CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder?

European Neuropsychopharmacology (2017) 27, 360–371

www.elsevier.com/locate/euroneuro

CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder? Christoph Schartnera, Christiane Zieglera, Miriam A. Schielea, Leonie Kollerta, Heike Webera,b, Peter Zwanzgerc,d,e, Volker Aroltc, Paul Paulif, Jürgen Deckerta, Andreas Reifb, Katharina Domschkea,g,n a

Department of Psychiatry, Psychosomatics and Psychotherapy, University of Wuerzburg, Wuerzburg, Germany Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Goethe-University, Frankfurt, Germany c Department of Psychiatry and Psychotherapy, University of Muenster, Muenster, Germany d kbo-Inn-Salzach-Klinikum, Wasserburg am Inn, Germany e Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University, Munich, Germany f Department of Psychology (Biological Psychology, Clinical Psychology and Psychotherapy), University of Wuerzburg, Wuerzburg, Germany g Department of Psychiatry, University of Freiburg, Freiburg, Germany b

Received 9 August 2016; received in revised form 4 November 2016; accepted 5 January 2017

KEYWORDS

Abstract

Corticotropin releasing hormone receptor 1; HPA axis; Methylation; Epigenetics; Panic disorder; Beck Anxiety Inventory

The corticotropin releasing hormone receptor 1 (CRHR1) is crucially involved in the hypothalamic-pituitary-adrenal axis and thus a major regulator of the stress response. CRHR1 gene variation is associated with several mental disorders including anxiety disorders. Studies in rodents have demonstrated epigenetic regulation of CRHR1 gene expression to moderate response to stressful environment. In the present study, we investigated CRHR1 promoter methylation for the first time regarding its role in panic disorder applying a case-control approach (N=131 patients, N =131 controls). In an independent sample of healthy volunteers (N=255), CRHR1 methylation was additionally analyzed for association with the Beck Anxiety Inventory (BAI) score as a dimensional panic-related intermediate phenotype. The functional relevance of altered CRHR1 promoter methylation was investigated by means of luciferasebased reporter gene assays. In panic disorder patients, a significantly decreased CRHR1 methylation was discerned (po0.001). Accordingly, healthy controls with high BAI scores showed significantly decreased CRHR1 methylation. Functional analyses revealed an increased gene expression in presence of unmethylated as compared to methylated pCpGl_CRHR1 reporter gene vectors. The present study identified a potential role of CRHR1 hypomethylation – conferring increased CRHR1 expression – in panic disorder and a related dimensional

n

Correspondence to: Department of Psychiatry, University of Freiburg, Hauptstr. 5, D-79104 Freiburg, Germany. E-mail address: [email protected] (K. Domschke).

http://dx.doi.org/10.1016/j.euroneuro.2017.01.005 0924-977X/& 2017 Elsevier B.V. and ECNP. All rights reserved.

CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder?

361

intermediate phenotype. This up-regulation of CRHR1 gene expression driven by demethylation might constitute a link between the stress response and panic disorder risk. & 2017 Elsevier B.V. and ECNP. All rights reserved.

1.

Introduction

The human stress response as governed by the hypothalamic-pituitary-adrenal (HPA) axis is considered to play a crucial role in the pathophysiology of stress-relatedand anxiety disorders. The corticotropin releasing factor (CRF) and its receptors are important components of the HPA axis and the stress response. By binding CRF, secreted from the hypothalamus upon stress signals, the corticotropin releasing hormone receptor 1 (CRHR1) triggers the release of the adrenocorticotropic hormone (ACTH), which in turn mediates cortisol excretion from the adrenal gland (Smith and Vale, 2006). CRHR1 expression, however, is not limited to the pituitary gland, but found throughout the brain with strongest expression in the brainstem, the medial and basolateral amygdala and the cerebellum (Aguilera et al., 2004), and influences the noradrenergic stress response as relevant with respect to anxiety by corticotropic innervations of e.g. the locus coeruleus (Binder and Nemeroff, 2010; Valentino et al., 1983). Thus, the CRHR1 gene constitutes a promising candidate gene for stressrelated- and particularly anxiety disorders. Along these lines, global Crhr1 knockout mice have been reported to display decreased anxiety-like behavior along with blunted ACTH and cortisol levels (Timpl et al., 1998). Accordingly, conditional anterior forebrain (Wang et al., 2012) and limbic brain structure Crhr1 knockout (Müller et al., 2003) as well as knockdown of Crhr1 mRNA expression in the basolateral amygdala (Sztainberg et al., 2010) induced a significant decrease in anxiety levels. In a juvenile rhesus macaque model, anxious temperament (AT) – analogous to a human childhood anxiety-risk phenotype – and related brain metabolic activity were influenced by CRHR1 variation (Rogers et al., 2013). Human fear acquisition deficits have been found to be driven by a single nucleotide polymorphism (SNP; rs878886) in the CRHR1 gene located on chromosome 17 (Heitland et al., 2013, 2015), and healthy CRHR1 rs17689918 risk allele carries scored higher on dimensional scales for anxiety sensitivity and agoraphobia (Weber et al., 2015). Finally, association of CRHR1 polymorphisms (rs12944712, rs110402, rs12938031, rs4792887, rs242924) with stress- or anxiety-related phenotypes has been extended to a clinical context, i.e. posttraumatic stress disorder (Amstadter et al., 2011; Boscarino et al., 2012; White et al., 2013) and panic disorder (Ishitobi et al., 2012; Keck et al., 2008). In a recent multilevel approach, it was shown that carriers of the CRHR1 rs17689918 risk allele displayed a significantly increased risk of panic disorder along with differential brain activation of the amygdalae and prefrontal cortices in a safety learning and differential conditioning task, respectively (Weber et al., 2015). Another study applying linkage and

