南方医科大学学报 ›› 2026, Vol. 46 ›› Issue (6): 1395-1406.doi: 10.12122/j.issn.1673-4254.2026.06.19

• • 上一篇    

HIV-1基因型和人口流动性对广州HIV-1传播的影响:基于分子传播网络分析

黄伟平1(), 颜欢畅2(), 李顺铭3, 吴昊3, 蔡衍珊3, 韩志刚3(), 唐时幸1,4()   

  1. 1.南方医科大学公共卫生学院流行病学系,广东 广州 510515
    2.中山大学公共卫生学院医学统计学系,广东 广州 510080
    3.广州市疾病预防控制中心艾滋病预防控制部,广东 广州 510440
    4.南方医科大学皮肤病医院全球健康研究院,广东 广州 510091
  • 收稿日期:2025-12-19 出版日期:2026-06-20 发布日期:2026-06-24
  • 通讯作者: 韩志刚,唐时幸 E-mail:1092064569@qq.com;yanhch7@mail.sysu.edu.cn;zhiganghan616@163.com;tamgshixing@smu.edu.cn
  • 作者简介:黄伟平,在读硕士研究生,E-mail: 1092064569@qq.com
    颜欢畅,博士,E-mail: yanhch7@mail.sysu.edu.cn
    第一联系人:同等贡献作者
  • 基金资助:
    国家自然科学基金青年科学基金(31800146);广东省医学科研基金(A2023393)

Impact of HIV-1 genotypes and population mobility on HIV-1 transmission in Guangzhou: a molecular transmission network analysis

Weiping HUANG1(), Huanchang YAN2(), Shunming LI3, Hao WU3, Yanshan CAI3, Zhigang HAN3(), Shixing TANG1,4()   

  1. 1.Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou 510515, China
    2.Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
    3.Department of AIDS Control and Prevention, Guangzhou Center for Disease Control and Prevention, Guangzhou 510440, China
    4.Institute for Global Health, Dermatology Hospital of Southern Medical University, Guangzhou 510091, China
  • Received:2025-12-19 Online:2026-06-20 Published:2026-06-24
  • Contact: Zhigang HAN, Shixing TANG E-mail:1092064569@qq.com;yanhch7@mail.sysu.edu.cn;zhiganghan616@163.com;tamgshixing@smu.edu.cn
  • Supported by:
    Youth Program of National Natural Science Foundation of China(31800146)

摘要:

目的 探讨广州市HIV-1基因型和人口流动性对HIV-1传播的影响,为精准防控提供科学依据。 方法 针对2008~2020年在广州新确诊的HIV-1感染者(PLWH),收集人口学信息,并根据感染者的户籍地和确诊后1年内住址变更信息,将其分为广州籍非流动(广州户籍、1年内住址无变化)、广州籍流动(广州户籍、1年内住址有变化)以及非广州籍非流动(非广州户籍、1年内住址无变化)和非广州籍流动(非广州户籍、1年内住址有变化)人口。同时收集PLWH HIV-1 pol基因序列并分型,采用HIV-TRACE方法构建分子传播网络,以传播网络的度值识别高风险传播者,并采用多分类Logistic回归模型识别感染者特征和HIV-1传播的危险因素。 结果 本研究共纳入6783名PLWH,广州籍非流动、广州籍流动、非广州籍非流动和非广州籍流动人口分别占24.0%、0.90%、56.4%和18.6%。主要流行的HIV-1基因型包括CRF07_BC(39.6%)、CRF01_AE(33.0%)、CRF55_01B(11.9%)、B亚型(4.7%)、CRF08_BC(3.0%)和CRF59_01B(2.3%)。分子传播网络分析发现,43.3%(2934/6783)的PLWH构成596个分子传播簇。与HIV-1 B亚型相比,CRF01_AE(aOR=1.384,95% CI:1.072~1.798)、CRF07_BC(aOR=2.462,95% CI:1.911~3.192)、CRF55_01B(aOR=3.209,95% CI:2.424~4.271)和CRF59_01B(aOR=2.149,95% CI:1.437~3.219)的PLWH更可能传播。人口流动性与HIV-1传播风险无统计学差异,广州籍居民更可能参与CRF08_BC传播(aOR=4.241,95% CI:1.494~12.790),而非广州籍的流动人口传播CRF01_AE(aOR=0.740,95% CI:0.576~0.946)和B亚型(aOR=0.429,95% CI:0.182~0.922)的风险较低。高风险传播者的特征包括广州籍居民(aOR=1.390,95% CI:1.141~1.695)、男性(aOR=4.449,95% CI:2.402~8.242)、男男性行为史(MSM,aOR=1.783,95% CI:1.414~2.248)、感染CRF07_BC(aOR=3.062,95% CI:1.963~4.777)或CRF55_01B(aOR=5.031,95% CI:3.159~8.014)者。 结论 尽管广州PLWH中广州籍居民仅占24.9%,但广州籍居民在HIV-1传播网络中表现较高的传播风险。此外,HIV-1基因型和MSM也是影响HIV-1传播的重要因素。分子传播网络分析可帮助识别HIV-1传播的关键人群,并揭示危险因素,是精准防控和控制HIV-1感染的重要工具。

