Content uploaded by Shufang Wang RENAULT
Author content
All content in this area was uploaded by Shufang Wang RENAULT on Aug 26, 2016
Content may be subject to copyright.
Available via license: CC BY-NC 4.0
Content may be subject to copyright.
EXTENDED REPORT
Overlap between differentially methylated DNA
regions in blood B lymphocytes and genetic at-risk
loci in primary Sjögren’s syndrome
Corinne Miceli-Richard,
1
Shu-Fang Wang-Renault,
2,3
Saida Boudaoud,
1
Florence Busato,
2
Céline Lallemand,
2
Kevin Bethune,
2
Rakiba Belkhir,
1
Gaétane Nocturne,
1
Xavier Mariette,
1
Jörg Tost
2
Handling editor Tore K Kvien
▸Additional material is
published online only. To view
please visit the journal online
(http://dx.doi.org/10.1136/
annrheumdis-2014-206998).
1
Université Paris-Sud, Hôpitaux
Universitaires Paris-Sud, AP-HP,
Institut National de la Santé et
de la Recherche Médicale
(INSERM) U1184, Center for
immunology of viral infections
and autoimmune diseases,
Le Kremlin Bicêtre, France
2
Laboratory for Epigenetics and
Environment, Centre National
de Génotypage—CEA/Institut
de Génomique, Evry, France
3
CEA, IDMIT Center, DSV/
iMETI, INSERM U1184,
Fontenay-aux-Roses, France
Correspondence to
Dr Jörg Tost, Laboratory for
Epigenetics and Environment,
Centre National de
Génotypage, CEA-Institut de
Génomique, Bâtiment G2,
2 rue Gaston Crémieux, CP
5721, Evry, Cedex 91057,
France; tost@cng.fr
CM-R and S-FW-R contributed
equally.
XM and JT are two senior
authors and contributed
equally.
Received 14 November 2014
Revised 6 April 2015
Accepted 26 April 2015
Published Online First
13 July 2015
To cite: Miceli-Richard C,
Wang-Renault S-F,
Boudaoud S, et al.Ann
Rheum Dis 2016;75:
933–940.
ABSTRACT
Background Beyond genetics, epigenetics alterations
and especially those related to DNA methylation, play
key roles in the pathogenesis of autoimmune diseases
such as primary Sjögren’s syndrome (pSS) and systemic
lupus erythematosus. This study aimed to assess the role
of methylation deregulation in pSS pathogeny through a
genome-wide methylation approach.
Patients and methods 26 female patients with pSS
and 22 age-matched controls were included in this
study. CD4+ T cells and CD19+ B cells were isolated
from peripheral blood mononuclear cells by magnetic
microbeads and their genome-wide DNA methylation
profiles were analysed using Infinium Human
Methylation 450 K BeadChips. Probes with a median
DNA methylation difference of at least 7% and p<0.01
between patients and controls were considered
significantly differentially methylated.
Results Methylation alterations were mainly present in
B cells compared with T cells. In B cells, an enrichment
of genes with differentially methylated probes in genetic
at-risk loci was observed, suggesting involvement of
both genetic and epigenetic abnormalities in the same
genes. Methylation alterations in B cells were more
frequent in some specific pathways including Interferon
Regulated Genes, mainly among patients who were
autoantibody positive. Moreover, genes with differentially
methylated probes were over-represented in B cells from
patients with active disease.
Conclusions This study demonstrated more important
deregulation of DNA methylation patterns in B cells
compared with T cells, emphasising the importance of B
cells in the pathogenesis of the disease. Overlap
between genes with differentially methylated probes in B
lymphocytes and genetic at-risk loci is a new finding
highlighting their importance in pSS.
INTRODUCTION
Primary Sjögren’s syndrome (pSS), also referred to
as autoimmune epithelitis, is a complex systemic
autoimmune disease (AID) affecting 0.01% to
0.3% of the general population with a 9/1 female
predisposition.
12
Lymphoid infiltration of lacrimal
and salivary glands leading to xerophthalmia and
xerostomia, as well as enhanced activation of poly-
clonal B lymphocytes, is the hallmark of the
disease. The disease mainly affects the exocrine
glands ( particularly salivary and lacrimal glands),
but one-third of the patients develop several
systemic complications, such as renal, pulmonary
or neurological manifestations. Around 5% of
patients with pSS will develop lymphoma. In spite
of the progress in the past 10 years, the pathogen-
esis of the disease remains to be elucidated.
3
Genetic studies represent a powerful tool for the
identification of new pathogenic pathways. Results
of the first genome-wide association study (GWAS)
among Caucasian patients with pSS were recently
published.
4
The genetic loci most significantly asso-
ciated with pSS were the major histocompatibility
complex/human leucocyte antigen (MHC/HLA)
region, IRF5,BLK,STAT4,IL12A,TNIP1 and
CXCR5. Therefore, the findings of this first GWAS
in pSS highlight the three major pathogenic steps
implicated in this disease: activation of the innate
immune system, notably through the interferon
(IFN) system; B cell activation, through CXCR5-
directed recruitment to lymphoid follicles and
B cell receptor activation involving Blk; and T cell/
NK cell activation owing to HLA susceptibility and
the interleukin (IL)-12–IFNγaxis.
