Finding Genes for Myocardial Infarction and Blood Lipid Levels in a Chinese Sample from Beijing

JI Program: Cardiovascular

Status: Completed

Summary

Myocardial infarction (MI) is the leading cause of death in the United States and the 2nd leading cause of death in China, responsible for 22.5% of deaths in the Chinese population. Despite nearly 2,300 Americans and 25,800 Chinese patients dying of cardiovascular diseases every day, little is known about the etiology of MI. Genome-wide association studies (GWAS) have been proven successful at mapping genomic loci that influence human disease and traits (www.genome.gov/gwastudies), including MI, cardiovascular diseases, and lipid levels. However, for MI, the vast majority of the heritability remains unexplained, due to the lack of complete understanding of the causal variants and genes at known loci. In addition, many additional disease genes were likely not found by the GWAS approach. This study hypothesizes that studying Chinese individuals with MI will test whether the same variants and genes identified in Europeans will also be associated in Asian individuals. Evidence for selection at lipid genes will also be investigated.

Outcomes

  • 8,621 samples from 4 hospitals were collected for genotyping.
  • 3 novel lipid variants present in Asians were identified.
  • New genes involved in blood cholesterol levels were discovered; one of which has already shown to increase risk of fatty liver diseases.

Publications

  1. Tang CS, Zhang H, Cheung CY,…Willer CJ, Gao W. (2015) Exome-wide association analysis reveals novel coding sequence variants associated with lipid traits in Chinese. Nat Commun. 2015;22(6):10206. doi: 10.1038/ ncomms10206.
  2. Lu X, Peloso G, Liu D,…Willer CJ. (2017) Exome chip meta-analysis identifies novel loci and East Asian–specific coding variants contributing to lipid levels and coronary artery disease. Nat. Genet. Dec;49(12):1722-1730. doi: 10.1038/ng.3978. Epub 2017 Oct 30.
  3. Ganesh SK, Chasman DI, Larson MG, Guo X, Verwoert G, Bis JC, Gu X, Smith AV, Yang ML, Zhang Y, Ehret G, Rose LM, Hwang SJ, Papanicolau GJ, Sijbrands EJ, Rice K, Eiriksdottir G, Pihur V, Ridker PM, Vasan RS, Newton-Cheh C; Global Blood Pressure Genetics Consortium, Raffel LJ, Amin N, Rotter JI, Liu K, Launer LJ, Xu M, Caulfield M, Morrison AC, Johnson AD, Vaidya D, Dehghan A, Li G, Bouchard C, Harris TB, Zhang H, Boerwinkle E, Siscovick DS, Gao W, Uitterlinden AG, Rivadeneira F, Hofman A, Willer CJ, Franco OH, Huo Y, Witteman JC, Munroe PB, Gudnason V, Palmas W, van Duijn C, Fornage M, Levy D, Psaty BM, Chakravarti A. Effects of Long-Term Averaging of Quantitative Blood Pressure Traits on the Detection of Genetic Associations. The American Journal of Human Genetics.2014; 95(1),49–65