Quantification of the clinical modifiers impacting high-density lipoprotein cholesterol in the community: Personalized Medicine Research Project.
Quantification of the clinical modifiers impacting high-density lipoprotein cholesterol in the community: Personalized Medicine Research Project.
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DOI：
10.1111/j.1751-7141.2009.00055.x
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发表时间：
2010-01-01
期刊：
影响因子：
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通讯作者：
McCarty, Catherine A
中科院分区：
文献类型：
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作者：
Wilke, Russell A;Berg, Richard L;McCarty, Catherine A
高密度脂蛋白（HDL）胆固醇水平与心血管疾病的发展呈负相关。迄今为止，遗传关联研究仅解释了HDL胆固醇总体变异的一小部分。需要在基于实践的队列中进行进一步研究，将遗传学发现与重要的临床变量（例如，年龄，性别，体重指数，药物使用和临床合并症）放在一起。马什菲尔德诊所个性化医学研究项目数据库是为在基于临床实践的环境中进行大规模遗传流行病学研究而设计的。由于其规模和其独特的实践为基础的设计，该资源将提供足够的统计能力，用于评估已知改变脂质稳态的协变量背景下与HDL胆固醇水平相关的遗传发现。作者报告了新的电子表型分析算法的构建和验证，该算法可用于在此基于实践的资源中模拟个体基线HDL胆固醇水平。由于这些算法是在反映常规临床护理的环境中开发的，因此在基于实践的DNA生物库中使用这些算法的未来遗传研究应有助于在调整已知临床因素后识别具有最佳效应大小的标记物，这些因素有助于社区内HDL胆固醇水平的总体差异。
High-density lipoprotein (HDL) cholesterol levels are inversely correlated with the development of cardiovascular disease. To date, genetic association studies have explained only a small proportion of the overall variance in HDL cholesterol. Further studies are needed, within practice-based cohorts, to place genetic findings into context alongside important clinical variables (eg, age, sex, body mass index, medication use, and clinical comorbidity). The Marshfield Clinic Personalized Medicine Research Project database was designed for large-scale studies of genetic epidemiology in a clinical practice-based setting. Because of its size and its unique practice-based design, this resource will provide adequate statistical power for the assessment of genetic findings related to HDL cholesterol level within the context of covariates known to modify lipid homeostasis. The authors report construction and validation of novel electronic phenotyping algorithms that can be used to model individual baseline HDL cholesterol levels within this practice-based resource. Because these algorithms were developed in a setting that reflects routine clinical care, future genetic studies using these algorithms within practice-based DNA biobanks should facilitate the identification of markers with optimal effect size after adjustment for known clinical factors contributing to the overall variance in HDL cholesterol level within the community.