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The combination of 9p21.3 genotype and biomarker profile improves a peripheral artery disease risk prediction model

机译:9p21.3基因型和生物标志物谱的组合改善了外周动脉疾病风险预测模型

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Peripheral artery disease (PAD) is a highly morbid condition affecting more than 8 million Americans. Frequently, PAD patients are unrecognized and therefore do not receive appropriate therapies. Therefore, new methods to identify PAD have been pursued, but have thus far had only modest success. Here we describe a new approach combining genomic and metabolic information to enhance the diagnosis of PAD. We measured the genotype of the chromosome 9p21 cardiovascular-risk polymorphism rs10757269 as well as the biomarkers C-reactive protein, cystatin C, β2-microglobulin, and plasma glucose in a study population of 393 patients undergoing coronary angiography. The rs10757269 allele was associated with PAD status (ankle-brachial index < 0.9) independent of biomarkers and traditional cardiovascular risk factors (odds ratio=1.92; 95% confidence interval, 1.29-2.85). Importantly, compared to a previously validated risk factor-based PAD prediction model, the addition of biomarkers and rs10757269 significantly and incrementally improved PAD risk prediction as assessed by the net reclassification index (NRI=33.5%; p=0.001) and integrated discrimination improvement (IDI=0.016; p=0.017). In conclusion, a model including a panel of biomarkers, which includes both genomic information (which is reflective of heritable risk) and metabolic information (which integrates environmental exposures), predicts the presence or absence of PAD better than established risk models, suggesting clinical utility for the diagnosis of PAD.
机译:周围动脉疾病(PAD)是一种高度病态的疾病,影响了超过800万美国人。通常,PAD患者无法识别,因此无法接受适当的治疗。因此,人们一直在寻求识别PAD的新方法,但迄今为止仅取得了很小的成功。在这里,我们描述了一种结合基因组和代谢信息以增强PAD诊断的新方法。我们在393例接受冠状动脉造影的患者中,测量了9p21染色体具有心血管风险的多态性rs10757269的基因型,以及生物标志物C反应蛋白,胱抑素C,β2-微球蛋白和血浆葡萄糖。 rs10757269等位基因与PAD状态(踝臂指数<0.9)相关,而与生物标志物和传统的心血管危险因素无关(优势比= 1.92; 95%置信区间为1.29-2.85)。重要的是,与先前验证的基于风险因子的PAD预测模型相比,通过净重分类指数(NRI = 33.5%; p = 0.001)和综合辨别力改善评估,添加生物标志物和rs10757269可以显着且逐步改善PAD风险预测。 IDI = 0.016; p = 0.017)。总之,一个包含一组生物标志物的模型比既定的风险模型更好地预测了PAD的存在或不存在,该模型既包含基因组信息(反映遗传风险)又包含代谢信息(整合环境暴露),比建立的风险模型更好用于诊断PAD。

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