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Background:Serum autoantibodies constitute the major biomarker of inflammatory myositis and have consistently served as a model for precision medicine by predicting clinical features and trajectories. To underscore this concept, inflammatory myositis are classified based on the positivity of different myositis-specific (MSA) and -associated (MAA) antibodies, but can also be diagnosed in the absence of MSA/MAA, thus requiring further research to delineate the clinical spectrum of seronegative myositis.Objectives:To analyse demographic, clinical and immunological features of patients with idiopathic inflammatory myositis without myositis-specific and associated autoantibodies, belonging to a monocentric cohort.Methods:A retrospective analysis was conducted on a cohort of 87 patients with inflammatory myositis followed in our Unit, with a focus on demographic, clinical, and serological features. Antinuclear antibodies (ANA) were tested on HEp-2 slides by an expert biologist following standard references. Seronegative IIM was defined if no connective tissue disease-related antibody (including MSA/MAA) could be identified using standard techniques together with RNA- and protein-immunoprecipitation.Results:Out of 87 patients, 18 were seronegative (21%), with a slight predominance of male subjects (19% vs 39%). Other demographic features, as well as cancer incidence, were equally distributed among seropositive and seronegative IIM patients. Notably, muscle involvement was significantly more common among seronegative subjects (100%) compared to the seropositive counterpart (71%; p = 0.009), while interstitial lung disease (ILD) was less common in the seronegative group compared to the seropositive subset (22% vs. 51%; p = 0.044). Nevertheless, the proportion of patients with a fibrotic ILD phenotype did not differ between the two subgroups. Clinical features suggestive of dermatomyositis, as well as Raynaud’s phenomenon, calcinosis, arthritis, and myocarditis, oropharyngeal dysphagia were equally distributed between the two groups. Considering the whole cohort, HEp-2 ANA immunofluorescence results were available for 86 (99%) patients, with 15/86 (17%) being ANA-negative, while nuclear staining was reported in 53/71 (75%), cytoplasmic staining in 23/71 (32%), and nucleolar staining in 15/71 (21%) IIM patients. ANA-negative IIM patients had more frequently clinical evidence of myositis (80% vs 60%; p = 0.09), while Gottron’s sign was less frequent in this subset (31% vs 60%; p = 0.03), and lymphopenia at diagnosis was observed only in ANA-positive inflammatory myositis patients (21/46, 46% vs 0/7, 0%; p = 0.02). Notably, ANA-negative subjects showed a significantly higher prevalence of anti-MDA5 antibodies (2/15, 13%, vs 1/71, 1%; p = 0.02).Conclusion:Seronegative inflammatory myositis represents one-fifth of our cohort and is characterized by high prevalence of skeletal muscle involvement, but less pulmonary disease, compared to the seropositive counterpart. Typical signs suggestive of a ‘type I interferon signature’ (e.g., Gottron’s, lymphopenia) are absent in ANA-negative inflammatory myositis, and this observation needs confirmation in larger datasets, with immunological studies particularly on type I interferons while we cannot rule out the possibility that muscle involvement is deemed necessary for the diagnosis of seronegative cases.REFERENCES:[1] Ceribelli A, et al. Front Med (Lausanne) 2023; Tonutti A, at al. Front Immunol 2022; Ceribelli A, et al. J Transl Autoimmun 2020; Ceribelli A, et al. Clin Rheumatol 2017.Acknowledgements:NIL.Disclosure of Interests:Antonio Tonutti: None declared, Natasa Isailovic: None declared, Maria De Santis: None declared, Carlo Selmi Consulting/ speakers fee (AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI), Research support (AbbVie, Amgen, Janssen, Novartis, Pfizer), Angela Ceribelli: None declared.

BackgroundCancer-associated myositis (CAM) remains a clinical challenge and established risk factors include older age, male sex, dermatomyositis (DM), and specific antibodies, including anti-TIF1gamma and -MJ/NXP2 [1]. However, a recent report suggests a lower risk of malignancy in -TIF1gamma positive patients with other concurrent autoantibodies (2,3), whereas the protective role against malignancy of antisynthetase or anti-Mi-2 antibodies is being questioned [1].ObjectivesTo describe the demographic, clinical, and serological characteristics of a cohort of patients with CAM in a specific autoantibody profile.MethodsRetrospective cohort analysis on electronic clinical charts, autoantibody analysis by serum immunoprecipitation and ELISA.ResultsMalignancy was observed in 17/73 (23%) patients with IIM, in 13/17 (76%) within 5 years before or after IIM diagnosis and cancer relapse or progression in 7 cases; 2/17 were men with a median age of 56 years. Breast cancer was the most frequent, followed by lung, thyroid, ovarian, and lymphoma. Four patients died, three for cancer-related complications and one for severe refractory IIM.Muscle injury was observed in 13/17 (76%) while 2/17 experienced dysphagia. Skin lesions were present in 14/17 (82%) patients, while ILD (24%) and arthritis (18%) rarely occurred; no cases of myocardial involvement were described.Anti-Ro52 was the most common antibody (5/17 – 29%) in our cohort, detected as the only specificity in 2/5 cases. Anti-TIF1gamma was described in 4/17 (24%, one case with concurrent -Ro52), followed by antisynthetase (3 – 18%), -Mi-2 (2 – 12%), -MJ/NXP2, -SAE1, -SRP (1 each – 6%). Combined anti-E2/E3 PDH (AMA) and anti-Ro positivity was found in a patient who developed lymphoma and cholangiocarcinoma within two years from IIM.We compared CAM patients with (n=4) and without (n=13) serum anti-TIF1gamma (Table 1). Albeit not reaching statistical significance, dysphagia and skin disease were more frequently observed with anti-TIF1gamma, whereas arthritis, Raynaud’s phenomenon, and capillaroscopy alterations were rarer in such group. Prevalence of early-stage cancer seemed more frequent with anti-TIF1gamma. 