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Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies

Published on: May 6, 2022

Atherosclerosis prediction by microarray-based DNA methylation analysis.

Wei-da Chen^1,2, Ting Song², Qiu-Hong Cao³

¹Health Care Department, Shandong University of Traditional Chinese Medicine, Jinan, Shandong 250355, P.R. China.

Experimental and Therapeutic Medicine

|August 9, 2020

Summary

This summary is machine-generated.

This study identified 971 differential DNA methylation markers in atherosclerosis patients. These DNA methylation markers show promise for the early diagnosis and treatment of atherosclerosis.

Keywords:

DNA methylation GO terms atherosclerosis pathways

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Targeted DNA Methylation Analysis by Next-generation Sequencing

Targeted DNA Methylation Analysis by Next-generation Sequencing

Published on: February 24, 2015

Area of Science:

Epigenetics
Molecular Biology
Cardiovascular Disease Research

Background:

Atherosclerosis pathogenesis requires further investigation for diagnostic markers.
DNA methylation plays a role in various diseases, but its specific role in atherosclerosis needs clarification.

Purpose of the Study:

To identify specific DNA methylation markers for diagnosing atherosclerosis.
To investigate the pathogenesis of atherosclerosis through DNA methylation analysis.

Main Methods:

Utilized Illumina Human Methylation 450 BeadChip for DNA methylation analysis.
Applied stringent filtering criteria to identify differentially methylated CpGs and genes.
Employed hierarchical clustering and heatmap visualization for data validation.
Performed Gene Ontology (GO) term and pathway enrichment analysis.

Main Results:

Identified 971 differentially methylated genes (1,458 CpGs) in atherosclerosis patients.
Confirmed the capacity of these markers to distinguish between atherosclerosis and healthy controls.
Highlighted key functional regions including cell adhesion and the PI3K-Akt signaling pathway.

Conclusions:

Atherosclerosis patients exhibit significantly altered DNA methylation patterns.
Identified DNA methylation markers hold potential for early atherosclerosis diagnosis.
These findings offer new avenues for therapeutic strategies targeting DNA methylation in atherosclerosis.