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BMC Medical Genetics

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Association study of genetic variants of pro-inflammatory chemokine and cytokine genes in systemic lupus erythematosus

  • Elena Sánchez1,
  • José M Sabio2,
  • José L Callejas3,
  • Enrique de Ramón4,
  • Rosa Garcia-Portales5,
  • Francisco J García-Hernández6,
  • Juan Jiménez-Alonso2,
  • Ma Francisca González-Escribano7,
  • Javier Martín1Email author and
  • Bobby P Koeleman8
Contributed equally
BMC Medical Genetics20067:48

https://doi.org/10.1186/1471-2350-7-48

Received: 10 March 2006

Accepted: 23 May 2006

Published: 23 May 2006

Abstract

Background

Several lines of evidence suggest that chemokines and cytokines play an important role in the inflammatory development and progression of systemic lupus erythematosus. The aim of this study was to evaluate the relevance of functional genetic variations of RANTES, IL-8, IL-1α, and MCP-1 for systemic lupus erythematosus.

Methods

The study was conducted on 500 SLE patients and 481 ethnically matched healthy controls. Genotyping of polymorphisms in the RANTES, IL-8, IL-1α, and MCP-1 genes were performed using a real-time polymerase chain reaction (PCR) system with pre-developed TaqMan allelic discrimination assay.

Results

No significant differences between SLE patients and healthy controls were observed when comparing genotype, allele or haplotype frequencies of the RANTES, IL-8, IL-1α, and MCP-1 polymorphisms. In addition, no evidence for association with clinical sub-features of SLE was found.

Conclusion

These results suggest that the tested functional variation of RANTES, IL-8, IL-1α, and MCP-1 genes do not confer a relevant role in the susceptibility or severity of SLE in the Spanish population.

Background

Systemic lupus erythematosus (SLE) is a chronic and systemic autoimmune disease with a complex pathogenesis involving multiple genetic and environmental factors. The disease is characterized by autoantibody production, abnormalities of immune-inflammatory system function and inflammatory manifestation in several organs. Although the pathogenesis of SLE is unknown, the increased concordance of SLE in monozygotic versus dizygotic twins and familial clustering provide evidences for the role of genetic factors in this disorder [1]. However, the genetic background of SLE is thought to be complex and involves multiple genes encoding different molecules with significant functions in the regulation of the immune system [14]. Among the genetic factors believed to influence susceptibility to SLE, the major histocompatibility complex (MHC) alleles show the most significant association. Importantly, several recent studies show that non-HLA genes play a role in the development of SLE [14]. In this respect, there are several lines of evidence that chemokines and cytokines play an important role in the inflammatory development and progression of autoimmune diseases as SLE [57]. Furthermore, it has been show that SLE patients show an up-regulation of inflammatory molecules [8, 9].

Regulated upon activation, normal T cell expressed and secreted (RANTES), interleukin 8 (IL-8) and monocyte chemoattractant protein-1 (MCP-1) are involved in the physiology and pathophysiology of acute and chronic inflammatory processes, by recruitment of monocytes, T lymphocytes and eosinophils to sites of inflammation [10, 11]. Substantial evidence suggest that IL-8 and MCP-1, contribute to kidney injury in the glomerulonephritis of SLE, through glomerular leukocyte infiltration [12, 13]. Serum levels of these inflammatory chemokines (RANTES, IL8 and MCP-1) are significantly higher in SLE patients than in control subjects, and correlated significant with SLEDAI score, suggesting a role in the pathogenesis of the disease [9]. As a consequence of renal disease, increased urine MCP-1 and urine IL-8 (uMCP-1, uIL-8) levels can be detected in SLE patients during active renal disease [14]. Interestingly some genetic variants within regulatory regions of these genes can affect the transcriptional activity and subsequent protein expression in human. For, RANTES the SNPs -403 G/A (rs2107538) and R3 (rs2306630) T/C, for IL-8 -353 T/A (rs4073) and for +781 C/T (rs2227306) and MCP-1 -2518 G/A (rs1024611) have been correlated to mRNA and or protein expression [1517].

