Investigating DNA Methylation of SHATI/NAT8L Promoter Sites in Blood of Unmedicated Patients with Major Depressive Disorder

Hajime Miyanishi; Kyosuke Uno; Mina Iwata; Yuu Kikuchi; Hidenaga Yamamori; Yuka Yasuda; Kazutaka Ohi; Ryota Hashimoto; Kotaro Hattori; Sumiko Yoshida; Yu-ichi Goto; Tomiki Sumiyoshi; Atsumi Nitta

doi:10.1248/bpb.b19-01099

Abstract

Major depressive disorder (MDD) is one of the most common psychiatric diseases. However, early detection and diagnosis of MDD is difficult, largely because there is no known biomarker or objective diagnostic examination, and its diagnosis is instead based on a clinical interview. The aim of this study was to develop a novel diagnostic tool using DNA methylation as a blood biomarker. We sought to determine whether unmedicated patients with MDD showed significant differences in DNA methylation in the promoter region of the SHATI/N-acetyltransferase 8 like (SHATI/NAT8L) gene compared to healthy controls. Sixty participants with MDD were recruited from all over Japan. They were diagnosed and assessed by at least two trained psychiatrists according to DSM-5 criteria. DNA was extracted from peripheral blood. We then assessed DNA methylation of the SHATI/NAT8L promoter regions in patients with MDD by pyrosequencing. Methylation levels of the SHATI/NAT8L promoter region at CpG sites in peripheral blood from unmedicated patients were significantly higher than in healthy controls. In contrast, medicated patients with MDD showed significantly lower methylation levels in the same region compared to healthy controls. Since previous studies of DNA methylation in MDD only assessed medicated patients, the methylation status of the SHATI/NAT8L promoter region in unmedicated patients presented herein may prove useful for the diagnosis of MDD. To our knowledge, this is the first attempt to measure methylation of the SHATI/NAT8L gene in drug-naïve patients with psychiatric diseases. Based on our findings, methylation of SHATI/NAT8L DNA might be a diagnostic biomarker of MDD.

INTRODUCTION

The prevalence of psychiatric diseases, such as major depressive disorder (MDD), schizophrenia, and bipolar disorder, is increasing worldwide. Of these conditions, MDD is one of the most commonly resistant to treatment.¹⁾ For example, antidepressants are associated with a relatively low response rate in 70–80% of patients.^2–4) The reliability of psychiatric disease diagnoses is an issue of concern, largely because there is no known biomarker or objective diagnostic examination, and physicians make a diagnosis based on the International Classification of Disease-10 by WHO or the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) by the American Psychological Association. As a new approach to diagnosing mental disorders based on the dimensions of observable behavior and neurobiological measures, the Research Domain Criteria (RDoC) project was initiated.⁵⁾ Elucidation of biomarkers for MDD based on neurobiological measures, such as the RDoC concept, are expected to effect earlier intervention and treatment,⁶⁾ and consequently, improve the QOL of patients, families, and society as a whole.

The SHATI/N-acetyltransferase 8 like (SHATI/NAT8L) shows N-acetyl transfer activity, which encodes a protein synthesizing N-acetylaspartate (NAA) from aspartate and acetyl-CoA. NAA is biosynthesized to N-acetylaspartylglutamate (NAAG) by condensation with glutamic acid by NAAG synthetase.⁷⁾ The levels of both NAA and NAAG have been reported to be decreased in the hippocampus of postmortem brains of patients with psychiatric diseases such as depression.⁸⁾ Given this evidence, SHATI/NAT8L is likely associated with MDD. In this study, we focused on SHATI/NAT8L as a biomarker for psychiatric diseases. We have previously reported that brain levels of Shati/Nat8l mRNA changed in a mouse model of depression (mice exposed to forced swim stress or chronic social defeat stress).^9,10)

Given that epigenetic changes are known to be involved in psychiatric diseases,^11–13) attempts to find biomarkers using SHATI/NAT8L are worthwhile. It has been reported that methylation of SHATI/NAT8L is altered in the promoter region in a mouse model of schizophrenia, possibly providing a biomarker.¹⁴⁾ Methylation of DNA is a chemical reaction carried out by DNA methyltransferase (DNMT), which adds a carbon atom to the fifth position of the pyrimidine ring of cytosine. Methylation mainly occurs at CpG sites, a nucleotide sequence in which guanine appears next to cytosine. Regions containing a high amount of CpG dinucleotide repeats are known as CpG islands.¹⁵⁾ The alteration of methylation of CpG islands is thought to be involved in the regulation of gene expression in many diseases.¹⁶⁾ However, gene expression can be influenced by epigenetic changes caused by medication.¹⁷⁾ Thus, when searching for peripheral biomarkers, the effect of medication should be carefully considered.¹⁸⁾ Specifically, a history of medication should be controlled for in the comparison of patients and healthy control subjects.

