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Analysis of DNA methylation landscape reveals the roles of DNA methylation in the regulation of drug metabolizing enzymes.

Habano W, Kawamura K, Iizuka N, Terashima J, Sugai T, Ozawa S - Clin Epigenetics (2015)

Bottom Line: Moreover, tissue-specific and age-dependent expression of UDP-glucuronosyltransferase 1A splicing variants was associated with DNA methylation status of individual first exons.Some DME genes were regulated by DNA methylation, potentially resulting in inter- and intra-individual differences in drug metabolism.Analysis of DNA methylation landscape facilitated elucidation of the role of DNA methylation in the regulation of DME genes, such as mediator of inter-individual variability, guide for correct alternative splicing, and potential tumor-suppressor or housekeeper.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacodynamics and Molecular Genetics, School of Pharmacy, Iwate Medical University, 2-1-1 Nishitokuta, Yahaba-Cho, Shiwa-Gun 028-3694 Japan.

ABSTRACT

Background: Drug metabolizing enzymes (DMEs) exhibit dramatic inter- and intra-individual variability in expression and activity. However, the mechanisms determining this variability have not been fully elucidated. The aim of this study was to evaluate the biological significance of DNA methylation in the regulation of DME genes by genome-wide integrative analysis.

Results: DNA methylation and mRNA expression profiles of human tissues and hepatoma cells were examined by microarrays. The data were combined with GEO datasets of liver tissues, and integrative analysis was performed on selected DME genes. Detailed DNA methylation statuses at individual CpG sites were evaluated by DNA methylation mapping. From analysis of 20 liver tissues, highly variable DNA methylation was observed in 37 DME genes, 7 of which showed significant inverse correlations between DNA methylation and mRNA expression. In hepatoma cells, treatment with a demethylating agent resulted in upregulation of 5 DME genes, which could be explained by DNA methylation status. Interestingly, some DMEs were suggested to act as tumor-suppressor or housekeeper based on their unique DNA methylation features. Moreover, tissue-specific and age-dependent expression of UDP-glucuronosyltransferase 1A splicing variants was associated with DNA methylation status of individual first exons.

Conclusions: Some DME genes were regulated by DNA methylation, potentially resulting in inter- and intra-individual differences in drug metabolism. Analysis of DNA methylation landscape facilitated elucidation of the role of DNA methylation in the regulation of DME genes, such as mediator of inter-individual variability, guide for correct alternative splicing, and potential tumor-suppressor or housekeeper.

No MeSH data available.


Related in: MedlinePlus

Distribution of maximum βR values of the DME and control genes. The maximum βR values of the eight control genes colored in red were relatively low (≤0.296). We defined highly variable DNA methylation status as a βR value of more than 0.296. The βR values of representative DME genes are also shown in the histogram. ACTB actin, beta, B2M β2 microglobulin, BMP4 bone morphogenetic protein 4, GAPDH glyceraldehyde-3-phosphate dehydrogenase, IGFBP3 insulin-like growth factor binding protein 3, MGMT O-6-methylguanine-DNA methyltransferase, MLH1 mutL homologue 1, TBP TATA box-binding protein
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Fig3: Distribution of maximum βR values of the DME and control genes. The maximum βR values of the eight control genes colored in red were relatively low (≤0.296). We defined highly variable DNA methylation status as a βR value of more than 0.296. The βR values of representative DME genes are also shown in the histogram. ACTB actin, beta, B2M β2 microglobulin, BMP4 bone morphogenetic protein 4, GAPDH glyceraldehyde-3-phosphate dehydrogenase, IGFBP3 insulin-like growth factor binding protein 3, MGMT O-6-methylguanine-DNA methyltransferase, MLH1 mutL homologue 1, TBP TATA box-binding protein