In addition to these three genes, IL-1α also constitutes a strong candidate gene for SLE, since it is a proinflammatory cytokine that plays and important role in initiating and modulating the immune responses. There is a functional polymorphism in the promoter region of IL-1α gene at position -889 C/T (rs1800587), and the -889 C homozygous genotype has been associated with significantly lower transcriptional activity of the IL-1α gene and lower levels of IL-1α in plasma compared with the TT genotype [18].

Overall, the chemokines RANTES, IL-8, MCP-1and cytokine IL-1α are strong candidate genes for which genetic association studies can shed light on the underlying mechanisms causing the immune dysregulation, such as inappropriate T cell activation or trafficking in SLE.

Therefore, the aim of this work was to test for association of the reported functional polymorphisms in RANTES, IL-8, MCP-1 and IL-1α with SLE susceptibility.

Methods

Patients

Peripheral blood samples were obtained after written informed consent from 500 SLE patients meeting the American College of Rheumatology (ACR) criteria for SLE [19]. These patients were recruited from five Spanish hospitals: Hospital Virgen de las Nieves and Hospital Clinico (Granada), Hospital Virgen del Rocio (Seville) and Hospital Carlos-Haya and Hospital Virgen de la Victoria (Malaga). Similarly, blood was taken from 481 blood bank and bone marrow donors of the corresponding cities that were included as healthy individuals. Both patient and control groups were of Spanish Caucasian origin and were matched for age and sex. Eighty seven percent of the SLE patients were women, the mean age of SLE patients at diagnosis was 43 ± 13.3 years and the mean age at disease onset of SLE symptoms was 32 ± 15 years. The SLE clinical manifestations studied were articular involvement (76%), renal affectation (37%), cutaneous lesions (62%), hematopoietic alterations (73%), photosensivity (51%), neurological disease (17%) and serositis (28%). The study was approved by all local ethical committees from the corresponding hospitals.

Genotyping

For all the considered SNPs, samples were genotyped using a pre-developed TaqMan allelic discrimination assay. Table 1 shows the part number and reference of each SNP (Applied Biosystems, Foster City, CA, USA). PCR was carried out with mixes consisting of 8 ng of genomic DNA, 2.5 μl of Taqman master mix, 0.125 μl of 20x assay mix and ddH2O up to 5 μl of final volume. The following amplification protocol was used: denaturation at 95°C for 10 min, followed by 40 cycles of denaturation at 92°C for 15 sec and annealing and extension at 60°C for 1 min. After PCR, the genotype of each sample was attributed automatically by measuring the allelic specific fluorescence on the ABI PRISM 7900 Sequence Detection Systems using the SDS 2.2.2 software for allelic discrimination (Applied Biosystems, Foster City, CA, USA).
Table 1

Taqman probes part number used for genotyping.

Polymorphisms

Part number

RANTES -403 G/A (rs2107538)

C_15874407_10

RANTES R3 C/T (rs2306630)

C_26625663_10

IL-8 -353 A/T (rs4073)

C_11748116_10

IL-8 +781 C/T (rs2227306)

C_11748169_10

IL-1α -889 C/T (rs1800587)

C_9546481_20

MCP-1 -2518 G/A (rs1024611)

C_2590362_10

Statistic analysis

Allele and genotype frequencies were obtained by direct counting. Hardy-Weinberg equilibrium and statistical analysis to compare allelic and genotypic distributions were performed using the chi-square test. Odds ratio (OR) with 95% confidence intervals (95%CI) were calculated according to Woolf's method. The software used was StatCalc program (Epi Info 2002; Centers of Disease Control and Prevention, Atlanta, GA, USA). For the haplotype analysis, pair-wise linkage disequilibrium measures were investigated and haplotypes were constructed using the expectation-maximization (EM) algorithm implemented in UNPHASED software [20]. P values below 0.05 were considered statistically significant. The power of the study to detect an effect of a polymorphism in disease susceptibility was estimated using the Quanto v 0.5 software (Department of Preventive Medicine University of Southern California, CA, USA).

