The Metabolic Theory of Pulmonary Arterial Hypertension
Bibliographic record
Abstract
Numerous molecular abnormalities have been described in pulmonary arterial hypertension (PAH), complicating the translation of candidate therapies to patients because, typically, 1 treatment addresses only 1 abnormality. The realization that in addition to pulmonary artery vascular cells, other tissues and cells are involved in the syndrome of PAH (eg, immune cells, right ventricular cardiomyocytes, skeletal muscle) further complicates the identification of optimal therapeutic targets. Here, we describe a metabolic theory that proposes that many apparently unrelated molecular abnormalities in PAH do have a common denominator; they either cause or promote a mitochondrial suppression (inhibition of glucose oxidation) in pulmonary vascular cells; in turn, the signaling downstream from this mitochondrial suppression can also explain numerous molecular events previously not connected. This integration of signals upstream and downstream of mitochondria has similarities to cancer and can explain many features of the PAH vascular phenotype, including proliferation and apoptosis resistance. This suppression of glucose oxidation (with secondary upregulation of glycolysis) also underlies the abnormalities in extrapulmonary tissues, suggesting a global metabolic disturbance. The metabolic theory places mitochondria at the center stage for our understanding of PAH pathogenesis and for the development of novel diagnostic and therapeutic tools. Current PAH therapies are each addressing 1 abnormality (eg, upregulation of endothelin-1) and were not developed specifically for PAH but for systemic vascular diseases. Compared with the available therapies, mitochondria-targeting therapies have the advantage of addressing multiple molecular abnormalities simultaneously (thus being potentially more effective) and achieving higher specificity because they address PAH-specific biology.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".