Session Type: ACR Poster Session A
Session Time: 9:00AM-11:00AM
Background/Purpose: Systemic sclerosis (SSc) is a remarkably heterogeneous autoimmune disease, for which effective disease-modifying therapies are still lacking. The most widely used classification divides SSc into two major subsets diffuse cutaneous (dcSSc) and limited (lcSSc) SSc by the extent and severity of skin fibrosis. However, not all patients fit into these subsets. This has created great interest to examine disease heterogeneity at the molecular level to uncover unrecognized SSc subtypes that may differ with regard to clinical manifestations, prognosis or therapy response. In large-scale “omics”-type autoantibody (AAB) profiling studies we have recently identified novel SSc-associated autoantigens. Here, we describe the development of a 20 marker multiplexed AAB assay and explored its utility for SSc patient subgroup analysis.
Methods: A Luminex bead-based AAB assay was designed by combining 8 connective tissue disease (anti-centromere, anti-Scl70, U1-snRNP, SSB, Ro52, Ro60, SmB, anti-ribosomal P) antigens with 12 novel antigens (including BICD2, JMJD3/KDM6B, and PPP1R2). Novel AAB targets were previously detected in SSc patients with a p-value <0.05 (Mann-Whitney-U-test) and frequency >15%. AAB reactivity was analysed in 100 SSc patients (dcSSc: n=32, lcSSc: n=50, SSc overlap: n=9, other: n=9). The mean modified Rodnan skin score (MRSS), mean disease duration (month), and mean age (years) of the SSc cohort was 10.51, 162.5 and 56.94, respectively. To analyze the individual-level patient similarity of AAB reactivity, the total number of AABs reactive in each patient was calculated and referenced to the number of all available antigens in percent. Hierarchical cluster analysis of marker co-prevalence and patient signature overlap was performed.
Results: Based on their AAB reactivity pattern, the SSc sample cohort can be decomposed into four main clusters. Cluster 1 includes 87% of all lcSSc patients characterized by an extended AAB repertoire (including BICD2, KDM6B and PPP1R2), MRSS below the average and longer disease duration. Cluster 2 includes 56% lcSSc and 26 % dcSSc patients characterized by MRSS above the average and anti-U1-snRNP antibodies. Cluster 3 includes SSc-overlap, lcSSc and dcSSc with higher MRSS compared to Cluster 1 and 2 and variable AAB profile. Cluster 4 includes mainly dcSSc patients with anti-Scl70 AAB and highest number of patients with MRSS above the average (83%).
Conclusion: The multiplexed analysis of AABs in SSc enables defining an AAB reactivity score and patient clusters. This might support to subclassify SSc beyond lcSSc and dSSc.
To cite this abstract in AMA style:Budde P, Zucht HD, Göhler H, Marquart K, Schulz-Knappe P, Schneider M, Hunzelmann N. Identifying and Assessing Subgroups in Systemic Sclerosis Patients Based on Comprehensive Autoantibody Profiling [abstract]. Arthritis Rheumatol. 2016; 68 (suppl 10). https://acrabstracts.org/abstract/identifying-and-assessing-subgroups-in-systemic-sclerosis-patients-based-on-comprehensive-autoantibody-profiling/. Accessed November 27, 2020.
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