Background Rheumatic diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), systemic sclerosis (SSc), axial spondyloarthritis (axSpA), and psoriatic arthritis (PsA) are characterized by a complex clinical and molecular heterogeneity. Novel and disruptive technologies might shed light on their pathogenesis and clinical management.

Objectives To evaluate the potential of the innovative proteomic technology “proximity extension assay” (PEA) to identify useful biomarkers, subgroups of patients, and novel insight into rheumatic diseases.

Methods 533 consecutive patients with rheumatic diseases (141 SLE, 120 RA, 72 SSc, 100 axSpA and 100 PsA) and 50 healthy donors (HDs) were included in the study where serum samples and clinical data were obtained. A signature of 368 proteins divided into 4 panels of 92 biomarkers associated with Inflammation (SLE, RA, SpA, and HDs), Organ Damage (SLE, SSc, and HDs), cardiovascular disease (RA, SpA, PsA, and HDs), and cardiometabolism (RA and HDs) was analysed by using PEA technology from Olink through its corelab Cobiomic Bioscience SL. PEA technology, already endorsed by more than 1000 peer-reviewed publications, recognizes proteins using antibody-pairs containing unique DNA sequences which are amplified by real-time PCR. Data analysis included t-test, unsupervised clustering analysis, ROC curves, and PCA among others.

Results In SLE patients, the unsupervised cluster analysis using the circulating proteome identified 2 clusters with distinctive clinical features mainly differentiating disease activity and the presence of renal damage. Several proteins were also identified as novel non-invasive biomarkers of lupus nephropathy. Similarly, in SSc, a panel of proteins related to organ damage identified a subgroup of patients characterized by multiple organ involvement including lung and skin fibrosis and oesophageal dysmotility, along with a preponderance of anti-scl70 antibodies positivity. In axSpA patients, the levels of several proteins related to inflammation and cardiovascular disease (CVD) were altered compared with HDs and associated with key clinical features.

In RA, a specific signature of chemokines before therapy identified non-responders patients to anti-TNF therapy and Methotrexate after 3 months of treatment, pointing out its role as a predictor of therapy response. Moreover, several proteins associated with CVD and metabolism were modulated by the effect of Methotrexate and Tofacitinib, which also underlined their role as biomarkers for treatment monitoring. In PsA patients, numerous proteins related to CVD were up-regulated in relation to HDs and associated with clinical markers of CVD risk. Various circulating proteins also distinguished the presence of insulin resistance, high activity, and poor therapeutic outcome to Methotrexate and Apremilast. Furthermore, the PEA analysis of the inflammatory proteome in PsA synovial fluid revealed novel biomarkers of disease and potential therapeutic targets.

Conclusion PEA technology might boost the future of precision medicine in rheumatic diseases through the identification of novel biomarkers of disease and therapy response and the stratification of patients with key clinical and molecular features.

Supported by: ISCIII PI21/0591, PI20/00079, PMP21/00119, RICORS, RD21/0002/0033 co-financed by ERDF, Consejería de Conocimiento, Investigación y Universidad de la Junta de Andalucía (P20_01367), RYC2021-033828-I, financed by MCIN/AEI/10.13039/501100011033 and the European union “NextGenerationEU”/PRTR.

REFERENCES:

NIL.

Acknowledgements: NIL.

Disclosure of Interests None Declared.

Keywords: Biomarkers

DOI: 10.1136/annrheumdis-2023-eular.3630