# Tumor Necrosis Factor Receptor Superfamily, Member 1B Haplotypes Increase or Decrease the Risk of Inflammatory Bowel Diseases in a New Zealand Caucasian Population

Authors: Lynnette R. Ferguson; Dug Yeo Han; Claudia Huebner; Ivonne Petermann; Murray L. Barclay; Richard B. Gearry; Alan McCulloch; Pieter S. Demmers
Journal: Gastroenterology Research and Practice
 (2009)

---

## Abstract

Inflammatory bowel diseases (IBDs) comprising Crohn disease (CD) and ulcerative colitis (UC) are chronic inflammatory conditions with polygenic susceptibility. Interactions between TNF-alpha and TNF-alpha receptor play a fundamental role in inflammatory response. This study investigates the role that selected single nucleotide polymorphisms (SNPs) and haplotypes in the TNF-alpha receptor (TNSFRSF1B) gene play in the risk of IBD in a New Zealand Caucasian population. DNA samples from 388 CD, 405 UC, 27 indeterminate colitis patients, and 293 randomly selected controls, from Canterbury, New Zealand were screened for 3 common SNPs in TNSFRSF1B: rs1061622 (c.676T>C), rs1061624 (c.∗1663A>G), and rs3397 (c.∗1690T>C), using TaqMan technologies. Carrying the rs1061624 variant decreased the risk of UC in the left colon (OR 0.73, 95% CI=0.54–1.00) and of being a smoker at diagnosis (OR 0.62; 95% CI=0.40–0.96). Carrying the rs3397 variant decreased the risk of penetrating CD (OR 0.62, 95% CI=0.40–0.95). Three marker haplotype analyses revealed highly significant differences between CD patients and control subjects (χ2=29.9, df=7, P=.0001) and UC cases and controls (χ2=46.3, df=7, P<.0001). We conclude that carrying a 3-marker haplotype in the TNSFRSF1B gene may increase (e.g., haplotype of GGC was 2.9-fold more in the CD or UCpatients) or decrease (e.g., TGT was 0.47-fold less in UC patients) the risk of IBD in a New Zealand Caucasian population.


