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Association of genetic variants with myocardial infarction in Japanese individuals with different lipid profiles

Authors:
Tetsuro Yoshida, Kimihiko Kato, Kiyoshi Yokoi, Mitsutoshi Oguri, Sachiro Watanabe, Norifumi Metoki, Hidemi Yoshida, Kei Satoh, Yukitoshi Aoyagi, Yoshinori Nozawa, Yoshiji Yamada

Affiliations:
Department of Cardiovascular Medicine, Inabe General Hospital, Inabe, Japan

Doi:
10.3892/ijmm_00000383

Pages:
607-616

Abstract:

Dyslipidemia is an important risk factor for myocardial infarction (MI). We previously showed that gene polymorphisms associated with MI differed among individuals with different lipid profiles. We further examined whether genetic variants that confer susceptibility to MI might differ among individuals with low or high serum concentrations of triglycerides, high density lipoprotein (HDL)-cholesterol, or low density lipoprotein (LDL)-cholesterol. The study population comprised 5270 Japanese individuals, including 1188 subjects with MI and 4082 controls. The 150 polymorphisms examined in the present study were selected by genome-wide association studies of MI and ischemic stroke with the use of the Affymetrix GeneChip Human Mapping 500K Array Set. The initial Chi-square test revealed that the A↷G polymorphism (rs12632110) of SEMA3F was significantly (false discovery rate <0.05) associated with MI among individuals with high serum HDL-cholesterol or among those with low serum LDL-cholesterol. Subsequent multivariable logistic regression analysis with adjustment for covariates revealed that rs12632110 was significantly (P<0.01) associated with MI in individuals with high serum HDL-cholesterol or with low serum LDL-cholesterol. The genetic variants that confer susceptibility to MI differ among individuals with different lipid profiles, and the genetic component for the development of MI is more apparent in individuals at low-risk (high HDL- and low LDL-cholesterol levels) compared to those at high-risk. Stratification of subjects according to lipid profiles may thus be important for personalized prevention of MI based on genetic information.

International Journal of Molecular Medicine

April 2010
Volume 25 Number 4


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