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全基因组表达数量性状位点共识及其与人类复杂性状疾病的关系。

Consensus Genome-Wide Expression Quantitative Trait Loci and Their Relationship with Human Complex Trait Disease.

作者信息

Yu Chen-Hsin, Pal Lipika R, Moult John

机构信息

1 Institute for Bioscience and Biotechnology Research, University of Maryland , Rockville, Maryland.

2 Molecular and Cell Biology Concentration Area, Biological Sciences Graduate Program, University of Maryland , College Park, Maryland.

出版信息

OMICS. 2016 Jul;20(7):400-14. doi: 10.1089/omi.2016.0063.

Abstract

Most of the risk loci identified from genome-wide association (GWA) studies do not provide direct information on the biological basis of a disease or on the underlying mechanisms. Recent expression quantitative trait locus (eQTL) association studies have provided information on genetic factors associated with gene expression variation. These eQTLs might contribute to phenotype diversity and disease susceptibility, but interpretation is handicapped by low reproducibility of the expression results. To address this issue, we have generated a set of consensus eQTLs by integrating publicly available data for specific human populations and cell types. Overall, we find over 4000 genes that are involved in high-confidence eQTL relationships. To elucidate the role that eQTLs play in human common diseases, we matched the high-confidence eQTLs to a set of 335 disease risk loci identified from the Wellcome Trust Case Control Consortium GWA study and follow-up studies for 7 human complex trait diseases-bipolar disorder (BD), coronary artery disease (CAD), Crohn's disease (CD), hypertension (HT), rheumatoid arthritis (RA), type 1 diabetes (T1D), and type 2 diabetes (T2D). The results show that the data are consistent with ∼50% of these disease loci arising from an underlying expression change mechanism.

摘要

大多数从全基因组关联(GWA)研究中确定的风险位点并未提供有关疾病生物学基础或潜在机制的直接信息。最近的表达定量性状位点(eQTL)关联研究提供了与基因表达变异相关的遗传因素信息。这些eQTL可能导致表型多样性和疾病易感性,但由于表达结果的低重复性,解释受到阻碍。为了解决这个问题,我们通过整合特定人群和细胞类型的公开可用数据,生成了一组共识eQTL。总体而言,我们发现超过4000个基因参与了高可信度的eQTL关系。为了阐明eQTL在人类常见疾病中所起的作用,我们将高可信度的eQTL与从威康信托病例对照协会GWA研究以及针对7种人类复杂性状疾病——双相情感障碍(BD)、冠状动脉疾病(CAD)、克罗恩病(CD)、高血压(HT)、类风湿性关节炎(RA)、1型糖尿病(T1D)和2型糖尿病(T2D)的后续研究中确定的335个疾病风险位点进行了匹配。结果表明,数据与约50%的这些疾病位点源于潜在的表达变化机制一致。

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