BioMed Research International
Volume 2017 (2017), Article ID 1274960, 8 pages
https://doi.org/10.1155/2017/1274960

Research Article

The Association of Chemokine Gene Polymorphisms with VKH and Behcet’s Disease in a Chinese Han Population

Yang Huang,¹ Hongsong Yu,¹ Qingfeng Cao,¹ Jing Deng,¹ Xinyue Huang,¹ Aize Kijlstra,² and Peizeng Yang¹

¹The First Affiliated Hospital of Chongqing Medical University, Chongqing Key Laboratory of Ophthalmology and Chongqing Eye Institute, Chongqing, China
²University Eye Clinic Maastricht, Maastricht, Netherlands

Correspondence should be addressed to Peizeng Yang; peizengycmu@126.com

Received 20 January 2017; Revised 4 April 2017; Accepted 12 April 2017; Published 14 May 2017

Academic Editor: Paolo Spagnolo

Copyright © 2017 Yang Huang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract.

To investigate the association of chemokine gene polymorphisms and Behcet’s disease (BD) and Vogt Koyanagi Harada (VKH) disease in a Chinese Han population. A case-control study was performed. Three hundred and seventy-one BD patients, 371 VKH disease patients, and 605 healthy controls were recruited to determine genetic variants of 26 SNPs in 12 chemokine genes with iPLEX Gold genotyping assay and Sequenom MassARRAY or TaqMan SNP assays. In this study, values showed a weak association of five SNPs of five genes in BD and three SNPs of three genes in VKH disease. However, after Bonferroni correction, the 26 investigated SNPs showed no significant differences in genetic variants, including genotype and allele frequencies, between BD or VKH disease patients and healthy individuals. Haplotype analysis for the chemokine genes showed a significant association with the TC haplotype of CXCL12 in VKH. Stratified gender analysis and genotype-phenotype analysis were conducted to analyze the association of the 26 SNPs of 12 chemokine genes with BD and VKH disease. However, no significant association was observed after Bonferroni correction. This study showed no association of 26 SNPs in 12 chemokine genes with both BD and VKH disease in a Chinese Han population.

1. Introduction

Uveitis is an intraocular inflammatory disease causing severe visual impairment worldwide [1]. In China, Behcet’s disease (BD) and Vogt-Koyanagi Harada (VKH) disease have the highest incidence in uveitis entities. BD is a chronic, relapsing, multisystemic inflammatory disorder, and its classical clinical characters include oral aphthae, genital ulcers, and recurrent iridocyclitis with hypopyon, which is probably due to an autoimmune response [2]. VKH disease is a multisystem autoimmune disease with a hallmark of diffuse granulomatous uveitis accompanied with poliosis, vitiligo, alopecia, and central nervous system abnormalities [3]. Various genes have been demonstrated to be relevant to different types of uveitis, comprising HLA-B27, HLA-A29, HLA-B51, HLA-DR4, IL-10, STAT4, STAT3, and UBAC2 [4–6] which suggested genetic factors are involved in the occurrence and development of uveitis.

Chemokines are a class of proinflammatory cytokines that are able to attract and activate the migration of circulating leukocytes under both physiological and pathological conditions [7]. According to the related structure and function, four subfamilies of human chemokines are classified: CC chemokines, CXC chemokines, CX3C family, and C family. Previous studies showed that chemokines are involved in various inflammatory and autoimmune diseases [8, 9]. Chemokines also contribute to the pathogenesis of uveitis, and previous researches showed that a higher chemokine production might be responsible for the more severe clinical manifestations in Behcet’s disease [10]. A comparison of Japanese VKH disease patients with controls indicated a dramatic decrease in the chemokine CSF-CCL2/MCP-1 [11].

