Open Access

DNA methylation profiling of the X chromosome reveals an aberrant demethylation on CXCR3 promoter in primary biliary cirrhosis

  • Ana Lleo1,
  • Weici Zhang6,
  • Ming Zhao2,
  • Yixin Tan2,
  • Francesca Bernuzzi1,
  • Bochen Zhu2,
  • Qian Liu2,
  • Qiqun Tan2,
  • Federica Malinverno3,
  • Luca Valenti4,
  • Tingting Jiang2,
  • Lina Tan2,
  • Wei Liao2,
  • Ross Coppel5,
  • Pietro Invernizzi1, 6,
  • Qianjin Lu2Email author,
  • David H. Adams7,
  • M. Eric Gershwin6Email author and
  • the PBC Epigenetic Study Group
Contributed equally
Clinical EpigeneticsThe official journal of the Clinical Epigenetics Society20157:61

https://doi.org/10.1186/s13148-015-0098-9

Received: 27 January 2015

Accepted: 23 June 2015

Published: 7 July 2015

Abstract

Background

Although the etiology of primary biliary cirrhosis (PBC) remains enigmatic, there are several pieces of data supporting the thesis that a strong genetic predisposition and environmental factors interact to produce a selective loss of tolerance. The striking female predominance of PBC has suggested that this sex predisposition may be secondary to epigenetic alterations on the X chromosome. In the present study, we rigorously defined the X chromosome methylation profile of CD4, CD8, and CD14 cells from 30 PBC patients and 30 controls. Genomic DNA from sorted CD4, CD8, and CD14 subpopulations was isolated, sonicated, and immunoprecipitated for analysis of methylation. All products were hybridized to a custom-tiled four-plex array containing 27,728 CpG islands annotated by UCSC and 22,532 well-characterized RefSeq promoter regions. Furthermore, bisulfite sequencing was then used for validation on a subsequent group of independent samples from PBC patients and controls. Thence, expression levels of selected X-linked genes were evaluated by quantitative real-time PCR with cDNA samples from all subjects.

Results

We report herein that a total of 20, 15, and 19 distinct gene promoters reflected a significant difference in DNA methylation in CD4+ T, CD8+ T, and CD14+ cells in patients with PBC. Interestingly, there was hypermethylation of FUNDC2 in CD8+ T cells and a striking demethylation of CXCR3 in CD4+ T cells, which inversely correlated with CXCR3 expression levels in CD4+ T cells from early-stage PBC patients.

Conclusions

Our data provides a set of genes with epigenetic alteration likely to be indicators of autoimmunity and emphasizes the role of CXCR3 in the natural history of PBC.

Keywords

X chromosome Primary biliary cirrhosis CXCR3

Background

Autoimmune diseases are multifactorial in origin. Genetic background confers susceptibility to disease onset but is not sufficient for disease development. Epigenetic mechanisms such as DNA methylation and histone modifications regulate gene expression levels and provide an alternative mechanism for modulating gene function and genetic changes. Importantly, DNA methylation plays an important role in T cell differentiation [1, 2], and the potential role of epigenetics in environment and genetics interaction has been widely suggested in autoimmunity [3, 4]. With these data in mind, we note that primary biliary cirrhosis (PBC) is characterized by the presence of high titers of circulating antimitochondrial antibodies (AMAs), innate immune system activation [57], and liver-infiltrating autoreactive CD4 and CD8 T lymphocytes [810], leading to the progressive destruction of small intrahepatic bile ducts [11, 12]. Genetic polymorphisms account for individual susceptibility to PBC in a minority of cases, as supported by genome-wide association (GWAS) data [1317], while environmental factors may act through epigenetic changes, as demonstrated for specific genes [1820]. It has long been known that there is a striking female sex bias in PBC [21], and recent data has suggested involvement of sex chromosomes [22, 23]. For example, an enhanced X monosomy rate in peripheral lymphocytes has been demonstrated in women with PBC [24], despite random X chromosome inactivation [25], as well as an increased Y loss in men with PBC [26].

