Purkinje Cell Protein 4 Expression Is Associated With DNA Methylation Status in Aldosterone-Producing Adenoma

Purkinje Cell Protein 4 Expression Is Associated With DNA Methylation Status in... Abstract Context Aldosterone production is stimulated by activation of calcium signaling in aldosterone-producing adenomas (APAs), and epigenetic factors such as DNA methylation may be associated with the expression of genes involved in aldosterone regulation. Objective Our aim was to investigate the DNA methylation of genes related to calcium signaling cascades in APAs and the association of mutations in genes linked to APAs with DNA methylation levels. Methods Nonfunctioning adrenocortical adenoma (n = 12) and APA (n = 35) samples were analyzed. The KCNJ5 T158A mutation was introduced into human adrenocortical cell lines (HAC15 cells) using lentiviral delivery. DNA methylation array analysis was conducted using adrenal tumor samples and HAC15 cells. Results The Purkinje cell protein 4 (PCP4) gene was one of the most hypomethylated in APAs. DNA methylation levels in two sites of PCP4 showed a significant inverse correlation with messenger RNA expression in adrenal tumors. Bioinformatics and multiple regression analysis revealed that CCAAT/enhancer binding protein alpha (CEBPA) may bind to the methylation site of the PCP4 promoter. According to chromatin immunoprecipitation assay, CEBPA was bound to the PCP4 hypomethylated region by chromatin immunoprecipitation assay. There were no significant differences in PCP4 methylation levels among APA genotypes. Moreover, KCNJ5 T158A did not influence PCP4 methylation levels in HAC15 cells. Conclusions We showed that the PCP4 promoter was one of the most hypomethylated in APAs and that PCP4 transcription may be associated with demethylation as well as with CEBPA in APAs. KCNJ5 mutations known to result in aldosterone overproduction were not related to PCP4 methylation in either clinical or in vitro studies. Primary aldosteronism (PA) is a major cause of secondary hypertension and is characterized by excessive and autonomous production of aldosterone (1). Patients with PA are at greater risk of cardiovascular and cerebrovascular diseases than are those with essential hypertension who have similar blood pressure and risk profiles (2, 3). PA has two main subtypes, aldosterone-producing adenoma (APA) and bilateral idiopathic hyperaldosteronism (1). The elevated aldosterone production in APAs is attributable mainly to upregulation of aldosterone synthase (CYP11B2), which catalyzes the final steps of aldosterone biosynthesis (4, 5). In APAs, CYP11B2 transcription is induced by the activation of intracellular calcium signaling (6). Recent studies demonstrated that 50% to 80% of APAs harbored somatic mutations in KCNJ5, ATP1A1, ATP2B3, or CACNA1D and that aldosterone production was affected by mutations that increase intracellular Ca2+ concentration and activate the calcium signaling cascade (7–10). Proteins belonging to the calmodulin family play a pivotal role in the transport of intracellular calcium from the cytoplasm to the nucleus in adrenal cells (11, 12). Epigenetic regulation, including DNA methylation and intracellular signaling cascades, is important for tumor progression, cell survival, DNA damage repair, and hormone secretion because it influences gene expression (13, 14). In the mammalian genome, 5′-cytosine-guanine-3′ (CpG) dinucleotides are preferentially methylated or demethylated by DNA methyltransferase or demethyltransferase enzymes, respectively (13). Hypomethylation of CpG islands in the promoter region is associated with gene expression primarily by facilitating the binding of transcription factors (13). We recently reported that CYP11B2 hypomethylation was associated with CYP11B2 expression in APAs (15). In addition, DNA methylation is actively involved in fetal adrenal development and adrenocortical cancer progression via the repression or activation of genes involved in differentiation and proliferation (16, 17). Taken together, these facts suggest that proteins belonging to the calmodulin family are regulated by DNA methylation as well as by intracellular signaling cascades in APAs. In this study, we examined the DNA methylation levels of calmodulin-related factors in APAs using a DNA methylation array. Our results showed that the Purkinje cell protein 4 (PCP4) gene was one of the most hypomethylated genes in APAs. PCP4 is known to be overexpressed in APAs, and it has been suggested that PCP4 stimulates CYP11B2 expression and aldosterone production in human adrenocortical cells (18). Therefore, we hypothesized that PCP4 transcription is associated with DNA methylation or demethylation in APAs. The objectives of our study were to clarify the relationship between PCP4 methylation and messenger RNA (mRNA) expression in adrenal tumors, including APA, and to identify transcription factors that may also be involved in PCP4 expression. In addition, we examined the effects of the APA genotype on PCP4 DNA methylation in clinical samples and an in vitro analysis. Methods Patients and tissue collection The diagnosis and subtype diagnosis of PA were performed according to guidelines from The Japan Endocrine Society (19) as previously described (20). Nonfunctioning adrenocortical adenomas (NFs) were diagnosed by the radiological detection of low augmentation signals from computed tomography or magnetic resonance imaging scans and from endocrinological data showing an absence of excess cortisol or aldosterone as previously reported (21). The clinical characteristics of patients are shown in Supplemental Table 1 and in previous reports (15, 22). Forty-seven adrenal tumors (12 NFs and 35 APAs) were obtained by surgical resection and stored at −80°C until use (15). The pathological diagnosis of APA was confirmed by detecting the expression of CYP11B2 by immunohistochemistry and by quantitative polymerase chain reaction (qPCR) assays as previously reported (5). Our study was approved by the ethics committee of Hiroshima University, and written informed consent was obtained from all patients. DNA extraction and genotyping The DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) was used for extraction of genomic DNA from adrenal tissues, peripheral leukocyte DNA, and human adrenocortical cell lines (HAC15 cells). Gene mutation analyses of KCNJ5, ATP1A1, ATP2B3, and