英国牛津大学Andrew P. Morris，Mark I. McCarthy和Anubha Mahajan共同合作近期取得重要工作进展。他们研究发现多血统遗传研究增强了在不同人群中发现和预测2型糖尿病遗传风险的能力。相关论文2022年5月12日在线发表于《自然—遗传学》杂志上。

研究人员通过跨种族关联研究的糖尿病元分析（DIAMANTE）联盟，收集了180,834名受影响的个体和1,159,055名对照者（48.9%为非欧洲人后裔）的2型糖尿病（T2D）全基因组关联研究（GWAS）的血统多样性集合。多血统GWAS元分析确定了237个达到严格的全基因组意义的基因座（P<5×10-9），这些基因座被划定为338个不同的关联信号。这些信号的精细映射因多血统元分析的样本量增加和人群多样性扩大而得到加强，该分析将54.4%的T2D关联定位为单一变体，后验概率大于50%。

这种改进的精细映射使研究人员能够系统地评估候选因果基因和T2D关联的分子机制，为功能研究奠定了基础。多血统的遗传风险评分增强了T2D预测在不同人群中的可转移性。他们的研究为T2D GWAS向更有效的临床转化迈出了一步，以改善全球所有人的健康，不论其遗传背景。

附：英文原文

Title: Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author: Mahajan, Anubha, Spracklen, Cassandra N., Zhang, Weihua, Ng, Maggie C. Y., Petty, Lauren E., Kitajima, Hidetoshi, Yu, Grace Z., Reger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M., Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R., Rayner, Nigel W., Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H., Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A., Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J., Yao, Jie, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P., Kals, Mart, Grarup, Niels, Schmidt, Ellen M., Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor J. Y.

Issue&Volume: 2022-05-12

Abstract: We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P<5×109), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

DOI: 10.1038/s41588-022-01058-3

Source:https://www.nature.com/articles/s41588-022-01058-3