The immune response mediator genes polymorphic variants as predictors of the etanercept efficacy in juvenile idiopathic arthritis

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Liliia Sh. Nazarova, Ksenia V. Danilko, Viktor A. Malievsky, Akhat B. Bakirov, Tatiana V. Viktorova
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e0204
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Abstract: 
Objective ― The aim of the study was to investigate the relationship of the alleles and genotypes of the immune response mediator genes polymorphic loci (rs1800629, rs909253, rs16944, rs6822844, rs2104286, rs1800795, rs1800872, rs3087243, rs755622 rs28362491, rs2240336, rs2476601) with the etanercept efficacy in juvenile idiopathic arthritis (JIA) patients. Material and Methods ― The study included 39 JIA patients from Bashkortostan, Russia. Achieving the American College of Rheumatology Pediatric 70 (ACR Pedi 70) response was regarded as the presence of the response to etanercept (otherwise – as the absence), while achieving clinical remission on medication – as the sufficient response (otherwise – as the insufficient). Genotyping was performed using real-time polymerase chain reaction method. Results ― The predictors of an increased risk of the non-response to etanercept were the IL1B rs16944*TT (pcor=0.023), NFKB1 rs28362491*II (pcor=0.042) genotypes, and of the increased risk of the insufficient response to etanercept – the IL2RA rs2104286*AA (pcor=0.010), NFKB1 rs28362491*II (pcor=0.026) genotypes. The markers of the decreased risk of the non-response to etanercept were the IL1B rs16944*C (pcor=0.046), NFKB1 rs28362491*D (pcor=0.029) alleles, and of the decreased risk of the insufficient response to etanercept – the IL2RA rs2104286*AG genotype (pcor=0.049), IL2RA rs2104286*G allele (pcor=0.005). Conclusion ― In this study the association of the alleles and genotypes of the IL1B rs16944, IL2RA rs2104286, NFKB1 rs28362491 polymorphic loci with the etanercept efficacy in JIA patients was established.
Cite as: 
Nazarova LS, Danilko KV, Malievsky VA, Bakirov AB, Viktorova TV. The immune response mediator genes polymorphic variants as predictors of the etanercept efficacy in juvenile idiopathic arthritis. Russian Open Medical Journal 2018; 7: e0204.

Introduction

Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic disease in children. The disease has no known cause, develops before the 16th birthday and is characterized by persistent joint inflammation (longer than 6 weeks) [1-3].

It was shown, that JIA can lead to severe disability and is accompanied by a significant impairment in the quality of life of patients [1, 4]. The important role in the preventing of JIA progression and patients disability is given to the timely appointment of an adequate therapy [5-8].

The main therapeutic agents for the JIA treatment include nonbiologic and biologic disease-modifying antirheumatic drugs (DMARDs), non-steroidal anti-inflammatory drugs (NSAIDs) and glucocorticosteroids, but their effectiveness is different in patients [7, 8]. Therefore, it is an essential problem to find the predictors of the corresponding drugs efficacy, primarily for the DMARDs.

According to the American College of Rheumatology (ACR) recommendations for the treatment of JIA (2011), three tumor necrosis factor alpha (TNFα) inhibitors (etanercept, adalimumab and infliximab) are recommended for the patients with an active arthritis and an insufficient response to the previous therapy [7].

Etanercept is a fully humanized soluble TNF receptor, which binds to TNFα and attenuates its effects [1]. Many cytokines, including TNFα, lymphotoxin alpha (LTα), macrophage migration inhibitory factor (MIF), interleukins (ILs), and other regulatory molecules (such as cytotoxic T-lymphocyte associated protein 4 (CTLA4), nuclear factor kappa B subunit 1 (NF-κB1), protein tyrosine phosphatase, non-receptor type 22 (PTPN22)), as well as their genes polymorphisms are believed to play an important role in JIA pathogenesis and the disease progression [9-11]. The complex interaction of immune cells and mediators determines the specific clinical manifestations of JIA [12]. Thus, it can be assumed, that the changes in the regulatory molecules production and underlying genetic factors also affect the treatment effectiveness in JIA.

