ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 1514

Serum Antigenome Profiling Reveals Diagnostic Models for Systemic Lupus Erythematosus

Yan Wang1, Lulu Cao2, Mengze Xu3, Jian Lu3, Jing He1, Fanlei Hu4 and Zhanguo Li5, 1Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China, Beijing, China (People's Republic), 2Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China, Beijing, 3State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing, China., Beijing, Beijing, China (People's Republic), 4Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China (People's Republic), 5Department of Rheumatology and Immunology, Peking University People's Hospital, Beijing, China, Beijing, Beijing, China (People's Republic)

Meeting: ACR Convergence 2025

Keywords: , ,

Session Information

Date: Monday, October 27, 2025

Title: (1467–1516) Systemic Lupus Erythematosus – Diagnosis, Manifestations, & Outcomes Poster II

Session Type: Poster Session B

Session Time: 10:30AM-12:30PM

Background/Purpose: Systemic lupus erythematosus (SLE) exhibits profound clinical and pathogenic heterogeneity, complicating diagnosis and treatment. Identifying subtype-specific biomarkers might intrinsically link to organ involvement.

Methods: Patients with SLE were classified into five subgroups, including renal, hematologic, mucocutaneous, neuropsychiatric, and cardiopulmonary subtypes. Serum antigens were captured by purified IgG from a cohort consisting of 10 SLE patients per subgroup, together with sex- and age-matched 10 rheumatoid arthritis (RA), 10 Sjogren’s syndrome (pSS), 10 anti-synthetase syndrome (ASS) patients and 10 healthy controls. Affinity Chromatography-purified autoantigens were set to liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis and machine learning to identify pathogenic molecules in different groups of SLE patients. The significantly upregulated and downregulated proteins with fold change > 2 (p < 0.05) were selected.

Results: We identified 39, 32, 36, 13 and 12 differentially expressed (DE) autoantigens in renal, hematological, mucocutaneous, neuropsychiatric, and cardiopulmonary subtypes, respectively. Based on the newly identified autoantigens, including CH60, FABPS, CREG1, ODO2, and TRY3, diagnostic prediction models were further constructed for SLE subtypes with renal, hematological, mucocutaneous, neuropsychiatric, and cardiopulmonary involvement. The average accuracy and AUC of the 5 groups were 92%/0.96, 93%/1.00, 95%/1.00, 89%/0.98, and 84%/0.99, respectively. The predominant autoantigens were enriched in distinct molecular pathways correlating with the clinical manifestations. Signal pathways were analyzed among these DE autoantigens.

Conclusion: These findings reveal SLE subtype-specific immune signatures, offering novel biomarkers for clinical stratification and potential targeted therapeutics.

Disclosures: Y. Wang: None; L. Cao: None; M. Xu: None; J. Lu: None; J. He: None; F. Hu: None; Z. Li: None.

To cite this abstract in AMA style:

Wang Y, Cao L, Xu M, Lu J, He J, Hu F, Li Z. Serum Antigenome Profiling Reveals Diagnostic Models for Systemic Lupus Erythematosus [abstract]. Arthritis Rheumatol. 2025; 77 (suppl 9). https://acrabstracts.org/abstract/serum-antigenome-profiling-reveals-diagnostic-models-for-systemic-lupus-erythematosus/. Accessed .

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