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  • Research article
  • Open Access
  • Open Peer Review

Genetically determined high activities of the TNF-alpha, IL23/IL17, and NFkB pathways were associated with increased risk of ankylosing spondylitis

  • 1, 2, 3, 4,
  • 5, 6Email authorView ORCID ID profile,
  • 7,
  • 8, 9,
  • 1, 5, 10,
  • 5,
  • 11,
  • 12,
  • 13,
  • 14, 15,
  • 16, 17,
  • 17, 18,
  • 3,
  • ^2, 19 and
  • 1, 5, 10, 20
^Deceased
BMC Medical Genetics201819:165

https://doi.org/10.1186/s12881-018-0680-z

  • Received: 17 May 2018
  • Accepted: 3 September 2018
  • Published:
Open Peer Review reports

Abstract

Background

Ankylosing spondylitis (AS) results from the combined effects of susceptibility genes and environmental factors. Polymorphisms in genes regulating inflammation may explain part of the heritability of AS.

Methods

Using a candidate gene approach in this case-control study, 51 mainly functional single nucleotide polymorphisms (SNPs) in genes regulating inflammation were assessed in 709 patients with AS and 795 controls. Data on the patients with AS were obtained from the DANBIO registry where patients from all of Denmark are monitored in routine care during treatment with conventional and biologic disease modifying anti-rheumatic drugs (bDMARDs).

The results were analyzed using logistic regression (adjusted for age and sex).

Results

Nine polymorphisms were associated with risk of AS (p < 0.05). The polymorphisms were in genes regulating a: the TNF-α pathway (TNF -308 G > A (rs1800629), and − 238 G > A (rs361525); TNFRSF1A -609 G > T (rs4149570), and PTPN22 1858 G > A (rs2476601)), b: the IL23/IL17 pathway (IL23R G > A (rs11209026), and IL18–137 G > C (rs187238)), or c: the NFkB pathway (TLR1 743 T > C (rs4833095), TLR4 T > C (rs1554973), and LY96–1625 C > G (rs11465996)).

After Bonferroni correction the homozygous variant genotype of TLR1 743 T > C (rs4833095) (odds ratios (OR): 2.59, 95% confidence interval (CI): 1.48–4.51, p = 0.04), and TNFRSF1A -609 G > T (rs4149570) (OR: 1.79, 95% CI: 1.31–2.41, p = 0.01) were associated with increased risk of AS and the combined homozygous and heterozygous variant genotypes of TNF -308 G > A (rs1800629) (OR: 0.56, 95% CI: 0.44–0.72, p = 0.0002) were associated with reduced risk of AS.

Conclusion

We replicated associations between AS and the polymorphisms in TNF (rs1800629), TNFRSF1A (rs4149570), and IL23R (rs11209026). Furthermore, we identified novel risk loci in TNF (rs361525), IL18 (rs187238), TLR1 (rs4833095), TLR4 (rs1554973), and LY96 (rs11465996) that need validation in independent cohorts. The results suggest that genetically determined high activity of the TNF-α, IL23/IL17, and NFkB pathways increase risk of AS.

Keywords

  • Ankylosing spondylitis
  • Single nucleotide polymorphism
  • SNP
  • Case-control study

Background

Ankylosing spondylitis (AS) is a type of spondyloarthritis in which hallmark clinical features are inflammation at entheses and subchondral bone of the pelvic and spinal joints with subsequent abnormal new bone formation at these sites. Ultimately, this leads to ossification of entheses and joints resulting in loss of joint mobility. The incidence varies between 0.1 and 1.8% with the highest incidence in Scandinavia. Onset is typically in young adults with a male predominance. Medications used include non-steroid anti-inflammatory drugs (NSAIDs), and biological disease-modifying anti-rheumatic drugs (bDMARDs), i.e. tumor necrosis factor-α inhibitors (anti-TNF) and more recently also an interleukin(IL)-17A inhibitor (secukinumab) [1].

The cause of AS is unknown but is believed to involve a combination of genetic and environmental factors [2]. The heritability is polygenic and estimated to exceed 90%, with the HLA-B27 allele as the major contributor accounting for approximately 25% of the heritability of AS [2]. The IL-17/ IL-23 pathway and the TNF-α pathway are central in the pathogenesis of AS and alterations in these pathways have been shown in mouse models to affect development and severity of enthesitis [3, 4].

TNF-α can be activated by Pathogen-Associated Molecular Patterns (PAMPs) such as bacterial or viral DNA, flagellin, or lipopolysaccharide (LPS), through the NFkB pathway. PAMPs can be recognized by Toll-like receptors (TLRs) thereby initiating a kinase cascade which phosphorylates and degrades the NFkB inhibitor IkBα [5]. This releases NFkB which is transported from the cytosol to the nucleus where it initiates expression of pro- and anti-inflammatory cytokines including TNF-α and IL-17 (http://www.bu.edu/nf-kb/gene-resources/target-genes/). The TNF-α and NFkB pathway are intertwined and TNF-α can feedback stimulate NFkB by binding to TNF receptors (TNFR1 or TNFR2), resulting in a kinase cascade similar to, but distinct from, the pathway induced by TLRs [5].

The IL23/IL17 pathway can also stimulate TNF-α activity. The pro-inflammatory cytokine IL-17 enhances the production of other pro-inflammatory cytokines including TNF-α, and the secretion IL-17 itself can be enhanced by IL-23 [6].

PAMPs can also be recognized by intracellular Nod-like receptors (NLRs). In turn, NLRs can activate pro-inflammatory cytokines including IL-18 [7]. IL-18 is invloved in the IL23/IL17 pathway and can enhance the production of IL-17 [8].

The aim of this study was to assess whether functional single nucleotide polymorphisms.

(SNPs) in genes involved in the TNF-α, IL23/IL17, NFkB, and other pro- and anti-inflammatory pathways were associated with risk of AS.

Methods

Patients and samples

The DANBIO registry includes prospectively collected clinical data on patients with inflammatory joint diseases including smoking status, disease characteristics e.g. HLA-B27 status, disease activity, treatment, and treatment outcomes. Patients from all of Denmark are monitored in routine care during treatment with conventional and biologic disease modifying anti-rheumatic drugs (bDMARDs) [9].

Screening for tuberculosis before initiation of treatment with biological drugs is routinely performed in Denmark. Left over blood clots (after whole blood analysis for Mycobacterium tuberculosis) were collected from all patients screened for tuberculosis at Statens Serum Institut (Copenhagen, Denmark) from 01.09.2009 to 31.01.2013; the Department of Respiratory Diseases B and the Department of Clinical Microbiology, Aarhus University Hospital (Aarhus, Denmark) from 01.01.2011 to 31.01.2014; the Department of Clinical Biochemistry, Herlev and Gentofte Hospital (Hellerup, Denmark) from 01.03.2012 to 31.01.2014; the Department of Biochemistry, Hospital of Lillebaelt (Vejle, Denmark); and the Department of Biochemistry, Hospital of Slagelse (Slagelse, Denmark) from 01.01.2014 to 31.01.2014. Furthermore, from 01.01.2013 to 31.12.2013 blood samples were collected from all patients with AS treated with or without anti-TNF drugs at the Department of Rheumatology, Frederiksberg Hospital (Frederiksberg, Denmark).

By linking the unique personal identification number of Danish citizens (CPR-number) from each blood sample with the clinical data from DANBIO, 709 patients with AS (ICD-10: M45.9) were identified. The control group consisted of 795 healthy blood donors recruited from Viborg, Denmark.

