The rationale for T cell biomarkers
Whilst several components of both the innate and adaptive immune systems are implicated in the beta cell destruction that leads to type 1 diabetes, current evidence suggests that T cells are the main mediators [16, 17]. Currently, the natural history of type 1 diabetes is routinely monitored using measurements of glucose metabolism (insulin or C-peptide) to assess residual beta cell function, but the change in these biomarkers lags behind the destructive process. Whilst measurements of islet-specific autoantibodies provide a useful biomarker of future disease, autoantibodies do not play a direct pathogenic role and have shown limited use in monitoring disease progression in immunotherapy trials. Assays that measure the frequency and/or functional capacity of T cells, which are associated with beta cell destruction, are therefore uniquely placed to gain key insights into the pathogenesis and progression of type 1 diabetes. Such T cell biomarkers will increase our understanding at each stage of disease, from the initial loss of tolerance to progression to clinical disease. They will also provide insight into the rate of beta cell loss following diagnosis. T cell biomarkers are also becoming a vital component of immunotherapy trials in type 1 diabetes, identifying logical targets for intervention, providing novel insights into why (or in whom) treatments succeed or fail and providing potential for participant stratification .
Measuring T cells in type 1 diabetes
T cell biomarkers in type 1 diabetes can be broadly divided into two categories: antigen specific and antigen non-specific.
Antigen-specific assays aim to enumerate and phenotype T cells with reactivity towards islet antigens. CD4 T cells are commonly detected by measuring proliferation, cytokine production, or upregulation of markers associated with cellular activation following incubation of peripheral blood mononuclear cells (PBMC) with recombinant islet antigens or peptides. Most assays use ‘classical’ antigens, like peptides originating from preproinsulin, but as with novel autoantibodies, T cell reactivity against neo-epitopes has also been described (e.g. against hybrid peptides present in beta cells) . CD4 and CD8 T cells can also be detected using soluble, multimeric MHC molecules loaded with islet peptide (p-MHC) which, when combined with multiparameter flow cytometry, enables the enumeration and phenotypic characterisation of these cells. In many cases, whilst these technologies demonstrate that beta cell-specific T cells are readily detectable in peripheral blood of individuals with type 1 diabetes, similar cells are also detected using these methods in individuals without diabetes who lack evidence of pathological autoimmunity [16, 20]. However, careful phenotyping has revealed important differences in the differentiation and polarisation of these cells depending on the clinical state of participants. For example, compared with individuals without diabetes, islet cell-specific CD4 T cells in type 1 diabetes are more proliferative and less reliant on co-stimulation, which is suggestive of previous in vivo activation . In type 1 diabetes, these cells typically secrete higher levels of proinflammatory cytokines (including IFN-γ, granulocyte-macrophage colony-stimulating factor [GM-CSF] or IL-17) [22, 23], although controversy exists regarding the precise role that each of these cytokines play in islet destruction. In contrast, T cells secreting the immunosuppressive cytokine IL-10 are characteristic of those without disease, those who develop type 1 diabetes at a later age or those who show a beneficial clinical response following antigen-specific immunotherapy [24, 25]. These findings suggest that the balance of responses, rather than the presence of islet-specific T cells per se, is key in determining the rate of beta cell destruction. Similarly, although islet-specific CD8 T cells can be detected in both individuals with and without type 1 diabetes, studies have suggested that they are increased in frequency and have a more antigen-experienced phenotype and enhanced effector function in individuals with type 1 diabetes, and these features inversely correlate with a positive outcome following immunotherapy [26, 27]. Recently, the field is moving towards use of single-cell omics platforms to gain deeper insight into the functional phenotype of islet-specific T cells. This approach has already yielded novel findings, which suggest that the proinflammatory signature of islet-specific CD4 T cells is established early in life, pre-dating autoantibody production, and may be targetable by immune intervention .
Disease-relevant biomarkers can also be derived by measuring the frequencies of specific T cell subsets and studying their functional characteristics or transcriptional profiles. T cell frequencies are routinely measured using multiparameter flow cytometry, using either PBMC or whole blood samples. This approach delivers rich and robust datasets from limited biological material. Such studies have identified biomarkers associated with progression to clinical type 1 diabetes and subsequent beta cell destruction. For example, an increased frequency of follicular helper cells has been observed before and at the time of type 1 diabetes diagnosis and may inversely correlate with C-peptide levels [29, 30]. Similarly, biomarkers of clinical efficacy (as indicated by a slower rate of C-peptide decline) have been identified in participants following immunotherapy, including increased levels of anergic or exhausted CD8 T cells following treatment with teplizumab (anti-CD3) , an increased frequency of central memory CD4 T cells following abatacept therapy  and increased levels of forkhead box P3 (FOXP3) in subsets of memory regulatory T cells (Treg) following peptide immunotherapy . Additional testing of these biomarkers in other settings will be required to establish if they are general biomarkers of beta cell decline or treatment specific.
The functional potential of T cell populations can also be tested through a range of in vitro assays, to reveal key biomarkers. For example, although there is no difference in the frequency of CD4 FOXP3+ Treg, the ability of these cells to control autologous effector T cells (Teff) is significantly reduced in individuals with type 1 diabetes, both before and after clinical diagnosis. Moreover, this functional deficiency appears to be influenced by type 1 diabetes susceptibility loci, suggesting that it may play a causative role in disease pathogenesis .
Detailed investigations have highlighted both Teff resistance to suppression and intrinsic Treg dysfunction (in at least a subset of individuals). This has led to the discovery of tractable biomarkers, such as reduced Treg stability and altered transcriptional signature and altered cytokine signalling (decreased IL-2 signalling in Treg and increased IL-6 signalling in Teff) [34,35,36,37,38], but has also revealed therapeutic opportunities (e.g. low dose IL-2 administration or anti-IL-6R therapy).
Scaling for widespread use
Despite their importance, developing standardised T cell biomarkers for routine use in type 1 diabetes remains a challenge. The inability to biopsy the site of tissue damage and the low frequency and affinity of islet-specific T cells in peripheral blood (typically 10–100-fold lower than pathogen-specific T cells) remain major hindrances. Emerging single-cell technologies will allow for deeper insights to be gained using lower sample quantity requirements, but these may have limited widespread use due to their high cost. Standardisation of immune phenotyping, as has been so successfully performed in the immune-oncology field, is a pressing need that will allow for easier comparisons of studies and faster confirmation of biomarkers using independent validation cohorts. Standardisation of sample preparation and preservation will also be required especially when assessing biomarkers of functional activity. A coordinated, collaborative approach, including large international consortia, will be necessary for progress in this area, to maximise the potential of T cell biomarkers in type 1 diabetes.