Abstract
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 estimates—as well as judgments of the ability of therapeutic interventions to alter the size of the replication-competent but transcriptionally inactive latent reservoir—rely 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.
Highlights
The latent HIV-1 reservoir that persists following treatment with suppressive antiretroviral therapy (ART) exists primarily in resting CD4+ T cells and is an obstacle to eradicating HIV-1 [1,2,3,4]
We describe Markov-chain Monte Carlo (MCMC) methods that we developed to account for these inevitable background sources of variation while estimating additional variation, including batch effects and inter-lab variation, as well as assessing the impact of freezing peripheral blood mononuclear cells (PBMC) samples on assay performance
We present the results of our method-validation simulations, estimated model parameters based on the results of four Quantitative viral outgrowth assays (QVOA) applied to 75 split samples, and simulation results evaluating some implications of the models, before concluding with some additional discussion
Summary
The latent HIV-1 reservoir that persists following treatment with suppressive ART exists primarily in resting CD4+ T cells and is an obstacle to eradicating HIV-1 [1,2,3,4]. Replication-competent HIV-1 can be measured by QVOA These terminal dilution assays place known numbers of resting CD4+ T cells in culture wells, usually in serial dilutions of cells that cover several orders of magnitude, with replicate wells at each dilution. The number of infectious units per million cells (IUPM) is estimated by maximum likelihood assuming single-hit Poisson dynamics [9]. This approach has represented the “gold standard,” because it measures replication-competent virus in latently infected cells, which is crucial because the majority of integrated HIV-1 DNA is replication-defective [10,11,12]
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