In the present study, we collected DNA samples from the blood of unmedicated patients from all over Japan. The extent of methylation of the SHATI/NAT8L gene was examined. NAA regulated by the SHATI/NAT8L is used as a biomarker of MDD in specific human brain regions using proton magnetic resonance spectroscopy (¹H-MRS).¹⁰⁾ However, methylation of SHATI/NAT8L from blood might be a biomarker that can be used more easily than using MRS. To our knowledge, this is the first attempt to measure methylation of the SHATI/NAT8L gene in drug-naïve patients with psychiatric diseases.

MATERIALS AND METHODS

Study Design and Subjects

DNA samples were obtained from 60 patients diagnosed with MDD. Of these, 20 patients (male:12, female:8) from the National Center of Neurology and Psychiatry (NCNP) Biobank were untreated; the other 40 patients (male: 14, female: 26) from Osaka University were treated. All patients had undergone a structured interview using the Mini-International Neuropsychiatric Interview (M.I.N.I.), modified in Japanese, and were diagnosed with MDD by trained psychologists or psychiatrists according to the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). Untreated patients had never taken psychotropic drugs such as antidepressants, antipsychotics, or mood-stabilizers. In treated patients, trained psychiatrists confirmed that patients had taken antidepressants, antipsychotics, or mood-stabilizers by checking medicine notebooks and medical records. Patient’s age is 12–60 years. 69 healthy volunteers aged 12–60 years were recruited from the NCNP Biobank and Osaka University as controls. In unmedicated patients, we collected blood samples at initial diagnosis. In medicated patients, we collected blood from patients at various therapeutic stages of major depression. Written informed consent was obtained from all participants. For patients aged between 12 and 19 years, written informed consent was obtained from their parents (or guardians). Detailed characteristics of patients with MDD are shown in Table 1. Patients with a history of drug or alcohol dependence, head injury, or epilepsy were excluded. Patients with an IQ below 75 and pregnant women were also excluded. The small sample size reflects the difficulty in recruiting unmedicated patients with MDD.

Table 1. Participant Characteristics

Sample		n	Age (years)	Sex (male/female)
Control		68	47.29 ± 1.94	30/38
MDD	Unmedicated	20	40.75 ± 2.58	12/8
MDD	Medicated	40	55.18 ± 1.00	14/26

Data are expressed as mean ± standard errors of the means (S.E.M.).

This study was performed in accordance with the Declaration of Helsinki and was approved by the Institutional Review Board at the University of Toyama (Permit number 24-6). Samples obtained from the NCNP Biobank (the only high-quality biobank in Japan; Permit number A2018-009) and the COCORO consortium at the University of Osaka (Permit number 423) were used. All participants provided written informed consent.

Bisulfite Conversion

Genomic DNA was used in bisulfite reactions, in which unmethylated cytosine residues were converted to uracil residues, using an EpiTect Bisulfite Kit (Qiagen, Hilden, Germany) according to the manufacturer’s guidelines and published methods.¹⁹⁾ DNA Protect Buffer, bisulfite solution, and DNA (200 ng) were mixed and incubated under the cycle conditions recommended by the manufacturer using a TaKaRa PCR Thermal Cycler Dice^® Gradient (TaKaRa, Shiga, Japan). The bisulfite conversion thermal cycler conditions were as follows: 1 cycle at 95°C for 5 min, 1 cycle at 60°C for 10 min, 1 cycle at 95°C for 5 min, and 1 cycle at 60°C for 10 min. Converted DNA was then purified and eluted with elution buffer.

