2026年9月3日，英国伦敦国王学院Julia S. El-Sayed Moustafa等科学家在《科学》（Science）发表研究，揭示了老龄化人群队列中基因表达与代谢组的纵向动态变化规律。
多组学分析在分子水平上提供了全面的生理学概览，但对其时空动态的理解在人群中仍然有限。研究人员对335名女性进行了为期8年的纵向全血基因表达和代谢物水平分析。5061个基因和181种代谢物的水平随时间发生变化，个体轨迹往往偏离群体水平的趋势。纵向变化的基因表现出细胞类型特异性，并与衰老相关通路（包括心脏代谢和神经退行性疾病）的富集相关。纵向轨迹还受到遗传、昼夜节律、季节性和环境污染物暴露的影响。整合分析揭示了广泛的静态和时变跨组学连接。纵向分析为在分子水平上理解年龄相关疾病的时间演变提供了洞见，理解这些纵向模式中的个体差异对于未来的精准医学方法至关重要。
附：英文原文
Title: Longitudinal dynamics of gene expression and metabolomics in an aging population cohort
Author: Julia S. El-Sayed Moustafa, Anna Ramisch, Yasrab N. Raza, Gwenael G. R. Leday, Yunlong Jiao, Dongmeng Wang, Michael Stevens, Amy L. Roberts, Max Tomlinson, Xinyu Yan, Elizabeth Ing-Simmons, Samuel Wadge, Moustafa Abdalla, Mario Falchi, Christopher C. Holmes, Cristina Menni, George Nicholson, Mark I. McCarthy, Emmanouil T. Dermitzakis, Sylvia Richardson, Tim D. Spector, Kerrin S. Small
Issue&Volume: 2026-09-03
Abstract: Multiomic profiling provides a comprehensive physiological overview at the molecular level, but understanding of its spatiotemporal dynamics remains limited in human populations. We profiled longitudinal whole-blood gene expression and metabolite levels in 335 females over 8 years. Levels of 5061 genes and 181 metabolites changed over time, with individual trajectories often diverging from population-level trends. Longitudinally variable genes showed cell type specificity and enrichment for aging-relevant pathways, including cardiometabolic and neurodegenerative disorders. Longitudinal trajectories were further shaped by genetics, circadian rhythm, seasonality, and environmental pollutant exposures. Integrative analyses revealed extensive static and time-variable cross-omic connectivity. Longitudinal profiling offers insight into the temporal evolution of age-related conditions at the molecular level, and understanding individual variation within these longitudinal patterns will be essential for future precision medicine approaches.
DOI: 10.1126/science.aed6452
Source: https://www.science.org/doi/10.1126/science.aed6452