Person:

Cheng, Susan

Background: Currently available screening tools for left ventricular (LV) hypertrophy (LVH) and systolic dysfunction (LVSD) are either expensive (echocardiography) or perform suboptimally (B‐type natriuretic peptide [BNP]). It is unknown whether newer biomarkers are associated with LVH and LVSD and can serve as screening tools. Methods and Results: We studied 2460 Framingham Study participants (mean age 58 years, 57% women) with measurements of biomarkers mirroring cardiac biomechanical stress (soluble ST‐2 [ST2], growth differentiation factor‐15 [GDF‐15] and high‐sensitivity troponin I [hsTnI]) and BNP. We defined LVH as LV mass/height2 ≥the sex‐specific 80th percentile and LVSD as mild/greater impairment of LV ejection fraction (LVEF) or a fractional shortening <0.29. Adjusting for standard risk factors in logistic models, BNP, GDF‐15, and hsTnI were associated with the composite echocardiographic outcome (LVH or LVSD), odds ratios (OR) per SD increment in log‐biomarker 1.29, 1.14, and 1.18 (95% CI: 1.15 to 1.44, 1.004 to 1.28, and 1.06 to 1.31), respectively. The C‐statistic for the composite outcome increased from 0.765 with risk factors to 0.770 adding BNP, to 0.774 adding novel biomarkers. The continuous Net Reclassification Improvement was 0.212 (95% CI: 0.119 to 0.305, P<0.0001) after adding the novel biomarkers to risk factors plus BNP. BNP was associated with LVH and LVSD in multivariable models, whereas GDF‐15 was associated with LVSD (OR 1.41, 95% CI: 1.16 to 1.70), and hsTnI with LVH (OR 1.22, 95% CI: 1.09 to 1.36). ST2 was not significantly associated with any outcome. Conclusions: Our community‐based investigation suggests that cardiac stress biomarkers are associated with LVH and LVSD but may have limited clinical utility as screening tools.

Objective: Metabolic syndrome (MetS) can lead to myocardial fibrosis, diastolic dysfunction and eventual heart failure. We evaluated alterations in myocardial microstructure in people with MetS using a novel algorithm to characterize ultrasonic signal intensity variation. Methods: Among 254 participants without existing cardiovascular disease (mean age 42 ± 11 years, 75% women), there were 162 with MetS, 47 with obesity without MetS, and 45 non-obese controls. Standard echocardiography was performed, and a novel validated computational algorithm was used to investigate myocardial microstructure based on sonographic signal intensity and distribution. We examined the signal intensity coefficient (SIC, left ventricular microstructure). Results: The SIC was significantly higher in people with MetS compared with people with (P<0.001) and without obesity (P=0.04), even after adjustment for age, sex, body mass index, hypertension, diabetes mellitus and triglyceride to HDL cholesterol (TG/HDL) ratio (P<0.05 for all). Clinical correlates of SIC included TG concentrations (r=0.21, P=0.0007) and the TG/HDL ratio (r=0.2, P=0.001). Conclusions: Our findings suggest that preclinical MetS and dyslipidemia in particular, are associated with altered myocardial signal intensity variation. Future studies are needed to determine whether the SIC may help detect subclinical disease in people with metabolic disease, with the ultimate goal of targeting preventive efforts.