3/13 patients without anti-TIF1gamma died due to cancer-related causes; the only death observed in the TIF1gamma positive group was due to progressive IIM, and occurred in a patient with complete cancer remission.ConclusionWe observed that DM remains the most common clinical subset of CAM, but other myositis phenotypes can be also observed. Anti-TIF1gamma remains the more prevalent autoantibody in CAM along with anti-Ro52. The role of AMA positivity may warrant further investigation, particularly in patients with seronegative CAM.References[1]Kardes S, et al. Best Pract Res Clin Rheumatol. 2022;[2]Fiorentino DF, et al. J Clin Invest. 2022;[3]Hosono Y, et al. Ann Rheum Dis. 2022.TableClinical features of patients with (+) and without (–) anti-TIF1gamma antibodiesAnti-TIF1gamma+ (n=4)Anti-TIF1gamma– (n=13)pAdvanced cancer at diagnosis, n.(%)0 (0)3 (23.1).3041Dysphagia, n.(%)1 (25)1 (7.7).3624Skin rash, n.(%)4 (100)10 (76.9).3041Gottron, n.(%)3 (75)6 (46.2).3276Raynaud, n.(%)0 (0)4 (30.8).2181Capillaroscopy alterations, n.(%)1 (25)9 (69.2).1276Arthritis, n.(%)0 (0)3 (23.1).3041Acknowledgements:NIL.Disclosure of InterestsAngela Ceribelli: None declared, Antonio Tonutti: None declared, Natasa Isailovic: None declared, Maria De Santis: None declared, Carlo Selmi Speakers bureau: ABBVIE, AMGEN, ALFA-WASSERMANN, BIOGEN, ELI-LILLY, GALAPAGOS, JANSSEN, NOVARTIS, PFIZER, SOBI, Grant/research support from: ABBVIE, AMGEN, PFIZER.

Background:Primary heart involvement (pHI) constitutes a significant source of morbidity and mortality in patients with systemic sclerosis (SSc) and cardiac magnetic resonance (CMR) serves as the standard diagnostic tool[1] for myocardial inflammation and fibrosis. Predictors of SSc-pHI remain poorly defined, as does the clinical profile of this patient subgroup.Objectives:To analyze the clinical, serological, and imaging features of patients with SSc and CMR-confirmed pHI, and to compare patients with inflammatory vs. fibrotic myocardial lesions.Methods:In our retrospective cohort study, the signs of inflammatory myocarditis at CMR included increased T2 mapping native time, elevated T2 myocardial/skeletal muscle ratio, or the presence of areas of T2 TIRM. The presence of late gadolinium enhancement, as well as increased T1 mapping native time and extracellular volume in the absence of increased T2, suggested myocardial fibrosis.Results:Out of 350 SSc cases, 45 (13%) underwent CMR due to suspected pHI, defined by the presence of symptoms (palpitations, angor, dyspnea, syncope), elevated myocardial enzymes, or new-onset arrhythmia observed in the 24-hour Holter ECG. SSc-pHI was diagnosed in 37 out of 45 (82%) cases, and these patients had more frequently diffuse SSc (dcSSc) (32% vs. 0; p = 0.06), along with a lower prevalence of anti-topoisomerase-I (TOPO1 – 41% vs. 88%, p = 0.016; p = 0.024 at multivariable analysis). Moreover, increased serum CK-MB (30% vs. 0; p = 0.051) and troponins (32% vs. 0; p = 0.037) were associated with SSc-pHI (Table 1).Considering patients with CMR-confirmed SSc-pHI, a comparison was made between those with early (< 3 years) and longstanding SSc (≥ 3 years; median disease duration at pHI diagnosis 10.5 years, IQR 8.8-12.3) (Table 2). Anti-TOPO1 was more common in early SSc with pHI (65% vs. 20%; p = 0.006), while anticentromere (24% vs. 60%; p = 0.026) and anti-SSA (0 vs. 25%; p = 0.027) were more prevalent in longstanding SSc. Patients with early SSc and pHI exhibited a higher skin score (median 8 vs. 4; p = 0.06) and a higher prevalence of interstitial lung disease (76% vs. 45%; p = 0.052), while myositis was more common in SSc patients with longstanding disease and pHI (0 vs. 20%; p = 0.051). Elevation of C-reactive protein (53% vs. 20%; p = 0.036) or CK-MB (58% vs. 24%; p = 0.057) predicted pHI in early SSc but not in longstanding disease; conversely, exertional dyspnea (24% vs. 55%; p = 0.052) was a predictor of pHI in longstanding disease but not in early SSc.T1/T2 mapping was available for 33 patients: sixteen (48%) patients (five of them with also LGE areas) had an increase in both T1 and T2 mapping native times, 9 (27%) had isolated T2 increase, 6 (26%) had isolated T1 increase, and 2 (9%) had only LGE. These four CMR clusters were not significantly or differently associated with clinical, laboratory, or cardiac functional alterations, maybe due to the small sample size.Conclusion:The diffuse cutaneous phenotype and increased serum myocardial enzymes predict pHI at CMR in patients with SSc. In early SSc, pHI is associated with anti-TOPO1, elevated skin score, C-reactive protein, and CK-MB. A CMR-based phenotyping of pHI SSc patients warrants further investigation.REFERENCES:[1] Bruni C, et al. JSRD. 2023.Table 1. Predictors of SSc-pHI confirmed at CMR.Table 2. Comparison between patients with early vs. longstanding SSc and CMR-confirmed SSc-pHI.Acknowledgements:NIL.Disclosure of Interests:Maria De Santis: None declared, Antonio Tonutti: None declared, Francesca Motta: None declared, Angela Ceribelli: None declared, Stefano Rodolfi: None declared, Lorenzo Monti: None declared, Marco Francone: None declared, Carlo Selmi AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Janssen, Novartis, Pfizer.