We thus hypothesized that there is an X chromosome epigenetic component in PBC. Herein we performed an extensive X chromosome methylation analysis in CD4, CD8, and CD14 cells from PBC patients and controls, coupled with gene expression profile from the same cells. The frequency of CXCR3-expressing cells in peripheral blood is known to be higher in PBC patients, and CXCR3-positive cells are found in the portal areas of diseased livers, primarily on CD4+ T cells [27]. Moreover, we report that the CXCR3 promoter is demethylated in CD4+ T cells from PBC patients and the expression level of CXCR3 in CD4+ T cells is significantly increased in comparison to controls and inversely correlated with the overall methylation levels of the CXCR3 promoter, indicating that promoter demethylation status contributed to CXCR3 overexpression in CD4+ T cells. Hence, we submit that there is an epigenetic mechanism that underlies CXCR3 expression in PBC. Our findings not only identify potentially relevant DNA methylation markers for the clinical characterization of PBC patients but also support the thesis that epigenetic changes may be critical for the clinical manifestations of PBC.

Results

DNA methylation

Initially, X chromosome methylated DNA immunoprecipitation (MeDIP) arrays were performed on cell subsets from 10 PBC patients and 10 controls (Fig. 1). We identified 8 hypomethylated genes and 12 hypermethylated genes in CD4+ cells, 3 hypomethylated genes and 12 hypermethylated genes in CD8+ cells, and 9 hypomethylated genes and 10 hypermethylated genes in CD14+ cells in PBC compared with normal controls (Fig. 2, Table 1). Gene ontology (GO) analysis was conducted to identify the cell component, molecular function, and biological processes of these genes. Bisulfite sequencing was thence used to validate the results of the MeDIP-ChIP. Based on the GO analysis, four genes were chosen for validation in CD4+, CD8+, and CD14+ cells from 20 additional PBC patients and 20 additional normal controls. Importantly, CXCR3 was demonstrated to be significantly hypomethylated in CD4+ T cells from PBC patients (Fig. 3), whereas UBE2A and FUNDC2 were hypermethylated in CD4+ T cells and CD8+ T cells, respectively, in PBC patients (Figs. 4 and 5). IL1RAPL2 was hypermethylated in CD14+ cells in PBC (Fig. 6).
Fig. 1

Flow chart illustrating the study design

Fig. 2

Differential methylation between PBC-affected subjects (n = 10) and healthy controls (n = 10) in CD4+, CD8+, and CD14+ cells represented in a heat map. The genomic locations of genes are shown on the left of the X chromosome ideogram. On the right, different methylated regions (DMR) of genes are identified in at least 6/10 samples in one group and 3/10 samples in the other. The predicted DMR along with the names of the genes in each cell examined is depicted as a two-dimensional heat map, respectively. Black blocks represent zero peaks, and yellow blocks symbolize different peak numbers corresponding to the scale bar at the bottom

Table 1

Differentially methylated genes between PBC patients (n = 10) and controls (n = 10) in CD4+ T cells, CD8+ T cells, and CD14+ cells from MeDIP array

Gene symbol

Promoter methylation

Chromosome location

Peak start

Peak end

Molecular function

CD4+ T cells

     

 SHROOM2

Hypo

Xp22.3

9712072

9712217

Protein binding; actin binding; ion channel activity

 ATP6AP2

Hypo

Xp11.4

40325091

40325230

Receptor activity; protein binding; peptidase activity

 CXCR3

Hypo

Xq13

70754908

70755379

Protein binding; receptor activity

 KIAA1210

Hypo

Xq24

118168783

118168934

 RAP2C

Hypo

Xq25

131181458

131182027

Nucleotide binding; hydrolase activity

 HTATSF1

Hypo

Xq26.3

135407214

135407962

RNA binding; nucleotide binding

 SRPK3

Hypo

Xq28

152699372

152700237

Protein binding; nucleotide binding; protein kinase activity

 IDH3G

Hypo

Xq28

152712248

152713105

Nucleotide binding; catalytic activity; binding

 SH3KBP1

Hyper

Xp22.1-p21.3

19815048

19815499

Kinase activity; protein binding

 PHEX

Hyper

Xp22.2-p22.1

21960765

21961408

Binding; peptidase activity

 USP9X

Hyper

Xp11.4

40829716

40830189

 EBP

Hyper

Xp11.23-p11.22

48265283

48265716

 PQBP1

Hyper

Xp11.23

48638698

48639426

DNA binding; protein binding; transcription regulator activity

 KDM5C

Hyper

Xp11.22-p11.21

53270826

53271657

Catalytic activity; binding; DNA binding; transferase activity

 IL13RA1

Hyper

Xq24

117745388

117746245

Protein binding; receptor activity

 UBE2A

Hyper

Xq24

118592639

118593104

Catalytic activity; protein binding; nucleotide binding

 CUL4B

Hyper

Xq23

119578240

119579025

Protein binding

 DCAF12L1

Hyper

Xq25

125513992

125514963

 GPC4

Hyper

Xq26.1

132376771

132377010

Protein binding

 FAM50A

Hyper

Xq28

153325585

153326034

CD8+ T cells

     