The aim of the study was to investigate the relationship of the alleles and genotypes of the immune response mediator genes polymorphic loci (TNFA rs1800629 (-308G>A), LTA rs909253 (252A>G), IL1B rs16944 (-511C>T), IL2RA rs2104286, IL6 rs1800795 (-174G>C), IL10 rs1800872 (-592C>A), CTLA4 rs3087243, MIF rs755622 (-173G>C), NFKB1 rs28362491 (-94I>D), PADI4 rs2240336, PTPN22 rs2476601 (1858G>A)) and the intergenic region locus (IL2-IL21 rs6822844) with the etanercept efficacy in JIA patients.

 

Material and Methods

Study design

A case-control study was conducted. The study was approved by Local ethical committee of Bashkir State Medical University (Ufa, Russia). The parents of all patients signed the voluntary informed consent.

 

JIA patients’ characteristics

Initially the whole JIA group included 330 children, who underwent examination and treatment in the Republican Children's Clinical Hospital (Ufa, Russia) in 2012-2017 years. The JIA diagnosis was established according to the International League of Associations for Rheumatology (ILAR) criteria [3].

The inclusion criteria to the JIA group were:

  1. the presence of arthritis;
  2. the duration of arthritis more than 6 weeks;
  3. the patient's age less than 18 years;
  4. the onset of the disease at the age less than 16 years;
  5. the absence of other diseases accompanied by arthritis;
  6. the signing of the voluntary informed consent by the patient's parents.

The exclusion criteria were:

  1. the duration of arthritis less than 6 weeks;
  2. the patient's age 18 years and over;
  3. the onset of the disease at the age 16 years and over;
  4. the established diagnosis of other diseases accompanied by inflammation in the joints;
  5. the refusal to participate in the study by the patient or his parents.

The etanercept therapy (in a combination with methotrexate) was prescribed to 48 patients. The efficacy of the therapy was assessed in 39 JIA patients aged 1.9 to 16.7 years. The mean age of 39 examined JIA patients was 8.4±3.7 years, girls/boys ratio ‒ 1.8/1.0.

According to the ILAR criteria, the following JIA subtypes were presented: systemic arthritis (n=3), rheumatoid factor positive polyarthritis (n=3), rheumatoid factor negative polyarthritis (n = 16), persistent oligoarthritis (n = 1), extended oligoarthritis (n =9), enthesitis related arthritis (n =5), psoriatic arthritis (n = 1), undifferentiated arthritis (n=1). The duration of the etanercept treatment was from 8 months to 7 years. Achieving the ACR Pediatric 70 (ACR Pedi 70) response was regarded as the presence of the response to etanercept (otherwise – as the absence), while achieving clinical remission on medication (Wallace et al., 2011) was regarded as the sufficient response to etanercept (otherwise – as the insufficient) [1, 6, 13-15]. The presence of the response to etanercept was observed in 27 patients (69.23%), while the sufficient response – in 21 patients (53.85%).

Experimental methods

Deoxyribonucleic acid (DNA) was isolated from the lymphocytes of the whole blood samples using standard phenol-chloroform method [16].

Twelve polymorphic loci (TNFA rs1800629 (-308G>A), LTA rs909253 (252A>G), IL1B rs16944 (-511C>T), IL2-IL21 rs6822844, IL2RA rs2104286, IL6 rs1800795 (-174G>C), IL10 rs1800872 (-592C>A), CTLA4 rs3087243, MIF rs755622 (-173G>C), NFKB1 rs28362491 (-94I>D), PADI4 rs2240336, PTPN22 rs2476601 (1858G>A)) were examined. The genotyping was performed by real-time polymerase chain reaction (PCR) method using StepOnePlus™ Real-Time PCR System (Applied Biosystems, USA) and commercial kits of sequence-specific primers and allele-specific probes (DNK-syntez, Russia).

