ArticleCardiovascular research2026
Plasma proteomics stratification identifies phospholamban R14del carriers at risk for disease progression.
Article in Cardiovascular research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Phosphoproteomics distinguishes disease-specific mechanisms for human phospholamban cardiomyopathy reversible by RNA therapy.Signal transduction and targeted therapy · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
aimsIncomplete penetrance is common in genetic cardiomyopathy, but poorly understood. Here, we investigate the circulating molecular signature in a cohort of patients with one specific phospholamban (PLN) p.Arg14del (R14del, R14Δ/+) pathogenic variant underlying R14Δ/+ cardiomyopathy and its association with disease variability and progression. METHODS AND
resultsTargeted proteomics, metabolomics, and lipidomics were performed on plasma from 87 R14Δ/+ carriers across the disease spectrum. Unsupervised clustering of plasma proteomics classified R14Δ/+ carriers into clusters, which were evaluated using clinical data, including heart failure (HF) symptoms, echocardiographic parameters, and clinical follow-up. Metabolomics and lipidomics data were integrated. Five clusters of R14Δ/+ carriers were identified based on plasma proteomics (N = 2612 proteins). Clusters 3, 4, and 5 were enriched for higher N-terminal pro-B-type natriuretic peptide levels, and lower left ventricular ejection fraction, compared with Clusters 1 and 2. Ninety-six out of 148 metabolites were differentially expressed across the clusters. Levels of symmetric dimethylarginine, N-acetyl aspartate, cis-aconitic acid, S-adenosyl-L-methionine, acadesine, and succinate were elevated in disease condition Clusters 3, 4, and 5. Levels of energy metabolism-related metabolites (i.e. adenosine triphosphate and nicotinamide) were elevated in Clusters 1, 3, and 4 and correlated strongly with apoptosis markers, indicating ongoing cardiac damage. Clusters 1 and 2 represent seemingly asymptomatic R14Δ/+ carriers with Cluster 1 suspected at risk for cardiac damage due to elevated apoptosis markers. Cluster 3 shows an intermediate phenotype, and Clusters 4 and 5 consist of R14Δ/+ carriers with end-stage HF. Clinical follow-up confirmed Cluster 1 at risk for R14Δ/+ cardiomyopathy progression due to increased adverse events (HF hospitalization, all-cause mortality, or cardiac device implantation).
conclusionMolecular profiling of R14Δ/+ carriers reveals subgroups with very distinct risk profiles. Early markers of cardiac damage suggest that stratification may enable timely identification of high-risk individuals and improve understanding of disease variability.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.