An epidemiological introduction to human metabolomic investigations

Amit D Joshi; Ali Rahnavard; Priyadarshini Kachroo; Kevin M Mendez; Wayne Lawrence; Sachelly Julián-Serrano; Xinwei Hua; Harriett Fuller; Nasa Sinnott-Armstrong; Fred K Tabung; Katherine H Shutta; Laura M Raffield; Burcu F Darst; COMETS Early Career Scientist Working Group

doi:10.1016/j.tem.2023.06.006

An epidemiological introduction to human metabolomic investigations

Trends Endocrinol Metab. 2023 Sep;34(9):505-525. doi: 10.1016/j.tem.2023.06.006. Epub 2023 Jul 17.

Affiliations

¹ Clinical & Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA.
² Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.
³ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
⁴ Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
⁵ Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Public Health, University of Massachusetts Lowell, Lowell, MA, USA.
⁶ Clinical & Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA; Department of Cardiology, Peking University Third Hospital, Beijing, China.
⁷ Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
⁸ The Ohio State University College of Medicine and Comprehensive Cancer Center, Columbus, OH, USA.
⁹ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
¹⁰ Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹¹ Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA. Electronic address: bdarst@fredhutch.org.

PMID: 37468430
PMCID: PMC10527234 (available on 2024-09-01)
DOI: 10.1016/j.tem.2023.06.006

Abstract

Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.

Keywords: epidemiology; high-dimensional statistical methods; integrative omics; metabolites; metabolomic epidemiology; quality control.

An epidemiological introduction to human metabolomic investigations

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