Traditional risk factors are not major contributors to the variance in carotid intima-media thickness.
Traditional risk factors are not major contributors to the variance in carotid intima-media thickness.
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DOI：
10.1161/strokeaha.111.000745
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发表时间：
2013-08
期刊：
影响因子：
8.3
通讯作者：
Desvarieux M
中科院分区：
文献类型：
--
作者：
Rundek T;Blanton SH;Bartels S;Dong C;Raval A;Demmer RT;Cabral D;Elkind MS;Sacco RL;Desvarieux M
颈动脉内膜-中膜厚度（cIMT）是过去被广泛接受的亚临床动脉粥样硬化的超声标志物。虽然传统的风险因素可以解释大约50%的斑块负担差异，但它们可能无法解释如此高比例的IMT差异，特别是在无斑块位置测量时。我们的研究目的是确定无法解释传统危险因素的cIMT个体，为未来的环境和基因研究做准备。作为北曼哈顿研究的一部分，1790名无卒中患者（平均年龄69±9岁，60%为女性，61%为西班牙裔，19%为黑人，18%为白人）使用b型颈动脉超声进行cIMT评估。评估多元线性回归模型：(1)纳入预先设定的传统风险因素；(2)纳入不太传统的因素，如炎症生物标志物、脂联素、同型半胱氨酸和肾功能。构建标准化的cIMT残差评分来选择不明原因的cIMT个体。平均总cIMT为0.92±0.09 mm。传统模型解释了11%的cIMT方差。年龄（7%）、男性（3%）、葡萄糖（<1%）、吸烟年数（<1%）和低密度脂蛋白胆固醇（<1%）是显著的影响因素。包含炎症生物标志物的模型解释了cIMT中16%的差异。脂联素是导致cIMT变异的唯一重要因素。我们确定了358例（20%）被调查的危险因素无法解释的cIMT患者。血管危险因素只能解释cIMT的一小部分差异。鉴定不明原因的亚临床动脉粥样硬化的新遗传和环境因素对未来有效预防血管疾病至关重要。
Carotid Intima-Media Thickness (cIMT) was a widely accepted ultrasound marker of subclinical atherosclerosis in the past. Although traditional risk factors may explain approximately 50% of the variance in plaque burden, they may not explain such a high proportion of the variance in IMT, especially when measured in plaque free-locations. We aimed this study to identify individuals with cIMT unexplained by traditional risk factors for future environmental and genetic research. As part of the Northern Manhattan Study, 1,790 stroke-free individuals (mean age 69±9; 60% women; 61% Hispanic, 19% black, 18% white) were assessed for cIMT using B-mode carotid ultrasound. Multiple linear regression models were evaluated: (1) incorporating pre-specified traditional risk factors; and (2) including less traditional factors, such as inflammation biomarkers, adiponectin, homocysteine and kidney function. Standardized cIMT residual scores were constructed to select individuals with unexplained cIMT. Mean total cIMT was 0.92±0.09 mm. The traditional model explained 11% of the variance in cIMT. Age (7%), male sex (3%), glucose (<1%), pack years of smoking (<1%), and LDL-cholesterol (<1%) were significant contributing factors. The model including inflammatory biomarkers explained 16% of the variance in cIMT. Adiponectin was the only additional significant contributor to the variance in cIMT. We identified 358 (20%) individuals with cIMT unexplained by the investigated risk factors. Vascular risk factors explain only a small proportion of variance in cIMT. Identification of novel genetic and environmental factors underlying unexplained subclinical atherosclerosis is of outmost importance for future effective prevention of vascular disease.