Glucagon-induced PGC-1α4/PPARγ promotes hepatic lipid storage and macrosteatosis in fasting and MASLD
Bibliographic record
Abstract
ABSTRACT The liver plays a central role in regulating the transition between fasting and feeding states, coordinating glycogen breakdown, gluconeogenesis, fatty acid catabolism, and lipid storage. Disruptions in this balance contribute to metabolic disorders, including Metabolic dysfunction Associated Steatotic Liver Disease (MASLD). Here, we identify a novel biological pathway downstream of glucagon that promotes the hepatic lipid accumulation associated with fasting. Using gain- and loss-of-function in vivo and in vitro models, we found that glucagon induces sustained expression of PGC-1α4, promoting lipid uptake and storage in hepatocytes by increasing PPARγ activity. Increased PPARγ/PGC-1α4 promotes hepatic Fsp27/Cidec expression, leading to lipid droplet expansion and triglyceride trapping in liver. Activity of the PPARGC1A alternative promoter and PGC-1α4 expression were higher in livers of patients with MASLD, and PGC-1α4 expression correlated with macrosteatosis. Consistently, persistent expression of hepatic PGC-1α4 in mice fed a western diet promoted macrosteatosis, exacerbated oxidative stress and altered hepatic lipid composition to resemble worsening Metabolic dysfunction Associated Steatohepatitis (MASH) in humans. Our findings demonstrate that glucagon-induced hepatic PGC-1α4/PPARγ activity facilitates efficient uptake and storage of lipids during fasting, but over-activation of this coordinated metabolic pathway leads to lipid accumulation and worsening of steatosis in MASLD.
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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) | 0.001 | 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".