PRECISION MEDICINE IN RA- newer advances

precision medicine in RA

1. Precision M edicine in RA Ritasman Baisya Assistant Professor, Rheumatology & Clinical Immunology AIIMS , Kalyani

2. Points of discussion What is precision medicine (PM)? Role of PM in RA Areas of PM in RA – Clinical Antibodies Synovial histology Inflammatory cells Cytokines Future development, including OMICs

3. Role of PM

4. Current status of PM in  RA Diagnosis Prognosis Therapeutics Research

5. A reas to be targeted Clinical variables Antibody Synovial histology Different inflammatory cells including PRIME cells OMICs approach

6. Auto-antibody Rheumatoid factor Anti CCP antibody Shared epitope

7. RF/anti -CCP seropositivity enriches responses in rituximab.

8. A nti-CCP2 antibody-negative patients responded less well. At year 2, patients with the highest baseline antiCCP2 antibody concentrations had better clinical responses with Abatacept. Adalimumab doesn’t show such concentration-dependent improvement

9. Biologic naïve RA patients Biologic failure RA patients

10. Histologic pattern in RA synovial tissue Myeloid/lymphoid, diffuse myeloid, fibroid pauci-immune. Synovial gene expression may help us understand which patients may need to be more aggressively treated.

11. Lymphoid predominant Diffuse Myeloid Pauci-immune T , B , Plasma cell dominant Myeloid lineage Stromal cells Auto-antibody positivity Elevated acute phase reactant Not burned out state , a specific endotype Good response to therapy Good response to therapy Negative correlation with inflammatory markers Strong association with radiographic damage Correlated with disease activity Less response to immunomodulatory therapy Non-responders can have high myeloid signature even after therapy

12. Lewis MJ, et al . Molecular Portraits of Early Rheumatoid Arthritis Identify Clinical and Treatment Response Phenotypes. Cell Rep. 2019 Aug 27;28(9):2455-2470.e5

13. 144 consecutive treatment-naïve early RA U ltrasound-guided synovial biopsy before and 6 months after DMARD E levation of myeloid- and lymphoid-associated gene expression strongly correlated with D isease activity Acute phase reactants DMARD response at 6 months . Humby F, et al. Ann Rheum Dis 2019;78:761–772

14. Correlation Analysis

15. Higher myeloid and lymphoid eigengene expression (but not fibroid) was associated with larger decreases in DAS28-ESR scores post-treatment (myeloid, p=0.003; lymphoid, p=0.044 )

16. Radiographic progression is more in lymphoid variant

17. A biopsy-driven, randomized clinical trial in RA (R4RA) TNF-inhibitor-inadequate responders R andomized to either rituximab (anti-CD20 monoclonal antibody) or tocilizumab (anti-IL6R monoclonal antibody) S tratification according to synovial B cell signatures

18. Lymphoid cells were associated with response to rituximab – B cell genes, Igs, chemokines, and leukocyte genes. Myeloid cells were associated with response to tocilizumab F ibroid pauci -immune phenotype represents a refractory endotype

19. Inflammatory cell states in RA Transcriptomic and cellular profiling –single-cell technology Macrophage – inflammatory, resident Fibroblast- Lining, sub-lining Pathogenic lymphocytes

20. Pathogenic lymphocytes Fibroblasts Macrophage Autoimmune-associated B cells (ABCs) – produce auto-antibodies CD90+ sub lining fibroblasts - correlated with the severity of synovial tissue , secret e cytokine Distinct synovial sub-lining macrophages- high expression of IL1B & HBEGF –cytokine and inflammation T peripheral helper (T ph ) cells –recruit B cells, ectopic lymphoid structure formation Lining fibroblast – secrete MMP , degrade cartilage Tiissue macrophage –repair response CD8+ T cells- IFN gamma & TNF

21. Cellular profiling through single-cell RNAseq

22. Two study cohorts – CERTAIN & NETWORK 004. M olecular signature response classifier (MSRC) - RNA sequencing data from peripheral blood & clinical features TNFi- exposed patients - MSRC had significant odds ratios of 3.3–26.6 by ACR, DAS28-CRP, and CDAI metrics .