Background:Systemic sclerosis (SSc) is linked to an increased risk of cancer, and cancer-associated SSc is defined when occurring within three years of the detected malignancy. Predictors of cancer are poorly elucidated with clinical features, serum autoantibodies, and exposure to immunosuppressants proposed as candidates.Objectives:To investigate the clinical, serological, and therapeutic characteristics associated with the prevalence of cancer overall and cancer-associated SSc.Methods:In this retrospective cohort study, we analyzed the clinical features, including therapies, and the serum autoantibody profile obtained with RNA- and protein-immunoprecipitation, Western-blot, immunoblot, and ELISA. Patients negative for anticentromere (ACA), anti-Scl-70, and anti-RNA polymerase III (RNAP3) were defined CTP-negative.Results:A total of 290 patients with SSc (followed for a total of 5,370 patient-years) were included, with a mean age of 54 ± 16 years, 7% males, 25% with smoking history; 15% had diffuse SSc (dcSSc), 33% interstitial lung disease, 13% primary heart involvement, and 12% increased pulmonary arterial pressure. Autoantibody distribution was as follows: 56% ACA, 23% anti-Scl-70, and 9% anti-RNAP3.A diagnosis of cancer was made in 59 (20%) subjects, while cancer-associated SSc was observed in 23 (8%) cases. Both overall cancer and cancer-associated SSc were more frequent in patients who were older at the time of diagnosis and with anti-Ro52 or U3-RNP (Table 1). Combining clinical manifestations and autoantibodies, CTP-negative patients with dcSSc had a higher prevalence of cancer-associated SSc, as well as overall cancers.In the analysis of immunosuppressants, 13 patients in which cancer preceded SSc were excluded. The overall exposure to immunosuppressants was not associated with cancer occurrence. Fifty patients were on mycophenolate mofetil (MMF) treatment at the time of this analysis (median dosage 2 g/d – IQR 1.5-3; median duration 36 months – IQR 15-57): lower cancer prevalence was noted among patients on MMF (3/50, 6%) compared to counterparts not receiving any immunosuppressant [41/221, 19%; p = 0.030; OR 0.28, 95% CI (0.05-0.94)].The most common cancers originated from the breast [22/59 (37%)], lung [8/59 (14%)], or were hematologic [7/59 (12%)] malignancies. Older age, anti-Ro52, and CTP-negative status (especially in dcSSc) were observed more frequently in patients with breast cancer compared to cancer-negative SSc. Lung cancer was associated with older age, male sex, dcSSc, increased pulmonary arterial pressure, anti-Th/To, and U3-RNP, but not with interstitial lung disease. Hematologic malignancies were associated with a higher prevalence of anti-U3-RNP.Conclusion:We propose factors to be considered to stratify patients with SSc into different subsets according to cancer risk and maximize the efficacy of screening programs. Of note, we confirm the role of the CTP-negative status, and propose for the first time that rarer autoantibodies are associated with cancer in SSc.REFERENCES:NIL.Table 1. Demographic, clinical, and serological features of patients with SSc without cancer, overall cancers, and cancer-associated SSc.Table 2. Demographic, clinical, and serological features of patients with SSc according to different types of cancer, compared with the cancer-negative SSc counterpart.Acknowledgements:NIL.Disclosure of Interests:Maria De Santis: None declared, Antonio Tonutti: None declared, Francesca Motta: None declared, Angela Ceribelli: None declared, Natasa Isailovic: None declared, Rita Ragusa: None declared, Carlo Selmi AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Janssen, Novartis, Pfizer.

