Stilianakis N I, Boucher C A, De Jong M D, Van Leeuwen R, Schuurman R, De Boer R J
Theoretical Division, Group T-10, Los Alamos National Laboratory, Los Alamos, New Mexico 87545, USA.
J Virol. 1997 Jan;71(1):161-8. doi: 10.1128/JVI.71.1.161-168.1997.
Treatment of human immunodeficiency virus type 1 (HIV-1) infection during the clinical latency phase with drugs inhibiting reverse transcriptase (RT) reduces the HIV-1 RNA load and increases the CD4+ T-cell count. Typically, however, the virus evolves mutations in the RT gene that circumvent the drugs. We develop a mathematical model for this situation. The model distinguishes quiescent from activated CD4+ T cells, incorporates the fact that only activated cells can become productively infected by HIV-1, embodies empirical estimates for the drug resistance and the mutation frequency for each of the HIV-1 drug-resistant mutants, and assumes the antiviral immune response to remain constant over the course of the experiments. We analyze clinical data on the evolution of drug-resistant mutants for the RT inhibitors lamivudine and zidovudine. The results show that the evolutionary sequence of the drug-resistant mutants in both data sets is accounted for by our model, given that lamivudine is more effective than zidovudine. Thus, current empirical estimates of the mutation frequencies and the drug resistances of the mutants suffice for explaining the data. We derive a critical treatment level below which the wild-type HIV-1 RNA load can rebound before the first drug-resistant mutant appears. Our zidovudine data confirm this to be the case. Thus, we demonstrate in the model and the data that the rebound of the HIV-1 RNA load in the case of zidovudine is due to the outgrowth of wild-type virus and the first drug-resistant mutant, whereas that in the case of lamivudine can only be due to the drug-resistant mutants. The evolution of drug resistance proceeds slower in the case of zidovudine because (i) zidovudine is not as effective as lamivudine and (ii) the first zidovudine drug-resistant mutant is competing with the rebounding wild-type virus.
在临床潜伏期使用抑制逆转录酶（RT）的药物治疗人类免疫缺陷病毒1型（HIV-1）感染，可降低HIV-1 RNA载量并增加CD4+ T细胞计数。然而，通常情况下，病毒会在RT基因中发生突变，从而规避这些药物。我们针对这种情况开发了一个数学模型。该模型区分了静止的和活化的CD4+ T细胞，纳入了只有活化细胞才能被HIV-1有效感染这一事实，体现了对每种HIV-1耐药突变体的耐药性和突变频率的经验估计，并假设抗病毒免疫反应在实验过程中保持不变。我们分析了拉米夫定和齐多夫定这两种RT抑制剂耐药突变体进化的临床数据。结果表明，鉴于拉米夫定比齐多夫定更有效，我们的模型能够解释两个数据集中耐药突变体的进化序列。因此，目前对突变频率和突变体耐药性的经验估计足以解释这些数据。我们推导出了一个临界治疗水平，低于该水平时，野生型HIV-1 RNA载量在第一个耐药突变体出现之前就可能反弹。我们的齐多夫定数据证实了这种情况。因此，我们在模型和数据中证明，齐多夫定情况下HIV-1 RNA载量的反弹是由于野生型病毒和第一个耐药突变体的增殖，而拉米夫定情况下则只能归因于耐药突变体。齐多夫定情况下耐药性的进化较慢，原因如下：（i）齐多夫定不如拉米夫定有效；（ii）第一个齐多夫定耐药突变体与反弹的野生型病毒相互竞争。
