Reduced DNA methylation and psychopathology following endogenous hypercortisolism - A genome-wide study

Abstract

Patients with Cushing’s Syndrome (CS) in remission were used as a model to test the hypothesis that long-standing excessive cortisol exposure induces changes in DNA methylation that are associated with persisting neuropsychological consequences. Genome-wide DNA methylation was assessed in 48 women with CS in long-term remission (cases) and 16 controls matched for age, gender and education. The Fatigue impact scale and the comprehensive psychopathological rating scale were used to evaluate fatigue, depression and anxiety. Cases had lower average global DNA methylation than controls (81.2% vs 82.7%; p = 0.002). Four hundred and sixty-one differentially methylated regions, containing 3,246 probes mapping to 337 genes were identified. After adjustment for age and smoking, 731 probes in 236 genes were associated with psychopathology (fatigue, depression and/or anxiety). Twenty-four gene ontology terms were associated with psychopathology; terms related to retinoic acid receptor signalling were the most common (adjusted p = 0.0007). One gene in particular, COL11A2, was associated with fatigue following a false discovery rate correction. Our findings indicate that hypomethylation of FKBP5 and retinoic acid receptor related genes serve a potential mechanistic explanation for long-lasting GC-induced psychopathology.

Full text

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Scientific RepoRts | 7:44445 | DOI: 10.1038/srep44445
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Reduced DNA methylation and
psychopathology following
endogenous hypercortisolism –
a genome-wide study
Camilla A. M. Glad1, Johanna C. Andersson-Assarsson2, Peter Berglund3,
Ragnhildur Bergthorsdottir1, Oskar Ragnarsson1,* & Gudmundur Johannsson1,*
Patients with Cushing’s Syndrome (CS) in remission were used as a model to test the hypothesis that
long-standing excessive cortisol exposure induces changes in DNA methylation that are associated
with persisting neuropsychological consequences. Genome-wide DNA methylation was assessed
in 48 women with CS in long-term remission (cases) and 16 controls matched for age, gender and
education. The Fatigue impact scale and the comprehensive psychopathological rating scale were
used to evaluate fatigue, depression and anxiety. Cases had lower average global DNA methylation
than controls (81.2% vs 82.7%; p = 0.002). Four hundred and sixty-one dierentially methylated
regions, containing 3,246 probes mapping to 337 genes were identied. After adjustment for age and
smoking, 731 probes in 236 genes were associated with psychopathology (fatigue, depression and/or
anxiety). Twenty-four gene ontology terms were associated with psychopathology; terms related to
retinoic acid receptor signalling were the most common (adjusted p = 0.0007). One gene in particular,
COL11A2, was associated with fatigue following a false discovery rate correction. Our ndings indicate
that hypomethylation of FKBP5 and retinoic acid receptor related genes serve a potential mechanistic
explanation for long-lasting GC-induced psychopathology.
Hyperactivity of the hypothalamus-pituitary-adrenal (HPA)-axis, with subsequent increase in cortisol exposure
at the tissue level1,2, is implicated in neuropsychiatric disorders such as depression, post-traumatic stress disor-
der and anxiety2–9. Cortisol, the predominant glucocorticoid (GC) in humans, aects the central nervous sys-
tem through binding to its two receptors: the glucocorticoid receptor (GR) and the mineralocorticoid receptor,
encoded by the NR3C1 and NR3C2 genes, respectively. ese receptors are ubiquitously expressed in the brain,
particularly in the hippocampus, prefrontal cortex and the parvocellular nucleus of the hypothalamus10.
Early-life adverse events have been associated with long-lasting dysregulation of the HPA-axis11, which may
play a pathophysiological role in development of stress-related diseases12,13. is early-life molecular program-
ming of the HPA-axis is thought to be conveyed by epigenetic mechanisms14–20. Several studies have shown that
NR3C1 DNA methylation is inuenced by both quality of maternal care (rodents)20 and experience of child-
hood trauma (humans)14,16–19. Furthermore, increased DNA methylation of the NR3C1 gene promoter has been
observed in the hippocampus and prefrontal cortex in suicide victims with a history of childhood abuse15. e
mechanism behind this change in DNA methylation is not known, however it is plausible that the increased cor-
tisol exposure induced by psychological stress may be involved.
