Next Article in Journal
Non-Invasive Evaluation of Intradiscal Deformation during Axial Loading of the Spine Using Deformation-Field Magnetic Resonance Imaging: A Potential Tool for Micro-Instability Measurements
Next Article in Special Issue
Low Serum BAFF Concentration Is Associated with Response to TNF Inhibitors in Seropositive Patients with Rheumatoid Arthritis
Previous Article in Journal
A Proliferation-Inducing Ligand and B-Cell Activating Factor Are Upregulated in Patients with Essential Thrombocythemia
Previous Article in Special Issue
TNF-α Inhibitors in Combination with MTX Reduce Circulating Levels of Heparan Sulfate/Heparin and Endothelial Dysfunction Biomarkers (sVCAM-1, MCP-1, MMP-9 and ADMA) in Women with Rheumatoid Arthritis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 11
Issue 16
10.3390/jcm11164664
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis

by
Dominika Podgórska
1,*,
Marek Cieśla
2 and
Bogdan Kolarz
1
1
Department of Internal Diseases, Institute of Medical Sciences, College of Medical Sciences, University of Rzeszow, 35-959 Rzeszow, Poland
2
College of Medical Sciences, University of Rzeszow, 35-959 Rzeszow, Poland
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2022, 11(16), 4664; https://doi.org/10.3390/jcm11164664
Submission received: 14 June 2022 / Revised: 29 July 2022 / Accepted: 5 August 2022 / Published: 9 August 2022
(This article belongs to the Special Issue Rheumatoid Arthritis: Current Treatment and Future Options)
Browse Figure
Versions Notes

Abstract

:
Rheumatoid arthritis (RA) is a chronic autoimmune disease that, when improperly treated, leads to disability in patients. Various factors that may cause the development and activity of RA are being considered. Epigenetic factors are also receiving increasing attention. In our study, we analyzed the association between FCER1G gene methylation and RA activity. We conducted our study in 50 RA patients and 24 controls. The patients were divided into two groups in terms of high disease activity and remission. Quantitative real-time methylation-specific PCR was used to analyze the methylation status of the investigated genes. We observed that RA patients have lower levels of methylation of the FCER1G gene compared to controls, but we did not find any difference in the methylation status of this gene between patients with high disease activity and remission. The results of this study suggest that FCER1G gene methylation may be a new potential epigenetic marker of RA that is independent of disease activity.

1. Introduction

Rheumatoid arthritis (RA) is a chronic autoimmune disease that affects nearly 1% of the world’s population, in which progressive joint damage and systemic symptoms occur under the influence of immune processes [1]. Untreated RA leads to progressive disability that impairs daily functioning and can even result in death.
RA can be divided into serum-positive or serum-negative forms depending on the presence or absence of serum antibodies. Classification criteria take into account the presence of rheumatoid factor (RF) and/or antibodies to citrullinated peptides/proteins (ACPA, usually determined by anti-CCP assay) [2,3,4]. ACPA antibodies show high specificity and may appear many years before the diagnosis of RA [4]. It has been proven that other antibodies also appear in RA patients, including, among others, antibodies against carbamylated proteins [5,6], antibodies against malondialdehyde-acetaldehyds adducts [7], and antibodies against peptidyl-arginine deiminase type 4 [8,9].
Some roles in the predisposition to the development of RA have been attributed to genetics.
Past studies have led to the discovery of more than 150 loci associated with RA, but associations with human leukocyte antigen (HLA) remain the strongest [10,11,12].
Based on a meta-analysis of genome-wide association studies, it is surprising that about 80% of RA risk variants are found in non-coding DNA regions. An increasing role of the predisposition to RA risk has been attributed to changes affecting gene expression, histone modifications, chromatin conformation, or transcription factors [13,14,15]. A growing number of studies highlight the impact of epigenetic changes on the pathogenesis of RA. Epigenetics affects gene transcription, leading to heritable phenotypic changes, without altering the DNA sequence itself [16,17]. Epigenetic modifications are reversible and can be modulated by environmental factors, including diet or drugs [18,19,20].
Fc epsilon receptor Ig (FCER1G) is a gene located on chromosome 1 at position 1q23.3 that was first described in 1990. It encodes the γ chain of the Fc receptor, which is the third subunit of the high-affinity immunoglobulin E (IgE) receptor (Fcε RI). In the following years, it was observed that the Fc receptor γ chain is a common component of Fc receptors that are widely expressed in various types of immune cells.
The Fc receptor is a protein found on the surface of many different cells: neutrophils, basophils, eosinophils, platelets, macrophages, B lymphocytes, NK cells, mast cells, and dendritic cells [21]. It consists of one alpha (FCER1A) ligand binding subunit, one beta (FCER1B) signal enhancer and two gamma (FCER1G) signal transducers [22,23]. Its name comes from its binding to the Fc region of antibodies (crystallizing fragment) that are attached to infected cells or invading pathogens [21]. The binding of immunoglobulins to Fc receptors is involved in important functions of the immune system, such as phagocytosis and antibody-dependent cytotoxicity [21,24,25].
FCER1G represent a functional connection between acquired and innate immunity because they link interactions between circulating antibodies (including autoantibodies) and innate immunity cells [26,27].
FCER1G expression has been studied and described in various diseases, including squamous cell carcinoma, eczema, meningioma, leukemia, glioma, kidney disease, and even in acute myocardial infarction.
In the present study, we have investigated the effect of FCER1G gene methylation on the development of RA. To the best of our knowledge, this is the first study to examine this relationship in RA.