Beyond genetics, epigenetics alterations including
changes in DNA methylation, histone modifications
and microRNA expression probably play key roles in
the pathogenesis of AIDs such as pSS.
5–7
Although
the understanding of epigenetics in pSS is limited at
present, distinct salivary gland microRNA expression
patterns have been linked to the disease.
8
DNA
methylation is considered the core epigenetic mech-
anism that regulates gene expression by altering tran-
scriptional accessibility of gene regulatory regions.
Two recent studies investigated DNA methylation
changes in naïve CD4+ T cells from patients with
lupus and demonstrate that IFN-regulated genes
(IRGs) in blood CD4+ T cells from patients with
lupus are epigenetically poised for transcription.
910
The first epigenome-wide DNA methylation study in
patients with pSS analysing blood naive CD4+
T cells found a similar hypomethylation of a set of
IRGs.
11
In the present study, we performed a genome-
wide DNA methylation study in blood CD4+
T cells and in blood CD19+ B cells and found that
DNA methylation changes were significantly more
frequent in B cells compared with T cells and were
implicating the same genes and pathways found to
be associated with the disease in genetic studies.
The presence of abnormalities in pathways shared
by genetics and epigenetics provides a strong
Open Access
Scan to access more
free content
Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998 933
Basic and translational research
argument for the importance of these pathways in the pathogen-
esis of the disease.
PATIENTS AND METHODS
Patients
Twenty-six female Caucasian patients with pSS and 22 age- and
ethnicity-matched controls recruited in a tertiary national refer-
ence centre for pSS in France were included in this study. All
patients with pSS fulfilled the American European consensus
group (AECG) 2002 criteria for the disease. Activity of the
disease was assessed by the recently validated EULAR Sjögren’s
syndrome Disease Activity Index (ESSDAI) score.
12
Controls
were either healthy subjects or patients suffering from a mech-
anical rheumatological condition without any sign of auto-
immunity, cancer or inflammation. None were sicca controls.
The study was approved by the local ethics committee and
written informed consent was obtained from all patients and
controls.
Cell isolation and DNA preparation
CD4+ T lymphocytes and CD19+ B lymphocytes were purified
from peripheral blood mononuclear cells (PBMCs) of patients
and controls by direct magnetic labelling with CD4 and CD19
microbeads (Miltenyi Biotec, Paris, France), and their purity was
analysed on a BD FACSCanto (BD Biosciences, San Jose,
California, USA) and confirmed to be higher than 95%. DNAs
were extracted using the QIAamp DNA Mini Kit (Qiagen
GmbH, Hilden, Germany) according to the manufacturer’s
protocol.
Genome-wide DNA methylation study and validation of
differentially methylated CpG sites by pyrosequencing
DNAs were analysed using the Infinium Human Methylation
450 K BeadChips (Illumina, San Diego, California, USA) accord-
ing to the manufacturer’s protocol. Quantitative DNA methyla-
tion analysis for validation was performed by pyrosequencing
13
as described in detail in the online supplementary methods.
Statistical analyses
Raw signals of 450 K BeadChips were extracted using the
GenomeStudio software (V.2011.1, Illumina) and processed
using a refined version of the SQN pipeline
14
as described in
detail in the online supplementary methods. For the comparison
of DNA methylation levels of CpG sites between patients and
controls, CpG sites with a methylation difference of more than
7% and a statistical difference of p<0.01 in a non-parametric
Mann–Whitney test were considered as statistically significantly
differentially methylated. Genes were considered as differen-
tially methylated if two CpG fulfilled these differences. Analyses
restricted to the probes located at the gene start and promoter
regions were also provided. Potential enrichment of differen-
tially methylated regions in genomic intervals was tested using
an in-house developed R script. Significance of the enrichment
was estimated based on Monte Carlo simulations.
The most over-represented biological terms and canonical
pathways related to the differentially methylated genes were
identified using Ingenuity Pathway Analysis (Qiagen) by submit-
ting the gene lists as defined above. A Benjamini–Hochberg
corrected p value <0.05 was considered significant. The
Interferome database
15
(http://interferome.its.monash.edu.au/
interferome/home.jspx) was used for the analysis of the possible
involvement of significantly differentially methylated IRGs in
pSS. In addition, a manually curated list including ∼100 IRGs
based on the published literature was used for the same
purpose.
10 16–22
RESULTS
Twenty-six female Caucasian patients with pSS and 22 age- and
ethnicity-matched controls were included in this study (see
online supplementary table S1). Seventy-three per cent of the
patients had anti-SSA antibodies and 42% anti-SSB antibodies.