 MAGEB2

Hypo

Xp21.3

30142775

30143514

 PIN4

Hypo

Xq13

71318699

71318834

DNA binding; catalytic activity

 IDH3G

Hypo

Xq28

152713172

152713419

Nucleotide binding; catalytic activity; binding

 GPR143

Hyper

Xp22.3

9693469

9693810

Binding; protein binding

 CHST7

Hyper

Xp11.23

46317790

46318126

Transferase activity

 NDUFB11

Hyper

Xp11.23

46889596

46889747

 RBM10

Hyper

Xp11.23

46889596

46889747

RNA binding; nucleotide binding

 ZXDB

Hyper

Xp11.21

57635489

57636052

Nucleic acid binding; binding; protein binding; sequence-specific DNA binding transcription factor activity

 DOCK11

Hyper

Xq24

117514077

117514418

Enzyme regulator activity; lipid binding; protein binding

 IL13RA1

Hyper

Xq24

117745582

117746125

Protein binding; receptor activity

 RNF113A

Hyper

Xq24

118889675

118890227

Binding; protein binding

 AIFM1

Hyper

Xq26.1

129101688

129102158

Catalytic activity; nucleotide binding; protein binding; electron carrier activity; DNA binding

 MPP1

Hyper

Xq28

153686370

153686806

Kinase activity; protein binding

 FUNDC2

Hyper

Xq28

153908428

153908659

 RAB39B

Hyper

Xq28

154146437

154146790

Nucleotide binding

CD14+ cells

     

 SYAP1

Hypo

Xp22.2

16647938

16648203

 DYNLT3

Hypo

Xp21

37591227

37591696

 CASK

Hypo

Xp11.4

41667126

41667877

Protein binding; ATP binding; protein kinase activity

 GPR173

Hypo

Xp11

53095323

53095568

G protein-coupled receptor activity

 CITED1

Hypo

Xq13.1

71441965

71442118

Sequence-specific DNA binding transcription factor activity; protein binding; DNA binding; transcription regulator activity; chromatin binding; hydrolase activity

 GPRASP1

Hypo

Xq22.1

101790525

101790970

Protein binding

 RNF128

Hypo

Xq22.3

105824083

105824257

Binding; catalytic activity

 NSDHL

Hypo

Xq28

151750127

151750280

Catalytic activity

 SSR4

Hypo

Xq28

152710848

152711207

Calcium ion binding

 KAL1

Hyper

Xp22.32

8659278

8659655

Enzyme regulator activity; protein binding; carbohydrate binding; structural molecule activity

 SH3KBP1

Hyper

Xp22.1-p21.3

19815148

19815397

Protein binding

 USP11

Hyper

Xp11.23

46976944

46977091

Peptidase activity; protein binding; hydrolase activity

 PIM2

Hyper

Xp11.23

48661207

48661380

Protein kinase activity; nucleotide binding

 PCDH11X

Hyper

Xq21.3

90921374

90921541

Calcium ion binding

 IL1RAPL2

Hyper

Xq22

103696629

103696884

Protein binding; receptor activity

 PSMD10

Hyper

Xq22.3

107221347

107221874

Protein binding

 ATG4A

Hyper

Xq22.1-q22.3

107221347

107221874

Peptidase activity

 DCAF12L1

Hyper

Xq25

125513614

125513941

Protein binding

 FUNDC2

Hyper

Xq28

153908232

153908879

Fig. 3

Bisulfite sequencing-based DNA methylation analysis of the CXCR3 promoter region in CD4+ T cells. a Chromosomal sequence location of the CXCR3 promoter that was analyzed by bisulfite sequencing. This region contains four CpG sites (vertical bars) within a 471 bp region overlapping the transcription start site as shown. b Representative bisulfite sequencing data from CD4+ cells of a PBC sample and a normal control, respectively. Each circle represents a CpG site, and each line represents an individually sequenced clone. Filled circles represent methylated sites (protected from bisulfite conversion), while unfilled circles represent unmethylated CpG sites (converted). c Mean methylation level was calculated for each individual CpG site within the CXCR3 promoter region for all clones for PBC (n = 20) versus healthy (n = 20) CD4+ cells. d Overall percentage of methylation of CXCR3 was determined by the total number of methylated sites out of the total CpG sites in all clones and graphed as mean ± SD for PBC (n = 20) versus healthy (n = 20) CD4+ cells. **p < 0.01

