Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease and is extremely heterogeneous in terms of immunological features and clinical manifestations. This complexity could result in a delay in the diagnosis and treatment introduction, with impacts on long-term outcomes. In this view, the application of innovative tools, such as machine learning models (MLMs), could be useful. Thus, the purpose of the present review is to provide the reader with information about the possible application of artificial intelligence in SLE patients from a medical perspective. To summarize, several studies have applied MLMs in large cohorts in different disease-related fields. In particular, the majority of studies focused on diagnosis and pathogenesis, disease-related manifestations, in particular Lupus Nephritis, outcomes and treatment. Nonetheless, some studies focused on peculiar features, such as pregnancy and quality of life. The review of published data demonstrated the proposal of several models with good performance, suggesting the possible application of MLMs in the SLE scenario.

The introduction of the so-called immune checkpoint inhibitors (ICIs) substantially changed the history of cancer therapy. On the other hand, they can induce the development of rheumatic immune-related adverse events (Rh-irAEs). In the scenario of a joint oncology/rheumatology outpatient clinic, we conducted a single-centre descriptive study to define from a laboratory, clinical and therapeutic point of view, rheumatic conditions developed during anti-PD1 treatment. The study included 32 patients (M/F 16/16, median age 69, IQR 16.5). According to the international classification criteria, eight patients could be classified as affected by Rheumatoid Arthritis, one by Psoriatic Arthritis, six by Polymyalgia Rheumatica, five by systemic connective tissue diseases (two systemic lupus erythematosus, two Sjögren’s syndrome, one undifferentiated connective tissue disease). The remaining patients were diagnosed as having undifferentiated arthritis or inflammatory arthralgia. The median interval between ICIs starting and the onset of symptoms was 14 weeks (IQR 19.75). Moving to treatment, the longitudinal observation revealed that all RA, PsA and CTD patients required the introduction of treatment with DMARDs. In conclusion, the growing use of ICIs in a real-life setting confirmed the possible development of different rheumatological conditions, further emphasising the need for shared oncology/rheumatology management.

Objective: The purpose of this study was to determine the distribution of organ damage in a cohort of systemic lupus erythematosus (SLE) patients and to evaluate the roles of clinical and genetic factors in determining the development of chronic damage. Methods: Organ damage was assessed by the SLICC Damage Index (SDI). We analyzed a panel of 17 single-nucleotide polymorphism (SNPs) of genes already associated with SLE, and we performed a phenotype–genotype correlation analysis by evaluating specific domains of the SDI. Results: Among 175 Caucasian SLE patients, 105 (60%) exhibited damage (SDI ≥1), with a median value of 1.0 (IQR 3.0). The musculoskeletal (26.2%), neuropsychiatric (24.6%) and ocular domains (20.6%) were involved most frequently. The presence of damage was associated with higher age, longer disease duration, neuropsychiatric (NP) manifestations, anti-phospholipid syndrome and the positivity of anti-dsDNA. Concerning therapies, cyclophosphamide, mycophenolate mofetil and glucocorticoids were associated with the development of damage. The genotype–phenotype correlation analysis showed an association between renal damage, identified in 6.9% of patients, and rs2205960 of TNFSF4 (p = 0.001; OR 17.0). This SNP was significantly associated with end-stage renal disease (p = 0.018, OR 9.68) and estimated GFR < 50% (p = 0.025, OR 1.06). The rs1463335 of MIR1279 gene was associated with the development of NP damage (p = 0.029; OR 2.783). The multivariate logistic regression analysis confirmed the associations between TNFSF4 rs2205960 SNP and renal damage (p = 0.027, B = 2.47) and between NP damage and rs1463335 of MIR1279 gene (p = 0.014, B = 1.29). Conclusions: Our study could provide new insights into the role of genetic background in the development of renal and NP damage.

We longitudinally followed a single-center cohort of anti-phospholipid (aPL) positive healthy subjects to evaluate the evolution to systemic autoimmune diseases (sAD) and to describe clinical and serological associated features. Since 2010, we have consecutively screened healthy subjects who were positive, in at least two consecutive determinations, for one or more aPL [anti-Cardiolipin (aCL) IgM/IgG, anti-Beta2Glycoprotein I (aB2GPI) IgM/IgG, Lupus Anticoagulant (LA)]. All subjects were evaluated every six months, or in accordance with the patient’s clinical course, in order to record the development of clinical and laboratory features suggestive for sAD. Ninety-five subjects [M/F 20/75, median age at first determination 46 years, Interquartile Range (IQR) 19] were enrolled. Thirty-three subjects (34.7%) were positive for only one aPL [15 (15.8%) for aCL, 15 (15.8%) for LA, and 5 (5.3%) for aB2GPI]; 37 (38.9%) had double positivity [32 (33.6%) for aCL and aB2GPI; 5 (5.3%) for aCL and LA], 23 (24.2%) had triple positivity. We prospectively followed up our cohort for a median period of 72 months (IQR 84). During a total follow-up of 7692 person-months, we found an absolute risk for sAD development equal to 1.8%. Specifically, 14 (14.7%) patients developed a sAD: in four patients (4.2%), after developing a thrombotic event, an antiphospholipid syndrome was diagnosed, 7 (7.4%) patients developed an Undifferentiated Connective Tissue Disease after a median period of 76 months (IQR 75.5), and lastly, three (3.1%) patients could be classified as affected by Systemic Lupus Erythematosus according to the ACR/EULAR 2019 criteria. The presence of triple positivity status resulted in being significantly associated with the progression to sAD (p-value = 0.03). In conclusion, we observed the development of sAD in almost 15% of aPL positive subjects. Triple positivity was significantly associated with this progression, suggesting a possible role as biomarker for this condition. Thus, our results could suggest the need for periodic follow-up for such patients to assess early diagnosis and treatment.