Fibroblast Growth Factor 23 Regulation by Systemic and Local Osteoblast-Synthesized 1,25-Dihydroxyvitamin D
Bibliographic record
Abstract
Circulating levels of fibroblast growth factor 23 (FGF23) increase during the early stages of kidney disease, but the underlying mechanism remains incompletely characterized. We investigated the role of vitamin D metabolites in regulating intact FGF23 production in genetically modified mice without and with adenine-induced uremia. Exogenous calcitriol (1,25-dihydroxyvitamin D) and high circulating levels of calcidiol (25-hydroxyvitamin D) each increased serum FGF23 levels in wild-type mice and in mice with global deficiency of the Cyp27b1 gene encoding 25-hydroxyvitamin D 1-α-hydroxylase, which produces 1,25-hydroxyvitamin D. Compared with wild-type mice, normal, or uremic mice lacking Cyp27b1 had lower levels of serum FGF23, despite having high concentrations of parathyroid hormone, but administration of exogenous 1,25-dihydroxyvitamin D increased FGF23 levels. Furthermore, raising serum calcium levels in Cyp27b1-depleted mice directly increased FGF23 levels and indirectly enhanced the action of ambient vitamin D metabolites via the vitamin D receptor. In chromatin immunoprecipitation assays, 25-hydroxyvitamin D promoted binding of the vitamin D receptor and retinoid X receptor to the promoters of osteoblastic target genes. Conditional osteoblastic deletion of Cyp27b1 caused lower serum FGF23 levels, despite normal circulating levels of vitamin D metabolites. In adenine-induced uremia, only a modest increase in serum FGF23 levels occurred in mice with osteoblastic deletion of Cyp27b1 (12-fold) compared with a large increase (58-fold) in wild-type mice. Therefore, in addition to the direct effect of high circulating concentrations of 25-hydroxyvitamin D, local osteoblastic conversion of 25-hydroxyvitamin D to 1,25-dihydroxyvitamin D appears to be an important positive regulator of FGF23 production, particularly in uremia.
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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".