Familial aggregation of left ventricular geometry and association with parental heart failure: the Framingham Heart Study.

BACKGROUND: Data regarding the familial aggregation of left ventricular (LV) geometry and its relations to parental heart failure (HF) are limited. METHODS AND RESULTS: We evaluated concordance of LV geometry within 1093 nuclear families in 5758 participants of the original (parents) (n=2351) and offspring (n=3407) cohorts of the Framingham Heart Study undergoing routine echocardiography in mid- to late adulthood. LV geometry was categorized based on cohort- and sex-specific 80th percentile cutoffs of LV mass and relative wall thickness (RWT) into normal (both <80th percentile), concentric remodeling (LV mass <80th percentile; RWT >80th percentile), concentric hypertrophy (both >80th percentile), and eccentric hypertrophy (LV mass >80th percentile; RWT <80th percentile). Within nuclear families, LV geometry was concordant among related pairs (parent-child, sibling-sibling) (P=0.0015) but not among unrelated spousal pairs (P=0.60), a finding that remained unchanged after adjusting for clinical covariates known to influence LV remodeling (age, systolic blood pressure, body mass index), excluding individuals with prevalent HF and myocardial infarction, and varying the thresholds for defining LV geometry. The prevalence of abnormal LV geometry was higher in family members of affected individuals, with recurrence risks of 1.4 for concentric remodeling (95% CI, 1.2 to 1.7) and eccentric hypertrophy (95% CI, 1.1 to 1.8) and 3.9 (95% CI, 3.2 to 4.6) for concentric hypertrophy. In a subset of 1497 offspring, we observed an association between parental HF (n=458) and eccentric hypertrophy in offspring (P<0.0001). CONCLUSIONS: Our investigation of a 2-generational community-based sample demonstrates familial aggregation of LV geometry, with the greatest recurrence risk for concentric LV geometry, and establishes an association between eccentric LV geometry and parental HF.

Duke Scholars

Author Michael J Pencina Biostatistics & Bioinformatics, Division of Biostatistics