OBJECTIVE: To explore and compare the relations between proviral DNA load and CD4+ lymphocyte counts in both HIV-2 monotypic and HIV dual infection. STUDY DESIGN/ METHODS: In Dakar, Senegal, where the HIV-1 and HIV-2 epidemics overlap, serum and peripheral blood mononuclear cell (PBMC) DNA samples were collected from registered female sex workers and hospitalized patients. Sera were evaluated for reactivity to antigens of HIV-1 and HIV-2 by immunoblot; dual reactivity was confirmed with recombinant envelope peptides for HIV-1 and HIV-2. These samples were then subjected to HIV-1 and HIV-2 proviral DNA polymerase chain reaction (PCR). To evaluate the HIV-2 cellular proviral DNA loads, a quantitative competitive PCR (QC-PCR) was developed using nested primers to amplify the gag region of HIV-2. This assay used an internal competitor generated by inserting 25 bp in the first-round PCR target sequence. T-lymphocyte subset counts were estimated by flow cytometry for both HIV-2 monotypic and dually infected persons. RESULTS: 35 HIV-2-infected and 33 dually seroreactive samples were evaluated in this study. The CD4+ lymphocyte counts were similar in both groups, with mean values of 449 +/- 390 cells/mm3 for the HIV-2 monotypic infected persons and 476 +/- 308 cells/mm3 among the dually infected persons. However, the median proviral loads differed significantly, with those in the HIV-2 group ranging from 63.2 to 669.8 copies/10(5) CD4+ cells and demonstrating an inverse correlation with CD4+ lymphocyte count. The HIV dually infected persons showed less variation in viral load, ranging from 9.9 to 43.3 copies/10(5) CD4+ cells. Among the HIV dually infected persons, low HIV-2 proviral load was correlated with low CD4+ lymphocyte counts. CONCLUSIONS: The HIV-2 proviral loads in HIV dually infected persons were significantly lower than those in HIV-2 monotypically infected individuals (P < .0001), despite comparable CD4+ lymphocyte counts. These results suggest that different HIV-2 proviral dynamics prevail in HIV dual infection.
OBJECTIVE: To explore and compare the relations between proviral DNA load and CD4+ lymphocyte counts in both HIV-2 monotypic and HIV dual infection. STUDY DESIGN/ METHODS: In Dakar, Senegal, where the HIV-1 and HIV-2 epidemics overlap, serum and peripheral blood mononuclear cell (PBMC) DNA samples were collected from registered female sex workers and hospitalized patients. Sera were evaluated for reactivity to antigens of HIV-1 and HIV-2 by immunoblot; dual reactivity was confirmed with recombinant envelope peptides for HIV-1 and HIV-2. These samples were then subjected to HIV-1 and HIV-2 proviral DNA polymerase chain reaction (PCR). To evaluate the HIV-2 cellular proviral DNA loads, a quantitative competitive PCR (QC-PCR) was developed using nested primers to amplify the gag region of HIV-2. This assay used an internal competitor generated by inserting 25 bp in the first-round PCR target sequence. T-lymphocyte subset counts were estimated by flow cytometry for both HIV-2 monotypic and dually infected persons. RESULTS: 35 HIV-2-infected and 33 dually seroreactive samples were evaluated in this study. The CD4+ lymphocyte counts were similar in both groups, with mean values of 449 +/- 390 cells/mm3 for the HIV-2 monotypic infected persons and 476 +/- 308 cells/mm3 among the dually infected persons. However, the median proviral loads differed significantly, with those in the HIV-2 group ranging from 63.2 to 669.8 copies/10(5) CD4+ cells and demonstrating an inverse correlation with CD4+ lymphocyte count. The HIV dually infected persons showed less variation in viral load, ranging from 9.9 to 43.3 copies/10(5) CD4+ cells. Among the HIV dually infected persons, low HIV-2 proviral load was correlated with low CD4+ lymphocyte counts. CONCLUSIONS: The HIV-2 proviral loads in HIV dually infected persons were significantly lower than those in HIV-2 monotypically infected individuals (P < .0001), despite comparable CD4+ lymphocyte counts. These results suggest that different HIV-2 proviral dynamics prevail in HIV dual infection.
Authors: W P Schmidt; M Schim Van Der Loeff; P Aaby; H Whittle; R Bakker; M Buckner; F Dias; R G White Journal: Epidemiol Infect Date: 2007-06-11 Impact factor: 2.451
Authors: F Damond; D Descamps; I Farfara; J N Telles; S Puyeo; P Campa; A Leprêtre; S Matheron; F Brun-Vezinet; F Simon Journal: J Clin Microbiol Date: 2001-12 Impact factor: 5.948
Authors: Dana N Raugi; Geoffrey S Gottlieb; Papa S Sow; Macoumba Toure; Fatima Sall; Awa Gaye; Ibra N'doye; Nancy B Kiviat; Stephen E Hawes Journal: AIDS Date: 2013-09-24 Impact factor: 4.177
Authors: Melody G Duvall; Melissa L Precopio; David A Ambrozak; Assan Jaye; Andrew J McMichael; Hilton C Whittle; Mario Roederer; Sarah L Rowland-Jones; Richard A Koup Journal: Eur J Immunol Date: 2008-02 Impact factor: 5.532