Associations of cathepsins with pulmonary arterial hypertension mediated by circulating metabolites: A Mendelian randomization study
Bibliographic record
Abstract
The correlation between cathepsins and pulmonary arterial hypertension (PAH) is well-established, but the causative link between them remains uncertain. This study aimed to explore the causal role of circulating metabolites mediating cathepsins in PAH using Mendelian randomization (MR). A 2-sample 2-step MR method was used to identify causal relationship between cathepsins and PAH; causal relationship between circulating metabolites and PAH; and mediated effects of these circulating metabolites. GWAS summary statistics on circulating metabolites were from the Canadian longitudinal study on aging cohort, human plasma cathepsins from The INTERVAL study, and PAH from FinnGen version R10. Two-sample MR analyses involving 9 cathepsins (cathepsin B, E, F, G, H, L2, O, S, and Z). Cathepsin S was associated with high risk of PAH (OR: 1.346, 95% CI: 1.039-1.742, P = .024), and positively with circulating metabolite 1-oleoylglycerol (18:1) levels (OR: 1.062, 95% CI: 1.018-1.108, P = .005). Finally, mediation analysis showed evidence of mediated effect of cathepsin S on PAH through 1-oleoylglycerol (18:1) levels (OR: 0.062, CI: 0.0183-0.106) with a mediated proportion of 20.9% of the total effect. This study reveals cathepsin S increases the risk of PAH mediating by circulating metabolite 1-oleoylglycerol (18:1) levels.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".