High levels of LDL cholesterol (LDL-c) and low levels of HDL cholesterol (HDL-c) are independent risk factors for coronary artery disease (CAD). During the mentored phase of this award, we have identified 59 novel regions associated with lipid levels (Teslovich et al., 2010). We are continuing our research to identify novel genes and genetic regions associated with lipid levels through several strategies, several of which are extensions to successful aims from the Mentored Phase of this award. We will continue to test for association in a GWAS framework by testing the most promising 5,000 genetic variants in 100,000 additional samples. We are also involved in the analysis ofthe Exome Sequencing Project of NHLBI which has completed whole exome sequencing of 417 samples, all from the upper or lower 1% tails ofthe LDL-c distribution. Identification of novel, highly disruptive genetic mutations may provide valuable clues about which gene in a potentially large region may be involved in lipid metabolism, a reversal of the typical paradigm to identify common variants in genes that contain rare disruptive mutations for related Mendelian disorders. For the independent phase of this award, experiments designed to understand the functional basis of previously identified genetic signals will be undertaken, including aligning genetic variants that play a role in lipid levels with position of known transcription factor binding sites from publicly-available Chip-Seq data.
The final aim for the independent phase ofthe award is to use information from the 1000 Genomes Project to impute and test ~10 million SNPs for association with lipid levels, catalog associated variants in associated regions and refine signatures of long-range regulatory elements.

Public Health Relevance

The identification of novel genes and functional elements associated with HDL-cholesterol, LDL-cholesterol and triglyceride levels is likely to have a significant impact on our understanding of the mechanisms of heart disease and has the potential to lead to new treatments.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Research Transition Award (R00)
Project #
Application #
Study Section
Special Emphasis Panel (NSS)
Program Officer
Papanicolaou, George
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Michigan Ann Arbor
Biostatistics & Other Math Sci
Schools of Public Health
Ann Arbor
United States
Zip Code
Holmen, Oddgeir L; Zhang, He; Zhou, Wei et al. (2014) No large-effect low-frequency coding variation found for myocardial infarction. Hum Mol Genet 23:4721-8
Holmen, Oddgeir L; Zhang, He; Fan, Yanbo et al. (2014) Systematic evaluation of coding variation identifies a candidate causal variant in TM6SF2 influencing total cholesterol and myocardial infarction risk. Nat Genet 46:345-51
Lange, Leslie A; Hu, Youna; Zhang, He et al. (2014) Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol. Am J Hum Genet 94:233-45
Panagiotou, Orestis A; Willer, Cristen J; Hirschhorn, Joel N et al. (2013) The power of meta-analysis in genome-wide association studies. Annu Rev Genomics Hum Genet 14:441-65
(2013) Discovery and refinement of loci associated with lipid levels. Nat Genet 45:1274-83
(2013) Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nat Genet 45:621-31
Willer, Cristen J; Mohlke, Karen L (2012) Finding genes and variants for lipid levels after genome-wide association analysis. Curr Opin Lipidol 23:98-103