Background:Regenerative treatments like autologous blood-derived platelet-rich plasma (PRP) injections have shown promising results for knee osteoarthritis (OA), a degenerative disease-causing chronic disability worldwide. The absence of treatment response predictors limits the use of PRP injections[1].Objectives:To establish a serological profile predictive of the patients’ response to PRP injection for knee OAMethods:Seventy-nine patients with knee OA (58% females; median age 63 years – IQR 53.5-68.5; Kellgren and Lawrence radiological grade 2-3, excluding post-traumatic or inflammatory arthritis) were prospectively enrolled. Prior to PRP injection, peripheral blood samples were collected to analyze molecular markers associated with inflammatory (WNT, IL-1 superfamily, IFN-γ) and antioxidant (DPP3, 4-Hydroxy-2-nonenal – HNE) pathways through RT-qPCR, ELISA, and enzymatic assays. Thirty/79 patients completed the 12-month follow-up post-PRP injection; responders were defined if they had a significant improvement of the WOMAC pain, stiffness, and disability score at 12 months.Results:Among the 30 patients who completed the 12-month follow-up, 23 (77%) were responders. No significant differences were observed in age, sex, smoking history, or prior knee OA treatments between responders and non-responders.Responders exhibited significantly higher expression of WNT antagonists, specifically SFRP3/Frzb (Figure 1-A). RANKL and TNF-α levels were higher among responders, suggesting greater osteoclast activation through both RANKL-dependent and independent mechanisms (Figure 1-B). In terms of cytokines, responders showed higher levels of IL-18, which is known to induce chondrocyte apoptosis, and IL-36γ, which activates synoviocyte secretion of inflammatory molecules and catabolic enzymes (Figure 1-C). Despite heterogeneity in expression, levels of the antagonist IL-18BP were also higher among responders, possibly reflecting a counter-regulatory mechanism (Figure 1-D). Cellular expression of IL-1 receptor 1 and its related transduction protein MyD88 was more pronounced in responders, indicating a stronger tendency towards IL-1 signaling, and balanced by higher levels of the decoy IL-1 receptor 2 (Figure 1-E). Patients with higher baseline levels of IFN-γ and IL-7, an enhancer of IFN-γ expression in activated T cells, did not respond to PRP injection.Despite a non-significant difference in antioxidant capacity, responders had higher HNE levels, together with lower serum levels of DPP3 (Figure 2).Conclusion:Patients with knee OA responding to PRP injection are characterized by a pronounced inflammatory signature driven by IL-18 and IL-36 and lower IFN-γ, higher levels of WNT antagonists, and enhanced osteoclast-activating stimuli. Also, impaired oxidative stress protection mechanisms at baseline may characterize patients responding to PRP.REFERENCES:[1] Tonutti A et al. Front Aging. 2023 Jun 8:4:1201019Acknowledgements:Italian Ministry of Health, BANDO RICERCA FINALIZZATA 2019, project GR-2019-12370692.Disclosure of Interests:Antonio Tonutti: None declared, Valentina Granata: None declared, Veronica Marrella: None declared, Cristina Sobacchi: None declared, Rita Ragusa: None declared, Cristiano Sconza: None declared, Nicola Rani: None declared, Berardo Di Matteo: None declared, Carlo Selmi AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Janssen, Novartis, Pfizer, Angela Ceribelli: None declared.

BackgroundSustained minimal disease activity (MDA) is achieved by a minority of patients (pts) receiving biologics for psoriatic arthritis (PsA) [1]. Pt-reported MDA domains are less frequently achieved than physician-reported domains [2,3]. Here, we assessed MDA achievement in pts with PsA and inadequate response to 1–2 tumour necrosis factor inhibitors (TNFi-IR).ObjectivesIdentify PsA disease domains and factors contributing to the lack of MDA achievement at Week (W)48 for TNFi-IR PsA pts treated with guselkumab (GUS) using data from the Phase 3b COSMOS trial.MethodsIn COSMOS, adults with active PsA (swollen/tender joint counts [SJC/TJC] each ≥3) and TNFi-IR were randomized 2:1 to subcutaneous GUS 100 mg or placebo (PBO) at W0, W4, then every 8 weeks. PBO pts crossed over to GUS at W16 (early escape) or W24 (planned). MDA was defined as fulfilment of ≥5/7 domains: tender entheses (Leeds Enthesitis Index [LEI]; 0–6) ≤1; Health Assessment Questionnaire – Disability Index (HAQ-DI; 0–3) ≤0.5; pt pain (0–100) ≤15; Psoriasis Area and Severity Index.