Family history as a risk factor for early onset myocardial infarction in young women.

ABSTRACT

BACKGROUND: The relation between a family history of heart attack and the occurrence of early myocardial infarction (MI) has not been studied extensively in women. In addition, whether recognized and newly-identified coronary heart disease (CHD) risk factors account for the familial aggregation of these events remains unknown. We therefore examined these questions in a population-based case-control study among female 18- to 44-year-old residents of western Washington State. METHODS AND RESULTS: The patients consisted of 107 women with first acute MI, and the control subjects comprised 526 women similar in age identified from the community and without a history of recognized clinical coronary heart disease or stroke. Trained interviewers used a structured questionnaire to elicit a detailed history of heart attack in first-degree relatives. Information about other known MI risk factors was collected and biochemical measurements performed, and common polymorphisms in various candidate genes were determined. The rate of MI among first-degree relatives of MI cases was twice as high as among first-degree relatives of controls (relative risk, 1.96; 95% confidence interval (CI), 1.46-2.48); this association was present for each familial relationship. Sibling history of MI but not parental history was associated with MI, after controlling for established CHD risk factors. In a subsample of subjects with blood measurements, further adjustment for lipids, lipoproteins and specific genetic risk factors slightly reduced the association with sibling MI history (from odds ratio (OR), 5.17; 95% CI, 1.93-13.85 to OR, 3.97; 95% CI, 0.92-17.17). CONCLUSION: Family history of MI is positively associated with the risk of early MI in women. While the association with parental history of MI is mediated through the clustering of other common risk factors, the association of sibling history of MI with early-onset MI in young women is only partially explained by the clustering of established and newly-identified risk factors.