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期刊来源：Nat Med

原文链接：https://doi.org/10.1038/s41591-024-02865-3

摘要内容如下：

2型糖尿病（T2D）是一种具有遗传风险的多因素疾病，其潜在的生物学机制尚不完全清楚。在这项研究中，我们通过分析37个已发表的T2D全基因组关联研究中不同人群的遗传数据，确定了多祖先T2D基因簇，这些研究代表了140多万个个体。我们对650个T2D相关遗传变异和110个T2D相关性状实施了软聚类，在代表不同遗传祖先群体的两个独立生物库中捕获了具有不同心脏代谢性状关联的已知和新的T2D聚类（非洲，n=21，906；混血美国人，N=14，410；东亚，n=2，422；欧洲，N=90，093；南亚，N=1，262）。12个基因簇富集了特定的单细胞调控区。从聚类中得出的几个多基因评分在祖先群体中的分布不同，包括在东亚祖先中与脂肪营养不良相关的多基因风险的比例显著较高。身体质量指数（BMI）为30kgm-2的欧洲亚人群和24.2（22.9-25.5）KGM-2的东亚亚人群的T2D风险相等；在对集群特异性遗传风险进行调整后，东亚组的等效BMI阈值增加到28.5（27.1-30.0）KGM-2。因此，这些多祖先T2D基因簇包含了更广泛的生物学机制，并为解释T2D风险概况中与祖先相关的差异提供了初步见解。

英文原文如下：

Abstracts

Type 2 diabetes (T2D) is a multifactorial disease with substantial genetic risk, for which the underlying biological mechanisms are not fully understood. In this study, we identified multi-ancestry T2D genetic clusters by analyzing genetic data from diverse populations in 37 published T2D genome-wide association studies representing more than 1.4 million individuals. We implemented soft clustering with 650 T2D-associated genetic variants and 110 T2D-related traits, capturing known and novel T2D clusters with distinct cardiometabolic trait associations across two independent biobanks representing diverse genetic ancestral populations (African, n = 21,906; Admixed American, n = 14,410; East Asian, n =2,422; European, n = 90,093; and South Asian, n = 1,262). The 12 genetic clusters were enriched for specific single-cell regulatory regions. Several of the polygenic scores derived from the clusters differed in distribution among ancestry groups, including a significantly higher proportion of lipodystrophy-related polygenic risk in East Asian ancestry. T2D risk was equivalent at a body mass index (BMI) of 30 kg m-2 in the European subpopulation and 24.2 (22.9-25.5) kg m-2 in the East Asian subpopulation; after adjusting for cluster-specific genetic risk, the equivalent BMI threshold increased to 28.5 (27.1-30.0) kg m-2 in the East Asian group. Thus, these multi-ancestry T2D genetic clusters encompass a broader range of biological mechanisms and provide preliminary insights to explain ancestry-associated differences in T2D risk profiles.

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