MicroRNA Predictors of HIV Risk in Reproductive Age Women

对于面临艾滋病毒风险的妇女来说，目前的避孕选择有限。尽管有证据表明感染艾滋病毒的风险增加 与仅服用孕激素的避孕药(主要是DMPA)相关的获得，全球数百万女性 全世界继续使用DMPA，估计有1.4亿人使用这种或其他激素避孕药(HC)。 此外，DMPA是撒哈拉以南非洲最常见的避孕方法-该地区承受着 估计占全球艾滋病毒感染负担的70%。阴道生物失调是感染艾滋病毒的另一个风险因素， 在这个艾滋病毒高发地区的女性中也更为常见。我们从一项研究中获得的见解 旨在调查HC使用和HIV感染之间的关系的最大预期队列(HC- HIV研究)，支持以下范例：1)DMPA使用者出现异常的宫颈和系统免疫 这在HIV血清转换之前和2)阴道微生物区系改变加强了DMPA对宫颈的影响 豁免权。对HC-免疫-微生物区系潜在的分子机制缺乏了解 导致艾滋病毒易感性增加的相互作用限制了设计更安全的避孕和预防措施的努力 技术。我们提出了一种新的假设驱动的范式来测试microRNAs(MiRNAs)在风险中的作用 艾滋病病毒感染的记录。由于它们在循环中的稳定性，基因沉默功能无处不在，并不断涌现 证明小分子非编码RNA在控制HIV感染中的重要作用的证据，miRNAs是吸引人的新事物 治疗和诊断目标。没有与HC和异常相关的miRNA表达的信息 阴道微生物区系目前是可用的。为了填补这一机械论理解上的空白，我们提出如下建议 目的：(1)确定与HIV-1感染风险和先天免疫相关的循环异常miRNAs 育龄妇女；(2)确定预测艾滋病毒风险和免疫失衡的受激素调节的miRNAs 这在HIV血清转换之前；(3)确定受阴道生物失调调节的miRNAs可能有助于 与HIV风险相关的系统和粘膜免疫失衡之间的沟通。我们将利用 来自乌干达纵向HC-HIV队列的约1000份储存的血清和宫颈阴道分泌物 津巴布韦和在美国进行的四项临床试验，代表了不同种族的人口。 关于艾滋病毒风险的已知主要因素的全面人口统计、临床和实验室信息 这些队列中的数据将允许进行可靠的统计建模。我们将使用严格的最先进的技术和 转录组、蛋白质组学和功能基因组学的生物信息学工具，以生成差异表达谱 表达miRNAs和在艾滋病毒感染风险中起作用的靶基因和途径。这项研究 提供了一个独特的机会来阐明和验证内源和 通过分析共同生物基础上的miRNAs发现外源激素、细菌性阴道病和HIV-1 机械装置。

Current contraceptive options for women facing risk of HIV are limited. Despite evidence of increased risk of HIV acquisition associated with progestin-only contraceptives, predominantly DMPA, millions of women around the world continue using DMPA with an estimated >140 million using this or other hormonal contraceptives (HC). Moreover, DMPA is the most common contraceptive method in sub-Saharan Africa – the region that bears an estimated 70% of the global HIV-infection burden. Vaginal dysbiosis, another risk factor for HIV acquisition, is also more common in women in this high HIV incidence region. Insights from our research gained in one of the largest prospective cohorts designed to investigate the association between HC use and HIV acquisition (HC- HIV study), support the following paradigms: 1) DMPA users develop aberrant cervical and systemic immunity that precedes HIV seroconversion and 2) altered vaginal microbiota potentiates DMPA effects on cervical immunity. The lack of understanding of the molecular mechanisms underlying the HC-immunity-microbiota interactions leading to increased HIV susceptibility is limiting efforts to design safer contraceptive and preventive technologies. We propose a novel hypothesis-driven paradigm to test the role of micro-RNAs (miRNAs) in risk of HIV acquisition. Because of their stability in the circulation, ubiquitous gene silencing function, and emerging evidence of important roles of small non-coding RNAs in controlling HIV infection, miRNAs are attractive novel therapeutic and diagnostic targets. No information on miRNA expression in association with HC and abnormal vaginal microbiota is currently available. To fill this gap in mechanistic understanding, we propose the following aims: (1) Identify circulating aberrant miRNAs associated with risk of HIV-1 acquisition and innate immunity in reproductive age women; (2) Identify hormonally regulated miRNAs predictive of HIV risk and immune imbalance that precedes HIV seroconversion; (3) Identify miRNAs regulated by vaginal dysbiosis that may facilitate communication between systemic and mucosal immunity imbalance associated with HIV risk. We will utilize ~1000 banked sera and cervicovaginal secretions from the longitudinal HC-HIV cohorts in Uganda and Zimbabwe and four clinical trials conducted in the United States representing a racially diverse population. Comprehensive demographic, clinical and laboratory information available on known major factors for HIV risk in these cohorts will allow robust statistical modeling. We will use rigorous state-of-the-art technologies and bioinformatics tools for transcriptomic, proteomic and functional genomics to generate profiles of differentially expressed miRNAs and targeted genes and pathways with roles in the risk of HIV acquisition. This research provides a unique opportunity to elucidate and validate the complex associations between endogenous and exogenous hormones, bacterial vaginosis and HIV-1 through analysis of miRNAs underlying shared biological mechanisms.