PyroMark PCR

To prepare a single-stranded PCR product for use in the subsequent pyrosequencing procedure, one PCR primer must be labeled with biotin at its 5′ mark. PCR primers were designed by PyroMark Assay Design Software 2.0 (www.qiagen.com). PyroMark PCR was performed using the PyroMark PCR Kit (Qiagen) according to the manufacturer's guidelines and published methods.²⁰⁾ PCR Master Mix, CoralLoad Concentrate, primers, ribonuclease (RNase)-free water, and converted DNA (20 ng) were briefly mixed. The reaction was performed under the recommended cycle conditions with a TaKaRa PCR Thermal Cycler Dice^® Gradient (TaKaRa): 1 cycle at 95°C for 15 min; 45 cycles at 94°C for 30 s, 56°C for 30 s, and 72°C for 30 s; and 1 cycle at 72°C for 10 min. The PCR primer sequences used were as follows: 5′-GGA GTT ATG TGG GAT TTT TAA AGA TTA-3′ and 5′-AAA AAA ACA AAA TAC CTT CCA ACA AAT TAC C-3′ as primers for the CpG sites from the transcription start site (TSS); −1714, −1700, −1696 base pairs (bp) (up and down), 5′-GGG TAA TTG TTG GAA GGT ATT-3′ and 5′-CCC CCT CAA TAT CTA AAA CC-3′ as primers for the CpG sites from TSS; −1532, −1509, −1492, −1482, and 1480 bp (up and down). Primers were designed using PyroMark Assay Design Software 2.0 (Qiagen). The conditions for designing primers were as follows: %GC >55, CpG Is length: 300–4000 bp, and observed/expected CpG >0.65.

Pyrosequencing

Pyrosequencing was performed according to the PyroMark Q24 User Manual and previously published reports.²¹⁾ Streptavidin beads (GE Healthcare, Buckinghamshire, U.K.), PyroMark binding buffer (Qiagen), PCR product, and water were mixed and then agitated for 10 min using a mixer at 1400 rpm. The sequencing primer was diluted to 0.3 µM in annealing buffer (Qiagen), and the solution was added to each PyroMark Q24 Plate (Qiagen). PCR products were separated, denatured, washed, and added to the sequencing primer in annealing buffer using the PyroMark Q24 Vacuum Workstation (Qiagen). The primer was annealed by heating to 80°C for 2 min and then cooling to room temperature (25°C). PyroMark Gold Q96 reagents (Qiagen), which were used for the reaction and the PCR product plate, were set and analyzed by PyroMark Q24 device (Qiagen). The following primers were designed by PyroMark Assay Design Software 2.0 (www.qiagen.com): 5′-AGA GAT ATT TGA GTA TAG GGT TTT AGT-3′ as the primer for CpG sites from TSS: −1714, −1700, −1696, and 5′-ATT TTT GGT GAA TTT AGG AG-3′ as the primer for CpG sites from TSS: −1532, −1509, −1492, −1482, and −1480. These primers were also designed using PyroMark Assay Design Software 2.0 (Qiagen).

Statistical Analysis

All data are shown as the mean ± standard error of the mean (S.E.M.). Statistical analyses were performed using one-way ANOVA, followed by the Bonferroni’s post-hoc test (Prism version 5). The level of statistical significance was set at p < 0.05. Cohen’s-d was used as a measure of the effect size. Cohen defined effect sizes as “small, d = 0.2,” “medium, d = 0.5,” and “large, d = 0.8.” Receiver operating characteristic (ROC) curve analysis was used to determine the utility of the biomarker for MDD using pyrosequencing in predicting group status. The best possible cut-off value in the ROC curve was identified with the highest Youden index.

RESULTS

Methylation Rates Is Increased in Unmedicated Patients with MDD but Not Medicated Patients with MDD

We analyzed the methylation rates at CpG sites of the SHATI/NAT8L promoter in peripheral blood collected from unmedicated patients with MDD. We focused on the CpG sites −1714, −1700, −1696 −1532, −1509, −1492, −1482, and −1480 bp (8CpGs) from TSS where the DNA methylation pattern has been shown to change in patients with psychiatric disorder.¹⁴⁾ As shown in Table 2, methylation rate in peripheral blood from unmedicated patients with MDD was significantly increased at CpG sites −1700 (df = 78, p = 0.023, t = −2.49), −1532 (df = 84, p = 0.025, t = − 2.64), −1492 (df = 80, p = 0.035, t = −3.23) and −1482 (df = 72, p < 0.001, t = −2.78) bp compared to healthy controls. The effect size at CpG site −1700 (Cohen’s-d = 0.67) and −1532 (Cohen’s-d = 0.70) is medium, and −1492 (Cohen’s-d = 0.87) and −1482 (Cohen’s-d = 0.82) was large. In the ROC analysis, it is shown that the utility of the biomarker for MDD using pyrosequencing have modest sensitivity (0.733) and modest specificity (0.954) at CpG site −1482 (area under the curve (AUC) = 0.868) (Table 3).