Marked chronic excess and attenuation of the endogenous diurnal variation in cortisol secretion causes
Cushing’s syndrome (CS)21, most commonly caused by an ACTH-producing pituitary adenoma (Cushing’s dis-
ease; CD) or a cortisol-producing adrenal adenoma. Subjects with CS display a characteristic clinical pheno-
type including central obesity, muscle and skin atrophy and osteoporosis, as well as marked neuropsychological
1Department of Internal Medicine and Clinical Nutrition, Institute of Medicine at Sahlgrenska Academy, University of
Gothenburg and Department of Endocrinology, Sahlgrenska University Hospital, Gothenburg, Sweden. 2Department
of Molecular and Clinical Medicine, Institute of Medicine at Sahlgrenska Academy, University of Gothenburg,
Gothenburg, Sweden. 3Institute of Neuroscience and Physiology at Sahlgrenska Academy, University of Gothenburg,
Gothenburg, Sweden. *These authors contributed equally to this work. Correspondence and requests for materials
should be addressed to C.A.M.G. (email: camilla.glad@medic.gu.se)
Received: 19 October 2016
Accepted: 08 February 2017
Published: 16 March 2017
OPEN

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complaints such as mental fatigue, anxiety, depression and cognitive impairment22. Following treatment, most
features of the syndrome improve; however, despite long-term remission, we and others have shown that fatigue
and cognitive dysfunction commonly persists23–25. e mechanism for this persistent cognitive impairment is
not known, but the previous excess cortisol exposure is likely to play a mechanistic role26. In fact, in our previous
study there were no associations between aetiology, treatment (surgery and/or pituitary radiation therapy) or
hormone deciency and cognitive dysfunction23.
Due to previous observations of associations between epigenetics and psychopathology14–20, we hypothesized
that long-standing excessive cortisol exposure induces changes in DNA methylation that are associated with
long-lasting fatigue, depression and anxiety. Here, we used patients with CS as a unique human model of endog-
enous hypercortisolism to assess the impact of cortisol on genome-wide DNA methylation and its relation to
psychopathology.
Patients and Methods
Ethical considerations. Informed written consent was obtained from all patients and controls. e local
ethical committee of the University of Gothenburg, Sweden, approved the study. The study was conducted
according to the Declaration of Helsinki.
Design. is was a cross-sectional, case-controlled, single centre study including 55 patients with CS in remis-
sion and 55 controls matched for age, gender and educational level, as previously described23. In this part of the
study the association between DNA methylation and fatigue, depression and anxiety in 48 women with CS in
remission and 16 controls was analysed. e subjects were studied on three occasions, where medical history was
reviewed, physical examination and corticotropin releasing hormone (CRH) stimulation test were performed,
blood samples were drawn and psychopathology was evaluated. A 24-h urinary free cortisol (UFC) sampling
was performed between the second and last visits, and an overnight dexamethasone suppression test was done
following the last visit23.
Patients. e mean age of patients was 53 ± 14 years, and the mean age at diagnosis of CS was 37 ± 14 years
(Table1). irty-seven (77%) patients had CD and 11 (23%) had a cortisol producing adrenal adenoma. To verify
that the initial diagnosis of CD and cortisol producing adrenal adenoma were correct the clinical, biochemical,
radiological and histopathological data from the time of diagnosis were reviewed. In patients with CD in remis-
sion the primary treatment was transsphenoidal pituitary surgery in 25 (68%), radiotherapy in ve (14%) and
bilateral adrenalectomy in seven (19%). Fieen patients needed additional treatment. In total, 29 (78%) patients
with CD were treated with transsphenoidal pituitary surgery, 11 (30%) with radiotherapy and nine (24%) with
bilateral adrenalectomy. All patients with cortisol producing adrenal adenoma had been treated with unilat-
eral adrenalectomy. Eighteen (38%) patients had adrenal insuciency and received replacement therapy with
a mean daily hydrocortisone dose of 24 ± 8 mg/day. e mean urinary free cortisol (UFC) excretion was higher
in patients compared to controls (Table1). Seventeen (35%) patients had central (N = 15) or primary (N = 2)
hypothyroidism and were receiving a mean L-yroxine dose of 104 ± 31 μ g/day. Out of 37 patients with CD, 19
(51%) had growth hormone deciency of whom 15 were on growth hormone replacement therapy. Four out of
20 premenopausal woman (< 52 years) had hypogonadotropic hypogonadism and were receiving estrogen and
progesterone, 2 of 28 postmenopausal women were receiving treatment with oral estrogen. Two women received
replacement with dehydroepiandrosterone.
Controls. Controls to patients, matched for age and gender, were recruited from a random population sam-
ple obtained from the Swedish Tax Agency. Controls were approached through an invitation letter, responding
subjects were interviewed per telephone and those who matched the patient’s educational levels and had no
previously known psychiatric or chronic diseases known to aect cognitive function, were included. In this part
of the study data from one control (N = 16) per three patients (N = 48) were analysed. e mean age was 54 ± 16
years in controls (Table1).
Evaluation of hormone status. All patients were in remission, dened by an adequate suppression of
serum cortisol concentration (≤ 50 nmol/l) following a 1 mg overnight dexamethasone suppression test. e
median (interquartile range) duration of remission was 13 (5–19) years. A CRH test was performed in order
to evaluate the function of the HPA-axis. Serum cortisol was measured using competitive electrochemilumi-
nescence immunoassay (Cortisol Elecsys, Roche Diagnostics Scandinavia AB). Urinary free cortisol (UFC) was
measured using radioimmunoassay (SpectRia Cortisol 125I, Orion Diagnostica Oy, Finland). yroid function
was evaluated clinically and by measurements of free thyroxin and thyroid stimulating hormone (TSH) in serum.