Fig. 4

a Chromosomal sequence location of the region of the UBE2A promoter that was analyzed by bisulfite sequencing. This region contains 20 CpG sites (vertical bars) within a 542 bp region upstream of the transcription start site as shown. b Representative bisulfite sequencing data from CD4+ cells of a PBC sample and a normal control, respectively. Each circle represents a CpG site, and each line represents an individually sequenced clone. Filled circles represent methylated sites (protected from bisulfite conversion), while unfilled circles represent unmethylated CpG sites (converted). c Mean methylation level was calculated for each individual CpG site within the UBE2A promoter region for all clones for PBC (n = 20) versus healthy (n = 20) CD4+ cells. d Overall percentage of methylation of UBE2A was determined by the total number of methylated sites out of the total CpG sites in all clones and graphed as mean ± SD for PBC (n = 20) versus healthy (n = 20) CD4+ cells. *p < 0.05

Fig. 5

a Chromosomal sequence location of the region of the FUNDC2 promoter that was analyzed by bisulfite sequencing. This region contains 80 CpG sites (vertical bars) within a 696 bp region close to the transcription start site as shown. b Representative bisulfite sequencing data from CD8+ cells of a PBC sample and a normal control, respectively. Each circle represents a CpG site, and each line represents an individually sequenced clone. Filled circles represent methylated sites (protected from bisulfite conversion), while unfilled circles represent unmethylated CpG sites (converted). c Mean methylation level was calculated for each individual CpG site within the FUNDC2 promoter region for all clones for PBC (n = 20) versus healthy (n = 20) CD8+ cells. d Overall percentage of methylation of FUNDC2 was determined by the total number of methylated sites out of the total CpG sites in all clones and graphed as mean ± SD for PBC (n = 20) versus healthy (n = 20) CD8+ cells. *p < 0.05

Fig. 6

a Chromosomal sequence location of the region of the IL1RAPL2 promoter that was analyzed by bisulfite sequencing. This region contains 23 CpG sites (vertical bars) within a 423 bp region upstream of the transcription start site as shown. b Representative bisulfite sequencing data from CD14+ cells of a PBC sample and a normal control, respectively. Each circle represents a CpG site, and each line represents an individually sequenced clone. Filled circles represent methylated sites (protected from bisulfite conversion), while unfilled circles represent unmethylated CpG sites (converted). c Mean methylation level was calculated for each individual CpG site within the IL1RAPL2 promoter region for all clones for PBC (n = 20) versus healthy (n = 20) CD14+ cells. d Overall percentage of methylation of IL1RAPL2 was determined by the total number of methylated sites out of the total CpG sites in all clones and graphed as mean ± SD for PBC (n = 20) versus healthy (n = 20) CD14+ cells. **p < 0.01

Gene expression

CXCR3, UBE2A, FUNDC2, and IL1RAPL2 expression was studied by reverse transcription and quantitative polymerase chain reaction (RT-qPCR) in CD4+, CD8+, and CD14+ cells in a cohort of 30 PBC and 30 normal controls (Fig. 7).
Fig. 7

CXCR3 (a), and FUNDC2 (b) expression level was determined in CD4+, CD8+ T cells, and CD14+ cells in PBC patients and controls. Real-time threshold cycle values for cDNA were normalized with GADPH and compared to a calibrator. Limits (95 % CI) of the best-fit line are shown

Importantly, CXCR3 was significantly overexpressed in CD4+ T cells in PBC (p = 0.0055), whereas FUNDC2 was significantly less expressed in CD8+ T cells from PBC than controls (p = 0.0134). These results are concordant with the methylation data. IL1RAPL2 was not expressed in any cell subset in PBC or controls, and no significant differences were identified for UBE2A in the three subsets investigated (data not shown). Finally, a significant negative correlation between CXCR3 expression and overall methylation levels in CD4+ T cells was found in early-stage PBC patients (p < 0.05) (Fig. 8a). Of note, there was no difference observed based on UDCA treatment (data not shown). In addition, our data demonstrated that CXCR3 expression levels in CD4+ T cells were significantly associated with duration of disease (p < 0.01) (Fig. 8b) but not associated with age (data not shown).
Fig. 8

