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Heart failure (HF) is a major public health problem characterized by inability of the heart to maintain sufficient output of blood. The systematic characterization of circulating proteins across different stages of HF may provide pathophysiological insights and identify therapeutic targets. Here we report application of aptamer-based proteomics to identify proteins associated with prospective HF incidence in a population-based cohort, implicating modulation of immunological, complement, coagulation, natriuretic and matrix remodeling pathways up to two decades prior to overt disease onset. We observe further divergence of these proteins from the general population in advanced HF, and regression after heart transplantation. By leveraging coronary sinus samples and transcriptomic tools, we describe likely cardiac and specific cellular origins for several of the proteins, including Nt-proBNP, thrombospondin-2, interleukin-18 receptor, gelsolin, and activated C5. Our findings provide a broad perspective on both cardiac and systemic factors associated with HF development., Heart failure is a major health issue worldwide. Here, Egerstedt et al. perform proteomic profiling of human plasma at different stages of heart failure, providing a comprehensive analysis of changes in the plasma proteome during disease progression.

Introduction: The use of medications in the general population has increased over time. Information on active metabolite concentrations for common drugs in the general population is limited. Recent advances in metabolomic technologies have made high-throughput profiling of many active metabolites in large epidemiological cohorts increasingly feasible. Aim: 1. Prospective assessment of the proportion of measurable active metabolite levels of major drugs in the general population using mass spectrometry. 2. Relation of cardiovascular (CV) drugs with inadequate risk factor control and CV disease. Methods: Assessment of CV risk factors by coronary CT angiography and carotid ultrasound imaging in a large prospective cohort of 6,251 individuals randomly selected from the general population in Malmö, Sweden (age 50-64 years). Untargeted metabolomic profiling of fasting plasma was performed by Metabolon, USA in a random subset of 3,986 subjects. Results: Intake of at least one prescribed drug was reported in 1840 subjects (46%). Combination drugs were reported in 249 subjects (6%). The most common drug classes reported were lipid-lowering (n=369, 9% of which most were statins), beta blockers (n=307, 8%), ARB (n=272, 7%), and ACE inhibitors (268, 7%), followed by levothyroxine, CCB, antidepressants, glucocorticoids, PPI, antidiabetic, bronchodilators and diuretics. For major CV drugs, detectable active metabolite levels ranged from 54% (atorvastatin and enalapril) to 96% (metoprolol and metformin). Non-detectable levels of lipid-lowering, antihypertensive, and antidiabetic drugs were associated with higher LDL, cholesterol, BP and glucose, although only antidiabetic drugs were significant (p Conclusion: Our study provides an overview of the distribution of common drugs with detectable levels in a contemporary Swedish population. Pharmacometabolomic profiling revealed that non-measurable levels of common CV drugs were associated with lower risk factor control and non-significant trends towards more atherosclerotic disease by imaging in a substantial number of subjects.

Introduction: Bioactive adrenomedullin (bio-ADM) is a vascular-derived peptide hormone that has emerged as a promising biomarker for assessment of congestion in decompensated heart failure (HF). Hypothesis: We aimed to evaluate diagnostic and prognostic performance of bio-ADM for HF in comparison to amino-terminal pro-B-type natriuretic peptide (NT-proBNP), with decision thresholds derived from invasive hemodynamic and population-based studies. Methods and Results: Normal reference ranges (95% prediction interval) for bio-ADM were derived from a community-based cohort (n=5060): 8-39 pg/mL. In a cohort of HF patients undergoing right heart catheterization (n=346), bio-ADM was correlated with mean right atrial pressure (mRAP, r=0.55) and followed a concordant trajectory to mRAP after heart transplantation. In contrast, NT-proBNP was correlated with pulmonary arterial wedge pressure (PAWP). The area under the receiver operating characteristic curve (AUROC) for discrimination of elevated mRAP and PAWP was 0.74 (95%CI=0.67-0.79) and 0.70 (95%CI=0.64-0.75), respectively, with optimal bio-ADM decision cutoff of 39 pg/mL, concordant with cubic spline analyses. NT-proBNP discriminated PAWP slightly better than mRAP (AUROC 0.73 [95%CI=0.68-0.79] and 0.68 [95%CI=0.61-0.75]). In a cohort of patients presenting with acute dyspnea (n=1534), including patients with decompensated HF (n=570), a bio-ADM decision cutoff of 39 pg/mL was associated with 30- and 90-day mortality and conferred a 2-fold increased odds of HF diagnosis, independently from NT-proBNP. Conclusions: Bio-ADM tracks with mRAP and associates with measures of systemic congestion and with mortality in decompensated HF independently from NT-proBNP. Our findings support utility of bio-ADM as a biomarker of systemic venous congestion in HF and nominate a decision threshold.