Gene-environment interaction (G & times;E) analyses play a crucial role in advancing genetic discovery, addressing missing heritability, and facilitating precision medicine. However, existing G & times;E methods are mostly designed for cross-sectional data, limiting the utility of longitudinal data. Here we propose SAGELD, a scalable and accurate genome-wide G & times;E method for longitudinal traits that controls for sample relatedness in large-scale datasets. SAGELD uses matrix projection to construct test statistics and the SPAGRM framework to efficiently control for sample relatedness, achieving 10- to 10,000-fold speedups over existing methods while maintaining greater power than cross-sectional analyses. We evaluated SAGELD through extensive simulations and UK Biobank analyses. Using age and body mass index as environmental exposures, we identified 74 loci with genetic & times; age interactions and 5 loci with genetic & times; adiposity interactions in the pooled analysis of longitudinal primary care data and cross-sectional assessment data. These results highlight the advantages of leveraging longitudinal data in G & times;E analyses.

Publication:

NATURE COMPUTATIONAL SCIENCE

http://dx.doi.org/10.1038/s43588-026-01002-z

Author:

Xu, He

Peking Univ, Sch Basic Med Sci, Dept Med Genet, Beijing, Peoples R China

Ma, Yuzhuo

Peking Univ, Sch Basic Med Sci, Dept Med Genet, Beijing, Peoples R China

Liu, Yufei

Peking Univ, Sch Basic Med Sci, Dept Med Genet, Beijing, Peoples R China

Bi, Wenjian

Peking Univ, Sch Basic Med Sci, Dept Med Genet, Beijing, Peoples R China

Li, Yin

Peking Univ, Hlth Sci Ctr, Sch Basic Med Sci, Dept Biochem & Mol Biol, Beijing, Peoples R China

Zhang, Peipei

Peking Univ, Hlth Sci Ctr, Sch Basic Med Sci, Dept Biochem & Mol Biol, Beijing, Peoples R China

Wan, Lin

Capital Med Univ, Beijing Tongren Hosp, Dept Clin Psychol, Beijing, Peoples R China;

Zhang, Ji-Feng

Zhongyuan Univ Technol, Sch Automat & Elect Engn, Zhengzhou, Peoples R China

Chinese Acad Sci, Acad Math & Syst Sci, State Key Lab Math Sci, Beijing, Peoples R China

Zhao, Yanlong

Chinese Acad Sci, Acad Math & Syst Sci, State Key Lab Math Sci, Beijing, Peoples R China

Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China

Yue, Weihua

Peking Univ Sixth Hosp, Inst Mental Hlth, Beijing, Peoples R China

Peking Univ, Natl Clin Res Ctr Mental Disorders, NHC Key Lab Mental Hlth, Beijing, Peoples R China

Peking Univ, PKU IDG McGovern Inst Brain Res, Beijing, Peoples R China

Zhang, Peipei

Peking Univ, Key Lab Neurosci, Minist Educ, Natl Hlth & Family Planning Commiss, Beijing, Peoples R China

Bi, Wenjian(corresponding author)

Peking Univ, Ctr Med Genet, Sch Basic Med Sci, Beijing, Peoples R China

Peking Univ, Med Innovat Ctr Fundamental Res Major Immunol Rela, Beijing, Peoples R China;

Peking Univ, State Key Lab Vasc Homeostasis & Remodeling, Beijing, Peoples R China

Email：wenjianb@pku.edu.cn