High-density lipoprotein (HDL) cholesterol: leveraging practice-based biobank cohorts to characterize clinical and genetic predictors of treatment outcome.

High-density lipoprotein (HDL) cholesterol: leveraging practice-based biobank cohorts to characterize clinical and genetic predictors of treatment outcome.
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DOI:
10.1038/tpj.2010.86
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发表时间:
2011-06
期刊:
The pharmacogenomics journal
影响因子:
--
通讯作者:
Wilke RA
Wilke RA
中科院分区:
其他
文献类型:
--
作者:
Wilke RA

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在过去的十年中,大型多中心试验明确地证明,降低低密度脂蛋白(LDL)胆固醇可以减少高危患者的原发和继发心血管事件。然而,即使在最大限度降低低密度脂蛋白的情况下,仍有相当大的心血管风险残留。其中一些风险可以归因于高密度脂蛋白(HDL)胆固醇的变异性。因此,人们对定义高密度脂蛋白动态平衡的决定因素非常感兴趣。风险预测模型的构建基于(1)临床因素,(2)已知的分子决定因素,以及(3)高密度脂蛋白胆固醇水平的遗传结构。然而,到目前为止,还没有一个单一的资源在基于实践的数据集的背景下结合这些因素。最近,一些学术医疗中心已经开始建立DNA生物库,以保护各自电子病历的加密版本。随着这些生物库整合资源,临床社区能够以前所未有的规模描述与血脂相关的治疗结果。
Over the past decade, large multicenter trials have unequivocally demonstrated that decreasing low density lipoprotein (LDL) cholesterol can reduce both primary and secondary cardiovascular events in patients at risk. However, even in the context of maximal LDL lowering, there remains considerable residual cardiovascular risk. Some of this risk can be attributed to variability in high density lipoprotein (HDL) cholesterol. As such, there is tremendous interest in defining determinants of HDL homeostasis. Risk prediction models are being constructed based upon (1) clinical contributors, (2) known molecular determinants, and (3) the genetic architecture underlying HDL cholesterol levels. To date, however, no single resource has combined these factors within the context of a practice-based dataset. Recently, a number of academic medical centers have begun constructing DNA biobanks linked to secure encrypted versions of their respective electronic medical record. As these biobanks combine resources, the clinical community is in a position to characterize lipid-related treatment outcome on an unprecedented scale.
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