association analyses failed, however, to provide support for a role of CRHR1 variation in panic disorder (Hodges et al., 2009). Genetic effects might be modulated, strengthened or concealed by epigenetic mechanisms critically influencing gene regulation and mediating adaptation to environmental factors. Particularly, methylation of the cytosine pyrimidine ring in cytosine-guanine dinucleotides (CpG) has been shown to be of major functional significance by mainly silencing DNA transcription when occurring in the promoter region of a gene (Jaenisch and Bird, 2003; Suzuki and Bird, 2008). First studies with respect to anxiety disorders showed differential DNA methylation patterns in the monoamine oxidase A (MAOA) and glutamate decarboxylase 1 (GAD1) genes as well as in the oxytocin receptor (OXTR) gene to be associated with panic disorder (Domschke et al., 2013, 2012; Ziegler et al., 2016) and social anxiety disorder (Ziegler et al., 2015), respectively. To date, no data are available on the role of CRHR1 methylation in regard to anxiety disorders despite evidence from a rodent study for Crhr1 promoter demethylation induced by gestational hypoxia to be associated with anxiety-like behavior (Wang et al., 2013). Also, upon differential environmental stimulation, Sotnikov et al. observed bidirectional alterations of Crhr1 gene expression in the amygdala of high anxious (HAB) and low anxious (LAB) mouse strains associated with a rescue of the respective extreme anxiety-phenotype to be regulated by dynamics in Crhr1 promoter methylation (Sotnikov et al., 2014). Given the converging body of evidence for a genetically driven and potentially epigenetically modified involvement of the corticotropin releasing hormone receptor 1 in anxiety as reviewed above, here we studied CRHR1 promoter methylation for the first time regarding its role in panic disorder applying a case-control approach. In a large independent sample of healthy volunteers, CRHR1 methylation was additionally analyzed for association with a dimensional anxiety phenotype as ascertained by the Beck Anxiety Inventory (BAI), which has been shown to have a particularly strong ability to assess acute panic-related symptomatology (Leyfer et al., 2006; Muntingh et al., 2011). Finally, the functional relevance of altered CRHR1 promoter methylation was investigated by means of luciferase-based reporter gene assays. We hypothesized to discern decreased CRHR1 methylation – conferring increased CRHR1 expression – to be associated with panic disorder as well as with increased BAI scores.

2. 2.1.

Experimental procedures Samples

The panic disorder sample – constituting the discovery sample – consisted of 131 German patients with panic disorder (f=85, m=46;

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age: 35.83711.08 years7SD) as ascertained by experienced psychiatrists on the basis of medical records and a structured clinical interview according to the criteria of DSM-IV (SCID-I; Wittchen et al., 1997). Patients with mental retardation, neurological or neurodegenerative disorders impairing psychiatric evaluation were not included. Medication was recorded, 53 patients received SSRIs, other medication comprised venlafaxine (N=3) and trimipramine, agomelatine, opipramol, mirtazapine, valproate, quetiapine, and fluspirilene (each N=1). The control group consisted of 131 healthy subjects matched to the patient group by age (35.84710.9 years7SD, to0.001, p =1.0) and gender (f=85, m =46, χ2 =0.0, p=1.0). Absence of current or lifetime mental axis I disorders was ascertained by experienced psychologists on the basis of a structured clinical interview according to the criteria of DSM-IV (Mini International Neuropsychiatric Interview, M.I.N.I; Sheehan et al., 1998). Data on smoking was only available for the patient group (30.5% smokers). All participants were of Caucasian origin and were recruited at the University of Muenster, Germany. An independent sample of healthy probands comprised 255 subjects (f =181, m=74 males; age: 25.2976.02 years7SD) of Caucasian descent recruited at the University of Wuerzburg, Germany, within the Collaborative Research Center SFB-TRR58, subproject Z02. Absence of current or lifetime mental axis I disorders was established by experienced psychologists on the basis of the M.I.N.I according to DSM-IV criteria (Sheehan et al., 1998). Further exclusion criteria were severe medical conditions, intake of centrally active medication and excessive consumption of alcohol (415 units/ week) or caffeine (44 cups/ day). None of the recruited probands consumed nicotine. Dimensional anxiety was evaluated using the Beck Anxiety Inventory (BAI; mean7SD= 8.6177.39; Steer and Beck, 1990). The study was approved by the ethics committees of the Universities of Muenster and Wuerzburg, Germany, respectively. Written informed consent was obtained from all participating subjects, and the study was conducted according to the ethical principles of the Helsinki Declaration.

2.2.