Correlation analysis was performed to evaluate the relationship between CXCR3 gene expression levels, methylation status of CXCR3 promoter, and disease duration. a CXCR3 expression in CD4+ T cells inversely correlates with methylation status of CXCR3 promoter. b CXCR3 expression in CD4+ T cells correlates with disease duration. Real-time threshold cycle values for CXCR3 cDNA were normalized with GADPH and compared to a calibrator. Calibrated CXCR3 expression levels were correlated to disease duration (months). 95 % confidence limits of the best-fit line are shown (solid line)

CD4 T cell phenotype

Finally, we quantified CD4 T cell populations expressing CXCR3 in both PBC (n = 20) and controls (n = 10) by flow cytometry. Based on the expression data, patients with PBC had an increased number in the periphery of CD4 T cells expressing CXCR3. In addition, both naïve and memory CD4 T cells from PBC expressed a higher frequency of CXCR3 cells in the periphery than controls. However, only activated CD4+CD45RO+ cells expressed significantly higher levels of CXCR3 (41.82 % ± 4.37 versus 27.57 % ± 2.61, p = 0.0094) (Fig. 9). Please note we included both early (n = 10) and advanced (n = 10) stage patients with PBC (data not shown).
Fig. 9

CD4 T cell populations expressing CXCR3 in PBC (n = 20) and controls (n = 10) were quantified by flow cytometry. In PBC, there is an increased number of CD4 T cells in the periphery expressing CXCR3, in both naïve (CD45RA) and memory cells (CD45RO). Activated CD4+CD45RO+ cells express significantly higher levels of CXCR3 in PBC (41.82 % ± 4.37) compared to controls (27.57 % ± 2.61) (p = 0.0094)

Discussion

As the case for most autoimmune diseases, PBC results from the contribution of genetic and environmental factors, reflected by incomplete concordance in monozygotic twins [28]. Moreover, our group has suggested a significant role for X chromosome defects in PBC, based on the observation that women with PBC have a significantly enhanced monosomy X frequency in peripheral white blood cells compared to age- and disease stage-matched women with chronic viral hepatitis and to age-matched healthy women [24]. Epigenetic mechanisms act at the interface of genetic and environmental influences on human phenotype and disease risk by altering gene expression levels without altering DNA sequence or chromosome structure. In the case of autoimmune diseases, epigenetic mechanisms have been implicated in the pathogenesis of systemic lupus erythematosus [29, 30] and type I diabetes [31]. Moreover, we had previously explored the X chromosome epigenetic component in PBC [18].

Importantly, PBC is a complex autoimmune disease involving autoreactive CD4+ and CD8+ T cell responses, present in human circulating lymphocytes and liver, B cell compartment, and innate immunity, including macrophages [6, 3234].

In this study, we investigated for the first time the DNA methylation status of the X chromosome in CD4+, CD8+, and CD14+ cells isolated from PBC patients and well-matched controls. We herein demonstrate that the CXCR3 promoter is demethylated in CD4+ T cells from PBC patients compared to controls, which is supported by a significantly higher expression of CXCR3 in the same cell subtype of PBC patients. CXCR3 gene encodes a G protein-coupled receptor with selectivity for three chemokines: CXCL9 or MIG (monokine induced by IFNγ), CXCL10 or IP10 (IFNγ-inducible 10 kDa protein), and CXCL11 or I-TAC (IFN-inducible T cell α-chemoattractant). CXCR3 plays an important role in regulating leukocyte trafficking; indeed binding of chemokines induces cellular responses that are involved in leukocyte traffic, most notably integrin activation, cytoskeletal changes, and chemotactic migration. CXCR3 is expressed primarily on activated T lymphocytes and NK cells and some epithelial cells and endothelial cells. It had been implicated that CXCR3 is highly expressed on pro-inflammatory human CD4+Th17 cells [35], “pathogenic” human Th1/17 cells [36], and myelin oligodendrocyte glycoprotein-specific CD4+ T cells in experimental autoimmune encephalomyelitis mice in combination with other biomarkers [37]. Increased CXCR3 in portal tracts has also been reported in PBC patients [27]. Additionally, levels of CXCR3 ligands are markedly increased in inflammatory liver diseases [38, 39], including PBC [27]. Further, knockout of CXCR3 delays PBC progression in an animal model [40]. Most importantly, our data indicates that CXCR3 expression in CD4+ T cells inversely correlates with methylation levels and positively correlates with duration of disease. The accumulated data suggest a critical role of the CXCR3/chemokine system in the development of autoimmune disorders. In addition to its role in lymphocyte recruitment to tissues, CXCR3 is also implicated in the development of Th1 cells within lymph nodes [41]; thus, hypomethylation of CXCR3 and the consequent increased expression on CD4 T cells could promote disease progression through enhanced Th1 differentiation and increased recruitment. X chromosome demethylation has been shown to result in increased CXCR3 expression in lupus, suggesting this could be a common mechanism that contributes to the female susceptibility to autoimmune diseases [4]. Our findings are in agreement with previous studies; nevertheless, our findings strongly suggest an epigenetic mechanism underlying the elevated CXCR3 expression in PBC.

