Abstract 3189: Association of Gene Polymorphisms with Myocardial Infarction Among Men or Women or Among Individuals with or without Conventional Coronary Risk Factors
Objectives: The aim of the study was to assess the genetic risk for myocardial infarction (MI) for men or women independently, or for individuals with or without conventional coronary risk factors separately, and thereby to contribute to the personalized prevention of MI in such individuals.
Methods: The study population comprised 3483 unrelated Japanese individuals (1913 men, 1570 women). The 1192 subjects (926 men, 266 women) with MI and 2291 controls (987 men, 1304 women) either had or did not have conventional coronary risk factors, including hypertension, hypercholesterolemia, and diabetes mellitus. The genotypes for 164 polymorphisms of 137 candidate genes were determined by a method that combines the polymerase chain reaction and sequence-specific oligonucleotide probes with suspension array technology.
Results: Multivariable logistic regression analyses and stepwise forward selection procedures revealed that 10 different polymorphisms were significantly (P < 0.005) associated with MI among men or women or among individuals with or without hypertension, hypercholesterolemia, or diabetes mellitus. The 1018C→T polymorphism in GP1BA, the 804C→A in LTA, and the G→A in AGER were associated with MI for men; the 2445G→A in FABP2, the −108/3G→4G in IPF1, and the −55C→T in UCP3 for women; the 1018C→T in GP1BA, the −108/3G→4G in IPF1, the 677C→T in MTHFR, and G→A in UTS2 for hypertensive individuals; the 2445G→A in FABP2, the −108/3G→4G in IPF1, the 677C→T in MTHFR, the −11377C→G in ACDC, and the A→G in AKAP10 for individuals without hypercholesterolemia; the 2445G→A in FABP2 for diabetic individuals; and the −108/3G→4G in IPF1 for nondiabetic individuals.
Conclusions: Polymorphisms associated with MI may differ among women or men, or among individuals with different coronary risk factors. Stratification of subjects based on sex or conventional coronary risk factors may thus be important in order to achieve personalized prevention of MI with the use of genetic information.