DNA methylation analysis and genotyping

EDTA-blood was collected from all patients and healthy participants, and DNA was isolated using the FlexiGene DNA Kit (Qiagen, Hilden, Germany) or a standardized salting out procedure. Aliquots of isolated DNA were treated with sodium bisulfite using the EpiTect 96 Bisulfite Kit (Qiagen, Hilden, Germany) according to the manufacturer's protocol for all samples in one batch and in randomized order (Ziegler et al., 2015). The promoter region of the human CRHR1 gene was analyzed in silico using UCSC Genome Browser for CpG-rich regions (Kent et al., 2002) considering homologous regions previously analyzed for DNA methylation in mice (e.g. Sotnikov et al., 2014) and rats (e.g. Todkar et al., 2016) as well as distance to transcription start and abundance of transcription factor binding sites. The selected 293 bp amplicon (chr17:45,783,24945,783,542 based on UCSC Genome Browser (Kent et al., 2002) on Human Dec. 2013 [GRCh38/hg38] Assembly) covering the initial part of the CpG-Island (chr17:45,783,319-45,785,562, UCSC Genome Browser (Kent et al., 2002) on Human Dec. 2013 [GRCh38/hg38] Assembly) 1295 bp - 1002 bp upstream of the CRHR1 start codon (Figure 1A; Parham et al., 2004; Polymeropoulos et al., 1995) was analyzed for DNA methylation with the forward primer 50 AGTTTTGTTTATTTGGAAGGGTTGG-30 and the reverse primer 50 ACCCTTTAAACCTAAAAACCCCAAA-30 (Figure 1B). The amplicon is located 737 bp and 757 bp upstream of the two major transcriptional start sites, respectively, and 628 bp upstream of the basal promoter at  374 bp described in Parham et al. (Parham et al., 2004). The sequence containing 24 CpGs was PCR-amplified using the HotStarTaq Plus Master Mix (Qiagen, Hilden, Germany) with an optimized

Figure 1 Location of the investigated amplicon and CpG sites in the CRHR1 gene. (A) The investigated amplicon is located between. 1295 bp and 1002 bp upstream of the CRHR1 transcription start (ATG) (not to scale; Parham et al., 2004; Polymeropoulos et al., 1995). (B) Primer sequences used for PCR-amplification are double-underlined. Underlined CpG sites could not be analyzed due to technical issues (see methods); the 15 CpG sites robustly readable are boxed. Given insufficient methylation (o5%) of CpG sites 1–8 (see Table 1), only CpG sites 9–15 were selected for further analyses (boxed bold lowercase, see methods). The sequence in bold and lowercase was used for in silico and in vitro analyses (see Figs. 4 and S2). annealing temperature of 61.4 1C following a published protocol (Domschke et al., 2012). The amplicon was purified and sequenced by LGC Genomics (Berlin, Germany) on ABI 3730Xl sequencer platforms (Applied Biosystems by Life Technologies, Darmstadt, Germany). The obtained sequences were quantitatively analyzed using the Epigenetic Sequencing Methylation software (ESME; Lewin et al., 2004) as applied in previous studies (Alasaari et al., 2012; Domschke et al., 2012, 2014, 2015; Heberlein et al., 2013; Hillemacher et al., 2009; Tadić et al., 2014; Ziegler et al., 2015, 2016). To account for run variability, all samples were tested in duplicates, yielding a mean individual methylation score for each CpG site. To control for potential bisulfite conversion or PCR bias, commercially available fully methylated and fully non-methylated DNA was run as a control condition in all experiments. Due to thymine-stretches, created by bisulfite converted cytosines at the 50 and 30 ends of the amplicon, electropherograms were robustly readable for a reduced number of 15 CpG sites (see Figure 1B). Genotyping for CRHR1 SNP rs17689918 was performed using a restriction fragment length polymorphism (RFLP) assay. The target region of rs17689918 was amplified by polymerase chain reaction (PCR) using forward primer 50 -AGCCACTGGGGGTCTTCATA-30 and reverse primer 50 -AAAGTTGGAAGCAAGCACCG-30 in 35 cycles at 95 1C denaturation followed by annealing at 60.5 1C and elongation at 72 1C each for 45 s. The PCR amplicon was then digested with restriction enzyme HpyCH4V (New England Biolabs (NEB), Frankfurt, Germany) for 4 h at 37 1C and run on a 4% agarose gel. Genotypes were determined independently by two investigators blinded for clinical diagnoses. Hardy-Weinberg criteria, as calculated by the DeFinetti online program (https://ihg.gsf.de/cgi-bin/hw/hwa2.pl; Wienker TF and Strom TM), were fulfilled for CRHR1 rs17689918 genotype distribution (panic disorder sample: AA=5, AG=33, GG=89, missing=4; control sample: AA=4; AG=39, GG=88; inde pendent sample of healthy probands: AA=19, AG=81, GG=150, missing=5; all p40.05). For further analyses, genotypes were grouped according to a previous study (AA/AG genotype carriers=risk vs. GG genotype carriers=non-risk; Weber et al., 2015).

CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder?

