Lars Lind1, Sölve Elmståhl2, Erik Ingelsson3,4,5. 1. 1 Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden. 2. 2 Division of Geriatric Medicine, Department of Clinical Sciences, Lund University, Malmö University Hospital, Malmö, Sweden. 3. 3 Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California. 4. 4 Stanford Cardiovascular Institute, Stanford University, Stanford, California. 5. 5 Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
Abstract
Background: Although metabolic syndrome (MetS) was described in the late 80s, the molecular mechanisms underlying clustering of risk factors in certain individuals are not fully understood. The present study used targeted proteomics to establish cardiometabolic proteins related to all MetS components, thereby providing new hypotheses regarding pathways involved in the pathogenesis of MetS. Methods: In the EpiHealth study, 249 cardiometabolic proteins were measured by proximity extension assay (PEA) and related to the five MetS components [consensus-modified National Cholesterol Education Program (NCEP) criteria] in 2,444 participants aged 45-75 years (50% women). Results: Thirty-one proteins were associated with systolic blood pressure following adjustment for age and sex (P < 0.000040, taking multiple testing into account). The corresponding number of proteins significantly associated with fasting glucose, waist circumference, high-density lipoprotein cholesterol, and serum triglycerides were 58, 132, 127, and 148. Twenty-two proteins were significantly related to all 5 MetS components, and of those, 20 were with MetS as a binary outcome (n = 600, 24% of the sample) following adjustment for age, sex, fat mass, and lifestyle factors (alcohol intake, smoking, education, and exercise habits). Conclusion: Using targeted proteomics, we identified 20 proteins reflecting a range of pathways, such as immunomodulation at different levels; regulation of adipocyte differentiation; lipid, carbohydrate, and amino acid metabolism; or insulin-like growth factor signaling, to be strongly associated with MetS independently of fat mass and lifestyle factors. Whether some of these proteins are causally involved in the pathogenesis of clustering of multiple risk factors in the same individual remains to be investigated.
Background: Although metabolic syndrome (MetS) was described in the late 80s, the molecular mechanisms underlying clustering of risk factors in certain individuals are not fully understood. The present study used targeted proteomics to establish cardiometabolic proteins related to all MetS components, thereby providing new hypotheses regarding pathways involved in the pathogenesis of MetS. Methods: In the EpiHealth study, 249 cardiometabolic proteins were measured by proximity extension assay (PEA) and related to the five MetS components [consensus-modified National Cholesterol Education Program (NCEP) criteria] in 2,444 participants aged 45-75 years (50% women). Results: Thirty-one proteins were associated with systolic blood pressure following adjustment for age and sex (P < 0.000040, taking multiple testing into account). The corresponding number of proteins significantly associated with fasting glucose, waist circumference, high-density lipoprotein cholesterol, and serum triglycerides were 58, 132, 127, and 148. Twenty-two proteins were significantly related to all 5 MetS components, and of those, 20 were with MetS as a binary outcome (n = 600, 24% of the sample) following adjustment for age, sex, fat mass, and lifestyle factors (alcohol intake, smoking, education, and exercise habits). Conclusion: Using targeted proteomics, we identified 20 proteins reflecting a range of pathways, such as immunomodulation at different levels; regulation of adipocyte differentiation; lipid, carbohydrate, and amino acid metabolism; or insulin-like growth factor signaling, to be strongly associated with MetS independently of fat mass and lifestyle factors. Whether some of these proteins are causally involved in the pathogenesis of clustering of multiple risk factors in the same individual remains to be investigated.
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