Critical role of PCYT2 in muscle health and aging
Bibliographic record
Abstract
Abstract Muscle degeneration is the most prevalent cause for frailty and dependency in inherited diseases and ageing, affecting hundreds of millions of people. Elucidation of pathophysiological mechanisms, as well as effective treatments for muscle diseases represents an important goal in improving human health. Here, we show that phosphatidylethanolamine cytidyltransferase (PCYT2/ECT), the critical enzyme of the Kennedy branch of phosphatidylethanolamine (PE) synthesis pathway, has an essential role in muscle health. Human genetic deficiency in PCYT2 causes a severe disease with failure to thrive and progressive muscle weakness. Pcyt2 mutant zebrafish recapitulate the patient phenotypes, indicating that the role of PCYT2/PE in muscle is evolutionary conserved. Muscle specific Pcyt2 knockout mice exhibited failure to thrive, impaired muscle development, progressive muscle weakness, muscle loss, accelerated ageing, and reduced lifespan. Mechanistically, Pcyt2 deficiency affects mitochondrial bioenergetics and physicochemical properties of the myofiber membrane lipid bilayer, in particular under exercise strain. We also show that PCYT2 activity declines in the aging muscles of humans and mice. AAV-based delivery of PCYT2 rescued muscle weakness in Pcyt2 knock-out mice and, importantly, improved muscle strength in old mice, offering a novel therapeutic avenue for rare disease patients and muscle aging. Thus, PCYT2 plays a fundamental, specific, and conserved role in vertebrate muscle health, linking PCYT2 and PCYT2 synthesized PE lipids to severe muscle dystrophy, exercise intolerance and aging.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| 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".