Table 1

363

CRHR1 methylation in patients with panic disorder and matched healthy controls. Patients N = 120

Controls N= 117

Statistics

Mean methylation

SD

Mean methylation

SD

CpG1 CpG2 CpG3 CpG4 CpG5 CpG6 CpG7 CpG8

0.0133 0.0209 0.0096 0.0084 0.0037 0.0051 0.0221 0.0090

0.02656 0.04159 0.02163 0.01963 0.01514 0.01590 0.02838 0.02462

0.0075 0.0152 0.0155 0.0177 0.0012 0.0048 0.0242 0.0093

0.01397 0.01963 0.02521 0.03245 0.00417 0.01968 0.03186 0.02815

CpG9

0.0721

0.04418

0.0884

0.04689

CpG10

0.0807

0.06104

0.1025

0.06124

CpG11a)

0.1055

0.06957

0.1476

0.09189

CpG12

0.0840

0.06334

0.1027

0.06723

CpG13a)

0.1111

0.08093

0.1465

0.09106

CpG14

0.0485

0.04721

0.0531

0.04477

CpG15a)

0.0768

0.05572

0.1083

0.07206

Average CpGs 9-15

0.0827

0.04355

0.1070

0.05528

F1,235 =7.604, p =0.006nn, # F1,235 =7.551, p =0.006nn, # F1,217.821 =15.397, po0.001nnn, # F1,235 =4.893, p =0.028n F1,230.313 =10.012, p =0.002nn, # F1,235 =0.588, p =0.444, ns F1,218.326 =14.173, po0.001nnn, # F6,1410 =4.450, po0.001nnn

SD=standard deviation; Only CpGs 9–15 and average methylation across CpGs 9–15 (bold) entered analyses given a mean methylation o5% at CpGs 1–8. a) =no homogeneity of variances required use of Brown-Forsythe tests. F=ANOVA; p =p-value; n =po0.05; nn =po0.01; nnn =po0.001; ns =not significant; # =p-values remaining significant after Bonferroni correction for multiple testing.

2.3.

Functional analyses

Functional analyses of the target sequence were accomplished using the CpG-free luciferase reporter vector pCpGL by courtesy of Prof. M. Rehli, University of Regensburg, Germany (Klug and Rehli, 2014). A CMV/EF1α promoter was cloned into pCpGL-basic vectors using BglII and HindIII restriction enzymes, creating pCpGL_CMV/EF1α vectors (see Supplementary Figure S1). Subsequently, the sequence encompassing CpG sites 9–15 (see results and Figure 1B) was annealed as a triple repeat and ligated proximally to the CMV/EF1α promoter in a pCpGL-basic vector using PstI and BamHI restriction sites (see Supplementary Figure S2). A triple repeat of the sequence encompassing CpG sites 9–15 was used as an insert to enhance the anticipated effect of these CpG sites on promoter activity. The insert was obtained by annealing of synthesized forward and reverse strand (metabion, Martinsried, Germany) and ligated into the linearized pCpGL_CMV/EF1α vector using T4 DNA Ligase (Invitrogen, Darmstadt, Germany) according to the manufacturer's instructions. Successful ligation was validated by Sanger sequencing (LGC Genomics, Berlin, Germany). The pCpGL_CRHR1 vector and a control vector without the insert (pCpGL_CMV/EF1α) were methylated using the CpG methyltransferase M.SssI (NEB, Frankfurt, Germany) and transfected to HEK293 cells (ECACC, Salisbury, UK) using TransFast transfection reagent (Promega, Mannheim, Germany) according to the manufacturer's recommendations. In brief, 250 ng of total DNA (225 ng of pCpGL_CRHR1 or pCpGL_CMV/EF1α and 25 ng of pGL4.74 renilla

luciferase control vector) were co-transfected with 2.25 ml TransFast reagent (Promega, Mannheim, Germany) into HEK293 cells (5  104 cells per ml) in 24-well plates (Sarstedt, Nuembrecht, Germany) and incubated for 48 h until further use. Luciferase assays were performed using the Dual-Luciferases Reporter Assay System (Promega, Mannheim, Germany) according to the manufacturer's instructions on a GloMaxs-Multi Detection System luminometer (Promega, Mannheim, Germany). All analyses were conducted in technical triplicates.

2.4.

In silico analyses

In silico analyses to reveal potential transcription factor binding sites in the sequence spanning CpG sites 9–15 (see Figure 1B) were conducted using the online database JASPAR (http://jaspar.gen ereg.net/; Mathelier et al., 2015).

2.5.

Statistical analyses

DNA methylation patterns were assessed using mean methylation scores of each sample. CpG sites with a methylation o5% were excluded from further analyses (CpGs 1–8; see Table 1; Roberts et al., 2014). Associations between methylation and age were evaluated using Pearson correlation for each individual CpG site (CpGs 9–15). Impact of medication and smoking status on methylation in the patient group was assessed using Student´s t-tests.

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C. Schartner et al.

Genotype effects of rs17689918 on phenotype and methylation, respectively, were assessed by χ2 tests and mixed linear model for repeated measures, with methylation as within factor and rs17689918 genotype as between factor (cf. Schuster et al., 2016; Unternaehrer et al., 2015; Ziegler et al., 2016). Differences in DNA methylation between panic disorder patients and controls or between low anxious and high anxious healthy controls (groups generated by median split of the BAI sum score), respectively, were tested using mixed linear models for repeated measures, with CRHR1 methylation as within factor and group (panic disorder patients vs controls or high anxious vs low anxious healthy controls, respectively) as between factor (cf. Schuster et al., 2016; Unternaehrer et al., 2015; Ziegler et al., 2016). Follow-up analyses for individual CpG sites were performed using univariate ANOVA. Age was used as covariate when applicable. Significance level was set at po0.05. Bonferroni correction for multiple testing set the significance level to pr 0.007 (p-value of 0.05 divided by 7, since seven CpG sites (CpGs 9–15) entered final analyses after exclusion of CpG sites 1–8 due to a mean methylation of o5%, which is to be considered conservative given a high correlation among the individual CpG sites; see results). Luciferase assay data was normalized to transfection efficiency by renilla luciferase control and transformed to z-scores to eliminate day and measurement specific fluctuations. P-values o0.05 were considered significant. All statistical analyses were performed with SPSS version 23 (IBM Corp. Released 2014. IBM SPSS Statistics for Windows, Version 23.0, Armonk, NY, USA); all graphical analyses were done using GraphPad Prism version 5 (GraphPad Software, San Diego CA USA, www. graphpad.com); vector plasmid maps (see Supplementary data) were created using the PlasMapper version 2 online tool (http:// wishart.biology.ualberta.ca/PlasMapper/; Dong et al., 2004).

