Purpose of Review Diabetes mellitus can be categorized into two major variants, type 1 and type 2. A number of traits such as clinical phenotype, age at disease onset, genetic background, and underlying pathogenesis distinguish the two forms. Recent Findings Recent evidence indicates that type 1 diabetes can be accompanied by insulin resistance and type 2 diabetes exhibits self-reactivity. These two previously unknown conditions can influence the progression and outcome of the disease. Unlike most conventional considerations, diabetes appears to consist of a spectrum of intermediate phenotypes that includes monogenic and polygenic loci linked to inflammatory processes including autoimmunity, beta cell impairment, and insulin resistance. Summary Here we discuss why a shift of the classical bi-modal view of diabetes (autoimmune vs. non-autoimmune) is necessary in favor of a model of an immunological continuum of endotypes lying between the two extreme “insulin-resistant” and “autoimmune beta cell targeting,” shaped by environmental and genetic factors which contribute to determine specific immune-conditioned outcomes.

An unbiased and replicable profiling of type 1 diabetes (T1D)-specific circulating immunome at disease onset has yet to be identified due to experimental and patient selection limitations. Multicolor flow cytometry was performed on whole blood from a pediatric cohort of 107 patients with new-onset T1D, 85 relatives of T1D patients with 0-1 islet autoantibodies (pre-T1D_LR), 58 patients with celiac disease or autoimmune thyroiditis (CD_THY) and 76 healthy controls (HC). Unsupervised clustering of flow cytometry data, validated by a semi-automated gating strategy, confirmed previous findings showing selective increase of naïve CD4 T cells and plasmacytoid DCs, and revealed a decrease in CD56brightNK cells in T1D. Furthermore, a non-selective decrease of CD3+CD56+ regulatory T cells was observed in T1D. The frequency of naïve CD4 T cells at disease onset was associated with partial remission, while it was found unaltered in the pre-symptomatic stages of the disease. Thanks to a broad cohort of pediatric individuals and the implementation of unbiased approaches for the analysis of flow cytometry data, here we determined the circulating immune fingerprint of newly diagnosed pediatric T1D and provide a reference dataset to be exploited for validation or discovery purposes to unravel the pathogenesis of T1D.