Genotyping

Fifty-one SNPs in genes involved in the TNF-α, IL23/IL17, NFκB, and other pro- and anti-inflammatory pathways were assessed. A list of all SNPs studied and genotype distribution is presented in Table 1 and SNPs associated with AS are summarized in Table 2.
Table 1

Odds ratios (OR) and 95% confidence interval (95CI) for genotypes studied among healthy controls and patients with ankylosing spondylitis (AS)

Gene

rs-number

Healthy controls

AS

Unadjusted

Adjusted, age & sex

Adjusted, age, sex & smoking

OR (95 CI)

p

OR (9 5CI)

p

OR (95 CI)

p

TLR1

rs4833095

 TT

485

415

      

 TC

261

238

1.07 (0.86–1.33)

0.57

1.03 (0.82–1.29)

0.83

1.05 (0.78–1.42)

0.73

 CC

20

43

2.51 (1.45–4.34)

0.00095

2.59 (1.48–4.51)

0.00081

2.86 (1.44–5.68)

0.0026

 TC or CC

281

281

1.17 (0.95–1.44)

0.15

1.14 (0.91–1.41)

0.25

1.18 (0.89–1.58)

0.26

TLR2

rs3804099

 TT

241

197

      

 TC

393

354

1.10 (0.87–1.40)

0.42

1.07 (0.84–1.37)

0.58

1.02 (0.73–1.42)

0.90

 CC

144

142

1.21 (0.89–1.63)

0.22

1.24 (0.91–1.68)

0.17

1.30 (0.87–1.96)

0.20

 TC or CC

537

496

1.13 (0.90–1.41)

0.29

1.11 (0.89–1.40)

0.36

1.10 (0.80–1.50)

0.57

TLR2

rs11938228

 CC

327

314

      

 CA

368

313

0.89 (0.71–1.10)

0.27

0.86 (0.69–1.07)

0.17

0.80 (0.60–1.08)

0.15

 AA

76

69

0.95 (0.66–1.36)

0.76

0.92 (0.63–1.33)

0.66

1.03 (0.62–1.69)

0.92

 CA or AA

444

382

0.90 (0.73–1.10)

0.30

0.87 (0.70–1.07)

0.19

0.84 (0.63–1.11)

0.22

TLR2

rs4696480

 AA

199

179

      

 AT

417

348

0.93 (0.72–1.19)

0.55

0.89 (0.69–1.15)

0.38

0.84 (0.60–1.18)

0.31

 TT

155

169

1.21 (0.90–1.63)

0.20

1.16 (0.86–1.58)

0.33

1.18 (0.78–1.78)

0.44

 AT or TT

572

517

1.00 (0.79–1.27)

0.97

0.97 (0.76–1.23)

0.78

0.92 (0.67–1.27)

0.62

TLR4

rs5030728

 GG

359

322

      

 GA

323

298

1.03 (0.83–1.28)

0.80

1.01 (0.81–1.27)

0.91

0.93 (0.69–1.25)

0.62

 AA

78

70

1.00 (0.70–1.43)

1.00

0.98 (0.68–1.42)

0.93

0.87 (0.53–1.42)

0.57

 GA or AA

401

368

1.02 (0.83–1.26)

0.83

1.01 (0.82–1.25)

0.94

0.91 (0.69–1.21)

0.53

TLR4

rs1554973

 TT

440

395

      

 TC

272

261

1.07 (0.86–1.33)

0.55

1.06 (0.85–1.32)

0.62

0.98 (0.73–1.32)

0.90

 CC

62

33

0.59 (0.38–0.92)

0.02

0.55 (0.34–0.86)

0.01

0.68 (0.38–1.23)

0.20

 TC or CC

334

294

0.98 (0.80–1.21)

0.85

0.96 (0.78–1.19)

0.72

0.93 (0.70–1.24)

0.63

TLR4

rs12377632

 TT

306

271

      

 TC

358

319

1.01 (0.81–1.26)

0.96

1.05 (0.84–1.32)

0.66

1.07 (0.78–1.46)

0.67

 CC

102

96

1.06 (0.77–1.47)

0.71

1.11 (0.80–1.55)

0.52

1.41 (0.92–2.17)

0.12

 TC or CC

460

415

1.02 (0.83–1.26)

0.86

1.06 (0.86–1.32)

0.58

1.14 (0.85–1.53)

0.37

TLR5

rs5744168

 CC

672

605

      

 CT

94

89

1.05 (0.77–1.43)

0.75

1.05 (0.77–1.45)

0.74

0.89 (0.58–1.37)

0.60

 TT

5

2

0.44 (0.09–2.30)

0.33

0.45 (0.08–2.43)

0.35

0.04 (0.00–3.54)

0.16

 CT or TT

99

91

1.02 (0.75–1.39)

0.89

1.02 (0.75–1.40)

0.88

0.84 (0.55–1.29)

0.43

TLR5

rs5744174

 TT

215

216

      

 TC

399

337

0.84 (0.66–1.07)

0.15

0.85 (0.67–1.09)

0.20

0.82 (0.60–1.14)

0.24

 CC

144

138

0.95 (0.71–1.29)

0.76

1.02 (0.75–1.39)

0.91

0.87 (0.57–1.32)

0.51

 TC or CC

543

475

0.87 (0.69–1.09)

0.23

0.90 (0.71–1.13)

0.36

0.84 (0.62–1.14)

0.26

TLR9

rs187084

 TT

262

237

      

 TC

366

335

1.01 (0.80–1.27)

0.92

1.03 (0.82–1.31)

0.78

1.09 (0.79–1.50)

0.60

 CC

142

120

0.93 (0.69–1.26)

0.66

0.91 (0.67–1.24)

0.56

1.07 (0.71–1.61)

0.76

 TC or CC

508

455

0.99 (0.80–1.23)

0.93

1.00 (0.80–1.25)

0.98

1.08 (0.80–1.46)

0.60

TLR9

rs352139

 GG

255

211

      

 GA

347

324

1.13 (0.89–1.43)

0.32

1.08 (0.85–1.38)

0.52

1.01 (0.73–1.40)

0.93

 AA

167

139

1.01 (0.75–1.34)

0.97

0.96 (0.71–1.30)

0.79

0.80 (0.53–1.20)

0.27

 GA or AA

514

463

1.09 (0.87–1.36)

0.45

1.04 (0.83–1.31)

0.72

0.94 (0.69–1.27)

0.68

LY96

rs11465996

 CC

344

341

      

 CG

337

298

0.89 (0.72–1.11)

0.30

0.91 (0.73–1.14)

0.42

0.89 (0.66–1.20)

0.45

 GG

81

53

0.66 (0.45–0.96)

0.03

0.68 (0.46–1.00)

0.0498

0.65 (0.39–1.10)

0.11

 CG or GG

418

351

0.85 (0.69–1.04)

0.11

0.87 (0.70–1.07)

0.18

0.84 (0.63–1.12)

0.24

CD14

Rs2569190

 GG

236

194

      

 GA

360

339

1.15 (0.90–1.46)

0.27

1.18 (0.92–1.51)

0.19

1.27 (0.91–1.78)

0.16

 AA

170

157

1.12 (0.84–1.50)

0.43

1.20 (0.89–1.61)

0.24

1.46 (0.98–2.19)

0.06

 GA or AA

530

496

1.14 (0.91–1.43)

0.26

1.18 (0.94–1.50)

0.15

1.32 (0.96–1.82)

0.08

TIRAP

rs8177374

 CC

556

521

      

 CT

185

159

0.92 (0.72–1.17)

