Distinct T Cell Receptor Clonotypes in the Sardinian Population Highlight the Role of Mucosal‐Associated Invariant T Cells and Invariant Natural Killer T Cells in Multiple Sclerosis
Bibliographic record
Abstract
Multiple sclerosis (MS) is a chronic, autoimmune, inflammatory disease of the central nervous system, driven by T-cell mediated immune responses. Studying T-cell receptor (TCR) clonotypes specific to MS in distinct populations can provide insights into disease mechanisms. The Sardinian population, with its unique genetic background resulting from geographical isolation, presents a high-risk cohort for MS research, offering a valuable context for understanding the disease's pathogenesis. We analysed the frequency of unique TCR clonotypes in peripheral blood samples from Sardinian MS patients and healthy controls, focusing on TCRα and TCRβ CDR3 sequences. Clonotypes were functionally annotated for antigen-specific interactions, and hierarchical analysis was performed to identify shared TCR clonotypes between MS patients and healthy controls. A total of 119 TCRβ and 521 TCRα CDR3 clonotypes were significantly more frequent in MS patients compared to healthy controls (p < 0.05). Several TCR-α clonotypes, such as CAVLDSNYQLIW (a MAIT cell clonotype targeting the BST2 antigen) and CAVNTGNQFYF (cross-reactive to multiple antigens, including CMV p65 and BST2), were identified as specific to MS. Shared clonotype analysis revealed the involvement of mucosal-associated invariant T (MAIT) cells and invariant natural killer T (iNKT) cells in MS pathogenesis. Notably, HCV-specific TCR-α clonotypes (NS3-HCV) were significantly increased in MS patients, suggesting a link between infectious disease-related and autoimmune-related clonotypes. No significant differences were observed for other antigens, such as VP22, p65 and BST2. This study identifies distinct TCR clonotypes associated with MS in the Sardinian population, highlighting the role of MAIT and iNKT cells in the disease's pathogenesis. The findings suggest that HCV-specific TCR repertoires may contribute to the development of MS. These results improve our understanding of T-cell mediated immune mechanisms in MS and offer potential targets for therapeutic intervention, particularly within the Sardinian cohort.
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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 | 0.000 |
| 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) | 0.002 | 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".