Identical twins discordant for multiple sclerosis have a shift in their T-cell receptor repertoires
Bibliographic record
Abstract
CD4 T-cells have an important role in the autoimmune response in multiple sclerosis (MS). We investigate the possibility that a shift occurs in the T-cell receptor (TR) repertoire of identical twins discordant for MS. We compare the CDR3 spectratype distributions of 24 different TR V beta (TRBV) segments in naïve CD4 T-cells from discordant MS twins and from healthy identical twins. We also compare the CDR3 spectratype distributions in unrelated healthy pairs, formed by combining members of different healthy twins, with the CDR3 spectratype distributions in unrelated pairs of MS patients and in unrelated pairs of their apparently healthy cotwins, formed by combining members of different discordant twins. We use the correlation coefficient (r-value) as a measure of similarity of CDR3 spectratypes in each pair, and we test for the significance of the difference between r-values from the different pairs. We observe that the r-value for the CDR3 spectratype distributions among discordant twins differs significantly from the corresponding r-value for the healthy twins for two TRBV segments. Further, the r-values, for both the unrelated MS patient pairs and the unrelated pairs of their apparently healthy cotwins, differ significantly from the r-values for healthy unrelated pairs of individuals. We conclude that both the MS patients and their apparently healthy cotwins have shifts in their CDR3 repertoires. Because we study naïve CD4 T-cells, we postulate that CDR3 repertoire shifts precede MS and predispose to MS, but are unlikely to be sufficient to cause MS.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".