loci jointly influencing coronary artery disease risk and sleep traits of insomnia, sleep duration, and chronotype.

SLEEP MEDICINE(2020)

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摘要
Background: Accumulating evidence suggests a relationship between coronary artery disease (CAD) and sleep problems. Our study is aimed to investigate the shared genetic loci underlying this phenotypic association. Methods: Combining summary statistics from different genome-wide association studies, we investigated overlap in single-nucleotide polymorphisms (SNPs) associated with CAD and sleep traits (insomnia symptoms, sleep duration, and chronotype) using conditional/conjunctional false discovery rate (condFDR/conjFDR) approach. Relevant variants are further evaluated for differential expression analysis, expression quantitative trait locus (eQTL) functionality, and gene ontology (GO) enrichment analysis. Results: We observed substantial genetic enrichment in CAD condition on associations with sleep traits, which indicating polygenic overlap. Using conjFDR analysis, 26 loci jointly influencing CAD and sleep traits were identified. One locus was shared between CAD and sleep duration and represented the strongest shared signal detected (closest gene, MSL2; chromosome 3q22.3; conjFDR = 1.77 x 10(-4)). A consistent direction of allelic effect was observed between CAD and insomnia symptoms, while bidirectional effects were recognized between CAD, sleep duration, and chronotype. Replicable eQTL functionality was further identified for two loci: rs28398825 for FCHO1 in the frontal cortex and blood tissue, and rs8072451 for LRRC37A and its duplicate LRRC37A2 in several brain regions and blood tissue. GO analysis of the loci shared between CAD and sleep traits implicated cellular component related to synapse. Conclusions: Our findings provide new insight into the relationship between CAD and sleep traits. The mechanisms underlying these associations warrant further investigation. (C) 2020 Elsevier B.V. All rights reserved.
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关键词
Coronary artery disease,Sleep,Genetic pleiotropy,Genome-wide association study
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