Genetic variations of chemokine genes have been demonstrated responsible for the induction of chronic inflammation [7]. RANTES (CCL5) is associated with diabetes mellitus type 1 both genetically and functionally [12]. In the onset and development of childhood Idiopathic Thrombocytopenic Purpura, the polymorphism of SDF-1 (CXCL12) gene may be implicated [13]. Intron 1 of the CXCL9 gene (rs2276886) polymorphism may be closely related to pediatric Crohn’s disease [14]. Among Chinese Han individuals, genetic variations of CXCL12-3′G801A are involved in the pathogenesis of systemic lupus erythematosus [15]. Only few studies have analyzed the association of uveitis with chemokine gene polymorphisms. In Caucasian patients with HLA-B27 associated acute anterior uveitis, the CCL2-2518G allele was found significantly increased [16] and IL-8 (CXCL8) gene polymorphisms may affect susceptibility to BD in Turkey [17]. However, the association between other chemokine gene polymorphisms with uveitis is largely unknown and has been addressed recently by our group. Earlier we reported that CCL2 polymorphisms were protective for BD [18]. In this study, we expanded the amount of chemokines SNPs and also included VKH disease patients. The results show that none of the other chemokine genes polymorphisms showed an association with BD or VKH disease in the Chinese Han population.

2. Material and Methods

2.1. Study Population

Our study recruited 371 BD and 371 VKH disease patients and 605 healthy individuals which are all from Chinese Han population in the First Affiliated Hospital of Chongqing Medical University from January 2009 to April 2015 (Chongqing, China). According to race (Chinese Han) and geography, patients and the controls were matched. Diagnosis for BD and VKH disease followed the standard of the International Study Group for BD [19] and First International Workshop for VKH disease [20], respectively. The local research ethics committee approved the study and all the recruited individuals signed informed consent before donating blood samples. The Declaration of Helsinki adhered to the tenets.

2.2. Single Nucleotide Polymorphism (SNP) Selection

Screening of target chemokine gene SNPs was according to previously published studies which showed a positive association with other autoimmune and inflammatory diseases. Linkage disequilibrium (LD) data from the Han Chinese Hap Map database were taken into account. Twenty-seven SNPs of twelve genes with a minor allele frequency > 0.05 in Han Chinese were selected. These 27 SNPs in 12 chemokine genes, included 4 SNPs (rs1024610, rs1024611, rs13900, and rs4586) of CCL2 [21, 22], 5 SNPs (rs4251719, rs2306630, rs2107538, rs9355610, and rs2280788) of CCL5 [12, 23, 24], 1 SNP (rs854680) of CCL16 [25], 2 SNPs (rs223828 and rs223895) of CCL17 [26–28], 3 SNPs (rs951005, rs2492358, and rs2812378) of CCL21 [29–31], 1 SNP (rs4359426) of CCL22 [32], 2 SNPs (rs2302004 and rs2302005) of CCL24 [33], 3 SNPs (rs2227306, rs2227543, and rs4694178) of CXCL8 [34], 2 SNPs (rs2276886 and rs2869460) of CXCL9 [14, 35], 1 SNP (rs2869462) of CXCL10 [35], 2 SNPs (rs1801157 and rs2839693) of CXCL12 [13, 15], and 1 SNP (rs2277680) of CXCL16 [36]. We excluded rs1024611 of CCL2, since a study concerning this gene had been reported previously by our group [18].

2.3. DNA Extraction and Genotyping

Peripheral blood of the three experimental groups including BD and VKH disease patients and the controls was subjected to genomic DNA extraction with the QIAmp DNA Blood Mini Kit (Qiagen Inc., Valencia, CA, USA) and the DNA was stored at −80°C. The Applied Biosystems 7500 Real-Time PCR system was utilized to genotype CCL17/rs223828 (TagMan assay ID: C_30530263_10) by the TaqMan SNP Genotyping Assay (Applied Biosystems, Foster City, CA, USA). Genotype identification of the other 25 SNPs was conducted with the iPLEX Gold genotyping assay and Sequenom MassARRAY (Sequenom, CA, USA). Sequenom SNP Assay Design software version 3.0 was used to design primers of iPLEX reactions. Primer sequences used were shown in Table 1. The protocol and experimental requirements were performed strictly based on the instructions.

Table 1: Primers applied in the analysis of restriction fragment length polymorphism (RFLP) in the chemokine genes.