---

## Body

## 1. Introduction

Inflammatory bowel diseases (IBDs), including Crohn disease (CD) and ulcerative colitis (UC), provide a good
example of a disorder for which there is compelling evidence for
genetically determined susceptibility that interacts with environmental
factors, including microbiota and diet [1]. It is clear that there are strong ethnic differences in IBD susceptibility, and
that different populations may have varying levels of genetic involvement, with
distinctive risk alleles [2]. For example, although there is a very low
incidence of CD in Bangladesh, the children of Bangladesh immigrants to the UK
show a very high incidence of
the disease [2]. As recently as 2005, it seemed that a maximum of 10–12 genetic
loci could be involved in disease susceptibility [3], but whole genome
association studies have changed the landscape such that a more recent
meta-analysis [4] suggested involvement of more than 30 different loci. It
becomes important to establish which loci are relevant to individual population
groups living in specific locations.The prevalence and
incidence of IBD in New
Zealand
are believed to have increased
substantially in recent years, although stringently collated data are not
available prior to 2004 [5]. As at 1 June 2005, Gearry et al. (2006)
reported a prevalence of IBD in Canterbury,
New Zealand, as
308.3 per 100 000 subjects (155.2 with CD and 145 with UC per 100 000). Although
we have previously associated polymorphisms in several genes including
NOD1&2, TLR4, DLG5, ATG16L1, and IL23R with risk of IBD in New Zealand
[6–12], these only increase the IBD risk to a small extent and cannot
explain the high New Zealand disease incidence.
For example, carrying the common NOD2 1007-femtdsecond mutation increased the risk
of CD 4.4 fold (95% confidence interval 1.6–12) [12].Tumor necrosis factor-alpha (TNF-α) is a proinflammatory
cytokine that plays a central role in IBD pathogenesis [8]. An inhibitor
of TNF-α, infliximab (IFB), is an effective treatment of moderate to severe
IBD, and polymorphisms in the TNF-α gene not only affect the phenotype of IBD, but may also impact IFB
susceptibility [8, 13]. However, TNF-α does not work
independently in the cell, but acts through binding to two receptors, TNF receptor superfamily, member 1A (TNFRSF1A
or p55/p60) and TNF receptor superfamily,
member 1B (TNFRSF1B, also called TNFR, p75/p80). TNFRSF1B is the larger
of these receptors, being present on many cell types, and strongly expressed on
stimulated T and B lymphocytes [14]. There is evidence that it regulates the
binding of TNF-α to TNFRSF1A, and thus may regulate the levels of TNF-α necessary to
stimulate the action of the transcription factor, nuclear factor-kappa B
(NF-kB) [15]. The
gene for TNFRSF1B is located on chromosome 1p36.3-p36.2 [16–18], which
coincides with the previously identified IBD susceptibility locus, IBD7 [19].Single nucleotide polymorphisms (SNPs) in TNFRSF1B have been
suggested to modulate the risk of a number of autoimmune diseases, including
rheumatoid  arthritis, systemic lupus erythematosus, and CD [20–24]. This study considers the role of three SNPs in TNFRSF1B Table 1 on the overall risk or phenotype of
IBD in a New Zealand Caucasian population, recruited from the Canterbury region
in New Zealand [5] 2006. These SNPs were previously associated with CD risk in
other populations [22, 23].Table 1
TNFRSF1B polymorphisms tested in the Canterbury population.
rs numberLocationNucleotide changeAmino acid positionMajor allele in EuropeansFrequency in other European groupsrs.1061622Exon 6 (nonsynonymous)c.676T> G196T75%   [Hapmap]
80.2% [Wachke]rs.1061624Exon 10   3’UTRc.*1663A> GA51.7% [Hapmap]   55.2% [Washke]rs.3397Exon 10
3’UTRc.*1690T> CT52.6% [Hapmap]


## 2. Materials and Methods

### 2.1. Study Participants

The cases in this study are a random
subset of the Caucasian participants of the Canterbury Inflammatory Bowel Disease
Project, which has been described in detail elsewhere [5]. All subjects
consented to collection of peripheral blood for DNA extraction and
genotyping. Phenotypic characteristics of this cohort are
described in more detail by Tarrant et al. [25]. The database
included their clinical diagnosis and
IBD phenotype as defined using standard diagnostic criteria and using
the Montreal Classification system [26]. The Montreal
classification was current as of 1 June 2005.388 CD participants, 403  UC participants, and 27 indeterminate
colitis (IC) participants were genotyped for this study, as described in Table2. All participants self-reported European
ancestry, and patients who self-reported having any Maori or other
non-Caucasian ancestry are not included.Table 2
Summary of clinical and demographic data for the set of Caucasian IBD patients.
CDn (%)UCn (%)ICn (%)GenderFemale249 (64.2)214 (52.8)15 (55.6)Male139 (35.8)191 (47.2)12 (44.4)Age at first diagnosisBelow 1739 (10.0)26 (6.4)0Between 17 and 40199 (51.3)184 (45.4)15 (55.6)Above 40150 (38.7)195 (48.2)12 (44.4)CD locationIleal125 (32.2)Colonic169 (43.6)Ileocolonic90 (23.2)Unknown (U + UN)4 (1.0)UC locationProctitis140 (34.6)3 (11.1)Left colon107 (26.4)5 (18.5)Pancolitis154 (38.0)19 (70.4)Unknown4 (1.0)0BehaviourNonstricturing, nonpenetrating
perianal disease:With47 (21.5)Without172 (78.5)Stricturing perianal disease:With46 (38.0)Without75 (62.0)Penetrating perianal disease:With17 (35.4)Without31 (64.6)Any relative with IBD: Yes (n = 143)74 (19.1)65 (16.1)5 (18.5)Bowel resection: Yes (n = 214)142 (36.6)70 (17.3)2 (7.4)Smoker at diagnosis: Yes (n = 147)97 (25.7)49 (12.3)2 (7.7)Ever used immunomodulators: Yes
(n = 296)203 (52.3)86 (21.2)8 (29.6)Extraintestinal manifestations: Yes
(n = 142)75 (19.3)64 (15.8)3 (11.1)The New Zealand Caucasian controls (n = 293) were selected at random
from the electoral roll, comprising 93% of the population over eighteen years
of age in Canterbury, New Zealand [27].