CACNA1D were performed using a polymerase chain reaction‒based direct sequencing method as previously described (23). DNA methylation analysis DNA methylation analysis was performed as previously reported (15). Briefly, bisulfite conversion and methylation analysis were performed using the Infinium HumanMethylation450 BeadChip Kit (Illumina, San Diego, CA) according to the manufacturer’s instructions. BeadChip can identify more than 485,000 methylation sites per sample at single-nucleotide resolution and can recover up to 99% of RefSeq genes and 96% of CpG islands (24). Methylation levels of each CpG residue were presented as β values, which were derived from the signal intensity of methylated and unmethylated sites. Average β values were expressed as 0 to 1, representing completely unmethylated to completely methylated values, respectively. RNA extraction and qPCR assays Total RNA extraction and complementary DNA preparation were performed with the RNeasy Mini Kit (Qiagen, Hilden, Germany) and PrimeScript RT Master Mix (Takara Bio Inc., Shiga, Japan), respectively, as previously described (23). qPCR was performed with SYBR Green fluorescent dye using the 7500 Fast PCR Machine (Applied Biosystems, Waltham, MA). qPCR primers for PCP4, breast cancer gene 1 (BRCA1), CCAAT/enhancer binding protein alpha (CEBPA), CCAAT/enhancer binding protein beta (CEBPB), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) are shown in Supplemental Table 2. Gene expression levels were expressed as arbitrary units normalized against GAPDH mRNA expression. Cell culture and lentiviral infection HAC15 cells were kindly provided by W.E. Rainey (University of Michigan) and were cultured as previously reported (10). Plasmid pLX303 and pLX303-KCNJ5-T158A were prepared, and lentivirus production and infection in HAC15 cells were performed as previously reported (10). Chromatin immunoprecipitation assay Chromatin immunoprecipitation (ChIP) assays were performed with the SimpleChIP® Plus Enzymatic Chromatin IP Kit (#9005; Cell Signaling Technology, Danvers, MA) following the manufacture’s recommended protocol. Briefly, HAC15 cells were cross-linked with 1% formaldehyde, and they were digested with a supplied nuclease at 37°C for 20 minutes. The generated DNA was confirmed by agarose gel electrophoresis. Chromatin preparations were incubated with normal rabbit immunoglobulin G (supplied in the SimpleChIP® Plus Enzymatic Chromatin IP Kit) or C/EBPα antibody (sc-61; Santa Cruz Biotechnology, Heidelberg, Germany), and then they were incubated with supplied magnetic beads. Bound complexes were eluted from the beads, and cross-link was reversed at 65°C for 2 hours. Immunoprecipitated materials were analyzed by qPCR assay. The oligonucleotide primers of set A for the “c” region were 5′-ACC TGA AAG TGC GTG AGC GG-3′ and 5′-TTT CAA AGA TCA CAG GG-3′. The primers of set B for the “c” region were 5′-ACC TGA AAG TGC GTG AGC GG-3′ and 5′-CTG GGC AGC AGA ACG AGA CC-3′. Relative ChIP signals were calculated by a fold enrichment method. Statistical analysis Quantitative data are presented as means and standard deviations. The heat map was depicted using the R software package (University of Auckland), and subsequent analyses were performed using SPSS for Windows (release 24.0; SPSS Inc., Chicago, IL). Because PCP4 mRNA levels did not fit a normal distribution, they were converted to log-transformed data for analysis. Simple and multiple regression analyses were conducted to evaluate the relationships between PCP4 mRNA expression levels and methylation values. Values of statistical significance among genotypes were determined by one-way analysis of variance. Differences in the methylation levels between the HAC15 control and the KCNJ5 mutants were analyzed by the t test. The differences were considered to be significant at P < 0.05. Results DNA methylation analysis of genes involved in calmodulin binding For DNA methylation analysis, 180 calmodulin binding factors were extracted from the AmiGO gene ontologies Web site (http://amigo.geneontology.org/amigo), and 1820 methylation sites located in the promoter or 5′ untranslated region of these factors were targeted. The heat map of DNA methylation levels for 1820 methylation sites is depicted in Fig. 1. The most hypomethylated gene in APAs was tight junction protein 1 (TJP1), which may be involved in signal transduction at cell-cell junctions. According to our microarray data, there were no differences in TJP1 expression between NFs and APAs, and angiotensin II did not stimulate TJP1 expression in HAC15 cells (data not shown). The second most hypomethylated gene in APAs was PCP4. PCP4 was reported to be overexpressed in APAs, and it is thought to function as an important factor in calcium signaling (18). PCP4 gene expression levels in APAs were significantly higher than those in NFs (Supplemental Fig. 1), which is consistent with results in a previous study (18). Thus, we focused on the relationship between PCP4 DNA methylation and PCP4 mRNA expression levels. Figure 1. View largeDownload slide Heat map generated from the HumanMethylation450 BeadChip array analysis of NFs (n = 12) and APAs (n = 35). Methylation sites (1820) of 180 calmodulin binding factors are included. Figure 1. View largeDownload slide Heat map generated from the HumanMethylation450 BeadChip array analysis of NFs (n = 12) and APAs (n = 35). Methylation sites (1820) of 180 calmodulin binding factors are included. The association between PCP4 methylation and PCP4 mRNA expression Six presumed methylation sites of PCP4 genes were detected by DNA methylation array, and five of these six sites were located in the promoter region (Supplemental Fig. 2). First, the relationship between PCP4 methylation and PCP4 mRNA expression levels was analyzed by simple regression analysis. Two DNA methylations indicated as “c” and “f” showed a significant inverse correlation with PCP4 gene expression in the adrenal tumor (Fig. 2C and 2F), whereas the other sites showed no correlation with mRNA levels. Figure 2. View large Download slide Relationship between PCP4 methylation and PCP4 mRNA levels in adenomas. (A‒F) Relationships of PCP4 mRNA levels with each PCP4 methylation status are shown. APAs and NFs are indicated by closed and open circles, respectively. Each lowercase character indicates the methylation site of PCP4, which is shown in Supplemental