Proteomic diversity of high-density lipoprotein explains its association with clinical outcome in patients with heart failure.

AIMS: Previously, low high-density lipoprotein (HDL) cholesterol was found to be one of the strongest predictors of mortality and/or heart failure (HF) hospitalisation in patients with HF. We therefore performed in-depth investigation of the multifunctional HDL proteome to reveal underlying pathophysiological mechanisms explaining the association between HDL and clinical outcome. METHODS AND RESULTS: We selected a cohort of 90 HF patients with 1:1 cardiovascular death/survivor ratio from BIOSTAT-CHF. A novel optimised protocol for selective enrichment of lipoproteins was used to prepare plasma. Enriched lipoprotein content of samples was analysed using high resolution nanoscale liquid chromatography-mass spectrometry-based proteomics, utilising a label free approach. Within the HDL proteome, 49 proteins significantly differed between deaths and survivors. An optimised model of 12 proteins predicted death with 76% accuracy (Nagelkerke R2 =0.37, P < 0.001). The strongest contributors to this model were filamin-A (related to crosslinking of actin filaments) [odds ratio (OR) 0.31, 95% confidence interval (CI) 0.15-0.61, P = 0.001] and pulmonary surfactant-associated protein B (related to alveolar capillary membrane function) (OR 2.50, 95% CI 1.57-3.98, P < 0.001). The model predicted mortality with an area under the curve of 0.82 (95% CI 0.77-0.87, P < 0.001). Internal cross validation resulted in 73.3 ± 7.2% accuracy. CONCLUSION: This study shows marked differences in composition of the HDL proteome between HF survivors and deaths. The strongest differences were seen in proteins reflecting crosslinking of actin filaments and alveolar capillary membrane function, posing potential pathophysiological mechanisms underlying the association between HDL and clinical outcome in HF.

A systems BIOlogy Study to TAilored Treatment in Chronic Heart Failure: rationale, design, and baseline characteristics of BIOSTAT-CHF.

AIMS: Despite major improvements in pharmacological and device treatments, heart failure remains a syndrome with high morbidity and mortality, poor quality of life, and high health-care costs. Given the extensive heterogeneity among patients with heart failure, substantial differences in the response to therapy can be expected. We hypothesize that individualized therapy is an essential next step to improve outcomes in patients with heart failure. METHODS: The BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) included 2516 patients with worsening signs and/or symptoms of heart failure from 11 European countries, who were considered to be on suboptimal medical treatment. Another 1738 patients from Scotland were included in a validation cohort. Overall, both patient cohorts were well matched. The majority of patients were hospitalized for acute heart failure, and the remainder presented with worsening signs and/or symptoms of heart failure at outpatient clinics. Approximately half of the patients were in New York Heart Association class III, and 7% vs 34% of patients of the index vs validation cohort had heart failure with preserved ejection fraction. According to study design, all patients used diuretics, but owing to the inclusion criteria of both cohorts, patients were not on optimal, evidence-based medical therapy. In the follow-up phase, uptitration to guideline-recommended doses was encouraged. CONCLUSION: By using a novel systems biology approach, incorporating demographics, biomarkers, genome-wide analysis, and proteomics, a model that predicts response to therapy will be developed, which should be instrumental in developing alternative therapies for patients with suboptimal response to currently recommended therapies and thus further improve care for patients with heart failure.