GR.2 Obesity and multiple sclerosis severity: a Mendelian randomization study
Bibliographic record
Abstract
Background: Obesity is increasingly implicated in the development of multiple sclerosis (MS), but its effect on disease disability is less well-established. This study aims to investigate the association between obesity and MS severity utilizing Mendelian Randomization (MR). Methods: Employing a two-sample MR setting, we examined the effects of various obesity measures and adiposity distribution metrics on MS severity. Genetic proxies for body mass index (BMI) were selected from a study of 806,834 participants, with MS severity determined from a genetic study of age-related MS severity scores in 12,584 individuals with MS. Results: The main analysis reveals an association between elevated BMI and increased MS severity (P = 0.03). This is supported by a significant effect of whole body fat (P = 0.04), aligning with the hypothesis that obesity exacerbates MS disability. Sensitivity analyses suggest minimal heterogeneity and bias, indicating a potential causal effect. Conclusions: Our findings suggest that obesity adversely influences long-term disability outcomes in MS. The convergence of this genetic evidence with some of the prior observational studies strengthens the argument for a causal relationship between obesity and MS severity. These insights highlight obesity as a potentially modifiable risk factor in managing MS, underscoring the importance of weight management in MS treatment strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".