Results

Table 2 shows the allele and genotype distribution of the RANTES,IL-8, IL-1α, and MCP-1 polymorphisms. For all polymorphisms, the distribution of genotypes did not deviate from that expected from populations in Hardy-Weinberg equilibrium.
Table 2

Allele and genotype frequencies of RANTES, IL-8, MCP-1 and IL-1α polymorphisms in SLE patients and healthy controls.

 

SLE patients

Controls

P

OR (95%CI)

RANTES -403

n

%

n

%

  

Genotypes

      

GG

369

73.8

333

69.3

0.1

 

GA

113

22.6

135

28

0.04

0.75 (0.55–1.01)

AA

18

3.6

13

2.7

0.4

 

Alleles

      

G

851

85

801

83.3

  

A

149

15

161

16.7

0.2

 

RANTES R3

n

%

n

%

  

Genotypes

      

CC

326

73.8

340

77.6

0.06

 

CT

104

23.5

90

20.6

0.3

 

TT

12

2.7

8

1.8

0.4

 

Alleles

      

C

756

85.5

770

88

  

T

128

14.5

106

12

0.1

 

IL-8 -353

n

%

n

%

  

Genoypes

      

AA

126

28.7

125

30.3

0.6

 

AT

215

49

194

47.1

0.5

 

TT

98

22.3

93

22.6

0.9

 

Alleles

      

A

467

53.2

444

53.8

  

T

411

46.8

380

46.2

0.7

 

IL-8 +781

n

%

n

%

  

Genotypes

      

CC

164

35

143

33.3

0.6

 

CT

238

51

221

51.5

0.8

 

TT

65

14

65

15.2

0.6

 

Alleles

      

C

566

60.6

507

59.1

  

T

368

39.4

351

40.9

0.5

 

IL-1α -889

n

%

n

%

  

Genotypes

      

CC

220

52.7

209

49.7

0.4

 

CT

164

39.3

166

39.5

0.9

 

TT

33

7.9

45

10.7

0.2

 

Alleles

      

C

604

72.4

584

69.5

  

T

230

27.6

256

30.5

0.2

 

MCP-1 -2518

n

%

n

%

  

Genotypes

      

AA

238

57.2

250

58.5

0.6

 

AG

173

35

154

36

0.7

 

GG

39

7.8

23

5.4

0.1

 

Alleles

      

A

739

74.6

654

76.6

  

G

251

25.4

200

23.4

0.3

 

RANTEStyping

Genotyping of RANTES -403 G/A and R3 T/C was performed in 500 and 442 SLE patients and 481 and 438 healthy controls, respectively (table 2). No statistically significant differences were observed when the allele and genotype distribution was compared between SLE patients and healthy controls. Also, we found no association for the two marker haplotypes (table 3).
Table 3

Haplotype frequencies for RANTES and IL-8 polymorphisms in SLE patients and controls.

Gene

Haplotype

SLE patients

Healthy controls

P value

OR (95%CI)

RANTES

 

-403A/R3C

25 (5.7)

25 (5.8)

ns

 
 

-403A/R3T

50 (11.3)

40 (9.3)

ns

 
 

-403G/R3C

355 (80.7)

356 (83.4)

ns

 
 

-403G/R3T

10 (2.3)

6 (1.5)

ns

 

IL-8

 

-353T/+781C

69 (8.6)

48 (6.2)

0.08

1.41 (0.94–2.10)

 

-353T/+781T

316 (39.2)

303 (39.4)

ns

 
 

-353A/+781C

403 (50)

406 (52.7)

ns

 
 

-353A/+781T

18 (2.2)

13 (1.7)

ns

 

IL-8typing

IL-8 -353 T/A and +781 C/T was genotyping in 439 and 467 SLE patients and 412 and 429 healthy controls, respectively for each polymorphism. We found a similar distribution in the allele and genotype frequencies between SLE patients and controls for both genetic variants. The haplotype estimation for the -353 T/A and +781 C/T IL-8 polymorphisms revealed a strong degree of linkage disequilibrium between the two variants (D' = 0.9) and showed a slight but non-significant increase of the -353T-+781C haplotype in SLE patients (8.5% vs 6.2%, P = 0.08, OR = 1.41, 95%CI = 0.94–2.10) (Table 3).

