Treating Diabetes and Obesity with an FGF21-Mimetic Antibody Activating the βKlotho/FGFR1c Receptor Complex
Bibliographic record
Abstract
Fibroblast growth factor 21 (FGF21) is a distinctive member of the FGF family with potent beneficial effects on lipid, body weight, and glucose metabolism and has attracted considerable interest as a potential therapeutic for treating diabetes and obesity. As an alternative to native FGF21, we have developed a monoclonal antibody, mimAb1, that binds to βKlotho with high affinity and specifically activates signaling from the βKlotho/FGFR1c (FGF receptor 1c) receptor complex. In obese cynomolgus monkeys, injection of mimAb1 led to FGF21-like metabolic effects, including decreases in body weight, plasma insulin, triglycerides, and glucose during tolerance testing. Mice with adipose-selective FGFR1 knockout were refractory to FGF21-induced improvements in glucose metabolism and body weight. These results in obese monkeys (with mimAb1) and in FGFR1 knockout mice (with FGF21) demonstrated the essential role of FGFR1c in FGF21 function and suggest fat as a critical target tissue for the cytokine and antibody. Because mimAb1 depends on βKlotho to activate FGFR1c, it is not expected to induce side effects caused by activating FGFR1c alone. The unexpected finding of an antibody that can activate FGF21-like signaling through cell surface receptors provided preclinical validation for an innovative therapeutic approach to diabetes and obesity.
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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 | 0.001 |
| 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".