Circulating biomarkers predicting longitudinal changes in left ventricular structure and function in a general population

Abstract

Background Serial imaging studies in the general population remain important to evaluate the usefulness of pathophysiologically relevant biomarkers in predicting progression of left ventricular (LV) remodeling and dysfunction. Here, we assessed in a general population whether these circulating biomarkers at baseline predict longitudinal changes in LV structure and function.

Methods and Results In 592 participants (mean age, 50.8 years; 51.4% women; 40.5% hypertensive), we derived echocardiographic indexes reflecting LV structure and function at baseline and after 4.7 years. At baseline, we measured alkaline phosphatase, markers of collagen turnover (procollagen type I, C‐terminal telopeptide, matrix metalloproteinase‐1) and high‐sensitivity cardiac troponin T. We regressed longitudinal changes in LV indexes on baseline biomarker levels and reported standardized effect sizes as a fraction of the standard deviation of LV change. After full adjustment, a decline in LV longitudinal strain (−14.2%) and increase in E/e′ ratio over time (+18.9%; P≤0.019) was associated with higher alkaline phosphatase activity at baseline. Furthermore, longitudinal strain decreased with higher levels of collagen I production and degradation at baseline (procollagen type I, −14.2%; C‐terminal telopeptide, −16.4%; P≤0.029). An increase in E/e′ ratio over time was borderline associated with lower matrix metalloproteinase‐1 (+9.8%) and lower matrix metalloproteinase‐1/tissue inhibitor of metalloproteinase‐1 ratio (+11.9%; P≤0.041). Higher high‐sensitivity cardiac troponin T levels at baseline correlated significantly with an increase in relative wall thickness (+23.1%) and LV mass index (+18.3%) during follow‐up (P≤0.035).

Conclusions We identified a set of biomarkers predicting adverse changes in LV structure and function over time. Circulating biomarkers reflecting LV stiffness, injury, and collagen composition might improve the identification of subjects at risk for subclinical cardiac maladaptation.