23. PRIME cells Pre-inflammatory mesenchymal (PRIME) cells PRIME cells were activated in the blood by B cells one week before RA flares S hares molecular features with synovial sublining fibroblasts. Peripheral PRIME cells indicate they migrate to the synovium, differentiate into sub lining fibroblasts, contribute to disease pathogenesis.

24. Orange DE, Yao V, Sawicka K, Fak J, Frank MO, et al . RNA Identification of PRIME Cells Predicting Rheumatoid Arthritis Flares. N Engl J Med. 2020 Jul 16;383(3):218-228 Specimens were obtained from 364 time points during eight flares over a period of 4 years. blood transcriptional profiles 1 to 2 weeks before a rheumatoid arthritis flare. B-cell activation was followed by expansion of circulating CD45−CD31−PDPN+ PRIME , cells in the blood from patients with rheumatoid arthritis

25. Transcriptional Characteristics of Immune Activation before Symptom Onset in Rheumatoid Arthritis Flares Cluster 1 – active after flare AC2 – 2 weeks prior to flare AC3 – Just before flare

26. Cytokine precision S erum CXCL13 correlated with DAS28 , serology, ultrasonographic measures of disease activity , synovial histology . Serum MMP-3 - correlation with acute phase reactants, DAS28 score and synovial histology.

27. S ignificantly different microbiome traits between patients who eventually showed MCII and those who did not . Patients who achieved clinical improvement had higher alpha diversity in their gut microbiomes at both baseline and follow-up visits . Gupta VK, Cunningham KY, et al . Gut microbial determinants of clinically important improvement in patients with rheumatoid arthritis. Genome Med. 2021 Sep 14;13(1):149

28. Patient-derived organoids synovial tissue PDOs original cellular composition and the native synovial tissue microenvironment unique to each RA patient Therapeutic target

29. Metabolomics Useful in seronegative RA The lactic acid concentration in SF was elevated whereas that of glucose was decreased in RA. Plasma nucleotides elevated in RA Distinguished biomarker for ILD in RA tryptophan metabolite, kynurenine

30. AI & Machine learning in RA AI algorithms - naive Bayes, convolutional neural network (CNN), logistic regression, and support vector machine (SVMs) or deep learning imaging data, to detect subtle changes in the joints that may indicate early RA genetic data have identified immune-related biomarkers for rheumatoid arthritis

31. RA-DREAM CHALLENGE. Sun D, Nguyen TM, Allaway RJ, et al. A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in Rheumatoid Arthritis. JAMA Netw Open. 2022;5(8):e2227423. Published 2022 Aug 1. doi:10.1001/jamanetworkopen.2022.27423 This diagnostic/prognostic study describes the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM Challenge), which used existing radiographic images and expert-curated Sharp-van der Heijde ( SvH ) scores from 2 clinical studies (674 radiographic sets from 562 patients) for training (367 sets), leaderboard (119 sets), and final evaluation (188 sets).

32. Biomarkers as key tools towards personalized medicine in RA 3 distinct RA phenotypes: fibroblast-enriched macrophage-enriched, and lymphoid-myeloid-enriched phenotypes circulating mesenchymal cells in peripheral blood of RA patients before disease flares. Proteomic technologies – anti CCP in pre RA . Metabolomics

33. Tools for Precision medicine in RA Autoantibodies, clinical variables Clinical Imaging Complement levels and split products Soluble mediators: Cytokines, chemokines, and soluble receptors Transcriptomics : Molecular signatures Genetics: Disease-associated variants Immunophenotyping : Flow cytometry Tissue histology Environmental factors: Microbiomics , Exposomics

34. Take home message Precision medicine remains a major goal for research and clinical care Different synovial pathotypes and molecular signature exists at time of diagnosis and are associated with disease activity, radiographic progression and response to DMARDs. Gut microbiome and its metabolomics may predict response to drugs . Machine learning is of help

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