Table 2. Methylation Rates of SHATI/NAT8L DNA in Peripheral Blood from Unmedicated and Medicated Patients with MDD

		Subject			Cohen’s-d effect size
		Control	MDD		Control vs. unmedicated	Unmedicated vs. medicated
		Control	Unmedicated	Medicated	Control vs. unmedicated	Unmedicated vs. medicated
CpG site (position from the transcription start site)	−1714	78.23 ± 0.29	78.77 ± 0.56	78.40 ± 0.34	0.23	0.16
	−1700	49.78 ± 0.28	51.47 ± 0.82*	50.97 ± 0.30	0.67	0.20
	−1696	31.77 ± 0.42	32.82 ± 0.50	33.81 ± 0.30	0.26	0.50
	−1532	33.51 ± 0.36	36.52 ± 0.75*	34.08 ± 0.41^###	0.70	0.89
	−1509	34.70 ± 0.30	36.63 ± 0.52	35.33 ± 0.24^#	0.18	0.75
	−1492	42.58 ± 0.28	44.63 ± 0.53*	41.88 ± 0.67^##	0.87	0.75
	−1482	48.00 ± 0.36	52.71 ± 0.72***	47.65 ± 0.49^###	0.82	0.88
	−1480	31.04 ± 0.28	31.78 ± 0.72	31.33 ± 0.47	0.33	0.16

Data are expressed as mean ± S.E.M. Significance is set at * p < 0.05, *** p < 0.005 vs. control, ^#p < 0.05, ^## p < 0.01, ^### p < 0.005 vs. unmedicated.

Table 3. ROC Curve Analysis in Unmedicated Patients with MDD Compared with Controls

		ROC curve analysis
		Cut-off value	Sensitivity	Specificity	AUC
CpG site (position from the transcription start site)	−1714	>78.51	0.550	0.574	0.552
	−1700	>51.45	0.438	0.754	0.642
	−1696	>33.56	0.600	0.557	0.578
	−1532	>36.39	0.474	0.866	0.655
	−1509	>36.27	0.722	0.523	0.586
	−1492	>43.04	0.772	0.619	0.734
	−1482	>51.25	0.733	0.954	0.868
	−1480	>34.43	0.250	0.969	0.569

ROC: receiver operating characteristic.

Next, we also measured the methylation rates at CpG sites of the SHATI/NAT8L promoter in peripheral blood collected from medicated patients with MDD. We found that the increased methylation rates in the unmedicated patient with MDD were significantly decreased by medication at CpG sites −1532 (df = 56, p = 0.003, t = 3.12), −1509 (df = 55, p = 0.020, t = 2.58), −1492 (df = 55, p = 0.005, t = 2.60) and −1482 (df = 53, p < 0.001, t = 2.85), and there were no significant differences in methylation rates at that sites compared to healthy controls. The effect size at CpG site −1509 (Cohen’s-d = 0.75) and −1492 (Cohen’s-d = 0.75) compared to unmedicated patients was medium, and −1532 (Cohen’s-d = 0.89) and −1482 (Cohen’s-d = 0.88) was large.

DISCUSSION

Methylation levels of DNA from blood may be useful for the diagnosis of MDD. It has been reported that methylation of the BDNF gene is lower in the blood of patients with MDD.²²⁾ A combination of biomarkers is best for reliable diagnosis. In the present study, because medical treatment may induce epigenetic changes, we investigated methylation levels of DNA from unmedicated and medicated patients. Methylation levels of the SHATI/NAT8L promoter region at CpG sites in peripheral blood from unmedicated patients were significantly higher than those of healthy controls. However, medicated patients with MDD showed no significant difference in methylation levels in the same region compared to healthy controls, and showed significantly lower methylation levels compared to unmedicated patients. These findings suggest that SHATI/NAT8L methylation status could be a diagnostic marker in unmedicated patients.

Methylation of promoter-proximal DNA is involved in suppressing gene expression. On the other hand, in the absence of methylation, gene expression is facilitated.²³⁾ Our findings suggest that SHATI/NAT8L levels are decreased in the blood because DNA methylation is increased. NAA and NAAG have been reported to be decreased in postmortem brains of patients with depression,¹⁰⁾ which is consistent with decreased expression of the SHATI/NAT8L gene responsible for NAA and NAAG synthesis in the blood. However, some studies have reported that epigenetic regulation in the brain and peripheral blood may have anti-parallel relationship.^24,25) In fact, Shati/Nat8l mRNA is increased in the striatum in a mouse model of depression.²⁶⁾ Two possibilities are considered in this deference relationship of expression between in blood and brain: The first possibility is that altered expression of SHATI/NAT8L is region- or tissue-specific. The altered region of the brain in the mouse model of depression is the dorsal striatum, which differs from reports of regions where NAA is decreasing in human patients with depression, as there are no reports about the function of SHATI/NAT8L in the dorsal striatum in depression. The second possible reason is due to species differences. Methylation-related enzymes, such as DNMT1, are decreased in patients with depression, but DNMT1 is increased in a mouse model of depression in same region,²⁷⁾ resulting in making the differences of gene expression between in human and animals. Therefore, decreased levels of SHATI/NAT8L in the blood in humans is not considered inconsistent with increased levels in the dorsal striatum in a mouse model of depression. In our study, we wanted to emphasize that we do not need to focus on the brain to diagnose human psychiatric disease, we can readily assess DNA methylation from blood for this purpose.

