Alexithymia is associated with reduced vitamin D levels, but not polymorphisms of the vitamin D binding-protein gene
Bibliographic record
Abstract
OBJECTIVE: Alexithymia is a personality trait characterized by difficulties in identifying and describing emotions, which is associated with various psychiatric disorders, including depression and posttraumatic stress disorder (PTSD). Its pathogenesis is incompletely understood but previous studies suggested that genetic as well as metabolic factors, are involved. However, no results on the role of vitamin D and the polymorphisms rs4588 and rs7041 of the vitamin D binding protein (VDBP) have been published so far. METHODS: Serum levels of total 25(OH)D were measured in two general-population samples (total n = 5733) of the Study of Health in Pomerania (SHIP). The Toronto Alexithymia Scale-20 (TAS-20) was applied to measure alexithymia. Study participants were genotyped for rs4588 and rs7041. Linear and logistic regression analyses adjusted for sex, age, waist circumference, physical activity, season and study and, when applicable, for the batch of genotyping and the first three genetic principal components, were performed. In sensitivity analyses, the models were additionally adjusted for depressive symptoms. RESULTS: 25(OH)D levels were negatively associated with TAS-20 scores (β = -0.002; P < 0.001) and alexithymia according to the common cutoff of TAS-20>60 (β = -0.103; P < 0.001). These results remained stable after adjusting for depressive symptoms. The tested genetic polymorphisms were not significantly associated with alexithymia. CONCLUSIONS: Our results suggest that low vitamin D levels may be involved in the pathophysiology of alexithymia. Given that no associations between alexithymia and rs4588 as well as rs7041 were observed, indicates that behavioral or nutritional features of alexithymic subjects could also explain this association.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".