2013
DOI: 10.1097/01.aids.0000432536.85335.c8
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Abstract: The impact of host genetic variation on determining the differential outcomes after HIV infection has been studied by two approaches: targeting of candidate genes and genome-wide association studies (GWASs). The overlap in genetic variants that has been identified by these two means has essentially been restricted to variants near to the human leukocyte antigen (HLA) class I genes, although variation in the CCR5 locus, which was first shown to have an effect on HIV outcomes using the candidate gene approach, d… Show more

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Cited by 11 publications
(6 citation statements)
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“…Many other variants throughout the genome have been claimed to have an association with outcome after HIV-1 infection, but only variation within or near the HLA genes and, to a lesser extent, the CCR5 locus have been replicated in large GWAS 11,12 . Though these studies confirm the primary impact of variation in HLA genes on HIV-1 outcome, they do not address the role of variation in complex genetic regions such as those encoding T cell receptors (TCRs) and immunoglobulins, owing to variation in copy number and/or somatic recombination 13 . For example, variation in the genes encoding killer immunoglobulin-like receptor (KIR) proteins, particularly KIR3DL1 and KIR3DS1 , has been associated with HIV-1 outcomes in many genetic and functional studies 10 , but these have not been identifiable by GWAS, almost certainly because of the extreme inter- and intragenic diversification of the KIR haplotypes 14 .…”
mentioning
confidence: 90%
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“…Many other variants throughout the genome have been claimed to have an association with outcome after HIV-1 infection, but only variation within or near the HLA genes and, to a lesser extent, the CCR5 locus have been replicated in large GWAS 11,12 . Though these studies confirm the primary impact of variation in HLA genes on HIV-1 outcome, they do not address the role of variation in complex genetic regions such as those encoding T cell receptors (TCRs) and immunoglobulins, owing to variation in copy number and/or somatic recombination 13 . For example, variation in the genes encoding killer immunoglobulin-like receptor (KIR) proteins, particularly KIR3DL1 and KIR3DS1 , has been associated with HIV-1 outcomes in many genetic and functional studies 10 , but these have not been identifiable by GWAS, almost certainly because of the extreme inter- and intragenic diversification of the KIR haplotypes 14 .…”
mentioning
confidence: 90%
“…Interestingly, the first GWAS of HIV-1 control observed that there were no individual SNPs that strongly tagged HLA-B*27:05 , which is well known to reduce patient viral load. Many HLA variants are poorly tagged by individual SNPs 13 . Similarly, the CCR5Δ32 polymorphism is not captured on commercial arrays and, due to the underlying haplotype structure, cannot be accurately imputed 4 .…”
Section: Prospects For the Futurementioning
confidence: 99%
“…Whether HLA-C expression levels are directly responsible for the protective effect of −35 SNP (or 263 insertion/deletion polymorphism) or the strong linking disequilibrium between the protective variant − 35 C and other protective genes in the HLA locus exerts viral control is still unclear. This is extremely difficult to unravel; therefore, we cannot exclude the possibility that some protective HLA -alleles have an effect on the viral control independently or in conjunction with −35 SNP [ 20 , 25 ]. Certain HLA variants have been previously associated with viral control such as the protective alleles HLA-B ∗ 57 and HLA-B ∗ 27 [ 1 4 ].…”
Section: Discussionmentioning
confidence: 99%
“…Examining certain genes, we observe the balancing act between genomics and epigenomics within infectious diseases. One such example is the HLA-A gene, where specific HLA-A alleles are observed to possess individual HIV allelic effects, based on the peptide presented ( 88 ). However, more recently it has been shown HLA-A alleles possess distinct allele-specific promoter methylation and mRNA expression levels ( 89 ).…”
Section: Interplay Between Genomic Variations and Epigenomic Modulatimentioning
confidence: 99%