1st-PCRP
2nd-PCRP
UEP_SEQ

CCL2

    rs1024610
ACGTTGGATGTTCTTCCTAGGCCATCTCAC
ACGTTGGATGATTGAATGCGGTCCACCAAG
CATGGTAAAGGATGCACTAAC

    rs13900
ACGTTGGATGCTTAAGGCATAATGTTTCAC
ACGTTGGATGCCCAAGAATCTGCAGCTAAC
GGCCATAGCTTTCCCCAGACACC

    rs4586
ACGTTGGATGAGCTTCTTTGGGACACTTGC
ACGTTGGATGATGCAATCAATGCCCCAGTC
CTCCCAGTCACCTGCTG

CCL5

    rs4251719
ACGTTGGATGTCGTAGGTCCAGACACAAAG
ACGTTGGATGCTTGAGTGATAAAGTGCAGG
AGTGATAAAGTGCAGGTGTTTTA

    rs2306630
ACGTTGGATGTCTTTCTGGAACCTTGTGGG
ACGTTGGATGTGTGCCTCAATTGATCCCTG
AAGCTGAAAAACAAGGTTCTCT

    rs2107538
ACGTTGGATGACTGTATATCCAGAGGACCC
ACGTTGGATGTGAGTCTTCAAAGTTCCTGC
CTGCTTATTCATTACAGATCTTA

    rs9355610
ACGTTGGATGAGGTTAGCACACCAGTAGAG
ACGTTGGATGAATGCACCAGAACGCAAAGC
TGGCTCAGAATACTAGAAATTAG

    rs2280788
ACGTTGGATGCTTATGATACCGGCCAATGC
ACGTTGGATGCTCAGGCTGGCCCTTTATAG
GCCCTTTATAGGGCCAGTT

CCL16

    rs854680
ACGTTGGATGAAGTCAAACGGTCCAGCAAC
ACGTTGGATGCCACATGATTGAGCTCACAC
GTGAGCTCACACTCTTTC

CCL17

    rs223895
ACGTTGGATGCTGGTAATCACTGCCCAATG
ACGTTGGATGATCCTCAGCAATGTGGCTTC
TTGGCTTCCAGCTCTG

CCL21

    rs951005
ACGTTGGATGGCTCTTCTTGAGTTTGTGCG
ACGTTGGATGTGGGAAAGGGACCAACCATC
CAAACCTATATAGGACCCACA

    rs2492358
ACGTTGGATGGATCTGTTCAGTGTCAAGAG
ACGTTGGATGAGTCCGACATGCTTTTACTG
TTTTACTGTAACTTGTCACTT

    rs2812378
ACGTTGGATGCAGGCCCAGACATATTCAAC
ACGTTGGATGCTGAAAGCTGGATTTGCTGG
CCCCACTTATCTCAAACTAA

CCL22

    rs4359426
ACGTTGGATGCTATGTCCCTTTGCAGACAC
ACGTTGGATGAGTTGCTTGAAGCGCCACAG
GGCAGTCTGTAGGCGA

    rs2302004
ACGTTGGATGAACACCGCCAGTCCATTCAC
ACGTTGGATGATCATCCCTACGGGTAAGAC
CGCTGGGGAAAGGG

    rs2302005
ACGTTGGATGTGTTTGGTGCAGGGTTCAAG
ACGTTGGATGACAAAGAACATGCAGCAGGG
CCTAGAAGAGGAGAGAGA

CXCL8

    rs2227306
ACGTTGGATGCCCTTGACCTCAGTTAGTTC
ACGTTGGATGGGTATCACAGAGGATTATGC
ACTCTAACTCTTTATATAGGAAGT

    rs2227543
ACGTTGGATGCCTGGGCAAACTATGTATGG
ACGTTGGATGATCGTCATTAGGTATCTGCC
AGAAGCAATAGTGAGTTTGTTGTACT

    rs4694178
ACGTTGGATGTTTCTGCCACAAAGACATCC
ACGTTGGATGCCTCTCAAGAACAAACTTGG
TCTCAAGAACAAACTTGGAATTAA

CXCL9

    rs2276886
ACGTTGGATGGTTCTGCCTGCATTGAAGAG
ACGTTGGATGGTGTTTGACTTGGCAGATCG
TGAGAAGCTTTTATGACTGA

    rs2869460
ACGTTGGATGCTGCCCGAATATTACACCTG
ACGTTGGATGAGCGTGGAGTCTCTAAGAAG
GTTGTACACTTGATGTACACTTTA

CXCL10

    rs2869462
ACGTTGGATGCACTGTTGTATTACTGAGAC
ACGTTGGATGGAACATTTCCTTGTGTCTAC
TCTCATATTTCTAGCCTCTT

CXCL12

    rs1801157
ACGTTGGATGAAGCCTAGTGAAGGCTTCTC
ACGTTGGATGTGCTGCCTCAGCTCAGGGTA
