Analysis of plasma metabolomes from 11 309 subjects in five population-based cohorts.

Plasma metabolomics holds potential for precision medicine, but limited information is available to compare the performance of such methods across multiple cohorts. We compared plasma metabolite profiles after an overnight fast in 11,309 participants of five population-based Swedish cohorts (50-80 years, 52% women). Metabolite profiles were uniformly generated at a core laboratory (Metabolon Inc.) with untargeted liquid chromatography mass spectrometry and a comprehensive reference library. Analysis of a second sample obtained one year later was conducted in a subset. Of 1629 detected metabolites, 1074 (66%) were detected in all cohorts while only 10% were unique to one cohort, most of which were xenobiotics or uncharacterized. The major classes were lipids (28%), xenobiotics (22%), amino acids (14%), and uncharacterized (19%). The most abundant plasma metabolome components were the major dietary fatty acids and amino acids, glucose, lactate and creatinine. Most metabolites displayed a log-normal distribution. Temporal variability was generally similar to clinical chemistry analytes but more pronounced for xenobiotics. Extensive metabolite-metabolite correlations were observed but mainly restricted to within each class. Metabolites were broadly associated with clinical factors, particularly body mass index, sex and renal function. Collectively, our findings inform the conduct and interpretation of metabolite association and precision medicine studies.

Bioactive adrenomedullin for assessment of venous congestion in heart failure.

AIMS: 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). 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 haemodynamic and population-based studies. METHODS AND RESULTS: Normal reference ranges for bio-ADM were derived from a community-based cohort (n = 5060). Correlations with haemodynamic data were explored in a cohort of HF patients undergoing right heart catheterization (n = 346). Mortality and decision cutoffs for bio-ADM was explored in a cohort of patients presenting in the ER with acute dyspnoea (n = 1534), including patients with decompensated HF (n = 570). The normal reference range was 8-39 pg/mL. The area under the receiver operating characteristic curve (AUROC) for discrimination of elevated mean right atrial pressure (mRAP) and pulmonary arterial wedge pressure (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]). Bio-ADM correlated with (mRAP, r = 0.55) while NT-proBNP correlated with PAWP. Finally, a bio-ADM decision cutoff of 39 pg/mL associated with 30 and 90 day mortality and conferred a two-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.

Profiling of the plasma proteome across different stages of human heart failure.

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.