Association of CTLA4 Gene Polymorphisms with Rheumatoid Arthritis Susceptibility

Abstract

Background:

Rheumatoid arthritis (RA) is a chronic inflammatory disease, presenting with joint inflammation and its progressive destruction, affecting a range of about 0.24–1% of the population in different parts of the world. It is one of the major disabling conditions among middle-aged and older women. In this study, the association between five single nucleotide polymorphisms (SNPs) of the CTLA4 gene and RA was investigated.

Materials and Methods:

The study group included 200 patients with RA and 184 healthy individuals from the Iranian population as a control group. Results: After PCR and genotyping, 4 of the 5 SNPs studied showed a significant association with RA. Also, an association between specific haplotypes with RA was determined.

Conclusion:

Based on the results, it can be said that some SNPs of the CTLA4 gene may serve as genetic markers for predicting RA susceptibility or progression and using personalized treatment, lead to improved outcomes among patients with RA.

Introduction

The immune system targets the joints in rheumatoid arthritis (RA), a chronic inflammatory autoimmune disease (AD), due to aberrant autoimmunity (Cross et al., 2014). Between 0.2–1% of people worldwide have RA (Zhou et al., 2021). According to the COPCORD (Community-Oriented Plan for the Control of Musculoskeletal Disorders), which is one of the comprehensive studies on the prevalence of rheumatic diseases in Iranian population, the prevalence of RA is estimated to be between 0.33% and 0.7% (Mehrabi et al., 2019). Studies have shown that the prevalence of RA is higher among women than men, and it is often seen more in middle-aged and elderly people. Although the prevalence is lower compared to Western countries, it is still one of the common causes of physical disabilities in the country and requires special attention to prevention, timely diagnosis, and appropriate treatment (Jamshidi et al., 2014; Mehrabi et al., 2019).

RA most commonly damages the joints of the hands, feet, knees, and jaw and can eventually lead to joint deformities. In addition to the joints, RA can also damage the skin, eyes, and blood vessels. Apart from clinical and epidemiological reasons, awareness of the genetic determinants of RA is necessary for early diagnosis and individualized therapeutic interventions. RA has a well-documented genetic basis, as evidenced by family and twin studies (Conforti et al., 2021). In addition, RA development is influenced by three primary factors: genetic predisposition, environmental exposures, and immune dysregulation, with genetics accounting for about 60% of these factors. Although the exact mechanisms of RA are still not fully understood, several studies have shown that the loss of immune tolerance due to the overactivity of autoreactive T cells is one of the main causes of the disease. Human leukocyte antigen (HLA) genes are closely related to the incidence of RA, but some other genes outside the HLA region may also increase the risk of developing the disease (Van Drongelen and Holoshitz, 2017).

The CTLA4 gene (Cytotoxic T-Lymphocyte Associated Protein 4) is a member of the immunoglobulin superfamily that plays a role in regulating the immune system and balancing the body’s immune responses. This gene encodes a protein that transmits an inhibitory signal to T cells. Under normal conditions, CTLA4 acts as an inhibitory molecule in immune processes and helps protect the body from autoimmune attacks by preventing overactive T cells (Gough et al., 2005). Specifically, CTLA4 effectively competes with the stimulatory molecule CD28 by binding to CD80 and CD86 ligands present on antigen-presenting cells, thereby reducing stimulatory immune signals. This mechanism prevents unnecessary and destructive activation of the immune system and therefore plays a vital role in the prevention of autoimmune diseases, including RA (Ghaderi, 2011; Gough et al., 2005). CTLA4 is an essential inhibitory receptor that downregulates T cell activation and thereby maintains immune homeostasis. Studies have shown that genetic changes in the CTLA4 gene can be associated with an increased risk of autoimmune diseases, as a decrease in the inhibitory effect of CTLA4 on T cells can lead to chronic inflammation and damage to body tissues. Genetic polymorphisms (single nucleotide polymorphisms [SNPs] are one of the common types of genetic changes that are often used as genetic indicators in the investigation of hereditary diseases) within the CTLA4 gene, particularly in its promoter region, can alter its expression and reduce its inhibitory effect, potentially leading to immune dysregulation and autoimmune disease. For example, in a study by Mestre et al., using genotype analysis, it was shown that polymorphisms of the CTLA-4 gene, by regulating T cell activity, play an important role in vulnerability to autoimmune diseases (such as lupus, RA, and type 1 diabetes) as well as some infections (FernÂndez-Mestre et al., 2009).

