For use in humans, human immunodeficiency virus (HIV) DNA vaccines may need to include immunostimulatory adjuvant molecules. CD40 ligand (CD40L), a member of the tumor necrosis factor (TNF) superfamily (TNFSF), is one candidate adjuvant, but it has been difficult to use because it is normally expressed as a trimeric membrane molecule. Soluble trimeric forms of CD40L have been produced, but in vitro data indicate that multimeric, many-trimer forms of soluble CD40L are more active. This multimerization requirement was evaluated in mice using plasmids that encoded either 1-trimer, 2-trimer, or 4-trimer soluble forms of CD40L. Fusion with the body of Acrp30 was used to produce the 2-trimer form, and fusion with the body of surfactant protein D was used to produce the 4-trimer form. Using plasmids for secreted HIV-1 antigens Gag and Env, soluble CD40L was active as an adjuvant in direct proportion to the valence of the trimers (1 < 2 < 4). These CD40L-augmented DNA vaccines elicited strong CD8(+) T-cell responses but did not elicit significant CD4(+) T-cell or antibody responses. To test the applicability of the multimeric fusion protein approach to other TNFSFs, a 4-trimer construct for the ligand of glucocorticoid-induced TNF family-related receptor (GITR) was also prepared. Multimeric soluble GITR ligand (GITRL) augmented the CD8(+) T-cell, CD4(+) T-cell, and antibody responses to DNA vaccination. In summary, multimeric CD40L and GITRL are new adjuvants for DNA vaccines. Plasmids for expressing multimeric TNFSF fusion proteins permit the rapid testing of TNFSF molecules in vivo.
Viral dynamics were intensively investigated in eight patients with acute HIV infection to define the earliest rates of change in plasma HIV RNA before and after the start of antiretroviral therapy. We report the first estimates of the basic reproductive number (R0), the number of cells infected by the progeny of an infected cell during its lifetime when target cells are not depleted. The mean initial viral doubling time was 10 h, and the peak of viremia occurred 21 d after reported HIV exposure. The spontaneous rate of decline (α) was highly variable among individuals. The phase 1 viral decay rate (δI = 0.3/day) in subjects initiating potent antiretroviral therapy during acute HIV infection was similar to estimates from treated subjects with chronic HIV infection. The doubling time in two subjects who discontinued antiretroviral therapy was almost five times slower than during acute infection. The mean basic reproductive number (R0) of 19.3 during the logarithmic growth phase of primary HIV infection suggested that a vaccine or postexposure prophylaxis of at least 95% efficacy would be needed to extinguish productive viral infection in the absence of drug resistance or viral latency. These measurements provide a basis for comparison of vaccine and other strategies and support the validity of the simian immunodeficiency virus macaque model of acute HIV infection.
The relative capacity of several types of human cells and tissue to produce interferon was studied. Types of cells and tissue included were fibroblasts from embryos, foreskins, and biopsied skins; amnion cells; peripheral leukocytes; established lymphoid cell lines; established heteroploid cell lines; and chorioamniotic membrane. When Newcastle disease virus was used as the inducer, fibroblasts and amnion cells produced more interferon per 10 6 cells than leukocytes, lymphoid cells, and heteroploid cells. Only minor variations in interferon-producing capacity were observed among fibroblasts from 36 persons. Culture passage level, cell concentration, and inducer were factors that significantly affected interferon production.
To the Editor: Some HIV-infected individuals appear to maintain stable CD4 counts despite high viral replication. Considering that plasma HIV RNA level explains only a small part of the variability of CD4 decline,1 differences in host-mediated immune responses to viral antigen may be an important factor in determining the pace of HIV-1 disease progression. We hypothesized that some HIV-1-infected individuals better tolerate high viral replication and respond with less immune activation resulting in improved CD4+ T-cell maintenance during untreated HIV-1 infection. To evaluate this, we conducted a cross-sectional study within a university-based HIV outpatient clinic to determine the prevalence of slow HIV disease progressors with robust viral replication and determine if these individuals have a lower proportion of T-lymphocytes expressing markers of immune activation within differentiation stages, proliferation, activation-induced apoptosis and greater expression of regulatory function and naïve phenotype markers than fast progressors. Eligible HIV-1-infected subjects were asymptomatic and antiretroviral-naïve with at least 6 months of follow up, three or more CD4 measurements, and a mean viral load above 20,000 copies/mL. The slope of CD4+T-cell decline was calculated by least squares linear regression method of all available CD4 measurements. Subjects were then qualitatively categorized as “fast progressors” if CD4 decline was consistent with rates observed in other untreated cohorts2,3 or, if less, as “slow progressors.” Slow progressors were randomly selected among eligible patients from the Owen HIV Outpatient Care Center and compared with a convenience sample of recently HIV-diagnosed, asymptomatic individuals with declining CD4 counts (ie, fast progressors) who met the same selection criteria. After appropriate written and informed consent was obtained from all study participants, demographic/laboratory data and blood samples for peripheral blood mononuclear cells (PBMCs) were collected. No clinical/laboratory data were collected or analyzed for subjects identified as slow progressors but for whom consent was not obtained and/or were not contacted. Finally, stored PBMC samples from 10 HIV uninfected individuals were evaluated as a second comparator group. Statistical tests were performed using the open source statistical package R (Version 1.7.0). Records of all new patients from January 2000 to July 2006 were evaluated (n = 2793). Subjects were excluded if they were treatment-experienced (n = 1670), lost to follow up (n = 570), had