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一种新的样本选择方法,辅助识别与 HIV-1 感染控制相关的因素。

A Novel Sample Selection Approach to Aid the Identification of Factors That Correlate With the Control of HIV-1 Infection.

机构信息

IAVI Human Immunology Laboratory, Imperial College London, London, United Kingdom.

Kenya Medical Research Institute-Wellcome Trust Research Programme, Kilifi, Kenya.

出版信息

Front Immunol. 2021 Mar 11;12:634832. doi: 10.3389/fimmu.2021.634832. eCollection 2021.

Abstract

Individuals infected with HIV display varying rates of viral control and disease progression, with a small percentage of individuals being able to spontaneously control infection in the absence of treatment. In attempting to define the correlates associated with natural protection against HIV, extreme heterogeneity in the datasets generated from systems methodologies can be further complicated by the inherent variability encountered at the population, individual, cellular and molecular levels. Furthermore, such studies have been limited by the paucity of well-characterised samples and linked epidemiological data, including duration of infection and clinical outcomes. To address this, we selected 10 volunteers who rapidly and persistently controlled HIV, and 10 volunteers each, from two control groups who failed to control (based on set point viral loads) from an acute and early HIV prospective cohort from East and Southern Africa. A propensity score matching approach was applied to control for the influence of five factors (age, risk group, virus subtype, gender, and country) known to influence disease progression on causal observations. Fifty-two plasma proteins were assessed at two timepoints in the 1st year of infection. We independently confirmed factors known to influence disease progression such as the B57 HLA Class I allele, and infecting virus Subtype. We demonstrated associations between circulating levels of MIP-1α and IL-17C, and the ability to control infection. IL-17C has not been described previously within the context of HIV control, making it an interesting target for future studies to understand HIV infection and transmission. An in-depth systems analysis is now underway to fully characterise host, viral and immunological factors contributing to control.

摘要

个体感染 HIV 后,病毒控制和疾病进展的速度存在差异,只有一小部分个体在未经治疗的情况下能够自发地控制感染。在试图确定与 HIV 自然保护相关的相关性时,系统方法生成的数据集存在极大的异质性,这可能会因人群、个体、细胞和分子水平上固有的可变性而变得更加复杂。此外,这些研究受到缺乏特征良好的样本和相关流行病学数据的限制,包括感染持续时间和临床结果。为了解决这个问题,我们选择了 10 名快速且持续控制 HIV 的志愿者,以及 10 名来自东非和南非急性和早期 HIV 前瞻性队列中未能控制(基于设定点病毒载量)的两个对照组的志愿者。我们应用倾向评分匹配方法来控制五个已知会影响疾病进展的因素(年龄、风险群体、病毒亚型、性别和国家)对因果观察的影响。在感染的第一年,我们在两个时间点评估了 52 种血浆蛋白。我们独立证实了已知会影响疾病进展的因素,如 B57 HLA I 类等位基因和感染病毒亚型。我们发现循环 MIP-1α 和 IL-17C 水平与控制感染的能力之间存在关联。IL-17C 以前没有在 HIV 控制的背景下描述过,这使其成为未来研究理解 HIV 感染和传播的一个有趣目标。目前正在进行深入的系统分析,以充分描述宿主、病毒和免疫因素对控制的贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/05ba/7991997/e1e915fffec3/fimmu-12-634832-g0001.jpg

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