Analysis of gene subtypes and molecular transmission characteristics of HIV-1 infected individuals in Shanghai from 2015 to 2018

doi:10.16150/j.1671-2870.2024.06.002

Abstract

Abstract:

Objective Analyze the molecular epidemiological characteristics and influencing factors of human immunodeficiency virus type 1 (HIV-1) infected individuals in Shanghai, and to provide a scientific basis for developing effective intervention measures. Method A total of 1 322 serum samples from newly reported HIV-1 infected individuals between 2015 and 2018 were collected. Nested PCR was employed to amplify the HIV-1 pol gene sequences. Virus subtype analysis was then conducted based on the pol gene sequences, and a molecular network was constructed using the optimal gene distance. The characteristics of the molecular network and its influencing factors were analyzed. Results A total of 1 241 HIV-1 pol gene sequences were obtained from 1 322 samples, and 12 HIV genotypes were identified. The dominant subtypes were with CRF01_AE and CRF07_BC subtypes, accounting for 50.93% and 34.0%. respectively. Among these, 530 sequences entered the molecular network, with a clustering rate of 42.71% (530/1241), A total of 95 transmission clusters were formed, with cluster sizes ranging from 2 to 219 nodes. One large cluster contained 219 nodes (41.32%, 219/530). The highest clustering rate was observed in the CRF07_BC subtype (59.48%, 251/422), followed by 01B (52.46%, 32/61) and CRF01_AE (34.55%, 218/631). Male-to-male sexual transmission was more likely to form networks compared to heterosexual transmission. Conclusions The HIV-1 gene subtypes were diverse, with CRF01_AE and CRF07BC subtypes as the main dominant strainsin Shanghai. during 2015-2018, The molecular network showed an clustered distribution, and MSM are infected with HIV-1 have a faster ability to transmit the virus, leading to higher infection rates and easier entry into the network as high-risk carriers. Strengthening HIV-1 molecular monitoring can timely understand the transmission dynamics of the virus strain in different populations and help public health departments take effective intervention measures to reduce new HIV infections and prevent the spread of the epidemic

Key words: HIV-1 gene, Molecular network, Molecular cluster，Communication characteristics

CLC Number:

R512.91

WU Jian, CHEN Weihua, XU Hao, XU Yuan, SHEN Yongxiu, NING Zhen, QIN Ting, LIN Yi, SHEN Xin, YU Xiaolei. Analysis of gene subtypes and molecular transmission characteristics of HIV-1 infected individuals in Shanghai from 2015 to 2018[J]. Journal of Diagnostics Concepts & Practice, 2024, 23(06): 568-573.

