Human herpesvirus 7 and the risk of developing multiple sclerosis
Bibliographic record
Abstract
Abstract Epstein–Barr virus is now regarded as the critical risk factor for multiple sclerosis. However, Cytomegalovirus and human herpesvirus 6A have also been associated with altered multiple sclerosis risk, suggesting a multifactorial aetiology. Here, we present the first large-scale study of the association between human herpesvirus 7 and the risk of developing multiple sclerosis. A nested case-control study was performed by crosslinking Swedish registries and biobanks, identifying blood samples from 981 cases who later developed multiple sclerosis and 1278 matched controls. Serological testing was performed with a multiplex immunoassay. The association between viral serostatus and the risk of developing multiple sclerosis was analysed with conditional logistic regression, calculating an odds ratio with 95% confidence interval. Interactions between antibodies against human herpesvirus 7 and the Epstein–Barr virus nuclear antigen 1 regarding multiple sclerosis risk were analysed on the additive scale. Serological evidence of human herpesvirus 7 infection was associated with a higher risk of developing multiple sclerosis: odds ratio = 2.2 (95% confidence interval = 1.8–2.7), P < 0.001. The results remained similar when adjusting for cytomegalovirus, Epstein–Barr virus and human herpesvirus 6A serostatus. Synergistic interactions between human herpesvirus 7 and Epstein–Barr virus nuclear antigen 1 seroreactivity were observed: attributable proportion due to interaction = 0.51 (95% confidence interval = 0.34–0.68). These results suggest that human herpesvirus 7 could be a contributing factor in multiple sclerosis aetiology.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".