Metabolic characteristics of large and small extracellular vesicles from pleural effusion reveal biomarker candidates for the diagnosis of tuberculosis and malignancy

• Main Authors: Ping Luo, Kaimin Mao, Juanjuan Xu, Feng Wu, Xuan Wang, Sufei Wang, Mei Zhou, Limin Duan, Qi Tan, Guangzhou Ma, Guanghai Yang, Ronghui Du, Hai Huang, Qi Huang, Yumei Li, Mengfei Guo, Yang Jin
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2020-01-01
• Series: Journal of Extracellular Vesicles
• Subjects: extracellular vesicles; metabolic profiling; pleural effusion; biomarkers; diagnosis
• Online Access: http://dx.doi.org/10.1080/20013078.2020.1790158

Pleural effusion is a common respiratory disease worldwide; however, rapid and accurate diagnoses of tuberculosis pleural effusion (TPE) and malignancy pleural effusion (MPE) remain challenging. Although extracellular vesicles (EVs) have been confirmed as promising sources of disease biomarkers, little is known about the metabolite compositions of its subpopulations and their roles in the diagnosis of pleural effusion. Here, we performed metabolomics and lipidomics analysis to investigate the metabolite characteristics of two EV subpopulations derived from pleural effusion by differential ultracentrifugation, namely large EVs (lEVs, pelleted at 20,000 × g) and small EVs (sEVs, pelleted at 110,000 × g), and assessed their metabolite differences between tuberculosis and malignancy. A total of 579 metabolites, including amino acids, acylcarnitines, organic acids, steroids, amides and various lipid species, were detected. The results showed that the metabolic profiles of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. Additionally, different type of vesicles and pleural effusion showed unique metabolic enrichments. Furthermore, lEVs displayed more significant and larger metabolic alterations between the tuberculosis and malignancy groups, and their differential metabolites were more closely related to clinical parameters than those of sEV. Finally, a panel of four biomarker candidates, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3, in pleural lEVs was defined based on the comprehensive discovery and validation workflow. This panel showed high performance for distinguishing TPE and MPE, particularly in patients with delayed or missed diagnosis, such as the area under the receiver-operating characteristic curve (AUC) >0.95 in both sets. We conducted comprehensive metabolic profiling analysis of EVs, and further explored the metabolic reprogramming of tuberculosis and malignancy at the level of metabolites in lEVs and sEVs, providing insight into the mechanism of pleural effusion, and identifying novel biomarkers for diagnosing TPE and MPE.