Heart failure is a major health problem in western countries with high costs and poor outcome despite advances in therapy. 50% of patients die within 4 years of presentation, and 40% of patients admitted are dead or rehospitalised within 1 year. We searched for biomarkers in plasma that could predict treatment response in patients with heart failure, using bottom-up proteomics (liquid chromatography tandem mass spectrometry).Methods
Heart failure patients were recruited and their treatment with ACE-inhibitors and β–blockers was optimised over 6 months. Major adverse events (death or heart failure hospitalisation) were recorded over the next 24 months. Plasma proteins in 50 patients who responded to standard treatment (responders) were compared to 50 patients who did not respond (non-responders). Plasma samples were pooled, depleted of 14 high abundance proteins and then trypsinised to peptides. Peptides were analysed on 2-dimensional liquid chromatography coupled to electrospray high-definition ion mobility tandem mass spectrometry.Results
220 proteins were similar between responders and non-responders. A further 220 plasma proteins were identified which were over or under-expressed in responders, with 144 up-regulated and 76 down-regulated. Several of these proteins have the potential to become new biomarkers for predicting treatment response in patients with heart failure which are classified according to 5 pathobiological processes in heart failure: (1) Neurohormones: Hepatocyte growth factor like protein and Insulin like growth factor II; (2) Vascular system: Intercellular adhesion molecule 2, Sex hormone binding globulin and Prostaglandin H2 D isomerase; (3) Inflammation: C reactive protein and Mannose binding protein C; (4) Matrix and cellular remodelling: Retinol binding protein 4; (5) Cardio-renal system: Cystatin C.Implications
The discovery of new biomarkers for predicting treatment response in this study will lead to improved understanding of the basis of this response, as well as the development of a more personalised treatment by giving guidance to medical therapy. For example, in heart failure patients with abnormally elevated levels of a marker for matrix and cellular remodelling as Retinol binding protein 4 may benefit from a drug for reducing collagen deposition. In this way, the unnecessary prescription of therapy to non-responders may be avoided and novel therapeutic targets could be identified for design of therapies that may improve outcomes.