Personalised medicine for Systemic Autoinflammatory Diseases (PerSAIDs) project
The “Personalised Medicine for Systemic Autoinflammatory Diseases” (PerSAID) is an EU-funded project of the Transnational call for “Development of Clinical Support Tools for Personalized Medicine Implementation” (2021). It was born as a collaborative effort of a group of European investigators interested in the diagnosis, treatment and research on the field of systemic autoinflammatory diseases (SAIDs), who also participated in a previous EU-funded project entitled “A comprehensive clinical and experimental approach to personalized molecular medicine in patients with defined and undefined autoinflammatory disorders” (2016).
The PerSAID project would like to expand our previous experience in these diseases and take advantage of different repositories of patients’ samples to apply different tools of personalized medicine (multi-omics; ex-vivo studies; artificial intelligence tools;….) to improve the diagnosis and management of patients with these diseases, with an special focus in the continuously growing group of patients with undiagnosed SAIDs.
The Coordinator of the PerSAIDs project is Dr. Isabella Ceccherini, head of the Laboratory of Genetics and Genomics of Rare Diseases in the IRCCS Istituto Giannina Gaslini, Genoa, Italy. The partners of the project at different European countries are listed below:
What Systemic Autoinflammatory Diseases are?
The term autoinflammatory disease was coined in 1999 to describe the common pathophysiological mechanism of a group of inherited conditions characterized by recurrent episodes of sterile inflammation, which typically appears in the absence of a neoplastic, infectious or autoimmune etiology. Currently, these conditions are the prototype of inborn errors of innate immunity, and their number has increased up to 50. Most of these diseases are a consequence of mutations in proteins triggering or regulating the inflammatory process and/or the cell death, and are collectively named “inherited SAIDs”. On the basis of the main involved inflammatory pathway, the following different groups have been identified:
How the diagnosis of Systemic Autoinflammatory Diseases may be achieved?
The diagnosis of the classical inborn errors of immunity at routine laboratories is a multistep pathway that combines different strategies including immunophenotyping of circulating lymphocyte subpopulations, immunoglobulin and/or complement quantification, ex vivo functional assays, and genetic tests. In contrast, the diagnosis of the SAIDs mainly relies in the use of genetics tests, with few exceptions to this statement (i.e. the enzymatic quantification of ADA2 or mevalonate kinase activities for the diagnosis of deficiency of ADA2 or mevalonate kinase deficiencies, respectively). The technical advances in the sequencing methods obtained in the last decade associated with their continuously decreasing prices have made possible that these genetics tests, especially those based on the next-generation sequencing, could be available for the routine diagnosis of SAID in most medical centers in developed countries.
The problem of the continuously growing group of undefined/undiagnosed SAID
Despite these advances in the availability of genetic tests in routine laboratories, 40-60% of patients with phenotypes compatible with typical SAIDs remain without genetic confirmation, being collectively known as undefined/undiagnosed SAIDs (uSAIDs). This group is highly heterogeneous from a clinical and from a genetic point of view. Thus, at one end of this spectrum there is a minority group of patients in whom the disease is a consequence of mutations in a gene still not discovered. This group of patients is of high interest of research by using different genetic approaches, and once the genetic defect will be identified, these patients will be included in the category of defined or inherited SAIDs. In contrast, at the other end of the spectrum there are different and large groups of patients in whom the disease is probably polygenic or multifactorial origin, with environmental influence modulating the phenotype. The use of novel genetic strategies in these groups of patients does not identify often possible causative genes following a classical Mendelian inheritance, making necessary alternate strategies beyond classical approaches in which a single or few key mutations are singled out.
Main objectives of the PerSAID project
I. Clinical research
Samples collected from patients with both diagnosed and undiagnosed SAIDs and stored in different European repositories will be analyzed in this objective. The group of patients with diagnosed SAIDs (n: 100) will include: i) inflammasomopathies (i.e. Familial Mediterranean Fever, cryopyrin-associated periodic syndromes, NLRC4-associated autoinflammatory disease); ii) unfolded protein diseases (i.e. TNF receptor I-associated periodic syndrome); iii) type I Interferonopathies (i.e. SAVI syndrome, CANDLE/PRAAS syndrome); iv) inherited actinopathies (i.e. ARPC1B deficiency, WDR1 deficiency); v) NF-kb-related disorders; and vi) deficiency of ADA2 (DADA2). In contrast, the group of patients with undiagnosed SAIDs (n: 100) will include: i) PFAPA syndrome; ii) SURF; iii) chronic recurrent multifocal osteomyelitis (CRMO) / SAPHO syndrome; iv) systemic juvenile idiopathic arthritis (SoJIA); and v) undefined SAIDs.
The aim of this objective is to obtain a complete multi-omic profile of each enrolled patient, which means to collect results from genomics, epigenomics, transcriptomics, proteomics, lipidomics, immunomics and metabolomics studies.
II. Application of Artificial Intelligence Tools in SAIDs research
1. Identification of specific SAID signatures
The results of the multi-omics studies associated with the classical data of each patient (clinical manifestations, results of analytical tests, response to administered treatments, inheritance pattern of the disease) will be the basis to apply artificial intelligence tools, specifically conventional machine learning models, to identify specific signatures for the patients with diagnosed SAIDs. Once these signatures will be identified, their robustness will be assessed in a novel group of patients with the aim to validate them as efficient tools for the diagnosis and management of future patients. Simultaneously, these specific SAID signatures will be employed to compare them with those signatures obtained in patients with undiagnosed SAIDs.