ACAGAAGAGGCAGACC

    rs2839693
ACGTTGGATGCTCTGTTGCTCTCCATTCTC
ACGTTGGATGATCAGGAGCAAATACGCCAG
AAGACAGGATGCTCTAGG

CXCL16

    rs2277680
ACGTTGGATGGTGGGACCAGCATTTTTTTC
ACGTTGGATGCTCACTCGTCCCAATGAAAC
CCACAGTCTGGCAG

2.4. Statistical Analysis

Hardy-Weinberg equilibrium (HWE) analysis was carried out by the Chi-square () test in healthy samples while the genotype frequency was estimated by direct counting. No SNP significantly deviated from HWE (). Fisher’s exact test or test was applied to evaluate the differences in allele and genotype frequencies of all SNPs between patients and healthy controls using SPSS (version 17.0; SPSS Inc., Chicago, IL). The Bonferroni method was conducted to perform correction for multiple comparisons whereby the value was multiplied with the number of comparisons ( corrected ()). It was considered to be significant when . In those genes having more than one SNP we also performed a haplotype analysis. Haplotypes with a frequency of 0.03 or larger were included in the analysis [37, 38]. values for haplotypes were multiplied with the number of haplotypes in each gene. was considered as significant. Gene-gene interaction analysis was performed using MDR software (MDR 3.0.2 obtained from https://sourceforge.net/projects/mdr/).

3. Results

3.1. Clinical Features

The demographics and clinical symptoms of BD and VKH disease and demographics of controls are all showed in Table 2. The healthy cohort is comprised of 321 men and 284 women, who were on average years old. The BD patients consisted of 371 subjects (326 men and 45 women), years old on average. The VKH disease group contained 371 subjects (204 men and 167 women), and the patients were on average years old.

Table 2: Clinical features, age, and sex distribution of patients and controls.

Clinical features
Total
%

Patients with BD
371

Mean age ± SD

Male
326
87.9

Female
45
12.1

Uveitis
358
96.5

Oral ulcer
349
94

Genital ulcer
208
56.1

Skin lesion
272
73.3

Arthritis
53
14.3

Pathergy reaction
8
2.2

Patients with VKH disease
371

Mean age ± SD

Male
204
55

Female
167
45

Sunset glow fundus
182
49

Headache
157
42.3

Tinnitus
146
39.4

Vitiligo
123
33.2

Alopecia
136
36.7

Gray hair
58
15.6

Controls
605

Mean age ± SD

Male
321
53.1

Female
284
46.9

BD = Behcet’s disease, SD = standard deviation; VKH = Vogt-Koyanagi-Harada.

