The concept of classifying heart failure (HF) according to LVEF is being increasingly challenged and new approaches to phenotyping HF are being sought.
As presented today by Doctor Kayode Kuku (National Heart Lung and Blood Institute - Bethesda, USA), a team of researchers from the US explored the possibility of precision phenotyping, studying the protein signatures of patients with HF to identify proteins associated with mortality.
Proteomic profiles were analysed from plasma specimens collected from 1,388 patients with HF from a community cohort (2003–2012) who were predominantly of European ancestry (92%). The relative concentrations of circulating plasma proteins were measured using an aptamer-based proteomic assay containing 7,335 human protein targets. Proteins significantly associated with mortality were selected, adjusting for age, sex and renal function. Clustering analysis was performed, and multivariable Cox regression was used on the clusters, adjusting for the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score.
Based on 1,158 deaths, a significant association was observed between mortality and the concentrations of 447 proteins – 354 proteins were positively associated and 93 were negatively associated. Using these proteins, two distinct clusters were identified. The hazard ratio for mortality between cluster 2 versus cluster 1 was 2.04 (95% CI 1.78 to 2.34; p<0.0001 independent of MAGGIC). Cluster 1 contained 722 patients with a mean (SD) age of 72 (14) years and 26% had NYHA class IV HF, while cluster 2 contained 666 patients with a mean age of 79 (11) years and 31% had NYHA class IV HF. In total, 41% of patients in both clusters had NYHA class III HF and mean LVEF was similar (cluster 1: 47% ; cluster 2: 48% ).
Gene-set enrichment analysis of the 447 proteins revealed dominant biological domains related to cell adhesion, extracellular matrix organisation, enzyme-linked protein/tyrosine kinase signaling pathways, humoral immune response, tissue development, growth factor signaling, post-translational protein modification and platelet degranulation. Eighteen upstream regulators were identified that were predicted to be driving the expression of the 447 mortality-related proteins, including transforming growth factor-β1, interleukin-1β and oncostatin M.
Analyses such as these provide important mechanistic information that may help to guide individualisation of HF management strategies in the future. Further studies will examine the generalisability of these protein signatures of mortality in HF patients of non-European ancestry as well as in clinical trial participants.