All patients producing anti-SSB antibodies were also anti-SSA
positive. Mean ESSDAI was 3.5±4. The genome-wide DNA
methylation analysis using the 450 K BeadChips showed large
differences in DNA methylation patterns between CD19+ B
lymphocytes and CD4+ T lymphocytes from patients with pSS
with more than 60 000 CpG sites being differentially
methylated.
Methylation status of purified blood T cells from patients
with pSS
Among purified CD4+ T cells, only 119 probes were detected
in patients compared with the control cohort to be differentially
methylated at a threshold of 7% (see online supplementary data
file). These probes were distributed across 74 genes; 40 genes
(54%) were hypermethylated, 33 genes (45%) were hypomethy-
lated and a single gene displayed a mixed methylation pattern
(figure 1A). Forty-three probes were found when the DNA
methylation analysis was restricted to gene start and promoter
regions (where DNA methylation changes might correlate
inversely with the gene expression potential). These probes
were distributed across 37 genes including 18 hypermethylated
genes (49%) and 19 hypomethylated genes (51%) (figure 1B).
Furthermore, seven genes were differentially methylated at two
or more CpGs (figure 1C), four of which in the promoter
regions (figure 1D).
Methylation status of purified blood B cells from patients
with pSS
In B lymphocytes, out of a total 6707 probes, 3754 hyper-
methylated (56%) and 2953 (44%) hypomethylated probes
were found in patients compared with the control cohort. These
probes were distributed across 3619 genes including 1972
(55%) genes with only hypermethylated CG sites, 1389 (38%)
genes with only hypomethylated CG sites and 258 (7%) genes
with mixed methylation pattern of CpG sites (figure 2A).
Among them, 2393 probes were located in the gene start/pro-
moter regions (figure 2B). Eight hundred and ninety-nine genes
were differentially methylated at two or more CpG positions:
363 hypermethylated (40%), 278 hypomethylated (31%) and
258 (29%) displaying mixed methylation pattern (figure 2C).
A total number of 391 genes showed differential methylation in
the gene start/promoter regions corresponding to 162 hyper-
methylated (42%), 173 hypomethylated (44%) and 56 genes
(14%) displaying a mixed methylation pattern (figure 2D).
Increasing the methylation difference to 10%, 15% or 20%
did not change the proportions significantly (see online
supplementary figure S1). The differentially methylated genes
detected with different methylation thresholds are presented in
the online supplementary data file. Consistent with the similar
numbers of hyper and hypomethylated probes/genes found in
the genome-wide study, no change of the global methylation
status was observed by pyrosequencing analysis of multicopy
repetitive elements (ALU and LINE1) (data not shown).
Subsequently, the location of the differentially methylated CpG
sites in relation to genomic elements such as CpG islands
(islands, shores, shelves and other) or gene structure (TSS1500,
934 Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998
Basic and translational research
TSS200, 50UTR, first exon, gene body, 30UTR and intergenic)
was analysed to investigate a differential representation of func-
tional categories (see online supplementary figure S2). The
differentially methylated probes in CD19+ cells from patients
with pSS had a similar repartition in shores and shelves when
compared with the overall proportion of these probes on the
Figure 2 Methylation status of purified B lymphocytes from patients with primary Sjögren’s syndrome (pSS) compared with controls. (A) Probes
with at least 7% median difference of methylation and p<0.01 found in B lymphocytes from patients with pSS compared with the control cohort
and number of genes with at least one probe differentially methylated. (B) Probes in the TSS/promoter region with more than 7% median difference
of methylation and p<0.01 found in B lymphocytes from patients with pSS compared with the control cohort and number of genes with at least one
probe differentially methylated. (C) Number of the genes with a minimum of two probes using the same thresholds. (D) Number of genes with
minimum two probes in TSS/promoter regions with more than 7% median difference and p<0.01.
Figure 1 Methylation status of purified lymphocyte T cells from patients with primary Sjögren’s syndrome (pSS) compared with controls. (A)
Probes with at least 7% median difference of methylation and p<0.01 found in T lymphocytes from patients with pSS compared with the control
cohort and number of genes with at least one probe differentially methylated. (B) Probes in the TSS/promoter region with more than 7% median
difference of methylation and p<0.01 found in T lymphocytes from patients with pSS compared with the control cohort and number of genes with
at least one probe differentially methylated. (C) Number of the genes with a minimum of two probes using the same thresholds. (D) Number of
genes with minimum two probes in TSS/promoter regions with more than 7% median difference and p<0.01. Genes with hypermethylated probes
are denoted with ‘+’; genes with hypomethylated probes with ‘−’; genes with hyper and hypomethylated probes are annotated as mixed genes.
Similar representations for other methylation thresholds are shown in online supplementary figure S1.
Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998 935
Basic and translational research
BeadChip, but were significantly depleted in CpG islands
(14.6% vs 30. 9% of total probes; p<0.05 Monte Carlo simula-
tion, n=5000) and enriched outside CpG islands (47.74% vs
36.38% of total probes, p<0.05). No significant difference was
found with the location of differentially methylated CpG sites
in relation to gene structure (see online supplementary figure
S2). To investigate if DNA methylation alterations could cluster
at specific chromosomal loci such as the MHC, an enrichment
analysis was performed using the positions and density of
probes on the array as background. However, no loci were iden-
tified as enriched (data not shown).
