Name: Transcription profiling by array of human CD4+ T cells from HIV-resistant and HIV-susceptible individuals
Keywords: transcription profiling by array

Dataset Information

Transcription profiling by array of human CD4+ T cells from HIV-resistant and HIV-susceptible individuals

ABSTRACT: Understanding why some individual resist HIV-1 infection despite continued exposure is an important goal for vaccine development. We compared CD4+ T cell gene expression at baseline in HIV-1 resistant commercial sex-workers from Nairobi, Kenya to HIV-1 high-risk negative (non-resistant) commercial sex-workers using gene expression arrays Experiment Overall Design: CD4+ T cells from both HIV resistant and HIV low-risk negative individuals were isolated from PBMC after 24 hours of culture by negative selection. Total RNA was isolated and gene expression compared using Affymetrix total genome arrays.

REANALYSED by: E-GEOD-14278

INSTRUMENT(S): 418 [Affymetrix]

ORGANISM(S): Homo sapiens

SUBMITTER: Paul McLaren

PROVIDER: E-GEOD-14278 | ArrayExpress | 2009-01-17

SECONDARY ACCESSION(S): GSE14278PRJNA114563

REPOSITORIES: GEO, ArrayExpress

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Publications

HIV‐exposed seronegative commercial sex workers show a quiescent phenotype in the CD4+ T cell compartment and reduced expression of HIV‐dependent host factors.

McLaren Paul J PJ Ball T Blake TB Wachihi Charles C Jaoko Walter W Kelvin David J DJ Danesh Ali A Kimani Joshua J Plummer Francis A FA Fowke Keith R KR

The Journal of infectious diseases 20101101

Studies of human immunodeficiency virus (HIV)-exposed seronegative individuals are crucial to inform vaccine design. In the present study we demonstrated that HIV-exposed seronegative commercial sex workers produce lower levels of proinflammatory cytokines at baseline than HIV-negative control subjects. We also showed that CD4+ T cells of HIV-exposed seronegative commercial sex workers have a characteristically lower level of gene expression that can be seen in differentially expressed genes and ...[more]

PMID: 20887221

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Project description:We carried out a global whole blood genome wide expression profiling of HIV exposed and uninfected women from Nairobi to identify host factors which may be a key contribution to HIV resistance phenomenon. To identify novel biomarkers for HIV resistance including pathways that may be critical in anti-HIV vaccine design, we carried out a gene expression analysis on blood samples obtained from HIV Exposed and uninfected volunteers from a commercial sex worker cohort in Nairobi and compared their profiles to HIV susceptible negative controls. Whole blood samples were collected from 43 HIV resistant and a similar number of HIV negative antenatal clinic attendees and total RNA extracted and hybridized to the affymetrix HUG 133 Plus 2.0 micro arrays (Affymetrix, Santa Clara CA). More than 2,274 probe sets were differentially expressed in the HIV resistant women as compared to the control group (fold change ≥1.3; p value ≤ 0.0001, FDR <0.05) . Unsupervised hierarchical clustering of the differentially expressed genes readily distinguished EUs from susceptible controls. Pathway analysis of the differentially expressed genes through the KEGG signaling revealed a majority of the impacted pathways (13 of 15, 87%) were significantly down expressed. The most down expressed pathways were glycolysis/gluconeogenesis, pentose phosphate, Phosphatidyl inositol, Natural Killer cell cytotoxicity and T-cell receptor signaling. Ribosomal protein synthesis and tight junction genes were up expressed. We infer that the hallmark of HIV resistance is down regulation of genes in key signaling pathways that HIV depends on for infection and suggest that an anti-HIV vaccine design may need to incorporate components that switch down specific immune activating factors. Overall design: Whole blood samples were collected from 43 HIV resistant and a similar number of HIV negative women and total RNAs were extracted and hybridized on Affymetrix microarrays. We sought to compare gene expression patterns between two groups of women and infer the genes which may be involved in key signaling patheways that HIV depending on for infection.