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Hypertrophic cardiomyopathy: data of transcriptome profiling and epigenome-wide DNA methylation analysis

ABSTRACT: Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease, and its pathogenesis is still being intensively studied to explain the reasons of significant genetic and phenotypic heterogeneity of the disease. To search for possible HCM modifier genes involved in the HCM development we first attempted to analyze gene expression profile coupled with DNA methylation profile in the hypertrophied myocardium of HCM patients; the control group consisted of patients with aortic stenosis. The transcriptome analysis identified significant differences in levels of 193 genes, most of which were underexpressed in HCM. The methylome analysis revealed 1755 nominally significant differentially methylated positions (DMPs), mostly hypomethylated in HCM. The clear differences in DNA methylation profiles between the studied groups indicate the involvement of this process in the formation of primary left ventricle hypertrophy in HCM. Based on gene ontology enrichment analysis, the majority of biological processes, overrepresented by both differentially expressed genes (DEGs) and DMP-containing genes, are involved in the regulation of locomotion and muscle structure development. The intersection of 193 DEGs and 978 DMP-containing genes pinpointed eight genes, expression of which differed between studied groups and correlated with methylation levels of the neighboring DMPs. Half of these genes (AUTS2, GIGYF1, PRRT1, and SLC17A7) were found underexpressed in HCM and involved in neurogenesis and synapse functioning. Our data suggesting the possible involvement of innervation-associated genes in HCM provide additional insights in the disease pathogenesis and expand the field of further research.

ORGANISM(S): Homo sapiens

PROVIDER: GSE207095 | GEO | 2022/12/14

REPOSITORIES: GEO

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Project description:Background: Psoriasis is a T cell-mediated chronic autoimmune/inflammatory disease. While some patients experience disease limited to the skin (skin psoriasis), others develop joint involvement (psoriatic arthritis; PsA). In the absence of disease- and/or outcome-specific biomarkers, and as arthritis can precede skin manifestations, diagnostic and therapeutic delays are common and contribute to disease burden and damage accrual. Objective: Altered epigenetic marks, including DNA methylation, contribute to effector T cell phenotypes and altered cytokine expression in autoimmune/inflammatory diseases. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to heathy controls. Method: Peripheral blood CD8+ T cells from 9 healthy controls, 10 psoriasis and 7 PsA patients were collected to analyze DNA methylation marks using Illumina Human Methylation EPIC BeadChips (>850,000 CpGs per sample). Bioinformatic analysis was performed using R (minfi, limma, ChAMP and DMRcate packages). Results: DNA methylation profiles in CD8+ T cells differentiate healthy controls from psoriasis patients (397 Differentially Methylated Positions (DMPs); 9 Differentially Methylated Regions (DMRs) when ≥CpGs per DMR were considered; 2 DMRs for ≥10 CpGs). Furthermore, patients with skin psoriasis can be discriminated from PsA patients (1861 DMPs, 20 DMRs (≥5 CpGs per region), 4 DMRs (≥10 CpGs per region)). Gene ontology (GO) analyses considering genes with ≥1 DMP in their promoter delivered methylation defects in skin psoriasis and PsA primarily affecting the BMP signaling pathway and endopeptidase regulator activity, respectively. GO analysis of genes associated with DMRs between skin psoriasis and PsA demonstrated an enrichment of GABAergic neuron and cortex neuron development pathways. Treatment with cytokine blockers associated with DNA methylation changes (2372 DMPs; 1907 DMPs within promoters, 7 DMRs (≥5CpG per regions)) affecting transforming growth factor beta receptor and transmembrane receptor protein serine/threonine kinase signaling pathways. Lastly, a methylation score including TNF and IL-17 pathway associated DMPs inverse correlates with skin disease activity scores (PASI). Conclusion: Patients with skin psoriasis exhibit DNA methylation patterns in CD8+ T cells that allow differentiation from PsA patients and healthy individuals, and reflect clinical activity of skin disease. Thus, DNA methylation profiling promises potential as diagnostic and prognostic tool to be used for molecular patient stratification towards individualized treatment. This project aimed at the identification of disease-/outcome-specific DNA methylation signatures in CD8+ T cells from patients with psoriasis and PsA as compared to heathy controls.

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Hypertrophic cardiomyopathy: data of transcriptome profiling and epigenome-wide DNA methylation analysis

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