Validation of CpG methylation changes by pyrosequencing
To validate the results from the 450 K BeadChip, we quantita-
tively analysed DNA methylation patterns of the CpGs of inter-
est in B lymphocytes by pyrosequencing (figure 3A). All DNA
methylation alterations in IFN-related genes including IFITM1,
IFITM3,IFI44 L,IRF5 were validated by pyrosequencing with a
p value<0.05 (figure 3B). Other genes of potential interest for
their implication in the disease pathogenesis (RUNX3,TNFAIP8,
IKZF1,SLC15A4,GRB2,MIR21,IL21R,CXCR5, and TRAF5)
found with significantly differentially methylated probes were
also confirmed by pyrosequencing in patients with pSS com-
pared with controls (figure 3A) demonstrating the confidence in
the obtained gene lists.
Pathway analysis
To identify pathways possibly influenced by the differential methy-
lation in B lymphocytes from patients with pSS compared with
controls, we performed a pathway analysis using only genes with a
minimum of two differentially methylated CpG sites. IL-4, IL-8,
CXCR4, PTEN and B cell receptor signalling, B cell development,
altered Tcell and B cell signalling in rheumatoid arthritis and sys-
temic lupus erythematosus (SLE) signalling were identified as
enriched pathways (figure 4). Differentially methylated genes were
enriched for chronic inflammatory disease (p=6.76×10
−7
), arth-
ritis (p=3.16×10
−6
), rheumatic disease ( p=1.31×10
−5
), systemic
autoimmune disorder (p=1.24×10
−4
), lymphoid cancer
(p=1.26×10
−4
), lymphomagenesis (p=1.46×10
−4
) as disease
annotation. Furthermore, as ∼5% of patients with pSS develop
lymphoma, gene lists were investigated for genes associated with
B-cell lymphoma and 22 significantly differentially methylated
genes involved in lymphoma including TNFRSF10A, IRF8,
CXCR5, LTA, SOCS1, TNF, BCL2, PSMB2, PIK3CD
(p=5.37×10
−4
) were found.
Furthermore, although not differentially methylated them-
selves, several proteins and cytokines, including some which
have been previously implicated in AIDs, were identified as
upstream regulators, whose deregulation could be at least par-
tially responsible for the observed effects at the DNA methyla-
tion level: IL27 (p=3.54×10
−5
), IFNγ(p=0.002), IFNα
(p=0.002), CD40 L ( p=0.001), TLR3 ( p=9.11×10
−4
), TLR7
(p=0.006) as well as the oestrogen receptor ( p=7.71×10
−5
).
Overlap between genome-wide DNA methylation analysis
and genetic at-risk loci
A GWAS performed in American and European patients with
pSS showed that the HLA region on chromosome 6 was
strongly associated with pSS.
4
Furthermore, single nucleotide
polymorphisms (SNPs) in or close to IRF5-TNPO3,STAT4,
IL12A,FAM167A-BLK,DDX6-CXCR5 and TNIP1 were also
strongly associated with pSS; while TNFAIP3,DGKQ,ITSN2
showed associations with suggestive significance. Investigating
the overlap between the genes having at least one differentially
methylated probe and the GWAS at-risk loci, 7/17 GWAS as
at-risk loci (HLA-DRA, HLA-DQB1, IFR5,CXCR5,BLK,
PRDM1,ITSN2) for patients with pSS showed at least one sig-
nificantly differentially methylated probe (table 1A). Similarly,
Figure 3 Validation of DNA methylation changes in different genes by pyrosequencing. (A) A selection of genes found significantly differentially
methylated in 450 K BeadChip and validated by pyrosequencing. (B) Boxplots of DNA methylation levels of several representative interferon
regulated genes by pyrosequencing are shown.
936 Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998
Basic and translational research
the overlap was investigated with respect to the GWAS per-
formed in Han Chinese patients with pSS, and of the seven
genes identified in this study, four (GTF2I, HLA-DQA1,
HLA-DPB1, COL11A2) were also found with at least one sig-
nificantly differentially methylated probe in B cells from patients
with pSS (table 1B).
23
Association of DNA methylation with disease activity
in B lymphocytes from patients with pSS
To correlate DNA methylation with disease activity, we analysed
the methylation status of B lymphocytes from patients with pSS
with high (≥5) or low (<5) ESSDAI score compared with the
control cohort. Among the patients with pSS with high ESSDAI
score, 5687 genes were detected with at least one significantly
differentially methylated probe, while among those with low
ESSDAI score, much fewer genes (n=1772) were found (see
online supplementary figure S3). Some of the above described
canonical pathways like IL-8 and CXCR4 signalling (figure 4)
were only significantly enriched in patients with high ESSDAI
scores , while B cell development and altered Tcell and B cell sig-
nalling in rheumatoid arthritis was only found in patients with
low ESSDAI scores.