0.49

0.99 (0.77–1.27)

0.94

1.38 (0.99–1.91)

0.06

 TT

21

15

0.76 (0.39–1.49)

0.43

0.76 (0.38–1.53)

0.45

1.31 (0.55–3.12)

0.55

 CT or TT

206

174

0.90 (0.71–1.14)

0.39

0.97 (0.76–1.23)

0.81

1.38 (1.00–1.89)

0.047

SUMO4

rs237025

 TT

215

195

      

 TC

362

358

1.09 (0.86–1.39)

0.48

1.08 (0.84–1.38)

0.55

1.04 (0.75–1.44)

0.80

 CC

195

136

0.77 (0.57–1.03)

0.08

0.75 (0.55–1.01)

0.06

0.55 (0.36–0.84)

0.01

 TC or CC

557

494

0.98 (0.78–1.23)

0.85

0.96 (0.76–1.22)

0.75

0.87 (0.64–1.19)

0.38

NFKBIA

rs696

 GG

298

259

      

 GA

366

336

1.06 (0.85–1.32)

0.63

1.06 (0.84–1.33)

0.64

1.02 (0.75–1.39)

0.88

 AA

101

90

1.03 (0.74–1.43)

0.88

0.97 (0.69–1.36)

0.86

1.07 (0.67–1.69)

0.78

 GA or AA

467

426

1.05 (0.85–1.30)

0.65

1.04 (0.84–1.29)

0.73

1.03 (0.77–1.38)

0.84

NFKB1

rs28362491

 Ins/Ins

269

258

      

 Ins/−

376

316

0.88 (0.70–1.10)

0.25

0.89 (0.70–1.12)

0.31

0.74 (0.54–1.01)

0.06

 −/−

122

100

0.85 (0.62–1.17)

0.33

0.82 (0.59–1.13)

0.22

0.78 (0.51–1.19)

0.25

 Ins/− or −/−

498

416

0.87 (0.70–1.08)

0.21

0.87 (0.70–1.08)

0.21

0.75 (0.56–1.01)

0.06

TNF

rs1800629

 GG

527

549

      

 GA

223

129

0.56 (0.43–0.71)

0.0000032

0.58 (0.45–0.75)

0.000029

0.63 (0.45–0.89)

0.01

 AA

25

9

0.35 (0.16–0.75)

0.01

0.39 (0.18–0.85)

0.02

0.19 (0.04–0.79)

0.02

 GA or AA

248

138

0.53 (0.42–0.68)

0.00000030

0.56 (0.44–0.72)

0.0000047

0.59 (0.42–0.82)

0.0018

TNF

rs361525

 GG

708

669

      

 GA

60

30

0.53 (0.34–0.83)

0.01

0.52 (0.32–0.82)

0.0049

0.61 (0.33–1.12)

0.11

 AA

3

0

1.00 (1.00–1.00)

1.00

1.00 (1.00–1.00)

1.00

1.00 (1.00–1.00)

1.00

 GA or AA

63

30

0.50 (0.32–0.79)

0.0027

0.49 (0.31–0.78)

0.0024

0.58 (0.32–1.05)

0.07

TNFRSF1A

rs4149570

 GG

307

217

      

 GT

355

339

1.35 (1.07–1.70)

0.01

1.33 (1.05–1.68)

0.02

1.46 (1.06–2.00)

0.02

 TT

109

132

1.71 (1.26–2.33)

0.00060

1.79 (1.31–2.46)

0.00027

2.26 (1.48–3.47)

0.00017

 GT or TT

464

471

1.44 (1.16–1.78)

0.0010

1.44 (1.15–1.80)

0.0013

1.64 (1.21–2.22)

0.0014

TNFAIP3

rs6927172

 CC

473

415

      

 CG

264

245

1.06 (0.85–1.32)

0.61

1.06 (0.85–1.33)

0.61

1.03 (0.76–1.39)

0.85

 GG

40

25

0.71 (0.42–1.19)

0.20

0.70 (0.41–1.19)

0.18

0.51 (0.23–1.10)

0.09

 CG or GG

304

270

1.01 (0.82–1.25)

0.91

1.01 (0.82–1.26)

0.91

0.95 (0.71–1.27)

0.73

TGFB1

rs1800469

 CC

383

344

      

 CT

297

299

1.12 (0.90–1.39)

0.30

1.08 (0.87–1.35)

0.48

1.28 (0.95–1.71)

0.11

 TT

86

53

0.69 (0.47–1.00)

0.047

0.69 (0.47–1.02)

0.06

0.69 (0.40–1.17)

0.17

 CT or TT

383

352

1.02 (0.83–1.26)

0.83

1.00 (0.81–1.23)

0.97

1.14 (0.86–1.52)

0.35

PTPN22

rs2476601

 GG

588

557

      

 GA

166

122

0.78 (0.60–1.01)

0.06

0.77 (0.59–1.00)

0.05

0.75 (0.52–1.09)

0.13

 AA

11

6

0.58 (0.21–1.57)

0.28

0.57 (0.20–1.58)

0.28

0.83 (0.21–3.28)

0.80

 GA or AA

177

128

0.76 (0.59–0.99)

0.04

0.76 (0.58–0.98)

0.04

0.76 (0.53–1.09)

0.13

PPARG

rs1801282

 CC

548

511

      

 CG

207

167

0.87 (0.68–1.10)

0.23

0.85 (0.66–1.08)

0.18

0.87 (0.63–1.21)

0.42

 GG

14

15

1.15 (0.55–2.40)

0.71

1.33 (0.62–2.83)

0.46

1.54 (0.60–3.98)

0.37

 CG or GG

221

182

0.88 (0.70–1.11)

0.29

0.88 (0.69–1.11)

0.27

0.91 (0.67–1.26)

0.58

IL1B

rs4848306

 GG

246

215

      

 GA

373

352

1.08 (0.85–1.36)

0.52

1.09 (0.86–1.39)

0.48

1.16 (0.84–1.60)

0.38

 AA

151

125

0.95 (0.70–1.28)

0.72

0.96 (0.71–1.31)

0.81

0.88 (0.57–1.34)

0.55

 GA or AA

524

477

1.04 (0.83–1.30)

0.72

1.06 (0.84–1.33)

0.64

1.08 (0.79–1.46)

0.64

IL1B

rs1143623

 GG

401

365

      

 GC

316

278

0.97 (0.78–1.20)

0.76

0.98 (0.79–1.22)

0.87

1.07 (0.80–1.44)

0.66

 CC

55

52

1.04 (0.69–1.56)

0.85

1.12 (0.74–1.69)

0.59

0.87 (0.48–1.57)

0.64

 GC or CC

371

330

0.98 (0.80–1.20)

0.83

1.00 (0.81–1.24)

0.98

1.04 (0.78–1.38)

0.79

IL1B

rs1143627

 TT

340

305

      

 TC

339

305

1.00 (0.81–1.25)

0.98

1.00 (0.79–1.25)

0.97

1.05 (0.78–1.42)

0.75

 CC

97

86

0.99 (0.71–1.37)

0.94

1.01 (0.72–1.41)

0.95

0.85 (0.53–1.36)

0.50

 TC or CC

436

391

1.00 (0.81–1.23)

1.00

1.00 (0.81–1.24)

1.00

1.00 (0.76–1.34)

0.97

IL1RN

rs4251961

 TT

298

247

      

 TC

360

324

1.09 (0.87–1.36)

0.47

1.04 (0.83–1.32)

0.71

1.22 (0.89–1.67)

0.21

 CC

112

105

1.13 (0.83–1.55)

