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Effect of parental coronary artery disease on adverse effects of the metabolic syndrome and aging on carotid artery intima-media thickness (from the Bogalusa Heart Study)
Authors:Chen Wei  Srinivasan Sathanur R  Xu Jihua  Berenson Gerald S
Affiliation:Tulane Center for Cardiovascular Health and Department of Epidemiology, Tulane University Health Sciences Center, New Orleans, Louisiana, USA.
Abstract:Genetic susceptibility is considered an important predictor of coronary artery disease (CAD) and its risk factors. This study was conducted to assess the hypothesis that parental CAD, a surrogate measure of genetic susceptibility, increases the vulnerability of the arterial wall to adverse effects of the metabolic syndrome and the aging process in asymptomatic young adults. The study cohort consisted of 1,073 black and white subjects (29.1% black, 43.7% male) aged 25 to 44 years. Carotid intima-media thickness (IMT) of the common carotid, carotid bulb, and internal carotid segments was measured using B-mode ultrasound. Subjects with parental CAD had greater composite (average of 3 segments) carotid IMT (0.839 vs 0.802 mm, p = 0.04) and a higher prevalence of the metabolic syndrome (20.7% vs 13.3%, p <0.01) compared with those without such a history. Furthermore, the association of the metabolic syndrome with composite, carotid bulb, and internal carotid IMT was significantly stronger in subjects with parental CAD than those without such a history (p = 0.022, p = 0.032, and p = 0.035 for comparison of slopes, respectively). After adjusting for race, gender, and the metabolic syndrome components, only internal carotid IMT showed significantly more increase with age in subjects with parental CAD compared with those without such a history (regression coefficient: beta = 0.014 vs beta = 0.006, p = 0.010 for comparison of slopes). In conclusion, parental CAD amplifies the adverse effects of the metabolic syndrome and aging on carotid artery IMT, especially internal carotid IMT, in asymptomatic young adults. These findings reinforce the value of using family history of CAD in risk assessment algorithm.
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