Fine mapping spatiotemporal mechanisms of genetic variants underlying cardiac traits and disease

The causal variants and genes underlying thousands of cardiac GWAS signals have yet to be identified. Here, we leverage spatiotemporal information on 966 RNA-seq cardiac samples and perform an expression quantitative trait locus (eQTL) analysis detecting eQTLs considering both eGenes and eIsoforms. We identify 2,578 eQTLs associated with a specific developmental stage-, tissue- and/or cell type. Colocalization between eQTL and GWAS signals of five cardiac traits identified variants with high posterior probabilities for being causal in 210 GWAS loci. Pulse pressure GWAS loci are enriched for colocalization with fetal- and smooth muscle- eQTLs; pulse rate with adult- and cardiac muscle- eQTLs; and atrial fibrillation with cardiac muscle- eQTLs. Fine mapping identifies 79 credible sets with five or fewer SNPs, of which 15 were associated with spatiotemporal eQTLs. Our study shows that many cardiac GWAS variants impact traits and disease in a developmental stage-, tissue- and/or cell type-specific fashion. The mechanisms underlying many genetic variants associated with human traits are often unknown. Here, the authors identify the developmental stage-, organ-, tissue- and cell type-specific associations between genetic variation and gene expression in cardiac tissues, and describe how these associations affect complex cardiac traits and disease.

Automated summary

This study identifies 2,578 eQTLs associated with specific developmental stages, tissues, and cell types using spatiotemporal information of 966 RNA-seq cardiac samples. The colocalization between eQTLs and GWAS signals reveals the impact of genetic variants on cardiac traits and diseases. These findings shed light on the specific effects of cardiac GWAS variants on developmental stages, tissues, and cell types.