Molecular mechanism underlying the impact of vitamin D on disease activity of MS
Bibliographic record
Abstract
OBJECTIVE: Some previous studies suggest modest to strong effects of 25-hydroxyvitamin D (25(OH)D) on multiple sclerosis (MS) activity. The objective of this study was to explore the mechanistic rationale that may explain potential clinical effects of 25(OH)D. METHODS: This study measured serum 25(OH)D levels and global gene expression profiles over a course of up to 2 years in patients starting treatment with interferon beta-1b (IFNB-1b) after a clinically isolated syndrome. MS disease activity was assessed by the number of gadolinium-enhancing lesions present on repeated magnetic resonance imaging (MRIs). RESULTS: The number of gadolinium-enhancing lesions was highly significantly associated with 25(OH)D levels. Conducting various systems-level analyses on the molecular level, multiple lines of evidence indicated that 25(OH)D regulates expression dynamics of a large gene-gene interaction system which primarily regulates immune modulatory processes modulating MS activity. The vitamin D response element was significantly enriched in this system, indicating a direct regulation of this gene interaction network through the vitamin D receptor. With increasing 25(OH)D levels, resulting regulation of this system was associated with a decrease in MS activity. Within the complex network of genes that are regulated by 25(OH)D, well-described targets of IFNB-1b and a regulator of sphingosine-1-phosphate bioavailability were found. The 25(OH)D effects on MS activity were additively enhanced by IFNB-1b. INTERPRETATION: Here, we provide mechanistic evidence that an unbalanced 25(OH)D gene expression system may affect MS activity. Our findings support a potential benefit of monitoring and managing vitamin D levels (e.g., through supplementation) in early MS patients treated with IFN-beta-1b.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".