Integration of genome-wide DNA methylation and transcription uncovered aberrant methylation-regulated genes and pathways in the peripheral blood mononuclear cells of systemic sclerosis [gene expression]
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE117928 | GEO | 2018/09/01
REPOSITORIES: GEO
Similar Datasets
Project description:The identified MeDEGs may represent novel candidate factors which lead to the abnormal activation of immune regulatory pathways in the pathogenesis of SSc. They may also be used as diagnostic biomarkers for SSC and clinical complications
2018-09-01 | GSE117929 | GEO
Project description:Objective. Systemic sclerosis (SSc) is a systemic connective tissue disease of unknown etiology. Aberrant gene expression and epigenetic modifications in circulating immune cells have been implicated in the pathogenesis of SSc. This study is to delineate the interaction network between gene transcription and DNA methylation in PBMC of SSc patients and to identify methylation-regulated genes which are involved in the pathogenesis of SSc. Methods. Genome-wide mRNA transcription and global DNA methylation analysis were performed on PBMC from 18 SSc patients and 19 matched normal controls (NC) using Illumina BeadChips. Differentially expressed genes (DEGs) and differentially methylated positions (DMPs) were integrative analyzed to identify methylation-regulated genes and associated molecular pathways. Results. Transcriptome analysis distinguished 453 DEGs (269 up- and 184 downregulated) in SSc from NC. Global DNA methylation analysis identified 925 DMPs located on 618 genes. Integration of the two lists revealed only 20 DEGs which harbor inversely correlated DMPs, including 12 upregulated (ELANE, CTSG, LTBR, C3AR1, CSTA, SPI1, ODF3B, SAMD4A, PLAUR, NFE2, ZYX, and CTSZ) and eight downregulated genes (RUNX3, PRF1, PRKCH, PAG1, RASSF5, FYN, CXCR6, and F2R). These potential methylation-regulated DEGs (MeDEGs) are enriched in the pathways related to immune cell migration, proliferation, activation, and inflammation activities. Using a machine learning algorism, we identified six out of the 20 MeDEGs, including F2R, CXCR6, FYN, LTBR, CTSG, and ELANE, which distinguished SSc from NC with 100% accuracy. Four genes (F2R, FYN, PAG1, and PRKCH) differentially expressed in SSc with interstitial lung disease (ILD) compared to SSc without ILD. Conclusion. The identified MeDEGs may represent novel candidate factors which lead to the abnormal activation of immune regulatory pathways in the pathogenesis of SSc. They may also be used as diagnostic biomarkers for SSc and clinical complications.
| S-EPMC6139224 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2018-09-01 | GSE117931 | GEO
Project description:There is a pressing need to identify early biomarkers of lung involvement in systemic sclerosis (SSc) to start as soon as possible antifibrotic therapy. We aimed to identify extracellular vesicle-derived microRNAs (EV-miRNAs) that are differentially expressed between SSc patients with and without interstitial lung disease (ILD) and explore their diagnostic value. Small EVs derived from plasma were isolated from 20 well-characterised SSc patients with ILD (SSc-ILD, n=10), without ILD (SSc-no ILD, n=10) and 10 matched healthy subjects (HS). Small RNA sequencing was used to identify sEV-miRNAs associated to SSc-ILD.
2024-09-15 | E-MTAB-14290 | biostudies-arrayexpress
Project description:Objective: Pulmonary complications in systemic sclerosis (SSc), including pulmonary fibrosis (PF) and pulmonary arterial hypertension (PAH), are the leading cause of mortality. We compared the molecular fingerprint of SSc lung tissues and matching primary lung fibroblasts to those of normal donors, and patients with idiopathic pulmonary fibrosis (IPF) and idiopathic pulmonary arterial hypertension (IPAH). Methods: Lung tissues were obtained from 33 patients with SSc who underwent lung transplantation. Tissues and cells from a subgroup of SSc patients with predominantly PF or PAH were compared to those from normal donors, patients with IPF, or IPAH. Microarray data was analyzed using Efficiency Analysis for determination of optimal data processing methods. Real time PCR and immunohistochemistry were used to confirm differential levels of mRNA and protein, respectively. Results: We identified a consensus of 242 and 335 genes that were differentially expressed in lungs and primary fibroblasts, respectively. Enriched function groups in SSc-PF and IPF lungs included fibrosis, insulin-like growth factor signaling and caveolin-mediated endocytosis. Functional groups shared by SSc-PAH and IPAH lungs included antigen presentation, chemokine activity, and IL-17 signaling. Conclusion: Using microarray analysis on carefully phenotyped SSc and comparator lung tissues, we demonstrated distinct molecular profiles in tissues and fibroblasts of patients with SSc-associated lung disease compared to idiopathic forms of lung disease. Unique molecular signatures were generated that are disease- (SSc) and phenotype- (PF vs PAH) specific. These signatures provide new insights into pathogenesis and potential therapeutic targets for SSc lung disease. Lung tissues were obtained from 33 patients with SSc who underwent lung transplantation. Tissues and cells from a subgroup of SSc patients with predominantly PF or PAH were compared to those from normal donors, patients with IPF, or IPAH. Microarray data was analyzed using Efficiency Analysis for determination of optimal data processing methods. Real time PCR and immunohistochemistry were used to confirm differential levels of mRNA and protein, respectively.
