Association of the rs1801133 and rs1801131 polymorphisms in the MTHFR gene and the adverse drug reaction of methotrexate treatment in a sample of Iraqi rheumatoid arthritis patients

Qassim Mahdi Mutlak; Ali Abdulhussain Kasim

doi:10.3897/pharmacia.71.e113597

Research Article

Association of the rs1801133 and rs1801131 polymorphisms in the MTHFR gene and the adverse drug reaction of methotrexate treatment in a sample of Iraqi rheumatoid arthritis patients

Qassim Mahdi Mutlak^‡, Ali Abdulhussain Kasim^‡

‡ University of Baghdad, Baghdad, Iraq

Corresponding author: Qassim Mahdi Mutlak ( qasem.mahdi1100p@copharm.uobaghdad.edu.iq )

Academic editor: Magdalena Kondeva-Burdina

This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Citation: Mutlak QM, Kasim AA (2024) Association of the rs1801133 and rs1801131 polymorphisms in the MTHFR gene and the adverse drug reaction of methotrexate treatment in a sample of Iraqi rheumatoid arthritis patients. Pharmacia 71: 1-8. https://doi.org/10.3897/pharmacia.71.e113597

Abstract

Background: Methotrexate is one of the mainstays for treating rheumatoid arthritis (RA) with a wide range of adverse drug reactions, however, it’s the relationship between adverse drug reactions and genetic polymorphism remains to be highlighted, and there is a lack of studies concerning Arabic Iraqi population regarding this aspect.

Objective: Evaluate the association between genetic mutations in the MTHFR gene in SNPs (rs1801133G>A and rs1801131T>G) on the adverse drug reaction for RA Iraqi patients.

Methods: An observational study, that involved 95 Iraqi RA patients with established RA. Patients were divided according to the occurrence of adverse drug reactions. A polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was being utilized for MTHFR variants (rs1801133 and rs1801131). The Macrogen Company (Korea) provided the forward and reverse primers in lyophilized form. All PCR procedures are carried out using a PCR thermal cycler (Germany).

Results: The study included 95 patients with RA, with a mean age of 43.1 ± 10.6 years, most of the patients were female (85.3%), about 35.8% were smokers, most of the patients had disease low activity (45.2%), followed by moderate (41.1%), high (9.5%), and remission (4.2%). No significant association between individual genetic polymorphism with adverse drug reactions. AG haplotype for rs1801133 rs1801131 polymorphism is associated with reducing the risk of overall adverse drug reactions, meanwhile, GT haplotype for rs1801133, and rs1801131 polymorphism were marginally associated with increased risk of adverse drug reactions.

Conclusion: In conclusion, we have successfully found a panel of pharmacogenetic indicators that have the potential to be valuable in predicting the response to methotrexate treatment in patients with rheumatoid arthritis. Haplotypes for rs1801133 rs1801131 polymorphism are associated with reducing or increasing the risk of MTX adverse drug reactions. It is very important to evaluate patients’ haplotypes before starting the therapy program so that we can expect the treatment outcome with the most suitable dose and most tolerable one at the same time.

Keywords

methotrexate, rheumatoid arthritis, adverse drug reaction, polymorphism, MTHFR gene

Introduction

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disorder characterized by pain and swelling in the hands and feet on both sides (Faiq et al. 2019b; Kadhim Jwad et al. 2022; Mohammed et al. 2022b). It is characterized by both articular and extra-articular manifestations, and permanent joint deformities can develop in improperly managed cases (Ali et al. 2010; Hadi and Ali 2010; Mikhael and Ibrahim 2017).

Methotrexate (MTX) functions as a folic acid inhibitor, exerting anti-inflammatory and anti-proliferative effects by closely resembling the structural and physiochemical properties of folic acid. Methotrexate (MTX) is extensively employed in the treatment of rheumatoid arthritis (RA) due to its notable efficacy, favorable safety profile, and cost-effectiveness (Faiq et al. 2019a; Abdul-Wahab and Al-Shawi 2020). The enzyme known as methylenetetrahydrofolate reductase (MTHFR) plays a crucial role in the metabolic processes involving folate and homocysteine. The primary purpose of this entity is to enable the transformation of 5,10-methylenetetrahydrofolate into 5-methyltetrahydrofolate. The aforementioned form of folate is the prevailing circulating form and is employed in the process of remethylating homocysteine to methionine (Rosenblatt 1995).