2. Materials and Methods

Patients

A total of 74 subjects, 50 patients with RA and 24 controls, were enrolled in the study. Disease severity was estimated in the disease activity score (DAS28-ESR). From the RA group, 29 patients had high disease activity (DAS28-ESR > 5.1) and 21 patients in remission (DAS28-ESR ≤ 2.6). The diagnosis of RA was made according to the 2010 ACR/EULAR [4] or 1987 ACR [28] criteria for classification depending on the time of diagnosis. Clinical characteristics of the patients and controls are presented in Table 1 and Table 2. Variables included in the characteristics were taken from medical records. ACPAs (Anti CCP assay, DiaMetra, Segrate, Italy) and RF (EIA RF IgG, TestLine Clinical Diagnostics, Brno, Czech Republic) were determined in serum by enzyme-linked immunosorbent immunoassay and absorbance reader (Tecan Infinite M200 Pro reader and Magellan software, version 7.1, Mannedorf, Switzerland).
The Ethics Committee of the Lublin Medical University approved the study (protocol number KE-0254/7/2016), and the subjects provided their written informed consent. Blood samples were collected in ethylene diamine tetraacetic acid (EDTA) and stored at −80 °C until analysis.

3. Methylation Study

DNA was extracted and bisulfite converted as previously described [29]. Briefly, DNA was extracted from 200 µL of frozen whole blood and 1 µg DNA was converted using the EZ DNA Methylation Gold Kit (Zymo Research, Irvine, CA, USA) according to the manufacturer’s protocol with elution volume in 50 µL. The FCER1G target region (available from: https://epd.epfl.ch/cgi-bin/get_doc?db=hgEpdNew&format=genome&entry=FCER1G_1; accessed on 25 September 2017) was found in the Eukaryotic Promoter Database (EPD) [30]. The designed primers flanked the region from −130 to +29 bp relative to the transcription start site (TSS). Using the EPD motif tool (based on JASPAR core 2018 vertebrates), we found predictive binding sites for the transcriptional repressor CTCF (the cut-off p-value was 0.001) at positions −256 and −93 and +57 relative to TSS. The primers were designed using MethPrimer Software, version 1.0 [31]. Their sequences are presented in Table 3. The specificity of the primers was first tested in silico using the BiSearch tool [32]. In silico analysis predicted only one specific product in the region corresponding to the FCER1G gene. Then, the specificity of the primers was assessed by PCR with fully methylated and unmethylated DNA (EpiTect PCR Control DNA Set, Qiagen, Hilden, Germany) and was performed under the conditions corresponding to QMSP. PCR amplification products were visualized on a 2% agarose gel with the size marker.
The methylation status of the FCER1G target region was evaluated using primers complementary to the methylated sequences. The Q-MSP reaction contained 300 nM of each primer, as well as 2 µL bisulfite-treated DNA. The reaction was performed using the SG qPCR Master Mix (Eurx, Gdansk, Poland) in a total volume of 10 µL in a COBAS z480 Real-Time PCR System under the thermal cycling conditions given in the mix manual in 40 amplification cycles, except that the annealing step was carried out at 62 °C for 30 s. After each reaction, a melt curve analysis was performed. All samples were evaluated in triplicate. Q-MSP efficiency for reference and target genes was also evaluated as previously described [34]. The methylation data were analyzed using the advanced relative quantification module (LightCycler 480 SW, version 1.5.1.62 SP2–UDF v.2.0.0, Roche, Basel, Switzerland), with the maximum second derivative selected as the calculation model. The results were expressed as a fold change.

Statistical Analysis

Depending on the distribution, assessed by the Shapiro–Wilk W test, the quantitative values were presented as mean (SD) or median [25th–75th percentile]. Differences between two independent groups were compared using the Student’s t-test or the Mann–Whitney U test. Kruskal–Wallis ANOVA and post hoc multiple comparison analysis was used to compare data between more than two independent groups. The relationship between two continuous variables was analyzed using Spearman’s rank correlation and presented by the value of the correlation coefficient rs. Qualitative parameters are given as numbers with percentage and were evaluated using contingency tables with a χ2 test with Yates’s correction. A p-value < 0.05 was considered statistically significant. The analysis was performed with STATISTICA Version 13.1 (Dell Inc., Round Rock, TX, USA, 2016).