Fig. 2. Figure 2. View large Download slide Relationship between PCP4 methylation and PCP4 mRNA levels in adenomas. (A‒F) Relationships of PCP4 mRNA levels with each PCP4 methylation status are shown. APAs and NFs are indicated by closed and open circles, respectively. Each lowercase character indicates the methylation site of PCP4, which is shown in Supplemental Fig. 2. The potential transcription factors in a PCP4 promoter methylation site Because the “c” region but not the “f” region is located in the PCP4 promoter (Supplemental Fig. 2), we next focused on the relationship between the “c” region in the PCP4 promoter and transcription factors. Potential transcription factors such as BRCA1, CEBPA, and CEBPB that can bind to PCP4 promoter via the “c” region were suggested by bioinformatics analysis using the JASPAR database (http://jaspar.binf.ku.dk/; Supplemental Fig. 3). There were no differences in BRCA1, CEBPA, and CEBPB expression levels between NFs and APAs (Supplemental Fig. 1B‒1D). We applied multiple regression analysis to investigate the combined effect of DNA methylation and transcription factors on PCP4 expression. This model revealed that CEBPA as well as DNA methylation of the “c” region was a significant independent variable for PCP4 expression in adrenal tumor cells (Fig. 3). Figure 3. View largeDownload slide Multiple regression analysis performed to determine the effect of DNA methylation and candidate transcription factors on PCP4 expression. Unstandardized regression coefficients, 95% confidence intervals, and P values were determined using multivariate regression analysis. Figure 3. View largeDownload slide Multiple regression analysis performed to determine the effect of DNA methylation and candidate transcription factors on PCP4 expression. Unstandardized regression coefficients, 95% confidence intervals, and P values were determined using multivariate regression analysis. We investigated the association between the PCP4 promoter and CEBPA using the ChIP-qPCR method. The PCP4 promoter was detected by 2.4- to 3.0-fold in samples using the CEBPA antibody compared with those using control immunoglobulin G (Fig. 4). Therefore, CEBPA is likely to bind to the “c” region of the PCP4 promoter. Figure 4. View largeDownload slide ChIP signal of the PCP4 promoter region by ChIP-qPCR assay using a CEBPA antibody. HAC15 cells were cross-linked with 1% formaldehyde and digested with a nuclease. Chromatin preparation were incubated with normal rabbit immunoglobulin G (IgG) or C/EBPα antibody, and then they were incubated with magnetic beads. Immunoprecipitated materials were analyzed by qPCR assay using 2 types of primers denoted as set A and set B. Relative amount of ChiP-qPCR using IgG is expressed as 1.0 and horizontal dot line. The detection of PCP4 promoter by set A and set B were 3.0 ± 0.7- and 2.4 ± 0.6-fold in samples using CEBPA antibody compared to in those using control IgG, respectively. Figure 4. View largeDownload slide ChIP signal of the PCP4 promoter region by ChIP-qPCR assay using a CEBPA antibody. HAC15 cells were cross-linked with 1% formaldehyde and digested with a nuclease. Chromatin preparation were incubated with normal rabbit immunoglobulin G (IgG) or C/EBPα antibody, and then they were incubated with magnetic beads. Immunoprecipitated materials were analyzed by qPCR assay using 2 types of primers denoted as set A and set B. Relative amount of ChiP-qPCR using IgG is expressed as 1.0 and horizontal dot line. The detection of PCP4 promoter by set A and set B were 3.0 ± 0.7- and 2.4 ± 0.6-fold in samples using CEBPA antibody compared to in those using control IgG, respectively. The relationship between APA genotype and DNA methylation levels We compared DNA methylation values among APAs with different gene mutations. There were no differences in PCP4 methylation levels among APA genotypes, including wild-type, KCNJ5 mutant, and ATP1A1 mutant (Table 1). Table 1. Differences in PCP4 DNA Methylation Values Among Somatic Mutations in APAs   Methylation Rate (β Value)  P Value  Methylation Site  KCNJ5 Mutation (n = 21)  ATP1A1 Mutation (n = 5)  No Mutation (n = 9)  a  0.841 ± 0.020  0.870 ± 0.063  0.817 ± 0.086  0.188  b  0.414 ± 0.079  0.340 ± 0.144  0.382 ± 0.131  0.340  c  0.259 ± 0.095  0.209 ± 0.101  0.189 ± 0.130  0.226  d  0.058 ± 0.032  0.034 ± 0.021  0.042 ± 0.026  0.217  e  0.067 ± 0.017  0.044 ± 0.017  0.048 ± 0.018  0.063  f  0.327 ± 0.095  0.298 ± 0.138  0.274 ± 0.129  0.481    Methylation Rate (β Value)  P Value  Methylation Site  KCNJ5 Mutation (n = 21)  ATP1A1 Mutation (n = 5)  No Mutation (n = 9)  a  0.841 ± 0.020  0.870 ± 0.063  0.817 ± 0.086  0.188  b  0.414 ± 0.079  0.340 ± 0.144  0.382 ± 0.131  0.340  c  0.259 ± 0.095  0.209 ± 0.101  0.189 ± 0.130  0.226  d  0.058 ± 0.032  0.034 ± 0.021  0.042 ± 0.026  0.217  e  0.067 ± 0.017  0.044 ± 0.017  0.048 ± 0.018  0.063  f  0.327 ± 0.095  0.298 ± 0.138  0.274 ± 0.129  0.481  Data are expressed as mean ± standard deviation, and P values were determined by analysis of variance. View Large We introduced the KCNJ5 mutation (KCNJ5 T158A) into HAC15 cells using lentiviral delivery. Transduction of HAC15 cells with lentiviruses harboring the KCNJ5-T158A mutation increased aldosterone levels 5.4-fold in media compared with control HAC15 cells (data not shown). There were no differences in PCP4 DNA methylation between control and KCNJ5 mutant cells (Table 2). Table 2. Differences in PCP4 Methylation Values Between Control and KCNJ5 Mutation in HAC15 Cells   Methylation Rate (β Value)  Fold Change
(KCNJ5/Control)  P Value  Methylation Site  Control  KCNJ5 T158A  a  0.877 ± 0.009  0.893 ± 0.004  1.018  0.074  b  0.700 ± 0.009  0.731 ± 0.025  1.044  0.150  c  0.362 ± 0.027  0.378 ± 0.023  1.043  0.500  d  0.034 ± 0.011  0.032 ± 0.009  0.964  0.865  e  0.058 ± 0.001  0.056 ± 0.005  0.960  0.469  f  0.079 ± 0.009  0.079 ± 0.009  0.994  0.949    Methylation Rate (β Value)  Fold Change