Mentions: We examined DNA methylation profiles of two adult liver tissues (NLA and NL2), fetal liver tissue (NLF), adult small intestinal tissue (NSI), and three hepatoma cell lines (HepG2, HuH7, and JHH1) by HumanMethylation450 Bead Chip. These data were combined with GEO-registered datasets of 18 healthy adult liver tissues. The levels of DNA methylation for more than 480,000 CpG sites were determined as the β values (0 < β < 1). Cluster analysis demonstrated that methylation levels of DME genes, including 55 CYP genes and 62 phase II DME genes, differed markedly among distinct tissue groups. The representative profiles of six CYPs (CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, and CYP3A4), and two controls (ACTB and BMP4) were shown in Fig. 1. Although the 20 adult liver tissues were derived from two different race populations (2 Chinese and 18 German), they exhibited similar DNA methylation profiles. However, some DME genes such as CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 showed relatively variable methylation statuses, compared to CYP1B1 and two control genes. To examine the landscape of DNA methylation in more detail, we performed the DNA methylation mapping of individual DME genes (Fig. 2 and Additional file 1: Figure S1). For each CpG site, the range of variation was defined as a βR value, which was calculated from the difference between the highest and lowest β values among the 20 livers. Next, for all CpG sites located in the 5′ regulatory region (defined as TSS1500, TSS200, or 5′UTR in the array platform), the maximum βR value was used for estimation of the degree of inter-individual differences in DNA methylation. The distribution of maximum βR values (degrees of variation) of the genes is shown as a histogram in Fig. 3. We expected that the control genes would show the least variation because the expression of these genes should be tightly regulated by DNA methylation on their promoter CpG islands, as reported by Edgar et al. [19]. Therefore, these genes were used as negative controls of inter-individual variation. We finally identified 37 (32 %) DME genes with significantly variable DNA methylation statuses, for which the maximum βR values were more than those of all eight control genes (ACTB, B2M, GAPDH, TBP, BMP4, IGFBP3, MLH1, and MGMT) (maximum βR > 0.296).Fig. 1


Analysis of DNA methylation landscape reveals the roles of DNA methylation in the regulation of drug metabolizing enzymes.

Habano W, Kawamura K, Iizuka N, Terashima J, Sugai T, Ozawa S - Clin Epigenetics (2015)

Distribution of maximum βR values of the DME and control genes. The maximum βR values of the eight control genes colored in red were relatively low (≤0.296). We defined highly variable DNA methylation status as a βR value of more than 0.296. The βR values of representative DME genes are also shown in the histogram. ACTB actin, beta, B2M β2 microglobulin, BMP4 bone morphogenetic protein 4, GAPDH glyceraldehyde-3-phosphate dehydrogenase, IGFBP3 insulin-like growth factor binding protein 3, MGMT O-6-methylguanine-DNA methyltransferase, MLH1 mutL homologue 1, TBP TATA box-binding protein
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
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getmorefigures.php?uid=PMC4587720&req=5