In addition, genetic polymorphisms can be useful as predictive indicators in the diagnosis and prognosis of RA (Schork et al., 2000). However, the composition of SNPs in the genome of individuals has significant differences, especially among different ethnic groups (Komar, 2009). Although international researches have so far investigated the relationship between autoimmune diseases and immune regulatory genes, it is not yet clear whether this genetic susceptibility is also true in the Iranian population. Hence, the study of disease-associated SNPs in specific ethnic groups remains valuable and important. This study is focused on the association of 5 SNPs located in the promoter region of the CTLA4 gene with RA disease.

Materials and Methods

Study subjects

A total of 184 healthy individuals without immunological abnormalities and 200 patients with RA were included in this study. Informed consent was obtained from all participants prior to the collection of peripheral blood samples, and all procedures were carried out in compliance with relevant laws and regulations. The study was approved by the ethical committee of the National Institute of Genetic Engineering and Biotechnology (NIGEB Approval Number: IR. NIGEB.EC1397.11.39E). The RA categorization criteria served as the foundation for the RA inclusion criteria (Aletaha et al., 2010). Healthy controls were selected from the general population and included individuals not receiving immunosuppressive medications and without any known immunological disorders.

Polymerase chain reaction and SNP analysis

First, genomic DNA was extracted from peripheral blood samples using the QIAamp DNA Blood Mini Kit (Qiagen, Valencia, CA, USA). The concentration and purity of DNA were next evaluated using a NanoDrop ND-1000 UV–Vis Spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA) to evaluate DNA purity. The CTLA4 gene on chromosome 2 was the subject of this investigation. The promoter region of the CTLA4 gene was targeted, as polymorphisms in this region may influence gene expression (Robert and Pelletier, 2018). We obtained gene polymorphism data related to 5 SNPs of the CTLA4 gene from the SNP database of NCBI and designed specific primer for detecting its gene: F: 5′-GGCAACAGAGACCCCACCGTT-3′, R: 5′-GAGGACCTTCCTTAAATCTGGAGAG-3′ to amplify genomic DNA fragments containing these 5 SNPs. Sanger sequencing was used to verify the amplified polymorphic regions.

Statistical analysis

SPSS17.0 (SPSS Inc., Chicago, IL, USA) software was used for statistical analysis, including the chi-square test and Fisher’s exact test. A 95% confidence interval (CI) was given along with the odds ratio (OR), and the significance level was set at p < 0.05. By comparing the expected and observed frequencies of a haplotype involved in alleles from various loci, the D coefficient was utilized to assess linkage disequilibrium (LD). A haplotype block and a subset of haplotypes with a frequency of less than 1% were determined by Gabriel et al. (Gabriel et al., 2002). Haploview 4.2 was used to create the LD figure.

Results

A total of 200 RA patients were enrolled in the study, including 179 women (85%) and 21 men (15%), with a mean age of 38.9 ± 6.3 years. Additionally, 184 individuals without immunological abnormalities were included in our research; their average age was 47.2 ± 8.2 years, 150 (82%) of them were women, and 34 (18%) were men. Table 1 provides a summary of each patient’s clinical features.

Table 1.

Clinical Characteristics of the Studied Population

Parameters	RA (n = 200)	Ctrl (n = 184)
Female (n, %)	179 (85)	150 (82)
Male (n, %)	21 (15)	34 (18)
Age (mean ± SD)	38.9 ± 6.3	47.2 ± 8.2
RF positive (n, %)	181 (91)	—
Anti-ccp positive (n, %)	44 (22)	—
CRP positive (n, %)	161 (80)	—
ESR (mean ± SD)^*	29.19 ± 2.2	—

mm/h.