(KCNJ5/Control)  P Value  Methylation Site  Control  KCNJ5 T158A  a  0.877 ± 0.009  0.893 ± 0.004  1.018  0.074  b  0.700 ± 0.009  0.731 ± 0.025  1.044  0.150  c  0.362 ± 0.027  0.378 ± 0.023  1.043  0.500  d  0.034 ± 0.011  0.032 ± 0.009  0.964  0.865  e  0.058 ± 0.001  0.056 ± 0.005  0.960  0.469  f  0.079 ± 0.009  0.079 ± 0.009  0.994  0.949  DNA methylation rate was assessed in HAC15 cells infected with control (n = 3) or KCNJ5 T158A lentiviruses (n = 3). View Large Discussion We demonstrated that among the genes encoding calmodulin binding factors, PCP4 was one of the most hypomethylated in APAs and that methylation of its promoter was inversely correlated with its mRNA level. The transcription factor CEBPA, which binds to this region, was a significant independent variable for PCP4 expression. ChIP-qPCR analysis revealed that the hypomethylated region of the PCP4 promoter binds to CEBPA in HAC15 cells. Somatic mutations associated with APAs, such as KCNJ5 and ATP1A1, did not regulate PCP4 DNA methylation; in addition, the KCNJ5 mutants had no effect on PCP4 methylation in vitro. Our results showed that among the genes encoding calmodulin binding factors, PCP4 was one of the most strongly demethylated, and there was an inverse correlation between PCP4 methylation and mRNA expression (Fig. 2). A previous study suggested that APAs have higher PCP4 levels than normal adrenals, cortisol-producing adenomas, and tissues from idiopathic hyperaldosteronism; remarkably, PCP4 expressions was positively correlated with CYP11B2 expression in APAs (18). Furthermore, CYP11B2 expression was stimulated by PCP4 gene modulation in human adrenocortical cells (18). Together with our results, these findings suggest that PCP4 may be associated with DNA demethylation in APAs, and this increased PCP4 expression in turn leads to CYP11B2 upregulation. We identified three candidates that bind to the “c” region of the PCP4 promoter; CEBPA, as well as PCP4 methylation, was a significant independent variable for PCP4 mRNA expression. In general, demethylation of promoter regions typically acts to activate gene transcription by facilitating the binding of transcription factors (13); thus, transcription levels are usually determined by DNA methylation levels in the promoter and the expression levels of transcription factors. Bioinformatic and multiple regression analyses indicated that CEBPA may bind to the “c” region, and we demonstrated the binding of the hypomethylated region of the PCP4 promoter with CEBPA. In addition, because there was no difference in CEBPA levels between APAs and NFs, we suggest that PCP4 transcription is determined primarily by DNA methylation status in APAs. We compared PCP4 methylation levels among APA samples with different somatic mutations and found that these mutations were not associated with PCP4 methylation. Furthermore, KCNJ5 T158A mutation had no effect on PCP4 methylation levels in HAC15 cells. Although the KCNJ5 mutant stimulated aldosterone production in adrenal cells, the production was regulated by Ca2+ signaling, not by methylation of PCP4. We recently suggested that methylation of CYP11B2, which encodes the enzyme that catalyzes the final steps of aldosterone biosynthesis, was not associated with any of the studied somatic mutations (15). Therefore, aldosterone production resulting from mutant genes is most likely regulated by intracellular signaling, including Ca2+ signaling, and not by DNA methylation. The current study has several limitations. Because this was a cross-sectional study, we did not investigate the association of methylation and demethylation with causality of APAs or NFs. Use of methyltransferase or demethyltransferase agents may enable in vitro detection of DNA methylation. However, application of these methods may be problematic because these agents regulate the methylation of all genes and sites, including the genes of their own transcription factors. In addition, the regulation of transcription factors in adrenal cells influences myriad gene expression; thus, it is difficult to detect direct regulation between DNA methylation and transcription factors in an in vitro study. Further experiments using advanced methods are needed to clarify the relationship between DNA methylation and transcription factors. In conclusion, we showed that among the genes encoding calmodulin binding factors, PCP4 was one of the most hypomethylated in APAs, and its expression may be associated with DNA methylation in conjunction with the transcription factor CEBPA in APAs. In addition, we showed that KCNJ5 mutations known to drive aldosterone production had no effect on PCP4 methylation in clinical and in vitro studies. Thus, our study provides the basis for future studies addressing the role of DNA methylation and genomic alterations in the pathophysiology of APAs. Abbreviations: APA aldosterone-producing adenoma CEBPA CCAAT/enhancer binding protein alpha CEBPB CCAAT/enhancer binding protein beta ChIP chromatin immunoprecipitation CpG 5′-cytosine-guanine-3′ CYP11B2 aldosterone synthase HAC15 cell human adrenocortical cell line mRNA messenger RNA NF nonfunctioning adrenocortical adenoma PA primary aldosteronism PCP4 Purkinje cell protein 4 qPCR quantitative polymerase chain reaction TJP1 tight junction protein 1. Acknowledgments This work was carried out with the kind cooperation of the Analysis Center of Life Science, Hiroshima University. Financial Support: This study was financially supported by the Japan Society for the Promotion of Science KAKENHI Grants JP17K09883 (to K.O.) and JP17K16166 (to Y.Y.), the Okinaka Memorial Institute for Medical Research Grant (to K.O.), the SENSHIN Medical Research Foundation (to K.O.), the Japan Heart Foundation Dr. Hiroshi Irisawa & Dr. Aya Irisawa Memorial Research Grant (to K.O.), and the National Institutes of Health Grant HL27255 (to C.E.G.-S.). Disclosure Summary: The authors have nothing to disclose. References 1. Funder JW, Carey RM, Mantero F, Murad MH, Reincke M, Shibata H, Stowasser M, Young WF, Jr. The management of primary aldosteronism: case detection, diagnosis, and treatment: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab . 2016; 101( 5): 1889– 1916. Google Scholar CrossRef Search ADS PubMed  2. Milliez P, Girerd X, Plouin PF, Blacher J, Safar ME, Mourad JJ. 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Google Scholar CrossRef Search ADS PubMed  Copyright © 2018 Endocrine Society http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Clinical Endocrinology and Metabolism Oxford University Press

Purkinje Cell Protein 4 Expression Is Associated With DNA Methylation Status in Aldosterone-Producing Adenoma

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Endocrine Society
Copyright
Copyright © 2018 Endocrine Society
ISSN
0021-972X
eISSN
1945-7197
D.O.I.
