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Characterization of Host Genetic Expression Patterns in HIV-Infected Individuals with Divergent Disease Progression

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Characterization of Host Genetic Expression Patterns in HIV-Infected Individuals with Divergent Disease Progression View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Virology 411 (2011) 103–112 Contents lists available at ScienceDirect Virology journal homepage: www.elsevier.com/locate/yviro Characterization of host genetic expression patterns in HIV-infected individuals with divergent disease progression María Salgado a,c, Pedro López-Romero b,1, Sergio Callejas b, Mariola López a,c, Pablo Labarga a, Ana Dopazo b, Vincent Soriano a, Berta Rodés a,c,⁎ a Infectious Diseases Department, Hospital Carlos III, Madrid, Spain b Genomic Unit, CNIC, Madrid, Spain c Fundación Investigación Biomédica del Hospital Carlos III, Madrid, Spain article info abstract Article history: The course of HIV-1 infection shows a variety of clinical phenotypes with an important involvement of host Received 8 September 2010 factors. We compare host gene expression patterns in CD3+ T cells from two of these phenotypes: long-term Returned to author for revision non-progressor patients (LTNP) and matched control patients with standard HIV disease progression. Array 31 October 2010 analysis revealed over-expression of 322 genes in progressors and 136 in LTNP. Up-regulated genes in Accepted 19 December 2010 progressors were mainly implicated in the regulation of DNA replication, cell cycle and DNA damage stimulus Available online 15 January 2011 and mostly localized into cellular organelles. In contrast, most up-regulated genes in LTNP were located at the – Keywords: plasmatic membrane and involved in cytokine cytokine receptor interaction, negative control of apoptosis or LTNP regulation of actin cytoskeleton. Regarding gene interactions, a higher number of viral genes interacting with Microarrays cellular factors were seen in progressors. Our study offers new comparative insights related to disease status HIV and can distinguish differentiated patterns of gene expression among clinical phenotypes. Gene expression © 2010 Elsevier Inc. All rights reserved. Progression Introduction progression should provide a valuable approach to understand HIV pathogenesis. The natural course of HIV-1 infection shows variability among New high-throughput techniques, like microarray analysis, allow infected individuals. The majority of patients develop AIDS within 7– the management of huge information on gene expression patterns 10 years after infection but a small fraction (5%), called long-term- comparing different groups of samples. Using these methods, various non-progressors (LTNP), stay clinically asymptomatic for years in the studies analysed gene expression profiles in different cell types absence of antiretroviral therapy (Pantaleo et al., 1995). The infected with HIV-1 and using in vitro or in vivo approaches (Giri et al., mechanisms contributing to these different phenotypes of viral 2006). However, very few have monitored gene expression in T cells infection are a primary focus of current research in HIV pathogenesis. from patients with different stages of AIDS disease (Hyrcza et al., Despite great advances in recent years identifying several genetic and 2007; Sankaran et al., 2005; Wu et al., 2008). Most of these later viral factors associated with non-progression (Lama and Planelles, studies have examined limited number of samples for each group of 2007; Saksena et al., 2007), the cause for this lack of progression in patients (5 or less) and in some cases results oblige to combine similar many cases remains unclear. There is consensus, however, that is phenotypes in order to obtain more differently regulated genes governed by multiple factors resulting from the interaction between (Hyrcza et al., 2007). Sample size is important to detect not only the HIV and host response to the viral infection. It has been described that largest changes in the levels of gene expression but also more subtle HIV-1 infection has dramatic effects on host T cells physiology (Chan differences with any reliability, and also well define phenotypes are et al., 2007) with significant changes in the pattern of cell gene essential to avoid bias in large scale studies. For this reason, we expression. The identification of genes responsible for this non- decided to focus our analysis in two well defined different groups of patients with a good sample size in both. In the current study, we used a well characterized cohort of LTNP established in 1997 at the Hospital Carlos III (Rodes et al., 2004)to ⁎ Corresponding author. Laboratorio Biología molecular, Hospital Carlos III, Calle compare their gene expression profiles in CD3+ T cells with those in Sinesio Delgado, 10, 28029-Madrid, Spain. Fax: +34 91 733 6614. typical progressor HIV-1+ patients. Cells were obtained ex vivo from E-mail address: [email protected] (B. Rodés). 