Authors: F D Santiago R T Nakamura D Kaplan E C de Faria
Publish Date: 2009/10/30
Volume: 26, Issue: 1, Pages: 27-34
Abstract
To determine whether hyperalphalipoproteinemia modifies carotid intimamedia thickness cIMT and/or influences the relationship of clinical and biochemical parameters with cIMT This study was conducted on 169 asymptomatic individuals classified as hyperalphalipoproteinemic HyperA HyperA n = 71 HDLC ≥68 mg/dL and controls CTL CTL n = 98 HDLC 32 and 68 mg/dL Enzymatic nephelometric and ultracentrifugation methods were used for biochemical determinations Hepatic lipase HL lipoprotein lipase LPL cholesteryl ester transfer protein CETP and phospholipids transfer protein PLTP activities were measured by radiometric exogenous methods The prevalence of dyslipidemia hypertension smoking sedentariness postmenopausal women coronary artery disease CAD and familial history of CAD were determined High resolution βmode carotid ultrassonography was performed The HyperA group was older and had higher frequencies of hypercholesterolemia 40 hypertension 31 sedentariness 37 and postmenopausal women 1 In HyperA individuals the mean cIMT after adjustment for age and gender was similar between the groups 085 ± 024 mm HyperA versus 069 ± 017 mm CTL In multivariate models age was a significant predictor of cIMT in HyperA R 2 = 004 p ≤ 0001 independently of other clinical or biochemical factors In contrast to CTL where age R 2 = 063 p ≤ 0001 male sex R 2 = 003 p ≤ 0001 blood pressure R 2 = 0006 p ≤ 0001 and HDLC R 2 = 002 p 0022 accounted for the cIMT variations Despite an increased prevalence of cardiovascular risk factors in HyperA and resistance of carotid thickness to modulation by metabolic and anthropometric factors except age the similarity in cIMT between HyperA and healthy individuals emphasizes the atheroprotective effects of HDLThis work forms part of the master thesis of Fernanda Dutra Santiago and supported in part by grants from the Fundação de Amparo a Pesquisa de São Paulo FAPESP and Conselho Nacional de Desenvolvimento Científico e Tecnológico CNPq We thank Miriam Danelon for the excellent technical work and Helymar Machado for statistical support
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