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Rheumatoid Arthritis

      tRNA-derived RNA (tDR-1), circulating microbial RNA

      Associated w/ reduction in risk of RA conversion in asymptomatic CC

      Aurelie Najm AurelieRheumo

      1 week 3 days ago
      tRNA-derived RNA (tDR-1), circulating microbial RNA Associated w/ reduction in risk of RA conversion in asymptomatic CCP+ individuals (60 vs. 120+ ctrls), ‼️ tDR-1 alone over performs prediction model w/ smoking shared episode and RF w/ AUC 0.86 What is the mechanism? tDR-1 https://t.co/fuyk4NeOyA
      Ribeiro et al. Case series of combination bDMARD/tsDMARD in PsA from Toronto. 24 patients, median just over a year follo

      Richard Conway RichardPAConway

      1 week 3 days ago
      Ribeiro et al. Case series of combination bDMARD/tsDMARD in PsA from Toronto. 24 patients, median just over a year follow-up. Appear effective, especially for objective skin and joint measures. No major safety concerns but short follow-up to date. @RheumNow #ACR25 Abstr#565 https://t.co/Zk3odT2EX2
      #0775
      Higher circulating microbial small RNA tDR-1 linked to lower risk of developing RA in CCP3+ individuals (AUC 0.86)

      Mrinalini Dey DrMiniDey

      1 week 3 days ago
      #0775 Higher circulating microbial small RNA tDR-1 linked to lower risk of developing RA in CCP3+ individuals (AUC 0.86). tDR-1 downregulates interferon-response genes in vitro, suggesting microbiome-mediated anti-inflammatory mechanism in RA pathogenesis. @RheumNow #ACR25
      SLE & arthritis: Is there a difference?
      Abstract #0629:
      - Non-deforming (ND): 73% | Jaccoud’s: 19% | Rhupus: 8%
      -

      Akhil Sood MD, MS AkhilSoodMD

      1 week 3 days ago
      SLE & arthritis: Is there a difference? Abstract #0629: - Non-deforming (ND): 73% | Jaccoud’s: 19% | Rhupus: 8% - Vs ND, Rhupus had lower odds of type I IFN signature - Time to deformities: Jaccoud's ~2 yrs vs Rhupus ~5 yrs - RNP+ predictive of Jaccoud’s @RheumNow #ACR25
      Why do some clinics excel at RA disease activity tracking while others struggle? In the VA, success came down to structu

      Jiha Lee JihaRheum

      1 week 3 days ago
      Why do some clinics excel at RA disease activity tracking while others struggle? In the VA, success came down to structure: RA-specific clinics, templates, and staff. Barriers? Time, missing labs, and workflow gaps. @RheumNow #ACR25 Abstract#0222
      What can we learn from longitudinal peripheral blood multi-omic profiling in at-risk individuals?

      50 RA converters vs.

      Aurelie Najm AurelieRheumo

      1 week 3 days ago
      What can we learn from longitudinal peripheral blood multi-omic profiling in at-risk individuals? 50 RA converters vs. non converters from StopRA study Decision tree showing highest risk for conversion to clinical RA in Individuals w/ -CCP3 ≥108 units -T peripheral helpers https://t.co/jw53EB6tI6
      #0774
      Multi-omic profiling of anti-CCP3+ “at-risk” individuals reveals Tph & cytotoxic CD8+ expansions, altered

      Mrinalini Dey DrMiniDey

      1 week 3 days ago
      #0774 Multi-omic profiling of anti-CCP3+ “at-risk” individuals reveals Tph & cytotoxic CD8+ expansions, altered gene/chromatin profiles and predictive model (AUC 0.77) for RA conversion PTPN22 locus accessibility & Tph ≥ 2.45% identify highest risk. @RheumNow #ACR25 https://t.co/JDSMkdmoGv
      What's new in the Pre-RA world?
      Slowly unraveling mechanisms and biology associated to transition from CCP+ asymptomati

      Aurelie Najm AurelieRheumo

      1 week 3 days ago
      What's new in the Pre-RA world? Slowly unraveling mechanisms and biology associated to transition from CCP+ asymptomatic pre-RA state to clinical RA Here is my summary of a few abstracts presented at #ACR25 proposing biomarkers beyond the realm of clinical and classical
      Artificial intelligence isn’t a distant frontier anymore. It’s here, and it appears able to detect signs of rheumatoid arthritis, possibly before we can clinically detect it. Two studies presented at this year’s ACR meeting highlight just how close we may be to a future where algorithms flag disease before we can and monitor activity with minimal patient burden.
      We know that pre-RA is a definition that stands under a large umbrella, ranging from asymptomatic individuals with ACPA positivity to individuals with symptomatic pre-clinical synovitis. How can we predict the transition from the at-risk state to clinical RA outside the realm of clinical, conventional serological (RF/anti-CCP) or imaging (US/MRI synovitis) biomarkers?
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