Metagenomic next-generation sequencing improves diagnosis of Talaromyces marneffei and mixed infections in HIV/AIDS patients: a retrospective study
Year: 2026
Type: article
Study design: Observational Study
Abstract: Background Opportunistic infections remain a leading cause of morbidity in people living with HIV (PLWH). Talaromyces marneffei ( T. marneffei ) accounts for up to 15% of HIV-related hospitalizations in endemic regions. Metagenomic next-generation sequencing (mNGS) offers rapid pathogen detection; however, its utility in diagnosing HIV-associated coinfections is uncertain. Methods This retrospective study enrolled 56 hospitalized PLWH with coinfections at the Third Affiliated Hospital of Sun Yat-sen University from March 2022 to October 2024. All patients underwent pathogen detection using both mNGS and CTM, with their diagnostic performance compared. Clinical data, treatment adjustments, and outcomes were analyzed. Results mNGS demonstrated significantly higher detection rate (84.4%, 54/64; 95% CI: 73.1–92.2%) than CTM (28.1%, 18/64; 95% CI: 17.6–40.8%; p < 0.0001), especially for T. marneffei detection (100% vs. 45.5%, p < 0.0001). mNGS identified T. marneffei in 39.3% ( n = 22/56) of patients, including two rare cases (urinary and intracranial infections) missed by CTM. mNGS revealed mixed infections in 82.1% (46/56) of patients, substantially higher than the 5.4% detected by CTM. Notably, mNGS-guided therapy adjustments occurred in 74.1% of cases, compared with 22.2% for CTM ( p < 0.001), correlating with clinical improvement in 90% (36/40) of adjusted regimens. Conclusion Our data demonstrated that mNGS had a higher positive detection rate than CTM for detecting coinfections among PLWH, especially for T. marneffei and mixed infections. These results highlight the clinical value of mNGS as a complementary tool for pathogen identification in this vulnerable population.
Source: Frontiers in Medicine
Authors: Xiaodi Li, Dabiao Chen, Yunfei Xiao, Ziying Lei, Xiaohua Yang, Yeqiong Zhang, Lili Li, Yue Zheng, Ying Zhang, Zhanlian Huang, Bingliang Lin
Institution: Third Affiliated Hospital of Sun Yat-sen University
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,801
OpenAlex ID: W7151543890
