Literature DB >> 26990771

Molecular epidemiology identifies HIV transmission networks associated with younger age and heterosexual exposure among Korean individuals.

Bum Sik Chin1,2, Antoine Chaillon2, Sanjay R Mehta2, Joel O Wertheim2, Gayeon Kim1, Hyoung-Shik Shin1, Davey M Smith2,3.   

Abstract

To evaluate if HIV transmission networks could be elucidated from data collected in a short time frame, 131 HIV-1 pol sequences were analyzed which were generated from treatment-naïve Korean individuals who were sequentially identified over 1 year. A transmission linkage was inferred when there was a genetic distance <1.5% and a total of 16 clusters, involving 39/131 (29.8%), were identified. Younger age and heterosexual exposure were independently related with clustering in the inferred network, which demonstrated that molecular epidemiology with currently generated data (i.e., drug resistance genotypes) can be used to identify local transmission networks, even over a short timeframe. J. Med. Virol. 88:1832-1835, 2016.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  cluster analysis; human immunodeficiency virus; molecular epidemiology; phylogeny

Mesh:

Substances:

Year:  2016        PMID: 26990771      PMCID: PMC4969179          DOI: 10.1002/jmv.24523

Source DB:  PubMed          Journal:  J Med Virol        ISSN: 0146-6615            Impact factor:   2.327


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4.  Estimating the origin and evolution characteristics for Korean HIV type 1 subtype B using Bayesian phylogenetic analysis.

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5.  Phylogenetic analysis of the nef gene reveals a distinctive monophyletic clade in Korean HIV-1 cases.

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6.  Comparison of genotypic resistance mutations in treatment-naive HIV type 1-infected patients in Korea and China.

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Authors:  Ronald J Lubelchek; Sarah C Hoehnen; Anna L Hotton; Stacey L Kincaid; David E Barker; Audrey L French
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8.  Drug resistance mutations for surveillance of transmitted HIV-1 drug-resistance: 2009 update.

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9.  Epidemiological study of phylogenetic transmission clusters in a local HIV-1 epidemic reveals distinct differences between subtype B and non-B infections.

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10.  Using HIV networks to inform real time prevention interventions.

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Journal:  PLoS One       Date:  2014-06-05       Impact factor: 3.240

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