Fig3: Distribution of maximum βR values of the DME and control genes. The maximum βR values of the eight control genes colored in red were relatively low (≤0.296). We defined highly variable DNA methylation status as a βR value of more than 0.296. The βR values of representative DME genes are also shown in the histogram. ACTB actin, beta, B2M β2 microglobulin, BMP4 bone morphogenetic protein 4, GAPDH glyceraldehyde-3-phosphate dehydrogenase, IGFBP3 insulin-like growth factor binding protein 3, MGMT O-6-methylguanine-DNA methyltransferase, MLH1 mutL homologue 1, TBP TATA box-binding protein
Mentions: We examined DNA methylation profiles of two adult liver tissues (NLA and NL2), fetal liver tissue (NLF), adult small intestinal tissue (NSI), and three hepatoma cell lines (HepG2, HuH7, and JHH1) by HumanMethylation450 Bead Chip. These data were combined with GEO-registered datasets of 18 healthy adult liver tissues. The levels of DNA methylation for more than 480,000 CpG sites were determined as the β values (0 < β < 1). Cluster analysis demonstrated that methylation levels of DME genes, including 55 CYP genes and 62 phase II DME genes, differed markedly among distinct tissue groups. The representative profiles of six CYPs (CYP1A2, CYP1B1, CYP2C9, CYP2C19, CYP2D6, and CYP3A4), and two controls (ACTB and BMP4) were shown in Fig. 1. Although the 20 adult liver tissues were derived from two different race populations (2 Chinese and 18 German), they exhibited similar DNA methylation profiles. However, some DME genes such as CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 showed relatively variable methylation statuses, compared to CYP1B1 and two control genes. To examine the landscape of DNA methylation in more detail, we performed the DNA methylation mapping of individual DME genes (Fig. 2 and Additional file 1: Figure S1). For each CpG site, the range of variation was defined as a βR value, which was calculated from the difference between the highest and lowest β values among the 20 livers. Next, for all CpG sites located in the 5′ regulatory region (defined as TSS1500, TSS200, or 5′UTR in the array platform), the maximum βR value was used for estimation of the degree of inter-individual differences in DNA methylation. The distribution of maximum βR values (degrees of variation) of the genes is shown as a histogram in Fig. 3. We expected that the control genes would show the least variation because the expression of these genes should be tightly regulated by DNA methylation on their promoter CpG islands, as reported by Edgar et al. [19]. Therefore, these genes were used as negative controls of inter-individual variation. We finally identified 37 (32 %) DME genes with significantly variable DNA methylation statuses, for which the maximum βR values were more than those of all eight control genes (ACTB, B2M, GAPDH, TBP, BMP4, IGFBP3, MLH1, and MGMT) (maximum βR > 0.296).Fig. 1

Bottom Line: Moreover, tissue-specific and age-dependent expression of UDP-glucuronosyltransferase 1A splicing variants was associated with DNA methylation status of individual first exons.Some DME genes were regulated by DNA methylation, potentially resulting in inter- and intra-individual differences in drug metabolism.Analysis of DNA methylation landscape facilitated elucidation of the role of DNA methylation in the regulation of DME genes, such as mediator of inter-individual variability, guide for correct alternative splicing, and potential tumor-suppressor or housekeeper.

View Article: PubMed Central - PubMed

Affiliation: Department of Pharmacodynamics and Molecular Genetics, School of Pharmacy, Iwate Medical University, 2-1-1 Nishitokuta, Yahaba-Cho, Shiwa-Gun 028-3694 Japan.

ABSTRACT

Background: Drug metabolizing enzymes (DMEs) exhibit dramatic inter- and intra-individual variability in expression and activity. However, the mechanisms determining this variability have not been fully elucidated. The aim of this study was to evaluate the biological significance of DNA methylation in the regulation of DME genes by genome-wide integrative analysis.

Results: DNA methylation and mRNA expression profiles of human tissues and hepatoma cells were examined by microarrays. The data were combined with GEO datasets of liver tissues, and integrative analysis was performed on selected DME genes. Detailed DNA methylation statuses at individual CpG sites were evaluated by DNA methylation mapping. From analysis of 20 liver tissues, highly variable DNA methylation was observed in 37 DME genes, 7 of which showed significant inverse correlations between DNA methylation and mRNA expression. In hepatoma cells, treatment with a demethylating agent resulted in upregulation of 5 DME genes, which could be explained by DNA methylation status. Interestingly, some DMEs were suggested to act as tumor-suppressor or housekeeper based on their unique DNA methylation features. Moreover, tissue-specific and age-dependent expression of UDP-glucuronosyltransferase 1A splicing variants was associated with DNA methylation status of individual first exons.

Conclusions: Some DME genes were regulated by DNA methylation, potentially resulting in inter- and intra-individual differences in drug metabolism. Analysis of DNA methylation landscape facilitated elucidation of the role of DNA methylation in the regulation of DME genes, such as mediator of inter-individual variability, guide for correct alternative splicing, and potential tumor-suppressor or housekeeper.

No MeSH data available.


Related in: MedlinePlus