August 2010
Volume 51, Issue 8
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Immunology and Microbiology  |   August 2010
Cytokine Polymorphism in Noninfectious Uveitis
Author Affiliations & Notes
  • Denize Atan
    From the Clinical Sciences at South Bristol, Bristol Eye Hospital, Bristol, United Kingdom;
  • Samantha Fraser-Bell
    the Clinical Ophthalmology and Eye Health, Central Clinical School, University of Sydney, Sydney Eye Hospital Campus, Sydney, Australia;
  • Jarka Plskova
    the Institute of Medical Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom;
  • Lucia Kuffova
    the Institute of Medical Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom;
  • Aideen Hogan
    the Research Foundation, Royal Victoria Eye and Ear Hospital, Dublin, Ireland;
  • Adnan Tufail
    Moorfields Eye Hospital, London, United Kingdom; and
  • Dara J. Kilmartin
    the Research Foundation, Royal Victoria Eye and Ear Hospital, Dublin, Ireland;
  • John V. Forrester
    the Institute of Medical Sciences, University of Aberdeen, Aberdeen, Scotland, United Kingdom;
  • Jeff Bidwell
    the Department of Cellular & Molecular Medicine, University of Bristol, School of Medical Sciences, Bristol, United Kingdom.
  • Andrew D. Dick
    From the Clinical Sciences at South Bristol, Bristol Eye Hospital, Bristol, United Kingdom;
  • Amanda J. Churchill
    From the Clinical Sciences at South Bristol, Bristol Eye Hospital, Bristol, United Kingdom;
  • Corresponding author: Denize Atan, Clinical sciences at South Bristol, Bristol Eye Hospital, Lower Maudlin Street, Bristol, BS1 2LX, UK; denize.atan@bristol.ac.uk
Investigative Ophthalmology & Visual Science August 2010, Vol.51, 4133-4142. doi:10.1167/iovs.09-4583
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      Denize Atan, Samantha Fraser-Bell, Jarka Plskova, Lucia Kuffova, Aideen Hogan, Adnan Tufail, Dara J. Kilmartin, John V. Forrester, Jeff Bidwell, Andrew D. Dick, Amanda J. Churchill; Cytokine Polymorphism in Noninfectious Uveitis. Invest. Ophthalmol. Vis. Sci. 2010;51(8):4133-4142. doi: 10.1167/iovs.09-4583.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose.: Noninfectious uveitis is a sight-threatening immune-mediated intraocular inflammatory disorder. The inheritance of uveitis in multiplex families and its association with known monogenic and polygenic immunologic disorders suggests that common genetic variants underlie susceptibility to uveitis as well as to other immunologic disorders. TNFA and IL10 are strong candidate genes, given the influence of these cytokines on inflammation, immune tolerance, and apoptosis.

Methods.: The role of 12 polymorphisms spanning the TNFA and IL10 genomic regions was investigated in 192 uveitis patients and 92 population control subjects from four regional centers in the United Kingdom and Republic of Ireland.

Results.: The results demonstrate that uveitis is associated with three haplotype-tagging SNPs (htSNPs) in the IL10 gene: htSNP2 (rs6703630), htSNP5 (rs2222202), and htSNP6 (rs3024490). IL10htSNP2AG/htSNP5TC was the most significantly associated haplotype (P = 0.00085), whereas the LTA+252AA/TNFhtSNP2GG haplotype was protective (P = 0.00031). Furthermore, subgroup analysis showed that the frequency of the TNFd4 allele was higher in patients with nonremitting ocular disease and/or those requiring higher levels of maintenance immunosuppression. Although these associations lost significance after Bonferroni correction, they infer a relationship that may be validated by a larger study.

Conclusions.: Since these variants are implicated in the susceptibility and severity of several immunologic disorders, the results support the hypothesis that common genetic determinants influence shared mechanisms of autoimmunity.

