Expansion of Visceral Adipose Tissue over 12 Months Is Associated with Changes in Leptin and Fibroblast Growth Factor 23 (FGF-23) and Alterations in Vitamin D Metabolism in Patients with ESKD
Bibliographic record
Abstract
Background: Visceral adipose tissue (VAT) is hormonally active. Leptin, produced by adipocytes, is a cytokine-like hormone that is increased with obesity. Leptin stimulates FGF-23 expression in bone and decreases kidney expression of CYP27B1 in leptin-deficient mice.The objective was to examine the relationship between visceral and subcutaneous adipose tissue and changes over 12 months with leptin, FGF-23, and vitamin D metabolism through assessment of vitamin D metabolite (VMR) ratios of 25(OH)2D3 and 1,25(OH)2D3 in patients with ESKD. Methods: Visceral (VAT) and subcutaneous (SAT) adipose tissue cross sectional area (CSA) was assessed by computed tomography at the third lumbar vertebra at baseline and 12 months in hemodialysis patients. Serum vitamin D metabolites were measured by LC-MS/MS and leptin and iFGF-23 were measured by ELISA at baseline and 12 months. Results: There were 28 participants, 61% with diabetes. At baseline, VAT CSA was associated with higher 1,24,25(OH)3D3:1,25(OH)2D3 VMR with (r=0.43, p=0.04) and without (r=0.46, p=0.02) adjustment for iFGF-23. Increase in VAT was significantly associated with increase in leptin (r=0.6, p<0.001) and iFGF-23 (r=0.42, p<0.05), as well as increases in the 25(OH)D3:1,25(OH)2D3 VMR (r=0.5, p<0.05) and 1,24,25(OH)3D3:1,25(OH)2D3 VMR (r=0.5, p<0.05). Participants with an increase in VAT over 12 months (n=17) had significantly greater percent increase in leptin (22.4 [-33.0, 113.3]) and FGF-23 (94.8[26.4,208.9]) compared to those where VAT decreased (n=10) (-54.8 [-58.2, 11.1], p=0.03 for leptin) and -3.0[-31.7, 68.9], p=0.02 for FGF-23. In a linear regression model using log-transformed variables, a 10% increase in the change leptin was associated with a 1.9% increase in the change in FGF-23 (p=0.035) after adjustment for baseline FGF-23 and PTH. In contrast to VAT, SAT CSA was not associated with any VMR at baseline and there was no difference in leptin, FGF-23 or in any VMR between participants who gained SAT versus those where SAT decreased. Conclusion: VAT may contribute to calcitriol deficiency in patients with ESKD. Expanding VAT appears to enhance FGF-23 regulation of vitamin D metabolism possibly mediated by leptin. Funding: Government Support – Non-U.S.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".