An unresolved question has been whether there are different subgroups within young-onset type 1 diabetes. Now a study with DZD participation has identified ten different diabetes subgroups in young people, including seven groups of patients with islet autoantibody-positive type 1 diabetes (autoimmune disease) and three islet autoantibody-negative subgroups. The new findings could enable more precise diabetes prognosis and therapy in the future.
Type 1 diabetes (T1D) is the most common metabolic disease in children and adolescents. Approximately 1.1 million young people worldwide have this autoimmune disease. In T1D, the body produces antibodies against the insulin-producing beta cells (so-called islet autoantibodies) and destroys them. Other forms such as MODY diabetes or type 2 diabetes, in which the hormone insulin is less effective (decreasing insulin sensitivity), are less common in this age group. In order to be able to treat the respective diabetes correctly, an exact diagnosis is necessary. However, the forms of diabetes cannot always be clearly differentiated based on the clinical presentation and the biochemical measurements. The determination of islet autoantibodies and the recording of additional parameters such as beta cell function and insulin sensitivity as well as genetic tests can help distinguish between autoimmune and non-autoimmune forms of diabetes. Thus far it has not yet been clarified whether there are different subtypes in T1D, similar to type 2 diabetes. Studies suggest that there are differences depending on the age at which the disease occurs. For example, genetic load, functional beta cell reserve, and T and B cell responses to autoantigens vary with age at onset of diabetes. In addition, the patients respond differently to therapy depending on their age at the onset of the disease.
The aim of the current study was to use a multivariable approach to identify clinically relevant subgroups of autoimmune and non-autoimmune diabetes. For this purpose, parameters were sought in children and adolescents under 20 years of age with newly diagnosed diabetes that would enable the patients to be grouped with regard to the C-peptide concentration in the blood. The C-peptide is an indicator that insulin is still being formed (residual function of the beta cells).
The researchers identified ten subgroups: seven islet autoantibody-positive (autoimmune disease) and three islet autoantibody-negative. The parameters for the grouping were age, HbA1c value (long-term blood glucose level) and body mass index (BMI). The patients were further characterized based on biochemical measurements. There were significant differences between the groups regarding C-peptide, genetics, inflammatory markers, family history of diabetes, lipids, 25-OH vitamin D3, insulin treatment, insulin sensitivity and insulin autoimmunity. In this way, those examined could be divided into different subgroups with potentially different diabetes developments and prognoses.
In the subgroups of the youngest islet autoantibody-positive children and subjects with the lowest C-peptide levels, inflammatory scores (interferon-ɣ and/or tumor necrosis factor profiles) and insulin autoimmunity were particularly high. The subgroups of older islet autoantibody-positive children and adolescents with higher C-peptide levels showed characteristics that are more indicative of type 2 diabetes (T2D), such as lower insulin sensitivity or high BMI. In the study participants without islet autoantibodies, there were subgroups with values that are more typical of T2D or MODY diabetes, but also those with type 1 diabetes characteristics.
The study included a representative cohort of 1,192 children and adolescents and another independent cohort of 2,722 subjects under 20 years of age with newly diagnosed diabetes. The defined subgroups were found to have prognostic significance. In subjects of the respective subgroups, differences in HbA1c levels were detected even after seven years as shortly after the manifestation of diabetes.
Achenbach et al.: A classification and regression tree analysis identifies subgroups of childhood type 1 diabetes. eBioMedicine, 2022, 82, 104118.