Skip to main navigation Skip to search Skip to main content

Detection and phenotypic characterisation of acetylcholine receptor (AChR)-reactive CD4⁺ T cells in myasthenia gravis using antigen-reactive T cell enrichment (ARTE) and multiparameter flow cytometry

Research output: Chapter in Book/Report/Conference proceedingMeeting abstractResearchpeer-review

Abstract

Generalized myasthenia gravis (MG) is a chronic, relapse-prone autoimmune disease driven by pathogenic autoantibodies, most often directed against the acetylcholine receptor (AChR). Although established treatments such as thymectomy can lead to clinical improvement, a substantial proportion of patients experience incomplete remission or disease relapse, and no validated immunological biomarkers exist to predict long-term outcomes after surgery. In parallel, new targeted therapies, including efgartigimod alfa (Vyvgart®), a neonatal Fc receptor antagonist, have recently entered clinical practice; however, biomarkers that reflect underlying immune mechanisms or predict long-term therapeutic response are likewise lacking. Recent studies in other chronic antibody-mediated autoimmune diseases have identified a population of autoreactive CD4⁺ T cells with an exhaustion-like phenotype (ThEx) that persists despite treatment while retaining B cell helper capacity, potentially explaining chronicity and relapse in antibody-mediated autoimmunity. Whether such ThEx-like autoreactive CD4⁺ T cells are present in MG, and how they are affected by thymectomy or emerging therapies, remains unknown. To address this, we applied antigen-reactive T cell enrichment (ARTE) combined with multiparametric flow cytometry to directly detect and phenotype rare AChR-specific CD4⁺ T cells ex vivo. ARTE was used to track the frequency and phenotype of AChR-reactive CD4⁺ T cells before and after efgartigimod therapy and thymectomy. In parallel, comprehensive peripheral T and B cell immunophenotyping was performed, and in thymectomy cases, T and B cell subsets were additionally analysed in thymic tissue. Initial data show that AChR-reactive CD4⁺ T cells were present at higher frequencies in MG patients than in healthy controls and exhibited increased FOXP3 expression together with the inhibitory receptors PD-1 and TIGIT, while retaining a conventional T helper lineage, consistent with an exhaustion-like (ThEx) phenotype. Therapy-associated changes in the frequency and phenotype of AChR-reactive CD4⁺ T cells were observed, accompanied by alterations in peripheral T and B cell compartments following both efgartigimod therapy and thymectomy. Further in-depth phenotypic characterisation of peripheral and thymic immune cell subsets is ongoing. Overall, these preliminary findings demonstrate the feasibility of integrating autoreactive CD4⁺ T cell analysis with broader T and B cell immunophenotyping to explore immune signatures relevant to treatment response and disease course in MG.
Original languageEnglish
Title of host publication Baltic Flow Cytometry Society‘s conference 2026
Subtitle of host publicationInternational conference
Place of PublicationRiga
Pages38
Number of pages1
Publication statusPublished - 20 Mar 2026
EventBaltic Flow Cytometry Society 2026 International Conference - Rīga Stradiņš University, Dzirciema iela 16, Riga, Latvia
Duration: 19 Mar 202620 Mar 2026
https://balticflow.org/bfcs2026/

Conference

ConferenceBaltic Flow Cytometry Society 2026 International Conference
Abbreviated titleBFCS 2026
Country/TerritoryLatvia
CityRiga
Period19/03/2620/03/26
Internet address

Keywords*

  • Myasthenia gravis
  • Flow cytometry
  • Auto-antigen specific T cells

Field of Science*

  • 1.6 Biological sciences
  • 3.4 Medical biotechnology

Publication Type*

  • 3.4. Other publications in conference proceedings (including local)

Fingerprint

Dive into the research topics of 'Detection and phenotypic characterisation of acetylcholine receptor (AChR)-reactive CD4⁺ T cells in myasthenia gravis using antigen-reactive T cell enrichment (ARTE) and multiparameter flow cytometry'. Together they form a unique fingerprint.

Cite this