Dataset Information

Differentially methylated and expressed genes in familial type 1 diabetes.

ABSTRACT: There has recently been a growing interest in examining the role of epigenetic modifications, such as DNA methylation, in the etiology of type 1 diabetes (T1D). This study aimed to delineate differences in methylation patterns between T1D-affected and healthy individuals by examining the genome-wide methylation of individuals from three Arab families from Kuwait with T1D-affected mono-/dizygotic twins and non-twinned siblings. Bisulfite sequencing of DNA from the peripheral blood of the affected and healthy individuals from each of the three families was performed. Methylation profiles of the affected individuals were compared to those of the healthy individuals Principal component analysis on the observed methylation profiling based on base-pair resolution clustered the T1D-affected twins together family-wide. The sites/regions that were differentially methylated between the T1D and healthy samples harbored 84 genes, of which 18 were known to be differentially methylated in T1D individuals compared to healthy individuals in publicly available gene expression data resources. We further validated two of the 18 genes-namely ICA1 and DRAM1 that were hypermethylated in T1D samples compared to healthy samples-for upregulation in T1D samples from an extended study cohort of familial T1D. The study confirmed that the ICA1 and DRAM1 genes are differentially expressed in T1D samples compared to healthy samples.

SUBMITTER: Dashti M

PROVIDER: S-EPMC9247163 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Differentially methylated and expressed genes in familial type 1 diabetes.

Dashti Mohammed M Nizam Rasheeba R Hebbar Prashantha P Jacob Sindhu S John Sumi Elsa SE Channanath Arshad A Al-Kandari Hessa H Thanaraj Thangavel Alphonse TA Al-Mulla Fahd F

Scientific reports 20220630 1

There has recently been a growing interest in examining the role of epigenetic modifications, such as DNA methylation, in the etiology of type 1 diabetes (T1D). This study aimed to delineate differences in methylation patterns between T1D-affected and healthy individuals by examining the genome-wide methylation of individuals from three Arab families from Kuwait with T1D-affected mono-/dizygotic twins and non-twinned siblings. Bisulfite sequencing of DNA from the peripheral blood of the affected ...[more]

PMID: 35773317

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Project description:Increasing evidence has indicated that modulation of epigenetic mechanisms, especially methylation and long-non-coding RNA (lncRNA) regulation, plays a pivotal role in the process of atherosclerosis; however, few studies focused on revealing the epigenetic-related subgroups during atherosclerotic progression using unsupervised clustering analysis. Hence, we aimed to identify the epigenetics-related differentially expressed genes associated with atherosclerosis subtypes and characterize their clinical utility in atherosclerosis. Eighty samples with expression data (GSE40231) and 49 samples with methylation data (GSE46394) from a large artery plaque were downloaded from the GEO database, and aberrantly methylated-differentially expressed (AMDE) genes were identified based on the relationship between methylation and expression. Furthermore, we conducted weighted correlation network analysis (WGCNA) and co-expression analysis to identify the core AMDE genes strongly involved in atherosclerosis. K-means clustering was used to characterize two subtypes of atherosclerosis in GSE40231, and then 29 samples were recognized as validation dataset (GSE28829). In a blood sample cohort (GSE90074), chi-square test and logistic analysis were performed to explore the clinical implication of the K-means clusters. Furthermore, significance analysis of microarrays and prediction analysis of microarrays (PAM) were applied to identify the signature AMDE genes. Moreover, the classification performance of signature AMDE gene-based classifier from PAM was validated in another blood sample cohort (GSE34822). A total of 1,569 AMDE mRNAs and eight AMDE long non-coding RNAs (lncRNAs) were identified by differential analysis. Through the WGCNA and co-expression analysis, 32 AMDE mRNAs and seven AMDE lncRNAs were identified as the core genes involved in atherosclerosis development. Functional analysis revealed that AMDE genes were strongly related to inflammation and axon guidance. In the clinical analysis, the atherosclerotic subtypes were associated with the severity of coronary artery disease and risk of adverse events. Eight genes, including PARP15, SERGEF, PDGFD, MRPL45, UBR1, STAU1, WIZ, and LSM4, were selected as the signature AMDE genes that most significantly differentiated between atherosclerotic subtypes. Ultimately, the area under the curve of signature AMDE gene-based classifier for atherosclerotic subtypes was 0.858 and 0.812 in GSE90074 and GSE34822, respectively. This study identified the AMDE genes (lncRNAs and mRNAs) that could be implemented in clinical clustering to recognize high-risk atherosclerotic patients.

Project description:Background: Methylation plays a significant role in the etiology and pathogenesis of hepatocellular carcinoma (HCC). The aim of the present study is to identify aberrantly methylated-diferentially expressed genes (DEGs) and dysregulated pathways associated with the development of HCC through integrated analysis of gene expression and methylation microarray. Method: Aberrantly methylated-DEGs were identified from gene expression microarrays (GSE62232, GSE74656) and gene methylation microarrays (GSE44909, GSE57958). Functional enrichment and pathway enrichment analyses were performed through the database of DAVID. Protein-protein interaction (PPI) network was established by STRING and visualized in Cytoscape. Subsequently, overall survival (OS) analysis of hub genes was performed by OncoLnc. Finally, we validated the expression level of CDCA5 by quantitative real-time PCR (qRT-PCR) and western blotting, and performed Immunohistochemical experiments utilizing a tissue microarray. Cell growth assay and flow cytometry were behaved to explore the function of CDCA5. Results: Aberrantly methylated-DEGs were enriched in biological process, molecular function, cellular component and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Among them, cell cycle was enriched most frequently, and some terms associated with cancer were enriched, such as p53 signaling pathway, pathways in cancers, PI3K-Akt signaling pathway and AMPK signaling pathway. After survival analysis and validation in TCGA database including methylation and gene expression status, 12 hub genes were identified. Furthermore, the expression level of new gene CDCA5 was validated in HCC cell lines and hepatic normal cell lines through qRT-PCR and western blotting. In additional, immunohistochemistry experiments revealed higher CDCA5 protein expression from HCC tumor tissues compared with paracancer tissues by tissue microarray. Finally, through loss of function, we demonstrated that CDCA5 promoted proliferation by regulating the cell cycle. Conclusions: In summary, the present study implied possible aberrantly methylated-differentially expressed genes and dysregulated pathways in HCC by bioinformatics analysis and experiments, which could be helpful in understanding the molecular mechanisms underlying the development and progression of HCC. Hub genes including CDC20, AURKB, BIRC5, RRM2, MCM2, PTTG1, CDKN2A, NEK2, CENPF, RACGAP1, GNA14 and especially the new gene CDCA5 may serve as biomarkers for diagnosis, treatment and prognosis of HCC.

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Differentially methylated and expressed genes in familial type 1 diabetes.

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Differentially methylated and expressed genes in familial type 1 diabetes.

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