Advanced

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

Parikh, Hemang LU ; Lyssenko, Valeriya LU and Groop, Leif LU (2009) In BMC Medical Genomics 2.
Abstract
Background: 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 (cis) as well as distal (trans) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability. Methods: To prioritize SNPs from GWAS, we combined results from two GWAS related to T2DM, the Diabetes Genetics Initiative (DGI) and the Wellcome... (More)
Background: 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 (cis) as well as distal (trans) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability. Methods: 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. Results: We identified 1,170 SNPs associated with T2DM with P < 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, IGF2BP2, KCNJ11, NOTCH2, TCF7L2 and TSPAN8, 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%) (HHEX, HNF1B, IGF2BP2, IRS1, KCNJ11, KCNQ1, NOTCH2, PPARG, TCF7L2, THADA, TSPAN8 and WFS1) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies. Conclusions: 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. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
BMC Medical Genomics
volume
2
publisher
BioMed Central
external identifiers
  • wos:000274302300001
  • scopus:76749084749
ISSN
1755-8794
DOI
10.1186/1755-8794-2-72
language
English
LU publication?
yes
id
e00855d4-d90b-4490-abc5-7d2af9ca06ff (old id 1568018)
date added to LUP
2010-03-24 11:33:18
date last changed
2017-01-01 05:34:51
@article{e00855d4-d90b-4490-abc5-7d2af9ca06ff,
  abstract     = {Background: 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 (cis) as well as distal (trans) genomic locations by different mechanisms such as altering rate of transcription or splicing or transcript stability. Methods: 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. Results: We identified 1,170 SNPs associated with T2DM with P &lt; 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, IGF2BP2, KCNJ11, NOTCH2, TCF7L2 and TSPAN8, 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%) (HHEX, HNF1B, IGF2BP2, IRS1, KCNJ11, KCNQ1, NOTCH2, PPARG, TCF7L2, THADA, TSPAN8 and WFS1) out of 21 genes located in vicinity of these SNPs were showing aberrant expression in T2DM from the gene expression profiling studies. Conclusions: 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.},
  author       = {Parikh, Hemang and Lyssenko, Valeriya and Groop, Leif},
  issn         = {1755-8794},
  language     = {eng},
  publisher    = {BioMed Central},
  series       = {BMC Medical Genomics},
  title        = {Prioritizing genes for follow-up from genome wide association studies using information on gene expression in tissues relevant for type 2 diabetes mellitus},
  url          = {http://dx.doi.org/10.1186/1755-8794-2-72},
  volume       = {2},
  year         = {2009},
}