0.44

1.05 (0.76–1.46)

0.76

1.41 (0.92–2.17)

0.12

 TC or CC

472

429

1.10 (0.89–1.36)

0.40

1.05 (0.84–1.30)

0.68

1.26 (0.94–1.71)

0.12

IL4R

rs1805010

 AA

209

201

      

 AG

410

317

0.80 (0.63–1.02)

0.08

0.79 (0.62–1.02)

0.07

0.73 (0.52–1.02)

0.07

 GG

157

133

0.88 (0.65–1.19)

0.41

0.91 (0.67–1.24)

0.55

0.87 (0.58–1.33)

0.53

 AG or GG

567

450

0.83 (0.66–1.04)

0.10

0.83 (0.65–1.05)

0.12

0.77 (0.56–1.06)

0.11

IL6

rs10499563

 TT

476

439

      

 TC

259

225

0.94 (0.76–1.17)

0.60

0.94 (0.75–1.18)

0.60

0.77 (0.57–1.05)

0.10

 CC

35

26

0.81 (0.48–1.36)

0.42

0.72 (0.42–1.25)

0.24

0.80 (0.39–1.63)

0.53

 TC or CC

294

251

0.93 (0.75–1.14)

0.48

0.92 (0.74–1.14)

0.43

0.77 (0.57–1.04)

0.09

IL6R

rs4537545

 CC

289

247

      

 CT

369

324

1.03 (0.82–1.29)

0.82

1.05 (0.83–1.32)

0.71

1.07 (0.79–1.47)

0.65

 TT

117

113

1.13 (0.83–1.54)

0.44

1.18 (0.86–1.63)

0.30

1.17 (0.76–1.79)

0.48

 CT or TT

486

437

1.05 (0.85–1.30)

0.64

1.08 (0.86–1.34)

0.51

1.09 (0.81–1.47)

0.55

IL10

rs1800872

 CC

482

408

      

 CA

258

225

1.03 (0.83–1.29)

0.79

1.01 (0.80–1.27)

0.94

0.93 (0.68–1.26)

0.63

 AA

35

42

1.42 (0.89–2.26)

0.14

1.35 (0.83–2.18)

0.22

1.47 (0.79–2.73)

0.22

 CA or AA

293

267

1.08 (0.87–1.33)

0.50

1.05 (0.84–1.30)

0.67

0.99 (0.74–1.33)

0.95

IL10

rs3024505

 CC

518

467

      

 CT

221

200

1.00 (0.80–1.26)

0.97

1.01 (0.80–1.28)

0.95

1.19 (0.87–1.61)

0.28

 TT

22

24

1.21 (0.67–2.19)

0.53

1.32 (0.72–2.42)

0.37

1.80 (0.79–4.12)

0.16

 CT or TT

243

224

1.02 (0.82–1.27)

0.84

1.04 (0.83–1.30)

0.76

1.23 (0.92–1.66)

0.17

IL12B

rs3212217

 GG

499

460

      

 GC

235

200

0.92 (0.74–1.16)

0.49

0.95 (0.75–1.19)

0.64

0.94 (0.69–1.29)

0.72

 CC

25

21

0.91 (0.50–1.65)

0.76

0.94 (0.51–1.72)

0.84

0.57 (0.23–1.41)

0.22

 GC or CC

260

221

0.92 (0.74–1.15)

0.47

0.95 (0.76–1.19)

0.63

0.91 (0.67–1.23)

0.53

IL12B

rs6887695

 GG

385

324

      

 GC

293

301

1.22 (0.98–1.52)

0.07

1.24 (0.99–1.55)

0.06

1.31 (0.97–1.77)

0.07

 CC

72

70

1.16 (0.81–1.66)

0.43

1.16 (0.80–1.69)

0.43

0.98 (0.59–1.61)

0.94

 GC or CC

365

371

1.21 (0.98–1.49)

0.07

1.22 (0.99–1.51)

0.06

1.24 (0.93–1.64)

0.14

IL12RB1

rs401502

 CC

360

304

      

 CG

303

311

1.22 (0.98–1.51)

0.08

1.21 (0.96–1.51)

0.10

1.19 (0.88–1.61)

0.26

 GG

87

70

0.95 (0.67–1.35)

0.79

0.97 (0.68–1.39)

0.87

1.18 (0.74–1.88)

0.48

 CG or GG

390

381

1.16 (0.94–1.42)

0.17

1.15 (0.93–1.43)

0.19

1.19 (0.89–1.58)

0.24

IL17A

rs2275913

 GG

340

307

      

 GA

336

301

0.99 (0.80–1.24)

0.94

0.98 (0.79–1.23)

0.89

0.90 (0.67–1.22)

0.51

 AA

95

84

0.98 (0.70–1.36)

0.90

1.00 (0.71–1.40)

0.98

1.00 (0.63–1.57)

0.99

 GA or AA

431

385

0.99 (0.80–1.22)

0.92

0.99 (0.80–1.22)

0.89

0.92 (0.69–1.22)

0.57

IL18

rs187238

 GG

387

380

      

 GC

312

259

0.85 (0.68–1.05)

0.13

0.83 (0.66–1.03)

0.09

0.74 (0.55–1.00)

0.049

 CC

64

41

0.65 (0.43–0.99)

0.04

0.69 (0.45–1.06)

0.09

0.58 (0.32–1.04)

0.07

 GC or CC

376

300

0.81 (0.66–1.00)

0.0499

0.80 (0.65–0.99)

0.04

0.71 (0.53–0.95)

0.02

IL18

rs1946518

 GG

282

259

      

 GT

363

329

0.99 (0.79–1.24)

0.91

0.96 (0.76–1.21)

0.71

0.89 (0.65–1.21)

0.45

 TT

113

97

0.93 (0.68–1.29)

0.68

0.95 (0.68–1.31)

0.74

0.80 (0.51–1.24)

0.32

 GT or TT

476

426

0.97 (0.79–1.21)

0.81

0.96 (0.77–1.19)

0.68

0.86 (0.64–1.16)

0.32

IL23R

rs11209026

 GG

680

646

      

 GA

89

50

0.59 (0.41–0.85)

0.0045

0.63 (0.43–0.91)

0.02

0.64 (0.38–1.05)

0.08

 AA

5

1

1.00 (1.00–1.00)

1.00

1.00 (1.00–1.00)

1.00

1.00 (1.00–1.00)

1.00

 GA or AA

94

51

0.57 (0.40–0.82)

0.0021

0.60 (0.42–0.87)

0.01

0.63 (0.38–1.03)

0.06

IFNG

rs2430561

 TT

199

181

      

 TA

398

369

1.02 (0.80–1.30)

0.88

1.01 (0.79–1.30)

0.92

1.08 (0.77–1.52)

0.65

 AA

161

139

0.95 (0.70–1.29)

0.74

0.97 (0.71–1.32)

0.85

1.09 (0.72–1.64)

0.68

 TA or AA

559

508

1.00 (0.79–1.26)

0.99

1.00 (0.79–1.27)

0.99

1.08 (0.79–1.50)

0.62

IFNGR1

rs2234711

 TT

290

232

      

 TC

361

348

1.20 (0.96–1.51)

0.11

1.20 (0.95–1.51)

0.12

1.15 (0.84–1.57)

0.40

 CC

119

108

1.13 (0.83–1.55)

0.43

1.09 (0.79–1.50)

0.60

1.11 (0.72–1.70)

0.65

 TC or CC

480

456

1.19 (0.96–1.47)

0.12

1.17 (0.94–1.46)

