ArticlePloS one2008
CCL3L1-CCR5 genotype improves the assessment of AIDS Risk in HIV-1-infected individuals.
Article in PloS one, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.
- Pooled it
- Complex and multi-allelic copy number variation in human disease.Briefings in functional genomics · 2015Review
- Key role of human leukocyte antigen in modulating human immunodeficiency virus progression: An overview of the possible applications.World journal of virology · 2015Review
- Increased Levels of Macrophage Inflammatory Proteins Result in Resistance to R5-Tropic HIV-1 in a Subset of Elite Controllers.Journal of virology · 2015Article
- CCL3L1 gene copy number in individuals with and without HIV-associated neurocognitive disorder.Current biomarker findings · 2012Article
- Genetic correlates influencing immunopathogenesis of HIV infection.The Indian journal of medical research · 2011Review
- Copy number variation in chemokine superfamily: the complex scene of CCL3L-CCL4L genes in health and disease.Clinical and experimental immunology · 2010Review
- Antigen-presenting dendritic cells rescue CD4-depleted CCR2-/- mice from lethal Histoplasma capsulatum infection.Infection and immunity · 2010Article
- Variations in CCL3L gene cluster sequence and non-specific gene copy numbers.BMC research notes · 2010Article
- A whole genome association study of mother-to-child transmission of HIV in Malawi.Genome medicine · 2010Article
- Is systems biology the key to preventing the next pandemic?Future virology · 2009Article
- CCL3L1 and HIV/AIDS susceptibility.Nature medicine · 2009Article
- Article
- Role of CCL3L1-CCR5 genotypes in the epidemic spread of HIV-1 and evaluation of vaccine efficacy.PloS one · 2008Article
Corrections and comments
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Authors and funding
12 authors at 6 institutions in 1 country.
Funding
Abstract
backgroundWhether vexing clinical decision-making dilemmas can be partly addressed by recent advances in genomics is unclear. For example, when to initiate highly active antiretroviral therapy (HAART) during HIV-1 infection remains a clinical dilemma. This decision relies heavily on assessing AIDS risk based on the CD4+ T cell count and plasma viral load. However, the trajectories of these two laboratory markers are influenced, in part, by polymorphisms in CCR5, the major HIV coreceptor, and the gene copy number of CCL3L1, a potent CCR5 ligand and HIV-suppressive chemokine. Therefore, we determined whether accounting for both genetic and laboratory markers provided an improved means of assessing AIDS risk. METHODS AND
findingsIn a prospective, single-site, ethnically-mixed cohort of 1,132 HIV-positive subjects, we determined the AIDS risk conveyed by the laboratory and genetic markers separately and in combination. Subjects were assigned to a low, moderate or high genetic risk group (GRG) based on variations in CCL3L1 and CCR5. The predictive value of the CCL3L1-CCR5 GRGs, as estimated by likelihood ratios, was equivalent to that of the laboratory markers. GRG status also predicted AIDS development when the laboratory markers conveyed a contrary risk. Additionally, in two separate and large groups of HIV+ subjects from a natural history cohort, the results from additive risk-scoring systems and classification and regression tree (CART) analysis revealed that the laboratory and CCL3L1-CCR5 genetic markers together provided more prognostic information than either marker alone. Furthermore, GRGs independently predicted the time interval from seroconversion to CD4+ cell count thresholds used to guide HAART initiation.
conclusionsThe combination of the laboratory and genetic markers captures a broader spectrum of AIDS risk than either marker alone. By tracking a unique aspect of AIDS risk distinct from that captured by the laboratory parameters, CCL3L1-CCR5 genotypes may have utility in HIV clinical management. These findings illustrate how genomic information might be applied to achieve practical benefits of personalized medicine.
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