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Xiaolin Xing,1,2,* Can Guo,1,* Guizeng Zhao,1,* Duanduan Xie,1 Linbo Zhang,1 Ke Shi,1 Zhiqiang Zhang,1 Yu Pang,2 Junwei Cui1 1Department of Tuberculosis, The First Affiliated Hospital of Xinxiang Medical University, Weihui City, Henan Province, People’s Republic of China; 2Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis and Thoracic Tumor Research Institute, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Junwei Cui, Department of Tuberculosis, The First Affiliated Hospital of Xinxiang Medical University, No. 88 Jiankang Road, Weihui City, Henan Province, People’s Republic of China, Email cjw8693@163.com Yu Pang, Department of Bacteriology and Immunology Beijing Chest Hospital, Capital Medical University, No. 9 Beiguan Street, Tongzhou District, Beijing, People’s Republic of China, Email pangyupound@163.comBackground: Tuberculous pleural effusion (TPE) results from an inflammatory response triggered by tuberculosis infection. If not promptly diagnosed and treated, it can lead to severe pulmonary dysfunction and the risk of infection spread. However, TPE diagnosis remains a significant challenge. This study employs Olink proteomics to explore novel methods for diagnosing TPE.Methods: In this study, we collected 20 cases each of TPE, malignant pleural effusion (MPE), and parapneumonic pleural effusion (PPE) from patients at the First Affiliated Hospital of Xinxiang Medical University in Xinxiang, China, between January and April 2024. Using Olink proteomics, we quantified 92 inflammation-related proteins in pleural effusions across these three patient groups. Differentially expressed proteins were identified, followed by enrichment and pathway analyses to explore potential underlying mechanisms. An independent validation cohort, consisting of 36 TPE samples and 29 non-tuberculous pleural effusion samples collected between April and July 2024, was used to validate the diagnostic performance of selected biomarkers by enzyme-linked immunosorbent assay (ELISA). Diagnostic accuracy was evaluated using logistic regression and receiver operating characteristic (ROC) curve analysis.Results: A total of 92 inflammation-related proteins were identified in this study. Differential analysis identified 43 proteins with distinct expression levels between TPE and MPE, and 33 between TPE and PPE. Of these, 25 proteins were uniquely expressed in TPE. ELISA validation confirmed the expression of four key inflammatory proteins: IFN-γ, CXCL9, TNF-β and PD-L1. The combined area under the curve (AUC) for these markers was 0.963, with a sensitivity of 0.944 and specificity of 1, surpassing the sensitivity and specificity of individual or other biomarker combinations.Conclusion: This study identified a diagnostic method using a combination of four biomarkers: IFN-γ, CXCL9, TNF-β, and PD-L1, which can aid in the diagnosis of TPE.Keywords: tuberculous pleural effusion, Olink technology, inflammation-related biomarkers