Proteomics Identify Clinical Phenotypes and Predict Functional Outcomes in Heart Failure With Preserved Ejection Fraction: Insights From VITALITY-HFpEF
Bibliographic record
Abstract
BACKGROUND: Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome that may emerge from overlapping systemic processes associated with comorbidities. We assessed whether unique clusters of circulating proteins are associated with specific clinical characteristics and functional status at baseline and follow-up in a well-phenotyped cohort of patients with HFpEF. METHODS: We evaluated 368 proteins associated with cardiovascular disease and inflammation in prerandomization blood samples from 763 VITALITY-HFpEF (Vericiguat to Improve Physical Functioning in Daily Living Activities of Patients With HFpEF) participants who had a left ventricular ejection fraction ≥45% and a heart failure decompensation event within 6 months. Proteins were clustered, and their associations with clinical characteristics, baseline, and 24-week functional outcomes (Kansas City Cardiomyopathy Questionnaire Physical Limitation Score, 6-minute walk distance [6MWD], and Fried frailty phenotype) were estimated with linear regression. Elastic net regression was used to derive a proteomic summary composite to predict changes in 24-week functional outcomes. RESULTS: Four unique protein clusters were identified, containing 24, 66, 197, and 81 proteins. At baseline, 2 protein clusters with the hub proteins caspase-3 and Dickkopf-related protein 1 were associated with increased frailty, whereas the cluster with tumor necrosis factor receptor 1 as a hub protein was associated with lower Kansas City Cardiomyopathy Questionnaire Physical Limitation Score and shorter 6MWD. By contrast, the cluster with protein C as a hub protein was associated with less frailty and longer a 6MWD. The 24-week increase in 6MWD was negatively correlated with the protein cluster with caspase-3; the protein C cluster was correlated with less frailty at 24 weeks. The baseline proteomic summary composite predicted observed changes in Kansas City Cardiomyopathy Questionnaire Physical Limitation Score and 6MWD at 24 weeks (r=0.42 and 0.30; P <0.001 for both). CONCLUSIONS: Proteomics differentiate specific baseline functional traits associated with HFpEF and may facilitate phenotyping in a heterogeneous disease. These proteins also provide insights into the diverse pathophysiology of HFpEF and which patients may improve functional status during follow-up. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03547583.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".