 

Statistical analysis

The differences between the frequencies of the polymorphic loci alleles and genotypes in the studied groups were assessed using two-tailed Fisher's exact test in Microsoft Excel software. The odds ratio (OR) with 95% Baptista-Pike confidence interval (CI) were calculated for the identified markers in Microsoft Excel and R v.3.4.2 software [17].

The models of inheritance (co-dominant, dominant, recessive, over-dominant and log-additive) were studied by applying logistic regression in the SNPStats package [18]. The best model was the one with the lowest value of the Akaike information criterion (AIC). For the multiple comparison correction the permutation test with 10,000 permutes was performed in PowerMarker v.3.25 package (pcor) [19, 20].

In all the cases the results considered statistically significant at p<0.05.

 

Results

Genetic predictors of the non-response to etanercept

As a result of the comparative analysis it was shown, that the IL1B rs16944*TT genotype was significantly more common and the IL1B rs16944*C allele ‒ significantly less common in JIA patients with the absence of the response to etanercept, than in those with its presence (*TT: p=0.025, pcor=0.023, OR=13.00, 95% CI 1.57-163.39; *C: p=0.044, pcor=0.046, OR=0.33, 95% CI 0.13-0.89) (Table 1). The best inheritance model was the recessive (TT vs. CC+CT, p=0.014, OR=13.0, 95% CI 1.26-133.64). Due to the small sample size, the stratification by sex was not carried out.

The NFKB1 rs28362491 polymorphism analysis showed that the frequency of the NFKB1 rs28362491*II genotype was significantly higher, and the frequency of the NFKB1 rs28362491*D allele was significantly lower in etanercept non-responders, than in responders (*II: p=0.043, pcor=0.042, OR=5.75, 95% CI 1.28-22.26; *D: p=0.028, pcor=0.029, OR=0.31, 95% CI 0.12-0.85) (Table 1). The log-additive model of inheritance was the best (2DD+ID vs. II, p=0.016, OR=0.27, 95% CI 0.08-0.87).

For the other single nucleotide polymorphisms (SNPs) the differences were not significant (pcor>0.05). There was only a trend towards a lower frequency of the IL2RA rs2104286*G allele in JIA patients who did not respond to etanercept therapy in comparison with the responders (p=0.092, pcor=0.093).

 

Table 1. The distribution of the genotypes and alleles of the studied polymorphic loci in relation to the response to etanercept in JIA patients

Polymorphic loci

Response to etanercept

Absence

Presence

p-level

Insufficient

Sufficient

p-level

Gene, rs

Variants

Abs.

Freq. (%)

Abs.

Freq. (%)

Abs.

Freq. (%)

Abs.

Freq. (%)

