Artificial intelligence (AI) is transforming rheumatology research, with a myriad of studies aiming to improve diagnosis, prognosis and treatment prediction, while also showing potential capability to optimise the research workflow, improve drug discovery and clinical trials. Machine learning, a key element of discriminative AI, has demonstrated the ability of accurately classifying rheumatic diseases and predicting therapeutic outcomes by using diverse data types, including structured databases, imaging and text. In parallel, generative AI, driven by large language models, is becoming a powerful tool for optimising the research workflow by supporting with content generation, literature review automation and clinical decision support. This review explores the current applications and future potential of both discriminative and generative AI in rheumatology. It also highlights the challenges posed by these technologies, such as ethical concerns and the need for rigorous validation and regulatory oversight. The integration of AI in rheumatology promises substantial advancements but requires a balanced approach to optimise benefits and minimise potential possible downsides.

Sjögren’s syndrome is one of the most prevalent autoimmune diseases after rheumatoid arthritis, with a preference for middle age, and is characterised by exocrine glandular involvement leading to xerostomia and xerophthalmia. It can have systemic implications with vascular, neurological, renal, and pulmonary involvement, and in some cases, it may evolve to non-Hodgkin’s lymphoma. For a long time, B- and T-lymphocytes have been the focus of research and have been considered key players in Sjögren’s syndrome pathogenesis and evolution. With the development of new technologies, including omics, more insights have been found on the different signalling pathways that lead to inflammation and activation of the immune system. New evidence indicates that a third actor linking innate and adaptive immunity plays a leading role in the Sjögren’s syndrome play: the monocyte. This review summarises the recent insights from transcriptomic, proteomic, and epigenetic studies that help us to understand more about the Sjögren’s syndrome pathophysiology and redefine the involvement of monocytes in this disease.

Background: Uveitis is one of the most usual extraaxial manifestations of spondyloarthrities (SpA) but the impact of the date of the onset is no well-known. Objectives: a) To assess the prevalence of acute anterior uveitis (AAU) in the Spanish population with SpA; b) To describe the time of appearance of the AAU regarding to the onset of rheumatic symptoms and SpA diagnosis; c) To evaluate the impact of the moment of appearance of the AAU on the treatment and disease activity. Methods: A cross-sectional study with data extracted from REGISPONSER registry. First, the prevalence of AAU was determined. Patients were classified as AAU before/ concomitant/ after the onset of rheumatic symptoms and as AAU before/ concomitant/ after the SpA diagnosis regarding the date of appearance of each symptom and SpA diagnosis. Treatment and disease activity were compared between ‘AAU before or concomitant with rheumatic symptoms’ vs. ‘AAU after rheumatic symptoms’ groups, as well as ‘AAU before or concomitant with SpA diagnosis’ vs. ’AAU after the SpA diagnosis’ groups using Chi-square and T-Student tests. Results: Among the 2346 patients included in REGISPONSER, 379 (16.2%) had at least one episode of AAU. Information concerning the date of occurrence of rheumatic symptoms and SpA diagnosis was available in 280 and 284 patients, respectively. A total of 28 (9.7%), 31 (10.8%) and 229 (79.5%) patients suffered the first episode of AAU before, concomitantly and after the rheumatic symptoms, respectively; while 108 (38.0%), 38 (13.4%) and 138 (48.6%) suffered the episode of AAU before, concomitantly and after the SpA diagnosis, respectively. The comparison of patients with ‘AAU before or concomitant with rheumatic symptoms’ vs ‘AAU after rheumatic symptoms’ (Table 1), showed in the second group a younger age of symptoms onset, a greater diagnosis delay, higher disease activity (CRP and BASDAI), greater structural damage (BASRI). No significant differences were found in the use of biological (27.9% vs. 23.2%) or synthetic DMARDs (14.8% vs. 20.3%). The comparison of ‘AAU before or concomitant with the SpA diagnosis’ vs. ‘AAU after the SpA diagnosis’ groups (Table 1) showed similar results to the previous ones with no significant differences were obtained in the use of biological (28.8% vs 20.4%) or synthetic (17.2% vs 20.4%) DMARDs. Conclusion: These results suggest that patients who presented the first episode of AAU prior to the onset of rheumatic symptoms showed a later start of the disease with a shorter diagnosis delay, lower disease activity and less structural damage. Disclosure of Interests: Gómez García Ignacio: None declared, Clementina López-Medina: None declared, MLourdes Ladehesa Pineda: None declared, María del Carmen Castro Villegas: None declared, Pérez Sánchez Laura: None declared, María Ángeles Puche Larrubia: None declared, José Miguel Sequí-Sabater: None declared, Font Ugalde Pilar: None declared, Rafaela Ortega Castro: None declared, Alejandro Escudero Contreras Grant/research support from: ROCHE and Pfizer, Speakers bureau: ROCHE, Lilly, Bristol and Celgene., Eduardo Collantes Estevez Grant/research support from: ROCHE and Pfizer, Speakers bureau: ROCHE, Lilly, Bristol and Celgene