Methylation-related enzymes such as DNA demethylases (TET enzymes),²⁸⁾ DNMT,²⁹⁾ and Methyl-CpG binding protein (MeCP)³⁰⁾ are involved in inducing methylation changes. TET enzymes oxidize methylated cytosine and remove methyl groups. It has been reported that TET1 levels are higher in patients with psychiatric diseases than in healthy controls.³¹⁾ DNMT1 is an enzyme that methylates cytosine and is reportedly decreased in patients with depression.²⁷⁾ These two proteins are essential for DNA methylation and demethylation and are thought to affect gene expression. MeCP2 is a protein that binds only to methylated CpG sites and suppresses gene transcription.³²⁾ The expression changes of methylation-related enzymes may need to be considered to confirm that SHATI/NAT8L methylation is a useful blood diagnostic marker, resulting in greater reliability. However, it is presently virtually impossible to investigate these changes in the human brain.

Next, we examined the effect of treatment with antidepressant drugs on DNA methylation. In our study, methylation rates in medicated patients were lower than those in unmedicated patients. It has been reported that treatment with fluoxetine, a selective serotonin reuptake inhibitor (SSRI), reverses DNA methylation via phosphorylation of MeCP2, and regulates transcription in mice.¹⁷⁾ In addition, tricyclic antidepressant drugs, such as amitriptyline and imipramine, and the SSRI paroxetine, decrease DNMT activity.³³⁾ Therefore, medication might affect methylation-related enzymes and alter methylation levels. However, these studies were performed in the brain, not in blood. Understanding these mechanisms of DNA methylation regulation in the blood is very important. Future studies should validate this possibility by measuring the activity of these enzymes in the blood.

Recently, magnetic resonance spectroscopy (MRS) has enabled the determination of the concentration of neurotransmitters and changes in various metabolites.³⁴⁾ It might be possible to analyze NAA and NAAG via MRS. However, the MRS apparatus is not yet widely available and cannot be used at all hospitals. Thus, diagnosis of psychiatric disorders from blood samples would be more practical than diagnosis by MRS.

Previous studies have reported that age and/or gender affect DNA methylation.^35,36) Here, we did not observe a correlation or difference between DNA methylation of the SHATI/NAT8L promoter region and gender or age. This suggests that SHATI/NAT8L methylation levels can be used as a diagnostic marker for any patient. To be used as a reliable and accurate diagnostic biomarker, the standard values for each age and gender must be determined in future studies.

Our findings suggest that increased methylation of SHATI/NAT8L at the promoter-proximal CpG site, especially −1482 bp from the transcription start site, could be a diagnostic marker for MDD in unmedicated patients. We also showed that antidepressant medication causes epigenetic changes at this locus. This suggests the importance of using unmedicated patient subjects when searching for blood biomarkers in diagnosing MDD. In addition, SHATI/NAT8L methylation level might serve as a biomarker as well as an indicator of therapeutic response in patients with MDD. By establishing SHATI/NAT8L methylation in blood as a biomarker of MDD, earlier intervention and treatment would be expected. The prevalence of MDD is increasing each year^37–39); thus, the need for reliable biomarkers to diagnose MDD is increasing. The conformation of SHATI/NAT8L methylation level as a new diagnostic marker for MDD will be beneficial for many people.

Acknowledgments

A part of clinical samples were provided by NCNP Biobank, a member of National Center Biobank Network (NCBN). This work was supported by the grant-in-aid for Scientific Research (KAKENHI) (B) [JSPS KAKENHI Grant Number: JP15H04662], Challenging Exploratory Research [JSPS KAKENHI Grant Numbers: JP15K15050, JP17K19801] (AN), Uehara Memorial Foundation (AN), Uehara Memorial Foundation (AN), Smoking Research Foundation Grant for Biomedical Research and Foundation (AN). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Author Contributions

The study was designed HM and AN. HM, KU, MI and YK performed the assessment of DNA methylation. HM, YY, KO, RH, KH, SY, YG and TS collected the samples. HM, KU, RH and TS drafted the manuscript. AN provided critical revision of the manuscript for important intellectual content. All authors read and gave approval of the final manuscript.

Conflict of Interest

The authors declare no conflict of interest.

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