日本大阪大学Yukinori Okada小组宣布他们研究出基因-环境相互作用的跨种群概要。2026年1月28日，国际知名学术期刊《自然》发表了这一成果。

该课题组提供了一个基因与环境相互作用的跨种群图谱，其中包括来自欧洲和日本种群的440210个个体，并在来自不同种群的539794个个体中进行了复制。通过分解年龄、性别和生活方式的贡献，研究组描绘了这些基因-环境相互作用的病因学，包括与疾病相关的饮食改变带来的反向因果关系。全基因组分析揭示了基因组和环境的协同效应所导致的遗传力缺失和性状-性状关系，这系统性地影响了多基因预测的准确性和跨种群可移植性。单细胞投影揭示了负责遗传调控的途径和细胞类型的衰老转移。组学水平的基因环境分析确定了脂质代谢中多种性别不一致的遗传效应，为基因支持药物开发的临床试验失败提供了信息。他们全面的基因环境研究解码了遗传关联的动态，为复杂的性状生物学、个性化医学和药物开发提供了见解。

据了解，遗传效应大小的环境差异，即基因-环境相互作用，可能揭示表型可塑性的遗传编码。

附：英文原文

Title: A cross-population compendium of gene–environment interactions

Author: Namba, Shinichi, Sonehara, Kyuto, Koyanagi, Yuriko N., Kikuchi, Takezo, Ojima, Takafumi, Edahiro, Ryuya, Sato, Go, Yamaji, Taiki, Tomofuji, Yoshihiko, Ueda, Hiroyuki, Yamamoto, Kenichi, Ogawa, Yosuke, Suzuki, Ken, Kanai, Akinori, Higashiue, Shinichi, Kobayashi, Shuzo, Yamaguchi, Hiroki, Nagata, Yasunobu, Okazaki, Yasushi, Matsumoto, Naoyuki, Motomura, Kenta, Koga, Hidenobu, Hishida, Asahi, Ikezaki, Hiroaki, Hara, Megumi, Nagayoshi, Mako, Oze, Isao, Nakano, Shiori, Oda, Yoshiya, Suzuki, Yutaka, Iwasaki, Motoki, Sawada, Norie, Matsuo, Keitaro, Morisaki, Takayuki, Yamauchi, Toshimasa, Kadowaki, Takashi, Matsuda, Koichi, Okada, Yukinori

Issue&Volume: 2026-01-28

Abstract: Environmental differences in genetic effect sizes, namely, gene–environment interactions, may uncover the genetic encoding of phenotypic plasticity1,2,3. We provide a cross-population atlas of gene–environment interactions comprising 440,210 individuals from European and Japanese populations, with replication in 539,794 individuals from diverse populations. By decomposing the contributions from age, sex and lifestyles, we delineate the aetiology of these gene–environment interactions, including a reverse-causality from a disease-related dietary change. Genome-wide analyses uncovered missing heritability and trait–trait relationships connected by the synergistic effects of genome and environments, which systematically affected polygenic prediction accuracy and cross-population portability. Single-cell projection revealed aging shift of pathways and cell types responsible for genetic regulation. Omics-level gene–environment analyses identified multiple sex-discordant genetic effects in lipid metabolism, informing clinical trial failures for genetically supported drug development. Our comprehensive gene–environment study decodes the dynamics of genetic associations, offering insights into complex trait biology, personalized medicine and drug development.

DOI: 10.1038/s41586-025-10054-6

Source: https://www.nature.com/articles/s41586-025-10054-6