Snoeck Joke, Kantor Rami, Shafer Robert W, Van Laethem Kristel, Deforche Koen, Carvalho Ana Patricia, Wynhoven Brian, Soares Marcelo A, Cane Patricia, Clarke John, Pillay Candice, Sirivichayakul Sunee, Ariyoshi Koya, Holguin Africa, Rudich Hagit, Rodrigues Rosangela, Bouzas Maria Belen, Brun-Vézinet Françoise, Reid Caroline, Cahn Pedro, Brigido Luis Fernando, Grossman Zehava, Soriano Vincent, Sugiura Wataru, Phanuphak Praphan, Morris Lynn, Weber Jonathan, Pillay Deenan, Tanuri Amilcar, Harrigan Richard P, Camacho Ricardo, Schapiro Jonathan M, Katzenstein David, Vandamme Anne-Mieke
Rega Institute for Medical Research, Minderbroedersstraat 10, 3000 Leuven, Belgium.
Antimicrob Agents Chemother. 2006 Feb;50(2):694-701. doi: 10.1128/AAC.50.2.694-701.2006.
The major limitation of drug resistance genotyping for human immunodeficiency virus remains the interpretation of the results. We evaluated the concordance in predicting therapy response between four different interpretation algorithms (Rega 6.3, HIVDB-08/04, ANRS [07/04], and VGI 8.0). Sequences were gathered through a worldwide effort to establish a database of non-B subtype sequences, and demographic and clinical information about the patients was gathered. The most concordant results were found for nonnucleoside reverse transcriptase (RT) inhibitors (93%), followed by protease inhibitors (84%) and nucleoside RT inhibitor (NRTIs) (76%). For therapy-naive patients, for nelfinavir, especially for subtypes C and G, the discordances were driven mainly by the protease (PRO) mutational pattern 82I/V + 63P + 36I/V for subtype C and 82I + 63P + 36I + 20I for subtype G. Subtype F displayed more discordances for ritonavir in untreated patients due to the combined presence of PRO 20R and 10I/V. In therapy-experienced patients, subtype G displayed a lot of discordances for saquinavir and indinavir due to mutational patterns involving PRO 90 M and 82I. Subtype F had more discordance for nelfinavir attributable to the presence of PRO 88S and 82A + 54V. For the NRTIs lamivudine and emtricitabine, CRF01_AE had more discordances than subtype B due to the presence of RT mutational patterns 65R + 115 M and 118I + 215Y, respectively. Overall, the different algorithms agreed well on the level of resistance scored, but some of the discordances could be attributed to specific (subtype-dependent) combinations of mutations. It is not yet known whether therapy response is subtype dependent, but the advice given to clinicians based on a genotypic interpretation algorithm differs according to the subtype.
人类免疫缺陷病毒耐药基因分型的主要局限性仍然在于结果的解读。我们评估了四种不同解读算法（Rega 6.3、HIVDB-08/04、ANRS [07/04] 和 VGI 8.0）在预测治疗反应方面的一致性。通过全球范围内建立非B亚型序列数据库的努力收集了序列，并收集了患者的人口统计学和临床信息。非核苷类逆转录酶（RT）抑制剂的结果一致性最高（93%），其次是蛋白酶抑制剂（84%）和核苷类RT抑制剂（NRTIs）（76%）。对于初治患者，对于奈非那韦，特别是对于C型和G型亚型，不一致主要是由C型亚型的蛋白酶（PRO）突变模式82I/V + 63P + 36I/V和G型亚型的82I + 63P + 36I + 20I驱动的。由于PRO 20R和10I/V同时存在，F型亚型在未治疗患者中对利托那韦的不一致性更多。在经治患者中，由于涉及PRO 90 M和82I的突变模式，G型亚型对沙奎那韦和茚地那韦表现出很多不一致性。F型亚型对奈非那韦的不一致性更多，这归因于PRO 88S和82A + 54V的存在。对于NRTIs拉米夫定和恩曲他滨，由于分别存在RT突变模式65R + 115 M和118I + 215Y，CRF01_AE的不一致性比B型亚型更多。总体而言，不同算法在耐药评分水平上一致性良好，但一些不一致可归因于特定的（亚型依赖性）突变组合。尚不清楚治疗反应是否依赖于亚型，但根据基因型解读算法给予临床医生的建议因亚型而异。
