Molecular Epidemiology of HIV-1 in the California-Mexico Border Region

加利福尼亚-墨西哥边境地区 HIV-1 的分子流行病学

• 批准号: 8628031
• 负责人: Sanjay R Mehta
• 金额: $ 12.89万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-02-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8628031
• 关键词: AIDS prevention; Address; Alcohol or Other Drugs use; Behavioral; Bioinformatics; Blood specimen; Border Crossings; California; Chronic; Client; Clinical; Clinical Data; Cluster Analysis; County; Cross Infection; Data; Databases; Development; Drug resistance; Economics; Enrollment; Enzymes; Epidemic; Female; Genetic; Genetic Variation; Geographic Information Systems; HIV; HIV Infections; HIV Seropositivity; HIV diagnosis; HIV risk; HIV vaccine; HIV-1; Hot Spot; Immune system; Individual; Infection; Intervention; Knowledge; Location; Mental Depression; Methods; Mexico; Molecular; Molecular Epidemiology; Movement; Participant; Pathway interactions; Pattern; Phylogenetic Analysis; Population; Prevention strategy; Privacy; Public Health; RNA-Directed DNA Polymerase; Reporting; Research; Research Personnel; Research Project Grants; Risk Factors; Sampling; Sexual Transmission; Side; Signal Transduction; Social Network; Source; Structure; Techniques; Time; Virus; Work; abstracting; antiretroviral therapy; base; cohort; demographics; design; epidemiologic data; improved; injection drug use; men who have sex with men; reconstruction; residence; sex; socioeconomics; theories; time interval; tool; transmission process; virus genetics

DESCRIPTION (provided by applicant): Introduction: The poor fidelity of the HIV reverse transcriptase enzyme leads to a significant sequence diversity across infected individuals. Although this complicates antiretroviral therapy, this diversity allows researchers to characterize relationships between sampled viruses using phylogenetic tools. Once the phylogenetic relationships of HIV sampled from infected individuals are characterized, socio-demographic data from the sampled individuals may be overlaid onto these phylogenetic relationships leading to inferred reconstruction of social networks that may create a better understanding of socio-demographic patterns and drivers of the sampled epidemic. Previous work has characterized some of the risk factors for HIV infection in both San Diego, CA and Tijuana, Mexico. We propose to utilize objective sequence data along with clinical and socio-demographic data to improve the understanding of the relationship of the HIV-1 sub-epidemics along the San Diego-Tijuana border. Methods: In this proposal, sequence, clinical, and socio-demographic data gathered from HIV positive individuals enrolled in seven different collaborating cohorts along the San Diego- Tijuana border will be combined for analysis. HIV pol sequence data will be collected from the collaborating cohorts or generated from blood samples provided by them. Socio-demographic and clinical data will be abstracted from the databases of the cohorts in a de-identified manner, except for location of residence. Maximum likelihood based methods will then be used to determine the phylogenetic structure (i.e. clustering) of the sampled sequences, and then associations between the clustering and socio-demographic variables will be assessed including: location of residence, HIV risk factors, drug resistance, duration of infection, cross- border movement, and others. We will next determine the spatial and temporal dynamics of the HIV epidemics across the border region using geographic information systems, and coalescent theory based Bayesian phylogeographic analyses. These analyses can incorporate temporal and geographic data into the prior estimations of phylogenetic structure so that the final results may identify temporal and spatial transmission 'hot spots'. In order to address privacy issues, all geographic data will be smoothed at the time of presentation so that identification of individuals will not be possible. We will also work closely with our bioinformatics colleagues to understand the limitations of our convenience data, and develop statistical techniques to make our findings generalizable. Conclusions: We anticipate that our findings will improve understanding of HIV transmission dynamics in this region so that prevention strategies can be designed and targeted more effectively. This research project has two major aims: 1) to identify risk factors related to HIV transmission, and 2) identify temporal and spatial 'hot spots of transmission in the San Diego-Tijuana border region. These results will assist public health agencies in Mexico and the US to more efficiently develop appropriate and targeted intervention strategies to curb ongoing HIV transmission.

描述（由申请人提供）：简介：HIV逆转录酶的不良保真度导致受感染个体的显着序列多样性。尽管这使抗逆转录病毒疗法复杂化，但这种多样性使研究人员可以使用系统发育工具来表征采样病毒之间的关系。一旦表征了从受感染者采样的艾滋病毒的系统发育关系，就可以将来自采样个体的社会人口统计数据覆盖在这些系统发育关系上，从而推断社交网络的重建，从而可以更好地理解对采样流行病的社会人口统计学模式和驱动因素。先前的工作是在加利福尼亚州圣地亚哥和墨西哥蒂华纳州的艾滋病毒感染的一些危险因素。我们建议利用客观序列数据以及临床和社会人口统计学数据，以提高对HIV-1沿圣地亚哥tijuana边界之间关系的理解。方法：在此提案，序列，临床和社会人口统计学数据中，从艾滋病毒阳性个体中收集的人群将组合在圣地亚哥 - 蒂华纳边境沿线七个不同的协作人群中进行分析。 HIV POL序列数据将从协作人群中收集或从他们提供的血液样本中产生。除居住地点外，还将从同类的数据库中抽象出社会人口统计学和临床​​数据。然后，将使用最大似然的方法来确定采样序列的系统发育结构（即聚类），然后将评估聚类与社会人口统计学变量之间的关联，包括：居住地点，HIV风险因素，药物抵抗力，感染持续性，感染，交叉边界运动等。接下来，我们将使用地理信息系统和基于共同理论的贝叶斯植物学分析来确定整个边界区域的HIV流行病的空间和时间动力学。这些分析可以将时间和地理数据纳入系统发育结构的先前估计中，以便最终结果可以识别时间和空间传递“热点”。为了解决隐私问题，所有地理数据将在演示时进行平滑，以便无法识别个人。我们还将与生物信息学同事紧密合作，以了解我们的便利数据的局限性，并开发统计技术以使我们的发现可推广。结论：我们预计我们的发现将提高对该地区HIV传播动态的理解，以便可以更有效地设计和针对预防策略。 该研究项目具有两个主要目的：1）确定与HIV传播有关的危险因素，以及2）确定圣地亚哥蒂华纳边境地区传播的时间和空间热点。这些结果将有助于墨西哥和美国的公共卫生机构更有效地制定适当和有针对性的干预策略，以遏制正在进行的HIV传播。