3.2. Chemokine Genotyping Results

Twenty-six SNPs covering 12 chemokine genes (CCL2, CCL5, CCL16, CCL17, CCL21, CCL22, CCL24, CXCL8, CXCL9, CXCL10, CXCL12, and CXCL16) were genotyped successfully and all SNPs of controls met the Hardy-Weinberg equilibrium. There was no significant difference in allelic and genotypic frequencies for all the 26 SNPs in the patients of BD or VKH disease compared with the controls (Supplemental Tables and in Supplementary Material available online at https://doi.org/10.1155/2017/1274960). However, values showed a weak association of five SNPs of five genes in BD and three SNPs of three genes in VKH disease (Tables 3 and 4). Compared with BD patients, the frequency of the CCL5/rs2107538 CC genotype (, OR = 1.309, and 95% CI = 1.002–1.710) was decreased and the CCL5/rs2107538 CT genotype frequency (, OR = 0.76, and 95% CI = 0.583–0.991) was increased in the controls. A higher frequency of CCL17/rs223828 C allele (, OR = 1.582, and 95% CI = 1.048–2.389) and a lower TT genotype frequency (, OR = 0.795, and 95% CI = 0.655–0.965) were found in the patients of BD. In CCL22/rs4359426, the frequency of the AA genotype (, OR = 3.071, and 95% CI = 1.227–7.685) was increased in BD patients. The CXCL10/rs2869462 showed an increased frequency of the CC genotype and C allele (, OR = 1.347, and 95% CI = 1.023–1.774; , OR = 1.313, and 95% CI = 1.081–1.595, resp.), and CXCL12/rs1801157 showed a decreased frequency of the CT genotype (, OR = 0.761, and 95% CI = 0.581–0.996) in BD patients. In VKH disease patients, there was an increased frequency of the CCL5/rs9355610 A allele (, OR = 0.805, and 95% CI = 0.662–0.979) and CXCL8/rs2227543 CT genotype (, OR = 0.72, and 95% CI = 0.552–0.940). In CXCL12/rs1801157, a weak association was detected in the C allele and CC and CT genotype in VKH disease (, OR = 1.327, and 95% CI = 1.069–1.647; , OR = 1.556, and 95% CI = 1.190–2.033; , OR = 0.627, and 95% CI = 0.476–0.826). However, after correction for multiple comparisons, all associations described above lost statistical significance.

Table 3: Genotype and allele frequencies of five chemokine genes’ polymorphism in BD and healthy controls.

Gene
SNP

BD (%)
Controls (%)
value
value
OR
95% CI

CCL5
rs2107538
Total sample
368
556

CC
165 (0.448)
213 (0.383)
0.048
NS
1.309
1.002–1.710

CT
155 (0.421)
272 (0.489)
0.042
NS
0.760
0.583–0.991

TT
48 (0.130)
71 (0.128)
0.903
NS
1.025
0.692–1.517

C
485 (0.659)
698 (0.628)
0.170
NS
1.146
0.943–1.393

T
251 (0.341)
414 (0.372)

0.873
0.718–1.060

CCL17
rs223828
Total sample
371
604

CC
155 (0.418)
287 (0.575)
0.081
NS
0.793
0.611–1.029

CT
167 (0.450)
264 (0.437)
0.690
NS
1.054
0.813–1.368

TT
49 (0.132)
53 (0.088)
0.028
NS
1.582
1.048–2.389

C
477 (0.643)
838 (0.694)
0.020
NS
0.795
0.655–0.965

T
265 (0.357)
370 (0.306)

CCL22
rs4359426
Total sample
365
546

AA
14 (0.038)
7 (0.013)
0.012
NS
3.071
1.227–7.685

AC
93 (0.255)
134 (0.245)
0.749
NS
1.051
0.774–1.427

CC
258 (0.707)
405 (0.742)
0.246
NS
0.839
0.624–1.128

A
121 (0.166)
148 (0.136)
0.075
NS
1.267
0.976–1.645

C
609 (0.834)
944 (0.864)

0.789
0.608–1.024

CXCL10
rs2869462
Total sample
360
535

CC
149 (0.414)
184 (0.344)
0.034
NS
1.347
1.023–1.774

CG
160 (0.444)
243 (0.454)
0.773
NS
0.961
0.735–1.258

GG
51 (0.142)
108 (0.202)
0.210
NS
0.653
0.454–0.939

C
458 (0.636)
611 (0.571)
0.006
NS
1.313
1.081–1.595

G
262 (0.364)
459 (0.429)

0.761
0.627–0.925

CXCL12
rs1801157
Total sample
371
547

CC
207 (0.558)
271 (0.495)
0.063
NS
1.285
0.987–1.675

CT
139 (0.375)
241 (0.441)
0.047
NS
0.761
0.581–0.996

TT
25 (0.067)
35 (0.064)
0.838
NS
1.057
0.621–1.798

C
553 (0.745)
783 (0.716)
0.163
NS
1.162
0.941–1.435

T
189 (0.255)
311 (0.284)

0.860
0.697–1.063

Table 4: Genotype and allele frequencies of three chemokine genes’ polymorphism in VKH and healthy controls.

