Peng Cheng, Bao-Cui He, Zhi-Xing Wu, Jia-Fa Liu, Jia-Li Wang, Cui-Xian Yang, Sha Ma, Mi Zhang, Xing-Qi Dong, Jian-Jian Li
{"title":"基于分子传播网络解读云南昆明异性传播人群的 HIV-1 流行特征:一项回顾性队列研究。","authors":"Peng Cheng, Bao-Cui He, Zhi-Xing Wu, Jia-Fa Liu, Jia-Li Wang, Cui-Xian Yang, Sha Ma, Mi Zhang, Xing-Qi Dong, Jian-Jian Li","doi":"10.1089/aid.2023.0137","DOIUrl":null,"url":null,"abstract":"<p><p>Heterosexuals have become the most prevalent group of HIV-1 in Kunming, Yunnan Province. Utilizing the principle of genetic similarity between their gene sequences, we built a molecular transmission network by gathering data from earlier molecular epidemiological studies. This allowed us to analyze the epidemiological features of this group and offer fresh concepts and approaches for the prevention and management of HIV-1 epidemics. Cytoscope was used to visualize and characterize the network following the processing of the sample gene sequences by BioEdit and HyPhy. The number of possible links and the size of the clusters were investigated as influencing factors using a zero-inflated Poisson model and a logistic regression model, respectively. A scikit-learn-based prediction model was developed to account for the dynamic changes in the HIV-1 molecular network. Six noteworthy modular clusters with network scores ranging from 4 to 9 were found from 150 clusters using Molecular Complex Detection analysis at a standard genetic distance threshold of 0.01. The size of the number of possible links and the network's clustering rate were significantly impacted by sampling time, marital status, and CD4<sup>+</sup> T lymphocytes (all <i>p</i> < 0.05). The gradient boosting machine (GBM) model had the highest area under the curve value, 0.884 ± 0.051, according to scikit-learn. Though not all cluster subtypes grew equally, the network clusters were relatively specific and aggregated. The largest local transmission-risk group for HIV-1CRF08_BC is now the heterosexual transmission population. The most suitable model for constructing the HIV-1 molecular network dynamics prediction model was found to be the GBM model.</p>","PeriodicalId":7544,"journal":{"name":"AIDS research and human retroviruses","volume":" ","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Interpreting the Epidemiological Characteristics of HIV-1 in Heterosexually Transmitted Population Based on Molecular Transmission Network in Kunming, Yunnan: A Retrospective Cohort Study.\",\"authors\":\"Peng Cheng, Bao-Cui He, Zhi-Xing Wu, Jia-Fa Liu, Jia-Li Wang, Cui-Xian Yang, Sha Ma, Mi Zhang, Xing-Qi Dong, Jian-Jian Li\",\"doi\":\"10.1089/aid.2023.0137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Heterosexuals have become the most prevalent group of HIV-1 in Kunming, Yunnan Province. Utilizing the principle of genetic similarity between their gene sequences, we built a molecular transmission network by gathering data from earlier molecular epidemiological studies. This allowed us to analyze the epidemiological features of this group and offer fresh concepts and approaches for the prevention and management of HIV-1 epidemics. Cytoscope was used to visualize and characterize the network following the processing of the sample gene sequences by BioEdit and HyPhy. The number of possible links and the size of the clusters were investigated as influencing factors using a zero-inflated Poisson model and a logistic regression model, respectively. A scikit-learn-based prediction model was developed to account for the dynamic changes in the HIV-1 molecular network. Six noteworthy modular clusters with network scores ranging from 4 to 9 were found from 150 clusters using Molecular Complex Detection analysis at a standard genetic distance threshold of 0.01. The size of the number of possible links and the network's clustering rate were significantly impacted by sampling time, marital status, and CD4<sup>+</sup> T lymphocytes (all <i>p</i> < 0.05). The gradient boosting machine (GBM) model had the highest area under the curve value, 0.884 ± 0.051, according to scikit-learn. Though not all cluster subtypes grew equally, the network clusters were relatively specific and aggregated. The largest local transmission-risk group for HIV-1CRF08_BC is now the heterosexual transmission population. The most suitable model for constructing the HIV-1 molecular network dynamics prediction model was found to be the GBM model.</p>\",\"PeriodicalId\":7544,\"journal\":{\"name\":\"AIDS research and human retroviruses\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIDS research and human retroviruses\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1089/aid.2023.0137\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"IMMUNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIDS research and human retroviruses","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/aid.2023.0137","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"IMMUNOLOGY","Score":null,"Total":0}
Interpreting the Epidemiological Characteristics of HIV-1 in Heterosexually Transmitted Population Based on Molecular Transmission Network in Kunming, Yunnan: A Retrospective Cohort Study.
Heterosexuals have become the most prevalent group of HIV-1 in Kunming, Yunnan Province. Utilizing the principle of genetic similarity between their gene sequences, we built a molecular transmission network by gathering data from earlier molecular epidemiological studies. This allowed us to analyze the epidemiological features of this group and offer fresh concepts and approaches for the prevention and management of HIV-1 epidemics. Cytoscope was used to visualize and characterize the network following the processing of the sample gene sequences by BioEdit and HyPhy. The number of possible links and the size of the clusters were investigated as influencing factors using a zero-inflated Poisson model and a logistic regression model, respectively. A scikit-learn-based prediction model was developed to account for the dynamic changes in the HIV-1 molecular network. Six noteworthy modular clusters with network scores ranging from 4 to 9 were found from 150 clusters using Molecular Complex Detection analysis at a standard genetic distance threshold of 0.01. The size of the number of possible links and the network's clustering rate were significantly impacted by sampling time, marital status, and CD4+ T lymphocytes (all p < 0.05). The gradient boosting machine (GBM) model had the highest area under the curve value, 0.884 ± 0.051, according to scikit-learn. Though not all cluster subtypes grew equally, the network clusters were relatively specific and aggregated. The largest local transmission-risk group for HIV-1CRF08_BC is now the heterosexual transmission population. The most suitable model for constructing the HIV-1 molecular network dynamics prediction model was found to be the GBM model.
期刊介绍:
AIDS Research and Human Retroviruses was the very first AIDS publication in the field over 30 years ago, and today it is still the critical resource advancing research in retroviruses, including AIDS. The Journal provides the broadest coverage from molecular biology to clinical studies and outcomes research, focusing on developments in prevention science, novel therapeutics, and immune-restorative approaches. Cutting-edge papers on the latest progress and research advances through clinical trials and examination of targeted antiretroviral agents lead to improvements in translational medicine for optimal treatment outcomes.
AIDS Research and Human Retroviruses coverage includes:
HIV cure research
HIV prevention science
- Vaccine research
- Systemic and Topical PreP
Molecular and cell biology of HIV and SIV
Developments in HIV pathogenesis and comorbidities
Molecular biology, immunology, and epidemiology of HTLV
Pharmacology of HIV therapy
Social and behavioral science
Rapid publication of emerging sequence information.