Chromatin interactions and expression quantitative trait loci reveal genetic drivers of multimorbidities. Issue 1 (December 2018)

• Record Type: Journal Article
• Authors: Fadason, Tayaza; Schierding, William; Lumley, Thomas; O'Sullivan, Justin
• Is Part Of: Nature communications. Volume 9:Issue 1(2018)
• Page Start: 1
• Page End: 13
• Publication Date: 2018-12
• Subjects: Biology -- Periodicals; Physical sciences -- Periodicals; 505
• DOI: 10.1038/s41467-018-07692-y
• Languages: English
• ISSNs: 2041-1723

Abstract

Abstract Clinical studies of non-communicable diseases identify multimorbidities that suggest a common set of predisposing factors. Despite the fact that humans have ~24, 000 genes, we do not understand the genetic pathways that contribute to the development of multimorbid non-communicable disease. Here we create a multimorbidity atlas of traits based on pleiotropy of spatially regulated genes. Using chromatin interaction and expression Quantitative Trait Loci (eQTL) data, we analyse 20, 782 variants (p < 5 × 10−6 ) associated with 1351 phenotypes to identify 16, 248 putative spatial eQTL-eGene pairs that are involved in 76, 013 short- and long-range regulatory interactions (FDR < 0.05) in different human tissues. Convex biclustering of spatial eGenes that are shared among phenotypes identifies complex interrelationships between nominally different phenotype-associated SNPs. Our approach enables the simultaneous elucidation of variant interactions with target genes that are drivers of multimorbidity, and those that contribute to unique phenotype associated characteristics. Multimorbidities of common diseases often have shared underlying predisposing factors. Here Fadason et al. study the pleiotropy of SNPs and their effects on target genes by integrating chromatin interaction and expression quantitative trait loci data to identify target genes shared between phenotypes.