Uveitis is a sight-threatening intraocular inflammatory disorder with a prevalence exceeding 115 per 100,000. 1 Although uveitis itself is localized to the eye, it is a common manifestation of systemic immunologic disease, and is considered part of the immunologic disease continuum. 2  
The hypothesis that common genetic variants underlie susceptibility to uveitis and other immunologic diseases is strongly supported by several lines of evidence: the inheritance of uveitis in multiplex families, 3,4 the association of uveitis with known monogenic (Blau syndrome, neonatal-onset multisystem inflammatory disease) 5,6 and polygenic immunologic disorders (Crohn's disease, sarcoidosis) 7,8 and the varying susceptibility to uveitis of different animal species and strains. 9 Moreover, quantitative trait loci (QTLs) associated with a rat model of uveitis overlap with loci linked to rheumatoid arthritis (RA), multiple sclerosis (MS), and type 1 diabetes mellitus (T1D) in rats and humans. 10 Although there are several different animal models of uveitis, they appear to result in common effector T-cell responses, characterized by the ability to be adoptively transferred with T cells and inhibited by treatment with cyclosporine and other broad-spectrum immunosuppressants. 9 Current evidence suggests that both TH1 and TH17 effector cells can independently induce tissue damage in mouse models of uveitis. 11 In this respect, the central pathogenic role of TH1 and/or TH17 cells in mediating organ-specific autoimmunity is similar to mouse models of other immunologic diseases, such as experimental autoimmune encephalitis (MS) 12 and collagen-induced arthritis (RA). 13 Furthermore, both TH cell types characteristically produce and promote the production of the proinflammatory cytokine tumor necrosis factor alpha (TNF)-α. 
The eye is relatively protected from the immune system by the blood–ocular barrier, the immune-inhibitory environment, and active mechanisms of tolerance involving regulatory CD4+ T cells (Tregs). 14 Resident retinal cells, such as Müller glia and retinal pigment epithelium (RPE), contribute to the microenvironment through the constitutive expression of cytokines, such as TNFα and the counterregulatory interleukin (IL)-10, and there is evidence that differences between rodent strains in the constitutive or stimulated levels of expression of these cytokines by resident Müller glia, RPE, microglia, and infiltrating T cells, determines their varied susceptibility to the induction of uveitis. 1518 Furthermore, depletion of the CD4+CD25+ Treg population in naïve mice increases their susceptibility to uveitis induction, 19 and defective CD4+CD25high Treg cells have been detected in a human form of uveitis. 20 Hence, Treg cell function may influence susceptibility to uveitis as well as to other immunologic diseases, like MS, RA, and T1D. 2123 The influence of these cytokines on disease severity is clearly demonstrated by the effects of their neutralization: antagonism of TNF activity with anti-TNF monoclonal antibodies or TNFreceptor1-fusion protein, effectively reduces structural damage to the retina in mice and humans 24,25 ; conversely, neutralization of endogenous IL10 exacerbates inflammation, whereas treatment with IL10 or upregulation of IL10 gene expression corresponds with resolution of disease in mice. 26,27 Taken together, this evidence suggests that the consequences of relative differences in the levels of TNFα and IL10 expression, both constitutively and in response to a pathogenic insult, might influence uveitis susceptibility and severity. 
In this study, we sought to systematically investigate the role of polymorphisms in the TNF and IL10 genomic regions that might influence uveitis susceptibility and severity. We selected patients with well characterized uveitides, sharing a common T effector–cell response. Using this approach, our objective was to identify common genetic determinants of the uveitides, which are also likely to influence other immunologic disorders. 
Methods
Subjects
Subjects were recruited from four regional centers in Bristol (Bristol Eye Hospital), Aberdeen (Grampian University Hospitals), Dublin (The Royal Victoria Eye and Ear Hospital), and London (Moorfields Eye Hospital), including 27 patients from a previous study. 28,29 Informed consent was obtained from all participants, after explanation of the nature and possible consequences of the study. Subjects were white Caucasians of British or Irish descent for at least two generations. Ethical approval was given by each center and the study adhered to the tenets of the Declaration of Helsinki. 
All subjects (198 patients, 92 controls) were given a full ophthalmic examination and categorized into seven diagnostic groups (Table 1). In addition, all patients managed at the four regional centers had undergone routine diagnostic and pretreatment investigations, including a chest radiograph and syphilis serology. Further investigations (e.g., serology for Toxoplasma, Toxocara, Bartonella, Borrelia and Histoplasma capsulatum, for those who had visited endemic areas outside the United Kingdom and Ireland), and/or anterior chamber and vitreous tap, were performed where clinically indicated. Approximately equal numbers of subjects in each uveitic category were selected to mitigate potential stratification bias arising from any one subgroup, since different uveitides have varied prevalence in an unselected population. All patient groups were combined in statistical analyses for increased power. Mean age, age range, and male-female ratios of patients and control subjects were comparable between groups. 
Table 1.
 
Demographic Details of Study Participants
Table 1.
 
Demographic Details of Study Participants
Uveitis Classification n Age Sex Disease Duration at Recruitment (y) % in Remission at Recruitment % Controlled on Maintenance at Recruitment*
Mean Range Male Female Mean Range
Sarcoidosis† 30 61 41–86 13 17 11.8 0.2–48.2 23.3 56.5
Behçet's disease‡ 31 42 21–67 9 22 6.1 0.3–20.4 16.1 46.2
Sympathetic ophthalmia (SO)§ 32 60§ 19–91§ 17 15 9.4 1.3–22.4 12.5 71.4
Intermediate uveitis‖ 44 44 22–87 18 26 7.0 1.5–32.2 25.0 45.5
White dots with inflammation¶ 30 58 16–90 10 20 6.7 0.0–17.8 17.2 50.0
White dots without inflammation¶ 31 41 27–65 5 26 6.8 0.1–37.3 46.7 62.5
All patients with uveitis 198 50 16–91 72 126 8.0 0.0–48.2 23.5 55.3
Healthy controls# 92 50 22–89 27 65
For each patient, the clinical course of their ocular inflammatory disease, including visual acuities, disease remissions, and all treatments for eye disease, was documented from disease onset to a census date, common to all patient groups and regional centers and dated after study recruitment was complete. Since a significant proportion of patients were recruited at or soon after their disease onset, with ongoing disease activity (Table 1), we chose to assess clinical course up until a census date that was consistent across all subjects, since both date of recruitment and duration of disease at recruitment varied between patients. 
The patients were then assessed on three parameters of disease severity:
  1.  
    Ocular remission, defined according to SUN guidelines as inactive disease for at least 3 months after stopping all treatments for eye disease. 31
  2.  
    Maintenance level of immunosuppression required to control disease activity. Disease control was defined as unchanged or reduced SUN anterior uveitis score 31 or uveitis scoring system 32 (for posterior segment/intermediate disease) for at least 3 months, with no increase in immunosuppression during this period. We chose as the maintenance level of immunosuppression the most recent combination of medications to consistently sustain disease control (as just defined), since patients often experience multiple episodes of disease control and relapse during their clinical course until an individually tailored level of immunosuppression is achieved. Patients were then grouped according to their level of immunosuppression: Patients with remitting disease who did not require maintenance therapy were ranked the lowest, whereas patients who were uncontrolled despite three immunosuppressive treatments or on regular biological therapy (e.g., anti-TNF treatment), were ranked the highest (see Table 8 for a full description of the ranks).
  3.  
    Visual outcome, assessed in two ways: first, visual acuity (VA) at the census date, and second, the change in VA from disease onset to the census date (defined as a decrease in Snellen VA of >3 lines, in accordance with SUN guidelines 31 ).
htSNP Selection
Haplotype tagging SNPs (htSNPs) were selected, based on phased population haplotype data from SeattleSNPs (CEPH population; http://www.pga.mbt.washington.edu/ hosted by the University of Washington, Seattle, WA) and empiric data on a British control cohort from a concurrent study, 33 generated using the PHASE application. 34 htSNPs for haplotypes occurring with >5% population frequency were selected using SNPtagger, 35 resulting in nine htSNPs in the IL10 and TNF genomic regions. Three additional polymorphisms were included because of their known functional influence on transcription: IL101082A/G, 36 LTA+252G/A, 37 and TNFd 38 (Table 2). Sequence accession numbers were NT_021877 (RefSeq; http://www.ncbi.nlm.nih.gov/RefSeq; provided in the public domain by the National Center for Biotechnology Information, Bethesda, MD), AF418271 and AF295024 (SeattleSNPs) for IL10; NT_007592 (RefSeq), and AY214167 and AY216498 (SeattleSNPs) for TNFA
Table 2.
 
