Growth/differentiation factor 15 causes TGFβ-activated kinase 1-dependent muscle atrophy in pulmonary arterial hypertension
Bibliographic record
Abstract
INTRODUCTION: Skeletal muscle dysfunction is a clinically important complication of pulmonary arterial hypertension (PAH). Growth/differentiation factor 15 (GDF-15), a prognostic marker in PAH, has been associated with muscle loss in other conditions. We aimed to define the associations of GDF-15 and muscle wasting in PAH, to assess its utility as a biomarker of muscle loss and to investigate its downstream signalling pathway as a therapeutic target. METHODS: GDF-15 levels and measures of muscle size and strength were analysed in the monocrotaline (MCT) rat, Sugen/hypoxia mouse and in 30 patients with PAH. In C2C12 myotubes the downstream targets of GDF-15 were identified. The pathway elucidated was then antagonised in vivo. RESULTS: Circulating GDF-15 levels correlated with tibialis anterior (TA) muscle fibre diameter in the MCT rat (Pearson r=-0.61, p=0.003). In patients with PAH, plasma GDF-15 levels of <564 pg/L predicted those with preserved muscle strength with a sensitivity and specificity of ≥80%. In vitro GDF-15 stimulated an increase in phosphorylation of TGFβ-activated kinase 1 (TAK1). Antagonising TAK1, with 5(Z)-7-oxozeaenol, in vitro and in vivo led to an increase in fibre diameter and a reduction in mRNA expression of atrogin-1 in both C2C12 cells and in the TA of animals who continued to grow. Circulating GDF-15 levels were also reduced in those animals which responded to treatment. CONCLUSIONS: Circulating GDF-15 is a biomarker of muscle loss in PAH that is responsive to treatment. TAK1 inhibition shows promise as a method by which muscle atrophy may be directly prevented in PAH. TRIAL REGISTRATION NUMBER: NCT01847716; Results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".