(PASI; 0–72) ≤1; Pt Global Assessment (PtGA; 0–100) ≤20; SJC (0–66) ≤1; and.TJC (0–68) ≤1. Fibromyalgia (pFM) was defined at baseline (BL) using TJC minus SJC ≥7 as a proxy [3]. A longitudinal trajectory of achieving each MDA domain through W48 was derived (non-responder imputation). Time to achieving each domain was assessed with.Kaplan–Meier analyses; to account for differences in scales and domain strictness, scores were also normalized to SJC (0–66) scale. Response predictors (for pts not meeting each MDA domain criteria at BL) were identified using multivariate regression for time to achievement (Cox proportional hazards) and W48 achievement (logistic) of MDA.ResultsGUS pts (n=189) showed improvement from BL in all MDA domains, with overall W24/48 response rates (%) of: LEI (74.5/79.8), HAQ-DI (26.1/37.0), pt pain (14.7/30.6), PASI (66.8/81.5), PtGA (24.5/39.9), SJC (46.2/63.0) and TJC (14.7/28.3) respectively. Times to achievement of minimal scores for LEI, SJC and PASI were faster than for PtGA,HAQ-DI, pt pain and TJC for native-scale scores; when normalized, PtGA, HAQ-DI and pt pain showed a slower response (Figure 1). Higher BL HAQ-DI and worse fatigue (lower functional assessment of chronic illness therapy [FACIT]-fatigue score) were significantly associated with longer time to HAQ-DI ≤0.5; these factors plus older age predicted W48 non-achievement of HAQ-DI ≤0.5 (Table 1). Worse BL pt pain and fatigue were significant predictors of longer time to pt pain ≤15; these factors plus pFM predicted W48 non-achievement of pt pain ≤15. Worse BL fatigue was also significantly associated with longer time to PtGA ≤20 and W48 non-achievement of PtGA ≤20. Higher TJC, methotrexate (MTX) use and no pFM at BL were significantly associated with longer time to TJC ≤1; higher BL TJC, MTX and older age predicted W48 non-achievement of.TJC ≤1.ConclusionGUS provided sustainable improvement in all MDA domains through W48. Physician-reported domains (LEI, PASI and SJC) were achieved faster than pt-driven domains (PtGA, HAQ-DI, pt pain and TJC). BL domain scores, worse fatigue and MTX use (for TJC only) were inversely correlated with MDA in the refractory domains.References[1]Rahman P et al. BMJ Open 2017;7:e016619[2]Coates L et al. Ann Rheum Dis 2022;81:856–7[3]Kavanaugh A et al. Arthritis Rheumatol 2022;74(S9)Table 1.Predictors of time to achievement and achievement of pt-reported MDA domains at W48 in GUS ptsTime to achievementHR (95% CI)BL variableHAQ-DI ≤0.5Pt pain ≤15PtGA ≤20TJC ≤1FACIT-fatigue1.0(1.0–1.1)†1.0(1.0–1.1)†1.0(1.0–1.1)‡HAQ-DI0.3(0.2–0.6)‡Pt pain1.0(1.0–1.0)‡MTX use0.6(0.4–0.9)*pFM presence1.8(1.0–3.2)*TJC0.9(0.9–1.0)‡Achievement at W48OR (95% CI)Age1.0(0.9–1.0)*1.0(1.0–1.0)*FACIT-fatigue1.1(1.0–1.1)†1.1(1.0–1.1)†1.1(1.0–1.1)‡HAQ-DI0.2(0.1–0.5)†Pt pain1.0(1.0–1.0)†MTX use0.4(0.2–0.8)†pFM presence0.5(0.3–1.0)*TJC0.9(0.9–1.0)‡CI, confidence interval; HR, hazard ratio; OR, odds ratio*P<0.05; †P<0.01; ‡P<0.001Acknowledgements:NIL.Disclosure of InterestsLaura Coates Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Eli Lilly, Galapagos, Gilead, GSK, Janssen, Medac, Novartis, Pfizer and UCB, Consultant of: AbbVie, Amgen, Boehringer Ingelheim, Bristol Myers Squibb, Celgene, Eli Lilly, Gilead, Galapagos, Janssen, Moonlake, Novartis, Pfizer and UCB, Grant/research support from: AbbVie, Amgen, Celgene, Eli Lilly, Janssen, Novartis, Pfizer and UCB, Carlo Selmi Speakers bureau: AbbVie, Amgen, Alfa-Wassermann, Biogen, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, SOBI, Paid instructor for: Amgen, Eli Lilly, Janssen, Novartis, Consultant of: AbbVie, Amgen, Alfa-Wassermann, Biogen, Eli Lilly, Galapagos, Janssen, Novartis, Pfizer, SOBI, Grant/research support from: AbbVie, Amgen, Pfizer, Georg Schett: None declared, Pascal Richette Speakers bureau: UCB, Janssen, Pfizer, Abbvie, Lilly, Novartis, Consultant of: UCB, Janssen, Pfizer, Abbvie, Lilly, Novartis, Julio Ramírez Speakers bureau: Abbvie, UCB, Janssen, Novartis, Pfizer, Angem and Lilly, Paid instructor for: Novartis and Janssen, Consultant of: Janssen, Novartis, Abbvie and UCB, Grant/research support from: Pfizer, Wim Noel Shareholder of: Johnson and Johnson, Employee of: Janssen Pharmaceutical Companies of Johnson and Johnson, Emmanouil Rampakakis Consultant of: Employee of JSS Medical Research, a contract research organization (CRO) providing services to pharmaceutical and biotechnology stakeholders, Miriam Zimmermann Employee of: Janssen Pharmaceutical Companies of Johnson and Johnson, Mohamed Sharaf Employee of: Janssen Pharmaceutical Companies of Johnson and Johnson, Dennis McGonagle Speakers bureau: Abbvie, Celgene, MSD, UCB, Lilly, Novartis, Janssen, Paid instructor for: Abbvie, Celgene, MSD, UCB, Lilly, Novartis, Janssen, Grant/research support from: Abbvie, Celgene, MSD, UCB, Lilly, Novartis, Janssen.