Gonadal function was evaluated by asking for menstruation pattern and/or age at menopause as well as measure-
ments of estrogen and gonadotropins in serum. Growth hormone status was evaluated by review of previously
performed stimulation tests and measurement of insulin-like growth factor I.
Evaluation of fatigue, depression and anxiety. Fatigue was evaluated using the fatigue impact
scale, a 40 item questionnaire where dierent aspects of fatigue (physical, cognitive and social) are evaluated27.
Depression and anxiety were evaluated using the comprehensive psychopathological rating scale28.
DNA isolation and methylation assessment. DNA was isolated from whole blood using the QIAamp
DNA Blood Maxi kit (QIAGEN, Hilden, GE). DNA methylation was assessed on the Illumina Infinium
HumanMethylation450K BeadChip (Illumina, San Diego, CA, USA), which simultaneously interrogates
> 465,000 CpG sites and covers 99% of RefSeq genes and 96% of CpG islands. Probes are distributed in CpG
islands, shelves, shores, promoter regions, 5′ UTRs, rst exon, gene body and 3′ UTRs. Methylation assessment

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was performed at the Mutation Analysis Facility (MAF) at Karolinska University Hospital. e procedure is
briey described below:
Bisulte treatment. 500ng of genomic DNA (OD260/280 > 1.8) was bisulte treated using the EZ-96 DNA
Methylation Kit (D5004; Zymo Research, Inc., Irvine, CA, USA). e CT conversion reagent was mixed with
DNA and incubated in the dark at 50 °C for 16 hours. Aer desulfonation and washing steps, the samples were
puried using spin plates, eluted in 12 μ l elution buer and stored at − 20 °C prior to processing.
Innium Methylation assay. e Innium Methylation Assay was performed according to the manufactur-
er’s instructions. Briey, 4 μ l of denatured bisulte-treated DNA was isothermally amplied over night at 37 °C,
followed by an enzymatic fragmentation step. e fragmented DNA was precipitated, resuspended and loaded
(using a Tecan EVO robot) on the 12-sample BeadChip, which was then incubated overnight at 48 °C, allowing
the fragmented DNA to hybridize to locus-specic 50-mers. Non-specically hybridized DNA was washed away,
followed by a single-base extension reaction using DNP- and Biotin-labeled ddNTPs (with use of a Tecan EVO
robot). Subsequently, hybridized DNA was removed from the labeled oligonucleotide and chips were dried under
vacuum and imaged using an Illumina iScan scanner.
Statistical analyses. Clinical parameters. Statistical analyses were performed with IBM SPSS statistics,
version 22, or in R version 3.0.3. Data are presented as mean ± standard deviation or median (25–75 percentiles).
For comparison between groups we used unpaired t-test for normally distributed data and Mann-Whitney U-test
for non-normally distributed data. For proportions, Pearson Chi-square or Fishers exact test were used. Pearson’s
correlation was used to determine correlation between methylation and clinical parameters. Linear regression
(with adjustment for age and smoking habits) was used to analyse the eect of methylation on clinical parameters.
Patients Controls p
Age at diagnosis (yr) 37 ± 14 — —
Age at follow-up (yr) 53 ± 14 54 ± 16 0.9
Duration of remission (yr) 13 (5–19) — —
Educational level (%) 1.0
Elementary school 25 25
Upper secondary education 46 44
University education 29 31
Smoking habits (%) 0.8
Non-smoker 53 44
Ex-smoker 36 44
Smoker 11 13
Employment (%) 0.1
Full-time 34 63
Part-time 30 13
Sick leave/ Disability pension 11 —
Retirement 26 25
Psychopathology
Fatigue (total score) 63 (40–88) 25 (6–37) < 0.01
Depression (score) 4 (3–7) 2 (1–3) < 0.01
Anxiety (score) 5 (4–7) 3 (3–6) 0.08
Hormone measurements
S-cortisol – BL (nmol/l)*327 ± 129 305 ± 119 0.6
S-cortisol – Peak (nmol/l)*557 ± 147 584 ± 78 0.5
UFC (nmol/24 h) 202 ± 158 131 ± 59 0.02
FreeT4 (pmol/l) 16.7 ± 3.2 14.8 ± 1.5 < 0.01
IGF-I (μ g/l) 149 ± 78 151 ± 84 0.9
Table 1. Background characteristics, sociodemographic status, psychopathology and hormone
measurements in 48 patients with Cushing’s syndrome in remission and 16 controls, matched for age,
gender and educational level. Data is presented as mean ± standard deviation or median (interquartile range).
*S-cortisol levels were analyzed only in ACTH sucient patients (N = 30). S-cortisol was measured in the
morning, before (baseline; BL) and aer administration of CRH; S-cortisol – peak represents the highest level
measured aer CRH administration. Psychopathology was evaluated through Fatigue impact scale (FIS) and
comprehensive psychopathological rating scale (depression and anxiety).

