ACR Meeting Abstracts

ACR Meeting Abstracts

Abstract Number: 2347

Functional Single Nucleotide Polymorphisms In The Interferon-γ and The NLRP3 (Cryopyrin) Genes Associated With Anti-TNF Response In Danish Rheumatoid Arthritis Patients

Jacob Sode1,2,3, Niels H. H. Heegaard4, Henning Locht2, Ulla Vogel5, Steffen Bank6,7, Merete Lund Hetland8,9 and Vibeke Andersen3,7,10,11, 1Clinical Biochemistry, Immunology and Genetics, Statens Serum Institut, Copenhagen S, Denmark, 2Department of Rheumatology, Frederiksberg Hospital, Frederiksberg, Denmark, 3Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark, 4Department of Clinical Biochemistry, Immunology & Genetics, Statens Serum Institut, Copenhagen, Denmark, 5National Research Centre for the Working Environment, Copenhagen, Denmark, 6Institute of Human Genetics, University of Aarhus, Aarhus, Denmark, 7Medical Department, Viborg Regional Hospital, Viborg, Denmark, 8The Danish Rheumatologic Database (DANBIO), Glostrup Hospital, Glostrup, Denmark, 9Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, The Danish Rheumatologic Database (DANBIO), Glostrup Hospital., Copenhagen, Denmark, 10Medical Department, Hospital of Southern Jutland Aabenraa, Aabenraa, Denmark, 11Odense University Hospital, OPEN (Odense Patient data Explorative Network), Odense, Denmark

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: , , ,

Session Information

Title: Rheumatoid Arthritis Treatment - Small Molecules, Biologics and Gene Therapy III

Session Type: Abstract Submissions (ACR)

Background/Purpose:

Most patients with rheumatoid arthritis (RA) benefit from tumor necrosis factor-a blocking treatment (anti-TNF). About 1/3, however, do not respond to this costly and potentially harmful treatment. The objective of this study was to determine whether polymorphisms of inflammatory pathway genes may predict the variation in response to anti-TNF treatment in RA patients.

Methods:

Forty-one single nucleotide polymorphisms (SNPs), including 34 functional, in 28 genes involved in inflammatory pathways were assessed in 538 anti-TNF naive Danish RA patients. Prospectively collected clinical data including functional status (HAQ), patient global score, lifestyle factors (smoking), tender and swollen joint counts, treatments, rheumatoid factor status and CRP were obtained from the DANBIO registry. Multivariable logistic regression analyses were performed to test associations between genotypes and EULAR response at 3–6 months. ACR50 response and relative change in DAS28 were secondary outcomes. Subgroup analyses were stratified by smoking status, type of anti-TNF drug, and rheumatoid factor status.

Results:

Statistically significant associations with EULAR response were found for two SNPs in the total cohort (NLRP3 (rs4612666) and INFG (rs2430561), for seropositive RA patients (407) in TNFRS1A (rs4149570), and for seronegative RA patients (131) in IL17A (rs2275913), TLR2 (rs1816702), NFKB1 (rs28362491), LY96 (rs11465996), TGFB1 (rs1800469) and IL10 (rs1800872) (Table 1). Significant associations with ACR50-response were present for six SNPs (TLR4 (rs5030728), IL1B (rs1143623), TLR4 (rs12377632), IL17A (rs2275913), NFKB1 (rs28362491), TLR2 (rs1816702)). Baseline HAQ-score (OR=0.72 (0.53-0.96), p=0.025) and CRP>10 mg/L (OR=1.91 (1.27-2.86), p=0.002) were significant clinical predictors of EULAR good/moderate response, whereas smoking status, type of anti-TNF drug and rheumatoid factor status were not.

Conclusion:

Danish RA patients with genetically determined higher NLRP3– and IFNG (IFN-γ) expression were more likely to respond to anti-TNF treatment.  Further, the data suggest a difference in pathophysiology between seropositive and seronegative RA patients and validate HAQ-score and CRP as clinical predictors of anti-TNF responses. These findings should be replicated in independent cohorts and augmented by assessing cytokine levels and activity of the relevant gene products.

Table 1

Genotypes in Danish patients with Rheumatoid Arthritis.

Odds ratio (OR) for associations between gene variants and EULAR response to anti-TNF treatment.

GOOD/MODERATE

GOOD

GENE

(SNP)

GENOTYPE

NO.

NONE

MODERATE

GOOD

ADJ. OR

95% CI

P-VALUE

ADJ. OR

95% CI

P-VALUE

IFNG

TT

137

34

37

66

Ref.

Ref.

rs2430561

TA

263

74

71

118

0.81

(0.50-1.31)

0.395

0.75

(0.45-1.27)

0.285

AA

114

40

38

36

0.59

(0.34-1.02)

0.059

0.40

(0.21-0.76)

0.005**

TA/AA

377

114

109

154

0.73

(0.47-1.15)

0.177

0.63

(0.38-1.03)

0.067

TT/TA

400

108

108

184

Ref.