0.16

1.14 (0.84–1.53)

0.40

IFNGR2

rs8126756

 TT

553

522

      

 TC

168

130

0.82 (0.63–1.06)

0.13

0.83 (0.64–1.09)

0.18

0.86 (0.60–1.24)

0.42

 CC

18

12

0.71 (0.34–1.48)

0.36

0.69 (0.32–1.49)

0.35

0.53 (0.18–1.54)

0.24

 TC or CC

186

142

0.81 (0.63–1.04)

0.09

0.82 (0.64–1.06)

0.13

0.83 (0.59–1.17)

0.28

IFNGR2

rs17882748

 CC

199

173

      

 CT

391

341

1.00 (0.78–1.29)

0.98

1.00 (0.77–1.30)

0.99

1.01 (0.71–1.42)

0.97

 TT

153

174

1.31 (0.97–1.76)

0.08

1.31 (0.97–1.78)

0.08

1.16 (0.77–1.73)

0.48

 CT or TT

544

515

1.09 (0.86–1.38)

0.48

1.09 (0.86–1.39)

0.48

1.05 (0.76–1.45)

0.76

TBX21

rs17250932

 TT

526

497

      

 TC

210

179

0.90 (0.71–1.14)

0.39

0.94 (0.74–1.19)

0.61

0.84 (0.60–1.17)

0.30

 CC

32

19

0.63 (0.35–1.12)

0.12

0.66 (0.36–1.19)

0.17

0.37 (0.14–0.98)

0.046

 TC or CC

242

198

0.87 (0.69–1.08)

0.21

0.90 (0.72–1.14)

0.39

0.78 (0.56–1.07)

0.12

NLRP1

rs2670660

 AA

222

202

      

 AG

390

328

0.92 (0.73–1.18)

0.52

0.96 (0.75–1.23)

0.73

1.12 (0.80–1.56)

0.52

 GG

154

154

1.10 (0.82–1.47)

0.53

1.11 (0.82–1.49)

0.51

1.12 (0.75–1.67)

0.59

 AG or GG

544

482

0.97 (0.78–1.22)

0.82

1.00 (0.79–1.26)

0.98

1.11 (0.81–1.52)

0.50

NLRP1

rs878329

 GG

217

206

      

 GC

394

333

0.89 (0.70–1.13)

0.34

0.89 (0.69–1.14)

0.35

0.99 (0.71–1.38)

0.93

 CC

155

155

1.05 (0.79–1.41)

0.73

1.05 (0.78–1.41)

0.75

1.03 (0.69–1.54)

0.90

 GC or CC

549

488

0.94 (0.75–1.17)

0.57

0.93 (0.74–1.18)

0.56

1.00 (0.73–1.36)

0.98

NLRP3

rs10754558

 CC

294

248

      

 CG

355

324

1.08 (0.86–1.36)

0.50

1.06 (0.84–1.34)

0.61

1.10 (0.81–1.51)

0.54

 GG

111

116

1.24 (0.91–1.69)

0.18

1.25 (0.91–1.71)

0.17

1.11 (0.71–1.72)

0.65

 CG or GG

466

440

1.12 (0.90–1.39)

0.30

1.11 (0.89–1.38)

0.36

1.11 (0.82–1.49)

0.51

NLRP3

rs4612666

 CC

435

360

      

 CT

280

277

1.20 (0.96–1.49)

0.11

1.23 (0.99–1.54)

0.07

1.28 (0.95–1.72)

0.10

 TT

53

48

1.09 (0.72–1.66)

0.67

1.19 (0.78–1.82)

0.41

1.07 (0.59–1.94)

0.82

 CT or TT

333

325

1.18 (0.96–1.45)

0.12

1.23 (0.99–1.52)

0.06

1.24 (0.94–1.65)

0.13

CARD8

rs2043211

 AA

321

298

      

 AT

342

316

1.00 (0.80–1.24)

0.97

0.98 (0.79–1.23)

0.89

0.90 (0.67–1.22)

0.50

 TT

94

78

0.89 (0.64–1.25)

0.52

0.89 (0.63–1.26)

0.50

0.91 (0.57–1.44)

0.68

 AT or TT

436

394

0.97 (0.79–1.20)

0.80

0.96 (0.78–1.19)

0.72

0.90 (0.67–1.19)

0.45

JAK2

rs12343867

 TT

398

358

      

 TC

299

263

0.98 (0.79–1.22)

0.84

0.96 (0.76–1.20)

0.69

0.82 (0.61–1.12)

0.21

 CC

61

65

1.18 (0.81–1.73)

0.38

1.11 (0.75–1.63)

0.61

1.03 (0.62–1.71)

0.91

 TC or CC

360

328

1.01 (0.82–1.25)

0.90

0.98 (0.79–1.21)

0.86

0.86 (0.64–1.14)

0.29

Table 2

Biological interpretation of the single nucleotide polymorphisms (SNPs) associated with ankylosing spondylitis (AS)

Gene

Rs-number

Pathway

Model

OR (95% CI)

P-value / Bonferronia

Effect of minor-allele

Biological interpretation

TLR1

rs4833095

Pathogen recognition

CC vs TT

2.59 (1.48–4.51)

0.00081 / 0.04

743C increase TLR1 level in PBMC [56]

Increased TLR1 level was associated with increased risk of AS. This could indicate that a genetically determined high activity of the NFkB pathway, and thus high TNF-α and IL-17 activity, was associated with increased risk of AS.

TLR4

rs1554973

Pathogen recognition

CC vs TT

0.55 (0.34–0.86)

0.010 / 0.51

Unknown [67]

LY96

rs11465996

Pathogen recognition

GG vs CC

0.68 (0.46–1.00)

0.049 / 1.00

-1625G increase MD-2 and TNF-α levels in human U937 cells and whole blood leukocytes [57]

Increased MD-2 and TNF-α level was associated with a reduced risk of AS. In contrast to the other results this indicate that genetically determined high TNF-driven inflammatory response was associated with reduced risk of AS.

TNF

rs1800629

Cytokines

GA or AA vs GG

0.56 (0.44–0.72)

0.0000047 / 0.00024

-308A increase expression in jurkat cells [65], reduce mRNA level in PBMC and serum [48] or no association was found [49]

Reduced TNF-α mRNA level was associated with reduced risk of AS. This could indicate that genetically determined high TNF-driven inflammatory response was associated with increased risk of AS.

TNF

rs361525

Cytokines

GA or AA vs GG

0.49 (0.31–0.78)

0.0024 / 0.12

-238A reduce expression in PBMC [49]

Reduced TNF-α expression was associated with reduced risk of AS. This indicates that genetically determined high TNF-driven inflammatory response was associated with increased risk of AS.

TNFRSF1A

rs4149570

Cytokines

GT or TT vs GG

1.44 (1.15–1.80)

0.0013 / 0.066b

-609 T increase expression in PBMC [50]

Increased TNF-α receptor 1 expression was associated with increased risk of AS. This indicates that genetically determined high TNF-driven inflammatory response was associated with increased risk of AS.

PTPN22

rs2476601

Immune response

GA or AA vs GG

0.76 (0.58–0.98)

0.037 / 1.00

1858A reduce TNF-α level in serum [51]

Reduced TNF-α level was associated with reduced risk of AS. This indicates that genetically determined high TNF-driven inflammatory response was associated with increased risk of AS.

IL18

rs187238

Cytokines

GC or CC vs GG

0.80 (0.65–0.99)

0.044 / 1.00

-137C reduce IL-18 level in serum [53] and expression in PBMC [54]

Reduced IL-18 expression, and thus reduced IL-17 and TNF-α activity, was associated with reduced risk of AS.