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DNA methylation analyses. Data was extracted using GenomeStudio (Illumina, Methylation Module v1.9),
which was also used to subtract the background and to normalize staining intensities using internal controls
present on the chip. A beta-value was calculated to estimate the methylation level of each CpG locus using the
ratio of intensities between methylated and unmethylated alleles (0 = unmethylated, 1 = fully methylated). e
performances of the dierent controls used were evaluated and potential outliers identied. Data quality control
and analysis was performed using the ChAMP methylation analysis package (v. 1.4.0)29 in R. Briey, intensity data
from IDAT les were loaded, normalized using default settings (i.e. BMIQ) and corrected for batch eects using
ComBat. Dierentially methylated regions (DMR) were then identied using the Probe Lasso DMR Hunter func-
tion with Benjamini-Hochberg p-value adjustment. Correction for multiple testing was done using the “fdrtool”
package (v. 1.2.13) in R.
Gene ontology analyses. Gene ontology analyses were performed in DAVID Bioinformatics Resources 6.7
(NIAID/NIH) using the Functional Annotation Cluster and Functional Annotation Chart functions30,31. DAVID
provides unadjusted p-values as well as p-values adjusted for multiple testing using both the Bonferroni and the
Benjamini methods. Here we present Benjamini-adjusted p-values.
Results
Identication of dierentially methylated regions and overall DNA methylation. Initial quality
control (QC) analyses of the methylation raw data identied one case sample as a technical outlier due to low lev-
els of detected CpG:s (only 38,007 CpG:s were detected with a detection p-value < 0.01), this sample was removed
from further analysis. e nal data set consisted of 47 cases and 16 controls. On average, 485,001 CpG:s were
detected (484,979 in cases and 485,066 in controls, detection p-value < 0.01).
We rst performed DNA methylation analysis in ChAMP, to assess dierences between patients with CS in
long-term remission and matched controls (Table2). Overall, patients had lower average percentage of DNA
methylation than controls (81.2% vs 82.7%, p = 0.002; Fig.1a). ere were 3,903 probes that lay in dieren-
tially methylated regions (DMR:s; n = 461), the majority (n = 3,692; 94.6%) being hypomethylated. Of the 3,903
probes, 3,246 (83.2%) mapped to a gene (n = 337). Of the 337 genes, 278 were exclusively hypomethylated, 7
exclusively hypermethylated and 52 genes contained both hypo- and hypermethylated probes (Supplemental
Table1). Of the 3,903 probes, 55.9% (n = 2,183) had an annotated location; with the most common being gene
body (33.3%), 3′ -UTR (3.9%) and TSS15 (within 1,500 base pairs upstream or downstream of the transcriptional
start site, 2.8%; Fig.1b).
Identication of probes associated with fatigue, depression and anxiety. To investigate whether
the epigenetic status of the CS subjects is associated with persistent fatigue, anxiety or depression a regression
analysis adjusted for age and smoking habits was performed. We identied 731 probes in 236 genes that were
associated with at least one of the three clinical traits. Of these 731 probes; 434 were associated with fatigue, 374
with depression, and 452 with anxiety. One hundred and sixty ve probes in 108 genes were associated with all
three traits.
Aer multiple testing correction using false discovery rate (FDR; 10%), four probes remained signicantly
associated with fatigue; cg22890571 (qval: 0.052), cg16479323 (qval: 0.052), cg09502339 (qval: 0.073), and
cg07889869 (qval: 0.087). ese probes are annotated to the following genes: TFDP1, ITPK1, COL11A2, and
DAGLB. Notably all four probes were also associated with depression and anxiety, however the p-values did not
remain signicant following FDR testing (qval: 0.13–0.23).
Functional validation of identied probes through gene ontology analyses. To explore the func-
tional relevance of the identied DMR:s and clinically associated probes, we next performed gene ontology (GO)
analyses using DAVID30,31. We initially performed GO analysis of all 337 genes with probes that lay in DMR:s and
found 202 GO terms, of which 18 were signicant aer Benjamini correction (Fig.2a). Terms related to retinoic acid,
thyroid hormone receptor and hormone/nuclear hormone receptor binding was the most common (Figs2b and 3a).
Genes, probes and clinical traits No
Total no of probes in DMRs 3903
Signicantly associated with Anxiety 527 (75 does not match a gene)
Signicantly associated with Depression 436 (62 does not match a gene)
Signicantly associated with Fatigue 508 (76 does not match a gene)
Total no of probes in genes 3246
Total no of genes with probes 337
No of probes in genes and signicantly
associated with clinical traits 731
No of genes associated with Anxiety 183
No of genes associated with Depression 172
No of genes associated with Fatigue 194
No of genes associated with Anxiety,
Depression and/or Fatigue 236
Table 2. Summaries from DNA methylation analyses.

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When focusing the analysis on the 236 genes that were associated with at least one of the clinical traits fatigue,
depression, and anxiety, 184 terms were identied of which 24 terms were signicant aer Benjamini correction
(Table3). As before, terms related to retinoic acid were among the most common (Fig.3a).
