Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits

Pavlides, Jennifer M. Whitehead, Zhu, Zhihong, Gratten, Jacob, Mcrae, Allan F., Wray, Naomi R. and Yang, Jian (2016) Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits. Genome Medicine, 8 1: . doi:10.1186/s13073-016-0338-4


Author Pavlides, Jennifer M. Whitehead
Zhu, Zhihong
Gratten, Jacob
Mcrae, Allan F.
Wray, Naomi R.
Yang, Jian
Title Predicting gene targets from integrative analyses of summary data from GWAS and eQTL studies for 28 human complex traits
Journal name Genome Medicine   Check publisher's open access policy
ISSN 1756-994X
Publication date 2016-08-01
Sub-type Article (original research)
DOI 10.1186/s13073-016-0338-4
Open Access Status DOI
Volume 8
Issue 1
Total pages 6
Place of publication London, United Kingdom
Publisher BioMed Central
Language eng
Abstract Genome-wide association studies (GWAS) have identified hundreds of genetic variants associated with complex traits and diseases. However, elucidating the causal genes underlying GWAS hits remains challenging. We applied the summary data-based Mendelian randomization (SMR) method to 28 GWAS summary datasets to identify genes whose expression levels were associated with traits and diseases due to pleiotropy or causality (the expression level of a gene and the trait are affected by the same causal variant at a locus). We identified 71 genes, of which 17 are novel associations (no GWAS hit within 1 Mb distance of the genes). We integrated all the results in an online database (http://www.cnsgenomics/shiny/SMRdb/), providing important resources to prioritize genes for further follow-up, for example in functional studies.
Keyword Genome-wide association studies (GWAS)
Expression quantitative trait loci (eQTL)
Summary data-based Mendelian randomization (SMR)
Complex traits
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: HERDC Pre-Audit
Queensland Brain Institute Publications
Institute for Molecular Bioscience - Publications
 
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