BackgroundMyocardial involvement is frequently asymptomatic at the early stages in systemic sclerosis (SSc) but accounts for one-third of SSc-related deaths [1]. First-line screening tools include cardiac enzymes, Holter ECG, and echocardiography [2,3], while the diagnosis relies largely on cardiac magnetic resonance [4], assessing myocardial inflammation and fibrosis [5]. The prevalence of SSc myocardiopathy and the associated factors are poorly defined [2].ObjectivesTo evaluate the prevalence of myocardiopathy and the associated demographic, clinical, and instrumental features in a single center cohort of 317 SSc patients, including 49 (15%) early SSc, 66 (21%) anti-Scl70+, 178 (56%) anti-centromere (ACA)+, 45 (14%) diffuse, 99 (31%) ILD, 37 (12%) with pulmonary hypertension.MethodsRetrospective analysis; myocardiopathy in SSc was defined as increased myocardial tissue to skeletal muscle T2 ratio, T2 TIRM or delayed enhancement areas, or increased T1 or T2 mapping native time at cardiac magnetic resonance [6].ResultsForty-two SSc patients underwent cardiac magnetic resonance after developing symptoms (dyspnea, atypical angor, palpitations; 43%), elevated cardiac enzymes (55%), or Holter ECG alterations (38%). Myocardiopathy was detected in 29/42 patients (69%; 29/317, 9.2%). Early disease was significantly more frequent in patients with myocardiopathy (17/29, 59%; OR 7.8, 95% CI 1.45-41.7); 17/49, 35% considering early SSc in the whole cohort). Among patients with myocardiopathy, anti-Scl70 was more frequently observed in early compared to longstanding disease (9/17, 53% vs. 2/12, 17%; p = 0.05); the opposite was for ACA (4/17, 24% vs. 7/12, 58%; p = 0.06) (Figure 1).Clinical characteristics did not differ among patients with and without myocardiopathy, except digital ulcers (Table 1). Serum troponin I (TnI) was higher in patients with myocardiopathy (median 6 vs 1.6 ng/L; p = 0.049). Relevant alterations on Holter ECG, especially premature ventricular contractions (PVC) > 300/day, were observed more frequently in patients with myocardiopaty (p = 0.04 for both; Table 1).ConclusionWe report a relevant overall prevalence of myocardiopathy in a cohort of SSc patients, similar pulmonary hypertension, affecting one third of patients with early SSc, especially with anti-Scl70. Conversely, a delayed onset of myocardiopathy was associated with ACA. Among other predictors, higher serum troponins and Holter ECG alterations, especially PVC, were significantly associated to myocardiopathy. As the early suspicion and diagnosis of myocardiopathy are crucial for promptly starting immunosuppressive treatment, we submit that the risk stratification should be performed in patients with SSc.References[1]Champion HC. Rheum Dis Clin North Am. 2008.[2]Bruni C, Ross L. Best Practice & Research Clinical Rheumatology. 2021.[3]Ross L,et al. Semin Arthritis Rheum. 2021.[4]Basso C. N Engl J Med. 2022.[5]Ferreira VM, et al. J Am Coll Cardiol. 2018.[6]Mavrogeni S, et al. Semin Arthritis Rheum. 2022.Table 1CM (29)No CM (13)pSerologyScl-70 (%)11 (38)2 (15).15ACA (%)11 (38)9 (69).06RNA pol III (%)3 (10)2 (15).64ClinicaldcSSc (%)12 (41)3 (23).26mRSS4 (1-9)2 (0-10).81Early SSc (%)17 (59)3 (23).03ILD (%)16 (55)5 (39).32Ulcers (%)1 (3)3 (23).047Calcinosis (%)2 (7)1 (8).93Gut (%)7 (24)4 (31).65HolterHolter any (%)22/28 (79)6/13 (46).04PSVC > 1.27/h (%)21/28 (75)6/12 (50).13PVC > 300/d (%)11/28 (39)1/13 (8).04Cardiac magnetic resonancePericardial effusion (%)11 (38)3 (23).35LabBNP46.5 (34-138)113.5 (52-190).20CK88 (60-171)91 (61-153).96CK-MB3.2 (1.2-9.7)1.4 (1.1-3.3).32TnI6 (1.9-26)1.6 (0-4.5).049Legenda: dcSSc: diffuse SSc; mRSS: modified Rodnan skin score; P(S)VC: premature (supra)ventricular contractions; Holter any: PSVC > 1.27/h or PVC > 300/d. Continuous variables are reported as medians (interquartile range).Figure Autoantibody distribution in patients with SSc-myocardiopathyAcknowledgements:NIL.Disclosure of InterestsMaria De Santis: None declared, Antonio Tonutti: None declared, Francesca Motta: None declared, Stefano Rodolfi: None declared, Lorenzo Monti: None declared, Marco Francone: None declared, Carlo Selmi Speakers bureau: AbbVie, Amgen, Alfa-Wassermann, Biogen, Eli-Lilly, Galapagos, Janssen, Novartis, Pfizer, SOBI, Consultant of: AbbVie, Amgen, Alfa-Wassermann, Biogen, Eli-Lilly, Galapagos, Janssen, Novartis, Pfizer, SOBI, Grant/research support from: AbbVie, Amgen, Pfizer.