IL-1αtyping

IL-1α -889 was typing in 417 SLE patients and 420 healthy controls. We did not find any significant difference when allele and genotype frequencies were compared between SLE patients and healthy controls.

MCP-1typing

Table 2 show the allele and genotype distribution of the MCP-1 -2518 A/G polymorphism in 450 SLE patients and 427 controls. No significant differences in the allele and genotype frequencies of the MCP-1 -2518 A/G polymorphism were found between SLE patients and controls.

In addition, available clinical features of patients with SLE were analysed for possible association with the different alleles or genotypes of these polymorphisms. When we stratified SLE patients according to the presence of renal involvement, no statistically significant differences were observed in the distribution of RANTES -403, RANTES R3, IL-1α -889 and MCP-1 -2518 polymorphisms between SLE patients with and without lupus nephritis (table 4). Regarding IL-8 polymorphisms, the AT -353 genotype and the -353T/+781C haplotype showed an increased among lupus patients without nephritis compared with patients with nephritis (39.2% vs 49.4%, P = 0.03, OR = 0.66, 95%CI = 0.44–0.99 for AT -353 genotype) (5.7% vs 10%, P = 0.05, OR = 0.55, 95%CI = 0.28–1.05 for -353T/+781C haplotype) (table 4).
Table 4

Relationship between RANTES, IL-8, MCP-1 and IL-1α polymorphisms and the presence of nephritis in SLE Spanish patients.

 

SLE with nephritis

SLE without nephritis

P

OR (95%CI)

RANTES -403

n

%

n

%

  

Genotypes

      

GG

136

73.5

230

73

0.9

 

GA

44

23.8

71

22.5

0.7

 

AA

5

2.7

14

4.4

0.3

 

Alleles

      

G

54

14.6

99

15.7

  

A

316

85.4

531

84.3

0.6

 

RANTES R3

n

%

n

%

  

Genotypes

      

CC

89

77.4

225

68.8

0.08

 

CT

23

20

92

28.1

0.1

 

TT

3

2.6

10

3

0.8

 

Alleles

      

C

201

87.4

542

82.9

  

T

29

12.6

112

12.1

0.1

 

IL-8 -353

n

%

n

%

  

Genoypes

      

AA

47

26.7

59

22.4

0.3

 

AT

69

39.2

130

49.4

0.03

0.66 (0.44–0.99)

TT

60

34.1

74

28.2

0.2

 

Alleles

      

A

163

46.3

248

47.2

  

T

189

53.7

278

52.8

0.8

 

IL-8 +781

n

%

n

%

  

Genotypes

      

CC

74

39.6

99

35.3

0.3

 

CT

85

45.4

151

54

0.07

 

TT

28

15

30

10.7

0.2

 

Alleles

      

C

233

62.3

349

62.3

  

T

141

37.7

211

37.7

0.9

 

IL8 -353T/+781C

Haplotypes

      

-353T/+781C

15

5.7

39

10

0.05

0.55 (0.21–8.05)

-353T/+781T

104

39.7

149

38.2

0.7

 

-353A/+781C

140

53.4

193

49.5

0.3

 

-353A/+781T

3

1.2

9

2.3

0.3

 

IL-1α -889

      

Genotypes

      

CC

72

49.3

138

50.9

0.7

 

CT

59

40.4

115

42.4

0.7

 

TT

15

10.3

18

6.7

0.2

 

Alleles

      

C

203

69.5

391

72.1

  

T

89

30.5

151

27.9

0.4

 

MCP-1 -2518

Genotypes

      

AA

86

54.4

170

58.2

0.4

 

AG

61

38.6

100

34.2

0.3

 

GG

11

7

22

7.5

0.8

 

Alleles

      

A

233

73.7

440

75.3

  

G

83

26.3

144

24.7

0.6

 

Similarly, no significant differences were observed between all these genetic variants and the following variables: sex, age at onset, articular involvement, cutaneous lesions, photosensitivity, hematological alterations, neurological disorders and serositis (data not shown).

