The Interplay Between Host Genetic Variation, Viral Replication, and Microbial Translocation in Untreated HIV-Infected Individuals

Systemic immune activation, a major determinant of human immunodeficiency virus (HIV) disease progression, is the result of a complex interplay between viral replication, dysregulation of the immune system, and microbial translocation due to gut mucosal damage. Although human genetic variants influencing HIV load have been identified, it is unknown how much the host genetic background contributes to interindividual differences in other determinants of HIV pathogenesis such as gut damage and microbial translocation. Using samples and data from 717 untreated participants in the Swiss HIV Cohort Study and a genome-wide association study design, we searched for human genetic determinants of plasma levels of intestinal fatty acid-binding protein (I-FABP/FABP2), a marker of gut damage, and of soluble CD14 (sCD14), a marker of lipopolysaccharide bioactivity and microbial translocation. We also assessed the correlations between HIV load, sCD14, and I-FABP. Although we found no genome-wide significant determinant of the tested plasma markers, we observed strong associations between sCD14 and both HIV load and I-FABP, shedding new light on the relationships between processes that drive progression of untreated HIV infectio

Abstracts from the 20th International Symposium on Signal Transduction at the Blood-Brain Barriers

https://deepblue.lib.umich.edu/bitstream/2027.42/138963/1/12987_2017_Article_71.pd

T cell responses to JC virus target each viral protein.

<p>PBMC from individuals with MS treated with natalalizumab who did not have PML were stimulated with JCV peptide pools or costimulatory molecules alone (negative control) for 6 hours. Panel A shows memory CD4 T cells from 3 samples; Panel C shows memory CD8 T cells from 3 samples. The fluorescence intensity of IFNγ and TNF are shown on the X and Y-axes, respectively. Panels B and D show baseline pre-treatment responses from all eight longitudinal subjects with MS, with the background-subtracted magnitude of the response to each JCV protein depicted by colored bars. Responses were measured by production of any combination of IFNγ, TNF and IL-2, using Boolean gates and then background subtracting from each Boolean population.</p

Transient increase in IL-10-producing cells after natalizumab initiation and high frequency in individuals with PML.

<p>PBMC from all studied MS patients were stimulated with SEB. Background-subtracted frequency of memory CD4 T cells producing IL-10 is shown. <i>P</i> value from month 0 to month 1 is the result of Wilcoxon matched-pairs rank sum test. Panel A shows longitudinal samples from MS patients treated with natalizumab who did not have PML, and Panel B shows samples from 4 individuals with natalizumab-associated PML.</p

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

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

JCV-specific T cell responses in subjects with PML.

<p>Panel A shows the total response to JCV. For each of 4 subjects with PML, the summed frequency of memory CD4 (left) and CD8 (right) T cells producing IFNγ, TNF, IL-2 or IL-10 (indicated by colors) in response to all JCV peptides is shown. Red bars indicate frequency of cells producing IFNγ, including those that produce any combination of IL-2 and TNF in addition to IFNγ. The responses for subjects PML-1 and PML-2 are not significantly above background in these samples. Panel B shows the JCV-specific IL-10 response in subjects PML-3 and PML-4. Subjects PML-1, 2, 3 and 4 were sampled 2 weeks, 2 months, 4 months and 5 years, respectively, after diagnosis with PML.</p

Magnitude and functional profile of JCV and CMV-specific T cells do not change upon treatment.

<p>PBMC from individuals with MS treated with natalalizumab who did not have PML were stimulated with JCV peptide pools, CMV pp65 peptide pool or costimulatory molecules alone (negative control) for 6 hours. A response was considered positive if the frequency of memory T cells producing IFNγ, TNF or IL-2 was higher in the peptide-stimulated cells than in those stimulated with costimulatory molecules alone. Response size was calculated by measuring the frequency of cells producing each Boolean combination of cytokines, and subtracting the frequency of these cells in the negative control. Summing the background-subtracted Boolean subsets gave the total frequency of cytokine-producing memory T cells specific for the peptide pool. The total response to JCV (Panel A) was calculated by summing the frequency of cells specific for each of the 5 JCV peptide pools. The functional profile of the response is shown in the pie charts above, with the blue slice representing the proportion of responding cells that produce all 3 cytokines, the red slices representing the proportion of cells that produce a combination of 2 cytokines, and the green slices representing the proportion of cells that produce only 1 cytokine. Panel B shows the frequency of CD4 (left) and CD8 (right) memory T cells responding to the CMV pp65 peptide pool.</p

Preexisting influenza-specific CD4+ T cells correlate with disease protection against influenza challenge in humans

Protective immunity against influenza virus infection is mediated by neutralizing antibodies, but the precise role of T cells in human influenza immunity is uncertain. We conducted influenza infection studies in healthy volunteers with no detectable antibodies to the challenge viruses H3N2 or H1N1. We mapped T cell responses to influenza before and during infection. We found a large increase in influenza-specific T cell responses by day 7, when virus was completely cleared from nasal samples and serum antibodies were still undetectable. Preexisting CD4+, but not CD8+, T cells responding to influenza internal proteins were associated with lower virus shedding and less severe illness. These CD4+ cells also responded to pandemic H1N1 (A/CA/07/2009) peptides and showed evidence of cytotoxic activity. These cells are an important statistical correlate of homotypic and heterotypic response and may limit severity of influenza infection by new strains in the absence of specific antibody responses. Our results provide information that may aid the design of future vaccines against emerging influenza strains