Vitamin D Receptor Gene Polymorphisms Are Associated with Obesity and Inflammosome Activity
Bibliographic record
Abstract
To explore the mechanisms underlying the suggested role of the vitamin D/vitamin D receptor (VDR) complex in the pathogenesis of obesity we performed genetic and immunologic analyses in obese and non-obese Saudi individuals without other concomitant chronic diseases. Genomic DNA was genotyped for gene single nucleotide polymorphisms (SNPs) of VDR by allelic discrimination in 402 obese (body mass index -BMI≥30 kg/m2) and 489 non-obese (BMI<30 kg/m2) Saudis. Q-PCR analyses were performed using an ABI Prism 7000 Sequence Detection System. The inflammosome pathway was analysed by PCR, cytokines and plasma lipopolysaccaride (LPS) concentrations with ELISA assays. Results showed that the VDR SNPs rs731236 (G) (TaqI) and rs1544410 (T) (Bsm-I) minor allele polymorphisms are significantly more frequent in obese individuals (p = 0.009, β = 0.086 and p = 0.028, β = 0.072, respectively). VDR haplotypes identified are positively (GTA) (p = 0.008, β = 1.560); or negatively (ACC) (p = 0.044, β = 0.766) associated with obesity and higher BMI scores. The GTA "risk" haplotype was characterized by an up-regulation of inflammosome components, a higher production of proinflammatory cytokines (p<0.05) and a lower VDR expression. Plasma LPS concentration was also increased in GTA obese individuals (p<0.05), suggesting an alteration of gut permeability leading to microbial translocation. Data herein indicate that polymorphisms affecting the vitamin D/VDR axis play a role in obesity that is associated with an ongoing degree of inflammation, possibly resulting from alterations of gut permeability and microbial translocation. These results could help the definition of VDR fingerprints that predict an increased risk of developing obesity and might contribute to the identification of novel therapeutic strategies for this metabolic condition.
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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 | 0.000 |
| 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".