There are significant limitations in our study that should be discussed. First, of the genes studied herein, we note there were no significant differences identified for UBE2A gene expression, although UBE2A has been demonstrated to be hypermethylated in CD4+ T cells. This suggests that UBE2A expression is regulated by other epigenetic mechanisms rather than by methylation. Second, the pathogenetic mechanisms that underlie CXCR3 demethylation remain to be defined. Third, our study did not include men with PBC. This is of particular interest given the relevant function of the X chromosome. Fourth, the CD4 bias is interesting and it will be important to determine if this bias is found on other T cell subpopulations, particularly Th17, Tregs, or Th1 cells, all of which require CXCR3 to enter the liver. Finally, further studies will also need to focus on the differential expression of central versus effector memory cells. Our data highlight, however, the critical importance of epigenetics in PBC and likely for other autoimmune diseases.

Conclusions

CXCR3 promoter demethylation in CD4+ T cells from PBC patients, supported by a significantly higher expression of CXCR3 in the same cell subtype, emphasizes the well-known role of CXCR3 in the pathogenesis of PBC. Moreover, CXCR3 expression levels in CD4+ T cells are significantly associated with duration of disease. Whether CXCR3 may contribute to the female susceptibility to PBC warrants further investigation.

Methods

Subjects

Fresh heparinized peripheral blood samples were obtained from 30 patients diagnosed with PBC and 30 unaffected age- and sex-matched controls [11]. All patients (Table 2) were female, and 90 % had readily detectable AMA; the diagnosis was made based on internationally accepted criteria [11]. The mean age was 61 (43–78) years old (range years), and 100 % of them were taking ursodiol. Four percent of the PBC patients included in this study were histologically characterized as cirrhotics. Serum liver function tests were performed utilizing routine laboratory methods. Subjects were excluded from the study if they had malignancies or were using immunosuppressive drugs. Patients and controls were matched for age and sex. After approval from appropriate institutional review board, all subjects provided written informed consent prior to enrollment in the study. The study design is illustrated in Fig. 1.
Table 2

Clinical, biochemical, and serological characteristics of PBC patients

 

PBC patients

Healthy controls

(n = 30)

(n = 30)

Mean age (years, range)

64 (44–87)

60 (42–79)

Females (n, %)

30 (100 %)

30 (100 %)

AMA positivity (n, %)

28 (93 %)

n.a.

Liver cirrhosis (n, %)

4 (13 %)

n.a.

Total bilirubin (mg/dl) (n.v. <1.0)

0.64 ± 0.39

0.73 ± 0.18

Alkaline phosphatase (IU/l) (n.v. <279)

152.3 ± 207.3

168 ± 24

Alanine aminotransferase (U/l) (n.v. <50)

33 ± 26

32 ± 9

Albumin (g/dl) (n.v. >3.5)

4.33 ± 0.86

4.68 ± 0.03

Length of follow-up (months, range)

34 (14–56)

n.a.

Therapy with UDCA (n, %)

28 (93 %)

n.a.

Liver biopsy (n, %)

21 (72 %)

n.a.

