AB0107 CHANGES IN EXTRACELLULAR MATRIX BIOMARKER C3M CORRELATE WITH ABATACEPT RESPONSE IN SEROPOSITIVE EARLY RA
Authors: S. L. Bridges, J. Buckner, M. A. Maldonado, V. Bykerk, N. Ray, S. Mukherjee, N. Ohtsuka
Journal: Annals of the Rheumatic Diseases (2021)

Background: Effective biomarkers are needed to guide RA treatment selection, and the importance of evaluating synovial tissue is increasingly recognised. 1 Markers of extracellular matrix (ECM) turnover (e.g. C3M, a marker of interstitial tissue degradation) 2 may have clinical utility as disease-relevant and surrogate biomarkers of synovial joint pathophysiology. Objectives: To evaluate baseline (BL) correlations of ECM biomarkers with disease activity and the predictive value of ECM biomarkers in patients (pts) with seropositive early RA in the exploratory head-to-head Early AMPLE study ( NCT02557100 ), and to explore the impact of shared epitope (SE) status. Methods: Biologic-naive, MTX-inadequate responder adults with early (≤12 months’ duration), active, moderate-to-severe RA were enrolled if they were anti-cyclic citrullinated peptide 2+ and RF+. Pts were randomised 1:1 to receive SC abatacept (ABA) 125 mg weekly or SC adalimumab (ADA) 40 mg every 2 weeks (wks) for 24 wks (single-blind period). Linear correlations between levels of ECM serum biomarkers (Nordic Biosciences) and disease activity (DAS28 [CRP], SDAI) at BL and change from BL (CfB) at Wk 24 were assessed in the overall population and by SE status (+/–); early (Wk 4) changes in biomarkers were also assessed. Results: For SE+ (n=61) and SE– (n=18) pts at BL, mean (SD) DAS28 (CRP) was 5.3 (1.2) and 5.0 (1.0), and SDAI was 35.9 (16.2) and 34.0 (13.8), respectively. At BL in the overall population, significant medium correlations between C1M, C3M and C4M and disease activity were seen (Table 1). Correlations were generally higher in SE+ vs SE– pts, with C1M highly correlated with DAS28 (CRP) in SE+; correlations between C1M, C3M and C4M and disease activity were all significant in SE+ but not SE– pts. At Wk 24, overall CfB in C3M showed higher correlation with CfB in disease activity in pts receiving ABA (n=36; DAS28 [CRP]: 0.66 [p&lt;0.0001]; SDAI: 0.53 [p=0.0009]) vs ADA (n=32; DAS28 [CRP]: 0.33 [p=0.0644]; SDAI: 0.39 [p=0.0267]); this was more pronounced in SE+ pts (ABA, n=27; DAS28 [CRP]: 0.70 [p=0.0001]; SDAI: 0.63 [p=0.0005] vs ADA, n=25; DAS28 [CRP]: 0.33 [p=0.1120]; SDAI: 0.41 [p=0.0445]). Changes at Wk 4 in C3M showed higher correlation with response to ABA vs ADA (Figure 1). Correlations between CfB (at Wks 4 and 24) in other biomarkers and response were generally similar between treatment groups. Table 1. BL correlation of ECM biomarkers with BL disease activity Overall (N=77 ) SE+ (n=60 ) SE– (n=17 ) DAS28 (CRP ) SDAI DAS28 (CRP ) SDAI DAS28 (CRP ) SDAI CRPM 0.26 0.20 0.20 0.12 0.41 0.41 0.0207 0.0777 0.1324 0.3583 0.0981 0.1001 Osteocalcin 0.24 0.23 0.23 0.20 0.28 0.33 0.0380 0.0416 0.0763 0.1293 0.2818 0.1890 CTX-1 0.23 0.20 0.21 0.17 0.26 0.28 0.0440 0.0844 0.1104 0.1932 0.3089 0.2703 C1M 0.54 a 0.34 a 0.60 b 0.38 b 0.34 0.26 0.0000 0.0028 0.0000 0.0029 0.1822 0.3216 C2M −0.05 0.00 −0.06 0.01 −0.02 0.01 0.6774 0.9759 0.6565 0.9567 0.9441 0.9813 C3M 0.44 0.30 0.47 0.30 0.33 0.31 0.0001 0.0080 0.0001 0.0199 0.1943 0.2301 C4M 0.39 0.32 0.47 0.36 0.10 0.11 0.0004 0.0049 0.0001 0.0047 0.7012 0.6767 Data are Spearman correlation coefficient, p value. Linear correlations by shading: light grey, low (0–&lt;0.3); medium grey, medium (0.3–&lt;0.6); dark grey, high (0.6–1). Pts with missing SE allele data not included. a n=75. b n=58. C1M, C2M, C3M, C4M=MMP-mediated degradation products of collagen type I, II, III and IV, respectively; CRPM=neo-epitope of MMP-mediated degradation of CRP; CTX-1=neo-epitope of cathepsin-mediated degradation of type I collagen; MMP=matrix metalloproteinase; SE−=0 SE alleles; SE+=≥1 SE allele. Conclusion: Significant BL correlation between C1M, C3M and C4M and disease activity was seen and was generally numerically higher in SE+ vs SE– pts. Early (Wk 4) change in C3M and later (Wk 24) treatment response were more highly correlated in pts receiving abatacept vs adalimumab. The predictive value of ECM biomarkers for treatment response warrants study in a larger population. References: [1]Ouboussad L, et al. Front Med (Lausanne ) 2019;6:45. [2]Gudmann NS, et al. Clin Exp Rheumatol 2018;36:462–470. Acknowledgements: Professional medical writing and editorial assistance was provided by Joanna Wright at Caudex and was funded by Bristol Myers Squibb. Disclosure of Interests: S. Louis Bridges Grant/research support from: Bristol Myers Squibb, Jane Buckner Consultant of: Bristol Myers Squibb, Grant/research support from: Bristol Myers Squibb, Janssen, Michael A Maldonado Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Vivian Bykerk Consultant of: Grants from Amgen, Bristol Myers Squibb, Novartis, and UCB (given to institution); grants from the NIH, PCORI, and CIHR (given to institutions with whom she is affiliated); and personal fees from Amgen, Bristol Myers Squibb, Gilead, Pfizer, Regeneron, Roche, Sanofi Aventis, and UCB outside the submitted work., Grant/research support from: Grants from Amgen, Bristol Myers Squibb, Novartis, and UCB (given to institution); grants from the NIH, PCORI, and CIHR (given to institutions with whom she is affiliated); and personal fees from Amgen, Bristol Myers Squibb, Gilead, Pfizer, Regeneron, Roche, Sanofi Aventis, and UCB outside the submitted work., Neelanjana Ray Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Sumanta Mukherjee Shareholder of: Bristol Myers Squibb, GlaxoSmithKline, Employee of: Bristol Myers Squibb, GlaxoSmithKline, Nobuhisa Ohtsuka Employee of: Bristol Myers Squibb