Influence of polymorphisms within the methotrexate pathway genes on the toxicity and efficacy of methotrexate in patients with juvenile idiopathic arthritis

Authors


Dr Masakatsu Yanagimachi, Department of Pediatrics, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama 236-0004, Japan.
Tel.: +81 45 787 2800
Fax: +81 45 787 0461
E-mail: m-yanagi@mvi.biglobe.ne.jp

Abstract

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• Methotrexate (MTX), which causes adverse effects, such as liver and/or renal dysfunction, is the most common disease-modifying antirheumatic drug used for the treatment of rheumatoid arthritis and articular-type juvenile idiopathic arthritis (JIA).

• Pharmacogenetic studies analysing the MTX pathway genes would aid in the development of more personalized therapy.

• Results regarding the influence of gene polymorphisms on the toxicity and efficacy of MTX are conflicting, and there are marked differences between racial groups in pharmacogenetics.

WHAT THIS STUDY ADDS

• The non-TT genotype at γ-glutamyl hydrolase (GGH) T16C is associated with a high risk of liver dysfunction due to MTX, even after adjustment for duration of MTX treatment.

• Longer time interval from disease onset to MTX treatment and rheumatoid factor positivity are associated with lower efficacy of MTX in Japanese patients, as reported previously in Caucasian patients with JIA.

AIMS We investigated whether several polymorphisms within the methotrexate (MTX) pathway genes were related to the toxicity and efficacy of MTX in 92 Japanese patients with articular-type juvenile idiopathic arthritis (JIA).

METHODS Eight gene polymorphisms within the MTX pathway genes, namely, RFC, BCRP, MTHFR (two), FPGS, γ-glutamyl hydrolase (GGH; two) and ATIC, were genotyped using TaqMan assays. Liver dysfunction was defined as an increase in alanine transaminase to five times the normal upper limit. Non-responders to MTX were defined as patients refractory to MTX and were therefore treated with biologics.

RESULTS The non-TT genotype at GGH T16C was associated with a high risk of liver dysfunction (P = 0.028, odds ratio = 6.90, 95% confidence interval 1.38–34.5), even after adjustment for the duration of MTX treatment. A longer interval from disease onset to treatment (8.5 and 21.3 months, P = 0.029) and rheumatoid factor positivity (P = 0.026, odds ratio = 2.87, 95% confidence interval 1.11–7.39) were associated with lower efficacy of MTX.

CONCLUSIONS The non-TT genotype at GGH T16C was associated with a high risk of liver dysfunction, presumably because the C allele of GGH C16T may reduce the activity of GGH. The time interval before MTX treatment and rheumatoid factor positivity were associated with the efficacy of MTX treatment. The pharmacogenetics of the MTX pathway genes affects the toxicity and efficacy of MTX in Japanese JIA patients.

Introduction

Juvenile idiopathic arthritis (JIA) is one of the most common forms of paediatric chronic arthritis, with an incidence of approximately 9.7 per 100 000 children (aged 15 years and under) in Japan [1, 2]. Methotrexate (MTX) is the most common disease-modifying antirheumatic drug used for the treatment of articular-type JIA, namely the polyarticular- and oligoarticular-onset types of JIA [2]. Methotrexate is effective in about 75% of cases of the articular-type JIA, but causes adverse effects, such as liver and/or renal dysfunction [2, 3]. The effects of polymorphisms within the MTX pathway genes on the toxicity and efficacy of MTX in patients with rheumatoid arthritis (RA) and JIA have been studied [4–6].

The influence of polymorphisms within the MTX pathway genes encoding solute carrier family 19 member 1 (SLC19A1), also known as reduced folate carrier (RFC), 5,10-methylenetetrahydrofolate reductase (MTHFR), folypolyglutamate synthetase (FPGS), γ-glutamyl hydrolase (GGH), 5-aminomidazole-4-carboxamide ribonucleotide transformylase (ATIC) and breast cancer resistance protein (BCRP/ABCG2) on the toxicity and efficacy of MTX in patients with RA, JIA and other diseases has been studied [4–9]. However, results regarding the influence of these polymorphisms on the toxicity and efficacy of MTX are conflicting, and there are marked differences in pharmacogenetics between racial groups [10]. Therefore, we investigated whether polymorphisms within the MTX pathway genes were related to the toxicity and efficacy of MTX in 92 patients with articular-type JIA in Japan.

