AIMS: To identify novel risk markers for incident heart failure using proteomic profiling of 80 proteins previously associated with cardiovascular pathology.
METHODS AND RESULTS: Proteomic profiling (proximity extension assay) was performed in two community-based prospective cohorts of elderly individuals without heart failure at baseline: the Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS, n = 901, median age 70.2 (interquartile range 70.0-70.3) years, 80 events]; and the Uppsala Longitudinal Study of Adult Men [ULSAM, n = 685, median age 77.8 (interquartile range 76.9-78.1) years, 90 events]. Twenty-nine proteins were associated with incident heart failure in the discovery cohort PIVUS after adjustment for age and sex, and correction for multiple testing. Eighteen associations replicated in ULSAM. In pooled analysis of both cohorts, higher levels of nine proteins were associated with incident heart failure after adjustment for established risk factors: growth differentiation factor 15 (GDF-15), T-cell immunoglobulin and mucin domain 1 (TIM-1), tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2), spondin-1 (SPON1), matrix metalloproteinase-12 (MMP-12), follistatin (FS), urokinase-type plasminogen activator surface receptor (U-PAR), osteoprotegerin (OPG), and suppression of tumorigenicity 2 (ST2). Of these, GDF-15, U-PAR, MMP-12, TRAIL-R2, SPON1 and FS were associated with worsened echocardiographic left ventricular systolic function at baseline, while only TIM-1 was positively associated with worsened diastolic function (P < 0.02 for all).
CONCLUSION: Proteomic profiling identified several novel associations between proteins involved in apoptosis, inflammation, matrix remodelling, and fibrinolysis with incident heart failure in elderly individuals. Our results encourage additional studies investigating the underlying mechanisms and the clinical utility of our findings.
2018. Vol. 20, no 1, p. 55-62
Biomarkers, Epidemiology, Heart failure, Left ventricular dysfunction, Proteomics, Risk prediction