Pharmacogenetics refers to the examination of the correlations between genetic variations among individuals and their impact on the efficacy and adverse effects of specific drugs. Therefore, it has the potential to aid clinicians in tailoring treatment plans for individual patients (Malik and Ranganathan 2013).

The MTHFR gene is influenced by racial and ethnic differences (Hughes et al. 2006), some reported that the frequency of rs1801131 SNP varies racial and ethnicity in which the A allele is associated with more ADR in Caucasians (15.9 fold increase in risk) (Hughes et al. 2006), while rs1801133 reported increase association between TT genotype with Mexican Mestizo and Amerindian populations, while the AA genotype frequency was low in African and Asian ancestry populations (Binia et al. 2014).

Numerous studies have provided evidence of associations between genetic variations in the MTHFR gene and increased susceptibility to methotrexate (MTX) toxicity. The MTHFR 677C>T (rs1801133) genetic variant is associated with elevated hepatic enzyme levels, hyperhomocysteinemia, and increased susceptibility to methotrexate (MTX) toxicity. The single-nucleotide polymorphism (SNP) known as MTHFR 1298A>C (rs1801131) is associated with the combined adverse drug effects (ADEs) on the gastrointestinal, hematologic, and mucosal systems that are linked to the use of methotrexate (MTX) (Haagsma et al. 1999; van Ede et al. 2001; Urano et al. 2002; Berkun et al. 2004).

Numerous studies have been undertaken to examine the genetic polymorphism of enzymes implicated in the mechanisms of methotrexate (MTX) activity. The primary discoveries revolve around the genetic polymorphisms within the methylene tetrahydrofolate reductase (MTHFR) enzyme, which is involved in the activation of folic acid and therefore impacts the functions of MTX. Extensive research has been conducted on the polymorphisms of the gene located on chromosome 1 (1p36.3) due to the enzyme’s substantial role in DNA synthesis, repair, and methylation. This study primarily focused on the investigation of two missense mutations: the first mutation, denoted as the C677T substitution (rs1801133), and the second mutation, referred to as the A1298C substitution (rs1801131). The association between these genetic variations and the effectiveness and/or adverse effects of methotrexate (MTX) in the treatment of rheumatoid arthritis (RA) has been documented. However, the results of these investigations have produced contradictory and ambiguous results (Frosst et al. 1995; van der Put et al. 1998; Berkani et al. 2017; Muss et al. 2019).

The current study aims to evaluate the association between MTHFR gene SNPs (rs1801133G>A and rs1801131T>G) and the development of MTX adverse drug reactions in Arab Iraqi RA patients.

Methods

Study design

An observational study, that involved 95 Iraqi RA patients with established RA according to the revised 2010 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) Classification Criteria for RA (Kay and Upchurch 2012). Patients were classified according to the presence or absence of a specific or overall ADR.

Study settings

All the patients enrolled in this study were recruited from the Rheumatology Department of Diwaniya Teaching Hospital. The study was performed between the 1^st of June 2022 and to 1^st of March 2023.

Inclusion criteria

Adult patients (age ≥18 years), with confirmed RA according to revised 2010 ACR/EULAR RA classification criteria (Kay and Upchurch 2012), and all patients should be on MTX for at least 3 months.

Exclusion criteria

Patients with co-existent diseases other connective tissue diseases, patients who use additional disease-modifying antirheumatic drugs (DMARDs), biological drugs, incomplete data, patients with any chronic infectious diseases, cancer, hepatic or renal dysfunction, endocrinopathy, hematological and cardiac conditions.

Sample size

Sample size estimation was based on the following equation:

$m i n i m u m s a m p l e s i z e (n) = p \frac{(1 - p) Z_{0.95}^{2}}{d^{2}}$

Where n is the minimal sample size, and p is the prevalence of 2.2% of RA Iraq in 2019 (Al Badran et al. 2022). The Z represents the Z-score at a 95 % confidence interval, and it equals 1.96, d represents the marginal error which is accepted according to (Daniel and Cross 2018) to be 0.03. Thus, the minimal sample size was estimated to be approximately 92, and 95 was chosen as the final sample size to account for possible drop cases.

DNA extraction

The genomic DNA was isolated from the peripheral blood of subjects and then it was stored at (-20°C) until its analysis. The extracted DNA is based on Hashim and Al-Shuhaib’s study (Hashim and Al-Shuhaib 2020), which depends on non-organic procedures. After the extraction by agarose gel electrophoresis (1% agarose) [Bio-Rad Experion Automated Electrophoresis System (RRID: SCR_019691)], the DNA samples were verified by spectrophotometry using Shimadzu UV-1800 UV/Visible Scanning Spectrophotometer; 115 VAC (Germany) (Tataurov et al. 2008; Hegazi et al. 2018), see Fig. 1.

