Metabolomic epidemiology offers insights into disease aetiology

代谢组学 流行病学 疾病 医学 生物信息学 生物 病理
作者
Harriett Fuller,Yiwen Zhu,Jayna Nicholas,Haley Chatelaine,Emily Drzymalla,Afrand K. Sarvestani,Sachelly Julián‐Serrano,Usman A. Tahir,Nasa Sinnott-Armstrong,Laura M. Raffield,Ali Rahnavard,Xinwei Hua,Katherine H. Shutta,Burcu F. Darst
出处
期刊:Nature metabolism [Nature Portfolio]
卷期号:5 (10): 1656-1672 被引量:14
标识
DOI:10.1038/s42255-023-00903-x
摘要

Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression. This Review article discusses how the emerging field of metabolomic epidemiology gives insight into the aetiology of various diseases and how these findings could be translated into clinical applications.
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