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Expression data from HIV exposed and uninfected women

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NIAID Data Ecosystem2026-03-11 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE33580
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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. 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.
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2019-03-25
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