Fibroblast activation protein is dispensable for control of glucose homeostasis and body weight in mice
Bibliographic record
Abstract
Objective Fibroblast Activation Protein (FAP), an enzyme structurally related to dipeptidyl peptidase-4 (DPP-4), has garnered interest as a potential metabolic drug target due to its ability to cleave and inactivate FGF-21 as well as other peptide substrates. Here we investigated the metabolic importance of FAP for control of body weight and glucose homeostasis in regular chow-fed and high fat diet-fed mice. Methods FAP enzyme activity was transiently attenuated using a highly-specific inhibitor CPD60 and permanently ablated by genetic inactivation of the mouse Fap gene. We also assessed the FAP-dependence of CPD60 and talabostat (Val-boroPro), a chemical inhibitor reportedly targeting both FAP and dipeptidyl peptidase-4 Results CPD60 robustly inhibited plasma FAP activity with no effect on DPP-4 activity. Fap gene disruption was confirmed by assessment of genomic DNA, and loss of FAP enzyme activity in plasma and tissues. CPD60 did not improve lipid tolerance but modestly improved acute oral and intraperitoneal glucose tolerance in a FAP-dependent manner. Genetic inactivation of Fap did not improve glucose or lipid tolerance nor confer resistance to weight gain in male or female Fap −/− mice fed regular chow or high-fat diets. Moreover, talabostat markedly improved glucose homeostasis in a FAP- and FGF-21-independent, DPP-4 dependent manner. Conclusion Although pharmacological FAP inhibition improves glucose tolerance, the absence of a metabolic phenotype in Fap −/− mice suggest that endogenous FAP is dispensable for the regulation of murine glucose homeostasis and body weight. These findings highlight the importance of characterizing the specificity and actions of FAP inhibitors in different species and raise important questions about the feasibility of mouse models for targeting FAP as a treatment for diabetes and related metabolic disorders.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".