Assessing intra-lab precision and inter-lab repeatability of outgrowth assays of HIV-1 latent reservoir size
Assessing intra-lab precision and inter-lab repeatability of outgrowth assays of HIV-1 latent reservoir size
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DOI：
10.1371/journal.pcbi.1006849
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发表时间：
2019-04-01
影响因子：
4.3
通讯作者：
Lee, Sulggi
中科院分区：
文献类型：
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作者：
Rosenbloom, Daniel I. S.;Bacchetti, Peter;Lee, Sulggi
定量病毒生长测定（QVOA）使用限制稀释的CD4(+) T细胞来测量潜伏HIV-1储存库的大小，这是治愈HIV-1的主要障碍。努力减少储藏库需要能够可靠地量化其在血液和组织中的大小的分析。尽管QVOA被认为是水库测量的黄金标准，但人们对其准确性和精密度知之甚少，也不知道细胞储存条件或实验室特定实践如何影响结果。由于这种知识的缺乏，储存库大小估计的置信区间以及治疗干预改变复制能力但转录不活跃的潜在储存库大小的能力的判断依赖于稀释试验的理论统计假设。为了解决这一差距，我们对来自5名抗逆转录病毒治疗（ART）抑制参与者的75份外周血单个核细胞（PBMC）分离样本进行了QVOA可靠性的贝叶斯统计分析，在不同的实验室使用四种不同的QVOA进行了测量，估计了测定精度和冷冻细胞储存对估计库大小的影响。我们发现，典型的分析结果预计会与真实值相差1.6到1.9倍，上下浮动。系统分析差异包括最高和最低尺度的分析之间的24倍范围，可能反映了病毒输出读数和输入细胞刺激方案的差异。我们还发现，与使用新鲜细胞相比，样品的控制速率冷冻和储存并没有造成QVOA的实质性差异（95%的概率< 2倍变化），支持继续使用冷冻储存以允许样品的运输和批量分析。最后，我们模拟了一项早期临床试验，以证明对治疗前和治疗后样品的批量分析可以提高检测三倍储层减少的能力，提高15到24个百分点。静息CD4(+) T细胞的潜伏库是治疗HIV的主要障碍，如果不是主要障碍的话。定量病毒生长测定（QVOAs）用于测量art抑制hiv感染者的潜伏库。然而，使用QVOA很困难，因为构成潜伏库的细胞比例通常约为百万分之一，远低于其他传染病生物标志物。为了研究这些检测的可靠性，我们将来自5名art抑制hiv感染者的75份PBMC样本分布在4个实验室中，每个实验室都进行QVOA并遵循预先指定的样品批处理程序。使用贝叶斯统计方法，我们分析了详细的检测输出，以了解批次内、批次之间和实验室之间的结果变化。我们发现，如果批次变化可以控制（即，实验室在一个批次中分析所有样品），典型的分析结果预计将与真实值相差1.6至1.9倍。我们还发现，冷冻、储存和解冻样品以供以后分析，结果的变化不超过2倍。这些结果以及为获得这些结果而开发的统计方法，应该导致对艾滋病毒治愈战略进行更精确和有力的评估。
Quantitative viral outgrowth assays (QVOA) use limiting dilutions of CD4(+) T cells to measure the size of the latent HIV-1 reservoir, a major obstacle to curing HIV-1. Efforts to reduce the reservoir require assays that can reliably quantify its size in blood and tissues. Although QVOA is regarded as a gold standard for reservoir measurement, little is known about its accuracy and precision or about how cell storage conditions or laboratory-specific practices affect results. Owing to this lack of knowledge, confidence intervals around reservoir size estimatesas well as judgments of the ability of therapeutic interventions to alter the size of the replication-competent but transcriptionally inactive latent reservoirrely on theoretical statistical assumptions about dilution assays. To address this gap, we have carried out a Bayesian statistical analysis of QVOA reliability on 75 split samples of peripheral blood mononuclear cells (PBMC) from 5 antiretroviral therapy (ART)-suppressed participants, measured using four different QVOAs at separate labs, estimating assay precision and the effect of frozen cell storage on estimated reservoir size. We found that typical assay results are expected to differ from the true value by a factor of 1.6 to 1.9 up or down. Systematic assay differences comprised a 24-fold range between the assays with highest and lowest scales, likely reflecting differences in viral outgrowth readout and input cell stimulation protocols. We also found that controlled-rate freezing and storage of samples did not cause substantial differences in QVOA compared to use of fresh cells (95% probability of < 2-fold change), supporting continued use of frozen storage to allow transport and batched analysis of samples. Finally, we simulated an early-phase clinical trial to demonstrate that batched analysis of pre- and post-therapy samples may increase power to detect a three-fold reservoir reduction by 15 to 24 percentage points.Author summary The latent reservoir of resting CD4(+) T cells is a major, if not the primary, obstacle to curing HIV. Quantitative viral outgrowth assays (QVOAs) are used to measure the latent reservoir in ART-suppressed HIV-infected people. Using QVOA is difficult, however, as the fraction of cells constituting the latent reservoir is typically about one in one million, far lower than other infectious disease biomarkers. To study reliability of these assays, we distributed 75 PBMC samples from five ART-suppressed HIV-infected participants among four labs, each conducting QVOA and following prespecified sample batching procedures. Using a Bayesian statistical method, we analyzed detailed assay output to understand how results varied within batches, between batches, and between labs. We found that, if batch variation can be controlled (i.e., a lab assays all samples in one batch), typical assay results are expected to differ from the true value by a factor of 1.6 to 1.9 up or down. We also found that freezing, storing, and thawing samples for later analysis caused no more than a 2-fold change in results. These outcomes, and the statistical methods developed to obtain them, should lead towards more precise and powerful assessments of HIV cure strategies.