Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates
Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates
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DOI：
10.1097/qad.0b013e3282ef81ea
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发表时间：
2007-09-12
期刊：
影响因子：
3.8
通讯作者：
Harrigan, P. Richard
中科院分区：
文献类型：
--
作者：
Low, Andrew J.;Dong, Winnie;Harrigan, P. Richard
目的：将CCR 5拮抗剂整合到临床实践中将受益于辅助受体使用的准确测定设计：将已发表的基于HIV V3环的辅助受体使用预测因子与抗逆转录病毒初治个体的大队列中的实际表型嗜性结果进行比较，以确定临床样本的准确性并确定需要改进的领域。对齐的HIV包膜V3环序列（n=977），来自批量测序进行了分析，通过六种方法：11/25规则，神经网络（NN），两个支持向量机，和两个亚型B的位置特异性评分矩阵（PSSM）。共受体表型结果（Trofile共受体表型测定; Monogram Biosciences）通过CXCR 4相对光单位（RLU）读数和CD 4细胞计数分层。结果：共受体表型可用于920个具有少于7个氨基酸混合物的V3基因型的临床样本（n=769 R5; n=151 X4-capable）。评价了11/25规则（30%灵敏度/93%特异性）、NN（44%/88%）、PSSM（sinsi）（34%/96%）、PSSM（x4 r5）（24%/97%）、SVMgenomiac（22%/90%）和SVMgeno 2 pheno（50%/89%）预测X4容量的灵敏度和特异性。通过优化连续输出方法（PSSM方法）的临界值和/或整合临床数据（CD4%），可以获得灵敏度的定量增加。在表型检测中，灵敏度与X4信号强度成正比（P < 0.05）。结论：目前默认的共受体预测算法不足以预测临床样本中HIV X4共受体的使用，特别是那些具有低CXCR 4 RLU信号的X4表型。可以对基因型预测因子进行显著改进，包括对临床样本进行训练，使用额外的数据来改进预测，优化截止值并提高基因型敏感性。(C)2007年利平科特威廉姆斯&威尔金斯。
Objective: Integrating CCR5 antagonists into clinical practice would benefit from accurate assays of co-receptor usage (CCR5 versus CXCR4) with fast turnaround and low cost.Design: Published HIV V3-loop based predictors of co-receptor usage were compared with actual phenotypic tropism results in a large cohort of antiretroviral naive individuals to determine accuracy on clinical samples and identify areas for improvement.Methods: Aligned HIV envelope V3 loop sequences (n=977), derived by bulk sequencing were analyzed by six methods: the 11/25 rule; a neural network (NN), two support vector machines, and two subtype-B position specific scoring matrices (PSSM). Co-receptor phenotype results (Trofile Co-receptor Phenotype Assay; Monogram Biosciences) were stratified by CXCR4 relative light unit (RLU) readout and CD4 cell count.Results: Co-receptor phenotype was available for 920 clinical samples with V3 genotypes having fewer than seven amino acid mixtures (n=769 R5; n=151 X4-capable). Sensitivity and specificity for predicting X4 capacity were evaluated for the 11/25 rule (30% sensitivity/93% specificity), NN (44%/88%), PSSM(sinsi) (34%/96%), PSSM(x4r5) (24%/97%), SVMgenomiac (22%/90%) and SVMgeno2pheno (50%/89%). Quantitative increases in sensitivity could be obtained by optimizing the cut-off for methods with continuous output (PSSM methods), and/or integrating clinical data (CD4%). Sensitivity was directly proportional to strength of X4 signal in the phenotype assay (P < 0.05).Conclusions: Current default implementations of co-receptor prediction algorithms are inadequate for predicting HIV X4 co-receptor usage in clinical samples, particularly those X4 phenotypes with low CXCR4 RLU signals. Significant improvements can be made to genotypic predictors, including training on clinical samples, using additional data to improve predictions and optimizing cutoffs and increasing genotype sensitivity. (C) 2007 Lippincott Williams & Wilkins.