DNA methylation of the GC receptor gene (NR3C1). To explore the potential eect of hypercorti-
solism on DNA methylation of the NR3C1 gene, we analysed specically DNA methylation of this gene. Fieen
out of 49 probes annotated to the NR3C1 gene were signicantly dierentially methylated in CS cases compared
to controls. Aer multiple testing correction using false discovery rate (FDR, 10%), all 15 probes remained signif-
icant (qval 0.00019–0.065). e most signicant dierence was observed for probe cg15645634 (p = 8.31 × 10−6,
qval: 0.00019), located in intron 8 of the NR3C1 gene. Notably, out of these 15 dierentially methylated probes, 8
probes were specically hypermethylated and 7 probes were hypomethylated (Table4).
Correlation with markers of HPA-axis activity. To validate the functional value of DNA methylation of
the NR3C1 gene and the genes involved in retinoic acid signalling (in total, n = 672 probes), we performed cor-
relation analyses with urinary free cortisol (UFC; n = 47) and the change in serum cortisol concentration (delta
cortisol; n = 24) during a CRH-stimulation test as measures of cortisol exposure and HPA-axis activity, respec-
tively. e CRH-stimulation test was performed in a subgroup of CS patients who had not previously received
Figure 1. (a) Boxplot of average DNA methylation in cases vs controls. (b) Bar graph showing DNA
methylation in dierent regions in cases and controls.
Figure 2. (a) Pie chart showing frequency of DAVID terms. Input data: 337 genes, 18 signicant DAVID terms
aer Benjamini correction. ese 18 terms are grouped into 11 categories as shown above. Genes included in
the GO-term hormone/nuclear hormone receptor binding: ZBTB22, ZBTB9, PHB2, NCOA6, RING1, COL11A2,
DAXX, RGL2. Retinoic acid: RXRB, ZBTB22, ZBTB9, NCOA6, RING1, COL11A2, RGL2. yroid hormone
receptor: ZBTB22, ZBTB9, NCOA6, RING1, COL11A2, RGL2. (b) Venn diagram showing overlap of genes
included in the three most common GO term families: Retinoic acid (in light grey), Nuclear Receptors (in light
blue) and yroid (in dark grey). Numbers reect number of genes in each category.

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pituitary irradiation and who did not receive GC replacement therapy. irty-one probes were signicantly corre-
lated with UFC (SupplementalTable2), with the strongest correlation observed for probe cg02319187 annotated
to the RXRA gene (p = 0.005; Pearson’s r = 0.412). Twenty-ve probes were signicantly correlated with change
in serum cortisol in response to CRH (SupplementalTable3). e strongest correlation was observed for probe
cg00629244, located in the NR3C1 gene (p = 0.002; Pearson’s r = 0.598). ree probes (cg01367322, cg03058556
and cg03825390) annotated to the ZBTB22, ZBTB9 and RGL2 genes (respectively) were signicantly associated
with both UFC and the change in serum cortisol. None of the correlations remained signicant aer correction
for multiple testing (FDR, 10%).
Inuence of current GC replacement therapy on DNA methylation. To evaluate the eect of cur-
rent GC replacement therapy on DNA methylation, we performed a subgroup analysis using the entire data-
set, n = 468,149 probes, where patients were stratied by occurrence of current GC replacement therapy. 12,128
probes in 6,186 genes were dierentially methylated between the two groups. e most signicant dierentially
methylated probe (cg03546163, p = 2.99 × 10−6; Fig.3b) was located in the FKBP5 gene.
In total, there are 34 probes annotated to the FKBP5 gene on the Illumina 450 K methylation chip and four of
these probes showed dierential methylation (cg03546163, cg00058684, cg08586216 and cg25114611) in patients
with, as compared to without, current GC replacement therapy (Table5). Most probes annotated to FKBP5 were
hypomethylated in cases receiving GC replacement therapy; (Fig.3b). No probes remained signicantly dieren-
tially methylated aer multiple testing correction (FDR, 10%). However it is well worth noting that this correction
for multiple testing takes into account a very large number of tests, and that in particular the unadjusted p-value
for FKBP5 probe cg03546163 reached borderline genome-wide signicance (p = 2.99 × 10−6). Together, this sug-
gests a true relevance of this nding, despite qval > 0.1.
Discussion
Hyperactivity of the HPA-axis may increase susceptibility to neuropsychiatric disorders such as depres-
sion, post-traumatic stress disorder and anxiety2–9. Here we provide evidence for a distinguishable pattern of
genome-wide DNA methylation in patients previously treated for CS and propose a mechanism for the long-term
Figure 3. (a) Bar graph showing DNA methylation in retinoic acid-related genes in cases and controls. Only
probes that were dierentially methylated between cases and controls are included. (b) Bar graphs showing
DNA methylation in the FKBP5 gene in cases receiving glucocorticoid replacement therapy (black bars), in
cases not receiving such therapy (strong grey bars) and in controls (so grey bars). Only probes that were
dierentially methylated between cases receiving replacement therapy and cases not receiving such therapy are
included.

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adverse neuropsychological consequences of endogenous hypercortisolism, which is also commonly observed in
a number of dierent psychiatric disorders.
