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      Frequently Transmission and Close Relationship Among Immigrants in the China–Myanmar Border Region Indicated by Molecular Transmission Analysis From a Cross-Sectional Data

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          Abstract

          Background

          Accurate identification of molecular transmission clusters (MTCs) and understanding the dynamics of human immunodeficiency virus (HIV) transmission are necessary to develop targeted interventions to prevent HIV transmission. We evaluated the characteristics of antiretroviral therapy-naïve individuals who belonged to HIV-1 MTCs in the China–Myanmar border region to inform targeted effective HIV intervention.

          Methods

          Phylogenetic analyses were undertaken on HIV-1 pol sequences to characterize subtypes or circulating recombinant forms and identify MTCs. MTCs were defined as those with 2 or more sequences having bootstrap support > 80% and a pairwise gene distance less than or equal to 0.03. Factors correlated with MTCs were evaluated using logistic regression analysis. The chi-square test was used to compare differences between Chinese and Burmese participants belonging to MTCs.

          Results

          A total of 900 people had their pol gene successfully sequenced. Twenty-one MTCs were identified and included 110 individuals (12.2%). Individuals in MTCs were more likely to be Burmese [aOR = 2.24 (95% CI: 1.33, 3.79), P = 0.003], be younger [aOR = 0.34 (95% CI: 0.20, 0.58), P < 0.001 for age 26–50 vs. 25 years or younger], have a lower CD4 T cell count [aOR = 2.86 (95% CI: 1.34, 6.11), P = 0.007 for < 200 vs. 350 or greater], and have subtypes CRF07_BC or C [CRF07_BC: aOR = 7.88 (95% CI: 3.55, 17.52), P < 0.001; C: aOR = 2.38 (95% CI: 1.23, 4.62), P = 0.010 compared to CRF01_AE]. In MTCs, Burmese were younger (89.7 vs. 57.7% for age 25 years or younger), had a lower education level (41.0 vs. 8.5% for illiterate), were more likely to be infected through injection drug use (35.9 vs. 12.7%), and had a higher proportion of subtype BC (33.3 vs. 15.5%) and CRF01_AE (20.5 vs. 8.5%) compared to Chinese ( P < 0.05 for all).

          Conclusion

          Burmese participants were more likely to belong to MTCs, and most MTCs had both Burmese and Chinese participants. These data highlight the bidirectional transmission of HIV-1 frequently transmission and close relationship among immigrants in the China–Myanmar border region. Local health departments should pay more attention to HIV screening and intervention to immigrants Burmese with the characteristics of younger age, having lower CD4 T cell count and infected with HIV subtypes CRF07_ BC or C.

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          Most cited references41

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          Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees.

          K Tamura, M Nei (1993)
          Examining the pattern of nucleotide substitution for the control region of mitochondrial DNA (mtDNA) in humans and chimpanzees, we developed a new mathematical method for estimating the number of transitional and transversional substitutions per site, as well as the total number of nucleotide substitutions. In this method, excess transitions, unequal nucleotide frequencies, and variation of substitution rate among different sites are all taken into account. Application of this method to human and chimpanzee data suggested that the transition/transversion ratio for the entire control region was approximately 15 and nearly the same for the two species. The 95% confidence interval of the age of the common ancestral mtDNA was estimated to be 80,000-480,000 years in humans and 0.57-2.72 Myr in common chimpanzees.
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            Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data.

            Molecular sequences obtained at different sampling times from populations of rapidly evolving pathogens and from ancient subfossil and fossil sources are increasingly available with modern sequencing technology. Here, we present a Bayesian statistical inference approach to the joint estimation of mutation rate and population size that incorporates the uncertainty in the genealogy of such temporally spaced sequences by using Markov chain Monte Carlo (MCMC) integration. The Kingman coalescent model is used to describe the time structure of the ancestral tree. We recover information about the unknown true ancestral coalescent tree, population size, and the overall mutation rate from temporally spaced data, that is, from nucleotide sequences gathered at different times, from different individuals, in an evolving haploid population. We briefly discuss the methodological implications and show what can be inferred, in various practically relevant states of prior knowledge. We develop extensions for exponentially growing population size and joint estimation of substitution model parameters. We illustrate some of the important features of this approach on a genealogy of HIV-1 envelope (env) partial sequences.
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              The changing face of HIV in China.

              HIV has advanced from high-risk groups such as intravenous drug users to some in the general population, according to comprehensive new data from the south of China. What needs to be done to halt its spread?
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                Author and article information

                Contributors
                Journal
                Front Med (Lausanne)
                Front Med (Lausanne)
                Front. Med.
                Frontiers in Medicine
                Frontiers Media S.A.
                2296-858X
                27 April 2022
                2021
                : 8
                : 693915
                Affiliations
                [1] 1NHC Key Laboratory of AIDS Immunology (China Medical University), National Clinical Research Center for Laboratory Medicine, The First Affiliated Hospital of China Medical University , Shenyang, China
                [2] 2Key Laboratory of AIDS Immunology, Chinese Academy of Medical Sciences , Shenyang, China
                [3] 3Key Laboratory of AIDS Immunology of Liaoning Province , Shenyang, China
                [4] 4Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases , Hangzhou, China
                [5] 5Department of STD/AIDS Prevention and Control, Dehong Prefecture Center for Disease Control and Prevention , Mangshi, China
                [6] 6Key Laboratory of Digestive Cancer Full Cycle Monitoring and Precise Intervention of Shanghai Municipal Health Commission, Minhang Hospital, Fudan University , Shanghai, China
                [7] 7Department of Epidemiology, University of North Carolina at Chapel Hill , Chapel Hill, NC, United States
                [8] 8Institute for AIDS/STD Control and Prevention, Yunnan Center for Disease Control and Prevention , Kunming, China
                Author notes

                Edited by: Jun Chen, Fudan University, China

                Reviewed by: Yuhua Ruan, National Center for AIDS/STD Control and Prevention, Chinese Center for Disease Control and Prevention, China; Zixin Wang, The Chinese University of Hong Kong, Hong Kong SAR, China

                *Correspondence: Min Chen, chenminyx@ 123456hotmail.com

                These authors have contributed equally to this work and share first authorship

                §These authors have contributed equally to this work and share last authorship

                This article was submitted to Infectious Diseases – Surveillance, Prevention and Treatment, a section of the journal Frontiers in Medicine

                Article
                10.3389/fmed.2021.693915
                9094042
                35572804
                2ef8c837-7a7a-41df-9e9c-f6002134082a
                Copyright © 2022 Hu, Liu, Wang, Meng, Leuba, Wei, Duan, Chu, Chen, Shang and Xu.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 12 April 2021
                : 20 December 2021
                Page count
                Figures: 4, Tables: 3, Equations: 0, References: 41, Pages: 10, Words: 6472
                Categories
                Medicine
                Original Research

                hiv,molecular epidemiology,phylogenetic analysis,cross-border,subtype

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