Stratification of Atherosclerosis based on Plasma Metabolic States

• Published in: The journal of clinical endocrinology and metabolism Vol. 109; no. 5; pp. 1250 - 1262
• Main Authors: Menaker, Yuval, van den Munckhof, Inge, Scarpa, Alice, Placek, Katarzyna, Brandes-Leibovitz, Rachel, Glantzspiegel, Yossef, Joosten, Leo A B, Rutten, Joost H W, Netea, Mihai G, Gat-Viks, Irit, Riksen, Niels P
• Format: Journal Article
• Language: English
• Published: US Oxford University Press 01.05.2024
• Subjects: Arteriosclerosis; Atherosclerosis; Blood plasma; Body mass index; Cardiovascular diseases; Cerebral infarction; Development and progression; Estrogens; Glutamic acid; Health aspects; Homovanillic acid; Identification and classification; Medical research; Medicine, Experimental; Metabolic pathways; Metabolic syndrome; Metabolism; Metabolites; Metabolomics; Myocardial infarction; Phenylpropanoids; Physiological aspects; Netherlands; atherosclerosis; plasma metabolomics; disease stratification; diagnostic biomarkers
• ISSN: 0021-972X; 1945-7197; 1945-7197
• DOI: 10.1210/clinem/dgad672

Abstract Context Atherosclerosis is a dominant cause of cardiovascular disease (CVD), including myocardial infarction and stroke. Objective To investigate metabolic states that are associated with the development of atherosclerosis. Methods Cross-sectional cohort study at a university hospital in the Netherlands. A total of 302 adult subjects with a body mass index (BMI) ≥ 27 kg/m2 were included. We integrated plasma metabolomics with clinical metadata to quantify the “atherogenic state” of each individual, providing a continuous spectrum of atherogenic states that ranges between nonatherogenic states to highly atherogenic states. Results Analysis of groups of individuals with different clinical conditions—such as metabolically healthy individuals with obesity, and individuals with metabolic syndrome—confirmed the generalizability of this spectrum; revealed a wide variation of atherogenic states within each condition; and allowed identification of metabolites that are associated with the atherogenic state regardless of the particular condition, such as gamma-glutamyl-glutamic acid and homovanillic acid sulfate. The analysis further highlighted metabolic pathways such as catabolism of phenylalanine and tyrosine and biosynthesis of estrogens and phenylpropanoids. Using validation cohorts, we confirmed variation in atherogenic states in healthy subjects (before atherosclerosis plaques become visible), and showed that metabolites associated with the atherogenic state were also associated with future CVD. Conclusion Our results provide a global view of atherosclerosis risk states using plasma metabolomics.