Johns Hopkins Ciccarone Center for the Prevention of Heart Disease, Johns Hopkins Medicine, Baltimore, Maryland.
Clin Cardiol. 2013 Nov;36(11):641-8. doi: 10.1002/clc.22214. Epub 2013 Oct 1.
Blood lipids have major cardiovascular and public health implications. Lipid-lowering drugs are prescribed based in part on categorization of patients into normal or abnormal lipid metabolism, yet relatively little emphasis has been placed on: (1) the accuracy of current lipid measures used in clinical practice, (2) the reliability of current categorizations of dyslipidemia states, and (3) the relationship of advanced lipid characterization to other cardiovascular disease biomarkers. To these ends, we developed the Very Large Database of Lipids (NCT01698489), an ongoing database protocol that harnesses deidentified data from the daily operations of a commercial lipid laboratory. The database includes individuals who were referred for clinical purposes for a Vertical Auto Profile (Atherotech Inc., Birmingham, AL), which directly measures cholesterol concentrations of low-density lipoprotein, very low-density lipoprotein, intermediate-density lipoprotein, high-density lipoprotein, their subclasses, and lipoprotein(a). Individual Very Large Database of Lipids studies, ranging from studies of measurement accuracy, to dyslipidemia categorization, to biomarker associations, to characterization of rare lipid disorders, are investigator-initiated and utilize peer-reviewed statistical analysis plans to address a priori hypotheses/aims. In the first database harvest (Very Large Database of Lipids 1.0) from 2009 to 2011, there were 1 340 614 adult and 10 294 pediatric patients; the adult sample had a median age of 59 years (interquartile range, 49-70 years) with even representation by sex. Lipid distributions closely matched those from the population-representative National Health and Nutrition Examination Survey. The second harvest of the database (Very Large Database of Lipids 2.0) is underway. Overall, the Very Large Database of Lipids database provides an opportunity for collaboration and new knowledge generation through careful examination of granular lipid data on a large scale.
血脂对心血管和公众健康有重大影响。降脂药物的使用部分基于患者血脂代谢正常或异常的分类，但相对较少强调：（1）临床实践中使用的当前血脂测量的准确性，（2）当前血脂异常状态分类的可靠性，以及（3）先进的脂质特征与其他心血管疾病生物标志物的关系。为此，我们开发了非常大的脂质数据库（NCT01698489），这是一个正在进行的数据库方案，利用商业脂质实验室日常运营中的匿名数据。该数据库包括因临床目的而被转介的个体，用于垂直自动分析（Atherotech Inc.，阿拉巴马州伯明翰），该分析直接测量低密度脂蛋白、极低密度脂蛋白、中间密度脂蛋白、高密度脂蛋白及其亚类和脂蛋白（a）的胆固醇浓度。非常大的脂质数据库研究范围从测量准确性研究、血脂异常分类研究、生物标志物关联研究到罕见脂质疾病特征研究，均由研究者发起，并利用经过同行评审的统计分析计划来解决事先假设/目的。在 2009 年至 2011 年的第一个数据库收获（非常大的脂质数据库 1.0）中，有 1340614 名成年和 10294 名儿科患者；成年样本的中位年龄为 59 岁（四分位距，49-70 岁），性别分布均匀。脂质分布与代表性人群的国家健康和营养检查调查非常吻合。数据库的第二次收获（非常大的脂质数据库 2.0）正在进行中。总体而言，非常大的脂质数据库数据库通过仔细检查大规模的粒度脂质数据，为协作和新知识的产生提供了机会。
