AUTHOR=Yan Zhiyun , Sun Cheng , Tang Wanna , Cao Weitao , Lv Jin , Liang Zhike , Wei Shuquan , Zhong Weinong , Zhao Ziwen , Zhao Zhuxiang , Li Yujun 

TITLE=Application of the metagenomic next-generation sequencing technology to identify the causes of pleural effusion

JOURNAL=Frontiers in Medicine

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2025.1525100

DOI=10.3389/fmed.2025.1525100

ISSN=2296-858X

ABSTRACT=BackgroundPleural effusion (PE), frequently encountered in clinical practice, can arise from a variety of underlying conditions. Accurate differential diagnosis of PE is crucial, as treatment and prognosis are heavily dependent on the underlying etiology. However, diagnosing the cause of PE remains challenging, relying on mycobacteriological methods that lack sensitivity and are time-consuming, or on histological examinations that require invasive biopsies. The recent advancements in metagenomic next-generation sequencing (mNGS) have shown promising applications in the diagnosis of infectious diseases. Despite this, there is limited research on the utility of mNGS as a comprehensive diagnostic tool for simultaneously identifying the causes of PE, particularly in cases of tuberculosis or malignancy.MethodsThis study aimed to assess the efficacy of mNGS in detecting tuberculous pleural effusion (TPE) and malignant pleural effusion (MPE). A total of 35 patients with PE were included, and their PE samples were analyzed using mNGS.ResultsAmong the participants, 8 were ultimately diagnosed with TPE, and 10 were diagnosed with MPE, with lung adenocarcinoma being the most prevalent pathological type (50%, 5/10), according to established diagnostic criteria. Additionally, 7 patients were diagnosed with non-infectious PE. However, mNGS identified only 2 cases of TPE and 8 cases of MPE. The sensitivity of mNGS for detecting Mycobacterium tuberculosis was 25% (2/8), while the specificity was 100%. For tumor detection, mNGS demonstrated a sensitivity of 80%, a specificity of 92.6%, and an AUC of 0.882.ConclusionmNGS is effective in distinguishing MPE from non-MPE, but is not suitable for diagnosing TPE.