3. 3.1.

Results Sample characteristics

Due to insufficient quality of sequencing data regarding DNA methylation, a reduced sample of 120 patients with panic disorder (f = 76, age: 37.18710.6 years7SD; m = 44, age: 34.05711.7 years7SD) and 117 controls (f = 76, age: 37.24711.03 years7SD; m = 41, age: 33.76711.03 years7SD) entered final epigenetic analyses. For the independent sample of healthy probands, sequencing data was available for all 255 samples.

3.2.

CRHR1 methylation status

Across the 15 readable CpG sites in the analyzed amplicon (see methods and Figure 1), only at CpG sites 9–15 a mean methylation of at least 5% was detected in the discovery sample, i.e. the panic disorder/healthy control sample (see Table 1). Thus, all subsequent epigenetic analyses were carried out for those seven CpG sites (CpG 9–15) only. 3.2.1. Panic disorder/healthy control sample Individual average methylation of CpG sites 9–15 varied between 0.00 and 0.20 in patients and between 0.02 and 0.26 in controls (individual min-max; Table 1). Correlations among CpG sites varied between 0.169 and 0.827 with p-values ranging from po0.001 to p=0.065 (no correlation between CpG13 and CpG14) in patients; in controls, correlations ranged between 0.354 and 0.915 (all po0.001). There was no association of

methylation status (average methylation across CpG 9–15 and methylation at individual CpG sites) with age (complete sample), medication or smoking (data available for patients only; all p40.05). Neither an association of rs17689918 risk allele with panic disorder (χ2 =0.252; p=0.688) nor an effect of rs17689918 on average DNA methylation across CpGs 9–15 (F6,1386 =1.695, p=0.076) could be detected. 3.2.2. Independent sample of healthy controls Individual mean methylation varied between 0.01 and 0.21 (individual min-max; Table 2). For reasons of consistency with analyses in the panic disorder/healthy control sample (see above), CpG sites 14 and 15 were considered in the analyses despite showing mean methylation levels slightly below 5% in this independent sample of healthy controls. Correlations among the single CpG sites ranged from 0.253 to 0.904 (all po0.001). Average methylation across CpGs 9–15 correlated significantly with age (r=0.171, p=0.006) as did methylation at individual CpG sites 10, 11, 12 and 13. Thus, in further analyses age was used as covariate. No influence of rs17689918 genotype on average DNA methylation was detected (F6,1434 =0.386, p=0.888).

3.3.

CRHR1 methylation and panic disorder

In patients with panic disorder, average CRHR1 methylation was significantly decreased as compared to controls (F6,1410 = 4.450, po0.001). Analyses of individual CpG sites by means of univariate tests (ANOVA) revealed significantly decreased methylation at six CpG sites in patients as compared to controls (Figure 2). Results for CpG9, CpG10, CpG11, CpG13 and CpG15 survived Bonferroni correction for multiple testing (Table 1 and Figure 2).

3.4.

CRHR1 methylation and dimensional anxiety

The independent sample of healthy probands was stratified into low- and high-anxious groups based on a median split of Beck Anxiety Inventory (BAI) sum scores. High-anxious participants (BAI sum score Z 6) displayed significantly lower average CRHR1 methylation than low-anxious probands (BAI sum score o6), which held true for methylation at CpG sites 10–14 (see Table 2 and Figure 3). Results for methylation at CpG10, CpG11, CpG13 and CpG14 survived Bonferroni correction for multiple testing.

3.5. CRHR1 methylation and gene expression in vitro In order to validate a potentially functional effect of differential methylation at the presently investigated CpG sites on CRHR1 gene expression, in vitro luciferase assays were performed. In HEK293 cells, unmethylated pCpGL_CRHR1 vectors showed a significant increase in luciferase gene expression as compared to pCpGL_CRHR1 vectors methylated with M.SssI prior to transfection (t(16)=4.224, po0.001, Figure 4A). PCpGL_CMV/EF1α vectors without insert showed no significant difference between the methylated and the unmethylated state (t(16)=0.5271, p=0.605, Figure 4B).

CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder?