The relationship between SNPs and RA

In this study, the genotype frequencies of SNPs found in the CTLA4 gene were compared between RA patients and healthy controls. Four SNPs in the CTLA4 gene showed a statistically significant association with RA (Table 2).

Table 2.

The Genotype and Allele Frequencies of CTLA4 in RA Patients and Control Subjects

SNP ID	Model	Genotype	Ctrl (%)	RA (%)	Odd ratio (95%CI)	p value
rs733618	Additive	TT	71 (39)	63 (32)	1.00	—
		TC	92 (50)	89 (45)	1.09 (0.70–1.71)	0.705
		CC	21 (11)	48 (23)	2.58 (1.39–4.76)	0.003
	Dominant	TT vs.	71 (39)	63 (32)	1.00	—
	Dominant	TC+CC	113 (61)	137 (68)	1.36 (0.89–2.08)	0.146
	Recessive	TT+TC vs.	163 (89)	152 (77)	1.00	—
	Recessive	CC	21 (11)	48 (23)	2.45 (1.40–4.28)	0.002
	Alleles Freq	T	234 (64)	215 (54)	1.00	—
	Alleles Freq	C	134 (36)	185 (46)	1.50 (1.12–2.00)	0.006
rs11571316	Additive	GG	103 (56)	147 (73)	1.00	—
		GA	70 (38)	40 (20)	0.40 (0.25–0.63)	0.000
		AA	11 (6)	13 (7)	0.82 (0.35–1.92)	0.660
	Dominant	GG vs.	103 (56)	147 (73)	1.00	—
	Dominant	GA+AA	81 (44)	53 (27)	0.45 (0.29–0.70)	0.000
	Recessive	GG+GA vs.	173 (94)	187 (73)	1.00	—
	Recessive	AA	11 (6)	13 (7)	1.09 (0.47–2.50)	0.832
	Alleles Freq	G	276 (75)	334 (80)	1.00	—
	Alleles Freq	A	92 (25)	66 (20)	0.59 (0.41–0.84)	0.003*
rs4553808	Additive	AA	125 (68)	151 (75)	1.00	—
		AG	58 (31)	42 (21)	0.59 (0.37–0.95)	0.030
		GG	1 (1)	7 (4)	5.79 (0.70–47.73)	0.102
	Dominant	AA vs.	125 (68)	151 (75)	1.00	—
	Dominant	AG+GG	59 (32)	49 (25)	0.68 (0.43–1.07)	0.100
	Recessive	AA+AG vs.	183 (99)	193 (96)	1.00	—
	Recessive	GG	1 (1)	7 (4)	6.63 (0.80–54.47)	0.078
	Alleles Freq	A	308 (84)	344 (86)	1.00	—
	Alleles Freq	G	60 (16)	56 (14)	0.86 (0.57–1.27)	0.457
rs16840252	Additive	CC	135 (73)	164 (82)	1.00	—
		CT	49 (27)	31 (15)	0.52 (0.31–0.86)	0.011
		TT	0 (0)	5 (3)	9.06 (0.49–165.33)	0.136
	Dominant	CC vs.	135 (73)	164 (82)	1.00	—
	Dominant	CT+TT	49 (27)	36 (18)	0.60 (0.37–0.98)	0.042
	Recessive	CC+CT vs.	184 (100)	195 (97)	1.00	—
	Recessive	TT	0 (0)	5 (3)	10.38 (0.57–189.6)	0.114
	Alleles Freq	C	319 (87)	359 (90)	1.00	—
	Alleles Freq	T	49 (13)	41 (10)	0.74 (0.47–1.150	0.188
rs62182595	Additive	GG	112 (61)	127 (63)	1.00	—
		GA	59 (32)	58 (29)	0.86 (0.55–1.34)	0.527
		AA	13 (7)	15 (8)	1.01 (0.46–2.23)	0.965
	Dominant	GG vs.	112 (61)	127 (63)	1.00	—
	Dominant	GA+AA	72 (39)	73 (37)	0.89 (0.59–1.35)	0.595
	Recessive	GG+AG vs.	171 (93)	185 (92)	1.00	—
	Recessive	AA	13 (7)	15 (8)	1.06 (0.49–2.30)	0.870
	Alleles Freq	G	283 (77)	312 (78)	1.00	—
	Alleles Freq	A	98 (23)	88 (22)	0.81 (0.58–1.13)	0.222