### 2.2. Applied Biosystems Taqman SNP Genotyping Assay

SNPs were genotyped using the TaqMan MGB diallelic discrimination
system. Probes and oligonucleotides were obtained from Applied Biosystems  using
the Assay-by-Design product (listed in Table3). For the marker c.676T > C (rs1061622)
a predesigned SNP genotyping assay was available (C_8861232_20). The reactions were prepared by using 2x TaqMan
Universal Master Mix, 40x SNP Genotyping Assay Mix, DNase-free water, 10 ng
genomic DNA in a final volume of 5 uL per reaction. The PCR amplification was
performed using the ABI Prism 7900 HT sequence-detector machine under the
following conditions: 10 minutes 95°C enzyme activation followed by 40 cycles at
92°C for 15 seconds and 60°C for 1 minute (annealing/extension). The allelic
discrimination results were determined after the amplification by performing an
endpoint read. To estimate genotype accuracy approximately 5% of the samples, that is,
70 cases were genotyped in duplicate or triplicate for each of the markers. No conflicted duplicate genotypes were detected.Table 3
Primer and probe sequences for custom-made TaqMan SNP genotyping assay for TNFRSF1B.
TaqMan SNP genotyping assayDNA sequenceTNFRSF1B_*1663A> G forward primer5’ TGACCTGCAGGCCAAGAG 3’TNFRSF1B_*1663A> G_reverse primer5’ CCATGGCAGCAGAGGCTTT 3’TNFRSF1B_*1663A> G_VIC probe5’ CCACAACTCGCTGCC 3’TNFRSF1B_*1663A> G_FAM probe5’ CACAACCCGCTGCC 3’TNFRSF1B_*1690T> C_forward primer5’ TGACCTGCAGGCCAAGAG 3’TNFRSF1B_*1690T> C_reverse primer5’ CCATGGCAGCAGAGGCTTT 3’TNFRSF1B_*1690T> C_VIC probe5’ CATGGCGTGTCCC 3’TNFRSF1B_*1690T> C_FAM probe5’ CCATGGTGTGTCCC 3’


#### 2.2.1. Statistical Analysis

The allelic trend test [26] and Fisher’s exact genotypic test were
used to compare case and control allele frequencies. An exact test was used to test for departures
from Hardy-Weinberg equilibrium (HWE) in the case and the control samples [27].
Allelic odds ratios were calculated and confidence intervals for the allelic
odds ratio were also calculated under the assumption of HWE in the cases and
the control groups. Logistic regression analysis  was used to examine the relationship between genotypes and disease of
CD, UC, and IBD using SAS (V9.1 SAS Institute., Cary, NC, USA). Haplotype analysis was carried out using
haplo.stats in R [28] to test
associations between haplotypes and traits. We also performed an exploratory analysis of allele frequency
differences between controls and patient subgroups using the clinical
characteristics given in Table 2.