This indicates that a genetically determined high activity of the IL23/IL17 pathway was associated with increased risk of AS.

IL23R

rs11209026

Cytokines

GA or AA vs GG

0.60 (0.42–0.87)

0.0071 / 0.36

rs11209026A reduce IL-17 level in PBMC [52]

Reduced IL-17 level was associated with reduced risk of AS. This indicates that a genetically determined high activity of the IL23/IL17 pathway was associated with increased risk of AS.

OR Odds ratio

95% CI 95% confidence interval

PBMC peripheral blood mononuclear cell

aThe Bonferroni calculations were based on the 51 SNPs assessed in this study

bThe TNFRSF1A (rs4149570) TT vs GG: OR: 1.79, 95% CI: 1.31–2.41, p = 0.00027, Bonferroni = 0.014

DNA extraction (Maxwell 16 LEV Blood DNA Kit; Promega, Madison, WI, USA) was performed as described by Bank et al. [10]. For the healthy controls, DNA was extracted from EDTA-stabilized peripheral blood by either PureGene (Qiagen, Hilden, Germany) or Wizard Genomic (Promega, Madison, Wisconsin, USA) DNA purification kit according to the manufacturers` instructions [1117]. Competitive Allele-Specific Polymerase chain reaction (KASP™), an end-point PCR technology, was used by LGC Genomics for genotyping (LGC Genomics, Hoddesdon, United Kingdom) (http://www.lgcgenomics.com/).

Power calculation

The Genetic Power Calculator was utilized for power analysis of discrete traits (http://zzz.bwh.harvard.edu/gpc/cc2.html). The lowest minor allele frequency (MAF) of the studied SNPs was 0.10. The ‘high-risk allele frequency’ was set to 0.10, the ‘prevalence’ was set to 0.0018 [18], D-prime was set to 1, type I error rate was set to 0.05 and number of cases and control:case ratio was 795:709. This cohort study had more than 80% chance of detecting a dominant effect with an odds ratio (OR) of 1.4 for AS.

Statistical analysis

Logistic regression was used to compare genotype distributions among patients with AS versus healthy controls. Crude odds ratio, odds ratio adjusted for age and sex, and odds ratio adjusted for age, sex, and smoking status were assessed (Table 1). A chi-square test was used to test for deviation from Hardy-Weinberg equilibrium in the healthy controls and for haplotype analysis (Tables 345 and 6).
Table 3

Association of the TLR2 haplotype combinations and risk of ankylosing spondylitis (AS). The haplotype combinations in TLR2 described 93% of the genotypes observed

Haplotype combinations

Haplotypes

NAS (%)

NControl (%)

ORa

(95% CI)

P-value

rs4696480 A > T

rs11938228 C > A

rs3804099 T>Cb

11

T:T

A:A

T:T

69 (11)

76 (10)

1.00

22

A:A

C:C

C:C

72 (11)

74 (10)

1.07

0.68–1.70

0.82

33

A:A

C:C

T:T

28 (4)

34 (5)

0.91

0.50–1.65

0.76

44

T:T

C:C

C:C

14 (2)

10 (1)

1.52

0.64–3.70

0.38

12

T:A

C:A

C:T

158 (24)

197 (27)

0.88

0.60–1.30

0.55

13

T:A

C:A

T:T

76 (12)

103 (14)

0.81

0.52–1.26

0.37

14

T:T

C:A

C:T

59 (9)

49 (7)

1.33

0.80–2.19

0.31

23

A:A

C:C

C:T

77 (12)

89 (12)

0.95

0.61–1.49

0.91

24

T:A

C:C

C:C

52 (8)

55 (8)

1.04

0.63–1.72

0.90

34

T:A

C:C

C:T

51 (8)

44 (6)

1.28

0.76–2.14

0.43

OR Odds ratio

aOR was calculated for each haplotype combination by using the haplotype 11 as reference group

bThe variant allele of rs3804099T T > C has been shown to decrease TNF-α, IL-1β & IL-6 level [68]

Table 4

Association between TLR4 haplotype combinations and risk of ankylosing spondylitis (AS). The haplotype combinations in TLR4 described 94% of the genotypes observed

Haplotype combinations

Haplotypes

NAS (%)

NControl (%)

ORa

(95% CI)

P-value

rs12377632

T > C

rs1554973

T > C

rs5030728

G > A

11

C:C

T:T

G:G

95 (14)

101 (14)

1.00

22

T:T

T:T

A:A

69 (10)

74 (10)

0.99

0.64–1.53

1.00

33

T:T

C:C

G:G

29 (4)

57 (8)

0.54

0.32–0.92

0.03

44

T:T

T:T

G:G

3 (0)

5 (1)

0.64

0.15–2.74

0.72

12

T:C

T:T

G:A

154 (23)

188 (25)

0.87

0.61–1.24

0.47

13

T:C

T:C

G:G

126 (19)

129 (17)

1.04

0.72–1.51

0.85

14

T:C

T:T

G:G

30 (5)

32 (4)

1.00

0.56–1.77

1.00

23

T:T

T:C

G:A

99 (15)

106 (14)

0.99

0.67–1.47

1.00

24

T:T

T:T

G:A

31 (5)

24 (3)

1.37

0.75–2.51

0.36

34

T:T

T:C

G:G

28 (4)

26 (4)

1.14

0.63–2.09

0.76

OR Odds ratio

The biological effect of the three polymorphisms in TLR4 was unknown

aOR was calculated for each haplotype combination by using the haplotype 11 as reference group

Table 5

Association between IL1B haplotype combinations and risk of ankylosing spondylitis (AS). The haplotype combinations in IL1B described 97% of the genotypes observed

Haplotype combinations

Haplotypes

NAS (%)

NControl (%)

ORa

(95% CI)

P-value

rs4848306

-3737G > A [69, 70]

rs1143623

-1464G > C [69, 71]

rs1143627

-31 T > C [69, 71, 72]

11

A:A

G:G

T:T

125 (18)

148 (20)

1.00

22

G:G

C:C

C:C

52 (8)

54 (7)

1.14

0.73–1.79

0.65

33

G:G

G:G

T:T

32 (5)

41 (5)

0.92

0.55–1.55

0.79

44

G:G

G:G

C:C

5 (1)

3 (0)

1.97

0.46–8.42

0.48

12

A:G

G:C

T:C

163 (24)

185 (24)

1.04

0.76–1.43

0.81

13

A:G

G:G

T:T

141 (20)

147 (19)

1.14

0.82–1.58

0.50

14

A:G

G:G

T:C

44 (6)

38 (5)

1.37

0.84–2.25

0.26

23

G:G

C:G

C:T

84 (12)

92 (12)

1.08

0.74–1.58

0.70

24

G:G

C:G

C:C

28 (4)

34 (4)

0.98

0.56–1.70

1.00

34

G:G

G:G

T:C

14 (2)

16 (2)

1.04

0.49–2.21

1.00

OR Odds ratio

The variant allele of −3737 G > A [69], −1464 G > C [70] and − 31 T > C [71, 72] have been shown to decrease IL-1β level [6972]

aOR was calculated for each haplotype combination by using the haplotype 11 as reference group

Table 6

Association of the TNF haplotype combinations and risk of ankylosing spondylitis (AS). The haplotype combinations in TNF described 97% of the genotypes observed

Haplotype combinations

Haplotypes

NAS (%)

NControl (%)

ORa

(95% CI)

P-value

rs361525 G>Ab

rs1800629 G>Ac

11

G:G

G:G

523 (76)

469 (61)

1.00

22

G:G

A:A

9 (1)

25 (3)

0.32

(0.15–0.70)

0.005

12

G:G

G:A

125 (18)

210 (28)

0.53

(0.41–0.69)

< 0.0001

13

G:A

G:G

26 (4)

47 (6)

0.50

(0.30–0.81)

0.007

14

G:A

G:A

4 (1)

12 (2)

0.30

(0.10–0.93)

0.05

OR Odds ratio

aOR was calculated for each haplotype combination by using the haplotype 11 as reference group

bThe variant allele of TNF -238A rs361525A G > A has been shown to reduce expression of TNF-α [49]

cThe variant allele of TNF -308A rs1800629 G > A has been shown to reduce mRNA level [48]

Statistical analyses were performed using STATA version 15 (StataCorp LP, College Station, TX, USA).