Background:The diagnostic process for rheumatic diseases is challenging due to their wide clinical heterogeneity and long course. Electronic medical records (EMR) of these patients are often overdetailed anddo not allow a clear synthesis of the patient history. Natural Language Processing (NLP) techniques can have a crucial impact on the automated analysis of EMR clinical text data, aiding in this diagnostic process. We hypothesize that NLP tools are capable to discriminate rheumatic diseases from free-text narratives and ultimately assist physicians in diagnosing complex diseases, especially when clinical features overlap.Objectives:To investigate and compare various NLP-based solutions applied to medical records for the capacity to differentiate patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), or other diseases, namely osteoarthritis or fibromyalgia.Methods:The dataset consisted of 236 Italian outpatients EMR, extracted from the Electronic Health Record of Humanitas Research Hospital (Milan, Italy) from January 2016 to September 2023 by selecting those of patients with an established diagnosis and a regular follow up at Rheumatology Unit. The EMR of 55 patients diagnosed with RA, 68 with PsA, and 113 with other conditions were included and evaluated blindly for the aims of this study in terms of the diagnosis consistently made by experienced rheumatologists. Two techniques were employed for text embedding: Word2Vec, which captures just the semantic meaning of each word (Mikolov et al., 2013), and BERT, which also considers the contextual information within the text (Devlin et al., 2019). To compare the capability of these techniques in capturing relevant clinical information for classification purposes we used a deep-learning approach, the Convolutional Neural Network (CNN). We devised a novel method to maximize the potential of BERT, leveraging its embeddings that carry rich contextual meaning within the text: creating a new data vector that encapsulates the summary of BERT’s embedding allowed us to test other classification models as KNN, SVM, XGBOOST, RF LR and NN. Finally, we experimented an alternative method of classification, consisting in the fine-tuning of BERT’s built-in classification capabilities. Each of these models has different level of complexity, computational cost and methods of recognizing patterns in the data for classification purposes. By comparing the result from these models, we aim to identify the optimal Machine Learning architecture for our goal.Results:The approaches were compared in their capacity to assign each patient to the correct class (RA vs PsA vs others), expressed in terms of peak accuracy rates. Considering the embedding methods, BERT showed a better performance than Word2Vec in the CNN methods, achieving a peak accuracy of 0.69. The KNN outperformed the CNN achieving an accuracy of 0.73. The other classification models, including BERT’s fine-tuned downstream classifier, showed mixed results and, in general, worse performance than the CNN. Evaluating the confusion matrices, all models showed better performances in the prediction of the “other” category than in the differentiation between psoriatic and rheumatoid arthritis.Conclusion:Our models obtained favourable outcomes in the differentiation between inflammatory conditions (namely RA or PsA) and non-inflammatory diseases (osteoarthritis or fibromyalgia), particularly in the case of the KNN, the best performing model. We believe that our novel approach for handling BERT output might foster further investigation in the field for a more structured and organized use of BERT’s data. While we recognise that our model is not suitable for use in clinical practice, the future prospective analysis of an extended and standardized dataset could improve the performances.REFERENCES:[1] Mikolov T., Chen K., Corrado G., Dean J. (2013). Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781.[2] Devlin J, Chang MW, Lee K, Toutanova K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of NAACL-HLT (pp. 4171-4186).Acknowledgements:NIL.Disclosure of Interests:Antonio Papatolo: None declared, Benedetta Maizza: None declared, Alessandro Bellone: None declared, Sofia Di Giorgio: None declared, Gaia Tettamanzi: None declared, Maria Chiara Grondelli: None declared, Nicola Lambri: None declared, Nicoletta Luciano AbbVie, BMS, Eli-Lilly, Janssen, Galapagos, Novartis, Elisa Barone: None declared, Daniele Loiacono: None declared, Carlo Selmi AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Pfizer, Recordati, SOBI, AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Pfizer, Recordati, SOBI, Research support: AbbVie, Amgen, Janssen, Novartis, Pfizer.

Background:Risankizumab is the most recently approved drug used for the treatment of Psoriatic arthritis (PsA). Risankizumab is a humanized IgG1 monoclonal antibody that specifically inhibits interleukin 23 (IL-23) by binding to its p19 subunit.Objectives:The KEEPsAKE 1 and 2 trials have demonstrated the efficacy and safety of Risankizumab in naïve and TNF-experienced patients with PsA. Here we report the real-life efficacy and safety of Risankizumab in an Italian cohort of PsA patients.Methods:In this observational retrospective trial, we reported clinical data of PsA patients who satisfied CASPAR criteria admitted to the combined dermatologist-rheumatologist outpatient clinics of 5 Italian centers. Each patient underwent a complete clinical exam evaluating cutaneous and joint disease with activity index. We used DAPSA and VAS pain to assess the clinical activity of joint disease and BSA, PASI and VAS pruritus as dermatological indexes. All patients were treated with Risankizumab according to common clinical practice. The primary endpoint was the achievement of low disease activity or remission according to DAPSA after 6 months of therapy with good efficacy also on the skin component.Results:In this work, we enrolled 44 PsA patients (28 males and 16 females) who satisfied CASPAR criteria. The mean age was 56.2 years and most of the patients were overweight (mean BMI 29.1). Most of them had a long disease duration (mean duration 11.4 years) so it is not surprising that 73% of patients were already bDMARDs experienced (of them 61% TNF non-responders). At baseline, all patients reported moderate disease activity (mean DAPSA 19.7) with extensive skin psoriasis (mean Body surface area 21.3% and mean PASI 16.3). After 6 months of treatment with Risankizumab, 62% of patients obtained a good DAPSA response (p<0.0001). Figure 1 Of them 19% reached remission and 43% reached low disease activity. Moreover, good clinical responses were observed also for BSA and PASI with a reduction respectively of 75% and 87%. After 12 months of treatment, 82% of patients were in low disease activity or remission with a mean DAPSA of 7.4 (p<0.0001). Figure 2Conclusion:This is the first paper that evaluated the efficacy of Risankizumab in PsA patients in a real-life setting. Patients enrolled in clinical trials do not represent patients who are evaluated in a clinical setting and who have multiple comorbidities that influence therapeutic choice and pharmacological response. Particularly, our PsA patients had a long disease duration and most of them were bDMARDs experienced. Risankizumab was demonstrated to be efficacious both in naïve and in multi-failure patients. The primary and secondary endpoints were reached: 62% of patients had a good clinical response at 6 months and 82% of patients were in LDA/remission at 12 months of treatment. Numerous clinical trials and real-life data showed the effectiveness of Risankizumab on psoriasis, confirming the pivotal role of blocking IL-23 on the skin. The effectiveness on skin psoriasis was also confirmed in our work: after 6 months of treatment, a reduction in PASI of approximately 90% was recorded (mean PASI 2). During the entire follow-up period, no patient reported a reaction at the injection site, infectious episodes, or any adverse event worthy of medical discussion. In conclusion, risankizumab is a good option also for PsA patients who are multi-drug resistant. Further studies are necessary to confirm our results and to confirm the efficacy of risankizumab in “complex” patients in real life.REFERENCES:[1] Efficacy and safety of risankizumab for active psoriatic arthritis: 24-week results from the randomised, double-blind, phase 3 KEEPsAKE 1 trial. Kristensen LE, Keiserman M, Papp K, McCasland L, White D, Lu W, Wang Z, Soliman AM, Eldred A, Barcomb L, Behrens F. Ann Rheum Dis. 2022 Feb;81(2):225-231.[2] Efficacy and safety of risankizumab for active psoriatic arthritis: 52-week results from the KEEPsAKE 2 study.Östör A, Van den Bosch F, Papp K, Asnal C, Blanco R, Aelion J, Lu W, Wang Z, Soliman AM, Eldred A, Padilla B, Kivitz A.Rheumatology (Oxford). 2023 Jun 1;62(6):2122-2129.Acknowledgements:NIL.Disclosure of Interests:None declared.

