Long-Chain Acylcarnitines and Monounsaturated Fatty Acids Discriminate Heart Failure Patients According to Pulmonary Hypertension Status
Bibliographic record
Abstract
Defects in fatty acid (FA) utilization have been well described in group 1 pulmonary hypertension (PH) and in heart failure (HF), yet poorly studied in group 2 PH. This study was to assess whether the metabolomic profile of patients with pulmonary hypertension (PH) due HF, classified as group 2 PH, differs from those without PH. We conducted a proof-of-principle cross-sectional analysis of 60 patients with chronic HF with reduced ejection fraction and 72 healthy controls in which the circulating level of 71 energy-related metabolites was measured using various methods. Echocardiography was used to classify HF patients as noPH-HF (n = 27; mean pulmonary artery pressure [mPAP] 21 mmHg) and PH-HF (n = 33; mPAP 35 mmHg). The profile of circulating metabolites among groups was compared using principal component analysis (PCA), analysis of covariance (ANCOVA), and Pearson’s correlation tests. Patients with noPH-HF and PH-HF were aged 64 ± 11 and 68 ± 10 years, respectively, with baseline left ventricular ejection fractions of 27 ± 7% and 26 ± 7%. Principal component analysis segregated groups, more markedly for PH-HF, with long-chain acylcarnitines, acetylcarnitine, and monounsaturated FA carrying the highest loading scores. After adjustment for age, sex, kidney function, insulin resistance, and N-terminal pro-brain natriuretic peptide (NT-proBNP), 5/15 and 8/15 lipid-related metabolite levels were significantly different from controls in noPH-HF and PH-HF subjects, respectively. All metabolites for which circulating levels interacted between group and NT-proBNP significantly correlated with NT-proBNP in HF-PH, but none with HF-noPH. FA-related metabolites were differently affected in HF with or without PH, and may convey adverse outcomes given their distinct correlation with NT-proBNP in the setting of PH.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".