Gene
SNP

VKH (%)
Controls (%)
value
value
OR
95% CI

CCL5
rs9355610
Total sample
370
555

AA
97 (0.262)
138 (0.249)
0.644
NS
1.074
0.794–1.451

AG
188 (0.508)
273 (0.492)
0.629
NS
1.067
0.820–1.388

GG
85 (0.230)
144 (0.259)
0.305
NS
0.851
0.626–1.158

A
282 (0.516)
549 (0.495)
0.029
NS
0.805
0.662–0.979

G
358 (0.484)
561 (0.505)

1.242
1.022–1.511

CXCL8
rs2227543
Total sample
364
552

CC
146 (0.401)
187 (0.339)
0.055
NS
1.307
0.994–1.719

CT
155 (0.426)
280 (0.507)
0.016
NS
0.720
0.552–0.940

TT
63 (0.173)
85 (0.154)
0.442
NS
1.15
0.805–1.643

C
447 (0.614)
654 (0.592)
0.355
NS
1.095
0.904–1.326

T
281 (0.386)
450 (0.408)

0.914
0.754–1.106

CXCL12
rs1801157
Total sample
368
547

CC
223 (0.605)
271 (0.495)
0.001
NS
1.566
1.198–2.048

CT
122 (0.331)
241 (0.441)

NS
0.637
0.478–0.829

TT
23 (0.062)
35 (0.064)
0.928
NS
0.975
0.566–1.679

C
568 (0.771)
783 (0.716)
0.008
NS
1.343
1.081–1.668

T
168 (0.228)
311 (0.284)

0.745
0.600–0.925

3.3. Haplotype Analysis

The haplotypes of chemokine genes (CCL2, CCL5, CCL17, CCL21, CCL24, CXCL8, CXCL9, and CXCL12) having more than one SNP were analyzed using the website http://analysis.bio-x.cn/myAnalysis.php. The haplotype TC of the CXCL12 gene including two SNPs (rs1801157 and rs2839693) showed a significant association with VKH (, , OR = 0.745, and 95% CI = 0.599–0.927) (Table 5) compared with healthy controls. The other tested haplotypes failed to show an association with either BD or VKH.

Table 5: Haplotype analysis of CXCL12 gene polymorphisms in VKH.

Haplotype
VKH (%)
Control (%)

value
value
OR
95% CI

CC
466.03 (0.633)
630.97 (0.590)
2.875
0.089
NS
1.182
0.974–1.435

CT
104.97 (0.143)
135.03 (0.126)
0.916
0.338
NS
1.143
0.869–1.504

TC
164.97 (0.224)
297.03 (0.278)
6.959
0.008
0.032
0.745
0.599–0.927

TT
0.03 (0.000)
6.97 (0.007)

3.4. Stratified Analysis according to Gender and Main Clinical Manifestations of BD and VKH Disease

Stratified analyses were conducted to investigate whether the 26 SNPs have an association with gender and the primary clinical features in BD and VKH disease. BD in our population is more often seen in males and we therefore believe that a gender analysis might also be involved in the genetic predisposition to this disease and a previous study showed that chemokine gene SNPs of both CCL2 gene and CCL5 were more prevalent in males than females with BD [39]. To further confirm whether gender could influence genotype and allele frequencies in both diseases we performed the gender stratified study in these two diseases. We chose clinical manifestations with the frequency of approximately 50%. These included the presence of genital ulcers in BD and sunset glow fundus in VKH disease, respectively. Following Bonferroni correction, no association was observed after stratification by gender (Supplemental Tables and ). Also no significant differences were detected in these SNPs after stratifying VKH with sunset glow fundus or not. Additionally, no significant association was observed when BD was stratified by genital ulcer. MDR analysis was performed to test the gene-gene (epistatic effect) analysis interaction among 26 SNPs of 12 chemokine genes and this analysis showed that no gene-gene interaction existed in these two diseases. (Supplemental Tables and ).

