Cerebrospinal fluid proteome reveals novel biomarkers for differentiating central NPSLE from central nervous system infection

医学 队列 蛋白质组 蛋白质组学 脑脊液 免疫学 中枢神经系统 免疫系统 生物标志物 生物信息学 计算生物学 抗体 生物标志物发现 肿瘤科 生物 诊断生物标志物 队列研究 免疫球蛋白G 病理 混淆 一致性 定量蛋白质组学 代谢组
作者
Jingyi Xu,Chunshu Yang,Wei Li,赵传胜,Xiaobo Yu,Juan Cai,Lingling Xu,Jing Xue,Ling Qin,Pingting Yang
出处
期刊:Journal of Autoimmunity [Elsevier BV]
卷期号:165: 103644-103644
标识
DOI:10.1016/j.jaut.2026.103644
摘要

BACKGROUND: Central neuropsychiatric systemic lupus erythematosus (cNPSLE) is a major cause of mortality in systemic lupus erythematosus (SLE). Distinguishing cNPSLE from central nervous system (CNS) infections remains a critical clinical challenge due to overlapping clinical manifestations, often leading to diagnostic delays and inappropriate therapeutic interventions. We aimed to identify and validate cerebrospinal fluid (CSF) biomarkers to resolve this diagnostic dilemma. METHODS: We conducted the largest cNPSLE CSF proteomic investigation to date using high-throughput data-independent acquisition mass spectrometry (DIA-MS) in a discovery cohort comprising 20 patients with cNPSLE, 8 with CNS infection (cNIC), and 11 non-diseased controls (NDC). Differentially expressed proteins were analyzed for pathway enrichment. Candidate biomarkers were subsequently validated using enzyme-linked immunosorbent assay (ELISA) in two independent cohorts: an internal validation cohort (46 cNPSLE vs. 29 cNIC) and an external validation cohort (40 cNPSLE vs. 13 cNIC). Robustness of discovery-stage protein selection was assessed by stratified bootstrap resampling and leave-one-out analysis. The diagnostic panel was fitted and locked in the internal cohort, and applied to the external cohort without refitting. RESULTS: Our proteomic profiling quantified 2175 CSF proteins, revealing enrichment in immune and metabolic pathways. We identified three proteins, matrilin-3 (MATN3), tyrosine-protein kinase Mer (MERTK), and V-set and immunoglobulin domain-containing 4 (VSIG4), that were consistently upregulated in cNPSLE compared with both cNIC and NDC groups. In the internal and external validation cohorts, MATN3 demonstrated high diagnostic accuracy (AUC = 0.875 and 0.868, respectively), followed by MERTK (AUC = 0.801 and 0.775) and VSIG4 (AUC = 0.724 and 0.752). Notably, a composite three-protein panel achieved discriminatory performance, yielding AUCs of 0.921 in the internal cohort and 0.892 in the external cohort, when the locked model trained in the internal cohort was applied without refitting. CONCLUSION: We identified and validated a three-protein CSF panel (MATN3, MERTK, and VSIG4) that differentiates cNPSLE from CNS infections across multi-center cohorts. This diagnostic signature holds potential for clinical translation to facilitate early diagnosis and precise management of NPSLE.
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