Plasma metabolites to profile pathways in noncommunicable disease multimorbidity

• Published in: Nature medicine Vol. 27; no. 3; pp. 471 - 479
• Main Authors: Pietzner, Maik, Stewart, Isobel D., Raffler, Johannes, Khaw, Kay-Tee, Michelotti, Gregory A., Kastenmüller, Gabi, Wareham, Nicholas J., Langenberg, Claudia
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.03.2021; Nature Publishing Group
• Subjects: 631/114/2164; 631/114/2401; 631/67; 692/499; 692/53; Aged; Biomedical and Life Sciences; Biomedicine; Cancer Research; Chronic conditions; Chronic diseases; Chronic illnesses; Cohort Studies; Comorbidity; Development and progression; Electronic health records; Electronic medical records; Female; Global health; Glucose metabolism; Health aspects; Humans; Identification and classification; Infectious Diseases; Inflammation; Lipid metabolism; Lipids; Male; Metabolic Diseases; Metabolites; Metabolome; Metabolomics; Microorganisms; Middle Aged; Molecular Medicine; Multimorbidity; Neurosciences; Noncommunicable Diseases; Physiological aspects; Plasma - metabolism; Public health; Risk analysis; Risk factors; United Kingdom
• ISSN: 1078-8956; 1546-170X; 1546-170X
• DOI: 10.1038/s41591-021-01266-0

Multimorbidity, the simultaneous presence of multiple chronic conditions, is an increasing global health problem and research into its determinants is of high priority. We used baseline untargeted plasma metabolomics profiling covering >1,000 metabolites as a comprehensive readout of human physiology to characterize pathways associated with and across 27 incident noncommunicable diseases (NCDs) assessed using electronic health record hospitalization and cancer registry data from over 11,000 participants (219,415 person years). We identified 420 metabolites shared between at least 2 NCDs, representing 65.5% of all 640 significant metabolite–disease associations. We integrated baseline data on over 50 diverse clinical risk factors and characteristics to identify actionable shared pathways represented by those metabolites. Our study highlights liver and kidney function, lipid and glucose metabolism, low-grade inflammation, surrogates of gut microbial diversity and specific health-related behaviors as antecedents of common NCD multimorbidity with potential for early prevention. We integrated results into an open-access webserver ( https://omicscience.org/apps/mwasdisease/ ) to facilitate future research and meta-analyses. Untargeted metabolomics profiling coupled with analysis of electronic health records in over 11,000 participants in the EPIC-Norfolk cohort reveals shared pathways that contribute to multimorbidity of noncommunicable diseases.