OP0326 DO RA RISK FACTORS ALSO AFFECT THE SPEED OF CLINICAL RA ONSET

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Background: RA is a heterogenous disease with an incompletely understood but presumably heterogenous etiology. Age, sex, genetics, smoking, socio-economy and serological markers have all been identified as risk factors or determinants for RA. Whether such factors not only affect the risk of RA (vs. not RA) but also affect the speed at which clinical RA appears and RA is diagnosed remains unknown but of importance for our understanding of RA etiology and for future programs towards targeted preventive intervention of individuals at increased risk. Objectives: To investigate whether (combinations of) known RA risk factors are associated with the time between onset of RA symptoms and the clinical RA diagnosis. Methods: Using data from the Swedish EIRA case-control study we identified 2229 individuals diagnosed with RA within 12 months from the first reported onset of RA-symptoms 2004-2017. For each individual, we retrieved and categorized information on months of RA symptom duration at RA diagnosis, age, sex, year of diagnosis, the diagnosing rheumatology clinic, smoking status (current vs. former vs. past vs irregular), educational level (compulsory (≤9 years), 9-12 years or 12 or more years of formal education), RA serology (RF and/or CCP2 vs. neither), shared epitope (0 vs. 1 vs. 2 alleles) and polygenic risk score for RA (quintiles). For each risk factor/determinant, we calculated the median (IQR) time interval between the self-reported onset of RA-symptoms and the subsequent diagnosis. We used linear regression to assess the association between the risk factors/determinants and time interval, in months, between symptom onset and RA diagnosis. Since seropositive and seronegative RA are presumed to be fundamentally different conditions and since most known RA risk factors are linked to seropositivity, all but the initial descriptive analyses were restricted to the seropositive subset. Results: In seropositive RA, the median time from self-reported onset of RA symptoms until the RA diagnosis was remarkably similar across all investigated categories and combinations of established RA risk factors (Table 1). When (in analyses restricted to seropositive RA) adjusted for each other and for contextual factors, neither sex, shared epitope status, smoking nor RA polygenic risk scores demonstrated any independent association with symptom duration, with only a borderline association with age (Table 2). Conclusion: Among individuals diagnosed with RA within one year from their first reported onset of RA-symptoms, established RA risk factors do not seem to influence the time between onset of clinical RA symptoms and the clinical RA diagnosis. This lack of association does not preclude that the "speed of onset" of RA in its pre-clinical phase varies with the same risk factors. REFERENCES: NIL . Table 1Distribution of RA symptom duration (in months, max 12) at RA diagnosis, overall and stratified by risk factorsand combinations thereofPopulationCategoryN (%) of all seropositive patients*Symptom duration, median (IQR)All seropositive RAAll1622 (100)5.0 (5.0)-SexFemales1172 (72)5.0 (5.0)Males450 (28)5.0 (4.0)-Age at RA diagnosis65 or above392 (24)5.0 (4.0)Below 651230 (76)5.0 (5.0)-Shared Epitope (alleles)0174 (20)5.0 (5.0)1477 (54)6.0 (4.0)2225 (26)5.0 (5.0)-SmokingNever534 (33)5.0 (4.0)Former665 (41)5.0 (5.0)Current410 (25)6.0 (4.0)Irregular13 (8)5.0 (3.0)-RA Polygenic risk score (quartiles)1262 (22)5.0 (5.0)2296 (25)5.0 (5.0)3310 (26)6.0 (4.0)4321 (27)6.0 (4.0)-Former smokers with two shared epitope copies and CCP2 positivity87 (5)5.0 (4.0)-Current smokers with two shared epitope copies and CCP2 positivity57 (4)5.0 (5.0)All seronegative RAAllN/A4.0 (3.0)*For this analysis, data on shared epitope was available for 876 (54%) and data on RA PRS was available for n=1189 (73%) of the entire seropositive group. Table 2Association (linear regression, seropositive RA only) between RA risk factors and combinations thereof and RA symptom duration (in months, max 12) at RA diagnosis.Beta-coefficients, univariate*Beta-coefficients, fully adjusted**Sex0.31 (-0.01;0.63)-0.03 (-0.54;0.49)Age-0.03 (-0.04;- 0.01)-0.02 (-0.04;0.00)N shared epitope alleles0.05 (-0.25;0.34)-0.07 (-0.40;0.26)SmokingNeverRefRefFormer-0.21 (-0.55;0.13)0.13 (-0.41;0.67)Current0.11 (-0.27;0.50)-0.17 (-0.78;0.44)irregular-0.26 (-1.91;1.39)-0.57 (-3.96;2.82)RA PRS (per quartile increase of RA risk genetics)0.09 (-0.06;0.25)0.01 (-0.19;0.22)*adjusted for calendar year of RA diagnosis, educational level and participating RA centre.**adjusted for all variables in table, plus calendar year of RA diagnosis, educational level and participating RA centre, in the subset containing complete data on all variables Acknowledgements: Funding: Swedish Research Council, Vinnova, ERA-PerMed, Swedish Heart Lung Foundation, ALF. Disclosure of Interests: Helga Westerlind: None declared, Younes Laalou: None declared, Anton Sysojev Öberg: None declared, Leonid Padyukov: None declared, Lars Klareskog: None declared, Bénédicte Delcoigne: None declared, Saedis Saevarsdottir: None declared, Caroline Grönwall: None declared, Johan Askling Abbvie, BMS, Eli Lilly, Galapagos, MSD, Pfizer, Roche, Samsung Bioepis, Sanofi. © The Authors 2025. This abstract is an open access article published in Annals of Rheumatic Diseases under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Neither EULAR nor the publisher make any representation as to the accuracy of the content. The authors are solely responsible for the content in their abstract including accuracy of the facts, statements, results, conclusion, citing resources etc.

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