GDF10 blocks hepatic PPARγ activation to protect against diet-induced liver injury
Bibliographic record
Abstract
Objective Growth differentiation factors (GDFs) and bone-morphogenic proteins (BMPs) are members of the transforming growth factor β (TGFβ) superfamily and are known to play a central role in the growth and differentiation of developing tissues. Accumulating evidence, however, demonstrates that many of these factors, such as BMP-2 and -4, as well as GDF15, also regulate lipid metabolism. GDF10 is a divergent member of the TGFβ superfamily with a unique structure and is abundantly expressed in brain and adipose tissue; it is also secreted by the latter into the circulation. Although previous studies have demonstrated that overexpression of GDF10 reduces adiposity in mice, the role of circulating GDF10 on other tissues known to regulate lipid, like the liver, has not yet been examined. Methods Accordingly, GDF10 −/− mice and age-matched GDF10 +/+ control mice were fed either normal control diet (NCD) or high-fat diet (HFD) for 12 weeks and examined for changes in liver lipid homeostasis. Additional studies were also carried out in primary and immortalized human hepatocytes treated with recombinant human (rh)GDF10. Results Here, we show that circulating GDF10 levels are increased in conditions of diet-induced hepatic steatosis and, in turn, that secreted GDF10 can prevent excessive lipid accumulation in hepatocytes. We also report that GDF10 −/− mice develop an obese phenotype as well as increased liver triglyceride accumulation when fed a NCD. Furthermore, HFD-fed GDF10 −/− mice develop increased steatosis, endoplasmic reticulum (ER) stress, fibrosis, and injury of the liver compared to HFD-fed GDF10 +/+ mice. To explain these observations, studies in cultured hepatocytes led to the observation that GDF10 attenuates nuclear peroxisome proliferator-activated receptor γ (PPARγ) activity; a transcription factor known to induce de novo lipogenesis. Conclusion Our work delineates a hepatoprotective role of GDF10 as an adipokine capable of regulating hepatic lipid levels by blocking de novo lipogenesis to protect against ER stress and liver injury.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".