2013-06-21 | E-GEOD-48149 | biostudies-arrayexpress
Project description:Objective: Pulmonary complications in systemic sclerosis (SSc), including pulmonary fibrosis (PF) and pulmonary arterial hypertension (PAH), are the leading cause of mortality. We compared the molecular fingerprint of SSc lung tissues and matching primary lung fibroblasts to those of normal donors, and patients with idiopathic pulmonary fibrosis (IPF) and idiopathic pulmonary arterial hypertension (IPAH). Methods: Lung tissues were obtained from 33 patients with SSc who underwent lung transplantation. Tissues and cells from a subgroup of SSc patients with predominantly PF or PAH were compared to those from normal donors, patients with IPF, or IPAH. Microarray data was analyzed using Efficiency Analysis for determination of optimal data processing methods. Real time PCR and immunohistochemistry were used to confirm differential levels of mRNA and protein, respectively. Results: We identified a consensus of 242 and 335 genes that were differentially expressed in lungs and primary fibroblasts, respectively. Enriched function groups in SSc-PF and IPF lungs included fibrosis, insulin-like growth factor signaling and caveolin-mediated endocytosis. Functional groups shared by SSc-PAH and IPAH lungs included antigen presentation, chemokine activity, and IL-17 signaling. Conclusion: Using microarray analysis on carefully phenotyped SSc and comparator lung tissues, we demonstrated distinct molecular profiles in tissues and fibroblasts of patients with SSc-associated lung disease compared to idiopathic forms of lung disease. Unique molecular signatures were generated that are disease- (SSc) and phenotype- (PF vs PAH) specific. These signatures provide new insights into pathogenesis and potential therapeutic targets for SSc lung disease.
2013-06-21 | GSE48149 | GEO
Project description:Systemic sclerosis (SSc) is a rare but devastating disease of fibrosis impacting the dermis and multiple organ systems. The prevalence ranges from 4 to 489 cases per million individuals with ten year mortality rates reported around 18 percent. Survival is related to the extent of skin involvement, yet the precise mechanisms driving skin fibrosis in SSc remain unknown. In this study, we analyzed the shared and unique transcriptomic profiles of SSc and normal keratinocytes.
2018-03-21 | GSE81072 | GEO
Project description:Systemic sclerosis (SSc) is an autoimmune disease characterized by clinical heterogeneity, multi-organ involvement, and complex genetic risk. Here, we report the first multi-tissue meta-analysis of ten independent SSc gene expression datasets. We identify a common immune-fibrotic expression axis across all tissues that is associated with the most severe disease phenotypes. The coexpression patterns conserved across tissues and phenotypes were used to query functional genomic networks, which allowed us to identify common and tissue-specific disease drivers. We find evidence of pro-fibrotic macrophages (MØs) in SSc end-target organs. Prominent genes in the skin functional genomic network are associated with SSc genetic risk and are modulated by immunosuppressive treatment in clinical improvers. These data suggest the interactions between T lymphocytes and MØs are a critical driver of disease and implicate MØs as central to SSc pathogenesis. In total, this study presents a mechanism for fibrosis in SSc end-target tissues, a set of putative therapeutic targets for modulating SSc, and a framework for multi-tissue functional genomic studies of complex human disease.
2017-01-01 | GSE76806 | GEO
Project description:Background. The etiology and reasons underlying the ethnic disparities in systemic sclerosis (SSc) remain unknown. African-Americans (AA) are disproportionally affected by SSc, yet dramatically underrepresented in research. The role of DNA methylation in disease risk remains unclear. This analysis was conducted to comprehensive identify differentially methylated loci associated with SSc in AA. Methods. Genomic DNA was isolated from cultured dermal fibroblasts isolated from 15 AA SSc cases and 15 AA controls. All patients met the 2013 ACR/EULAR classification criteria for SSc, most (93%) presenting with diffuse cutaneous SSc. DNA methylation patterns were profiled through reduced representation bisulfite sequencing (RRBS). Alignment and methylation calling were performed using Bismarck v0.16.3 and the GRCh37/hg19 reference genome. Data was filtered, normalized, and analyzed with RnBeads v1.6.1. Differential methylation analysis was conducted on CpG, promoter, gene and system level. Results. We generated DNA methylation data for over 5 million CpGs in each sample and between 10x to 40x coverage in CpGs sites. Using the Combined Score approach implemented in RnBeads, a total of 9 CpG islands, 17 genes and 11 promoters showed significant differential methylation levels between cases and controls at the gene-level. The top differentially methylated genes constitute mostly non-coding RNA genes (42%), followed by pseudogenes (27%), then protein coding genes (19%). Enrichment analysis revealed that both hypo- and hypermethylated genes and their promoter regions were enriched for cell differentiation and immune-related gene ontology terms (hypermethylated regions: mesenchymal cell transition and differentiation; hypomethylated regions: type I IFN signaling). Conclusion. The observed DNA methylation differences between cases and controls support a modest role for DNA methylation differences in mediating susceptibility to SSc in AA. Instead of protein-coding, most differentially methylated genes comprise non-coding RNA genes, supporting a larger contribution of dysregulated regulatory elements to disease. While previous DNA methylation profiling analyses in European-Americans reported an enrichment of extracellular matrix and focal adhesion genes, our data supports a potentially stronger immune-driven etiology in AA.
2021-01-19 | GSE150592 | GEO
Project description:Systemic scleroderma (SSc) is an autoimmune disease which results in fibrotic production in the lung. Resultant SSC-pulmonary fibrosis is the main cause of mortality among SSc patients. From high throughput RNAi screening, we uncovered the ubiquitin E3 ligase KLHL42 as a potential pro-fibrotic mediator of TGFb-dependent fibrotic signaling in primary SSc lung fibroblasts. In this analysis, we sought to uncover putative substrates for KLHL42 by comparing SSc lung fibroblasts with control or KLHL42 siRNA prior to TGFb-treatment, lysis, and TUBE precipitation. The resultant pull-down was analyzed with LC-MS/MS.
2020-01-14 | MSV000084800 | MassIVE