2015
DOI: 10.1371/journal.pone.0136989
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Identification of Genes Whose Expression Profile Is Associated with Non-Progression towards AIDS Using eQTLs

Abstract: BackgroundMany genome-wide association studies have been performed on progression towards the acquired immune deficiency syndrome (AIDS) and they mainly identified associations within the HLA loci. In this study, we demonstrate that the integration of biological information, namely gene expression data, can enhance the sensitivity of genetic studies to unravel new genetic associations relevant to AIDS.MethodsWe collated the biological information compiled from three databases of expression quantitative trait l… Show more

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Cited by 10 publications
(4 citation statements)
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“…Lastly, TCP1 chaperon complex member 8 (CCT8) was found to be an important marker for disease progression towards AIDS, showing low expression during slow/nonprogression, and increasing correspondingly in AIDS [77]. Moreover, TCP1 is able to interact with the HIV accessory protein Vif.…”
Section: Discussionmentioning
confidence: 99%
“…Lastly, TCP1 chaperon complex member 8 (CCT8) was found to be an important marker for disease progression towards AIDS, showing low expression during slow/nonprogression, and increasing correspondingly in AIDS [77]. Moreover, TCP1 is able to interact with the HIV accessory protein Vif.…”
Section: Discussionmentioning
confidence: 99%
“…As yet no studies have reported an association between rs200730619 and disease risk. It has been suggested that mitochondrial ribosomal proteins (MRPs) could be central to the effectiveness of HIV infection [ 51 ], and expression of MRPs was increased in dengue shock syndrome patients [ 52 ]. Moreover, several MRPs were involved in inflammatory and oxidative responses induced by Candida albicans [ 53 ].…”
Section: Discussionmentioning
confidence: 99%
“…In light of the available biological information provided by the other large-scale studies such as transcriptomic or functional genomic studies presented in this review, it appears important to reanalyze the genomic data by integrating biological information in order to enhance the genetic association results. For instance, our group has successfully implemented such approaches by pre-selecting relevant SNPs defined either by their low frequency (Le Clerc et al, 2011) or by their functional impact as potential expression quantitative trait loci (eQTLs) (Spadoni et al, 2015). More generally, there are several methods for data integration, the first one being to cross-check the results obtained by one method through another, for instance, using GWAS to identify SNPs with low P-values, even non-significant, and then using transcriptomics to pick genes that are differentially expressed in a relevant cell type or tissue.…”
Section: Discussionmentioning
confidence: 99%