文章摘要
王晓林,贾磊,李韩平,刘永健,韩婧婉,李天一,李敬云,李林.1996-2014年中国HIV-1毒株CRF01_AE亚型传播簇和传播网络研究[J].中华流行病学杂志,2019,40(1):84-88
1996-2014年中国HIV-1毒株CRF01_AE亚型传播簇和传播网络研究
Transmission cluster and network of HIV-1 CRF01_AE strain in China, 1996-2014
投稿时间:2018-07-23  
DOI:10.3760/cma.j.issn.0254-6450.2019.01.017
中文关键词: 艾滋病病毒;CRF01_AE亚型;传播簇;传播网络
英文关键词: HIV-1;CRF01_AE subtype;Transmission cluster;Transmission network
基金项目:国家自然科学基金(81773493);北京市科技计划(D141100000314001)
作者单位E-mail
王晓林 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
贾磊 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
李韩平 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
刘永健 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
韩婧婉 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
李天一 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
李敬云 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071  
李林 军事科学院军事医学研究院微生物流行病研究所病原微生物生物安全国家重点实验室, 北京 100071 dearwood@sina.com 
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中文摘要:
      目的 了解我国HIV-1毒株CRF01_AE亚型在省内和省际的传播规律和风险因素,为实施精准干预提供参考依据。方法 收集我国19个省份1996-2014年已有的2 094条CRF01_AE pol区基因序列,利用PhyML 3.0软件构建系统进化树,确定传播簇,利用Cytoscape 3.6.0软件构建传播网络,结合背景信息分析传播风险。结果 发现82个传播簇,包含255条序列(12.18%,255/2 094),省内传播簇数量和包含序列数(61个,173条)明显多于跨省传播簇(21个,82条)。传播簇中男男性传播人群的成簇比例随时间上升趋势明显,由1996-2008年的2.41%(2/83)上升为2013-2014年的23.61%(72/305)(χ2=27.800,df=1,P=0.000)。跨省传播簇的男男性传播人群比例明显高于省内传播簇,由1996-2008年的0.67%(2/297)上升为2013-2014年的6.36%(30/472),具有随时间的上升趋势(χ2=20.276,df=1,P=0.000)。跨省传播簇中男男性传播的比例(86.59%,71/82)明显高于省内传播簇(56.65%,98/173),差异有统计学意义(χ2=22.792,P=0.000)。含2种及以上传播途径的跨省传播簇的比例(33.33%,7/21)明显高于省内传播簇(13.11%,8/61),差异有统计学意义(χ2=4.273,P=0.039)。传播网络分析发现,跨省传播簇内高传播风险人群比例(51.22%,42/82)明显高于省内传播簇(26.59%,46/173),差异有统计学意义(χ2=14.932,P=0.000)。跨省传播簇以男男性传播人群为主。结论 我国HIV-1毒株CRF01_AE亚型存在复杂的传播网络,跨省传播簇快速增长,其中高风险传播者对HIV-1亚型的大范围传播起到重要作用,应深入进行传播网络研究以指导精准干预。
英文摘要:
      Objective To understand the transmission patterns and risk factors of HIV-1 strain CRF01_AE subtypes in China, and to provide guidance for the implementation of precise intervention. Methods A total of 2 094 CRF01_AE pol sequences were collected in 19 provinces in China between 1996 and 2014. Phylogenetic tree was constructed by PhyML 3.0 software to select the transmission clusters. Transmission network was constructed by Cytoscape 3.6.0, which was further used for exploring of the major risk factors. Results Of the 2 094 sequences, 12.18% (255/2 094) were in clusters. A total of 82 transmission clusters were identified. The numbers of clusters and contained sequences in intra-provincial transmission (61, 173) were significantly more than those in inter-provincial transmission (21, 82). The ratio of transmission clustering in MSM increased over time from 2.41% (2/83) during 1996-2008 to 23.61% (72/305) during 2013-2014, showing a significant upward trend (χ2=27.800, df=1, P=0.000). The proportion of MSM with inter-provincial transmission clusters were higher than those with intra-provincial transmission clusters, which increased from 0.67%(2/297) during 1996-2008 to 6.36%(30/472) during 2013-2014, showing a significant upward trend (χ2=20.276, df=1, P=0.000). The transmission rate in homosexuals of the inter-transmission clusters (86.59%, 71/82) was higher than that of intra-provincial transmission clusters (56.65%, 98/173), and the difference was statistically significant (χ2=22.792, P=0.000). The proportion of inter-provincial transmission clusters with more than 2 transmission routes (33.33%, 7/21) was higher than that of intra-provincial clusters (13.11%, 8/61), and the difference was statistically significant (χ2=4.273, P=0.039). Results from the transmission network analysis indicated that the proportion of high risk population (degree ≥ 4) with inter-provincial transmission clusters (51.22%, 42/82) was significantly higher than that with intra-provincial transmission clusters (26.59%, 46/173), and the difference was statistically significant (χ2=14.932, P=0.000). Inter-provincial clusters were mainly detected in and and MSM. Conclusions Complex transmission networks were found for HIV-1 CRF01_AE strains in the mainland of China. Inter-provincial transmission clusters increased rapidly, MSM played an important role in the wide spread of the strain. More researches in transmission networks are needed to guide the precision intervention.
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