Patients and methods

Study population

Patients were eligible if they met the International League of Association for Rheumatology classification criteria for articular-type JIA [11]. A total of 92 children (74 girls and 18 boys; 12 with seronegative polyarticular onset, 46 with seropositive polyarticular onset and 34 with oligoarticular onset) in this study were treated at the Yokohama City University Hospital between December 2007 and December 2009.

All 92 patients had been treated with MTX for at least 3 months without biologics. Initially, MTX was administered orally at a dosage of 4–5 mg m−2 per week. Then the dosage was adjusted depending on tolerability and response (maximal dosage, 10 mg m−2 week–1) [2]. Prednisolone was used concomitantly with MTX in 89 patients (96.7%). Folic acid supplementation was performed in nine patients (9.9%). Clinical data were collected from a patient's medical record without any knowledge of the individual's polymorphisms.

The study was performed in accordance with the Declaration of Helsinki, and approval for it was obtained from the Yokohama City University School of Medicine Ethics Committee. Each patient or his/her guardians gave written informed consent to participate in this study.

Definitions of toxicity and efficacy

For the evaluation of toxicity, liver dysfunction was defined as an increase in serum alanine transaminase (ALT) level to five times the normal upper limit before the addition of biologics.

Responders to MTX were defined as follows: (i) patients in whom the medication was terminated because they had remission of symptoms; (ii) patients who continued the treatment with stable doses of MTX; and (iii) patients who continued MTX treatment with the concomitant use of acceptable doses of prednisolone, without the addition of biologics, such as anti-tumour necrosis factor therapy [12] and anti-interleukin-6 receptor antibody therapy [13, 14].

Non-responders to MTX were defined as patients who were refractory to MTX and thus treated with biologics. Treatment with biologics was conducted according to the following criteria: (i) patients with a history of treatment with nonsteroidal anti-inflammatory drugs and MTX; and (ii) patients who had the active disease for at least 3 months after MTX treatment (up to 10 mg m−2 week–1). Active disease was characterized by five or more swollen joints and three or more joints with limited range of movement accompanied by pain and/or tenderness, or the use of high doses of corticosteroids (>0.25 mg kg−1 daily), with accompanying unacceptable side-effects [12, 13].

Clinical predictors

Clinical predictors that may influence a patient's disease state and the toxicity and efficacy of MTX were selected on the basis of previous reports [5, 6, 15, 16]. The following factors were included: sex; age at disease onset; duration of MTX treatment; time interval from disease onset to MTX treatment; rheumatoid factor (RF) status; anti-cyclic citrullinated peptide (anti-CCP) status; and concomitant use of prednisolone and folic acid.

Genetic predictors

Genomic DNA was isolated from peripheral blood using the QIAamp DNA Mini kit (Qiagen K.K., Tokyo, Japan).

The following eight single nucleotide polymorphisms (SNPs) within the MTX pathway genes encoding RFC, MTHFR, FPGS, GGH, ATIC and BCRP were selected according to previous reports [4–9]. Genotyping for the SNPs of RFC G80A (rs1051266), MTHFR A1298C (rs1801131), MTHFR C677T (rs1801133), FPGS A1994G (rs10106), GGH C452T (rs11545078), GGH T16C (rs1800909), ATIC C347G (rs2372536) and BCRP C421A (rs2231142) was performed using the TaqMan assay (Applied Biosystems, Foster City, CA, USA). TaqMan SNP Genotyping Assays were used for MTHFR A1298C and MTHFR C677T, and Custom TaqMan SNP Genotyping Assays were used for RFC G80A, FPGS A1994G, GGH C452T, GGH T16C, ATIC C347G and BCRP C421A [9] (see Supplementary data 1). These SNPs were analysed in real-time PCRs by the AB7500 Real Time PCR system (Applied Biosystems), in the conditions recommended by the manufacturer. Allele discrimination was performed using SDS software version 1.4 (Applied Biosystems).