Aberrations in DNA methylation has been associated with neurological and neuropsychiatric disorders such
as autism32, schizophrenia33 and Alzheimer’s disease34, as well as early life adverse events such as child maltreat-
ment and parental stress17. Childhood adverse events may inuence the life-time set point of the HPA-axis35; one
plausible mechanism for the induction of a programmed HPA-axis is through GC-induced epigenetic changes.
GO-terms No of genes Unadjusted P-value Benjamini-adjusted P-value
Alternative splicing 135 4.91E-07 0.0002
Genomewide Association Study of an AIDS-Nonprogression
Cohort Emphasizes the Role Played by HLA Genes (ANRS
Genomewide Association Study 02)
5 3.36E-06 0.0003
GO:0008134~transcription factor binding 23 2.70E-06 0.0006
GO:0004886~retinoid-X receptor activity 5 4.36E-06 0.0007
GO:0042974~retinoic acid receptor binding 6 2.69E-06 0.0012
GO:0030375~thyroid hormone receptor coactivator activity 5 1.12E-05 0.0013
GO:0010861~thyroid hormone receptor activator activity 5 1.12E-05 0.0013
GO:0003708~retinoic acid receptor activity 5 1.66E-05 0.0015
GO:0051059~NF-kappaB binding 6 4.51E-05 0.0034
GO:0030546~receptor activator activity 5 7.55E-05 0.0042
GO:0046966~thyroid hormone receptor binding 6 7.39E-05 0.0047
GO:0006986~response to unfolded protein 9 4.56E-06 0.0062
Splice variant 131 6.79E-06 0.0063
GO:0030374~ligand-dependent nuclear receptor transcription
coactivator activity 6 1.32E-04 0.0066
GO:0042809~vitamin D receptor binding 5 2.63E-04 0.0117
GO:0030545~receptor regulator activity 5 7.54E-04 0.0278
GO:0035257~nuclear hormone receptor binding 7 7.06E-04 0.0284
GO:0046978~TAP1 binding 3 1.14E-03 0.0386
GO:0046979~TAP2 binding 3 1.14E-03 0.0386
GO:0046977~TAP binding 3 1.14E-03 0.0386
GO:0042288~MHC class I protein binding 4 1.31E-03 0.0410
GO:0046983~protein dimerization activity 18 1.51E-03 0.0416
GO:0051427~hormone receptor binding 7 1.42E-03 0.0417
GO:0042824~MHC class I peptide loading complex 4 1.65E-04 0.0419
Table 3. DAVID gene ontology analysis with 236 genes with probes signicantly associated with at least
one clinical trait.
Probe PositionaStrand Loc ation
Intron
number CasesbControlsc
Delta-
betadpqvale
cg15645634 142783639 F Intron 8 0.0356 0.0261 0.0095 8.31E-06 0.000189
cg14558428 142784982 R Intron 8 0.0396 0.0314 0.0082 0.000396 0.004514
cg17860381 142783569 R Intron 8 0.0412 0.0336 0.0076 0.00306 0.015499
cg26464411 142784222 R Intron 8 0.0556 0.0465 0.0091 0.00406 0.017017
cg18019515 142783385 R Intron 8 0.0235 0.0192 0.0043 0.00437 0.017388
cg18146873 142782827 F Intron 8 0.0279 0.0211 0.0068 0.00550 0.018472
cg07733851 142781498 R Intron 8 0.375 0.407 − 0.032 0.00573 0.018648
cg25535999 142757312 R Intron 7 0.922 0.935 − 0.013 0.0110 0.030167
cg18594054 142623446 R Upstream 0.926 0.939 − 0.013 0.0144 0.035689
cg04097219 142629749 F Upstre am 0.972 0.978 − 0.006 0.0177 0.040303
cg06770322 142851098 F Downstream 0.960 0.966 − 0.006 0.0279 0.051311
cg23273257 142658828 R 5′ UTR 0.977 0.982 − 0.005 0.0279 0.051315
cg21702128 142784721 F Intron 8 0.0516 0.0473 0.0043 0.0306 0.053550
cg25781210 142610141 F Upstre am 0.959 0.967 − 0.008 0.0429 0.064421
cg06521673 142782072 R Intron 8 0.0227 0.0201 0.0026 0.0435 0.064851
Table 4. Methylation in een signicantly dierentially methylated probes in NR3C1. Methylation in
een signicantly dierentially methylated probes (reported as beta-values) in NR3C1 on chromosome 5.
aHuman genome build 37. bCS patients. cControls. dDierence in methylation between cases and controls.
eq-values from multiple correction analysis using a 10% FDR.

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We performed a global DNA methylation analysis to assess dierences between patients with CS in long-term
remission and matched controls. Generally, patients with CS had lower levels of DNA methylation than controls.