htSNPS Selected in the IL10 and TNF Regions
Table 2.
 
htSNPS Selected in the IL10 and TNF Regions
htSNP Position in Relation to Start Codon Location in Gene rs Number in dbSNP* Correlated SNPs and Their Location
IL10htSNP1 −3575 Promoter rs1800890 N/A
IL10htSNP2 −2849 Promoter rs6703630 N/A
IL10htSNP3 −1082 Promoter rs1800896 N/A
IL10htSNP4 −819 Promoter rs1800871 rs1800872 (promoter)
IL10htSNP5 +434 Intron 1 rs2222202 rs3024491 (intron 1), rs1878672 (intron 3), rs3024496 (3′UTR), rs3024500 and rs3024502 (3′ region)
IL10htSNP6 +504 Intron 1 rs3024490 rs1518110 (intron 1), rs1518111 and rs1554286 (intron 2)
IL10htSNP7 +1847 Intron 3 rs3024493 rs3024495 (intron 4), rs3024505 (3′ region)
LTA+252 LTA+252 (−3025 bp from TNFA start codon) Intron 1 of LTA rs909253 N/A
TNFhtSNP1 −308 Promoter rs1800629 rs1800628 (3′ region)
TNFhtSNP2 −238 Promoter rs361525 rs3093661 and rs3093662 (intron 1), rs3093664 (intron 3), rs3093726 and rs3093727 (3′ region)
TNFhtSNP3 +488 Intron 1 rs1800610 rs769178 (3′ region)
TNFd TNFd (GA)n (+12785 bp from TNFA start codon) Intron 4 of LST1 UniSTS 256848 N/A
SNP Genotyping
DNA was extracted from peripheral blood mononuclear cells. 39 IL10htSNP1, IL10htSNP2, and IL10htSNP7 were genotyped by restriction fragment length polymorphism-PCR (RFLP-PCR); IL10htSNP5 and IL10htSNP6 were sequenced together using the same primers; the remaining IL10 and TNF htSNPs were genotyped using sequence specific primers (SSP-PCR) and control primers (recognizing an intronic sequence in HLA-DRB1 40 ; Supplementary Table S1). Primers used for IL10htSNP3, IL10htSNP4, LTA+252, and TNFhtSNP1 genotyping are described elsewhere. 41,42  
PCR mixtures contained 50 ng genomic DNA, MgCl2 (Supplementary Table S1), 200 μM of each dNTP (Applied Biosystems, Warrington, UK), 1 μM of specific primers with and without control primers (Eurogentec, Romsey, UK), and 0.5 U DNA polymerase (AmpliTaq Gold; Applied Biosystems, Warrington, Cheshire, UK) in 25 μL. Cycling conditions were: 94°C for 5 minutes; 30 cycles of 94°C for 1 minute, Tm°C for 1 minute (Supplementary Table S1), 72°C for 1.5 minutes, and 72°C for 5 minutes on a thermal cycler (Peltier Thermal Cycler, Model 220; MJ Research Systems, Watertown, MA). PCR and restriction digest products were visualized by standard agarose gel electrophoresis. 
Quality Control
For a random subset of subjects, the reliability and accuracy of SSP-PCR was checked by DNA sequencing. 
TNFd Microsatellite Genotyping
The TNFd microsatellite was genotyped as previously described. 43  
HLA Typing
HLA class I (A, B, and C) and II (DRB1, DRQA1, and DRQB1) typing was performed by using SSP-PCR at medium resolution, 44 to ensure that any associations demonstrated between specific TNF alleles and disease were not secondary to linkage to an associated HLA allele. 
Statistical Analyses
Patient and control genotype distributions were analyzed by two-tailed χ2 test or Fisher's exact test (SPSS ver. 14.0; SPSS UK Ltd., Woking, UK, and Epi Info 6.04d; Centers for Disease Control and Prevention, Atlanta, GA). The Bonferroni correction was applied to adjust for number of comparisons (n = total number of loci). The distributions of ordinal phenotypic characteristics were compared by using the Kruskal-Wallis nonparametric test, and the two-tailed χ2 test or Fisher's exact test was used to compare dichotomous groups. 
Modeling of haplotypes, genotypes, and allelic associations was performed with the UNPHASED application. 45  
Hardy-Weinberg Equilibrium
Hardy-Weinberg probabilities for the 11 bi-allelic SNPs were determined for the entire cohort: SNPs at eight loci were in Hardy-Weinberg equilibrium (HWE), whereas SNPs at three loci, IL10htSNP1(−3545), IL10htSNP3(−1082), and LTA+252 were not. Although there are no SeattleSNP data available for IL10htSNP1 and IL10htSNP3, genotype frequencies did not differ significantly from those of a British control cohort. 33 Similarly, LTA+252 genotype frequencies did not differ significantly from either the SeattleSNP (CEPH) 46 or HapMap (CEU) populations, 47 which most closely approximate the British and Irish populations (see Table 3 for comparative minor allele frequencies). 
Table 3.
 
