Machine learning application in autoimmune diseases: State of art and future prospectives.

Autoimmune diseases are a group of disorders resulting from an alteration of immune tolerance, characterized by the formation of autoantibodies and the consequent development of heterogeneous clinical manifestations. Diagnosing autoimmune diseases is often complicated, and the available prognostic tools are limited. Machine learning allows us to analyze large amounts of data and carry out complex calculations quickly and with minimal effort. In this work, we examine the literature focusing on the use of machine learning in the field of the main systemic (systemic lupus erythematosus and rheumatoid arthritis) and organ-specific autoimmune diseases (type 1 diabetes mellitus, autoimmune thyroid, gastrointestinal, and skin diseases). From our analysis, interesting applications of machine learning emerged for developing algorithms useful in the early diagnosis of disease or prognostic models (risk of complications, therapeutic response). Subsequent studies and the creation of increasingly rich databases to be supplied to the algorithms will eventually guide the clinician in the diagnosis, allowing intervention when the pathology is still in an early stage and immediately directing towards a correct therapeutic approach.

Alarmins in autoimmune diseases.

Alarmins are endogenous, constitutively expressed, chemotacting and immune activating proteins or peptides released because of non-programmed cell death (i.e. infections, trauma, etc). They are considered endogenous damage-associated molecular patterns (DAMPs), able to induce a sterile inflammation. In the last years, several studies highlighted a possible role of different alarmins in the pathogenesis of various autoimmune and immune-mediated diseases. We reviewed the relevant literature about this topic, for about 160 articles. Particularly, we focused on systemic autoimmune diseases (systemic lupus erythematosus, rheumatoid arthritis, idiopathic inflammatory myopathies, ANCA-associated vasculitides, Behçet's disease) and cutaneous organ-specific autoimmune diseases (vitiligo, psoriasis, alopecia, pemphigo). Finally, we discussed about future perspectives and potential therapeutic implications of alarmins in autoimmune diseases. In fact, identification of receptors and downstream signal transducers of alarmins may lead to the identification of antagonistic inhibitors and agonists, with the capacity to modulate alarmins-related pathways and potential therapeutic applicability.