Patients with pSS were also divided into three sub-groups
based on the production of anti-SSA and anti-SSB autoanti-
bodies. In B lymphocytes from patients who were anti-SSA
negative, only 535 genes were found with at least one signifi-
cantly differentially methylated probe (see online supplementary
figure S4), while B lymphocytes from patients who were
anti-SSA+/anti-SSB−and anti-SSA+/anti-SSB+ pSS showed
1798 and 3674 genes, respectively. The identified significantly
enriched pathways shown in figure 4 were only found in auto-
antibody producing subgroups (figure 4).
As IFNαand IFNγwere found as predicted upstream regula-
tors of the observed changes in this study, patients with pSS were
reported to show an IFN signature
16
and IPA has been reported
to have some shortcomings in the identification of an IFN
signature,
10
we submitted the gene lists with at least two differen-
tially methylated CpG positions to the interferome database
15
to
identify IRGs. Compared with the controls, B lymphocytes from
patients with pSS producing only anti-SSA antibodies, or both
anti-SSA and anti-SSB, showed a similar proportion of differen-
tially methylated IRGs (9.9% vs 10.9%), whereas this proportion
dropped significantly (4.3%) in B lymphocytes from patients
with pSS without autoantibodies (see table 2 and online
supplementary table S2). The difference in IFN signatures
between the patients producing autoantibodies and the seronega-
tive patients was also confirmed by crossing our gene lists with a
manually curated IRG list (data not shown). All these results lead
to the conclusion that in B lymphocytes the level of methylation
of a large number of genes including those involved in the IFN
signature is associated with disease activity in patients with pSS.
DISCUSSION
This genome-wide methylation study on cell sorted PBMC
populations of patients with pSS revealed that methylation
alterations are mainly present in B cells compared with T cells.
In contrast to previous reports on DNA methylation changes in
AIDs,
24
we did not observe a global hypomethylation in our
study with relatively equal number of hypermethylated and
hypomethylated genes as well as an absence of changes of DNA
methylation patterns at repetitive elements.
Very interestingly, 40% of genes genetically associated to the
disease were detected with at least one differentially methylated
CpG site, suggesting the involvement of both genetic and epi-
genetic abnormalities in the same genes and emphasising the
role of these genes in the pathogenesis of the disease. The
mechanisms causing AIDs are poorly understood. Different cells
might play a biased role in the development of different AIDs.
Our study is the first to analyse genome-wide DNA methylation
patterns in B cells of patients with pSS . Recently, Altorok et al
reported the methylation deregulation in naïve CD4+ T cells
from patients with pSS using the same technology as in our
study.
11
They identified about 426 differentially methylated
genes with three quarters of them being hypomethylated. This
number is much larger than the genes identified in the current
study (n=74). Of note, in T cells, four hypomethylated (STAT1,
SH3PDX2A,FLI37453, USP18) and one hypermethylated gene
(FBXL16) were found in both studies. The observed difference
might be due to a difference in the analysed cell population as
Altorok et al analysed only naïve CD4+ T cells, while ours ana-
lysed all CD4+ cells as well as differences in the patient popula-
tion such as a younger age in the Altorok study and different
prevalence of autoantibodies, different treatments and different
disease activity, which might influence T cell populations.
Furthermore, the time point in the disease course, at which sam-
pling has occurred, or lifestyle factors might have an impact on
the DNA methylation profile.
Analysis of genome-wide DNA methylation patterns in
CD4+ T cells, CD19+ B cells and CD14+ monocytes from
patients with SLE
10
showed six times more DNA methylation
changes in T cells compared with B cells and ten times more
than in monocytes, in concordance with the hypothesis that T
lymphocytes play a central role in the development of SLE.
25
Our results show that the situation is different in pSS with more
DNA methylation alterations present in B lymphocytes com-
pared with T cells. These findings are in concordance with
several recent reports showing that B cells may play a central
role in the development of pSS.
326
Only few markers differen-
tially methylated in both T cells and B cells were identified in
our study, underlining the importance that methylation studies
Figure 4 Pathway analysis of the differentially methylated genes in
CD19+ B cells from patients with pSS or from sub-groups of patients.
The dashed line represents a p value of 0.05. BL, Total B lymphocytes;
IL, interleukin; pSS, primary Sjögren’s syndrome; RA, rheumatoid
arthritis; SLE, systemic lupus erythematosus.
Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998 937
Basic and translational research
have to be conducted in well-characterised pure cell popula-
tions
27
and that the choice of the selected cell population is of
critical importance to decipher a disease. It would have been
desirable to analyse even more specific subpopulation of the B
cells, which might show a more pronounced epigenetic deregu-
lation such as naïve B cells, memory B cells or plasmablasts.
However, the quantity of blood required for the 450 K
BeadChips cannot be reasonably obtained from patients and
controls. The observed DNA methylation changes should
however not be due to a shift in the subpopulations as the total
number of lymphocytes is decreased in patients with pSS, but
the percentage of B cells, naïve B cells, memory B cells, CD4,
CD8 and NK cells is the same as in controls (Mariette, unpub-
lished data).