Table 2

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CRHR1 methylation in high and low anxious healthy probands. High anxious (BAI ≥ 6), N=146

Low anxious (BAI o 6), N=109

Mean Methylation

SD

Mean Methylation

SD

CpG1 CpG2 CpG3 CpG4 CpG5 CpG6 CpG7 CpG8 CpG9

0.0175 0.0094 0.0038 0.0113 0.0043 0.0057 0.0104 0.0070 0.0751

0.01964 0.01514 0.00772 0.02272 0.01317 0.01732 0.01562 0.02059 0.04032

0.0204 0.0087 0.0064 0.0118 0.0048 0.0059 0.0137 0.0067 0.0793

0.03916 0.0122 0.01529 0.01884 0.00948 0.01267 0.01829 0.01657 0.04651

CpG10

0.0732

0.03490

0.0836

0.04049

CpG11

0.0782

0.04664

0.0942

0.05470

CpG12

0.0586

0.03692

0.0701

0.04218

CpG13

0.0828

0.06580

0.1055

0.07486

CpG14

0.0371

0.03330

0.0529

0.03991

CpG15

0.0396

0.03110

0.0442

0.03599

Average CpGs 9-15

0.0635

0.03115

0.0757

0.03672

Statistics

F2,252=0.334, p=0.717, ns F2,252=5.282, p=0.006**, # F2,252=7.699, p=0.001***, # F2,252=4.631, p=0.011* F2,252=10.405, po0.001***, # F2,252=6.016, p=0.003**, # F2,252=1.075, p=0.343, ns F6,1512=2.269, p=0.035*

Legend to table 2: Low anxious: probands with BAI scores o 6; high anxious: probands with BAI scores ≥ 6 according to median split. BAI = Beck Anxiety Inventory (Steer and Beck, 1990); SD = standard deviation; Only CpGs 9-15 and average methylation across CpGs 915 (bold) entered analyses given a mean methylation o5% at CpGs 1-8. F = ANOVA; p = p-value; * = po0.05; ** = po0.01; *** = po0.001; ns = not significant; # = p-values remaining significant after Bonferroni correction for multiple testing.

3.6. In silico prediction of transcription factor binding sites Analysis of the sequence spanning CpG sites 9–15 (see Figure 1B) revealed putative transcription factor binding sites (Table 3).

4.

Discussion

In the present study, methylation patterns of a CpG island in the CRHR1 promoter region were for the first time investigated with respect to panic-related phenotypes. Patients with panic disorder were found to display significantly decreased CRHR1 methylation when compared with a sample of healthy controls. Accordingly, an independent sample of healthy volunteers with an increased score on the Beck Anxiety Index (BAI), which has been proposed as a particularly suitable intermediate phenotype of anxiety disorders with a high somatic component such as panic disorder (Cox et al., 1996; Creamer et al., 1995), showed decreased CRHR1 methylation. The functional relevance of differential methylation of the investigated target sequence was confirmed with reporter gene assays which revealed an

increased CRHR1 gene expression in non-methylated samples (Jaenisch and Bird, 2003; Suzuki and Bird, 2008). The present findings suggest CRHR1 hypomethylation conferring increased CRHR1 expression as a marker of panic-related pathology and thus provide the first translational support for a recent epigenetic study in rodents reporting Crhr1 DNA demethylation to drive elevated CRHR1 mRNA expression and concomitantly increased anxiety-like behavior (Wang et al., 2013). Our results are furthermore in line with global Crhr1 knockout mice displaying decreased anxiety-related behavior compared to wild types accompanied by blunted ACTH and cortisol levels (Timpl et al., 1998), and with the conditional knockout/knockdown of Crhr1 in the anterior forebrain (Wang et al., 2012) as well as in limbic brain regions (Rogers et al., 2013; Sztainberg et al., 2010) leading to hypersensitivity to stress along with decreased anxiety-related behavior. Synoptically, these converging findings suggest a putative epigenetically driven hyperactive stress axis with enhanced CRHR1 signaling to increase anxiety risk. However, mouse models point to a more complex, bidirectional model depending on cell type, e.g. with Crhr1 deletion in glutamatergic forebrain circuits reducing anxiety, but a lack of Crhr1 expression in dopaminergic

366

C. Schartner et al.

Figure 2 CRHR1 methylation in patients with panic disorder (N=120) and matched healthy controls (N =117). Mixed linear model for repeated measures revealed a significant group effect on average DNA methylation (cf. Schuster et al., 2016; Unternaehrer et al., 2015; Ziegler et al., 2016). Subsequent univariate analyses showed significantly decreased methylation at 6 out of 7 investigated CpG sites in patients. *=po0.05; ** =po0.01; ***=po0.001; ns =not significant. Results at CpG sites 9, 10, 11, 13 and 15 survived Bonferroni correction for multiple testing (cf. Table 1).

Figure 3 CRHR1 methylation and dimensional anxiety in healthy probands (N=255). Low anxious: probands with BAI scores o6; high anxious: probands with BAI scores Z6 according to median split. BAI=Beck Anxiety Inventory (Steer and Beck, 1990). Mixed linear model for repeated measures with covariate age revealed a significant group effect on average DNA methylation (cf. Schuster et al., 2016; Unternaehrer et al., 2015; Ziegler et al., 2016). Subsequent univariate analyses showed significantly decreased methylation at 5 out of 7 CpG sites in high anxious probands; *=po0.05; **=po0.01; ***=po0.001; ns=not significant. Results at CpG sites 10, 11, 13 and 14 survived Bonferroni correction for multiple testing (cf. Table 2).

midbrain neurons increasing anxiety-like behavior (Refojo et al., 2011). Also in the human model, the directionality of CRHR1 signaling in mediating anxiety is not unequivocally clarified. For instance, a recent genetic study reported association of panic disorder with the minor allele of the CRHR1 rs17689918 polymorphism conferring