## 2.1. Study Participants

The cases in this study are a random
subset of the Caucasian participants of the Canterbury Inflammatory Bowel Disease
Project, which has been described in detail elsewhere [5]. All subjects
consented to collection of peripheral blood for DNA extraction and
genotyping. Phenotypic characteristics of this cohort are
described in more detail by Tarrant et al. [25]. The database
included their clinical diagnosis and
IBD phenotype as defined using standard diagnostic criteria and using
the Montreal Classification system [26]. The Montreal
classification was current as of 1 June 2005.388 CD participants, 403  UC participants, and 27 indeterminate
colitis (IC) participants were genotyped for this study, as described in Table2. All participants self-reported European
ancestry, and patients who self-reported having any Maori or other
non-Caucasian ancestry are not included.Table 2
Summary of clinical and demographic data for the set of Caucasian IBD patients.
CDn (%)UCn (%)ICn (%)GenderFemale249 (64.2)214 (52.8)15 (55.6)Male139 (35.8)191 (47.2)12 (44.4)Age at first diagnosisBelow 1739 (10.0)26 (6.4)0Between 17 and 40199 (51.3)184 (45.4)15 (55.6)Above 40150 (38.7)195 (48.2)12 (44.4)CD locationIleal125 (32.2)Colonic169 (43.6)Ileocolonic90 (23.2)Unknown (U + UN)4 (1.0)UC locationProctitis140 (34.6)3 (11.1)Left colon107 (26.4)5 (18.5)Pancolitis154 (38.0)19 (70.4)Unknown4 (1.0)0BehaviourNonstricturing, nonpenetrating
perianal disease:With47 (21.5)Without172 (78.5)Stricturing perianal disease:With46 (38.0)Without75 (62.0)Penetrating perianal disease:With17 (35.4)Without31 (64.6)Any relative with IBD: Yes (n = 143)74 (19.1)65 (16.1)5 (18.5)Bowel resection: Yes (n = 214)142 (36.6)70 (17.3)2 (7.4)Smoker at diagnosis: Yes (n = 147)97 (25.7)49 (12.3)2 (7.7)Ever used immunomodulators: Yes
(n = 296)203 (52.3)86 (21.2)8 (29.6)Extraintestinal manifestations: Yes
(n = 142)75 (19.3)64 (15.8)3 (11.1)The New Zealand Caucasian controls (n = 293) were selected at random
from the electoral roll, comprising 93% of the population over eighteen years
of age in Canterbury, New Zealand [27].


## 2.2. Applied Biosystems Taqman SNP Genotyping Assay

SNPs were genotyped using the TaqMan MGB diallelic discrimination
system. Probes and oligonucleotides were obtained from Applied Biosystems  using
the Assay-by-Design product (listed in Table3). For the marker c.676T > C (rs1061622)
a predesigned SNP genotyping assay was available (C_8861232_20). The reactions were prepared by using 2x TaqMan
Universal Master Mix, 40x SNP Genotyping Assay Mix, DNase-free water, 10 ng
genomic DNA in a final volume of 5 uL per reaction. The PCR amplification was
performed using the ABI Prism 7900 HT sequence-detector machine under the
following conditions: 10 minutes 95°C enzyme activation followed by 40 cycles at
92°C for 15 seconds and 60°C for 1 minute (annealing/extension). The allelic
discrimination results were determined after the amplification by performing an
endpoint read. To estimate genotype accuracy approximately 5% of the samples, that is,
70 cases were genotyped in duplicate or triplicate for each of the markers. No conflicted duplicate genotypes were detected.Table 3
Primer and probe sequences for custom-made TaqMan SNP genotyping assay for TNFRSF1B.
TaqMan SNP genotyping assayDNA sequenceTNFRSF1B_*1663A> G forward primer5’ TGACCTGCAGGCCAAGAG 3’TNFRSF1B_*1663A> G_reverse primer5’ CCATGGCAGCAGAGGCTTT 3’TNFRSF1B_*1663A> G_VIC probe5’ CCACAACTCGCTGCC 3’TNFRSF1B_*1663A> G_FAM probe5’ CACAACCCGCTGCC 3’TNFRSF1B_*1690T> C_forward primer5’ TGACCTGCAGGCCAAGAG 3’TNFRSF1B_*1690T> C_reverse primer5’ CCATGGCAGCAGAGGCTTT 3’TNFRSF1B_*1690T> C_VIC probe5’ CATGGCGTGTCCC 3’TNFRSF1B_*1690T> C_FAM probe5’ CCATGGTGTGTCCC 3’


