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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

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2018 Impact Factor: 1.847

Front. Med.    2020, Vol. 14 Issue (2) : 136-148    https://doi.org/10.1007/s11684-020-0756-y
REVIEW
Molecular network-based intervention brings us closer to ending the HIV pandemic
Xiaoxu Han1,2,3, Bin Zhao1,2,3, Minghui An1,2,3, Ping Zhong1,4, Hong Shang1,2,3()
1. Key Laboratory of AIDS Immunology of National Health Commission, Department of Laboratory Medicine, The First Affiliated Hospital, China Medical University, Shenyang 110001, China
2. Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences, Shenyang 110001, China
3. Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, Hangzhou 310003, China
4. Department of AIDS and STD, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
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Abstract

Precise identification of HIV transmission among populations is a key step in public health responses. However, the HIV transmission network is usually difficult to determine. HIV molecular networks can be determined by phylogenetic approach, genetic distance-based approach, and a combination of both approaches. These approaches are increasingly used to identify transmission networks among populations, reconstruct the history of HIV spread, monitor the dynamics of HIV transmission, guide targeted intervention on key subpopulations, and assess the effects of interventions. Simulation and retrospective studies have demonstrated that these molecular network-based interventions are more cost-effective than random or traditional interventions. However, we still need to address several challenges to improve the practice of molecular network-guided targeting interventions to finally end the HIV epidemic. The data remain limited or difficult to obtain, and more automatic real-time tools are required. In addition, molecular and social networks must be combined, and technical parameters and ethnic issues warrant further studies.

Keywords human immunodeficiency virus type 1      molecular cluster      transmission cluster      risk network      targeted intervention      evaluation     
Corresponding Author(s): Hong Shang   
Just Accepted Date: 28 February 2020   Online First Date: 24 March 2020    Issue Date: 09 May 2020
 Cite this article:   
Xiaoxu Han,Bin Zhao,Minghui An, et al. Molecular network-based intervention brings us closer to ending the HIV pandemic[J]. Front. Med., 2020, 14(2): 136-148.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-020-0756-y
https://academic.hep.com.cn/fmd/EN/Y2020/V14/I2/136
Fig.1  Molecular network and underlying transmission and risk networks.
Method Model/techniques Cutoff values Objects Source/method References
GD-based method
Threshold bootstrap clustering (TBC) Resampling techniques and models of sequence evolution, such as the LogDet distance Need to be set for research purposes HIV group M (n = 38)/HIV-pol gene (subtype B, n = 356)/HCV Source code attached to study [97]
Gap Procedure Adjusted versions of the K80 distance No user-specific threshold values HIV-pol gene (subtype B, n = 1571) GapProcedure package (https://github.com/vrbiki/GapProcedure) [98]
TRAnsmission Cluster Engine (HIV-TRACE) TNa93 distances ≤1.5% genetic distance for subtype B HIV-pol gene (subtype B, n = 605) www.hivtrace.org /www.github.com/veg/hivtrace [8,99]
Phylogeny-based method
Bootstrap subtrees NJb tree with the bootstrap value Bootstrap (>85%) HIV-pol gene (subtype B, n = 191) PHYLIP package [15]
Bootstrap and branch-lengths NJb tree constructed from HKYc85 distances Bootstrap>99%, mean branch length<1.5% HIV-pol gene (subtype B, n = 193) Paup software [100]
PhyloPart MLd tree was constructed by FastTree with support values based on the SHe test; the median patristic distances within a given subtree was computed SH tested support value (>90%); genetic distances (4%–8% nucleotide substitutions per site) HIV-pol gene (subtype B, n = 11 541) Attached to the study [28]
Cluster Picker MLdtree was constructed by FastTree2 with support values based on the SHe test; the maximum pairwise distance within the subtree was computed SHe tested support value (70%–99%); genetic distances (1.5%–4.5% nucleotide substitutions per site) HIV-pol gene (subtype B, n = 1381) /HCV/Flu sequences http://hiv.bio.ed.ac.uk/software.html [29]
Tab.1  Tools for GD-based and phylogeny-based approaches
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