Associations between Polymorphic Loci and Uveitis
Table 3.
 
Associations between Polymorphic Loci and Uveitis
Locus rs Number Minor Allele Frequencies Comparison of Patients versus Control Subjects
Study Cohort Reference Population* P uncorr P ¢
IL10htSNP1 (−3545) rs1800890 0.48 0.44† 0.745 NS
IL10htSNP2 (−2849) rs6703630 0.35 0.31 0.001 0.012
IL10htSNP3 (−1082) rs1800896 0.44 0.49† 0.106 NS
IL10htSNP4 (−819) rs1800871 0.18 0.23 0.134 NS
IL10htSNP5 (+434) rs2222202 0.43 0.46 0.001 0.012
IL10htSNP6 (+504) rs3024490 0.19 0.26 0.002 0.024
IL10htSNP7 (+1847) rs3024493 0.27 0.22 0.480 NS
LTA+252 rs909253 0.37 0.34† 0.008 NS
TNFhtSNP1 (−308) rs1800629 0.21 0.18 0.069 NS
TNFhtSNP2 (−238) rs361525 0.08 0.07 0.012 NS
TNFhtSNP3 (+488) rs1800610 0.06 0.07 0.791 NS
TNFd UniSTS 256848 0.212 NS
The allele frequencies for the microsatellite marker, TNFd, did not differ significantly from published UK data 48 (data not shown). 
Results
Prevalence of a self-reported family history of immune-mediated inflammatory disease was 22%: most commonly, RA (20%), undefined “arthritis” (17.5%), uveitis (12.5%), undefined (Type 1 or 2) diabetes mellitus (10%), sarcoidosis (7.5%), MS (7.5%), SLE (5%), Graves' disease (5%), Behçet's disease (5%), psoriasis (2.5%), inflammatory bowel disease (2.5%), celiac disease (2.5%), and AS (2.5%). Excluding histories of undefined arthritis or diabetes, the prevalence of a family history of autoimmunity was 16%. 
Associations between IL10 and TNF Polymorphisms and Uveitis
Linkage disequilibrium (LD) between the 11 bi-allelic SNPs analyzed in this study is compared with the haplotype block structure of TNF and IL10 in the HapMap CEU population 47 in Figure 1
Figure 1.
 
(A) Haplotype block structure and LD in the region of the LTA, TNF, and LST1 genes on chromosome 6 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of TNFA and LTA in the study population according to Haploview 4.1. 49 (B) Haplotype block structure and LD in the IL10 gene on chromosome 1 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of IL10 in the study population using Haploview 4.1. 49
Figure 1.
 
(A) Haplotype block structure and LD in the region of the LTA, TNF, and LST1 genes on chromosome 6 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of TNFA and LTA in the study population according to Haploview 4.1. 49 (B) Haplotype block structure and LD in the IL10 gene on chromosome 1 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of IL10 in the study population using Haploview 4.1. 49
SNPs at three loci were significantly associated with uveitis: IL10htSNP2, IL10htSNP5, and htSNP6 (Table 3). Further analysis revealed that the alleles IL10htSNP2A, IL10htSNP5T, and htSNP6G were responsible for the association (Table 4). Stratification analyses were performed with UNPHASED, to determine whether a single IL10 locus or combination of IL10 loci contributes most significantly to the association with uveitis. In these analyses, an association with IL10htSNP2 remained significant throughout, in combination with either an association with IL10htSNP5 (P = 0.0072) or with IL10htSNP6 (P = 0.0072), whereas the associations with htSNP5 and htSNP6 (P = 0.0227) or all three SNPs together (P = 0.0081) were less significant. 
Table 4.
 
Associations Between IL10htSNP2A, IL10htSNP5T, and IL10htSNP6G and Uveitis
Table 4.
 
Associations Between IL10htSNP2A, IL10htSNP5T, and IL10htSNP6G and Uveitis
Allele SNP rs Number Patient Carriers Control Carriers P OR (95% CI)
n % n %
IL10htSNP2A (−2849) rs6703630 124 63.3 40 43.5 0.002 2.2 (1.4–3.7)
IL10htSNP5T (+434) rs2222202 166 83.8 66 71.7 0.017 2.0 (1.1–3.7)
IL10htSNP6G (+504) rs3024490 192 97.0 82 89.1 0.007 3.9 (1.4–10.7)
Further analyses of genotype combinations at these three loci showed that the combination of genotypes, IL10htSNP2AG and IL10htSNP5TC, was the most significantly associated with uveitis (P = 0.00085, odds ratio [OR], 8.13; 95% confidence interval [CI], 2.29–28.82). Two haplotypes with the IL10htSNP2AG/htSNP5TC combination were significantly associated with uveitis in three loci analyses, whereas the IL10htSNP2GG/htSNP5CC/htSNP6GG haplotype was protective, suggesting that IL10htSNP2A and IL10htSNP5T are the risk-conferring alleles (Table 5). 
Table 5.
 
Significant Associations Shown by UNPHASED between IL10htSNP2, htSNP5, and htSNP6 Haplotypes and Uveitis in Three Loci Analyses
Table 5.
 
