CHD Risk and Metabolomic Profiles of Discordant Lipids

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Project Number: Contact PI / Project Leader: DEMLER, OLGA Title: CHD RISK AND METABOLOMIC PROFILES OF DISCORDANT LIPIDS Awardee Organization: BRIGHAM AND WOMEN'S HOSPITAL Abstract Text: DESCRIPTION (provided by applicant): The primary objective of this proposal is to create a multidisciplinary research and training environment that will provide the candidate, Dr. Olga Demler, with knowledge and experience necessary to launch a successful career as an independent researcher in the statistical analysis of metabolomics data with the focus on lipidomics and cardiovascular outcomes. The training program builds upon the candidate's background in methodological research in biostatistics and risk prediction modelling and is focused on learning lipidomics and advanced statistical techniques that are used in targeted, untargeted and network pathway analyses of metabolomics data. This application is supported by a team of established mentors and by a strong institutional commitment of a leading research hospital which is part of a network of Boston-area universities and institutions with abundant opportunities to learn about cutting edge medical research, and to build cross- disciplinary collaborations. The research goal of this proposal is to define lipid profiles that best predict the risk of coronary heart disease (CHD) and to characterize their metabolomic signatures. Low-density lipoprotein (LDL) particles are a causal biomarker in the development of atherosclerosis and CHD. Yet recent studies reported that there is residual lipid-related risk information beyond standard lipid biomarkers. Dr. Demler will extend the standard lipid panel and use additional lipid parameters such as non-high density lipoprotein cholesterol, apolipoprotein B (apoB), and LDL particle concentration, among others. Of special interest are the individuals with discordant combinations of LDL-C and apoB (e.g. low LDL-C, but higher than expected apoB), a group that has substantially higher CHD risk than those with concordant combination of the two parameters even after controlling for LDL-C level and standard risk factors. First, in the Women's Health Study, Dr. Demler will find the most informative combinations of lipid parameters and discordant lipids that best predict CHD events. She will validate these findings in a more demographically diverse VITAL cohort. Second, Dr. Demler will characterize the metabolomic profiles of lipids and lipid combinations including discordant lipids associated with CHD in the VITAL metabolomic sub-study, using state-of-the-art statistical techniques in untargeted, and network metabolomic analyses. This project leverages the candidate's strong background in risk prediction and combines an outstanding research and training environment with already collected CHD outcomes, lipid measurements, and large-scale metabolomics data, providing a unique opportunity to the candidate to gain skills and experience necessary for her career as an independent researcher in statistical analysis of metabolomics/lipidomics data in cardiovascular diseases. The knowledge gained from this project will increase our understanding of specific metabolic mechanisms that govern the association between wide array of lipid measures and CHD by identifying their underlying metabolic dysregulation. Thus, it will address important public health issues and could provide insight into disease pathogenesis and potential development of therapeutic targets.