Results

Study population

Among the patients with AS the median age was 32 years (SD: 11.5) and 68% (483/709) were males. The healthy controls had a median age of 43 years (SD: 11.5) and 52% (411/384) were males. Among the patients 37% (118/323), 23% (73/323), and 41% (132/323) and among the controls 26% (207/788), 24% (189/788), and 50% (392/788) were current smokers, former smokers and never smokers, respectively. HLA-B27 staus was available for 498 patients of which 83% (411/498) were positive. Sixty percent (427/709) of the patients were treated with anti-TNF.

The genotype distributions among the healthy controls deviated from Hardy-Weinberg equilibrium for TLR1 (743 T > C (rs4833095)) (p = 0.03), TLR2 (− 16,934 A > T (rs4696480)) (p = 0.02), TLR4 (rs1554973 T > C) (p = 0.03), TLR9 (1174 G > A (rs352139)) (p = 0.02) and TGFB1 (− 509 C > T (rs1800469)) (p = 0.02). After correction for multiple testing, all SNPs studied were in Hardy-Weinberg equilibrium.

Polymorphisms associated with susceptibility of AS

In the age and sex adjusted analysis, the homozygous variant genotype of TLR1 743 T > C (rs4833095) (OR: 2.59, 95% CI: 1.48–4.51, p = 0.0008) and the combined homozygous and the heterozygous variant genotypes of TNFRSF1A -609 G > T (rs4149570) (OR: 1.44, 95% CI: 1.15–1.80, p = 0.001) were associated with increased risk of AS. The homozygous variant genotype of TLR4 T > C (rs1554973) (OR: 0.55, 95% CI: 0.34–0.86, p = 0.01) and LY96–1625 C > G (rs11465996) (OR: 0.68, 95% CI: 0.46–1.00, p = 0.05), and the combined homozygous and the heterozygous variant genotypes of TNF -308 G > A (rs1800629) (OR: 0.56, 95% CI: 0.44–0.72, p = 0.000005), TNF -238 G > A (rs361525) (OR: 0.49, 95% CI: 0.31–0.78, p = 0.002), PTPN22 1858 G > A (rs2476601) (OR: 0.76, 95% CI: 0.58–0.98, p = 0.04), IL18–137 G > C (rs187238) (OR: 0.80, 95% CI: 0.65–0.99, p = 0.04), and IL23R G > A (rs11209026) (OR: 0.60, 95% CI: 0.42–0.87, p = 0.01) were associated with reduced risk of AS (Table 1).

After Bonferroni correction for multiple testing the homozygous variant genotype of TLR1 743 T > C (rs4833095) (OR: 2.59, 95% CI: 1.48–4.51, p = 0.04) and TNFRSF1A -609 G > T (rs4149570) (OR: 1.79, 95% CI: 1.31–2.41, p = 0.01) were associated with increased risk of AS and the combined homozygous and the heterozygous variant genotypes of TNF -308 G > A (rs1800629) (OR: 0.56, 95% CI: 0.44–0.72, p = 0.0002) were associated with reduced risk of AS (Table 2).

SNPs associated with AS and the biological effect of the SNPs are summarized in Table 2.

Haplotype analysis

Haplotype analyses of TLR2, TLR4, IL1B and TNF are shown in Tables 345 and 6, respectively.

The TLR4 haplotype combination 33 (rs12377632TT, rs1554973CC and rs5030728GG) was associated with reduced risk of AS (OR: 0.54, 95% CI: 0.32–0.92, p = 0.03) compared to the haplotype combination 11. In TNF all haplotype combinations were associated with reduced risk of AS compared to the haplotype combination 11 (rs361525GG and rs1800629GG).

No associations were found for haplotype combinations of TLR2 or IL1B.

Discussion

In this case-control study, polymorphisms in a: the TNF-α (TNF (rs1800629 and rs361525), TNFRSF1A (rs4149570), and PTPN22 (rs2476601)), b: the IL23/IL17 (IL23R (rs11209026), and IL18 (rs187238)), or c: the NFkB (TLR1 (rs4833095), TLR4 (rs1554973), and LY96 (rs11465996)) pathways were associated with risk of AS.

The found assocaitions for TNF (rs1800629) [1922], TNFRSF1A (rs4149570) [23], and IL23R (rs11209026) [2433] are in agreement with other case-control studies. Furthermore, Zhao et al. found that the variant allele of NLRP3 (rs4612666) was associated with increased risk of AS in Chinese patients [23]. In our study we found a trend for associations of the variant allele of NLRP3 (rs4612666) with increased risk of AS (p = 0.06). However, our results are in contrast to a meta-analysis of the PTPN22 (rs2476601) polymorphism that did not find an association with AS [34]. Finally, we identified novel risk loci in TNF (rs361525), IL18 (rs187238), TLR1 (rs4833095), TLR4 (rs1554973), and LY96 (rs11465996) that need validation in independent cohorts.

Most of the SNPs assessed in our study have known biological effects thus allowing a biological interpretation of the observed associations based on increased or reduced gene activity as summarized in Table 2 [3547]. The associations observed for the TNF (rs1800629 and rs361525) polymorphisms suggest that reduced TNF-α mRNA level and expression of TNF-α was associated with reduced risk of AS [48, 49]. This is supported by our haplotype analysis which also suggests that the variant alleles of TNF rs1800629 and rs361525 were associated with reduced risk of AS. Likewise, the associations observed for the TNFRSF1A (rs4149570) polymorphism indicates that increased expression of the TNF-α receptor 1 was associated with increased risk of AS [50]. Furthermore, the associations observed for the PTPN22 (rs2476601) polymorphism suggests that reduced TNF-α serum level was associated with reduced risk of AS [51]. Taken together, this suggests that genetically determined high activity of the TNF-α pathway was associated with increased risk of AS.

IL-17 is known to induce the production of many cytokines including TNF-α [6]. IL-18 is a pro-inflammatory cytokine known to enhance the production of IL-17, TNF-α, and IL-1β [8]. In this study, the association observed for the IL23R (rs11209026) polymorphism suggests that reduced IL-17 serum level, and thus reduced TNF-α activity, was associated with reduced risk of AS [52]. Furthermore, the associations observed for the IL18 (rs187238) polymorphism indicates that reduced IL-18 expression, and thus reduced IL-17 and TNF-α activity, was associated with reduced risk of AS [53, 54]. The associations found in the IL23R (rs11209026) and the IL18 (rs187238) polymorphisms thus suggest that a genetically determined high activity of the IL23/IL17 pathway was associated with increased risk of AS. The two SNPs furthermore support that genetically determined high activity of the TNF-α pathway was associated with increased risk of AS. The observed associations between the polymorphisms in IL23R and IL18 and risk of AS are in line with previous studies pointing out the IL23/IL17 pathway as central to the pathophysiology of AS [3, 4, 55].