### 2.2.1. Statistical Analysis

The allelic trend test [26] and Fisher’s exact genotypic test were
used to compare case and control allele frequencies. An exact test was used to test for departures
from Hardy-Weinberg equilibrium (HWE) in the case and the control samples [27].
Allelic odds ratios were calculated and confidence intervals for the allelic
odds ratio were also calculated under the assumption of HWE in the cases and
the control groups. Logistic regression analysis  was used to examine the relationship between genotypes and disease of
CD, UC, and IBD using SAS (V9.1 SAS Institute., Cary, NC, USA). Haplotype analysis was carried out using
haplo.stats in R [28] to test
associations between haplotypes and traits. We also performed an exploratory analysis of allele frequency
differences between controls and patient subgroups using the clinical
characteristics given in Table 2.


## 2.2.1. Statistical Analysis

The allelic trend test [26] and Fisher’s exact genotypic test were
used to compare case and control allele frequencies. An exact test was used to test for departures
from Hardy-Weinberg equilibrium (HWE) in the case and the control samples [27].
Allelic odds ratios were calculated and confidence intervals for the allelic
odds ratio were also calculated under the assumption of HWE in the cases and
the control groups. Logistic regression analysis  was used to examine the relationship between genotypes and disease of
CD, UC, and IBD using SAS (V9.1 SAS Institute., Cary, NC, USA). Haplotype analysis was carried out using
haplo.stats in R [28] to test
associations between haplotypes and traits. We also performed an exploratory analysis of allele frequency
differences between controls and patient subgroups using the clinical
characteristics given in Table 2.