1 Present address: Epidemiology, Atherothrombosis and Imaging Department, CNIC, HIV-1 infected patients presenting these two different clinical Madrid, Spain. phenotypes. 0042-6822/$ – see front matter © 2010 Elsevier Inc. All rights reserved. doi:10.1016/j.virol.2010.12.037 104 M. Salgado et al. / Virology 411 (2011) 103–112 Results Regarding the main localization of differentially expressed genes between LTNP and progressors, we noticed that despite a wide Patients distribution of genes in both groups, up-regulated genes in LTNPs were localized in higher proportion within the plasmatic membrane. Patient's characteristics at the time of the analysis are described in These include GPR15, IL-17RA, BMPR2, among others. Otherwise, up- detail in Table 1. Sequencing analyses showed all patients carried HIV- regulated genes in progressors were found inside the cell and 1 subtype B. The majority of patients had a wild type CCR5 genotype principally in the nucleus, associated to chromosomes and with and only 4 LTNPs and 1 progressor had the 32-bp CCR5 deletion in intracellular organelles (Fig. 1a and Table 2 section a). The location heterozygosis. determines the cell part activated in each case. For biological processes, some differences emerged in gene Microarray and differential analysis expression between LTNP and progressors that may be relevant to the progression of the infection. Despite up-regulated cell cycle genes RNA from ex vivo CD3+ T cells was used to obtain gene expression present in both groups (Fig. 1b and Table 2 section b), there was a data from Agilent microarrays; witch contained 43,377 probe sets significant higher number of expressed genes in progressors, where corresponding to approximately 30,000 genes described for whole the virus has a fairly high replication. In fact, most of the up-regulated human genome. genes in progressors were related to cell cycle, specifically to the Differences in gene expression were measured with a moderated mitosis phase, nucleic acid metabolic processes and regulation of cell t-statistic. The t-statistic means have been moderated across genes. To cycle progression. Furthermore, the remaining up-regulated genes do that, the sample standard deviation is shrunk towards a pooled were related to endogenous stimulus response, more specifically DNA standard deviation value using empirical Bayes methods. Data are damage stimulus and DNA repair. On the other hand, up-regulated presented as progressors versus LTNP gene expression (t=P-LTNP). genes in LTNPs were mostly associated with other specific functions The analysis revealed a total of 458 differentially expressed genes different than cell cycle. These included cell surface receptor linked between both groups of patients (see Supplementary data). Whereas signal transduction, actin cytoskeleton organization and biogenesis, as in the progressors’ group 322 genes were up-regulated genes well as negative regulation of apoptosis. (t=positive value), only 136 were seen in the non-progressors When analysing for molecular function most up-regulated genes (t=negative value), indicating a higher cell activity in more effective were within LTNPs and very few in progressors (Fig. 1c and Table 2 infections and two different patterns of gene expression according to section c). Functions detected were related to ion binding, trans- phenotype. membrane receptor and G-protein coupled receptor activities. An overlap analysis of these differentially expressed genes found Progressors had only up-regulated the nucleic acid binding function. in our study with other reported genome-wide analysis and host These results are in agreement with observations above, supporting factor studies (Brass et al., 2008; König et al., 2008; Zhou et al., 2008; the idea that in LTNP there was an activation of membrane signalling Bushman et al., 2009) showed 23 coincident genes (gene symbols: functions, whereas in progressors prevailed the cellular cycle HMGB1, THOC4, SNRPD1, RAD51, RANBP1, SUMO1, FEN1, BAZ2B, activities, specifically replication. By the analysis approach we could TUBB, NUDT1, SNRPA1, GINS4, PLK1, KIAA1012, MND1, PSMC3, also say that in LTNP the cellular cycle activities were reduced. YWHAQ, MICB, PRKX, SSR1, BCRA1, UBE2C, ASB1). Finally, specific metabolic pathways were analysed using the KEGG database. In LTNPs activated genes were associated to the cytokine– Functional analysis cytokine receptor interaction, regulation of actin cytoskeleton and focal adhesion processes whereas genes from progressors were Genes operate with an intricate network of interactions within the mainly related to cell cycle pathway (Fig. 2). cell and in some cases in a redundant manner. Complex traits such In conclusion, we have seen differential characteristic
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