Mean values ± standard deviation unless otherwise stated

n.a. not applicable, n.v. normal value

CD14+, CD4+ T cell, and CD8+ T cell purification

Peripheral blood mononuclear cells (PBMC) were isolated by centrifugation on a Ficoll-Hypaque gradient for 30 min at 500g. First, CD14+ cells were isolated from PBMC by positive selection under endotoxin-free conditions using anti-CD14 conjugated microbeads (Miltenyi Biotec, San Diego, CA, USA). Thence, CD8+ cells were isolated from the eluate by positive selection using anti-CD8 conjugated microbeads (Miltenyi Biotec, San Diego, CA, USA). Finally, the CD4+ T cells were isolated by negative selection using a cocktail of antibodies against CD8, CD14, CD16, CD19, CD36, CD56, CD123, TCR γ/δ, and CD235a (Miltenyi Biotec, San Diego, CA, USA). Aliquots of the CD14+, CD8+, and CD4+ T cells were subjected to viability assays and flow cytometry analysis. The purity of these lymphocytic populations was >95 % and the viability >95 %. Genomic DNA from the isolated CD14+, CD8+, and CD4+ T cells was isolated using TRI Reagent (Sigma-Aldrich, St. Louis, MO, USA) [42].

Methylated DNA immunoprecipitation and methylation microarrays

DNA samples from PBC patients (n = 10) and controls (n = 10) were sonicated to generate fragments between 200 and 1000 base pairs (bp), and then immunoprecipitated with a murine monoclonal antibody that specifically recognizes 5-methylcytidine (Diagenode, Liège, Belgium). The immunoprecipitated DNA fragments were recovered using anti-mouse IgG magnetic beads. The MeDIP-enriched DNA was amplified by PCR using universal primers and a limited number of cycles (GenomePlex® Complete Whole Genome Amplification kit). The amplified DNA samples were then purified with QIAquick PCR purification kit (Qiagen, Valencia, CA, USA). One microgram of immunoprecipitated and reference DNA was tagged respectively with Cyanine-5 (Cy5) and Cyanine-3 (Cy3) labeled random 9-mers and then hybridized by the NimbleGen Array Hybridization Kit (Roche NimbleGen, Madison, WI, USA). The labeled DNA was then purified by isopropanol/ethanol precipitation. For array hybridization, Roche NimbleGen’s Human Promoter plus CpG Island array was used, a 3 × 720k format array design containing 27,728 CpG islands and all well-characterized promoter regions (from about −2440 to +610 bp of the TSSs) totally covered by ~720,000 probes.

Bisulfite sequencing

The CpG island DNA methylation status was determined by sequencing bisulfite-modified genomic DNA [43] from PBC patients (n = 20) and controls (n = 20). One microgram of genomic DNA was bisulfite-converted using the EpiTect Bisulfite Kit (Qiagen, Valencia, CA, USA). For each gene, primers were designed using the Methyl Primer Express v1.0 program (Life Technologies-Applied Biosystems, Carlsbad, CA, USA) corresponding to the region containing the oligonucleotide probe represented in the DNA methylation bead array. Ten positive recombinant clones were selected randomly and sequenced using ABI 3730 (Life Technologies-Applied Biosystems, Carlsbad, CA, USA). The methylation level of gene is assessed according to the percentage of the methylated CG sites in 10 clones. All primer sequences are listed in Additional file 1: Table S1.

Reverse transcription and quantitative polymerase chain reaction

Total RNA was extracted from all isolated samples (PBC n = 30, controls n = 30) using TRI Reagent (Sigma-Aldrich, St. Louis, MO, USA). cDNA was synthesized from all different cell types using High Capacity cDNA Reverse Transcription Kits (Life Technologies-Applied Biosystems, Carlsbad, CA, USA). One hundred nanograms of cDNA in a total volume of 20 μl was amplified for 40 cycles on an Applied Biosystems 7900 HT Sequence Detection System, using a TaqMan Gene Expression Assay specific for CXCR3, UBE2A, FUNDC2, and IL1RAPL2 (Cat. #4331182, #4351372, Life Technologies-Applied Biosystems, Carlsbad, CA, USA). TaqMan® Gene Expression Assays consist of a pair of unlabeled PCR primers and a TaqMan® probe with a FAM™ dye label on the 5′ end and minor groove binder (MGB) nonfluorescent quencher (NFQ) on the 3′ end. RNA from samples of interest is reverse transcribed into cDNA, and the synthesized cDNA serves as the template for real-time PCR. ROX™ dye is used as a passive reference to normalize real-time PCR reactions. ROX™ dye provides an internal reference to which the FAM™ reporter dye signal can be normalized, which is necessary to correct for fluorescent fluctuations due to changes in concentration, volume, or light source intensity. Normalization of the reporter dye signal results in increased data precision. All reactions were run in duplicate. The relative mRNA expression level of each gene was determined by normalizing its mRNA level to the internal control glyceraldehyde 3-phosphate dehydrogenase (GAPDH).

