PT  - JOURNAL ARTICLE
AU  - Farhad Hormozdiari
AU  - Steven Gazal
AU  - Bryce van de Geijn
AU  - Hilary Finucane
AU  - Chelsea J.-T. Ju
AU  - Po-Ru Loh
AU  - Armin Schoech
AU  - Yakir Reshef
AU  - Xuanyao Liu
AU  - Luke O’Connor
AU  - Alexander Gusev
AU  - Eleazar Eskin
AU  - Alkes L. Price
TI  - Leveraging molecular QTL to understand the genetic architecture of diseases and complex traits
AID  - 10.1101/203380
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 203380
4099  - http://biorxiv.org/content/early/2017/10/15/203380.short
4100  - http://biorxiv.org/content/early/2017/10/15/203380.full
AB  - There is increasing evidence that many GWAS risk loci are molecular QTL for gene ex-pression (eQTL), histone modification (hQTL), splicing (sQTL), and/or DNA methylation (meQTL). Here, we introduce a new set of functional annotations based on causal posterior prob-abilities (CPP) of fine-mapped molecular cis-QTL, using data from the GTEx and BLUEPRINT consortia. We show that these annotations are very strongly enriched for disease heritability across 41 independent diseases and complex traits (average N = 320K): 5.84x for GTEx eQTL, and 5.44x for eQTL, 4.27-4.28x for hQTL (H3K27ac and H3K4me1), 3.61x for sQTL and 2.81x for meQTL in BLUEPRINT (all P ≤ 1.39e-10), far higher than enrichments obtained using stan-dard functional annotations that include all significant molecular cis-QTL (1.17-1.80x). eQTL annotations that were obtained by meta-analyzing all 44 GTEx tissues generally performed best, but tissue-specific blood eQTL annotations produced stronger enrichments for autoimmune dis-eases and blood cell traits and tissue-specific brain eQTL annotations produced stronger enrich-ments for brain-related diseases and traits, despite high cis-genetic correlations of eQTL effect sizes across tissues. Notably, eQTL annotations restricted to loss-of-function intolerant genes from ExAC were even more strongly enriched for disease heritability (17.09x; vs. 5.84x for all genes; P = 4.90e-17 for difference). All molecular QTL except sQTL remained significantly enriched for disease heritability in a joint analysis conditioned on each other and on a broad set of functional annotations from previous studies, implying that each of these annotations is uniquely informative for disease and complex trait architectures.