Pulse Brain · Growing Health Evidence Index
Tier 1 — Meta-analysis / systematic reviewPeer-reviewed

The trans-ancestral genomic architecture of glycemic traits

Jihua Chen, Cassandra N. Spracklen, Gaëlle Marenne, Arushi Varshney, Laura J. Corbin, Jian’an Luan, Sara M. Willems, Ying Wu, Xiaoshuai Zhang, Momoko Horikoshi, Thibaud Boutin, Reedik Mägi, Johannes Waage, Ruifang Li‐Gao, Kei Hang Katie Chan, Jie Yao, Mila Desi Anasanti, Audrey Y. Chu, Annique Claringbould, Jani Heikkinen, Jaeyoung Hong, Jouke‐Jan Hottenga, Shaofeng Huo, Marika Kaakinen, Tin Louie, Winfried März, Hortensia Moreno-Macías, 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, Noël P. Burtt, Claudia 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, Ayşe Demirkan, Qing Duan, Jorgen Engmann, Segun Fatumo, Javier Gayán, Franco Giulianini, Jung Ho Gong, Stefan Gustafsson, Yang Hai, Fernando Pires Hartwig, Jing He, Yoriko Heianza, Tao Huang, Alicia Huerta‐Chagoya, Mi Yeong Hwang, Richard A. Jensen, Takahisa Kawaguchi, Katherine A. Kentistou, Young Jin Kim, Marcus E. Kleber, Ishminder K. Kooner, Shuiqing Lai, Leslie A. Lange, Carl D. Langefeld, Marie Lauzon, Man Li, Symen Ligthart, Jun Liu, Marie Loh, Jirong Long, Valeriya Lyssenko, Massimo Mangino, Carola Marzi, May E. Montasser, Abhishek Nag, Masahiro Nakatochi, Damia Noce, Raymond Noordam, Giorgio Pistis, Michael Preuß, Laura M. Raffield

Nature Genetics · 2021

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Summary

This large-scale trans-ancestral GWAS meta-analysis, published in Nature Genetics in 2021, examined the genetic architecture of glycaemic traits across diverse populations. By combining data across multiple ancestral groups, the study aimed to identify both shared and ancestry-specific genetic variants influencing glucose metabolism and insulin regulation. The work contributes to understanding of cardiometabolic disease susceptibility and suggests that genomic architecture of metabolic health traits varies meaningfully across populations.

Regional applicability

Findings may inform genetic risk stratification and precision health approaches in UK clinical and public health settings. However, the applicability depends on representation of UK population ancestry in the analysis; if predominantly European ancestry, transferability to UK minority populations may be limited.

Key measures

Fasting glucose, fasting insulin, 2-hour glucose, HOMA-IR (insulin resistance index), and related glycaemic phenotypes; genetic effect sizes and ancestry-specific allele frequencies

Outcomes reported

The study identified genetic variants associated with glycaemic traits (fasting glucose, fasting insulin, and related measures) across multiple ancestral populations. It characterised the trans-ancestral genomic architecture underlying glycaemic regulation and metabolic health.

Theme
Nutrition & health
Subject
Dietary patterns & chronic disease
Study type
Meta-analysis
Study design
Genome-wide association study (GWAS) meta-analysis
Source type
Peer-reviewed study
Status
Published
Geography
International
System type
Human clinical
DOI
10.1038/s41588-021-00852-9
Catalogue ID
SNmois85jd-sy896n

Topic tags

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