Inverse agonism of the FFA4 free fatty acid receptor controls both adipogenesis and mature adipocyte function
Bibliographic record
Abstract
Adipocyte disfunction is an important component of many metabolic disorders and there is a need for pharmacological approaches that can restore normal adipocyte function. The FFA4 receptor is a G protein coupled receptor (GPCR), activated by long chain free fatty acids (FFAs), that controls adipocyte function. Importantly, adipocytes produce FFAs, which may directly activate FFA4 and there is a need to better understand how FFAs produced by adipocytes interact with FFA4 signalling. In this study we have employed human and mouse adipocyte cell models to determine how pharmacological agonism or antagonism of FFA4 affects adipogenesis, lipolysis and glucose uptake. We show that a commonly used FFA4 antagonist, AH7614, is an inverse agonist and that treating adipocytes with this compound suppressed adipogenesis, inhibits glucose uptake and enhances isoprenaline stimulated lipolysis. In contrast, treatment with a synthetic FFA4 agonist, TUG-891, has only modest effects on adipogenesis and lipolysis, while showing no effect on glucose uptake. To explore the mechanism for why AH7614 but not TUG-891 affects adipocyte function, we demonstrate that during adipogenic differentiation sufficient FFAs are released into the culture medium to activate FFA4, suggesting AH7614 inhibits an autocrine feedback loop to suppress adipogenesis. In contrast, during lipolysis experiments, insufficient FFAs were released to activate the receptor, suggesting that AH7614 must enhance lipolysis by either inhibiting ligand independent FFA4 signalling, or FFA signalling that does not require the FFAs to be released from the cell. This study will help establish how FFA4 targeting therapeutics could be used to treat adipocyte dysfunction. • The FFA4 negative allosteric modulator AH7614, is an inverse agonist of constitutive receptor signalling. • Antagonism of FFA4 by AH7614 inhibits adipogenic differentiation in both human and mouse cell models by inhibiting autocrine FFA4 signalling. • Agonism and antagonism of FFA4 negatively and positively regulate lipolysis respectively. • Antagonism of FFA4 with the inverse agonist AH7614 inhibits both insulin dependent and insulin independent glucose uptake in adipocytes.
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 | 0.001 |
| 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 | 0.001 |
| 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".