Key result
Multiprotein biomarkers improve incident heart failure prediction up to ~11% beyond clinical factors and NT-proBNP.
Why the study?
To identify protein biomarkers of new-onset HF across three independent cohorts and assess whether they improve HF risk prediction compared with clinical risk factors alone.
Does a multiprotein biomarker approach improve the prediction of incident heart failure compared to clinical risk factors and NT-proBNP?
Case-Control (n=2,315)
Yes
Does a multiprotein biomarker approach improve the prediction of incident heart failure compared to clinical risk factors and NT-proBNP?
Effect estimate: C-index increment 11.1% (ARIC), 5.9% (FHS), 7.5% (HOMAGE) (95% CI 7.5-14.7 (ARIC), 2.6-9.2 (FHS), 5.4-9.5 (HOMAGE))
p-value: p=<0.001
A multiprotein biomarker approach significantly improves the prediction of incident heart failure when added to standard clinical risk factors and natriuretic peptides.
Should not yet change clinical HF risk assessment; hypothesis-generating for multiprotein biomarkers pending prospective validation.
Background: We sought to identify protein biomarkers of new-onset heart failure (HF) in 3 independent cohorts (HOMAGE cohort [Heart Omics and Ageing], ARIC study [Atherosclerosis Risk in Communities], and FHS [Framingham Heart Study]) and assess if and to what extent they improve HF risk prediction compared to clinical risk factors alone. Methods: A nested case-control design was used with cases (incident HF) and controls (without HF) matched on age and sex within each cohort. Plasma concentrations of 276 proteins were measured at baseline in ARIC (250 cases/250 controls), FHS (191/191), and HOMAGE cohort (562/871). Results: In single protein analysis, after adjusting for matching variables and clinical risk factors (and correcting for multiple testing), 62 proteins were associated with incident HF in ARIC, 16 in FHS, and 116 in HOMAGE cohort. Proteins associated with incident HF in all cohorts were BNP (brain natriuretic peptide), NT-proBNP (N-terminal pro-B-type natriuretic peptide), eukaryotic translation initiation factor 4E-BP1 (4E-binding protein 1), hepatocyte growth factor (HGF), Gal-9 (galectin-9), TGF-alpha (transforming growth factor alpha), THBS2 (thrombospondin-2), and U-PAR (urokinase plasminogen activator surface receptor). The increment in C -index for incident HF based on a multiprotein biomarker approach, in addition to clinical risk factors and NT-proBNP, was 11.1% (7.5%–14.7%) in ARIC, 5.9% (2.6%–9.2%) in FHS, and 7.5% (5.4%–9.5%) in HOMAGE cohort, all P <0.001), each of which was a larger increase than that for NT-proBNP on top of clinical risk factors. Complex network analysis revealed a number of overrepresented pathways related to inflammation (eg, tumor necrosis factor and interleukin) and remodeling (eg, extracellular matrix and apoptosis). Conclusions: A multiprotein biomarker approach improves prediction of incident HF when added to natriuretic peptides and clinical risk factors.
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Girerd et al. (2023) conducted a case-control in New-onset heart failure (n=2,315). Multiprotein biomarker approach vs. Clinical risk factors and NT-proBNP was evaluated on Increment in C-index for incident heart failure (C-index increment 11.1% (ARIC), 5.9% (FHS), 7.5% (HOMAGE), 95% CI 7.5-14.7 (ARIC), 2.6-9.2 (FHS), 5.4-9.5 (HOMAGE), p=<0.001). A multiprotein biomarker approach improved the C-index for incident heart failure prediction by 5.9% to 11.1% (all P<0.001) when added to clinical risk factors and NT-proBNP.
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