Peyser, Patricia A.

Background— Obesity is associated with coronary artery calcification (CAC), a marker of the presence and extent of subclinical coronary atherosclerosis. Obesity adds incremental information in identifying those at higher risk of coronary heart disease to traditional risk factor assessment. The present study examined associations between obesity measures and progression of CAC in those at higher (≥10%) and lower (<10%) 10-year coronary heart disease risk according to the Framingham risk equation. Methods and Results— In this study, 443 asymptomatic white individuals >30 years of age (243 men) had baseline and follow-up CAC measurements an average of 8.9 years apart. Multivariable linear regression models were fit to determine associations of obesity measures at baseline with progression of CAC defined as log e of the difference between follow-up and baseline CAC area plus 1 divided by time (in years) between examinations, adjusting for baseline CAC quantity, age, sex, baseline hypertension status, and baseline cholesterol level. Among 329 participants (74.3%) in the lower-risk group, waist circumference ( P =0.024), waist-to-hip ratio ( P <0.001), body mass index ( P =0.036), and being overweight compared with being underweight or of normal weight ( P =0.008) were each significantly positively associated with progression of CAC. Among those at higher coronary heart disease risk, no baseline obesity measures were associated with CAC progression. Conclusions— Various measures of obesity were associated with increased progression of CAC in those at lower risk of coronary heart disease. Future studies examining the effectiveness of weight reduction strategies in reducing CAC progression among those with an otherwise favorable risk factor profile may be warranted.

Background— Electron-beam computed tomography (EBCT) is used to measure coronary calcification but not for aortic valve calcification (AVC). Its accuracy, association with aortic stenosis (AS) severity, and diagnostic and prognostic value with respect to AVC are unknown. Methods and Results— In 30 explanted aortic valves, the AVC score by EBCT (1125±1294 Agatston units [AU]) showed a strong linear correlation ( r =0.96, P <0.0001) with valvular calcium weight (653±748 mg) by pathology that allowed estimation of calcium weight as AVC score/1.7, with a small standard error of the estimate (53 mg). In 100 consecutive clinical patients, we measured AVC by EBCT and AS severity by echocardiographic aortic valve area (AVA). The AVC score was 1316±1749 AU (range 0 to 7226 AU). Intraobserver and interobserver variabilities were excellent (4±4% and 4±10%, respectively). AVC and AVA were strongly associated ( r =0.79, P <0.0001) but had a curvilinear relationship that suggested that AVC and AVA provide complementary information. AVC score ≥1100 AU provided 93% sensitivity and 82% specificity for diagnosis of severe AS (AVA <1 cm 2 ), with a receiver operator characteristic curve area of 0.89. AVC assessment by echocardiography was often more severe than by EBCT ( P <0.0001). During follow-up, 22 patients either died, developed heart failure, or required surgery. With adjustment for age, sex, symptoms, ejection fraction, and AVA, the AVC score was independently predictive of event-free survival (risk ratio 1.06 per 100-AU increment [1.02 to 1.10], P <0.001), even after adjustment for echocardiographic calcifications. Conclusions— AVC is accurately and reproducibly measured by EBCT and shows a strong association and diagnostic value for severe AS. The curvilinear relationship between AVC and AVA suggests these measures are complementary, and indeed, AVC provides independent outcome information. Thus, AVC is an important measurement in the evaluation of patients with AS.

Abstract— Coronary artery disease (CAD) is the leading cause of mortality in the developed world. Although several CAD risk factors, including measures of lipid metabolism, obesity, and blood pressure, have a genetic basis, many genes for CAD susceptibility have yet to be identified. Coronary atherosclerosis is the major cause of CAD, but many with coronary atherosclerosis lack symptoms. Thus, a major limitation of using symptomatic CAD endpoints (eg, sudden coronary death, myocardial infarction) as a study outcome is substantial disease misclassification. Coronary artery calcification (CAC) is part of the atherosclerotic process and is an independent predictor of CAD endpoints. In the present study, CAC was noninvasively quantified by electron beam computed tomography. We performed genome-wide multipoint mode-of-inheritance-free linkage analysis on affected sib pairs, defined as being ≥ the 70th sex- and age-specific percentile for CAC quantity, in a sample of 29 families enriched for hypertension. Almost 95% of participants were asymptomatic for CAD. Our LOD score (log 10 odds in favor of linkage) results provide evidence that chromosomal regions 6p21.3 (maximum LOD score=2.22, P =0.00070) and 10q21.3 (maximum LOD score=3.24, P =0.000057) may harbor genes associated with subclinical coronary atherosclerosis.

Background — Electron beam computed tomography is an accurate, noninvasive method to detect and quantify coronary artery calcification (CAC), a marker of subclinical and clinical coronary artery atherosclerosis. CAC quantity predicts future coronary artery disease end points in asymptomatic adults, but measured risk factors explain less than half the variability in CAC quantity. Although several candidate genes for CAC have been identified, the relative importance of genetic influences on CAC quantity has not been assessed in asymptomatic adults in a community. Methods and Results — We quantified the relative contributions of measured risk factors and genetic influences on CAC quantity measured by electron beam computed tomography in 698 asymptomatic white adults from 302 families. Before adjusting for any risk factors, 43.5% of the variation in CAC quantity was attributable to genetic factors ( P =0.0007). Independent predictors of CAC quantity were identified with stepwise linear regression. After adjusting for these risk factors, including age, sex, fasting glucose level, systolic blood pressure, pack-years of smoking, and LDL cholesterol, 41.8% of the residual variation in CAC quantity was attributable to genetic factors ( P =0.0003). Conclusions — These results demonstrate the importance of genetic factors in subclinical coronary atherosclerosis variation as measured by CAC quantity. The presence of genetic effects suggests that unknown genes that influence CAC quantity are yet to be identified.