Perturbation of B Cell Gene Expression Persists in HIV-Infected Children Despite Effective Antiretroviral Therapy and Predicts H1N1 Response

Abstract

Despite effective antiretroviral therapy (ART), HIV-infected individuals with apparently similar clinical and immunological characteristics can vary in responsiveness to vaccinations. However, molecular mechanisms responsible for such impairment, as well as biomarkers able to predict vaccine responsiveness in HIV-infected children, remain unknown. Following the hypothesis that a B cell qualitative impairment persists in HIV-infected children (HIV) despite effective ART and phenotypic B cell immune reconstitution, the aim of the current study was to investigate B cell gene expression of HIV compared to age-matched healthy controls (HCs) and to determine whether distinct gene expression patterns could predict the ability to respond to influenza vaccine. To do so, we analyzed prevaccination transcriptional levels of a 96-gene panel in equal numbers of sort-purified B cell subsets (SPBS) isolated from peripheral blood mononuclear cells using multiplexed RT-PCR. Immune responses to H1N1 antigen were determined by hemaglutination inhibition and memory B cell ELISpot assays following trivalent-inactivated influenza vaccination (TIV) for all study participants. Although there were no differences in terms of cell frequencies of SPBS between HIV and HC, the groups were distinguishable based upon gene expression analyses. Indeed, a 28-gene signature, characterized by higher expression of genes involved in the inflammatory response and immune activation was observed in activated memory B cells (CD27⁺CD21^-) from HIV when compared to HC despite long-term viral control (>24 months). Further analysis, taking into account H1N1 responses after TIV in HIV participants, revealed that a 25-gene signature in resting memory (RM) B cells (CD27⁺CD21⁺) was able to distinguish vaccine responders from non-responders (NR). In fact, prevaccination RM B cells of responders showed a higher expression of gene sets involved in B cell adaptive immune responses (APRIL, BTK, BLIMP1) and BCR signaling (MTOR, FYN, CD86) when compared to NR. Overall, these data suggest that a perturbation at a transcriptional level in the B cell compartment persists despite stable virus control achieved through ART in HIV-infected children. Additionally, the present study demonstrates the potential utility of transcriptional evaluation of RM B cells before vaccination for identifying predictive correlates of vaccine responses in this population.

Keywords: B cell receptor; B cells; H1N1; influenza vaccination; pediatric HIV; systems biology; transcriptomics; vaccinomics.

Figure 1

B cell phenotype in HIV and age-matched healthy control (HC). Representative gates (A) and comparisons of B cell percentages (B,C). Two tailed Mann–Whitney was used for comparisons. CD20⁺ cells established the B cell population, and expression of IgD, CD27, CD21, and CD10 was used to define total naive (CD27⁻IgD⁺), class switched CD27⁺ memory B cells (CD27⁺IgD⁻), double-negative (DN; CD27⁻IgD⁻), resting memory (RM), tissue-like (TL), activated memory (AM), and naive. FSC, forward scatter; SSC, side scatter. Contingency plot in (C) represents frequency of AM and RM in HIV and HC.

Figure 2

HIV present higher expression of genes involved in immuneactivation and inflammation in activated memory (AM) B cells despite effective antiretroviral therapy (ART) and long-term viral suppression. Graphs in panels (A,B) show comparisons in gene expression between healthy control (HC) and HIV. (A) Spider plot shows number of differentially expressed genes (DEGs) for all the subsets and total peripheral blood mononuclear cells (PBMCs). Box plots in panel (B) show gene expression averages from DEGS resulting in AM between HIV and HC (gene ranking defined by fold change). In this figure, p-values resulting from ANOVA analysis are shown. Color-labeled genes are defined according gene set enrichment analysis (performed by genemania.org) as described in the legend.

Figure 3

H1N1 response after trivalent inactivated influenza in HIV and perturbation of the memory compartment among non-responders. (A) The flow chart describes the criteria of selection used to define responders and non-responders to trivalent-inactivated influenza vaccination (TIV) among HIV-infected children. As a first criteria of selection, all patients were selected according to the fold increase of H1N1 hemagglutination inhibition (HAI) titer. Patients responding or not responding to the first selection criteria were further selected according to H1N1 ELISpot response. Selected healthy donors responded to the vaccination and met both criteria of selection. Representative ELISpot assay (B) and scatter dot plot (C) show ELISpot data for H1N1.

Figure 4

Prevaccination gene signatures in RM B cell subset discriminate HIV-infected R and non-responder (NR). (A) Spider plot shows number of differentially expressed genes (DEGs) for all the subsets and total peripheral blood mononuclear cells (PBMCs). (B) Heatmap shows gene expression in R and NR. Colored genes’ names refer to gene set enrichment analysis (GSEA) legend. In panels (C,D), correlation between gene expression in resting memory and H1N1-seroconversion (C) and ELISpot at T1 (D) are shown. p and r values show results from correlation analyses (Pearson or Spearman tests for parametric and non-parametric data, respectively).