利用与 2 型糖尿病相关组织中的基因表达信息,对全基因组关联研究中的基因进行后续研究的优先级排序。

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

机构信息

Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, University Hospital Malmö, Malmö, Sweden.

出版信息

BMC Med Genomics. 2009 Dec 31;2:72. doi: 10.1186/1755-8794-2-72.

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 < 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.

摘要

背景

全基因组关联研究(GWAS)已成为鉴定与多基因疾病(如 2 型糖尿病(T2DM))相关的易感基因座的强大方法。然而,在不同人群中进一步复制 GWAS 中的单核苷酸多态性(SNP)仍然是一项艰巨的任务。最近的几项研究表明,遗传变异通常通过不同的机制影响近端(顺式)和远端(反式)基因组位置的基因表达,例如改变转录或剪接或转录本稳定性的速率。

方法

为了优先考虑 GWAS 中的 SNP,我们将与 T2DM 相关的两项 GWAS(糖尿病遗传学倡议(DGI)和惠康信托基金病例对照联合会(WTCCC))的结果与来自有或没有 T2DM 或动物模型的个体的胰腺、脂肪组织、肝脏和骨骼肌的全基因组表达数据相结合,以确定 T2DM 易感性基因座。

结果

我们在两项 GWAS 中都发现了 1170 个与 T2DM 相关的 SNP,P < 0.05,并且这些 SNP 附近还存在 243 个基因。在这 243 个基因中,我们在公开的基因表达谱数据中鉴定出 115 个差异表达的基因。值得注意的是,其中五个基因,IGF2BP2、KCNJ11、NOTCH2、TCF7L2 和 TSPAN8,随后在不同人群中被证明与 T2DM 相关。为了进一步验证我们的方法,我们采用了相反的方法,从 26 个与 T2DM 及相关特征相关的已知 SNP 开始。我们可以证明,在 21 个位于这些 SNP 附近的基因中,有 12 个(57%)(HHEX、HNF1B、IGF2BP2、IRS1、KCNJ11、KCNQ1、NOTCH2、PPARG、TCF7L2、THADA、TSPAN8 和 WFS1)在 T2DM 基因表达谱研究中表现出异常表达。

结论

利用来自有或没有 T2DM 或动物模型的个体的不同组织的基因表达谱数据是优先考虑 GWAS 中 SNP 以进行进一步复制研究的有力工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f39f/2815699/fd1cb1a50a5d/1755-8794-2-72-1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索