APOE ε4 and the cognitive genetics of multiple sclerosis
Bibliographic record
Abstract
BACKGROUND: Evidence linking APOE to myelin repair, neuronal plasticity, and cerebral inflammatory processes suggests that it may be relevant in multiple sclerosis (MS). The purpose of this study was to determine whether the epsilon4 allele of APOE is associated with cognitive deficits in patients with MS. METHOD: Using a case-control design, 50 patients with MS with the epsilon4 allele (epsilon4+) and 50 epsilon4-negative (epsilon4-) patients with MS were tested using a comprehensive battery of tests evaluating the cognitive domains most often affected in MS. RESULTS: The epsilon4+ and epsilon4- patients with MS were well-matched with respect to demographic variables (age, gender, ethnicity, education, employment status, premorbid IQ) and disease variables (disease course, disease duration, Expanded Disability Status Scale, 25-foot timed walk, 9-hole pegboard test). In addition, the groups were similar in depressive symptoms, in the proportion of patients receiving disease-modifying therapy, and in carriage of the APOE epsilon2 allele. Results showed that none of the 11 cognitive outcome variables differed between epsilon4+ and epsilon4- patients with MS. Cognitive measures were also unrelated to epsilon4 interactions with age and gender. The incidence of overall cognitive dysfunction did not differ between epsilon4+ and epsilon4- groups, nor did failure on any test, and epsilon4 carriage was not a significant predictor of any adverse cognitive outcome. These negative results endured with the exclusion of epsilon2+ subjects from the analyses. CONCLUSION: This study does not support a role for the epsilon4 allele in cognitive dysfunction in multiple sclerosis.
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 | 0.001 | 0.002 |
| 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".