# T-cell repertoire correlates with cytokine imbalance in multiple sclerosis patients

**Authors:** Lisa Weidner, Rodolphe Poupardin, Tobias Zrzavy, Sandra Laner-Plamberger, Georg Gratz, Tanja Eichhorn, Viktoria Weber, Paulus S. Rommer, Christof Jungbauer, Dirk Strunk

PMC · DOI: 10.3389/fimmu.2025.1604452 · Frontiers in Immunology · 2025-07-01

## TL;DR

This study links T-cell diversity and cytokine imbalances in MS patients, suggesting immune patterns, not single proteins, may be key for future diagnostics.

## Contribution

The study integrates TCR repertoire analysis with cytokine profiling to reveal immune response networks in MS.

## Key findings

- MS patients showed elevated MIP-1α and IP-10 in cerebrospinal fluid and 36 blood cytokines.
- TCR sequencing revealed more productive rearrangements in MS cerebrospinal fluid and higher shared clone recovery in blood.
- A Th1-biased immune response was associated with T-cell clonal expansions targeting infectious agents like EBV and CMV.

## Abstract

Multiple sclerosis (MS) is mediated by innate and adaptive immune response deviation involving immune cells and cytokines. Here, we investigated whether combined cytokine profiling and T-cell receptor (TCR) repertoire analysis can better display the complex landscape of MS-driving immune responses.

We used advanced computational methods to systematically cluster highly variable individual levels of 48 cytokines in cerebrospinal fluid (CSF) and blood of 24 MS patients compared to that of nine controls. Relevant TCR sequences were compared to 88 healthy controls. We correlated cytokines with predominant shared TCR sequences to identify immune response networks.

MS patients had significantly elevated MIP-1α and IP-10 levels in CSF, and additional 36 blood cytokines variably but significantly elevated. We identified 77 predominantly pro-inflammatory cytokine correlations in MS-CSF. TCR sequencing revealed more productive rearrangements in CSF of MS and a significantly higher shared clone recovery rate in blood. We found significant associations involving 492 unique sequences and 34 cytokines in blood. Particularly, the less significant individual cytokine deviations were found to contribute to a general Th1-biased type I immune response correlating with clonal expansion of T cells directed against EBV, CMV, and other infectious agents.

Correlation of significantly altered T-cell repertoire with cytokine deviations in MS despite individual patient data variability indicates that future diagnostic strategies may need to address immune response patterns rather than individual protein targets.

Correlation of cytokine profile and T-cell receptor (TCR) repertoire in cerebrospinal fluid (CSF) and blood of multiple sclerosis (MS) patients compared to that in control patients. Differential expression in MS (arrow up for IP-10 and MIP-1α) and selected significant correlation pattern (adjusted p < 0.05) found between different cytokines (color-coded rings): positive (pink) and negative correlations (light blue). The integrative analysis in this study revealed a pro-inflammatory cytokine signature, predominantly driven by type I immunity and Th1-related cytokines (e.g., IFN-γ and TNF-β), with significant correlation between specific TCR sequences (directed against infectious targets) and cytokine levels, primarily in blood, with just limited overlap to CSF. Cytokine-TCR interactions are considered to extend across the altered blood-brain barrier.

Visualization depicts the relationship between blood and cerebrospinal fluid (CSF) in multiple sclerosis (MS) versus control patients. It includes TCR sequences, cytokine networks, and McPAS targets. The upper section shows a Venn diagram of TCR clones shared between blood and CSF alongside graphs with TCR sequences and CSF cytokines for MS and controls. The lower section highlights cytokine interactions, T-cell receptors, and McPAS targets. Arrows indicate positive and negative correlations, specific to MS patients. Chemokines and growth factors are also marked. The diagram emphasizes MS’s pro-inflammatory cytokine signature, increasing blood-brain barrier permeability.

## Linked entities

- **Proteins:** CCL3 (C-C motif chemokine ligand 3), CXCL10 (C-X-C motif chemokine ligand 10), IFNG (interferon gamma), LTA (lymphotoxin alpha)
- **Diseases:** multiple sclerosis (MONDO:0005301)

## Full-text entities

- **Genes:** CCL3 (C-C motif chemokine ligand 3) [NCBI Gene 6348] {aka G0S19-1, LD78, LD78ALPHA, MIP-1-alpha, MIP1A, SCI}, TRBV20OR9-2 (T cell receptor beta variable 20/OR9-2 (non-functional)) [NCBI Gene 6962] {aka CDR3, TCRBV20S2, TCRBV2O, TCRBV2S2O}, CXCL10 (C-X-C motif chemokine ligand 10) [NCBI Gene 3627] {aka C7, IFI10, INP10, IP-10, SCYB10, crg-2}
- **Diseases:** CMV (MESH:D003586), MS (MESH:D009103), inflammatory (MESH:D007249)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

7 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12259453/full.md

## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12259453/full.md

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Source: https://tomesphere.com/paper/PMC12259453