Using molecular transmission networks to analyze the epidemiological characteristics of HIV-1 CRF01_AE in Kunming

CHENG Peng; LIU Jiafa; WANG Jiali; YANG Cuixian; HE Baocui; ZHANG Mi; LI Jianjian; DONG Xingqi

doi:10.16462/j.cnki.zhjbkz.2024.05.013

Volume 28 Issue 5

May 2024

Turn off MathJax

Article Contents

Article Navigation > CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION > 2024 > 28(5): 574-580

CHENG Peng, LIU Jiafa, WANG Jiali, YANG Cuixian, HE Baocui, ZHANG Mi, LI Jianjian, DONG Xingqi. Using molecular transmission networks to analyze the epidemiological characteristics of HIV-1 CRF01_AE in Kunming[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(5): 574-580. doi: 10.16462/j.cnki.zhjbkz.2024.05.013

Citation:

CHENG Peng, LIU Jiafa, WANG Jiali, YANG Cuixian, HE Baocui, ZHANG Mi, LI Jianjian, DONG Xingqi. Using molecular transmission networks to analyze the epidemiological characteristics of HIV-1 CRF01_AE in Kunming[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(5): 574-580. doi: 10.16462/j.cnki.zhjbkz.2024.05.013

Citation:

CHENG Peng, LIU Jiafa, WANG Jiali, YANG Cuixian, HE Baocui, ZHANG Mi, LI Jianjian, DONG Xingqi. Using molecular transmission networks to analyze the epidemiological characteristics of HIV-1 CRF01_AE in Kunming[J]. CHINESE JOURNAL OF DISEASE CONTROL & PREVENTION, 2024, 28(5): 574-580. doi: 10.16462/j.cnki.zhjbkz.2024.05.013

PDF( 5927 KB)

Using molecular transmission networks to analyze the epidemiological characteristics of HIV-1 CRF01_AE in Kunming

doi: 10.16462/j.cnki.zhjbkz.2024.05.013

CHENG Peng^{1, 2},
LIU Jiafa¹,
WANG Jiali¹,
YANG Cuixian¹,
HE Baocui²,
ZHANG Mi¹,
LI Jianjian^{1
,
,},
DONG Xingqi^{2, 3
,
,}

1.
Yunnan Infectious Disease Hospital, Department of Laboratory, Yunnan AIDS Care Center, Kunming 650301, China
2.
Department of Epidemiology, School of Public Health, Kunming Medical University, Kunming 650000, China
3.
Office of the Chief Expert, Yunnan Infectious Disease Hospital, Yunnan AIDS Care Center, Kunming 650301, China

Funds:

Yunnan Provincial Department of Science and Technology-Kunming Medical University Joint Special Funds for Applied Basic Research 202201AY070001-208

Yunnan Provincial Department of Science and Technology-Kunming Medical University Joint Special Funds for Applied Basic Research 202101AY070001-223

Yunnan Provincial Research Center for Technological Innovation in HIV Virology and Clinical Diagnosis and Treatment 202102AA310005

Innovative Team of Yunnan Provincial Department of Education CXTD202111

More Information

Corresponding author: LI Jianjian, E-mail: jianandni@163.com; DONG Xingqi, E-mail: dongxq8001@126.com
Received Date: 2023-07-07
Rev Recd Date: 2023-07-07