TNFA

rs1800629

GG

12

100.00

23

85.19

0.292

16

88.89

19

90.48

1.000

GA

0

0.00

4

14.81

0.292

2

11.11

2

9.52

1.000

AA

0

0.00

0

0.00

1.000

0

0.00

0

0.00

1.000

G

24

100.00

50

92.59

0.306

34

94.44

40

95.24

1.000

A

0

0.00

4

7.41

0.306

2

5.56

2

4.76

1.000

LTA

rs909253

AA

6

50.00

11

40.74

0.730

8

44.44

9

42.86

1.000

AG

5

41.67

14

51.85

0.731

8

44.44

11

52.38

0.751

GG

1

8.33

2

7.41

1.000

2

11.11

1

4.76

0.586

A

17

70.83

36

66.67

0.797

24

66.67

29

69.05

1.000

G

7

29.17

18

33.33

0.797

12

33.33

13

30.95

1.000

IL1B

rs16944

CC

2

16.67

11

40.74

0.269

4

22.22

9

42.86

0.307

CT

6

50.00

15

55.56

1.000

10

55.56

11

52.38

1.000

TT

4

33.33

1

3.70

0.025

4

22.22

1

4.76

0.162

C

10

41.67

37

68.52

0.044

18

50.00

29

69.05

0.107

T

14

58.33

17

31.48

0.044

18

50.00

13

30.95

0.107

IL2-21

rs6822844

GG

11

91.67

19

70.37

0.228

14

77.78

16

76.19

1.000

GT

1

8.33

8

29.63

0.228

4

22.22

5

23.81

1.000

TT

0

0.00

0

0.00

1.000

0

0.00

0

0.00

1.000

G

23

95.83

46

85.19

0.261

32

88.89

37

88.10

1.000

T

1

4.17

8

14.81

0.261

4

11.11

5

11.90

1.000

IL2RA

rs2104286

AA

11

91.67

18

66.67

0.131

17

94.44

12

57.14

0.011

AG

1

8.33

7

25.93

0.394

1

5.56

7

33.33

0.049

GG

0

0.00

2

7.41

1.000

0

0.00

2

9.52

0.490

A

23

95.83

43

79.63

0.092

35

97.22

31

73.81

0.004

G

1

4.17

11

20.37

0.092

1

2.78

11

26.19

0.004

IL6

rs1800795

GG

7

58.33

12

44.44

0.501

10

55.56

9

42.86

0.527

GC

5

41.67

13

48.15

0.742

8

44.44

10

47.62

1.000

CC

0

0.00

2

7.41

1.000

0

0.00

2

9.52

0.490

G

19

79.17

37

68.52

0.420

28

77.78

28

66.67

0.321

C

5

20.83

17

31.48

0.420

8

22.22

14

33.33

0.321

IL10

rs1800872

CC

5

41.67

14

51.85

0.731

8

44.44

11

52.38

0.751

CA

6

50.00

9

33.33

0.478

9

50.00

6

28.57

0.203

AA

1

8.33

4

14.81

1.000

1

5.56

4

19.05

0.349

C

16

66.67

37

68.52

1.000

25

69.44

28

66.67

0.813

A

8

33.33

17

31.48

1.000

11

30.56

14

33.33

0.813

MIF

rs755622

GG

6

50.00

15

55.56

1.000

10

55.56

11

52.38

1.000

GC

5

41.67

11

40.74

1.000

6

33.33

10

47.62

0.516

CC

1

8.33

1

3.70

0.526

2

11.11

0

0.00

0.206

G

17

70.83

41

75.93

0.779

26

72.22

32

76.19

0.796

C

7

29.17

13

24.07

0.779

10

27.78

10

23.81

0.796

CTLA4

rs3087243

GG

5

41.67

11

40.74

1.000

8

44.44

8

38.10

0.752

GA

6

50.00

16

59.26

0.730

9

50.00

13

61.90

0.528

AA

1

8.33

0

0.00

0.308

1

5.56

0

0.00

0.462

G

16

66.67

38

70.37

0.794

25

69.44

29

69.05

1.000

A

8

33.33

16

29.63

0.794

11

30.56

13

30.95

1.000

NFKB1

rs28362491

II

6

50.00

4

14.81

0.043

8

44.44

2

9.52

0.025

ID

5

41.67

15

55.56

0.501

6

33.33

14

66.67

0.056

DD

1

8.33

8

29.63

0.228

4

22.22

5

23.81

1.000

I

17

70.83

23

42.59

0.028

22

61.11

18

42.86

0.119

D

7

29.17

31

57.41

0.028

14

38.89

24

57.14

0.119

PADI4

rs2240336

GG

3

25.00

7

25.93

1.000

4

22.22

6

28.57

0.726

GA

7

58.33

17

62.96

1.000

11

61.11

13

61.90

1.000

AA

2

16.67

3

11.11

0.634

3

16.67

2

9.52

0.647

G

13

54.17

31

57.41

0.809

19

52.78

25

59.52

0.648

A

11

45.83

23

42.59

0.809

17

47.22

17

40.48

0.648

PTPN22

rs2476601

GG

10

83.33

19

70.37

0.693

14

77.78

15

71.43

0.726

GA

2

16.67

7

25.93

0.693

4

22.22

5

23.81

1.000

AA

0

0.00

1

3.70

1.000

0

0.00

1

4.76

1.000

G

22

91.67

45

83.33

0.487

32

88.89

35

83.33

0.533

A

2

8.33

9

16.67

0.487

4

11.11

7

16.67

0.533

Statistically significant results are in bold. Abs., absolute values; Freq., frequencies.

