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| ORIGINAL ARTICLE |
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| Year : 2016 | Volume
: 11
| Issue : 4 | Page : 197-201 |
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Lack of association between btb domain and cnc homolog 2 polymorphism and susceptibility to rheumatoid arthritis in Iranian population
Zahra Malekshahi1, Mahdi Mahmoudi2, Massoomeh Akhlaghi2, Masoud Garshasbi3, Ahmad Reza Jamshidi2, Mohammad Hossein Nicknam MD, PhD 4
1 Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2 Rheumatology Research Center, Tehran University of Medical Sciences, Tehran, Iran
3 Department of Medical Genetics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran
4 Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran; Molecular Immunology Research Center, Tehran University of Medical Sciences, Tehran, Iran
| Date of Web Publication | 8-Nov-2016 |
Correspondence Address:
Prof. Mohammad Hossein Nicknam
Molecular Immunology Research Center, Tehran University of Medical Sciences, Poursina Ave, Tehran
Iran
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/0973-3698.192682
Background: Rheumatoid arthritis (RA) is an autoimmune systemic inflammatory disease, which mostly occurs in genetically susceptible individuals. Single-nucleotide polymorphism (SNP), as the major type of genetic variations, is one of the controversial issues discussed in a large portion of autoimmune disorders. BTB domain and CNC homolog 2 (BACH2), encoded by BACH2 gene, is a regulator of the immune system which reduces activation of T cells and suppresses the inflammation. In this study, we surveyed association of rs72928038 Single-nucleotide polymorphism (SNP) located in an intron region of BACH2 gene in Iranian RA population.
Methods: Blood samples were collected from 623 RA patients and 412 age-, sex-, and ethnicity-matched healthy controls. In order to genotyping the rs72928038 SNP, amplification refractory mutation system-polymerase chain reaction was employed.
Results: None of the alleles and genotypes of rs72928038 SNP had significantly different distributions between RA patients and healthy controls. The GA, GG, and AA genotypes were slightly frequent in patients compared with healthy controls but with no significant differences.
Conclusions: This study did not show rs72928038 as a risk factor for RA in the Iranian population, which was strongly associated with other populations. This underscores genetic diversity in RA susceptibility in different populations. Keywords: BTB domain, CNC homolog, rheumatoid arthritis, single-nucleotide polymorphism
How to cite this article:
Malekshahi Z, Mahmoudi M, Akhlaghi M, Garshasbi M, Jamshidi AR, Nicknam MH. Lack of association between btb domain and cnc homolog 2 polymorphism and susceptibility to rheumatoid arthritis in Iranian population. Indian J Rheumatol 2016;11:197-201 |
How to cite this URL:
Malekshahi Z, Mahmoudi M, Akhlaghi M, Garshasbi M, Jamshidi AR, Nicknam MH. Lack of association between btb domain and cnc homolog 2 polymorphism and susceptibility to rheumatoid arthritis in Iranian population. Indian J Rheumatol [serial online] 2016 [cited 2021 Jan 19];11:197-201. Available from: https://www.indianjrheumatol.com/text.asp?2016/11/4/197/192682 |
| Introduction | |  |
Rheumatoid arthritis (RA) is a chronic autoimmune disease which is categorized by affection of small joints in the hands and feet. It causes pain, stiffness, swelling, and tenderness of joints, which makes bone erosion and joint destruction. Deformed joints usually appear in progressive stages which can result in loss of function and disability.[1] RA may affect the other organs such as eyes, lungs, skin, heart, and blood vessels in more than 15–25% of the cases.[2] The disease involves 0.5%–1% of population worldwide and it is much more common in women.[3] The disease may occur at any age, but it usually appears after age of 40 years. RA is a multifactorial disorder, but its etiology has not been yet completely clarified. Genes, environmental factors, especially smoking and hormonal agents, are the most well-known interfering factors, which can trigger the onset and progression of the disease.[4]
The contribution of genetic variations is about 60% of the risk of RA. Various genome-wide association (GWA) studies have demonstrated common genetic variants including human leukocyte antigen (HLA) and the non-HLA loci that are related to the predisposition toward RA.[5] In addition to HLA-DRB1, some of the important genes associated with RA include STAT4, PTPN22, TRAF1-C5, CD40, PADI4, OLIG3-TNFAIP3, and CCL2.[6] Based on the genetic studies in the Asian and Caucasian populations, expression of these genes among different races may be different.[7],[8],[9] As an example, PADI4 haplotype association with RA has been confirmed in Asian cohorts but not in Caucasian population, or the rs247661 single-nucleotide polymorphism (SNP) in PTPN22 gene was associated with RA while it was not reported in Han Chinese RA patients.[8],[10] On the other hand, some SNPs were proved to be significant in both populations such as some loci in STAT4 and CCR6.[11]
BTB domain and CNC homolog 2 (BACH2) gene is expressed in primary differentiation stages of B cells and plays a key role in immunoglobulin class switching.[12],[13] Furthermore, some lines of evidence have revealed its restrictive impacts on conventional CD4+ T cells and sustaining homeostasis of the immune system.[14],[15] Other possible functions of BACH2 are listed as regulator in antiviral responses and performing as an antioxidant trigger by playing its role as a transcriptional repressor.[16],[17] GWA study and subsequent meta-analysis in the United Kingdom population demonstrate a novel SNP (rs72928038) in BACH2 as a risk factor for RA proneness.[18],[19] Some other studies confirmed this strong association along with other SNPs in multiple sclerosis, autoimmune thyroid disease, and type 1 diabetes in BACH2 gene.[20] Considering this evidence, we evaluate genetic association of rs72928038 SNP in BACH2 with RA susceptibility in Iranian population.
