ArticleJournal of virology2006
A reliable phenotype predictor for human immunodeficiency virus type 1 subtype C based on envelope V3 sequences.
Article in Journal of virology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 1 of them a synthesis that pooled it.
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Who cites it
75 citing papers in PubMed, 1 synthesis or guideline pooled it, 136 citations in OpenAlex.
- HIV-1 subtype C predicted co-receptor tropism in Africa: an individual sequence level meta-analysis.AIDS research and therapy · 2020Pooled it
- Untangling the effects of within-host and between-host natural selection in viruses with applications to evolution of HIV-1 co-receptor usage.Journal of the Royal Society, Interface · 2026Article
- Quantification and localization of integrated HIV-1 in memory and naïve CD4+ T cells from adolescents and young adults with perinatally-acquired HIV-1.PLoS pathogens · 2026Article
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- Molecular characterization of a unique Recombinant form of HIV-1 subtype F2/CRF02_AG identified in Guangdong, China.Virology journal · 2025Article
- Benchmarking Machine Learning Models for HIV-1 Protease Inhibitor Resistance Prediction: Impact of Data Set Construction and Feature Representation.Journal of chemical information and modeling · 2025Article
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- SHIV-C109p5 NHP induces rapid disease progression in elderly macaques with extensive GI viral replication.Journal of virology · 2024Article
- Immune activation correlates with and predicts CXCR4 co-receptor tropism switch in HIV-1 infection.Scientific reports · 2020Article
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- Delineation of Homeostatic Immune Signatures Defining Viremic Non-progression in HIV-1 Infection.Frontiers in immunology · 2020Article
- HIV-1 tropism prediction by the XGboost and HMM methods.Scientific reports · 2019Article
- Ultradeep single-molecule real-time sequencing of HIV envelope reveals complete compartmentalization of highly macrophage-tropic R5 proviral variants in brain and CXCR4-using variants in immune and peripheral tissues.Journal of neurovirology · 2018Article
- Next generation sequencing reveals a high frequency of CXCR4 utilizing viruses in HIV-1 chronically infected drug experienced individuals in South Africa.Journal of clinical virology : the official publication of the Pan American Society for Clinical Virology · 2018Article
- Phenotypic co-receptor tropism and Maraviroc sensitivity in HIV-1 subtype C from East Africa.Scientific reports · 2018Article
- Prediction of coreceptor usage by five bioinformatics tools in a large Ethiopian HIV-1 subtype C cohort.PloS one · 2017Article
- HIV-1 Group O Genotypes and Phenotypes: Relationship to Fitness and Susceptibility to Antiretroviral Drugs.AIDS research and human retroviruses · 2016Article
- Features of Recently Transmitted HIV-1 Clade C Viruses that Impact Antibody Recognition: Implications for Active and Passive Immunization.PLoS pathogens · 2016Article
- HIV coreceptor tropism determination and mutational pattern identification.Scientific reports · 2016Article
- Characteristics and spread to the native population of HIV-1 non-B subtypes in two European countries with high migration rate.BMC infectious diseases · 2015Article
15 more citing papers are in PubMed but not listed here.
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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
In human immunodeficiency virus type 1 (HIV-1) subtype B infections, the emergence of viruses able to use CXCR4 as a coreceptor is well documented and associated with accelerated CD4 decline and disease progression. However, in HIV-1 subtype C infections, responsible for more than 50% of global infections, CXCR4 usage is less common, even in individuals with advanced disease. A reliable phenotype prediction method based on genetic sequence analysis could provide a rapid and less expensive approach to identify possible CXCR4 variants and thus increase our understanding of subtype C coreceptor usage. For subtype B V3 loop sequences, genotypic predictors have been developed based on position-specific scoring matrices (PSSM). In this study, we apply this methodology to a training set of 279 subtype C sequences of known phenotypes (228 non-syncytium-inducing [NSI] CCR5(+) and 51 SI CXCR4(+) sequences) to derive a C-PSSM predictor. Specificity and sensitivity distributions were estimated by combining data set bootstrapping with leave-one-out cross-validation, with random sampling of single sequences from individuals on each bootstrap iteration. The C-PSSM had an estimated specificity of 94% (confidence interval [CI], 92% to 96%) and a sensitivity of 75% (CI, 68% to 82%), which is significantly more sensitive than predictions based on other methods, including a commonly used method based on the presence of positively charged residues (sensitivity, 47.8%). A specificity of 83% and a sensitivity of 83% were achieved with a validation set of 24 SI and 47 NSI unique subtype C sequences. The C-PSSM performs as well on subtype C V3 loops as existing subtype B-specific methods do on subtype B V3 loops. We present bioinformatic evidence that particular sites may influence coreceptor usage differently, depending on the subtype.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.