英国埃克塞特大学Inês Barroso等研究人员合作揭示血糖性状的跨祖先基因组结构。相关论文于2021年5月31日在线发表在《自然—遗传学》杂志上。

研究人员整合了基因组范围的关联研究，该研究包含高达281,416名没有糖尿病的个体（30％的非欧洲祖先），用于分析空腹葡萄糖、饮用葡萄糖后的2小时葡萄糖、糖化血红蛋白和空腹胰岛素数据。跨祖先和单祖先分析确定了242个基因座（99个新的; p<5×10^-8），其中80％没有显著的祖先异质性证据。限定于欧洲祖先的分析（具有相同的样本大小）产生了24个新的基因座。

与单祖先分析相比，等样本大小的跨祖先精细映射减少了估计变体的数量。基因组特征、基因表达和基因集分析显示了每个性状的明显生物特征，突出了不同的潜在生物途径。这些结果通过使用跨祖先研究来提高了分析了和分辨率，从而增加了对糖尿病病理生理学的理解。

据介绍，血糖性状被用于诊断和监测2型糖尿病和心脏素质健康。迄今为止，血糖性状的大多数遗传学研究都集中在欧洲血统的个体上。

附：英文原文

Title: The trans-ancestral genomic architecture of glycemic traits

Author: Ji Chen, Cassandra N. Spracklen, Galle Marenne, Arushi Varshney, Laura J. Corbin, Jianan Luan, Sara M. Willems, Ying Wu, Xiaoshuai Zhang, Momoko Horikoshi, Thibaud S. Boutin, Reedik Mgi, Johannes Waage, Ruifang Li-Gao, Kei Hang Katie Chan, Jie Yao, Mila D. Anasanti, Audrey Y. Chu, Annique Claringbould, Jani Heikkinen, Jaeyoung Hong, Jouke-Jan Hottenga, Shaofeng Huo, Marika A. Kaakinen, Tin Louie, Winfried Mrz, Hortensia Moreno-Macias, Anne Ndungu, Sarah C. Nelson, Ilja M. Nolte, Kari E. North, Chelsea K. Raulerson, Debashree Ray, Rebecca Rohde, Denis Rybin, Claudia Schurmann, Xueling Sim, Lorraine Southam, Isobel D. Stewart, Carol A. Wang, Yujie Wang, Peitao Wu, Weihua Zhang, Tarunveer S. Ahluwalia, Emil V. R. Appel, Lawrence F. Bielak, Jennifer A. Brody, Nol P. Burtt, Claudia P. Cabrera, Brian E. Cade, Jin Fang Chai, Xiaoran Chai, Li-Ching Chang, Chien-Hsiun Chen, Brian H. Chen, Kumaraswamy Naidu Chitrala, Yen-Feng Chiu, Hugoline G. de Haan, Graciela E. Delgado, Ayse Demirkan, Qing Duan, Jorgen Engmann, Segun A. Fatumo

Issue&Volume: 2021-05-31

Abstract: Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242loci (99 novel; P<5×108), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.

DOI: 10.1038/s41588-021-00852-9

Source: https://www.nature.com/articles/s41588-021-00852-9