Bold data indicates significant p values.

The rs733618 polymorphism was significantly associated with RA under an additive homozygous model (CC, p = 0.003 OR = 2.58, 95% CI = 1.39–4.76), and a recessive model (TT + CT vs. CC, p = 0.002, OR = 2.45, 95% CI = 1.40–4.28). The C allele of rs733618 was also significantly associated with increased RA risk (p = 0.006, OR = 1.50, 95% CI = 1.12–2.00). The rs11571316 was associated with RA based on the additive heterozygous model (GA, p = 0.000, OR = 0.40, 95% CI = 0.25–0.63), the dominant model (GG vs. GA+AA, p = 0.000, OR = 0.45, 95% CI = 0.29–0.70), and also allele A in this SNP was associated to RA (p = 0.003, OR = 0.59, 95%CI= 0.41–0.84). The genotype frequency of rs4553808 was associated with RA based on the additive heterozygous model (AG, p = 0.030, OR = 0.59, 95% CI =0.37–0.95). The rs16840252 was associated with RA based on the additive heterozygous model (CT, p = 0.011 OR = 0.052, 95% CI = 0.31–0.86) and the dominant model (CC vs. CT+TT, p = 0.042, OR = 0.60, 95% CI = 0.37–0.98). However, no significant association was found between rs62182595 and RA in the comparison of the patient and control groups.

Linkage disequilibrium and haplotype analysis

Due to variations in incidence and susceptibility SNPs between groups, RA may be linked to a particular haplotype. As a result, the SNP analysis was carried out before the haplotype analysis. Four haplotypes showed statistically significant associations with RA after excluding those with frequencies <1% were eliminated (GAT: OR = 0.63, 95% CI = 0.43–0.93, p = 0.01; GGC: OR = 0.69, 95% CI = 0.50–0.95, p = 0.02; GGT: OR = 0.57, 95% CI = 0.38–0.86, p = 0.00; AGC: OR = 0.48, 95% CI = 0.31–0.75, p = 0.00). The haplotype contained rs11571316 G/A, rs62182595 G/A, and rs16840252 C/T (Table 3).

Table 3.

The Haplotypes Associated to RA

Haplotype	Ctrl freq (%)	RA freq (%)	OR (95%CI)	p value
GAT	91 (49)	63 (31)	0.63 (0.43–0.93)	0.01
GGC	139 (76)	105 (52)	0.69 (0.50–0.95)	0.02
GGT	83 (45)	52 (26)	0.57 (0.38–0.86)	0.00
AGC	74 (40)	39 (19)	0.48 (0.31–0.75)	0.00

Haplotype contained rs11571316 G/A, rs62182595 G/A and rs16840252 C/T.

The SNPs associated with the immunological factors of RA

Three SNPs of the CTLA4 gene were associated with immunological factors of RA. rs733618 of the CTLA4 gene was associated with CRP (C-Reactive Protein) based on the additive model (TT vs. CT vs. CC, OR = 0.64, 95% CI = 1.02–2.67, p = 0.04), and the recessive model (TT + CT vs. CC, OR = 0.780; 95% CI = 0.39–0.95, p = 0.041). rs11571316 of the CTLA4 gene was associated with CRP based on the additive model (GG vs. AG vs. AA, OR = 1.01, 95% CI = 0.89–1.48, p = 0.008), dominant model (GG vs. AG + AA, OR = 0.715; 95% CI = 0.34–0.76, p = 0.02), and heterozygous model (GG vs. AG, OR = 1.08; 95% CI = 0.95–1.83, p = 0.001). rs4553808 was associated with RF (Rheumatoid Factor) based on the additive model (AA & AG & GG, OR = 5.78, 95% CI = 1.99–16.83, p = 0.001).