 

Genetic predictors of the insufficient response to etanercept

It was shown, that the IL2RA rs2104286*AA genotype was significantly more common, while the IL2RA rs2104286*AG genotype and the IL2RA rs2104286*G allele were significantly less common in JIA patients with the insufficient response to etanercept, than in those with the sufficient response (*AA: p=0.011, pcor=0.010, OR=12.75, 95% CI 1.84-146.67; *AG: p=0.049, pcor=0.049, OR=0.12, 95% CI 0.01-0.88; *G: p=0.004, pcor=0.005, OR=0.08, 95% CI 0.01-0.53) (Table 1). The log-additive model described the results better than the others (2GG+AG vs. AA, p=0.0037, OR=0.09, 95% CI 0.01-0.81).

Analysis of the NFKB1 rs28362491 polymorphism revealed a significant increase of the NFKB1 rs28362491*II genotype proportion, and a trend towards a decrease of the NFKB1 rs28362491*ID genotype proportion in JIA patients who did not achieve clinical remission on medication (on etanercept), compared with those who achieved (*II: p=0.025, pcor=0.026, OR=7.60, 95% CI 1.53-38.68 and *ID: p=0.056, pcor=0.054) (Table 1). The best inheritance model was the dominant (ID+DD vs. II, p=0.011, OR=0.13, 95% CI 0.02-0.74).

At the same time, for the other SNPs no significant differences were observed (pcor>0,05). Only testing the inheritance models revealed a trend towards the presence of an effect, that increases the risk of the insufficient response to etanercept, in the IL1B rs16944*T allele (log-additive model, 2TT+CT vs. CC, p=0.063) and the MIF rs755622*CC genotype (recessive model, CC vs. GG+GC, p=0.073).

 

Discussion

The analysis of the association between the polymorphic variants of the immune response mediator genes and the efficacy of the etanercept therapy in JIA patients was performed in this study. The predictors of the increased risk of the non-response to etanercept were the IL1B rs16944*TT (pcor=0.023), NFKB1 rs28362491*II (pcor=0.042) genotypes, and of the increased risk of the insufficient response to etanercept – the IL2RA rs2104286*AA (pcor=0.010), NFKB1 rs28362491*II (pcor=0.026) genotypes. The markers of the decreased risk of the non-response to etanercept were the IL1B rs16944*C (pcor=0.046), NFKB1 rs28362491*D (pcor=0.029) alleles, and of the decreased risk of the insufficient response to etanercept – the IL2RA rs2104286*AG genotype (pcor=0.049), IL2RA rs2104286*G allele (pcor=0.005).

According to the literature, the association of only the TNFA rs1800629 locus polymorphic variants was previously investigated with the etanercept efficacy in JIA. Schmeling H. and Horneff G. (2007) showed that the TNFA rs1800629*GG genotype serves as a protective marker in relation to non-achieving the ACR Pedi 30 response to etanercept in patients with rheumatoid factor negative polyarticular JIA, but not in the entire JIA group [21]. According to Basic J. et al. (2010), the ACR Pedi 50 response in a year after the etanercept initiation was observed significantly more frequent in polyarticular JIA course patients with the TNFA rs1800629*GG genotype, than in those with the TNFA rs1800629*AA genotype, but not with the TNFA rs1800629*A allele generally [22]. Cimaz R. et al. (2007) did not find the relationship of the TNFA rs1800629 locus polymorphic variants with achieving the ACR Pedi 30 response to TNFα inhibitors as a whole (infliximab, etanercept, adalimumab) in JIA patients [23]. These data are consistent with the results of the present work, where no association of the TNFA rs1800629 locus polymorphic variants with the response to the etanercept therapy in the entire JIA group was found. Nevertheless, Hong Y. and Wang R. (2016) showed, that the frequency of the TNFA rs1800629*GG genotype was significantly increased in Chinese JIA patients achieved the ACR Pedi 50 response with the etanercept therapy [24].