Ref.

AA

114

40

38

36

0.67

(0.43-1.06)

0.084

0.48

(0.29-0.82)

0.007**

NLRP3

CC

275

69

84

122

Ref.

Ref.

rs4612666

CT

210

73

54

83

0.62

(0.42-0.92)

0.018*

0.62

(0.40-0.97)

0.037*

TT

31

9

8

14

0.85

(0.37-1.96)

0.707

0.89

(0.36-2.24)

0.808

CT/TT

241

82

62

97

0.64

0.44-0.95)

0.025*

0.65

(0.43-1.00)

0.050*

SEROPOSITIVE RA

IFNG

TT

106

26

30

50

Ref.

Ref.

rs2430561

TA

205

56

55

94

0.85

(0.49-1.46)

0.547

0.83

(0.43-1.51)

0.544

AA

78

30

21

27

0.51

(0.26-0.96)

0.038*

0.42

(0.20-0.87)

0.020*

TA/AA

283

86

76

121

0.73

(0.43-1.22)

0.229

0.69

(0.39-1.21)

0.196

TT/TA

311

Ref.

Ref.

AA

78

30

21

27

0.57

(0.33-0.96)

0.034*

0.48

(0.26-0.87)

0.016*

NLRP3

CC

212

51

62

99

Ref.

Ref.

rs4612666

CT

156

55

39

62

0.58

(0.37-0.92)

0.020*

0.58

(0.35-0.96)

0.035*

TT

25

9

5

11

0.59

(0.24-1.43)

0.241

0.64

(0.24-1.71)

0.375

CT/TT

181

64

44

73

0.58

(0.37-0.90)

0.016*

0.59

(0.36-0.96)

0.032*

TNFRSF1A

GG

137

33

40

64

Ref.

Ref.

rs4149570

GT

196

68

47

81

0.59

(0.36-0.98)

0.040*

0.63

(0.37-1.09)

0.102

TT

56

15

18

23

0.89

(0.43-1.85)

0.76

0.82

(0.37-1.82)

0.619

GT/TT

252

83

65

104

0.65

(0.40-1.04)

0.074

0.67

(0.39-1.13)

0.13

SERONEGATIVE RA

IL10

CC

76

28

19

29

Ref.

Ref.

rs1800872

CA

45

7

19

19

2.99

(1.14-7.85)

0.026*

2.47

(0.85-7.16)

0.097

AA

5

2

2

1

0.67

(0.09-4.77)

0.692

0.33

(0.03-4.16)

0.39

CA/AA

50

9

21

20

2.48

(1.01-6.07)

0.047*

1.93

(0.72-5.22)

0.192

IL17A

GG

58

11

20

27

Ref.

Ref.

rs2275913

GA

56

23

16

17

0.37

(0.16-0.90)

0.028*

0.29

(0.11-0.78)

0.014*

AA

11

3

3

5

0.56

(0.12-2.74)

0.478

0.59

(0.11-3.29)

0.551

GA/AA

67

26

19

22

0.4

(0.17-0.93)

0.033*

0.32

(0.12-0.84)

0.020*

NFKB1

WW

56

12

18

26

Ref.

Ref.

rs28362491

WM

46

18

13

15

0.34

(0.14-0.88)

0.026*

0.31

(0.10-0.89)

0.030*

MM

22

5

9

8

0.87

(0.25-2.97)

0.819

0.69

(0.17-2.76)

0.6

WM/MM

68

23

22

23

0.46

(0.19-1.09)

0.076

0.39

(0.15-1.04)

0.059

TGFB1

CC

57

21

18

18

Ref.

Ref.

rs1800469

CT

57

10

19

28

2.74

(1.11-6.76)

0.029*

2.87

(1.04-7.88)

0.041*

TT

11

5

3

3

0.65

(0.16-2.59)

0.544

0.68

(0.13-3.55)

0.65

CT/TT

68

15

22

31

2.05

(0.90-4.64)

0.087

2.17

(0.85-5.56)

0.107

TLR2

CC

100

23

32

45

Ref.

Ref.

rs1816702

CT

25

13

8

4

0.25

(0.09-0.68)

0.006**

0.13

(0.03-0.50)

0.003**

TT

0

0

0

0

–

–

–

CT/TT

25

13

8

4

0.25

(0.09-0.68)

0.006**

0.13

(0.03-0.50)

0.003**

Logistic regression, adjusted for gender, age, HAQ-, DMARD at baseline, CRP, presence of RF/ACPA under assumption of a dominant model.

Disclosure:

J. Sode,
None;

N. H. H. Heegaard,
None;

H. Locht,
None;

U. Vogel,
None;

S. Bank,
None;

M. L. Hetland,
None;

V. Andersen,
None.

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