Significant Associations Shown by UNPHASED between IL10htSNP2, htSNP5, and htSNP6 Haplotypes and Uveitis in Three Loci Analyses
IL10htSNP2/htSNP5/htSNP6 Genotype/Haplotype Patients Control Subjects χ2 P
n % n %
AG-TC-TG 21 11.1 3 3.5 4.041 0.044
AG-TC-GG 37 19.5 4 4.7 7.248 0.007
GG-CC-GG 5 2.6 9 10.5 8.816 0.003
Using UNPHASED to model allelic haplotypes, eight IL10 haplotypes (from seven loci) were predicted with certainty, but none were associated with uveitis. 
Although there were no significant associations between the TNF loci and uveitis after Bonferroni correction, we observed phenotypic associations with three alleles: LTA+252G, TNFhtSNP1A and TNFhtSNP2A (Table 6). These results were suggestive of an underlying relationship with uveitis, involving these three loci, that our study was inadequately powered to detect. Stratification analyses using UNPHASED determined that LTA+252 and TNFhtSNP2 genotypes in combination were significantly associated with uveitis (P = 0.0004); whereas associations with LTA+252 and TNFhtSNP1 (P = 0.0147) or TNFhtSNP1 and TNFhtSNP2 (P = 0.0264) or all three SNPs (P = 0.0099) were less significant. The combination of LTA+252AA and TNFhtSNP2GG genotypes was significantly protective with P = 0.00031. 
Table 6.
 
Association Between TNF Alleles and Uveitis
Table 6.
 
Association Between TNF Alleles and Uveitis
Allele SNP rs Number Patients Controls P OR (95% CI)
n % n %
LTA+252G rs909253 137 69.2 47 51.1 0.003 2.2 (1.3–3.6)
TNFhtSNP1A (−308) rs1800629 84 42.4 26 28.3 0.021 1.9 (1.1–3.2)
TNFhtSNP2A (−238) rs361525 36 18.2 7 8.2 0.018 2.7 (1.2–6.2)
Ten allelic TNF haplotypes (from five loci) were predicted with certainty using UNPHASED, but none were associated with uveitis. Further stratification analyses to determine whether an HLA class I or II allele was associated with uveitis in general, were not significant (see Supplementary Table S2). Nevertheless, we did observe a higher frequency of HLA-B*51 (12.9% patients vs. 3.9% control subjects, P uncorr = 0.023; OR, 5.4) in patients with Behçet's disease compared with controls, 50 and an association between HLA-DRB1*04 with sympathetic ophthalmia that we have described previously. 29  
Associations between IL10 and TNF Polymorphisms with Severity of Uveitis
We performed subgroup analyses to determine whether there were additional associations between the 12 loci and three parameters of uveitis severity. We observed a relationship between uveitis severity and the TNFd locus that lost significance after Bonferroni correction. TNFd genotypes were linked to both the incidence of ocular remission and the maintenance level of immunosuppression required to control ocular disease activity. Analyses using both parameters showed a consistent association between TNFd4+ patients and more severe disease, while TNFd1+ patients were more likely to have remitting disease or require lower levels of immunosuppression (Tables 7, 8). 
Table 7.
 
Association Between TNFd Phenotypes and Ocular Remission in Uveitis by χ2 Analysis
Table 7.
 
Association Between TNFd Phenotypes and Ocular Remission in Uveitis by χ2 Analysis
TNFd Phenotype Nonremitting Disease Remitting Disease P uncorr OR (95% CI)
n % n %
TNFd1+ 15 19.5 32 35.2 0.024* 0.4 (0.2–0.9)
TNFd4+ 48 62.3 37 40.7 0.005* 2.4 (1.3–4.5)
Table 8.
 
Association between TNFd Genotypes, Ocular Remission, and Level of Maintenance Immunosuppression by χ2 and Kruskal-Wallis Analysis
Table 8.
 
