Emerging approaches to the diagnosis, prevention, and personalised management of type 1 diabetes in the era of personalised medicine

Abstract

Type 1 diabetes (T1D) is an autoimmune condition characterised by selective destruction of pancreatic beta cells, resulting in complete insulin insufficiency and a lifelong need for insulin. Current diagnostic and therapeutic approaches focus on symptom management rather than retaining residual beta-cell function and/or preventing autoimmune attack. This thesis addresses new strategies for diagnosis, prevention and treatment of T1D, looking at combined genetic, immunologic, molecular and metabolic markers for risk prediction and early intervention. Immunomodulatory therapy (anti-CD3 antibodies, vaccines and regulatory T cells) is considered alongside regenerative therapies, such as stem cellderived and gene-edited beta cells, encapsulation and combined immunotherapy-cell replacement therapy. Personalised approaches to glucose regulation, including continuous glucose monitoring, closed-loop insulin delivery, wearables, and pharmacogenomic approaches to therapy are discussed to optimise care. Ethical, regulatory and economic considerations are discussed, including the importance for fair access and implementation. Combining multi-omic technologies with machine learning allows disease and therapeutic response prediction, for predictive, precision medicine. These innovations will enable preventative, curative and personalised therapies, offering to transform treatment of T1D, prevent complications and enhance the quality of life.