Rxivist logo

Estimating the causal tissues for complex traits and diseases

By Halit Ongen, Andrew A Brown, O. Delaneau, Nikolaos Panousis, Alexandra C Nica, GTEx Consortium, Emmanouil T. Dermitzakis

Posted 11 Sep 2016
bioRxiv DOI: 10.1101/074682 (published DOI: 10.1038/ng.3981)

Interpretation of biological causes of the predisposing markers identified through Genome Wide Association Studies (GWAS) remains an open question. One direct and powerful way to assess the genetic causality behind GWAS is through expression quantitative trait loci (eQTLs). Here we describe a novel approach to estimate the tissues giving rise to the genetic causality behind a wide variety of GWAS traits, using the cis-eQTLs identified in 44 tissues of the GTEx consortium. We have adapted the Regulatory Trait Concordance (RTC) score, to on the one hand measure the tissue sharing probabilities of eQTLs, and also to calculate the probability that a GWAS and an eQTL variant tag the same underlying functional effect. We show that our tissue sharing estimates significantly correlate with commonly used estimates of tissue sharing. By normalizing the GWAS-eQTL probabilities with the tissue sharing estimates of the eQTLs, we can estimate the tissues from which GWAS genetic causality arises. Our approach not only indicates the gene mediating individual GWAS signals, but also can highlight tissues where the genetic causality for an individual trait is manifested.

Download data

  • Downloaded 1,563 times
  • Download rankings, all-time:
    • Site-wide: 5,695 out of 92,411
    • In genetics: 414 out of 4,738
  • Year to date:
    • Site-wide: 68,767 out of 92,411
  • Since beginning of last month:
    • Site-wide: 48,756 out of 92,411

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News