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。

IF 1.5 4区 医学 Q4 IMMUNOLOGY
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}
引用次数: 0

摘要

异性恋者已成为云南省昆明市 HIV-1 的高发人群。我们利用其基因序列之间的遗传相似性原理,通过收集早期分子流行病学研究的数据,建立了一个分子传播网络。这使我们能够分析该群体的流行病学特征,并为预防和管理 HIV-1 流行病提供新的概念和方法。在使用 BioEdit 和 HyPhy 处理样本基因序列后,我们使用 Cytoscope 对网络进行了可视化和特征描述。使用零膨胀泊松模型和逻辑回归模型分别研究了可能链接的数量和聚类大小的影响因素。为了解释 HIV-1 分子网络的动态变化,我们开发了一个基于 scikit-learn 的预测模型。在标准遗传距离阈值为 0.01 的条件下,通过分子复杂性检测分析,从 150 个簇中发现了 6 个值得注意的模块簇,其网络得分从 4 到 9 不等。取样时间、婚姻状况和 CD4+ T 淋巴细胞对可能链接数的大小和网络聚类率有显著影响(均 p < 0.05)。根据 scikit-learn 方法,梯度提升机(GBM)模型的曲线下面积值最高,为 0.884 ± 0.051。虽然并非所有群组亚型的增长都相同,但网络群组相对特殊且聚集。目前,HIV-1CRF08_BC 在当地最大的传播风险群体是异性传播人群。研究发现,最适合构建 HIV-1 分子网络动力学预测模型的是 GBM 模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.10
自引率
6.70%
发文量
201
审稿时长
3-6 weeks
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信