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欧洲和非洲特异性血浆蛋白数量性状基因座及代谢物数量性状基因座分析确定了特定血统的2型糖尿病效应蛋白和代谢物。

European and African-specific plasma protein-QTL and metabolite-QTL analyses identify ancestry-specific T2D effector proteins and metabolites.

作者信息

Cruchaga Carlos, Yang Chengran, Gorijala Priyanka, Timsina Jigyasha, Wang Lihua, Liu Menghan, Wang Ciyang, Brock William, Wang Yueyao, Sung Yun Ju

机构信息

Washington University.

Washington University in St. Louis.

出版信息

Res Sq. 2024 Jul 22:rs.3.rs-3617016. doi: 10.21203/rs.3.rs-3617016/v1.

Abstract

Initially focused on the European population, multiple genome-wide association studies (GWAS) of complex diseases, such as type-2 diabetes (T2D), have now extended to other populations. However, to date, few ancestry-matched omics datasets have been generated or further integrated with the disease GWAS to nominate the key genes and/or molecular traits underlying the disease risk loci. In this study, we generated and integrated plasma proteomics and metabolomics with array-based genotype datasets of European (EUR) and African (AFR) ancestries to identify ancestry-specific muti-omics quantitative trait loci (QTLs). We further applied these QTLs to ancestry-stratified T2D risk to pinpoint key proteins and metabolites underlying the disease-associated genetic loci. We nominated five proteins and four metabolites in the European group and one protein and one metabolite in the African group to be part of the molecular pathways of T2D risk in an ancestry-stratified manner. Our study demonstrates the integration of genetic and omic studies of different ancestries can be used to identify distinct effector molecular traits underlying the same disease across diverse populations. Specifically, in the AFR proteomic findings on T2D, we prioritized the protein QSOX2; while in the AFR metabolomic findings, we pinpointed the metabolite GlcNAc sulfate conjugate of C21H34O2 steroid. Neither of these findings overlapped with the corresponding EUR results.

摘要

最初聚焦于欧洲人群,诸如2型糖尿病(T2D)等复杂疾病的多项全基因组关联研究(GWAS)现已扩展到其他人群。然而,迄今为止,几乎没有生成与疾病GWAS相匹配的血统组学数据集,也没有将其进一步整合以确定疾病风险位点背后的关键基因和/或分子特征。在本研究中,我们生成了欧洲(EUR)和非洲(AFR)血统的血浆蛋白质组学和代谢组学数据,并将其与基于阵列的基因型数据集整合,以识别特定血统的多组学数量性状位点(QTL)。我们进一步将这些QTL应用于按血统分层的T2D风险分析,以确定疾病相关基因位点背后的关键蛋白质和代谢物。我们以血统分层的方式确定欧洲组中有五种蛋白质和四种代谢物、非洲组中有一种蛋白质和一种代谢物是T2D风险分子途径的一部分。我们的研究表明,整合不同血统的遗传和组学研究可用于识别不同人群中同一疾病背后不同的效应分子特征。具体而言,在非洲血统人群关于T2D的蛋白质组学研究结果中,我们将蛋白质QSOX2列为重点;而在非洲血统人群的代谢组学研究结果中,我们确定了甾体C21H34O2的硫酸葡萄糖胺共轭物为关键代谢物。这些结果均与相应的欧洲血统人群结果无重叠。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e2a5/11302687/e79485d0a6fd/nihpp-rs3617016v1-f0001.jpg

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