10.1210/jc.2017-01996
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Abstract

Abstract Context Aldosterone production is stimulated by activation of calcium signaling in aldosterone-producing adenomas (APAs), and epigenetic factors such as DNA methylation may be associated with the expression of genes involved in aldosterone regulation. Objective Our aim was to investigate the DNA methylation of genes related to calcium signaling cascades in APAs and the association of mutations in genes linked to APAs with DNA methylation levels. Methods Nonfunctioning adrenocortical adenoma (n = 12) and APA (n = 35) samples were analyzed. The KCNJ5 T158A mutation was introduced into human adrenocortical cell lines (HAC15 cells) using lentiviral delivery. DNA methylation array analysis was conducted using adrenal tumor samples and HAC15 cells. Results The Purkinje cell protein 4 (PCP4) gene was one of the most hypomethylated in APAs. DNA methylation levels in two sites of PCP4 showed a significant inverse correlation with messenger RNA expression in adrenal tumors. Bioinformatics and multiple regression analysis revealed that CCAAT/enhancer binding protein alpha (CEBPA) may bind to the methylation site of the PCP4 promoter. According to chromatin immunoprecipitation assay, CEBPA was bound to the PCP4 hypomethylated region by chromatin immunoprecipitation assay. There were no significant differences in PCP4 methylation levels among APA genotypes. Moreover, KCNJ5 T158A did not influence PCP4 methylation levels in HAC15 cells. Conclusions We showed that the PCP4 promoter was one of the most hypomethylated in APAs and that PCP4 transcription may be associated with demethylation as well as with CEBPA in APAs. KCNJ5 mutations known to result in aldosterone overproduction were not related to PCP4 methylation in either clinical or in vitro studies. Primary aldosteronism (PA) is a major cause of secondary hypertension and is characterized by excessive and autonomous production of aldosterone (1). Patients with PA are at greater risk of cardiovascular and cerebrovascular diseases than are those with essential hypertension who have similar blood pressure and risk profiles (2, 3). PA has two main subtypes, aldosterone-producing adenoma (APA) and bilateral idiopathic hyperaldosteronism (1). The elevated aldosterone production in APAs is attributable mainly to upregulation of aldosterone synthase (CYP11B2), which catalyzes the final steps of aldosterone biosynthesis (4, 5). In APAs, CYP11B2 transcription is induced by the activation of intracellular calcium signaling (6). Recent studies demonstrated that 50% to 80% of APAs harbored somatic mutations in KCNJ5, ATP1A1, ATP2B3, or CACNA1D and that aldosterone production was affected by mutations that increase intracellular Ca2+ concentration and activate the calcium signaling cascade (7–10). Proteins belonging to the calmodulin family play a pivotal role in the transport of intracellular calcium from the cytoplasm to the nucleus in adrenal cells (11, 12). Epigenetic regulation, including DNA methylation and intracellular signaling cascades, is important for tumor progression, cell survival, DNA damage repair, and hormone secretion because it influences gene expression (13, 14). In the mammalian genome, 5′-cytosine-guanine-3′ (CpG) dinucleotides are preferentially methylated or demethylated by DNA methyltransferase or demethyltransferase enzymes, respectively (13). Hypomethylation of CpG islands in the promoter region is associated with gene expression primarily by facilitating the binding of transcription factors (13). We recently reported that CYP11B2 hypomethylation was associated with CYP11B2 expression in APAs (15). In addition, DNA methylation is actively involved in fetal adrenal development and adrenocortical cancer progression via the repression or activation of genes involved in differentiation and proliferation (16, 17). Taken together, these facts suggest that proteins belonging to the calmodulin family are regulated by DNA methylation as well as by intracellular signaling cascades in APAs. In this study, we examined the DNA methylation levels of calmodulin-related factors in APAs using a DNA methylation array. Our results showed that the Purkinje cell protein 4 (PCP4) gene was one of the most hypomethylated genes in APAs. PCP4 is known to be overexpressed in APAs, and it has been suggested that PCP4 stimulates CYP11B2 expression and aldosterone production in human adrenocortical cells (18). Therefore, we hypothesized that PCP4 transcription is associated with DNA methylation or demethylation in APAs. The objectives of our study were to clarify the relationship between PCP4 methylation and messenger RNA (mRNA) expression in adrenal tumors, including APA, and to identify transcription factors that may also be involved in PCP4 expression. In addition, we examined the effects of the APA genotype on PCP4 DNA methylation in clinical samples and an in vitro analysis. Methods Patients and tissue collection The diagnosis and subtype diagnosis of PA were performed according to guidelines from The Japan Endocrine Society (19) as previously described (20). Nonfunctioning adrenocortical adenomas (NFs) were diagnosed by the radiological detection of low augmentation signals from computed tomography or magnetic resonance imaging scans and from endocrinological data showing an absence of excess cortisol or aldosterone as previously reported (21). The clinical characteristics of patients are shown in Supplemental Table 1 and in previous reports (15, 22). Forty-seven adrenal tumors (12 NFs and 35 APAs) were obtained by surgical resection and stored at −80°C until use (15). The pathological diagnosis of APA was confirmed by detecting the expression of CYP11B2 by immunohistochemistry and by quantitative polymerase chain reaction (qPCR) assays as previously reported (5). Our study was approved by the ethics committee of Hiroshima University, and written informed consent was obtained from all patients. DNA extraction and genotyping The DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany) was used for extraction of genomic DNA from adrenal tissues, peripheral leukocyte DNA, and human adrenocortical cell lines (HAC15 cells). Gene mutation analyses of KCNJ5, ATP1A1, ATP2B3, and CACNA1D were performed using