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Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
Published on: June 16, 2017
[Differences in DNA methylation alterations in blood samples from patients with silicosis and coal workers'
Zitong Chen1, Xue Li1, Rangrang Su1
1National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Objective:
To explore the biological processes and regulatory mechanisms of methylation alterations in genes involved in silicosis and coal workers' pneumoconiosis(CWP).
Methods:
Differentially methylated genes(DMGs) volcano map, pheatmap package was used to construct heatmap; using sesame(SEnsible Step-wise Analysis of DNA MEthylation BeadChips) software mixed linear model for each two groups of samples were analyzed to obtain the detected differentially methylated CpG(DMC) sites, then FDR corrected to obtain the corrected P value, and screened using P<0.05 and Δβ absolute value >0.05. Gene ontology(GO) enrichment was performed on the differentially methylated gene analysis to find the biological processes in which they are mainly involved, kyoto encyclopedia of genes and genomes(KEGG) pathway analysis was used to find relevant cellular pathways that may be involved, and potential biomarkers were further identified based on the overlap of Venn diagrams and the result of unique DMGs.
Results:
The group of silicosis patients consisted of 4 males and 1 female, with an average age of(54.60±2.70) years old and an average duration of occupational hazard exposure of(12.80±8.01) years. Coal workers' pneumoconiosis patient group had 15 males and 1 female, with an average age of(74.80±8.14) years old and an average duration of occupational hazard exposure of(31.38±10.11) years. The control group consisted of 49 males and 7 females with a mean age of(64.91±12.29) years old. The differences in age(F=7.78, P<0.01), length of service(t=4.67, P<0.01), and smoking(χ~2=16.41, P<0.01) were statistically significant between the groups, and the differences in gender(χ~2=0.88, P>0.05) were not statistically significant between the groups. The result of gene sequencing showed that there were 1128 significantly different DMGs(including 720 up-regulated and 408 down-regulated DMGs) in the group of silicosis patients compared to the control group. A total of 423 significantly different DMGs were found in the group of CWP patients(including 139 up-regulated and 284 down-regulated DMGs). Compared to CWP, a total of 711 significantly different DMGs were found in the group of silicosis patients(including 440 up-regulated and 271 down-regulated DMGs). GO enrichment analysis showed that the differential genes between silicosis and CWP were associated with 276 biological processes, 45 cellular components, and 64 molecular functions. KEGG analysis revealed that the differential genes were significantly enriched in 30 signaling pathways.
Conclusion:
There are differences in the distribution of DMGs in blood samples from patients with silicosis and CWP, as well as in the involved biological processes and regulatory mechanisms.

