A ChIP-seq defined genome-wide map of vitamin D receptor binding: Associations with disease and evolution
Bibliographic record
Abstract
Initially thought to play a restricted role in calcium homeostasis, the pleiotropic actions of vitamin D in biology and their clinical significance are only now becoming apparent. However, the mode of action of vitamin D, through its cognate nuclear vitamin D receptor (VDR), and its contribution to diverse disorders, remain poorly understood. We determined VDR binding throughout the human genome using chromatin immunoprecipitation followed by massively parallel DNA sequencing (ChIP-seq). After calcitriol stimulation, we identified 2776 genomic positions occupied by the VDR and 229 genes with significant changes in expression in response to vitamin D. VDR binding sites were significantly enriched near autoimmune and cancer associated genes identified from genome-wide association (GWA) studies. Notable genes with VDR binding included IRF8, associated with MS, and PTPN2 associated with Crohn's disease and T1D. Furthermore, a number of single nucleotide polymorphism associations from GWA were located directly within VDR binding intervals, for example, rs13385731 associated with SLE and rs947474 associated with T1D. We also observed significant enrichment of VDR intervals within regions of positive selection among individuals of Asian and European descent. ChIP-seq determination of transcription factor binding, in combination with GWA data, provides a powerful approach to further understanding the molecular bases of complex diseases.
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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 | 0.001 | 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".