Statistical analysis

For continuous predictors, such as age and duration of MTX treatment, Student's unpaired t-test was used to assess the association between clinical predictors and the toxicity and efficacy. For categorical predictors, such as genetic predictors and sex, a χ2 test and Fisher's exact test were used to assess the association between predictors and the toxicity and efficacy. Possible confounding effects among the predictors were adjusted using a multiple logistic regression model.

Haplotype phases and haplotype frequencies were estimated using the Expectation-Maximization algorithm (minimum haplotype frequency >0.05). All statistical analyses were carried out using the SAS system version 9 (SAS Institute Inc., Cary, NC, USA).

Results

Distribution of the polymorphisms within the MTX pathway genes

The genotype frequencies for the eight SNPs under study were in Hardy–Weinberg equilibrium (P > 0.05). Each result was consistent with the findings of a previous report (see Supplementary data 2) [17].

The toxicity of MTX

Of 92 patients, 10 developed liver dysfunction. Methotrexate treatment of longer duration was a risk factor for liver dysfunction (104.3 months with liver dysfunction, 53.6 months without, P = 0.005). No other clinical variables were associated with liver dysfunction (Table 1). None of the patients with folic acid supplementation had liver dysfunction. However, this correlation of folic acid supplementation preventing liver dysfunction was not statistically significant, presumably because of the small study population.

Table 1. 
Association between clinical predictors and liver dysfunction
 ALT >5.0 times normal (n = 10)ALT ≤5.0 times normal (n = 82)P value
  1. ALT, alanine transaminase.

Age at onset (years, mean)9.57.40.138
Sex (male)20.0%19.5%0.971
Time interval from onset to treatment (months, mean)17.717.90.987
Prednisolone90.0%97.6%0.204
Folic acid0.0%11.0%0.270
Duration of MTX treatment (months, mean)104.352.60.005
MTX efficacy30.0%26.8%0.832

Regarding the association between liver dysfunction and genetic predictors, the TT genotype at GGH T16C was a low risk factor for liver dysfunction [P = 0.031, odds ratio (OR) = 0.20, 95% confidence interval (CI) 0.03–0.98; Table 2 and Supplementary data 3]. In contrast, the non-TT genotype at GGH T16C was a high risk factor for liver dysfunction (P = 0.031, OR = 5.10, 95% CI 1.02–25.6), which is of significant clinical interest. This association was statistically significant even after adjustment for duration of MTX treatment (P = 0.028, OR = 6.90, 95% CI 1.38–34.5). None of the other SNPs was associated with liver dysfunction.

Table 2. 
Association between genetic predictors and liver dysfunction
GenotypeAllele model*Dominant model*Recessive model*
ORP valueORP valueORP value
  1. M, major allele; and m, minor allele. Major alleles are the A allele at RFC G80A, C allele at BRCP C421A, C allele at MTHFR C677T, A allele at MTHFR A1298C, G allele at FPGS A1994G, T allele at GGH T16C, C allele at GGH C452T and C allele at ATIC C347G. *Allele model: M vs. m; dominant model, (MM or Mm) vs. mm; recessive model, MM vs. (Mm or mm). †Non-adjusted odds ratio.

RFC G80A1.510.4140.210.1210.590.627
BCRP C421A1.050.9300.800.8400.990.988
MTHFR C677T1.450.4511.120.8962.280.214
MTHFR A1298C0.890.8521.080.5390.740.655
FPGS A1994G0.540.2494.880.0680.700.600
GGH T16C0.420.1180.830.4750.200.031
GGH C452T0.610.5060.610.502
ATIC C347G1.400.5600.480.8141.170.336

The MTHFR haplotypes and GGH haplotypes showed no significant association with liver dysfunction (data not shown).

