Biologic treatment of type 1 diabetes (T1D) with agents including anti-CD3 (otelixizumab and teplizumab), anti-CD20 (rituximab), LFA3Ig (alafacept), and CTLA4Ig (abatacept) results in transient stabilization of insulin C-peptide, a surrogate for endogenous insulin secretion. With the goal of inducing more robust immune tolerance, we used systems biology approaches to elucidate mechanisms associated with C-peptide stabilization in clinical trial blood samples from new-onset T1D subjects treated with the B cell-depleting drug, rituximab. RNA sequencing (RNA-seq) analysis of whole-blood samples from this trial revealed a transient increase in heterogeneous T cell populations, which were associated with decreased pharmacodynamic activity of rituximab, increased proliferative responses to islet antigens, and more rapid C-peptide loss. Our findings illustrate complexity in hematopoietic remodeling that accompanies B cell depletion by rituximab, which impacts and predicts therapeutic efficacy in T1D. Our data also suggest that a combination of rituximab with therapy targeting CD4 + T cells may be beneficial for T1D subjects.

Permutational analysis of the immune system reveals advanced immune aging in individuals with Down syndrome and in individuals with type 1 diabetes.

Adoptive transfer of regulatory T cells (T regs ) is therapeutic in type 1 diabetes (T1D) mouse models. T regs that are specific for pancreatic islets are more potent than polyclonal T regs in preventing disease. However, the frequency of antigen-specific natural T regs is extremely low, and ex vivo expansion may destabilize T regs , leading to an effector phenotype. Here, we generated durable, antigen-specific engineered T regs (EngT regs ) from primary human CD4 + T cells by combining FOXP3 homology-directed repair editing and lentiviral T cell receptor (TCR) delivery. Using TCRs derived from clonally expanded CD4 + T cells isolated from patients with T1D, we generated islet-specific EngT regs that suppressed effector T cell (T eff ) proliferation and cytokine production. EngT regs suppressed T effs recognizing the same islet antigen in addition to bystander T effs recognizing other islet antigens through production of soluble mediators and both direct and indirect mechanisms. Adoptively transferred murine islet-specific EngT regs homed to the pancreas and blocked diabetes triggered by islet-specific T effs or diabetogenic polyclonal T effs in recipient mice. These data demonstrate the potential of antigen-specific EngT regs as a targeted therapy for preventing T1D.

The goal of personalized medicine is to match the right drugs to the right patients at the right time. Personalized medicine has been most successful in cases where there is a clear genetic linkage between a disease and a therapy. This is not the case with type 1 diabetes (T1D), a genetically complex immune-mediated disease of β-cell destruction. Researchers over decades have traced the natural history of disease sufficiently to use autoantibodies as predictive biomarkers for disease risk and to conduct successful clinical trials of disease-modifying therapy. Recent studies, however, have highlighted heterogeneity associated with progression, with nonuniform rate of insulin loss and distinct features of the peri-diagnostic period. Likewise, there is heterogeneity in immune profiles and outcomes in response to therapy. Unexpectedly, from these studies demonstrating perplexing complexity in progression and response to therapy, new biomarker-based principles are emerging for how to achieve personalized therapies for T1D. These include therapy timed to periods of disease activity, use of patient stratification biomarkers to align therapeutic target with disease endotype, pharmacodynamic biomarkers to achieve personalized dosing and appropriate combination therapies, and efficacy biomarkers for “treat-to-target” strategies. These principles provide a template for application of personalized medicine to complex diseases.

It has been 100 years since the life-saving discovery of insulin, yet daily management of type 1 diabetes (T1D) remains challenging. Even with closed-loop systems, the prevailing need for persons with T1D to attempt to match the kinetics of insulin activity with the kinetics of carbohydrate metabolism, alongside dynamic life factors affecting insulin requirements, results in the need for frequent interventions to adjust insulin dosages or consume carbohydrates to correct mismatches. Moreover, peripheral insulin dosing leaves the liver underinsulinized and hyperglucagonemic and peripheral tissues overinsulinized relative to their normal physiologic roles in glucose homeostasis. Disease-modifying therapies (DMT) to preserve and/or restore functional β-cell mass with controlled or corrected autoimmunity would simplify exogenous insulin need, thereby reducing disease mortality, morbidity, and management burdens. However, identifying effective DMTs for T1D has proven complex. There is some consensus that combination DMTs are needed for more meaningful clinical benefit. Other complexities are addressable with more innovative trial designs and logistics. While no DMT has yet been approved for marketing, existing regulatory guidance provides opportunities to further “de-risk” development. The T1D development ecosystem can accelerate progress by using more innovative ways for testing DMTs for T1D. This perspective outlines suggestions for accelerating evaluation of candidate T1D DMTs, including combination therapies, by use of innovative trial designs, enhanced logistical coordination of efforts, and regulatory guidance for expedited development, combination therapies, and adaptive designs.