Dataset Information

An integrative module analysis of DNA methylation landscape in aging.

ABSTRACT: To investigate the molecular mechanism of aging, the combination of module analysis and DNA methylation data was used to detect dynamically controlled modules for aging. Multiple differential expression networks (DENs) were constructed based on the microarray profiles across different aging groups (<70 years, 70-80 years, and >80 years). Next, a module-based approach was utilized to extract the common candidate modules across all age groups. We used Module Connectivity Dynamic Score (MCDS) to quantify the connectivity change of the common modules among the different age groups. Functional analyses were implemented for the genes in the common modules to further identify the significant biological processes. A total of two DENs were constructed. Overall 657 informative genes were screened out. When false discovery rate (FDR) was set as 0.05, we found that 148 modules were significant. Only 1 significant 2-differential modules (DMs) (module 493) with dynamic changes was discovered. Significantly, the genes in the module 493 participated in 7 significant pathways, including pentose phosphate pathway, carbon metabolism, and citrate cycle (TCA cycle). In conclusion, pathway functions [pentose phosphate pathway, carbon metabolism, citrate cycle (TCA cycle), chromosomal instability, ateroid biosynthesis, PPAR signaling pathway, and immune response] may serve as potential therapeutic targets in aging.

SUBMITTER: Li G

PROVIDER: S-EPMC6447821 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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An integrative module analysis of DNA methylation landscape in aging.

Li Gang G Liu Ke-Yu KY Qiu Zhong-Peng ZP

Experimental and therapeutic medicine 20190301 5

To investigate the molecular mechanism of aging, the combination of module analysis and DNA methylation data was used to detect dynamically controlled modules for aging. Multiple differential expression networks (DENs) were constructed based on the microarray profiles across different aging groups (<70 years, 70-80 years, and >80 years). Next, a module-based approach was utilized to extract the common candidate modules across all age groups. We used Module Connectivity Dynamic Score (MCDS) to qu ...[more]

PMID: 30988719

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Project description:Pancreatic adenocarcinoma (PAAD) is a painful and fatal disease that undoubtedly remains a health care priority and offers significant therapeutic challenges. The significance of epigenetic modifications, including DNA methylation in tumor development, has gained the attention of researchers. Identifying DNA methylation-driven genes and investigating the mechanisms underlying the tumorigenesis of PAAD are of substantial importance for developing methods of physiological evaluation, treatment planning and prognostic prediction for PAAD. In the present study, a comprehensive analysis of DNA methylation and gene expression data from 188 clinical samples was performed to identify DNA methylation-driven genes in PAAD. In addition, the diagnostic and prognostic value of DNA methylation-driven genes was evaluated using receiver operating characteristic curve, survival and recurrence analyses. A total of 7 DNA methylation-driven genes, namely zinc finger protein 208 (ZNF208), eomesodermin (EOMES), prostaglandin D2 receptor (PTGDR), chromosome 12 open reading frame 42 (C12orf42), integrin subunit ? 4 (ITGA4), dedicator of cytokinesis 8 and protein phosphatase 1 regulatory inhibitor subunit 14D (PPP1R14D), were identified. All of them may be used to diagnose PAAD with excellent specificity and sensitivity (area under curve, >0.8). Of the 7 DNA methylation-driven genes, 6 were significantly associated with overall survival (OS) and recurrence-free survival (RFS) P<0.05). Among them, ZNF208, EOMES, PTGDR, C12orf42 and ITGA4 were significantly negatively associated with the OS rate and positively associated with the recurrence rate, while PPP1R14D was significantly positively associated with the OS rate and negatively associated with the recurrence rate. The present study provides novel insight into the epigenetic alterations associated with the occurrence and progression of PAAD, thereby increasing the mechanistic understanding of this disease, offering potential novel molecular biomarkers and contributing to the development of therapeutic targets for PAAD.

Dataset Information

An integrative module analysis of DNA methylation landscape in aging.

Publications

An integrative module analysis of DNA methylation landscape in aging.

Similar Datasets

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