Leveraging molecular quantitative trait loci to understand the genetic architecture of diseases and complex traits.

Nat Genet
Authors
Keywords
Abstract

There is increasing evidence that many risk loci found using genome-wide association studies are molecular quantitative trait loci (QTLs). Here we introduce a new set of functional annotations based on causal posterior probabilities of fine-mapped molecular cis-QTLs, using data from the Genotype-Tissue Expression (GTEx) and BLUEPRINT consortia. We show that these annotations are more strongly enriched for heritability (5.84× for eQTLs; P = 1.19 × 10) across 41 diseases and complex traits than annotations containing all significant molecular QTLs (1.80× for expression (e)QTLs). eQTL annotations obtained by meta-analyzing all GTEx tissues generally performed best, whereas tissue-specific eQTL annotations produced stronger enrichments for blood- and brain-related diseases and traits. eQTL annotations restricted to loss-of-function intolerant genes were even more enriched for heritability (17.06×; P = 1.20 × 10). All molecular QTLs except splicing QTLs remained significantly enriched in joint analysis, indicating that each of these annotations is uniquely informative for disease and complex trait architectures.

Year of Publication
2018
Journal
Nat Genet
Volume
50
Issue
7
Pages
1041-1047
Date Published
2018 07
ISSN
1546-1718
DOI
10.1038/s41588-018-0148-2
PubMed ID
29942083
PubMed Central ID
PMC6030458
Links
Grant list
R01 MH101782 / MH / NIMH NIH HHS / United States
T32 GM007753 / GM / NIGMS NIH HHS / United States
T32 DK110919 / DK / NIDDK NIH HHS / United States
U01 HG009379 / HG / NHGRI NIH HHS / United States
R01 MH101244 / MH / NIMH NIH HHS / United States
R01 MH109978 / MH / NIMH NIH HHS / United States
F32 HG009987 / HG / NHGRI NIH HHS / United States
R01 MH107649 / MH / NIMH NIH HHS / United States