a history of an AIDS-defining illness (n = 197), or had insufficient laboratory data (n = 86). Of the 467 newly presenting, antiretroviral-naïve patients, we identified 19 as slow progressors (4.1% period prevalence). Of these 19 slow progressors, PBMC samples in six were compared with samples obtained from six fast progressors. Both slow progressors and fast progressors had high presenting CD4 counts (648 versus 572 cells/mL, respectively) and similar durations of HIV infection (3 versus 2.5 years, respectively). Median annual rates of CD4 decline among slow progressors were -5.6 cells/mm3 per year versus -84.3 cells/mm3 per year despite similar viral loads (4.59 log10 [39,743] copies/mL versus 4.82 log10 [67,075] copies/mL; P > 0.3). Because variability in CD4 measurement can increase at higher counts,4 individual rates of CD4 decline were also adjusted by presenting CD4 counts. Overall, slow progressors lost less than 1% of their initial CD4 count per year, whereas progressors lost 18% per year. To determine if increased immune activation, proliferation, and apoptosis were associated with more rapid CD4 decline, we determined the frequency of these subsets between slow and fast progressors and compared them with HIV-1-uninfected controls. Immune activation was defined as the proportion of CD4+ and CD8+ T-cells expressing CD38 with or without HLA-DR coexpression and was measured in various maturation phenotypes, including early (CD45RA+CD27+), intermediate (CD45RA−CD27−), and late (CD45RA+CD27−) differentiation steps (Table 1). HIV-1-uninfected controls displayed less immune activation within these CD4+ and CD8+ T-cell subsets (all P < 0.01); however, no difference was observed between slow and fast progressors. Similarly, CD4+ and CD8+ T-cell proliferation (Ki67+) was also significantly less in HIV-1-uninfected controls but did not differentiate slow and fast progressors. Although the proportion of PHA-stimulated CD4+ and CD8+ (Annexin V+) were similar among all three groups, unstimulated (CD69-Annexin V+) CD4+ and CD8+ T-cells undergoing apoptosis were significantly lower in HIV-uninfected controls but, again, did not differentiate rates of disease progression.TABLE 1: T-Cell Phenotypes and Activation-Induced ApoptosisIn this study, we did not evaluate markers of thymic output or peripheral expansion to determine whether increased CD4+ production explains the difference in slow versus fast disease progression. Rather, we evaluated the proportion of naïve T-cells and regulatory CD4+ T-cell (Table 1) because depletion of regulatory T-cells has been associated with increased immune activation and lower CD4+ T-cell counts during untreated HIV-1 infection.5 The proportion of naïve (CDRA+CD27+) CD4+ T-cells was similar for HIV-1-uninfected and HIV-infected with slow and fast disease progression (median, 38%, 44%, and 50%, respectively). Frequencies of naïve CD8+ T-cells were also similar between HIV-1-uninfected and slow progressions, but there was a trend for lower naïve CD8+ T-cells among fast progressors and uninfected controls (median, 14% versus 28%; P = 0.05). Differences in the proportion of regulatory CD4+ T-cells varied by how these cells were identified. When defined by FoxP3 expression, there was slightly higher frequencies in HIV-1-uninfected controls (P = 0.01), but when further subgrouped into those CD4+FoxP3+ cells with CD25+CD127−, there were no significant differences among the three groups. In this work, we sought to address the question as to whether some HIV-infected individuals with robust viral replication respond clinically like Sooty Mangabey's with SIV infection. First, we selected treatment-naïve individuals with robust viral replication and sufficient follow up to estimate their rate of CD4+ T-cell decline as a surrogate marker for HIV disease host response. Slow and fast progressors were identified from subjects representing opposite poles of HIV disease progression. This strategy of choosing “pure” cases and controls is appropriate for this type of pilot pathophysiological study.6 Second, we attempted to adjust for HIV disease stage and viral load in our selection process by including only asymptomatic individuals with robust viral replication. Although viral load tended to be higher in fast progressors, it is unlikely that an increase of 0.23 log10 copies/mL explains the relatively large difference in rates of CD4+ T-cell loss among these groups. However, using these strict criteria, we identified just 19 individuals as slow progressors from which PBMCs were obtained in only six. This small sample size significantly limited the power of our study and may explain why we did not observe any distinguishing immune phenotypic characteristics between slow and fast progressors. As expected we did observe higher rates of immune activation and spontaneous CD4+ T-cell apoptosis in HIV-infected individuals, regardless of the rate of disease progression, than uninfected controls. Consistent with a recent report,7 we also observed similar proportions of naïve CD4+ T-cells among the three groups. Therefore, if the magnitude of activation-induced apoptosis is similar between slow and fast progressors, potentially it is the pace of naïve CD4+ T-cell replacement that explains the difference in overall rates of CD4+ T-cell decline. Slow HIV disease progression despite robust viral replication is an underrecognized disease response in humans that may occur in approximately 4% of untreated individuals. However, in this small study, we did not observe any significant differences in the proportions of T-cells that were activated within various memory subsets proliferating or undergoing apoptosis in slow versus fast progressors. Miguel Goicoechea, MD* Davey Smith, MD*† Susanne May, PhD‡ Chris Mathews, MD* Celsa Spina, PhD§ *Department of Medicine University of California San Diego San Diego, CA †Veterans Administration San Diego Healthcare System San Diego, CA ‡Division of Biostatistics and Bioinformatics Department of Family and Preventive Medicine University of California San Diego San Diego, CA §Department of Pathology University California San Diego San Diego, CA Veterans Administration San Diego Healthcare System San Diego, CA
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