Novel CSF biomarkers for diagnosis and integrated analysis of neuropsychiatric systemic lupus erythematosus: based on antibody profiling

Arthritis Research & Therapy

Research

Chen Chen¹  Jun Liang²  Shuangan Wang³  Xuan Liu³  Liping Tan³  Li Lu³  Yu Fan³  Jiali Ni³  Yayi Hou⁴  Huan Dou⁴ 

[1] Department of Clinical Nutrition, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, 210008, Nanjing, China;Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, 210008, Nanjing, China;Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, 210008, Nanjing, China;The State Key Laboratory of Pharmaceutical Biotechnology, Division of Immunology, Medical School, Nanjing University, 210093, Nanjing, China;The State Key Laboratory of Pharmaceutical Biotechnology, Division of Immunology, Medical School, Nanjing University, 210093, Nanjing, China;Jiangsu Key Laboratory of Molecular Medicine, 210093, Nanjing, China;

关键词: NPSLE;    Biomarkers;    Diagnosis;    Protein array;    Machine learning;   

DOI  :  10.1186/s13075-023-03146-z

 received in 2023-05-12, accepted in 2023-08-23,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundNeuropsychiatric systemic lupus erythematosus (NPSLE), with various morbidities and multiple manifestations in the central nervous system, remains a limited standard for diagnosis. Our study was to discover novel biomarkers for improving the diagnostic efficiency for NPSLE.MethodsWe performed a quantitative planar protein antibody microarray to screen 1000 proteins in cerebrospinal fluid from controls, systemic lupus erythematosus (SLE, non-NPSLE) patients, and NPSLE patients. Differentially expressed proteins (DEPs) as candidate biomarkers were developed into a custom multiplexed protein antibody array for further validation in an independent larger cohort. Subsequently, we used least absolute shrinkage and selection operator regression (LASSO) analysis and multivariable logistic regression analysis for optimizing feature selection and constructing a diagnostic model. A receiver operating characteristic curve (ROC) was generated to assess the effectiveness of the models.ResultsThe expression of 29 proteins in CSF was significantly altered in the comparison of the three groups. We selected 17 proteins as candidate biomarkers in accordance with protein interaction analysis. In the larger cohort, we identified 5 DEPs as biomarkers for NPSLE, including TCN2, CST6, KLK5, L-selectin, and Trappin-2. The diagnostic model included 3 hub proteins (CST6, TCN2, KLK5) and was best at discriminating NPSLE from SLE patients. These CSF biomarkers were also highly associated with disease activity. In addition, there were 6 molecules with remarkable changes in NPSLE CSF and hippocampus, which indicated the consistency of the environment in the brain and the promising molecular targets in the pathogenesis of NPSLE.ConclusionsThe dual-chips screening strategy demonstrated KLK5, L-selectin, Trappin-2, TCN2, and CST6 as CSF biomarkers for diagnosing NPSLE.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

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