Four hundred and sixty-one dierentially methylated regions were identied, with the majority being hypo-
methylated in patients. Also, we identied 731 probes in 236 genes that were associated with at least one of three
psychopathological traits; fatigue, anxiety and/or depression. Gene ontology analyses revealed an enrichment of
genes functioning as retinoic acid receptors, thyroid hormone receptors or hormone/nuclear hormone receptors.
ese receptors all belong to the nuclear receptor superfamily36 and serve as ligand-activated regulators of gene
transcription and stimulators of intracellular pathways. ese genes were hypomethylated in cases as compared
to controls, and associated with psychopathology in the patients.
e DNA methylation of the genes belonging to the retinoic acid receptor family was also correlated with
UFC and change in cortisol concentrations during a CRH-stimulation test, suggesting a functional link between
retinoic acid receptor and HPA-axis activity. e retinoic acid family includes Vitamin A and its derivatives, 13-cis
retinoic acid and all-trans retinoic acid. Retinoic acid is a transcriptionally active compound that regulates gene
expression via binding to specic nuclear receptors termed RARs37, or retinoic X receptors (RXRs)38. Retinoic
acid is crucial during development of the central nervous system39–41 and for neuronal plasticity in adult brain42–44.
Previous data suggests an involvement of the retinoic acid family in the regulation of the HPA-axis. Both chronic
(rats)45 and intermittent (humans)46 retinoic acid treatment has been shown able to induce HPA-axis hyperactiv-
ity and anxiety-like, as well as depressive, behaviour. A plausible mechanism may be that the retinoic acid inter-
rupts the GC receptor induced negative feedback47 by down-regulating 11β-HSD1 expression and by inhibiting
GC receptor transactivation48.
Probe PositionaGCRT - yesbGCRT - nocDelta_betadpqvale
cg03546163 35654363 0.484 0.588 − 0.104 2.99E-06 1
cg00052684 35694245 0.514 0.550 − 0.036 0.00159 1
cg08586216 35612351 0.981 0.976 0.0050 0.0122 1
cg25114611 35696870 0.314 0.339 − 0.025 0.0218 1
cg08915438 35697759 0.559 0.588 − 0.029 0.0599 1
cg16052510 35603143 0.809 0.783 0.026 0.0995 1
cg20813374 35657180 0.442 0.462 − 0.020 0.109 1
cg00130530 35657202 0.690 0.710 − 0.020 0.115 1
cg19226017 35697185 0.752 0.770 − 0.018 0.137 1
cg10300814 35565116 0.948 0.953 − 0.0050 0.175 1
cg06087101 35551932 0.418 0.440 − 0.022 0.197 1
cg14642437 35652521 0.876 0.888 − 0.012 0.204 1
cg19014730 35635985 0.681 0.695 − 0.014 0.226 1
cg07843056 35656848 0.0257 0.0229 0.0028 0.305 1
cg07485685 35696061 0.0394 0.0375 0.0019 0.409 1
cg17085721 35645341 0.945 0.949 − 0.004 0.442 1
cg07061368 35631736 0.894 0.901 − 0.007 0.485 1
cg17030679 35696300 0.0215 0.0227 − 0.0012 0.520 1
cg00610228 35695934 0.0368 0.0359 0.0009 0.582 1
cg16012111 35656758 0.0484 0.0500 − 0.0016 0.585 1
cg23416081 35693573 0.208 0.199 0.009 0.613 1
cg11845071 35695859 0.0209 0.0202 0.0007 0.616 1
cg00140191 35656242 0.0634 0.0615 0.0019 0.661 1
cg08636224 35657921 0.961 0.962 − 0.001 0.686 1
cg01294490 35656906 0.0934 0.0913 0.0021 0.687 1
cg18726036 35543610 0.946 0.947 − 0.001 0.707 1
cg03591753 35659141 0.539 0.534 0.005 0.720 1
cg14284211 35570224 0.139 0.134 0.005 0.738 1
cg06937024 35695489 0.0259 0.0264 − 0.0005 0.791 1
cg00862770 35655764 0.0256 0.0251 0.0005 0.795 1
cg02665568 35544468 0.921 0.923 − 0.002 0.799 1
cg07633853 35569471 0.155 0.157 − 0.002 0.829 1
cg15929276 35687457 0.187 0.186 0.001 0.911 1
cg10913456 35656590 0.0175 0.0175 0.000 0.989 1
Table 5. Methylation in FKBP5, grouped based on GC replacement therapy. Summary of methylation
(reported as beta-values) in FKBP5 on chromosome 6. GCRT = glucocorticoid replacement therapy. aHuman
genome build 37. bPatients receiving GCRT. cPatients not receiving GCRT. dDierence in methylation between
patients receiving GCRT and those not receiving such therapy. eq-values from multiple correction analysis using
a 10% FDR.