Discussion

Studies have shown that some polymorphisms of the CTLA4 gene, specifically in the promoter site, have been reported to be linked to elevated or decreased risk of RA since these changes could affect the expression and function of the gene. Identification of these SNPs could help in predicting RA risk and prognosis and result in the formulation of targeted and individualized therapy in patients (Gough et al., 2005; Li et al., 2012; Mousavi et al., 2021; Zhou et al., 2021).

This study investigated five promoter-region SNPs in the CTLA4 gene among 200 Iranian RA patients and 184 healthy controls. Four of these SNPs were significantly associated with RA. Also, the relationship between these SNPs and immunological parameters in patients with RA was evaluated. Based on the reviews and studies, it is clearly established that parameters such as RF, antibodies against citrullinated proteins (ACPA) such as ACCP, and CRP, which is an inflammatory protein, play an important role in diagnosis. The severity of the disease is RA (Nakken et al., 2017). In addition, erythrocyte sedimentation rate is another immunological measure to evaluate the severity and activity of RA (Sokka and Pincus, 2009).

rs733618

According to the results of this investigation, there was a significant relationship between rs733618 and both RA and CRP. Numerous statistical models have identified this SNP as one of the genetic markers that effectively raises the risk of RA because it directly influences the regulation and expression of the CTLA4 gene. According to the recessive hypothesis, those who have the CC genotype are more likely to develop RA than people who carry at least one T allele (CT or TT genotypes). The CC genotype at rs733618, in particular, has been shown to raise the risk of RA by about 2.58 times, demonstrating the important role this SNP plays in controlling immunological pathways and impacting the prevalence of inflammatory events in RA (Chen et al., 2023; Mukhtar et al., 2021). This SNP has been linked to a number of different illnesses, such as Graves’ disease, systemic lupus erythematosus, type 1 diabetes, and other autoimmune and inflammatory conditions (Cai et al., 2019; Chen et al., 2019; Liu and Zhang, 2013).

rs11571316

The results obtained identified rs11571316 as being associated with both CRP and RA, hence a factor in RA pathogenesis and inflammation response. The same evidence is obtained in similar studies. For instance, the study by Chen et al. (2023) has shown that individuals with the risky allele of rs11571316 are more likely to develop rheumatoid arthritis, validating the role of CTLA4 gene polymorphisms in the development of the disease (Chen et al., 2023). In another study on the relationship between CTLA4 SNPs and various autoimmune diseases, it was observed that SNP rs11571316 was associated to RA and other disorders such as lupus (Kasamatsu et al., 2018). CTLA4 expression could be upregulated in the etiology of RA and the inflammatory response (Chen et al., 2023).

rs4553808

The rs4553808 SNP proved to be another significantly associated polymorphism for susceptibility in RA and RF. Similarly, it has been reported that this SNP is associated with RA vulnerability according to studies. More precisely, the studies show that this polymorphism may increase the level of CTLA4 protein by augmenting the activity in immunological regulation against inflammation (Chen et al., 2023; Mukhtar et al., 2021).

16840252

According to the investigations and the results of this study, the relationship between rs16840252 and RA was proven. In the research of Chen et al., the association of SNP rs16840252 and other CTLA4 SNPs with RA in the Chinese population was investigated. The results of Chen’s research have shown that this SNP is related not only to RA but also to other autoimmune diseases (Chen et al., 2023). But in another study that investigated the Han Chinese population, this relationship was rejected (Liu et al., 2021).

