Incorporating additive genetic effects and linkage disequilibrium information to discover gene-environment interactions using BV-LDER-GE

IF 10.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Genome Biology Pub Date : 2025-10-03 DOI:10.1186/s13059-025-03815-z

Zihan Dong, Wei Jiang, Jiangnan Shen, Hongyu Li, Yuhan Xie, Andrew T. DeWan, Hongyu Zhao

引用次数: 0

Abstract

Uncovering environmental factors interacting with genetic factors to influence complex traits is important in genetic epidemiology and disease etiology. We introduce BiVariate Linkage-Disequilibrium Eigenvalue Regression for Gene-Environment interactions (BV-LDER-GE), a statistical method that detects the overall contributions of G × E interactions in the genome using summary statistics of complex traits. In comparison to existing methods which either ignore correlations with additive effects or use partial information of linkage disequilibrium (LD), BV-LDER-GE harnesses correlations with additive genetic effects and full LD information to enhance the statistical power to detect genome-scale G × E interactions.

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结合加性遗传效应和连锁不平衡信息，利用BV-LDER-GE发现基因与环境的相互作用

揭示环境因素与遗传因素相互作用对复杂性状的影响在遗传流行病学和疾病病因学中具有重要意义。我们介绍了基因-环境相互作用的双变量联动-不平衡特征值回归（BV-LDER-GE），这是一种利用复杂性状的汇总统计来检测基因组中G × E相互作用的总体贡献的统计方法。与现有方法忽略加性效应的相关性或使用连锁不平衡（LD）的部分信息相比，BV-LDER-GE利用加性遗传效应的相关性和完整的LD信息来提高检测基因组尺度G × E相互作用的统计能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Genome Biology Biochemistry, Genetics and Molecular Biology-Genetics

CiteScore

21.00

自引率

3.30%

发文量

241

审稿时长

2 months

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