Association between TNFd Genotypes, Ocular Remission, and Level of Maintenance Immunosuppression by χ2 and Kruskal-Wallis Analysis
TNFd Genotype Nonremitting Disease Remitting Disease Mean Rank* †
n % n %
d1, d1 0 0 4 4.4 24.13
d1, d3 7 9.1 16 17.6 76.91
d1, d4 4 5.2 4 4.4 99.00
d1, d5 4 5.2 8 8.8 81.75
d2, d3 4 5.2 1 1.1 86.80
d3, d3 14 18.2 25 27.5 80.18
d3, d4 21 27.3 18 19.8 92.47
d3, d5 5 6.5 8 8.8 56.15
d4, d4 14 18.2 3 3.3 112.11
d4, d5 4 5.2 4 4.4 101.38
P uncorr 0.014‡ 0.015‡
There were no significant associations with visual outcome by either measure after Bonferroni correction (data not shown). 
Discussion
The hypothesis that common genetic determinants underlie susceptibility to uveitis and other immunologic diseases is suggested by its inheritance in multiplex families. 3,4 In this study, at least 16% of uveitis patients reported a family history of AI or inflammatory disease, a significantly high number compared with estimates of the U.S. population prevalence of autoimmunity of 5% to 8% (based on >80 recognized AI disorders). 51 Experimental models and clinical studies suggest that similar deviations in immune-mediated effector pathways and mechanisms of tolerance increase our overall susceptibility to autoimmunity. This effect may involve (1) central mechanisms of tolerance: the clonal deletion of autoreactive T cells and the generation of naturally occurring Ag-specific CD4+CD25+ Tregs, regulated by thymic expression of tissue-specific antigens and autoimmune transcriptional regulator (AIRE); (2) peripheral mechanisms of tolerance: the induction of Ag-specific Tregs from naïve CD4+CD25 T cells and T effector cell anergy, critically mediated by IL10; and (3) the ability to mount a TH1 and/or TH17 effector cell response, orchestrated largely through TNFα. The constitutive and inducible levels of expression of key cytokines, such as TNFα and IL10, influence the maturational pathways of specific cell types coordinating the immune response; for example, IL10 promotes the induction of IL10-producing dendritic cells, Tregs, and macrophages which promote tolerance and the resolution of inflammation, whereas TNFα is clearly important during the effector stage of disease through its effects on T effector cell function, proliferation and macrophage activation, when antigen specificity becomes less relevant and inflammation is mediated more by cytokines and bystander recruitment. 52 In this study, we have demonstrated significant relationships between uveitis and 3 IL10 loci: htSNP2(−2849), htSNP5, and htSNP6. Moreover, we have identified phenotypic associations between uveitis and LTA+252 and TNFhtSNP2(−238), and a relationship between the TNFd microsatelite polymorphism and two parameters of uveitis severity: nonremitting ocular disease and maintenance level of immunosuppression. We can speculate that IL10 polymorphisms, associated with an increased susceptibility to uveitis, perturb the mechanisms that normally uphold peripheral tolerance to retinal antigens, whereas genetic variants of TNFA are more likely to affect uveitis severity through their influence on the effector stage of disease. 
The transcriptional regulation of gene expression is now known to depend on conserved noncoding sequences (CNS) far upstream of conventionally annotated promoter regions, within introns and even between genes. These regions are known to harbor regulatory elements, such as enhancers, locus control regions, silencers, insulators, and matrix attachment regions. Nucleosome-free transcriptionally active regions of a gene, identified by hypersensitivity to DNaseI endonuclease activity (hypersensitivity sites or HS), are often found near CNS. Consequently, genetic variants may be associated with a functional effect on transcription either because (1) they are, themselves, positioned within CNS containing regulatory elements and have a direct influence on transcription or (2) they are in LD with other variants that are influencing transcription; in other words, they are found in the same haplotype and they are inherited together (haplotype-tagging). 
IL10 is predominantly regulated by transcription, 53 and genetic factors account for 75% of interindividual differences in IL10 production. 54 However, studies that have linked IL10 transcription to SNPs within 1.4kb 5′ of the transcription start site (TSS) report various results. 55 Some variation may be due to differences in experimental conditions and protocol, although more recent evidence suggests that the IL10 promoter extends at least 4 kb 5′ to the TSS of the gene. Hence, the variable association of proximal promoter haplotypes, GCC, ACC, and ATA (−1082, −819, −592) with more distal functionally important SNPs (and others that remain uncharacterized) may account for these conflicting results. 53,56 Several studies have found associations between the more distal IL10.R microsatellite and IL10 production. 57,58 IL10–2849A associates with IL10.R3, linked with low IL10 secretion, while IL10.R2 is linked to high IL10 secretion. 58 Whether these loci or another variant linked to them (inherited in the same haplotype) directly influence gene transcription is currently unknown. Nevertheless, carriers of the IL10–2849AA genotype produced significantly less IL10 in response to endotoxin in independent studies. 58,59 In our study, IL10htSNP2A(−2849A) was associated with uveitis with an OR of 2.2 (95% CI, 1.4–3.7). Hence, individuals who are genetically predisposed to be low IL10 producers, an anti-inflammatory cytokine that promotes tolerance, may be expected to have an increased prevalence of inflammatory disease. 
We have also found that IL10htSNP5T and htSNP6G are associated with uveitis with ORs of 2.0 (95% CI, 1.1–3.7) and 3.9 (95% CI, 1.4–10.7), respectively. Most studies have neglected potential functional variants in intronic or 3′UTR noncoding sequences. Hence, the importance of IL10htSNP5 and htSNP6 and the SNPs linked to them has been underinvestigated. Both TH1 and TH2 cells display a strong constitutive and inducible HS site in the 3′ UTR, and TH1 cells develop HS sites in introns 3 and 4 on stimulation. 60 The IL10htSNP5 and htSNP6 loci, located in intron 1, are in LD with several other intronic SNPs further 3′ in the gene (Table 2, Fig. 1); in particular, IL10htSNP5 is linked to SNPs in intron 3 (rs1878672) and the 3′UTR (rs3024496). Although direct evidence is lacking, it remains to be seen whether IL10htSNP5 is the functionally relevant SNP modulating ocular inflammation, or a SNP linked to it. Nevertheless, these data may direct future research to investigate the functional influence of IL10htSNP5 and other noncoding variants in cell types specifically implicated in the pathogenesis of ocular inflammation. 
The major histocompatibility complex (MHC) on chromosome 6, differs from the IL10 genomic region, with several examples of long range LD. Although the blocklike microstructure of this region is similar (Fig. 1), longer range LD arises in a subset of MHC haplotypes because of linkage between segments of strong LD. The TNFA and LTA genes are tandemly arranged in the MHC class III region—only 1.2 kb separates the polyadenylation site of LTA and the TSS of TNFA. Strong LD has been demonstrated between TNF coding and promoter SNPs, as far upstream as the LTA+252 SNP, and 8 kb downstream to the TNFd microsatellite locus, in intron 4 of LST1. 61 Both loci are linked to extended haplotypes across the human MHC region and to the transcriptional activity of TNFA. 37,38 Some variability in the results of these studies may be attributable again to differences in experimental method and the chance representation of different haplotypes in this region. 55,56 Nevertheless, the TNFA308A polymorphism associates with the LTA+252G polymorphism in several combined HLA-TNF-LT haplotypes 62 ; and these haplotypes have been linked to TNF production levels and numerous immunopathologic diseases by several independent studies. 6365 Furthermore, the TNFd4 allele is linked to high TNFα production by leukocytes in vitro, 38 and the TNFd4b allele shows strong LD with TNF238A. 48 This may explain why, in this study, carriers of LTA+252G, TNFhtSNP1A(−308A) and TNFhtSNP2A(−238A), associated with increased TNFα production, have a greater chance of developing uveitis, and TNFd4 carriers were more frequently patients with nonremitting ocular inflammation or those requiring higher levels of immunosuppression. We did not demonstrate any associations between TNF polymorphisms and visual outcome. While a census date was chosen to make a final assessment of clinical course that was consistent across patient groups, the duration of disease at this date did vary between patients. Furthermore, both measures were likely confounded by ongoing disease activity and/or the incidence of cataract and other complications. Further analysis of visual outcome in uveitis would be desirable, correlated with the development of complications and disease duration. Such an analysis would necessitate a larger prospective study with appropriate statistical power. 
Although few studies have directly examined the effects of variants in these genes on transcription factor binding and subsequent TNFA expression, HS sites have been identified in the highly conserved proximal TNFA and LTA promoters in several cell lines, including a constitutively active site in human monocyte and T-cell lines. 6668 Furthermore, specific enhancer complexes have been identified in these regions that depend on transcription factor, cell type, and stimulus. 69,70 Other regulatory elements and HS have been reported further upstream of the LTA and TNFA promoters, 71,72 within TNFA intron 3, 73 the TNFA 3′-UTR, 74 intergenic regions of the TNF locus, 69 and a CpG island in exon 4 of the LTB gene. The latter was detected across a range of cell types and demonstrated histone modifications associated with active transcription. 75 Hence, the TNFA−308 and −238 loci coincide with highly CNS close to the TSS of the TNFA gene and a constitutive HS spot in T cells, which could account for their influence on transcription. Associations between the LTA+252 and TNFd polymorphisms with disease may again arise due to their influence on transcription in other cell types that have not yet been investigated, or because they are linked to other functional polymorphisms—for example, variants in the highly conserved LTA promoter or CpG island of LTB, that are likely to have regulatory function. 
We did not identify a common HLA haplotype or allele that was associated with uveitis susceptibility or severity overall. Our hypothesis would be that tissue-specific factors, influenced by cognate (self-)antigen presentation to MHC-restricted T cells, govern the sites of inflammation in immunologic disease, whereas factors affecting the shared mechanisms described above will affect the risk and severity of autoimmunity as a whole. We have found that polymorphisms, IL102849, LTA+252, TNF238 and TNFd were linked to uveitis, loci that have been implicated in many other immune-mediated inflammatory disorders. 55 Furthermore, these loci and the two additional SNPs associated with uveitis in this study, IL10htSNP5 and htSNP6, are either located within CNS with functional relevance, or they are linked to regions identified by chromatin assays of inflammatory cell types that are. Hence, the results of transcriptional assays should be interpreted contextually, taking into account cell-type and stimulus and the relationship between loci in the same haplotype or chromosome. Taken together, our results lend further weight to the hypothesis that common genetic determinants underlie the risk of autoimmunity. 
Supplementary Materials
Footnotes
 Supported by the National Eye Research Centre and Medical Research Committee of the Charitable Trusts of the United Bristol Hospitals.
Footnotes
 Disclosure: D. Atan, None; S. Fraser-Bell, None; J. Plskova, None; L. Kuffova, None; A. Hogan, None; A. Tufail, None; D.J. Kilmartin, None; J.V. Forrester, None; J. Bidwell, None; A.D. Dick, None; A.J. Churchill, None
The authors thank the Immunology and Immunogenetics Department at Southmead Hospital, North Bristol Health care Trust for HLA typing and all patients and control subjects who participated. 
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Figure 1.
 
