T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection
T-cell exhaustion, co-stimulation and clinical outcome in autoimmunity and infection
The clinical course of autoimmune and infectious disease varies greatly, even between individuals with the same condition. An understanding of the molecular basis for this heterogeneity could lead to significant improvements in both monitoring and treatment. During chronic infection the process of T-cell exhaustion inhibits the immune response, facilitating viral persistence. Here we show that a transcriptional signature reflecting CD8 T-cell exhaustion is associated with poor clearance of chronic viral infection, but conversely predicts better prognosis in multiple autoimmune diseases. The development of CD8 T-cell exhaustion during chronic infection is driven both by persistence of antigen and by a lack of accessory 'help' signals. In autoimmunity, we find that where evidence of CD4 T-cell co-stimulation is pronounced, that of CD8 T-cell exhaustion is reduced. We can reproduce the exhaustion signature by modifying the balance of persistent stimulation of T-cell antigen receptors and specific CD2-induced co-stimulation provided to human CD8 T cells in vitro, suggesting that each process plays a role in dictating outcome in autoimmune disease. The 'non-exhausted' T-cell state driven by CD2-induced co-stimulation is reduced by signals through the exhaustion-associated inhibitory receptor PD-1, suggesting that induction of exhaustion may be a therapeutic strategy in autoimmune and inflammatory disease. Using expression of optimal surrogate markers of co-stimulation/exhaustion signatures in independent data sets, we confirm an association with good clinical outcome or response to therapy in infection (hepatitis C virus) and vaccination (yellow fever, malaria, influenza), but poor outcome in autoimmune and inflammatory disease (type 1 diabetes, anti-neutrophil cytoplasmic antibody-associated vasculitis, systemic lupus erythematosus, idiopathic pulmonary fibrosis and dengue haemorrhagic fever). Thus, T-cell exhaustion plays a central role in determining outcome in autoimmune disease and targeted manipulation of this process could lead to new therapeutic opportunities.
- University Of Cambridge
- Cambridge University Hospitals NHS Foundation Trust United Kingdom
- University of Cambridge United Kingdom
- Addenbrooke's Hospital United Kingdom
- University of Cambridge
CD4-Positive T-Lymphocytes, Inflammation, Receptors, Interleukin-7, Programmed Cell Death 1 Receptor, CD2 Antigens, Receptors, Antigen, T-Cell, Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis, Autoimmunity, CD8-Positive T-Lymphocytes, Infections, Inflammatory Bowel Diseases, Article, Autoimmune Diseases, Mice, Phenotype, Animals, Humans, Lupus Erythematosus, Systemic, Transcriptome
CD4-Positive T-Lymphocytes, Inflammation, Receptors, Interleukin-7, Programmed Cell Death 1 Receptor, CD2 Antigens, Receptors, Antigen, T-Cell, Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis, Autoimmunity, CD8-Positive T-Lymphocytes, Infections, Inflammatory Bowel Diseases, Article, Autoimmune Diseases, Mice, Phenotype, Animals, Humans, Lupus Erythematosus, Systemic, Transcriptome
8 Research products, page 1 of 1
- 1995IsAmongTopNSimilarDocuments
- 2015IsAmongTopNSimilarDocuments
- 1989IsAmongTopNSimilarDocuments
- 1998IsAmongTopNSimilarDocuments
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).591 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