4. Results

RA patients have had a lower level of FCER1G methylation than a control group (median [25th–75th percentile]) 0.98 [0.73–1.46] vs. 1.96 [1.44–3] p < 0.0001). No differences in methylation status were found between RA patients in high disease activity and remission; however, both activity groups were different compared to HC (p = 0.0014 and p < 0.0001, respectively). Detailed data were presented in Figure 1.
The methylation status was only correlated with ACPA levels (−0.32) and was not correlated with other clinical variables: DAS28-ESR (rs = 0.13), number of swollen joints (rs = 0.21), number of painful joints (rs = 0.11), ESR (rs = 0.09), CRP (rs = −0.1) and RF (−0.17), white blood count (rs = −0.16), platelet count (rs = −0.15). FCER1G methylation levels were not different (p = 0.21) between patients treated with methotrexate (n = 37) and patients without the drug (n = 13). In the group treated with methotrexate, there was no correlation between the dose of the drug and the level of FCER1G methylation (rs = −0.14).

5. Discussion

In our study, we have found that RA patients had lower levels of FCER1G gene methylation compared to controls. However, we did not observe any difference in the methylation of the studied gene between the group of RA patients with high disease activity and remission, therefore, further functional experiments are necessary to explain the biological function of FCER1G and its association with the development of RA. FCER1G gene methylation may be considered as a new epigenetic marker of RA that is not related to disease activity and unrelated to common markers of inflammation, i.e., ESR or CRP. We have also found that FcRγ may play an important role in RA pathogenesis.
The pathogenesis of RA is multifactorial, with multiple immunological, genetic, epigenetic, and environmental factors playing an important role in its development.
The role of FCER1G has not been thoroughly understood and we are gaining more information about its functions over time. Studies on FCER1G have shown that it is a key molecule in signaling pathways that are widely involved in a variety of immune responses and cell types [25]. Based on mouse models, we can observe that abnormal expression of FcR can result in an uncontrolled immune response and the initiation of autoimmune disease [35]. Recent studies have shown that FcRs are important elements in several processes that, if not properly regulated, can lead to the appearance of autoreactive antibodies or autoimmune phenotypes [36,37]. Binding between the Fc of immunoglobulin and the FcR of the immune cell activates cellular effector functions through an antigen–antibody binding reaction. In a normal state of the immune system through this combination, foreign antigens are recognized and eliminated, whereas in a pathological immune response, the same combination can cause destructive inflammation, immune cell activation, phagocytosis, bursting and oxidative release of cytokines [38,39].
Activation of Fcγ receptors present on the neutrophil surface and associated with the γ chain of the Fc receptor (FcRγ) is important in mediating various cell responses, including activation of cells induced by immune complexes, removal of immune complexes, and phagocytosis of opsonized particles [35,40,41]. These processes are implicated in the pathogenesis of various autoimmune diseases, including rheumatoid arthritis [35,41,42,43].
The FCER1G gene is also involved in various biological processes, including neutrophil activation, T cell differentiation, Fc receptor-mediated signaling pathway, immunoglobulin-mediated immune response, positive regulation of interleukin-4 production, interleukin-3-mediated signaling pathway, innate immune response, positive regulation of phagocytosis, and others [44]. FCER1G may interact with members of the Dectin-2 family which was identified as a locus associated with various autoimmune disorders, including systemic lupus erythematosus and RA. It should be emphasized that there was no functional analysis related to FCER1G and RA development, therefore the matching of the FCER1G with RA development is purely theoretical and must be confirmed by functional experiments. The study conducted by Gordon et al. showed that mouse mast cells produced IL-6 when exposed to thrombin and FceRI. Thrombin is also responsible for IL-6 secretion by fibroblasts and monocytes [45], the FceRI signaling pathway has been widely studied in mast cells. Its activation is responsible for the allergic process inducing mast cells degranulation with histamine production and the synthesis of proinflammatory cytokines-TNF-α and IL-6–key molecules in the RA development. Furthermore, the release of proinflammatory cytokines was observed in dendritic cells and monocytes [46]. The study conducted by Liang et al. [47] showed that FCER1G expression is inverse to the methylation status, therefore, lower methylation is associated with higher mRNA expression. The results were obtained from peripheral blood monocytes from patients with atopic dermatitis. These data suggest that the methylation status of whole blood leukocytes may be a new epigenetic marker of gene activation and protein production. Hypomethylation of FCER1G observed in our study may be associated with higher gene expression and activation of FcRγ dependent pathway and the proinflammatory effect. Differences in methylation status were observed between patients with high disease activity and remission, but without statistical importance.
The expression of the FCER1G gene is correlated with the development of various diseases other than RA, and sometimes also affects a prognosis or response to treatment. Previous studies have shown that FCER1G is involved in the development of innate immunity and may be responsible for the development of eczema, meningioma and childhood leukemia [22,48,49]. An increased expression of FCER1G was reported in osteoarthritis cartilage compared to healthy controls [50]. A higher expression level of FCER1G has also been observed in patients with acute myocardial infarction [1]. An association between FCER1G gene expression and clear cell renal cell carcinoma (ccRCC) was also noted. The researchers noted that despite the lack of a close association between FCER1G and cancer, FCER1G expression is significantly higher in cancer cells than in normal kidney tissue. Chronic inflammation mediated by the FCER1G gene was found to be closely associated with oncogenesis [51]. The above conclusions were extended in the studies by Dong and colleagues who noted that FCER1G was more expressed in tumor tissues of ccRCC patients [52].
Our study has a few limitations. First of all, the small size of the groups means that further investigations in a larger cohort of patients are necessary to confirm our findings, especially the conclusions regarding the usefulness of FCER1G methylation as a potential marker to distinguish patients with RA and healthy controls. Moreover, subjects were enrolled in one medical center, thus an independent validation cohort is needed. The second limitation is associated with applied methodology. The methylation study was conducted based on the QMSP method, therefore results should be confirmed with a different methodology. Our finding may be considered as a basic study; further experiments are necessary to confirm the role of FCER1G in the development of RA. We compared well-established RA to healthy controls, but further studies including early RA and pre-RA patients as well as cell line models are required to better understand the role of FCER1G in disease development and pathogenesis.
In conclusion, FCER1G methylation levels may be considered as novel supportive markers in well-established RA, independent of disease activity based on DAS28 and unrelated to common laboratory markers of inflammation.