| Subjects and Methods | | |
The participants in the study were 623 RA patients who fulfilled the 1997 revised American College of Rheumatology classification criteria [21] and 412 healthy unrelated controls without any rheumatologic or other autoimmune diseases. The case and control groups were matched for ethnicity, gender, and age. All participants fulfilled informed consent with complete satisfaction. The Human Research Ethics Committee of Tehran University of Medical Sciences approved this study.
Genotyping
Genomic DNA from peripheral blood was extracted using proteinase K digestion and phenol/chloroform extraction method.[22] It was stored in −20°C until genotyping, which was carried out by conventional amplification refractory mutation system-polymerase chain reaction (ARMS-PCR).[23] The ARMS assay is a simple and quite sensitive method for detecting any mutation which uses allele-specific primers designated for both mutant and wild-type alleles. PCR was performed in a 15.5 µl reaction mixture including 2 µl DNA template, 10 mM dNTP (SinaClon, Iran), 5U Taq DNA polymerase (SinaClon, Iran), 2 µl 10X PCR buffer (SinaClon, Iran), and 1 μL of each primer (10 pmol/µl). Three primers had been used, one common reverse and two forward (mutant and wild type), were designed using NCBI (http://www.ncbi.nlm.nih.gov), UCSC (http://genome.ucsc.edu/cgi-bin/hgpcr?command = start), and primer3 (http://primer3.ut.ee) online tools. In each PCR reaction, two internal controls were also applied [Table 1]. The PCR amplification condition was an initial denaturation of 5 min in 95°C, followed by ten cycles of DNA amplification through 30s in 95°C, 30s of 62.7°C, and 60s of 72°C; and 25 cycles over 30s in 95°C, 30s of 57.6°C, and 60s for 72°C. Thereafter, final extension was run over 10 min in 95°C. PCR products were verified via electrophoresis on 2% agarose gel, and the reactions were visualized using UV transilluminator [Figure 1]. Randomly selected samples were sequenced (Macrogen, Seoul, Korea) for validation [Figure 2]. | Table 1: Primers used in amplification refractory mutation system-polymerase chain reaction for BTB domain and CNC homolog 2 rs72928038 genotyping
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 | Figure 1: Gel electrophoresis patterns for ARMS-PCR based detection of rs72928038 SNP in BACH2 gene. The first line shows Internal Control with 367bp product size. The second line depicts DNA bands of every sample with 180bp of size; in each sample from right to left the first one is for Mutant DNA and the second is for Normal DNA. Patients 1, 4 heterozygote for rs72928038 A/G; patients 2, 3, 5, 6 homozygote for Normal allele. DNA ladder and No template control (NTC) are showed in the left of the figure subsequently
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Statistical analysis
Pearson's Chi-square test was used for deviation from the Hardy–Weinberg equilibrium in controls. Chi-square test was applied to test for association between genotype and allele frequencies in two groups. The odds ratio (OR) and 95% confidence interval (CI) were also reported. The differences between clinical manifestations and the genotypes were also evaluated by one-way analysis of variance using SPSS software version 22 (SPSS Inc., Chicago, IL, USA). P < 0.05 was considered statistically significant.