Figure 4 Functional analyses of CRHR1 methylation using luciferase-based reporter gene assays. CpG-free luciferasebased reporter gene vectors pCpGL were in vitro methylated using M.SssI (white plots) or unmethylated (dark plots, see methods). (A) Normalized luciferase gene expression was significantly decreased in presence of methylated pCpGL_CRHR1 vectors, containing triple repeats of the sequence spanning CpGs 9–15 (see Fig. 1B) compared to unmethylated vectors. *** =po0.001. (B) No significant difference in normalized luciferase gene expression was discerned between methylated or unmethylated pCpGL_CMV/EF1α control vectors lacking the insert of the sequence spanning CpGs 9–15.

decreased CRHR1 mRNA levels in several anxiety-related brain regions (Weber et al., 2015). These apparently diverging findings might be reconciled when considering acute panic states with its strong physiological somatic characteristics on the one hand and chronic anxious apprehension on the other hand as separate phenomena (cf. Hamm et al., 2014). While the aforementioned genetic study (Weber et al., 2015) mainly focused on the latter aspect, phenotypes investigated in the present study rather capture the acute panic state with strong autonomic arousal, where increased CRH transmission via enhanced CRHR1 expression conferred by decreased methylation might be a relevant underlying pathogenetic mechanism. Also, epigenetic processes might constitute a biological attempt to antagonize genetic or environmental effects and thus a rather compensatory than pathogenetically

CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder?

Table 3

367

Predicted transcription factor binding sites in the CRHR1 amplicon encompassing CpG sites 9–15.

Transcription factor

Gene name

Start

End

DNA-Strand

Predicted site sequence

HINFP E2F4 NFIX

Histone H4 Transcription Factor E2F Transcription Factor 4 Nuclear Factor I X

TEAD1 TEAD4 NOTO TEAD3 NRF1 TFAP2A

TEA Domain Family Member 1 TEA Domain Family Member 4 Notochord Homeobox TEA Domain Family Member 3 Nuclear Respiratory Factor 1 Transcription Factor AP-2 Alpha

TFAP2B TFAP2C

Transcription Factor AP-2 Beta Transcription Factor AP-2 Gamma

HIC2 THAP1 REL RELA

Hypermethylated In Cancer 2 THAP domain containing 1 REL proto-oncogene, NF-kB subunit RELA proto-oncogene, NF-kB subunit

172 176 185 199 191 191 192 192 197 199 199 199 199 199 200 200 204 204

183 186 193 207 200 200 201 199 207 209 209 209 209 209 208 208 213 213

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

CAGCG8TTCG9CCG10 11 GC10GCG9GCGAAC 12 CGTTGCAGC11 CG13CG14CCCG15G C13GCATT12GCGT C13GCATT12GCGT 14 GC13GCATT12GCG 13 GCATT12GCG C15CGGG14CG13CGCA AGC15CGGG14CG13CG CG13CG14CCCG15GCT CG13CG14CCCG15GCT AGC15CGGG14CG13CG CG13CG14CCCG15GCT G13CG14CCCG15GC G13CG14CCCG15GC CCG15GCTTTCC CCG15GCTTTCC

Prediction is based on results generated from JASPAR database (http://jaspar.genereg.net/; Mathelier et al., 2015). ‘Start’ and ‘End’ point indicate the respective bp in the investigated CpG island (see Figure 1B); ‘DNA-Strand’ labels orientation on forward strand (1) or reverse strand ( 1). Numbers within the recognition sequence indicate the respective CpG sites in the binding sequence (cf. Figure 1B).

relevant mechanism. Finally, the present lack of association of rs17689918 with methylation status suggests that allele-specific methylation does not apply to this particular CRHR1 promoter region and thus independence of genetic and epigenetic mechanisms, which however, could entirely be owed to the limited size of the present sample. Replication of previous categorical associations of CRHR1 gene variation with panic disorder in concert with epigenetic variation and under careful consideration of the clinical phenotype, comorbidities, duration of the disorder, medication and family history in sufficiently powered samples might thus reconcile apparently inconsistent findings. On gene expression level, putative masking of binding sites for transcription factors might constitute a mechanism by which DNA methylation at CpG sites 9–15 regulates CRHR1 expression. The presently identified abundance of predicted binding sites for transcription factors TFAP2 and NFκB in the CRHR1 promoter region has been described previously (Parham et al., 2004). The possibly most relevant candidates in the present context are transcription factors TFAP2A and TFAP2B (Transcription Factor AP-2 [Activating Enhancer Binding Protein 2] Alpha/Beta). TFAP2 has been associated with antidepressant treatment and anxiety-related personality traits (Damberg et al., 2000, 2003), and is an important regulator of serotonergic, dopaminergic and noradrenergic signaling, the latter via CRF and CRHR1 pathways (Mitchell et al., 1991; Salim et al., 2007). Moreover, TFAP2A has been shown to be involved in CRH dependent regulation of gene expression (Cheng and Handwerger, 2002; Damberg et al., 2000; Hubert et al., 2010). Transcription factors THAP1 (THAP Domain Containing 1) and REL/RELA (REL proto-oncogene, NF-kB subunit/RELA protooncogene, NF-kB subunit) have been shown to be involved in regulation of CRH and CRHR1 expression in inflammatory

