Estimating the causal tissues for complex traits and diseases

GTEx Consortium; Halit Ongen; Andrew A Brown; Olivier Delaneau; Nikolaos I Panousis; Alexandra C Nica; Emmanouil T Dermitzakis

doi:10.1038/ng.3981

Estimating the causal tissues for complex traits and diseases

GTEx Consortium, Halit Ongen (Lead / Corresponding author), Andrew A Brown, Olivier Delaneau, Nikolaos I Panousis, Alexandra C Nica, Emmanouil T Dermitzakis (Lead / Corresponding author)

Population Health and Genomics

Research output: Contribution to journal › Article › peer-review

122 Citations (Scopus)

Abstract

How to interpret the biological causes underlying 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 analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.

Original language	English
Pages (from-to)	1676-1683
Number of pages	8
Journal	Nature Genetics
Volume	49
Issue number	12
DOIs	https://doi.org/10.1038/ng.3981
Publication status	Published - 23 Oct 2017

Keywords

Gene Expression Profiling
Genetic Association Studies
Genetic Predisposition to Disease/genetics
Genome-Wide Association Study
Genotype
Humans
Organ Specificity/genetics
Phenotype
Polymorphism, Single Nucleotide
Quantitative Trait Loci/genetics

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10.1038/ng.3981

Brown, Andrew
- Population Health and Genomics - Principal Investigator (Tenure Track)
Person: Academic

Cite this

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title = "Estimating the causal tissues for complex traits and diseases",

abstract = "How to interpret the biological causes underlying 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 analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.",

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AU - GTEx Consortium

AU - Ongen, Halit

AU - Brown, Andrew A

AU - Delaneau, Olivier

AU - Panousis, Nikolaos I

AU - Nica, Alexandra C

AU - Dermitzakis, Emmanouil T

PY - 2017/10/23

Y1 - 2017/10/23

N2 - How to interpret the biological causes underlying 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 analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.

AB - How to interpret the biological causes underlying 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 analysis of expression quantitative trait loci (eQTLs). Here we describe a new approach to estimate the tissues behind the genetic causality of a variety of GWAS traits, using the cis-eQTLs in 44 tissues from the Genotype-Tissue Expression (GTEx) Consortium. We have adapted the regulatory trait concordance (RTC) score to measure the probability of eQTLs being active in multiple tissues and to calculate the probability that a GWAS-associated variant and an eQTL tag the same functional effect. By normalizing the GWAS-eQTL probabilities by the tissue-sharing estimates for eQTLs, we generate relative tissue-causality profiles for GWAS traits. Our approach not only implicates the gene likely mediating individual GWAS signals, but also highlights tissues where the genetic causality for an individual trait is likely manifested.

KW - Gene Expression Profiling

KW - Genetic Association Studies

KW - Genetic Predisposition to Disease/genetics

KW - Genome-Wide Association Study

KW - Genotype

KW - Humans

KW - Organ Specificity/genetics

KW - Phenotype

KW - Polymorphism, Single Nucleotide

KW - Quantitative Trait Loci/genetics

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DO - 10.1038/ng.3981

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VL - 49

SP - 1676

EP - 1683

JO - Nature Genetics

JF - Nature Genetics

IS - 12

ER -

Estimating the causal tissues for complex traits and diseases

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Keywords

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Brown, Andrew

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