Significant effects of antiretroviral therapy on global gene expression in brain tissues of patients with HIV-1-associated neurocognitive disorders

Abstract

Antiretroviral therapy (ART) has reduced morbidity and mortality in HIV-1 infection; however HIV-1-associated neurocognitive disorders (HAND) persist despite treatment. The reasons for the limited efficacy of ART in the brain are unknown. Here we used functional genomics to determine ART effectiveness in the brain and to identify molecular signatures of HAND under ART. We performed genome-wide microarray analysis using Affymetrix U133 Plus 2.0 Arrays, real-time PCR, and immunohistochemistry in brain tissues from seven treated and eight untreated HAND patients and six uninfected controls. We also determined brain virus burdens by real-time PCR. Treated and untreated HAND brains had distinct gene expression profiles with ART transcriptomes clustering with HIV-1-negative controls. The molecular disease profile of untreated HAND showed dysregulated expression of 1470 genes at p<0.05, with activation of antiviral and immune responses and suppression of synaptic transmission and neurogenesis. The overall brain transcriptome changes in these patients were independent of histological manifestation of HIV-1 encephalitis and brain virus burdens. Depending on treatment compliance, brain transcriptomes from patients on ART had 83% to 93% fewer dysregulated genes and significantly lower dysregulation of biological pathways compared to untreated patients, with particular improvement indicated for nervous system functions. However a core of about 100 genes remained similarly dysregulated in both treated and untreated patient brain tissues. These genes participate in adaptive immune responses, and in interferon, cell cycle, and myelin pathways. Fluctuations of cellular gene expression in the brain correlated in Pearson's formula analysis with plasma but not brain virus burden. Our results define for the first time an aberrant genome-wide brain transcriptome of untreated HAND and they suggest that antiretroviral treatment can be broadly effective in reducing pathophysiological changes in the brain associated with HAND. Aberrantly expressed transcripts common to untreated and treated HAND may contribute to neurocognitive changes defying ART.

Figure 1. Similarity of brain transcriptomes of untreated HAND patients with and without encephalitis.

A. Using Affymetrix microarrays we evaluated gene expression in brain tissue. Normalized data from HAND patients with or without encephalitis were analyzed by Hierarchical Clustering using Genesis software. B. Gene set analysis was conducted by GAzer software to identify biological pathways most significantly up-regulated (right panel) or down-regulated (left panel) in untreated HAND without or with encephalitis (HAND/HIVE) vs. uninfected controls.

Figure 2. The pattern of changes in brain cell gene expression relative to uninfected subjects differs significantly between untreated HAND patients and HAND patients treated with ART.

A. The Venn diagram displays the number and overlap of transcripts differentially expressed relative to uninfected subjects from HAND, ART, and HAND patients excluding low adherence patients ART3 and ART5 (ARTa). B. GAzer was employed to identify the eight most dysregulated biological pathways relative to uninfected subjects in the HAND dataset and the extent of change in the same pathways in ART and ARTa datasets are shown for comparison with Z-scores plotted for the significantly up-regulated (right panel) and down-regulated (left panel) pathways. C. QPCR analysis of gene expression in HAND and ARTa patients plotting fold change of expression uninfected subjects. Asterisks represent p-value<0.05 in t-test analysis, asterisks over column indicate comparison to values from uninfected subjects, asterisks between columns represent their comparison. D. Immunostaining and quantitation of selected proteins in brain tissue of uninfected subjects (C), HAND and ART patients.

Figure 3. Extent and kind of differences in brain cell gene expression in untreated HAND patients and HAND patients receiving ART.

A. Selecting the transcripts differentially expressed in brain tissue from HAND patients relative to uninfected subjects, hierarchical cluster analysis was performed on extent of expression from all subjects using Genesis software. Red represents up-regulation, green represents down-regulation. B. Gene ontology analysis of ART dataset vs. HAND dataset was performed using GAzer software. The upper panel shows pathways elevated in ART and the lower panel shows pathways suppressed in ART relative to HAND brain samples.

Figure 4. Predicted interaction networks of brain cell genes significantly downmodulated in untreated HAND and expressed at close to control levels in HAND patients under ART.

The interactions between genes were identified using STRING software with each type of interaction distinguished by color. The most significantly regulated pathways identified in this analysis are synaptic transmission, nervous system development and GABA neurotransmission pathway.

Figure 5. Common dysregulated genes in brain tissues of treated and untreated HAD patients.

A. Selected genes significantly up or down-regulated in HAND or ART patients compared to uninfected subjects are tabulated (FC: Fold-change, pv: t-test p-value). B. Heatmap representation of significantly dysregulated genes in both HAND and ART datasets relative to uninfected subjects. C. QPCR analysis of expression of selected genes in HAND and ART patients relative to uninfected subjects. D. Immunostaining and quantitation of selected proteins in brain tissue.

Figure 6. Global gene expression changes in HAND brain correlated the most with plasma and less with CSF and brain virus load.

A. Examples of individual genes whose expression positively correlates with plasma virus load (r²: Coefficient of determination, PC: Pearson correlation). B. The upper panel shows positive correlations and the lower panel shows negative correlations with virus load (vl) in plasma, CSF, or brain respectively and gene expression in the brain. Genes that correlated positively and highly with virus load were analyzed using EASE software also negative correlations. The EASE score represent the significance of the regulated pathways.