小柯机器人

德国慕尼黑工业大学Eleftheria Zeggini等研究人员合作揭示2型糖尿病病理生理学异质性的遗传驱动因素。相关论文于2024年2月19日在线发表于国际学术期刊《自然》。

研究人员汇总了来自2535601人（39.7%非欧洲血统）的全基因组关联研究数据，其中包括428452例2型糖尿病（T2D）病例，以描述不同血统群体对这些过程的遗传贡献。研究人员发现了1289个具有全基因组显著性（P<5×10^-8）的独立关联信号，这些信号映射到611个位点，其中145个位点以前从未报道过。研究人员定义了八个不重叠的T2D信号群，这些信号群具有不同的心脏代谢特征关联特征。这些集群不同程度地富集于细胞类型特异的开放染色质区域，包括胰岛、脂肪细胞、内皮细胞和肠内分泌细胞。

研究人员还在279552名不同血统的个体（包括30288例T2D患者）中建立了群组特异性分区多基因评分，并检验了它们与T2D相关血管结果的关联。不同祖先群体的聚类特异性分区多基因评分与冠状动脉疾病、外周动脉疾病和终末期糖尿病肾病相关，这突出了肥胖相关过程在血管疾病发展过程中的重要性。这些研究结果表明，将多血统全基因组关联研究数据与单细胞表观基因组学结合起来，以揭示驱动T2D发生和发展的病因异质性，具有重要价值。这可能为优化全球糖尿病基因护理提供了一条途径

据了解，T2D是一种异质性疾病，通过不同的病理生理过程和通常针对特定细胞类型的分子机制发展而来。

附：英文原文

Title: Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Author: Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J., Yin, Xianyong, Lorenz, Kim M., Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio E. M., Kanoni, Stavroula, Rayner, Nigel W., Bocher, Ozvan, Arruda, Ana Luiza, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S. K., Preuss, Michael H., Petty, Lauren E., Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A., Cook, James P., Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J., Chai, Jin-Fang, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chlo, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj S., Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M.

Issue&Volume: 2024-02-19

Abstract: Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P<5×108) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

DOI: 10.1038/s41586-024-07019-6

Source: https://www.nature.com/articles/s41586-024-07019-6

Nature：《自然》，创刊于1869年。隶属于施普林格·自然出版集团，最新IF：69.504
官方网址：http://www.nature.com/
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