BACKGROUND: The metabolic syndrome (MetS) is associated with increased cardiovascular risk. We evaluated the relative contributions of circulating biomarkers representing distinct biological pathways to the incidence of MetS and to longitudinal changes of its constituent risk factors. METHODS AND RESULTS: We measured 8 circulating biomarkers reflecting inflammation (C-reactive protein), hemostasis (plasminogen activator inhibitor-1, fibrinogen), neurohormonal activity (aldosterone, renin, B-type natriuretic peptide, N-terminal proatrial natriuretic peptide), and endothelial dysfunction (homocysteine) in 2292 Framingham Offspring Study participants (mean age, 57 years; 56% women). We related the biomarker panel to incidence of MetS on follow-up initially and then related biomarkers associated with incident MetS to longitudinal change in its components. On follow-up (mean, 2.9 years), 282 participants (of 1473 participants without prevalent MetS at baseline) developed MetS. After adjustment for clinical risk factors, the biomarker panel was associated with incident MetS (P=0.008). On backward elimination, plasminogen activator inhibitor-1 and aldosterone remained associated with incident MetS (multivariable-adjusted odds ratio per 1-SD increment log marker, 1.31 [P=0.004] and 1.21 [P=0.015], respectively). In multivariable analyses evaluating longitudinal change in MetS components (analyzed as continuous variables), plasminogen activator inhibitor-1 was significantly and positively associated with changes in fasting glucose, systolic blood pressure, and triglycerides (all P<0.05). Serum aldosterone was associated positively with change in systolic blood pressure (P=0.023) and inversely with change in high-density lipoprotein cholesterol (P=0.001). CONCLUSIONS: Higher circulating plasminogen activator inhibitor-1 and aldosterone levels are associated with the development of MetS and with longitudinal change of its components, suggesting that these biomarkers and related pathways play a key role in mediating metabolic risk.
BACKGROUND: The metabolic syndrome (MetS) is associated with increased cardiovascular risk. We evaluated the relative contributions of circulating biomarkers representing distinct biological pathways to the incidence of MetS and to longitudinal changes of its constituent risk factors. METHODS AND RESULTS: We measured 8 circulating biomarkers reflecting inflammation (C-reactive protein), hemostasis (plasminogen activator inhibitor-1, fibrinogen), neurohormonal activity (aldosterone, renin, B-type natriuretic peptide, N-terminal proatrial natriuretic peptide), and endothelial dysfunction (homocysteine) in 2292 Framingham Offspring Study participants (mean age, 57 years; 56% women). We related the biomarker panel to incidence of MetS on follow-up initially and then related biomarkers associated with incident MetS to longitudinal change in its components. On follow-up (mean, 2.9 years), 282 participants (of 1473 participants without prevalent MetS at baseline) developed MetS. After adjustment for clinical risk factors, the biomarker panel was associated with incident MetS (P=0.008). On backward elimination, plasminogen activator inhibitor-1 and aldosterone remained associated with incident MetS (multivariable-adjusted odds ratio per 1-SD increment log marker, 1.31 [P=0.004] and 1.21 [P=0.015], respectively). In multivariable analyses evaluating longitudinal change in MetS components (analyzed as continuous variables), plasminogen activator inhibitor-1 was significantly and positively associated with changes in fasting glucose, systolic blood pressure, and triglycerides (all P<0.05). Serum aldosterone was associated positively with change in systolic blood pressure (P=0.023) and inversely with change in high-density lipoprotein cholesterol (P=0.001). CONCLUSIONS: Higher circulating plasminogen activator inhibitor-1 and aldosterone levels are associated with the development of MetS and with longitudinal change of its components, suggesting that these biomarkers and related pathways play a key role in mediating metabolic risk.
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Authors: J M Luther; P Luo; M T Kreger; M Brissova; C Dai; T T Whitfield; H S Kim; D H Wasserman; A C Powers; N J Brown Journal: Diabetologia Date: 2011-04-26 Impact factor: 10.122
Authors: Véronique L Roger; Alan S Go; Donald M Lloyd-Jones; Emelia J Benjamin; Jarett D Berry; William B Borden; Dawn M Bravata; Shifan Dai; Earl S Ford; Caroline S Fox; Heather J Fullerton; Cathleen Gillespie; Susan M Hailpern; John A Heit; Virginia J Howard; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Diane M Makuc; Gregory M Marcus; Ariane Marelli; David B Matchar; Claudia S Moy; Dariush Mozaffarian; Michael E Mussolino; Graham Nichol; Nina P Paynter; Elsayed Z Soliman; Paul D Sorlie; Nona Sotoodehnia; Tanya N Turan; Salim S Virani; Nathan D Wong; Daniel Woo; Melanie B Turner Journal: Circulation Date: 2011-12-15 Impact factor: 29.690
Authors: Véronique L Roger; Alan S Go; Donald M Lloyd-Jones; Robert J Adams; Jarett D Berry; Todd M Brown; Mercedes R Carnethon; Shifan Dai; Giovanni de Simone; Earl S Ford; Caroline S Fox; Heather J Fullerton; Cathleen Gillespie; Kurt J Greenlund; Susan M Hailpern; John A Heit; P Michael Ho; Virginia J Howard; Brett M Kissela; Steven J Kittner; Daniel T Lackland; Judith H Lichtman; Lynda D Lisabeth; Diane M Makuc; Gregory M Marcus; Ariane Marelli; David B Matchar; Mary M McDermott; James B Meigs; Claudia S Moy; Dariush Mozaffarian; Michael E Mussolino; Graham Nichol; Nina P Paynter; Wayne D Rosamond; Paul D Sorlie; Randall S Stafford; Tanya N Turan; Melanie B Turner; Nathan D Wong; Judith Wylie-Rosett Journal: Circulation Date: 2010-12-15 Impact factor: 29.690
Authors: Andrea Vecchiola; Carlos F Lagos; Cristian A Carvajal; Rene Baudrand; Carlos E Fardella Journal: Curr Hypertens Rep Date: 2016-03 Impact factor: 5.369
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