a polymerase chain reaction‒based direct sequencing method as previously described (23). DNA methylation analysis DNA methylation analysis was performed as previously reported (15). Briefly, bisulfite conversion and methylation analysis were performed using the Infinium HumanMethylation450 BeadChip Kit (Illumina, San Diego, CA) according to the manufacturer’s instructions. BeadChip can identify more than 485,000 methylation sites per sample at single-nucleotide resolution and can recover up to 99% of RefSeq genes and 96% of CpG islands (24). Methylation levels of each CpG residue were presented as β values, which were derived from the signal intensity of methylated and unmethylated sites. Average β values were expressed as 0 to 1, representing completely unmethylated to completely methylated values, respectively. RNA extraction and qPCR assays Total RNA extraction and complementary DNA preparation were performed with the RNeasy Mini Kit (Qiagen, Hilden, Germany) and PrimeScript RT Master Mix (Takara Bio Inc., Shiga, Japan), respectively, as previously described (23). qPCR was performed with SYBR Green fluorescent dye using the 7500 Fast PCR Machine (Applied Biosystems, Waltham, MA). qPCR primers for PCP4, breast cancer gene 1 (BRCA1), CCAAT/enhancer binding protein alpha (CEBPA), CCAAT/enhancer binding protein beta (CEBPB), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH) are shown in Supplemental Table 2. Gene expression levels were expressed as arbitrary units normalized against GAPDH mRNA expression. Cell culture and lentiviral infection HAC15 cells were kindly provided by W.E. Rainey (University of Michigan) and were cultured as previously reported (10). Plasmid pLX303 and pLX303-KCNJ5-T158A were prepared, and lentivirus production and infection in HAC15 cells were performed as previously reported (10). Chromatin immunoprecipitation assay Chromatin immunoprecipitation (ChIP) assays were performed with the SimpleChIP® Plus Enzymatic Chromatin IP Kit (#9005; Cell Signaling Technology, Danvers, MA) following the manufacture’s recommended protocol. Briefly, HAC15 cells were cross-linked with 1% formaldehyde, and they were digested with a supplied nuclease at 37°C for 20 minutes. The generated DNA was confirmed by agarose gel electrophoresis. Chromatin preparations were incubated with normal rabbit immunoglobulin G (supplied in the SimpleChIP® Plus Enzymatic Chromatin IP Kit) or C/EBPα antibody (sc-61; Santa Cruz Biotechnology, Heidelberg, Germany), and then they were incubated with supplied magnetic beads. Bound complexes were eluted from the beads, and cross-link was reversed at 65°C for 2 hours. Immunoprecipitated materials were analyzed by qPCR assay. The oligonucleotide primers of set A for the “c” region were 5′-ACC TGA AAG TGC GTG AGC GG-3′ and 5′-TTT CAA AGA TCA CAG GG-3′. The primers of set B for the “c” region were 5′-ACC TGA AAG TGC GTG AGC GG-3′ and 5′-CTG GGC AGC AGA ACG AGA CC-3′. Relative ChIP signals were calculated by a fold enrichment method. Statistical analysis Quantitative data are presented as means and standard deviations. The heat map was depicted using the R software package (University of Auckland), and subsequent analyses were performed using SPSS for Windows (release 24.0; SPSS Inc., Chicago, IL). Because PCP4 mRNA levels did not fit a normal distribution, they were converted to log-transformed data for analysis. Simple and multiple regression analyses were conducted to evaluate the relationships between PCP4 mRNA expression levels and methylation values. Values of statistical significance among genotypes were determined by one-way analysis of variance. Differences in the methylation levels between the HAC15 control and the KCNJ5 mutants were analyzed by the t test. The differences were considered to be significant at P < 0.05. Results DNA methylation analysis of genes involved in calmodulin binding For DNA methylation analysis, 180 calmodulin binding factors were extracted from the AmiGO gene ontologies Web site (http://amigo.geneontology.org/amigo), and 1820 methylation sites located in the promoter or 5′ untranslated region of these factors were targeted. The heat map of DNA methylation levels for 1820 methylation sites is depicted in Fig. 1. The most hypomethylated gene in APAs was tight junction protein 1 (TJP1), which may be involved in signal transduction at cell-cell junctions. According to our microarray data, there were no differences in TJP1 expression between NFs and APAs, and angiotensin II did not stimulate TJP1 expression in HAC15 cells (data not shown). The second most hypomethylated gene in APAs was PCP4. PCP4 was reported to be overexpressed in APAs, and it is thought to function as an important factor in calcium signaling (18). PCP4 gene expression levels in APAs were significantly higher than those in NFs (Supplemental Fig. 1), which is consistent with results in a previous study (18). Thus, we focused on the relationship between PCP4 DNA methylation and PCP4 mRNA expression levels. Figure 1. View largeDownload slide Heat map generated from the HumanMethylation450 BeadChip array analysis of NFs (n = 12) and APAs (n = 35). Methylation sites (1820) of 180 calmodulin binding factors are included. Figure 1. View largeDownload slide Heat map generated from the HumanMethylation450 BeadChip array analysis of NFs (n = 12) and APAs (n = 35). Methylation sites (1820) of 180 calmodulin binding factors are included. The association between PCP4 methylation and PCP4 mRNA expression Six presumed methylation sites of PCP4 genes were detected by DNA methylation array, and five of these six sites were located in the promoter region (Supplemental Fig. 2). First, the relationship between PCP4 methylation and PCP4 mRNA expression levels was analyzed by simple regression analysis. Two DNA methylations indicated as “c” and “f” showed a significant inverse correlation with PCP4 gene expression in the adrenal tumor (Fig. 2C and 2F), whereas the other sites showed no correlation with mRNA levels. Figure 2. View large Download slide Relationship between PCP4 methylation and PCP4 mRNA levels in adenomas. (A‒F) Relationships of PCP4 mRNA levels with each PCP4 methylation status are shown. APAs and NFs are indicated by closed and open circles, respectively. Each lowercase character indicates the