Early adaptive immune activation detected in monozygotic twins with prodromal multiple sclerosis
Bibliographic record
Abstract
Multiple sclerosis (MS) is a disabling disease of the CNS. Inflammatory features of MS include lymphocyte accumulations in the CNS and cerebrospinal fluid (CSF). The preclinical events leading to established MS are still enigmatic. Here we compared gene expression patterns of CSF cells from MS-discordant monozygotic twin pairs. Six "healthy" co-twins, who carry a maximal familial risk for developing MS, showed subclinical neuroinflammation (SCNI) with small MRI lesions. Four of these subjects had oligoclonal bands (OCBs). By single-cell RNA sequencing of 2752 CSF cells, we identified clonally expanded CD8+ T cells, plasmablasts, and, to a lesser extent, CD4+ T cells not only from MS patients but also from subjects with SCNI. In contrast to nonexpanded T cells, clonally expanded T cells showed characteristics of activated tissue-resident memory T (TRM) cells. The TRM-like phenotype was detectable already in cells from SCNI subjects but more pronounced in cells from patients with definite MS. Expanded plasmablast clones were detected only in MS and SCNI subjects with OCBs. Our data provide evidence for very early concomitant activation of 3 components of the adaptive immune system in MS, with a notable contribution of clonally expanded TRM-like CD8+ cells.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".