Cargando…

Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases

The genes and cells that mediate genetic associations identified through genome-wide association studies (GWAS) are only partially understood. Several studies that have investigated the genetic regulation of gene expression have shown that disease-associated variants are over-represented amongst exp...

Descripción completa

Detalles Bibliográficos
Autores principales: Guo, Hui, Fortune, Mary D., Burren, Oliver S., Schofield, Ellen, Todd, John A., Wallace, Chris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4498151/
https://www.ncbi.nlm.nih.gov/pubmed/25743184
http://dx.doi.org/10.1093/hmg/ddv077
_version_ 1782380578264317952
author Guo, Hui
Fortune, Mary D.
Burren, Oliver S.
Schofield, Ellen
Todd, John A.
Wallace, Chris
author_facet Guo, Hui
Fortune, Mary D.
Burren, Oliver S.
Schofield, Ellen
Todd, John A.
Wallace, Chris
author_sort Guo, Hui
collection PubMed
description The genes and cells that mediate genetic associations identified through genome-wide association studies (GWAS) are only partially understood. Several studies that have investigated the genetic regulation of gene expression have shown that disease-associated variants are over-represented amongst expression quantitative trait loci (eQTL) variants. Evidence for colocalisation of eQTL and disease causal variants can suggest causal genes and cells for these genetic associations. Here, we used colocalisation analysis to investigate whether 595 genetic associations to ten immune-mediated diseases are consistent with a causal variant that regulates, in cis, gene expression in resting B cells, and in resting and stimulated monocytes. Previously published candidate causal genes were over-represented amongst genes exhibiting colocalisation (odds ratio > 1.5), and we identified evidence for colocalisation (posterior odds > 5) between cis eQTLs in at least one cell type and at least one disease for six genes: ADAM15, RGS1, CARD9, LTBR, CTSH and SYNGR1. We identified cell-specific effects, such as for CTSH, the expression of which in monocytes, but not in B cells, may mediate type 1 diabetes and narcolepsy associations in the chromosome 15q25.1 region. Our results demonstrate the utility of integrating genetic studies of disease and gene expression for highlighting causal genes and cell types.
format Online
Article
Text
id pubmed-4498151
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-44981512015-07-15 Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases Guo, Hui Fortune, Mary D. Burren, Oliver S. Schofield, Ellen Todd, John A. Wallace, Chris Hum Mol Genet Articles The genes and cells that mediate genetic associations identified through genome-wide association studies (GWAS) are only partially understood. Several studies that have investigated the genetic regulation of gene expression have shown that disease-associated variants are over-represented amongst expression quantitative trait loci (eQTL) variants. Evidence for colocalisation of eQTL and disease causal variants can suggest causal genes and cells for these genetic associations. Here, we used colocalisation analysis to investigate whether 595 genetic associations to ten immune-mediated diseases are consistent with a causal variant that regulates, in cis, gene expression in resting B cells, and in resting and stimulated monocytes. Previously published candidate causal genes were over-represented amongst genes exhibiting colocalisation (odds ratio > 1.5), and we identified evidence for colocalisation (posterior odds > 5) between cis eQTLs in at least one cell type and at least one disease for six genes: ADAM15, RGS1, CARD9, LTBR, CTSH and SYNGR1. We identified cell-specific effects, such as for CTSH, the expression of which in monocytes, but not in B cells, may mediate type 1 diabetes and narcolepsy associations in the chromosome 15q25.1 region. Our results demonstrate the utility of integrating genetic studies of disease and gene expression for highlighting causal genes and cell types. Oxford University Press 2015-06-15 2015-03-05 /pmc/articles/PMC4498151/ /pubmed/25743184 http://dx.doi.org/10.1093/hmg/ddv077 Text en © The Author 2015. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Guo, Hui
Fortune, Mary D.
Burren, Oliver S.
Schofield, Ellen
Todd, John A.
Wallace, Chris
Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
title Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
title_full Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
title_fullStr Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
title_full_unstemmed Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
title_short Integration of disease association and eQTL data using a Bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
title_sort integration of disease association and eqtl data using a bayesian colocalisation approach highlights six candidate causal genes in immune-mediated diseases
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4498151/
https://www.ncbi.nlm.nih.gov/pubmed/25743184
http://dx.doi.org/10.1093/hmg/ddv077
work_keys_str_mv AT guohui integrationofdiseaseassociationandeqtldatausingabayesiancolocalisationapproachhighlightssixcandidatecausalgenesinimmunemediateddiseases
AT fortunemaryd integrationofdiseaseassociationandeqtldatausingabayesiancolocalisationapproachhighlightssixcandidatecausalgenesinimmunemediateddiseases
AT burrenolivers integrationofdiseaseassociationandeqtldatausingabayesiancolocalisationapproachhighlightssixcandidatecausalgenesinimmunemediateddiseases
AT schofieldellen integrationofdiseaseassociationandeqtldatausingabayesiancolocalisationapproachhighlightssixcandidatecausalgenesinimmunemediateddiseases
AT toddjohna integrationofdiseaseassociationandeqtldatausingabayesiancolocalisationapproachhighlightssixcandidatecausalgenesinimmunemediateddiseases
AT wallacechris integrationofdiseaseassociationandeqtldatausingabayesiancolocalisationapproachhighlightssixcandidatecausalgenesinimmunemediateddiseases