Differential DNA methylation in B lymphocytes was found
among other loci in HLA-DRA, HLA-DQB1, IRF5,CXCR5,
BLK,PRDM1,ITSN2 which were all identified in a recent
GWAS as at-risk loci,
4
suggesting that both genetic and epigen-
etic alterations in the same genes closely interact in the develop-
ment and course of AIDs emphasising the probable important
role of these genes in the pathogenesis of the disease. Similar
observations have been previously reported in other AIDs such
as rheumatoid arthritis with multiple interactions between
genetic and epigenetic variants in the MHC region
28
or lupus.
29
We previously investigated in a gene-specific study the pro-
moter region of IRF5 since an SNP associated with pSS con-
sisted of a four times repeat of a CGGGG motif which is
repeated only three times in the wild type allele.
30
As this
Table 1 Genes with significantly differentially methylated probes found at GWAS at-risk loci
GeneID ProbeID on 450 K BeadChips CHR Chromosome position
Difference in median of DNA
methylation in patients vs controls (%)
Panel (A): Overlap with GWAS at-risk loci in American and French patients with pSS
HLA-DRA cg00383136 6 32410247 7.25
HLA-DRA cg05500783 6 32410873 9.00
HLA-DRA cg13022993 6 32409856 9.85
HLA-DRA cg22937462 6 32411185 12.00
HLA-DRA cg25764570 6 32407289 9.37
HLA-DRA cg26684131 6 32410365 8.41
HLA-DRA cg17606183 6 32409413 13.11
HLA-DRA cg23732629 6 32409386 8.80
HLA-DQB1 cg24593918 6 32633157 11.44
HLA-DQA1 cg10217052 6 32607174 8.57
IRF5 cg04864179 7 128579964 13.23
IRF5 cg12816198 7 128577593 14.23
CXCR5 cg04537602 11 118763859 9.49
CXCR5 cg13298528 11 118763863 9.03
CXCR5 cg24342283 11 118758603 8.18
CXCR5 cg19791714 11 118763901 9.66
CXCR5 cg01943632 11 118764337 8.54
CXCR5 cg06583259 11 118758992 7.31
BLK cg04441667 8 11356603 7.26
BLK cg16861076 8 11421594 −7.14
PRDM1 cg17143179 6 106546824 9.44
ITSN2 cg11724461 2 24553192 14.89
ITSN2 cg06652632 2 24584081 7.83
Panel (B): Overlap with GWAS at-risk loci in Chinese Han patients with pSS
GTF2I cg21983531 7 74075317 18.21
HLA-DQA1 cg10217052 6 32607174 8.57
HLA-DPB1 cg21151963 6 33043220 11.69
HLA-DPB1 cg10136841 6 33046582 10.43
HLA-DPB1 cg23750365 6 33043072 10.24
COL11A2 cg13390480 6 33138503 7.64
GWAS, genome-wide association study; pSS, primary Sjögren’s syndrome.
Table 2 Number and percentage of significantly differentially methylated IFN-regulated genes found in B lymphocytes from patients with pSS
who were autoantibody positive or negative compared with the control cohort, respectively
Patients subgroups
compared with controls
Differentially methylated
genes used for analysis
Differentially methylated
IRGs found
Percentage of differentially
methylated IRGs found
Anti SSA+ anti-SSB+ 699 genes 76 genes 10.9
Anti SSA+ anti-SSB−242 genes 24 genes 9.9
Anti-SSA−47 genes 2 genes 4.3
Genes with at least two CpG sites significantly differentially methylated (at least 7% median difference of methylation, p<0.01) were included in the analysis.
IFN, interferon; IRGs, IFN-regulated genes; pSS, primary Sjögren’s syndrome.
938 Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998
Basic and translational research
polymorphism introduces a supplementary CpG, we investi-
gated CpGs around this location as well as the transcription
start site of IRF5, but found no significant differences. In the
present study, we confirm the lack of a significant difference
between patients with pSS and controls regarding the previously
studied CpGs, but identified differentially methylated CpG in
IRF5 locus 400 bp apart from the previously studied CpGs and
closer to the locus of genetic association, which is ∼2 kb further
upstream. This observation reinforces the usefulness of tools
that assess the methylation with a large number of probes like
the 450 K BeadChip.
The genes with significantly different DNA methylation pat-
terns in our study were enriched for several pathways related to
B cell signalling, inflammation and AIDs, further emphasising
the involvement of disease-relevant changes in B cells.
Significant changes in the DNA methylation patterns observed
in CD19+ cells from patients with pSS included a number of
IRGs, which were also confirmed by pyrosequencing of IFITM1,
IFITM3, IFI44L, IRF5, TNFAIP8, IKZF1. Furthermore, we
found more genes with differentially methylated CpG sites in B
cells from patients with active disease as defined by the ESSDAI
score and in patients who were auto-antibody positive and the
DNA methylation signature of IRGs was more prominent in the
patients who were autoantibody positive. Microarray-based gene
expression studies on labial salivary glands and peripheral blood
showed that in patients with pSS type I IFN-inducible genes
were deregulated.
