PNPLA3 is a triglyceride lipase that mobilizes polyunsaturated fatty acids to facilitate hepatic secretion of large-sized very low-density lipoprotein
Bibliographic record
Abstract
The I148M variant of PNPLA3 is closely associated with hepatic steatosis. Recent evidence indicates that the I148M mutant functions as an inhibitor of PNPLA2/ATGL-mediated lipolysis, leaving the role of wild-type PNPLA3 undefined. Despite showing a triglyceride hydrolase activity in vitro, PNPLA3 has yet to be established as a lipase in vivo. Here, we show that PNPLA3 preferentially hydrolyzes polyunsaturated triglycerides, mobilizing polyunsaturated fatty acids for phospholipid desaturation and enhancing hepatic secretion of triglyceride-rich lipoproteins. Under lipogenic conditions, mice with liver-specific knockout or acute knockdown of PNPLA3 exhibit aggravated liver steatosis and reduced plasma VLDL-triglyceride levels. Similarly, I148M-knockin mice show decreased hepatic triglyceride secretion during lipogenic stimulation. Our results highlight a specific context whereby the wild-type PNPLA3 facilitates the balance between hepatic triglyceride storage and secretion, and suggest the potential contribution of a loss-of-function by the I148M variant to the development of fatty liver disease in humans.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".