Flow cytometry

Phenotypic analysis of CD4 T cells was assessed using fluorochrome-conjugated monoclonal antibodies against cell surface markers on a FACSCantoII (BD Biosciences, San Diego, CA, USA) using FACSDiva™ software (BD Biosciences, San Diego, CA, USA). Monoclonal antibodies against human CD3, CD4, CD45RA, CD45RO, and CD183 (CXCR3) were purchased from BioLegend (San Diego, CA, USA). Frozen cells were thawed and prepared for flow cytometry as described [44]. Cells were stained for 15 min at room temperature with Aqua viability dye (Life Technologies). Optimal concentrations of the mAbs were used throughout, and all assays included positive and negative controls.

Statistical methods

NimbleScan software v2.5 (Roche NimbleGen, Madison, WI, USA) was utilized for DNA methylation data analysis using a threshold p value of 0.05 equivalent to 1.31 based on the Gaussian distribution of data. Second, exclusive elements corresponding to specific microarray probes were identified using a one-sided Kolmogorov-Smirnov (KS) test in affected and healthy subjects; peaks found only in either group were selected for further analysis. Peaks within 500 bp of each other are merged. If several adjacent probes rise significantly above a set threshold, the region is assigned to an enrichment peak (EP). NimbleScan detects peaks by searching for at least two probes above a p value minimum cutoff (−log10) of 2. Third, elements of interest were inserted into the UCSC Genome Browser to identify corresponding genes. The filter condition of different methylated regions was set to be no less than six EPs in one group and not more than three EPs in the other group. Based on GO analysis and potential involvement in the pathogenesis of PBC, four genes were selected for validation using isolated CD4+, CD8+, and CD14+ cells from 20 additional patients with PBC and 20 additional normal controls. For RT-qPCR, the data were analyzed with Delta Delta Ct using global normalization. Statistical differences between groups were identified using an unpaired t test taking into account transcripts with p value <0.05.

Notes

Abbreviations

AMAs: 

antimitochondrial antibodies

GAPDH: 

glyceraldehyde 3-phosphate dehydrogenase

GWAS: 

genome-wide association

IP10: 

IFNγ-inducible 10 kDa protein

KS: 

Kolmogorov-Smirnov

MeDIP: 

methylated DNA immunoprecipitation

PBC: 

primary biliary cirrhosis

RT-qPCR: 

reverse transcription and quantitative polymerase chain reaction

Declarations

Acknowledgements

This study was supported in part by a research grant from the National Institutes of Health, DK39588.

PBC Epigenetic Study Group

Ilaria Bianchi (Humanitas, Rozzano (MI), Italy), Roberto Ceriani (Humanitas, Rozzano (MI), Italy), Massimo Colombo (Ospedale Policlinico, Milano, Italy), Francesca Donato (Ospedale Policlinico, Milano, Italy), Silvia Fargion (Ospedale Policlinico, Milano, Italy), Elisabetta Mascia (Humanitas, Rozzano (MI), Italy), Claudia Mascheroni (Humanitas, Rozzano (MI), Italy), Mauro Podda (Humanitas, Rozzano (MI), Italy), Edoardo Pulixi (Ospedale Policlinico, Milano, Italy), Francesca Traiani (Humanitas, Rozzano (MI), Italy)

Authors’ Affiliations

(1)
Liver Unit and Center for Autoimmune Liver Diseases, Humanitas Clinical and Research Center
(2)
Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, The Second Xiangya Hospital, Central South University
(3)
Migliavacca Center for the Study of Liver Disease, 1st Division of Gastroenterology, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ca’ Granda - Ospedale Maggiore Policlinico Milano
(4)
Internal Medicine, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Ca’ Granda - Ospedale Maggiore Policlinico Milano
(5)
Department of Microbiology, Monash University
(6)
Division of Rheumatology, Allergy and Clinical Immunology, University of California at Davis School of Medicine
(7)
Centre for Liver Research and NIHR Biomedical Research Unit for Liver Disease, University of Birmingham

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© Lleo et al. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.