Author Contributions

Conceptualization, M.C. and D.P.; Methodology, M.C.; Formal Analysis, D.P. and M.C.; Investigation, D.P.; Writing—Original Draft Preparation, D.P.; Writing—Review and Editing, B.K.; Visualization, M.C.; Supervision, B.K.; Project Administration, B.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the Ethics Committee of Bioethics Committee at the Medical University of Lublin (protocol code KE-0254/7/2016, date of approval 28 January 2016).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Data generated and analyzed during the current study are available from the corresponding author on reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mikhaylenko, D.S.; Nemtsova, M.V.; Bure, I.V.; Kuznetsova, E.B.; Alekseeva, E.A.; Tarasov, V.V.; Lukashev, A.N.; Beloukhova, M.I.; Deviatkin, A.A.; Zamyatnin, A.A. Genetic Polymorphisms Associated with Rheumatoid Arthritis Development and Antirheumatic Therapy Response. Int. J. Mol. Sci. 2020, 21, 4911. [Google Scholar] [CrossRef]
  2. Padyukov, L. Genetics of Rheumatoid Arthritis. Semin. Immunopathol. 2022, 44, 47–62. [Google Scholar] [CrossRef] [PubMed]
  3. McInnes, I.B.; Schett, G. The Pathogenesis of Rheumatoid Arthritis. N. Engl. J. Med. 2011, 365, 2205–2219. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Aletaha, D.; Neogi, T.; Silman, A.J.; Funovits, J.; Felson, D.T.; Bingham, C.O.; Birnbaum, N.S.; Burmester, G.R.; Bykerk, V.P.; Cohen, M.D.; et al. 2010 Rheumatoid Arthritis Classification Criteria: An American College of Rheumatology/European League Against Rheumatism Collaborative Initiative. Ann. Rheum. Dis. 2010, 69, 1580–1588. [Google Scholar] [CrossRef] [PubMed]
  5. Jiang, X.; Trouw, L.A.; van Wesemael, T.J.; Shi, J.; Bengtsson, C.; Källberg, H.; Malmström, V.; Israelsson, L.; Hreggvidsdottir, H.; Verduijn, W.; et al. Anti-CarP Antibodies in Two Large Cohorts of Patients with Rheumatoid Arthritis and Their Relationship to Genetic Risk Factors, Cigarette Smoking and Other Autoantibodies. Ann. Rheum. Dis. 2014, 73, 1761–1768. [Google Scholar] [CrossRef]
  6. Volkov, M.; van Schie, K.A.; van der Woude, D. Autoantibodies and B Cells: The ABC of Rheumatoid Arthritis Pathophysiology. Immunol. Rev. 2019, 294, 148–163. [Google Scholar] [CrossRef] [Green Version]
  7. Strollo, R.; Ponchel, F.; Malmström, V.; Rizzo, P.; Bombardieri, M.; Wenham, C.Y.; Landy, R.; Perret, D.; Watt, F.; Corrigall, V.M.; et al. Autoantibodies to Posttranslationally Modified Type II Collagen as Potential Biomarkers for Rheumatoid Arthritis. Arthritis Rheum. 2013, 65, 1702–1712. [Google Scholar] [CrossRef]
  8. Darrah, E.; Giles, J.T.; Ols, M.L.; Bull, H.G.; Andrade, F.; Rosen, A. Erosive Rheumatoid Arthritis Is Associated with Antibodies That Activate PAD4 by Increasing Calcium Sensitivity. Sci. Transl. Med. 2013, 5, 186ra65. [Google Scholar] [CrossRef] [Green Version]
  9. Kolfenbach, J.R.; Deane, K.D.; Derber, L.A.; O’Donnell, C.I.; Gilliland, W.R.; Edison, J.D.; Rosen, A.; Darrah, E.; Norris, J.M.; Holers, V.M. Autoimmunity to Peptidyl Arginine Deiminase Type 4 Precedes Clinical Onset of Rheumatoid Arthritis. Arthritis Rheum. 2010, 62, 2633–2639. [Google Scholar] [CrossRef] [Green Version]
  10. Okada, Y.; Wu, D.; Trynka, G.; Raj, T.; Terao, C.; Ikari, K.; Kochi, Y.; Ohmura, K.; Suzuki, A.; Yoshida, S.; et al. Genetics of Rheumatoid Arthritis Contributes to Biology and Drug Discovery. Nature 2014, 506, 376–381. [Google Scholar] [CrossRef]