The efficacy of MTX

Of 92 patients, 67 were non-responders to MTX. Delayed MTX treatment from disease onset (21.3 months with non-responders vs. 8.5 months with responders, P = 0.029) and RF positivity (P = 0.026, OR = 2.87, 95% CI 1.11–7.39) were risk factors for lower efficacy of MTX (Table 3). No other clinical variables were associated with efficacy.

Table 3. 
Association between clinical predictors and methotrexate efficacy
 Responder (n = 25)Non-responder (n = 67)P value
Age at onset (years, mean)6.67.90.180
Sex (male)12.0%22.4%0.264
Time interval from onset to treatment (months, mean)8.521.30.029
Prednisolone96.0%97.0%0.807
Folic acid4.0%11.9%0.254
C-reactive protein at start of treatment (mg dl−1, mean)2.83.30.685
Anti-cyclic citrullinated peptide [>4.5 (U ml−1)]32.0%55.2%0.062
Rheumatoid factor [>14 (IU ml−1)]40.0%65.7%0.026

Regarding the association between the efficacy of MTX and genetic predictors, there was no gene polymorphism significantly associated with efficacy (Table 4). The MTHFR haplotypes and GGH haplotypes showed no significant association with efficacy (data not shown).

Table 4. 
Association between genetic predictors and methotrexate efficacy
GenotypeAllele model*Dominant model*Recessive model*
ORP valueORP valueORP value
  • *

    Allele model: M vs. m.; dominant model, (MM or Mm) vs. mm; recessive model, MM vs. (Mm or mm).

  • †Non-adjusted odds ratio.

RFC G80A1.010.9791.320.5721.610.435
BCRP C421A1.280.4960.240.1510.990.979
MTHFR C677T0.750.3990.790.7080.420.115
MTHFR A1298C1.050.9180.360.2820.870.775
FPGS A1994G0.950.9001.370.7261.010.984
GGH T16C1.010.9862.830.2941.240.654
GGH C452T1.150.8051.150.805
ATIC C347G0.650.2371.080.9310.500.139

In 64 patients treated with MTX within 1 year of disease onset, the CC genotype at ATIC C347G tended to be associated with lower efficacy. However, this was not statistically significantly after adjustment for the time interval and RF (P = 0.106, OR = 0.38, 95% CI 0.12–1.23) (Table 5).

Table 5. 
Association between ATIC 347CC genotype and methotrexate efficacy in patients with the early phase of juvenile idiopathic arthritis
(a)OR95% Confidence intervalP value
ATIC 347CC genotype0.320.11–0.930.033
(b)OR95% Confidence intervalP value
  • *

    Time interval, time interval from disease onset to methotrexate treatment.

  • †Non-adjusted odds ratio.

  • ‡Adjusted odds ratio.

ATIC 347CC genotype0.380.12–1.230.106
Rheumatoid factor [>14 (IU ml−1)]0.220.07–0.720.012
Time interval*0.850.70–1.040.12

Discussion

Several studies have shown the influence of polymorphisms within the MTX pathway genes on the toxicity and efficacy of MTX in patients with RA [4, 8, 9]. However, results are conflicting, and there are marked differences between racial groups in pharmacogenetic studies [10]. We could find only two studies on the pharmacogenetics of MTX in patients with JIA in Caucasian patients [5, 6], but not one in an Asian population. This is the first reported study on pharmacogenetics of MTX in patients with JIA in an Asian population.

First, we found that the non-TT genotype at GGH T16C was associated with a high risk of liver dysfunction. This should be taken into consideration in treating patients carrying the non-TT genotype at GGH T16C with MTX in order to prevent liver dysfunction.

Once inside the cell, MTX undergoes FPGS-catalysed polyglutamation by the addition of two to seven glutamic acid groups. The polyglutamated form is not readily transported across the cell membrane, and thus, the intracellular half-life of MTX is increased. This polyglutamation process is reversed via GGH-catalysed removal of the glutamic acid groups. Therefore, the amount of intracellular MTX-polyglutamates (MTX-PGs) depends on the net rate of polyglutamation determined by the opposing activities of FPGS and GGH [8].

