Bayesian network analysis of resistance pathways against HIV-1 protease inhibitors
Bayesian network analysis of resistance pathways against HIV-1 protease inhibitors
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DOI：
10.1016/j.meegid.2006.09.004
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发表时间：
2007-06-01
影响因子：
3.2
通讯作者：
Vandamme, A.-M.
中科院分区：
文献类型：
--
作者：
Deforche, K.;Camacho, R.;Vandamme, A.-M.
人类免疫缺陷病毒1（HIV-1）基因型耐药性的解释仍然是感染患者抗病毒治疗随访的主要挑战。由于HIV-1的高度自然变异、复杂的相互作用和进化的随机行为，在许多情况下，耐药性突变的作用还没有得到很好的理解。使用贝叶斯网络学习不同亚型（A、B、C、F和G）的HIV-1序列数据，我们可以确定许多耐药突变对蛋白酶抑制剂（PI）奈非那韦（NFV）、茚地那韦（IDV）和沙奎那韦（SQV）的特定作用。这种网络以图形方式可视化治疗、耐药突变选择和多态性存在之间的关系。分析确定奈非那韦的30 N、88 S和90 M，沙奎那韦的90 M，茚地那韦的82 A/T和46 I/L为最可能的主要耐药突变。此外，我们发现许多突变对所有这些药物的作用有惊人的相似性。例如，对于所有三种抑制剂，我们发现新突变891是次要的，并且与位置90和71处的突变相关。贝叶斯网络学习提供了一种自主的方法来深入了解耐药突变的作用和HIV-1自然变异的影响。我们成功地将该方法应用于三种蛋白酶抑制剂。分析显示与当前知识的差异，特别是关于几个非B亚型的耐药性发展。(C)由Elsevier B. V.出版。
Interpretation of Human Immunodeficiency Virus 1 (HIV-1) genotypic drug resistance is still a major challenge in the follow-up of antiviral therapy in infected patients. Because of the high degree of HIV-1 natural variation, complex interactions and stochastic behaviour of evolution, the role of resistance mutations is in many cases not well understood. Using Bayesian network learning of HIV-1 sequence data from diverse subtypes (A, B, C, F and G), we could determine the specific role of many resistance mutations against the protease inhibitors (PIs) nelfinavir (NFV), indinavir (IDV), and saquinavir (SQV). Such networks visualize relationships between treatment, selection of resistance mutations and presence of polymorphisms in a graphical way. The analysis identified 30N, 88S, and 90M for nelfinavir, 90M for saquinavir, and 82A/T and 46I/L for indinavir as most probable major resistance mutations. Moreover we found striking similarities for the role of many mutations against all of these drugs. For example, for all three inhibitors, we found that the novel mutation 891 was minor and associated with mutations at positions 90 and 71. Bayesian network learning provides an autonomous method to gain insight in the role of resistance mutations and the influence of HIV-1 natural variation. We successfully applied the method to three protease inhibitors. The analysis shows differences with current knowledge especially concerning resistance development in several non-B subtypes. (C) 2007 Published by Elsevier B.V..