  11. Ha, E.; Bae, S.-C.; Kim, K. Large-Scale Meta-Analysis across East Asian and European Populations Updated Genetic Architecture and Variant-Driven Biology of Rheumatoid Arthritis, Identifying 11 Novel Susceptibility Loci. Ann. Rheum. Dis. 2021, 80, 558–565. [Google Scholar] [CrossRef] [PubMed]
  12. Ishigaki, K.; Sakaue, S.; Terao, C.; Luo, Y.; Sonehara, K.; Yamaguchi, K.; Amariuta, T.; Too, C.L.; Laufer, V.A.; Scott, I.C.; et al. Trans-Ancestry Genome-Wide Association Study Identifies Novel Genetic Mechanisms in Rheumatoid Arthritis. medRxiv 2021. [Google Scholar] [CrossRef]
  13. Okada, Y.; Eyre, S.; Suzuki, A.; Kochi, Y.; Yamamoto, K. Genetics of Rheumatoid Arthritis: 2018 Status. Ann. Rheum. Dis. 2019, 78, 446–453. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Kolarz, B.; Podgorska, D.; Podgorski, R. Insights of Rheumatoid Arthritis Biomarkers. Biomarkers 2020, 26, 1–34. [Google Scholar] [CrossRef] [PubMed]
  15. Hammaker, D.; Firestein, G.S. Epigenetics of Inflammatory Arthritis. Curr. Opin. Rheumatol. 2018, 30, 188–196. [Google Scholar] [CrossRef] [PubMed]
  16. Nemtsova, M.V.; Zaletaev, D.V.; Bure, I.V.; Mikhaylenko, D.S.; Kuznetsova, E.B.; Alekseeva, E.A.; Beloukhova, M.I.; Deviatkin, A.A.; Lukashev, A.N.; Zamyatnin, A.A.J. Epigenetic Changes in the Pathogenesis of Rheumatoid Arthritis. Front. Genet. 2019, 10, 570. [Google Scholar] [CrossRef] [Green Version]
  17. Golbabapour, S.; Abdulla, M.A.; Hajrezaei, M. A Concise Review on Epigenetic Regulation: Insight into Molecular Mechanisms. Int. J. Mol. Sci. 2011, 12, 8661–8694. [Google Scholar] [CrossRef]
  18. Bottini, N.; Firestein, G.S. Epigenetics in Rheumatoid Arthritis: A Primer for Rheumatologists. Curr. Rheumatol. Rep. 2013, 15, 372. [Google Scholar] [CrossRef]
  19. Glant, T.T.; Mikecz, K.; Rauch, T.A. Epigenetics in the Pathogenesis of Rheumatoid Arthritis. BMC Med. 2014, 12, 35. [Google Scholar] [CrossRef] [Green Version]
  20. Klein, K.; Gay, S. Epigenetic Modifications in Rheumatoid Arthritis, a Review. Curr. Opin. Pharmacol. 2013, 13, 420–425. [Google Scholar] [CrossRef] [Green Version]
  21. Anderson, R. Manipulation of Cell Surface Macromolecules by Flaviviruses. In Advances in Virus Research; Academic Press: Cambridge, MA, USA, 2003; Volume 59, pp. 229–274. [Google Scholar]
  22. Mahachie John, J.M.; Baurecht, H.; Rodríguez, E.; Naumann, A.; Wagenpfeil, S.; Klopp, N.; Mempel, M.; Novak, N.; Bieber, T.; Wichmann, H.-E.; et al. Analysis of the High Affinity IgE Receptor Genes Reveals Epistatic Effects of FCER1A Variants on Eczema Risk. Allergy 2010, 65, 875–882. [Google Scholar] [CrossRef] [PubMed]
  23. Kraft, S.; Kinet, J.-P. New Developments in FcεRI Regulation, Function and Inhibition. Nat. Rev. Immunol. 2007, 7, 365–378. [Google Scholar] [CrossRef] [PubMed]
  24. Küster, H.; Thompson, H.; Kinet, J.P. Characterization and Expression of the Gene for the Human Fc Receptor Gamma Subunit. Definition of a New Gene Family. J. Biol. Chem. 1990, 265, 6448–6452. [Google Scholar] [CrossRef]
  25. Fu, L.; Cheng, Z.; Dong, F.; Quan, L.; Cui, L.; Liu, Y.; Zeng, T.; Huang, W.; Chen, J.; Pang, Y.; et al. Enhanced Expression of FCER1G Predicts Positive Prognosis in Multiple Myeloma. J. Cancer 2020, 11, 1182–1194. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Andreu, P.; Johansson, M.; Affara, N.I.; Pucci, F.; Tan, T.; Junankar, S.; Korets, L.; Lam, J.; Tawfik, D.; DeNardo, D.G.; et al. FcRγ Activation Regulates Inflammation-Associated Squamous Carcinogenesis. Cancer Cell 2010, 17, 121–134. [Google Scholar] [CrossRef] [Green Version]
