Abstract:
Objectives To investigate the molecular epidemiological characteristics of HIV-1 infection among men who had sex with men (MSM) in Taizhou City, Zhejiang Province, and to provide a scientific reference for acquired immune deficiency syndrome prevention and control efforts.
Methods The research subjects were all newly reported MSM population in Taizhou City from 2020 to 2023. Blood samples without antiviral therapy were collected. The HIV-1 pol gene was amplified and sequenced, and the sequences were submitted to the Stanford University drug resistance database to identify the mutation sites and drug resistance. MEGA 11.0 software was used to analyze the nucleic acid sequences, construct phylogenetic tree, and calculate genetic distance of gene sequences. The molecular transmission network diagram of HIV-1 was constructed using Cytoscape_v3.10.1, and the influencing factors of network entry were analyzed by logistic regression.
Results A total of 363 newly reported HIV-infected MSM patients were included, with a median age M (P25, P75) of 34 (26,47) years old. The majority had an educational level of junior high school or below (55.65%). A total of eight subtypes were found, mainly CRF07_BC and CRF01_AE. The primary drug resistance rate was 10.47% (38/363). The optimal molecular network gene distance was 0.019, with a network access rate of 42.70% (155/363), and a total of 47 molecular clusters were formed. Multivariate logistic analyses showed that compared with the CRF01_AE subtype, the clustering risk of CRF07_BC subtype was higher (OR=1.916, 95%CI: 1.191‒3.109), cases with drug resistance had a higher risk of cluster formation than those without drug resistance (OR=2.011, 95%CI: 1.006‒4.080), and recent infected patients had a lower risk of entering the largest molecular cluster than long-term infected patients (OR=0.376, 95%CI: 0.137‒0.928).
Conclusion The newly diagnosed infections among the MSM population are active in Taizhou City, Zhejiang Province, with a high level of primary drug resistance. Individuals carrying drug-resistant strains are more likely to cluster. Drug resistance monitoring should be strengthened to prevent further spread of drug-resistant strains in the network.