关键词: HIV-1, 传播, 分子传播网络, 基因型, 流动人口

Abstract:

Objective To investigate the impact of HIV-1 genotypes and population mobility on HIV-1 transmission in Guangzhou to obtain evidence for devising precision prevention and control strategies. Methods Demographic data and HIV-1 pol sequences were obtained from 6783 newly diagnosed people living with HIV (PLWH) in 2008-2020 in Guangzhou, including 24.0% local Guangzhou residents, 0.9% mobile Guangzhou residents, 56.4% local non-Guangzhou residents, and 18.6% mobile non-Guangzhou residents. HIV-1 genotypes were determined and molecular transmission networks were constructed using HIV-TRACE. Degree centrality and multinomial logistic regression were used to identify the key characteristics of the PLWH and risk factors of HIV-1 transmission. Results Among the PLWH, the dominated HIV-1 genotypes were CRF07_BC (39.6%), CRF01_AE (33.0%), and CRF55_01B (11.9%), and 43.3% of the PLWH formed 596 transmission clusters. Compared with subtype B, CRF01_AE (aOR=1.384, 95% CI: 1.072-1.798), CRF07_BC (aOR=2.462, 95% CI: 1.911-3.192), CRF55_01B (aOR=3.209, 95% CI: 2.424-4.271), and CRF59_01B (aOR=2.149, 95% CI: 1.437-3.219) were more likely to cluster. Population mobility was not associated with overall HIV-1 transmission, and local Guangzhou residents were more likely to be involved in CRF08_BC transmission (aOR=4.241, 95% CI: 1.494-12.790), whereas migrants had lower odds of transmitting CRF01_AE (aOR=0.740, 95% CI: 0.576-0.946) and subtype B (aOR=0.429, 95% CI: 0.182-0.922). The characteristics of high-risk individuals for HIV-1 transmission included local Guangzhou residents (aOR=1.390, 95% CI: 1.141-1.695), men (aOR=4.449, 95% CI: 2.402-8.242), MSM (aOR=1.783, 95% CI: 1.414-2.248), and infection with CRF07_BC (aOR=3.062, 95% CI: 1.963-4.777) or CRF55_01B (aOR=5.031, 95% CI: 3.159-8.014). Conclusions Local Guangzhou residents, though accounting for only 24.9% in the PLWH, have a high risk of HIV-1 transmission, to which HIV-1 genotypes and MSM are also important contributors. Molecular network analysis provide important assistance for precision prevention and control of HIV-1 transmission.

Key words: HIV-1, transmission, molecular transmission network, genotype, migrants