  27. Nimmerjahn, F.; Ravetch, J.V. Fcγ Receptors as Regulators of Immune Responses. Nat. Rev. Immunol. 2008, 8, 34–47. [Google Scholar] [CrossRef]
  28. Arnett, F.C.; Edworthy, S.M.; Bloch, D.A.; McShane, D.J.; Fries, J.F.; Cooper, N.S.; Healey, L.A.; Kaplan, S.R.; Liang, M.H.; Luthra, H.S. The American Rheumatism Association 1987 Revised Criteria for the Classification of Rheumatoid Arthritis. Arthritis Rheum. 1988, 31, 315–324. [Google Scholar] [CrossRef]
  29. Podgórska, D.; Cieśla, M.; Majdan, M.; Podgórski, R.; Kolarz, B. The Relationship of ADAMTSL2 and LRPAP1 Gene Methylation Level with Rheumatoid Arthritis Activity. Clin. Exp. Rheumatol. 2021. [Google Scholar] [CrossRef]
  30. Dreos, R.; Ambrosini, G.; Périer, R.C.; Bucher, P. The Eukaryotic Promoter Database: Expansion of EPDnew and New Promoter Analysis Tools. Nucleic Acids Res. 2015, 43, D92–D96. [Google Scholar] [CrossRef]
  31. Li, L.-C.; Dahiya, R. MethPrimer: Designing Primers for Methylation PCRs. Bioinformatics 2002, 18, 1427–1431. [Google Scholar] [CrossRef] [Green Version]
  32. Tusnády, G.E.; Simon, I.; Váradi, A.; Arányi, T. BiSearch: Primer-Design and Search Tool for PCR on Bisulfite-Treated Genomes. Nucleic Acids Res. 2005, 33, e9. [Google Scholar] [CrossRef] [PubMed]
  33. Cieśla, M.; Kolarz, B.; Majdan, M.; Darmochwał-Kolarz, D. IRF5 Promoter Methylation as a New Potential Marker of Rheumatoid Arthritis. Pol. Arch. Intern. Med. 2019, 129, 370–376. [Google Scholar] [CrossRef]
  34. Livak, K.J.; Schmittgen, T.D. Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  35. Nimmerjahn, F. Activating and Inhibitory FcγRs in Autoimmune Disorders. Springer Semin. Immun. 2006, 28, 305–319. [Google Scholar] [CrossRef] [PubMed]
  36. Takai, T. Roles of Fc Receptors in Autoimmunity. Nat. Rev. Immunol. 2002, 2, 580–592. [Google Scholar] [CrossRef]
  37. Ravetch, J.V.; Kinet, J.P. Fc Receptors. Annu. Rev. Immunol. 1991, 9, 457–492. [Google Scholar] [CrossRef] [PubMed]
  38. Liu, S.; Wang, C.; Yang, H.; Zhu, T.; Jiang, H.; Chen, J. Weighted Gene Co-Expression Network Analysis Identifies FCER1G as a Key Gene Associated with Diabetic Kidney Disease. Ann. Transl. Med. 2020, 8, 1427. [Google Scholar] [CrossRef]
  39. Brandsma, A.M.; Hogarth, P.M.; Nimmerjahn, F.; Leusen, J.H.W. Clarifying the Confusion between Cytokine and Fc Receptor “Common Gamma Chain”. Immunity 2016, 45, 225–226. [Google Scholar] [CrossRef] [Green Version]
  40. Bruhns, P.; Jönsson, F. Mouse and Human FcR Effector Functions. Immunol. Rev. 2015, 268, 25–51. [Google Scholar] [CrossRef] [Green Version]
  41. Futosi, K.; Mócsai, A. Tyrosine Kinase Signaling Pathways in Neutrophils. Immunol. Rev. 2016, 273, 121–139. [Google Scholar] [CrossRef]
  42. Ludwig, R.J.; Vanhoorelbeke, K.; Leypoldt, F.; Kaya, Z.; Bieber, K.; McLachlan, S.M.; Komorowski, L.; Luo, J.; Cabral-Marques, O.; Hammers, C.M.; et al. Mechanisms of Autoantibody-Induced Pathology. Front. Immunol. 2017, 8, 603. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Németh, T.; Futosi, K.; Szabó, M.; Aradi, P.; Saito, T.; Mócsai, A.; Jakus, Z. Importance of Fc Receptor γ-Chain ITAM Tyrosines in Neutrophil Activation and in Vivo Autoimmune Arthritis. Front. Immunol. 2019, 10, 252. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  44. Cunningham, F.; Allen, J.E.; Allen, J.; Alvarez-Jarreta, J.; Amode, M.R.; Armean, I.M.; Austine-Orimoloye, O.; Azov, A.G.; Barnes, I.; Bennett, R.; et al. Ensembl 2022. Nucleic Acids Res. 2022, 50, D988–D995. [Google Scholar] [CrossRef] [PubMed]