It was reported that GGH T16C, which results in a Cys6Arg substitution, was associated with the efficacy of MTX in patients with RA. The variant C allele may cause a loss of GGH activity, resulting in decreased efflux of MTX and thus increased intracellular MTX-PG levels [8]. This result was consistent with ours. Although we did not address the MTX-PG levels in hepatic cells, it is possible that the C allele at GGH T16C was associated with reduced GGH activity and thereby increased the MTX-PG levels in hepatic cells. As a result, the risk of liver dysfunction rises. The AA genotype at FPGS A1994G tended to be associated with liver dysfunction (P = 0.068, OR = 4.88, 95% CI 0.78–30.9). Future research using large study populations to address the effects of the combination of GGH and FPGS polymorphisms on MTX toxicity is needed.

The MTX dosage was probably associated with the toxicity and efficacy of the drug. In this cohort study, some patients underwent MTX treatment at other hospitals and had liver dysfunction before being referred to our institution. For these patients, we did not have access to previous medical records concerning the exact dosage of MTX at the time of liver dysfunction. As a general rule, non-responders to MTX received higher dosages of MTX (up to 10 mg m−2) before the introduction of biologics than the responders. We therefore used MTX efficacy as the clinical predictor instead of MTX dosage. The MTX efficacy tended to be associated with liver dysfunction (P = 0.083), although the effect of MTX dosage on the toxicity and efficacy of this drug should be evaluated directly in the future.

Second, we found that the longer time interval from disease onset to MTX treatment and RF positivity were associated with lower efficacy of MTX. This was consistent with previous research results. Time to treatment was reported as an important factor in the response to MTX in patients with JIA [6], and RF positivity was associated with worse disease activity [18, 19].

Paediatric rheumatologists have recently been able to use MTX for patients with earlier phases of JIA, because MTX has become well known as a first-line drug in the treatment of RA and JIA [2, 3]. Therefore, we analysed the subgroup of early JIA patients. In those who were treated with MTX within 1 year of disease onset, the CC genotype at ATIC C347G tended to be associated with the lower efficacy of MTX. Methotrexate-polyglutamates inhibit ATIC, the last enzyme in the de novo purine synthesis pathway. Methotrexate achieves part of its anti-inflammatory effect through inhibition of ATIC, which results in the release of the anti-inflammatory agent, adenosine [9].

It was reported that RA patients with the G allele at ATIC C347G, resulting in a Thr116Ser substitution, were likely to have a good response to MTX [9]. Although the effect of the C347G polymorphism on ATIC enzyme activity is unknown, ATIC C347G may be in linkage disequilibrium with an unknown functional variant, which is associated with the activity of the purine synthesis pathway and with the level of adenosine production. Future basic and clinical prospective studies on a large number of patients are needed to elucidate this association.

There are some limitations to the present study. The incidence of RF positivity in the patient population studied was higher than generally seen (∼10%) [18], presumably because our institution is one of the very few paediatric rheumatology centres in Japan, and many severe cases with RF positive are referred to our institution for highly specialized treatment with biologics [13, 20]. The efficacy rate of MTX in this study (28%) was significantly lower than those in previous Japanese reports [2, 3]. This may be due to the use of a new second-line choice of biologics, as well as the characteristics of our institution and the lower limit of the maximal MTX dosage (10 mg m−2) for the treatment of JIA in Japan [2].

In summary, we found an association between the non-TT genotype at GGH T16C and liver dysfunction due to MTX. We also found an influence of time interval from disease onset to MTX treatment on the efficacy of MTX in Japanese patients with JIA. Our study showed the importance of early use of MTX for patients with JIA as well as the possibility of more personalized therapy for patients with JIA based on pharmacogenetic study of the MTX pathway genes.

Competing Interests

There are no competing interests to declare.

This work was supported by a grant from Grand-in-Aid for Scientific Research from Japan Society for the Promotion of Science (No. 16790583). We are grateful to Mr C. W. P. Reynolds and Teddy Kamata for their careful linguistic assistance with this manuscript.

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