Figure 1.

Total number of patients who participated in the current study.

Primer selection

The design of PCR primers for MTHFR variants (rs1801133 and rs1801131) according to the following (see Table 1); briefly as follows The primers were designed with the aid of NCBI-primer BLAST online software [NCBI BLAST (RRID: SCR_004870)], at the same time the produced primers was checked for specificity for their target sequences by performing the BLAST against the human genome, then the primers pair was selected according to the demand criteria such as product length, the similarity of melting temperature, primers length, specificity, etc. The primer ability to form a secondary structure was checked with the aid of Oligo Calc online software [OligoCalc (RRID: SCR_022663)], the primer would be rejected if it had 5 bases or more able to form self-dimerization and/or it had 4 bases able to form hairpin. Each primer pair was checked for dimer formation with the aid of “Multiple Primer Analyzer” online software from Thermo Fisher Scientific Inc.^©, the sensitivity of the software was adjusted to the value 2, the primer pair would be rejected if it made any dimers in this degree of sensitivity (Kibbe 2007; Qu et al. 2012; Al-Radeef et al. 2019).

Table 1.

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Primers sequence, GC%, annealing temperature (Ta), and product size of MTHFR genes 1298 (rs1801131) SNP and 677 (rs1801133) SNP (302).

MTHFR Gene 1298 (rs1801131) SNP
Ta	60°C
Product size	90 bp
Primers	Sequence	GC%
Forward primer	TCCCGAGAGGTAAAGAACGtAGAC	50
Reverse primer	TCCCCCAAGGAGGAGCTGCTGtAGA	60
MTHFR Gene 677 (rs1801133) SNP
Ta	°C
Product size	254 bp
Primers	Sequence	GC%
Forward primer	CCTGGATGGGAAAGATCCCG	60
Reverse primer	CATCCCTCGCCTTGAACAGG	60

Genotyping of polymorphisms

A polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) was being utilized for MTHFR variants (rs1801133 and rs1801131). The Macrogen Company (Korea) provided the forward and reverse primers in lyophilized form. All PCR procedures are carried out using a PCR thermal cycler (Germany). Reactions were adjusted to a final volume of 20 µL including Master mix probes and 10–20 ng/µL of genomic DNA (see Table 2), with the following amplification protocol illustrated in Table 3.

Table 2.

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The components of PCR for amplification MTHFR gene.

Reagents	Concentration	Volume
Genomic template DNA	10–20 ng/μL	2 μL
Master mix	2.5 x	8 μL
Forward primer (100 pmol/µL)	10 pmol/μL	1 μL
Reverse primer (100 pmol/µL)	10 pmol/μL	1 μL
MgCl₂	25 mM/0.5 mL	0.5 μL
Nuclease free water	–	7.5 μL
reaction total volume	–	20 μL

Table 3.

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The components of PCR for amplification MTHFR gene.

Stage	Step	Temperature	Interval	Cycles number
1	Initial Denaturation	94 °C	5 minutes	1
2	Denaturation	94 °C	30 seconds	35
3	Annealing	58 °C	30 seconds
4	Elongation	72 °C	30 seconds
5	Final Elongation	72 °C	5 minutes	1

Ethical considerations

The study was approved by College of Pharmacy, Baghdad University (Approval number: RECAUBCP 6620226, date: 6^th June 2022), and written informed consent was obtained from all participants in the study, in accordance with the Helsinki Declaration and its later amendments.

Statistical analysis

The genotyping results were analyzed, and frequencies of alleles and genotypes were calculated. Hardy-Weinberg Equilibrium (HWE) Calculator for 2 Alleles using online calculator using the difference in distribution between the actual frequency of genotype compared (observed) to the expected frequency of genotype (Schaid et al. 2006). Both rs1801133 (p-value = 0.018) and rs1801131 (p-value = 0.304) follow HWE (p-value of 0.0057 used for allele frequency less than 100, assuming type I error (α) = 0.01) (Wigginton et al. 2005).

Haplotyping analysis was carried out using SHEsis online software which is based on the partition-ligation-combination-subdivision EM algorithm for haplotype inference with multiallelic markers (Shi and He 2005; Li et al. 2009).