  45. Gordon, J.R.; Zhang, X.; Stevenson, K.; Cosford, K. Thrombin Induces IL-6 but Not TNFalpha Secretion by Mouse Mast Cells: Threshold-Level Thrombin Receptor and Very Low Level FcepsilonRI Signaling Synergistically Enhance IL-6 Secretion. Cell Immunol. 2000, 205, 128–135. [Google Scholar] [CrossRef]
  46. Shin, J.-S.; Greer, A.M. The Role of FcεRI Expressed in Dendritic Cells and Monocytes. Cell. Mol. Life Sci. 2015, 72, 2349–2360. [Google Scholar] [CrossRef] [Green Version]
  47. Liang, Y.; Wang, P.; Zhao, M.; Liang, G.; Yin, H.; Zhang, G.; Wen, H.; Lu, Q. Demethylation of the FCER1G Promoter Leads to FcεRI Overexpression on Monocytes of Patients with Atopic Dermatitis. Allergy 2012, 67, 424–430. [Google Scholar] [CrossRef]
  48. Rajaraman, P.; Brenner, A.V.; Neta, G.; Pfeiffer, R.; Wang, S.S.; Yeager, M.; Thomas, G.; Fine, H.A.; Linet, M.S.; Rothman, N.; et al. Risk of Meningioma and Common Variation in Genes Related to Innate Immunity. Cancer Epidemiol. Biomark. Prev. 2010, 19, 1356–1361. [Google Scholar] [CrossRef] [Green Version]
  49. Han, S.; Lan, Q.; Park, A.K.; Lee, K.-M.; Park, S.K.; Ahn, H.S.; Shin, H.Y.; Kang, H.J.; Koo, H.H.; Seo, J.J.; et al. Polymorphisms in Innate Immunity Genes and Risk of Childhood Leukemia. Hum. Immunol. 2010, 71, 727–730. [Google Scholar] [CrossRef] [Green Version]
  50. Karlsson, C.; Dehne, T.; Lindahl, A.; Brittberg, M.; Pruss, A.; Sittinger, M.; Ringe, J. Genome-Wide Expression Profiling Reveals New Candidate Genes Associated with Osteoarthritis. Osteoarthr. Cartil. 2010, 18, 581–592. [Google Scholar] [CrossRef] [Green Version]
  51. Chen, L.; Yuan, L.; Wang, Y.; Wang, G.; Zhu, Y.; Cao, R.; Qian, G.; Xie, C.; Liu, X.; Xiao, Y.; et al. Co-Expression Network Analysis Identified FCER1G in Association with Progression and Prognosis in Human Clear Cell Renal Cell Carcinoma. Int. J. Biol. Sci. 2017, 13, 1361–1372. [Google Scholar] [CrossRef] [Green Version]
  52. Dong, K.; Chen, W.; Pan, X.; Wang, H.; Sun, Y.; Qian, C.; Chen, W.; Wang, C.; Yang, F.; Cui, X. FCER1G Positively Relates to Macrophage Infiltration in Clear Cell Renal Cell Carcinoma and Contributes to Unfavorable Prognosis by Regulating Tumor Immunity. BMC Cancer 2022, 22, 140. [Google Scholar] [CrossRef] [PubMed]
Jcm 11 04664 g001 550
Figure 1. The methylation level of FCER1G in patients with rheumatoid arthritis divided into activity groups and healthy control. Abbreviations: NS, no significant.
Figure 1. The methylation level of FCER1G in patients with rheumatoid arthritis divided into activity groups and healthy control. Abbreviations: NS, no significant.
Jcm 11 04664 g001
Table
Table 1. Characteristics of subjects.
Table 1. Characteristics of subjects.
CharacteristicsRA Overall
n = 50		Controls
n = 24		p-Value
RA Overall vs. HC
Age, years (SD)51 (12.8)53 (8.5)0.45
Females42 (84%)17 (70.8%)0.31
Disease duration, years10 (3–16)n/an/a
RF-positive34 (68%)nonen/a
ACPA-positive46 (92%)nonen/a
ESR, mm/h23.5 (8–57)15 (7–19)0.07
DAS285.3 (2.11–6.12)n/an/a
CRP, mg/dL6.52 (0.51–20.76)0.58 (0.19–1.97)0.003
Number of swollen joints3 (0–7)n/an/a
Number of painful joints4 (1–12)n/an/a
VAS PGA47.5 (8–70)n/an/a
VAS PhGA39.5 (5–60)n/an/a
