ORIGINAL RESEARCH article
Front. Immunol.
Sec. Autoimmune and Autoinflammatory Disorders : Autoimmune Disorders
This article is part of the Research TopicIntegrative Multi-Omics data Analysis to Identify Biomarkers for SLEView all articles
Unveiling Biomarkers of Telitacicept's Efficacy in SLE Treatment Through Proteomics and Metabolomics
Provisionally accepted
Huiyu NieSiyuan ChangHanhan ChenJiahui Shi
Shu LiXiaofei Peng
Wei ChengJia WangQi Tang
Yan Ge
Xi Xie
Fen Li*- Second Xiangya Hospital, Central South University, Changsha, China
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Background: The pathogenesis of systemic lupus erythematosus (SLE) is closely associated with abnormal activation of B lymphocytes. Telitacicept simultaneously blocks B-cell stimulating factors and proliferation-inducing ligands, thereby inhibiting B-cell proliferation and differentiation, demonstrating favorable therapeutic efficacy in the majority of SLE patients. However, there is a lack of reliable biomarkers of efficacy and systematic elucidation of its mechanism of action. Methods: The study employed proteomics and metabolomics analysis to explore biomarkers and mechanisms underlying therapeutic response variability to Telitacicept in SLE patients. Twenty-five SLE patients were enrolled and divided into the responder group and non-responder group based on the SLE Response Index 4 to identify key proteins, metabolites, and mechanisms associated with treatment response. Results: Proteomics results revealed XPNPEP3, SRSF5, SRSF6, WARS1, IDH1, and ITLN1 as protein biomarkers correlated with Telitacicept efficacy in SLE patients. Metabolomics results indicated that pyruvate was a potential metabolic biomarker for responder group, while gamma-aminobutyric acid (GABA) was a potential biomarker for non-responder group. The combined analysis revealed that both pyruvate and IDH1 participate in the citric acid cycle. GABA showed a negative correlation with XPNPEP3. Conclusions: The above results reveal biomarkers related to the differential efficacy of Telitacicept in treating SLE patients and potential mechanisms underlying these differences, which may provide a reference for personalized treatment and mechanistic research in SLE.
Keywords: biomarker, Metabolomics, Proteomics, systemic lupus erythematosus, Telitacicept
Received: 03 Jan 2026; Accepted: 16 Feb 2026.
Copyright: © 2026 Nie, Chang, Chen, Shi, Li, Peng, Cheng, Wang, Tang, Ge, Xie and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Fen Li
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