processes and during pregnancy (e.g., REL/RELA; Markovic et al., 2013; Zocco et al., 2010) as well as frustration behavior (THAP1; Sabariego et al., 2013). Further studies on DNA-protein interaction using methylated and unmethylated DNA are needed to clarify the exact mechanisms involved in the regulation of gene expression and its relevance for stressand particularly panic-related anxiety. Given the cross-sectional design of the case-control study, the nature and function of the presently observed CRHR1 hypomethylation in patients with panic disorder as well as in probands with high anxiety cannot be evaluated conclusively. In this effort, longitudinal studies are clearly needed. These cohort studies will additionally allow for evaluating the potential dynamics of CRHR1 methylation dependent on the experience of life events. Given the crucial involvement of CRHR1 gene variation in the stress-axis dependent on environmental factors (Tyrka et al., 2009) and further, the bidirectional dynamic alterations of Crhr1 expression driven by promoter methylation upon differential environmental stimulation observed in the amygdala of high anxious (HAB) and low anxious (LAB) mouse strains (Sotnikov et al., 2014), this aspect is highly relevant (Holsboer, 1999; Risbrough and Stein, 2006; Schreiber et al., 1996). Besides the above mentioned caveats and suggestions for future studies, the following limitations have to be considered when interpreting the present results: Despite not having discerned an influence of psychotropic medication or smoking on CRHR1 methylation, future studies are warranted to systematically explore the effects of antidepressants and smoking as well as other potentially confounding factors on CRHR1 methylation. Additionally, a median BAI score of 6 in the independent sample of healthy controls suggests rather low general anxiety levels in this sample. Thus, future studies exploiting a wider variation in dimensional anxiety levels are

368 warranted. Furthermore, the presently applied luciferase assay encompassing the seven CpG sites found to be relevant in the current context does not allow for evaluating CRHR1 promoter regulation in toto. Along these lines, as for both samples no data regarding CRHR1 mRNA expression or protein expression was available, extrapolation of CRHR1 methylation levels to gene expression is to be considered suggestive, but not conclusive. Technically, DNA methylation was measured in blood samples entailing cell-composition effects as a possible confounder. In general, investigation of epigenetic patterns in peripheral human biomaterial most certainly does not allow for direct conclusions regarding central mechanisms, despite increasing evidence for blood methylation patterns possibly constituting viable proxies for methylation correlates in brain tissue (Davies et al., 2012; Ewald et al., 2014; Massart et al., 2016; Provençal et al., 2012; Ursini et al., 2011). In this respect, ‘imaging epigenetic’ studies using fMRI or PET correlating peripheral CRHR1 methylation in leucocytes with brain activation patterns or central biochemical activity, respectively (cf. Demers et al., 2016; Shumay et al., 2012), will greatly advance our understanding of systemic epigenetic processes as sensors of alterations in the nervous system relevant for panic-related psychopathology. In summary, the present results suggest hypomethylation of the CRHR1 promoter region up-regulating CRHR1 gene expression as a marker of panic disorder, which could also be shown for a dimensional panic-related phenotype in healthy volunteers. These findings are to be considered a first stepping stone towards unraveling the role of epigenetic modification of the CRHR1 gene in the context of panic-related anxiety in humans and need to be followed-up in concert with relevant CRHR1 gene variation, with variants in genes regulating or interacting with CRHR1 gene function, and with fine-grained methylation analyses covering the entirety of functionally relevant CpG islands in the CRHR1 gene in sufficiently powered, longitudinally designed studies additionally accounting for environmental stressors. Prospectively, epigenetic patterns like decreased CRHR1 methylation might add to a panel of risk markers informing indicated, i.e. targeted and therefore highly effective primary preventive measures aiming at reducing the incidence and thus, the individual and socioeconomic burden of panic disorder.

Contributors CS, AR, JD and KD designed the studies; CS and LK conducted the functional analyses; CS, MAS, HW and CZ conducted the epigenetic and statistical analyses; MAS, PZ, PP, VA and KD recruited the samples; CS and KD wrote the manuscript; all authors contributed to the final version of the manuscript.

Role of funding source The present project was supported by the German Research Foundation (DFG), Collaborative Research Centre “Fear, Anxiety, Anxiety Disorders” SFB-TRR-58, projects C02 (to KD and JD), and Z02 (to JD, PP and AR), and the German Ministry of Research and Education (BMBF, 01EE1402A, PROTECT-AD, P5 to KD and JD). None of the funding sources have been involved in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

C. Schartner et al.

Conflict of interest Over the last three years, VA has received compensations for his contributions as member of advisory boards and for presentations for the following companies: Astra-Zeneca, Eli Lilly, Janssen-Organon, Lundbeck, Otsuka, Servier, and Trommsdorff. AR received an investigator initiated grant from Medice. PZ has received speaker fees or honoraria for advisory board participation from Pfizer, Servier, Lilly, Merz, Trommsdorff and Hexal. All these affiliations have no relevance to the work covered in the manuscript. All authors declare no conflicts of interest regarding this publication.

Acknowledgements We thank all individuals who participated in this study. We gratefully acknowledge Prof. M. Rehli for providing the pCpGL vector, the RTG 1253/2 “GK Emotions” and the Graduate School of Life Science, University of Wuerzburg. We thank Carola Gagel and Inge Reck for excellent technical assistance.

Appendix A.

Supporting information

Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/ j.euroneuro.2017.01.005.

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