Clonally expanded PD-1-expressing T cells are enriched in synovial fluid of juvenile idiopathic arthritis patients.
Anna VanniAlessio MazzoniRoberto SemeraroManuela CaponePatrick MaschmeyerGiulia LamacchiaLorenzo SalvatiAlberto CarnascialiParham FarahvachiTeresa GianiGabriele SimoniniGiovanni FilocamoMicol RomanoFrancesco LiottaMir-Farzin MashreghiLorenzo CosmiRolando CimazAlberto MagiLaura MaggiFrancesco AnnunziatoPublished in: European journal of immunology (2023)
Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition in childhood. The disease etiology remains largely unknown; however, a key role in JIA pathogenesis is surely mediated by T cells. T-lymphocytes activity is controlled via signals, known as immune checkpoints. Delivering an inhibitory signal or blocking a stimulatory signal to achieve immune suppression is critical in autoimmune diseases. However, the role of immune checkpoints in chronic inflammation and autoimmunity must still be deciphered. In this study, we investigated at the single-cell level the feature of T cells in JIA chronic inflammation, both at the transcriptome level via single-cell RNA sequencing and at the protein level by flow cytometry. We found that despite the heterogeneity in the composition of synovial CD4 + and CD8 + T cells, those characterized by PD-1 expression were clonally expanded tissue-resident memory (Trm)-like cells and displayed the highest proinflammatory capacity, suggesting their active contribution in sustaining chronic inflammation in situ. Our data support the concept that novel therapeutic strategies targeting PD-1 may be effective in the treatment of JIA. With this approach, it may become possible to target overactive T cells regardless of their cytokine production profile.
Keyphrases
- juvenile idiopathic arthritis
- single cell
- rna seq
- disease activity
- oxidative stress
- flow cytometry
- end stage renal disease
- chronic kidney disease
- rheumatoid arthritis
- gene expression
- high throughput
- newly diagnosed
- ejection fraction
- machine learning
- prognostic factors
- systemic lupus erythematosus
- deep learning
- drug induced
- dna methylation
- big data
- patient reported
- combination therapy
- working memory
- small molecule
- mass spectrometry
- young adults