Venkatesh L Murthy1, Bing Yu2, Wenshuang Wang2, Xiuyan Zhang3, Taryn Alkis2, Alexander R Pico4, Ashish Yeri5, Shilpa N Bhupathiraju6,7, Jan Bressler2, Christie M Ballantyne8, Jane E Freedman9, Jose Ordovas10, Eric Boerwinkle2, Katherine L Tucker3, Ravi Shah5. 1. Frankel Cardiovascular Center, Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor. 2. Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston. 3. Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, Lowell. 4. Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, California. 5. Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston. 6. Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts. 7. Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts. 8. Department of Medicine, Baylor College of Medicine, Houston, Texas. 9. UMass Memorial Heart and Vascular Center, University of Massachusetts Medical School, Worcester. 10. Friedman School of Nutrition Science and Policy, School of Graduate Biomedical Sciences, Tufts University, Boston, Massachusetts.
Abstract
Importance: Cardiometabolic disease is responsible for decreased longevity and poorer cardiovascular outcomes in the modern era. Metabolite profiling provides a specific measure of global metabolic function to examine specific metabolic mechanisms and pathways of cardiometabolic disease beyond its clinical definitions. Objectives: To define a molecular basis for cardiometabolic stress and assess its association with cardiovascular prognosis. Design, Setting, and Participants: A prospective observational cohort study was conducted in a population-based setting across 2 geographically distinct centers (Boston Puerto Rican Health Study [BPRHS], an ongoing study of individuals enrolled between June 1, 2004, and October 31, 2009; and Atherosclerosis Risk in Communities [ARIC] study, whose participants were originally sampled between November 24, 1986, and February 10, 1990, and followed up through December 31, 2017). Participants in the BPRHS were 668 Puerto Rican individuals with metabolite profiling living in Massachusetts, and participants in the ARIC study were 2152 individuals with metabolite profiling and long-term follow-up for mortality and cardiovascular outcomes. Statistical analysis was performed from October 1, 2018, to March 13, 2020. Exposure: The primary exposure was metabolite profiles across both cohorts. Main Outcomes and Measures: Outcomes included associations with multisystem cardiometabolic stress and all-cause mortality and incident coronary heart disease (in the ARIC study). Results: Participants in the BPRHS (N = 668; 491 women; mean [SD] age, 57.0 [7.4] years; mean [SD] body mass index [calculated as weight in kilograms divided by height in meters squared], 32.0 [6.5]) had higher prevalent cardiometabolic risk relative to those in the ARIC study (N = 2152; 599 African American individuals; 1213 women; mean [SD] age, 54.3 [5.7] years; mean [SD] body mass index, 28.0 [5.5]). Multisystem cardiometabolic stress was defined for 668 Puerto Rican individuals in the BPRHS as a multidimensional composite of hypothalamic-adrenal axis activity, sympathetic activation, blood pressure, proatherogenic dyslipidemia, insulin resistance, visceral adiposity, and inflammation. A total of 260 metabolites associated with cardiometabolic stress were identified in the BPRHS, involving known and novel pathways of cardiometabolic disease (eg, amino acid metabolism, oxidative stress, and inflammation). A parsimonious metabolite-based score associated with cardiometabolic stress in the BPRHS was subsequently created; this score was applied to shared metabolites in the ARIC study, demonstrating significant associations with coronary heart disease and all-cause mortality after multivariable adjustment at a 30-year horizon (per SD increase in metabolomic score: hazard ratio, 1.14; 95% CI, 1.00-1.31; P = .045 for coronary heart disease; and hazard ratio, 1.15; 95% CI, 1.07-1.24; P < .001 for all-cause mortality). Conclusions and Relevance: Metabolites associated with cardiometabolic stress identified known and novel pathways of cardiometabolic disease in high-risk, community-based cohorts and were associated with coronary heart disease and survival at a 30-year time horizon. These results underscore the shared molecular pathophysiology of metabolic dysfunction, cardiovascular disease, and longevity and suggest pathways for modification to improve prognosis across all linked conditions.
Importance: Cardiometabolic disease is responsible for decreased longevity and poorer cardiovascular outcomes in the modern era. Metabolite profiling provides a specific measure of global metabolic function to examine specific metabolic mechanisms and pathways of cardiometabolic disease beyond its clinical definitions. Objectives: To define a molecular basis for cardiometabolic stress and assess its association with cardiovascular prognosis. Design, Setting, and Participants: A prospective observational cohort study was conducted in a population-based setting across 2 geographically distinct centers (Boston Puerto Rican Health Study [BPRHS], an ongoing study of individuals enrolled between June 1, 2004, and October 31, 2009; and Atherosclerosis Risk in Communities [ARIC] study, whose participants were originally sampled between November 24, 1986, and February 10, 1990, and followed up through December 31, 2017). Participants in the BPRHS were 668 Puerto Rican individuals with metabolite profiling living in Massachusetts, and participants in the ARIC study were 2152 individuals with metabolite profiling and long-term follow-up for mortality and cardiovascular outcomes. Statistical analysis was performed from October 1, 2018, to March 13, 2020. Exposure: The primary exposure was metabolite profiles across both cohorts. Main Outcomes and Measures: Outcomes included associations with multisystem cardiometabolic stress and all-cause mortality and incident coronary heart disease (in the ARIC study). Results: Participants in the BPRHS (N = 668; 491 women; mean [SD] age, 57.0 [7.4] years; mean [SD] body mass index [calculated as weight in kilograms divided by height in meters squared], 32.0 [6.5]) had higher prevalent cardiometabolic risk relative to those in the ARIC study (N = 2152; 599 African American individuals; 1213 women; mean [SD] age, 54.3 [5.7] years; mean [SD] body mass index, 28.0 [5.5]). Multisystem cardiometabolic stress was defined for 668 Puerto Rican individuals in the BPRHS as a multidimensional composite of hypothalamic-adrenal axis activity, sympathetic activation, blood pressure, proatherogenic dyslipidemia, insulin resistance, visceral adiposity, and inflammation. A total of 260 metabolites associated with cardiometabolic stress were identified in the BPRHS, involving known and novel pathways of cardiometabolic disease (eg, amino acid metabolism, oxidative stress, and inflammation). A parsimonious metabolite-based score associated with cardiometabolic stress in the BPRHS was subsequently created; this score was applied to shared metabolites in the ARIC study, demonstrating significant associations with coronary heart disease and all-cause mortality after multivariable adjustment at a 30-year horizon (per SD increase in metabolomic score: hazard ratio, 1.14; 95% CI, 1.00-1.31; P = .045 for coronary heart disease; and hazard ratio, 1.15; 95% CI, 1.07-1.24; P < .001 for all-cause mortality). Conclusions and Relevance: Metabolites associated with cardiometabolic stress identified known and novel pathways of cardiometabolic disease in high-risk, community-based cohorts and were associated with coronary heart disease and survival at a 30-year time horizon. These results underscore the shared molecular pathophysiology of metabolic dysfunction, cardiovascular disease, and longevity and suggest pathways for modification to improve prognosis across all linked conditions.
Authors: Kyae Hyung Kim; Seulggie Choi; Kyuwoong Kim; Jooyoung Chang; Sung Min Kim; Seong Rae Kim; Yoosun Cho; Yun Hwan Oh; Gyeongsil Lee; Joung Sik Son; Sang Min Park Journal: Breast Cancer Res Treat Date: 2021-02-18 Impact factor: 4.872