This study also suggests that the NFkB pathway may be involved in the etiology of AS. The associations observed for the TLR1 (rs4833095) polymorphism suggests that increased TLR1 level was associated with increased risk of AS [56]. High level of TLR1 may lead to increased NFkB activation and thus increased TNF-α and IL-17 activity, which is in line with the other results. However, in contrast to the other results, the associations observed for the LY96 (rs11465996) polymorphism suggests that increased MD-2 (LY96) and TNF-α level was associated with a reduced risk of AS [57]. Finally, the TLR4 (rs1554973) polymorphism was associated with reduced risk of AS which was supported by the haplotype results (Table 4). The biological effect of the TLR4 (rs1554973) polymorphism is unknown, however, the result supports the notion that the NFkB pathway may be involved in the etiology of AS.

Both TNF-α [58] and interleukin-17 inhibitors [59] have been shown to reduce inflammation and improve symptoms in patients with AS [60]. Furthermore, increased levels of TNF-α, IL-17, IL-23, IL-1β, and IL-6 have been found in sera and synovial fluid from AS patients [6164]. The genetic associations between AS and the polymorphisms in TLR1, TLR4, LY96, TNF, TNFRSF1A, IL18, and IL23R found in this study, could potentially – in part – explain this altered cytokine milieu present in AS patients.

There are aspects of this study which should be interpreted with care. Conflicting results have been reported for the TNF (rs1800629) polymorphism [48, 49, 65]. Furthermore, the TNF polymorphisms, as well as the HLA-B27 locus, are located on chromosome 6, and there is a risk that even a minor linkage disequilibrium could have confounded our results [2]. TLR1 (rs4833095), TLR2 (rs4696480), TLR4 (rs1554973), TLR9 (rs352139), and TGFB1 (rs1800469) were not in Hardy-Weinberg equilibrium among the healthy controls. Due to the number of polymorphisms analyzed this is probably a type II error. The polymorphisms do not deviate from Hardy-Weinberg equilibrium when corrected for multiple testing. We cannot exclude that some of our positive findings may be due to chance due to the obtained p-values and the number of statistical tests performed. When the results were corrected for multiple testing only the variant allele of TLR1 (rs4833095) and TNFRSF1A (rs4149570) were associated with increased risk of AS and the variant allele of TNF (rs1800629) was associated with reduced risk of AS.

A major strength of this study was that the cohort was rather large including 709 patients with AS and 795 healthy controls and the associations that we report were biologically plausible. Also, the validity of the diagnosis is expected to be high, since the patients were identified via a clinical database that the rheumatologist use for prospective monitoring of patients as part of routine care [66].

Conclusions

In conclusion, we replicated associations between AS and the polymorphism TNF (rs1800629), TNFRSF1A (rs4149570), and IL23R (rs11209026). Furthermore, we identified novel risk loci in TNF (rs361525), IL18 (rs187238), TLR1 (rs4833095), TLR4 (rs1554973), and LY96 (rs11465996) that need validation in independent cohorts. The results suggest that genetically determined high activity of the TNF-α, IL23/IL17, and NFkB pathways increase the risk of AS.

Notes

Declarations

Acknowledgments

We thank Ewa Kogutowska and Mette Errebo Rønne, Statens Serum Institut, for laboratory support; and Niels Steen Krogh, Zitelab Aps, Copenhagen, Denmark for database management. We also thank Department of Medicine, Viborg Regional Hospital, Denmark and OPEN (Odense Patient data Explorative Network), Odense University Hospital, Denmark for supporting this work.

In memory of Niels Henrik Heegaard:

Co-author Niels H.H. Heegaard, Professor, MD, DMSc, DNatSc, died unexpectedly on September 26, 2017, at age 57. As director of the Department of Autoimmunology and Biomarkers, Statens Serum Institut, Copenhagen, Dr. Heegaard advanced research in autoimmunology and neurodegenerative disease. He had an extensive international research network and published more than 200 papers in scientific journals, focusing on biomarkers such as autoantibodies, microRNA, and microparticle proteins. He was a patient and unpretentious collaborator who always sought to highlight the work of other collaborators and co-workers. Dr. Heegaard was characterized by humor, kindness, and optimism. He is survived by his wife and 2 children.

Funding

This study was funded by the Danish Rheumatism Association (A1923, A3037, and A3570 - www. Gigtforeningen.dk) and Region of Southern Denmark’s PhD Fund, 12/7725 (www. Regionsyddanmark.dk).

Availability of data and materials

The datasets used during the current study are available from the corresponding author on reasonable request.

Authors’ contributions

JS, SB, UV, PSA, SBS, HL, NHH and VA designed the research study and PSA, ABB, MRA, IB, RBD, HJH, BG and MLH collected the materials. JS and SB analysed the data and wrote the first draft. UV, PSA, SBS, ABB, MRA, IB, RBD, HJH, BG, MLH, HL and VA critically revised the manuscript. All authors agreed to be accountable for all aspects of the work and approved the final version of the manuscript.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki and was approved by the Regional Ethics Committees of Central (M20100153) and Southern (S-20120113) Denmark and the Danish Data Protection Agency of Central (RM: J. 2010–41-4719) and Southern (RSD: 2008–58-035) Denmark. For blood samples collected after routine TB screening, the Ethics Committees gave exemption from informed consent requirements because samples were taken as part of routine care and data were not identifiable. Written informed consent was obtained from patients donating blood samples at Frederiksberg Hospital as this involved collecting additional samples from patients.

Consent for publication

Not applicable.

Competing interests

VA receives compensation as a consultant and for being member of an advisory board for MSD and Janssen. BG has recived research funding from AbbVie, Biogen, Pfizer. The other authors declare no conflicts of interest.

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Authors’ Affiliations

(1)
Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
(2)
Department of Autoimmunology and Biomarkers, Statens Serum Institut, Copenhagen, Denmark
(3)
Department of Rheumatology, Frederiksberg Hospital, Frederiksberg, Denmark
(4)
Department of Rheumatology, Skåne University Hospital, Lund, Sweden
(5)
Focused Research Unit for Molecular Diagnostic and Clinical Research, Hospital of Southern Jutland, Aabenraa, Denmark
(6)
Medical Department, Viborg Regional Hospital, Viborg, Denmark
(7)
National Research Centre for the Working Environment, Copenhagen, Denmark
(8)
Microbiology and Infection Control, Statens Serum Institut, Copenhagen, Denmark
(9)
Veterinary Disease Biology, University of Copenhagen, Copenhagen, Denmark
(10)
Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
(11)
Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Hellerup, Denmark
(12)
Department of Biochemistry, Hospital of Lillebaelt, Vejle, Denmark
(13)
Department of Clinical Microbiology, Slagelse Hospital, Slagelse, Denmark
(14)
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
(15)
Department of Respiratory Diseases B, Aarhus University Hospital, Aarhus, Denmark
(16)
Department of Rheumatology, Gentofte and Herlev Hospital, Hellerup, Denmark
(17)
The DANBIO Registry, Copenhagen Center for Arthritis Research, Center for Rheumatology and Spine Diseases, Rigshospitalet, Glostrup, Denmark
(18)
Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
(19)
Clinical Biochemistry, Clinical Institute, University of Southern Denmark, Odense, Denmark
(20)
OPEN Odense Patient Data Explorative Network, Odense University Hospital, Odense, Denmark

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