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

The Pharmacogenomics Journal volume 11, pages 162–173 (2011)Cite this article

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Abstract

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 data set. 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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Acknowledgements

Dr Wilke would like to thank Erin MacKinney for assistance in the preparation of this manuscript. This work was funded by R01DK080007, U01HL069757 and U01HG004608.

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  1. Department of Medicine, Vanderbilt University, Nashville, TN, USA

    R A Wilke

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Wilke, R. High-density lipoprotein (HDL) cholesterol: leveraging practice-based biobank cohorts to characterize clinical and genetic predictors of treatment outcome. Pharmacogenomics J 11, 162–173 (2011). https://doi.org/10.1038/tpj.2010.86

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