Figures/Tables 3

Fig.1

Fig.2

Table 1

References 18

[1]	SMITH D M, MAY S J, TWEETEN S, et al. A public health model for the molecular surveillance of HIV transmission in San Diego, California[J]. AIDS, 2009, 23(2):225-232. doi: 10.1097/QAD.0b013e32831d2a81 pmid: 19098493
[2]	LITTLE S J, KOSAKOVSKY POND S L, ANDERSON C M, et al. Using HIV networks to inform real time prevention interventions[J]. PLoS One, 2014, 9(6):e98443.
[3]	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.
	GAN M Z, 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.
[4]	冯毅, 王栋, 邢辉. HIV分子传播网络助力我国艾滋病精准防控[J]. 中国艾滋病性病, 2023, 29(1):1-8.
	FENG Y, WANG D, XING H. HIV molecular transmission network helps precise prevention and control of AIDS in China[J]. Chin J AIDS & STD, 2023, 29(1):1-8.
[5]	李一, 惠珊, 张锦慧, 等. 黑龙江省2018年新发现HIV-1感染者毒株亚型分子簇及耐药情况[J]. 中国艾滋病性病, 2021, 27(7):680-684.
	LI Y, HUI S, ZHANG J H, et al. Analysis on HIV subtypes,molecular clusters and drug resistance among newly reported infections in Heilongjiang Province in 2018[J]. Chin J AIDS & STD, 2021, 27(7):680-684.
[6]	NATIONAL CENTER FOR AIDS/STD CONTROL AND PREVENTION C C F D C A P. Guideline of monitor and intervention technique of HIV transmission network in China has been issued[Z]. 2021.
[7]	HAO J, ZHENG S, GAN M, et al. Changing proportions of HIV-1 subtypes and transmitted drug resistance among newly diagnosed HIV/AIDS individuals - China, 2015 and 2018[J]. China CDC Wkly, 2021, 3(53):1133-1138.
[8]	FAN Q, ZHANG J, LUO M, 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.
[9]	郭琪, 王慧, 齐晓晨, 等. 吉林省HIV-1感染者传播簇和分子网络特征研究[J]. 中国卫生工程学, 2023, 22(06):732-736.
	GUO Q, WANG H, QI X C, et al. Molecular transmission cluster and network characteristics of untreated HIV-1 infected persons in Jilin Orovince[J]. Chin J Public Health Eng, 2023, 22(06):732-736.
[10]	宋玲, 杨东智, 曹慜, 等. 2012-2020年宁夏HIV-1感染者分子传播网络特征分析[J]. 宁夏医学杂志, 2022, 44(6):504-508.
	SONG L, YANG D Z, CAO M, et al. Analysis of molecular transmission network characteristics of HIV-1 infected person in Ningxia from 2012 to 2020[J]. Ningxia Med J, 2022, 44(6):504-508.
[11]	江河, 唐凯玲, 黄精华, 等. 基于分子网络的广西壮族自治区HIV传播热点和跨地区传播特征分析[J]. 中华流行病学杂志, 2022, 43(9):1423-1429.
	JIANG H, TANG K L, HUANG J H, et al. Analysis of HIV transmission hotspots and characteristics of cross-regional transmission in Guangxi Zhuang Autonomous Region based on molecular network[J]. Chin J Epidemiol, 2022, 43(9):1423-1429.
[12]	朱可心, 庄勋, 周元, 等. 人类免疫缺陷病毒-1 CRF01 AE 毒株在我国的分子流行特征分析[J]. 中华传染病杂志, 2015(7):396-402.
	ZHU K X, ZHUANG X, ZHOU Y, et al. Molecular epidemiological characterization of human immunodeficiency virus-1 CRF01 AE strains in China[J]. Chin J Infect Dis, 2015(7):396-402.
[13]	林怡, 薛以乐, 王绪琴, 等. 上海市男男性行为者中感染HIV-1的CRF01_AE毒株传播簇分析[J]. 中国艾滋病性病, 2016, 22(3):165-169.
	LIN Y, XUE Y L, WANG X Q, et al. HIV-1 transmission clusters among men who have sex with men in Shanghai[J]. Chin J AIDS STD, 2016, 22(3):165-169.
[14]	王栋, 冯毅, 郝静静, 等. 基于HIV-1的pol基因区序列分析我国CRF07_BC毒株的跨地区传播特征[J]. 中国艾滋病性病, 2024, 30(3):232-239.
	WANG D, FENG Y, HAO J J, et al. Characterization of cross-regional transmission on the predominantly endemic CRF07_BC strain in China through the sequence of the pol gene region of HIV-1[J]. Chin J AIDS STD, 2024, 30(3):232-239.
[15]	GAN M, ZHENG S, HAO J, et al. Spatiotemporal patterns of CRF07_BC in China: A population-based study of the HIV strain with the highest infection rates[J]. Front Immunol, 2022, 13:824178.
[16]	刘欢, 金怡晨, 汤后林. HIV感染者的高危行为接触者追踪研究进展[J]. 中华流行病学杂志, 2024, 45(5):755-760.
	LIU H, JIN Y C, TAN H L. Progress in research of tra-cing contacts exposed to high risk behaviors of HIV-infected patients[J]. Chin J Epidemiol, 2024, 45(5):755-760.
[17]	赖静兰, 陈雅红, 叶寒辉, 等. 艾滋病合并马尔尼菲篮状菌病患者贫血特征分析[J]. 中国临床研究, 2023, 36(11):1691-1694.
	LAI JL, CHEN YH, YE H H, et al. Analysis of anemia characteristics of AIDS patients with Marneffei's basket shaped mycosis[J]. Chin Clin Res, 2023, 36(11):1691-1694.
[18]	宋明明, 张晓, 刘冬莹, 等. HIV/AIDS患者更换二线抗病毒治疗药物效果评价[J]. 中国临床研究, 2023, 36(10):1509-1512.
	SONG M M, ZHANG X, LIU D Y, et al. Evaluation of the effectiveness of switching second-line antiviral drugs in HIV/AIDS patients[J]. Chin Clin Res, 2023, 36(10):1509-1512.

Variables	Sample size	2015	2016	2017	2018	Clustered		Non-clustered		χ²	P value
Variables	Sample size	2015	2016	2017	2018	Count	Proportion	Count	Proportion	χ²	P value
Age at diagnosis										1.348	0.72
≤24	234	103	56	37	38	101	43.16%	133	56.84%
25-39	647	299	159	94	95	283	43.74%	364	56.26%
40-54	230	103	67	38	22	96	41.74%	134	58.26%
≥55	130	55	39	26	10	50	38.46%	80	61.54%
Sex										8.82	0.003
Male	1168	526	295	182	165	511	43.75%	657	56.25%
Female	73	34	26	13	0	19	26.03%	54	73.97%
Registered residence										0.6138	0.43
Shanghai	432	201	121	69	41	191	44.21%	241	55.79%
Other provinces	809	359	200	126	124	339	41.90%	470	58.10%
Ethnicity										7.466	0.006
Han	1200	533	315	192	160	521	43.42%	679	56.58%
Others	41	27	6	3	5	9	21.95%	32	78.05%
Marital status										2.586	0.46
Unmarried	835	369	209	125	132	362	43.35%	473	56.65%
Married	266	132	67	44	23	110	41.35%	156	58.65%
Divorced or widowed	137	59	45	24	9	58	42.34%	79	57.66%
Unknown	3	0	0	2	1	0	0.00%	3	100.00%
Education level										4.773	0.44
Illiterate	11	6	2	3	0	3	27.27%	8	72.73%
Primary school	79	50	18	7	4	27	34.18%	52	65.82%
Junior high school	253	125	78	38	12	110	43.48%	143	56.52%
High School	299	140	73	47	39	126	42.14%	173	57.86%
College and above	600	239	150	100	110	264	44.07%	335	55.93%
Transmission route										19.55	<0.001
Transmission route	884	372	231	135	146	407	46.04%	477	53.96%
Transmission route	309	158	85	52	14	114	36.89%	195	63.11%
Heterosexual	43	30	5	4	4	8	18.60%	35	81.40%
Injection drug use	5	0	0	4	1	1	20.00%	4	80.00%
Subtype										74.57	<0.001
CRF01_AE	632	303	155	92	82	218	34.65%	413	65.35%
CRF 07_BC	422	182	101	71	68	251	59.48%	171	40.52%
CRF 08_BC	28	13	8	5	2	7	25.00%	21	75.00%
Others	159	62	57	27	13	53	33.33%	106	66.67%