基于短反转录酶序列与全长序列的 HIV 耐药性解读的比较分析。

BACKGROUND

As second-line antiretroviral treatment (ART) becomes more accessible in resource-limited settings (RLS), the need for more affordable monitoring tools such as point-of-care viral load assays and simplified genotypic HIV drug resistance (HIVDR) tests increases substantially. The prohibitive expenses of genotypic HIVDR assays could partly be addressed by focusing on a smaller region of the HIV reverse transcriptase gene (RT) that encompasses the majority of HIVDR mutations for people on ART in RLS. In this study, an in silico analysis of 125,329 RT sequences was performed to investigate the effect of submitting short RT sequences (codon 41 to 238) to the commonly used virco®TYPE and Stanford genotype interpretation tools.

RESULTS

Pair-wise comparisons between full-length and short RT sequences were performed. Additionally, a non-inferiority approach with a concordance limit of 95% and two-sided 95% confidence intervals was used to demonstrate concordance between HIVDR calls based on full-length and short RT sequences.The results of this analysis showed that HIVDR interpretations based on full-length versus short RT sequences, using the Stanford algorithms, had concordance significantly above 95%. When using the virco®TYPE algorithm, similar concordance was demonstrated (>95%), but some differences were observed for d4T, AZT and TDF, where predictions were affected in more than 5% of the sequences. Most differences in interpretation, however, were due to shifts from fully susceptible to reduced susceptibility (d4T) or from reduced response to minimal response (AZT, TDF) or vice versa, as compared to the predicted full RT sequence. The virco®TYPE prediction uses many more mutations outside the RT 41-238 amino acid domain, which significantly contribute to the HIVDR prediction for these 3 antiretroviral agents.

CONCLUSIONS

This study illustrates the acceptability of using a shortened RT sequences (codon 41-238) to obtain reliable genotype interpretations by virco®TYPE and Stanford algorithms. Implementation of this simplified protocol could significantly reduce the cost of both resistance testing and ARV treatment monitoring in RLS.

背景

随着二线抗逆转录病毒治疗（ART）在资源有限的环境（RLS）中变得更加普及，对更经济实惠的监测工具（如即时病毒载量检测和简化的基因型 HIV 耐药性（HIVDR）检测）的需求大幅增加。由于基因型 HIVDR 检测费用昂贵，因此可以通过关注 RT 基因（HIV 逆转录酶）较小的区域来部分解决这个问题，该区域涵盖了 RLS 中接受 ART 治疗的人群中大多数 HIVDR 突变。在这项研究中，对 125329 个 RT 序列进行了计算机分析，以研究提交短 RT 序列（密码子 41 至 238）到常用的 virco®TYPE 和斯坦福基因型解释工具的效果。

结果

进行了全长和短 RT 序列之间的两两比较。此外，还使用了非劣效性方法，置信区间为 95%，置信区间为双侧 95%，以证明基于全长和短 RT 序列的 HIVDR 检测结果之间的一致性。该分析结果表明，基于斯坦福算法，全长与短 RT 序列的 HIVDR 解释具有显著高于 95%的一致性。当使用 virco®TYPE 算法时，也表现出类似的一致性（>95%），但在 d4T、AZT 和 TDF 中观察到一些差异，在超过 5%的序列中影响了预测。然而，大多数解释上的差异是由于从完全敏感变为敏感性降低（d4T）或从反应降低变为最小反应（AZT、TDF），与预测的全长 RT 序列相比。virco®TYPE 预测使用了 RT 41-238 个氨基酸域之外的更多突变，这些突变对这 3 种抗逆转录病毒药物的 HIVDR 预测有显著贡献。