It should be noted, that according to Sode J. et al. (2014), the NFKB1 rs28362491*D allele serves as a protective marker in relation to the non-response (European League Against Rheumatism (EULAR) criteria) to etanercept in seropositive rheumatoid arthritis patients from Denmark [25]. In addition, Gębura K. et al. (2017) showed, that the presence of the homozygous genotype NFKB1 rs28362491*II was associated with the increased risk of the non-response (EULAR criteria) to TNFα inhibitors (as a whole), whereas the presence of the NFKB1 rs28362491*D allele, and in particular the NFKB1 rs28362491*ID genotype, ‒ with a higher efficacy of this treatment in rheumatoid arthritis patients from Poland [26]. The results of the current work also indicate, that the NFKB1 rs28362491*D allele reduces the risk of non-achieving the ACR Pedi 70 response to etanercept in JIA patients.

 

Conclusion

In this study the association of the alleles and genotypes of the IL1B rs16944, IL2RA rs2104286, NFKB1 rs28362491 polymorphic loci with the etanercept efficacy in JIA patients was established.

 

Acknowledgments

The work was supported by:

  1. Government project: “Study of molecular genetic mechanisms of formation of multifactorial pathology”, No. 115060810015 (08 June 2015).
  2. Grant of the Republic of Bashkortostan to young scientists and youth scientific teams, contract No. 6 (25 March 2016).
  3. The program "Participant of the Youth Scientific and Innovation Contest" ("UMNIK"), contracts No. 10/16859 (28 May 2012) and No. 10/20810 (01 July 2013).

 

Conflict of interest: none declared.

 

Ethical approval: All procedures performed in studies involving human participants were in accordance with the standards of the Local ethical committee of Bashkir State Medical University (Ufa, Russia) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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About the Authors: 

Liliia Sh. Nazarova ‒ MD, Assistant, Department of Therapy and Clinical Pharmacology, Institute of Postgraduate Education, Bashkir State Medical University, Ufa, Russia. http://orcid.org/0000-0002-9666-5650.
Ksenia V. Danilko ‒ PhD, Associate Professor of the Department of Biology, Senior Researcher of the Central Research Laboratory, Bashkir State Medical University, Ufa, Russia. http://orcid.org/0000-0002-4374-2923.
Viktor A. Malievsky ‒ MD, DSc, Professor, Head of the Department of Hospital Pediatrics, Bashkir State Medical University, Ufa, Russia. http://orcid.org/0000-0003-0522-7442.
Akhat B. Bakirov ‒ MD, DSc, Professor, Academician of Academy of Sciences of the Republic of Bashkortostan, Head of the Department of Therapy and Clinical Pharmacology, Institute of Postgraduate Education, Bashkir State Medical University; Director, Ufa Research Institute of Occupational Health and Human Ecology, Ufa, Russia. http://orcid.org/0000-0003-3510-2595.
Tatiana V. Viktorova ‒ MD, DSc, Professor, Head of the Department of Biology, Bashkir State Medical University; Chief Researcher, Laboratory of Physiological Genetics, Institute of Biochemistry and Genetics, Ufa, Russia. http://orcid.org/0000-0001-8900-2480

Received 2 December 2017, Revised 4 March 2018, Accepted 6 March 2018

© 2017, Nazarova L.S., Danilko K.V., Malievsky V.A., Bakirov A.B., Viktorova T.V.
© 2017, Russian Open Medical Journal

Correspondence to Liliia Sh. Nazarova. Address: 47, Zaki Validi Str., Ufa, 450077, Russia. Phone: +7 (347) 273-58-75. E‐mail: lilinaz19@mail.ru.

DOI: 
10.15275/rusomj.2018.0204