The Wistar Institute, Philadelphia, PA, USA.
The Burnet Institute, Melbourne, VIC, Australia.
Nat Commun. 2021 Jun 29;12(1):3922. doi: 10.1038/s41467-021-24077-w.
Non-invasive biomarkers that predict HIV remission after antiretroviral therapy (ART) interruption are urgently needed. Such biomarkers can improve the safety of analytic treatment interruption (ATI) and provide mechanistic insights into the host pathways involved in post-ART HIV control. Here we report plasma glycomic and metabolic signatures of time-to-viral-rebound and probability-of-viral-remission using samples from two independent cohorts. These samples include a large number of post-treatment controllers, a rare population demonstrating sustained virologic suppression after ART-cessation. These signatures remain significant after adjusting for key demographic and clinical confounders. We also report mechanistic links between some of these biomarkers and HIV latency reactivation and/or myeloid inflammation in vitro. Finally, machine learning algorithms, based on selected sets of these biomarkers, predict time-to-viral-rebound with 74% capacity and probability-of-viral-remission with 97.5% capacity. In summary, we report non-invasive plasma biomarkers, with potential functional significance, that predict both the duration and probability of HIV remission after treatment interruption.
目前迫切需要能够预测抗逆转录病毒治疗 (ART) 中断后 HIV 缓解的非侵入性生物标志物。这些生物标志物可以提高分析性治疗中断 (ATI) 的安全性，并为涉及 ART 后 HIV 控制的宿主途径提供机制见解。在这里，我们使用来自两个独立队列的样本报告了血浆糖组学和代谢特征与病毒反弹时间和病毒缓解概率的关系。这些样本包括大量治疗后控制者，这是一个罕见的人群，在停止 ART 后表现出持续的病毒学抑制。在调整了关键的人口统计学和临床混杂因素后，这些特征仍然显著。我们还报告了这些生物标志物中的一些与 HIV 潜伏期再激活和/或体外髓样炎症之间的机制联系。最后，基于这些生物标志物的选定集合的机器学习算法，以 74%的能力预测病毒反弹时间，以 97.5%的能力预测病毒缓解概率。总之，我们报告了非侵入性的血浆生物标志物，这些标志物具有潜在的功能意义，可以预测治疗中断后 HIV 缓解的持续时间和概率。