The chi-square test is employed to assess discrete variables. In cases where the chi-square test is not applicable, such as when the sample size is less than 20 or when there are two or more categories with anticipated frequencies less than 5, the Fisher exact test is used as an alternative. The Fisher-Freeman-Halton exact test of independence is employed for n x k tables, which are an extension of the conventional 2x2 Fisher exact test, where the predicted frequency is below 5% (Ghent 1972). Binary logistic regression analysis was used to calculate the odds ratio (OR) and their 95% confidence intervals when the outcome can be categorized into two binary levels, and Wald was used to assessing which parameters had a stronger effect (Wald is t² which is Chi-Square distributed with df=1). GraphPad Prism version 10.0.0 for Windows [GraphPad Prism (RRID: SCR_002798)] was used to make the statistical analysis, p-value considered when appropriate to be significant if less than 0.05. The genotypes of the participants were subjected to association testing, logistic regression, and haplotype analysis.

Data availability

Underlying data: Zenodo: polymorphisms in the MTHFR gene and the adverse drug reaction of methotrexate. https://doi.org/10.5281/zenodo.8400501

The project contains the following underlying data: polymorphisms in the MTHFR gene and the adverse drug reaction of methotrexate.

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Results

Demographic and clinical data

The study included 95 patients with RA, with a mean age of 43.1 ± 10.6 years, most of the patients were female (85.3%), and about 35.8% were smokers. The distribution of SE per organ system and overall are illustrated in Tables 4, 5.

Table 4.

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Assessment of demographic, laboratory, and disease characteristics of RA patients.

Variables	Value
Number	95
Age (years), mean ± SD	43.1 ± 10.6
Sex, n (%)
Female	81 (85.3%)
Male	14 (14.7%)
Smoking, n (%)	34 (35.8%)
ESR (mm/hour), median (IQR)	24.0(16.0–39.0)
RF (U/ml), median (IQR)	23.0(16.4–29.0)
MTX dose (mg), median (IQR)	10.0(7.5–10.0)
MTX duration (month), median (IQR)	19.0(11.0–31.0)
Duration of disease, median (IQR)	23.0(12.0–34.0)

Table 5.

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Assessment of the adverse drug reactions.

ADR	N (%)
Dermatological	21 (22.1%)
Liver	7 (7.4%)
GIT	43 (45.3%)
Respiratory	8 (8.4%)
Hematological	4 (4.2%)
Renal	1 (1.1%)
Overall	84 (88.4%)

Study limitations

This study suffers from some objective limitations, one is the–sectional nature of the study, second, a single ethnic group was examined – namely Arabic sample, and we could not examine other ethnicities like Caucasian, African, and Kurdish, which will limit the generalizability of our findings and limit them to Arabic ethnicity.

Conclusion

In conclusion, we have successfully found a panel of pharmacogenetic indicators that have the potential to be valuable in predicting the response to methotrexate treatment in patients with rheumatoid arthritis. The results of our study may assist healthcare professionals in identifying patients who are unlikely to derive optimal benefits from methotrexate (MTX) treatment. These individuals may require supplementary drugs or greater therapeutic doses of MTX. This will enhance the quality of therapy decisions for people with rheumatoid arthritis (RA). Haplotypes for rs1801133 rs1801131 polymorphism are associated with reducing or increasing the risk of MTX adverse drug reactions. It is very important to evaluate patients’ haplotypes before starting the therapy program, so that we can expect the treatment outcome with the most suitable dose and most tolerable one at the same time.

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﻿Abstract

Keywords

﻿Introduction

﻿Methods

﻿Study design

﻿Study settings

﻿Inclusion criteria

﻿Exclusion criteria

﻿Sample size

﻿DNA extraction

﻿Primer selection

﻿Genotyping of polymorphisms

﻿Ethical considerations

﻿Statistical analysis

﻿Data availability

﻿Results

﻿Demographic and clinical data

﻿Adverse drug reaction

﻿Liver ADR

﻿Skin ADR

﻿GIT ADR

﻿Respiratory ADR

﻿Overall ADR

﻿Haplotyping analysis

﻿Discussion

﻿Study limitations

﻿Conclusion

﻿References

Abstract

Introduction

Methods

Study design

Study settings

Inclusion criteria

Exclusion criteria

Sample size

DNA extraction

Primer selection

Genotyping of polymorphisms

Ethical considerations

Statistical analysis

Data availability

Results

Demographic and clinical data

Adverse drug reaction

Liver ADR

Skin ADR

GIT ADR

Respiratory ADR

Overall ADR

Haplotyping analysis

Discussion

Study limitations

Conclusion

References