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Early adverse events and poor maternal care have been linked to changes in the GC receptor (NR3C1) DNA
methylation. To explore the potential eect of hypercortisolism on NR3C1 DNA methylation specically, we
analysed methylation in this gene and found that 15 out of 49 probes annotated to the NR3C1 gene were dier-
entially methylated in cases as compared to controls. Previously, increased levels of NR3C1 methylation has been
observed in post-mortem hippocampal brain tissue from suicide victims who had endured childhood abuse15,
and in peripheral blood from subjects with a history of perinatal stress16–18 and neglect or abuse during child-
hood49,50. Recently, common stressful life events were found to be associated with higher blood DNA methyla-
tion of the NR3C1 gene in adolescents51, suggesting that the NR3C1 DNA methylation is subject to change not
only during childhood. In accordance, herein we report that adults who have endured long-term endogenous
hypercortisolism have a dierential pattern of NR3C1 DNA methylation than matched controls, lending further
support for the importance of excess cortisol exposure as a possible cause in the programming of the HPA-axis
and its psychological consequences.
To evaluate the possibly confounding eect of current GC replacement therapy on our results, we performed
a subgroup analysis dividing the cases into groups of patients receiving GC replacement or not. ese analyses
revealed that the DNA methylation of 12,128 probes in 6,186 genes was inuenced by current GC replacement
therapy. One of the genes that were specically hypomethylated in cases compared to controls, with an additional
reduction in patients currently receiving GC replacement therapy, was the FK506 binding protein 5 (FKBP5).
FKBP5 binds to and negatively regulates GR function, which subsequently reduces anity of the GR to corti-
sol52. Common genetic variants in the FKBP5 gene have been associated with a relative GR resistance, and found
to interact with childhood abuse to predict post-traumatic stress disorder53. Previously, studies in mice have
reported that long-lasting exposure to GC decreases FKBP5 DNA methylation in the hippocampus, hypothala-
mus and blood, and that this demethylation is associated with anxiety-like behavior54,55 and reect previous GC
load55. Consistent with these ndings, herein we show that FKBP5 is indeed hypomethylated in CS patients as
compared to controls, and that the methylation is further reduced in a sub-group of CS patients receiving GC
replacement. ese ndings validate the suitability of CS as study model for GC exposure and further enlighten
the strong eect of GC on DNA methylation.
Despite the rigorous study protocol and adequate study model this project is not without limitations. Firstly,
the DNA methylation was assessed in whole blood and not in brain or any other isolated GC target tissue. A
recent study, however, provided evidence that DNA methylation variation observed in the brain is in fact reected
in the blood56. Secondly, the ndings herein remain to be validated and further explored as for whether the
observed changes in DNA methylation are indeed associated with subsequent changes in mRNA and protein
expression. Lastly, these ndings remain to be validated in studies of patients with specic psychiatric disorders
with HPA-axis hyperactivity.
In conclusion, our ndings suggest that long-standing hypercortisolism reduces global DNA methylation,
specically in genes that are known to attenuate the sensitivity of the GC receptor and therefore may induce
hyperactivity of the HPA-axis. Consequently, this may be of importance for the action of cortisol on the central
nervous system, and by such contribute to the frequent psychopathology observed in our patients. e mecha-
nism proposed might also apply to other disorders with transient or chronic hyperactivation of the HPA-axis that
aects a considerable part of the general population; such as depression, generalised anxiety and post-traumatic
stress.
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Acknowledgements
We would like to extend our gratitude to all of those who aided in performing this study, especially Ann-Charlotte
Olofsson and Jenny Tiberg at the Centre for Endocrinology and Metabolism at Sahlgrenska University Hospital,
for their skilful technical support and to Jessica Lindvall, Kristina Duvefelt and Gunnar Falk at the Mutation
Analysis Facility at Karolinska University Hospital for excellence in planning, running and correspondence
related to the DNA methylation analyses. Last but not least, we are indebted to the patients and controls that
participated in this study. is project has received nancial support from the Swedish federal government
under the LUA/ALF agreement (Drs Ragnarsson and Johannsson), e Health & Medical Care Committee of
the Regional Executive Board, Region Västra Götaland (Dr Ragnarsson), e Swedish Society of Medicine (Dr
Ragnarsson) and e Swedish Society of Endocrinology (Dr Ragnarsson).
Author Contributions
Dr Johannsson had full access to all the data in the study and takes responsibility for the integrity of the data
and the accuracy of the data analysis. Study concept and design: Glad, Berglund, Bergthorsdottir, Ragnarsson,
Johannsson, Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: Glad,
Ragnarsson. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis:
Glad, Andersson-Assarsson. Obtained funding: Ragnarsson, Johannsson. Administrative, technical, or material
support: Glad, Andersson-Assarsson, Berglund. Study supervision: Ragnarsson, Johannsson.
Additional Information
Supplementary information accompanies this paper at http://www.nature.com/srep
Competing Interests: CG, JAA, RB and OR have no disclosures. PB has received lecture fees from Boehringer
Ingelheim and Lundbeck. GJ has received lecture fees from NovoNordisk, Pzer, Otsuka and Shire, and has
been a consultant for Viropharma/Shire and Astra Zeneca.
How to cite this article: Glad, C. A. M. et al. Reduced DNA methylation and psychopathology following
endogenous hypercortisolism – a genome-wide study. Sci. Rep. 7, 44445; doi: 10.1038/srep44445 (2017).
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