Background:Apremilast, a phosphodiesterase-4 inhibitor, is approved for treating psoriatic arthritis (PsA) but its mechanisms of action remain elusive. Conventional T cells and innate lymphocytes, including NK cells, NKT cells, γδT cells, innate lymphoid cells (ILCs), and mucosal-associated invariant T (MAIT) cells play a pivotal role in PsA pathogenesis, contributing to IL-23-dependent and -independent pathways to IL-17 expression.Objectives:To investigate the ex vivo effects of apremilast in PsA patients by characterizing: 1. the conventional T and innate lymphocytes (NK, NKT-like, γδT, ILC1/2/3, and MAIT); 2. The production of IL-17 by T cells, ILCs, and MAIT cells; 3. The production of IFN-γ, IL-9, and IL-10 from T cells, NK cells, NKT-like cells, γδT cells, and ILCs.Methods:Peripheral blood samples were collected from 7 treatment-naïve patients with peripheral PsA (median age 48 years, IQR 44-58; 2 females; median DAPSA 15, IQR 10-18) prior to and 4 months after being treated with apremilast 30mg BID, and 5 knee osteoarthritis (OA) controls (median age 61, IQR 48-74; 2 females). Lymphocyte phenotype and cytokine production were analyzed by flow cytometry using unstimulated or stimulated conditions (PMA 50 ng/mL + ionomycin 1 μg/mL together with BFA) at baseline in both OA and PsA patients, and after 4 months of apremilast in PsA.Results:At baseline, PsA patients had higher percentages of IFN-γ+ γδT cells, IL-9+ NK cells, and IL-10+ NKT-like, NK, and γδT cells compared to OA (Figure 1, panels a-c). Baseline IL-17 expression was similar between PsA and OA cells. After 4 months of apremilast therapy, all patients achieved low disease activity and a significant reduction in IFN-γ+ γδT cells, in IL-17+ conventional T cells, and in IL-17+ ILC1 cells was observed (Figure 2, panels a-c). Apremilast also led to a reduction in IL-10+ NK, NKT-like, and γδT lymphocytes (Figure 2, panel d). No significant effects in terms of cytokine production were induced on MAIT cells after apremilast treatment.Conclusion:In responder PsA patients, apremilast down-modulates IFN-γ production mainly from innate-like cells, particularly γδT cells, whereas IL-17 production is inhibited also in conventional T cells. An IL-10 signature characterizes innate-like cells from patients with active PsA, and is down-regulated by apremilast, thus likely representing a counter-regulatory mechanism of the immune system towards dysregulated inflammation.REFERENCES:NIL.Figure 1.IFN-γ, IL-9, and IL-10 expressing cells in psoriatic arthritis (PsA) patients before apremilast use and in osteoarthritis (OA) controls.Figure 2.Effect of apremilast on selected cytokines by different lymphocyte subsets from patients with PsA.Acknowledgements:NIL.Disclosure of Interests:Maria De Santis: None declared, Antonio Tonutti: None declared, Francesca Motta: None declared, Natasa Isailovic: None declared, Angela Ceribelli: None declared, Giacomo Maria Guidelli AbbVie, BMS, Eli-Lilly, Galapagos, Janssen, Novartis, AbbVie, BMS, Eli-Lilly, Galapagos, Janssen, Novartis, Marta Caprioli: None declared, Daniela Renna Janssen, Nicoletta Luciano AbbVie, BMS, Eli-Lilly, Galapagos, Janssen, AbbVie, BMS, Eli-Lilly, Galapagos, Janssen, Carlo Selmi AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Alfa-Sigma, Biogen, Eli-Lilly, EUSA Pharma - Recordati, Galapagos, Janssen, Novartis, Octapharma, Pfizer, Recordati Rare Disease, SOBI, AbbVie, Amgen, Janssen, Novartis, Pfizer.