Available Online: 2024-06-05

Publish Date: 2024-05-10

Abstract

Abstract

Objective To construct the molecular transmission network of the HIV-1 CRF01_AE strain in Kunming, to analyze its epidemiological characteristics, to observe its dynamic epidemiological trends, and to provide a scientific basis for the development of local epidemic prevention and control interventions. Methods A total of 253 newly infected patients with HIV-1 CRF01_AE in Kunming who received treatment at Yunnan Infectious Disease Hospital from 2015 to 2021 were selected as study subjects. Their gene sequences were successfully amplified using RT-nested PCR (reverse transcription nested polymerase chain reaction), and the sequences were compared and imported into HyPhy 2.2.4 software for the calculation of paired gene distances. GraphPad-Prism 8.0 software was used to determine the optimal gene distance threshold, and Cytoscope 3.7.2 software was used for network visualization. Network characterization was performed using the Network Analyzer and MCODE (Molecular Complex Detection) tools. Results At an optimal genetic distance threshold of 0.018, 118 of 253 study subjects (46.64%) entered the network analysis, forming a total of 38 molecular clusters with composition sizes ranging from 2 to 17 nodes. The network clusters were mainly heterosexual (51.78%) and homosexual (37.94%), and the age group was mainly distributed between 20 and 40 years old (77.47%). The total number of links for all nodes in the network was 226; the maximum number of links for a single node was 10. MCODE identified three important molecular clusters, types B, C and D. Type B consisted of 17 nodes and 19 link counts and was a homosexually propagating cluster in a low-growth state. Types C and D both consisted of 5 nodes and 10 link counts, were heterosexually propagating clusters, and were stationary. Conclusions The molecular clusters in the molecular transmission network of the HIV-1 CRF01_AE strain in Kunming have certain specificity and aggregation. Homosexual and heterosexual transmission populations have become the two major risk groups for HIV-1 CRF01_AE strain infection in Kunming, while cross-transmission occurs in both groups. It is worth noting that there is a large cluster of same-sex transmission in the transmission network with high transmission risk and activity, which needs to be monitored. Targeted interventions should be developed to prevent and control the "core population" in the cluster.
- HIV-1 CRF01_AE,
- Molecular transmission network,
- Paired genetic distances,
- Molecular cluster

FullText(HTML)

References(24)