16 31
Cross-talk of the IFN type I pathway
with the IFN type II pathway reciprocally has been found to
affect each other’s production and signalling in patients with
AID.
32 33
The significant changes in the DNA methylation pat-
terns observed in CD19+ cells from patients with pSS also
included a number of IRGs, which also correlated with the
autoantibody status. Similar findings have previously been made
in type 1 diabetes, where disease-specific markers were also
present in autoantibody positive individuals that were not yet
showing overt clinical symptoms of the disease.
34
In summary, we performed a comprehensive genome-wide
DNA methylation analysis in patients with pSS in blood-derived
T and B cells and demonstrated more important DNA methyla-
tion deregulation in B cells than in T cells, emphasising
the importance of B cells in the pathogenesis of the disease.
Altered DNA methylation patterns were found in the same
genes previously reported to contain genetic variation associated
with the disease, which suggests the importance of combined
analysis of genetic and epigenetic variations to identify
new targets involved in the pathogenesis of AIDs. While this
study as well as the previously published study by Altorok
et al
11
provide new avenues for research in pSS and AIDs in
general, larger studies as well as the analysis of additional cell
types are required to gain a more comprehensive understanding
of DNA methylation changes implicated in the pathogenesis.
In addition, other epigenetic mechanisms influencing gene
expression, such as abnormal expression of microRNAs, which
has been found to be involved in pSS in specific cellular popula-
tions,
8
will also help identifying new therapeutic targets in this
disease.
Contributors CM-R, XM and JT designed the study; CM-R, SB, RB, GN and XM
collected patient material and assessed clinical parameters; SB, FB, CL and KB
performed molecular experiments; CM-R, S-FW-R, FB, XM and JT analysed the data;
CM-R, S-FW-R, XM and JT drafted the manuscript. All authors read and accepted
the final version of the manuscript. CM-R and S-FW-R contributed equally to the
study. XM and JT contributed equally to the study.
Funding The research described in this manuscript was funded by a grant from the
French National Research Agency (ANR- 2010-BLAN-1133 01).
Competing interests None declared.
Ethics approval CCP Ile de France VII No. CO-10-003 on 3rd February 2010.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement Normalised or raw data of the 450 K BeadChips is
available upon request from the authors.
Open Access This is an Open Access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non-commercially,
and license their derivative works on different terms, provided the original work is
properly cited and the use is non-commercial. See: http://creativecommons.org/
licenses/by-nc/4.0/
REFERENCES
1 Qin B, Wang J, Yang Z, et al. Epidemiology of primary Sjogren’s syndrome:
a systematic review and meta-analysis. Ann Rheum Dis 2015;74:1983–9.
2 Bowman SJ, Ibrahim GH, Holmes G, et al. Estimating the prevalence among
Caucasian women of primary Sjogren’s syndrome in two general practices in
Birmingham, UK. Scand J Rheumatol 2004;33:39–43.
3 Nocturne G, Mariette X. Advances in understanding the pathogenesis of primary
Sjogren’s syndrome. Nat Rev Rheumatol 2013;9:544–56.
4 Lessard CJ, Li H, Adrianto I, et al. Variants at multiple loci implicated in both innate
and adaptive immune responses are associated with Sjogren’s syndrome. Nat Genet
2013;45:1284–92.
5 Lu Q. The critical importance of epigenetics in autoimmunity. J Autoimmun
2013;41:1–5.
6 Miceli-Richard C, Criswell LA. Genetic, genomic and epigenetic studies as tools for
elucidating disease pathogenesis in primary Sjogren’s syndrome. Expert Rev Clin
Immunol 2014;10:437–44.
7 Nielsen HM, Tost J. Epigenetic changes in inflammatory and autoimmune diseases.
Subcell Biochem 2012;61:455–78.
8 Alevizos I, Alexander S, Turner RJ, et al. MicroRNA expression profiles as
biomarkers of minor salivary gland inflammation and dysfunction in Sjogren’s
syndrome. Arthritis Rheum 2011;63:535–44.
9 Coit P, Jeffries M, Altorok N, et al. Genome-wide DNA methylation study suggests
epigenetic accessibility and transcriptional poising of interferon-regulated genes in
naive CD4+ T cells from lupus patients. J Autoimmun 2013;43:78–84.
10 Absher DM, Li X, Waite LL, et al. Genome-wide DNA methylation analysis of
systemic lupus erythematosus reveals persistent hypomethylation of interferon genes
and compositional changes to CD4+ T-cell populations. PLoS Genet 2013;9:
e1003678.
11 Altorok N, Coit P, Hughes T, et al. Genome-wide DNA methylation patterns in naive
CD4+ T cells from patients with primary Sjogren’s syndrome. Arthritis Rheum
2014;66:731–9.
