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Computationally inferred cell-type specific epigenome-wide DNA methylation analysis unveils distinct methylation patterns among immune cells for HIV infection in three cohorts.
Zhang, Xinyu; Hu, Ying; Vandenhoudt, Ral E; Yan, Chunhua; Marconi, Vincent C; Cohen, Mardge H; Wang, Zuoheng; Justice, Amy C; Aouizerat, Bradley E; Xu, Ke.
Affiliation
  • Zhang X; Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Hu Y; VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.
  • Vandenhoudt RE; Center for Biomedical Information and Information Technology, National Cancer Institute, Rockville, Maryland, United States of America.
  • Yan C; Department of Psychiatry, Yale School of Medicine, New Haven, Connecticut, United States of America.
  • Marconi VC; VA Connecticut Healthcare System, West Haven, Connecticut, United States of America.
  • Cohen MH; Center for Biomedical Information and Information Technology, National Cancer Institute, Rockville, Maryland, United States of America.
  • Wang Z; Division of Infectious Diseases, Emory University School of Medicine and Department of Global Health, Rollins School of Public Health, Emory University, Georgia, United States of America.
  • Justice AC; Atlanta Veterans Affairs Healthcare System, Decatur, Georgia, United States of America.
  • Aouizerat BE; Department of Medicine, Stroger Hospital of Cook County, Chicago, Illinois, United States of America.
  • Xu K; Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, United States of America.
PLoS Pathog ; 20(3): e1012063, 2024 Mar.
Article in En | MEDLINE | ID: mdl-38466776
ABSTRACT

BACKGROUND:

Epigenome-wide association studies (EWAS) have identified CpG sites associated with HIV infection in blood cells in bulk, which offer limited knowledge of cell-type specific methylation patterns associated with HIV infection. In this study, we aim to identify differentially methylated CpG sites for HIV infection in immune cell types CD4+ T-cells, CD8+ T-cells, B cells, Natural Killer (NK) cells, and monocytes.

METHODS:

Applying a computational deconvolution method, we performed a cell-type based EWAS for HIV infection in three independent cohorts (Ntotal = 1,382). DNA methylation in blood or in peripheral blood mononuclear cells (PBMCs) was profiled by an array-based method and then deconvoluted by Tensor Composition Analysis (TCA). The TCA-computed CpG methylation in each cell type was first benchmarked by bisulfite DNA methylation capture sequencing in a subset of the samples. Cell-type EWAS of HIV infection was performed in each cohort separately and a meta-EWAS was conducted followed by gene set enrichment analysis.

RESULTS:

The meta-analysis unveiled a total of 2,021 cell-type unique significant CpG sites for five inferred cell types. Among these inferred cell-type unique CpG sites, the concordance rate in the three cohorts ranged from 96% to 100% in each cell type. Cell-type level meta-EWAS unveiled distinct patterns of HIV-associated differential CpG methylation, where 74% of CpG sites were unique to individual cell types (false discovery rate, FDR <0.05). CD4+ T-cells had the largest number of unique HIV-associated CpG sites (N = 1,624) compared to any other cell type. Genes harboring significant CpG sites are involved in immunity and HIV pathogenesis (e.g. CD4+ T-cells NLRC5, CX3CR1, B cells IFI44L, NK cells IL12R, monocytes IRF7), and in oncogenesis (e.g. CD4+ T-cells BCL family, PRDM16, monocytes PRDM16, PDCD1LG2). HIV-associated CpG sites were enriched among genes involved in HIV pathogenesis and oncogenesis that were enriched among interferon-α and -γ, TNF-α, inflammatory response, and apoptotic pathways.

CONCLUSION:

Our findings uncovered computationally inferred cell-type specific modifications in the host epigenome for people with HIV that contribute to the growing body of evidence regarding HIV pathogenesis.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / DNA Methylation Limits: Humans Language: En Journal: PLoS Pathog Year: 2024 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: HIV Infections / DNA Methylation Limits: Humans Language: En Journal: PLoS Pathog Year: 2024 Type: Article Affiliation country: United States