methylation site of PCP4, which is shown in Supplemental Fig. 2. Figure 2. View large Download slide Relationship between PCP4 methylation and PCP4 mRNA levels in adenomas. (A‒F) Relationships of PCP4 mRNA levels with each PCP4 methylation status are shown. APAs and NFs are indicated by closed and open circles, respectively. Each lowercase character indicates the methylation site of PCP4, which is shown in Supplemental Fig. 2. The potential transcription factors in a PCP4 promoter methylation site Because the “c” region but not the “f” region is located in the PCP4 promoter (Supplemental Fig. 2), we next focused on the relationship between the “c” region in the PCP4 promoter and transcription factors. Potential transcription factors such as BRCA1, CEBPA, and CEBPB that can bind to PCP4 promoter via the “c” region were suggested by bioinformatics analysis using the JASPAR database (http://jaspar.binf.ku.dk/; Supplemental Fig. 3). There were no differences in BRCA1, CEBPA, and CEBPB expression levels between NFs and APAs (Supplemental Fig. 1B‒1D). We applied multiple regression analysis to investigate the combined effect of DNA methylation and transcription factors on PCP4 expression. This model revealed that CEBPA as well as DNA methylation of the “c” region was a significant independent variable for PCP4 expression in adrenal tumor cells (Fig. 3). Figure 3. View largeDownload slide Multiple regression analysis performed to determine the effect of DNA methylation and candidate transcription factors on PCP4 expression. Unstandardized regression coefficients, 95% confidence intervals, and P values were determined using multivariate regression analysis. Figure 3. View largeDownload slide Multiple regression analysis performed to determine the effect of DNA methylation and candidate transcription factors on PCP4 expression. Unstandardized regression coefficients, 95% confidence intervals, and P values were determined using multivariate regression analysis. We investigated the association between the PCP4 promoter and CEBPA using the ChIP-qPCR method. The PCP4 promoter was detected by 2.4- to 3.0-fold in samples using the CEBPA antibody compared with those using control immunoglobulin G (Fig. 4). Therefore, CEBPA is likely to bind to the “c” region of the PCP4 promoter. Figure 4. View largeDownload slide ChIP signal of the PCP4 promoter region by ChIP-qPCR assay using a CEBPA antibody. HAC15 cells were cross-linked with 1% formaldehyde and digested with a nuclease. Chromatin preparation were incubated with normal rabbit immunoglobulin G (IgG) or C/EBPα antibody, and then they were incubated with magnetic beads. Immunoprecipitated materials were analyzed by qPCR assay using 2 types of primers denoted as set A and set B. Relative amount of ChiP-qPCR using IgG is expressed as 1.0 and horizontal dot line. The detection of PCP4 promoter by set A and set B were 3.0 ± 0.7- and 2.4 ± 0.6-fold in samples using CEBPA antibody compared to in those using control IgG, respectively. Figure 4. View largeDownload slide ChIP signal of the PCP4 promoter region by ChIP-qPCR assay using a CEBPA antibody. HAC15 cells were cross-linked with 1% formaldehyde and digested with a nuclease. Chromatin preparation were incubated with normal rabbit immunoglobulin G (IgG) or C/EBPα antibody, and then they were incubated with magnetic beads. Immunoprecipitated materials were analyzed by qPCR assay using 2 types of primers denoted as set A and set B. Relative amount of ChiP-qPCR using IgG is expressed as 1.0 and horizontal dot line. The detection of PCP4 promoter by set A and set B were 3.0 ± 0.7- and 2.4 ± 0.6-fold in samples using CEBPA antibody compared to in those using control IgG, respectively. The relationship between APA genotype and DNA methylation levels We compared DNA methylation values among APAs with different gene mutations. There were no differences in PCP4 methylation levels among APA genotypes, including wild-type, KCNJ5 mutant, and ATP1A1 mutant (Table 1). Table 1. Differences in PCP4 DNA Methylation Values Among Somatic Mutations in APAs   Methylation Rate (β Value)  P Value  Methylation Site  KCNJ5 Mutation (n = 21)  ATP1A1 Mutation (n = 5)  No Mutation (n = 9)  a  0.841 ± 0.020  0.870 ± 0.063  0.817 ± 0.086  0.188  b  0.414 ± 0.079  0.340 ± 0.144  0.382 ± 0.131  0.340  c  0.259 ± 0.095  0.209 ± 0.101  0.189 ± 0.130  0.226  d  0.058 ± 0.032  0.034 ± 0.021  0.042 ± 0.026  0.217  e  0.067 ± 0.017  0.044 ± 0.017  0.048 ± 0.018  0.063  f  0.327 ± 0.095  0.298 ± 0.138  0.274 ± 0.129  0.481    Methylation Rate (β Value)  P Value  Methylation Site  KCNJ5 Mutation (n = 21)  ATP1A1 Mutation (n = 5)  No Mutation (n = 9)  a  0.841 ± 0.020  0.870 ± 0.063  0.817 ± 0.086  0.188  b  0.414 ± 0.079  0.340 ± 0.144  0.382 ± 0.131  0.340  c  0.259 ± 0.095  0.209 ± 0.101  0.189 ± 0.130  0.226  d  0.058 ± 0.032  0.034 ± 0.021  0.042 ± 0.026  0.217  e  0.067 ± 0.017  0.044 ± 0.017  0.048 ± 0.018  0.063  f  0.327 ± 0.095  0.298 ± 0.138  0.274 ± 0.129  0.481  Data are expressed as mean ± standard deviation, and P values were determined by analysis of variance. View Large We introduced the KCNJ5 mutation (KCNJ5 T158A) into HAC15 cells using lentiviral delivery. Transduction of HAC15 cells with lentiviruses harboring the KCNJ5-T158A mutation increased aldosterone levels 5.4-fold in media compared with control HAC15 cells (data not shown). There were no differences in PCP4 DNA methylation between control and KCNJ5 mutant cells (Table 2). Table 2. Differences in PCP4 Methylation Values Between Control and KCNJ5 Mutation in HAC15 Cells   Methylation Rate (β Value)  Fold Change
(KCNJ5/Control)  P Value  Methylation Site  Control  KCNJ5 T158A  a  0.877 ± 0.009  0.893 ± 0.004  1.018  0.074  b  0.700 ± 0.009  0.731 ± 0.025  1.044  0.150  c  0.362 ± 0.027  0.378 ± 0.023  1.043  0.500  d  0.034 ± 0.011  0.032 ± 0.009  0.964  0.865  e  0.058 ± 0.001  0.056 ± 0.005  0.960  0.469  f  0.079 ± 0.009  0.079 ± 0.009  0.994  0.949    Methylation Rate (β Value)  Fold Change