12 Seror R, Theander E, Brun JG, et al. Validation of EULAR primary Sjogren’s
syndrome disease activity (ESSDAI) and patient indexes (ESSPRI). Ann Rheum Dis
2015;74:859–66.
13 Tost J, Gut IG. Analysis of gene-specific DNA methylation patterns by
pyrosequencing technology. Methods Mol Biol 2007;373:89–102.
14 Touleimat N, Tost J. Complete pipeline for Infinium((R)) Human Methylation 450 K
BeadChip data processing using subset quantile normalization for accurate DNA
methylation estimation. Epigenomics 2012;4:325–41.
15 Rusinova I, Forster S, Yu S, et al. Interferome v2.0: an updated database of
annotated interferon-regulated genes. Nucleic Acids Res 2013;41(Database issue):
D1040–6.
16 Gottenberg JE, Cagnard N, Lucchesi C, et al. Activation of IFN pathways and
plasmacytoid dendritic cell recruitment in target organs of primary Sjogren’s
syndrome. Proc Natl Acad Sci USA 2006;103:2770–5.
17 Hall JC, Casciola-Rosen L, Berger AE, et al. Precise probes of type II interferon
activity define the origin of interferon signatures in target tissues in rheumatic
diseases. Proc Natl Acad Sci USA 2012;109:17609–14.
18 Maria NI, Brkic Z, Waris M, et al. MxA as a clinically applicable biomarker for
identifying systemic interferon type I in primary Sjogren’s syndrome. Ann Rheum Dis
2014;73:1052–9.
19 Chiche L, Jourde-Chiche N, Whalen E, et al. Modular transcriptional repertoire
analyses of adults with systemic lupus erythematosus reveal distinct type I and type
II interferon signatures. Arthritis Rheum 2014;66:1583–95.
20 Naves R, Singh SP, Cashman KS, et al. The interdependent, overlapping, and
differential roles of type I and II IFNs in the pathogenesis of experimental
autoimmune encephalomyelitis. J Immunol 2013;191:2967–77.
21 Yao Y, Richman L, Morehouse C, et al. Type I interferon: potential therapeutic
target for psoriasis? PLoS ONE 2008;3:e2737.
22 Der SD, Zhou A, Williams BR, et al. Identification of genes differentially regulated
by interferon alpha, beta, or gamma using oligonucleotide arrays. Proc Natl Acad
Sci USA 1998;95:15623–8.
Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998 939
Basic and translational research
23 Li Y, Zhang K, Chen H, et al. A genome-wide association study in Han Chinese
identifies a susceptibility locus for primary Sjogren’s syndrome at 7q11.23.
Nat Genet 2013;45:1361–5.
24 Quintero-Ronderos P, Montoya-Ortiz G. Epigenetics and autoimmune diseases.
Autoimmune Dis 2012;2012:593720.
25 Mak A, Kow NY. The pathology of T cells in systemic lupus erythematosus.
J Immunol Res 2014;2014:419029.
26 Cornec D, Devauchelle-Pensec V, Tobon GJ, et al. B cells in Sjogren’s
syndrome: from pathophysiology to diagnosis and treatment. J Autoimmun
2012;39:161–7.
27 Jaffe AE, Irizarry RA. Accounting for cellular heterogeneity is critical in
epigenome-wide association studies. Genome Biol 2014;15:R31.
28 Liu Y, Aryee MJ, Padyukov L, et al. Epigenome-wide association data implicate
DNA methylation as an intermediary of genetic risk in rheumatoid arthritis.
Nat Biotechnol 2013;31:142–7.
29 Koelsch KA, Webb R, Jeffries M, et al. Functional characterization of the MECP2/
IRAK1 lupus risk haplotype in human T cells and a human MECP2 transgenic
mouse. J Autoimmunity 2013;41:168–74.
30 Gestermann N, Koutero M, Belkhir R, et al. Methylation profile of the promoter
region of IRF5 in primary Sjogren’s syndrome. Eur Cytokine Netw 2012;23:166–72.
31 Emamian ES, Leon JM, Lessard CJ, et al. Peripheral blood gene expression profiling
in Sjogren’s syndrome. Genes Immun 2009;10:285–96.
32 Baechler EC, Batliwalla FM, Karypis G, et al. Interferon-inducible gene expression
signature in peripheral blood cells of patients with severe lupus. Proc Natl Acad Sci
USA 2003;100:2610–15.
33 Bennett L, Palucka AK, Arce E, et al. Interferon and granulopoiesis signatures in
systemic lupus erythematosus blood. J Exp Med 2003;197:711–23.
34 Rakyan VK, Beyan H, Down TA, et al. Identification of type 1 diabetes-associated
DNA methylation variable positions that precede disease diagnosis. PLoS Genet
2011;7:e1002300.
940 Miceli-Richard C, et al.Ann Rheum Dis 2016;75:933–940. doi:10.1136/annrheumdis-2014-206998
Basic and translational research