4. Discussion

In the present study, we described the genotyping of 371 BD and 371 VKH patients and 605 controls from Chinese Han population for twenty-six SNPs in twelve chemokine genes. The AA genotype of MCP-1-2518 (rs1024611/CCL2) has been shown by our previous research to have a protective association with BD in the Chinese Han population [18]. Extension of this latter study with other chemokine polymorphisms and including another uveitis entity (VKH) did not reveal any new associations, although haplotype analysis did show that the haplotype TC of the CXCL12 gene including rs1801157 and rs2839693 shows a significant association with VKH.

Behcet’s disease, which is considered an autoinflammatory disorder, is characterized by posterior or generalized uveitis with a chronic nature and with recurrent episodes [2]. VKH disease is considered as a multisystem disorder caused by an autoimmune response against melanocyte associated antigens [3]. The attraction of leukocytes to tissues is an important feature of inflammation and is mediated by the local release of chemokines [40]. Genetic variation in the genes encoding these chemokines may affect their function and may be associated with disease predisposition. Several studies have reported investigations concerning the association of a limited number of chemokine genetic variations in patients with different uveitis entities [21, 39, 41], but a large scale analysis on chemokine gene associations with BD or VKH disease has not been reported.

Despite the fact that the 26 SNPs chosen for our study have been proved to be associated with several other immune-mediated diseases, we did not detect any significant association between these SNPs and the two uveitis entities, BD or VKH disease. An exception is the association of the haplotype TC of the CXCL12 gene including rs1801157 and rs2839693 with VKH, which suggests that CXCL12 polymorphisms might be a risk factor contributing to VKH disease in the Chinese population. Our study confirms earlier data presenting the absence of an association between the chemokine genes rs1024610/CCL2 and rs2280788/rs2107538/CCL5 with Behcet’s disease or retinal vasculitis in patients from UK [39]. Others showed that the frequency of the T allele of MCP-1 63555 (rs1024610/CCL2) was significantly associated with idiopathic anterior uveitis in Caucasian patients [21], which could not be shown in the uveitis entities we studied. This discrepancy may be due to differences in the uveitis entity studied or due to ethnic effects.

Selection of candidate SNPs is a crucial step for a gene variation study. In our study, 26 SNPs covering 12 chemokine genes (CCL2, CCL5, CCL16, CCL17, CCL21, CCL22, CCL24, CXCL8, CXCL9, CXCL10, CXCL12, and CXCL16) were selected on the basis of earlier association studies in autoimmune diseases, including type 1 diabetes [12], pediatric Crohn’s disease [14], and systemic lupus erythematosus [15]. It should be noted that composition and stratification of recruiting population may conclude to different results of an association study. To make sure that our data and results were valid, a series of efforts were made. First of all, the BD patients were diagnosed in strict accordance with the criteria of the International Study Group for BD while the VKH patients were diagnosed in strict accordance with the First International Workshop criteria of VKH disease. Any doubt or uncertainty in patient diagnosis is not allowed. Beyond that, to avoid ethnic bias, BD and VKH disease patients from other ethnic populations other than Chinese Han population were excluded.

Our study has several limitations. We only chose SNPs that have been previously reported to be related to autoimmune and inflammatory diseases, thus other unknown SNPs of chemokine genes with potential association with BD and VKH disease might be excluded. Furthermore, we studied only two common types of uveitis, with all the participants from Chinese Han population. Association of chemokine genes with other types of uveitis or different ethnic populations might also exist and awaits further investigation.

5. Conclusions

A large scale analysis of the role of chemokine genes only shows an association of CCL2 with BD but no effect on predisposition to VKH in Chinese Han population. The haplotype TC of the CXCL12 gene however did show a significant association with VKH compared with healthy controls.

Conflicts of Interest

The authors declare no conflicts of interest.

Acknowledgments

The authors would like to thank all donors enrolled in the present study. This work was supported by Natural Science Foundation Major International (Regional) Joint Research Project (81320108009), National Natural Science Foundation Project (31370893), Chongqing Key Laboratory of Ophthalmology (CSTC, 2008CA5003), National Key Clinical Specialties Construction Program of China, Key Project of Health Bureau of Chongqing (2012-1-003), Chongqing Science & Technology Platform and Base Construction Program (cstc2014pt-sy10002), and the Major Research Development Program of China (2016YFC0904000).

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