Mining for humoral correlates of HIV control and latent reservoir size.
Mining for humoral correlates of HIV control and latent reservoir size.
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DOI：
10.1371/journal.ppat.1008868
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发表时间：
2020-10
期刊：
影响因子：
6.7
通讯作者：
Alter G
中科院分区：
文献类型：
--
作者：
Das J;Devadhasan A;Linde C;Broge T;Sassic J;Mangano M;O'Keefe S;Suscovich T;Streeck H;Irrinki A;Pohlmeyer C;Min-Oo G;Lin S;Weiner JA;Cihlar T;Ackerman ME;Julg B;Deeks S;Lauffenburger DA;Alter G
虽然抗逆转录病毒疗法（ART）有效地彻底改变了艾滋病毒护理，但病毒从未完全消除。相反，由持续的非特异性免疫激活驱动的免疫功能障碍，增强并逐渐导致过早的免疫老化。目前监测免疫学变化的生物标志物包括通用的炎性生物标志物，其也可能随着其他感染或疾病状态而变化，排除了HIV感染相关疾病变化的抗原特异性监测。鉴于我们越来越认识到HIV感染中疾病特异性抗体的定性和定量特性的显著变化，我们使用系统方法来探索与HIV控制相关的体液特征。我们发现，HIV特异性抗体谱因HIV的自发控制、治疗状态、病毒载量和储存库大小而不同。具体而言，代表病毒载量变化的HIV特异性抗体谱在很大程度上是定量的，反映了不同的HIV特异性抗体水平和Fc受体结合。相反，用储库大小追踪的HIV特异性抗体特征表现出定量和定性变化的组合，其特征在于更明显的亚类选择谱和独特的HIV特异性Fc-聚糖。我们的分析表明，艾滋病毒特异性抗体Fc谱对无细胞和细胞相关病毒载量都提供了抗原特异性分辨率，这表明潜在的新型生物标志物可以监测储存库活性。目前的联合抗逆转录病毒疗法（ART）方案已经扭转了与艾滋病毒诊断相关的死刑判决。然而，病毒从未被完全消灭。相反，潜伏感染的细胞与整合的病毒（潜伏水库）持续存在，病毒迅速反弹后停止治疗。此外，即使对于那些接受ART的人，由持续的非特异性免疫激活驱动的免疫功能障碍也会增强并逐渐导致过早的免疫老化。目前监测这些变化的生物标志物是非特异性的-它们专注于一般的炎症变化，这些变化也可能与其他感染或疾病状态有关。在这份手稿中，我们使用了一个公正的分析系统的方法，以确定抗原特异性的生物标志物的艾滋病毒疾病状态/治疗状态，活动性病毒血症和潜在的水库。由于它们是抗原特异性的，这些是HIV疾病进展、病毒血症和储库大小的稳健的背景特异性生物标志物。我们的框架强调了使用系统方法识别体液生物标志物的优势，并可用于其他情况下，以确定传染病结果的抗原特异性相关性。
While antiretroviral therapy (ART) has effectively revolutionized HIV care, the virus is never fully eliminated. Instead, immune dysfunction, driven by persistent non-specific immune activation, ensues and progressively leads to premature immunologic aging. Current biomarkers monitoring immunologic changes encompass generic inflammatory biomarkers, that may also change with other infections or disease states, precluding the antigen-specific monitoring of HIV-infection associated changes in disease. Given our growing appreciation of the significant changes in qualitative and quantitative properties of disease-specific antibodies in HIV infection, we used a systems approach to explore humoral profiles associated with HIV control. We found that HIV-specific antibody profiles diverge by spontaneous control of HIV, treatment status, viral load and reservoir size. Specifically, HIV-specific antibody profiles representative of changes in viral load were largely quantitative, reflected by differential HIV-specific antibody levels and Fc-receptor binding. Conversely, HIV-specific antibody features that tracked with reservoir size exhibited a combination of quantitative and qualitative changes marked by more distinct subclass selection profiles and unique HIV-specific Fc-glycans. Our analyses suggest that HIV-specific antibody Fc-profiles provide antigen-specific resolution on both cell free and cell-associated viral loads, pointing to potentially novel biomarkers to monitor reservoir activity. Current combination antiretroviral therapy (ART) regimens have reversed the death sentence once associated with an HIV diagnosis. However, the virus is never fully eliminated. Rather, latently infected cells with integrated virus (latent reservoir) persist and the virus rebounds rapidly upon discontinuation of therapy. Further, even for those on ART, immune dysfunction, driven by persistent non-specific immune activation, ensues and progressively leads to premature immunologic aging. Current biomarkers monitoring these changes are non-specific–they focus on generic inflammatory changes that may also track with other infections or disease states. In this manuscript, we used an unbiased analytical systems approach to identify antigen-specific biomarkers of HIV disease state/treatment status, active viremia and the latent reservoir. By virtue of them being antigen-specific, these are robust context-specific biomarkers of HIV disease progression, viremia and reservoir size. Our framework highlights the strength of using systems approaches in identifying humoral biomarkers, and can be used in other contexts to identify antigen-specific correlates of infectious disease outcome.
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免疫途径定义了疫苗介导的对SIV的保护的多种机制。
影响因子：
82.9
作者：
Ackerman ME;Das J;Pittala S;Broge T;Linde C;Suscovich TJ;Brown EP;Bradley T;Natarajan H;Lin S;Sassic JK;O'Keefe S;Mehta N;Goodman D;Sips M;Weiner JA;Tomaras GD;Haynes BF;Lauffenburger DA;Bailey-Kellogg C;Roederer M;Alter G
通讯作者：
Alter G
影响因子：
9.9
作者：
Alter G;Dowell KG;Brown EP;Suscovich TJ;Mikhailova A;Mahan AE;Walker BD;Nimmerjahn F;Bailey-Kellogg C;Ackerman ME
通讯作者：
Ackerman ME
影响因子：
6.7
作者：
Abdel-Mohsen M;Chavez L;Tandon R;Chew GM;Deng X;Danesh A;Keating S;Lanteri M;Samuels ML;Hoh R;Sacha JB;Norris PJ;Niki T;Shikuma CM;Hirashima M;Deeks SG;Ndhlovu LC;Pillai SK
通讯作者：
Pillai SK
影响因子：
6.7
作者：
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通讯作者：
Henrich, Timothy J.
影响因子：
20.3
作者：
Deeks, SG;Kitchen, CMR;Hecht, FM
通讯作者：
Hecht, FM