rs62182595 did not show a statistically significant relationship in individual SNP analysis, but in haplotype analysis, this SNP interacted with two other SNPs and was associated with RA. Some studies have confirmed our findings in this case. For example, in a study by Mukhtar et al., the effect of SNP rs62182595 on the risk of RA was investigated. This study concluded that this SNP was not significantly associated with RA, and these findings imply that other genetic or environmental factors may play a greater role in the development of RA (Mukhtar et al., 2021). In Chen et al.’s study, the rs62182595 polymorphism showed no significant difference between RA patients and the control group, and its relationship with RA was not confirmed (Chen et al., 2023). On the contrary, in a study, the association between this SNP and the prognosis of leukemia patients after hematopoietic stem cell transplantation (HSCT) was investigated, and this SNP has shown a protective effect against the development of graft-versus-host disease in patients with acute myeloid leukemia and acute lymphoblastic leukemia. Based on the findings of this study, rs62182595 was considered as a genetic marker for identifying suitable donors in HSCT transplantation and a key role in regulating immune responses (Chen et al., 2021).

Additionally, three SNPs with significant LD in the CTLA4 locus were identified by haplotype analysis: rs11571316, rs62182595, and rs16840252. In a number of haplotypes, these three SNPs were shown to be substantially associated with RA. Haplotype analysis revealed a statistically significant association with rs62182595, despite the fact that individual SNP analysis did not. This suggested that the SNPs that cause RA could interact with one another. Therefore, further research is required to determine the role of the CTLA4 haplotype that predisposes RA. Similar correlations between these SNP haplotypes and RA were found in the Chen et al. investigation (Chen et al., 2023).

After studying and reviewing the available literature, we concluded that SNPs associated with RA are also associated with other autoimmune diseases. These findings indicate the key role of these SNPs in immune responses. It was also found that the association of several SNPs with RA risk was dependent on RF, ACCP, and CRP status. These immunoregulatory genes play an important role in the process of T cell activation (Iaremenko and Mykytenko, 2021), and the SNPs investigated in our study are all located in the promoter region. This point indicates that these important SNPs can affect the binding points of transcription factors or interfere with mRNA stability and thus cause changes in gene expression and disease occurrence (Boag et al., 2020). The findings suggest that CTLA4 SNPs act, in a haplotype manner particularly, to play a role in RA pathogenesis. The SNPs may affect inflammatory mechanisms in RA by impairing CD4 T cell function and regulating the expression levels of immunogenic genes. Additional functional research with the aim of elucidating gene and protein expression alterations within the setting of these SNPs would provide greater insights.

Conclusion

This study showed that certain SNPs of the CTLA4 gene can be associated with an increased risk of RA and also with immunological parameters of this disease, such as CRP, RF, and ACPA. SNPs such as rs733618 and rs11571316 affect the regulation and expression of the CTLA4 gene and can contribute to inflammation and reduced immune tolerance in RA. It also showed that due to the location in the promoter region of the gene, some of these polymorphisms might change the level of gene expression and protein function by interference with the binding points of transcription factors. The findings of this study can play an effective role in diagnosing genetic markers for forecasting and managing RA and ultimately developing individualized treatment of patients.

Footnotes

Confirmation Statement

All authors confirm that their research was supported by institutions primarily engaged in education or research. Specifically, the Iranian authors are affiliated with academic institutions that are fundamentally involved in educational and scientific activities.

Acknowledgments

The authors deeply appreciate the participation and cooperation of all individuals, especially, Dr. Rana Sarmiti, who took part in this study. Rana Sarmiti’s contribution has been instrumental in helping them achieve the objectives of their research. This work would not have been possible without your time and effort.

Research Ethics Statement

The study was approved by the ethical committee of National Institute of Genetic Engineering and Biotechnology (NIGEB Approval Number: IR. NIGEB.EC1397.11.39E).

All participants in this study, after receiving complete information about the objectives, methods, and their rights, signed a written informed consent form and agreed to participate in the study.

Authors’ Contributions

Writing—original draft, project administration: A.A.; Data curation: M.H.; Formal analysis and investigation: A.A. and M.H.; Writing—review and editing and validation: A.A., I.T., and M.H.

Author Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

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