Short Communication

HIV-1 Transmission Networks Across South Korea

Mi Young Ahn, Joel O. Wertheim, Woo Joo Kim, Shin Woo Kim, Jin Soo Lee, Hea Won Ann, Yongduk Jeon, Jin Young Ahn, Je Eun Song, Dong Hyun Oh, Yong Chan Kim, Eun Jin Kim, In Young Jung, Moo Hyun Kim, Wooyoung Jeong, Su Jin Jeong, Nam Su Ku, June Myung Kim, Davey M. Smith, JunYong Choi

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Molecular epidemiology can help clarify the properties and dynamics of HI-1 transmission networks in both global and regional scales. We studied 143 HIV-1-infected individuals recruited from four medical centers of three cities in South Korea between April 2013 and May 2014. HIV-1 env V3 sequence data were generated (337-793 bp) and analyzed using a pairwise distance-based clustering approach to infer putative transmission networks. Participants whose viruses were ≤2.0% divergent according to Tamura-Nei 93 genetic distance were defined as clustering. We collected demographic, risk, and clinical data and analyzed these data in relation to clustering. Among 143 participants, we identified nine putative transmission clusters of different sizes (range 2-4 participants). The reported risk factor of participants were concordant in only one network involving two participants, that is, both individuals reported homosexual sex as their risk factor. The participants in the other eight networks did not report concordant risk factors, although they were phylogenetically linked. About half of the participants refused to report their risk factor. Overall, molecular epidemiology provides more information to understand local transmission networks and the risks associated with these networks.

Original languageEnglish
Pages (from-to)827-831
Number of pages5
JournalAIDS Research and Human Retroviruses
Volume33
Issue number8
DOIs
Publication statusPublished - 2017 Aug 1

Fingerprint

Republic of Korea
HIV-1
Communication
Cluster Analysis
Molecular Epidemiology
Demography
Viruses

All Science Journal Classification (ASJC) codes

  • Immunology
  • Virology
  • Infectious Diseases

Cite this

Ahn, M. Y., Wertheim, J. O., Kim, W. J., Kim, S. W., Lee, J. S., Ann, H. W., ... Choi, J. (2017). Short Communication: HIV-1 Transmission Networks Across South Korea. AIDS Research and Human Retroviruses, 33(8), 827-831. https://doi.org/10.1089/aid.2016.0212
Ahn, Mi Young ; Wertheim, Joel O. ; Kim, Woo Joo ; Kim, Shin Woo ; Lee, Jin Soo ; Ann, Hea Won ; Jeon, Yongduk ; Ahn, Jin Young ; Song, Je Eun ; Oh, Dong Hyun ; Kim, Yong Chan ; Kim, Eun Jin ; Jung, In Young ; Kim, Moo Hyun ; Jeong, Wooyoung ; Jeong, Su Jin ; Ku, Nam Su ; Kim, June Myung ; Smith, Davey M. ; Choi, JunYong. / Short Communication : HIV-1 Transmission Networks Across South Korea. In: AIDS Research and Human Retroviruses. 2017 ; Vol. 33, No. 8. pp. 827-831.
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abstract = "Molecular epidemiology can help clarify the properties and dynamics of HI-1 transmission networks in both global and regional scales. We studied 143 HIV-1-infected individuals recruited from four medical centers of three cities in South Korea between April 2013 and May 2014. HIV-1 env V3 sequence data were generated (337-793 bp) and analyzed using a pairwise distance-based clustering approach to infer putative transmission networks. Participants whose viruses were ≤2.0{\%} divergent according to Tamura-Nei 93 genetic distance were defined as clustering. We collected demographic, risk, and clinical data and analyzed these data in relation to clustering. Among 143 participants, we identified nine putative transmission clusters of different sizes (range 2-4 participants). The reported risk factor of participants were concordant in only one network involving two participants, that is, both individuals reported homosexual sex as their risk factor. The participants in the other eight networks did not report concordant risk factors, although they were phylogenetically linked. About half of the participants refused to report their risk factor. Overall, molecular epidemiology provides more information to understand local transmission networks and the risks associated with these networks.",
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Ahn, MY, Wertheim, JO, Kim, WJ, Kim, SW, Lee, JS, Ann, HW, Jeon, Y, Ahn, JY, Song, JE, Oh, DH, Kim, YC, Kim, EJ, Jung, IY, Kim, MH, Jeong, W, Jeong, SJ, Ku, NS, Kim, JM, Smith, DM & Choi, J 2017, 'Short Communication: HIV-1 Transmission Networks Across South Korea', AIDS Research and Human Retroviruses, vol. 33, no. 8, pp. 827-831. https://doi.org/10.1089/aid.2016.0212

Short Communication : HIV-1 Transmission Networks Across South Korea. / Ahn, Mi Young; Wertheim, Joel O.; Kim, Woo Joo; Kim, Shin Woo; Lee, Jin Soo; Ann, Hea Won; Jeon, Yongduk; Ahn, Jin Young; Song, Je Eun; Oh, Dong Hyun; Kim, Yong Chan; Kim, Eun Jin; Jung, In Young; Kim, Moo Hyun; Jeong, Wooyoung; Jeong, Su Jin; Ku, Nam Su; Kim, June Myung; Smith, Davey M.; Choi, JunYong.

In: AIDS Research and Human Retroviruses, Vol. 33, No. 8, 01.08.2017, p. 827-831.

Research output: Contribution to journalArticle

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T1 - Short Communication

T2 - HIV-1 Transmission Networks Across South Korea

AU - Ahn, Mi Young

AU - Wertheim, Joel O.

AU - Kim, Woo Joo

AU - Kim, Shin Woo

AU - Lee, Jin Soo

AU - Ann, Hea Won

AU - Jeon, Yongduk

AU - Ahn, Jin Young

AU - Song, Je Eun

AU - Oh, Dong Hyun

AU - Kim, Yong Chan

AU - Kim, Eun Jin

AU - Jung, In Young

AU - Kim, Moo Hyun

AU - Jeong, Wooyoung

AU - Jeong, Su Jin

AU - Ku, Nam Su

AU - Kim, June Myung

AU - Smith, Davey M.

AU - Choi, JunYong

PY - 2017/8/1

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N2 - Molecular epidemiology can help clarify the properties and dynamics of HI-1 transmission networks in both global and regional scales. We studied 143 HIV-1-infected individuals recruited from four medical centers of three cities in South Korea between April 2013 and May 2014. HIV-1 env V3 sequence data were generated (337-793 bp) and analyzed using a pairwise distance-based clustering approach to infer putative transmission networks. Participants whose viruses were ≤2.0% divergent according to Tamura-Nei 93 genetic distance were defined as clustering. We collected demographic, risk, and clinical data and analyzed these data in relation to clustering. Among 143 participants, we identified nine putative transmission clusters of different sizes (range 2-4 participants). The reported risk factor of participants were concordant in only one network involving two participants, that is, both individuals reported homosexual sex as their risk factor. The participants in the other eight networks did not report concordant risk factors, although they were phylogenetically linked. About half of the participants refused to report their risk factor. Overall, molecular epidemiology provides more information to understand local transmission networks and the risks associated with these networks.

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