## 3. Results

No significant deviation from Hardy-Weinberg Equilibrium was found
in the control group for all three SNPs.
For each of the polymorphisms studied, the risks of carrying the variant
was compared CD and UC patients with the control group, as shown in Tables4
and 5. There was no significant
difference in the allele frequencies of the TNFRSF1B rs1061622,
rs1061624, and rs3397 variants between CD or UC patients and healthy
control subjects.Table 4
Genotype and allele counts for TNFRSF1B
variants in New Zealand IBD patients and in New Zealand Caucasians.
SNPControlsCDUCCD + UCICN(%)N(%)OR (95% CI)N(%)OR (95% CI)N(%)OR (95% CI)N(%)TNFRSF1B_1061622GG12
(4.1)18
(4.7)1.12
(0.55–2.28)23
(5.8)1.42
(0.72–2.79)41
(5.2)1.27
(0.69–2.34)0GT102
(34.8)144
(37.6)1.17
(0.86–1.59)154
(38.6)1.22
(0.90–1.65)298
(38.1)1.19
(0.91–1.56)8 (30.8)TT179
(61.1)221
(57.7)1.00222
(55.6)1.00443
(56.6)1.0018 (69.2)GenotypeP-value0.670.290.38HWEP-value.73.37.58.32G126
(21.5)180
(23.5)200
(25.1)380
(24.3)44 (84.6)T460
(78.5)586
(76.5)598
(74.9)1184
(75.7)8 (15.4)OR (95% CI)1.12
(0.87–1.45)1.22
(0.95–1.57)1.17
(0.93–1.47)AllelicP-value.38.12.17TNFRSF1B_1061624AA65 (22.2)94 (24.5)1.0096 (24.1)1.00190 (24.3)1.004 (16.0)AG158 (53.9)185 (48.3)0.85 (0.59–1.22)185 (46.4)0.84 (0.59–1.21)370 (47.3)0.85 (0.62–1.16)20 (80.0)GG70 (23.9)104 (27.2)1.05 (0.69–1.59)118 (23.9)1.21 (0.80–1.82)222 (28.4)1.13 (0.79–1.63)1 (4.0)GenotypeP-value0.430.120.16HWEP-value.20.51.16.14A288 (49.1)373 (48.7)377 (47.2)750 (48.0)28 (56.0)G298 (50.9)393 (51.3)421 (52.8)814 (52.0)22 (44.0)OR (95% CI)0.98 (0.79–1.22)0.93 (0.75–1.15)0.95 (0.79–1.15)AllelicP-value.87.48.62TNFRSF1B_3397CC112 (38.2)135 (35.2)1.00165 (41.4)1.00300 (38.4)1.0011 942.3)CT138 (47.1)186 (48.6)1.22 (0.89–1.67)169 (42.4)0.88 (0.65–1.21)355 (45.4)1.03 (0.78–1.36)11 (42.3)TT43 (14.7)62 (16.2)1.29 (0.83–2.02)65 (16.3)1.09 (0.71–1.68)127 (16.2)1.18 (0.80–1.74)4 (15.4)GenotypeP-value.70.46.79HWEP-value1.000.880.050.20C362 (61.8)456 (59.5)499 (62.5)955 (61.1)33 (63.5)T224 (38.2)310 (40.5)299 (37.5)609 (38.9)19 (36.5)OR (95% CI)0.91 (0.73–1.13)1.03 (0.83–1.29)0.97 (0.80–1.18)AllelicP-value.40.77.76Table 5
Allelic odds ratios and 95% confidence
intervals for comparison of TNFRSF1B variants with IBD status in New Zealand
IBD patients and Caucasians.
Allelic odds ratios and 95%Allelic odds ratios and 95%Allelic odds ratios and 95%confidence intervals for comparison ofconfidence intervals for comparison ofconfidence intervals for comparison ofTNFRSF1_B1061622TNFRSF1B_1061624TNFRSF1B_3397Crohns diseaseUlcerative colitisCrohns diseaseUlcerative colitisCrohns diseaseUlcerative colitisOR95% CIOR95% CIOR95% CIOR95% CIOR95% CIOR95% CIFemale1.200.86–1.671.380.99–1.931.100.84–1.441.000.76–1.320.850.65–1.120.960.72–1.27Male1.050.72–1.541.020.72–1.450.820.59–1.140.790.59–1.070.890.64–1.241.040.76–1.42Age at first diagnosis0–16 years0.850.47–1.541.080.55–2.110.880.55–1.421.300.74–2.290.860.53–1.391.220.67–2.2217–40 years1.260.94–1.681.180.87–1.591.010.79–1.290.930.72–1.200.850.66–1.090.960.74–1.25>40 years1.010.73–1.411.240.93–1.660.950.72–1.250.830.65–1.070.890.67–1.171.000.77–1.29CD locationIleal0.910.63–1.301.130.85–1.510.880.65–1.18Colonic1.170.86–1.590.900.69–1.170.910.70–1.19Ileocolonic1.270.87–1.860.900.64–1.260.780.56–1.09UC locationPancolitis1.130.82–1.560.940.72–1.231.140.86–1.51Left colon1.240.87–1.780.730.54–1.000.920.67–1.26Proctitis1.270.92–1.761.000.76–1.320.930.70–1.24CD BehaviorInflammatory1.170.88–1.560.880.69–1.120.920.72–1.18Stricturing1.030.72–1.471.010.75–1.360.900.67–1.22Penetrating1.130.68–1.871.380.90–2.120.620.40–0.95Ileal/stricturing0.860.55–1.341.030.72–1.460.930.65–1.33Colonic/inflammatory1.240.90–1.710.840.64–1.110.930.70–1.23Any relative with IBD1.220.80–1.861.150.74–1.790.780.54–1.120.880.60–1.280.970.67–1.400.830.57–1.22Bowel resection0.930.66–1.311.100.71–1.701.090.83–1.440.790.55–1.140.770.58–1.021.290.87–1.90Smoker at diagnosis0.960.65–1.421.160.71–1.901.010.73–1.390.620.40–0.960.920.66–1.281.220.78–1.91Ever used immunomodulators1.080.80–1.451.430.98–2.091.070.84–1.371.160.83–1.620.820.64–1.050.880.63–1.24Any EIMs1.050.68–1.611.050.66–1.661.060.74–1.510.830.57–1.210.890.62–1.280.810.55–1.19Individuals carrying the rs1061622 variant showed no significant
differences from those carrying the reference allele (the G allele), for
overall risk of IBD or for any phenotypic class. No significant differences found any of the
age at first diagnosis, any location of CD and UC, or CD behavior. Having any relatives with IBD, bowel
resection, smoke at diagnosis, ever used immunomodulators, or any EIMs were not
significanty different between CD or UC patients and controls.For the rs1061624 variant, those individuals carrying the A allele had
a decreased probability of developing UC located in the left colon (OR = 0.73,
95% CI =0.54–1.00, P = .05). Carrying the A allele also reduced the
probability of UC patients having smoked at diagnosis (OR = 0.62, 95%
CI = 0.40–0.96, P = .03) but showed no
statistically significant effects in patterns of CD disease risk.Those individuals carrying the variant TNFRSF1B rs3397 C allele
showed a statistically significant reduction in the probability of developing
CD with penetrating behavior, as compared with those carrying the T allele
(OR = 0.62, 95% CI =0.40–0.95, P = .03). No other phenotypes showed significant
effects in patterns of disease risk of CD.
For UC patients, those individuals carrying the variant rs3397 C allele
showed no statistically significant effects in patterns of IBD (Table 4).


