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Comparative transcriptomics of extreme phenotypes of human HIV-1 infection and SIV infection in sooty mangabey and rhesus macaque.

Type of publication Peer-reviewed
Publikationsform Original article (peer-reviewed)
Publication date 2011
Author Rotger Margalida, Dalmau Judith, Rauch Andri, McLaren Paul, Bosinger Steven E, Martinez Raquel, Sandler Netanya G, Roque Annelys, Liebner Julia, Battegay Manuel, Bernasconi Enos, Descombes Patrick, Erkizia Itziar, Fellay Jacques, Hirschel Bernard, Miró Jose M, Palou Eduard, Hoffmann Matthias, Massanella Marta, Blanco Julià, Woods Matthew, Günthard Huldrych F, de Bakker Paul, Douek Daniel C, Silvestri Guido,
Project Host evolutionary genomics of HIV-1 and other retroviruses
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Original article (peer-reviewed)

Journal The Journal of clinical investigation
Volume (Issue) 121(6)
Page(s) 2391 - 400
Title of proceedings The Journal of clinical investigation
DOI 10.1172/JCI45235

Abstract

High levels of HIV-1 replication during the chronic phase of infection usually correlate with rapid progression to severe immunodeficiency. However, a minority of highly viremic individuals remains asymptomatic and maintains high CD4⁺ T cell counts. This tolerant profile is poorly understood and reminiscent of the widely studied nonprogressive disease model of SIV infection in natural hosts. Here, we identify transcriptome differences between rapid progressors (RPs) and viremic nonprogressors (VNPs) and highlight several genes relevant for the understanding of HIV-1-induced immunosuppression. RPs were characterized by a specific transcriptome profile of CD4⁺ and CD8⁺ T cells similar to that observed in pathogenic SIV-infected rhesus macaques. In contrast, VNPs exhibited lower expression of interferon-stimulated genes and shared a common gene regulation profile with nonpathogenic SIV-infected sooty mangabeys. A short list of genes associated with VNP, including CASP1, CD38, LAG3, TNFSF13B, SOCS1, and EEF1D, showed significant correlation with time to disease progression when evaluated in an independent set of CD4⁺ T cell expression data. This work characterizes 2 minimally studied clinical patterns of progression to AIDS, whose analysis may inform our understanding of HIV pathogenesis.
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