Cardiometabolic Biomarkers and Their Temporal Patterns Predict Poor Outcome in Chronic Heart Failure (Bio-SHiFT Study).

Abstract

Multiple hormonal and metabolic alterations occur in chronic heart failure (CHF), but their proper monitoring during clinically silent progression of CHF remains challenging. Hence, our objective was to explore whether temporal patterns of six emerging cardiometabolic biomarkers predict future adverse clinical events in stable patients with CHF. In 263 patients with CHF, we determined the risk of a composite end point of heart failure hospitalization, cardiac death, left ventricular assist device implantation, and heart transplantation in relation to serially assessed blood biomarker levels and slopes (i.e., rate of biomarker change per year). During 2.2 years of follow-up, we repeatedly measured IGF binding proteins 1, 2, and 7 (IGFBP-1, IGFBP-2, IGFBP-7), adipose fatty acid binding protein 4 (FABP-4), resistin, and chemerin (567 samples in total). Serially measured IGFBP-1, IGFBP-2, IGFBP-7, and FABP-4 levels predicted the end point [univariable hazard ratio (95% CI) per 1-SD increase: 3.34 (2.43 to 4.87), 2.86 (2.10 to 3.92), 2.45 (1.91 to 3.13), and 2.46 (1.88 to 3.24), respectively]. Independently of the biomarkers' levels, their slopes were also strong clinical predictors [per 0.1-SD increase: 1.20 (1.11 to 1.31), 1.27 (1.14 to 1.45), 1.23 (1.11 to 1.37), and 1.27 (1.12 to 1.48)]. All associations persisted after multivariable adjustment for patient baseline characteristics, baseline N-terminal pro-hormone brain natriuretic peptide and cardiac troponin T, and pharmacological treatment during follow-up. The temporal patterns of IGFBP-1, IGFBP-2, IGFBP-7, and adipose FABP-4 predict adverse clinical outcomes during outpatient follow-up of patients with CHF and may be clinically relevant as they could help detect more aggressive CHF forms and assess patient prognosis, as well as ultimately aid in designing more effective biomarker-guided therapy.