References

[1]	Shushtari ZJ, Hosseini SA, Sajjadi H, et al. Social network and HIV risk behaviors in female sex workers: a systematic review[J]. BMC Public Health, 2018, 18(1): 1020. DOI: 10.1186/s12889-018-5944-1.
[2]	Billock RM, Powers KA, Pasquale DK, et al. Prediction of HIV transmission cluster growth with statewide surveillance data[J]. JAIDS J Acq Imm Def, 2019, 80(2): 152-159. DOI: 10.1097/qai.0000000000001905.
[3]	Fan Q, Zhang JF, Luo MY, et al. Molecular genetics and epidemiological characteristics of HIV-1 epidemic strains in various sexual risk behaviour groups in developed Eastern China, 2017-2020[J]. Emerg Microbes Infect, 2022, 11(1): 2326-2339. DOI: 10.1080/22221751.2022.2119167.
[4]	Aldous JL, Pond SK, Poon A, et al. Characterizing HIV transmission networks across the United States[J]. Clin Infect Dis, 2012, 55(8): 1135-1143. DOI: 10.1093/cid/cis612.
[5]	Brenner BG, Roger M, Moisi DD, et al. Transmission networks of drug resistance acquired in primary/early stage HIV infection[J]. AIDS, 2008, 22(18): 2509-2515. DOI: 10.1097/qad.0b013e3283121c90.
[6]	Gibson KM, Jair K, Castel AD, et al. A cross-sectional study to characterize local HIV-1 dynamics in Washington, DC using next-generation sequencing[J]. Sci Rep, 2020, 10: 1989. DOI: 10.1038/s41598-020-58410-y.
[7]	Chen M, Ma YL, Chen HC, et al. Spatial clusters of HIV-1 genotypes in a recently infected population in Yunnan, China[J]. BMC Infect Dis, 2019, 19(1): 669. DOI: 10.1186/s12879-019-4276-9.
[8]	Chen M, Yang L, Ma YL, et al. Emerging variability in HIV-1 genetics among recently infected individuals in Yunnan, China[J]. PLoS One, 2013, 8(3): e60101. DOI: 10.1371/journal.pone.0060101.
[9]	Li K, Liu ML, Chen HH, et al. Using molecular transmission networks to understand the epidemic characteristics of HIV-1 CRF08_BC across China[J]. Emerg Microbes Infect, 2021, 10(1): 497-506. DOI: 10.1080/22221751.2021.1899056.
[10]	Deng XM, Liu JF, Li JJ, et al. Prevalence of HIV-1 drug-resistance genotypes among unique recombinant forms from Yunnan Province, China in 2016-2017[J]. AIDS Res Hum Retroviruses, 2020, 36(5): 389-398. DOI: 10.1089/aid.2019.0041.
[11]	Tamura K, Nei M. Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees[J]. Mol Biol Evol, 1993, 10(3): 512-526. DOI: 10.1093/oxfordjournals.molbev.a040023.
[12]	Otasek D, Morris JH, Bouças J, et al. Cytoscape Automation: empowering workflow-based network analysis[J]. Genome Biol, 2019, 20(1): 185. DOI: 10.1186/s13059-019-1758-4.
[13]	Halary S, Leigh JW, Cheaib B, et al. Network analyses structure genetic diversity in independent genetic worlds[J]. Proc Natl Acad Sci USA, 2010, 107(1): 127-132. DOI: 10.1073/pnas.0908978107.
[14]	Zhang YY, Dai J, Li ZX, et al. Using molecular network analysis to explore the characteristics of HIV-1 transmission in a China-Myanmar border area[J]. PLoS One, 2022, 17(5): e0268143. DOI: 10.1371/journal.pone.0268143.
[15]	Banerjee S, Baah-Acheamfour M, Carlyle CN, et al. Determinants of bacterial communities in Canadian agroforestry systems[J]. Environ Microbiol, 2016, 18(6): 1805-1816. DOI: 10.1111/1462-2920.12986.
[16]	赵帅, 冯毅, 辛若雷, 等. 应用分子传播网络研究北京男男性行为者HIV-1毒株的传播特征[J]. 中国艾滋病性病, 2018, 24(3): 241-245, 306. DOI: 10.13419/j.cnki.aids.2018.03.08. Zhao S, Feng Y, Xin RL, et al. Using molecular transmission network to explore the transmission characteristics of HIV-1 among men who have sex with men in Beijing[J]. Chin J AIDS STD, 2018, 24(3): 241-245, 306. DOI: 10.13419/j.cnki.aids.2018.03.08.
[17]	Wertheim JO, Kosakovsky Pond SL, Forgione LA, et al. Social and genetic networks of HIV-1 transmission in New York city[J]. PLoS Pathog, 2017, 13(1): e1006000. DOI: 10.1371/journal.ppat.1006000.
[18]	Delva W, Leventhal GE, Helleringer S. Connecting the dots: network data and models in HIV epidemiology[J]. AIDS Lond Engl, 2016, 30(13): 2009-2020. DOI: 10.1097/QAD.0000000000001184.
[19]	杨垚, 梁华悦, 钟姗妹, 等. 2018年广西崇左边境ART人群HIV-1分子网络特征分析[J]. 中国艾滋病性病, 2021, 27(6): 577-581. DOI: 10.13419/j.cnki.aids.2021.06.03. Yang Y, Liang HY, Zhong SM, et al. Molecular Network Analysis of HIV/AIDS patients receiving antiviral therapy in Chongzuo, Guangxi in 2018[J]. Chin J AIDS STD, 2021, 27(6): 577-581. DOI: 10.13419/j.cnki.aids.2021.06.03.
[20]	甘梦泽, 冯毅, 邢辉. 基于分子网络方法研究HIV感染者传播特征的相关进展[J]. 中华流行病学杂志, 2019, 40(11): 1487-1491. DOI: 10.3760/cma.j.issn.0254-6450.2019.11.026. Gan MZ, Feng Y, Xing H. Progress in research on the transmission characteristics of HIV-infected persons based on molecular network method[J]. Chin J Epidemiol, 2019, 40(11): 1487-1491. DOI: 10.3760/cma.j.issn.0254-6450.2019.11.026.
[21]	Chen M, Ma YL, Chen HC, et al. HIV-1 genetic transmission networks among men who have sex with men in Kunming, China[J]. PLoS One, 2018, 13(4): e0196548. DOI: 10.1371/journal.pone.0196548.
[22]	Wertheim JO, Murrell B, Mehta SR, et al. Growth of HIV-1 molecular transmission clusters in New York city[J]. J Infect Dis, 2018, 218(12): 1943-1953. DOI: 10.1093/infdis/jiy431.
[23]	Mehta SR, Wertheim JO, Brouwer KC, et al. HIV transmission networks in the San diego-tijuana border region[J]. EBioMedicine, 2015, 2(10): 1456-1463. DOI: 10.1016/j.ebiom.2015.07.024.
[24]	Han X, Zhao B, An M, et al. Molecular network-based intervention brings us closer to ending the HIV pandemic[J]. Front Med. 2020, 14(2): 136-148. DOI: 10.1007/s11684-020-0756-y.