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揭示全球人群和疾病相关组织中导致2型糖尿病的分子机制。

Unravelling the molecular mechanisms causal to type 2 diabetes across global populations and disease-relevant tissues.

作者信息

Bocher Ozvan, Arruda Ana Luiza, Yoshiji Satoshi, Zhao Chi, Su Chen-Yang, Yin Xianyong, Cammann Davis, Taylor Henry J, Chen Jingchun, Suzuki Ken, Mandla Ravi, Huerta-Chagoya Alicia, Yang Ta-Yu, Matsuda Fumihiko, Mercader Josep M, Flannick Jason, Meigs James B, Wood Alexis C, Vujkovic Marijana, Voight Benjamin F, Spracklen Cassandra N, Rotter Jerome I, Morris Andrew P, Zeggini Eleftheria

机构信息

Institute of Translational Genomics, Helmholtz Munich, Neuherberg, 85764, Germany.

Univ Brest, Inserm, EFS, UMR 1078, GGB, F-29200 Brest, France.

出版信息

medRxiv. 2025 May 7:2025.05.05.25326880. doi: 10.1101/2025.05.05.25326880.

Abstract

Type 2 diabetes (T2D) is a prevalent disease that arises from complex molecular mechanisms. Here, we leverage T2D multi-ancestry genetic associations to identify causal molecular mechanisms in an ancestry- and tissue-aware manner. Using two-sample Mendelian Randomization corroborated by colocalization across four global ancestries, we analyze 20,307 gene and 1,630 protein expression levels using blood-derived -quantitative trait loci (QTLs). We detect causal effects of genetically predicted levels of 335 genes and 46 proteins on T2D risk, with 16.4% and 50% replication in independent cohorts, respectively. Using gene expression -QTLs derived from seven T2D-relevant tissues, we identify causal links between the expression of 676 genes and T2D risk, including novel associations such as and . Causal effects are mostly shared across ancestries, but highly heterogeneous across tissues. Our findings provide insights in cross-ancestry and tissue-informed multi-omics causal inference analysis approaches and demonstrate their power in uncovering molecular processes driving T2D.

摘要

2型糖尿病(T2D)是一种由复杂分子机制引发的常见疾病。在此,我们利用T2D多祖先遗传关联,以一种考虑祖先和组织的方式识别因果分子机制。通过两样本孟德尔随机化并结合来自四个全球祖先的共定位分析,我们使用血液来源的定量性状位点(QTLs)分析了20307个基因和1630种蛋白质的表达水平。我们检测到335个基因和46种蛋白质的遗传预测水平对T2D风险有因果效应,在独立队列中的复制率分别为16.4%和50%。利用来自七个与T2D相关组织的基因表达-QTLs,我们确定了676个基因的表达与T2D风险之间的因果联系,包括诸如 和 等新关联。因果效应大多在不同祖先之间共享,但在不同组织之间高度异质。我们的研究结果为跨祖先和组织信息的多组学因果推断分析方法提供了见解,并展示了它们在揭示驱动T2D的分子过程中的作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4ec5/12083623/aab75b25db34/nihpp-2025.05.05.25326880v1-f0001.jpg

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