| Results | | |
Demographic data and laboratory measurements of RA patients and healthy controls are represented in [Table 2]. | Table 2: Demographic data and laboratory specifications of rheumatoid arthritis patients and healthy controls
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The allele and genotype distributions were not significantly deviated from the Hardy–Weinberg equilibrium. [Table 3] shows the allelic and genotype frequencies of rs72928038 SNP in BACH2 gene in RA patients and healthy controls. RA patients and healthy individuals did not reveal unequal frequency in alleles and genotypes. While the GG genotype was seen in large percentage of the RA and control groups (84.9% vs. 85.7%), the difference between the groups was not statistically significant (OR = 0.94; 95% CI: 0.65–1.33; P = 0.73). Moreover, the GA genotype was slightly frequent in patients compared with healthy controls; however, no significant difference was observed in GA genotype frequency between two study groups (OR = 1.05; 95% CI: 0.73–1.51; P = 0.75). | Table 3: Allele and genotype distribution of BTB domain and CNC homolog 2 rs72928038 single-nucleotide polymorphism in rheumatoid arthritis patients and healthy controls
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Investigation of correlation between the genotypes of rs72928038 SNP and clinical manifestations of RA, including erythrocyte sedimentation rate (ESR), disease activity score in 28 Joints (DAS28), rheumatoid factor (RF), and anti-cyclic citrullinated peptide antibody (Anti-CCP), eventuated in statistically insignificant difference from many values among patients with distinct three genotypes [Table 4]. | Table 4: Association of BTB domain and CNC homolog 2 gene rs72928038 genotypes with various clinical features of rheumatoid arthritis patients
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| Discussion | | |
Several studies have indicated the genetic contribution to most of the autoimmune diseases. Studies are still ongoing to detect new susceptibility genes related to the diseases to possibly find effective approaches to diagnose and treat.[24]
RA is a common rheumatologic disorder which is estimated to have 60% contingency to be inherited.[6],[25] Several non-HLA loci have been identified in the pathogenesis of RA including BACH2 rs72928038 SNP, which was investigated in this study. Transcription regulator protein BACH2 is expressed primarily in B lymphocytes and suppresses B lymphocyte-induced maturation protein 1 expression, which, in turn, promote expression of Class Switch DNA Recombination (CSR).[12],[26] It is also required for somatic hypermutation (SHM); hence, BACH2-deficient mice show impaired patterns of both CSR and SHM, manifested as incapacitated immunoglobulin SHM and class switching.[27],[28] Furthermore, BACH2 is required to repress inflammatory responses mediated by regulatory T-cell development and restricted differentiation of effector cells.[14]
SNPs in BACH2 gene have been associated with some autoimmune disease including RA.[14],[18] The rs72928038 SNP of BACH2 gene was realized to be strongly associated with RA susceptibility in previous meta-analysis by McAllister et al.[18] Moreover, using the high-density genetic mapping to identify the susceptibility loci for RA in European ancestry, BACH2 rs72928038 SNP was introduced to be significantly associated with RA.[19] On the contrary, the current study revealed no association between rs72928038 allele and genotype frequencies and the risk of RA in the Iranian population. These contradictory findings may be due to racial differences between Iranians and other populations, which possibly stem from genetic differences. In fact, based on geographical situation and ethnic and racial background, allele frequencies and genes variation including SNPs between human populations may vary. In this case, some races keep the ancestral allele and the genes of others comprise both alleles. Of other plausible factors of this discrepancy, different sample size can be pointed out. Low minor allele frequency of rs72928038 SNP was a possible reason to pick a large number of sample size, but it was really difficult to select in our center and it required a long period. In addition, association of clinical manifestations such as Anti-CCP, ESR, RF, and DAS28 with the genotypes of rs72928038 SNP in RA patients were also surveyed, facing no significant relation between none of the aforementioned clinical symptoms.
| Conclusion | | |
Our study does not support the BACH2 rs72928038 SNP as a risk factor for RA in the Iranian population. Because of the important role of BACH2 in immune homeostasis, perhaps other SNPs in this gene are involved in RA predisposition in the Iranian patients. Further studies will still be required to determine involved risk factors for RA etiopathogenesis in BACH2 gene.
Financial support and sponsorship
This survey was supported by the grants from research deputy of Tehran University of Medical Sciences (Grant no. 93-02-30-26181).
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4]
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