(A) Haplotype block structure and LD in the region of the LTA, TNF, and LST1 genes on chromosome 6 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of TNFA and LTA in the study population according to Haploview 4.1. 49 (B) Haplotype block structure and LD in the IL10 gene on chromosome 1 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of IL10 in the study population using Haploview 4.1. 49
Figure 1.
 
(A) Haplotype block structure and LD in the region of the LTA, TNF, and LST1 genes on chromosome 6 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of TNFA and LTA in the study population according to Haploview 4.1. 49 (B) Haplotype block structure and LD in the IL10 gene on chromosome 1 in the CEU population of the HapMap project. 47 Inset: LD between htSNPs of IL10 in the study population using Haploview 4.1. 49
Table 1.
 
Demographic Details of Study Participants
Table 1.
 
Demographic Details of Study Participants
Uveitis Classification n Age Sex Disease Duration at Recruitment (y) % in Remission at Recruitment % Controlled on Maintenance at Recruitment*
Mean Range Male Female Mean Range
Sarcoidosis† 30 61 41–86 13 17 11.8 0.2–48.2 23.3 56.5
Behçet's disease‡ 31 42 21–67 9 22 6.1 0.3–20.4 16.1 46.2
Sympathetic ophthalmia (SO)§ 32 60§ 19–91§ 17 15 9.4 1.3–22.4 12.5 71.4
Intermediate uveitis‖ 44 44 22–87 18 26 7.0 1.5–32.2 25.0 45.5
White dots with inflammation¶ 30 58 16–90 10 20 6.7 0.0–17.8 17.2 50.0
White dots without inflammation¶ 31 41 27–65 5 26 6.8 0.1–37.3 46.7 62.5
All patients with uveitis 198 50 16–91 72 126 8.0 0.0–48.2 23.5 55.3
Healthy controls# 92 50 22–89 27 65
Table 2.
 
htSNPS Selected in the IL10 and TNF Regions
Table 2.
 
