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