Discussion

In this work, we have tested six functional polymorphisms of four strong candidate genes for association with SLE. No evidence of association was detected for RANTES (-403 G/A, R3 T/C),IL-8 (-353 A/T, +781 C/T), IL-1α (-889C/T), and MCP-1 (-2518 G/A) polymorphisms. However, a significant association was observed for the IL-8 haplotype with SLE nephritis, which cannot be considered as significant after correction for multiple comparisons.

All these genes have been previously associated with susceptibility and development to several autoimmune disorders, included SLE [16, 2127]. For example, recent studies in Asian populations found another RANTES polymorphism (-28C/G) to be associated with increased risk of developing SLE, but failed to detect any association of RANTES -403 polymorphisms with SLE [22, 23]. We did not test the -28C/G variant as -28G allele is relatively uncommon in Caucasians [28].

The genetic variant IL-8 -845C showed a high association to severe lupus nephritis (LN) in an African American population [16], but also this allele has a very low frequency in Caucasian populations [16, 29]. The trend of association that we have found between the haplotypes and LN and the reported association of other IL-8 variants this African American population, shows that variants in this chemokine may have a minor influence on the risk of developing nephritis in SLE patients.

Similar observation could be made for the reported association of the IL-1α -889C/T variant to SLE in a White and African American populations from United States, which we failed to replicate [30]. With regard to the MCP-1 -2518 polymorphism, an American study showed that an A/G or G/G genotype may predispose to the development of SLE and further indicated that SLE patients with these genotypes may be at higher risk of developing LN [3].

The fact that we do not observe an association and fail to confirm some previous studies may be caused by a Type II error (false-negative). This is however unlikely because our sample has more than 80% power to detect the relative risk similar to the other studies at the 5% significance level. Furthermore, the genotype frequencies did not differ from Hardy-Weinberg expectations, and allele and genotype frequencies in our Spanish population are similar to those reported previously in other Caucasian populations [16, 26, 31, 32]. The failure to replicate reported associations is a common event in the search for genetic determinants of complex diseases, due either to genuine population heterogeneity or a different sort of bias [33]. The lack of replication in our population may alternatively be explained by a different racial composition of that study from ours, or that presence of environmental factors to which the Asian, American, and African populations, but not the Spanish population, are exposed. In addition, genetic differences are known to exist between the different ethnic groups, such as, African American and Caucasians.

Conclusion

In conclusion, our results suggest that functional genetics variation in RANTES, IL-8, IL-1α, and MCP-1 do not play a major role in SLE susceptibility in the Spanish population.

Notes

Declarations

Acknowledgements

This work was supported by grant SAF03-3460 from Plan Nacional de I+D+I, and in part by the Junta de Andalucía, grupo CTS-180. We thank Sasha Zhernakova for her excellent technical assistance. Finally, we thank Cisca Wijmenga for support.

Authors’ Affiliations

(1)
Instituto de Parasitología y Biomedicina López-Neyra, CSIC
(2)
Servicio de Medicina Interna, Hospital Virgen de las Nieves
(3)
Servicio de Medicina Interna, Hospital Clínico San Cecilio
(4)
Servicio de Medicina Interna, Hospital Carlos-Haya
(5)
Servicio de Reumatología, Hospital Virgen de la Victoria
(6)
Servicio de Medicina Interna, Hospital Virgen del Rocio
(7)
Servicio de Inmunología, Hospital Virgen del Rocío
(8)
Department of Biomedical Genetics, Utrecht University Medical Centre

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  34. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/7/48/prepub

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© Sánchez et al; licensee BioMed Central Ltd. 2006

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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