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本文引用的文献

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Gene-environment interactions in genome-wide association studies: a comparative study of tests applied to empirical studies of type 2 diabetes.全基因组关联研究中的基因-环境相互作用:应用于 2 型糖尿病实证研究的检验方法的比较研究。
Am J Epidemiol. 2012 Feb 1;175(3):191-202. doi: 10.1093/aje/kwr368. Epub 2011 Dec 22.
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A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort.对病态肥胖队列的胃、肝和脂肪组织基因表达的遗传学调查。
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3
Transcription factor 7-like 2 (TCF7L2) polymorphism and context-specific risk of impaired fasting glucose in African American and Caucasian adults: the atherosclerosis risk in communities (ARIC) study.转录因子 7 样 2(TCF7L2)多态性与非裔美国人和白种成年人空腹血糖受损的特定环境风险:社区动脉粥样硬化风险(ARIC)研究。
Diabetes Metab Res Rev. 2010 Jul;26(5):371-7. doi: 10.1002/dmrr.1087.
4
Powerful SNP-set analysis for case-control genome-wide association studies.基于全基因组关联研究的病例对照 SNP 集分析。
Am J Hum Genet. 2010 Jun 11;86(6):929-42. doi: 10.1016/j.ajhg.2010.05.002.
5
Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes.与肝脏和脂肪表达相关的单核苷酸多态性与 2 型糖尿病的相关性富集。
PLoS Genet. 2010 May 6;6(5):e1000932. doi: 10.1371/journal.pgen.1000932.
6
Genetic variants at 2q24 are associated with susceptibility to type 2 diabetes.2q24 上的遗传变异与 2 型糖尿病易感性相关。
Hum Mol Genet. 2010 Jul 1;19(13):2706-15. doi: 10.1093/hmg/ddq156. Epub 2010 Apr 23.
7
Integrating pathway analysis and genetics of gene expression for genome-wide association studies.整合通路分析和基因表达的遗传学用于全基因组关联研究。
Am J Hum Genet. 2010 Apr 9;86(4):581-91. doi: 10.1016/j.ajhg.2010.02.020. Epub 2010 Mar 25.
8
ProbABEL package for genome-wide association analysis of imputed data.ProbABEL 软件包可用于分析基于孟德尔随机化的全基因组关联研究数据。
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Genotype imputation.基因型推算
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10
Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions.识别基因组疾病区域之间的关系:预测致病性单核苷酸多态性关联和罕见缺失中的基因。
PLoS Genet. 2009 Jun;5(6):e1000534. doi: 10.1371/journal.pgen.1000534. Epub 2009 Jun 26.

整合遗传关联、基因表达遗传学和单核苷酸多态性集分析,以鉴定 2 型糖尿病易感性基因座。

Integrating genetic association, genetics of gene expression, and single nucleotide polymorphism set analysis to identify susceptibility Loci for type 2 diabetes mellitus.

机构信息

Department of Genetics, Merck Research Laboratories, Pasteur, Boston, MA 02115, USA.

出版信息

Am J Epidemiol. 2012 Sep 1;176(5):423-30. doi: 10.1093/aje/kws123. Epub 2012 Aug 2.

DOI:10.1093/aje/kws123
PMID:22865700
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3499116/
Abstract

Large-scale genome-wide association studies (GWAS) have identified over 40 genomic regions significantly associated with type 2 diabetes mellitus. However, GWAS results are not always straightforward to interpret, and linking these loci to meaningful disease etiology is often difficult without extensive follow-up studies. The authors expanded on previously reported type 2 diabetes mellitus GWAS from the nested case-control studies of 2 prospective US cohorts by incorporating expression single nucleotide polymorphism (SNP) information and applying SNP set enrichment analysis to identify sets of SNPs associated with genes that could provide further biologic insight to traditional genome-wide analysis. Using data collected between 1989 and 1994 in these previous studies to form a nested case-control study, the authors found that 3 of the most significantly associated SNPs to type 2 diabetes mellitus in their study are expression SNPs to the lymphocyte antigen 75 gene (LY75), the ubiquitin-specific peptidase 36 gene (USP36), and the phosphatidylinositol transfer protein, cytoplasmic 1 gene (PITPNC1). SNP set enrichment analysis of the GWAS results identified enrichment for expression SNPs to the macrophage-enriched module and the Gene Ontology (GO) biologic process fat cell differentiation human, which includes the transcription factor 7-like 2 gene (TCF7L2), as well as other type 2 diabetes mellitus-associated genes. Integrating genome-wide association, gene expression, and gene set analysis may provide valuable biologic support for potential type 2 diabetes mellitus susceptibility loci and may be useful in identifying new targets or pathways of interest for the treatment and prevention of type 2 diabetes mellitus.

摘要

大规模全基因组关联研究(GWAS)已经确定了 40 多个与 2 型糖尿病显著相关的基因组区域。然而,GWAS 结果并不总是易于解释,如果没有广泛的后续研究,将这些位点与有意义的疾病病因联系起来通常是困难的。作者通过纳入表达单核苷酸多态性(SNP)信息并应用 SNP 集富集分析来识别与基因相关的 SNP 集,为传统的全基因组分析提供进一步的生物学见解,从而扩展了先前报道的来自 2 个前瞻性美国队列的嵌套病例对照研究的 2 型糖尿病 GWAS。利用之前研究中在 1989 年至 1994 年之间收集的数据形成嵌套病例对照研究,作者发现他们的研究中与 2 型糖尿病最显著相关的 3 个 SNP 是淋巴细胞抗原 75 基因(LY75)、泛素特异性肽酶 36 基因(USP36)和磷酸肌醇转移蛋白、细胞质 1 基因(PITPNC1)的表达 SNP。GWAS 结果的 SNP 集富集分析确定了富含表达 SNP 的巨噬细胞富集模块和基因本体论(GO)生物学过程人类脂肪细胞分化的富集,其中包括转录因子 7 样 2 基因(TCF7L2)以及其他 2 型糖尿病相关基因。整合全基因组关联、基因表达和基因集分析可能为潜在的 2 型糖尿病易感基因座提供有价值的生物学支持,并可能有助于确定 2 型糖尿病治疗和预防的新靶点或感兴趣的途径。