Data are presented as mean SD; number (%) or median [25th–75th percentile]. Abbreviations: ACPA, anti-citrullinated protein antibodies; CRP, C-reactive protein; DAS28, disease activity score; ESR, erythrocyte sedimentation rate; HC, healthy controls; RA, rheumatoid arthritis patients; RF, rheumatoid factor; VAS PhGA, visual analog scale physician global assessments; VAS PGA, visual analog scale patient global assessments. The differences between two independent groups, according to data distribution, were assessed by the Student’s t-test or the Mann–Whitney U test. Significant differences (p-value < 0.05) were bolded.
Table
Table 2. Characteristics of the patients with rheumatoid arthritis.
Table 2. Characteristics of the patients with rheumatoid arthritis.
CharacteristicsRA in High Disease Activity, n = 29RA in Remission,
n = 21		p-Value
Age, years (SD)54 (13.1)47 (11.7)0.07
Females21 (72.4%)21 (100%)0.025
Disease duration, years10 (3–16)9.5 (3–16)0.96
RF-positive22 (75.9%)12 (57.1%)0.27
ACPA-positive27 (93.1%)19 (90.5%)0.85
ESR, mm/h57 (28–67)7 (2–9)<0.0001
DAS285.89 (5.34–6.37)1.99 (1.58–2.31)<0.0001
CRP, mg/dL17.47 (8.58–29.1)0.4 (0.15–1.4)<0.0001
Number of swollen joints6 (4–10)0 (0–1)<0.0001
Number of painful joints11 (5–13)1 (0–1)<0.0001
VAS PGA68 (55–73)8 (3–10)<0.0001
VAS PhGA60 (49–70]5 (2–10)<0.0001
Methotrexate treatment
(alone or as a concomitant drug)		22 (75.9)15 (71.4)0.98
Methotrexate dose, mg/week20 (15–25)20 (12.5–25)0.64
Data are presented as mean SD; number (%) or median [25th–75th percentile]. Abbreviations: please refer to Table 1. The differences between two independent groups, according to data distribution, were assessed by the Student’s t-test or the Mann–Whitney U test. Significant differences (p-value < 0.05) were bolded.
Table
Table 3. Characteristics of primers.
Table 3. Characteristics of primers.
GenePrimer NameSequence 5′ → 3′ aAmplicon Size [bp]Amplicon Location with Reference to
Assembly GRCh38
[Chromosome:Start:end:Strand]		Primer
Complementary to Methylated/
Unmethylated
Sequences
FCER1GFCER1G
methylated_sense		TGGTTTTTTCGGGAGTCGTTC1601:161215165:161215324:+methylated sequences
FCER1G
methylated_antisense		CATCTTAAACTAAAAATCGACCGTTCT
a CpG sites in primer sequence are in bold. Abbreviations: FCER1G, Fc epsilon receptor Ig gene. To normalize DNA input after bisulfite conversion, the promoter region free of CpG sites in the beta-actin gene (ACTB) was amplified using the primers described previously [33]. Quantitative real-time methylation-specific PCR (Q-MSP) was used to analyze the methylation status.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Podgórska, D.; Cieśla, M.; Kolarz, B. FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis. J. Clin. Med. 2022, 11, 4664. https://doi.org/10.3390/jcm11164664

AMA Style

Podgórska D, Cieśla M, Kolarz B. FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis. Journal of Clinical Medicine. 2022; 11(16):4664. https://doi.org/10.3390/jcm11164664

Chicago/Turabian Style

Podgórska, Dominika, Marek Cieśla, and Bogdan Kolarz. 2022. "FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis" Journal of Clinical Medicine 11, no. 16: 4664. https://doi.org/10.3390/jcm11164664

APA Style

Podgórska, D., Cieśla, M., & Kolarz, B. (2022). FCER1G Gene Hypomethylation in Patients with Rheumatoid Arthritis. Journal of Clinical Medicine, 11(16), 4664. https://doi.org/10.3390/jcm11164664

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop