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利用多元分析方法在多民族 ARIC 研究中对非传统血糖生物标志物的常见和罕见变异进行特征分析。

Characterizing Common and Rare Variations in Nontraditional Glycemic Biomarkers Using Multivariate Approaches on Multiancestry ARIC Study.

机构信息

Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.

Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.

出版信息

Diabetes. 2024 Sep 1;73(9):1537-1550. doi: 10.2337/db23-0318.

DOI:10.2337/db23-0318
PMID:38869630
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11333373/
Abstract

Genetic studies of nontraditional glycemic biomarkers, glycated albumin and fructosamine, can shed light on unknown aspects of type 2 diabetes genetics and biology. We performed a multiphenotype genome-wide association study of glycated albumin and fructosamine from 7,395 White and 2,016 Black participants in the Atherosclerosis Risk in Communities (ARIC) study on common variants from genotyped/imputed data. We discovered two genome-wide significant loci, one mapping to a known type 2 diabetes gene (ARAP1/STARD10) and another mapping to a novel region (UGT1A complex of genes), using multiomics gene-mapping strategies in diabetes-relevant tissues. We identified additional loci that were ancestry- and sex-specific (e.g., PRKCA in African ancestry, FCGRT in European ancestry, TEX29 in males). Further, we implemented multiphenotype gene-burden tests on whole-exome sequence data from 6,590 White and 2,309 Black ARIC participants. Ten variant sets annotated to genes across different variant aggregation strategies were exome-wide significant only in multiancestry analysis, of which CD1D, EGFL7/AGPAT2, and MIR126 had notable enrichment of rare predicted loss of function variants in African ancestry despite smaller sample sizes. Overall, 8 of 14 discovered loci and genes were implicated to influence these biomarkers via glycemic pathways, and most of them were not previously implicated in studies of type 2 diabetes. This study illustrates improved locus discovery and potential effector gene discovery by leveraging joint patterns of related biomarkers across the entire allele frequency spectrum in multiancestry analysis. Future investigation of the loci and genes potentially acting through glycemic pathways may help us better understand the risk of developing type 2 diabetes.

摘要

非传统血糖生物标志物糖化白蛋白和果糖胺的遗传研究可以揭示 2 型糖尿病遗传学和生物学未知的方面。我们对来自动脉粥样硬化风险社区(ARIC)研究的 7395 名白人和 2016 名黑种人参与者的糖化白蛋白和果糖胺进行了多表型全基因组关联研究,这些参与者的常见变体来自基因分型/推断的数据。我们使用与糖尿病相关组织中的多组学基因映射策略,发现了两个全基因组显著的基因座,一个映射到一个已知的 2 型糖尿病基因(ARAP1/STARD10),另一个映射到一个新的区域(UGT1A 基因复合物)。我们还确定了其他与祖先和性别特异性相关的基因座(例如,非洲裔中的 PRKCA,欧洲裔中的 FCGRT,男性中的 TEX29)。此外,我们在来自 6590 名白人和 2309 名黑种人 ARIC 参与者的全外显子组序列数据上实施了多表型基因负担测试。在多祖先分析中,10 个变异集注释到不同变异聚集策略的基因,仅在全外显子组范围内具有统计学意义,其中 CD1D、EGFL7/AGPAT2 和 MIR126 尽管样本量较小,但在非洲裔中罕见的预测功能丧失变异明显富集。总的来说,在 14 个发现的基因座和基因中,有 8 个通过血糖途径影响这些生物标志物,而且其中大多数以前没有在 2 型糖尿病研究中被提及。这项研究说明了通过在多祖先分析中利用整个等位基因频率谱上相关生物标志物的联合模式,可以提高基因座的发现和潜在效应基因的发现。对潜在通过血糖途径发挥作用的基因座和基因的进一步研究可能有助于我们更好地了解 2 型糖尿病的发病风险。