Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Alvaro N. Barbeira, Scott P. Dickinson, Jason M. Torres, Jiamao Zheng, Eric S. Torstenson, Heather E. Wheeler, Kaanan P. Shah, Rodrigo Bonazzola, Tzintzuni Garcia, Todd Edwards, GTEx Consortium, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im
doi: https://doi.org/10.1101/045260
Alvaro N. Barbeira
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Scott P. Dickinson
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jason M. Torres
2Committee on Molecular Metabolism and Nutrition, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jiamao Zheng
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Eric S. Torstenson
3Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Heather E. Wheeler
4Departments of Biology and Computer Science, Loyola University Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kaanan P. Shah
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Rodrigo Bonazzola
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tzintzuni Garcia
5Center for Research Informatics, The University of Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Todd Edwards
3Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dan L. Nicolae
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nancy J. Cox
3Vanderbilt Genetic Institute, Vanderbilt University Medical Center, Nashville, TN, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Hae Kyung Im
1Section of Genetic Medicine, The University of Chicago, Chicago, IL, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: haky@uchicago.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Scalable, integrative methods to understand mechanisms that link genetic variants with phenotypes are needed. Here we derive a mathematical expression to compute PrediXcan (a gene mapping approach) results using summary data (S-PrediXcan) and show its accuracy and general robustness to misspecified reference sets. We apply this framework to 44 GTEx tissues and 100+ phenotypes from GWAS and meta-analysis studies, creating a growing public catalog of associations that seeks to capture the effects of gene expression variation on human phenotypes. Replication in an independent cohort is shown. Most of the associations were tissue specific, suggesting context specificity of the trait etiology. Colocalized significant associations in unexpected tissues underscore the need for an agnostic scanning of multiple contexts to improve our ability to detect causal regulatory mechanisms. Monogenic disease genes are enriched among significant associations for related traits, suggesting that smaller alterations of these genes may cause a spectrum of milder phenotypes.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted October 03, 2017.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics
Alvaro N. Barbeira, Scott P. Dickinson, Jason M. Torres, Jiamao Zheng, Eric S. Torstenson, Heather E. Wheeler, Kaanan P. Shah, Rodrigo Bonazzola, Tzintzuni Garcia, Todd Edwards, GTEx Consortium, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im
bioRxiv 045260; doi: https://doi.org/10.1101/045260
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics
Alvaro N. Barbeira, Scott P. Dickinson, Jason M. Torres, Jiamao Zheng, Eric S. Torstenson, Heather E. Wheeler, Kaanan P. Shah, Rodrigo Bonazzola, Tzintzuni Garcia, Todd Edwards, GTEx Consortium, Dan L. Nicolae, Nancy J. Cox, Hae Kyung Im
bioRxiv 045260; doi: https://doi.org/10.1101/045260

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Genomics
  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4382)
  • Biochemistry (9591)
  • Bioengineering (7090)
  • Bioinformatics (24857)
  • Biophysics (12600)
  • Cancer Biology (9956)
  • Cell Biology (14349)
  • Clinical Trials (138)
  • Developmental Biology (7948)
  • Ecology (12105)
  • Epidemiology (2067)
  • Evolutionary Biology (15988)
  • Genetics (10925)
  • Genomics (14738)
  • Immunology (9869)
  • Microbiology (23660)
  • Molecular Biology (9484)
  • Neuroscience (50860)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2682)
  • Physiology (4013)
  • Plant Biology (8657)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2394)
  • Systems Biology (6433)
  • Zoology (1346)