Cell-type based epigenomic analysis to identify druggable genes for people living with HIV infection and using cannabis

Cannabis (CB) is frequently used by people with HIV (PWH) for its claimed benefits alongside antiretroviral therapy. However, the immunomodulatory impact of CB in the context of the chronic inflammation experienced among PWH is unclear. The interaction between HIV and CB in the host genome remains poorly understood. Previous studies on the epigenetic effects of HIV and CB have been limited and most studies conducted in bulk peripheral blood mononuclear cells (PBMCs), which only provides an average view of DNA methylation (DNAm) changes across various cell types. Our recent research of DNAm in CD4+ T cells isolated from PWH identified DNAm CpG sites that were linked to HIV-1 latent reservoir and a set of druggable genes, including the target for Ibalizumab, a medication for treatment resistant of HIV infection. The result underscores the value of cell specific DNAm analysis in uncovering mechanisms of HIV pathogenesis and potential therapeutic targets. Nonetheless, the combined effects of HIV infection and CB use on DNAm, particularly considering genetic variants that influence DNAm (methylation quantitative trait loci, meQTL), have yet to be fully explored. To address these gaps, we hypothesize that CB use alters DNAm in a cell type-specific manner within the HIV-infected host, with these changes potentially modulated by meQTL specific to each cell type. Our study aims to dissect the epigenomic landscape of CB and HIV interaction by conducting cell-type based genome-wide DNAm and meQTL analyses in two large cohorts of PWH, assessing their potential for druggable targets. This will involve comprehensive profiling of DNAm across five different cell types isolated from PBMCs, alongside functional validation studies both in vivo and in vitro. The functional validation involves transcriptome-wide association analyses, single-nucleus RNA and ATAC sequencing to elucidate the functional impact of specific epigenetic modifications and their relevance to drug development. In preliminary work, we employed a computational algorithm to deconvolve DNAm data to specific cell types and validated these findings through direct sequencing. This has revealed a more nuanced understanding of HIV's impact at the cellular level, identifying cell type specific DNAm sites and highlighting the unique genetic landscapes influenced by HIV across different cell populations. Furthermore, we have developed a novel algorithm, Hierarchical Bayesian Interaction model, to uncover genetically influenced DNAm at cell type level. These preliminary findings provide the framework for this proposed project. Our team's established expertise in epigenomics among PWH, positions us uniquely to achieve our goal. Successful completion of this study promises to deliver unprecedented insights into the mechanisms of CB's immunomodulatory effects in HIV, paving the way for novel therapeutic strategies through targeted drug repositioning.