Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus

<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying susceptibility loci associated with polygenetic diseases such as type 2 diabetes mellitus (T2DM). However, it is still a daunting task to prio...

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Main Authors: Lyssenko Valeriya, Parikh Hemang, Groop Leif C
Format: Article
Language:English
Published: BMC 2009-12-01
Series:BMC Medical Genomics
Online Access:http://www.biomedcentral.com/1755-8794/2/72
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spelling doaj-e8dff97b52a542cbb65ffecd979e67a72021-04-02T07:57:39ZengBMCBMC Medical Genomics1755-87942009-12-01217210.1186/1755-8794-2-72Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitusLyssenko ValeriyaParikh HemangGroop Leif C<p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying susceptibility loci associated with polygenetic diseases such as type 2 diabetes mellitus (T2DM). However, it is still a daunting task to prioritize single nucleotide polymorphisms (SNPs) from GWAS for further replication in different population. Several recent studies have shown that genetic variation often affects gene-expression at proximal (<it>cis</it>) as well as distal (<it>trans</it>) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability.</p> <p>Methods</p> <p>To prioritize SNPs from GWAS, we combined results from two GWAS related to T2DM, the Diabetes Genetics Initiative (DGI) and the Wellcome Trust Case Control Consortium (WTCCC), with genome-wide expression data from pancreas, adipose tissue, liver and skeletal muscle of individuals with or without T2DM or animal models thereof to identify T2DM susceptibility loci.</p> <p>Results</p> <p>We identified 1,170 SNPs associated with T2DM with <it>P </it>< 0.05 in both GWAS and 243 genes that were located in the vicinity of these SNPs. Out of these 243 genes, we identified 115 differentially expressed in publicly available gene expression profiling data. Notably five of them, <it>IGF2BP2</it>, <it>KCNJ11</it>, <it>NOTCH2</it>, <it>TCF7L2 </it>and <it>TSPAN8</it>, have subsequently been shown to be associated with T2DM in different populations. To provide further validation of our approach, we reversed the approach and started with 26 known SNPs associated with T2DM and related traits. We could show that 12 (57%) (<it>HHEX</it>, <it>HNF1B</it>, <it>IGF2BP2</it>, <it>IRS1</it>, <it>KCNJ11</it>, <it>KCNQ1</it>, <it>NOTCH2</it>, <it>PPARG</it>, <it>TCF7L2</it>, <it>THADA</it>, <it>TSPAN8 </it>and <it>WFS1</it>) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies.</p> <p>Conclusions</p> <p>Utilizing of gene expression profiling data from different tissues of individuals with or without T2DM or animal models thereof is a powerful tool for prioritizing SNPs from WGAS for further replication studies.</p> http://www.biomedcentral.com/1755-8794/2/72
collection DOAJ
language English
format Article
sources DOAJ
author Lyssenko Valeriya
Parikh Hemang
Groop Leif C
spellingShingle Lyssenko Valeriya
Parikh Hemang
Groop Leif C
Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
BMC Medical Genomics
author_facet Lyssenko Valeriya
Parikh Hemang
Groop Leif C
author_sort Lyssenko Valeriya
title Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
title_short Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
title_full Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
title_fullStr Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
title_full_unstemmed Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
title_sort prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus
publisher BMC
series BMC Medical Genomics
issn 1755-8794
publishDate 2009-12-01
description <p>Abstract</p> <p>Background</p> <p>Genome-wide association studies (GWAS) have emerged as a powerful approach for identifying susceptibility loci associated with polygenetic diseases such as type 2 diabetes mellitus (T2DM). However, it is still a daunting task to prioritize single nucleotide polymorphisms (SNPs) from GWAS for further replication in different population. Several recent studies have shown that genetic variation often affects gene-expression at proximal (<it>cis</it>) as well as distal (<it>trans</it>) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability.</p> <p>Methods</p> <p>To prioritize SNPs from GWAS, we combined results from two GWAS related to T2DM, the Diabetes Genetics Initiative (DGI) and the Wellcome Trust Case Control Consortium (WTCCC), with genome-wide expression data from pancreas, adipose tissue, liver and skeletal muscle of individuals with or without T2DM or animal models thereof to identify T2DM susceptibility loci.</p> <p>Results</p> <p>We identified 1,170 SNPs associated with T2DM with <it>P </it>< 0.05 in both GWAS and 243 genes that were located in the vicinity of these SNPs. Out of these 243 genes, we identified 115 differentially expressed in publicly available gene expression profiling data. Notably five of them, <it>IGF2BP2</it>, <it>KCNJ11</it>, <it>NOTCH2</it>, <it>TCF7L2 </it>and <it>TSPAN8</it>, have subsequently been shown to be associated with T2DM in different populations. To provide further validation of our approach, we reversed the approach and started with 26 known SNPs associated with T2DM and related traits. We could show that 12 (57%) (<it>HHEX</it>, <it>HNF1B</it>, <it>IGF2BP2</it>, <it>IRS1</it>, <it>KCNJ11</it>, <it>KCNQ1</it>, <it>NOTCH2</it>, <it>PPARG</it>, <it>TCF7L2</it>, <it>THADA</it>, <it>TSPAN8 </it>and <it>WFS1</it>) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies.</p> <p>Conclusions</p> <p>Utilizing of gene expression profiling data from different tissues of individuals with or without T2DM or animal models thereof is a powerful tool for prioritizing SNPs from WGAS for further replication studies.</p>
url http://www.biomedcentral.com/1755-8794/2/72
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