Cargando…

Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016

We aimed to elucidate the characteristics of HIV molecular epidemiology and identify transmission hubs in eastern China using genetic transmission network and lineage analyses. HIV-TRACE was used to infer putative relationships. Across the range of epidemiologically-plausible genetic distance (GD) t...

Descripción completa

Detalles Bibliográficos
Autores principales: Ding, Xiaobei, Chaillon, Antoine, Pan, Xiaohong, Zhang, Jiafeng, Zhong, Ping, He, Lin, Chen, Wanjun, Fan, Qin, Jiang, Jun, Luo, Mingyu, Xia, Yan, Guo, Zhihong, Smith, Davey M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202869/
https://www.ncbi.nlm.nih.gov/pubmed/35709166
http://dx.doi.org/10.1371/journal.pone.0269973
_version_ 1784728603733262336
author Ding, Xiaobei
Chaillon, Antoine
Pan, Xiaohong
Zhang, Jiafeng
Zhong, Ping
He, Lin
Chen, Wanjun
Fan, Qin
Jiang, Jun
Luo, Mingyu
Xia, Yan
Guo, Zhihong
Smith, Davey M.
author_facet Ding, Xiaobei
Chaillon, Antoine
Pan, Xiaohong
Zhang, Jiafeng
Zhong, Ping
He, Lin
Chen, Wanjun
Fan, Qin
Jiang, Jun
Luo, Mingyu
Xia, Yan
Guo, Zhihong
Smith, Davey M.
author_sort Ding, Xiaobei
collection PubMed
description We aimed to elucidate the characteristics of HIV molecular epidemiology and identify transmission hubs in eastern China using genetic transmission network and lineage analyses. HIV-TRACE was used to infer putative relationships. Across the range of epidemiologically-plausible genetic distance (GD) thresholds (0.1–2.0%), a sensitivity analysis was performed to determine the optimal threshold, generating the maximum number of transmission clusters and providing reliable resolution without merging different small clusters into a single large cluster. Characteristics of genetically linked individuals were analyzed using logistic regression. Assortativity (shared characteristics) analysis was performed to infer shared attributes between putative partners. 1,993 persons living with HIV-1 were enrolled. The determined GD thresholds within subtypes CRF07_BC, CRF01_AE, and B were 0.5%, 1.2%, and 1.7%, respectively, and 826 of 1,993 (41.4%) sequences were linked with at least one other sequence, forming 188 transmission clusters of 2–80 sequences. Clustering rates for the main subtypes CRF01_AE, CRF07_BC, and B were 50.9% (523/1027), 34.2% (256/749), and 32.1% (25/78), respectively. Median cluster sizes of these subtypes were 2 (2–52, n = 523), 2 (2–80, n = 256), and 3 (2–6, n = 25), respectively. Subtypes in individuals diagnosed and residing in Hangzhou city (OR = 1.423, 95% CI: 1.168–1.734) and men who have sex with men (MSM) were more likely to cluster. Assortativity analysis revealed individuals were more likely to be genetically linked to individuals from the same age group (AI(age) = 0.090, P<0.001) and the same area of residency in Zhejiang (AI(city) = 0.078, P<0.001). Additionally, students living with HIV were more likely to be linked with students than show a random distribution (AI (student) = 0.740, P<0.01). These results highlight the importance of Hangzhou City in the regional epidemic and show that MSM comprise the population rapidly transmitting HIV in Zhejiang Province. We also provide a molecular epidemiology framework for improving our understanding of HIV transmission dynamics in eastern China.
format Online
Article
Text
id pubmed-9202869
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-92028692022-06-17 Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016 Ding, Xiaobei Chaillon, Antoine Pan, Xiaohong Zhang, Jiafeng Zhong, Ping He, Lin Chen, Wanjun Fan, Qin Jiang, Jun Luo, Mingyu Xia, Yan Guo, Zhihong Smith, Davey M. PLoS One Research Article We aimed to elucidate the characteristics of HIV molecular epidemiology and identify transmission hubs in eastern China using genetic transmission network and lineage analyses. HIV-TRACE was used to infer putative relationships. Across the range of epidemiologically-plausible genetic distance (GD) thresholds (0.1–2.0%), a sensitivity analysis was performed to determine the optimal threshold, generating the maximum number of transmission clusters and providing reliable resolution without merging different small clusters into a single large cluster. Characteristics of genetically linked individuals were analyzed using logistic regression. Assortativity (shared characteristics) analysis was performed to infer shared attributes between putative partners. 1,993 persons living with HIV-1 were enrolled. The determined GD thresholds within subtypes CRF07_BC, CRF01_AE, and B were 0.5%, 1.2%, and 1.7%, respectively, and 826 of 1,993 (41.4%) sequences were linked with at least one other sequence, forming 188 transmission clusters of 2–80 sequences. Clustering rates for the main subtypes CRF01_AE, CRF07_BC, and B were 50.9% (523/1027), 34.2% (256/749), and 32.1% (25/78), respectively. Median cluster sizes of these subtypes were 2 (2–52, n = 523), 2 (2–80, n = 256), and 3 (2–6, n = 25), respectively. Subtypes in individuals diagnosed and residing in Hangzhou city (OR = 1.423, 95% CI: 1.168–1.734) and men who have sex with men (MSM) were more likely to cluster. Assortativity analysis revealed individuals were more likely to be genetically linked to individuals from the same age group (AI(age) = 0.090, P<0.001) and the same area of residency in Zhejiang (AI(city) = 0.078, P<0.001). Additionally, students living with HIV were more likely to be linked with students than show a random distribution (AI (student) = 0.740, P<0.01). These results highlight the importance of Hangzhou City in the regional epidemic and show that MSM comprise the population rapidly transmitting HIV in Zhejiang Province. We also provide a molecular epidemiology framework for improving our understanding of HIV transmission dynamics in eastern China. Public Library of Science 2022-06-16 /pmc/articles/PMC9202869/ /pubmed/35709166 http://dx.doi.org/10.1371/journal.pone.0269973 Text en © 2022 Ding et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ding, Xiaobei
Chaillon, Antoine
Pan, Xiaohong
Zhang, Jiafeng
Zhong, Ping
He, Lin
Chen, Wanjun
Fan, Qin
Jiang, Jun
Luo, Mingyu
Xia, Yan
Guo, Zhihong
Smith, Davey M.
Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016
title Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016
title_full Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016
title_fullStr Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016
title_full_unstemmed Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016
title_short Characterizing genetic transmission networks among newly diagnosed HIV-1 infected individuals in eastern China: 2012–2016
title_sort characterizing genetic transmission networks among newly diagnosed hiv-1 infected individuals in eastern china: 2012–2016
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9202869/
https://www.ncbi.nlm.nih.gov/pubmed/35709166
http://dx.doi.org/10.1371/journal.pone.0269973
work_keys_str_mv AT dingxiaobei characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT chaillonantoine characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT panxiaohong characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT zhangjiafeng characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT zhongping characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT helin characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT chenwanjun characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT fanqin characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT jiangjun characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT luomingyu characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT xiayan characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT guozhihong characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016
AT smithdaveym characterizinggenetictransmissionnetworksamongnewlydiagnosedhiv1infectedindividualsineasternchina20122016