htSNPS Selected in the IL10 and TNF Regions
htSNP Position in Relation to Start Codon Location in Gene rs Number in dbSNP* Correlated SNPs and Their Location
IL10htSNP1 −3575 Promoter rs1800890 N/A
IL10htSNP2 −2849 Promoter rs6703630 N/A
IL10htSNP3 −1082 Promoter rs1800896 N/A
IL10htSNP4 −819 Promoter rs1800871 rs1800872 (promoter)
IL10htSNP5 +434 Intron 1 rs2222202 rs3024491 (intron 1), rs1878672 (intron 3), rs3024496 (3′UTR), rs3024500 and rs3024502 (3′ region)
IL10htSNP6 +504 Intron 1 rs3024490 rs1518110 (intron 1), rs1518111 and rs1554286 (intron 2)
IL10htSNP7 +1847 Intron 3 rs3024493 rs3024495 (intron 4), rs3024505 (3′ region)
LTA+252 LTA+252 (−3025 bp from TNFA start codon) Intron 1 of LTA rs909253 N/A
TNFhtSNP1 −308 Promoter rs1800629 rs1800628 (3′ region)
TNFhtSNP2 −238 Promoter rs361525 rs3093661 and rs3093662 (intron 1), rs3093664 (intron 3), rs3093726 and rs3093727 (3′ region)
TNFhtSNP3 +488 Intron 1 rs1800610 rs769178 (3′ region)
TNFd TNFd (GA)n (+12785 bp from TNFA start codon) Intron 4 of LST1 UniSTS 256848 N/A
Table 3.
 
Associations between Polymorphic Loci and Uveitis
Table 3.
 
Associations between Polymorphic Loci and Uveitis
Locus rs Number Minor Allele Frequencies Comparison of Patients versus Control Subjects
Study Cohort Reference Population* P uncorr P ¢
IL10htSNP1 (−3545) rs1800890 0.48 0.44† 0.745 NS
IL10htSNP2 (−2849) rs6703630 0.35 0.31 0.001 0.012
IL10htSNP3 (−1082) rs1800896 0.44 0.49† 0.106 NS
IL10htSNP4 (−819) rs1800871 0.18 0.23 0.134 NS
IL10htSNP5 (+434) rs2222202 0.43 0.46 0.001 0.012
IL10htSNP6 (+504) rs3024490 0.19 0.26 0.002 0.024
IL10htSNP7 (+1847) rs3024493 0.27 0.22 0.480 NS
LTA+252 rs909253 0.37 0.34† 0.008 NS
TNFhtSNP1 (−308) rs1800629 0.21 0.18 0.069 NS
TNFhtSNP2 (−238) rs361525 0.08 0.07 0.012 NS
TNFhtSNP3 (+488) rs1800610 0.06 0.07 0.791 NS
TNFd UniSTS 256848 0.212 NS
Table 4.
 
Associations Between IL10htSNP2A, IL10htSNP5T, and IL10htSNP6G and Uveitis
Table 4.
 
Associations Between IL10htSNP2A, IL10htSNP5T, and IL10htSNP6G and Uveitis
Allele SNP rs Number Patient Carriers Control Carriers P OR (95% CI)
n % n %
IL10htSNP2A (−2849) rs6703630 124 63.3 40 43.5 0.002 2.2 (1.4–3.7)
IL10htSNP5T (+434) rs2222202 166 83.8 66 71.7 0.017 2.0 (1.1–3.7)
IL10htSNP6G (+504) rs3024490 192 97.0 82 89.1 0.007 3.9 (1.4–10.7)
Table 5.
 
Significant Associations Shown by UNPHASED between IL10htSNP2, htSNP5, and htSNP6 Haplotypes and Uveitis in Three Loci Analyses
Table 5.
 
Significant Associations Shown by UNPHASED between IL10htSNP2, htSNP5, and htSNP6 Haplotypes and Uveitis in Three Loci Analyses
IL10htSNP2/htSNP5/htSNP6 Genotype/Haplotype Patients Control Subjects χ2 P
n % n %
AG-TC-TG 21 11.1 3 3.5 4.041 0.044
AG-TC-GG 37 19.5 4 4.7 7.248 0.007
GG-CC-GG 5 2.6 9 10.5 8.816 0.003
Table 6.
 
Association Between TNF Alleles and Uveitis
Table 6.
 
Association Between TNF Alleles and Uveitis
Allele SNP rs Number Patients Controls P OR (95% CI)
n % n %
LTA+252G rs909253 137 69.2 47 51.1 0.003 2.2 (1.3–3.6)
TNFhtSNP1A (−308) rs1800629 84 42.4 26 28.3 0.021 1.9 (1.1–3.2)
TNFhtSNP2A (−238) rs361525 36 18.2 7 8.2 0.018 2.7 (1.2–6.2)
Table 7.
 
Association Between TNFd Phenotypes and Ocular Remission in Uveitis by χ2 Analysis
Table 7.
 
Association Between TNFd Phenotypes and Ocular Remission in Uveitis by χ2 Analysis
TNFd Phenotype Nonremitting Disease Remitting Disease P uncorr OR (95% CI)
n % n %
TNFd1+ 15 19.5 32 35.2 0.024* 0.4 (0.2–0.9)
TNFd4+ 48 62.3 37 40.7 0.005* 2.4 (1.3–4.5)
Table 8.
 
Association between TNFd Genotypes, Ocular Remission, and Level of Maintenance Immunosuppression by χ2 and Kruskal-Wallis Analysis
Table 8.
 
Association between TNFd Genotypes, Ocular Remission, and Level of Maintenance Immunosuppression by χ2 and Kruskal-Wallis Analysis
TNFd Genotype Nonremitting Disease Remitting Disease Mean Rank* †
n % n %
d1, d1 0 0 4 4.4 24.13
d1, d3 7 9.1 16 17.6 76.91
d1, d4 4 5.2 4 4.4 99.00
d1, d5 4 5.2 8 8.8 81.75
d2, d3 4 5.2 1 1.1 86.80
d3, d3 14 18.2 25 27.5 80.18
d3, d4 21 27.3 18 19.8 92.47
d3, d5 5 6.5 8 8.8 56.15
d4, d4 14 18.2 3 3.3 112.11
d4, d5 4 5.2 4 4.4 101.38
P uncorr 0.014‡ 0.015‡
Supplementary Table S1
Supplementary Table S2
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