ObjectiveWe examined genome-wide DNA methylation changes in CD8+ T cells from patients with lupus and controls and investigated the functional relevance of some of these changes in lupus.MethodsGenome-wide DNA methylation of lupus and age, sex and ethnicity-matched control CD8+ T cells was measured using the Infinium MethylationEPIC arrays. Measurement of relevant cell subsets was performed via flow cytometry. Gene expression was quantified by qPCR. Inhibiting STAT1 and CIITA was performed using fludarabine and CIITA siRNA, respectively.ResultsLupus CD8+ T cells had 188 hypomethylated CpG sites compared with healthy matched controls. Among the most hypomethylated were sites associated with HLA-DRB1. Genes involved in the type-I interferon response, including STAT1, were also found to be hypomethylated. IFNα upregulated HLA-DRB1 expression on lupus but not control CD8+ T cells. Lupus and control CD8+ T cells significantly increased STAT1 mRNA levels after treatment with IFNα. The expression of CIITA, a key interferon/STAT1 dependent MHC-class II regulator, is induced by IFNα in lupus CD8+ T cells, but not healthy controls. CIITA knockdown and STAT1 inhibition experiments revealed that HLA-DRB1 expression in lupus CD8+ T cells is dependent on CIITA and STAT1 signalling. Coincubation of naïve CD4+ T cells with IFNα-treated CD8+ T cells led to CD4+ T cell activation, determined by increased expression of CD69 and cytokine production, in patients with lupus but not in healthy controls. This can be blocked by neutralising antibodies targeting HLA-DR.ConclusionsLupus CD8+ T cells are epigenetically primed to respond to type-I interferon. We describe an HLA-DRB1+ CD8+ T cell subset that can be induced by IFNα in patients with lupus. A possible pathogenic role for CD8+ T cells in lupus that is dependent on a high type-I interferon environment and epigenetic priming warrants further characterisation.

The MHC region encodes HLA genes and is the most complex region in the human genome. The extensively polymorphic nature of the HLA hinders accurate localization and functional assessment of disease risk loci within this region. Using targeted capture sequencing and constructing individualized genomes for transcriptome alignment, we identified 908 novel transcripts within the human MHC region. These include 593 novel isoforms of known genes, 137 antisense strand RNAs, 119 novel long intergenic noncoding RNAs, and 5 transcripts of 3 novel putative protein-coding human endogenous retrovirus genes. We revealed allele-dependent expression imbalance involving 88% of all heterozygous transcribed single nucleotide polymorphisms throughout the MHC transcriptome. Among these variants, the genetic variant associated with Behçet's disease in the / region, which tags , is within novel long intergenic noncoding RNA transcripts that are exclusively expressed from the haplotype with the protective but not the disease risk allele. Further, the transcriptome within the MHC region can be defined by 14 distinct coexpression clusters, with evidence of coregulation by unique transcription factors in at least 9 of these clusters. Our data suggest a very complex regulatory map of the human MHC, and can help uncover functional consequences of disease risk loci in this region.

Recent developments in bioinformatics technologies have led to advances in our understanding of how oncogenic viruses such as the human papilloma virus drive cancer progression and evade the host immune system. Here, we focus our review on understanding how these emerging bioinformatics technologies influence our understanding of how human papilloma virus (HPV) drives immune escape in cancers of the head and neck, and how these new informatics approaches may be generally applicable to other virally driven cancers. Indeed, these tools enable researchers to put existing data from genome wide association studies, in which high risk alleles have been identified, in the context of our current understanding of cellular processes regulating neoantigen presentation. In the future, these new bioinformatics approaches are highly likely to influence precision medicine-based decision making for the use of immunotherapies in virally driven cancers.

Objective: We examined genome-wide DNA methylation changes in CD8+ T cells from lupus patients and controls, and investigated the functional relevance of some of these changes in lupus.Methods: Genome-wide DNA methylation of lupus and age, sex, and ethnicity-matched control CD8+ T cells was measured using the Infinium MethylationEPIC arrays.Measurement of relevant cell subsets was performed via flow cytometry. Gene expression was quantified by qPCR.

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