(KCNJ5/Control)  P Value  Methylation Site  Control  KCNJ5 T158A  a  0.877 ± 0.009  0.893 ± 0.004  1.018  0.074  b  0.700 ± 0.009  0.731 ± 0.025  1.044  0.150  c  0.362 ± 0.027  0.378 ± 0.023  1.043  0.500  d  0.034 ± 0.011  0.032 ± 0.009  0.964  0.865  e  0.058 ± 0.001  0.056 ± 0.005  0.960  0.469  f  0.079 ± 0.009  0.079 ± 0.009  0.994  0.949  DNA methylation rate was assessed in HAC15 cells infected with control (n = 3) or KCNJ5 T158A lentiviruses (n = 3). View Large Discussion We demonstrated that among the genes encoding calmodulin binding factors, PCP4 was one of the most hypomethylated in APAs and that methylation of its promoter was inversely correlated with its mRNA level. The transcription factor CEBPA, which binds to this region, was a significant independent variable for PCP4 expression. ChIP-qPCR analysis revealed that the hypomethylated region of the PCP4 promoter binds to CEBPA in HAC15 cells. Somatic mutations associated with APAs, such as KCNJ5 and ATP1A1, did not regulate PCP4 DNA methylation; in addition, the KCNJ5 mutants had no effect on PCP4 methylation in vitro. Our results showed that among the genes encoding calmodulin binding factors, PCP4 was one of the most strongly demethylated, and there was an inverse correlation between PCP4 methylation and mRNA expression (Fig. 2). A previous study suggested that APAs have higher PCP4 levels than normal adrenals, cortisol-producing adenomas, and tissues from idiopathic hyperaldosteronism; remarkably, PCP4 expressions was positively correlated with CYP11B2 expression in APAs (18). Furthermore, CYP11B2 expression was stimulated by PCP4 gene modulation in human adrenocortical cells (18). Together with our results, these findings suggest that PCP4 may be associated with DNA demethylation in APAs, and this increased PCP4 expression in turn leads to CYP11B2 upregulation. We identified three candidates that bind to the “c” region of the PCP4 promoter; CEBPA, as well as PCP4 methylation, was a significant independent variable for PCP4 mRNA expression. In general, demethylation of promoter regions typically acts to activate gene transcription by facilitating the binding of transcription factors (13); thus, transcription levels are usually determined by DNA methylation levels in the promoter and the expression levels of transcription factors. Bioinformatic and multiple regression analyses indicated that CEBPA may bind to the “c” region, and we demonstrated the binding of the hypomethylated region of the PCP4 promoter with CEBPA. In addition, because there was no difference in CEBPA levels between APAs and NFs, we suggest that PCP4 transcription is determined primarily by DNA methylation status in APAs. We compared PCP4 methylation levels among APA samples with different somatic mutations and found that these mutations were not associated with PCP4 methylation. Furthermore, KCNJ5 T158A mutation had no effect on PCP4 methylation levels in HAC15 cells. Although the KCNJ5 mutant stimulated aldosterone production in adrenal cells, the production was regulated by Ca2+ signaling, not by methylation of PCP4. We recently suggested that methylation of CYP11B2, which encodes the enzyme that catalyzes the final steps of aldosterone biosynthesis, was not associated with any of the studied somatic mutations (15). Therefore, aldosterone production resulting from mutant genes is most likely regulated by intracellular signaling, including Ca2+ signaling, and not by DNA methylation. The current study has several limitations. Because this was a cross-sectional study, we did not investigate the association of methylation and demethylation with causality of APAs or NFs. Use of methyltransferase or demethyltransferase agents may enable in vitro detection of DNA methylation. However, application of these methods may be problematic because these agents regulate the methylation of all genes and sites, including the genes of their own transcription factors. In addition, the regulation of transcription factors in adrenal cells influences myriad gene expression; thus, it is difficult to detect direct regulation between DNA methylation and transcription factors in an in vitro study. Further experiments using advanced methods are needed to clarify the relationship between DNA methylation and transcription factors. In conclusion, we showed that among the genes encoding calmodulin binding factors, PCP4 was one of the most hypomethylated in APAs, and its expression may be associated with DNA methylation in conjunction with the transcription factor CEBPA in APAs. In addition, we showed that KCNJ5 mutations known to drive aldosterone production had no effect on PCP4 methylation in clinical and in vitro studies. Thus, our study provides the basis for future studies addressing the role of DNA methylation and genomic alterations in the pathophysiology of APAs. Abbreviations: APA aldosterone-producing adenoma CEBPA CCAAT/enhancer binding protein alpha CEBPB CCAAT/enhancer binding protein beta ChIP chromatin immunoprecipitation CpG 5′-cytosine-guanine-3′ CYP11B2 aldosterone synthase HAC15 cell human adrenocortical cell line mRNA messenger RNA NF nonfunctioning adrenocortical adenoma PA primary aldosteronism PCP4 Purkinje cell protein 4 qPCR quantitative polymerase chain reaction TJP1 tight junction protein 1. Acknowledgments This work was carried out with the kind cooperation of the Analysis Center of Life Science, Hiroshima University. Financial Support: This study was financially supported by the Japan Society for the Promotion of Science KAKENHI Grants JP17K09883 (to K.O.) and JP17K16166 (to Y.Y.), the Okinaka Memorial Institute for Medical Research Grant (to K.O.), the SENSHIN Medical Research Foundation (to K.O.), the Japan Heart Foundation Dr. Hiroshi Irisawa & Dr. Aya Irisawa Memorial Research Grant (to K.O.), and the National Institutes of Health Grant HL27255 (to C.E.G.-S.). Disclosure Summary: The authors have nothing to disclose. References 1. Funder JW, Carey RM, Mantero F, Murad MH, Reincke M, Shibata H, Stowasser M, Young WF, Jr. The management of primary aldosteronism: case detection, diagnosis, and treatment: an Endocrine Society clinical practice guideline. J Clin Endocrinol Metab . 2016; 101( 5): 1889– 1916. Google Scholar CrossRef Search ADS PubMed  2. Milliez P, Girerd X, Plouin PF, Blacher J, Safar ME, Mourad JJ. 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Google Scholar CrossRef Search ADS PubMed  Copyright © 2018 Endocrine Society

Journal

Journal of Clinical Endocrinology and MetabolismOxford University Press

Published: Mar 1, 2018

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