### 3.1. Haplotype Analysis

Table6 summarizes the results of haplotype analysis of the three TNFRSF1B
SNPs (rs1061622, rs1061624, and
rs3397). Haplotype frequencies were estimated, and association analyses were
performed with respect to CD and UC in New Zealand IBD patients and Caucasian
controls. A score for each haplotype
(Hap-score) was calculated and P-value also calculated for the significance of
each Hap-score. A positive hap-score implies that the haplotype occurs more
frequently in the CD or UC case group than control subjects. A global P-value
tests the overall association between haplotypes and the response.Table 6
Haplotype analysis of three-SNP TNFRSF1B haplotype in IBD status in New Zealand IBD patients and
Caucasians.
HaplotypeCase
frequencyControl
frequencyHap frequencyHap-scoreP-valueGlobal score statisticsCDThree
SNPs TNFRSF1B region
(rs1061622,
rs1061624, rs3397)GAC0.0570.1010.075−1.55.12χ2 = 29.9, df =
7,
P =
.0001GAT0.0480.0500.0510.09.93GGC0.0910.0310.0642.78.005GGT0.0390.0330.0360.77.44TAC0.2100.2770.241−1.88.06TAT0.1720.0640.1223.29.001TGC0.2380.2090.2240.16.88TGT0.1450.2360.186−1.90.06UCThree
SNPs TNFRSF1B region
(rs1061622,
rs1061624, rs3397)GAC0.0670.1010.078−0.92.36χ2 = 46.3, df = 7, P < .0001GAT0.0570.0500.0560.43.67GGC0.0910.0310.0673.32<.0001GGT0.0360.0330.0340.63.53TAC0.1790.2770.278−2.81.005TAT0.1700.0640.1282.76.006TGC0.2890.2090.2591.75.08TGT0.1120.2360.159−3.40.0007There was a significant difference between these haplotypes for CD
patients and control subjects (χ2 = 29.9, df = 7, P = .0001). In the three SNPs (rs1061622, rs1061624, and rs3397) in
CD, the frequencies of haplotypes of GGC (9.1% for case versus 3.1% for control
group, P = .005) and TAT (17.2% versus 6.4%, P = .001) were significantly different, with
haplotypes GGC and TAT occurring more in CD cases than the control group. TAC (21.0% versus 27.7%, P = .06) and TGT (14.5%
versus 23.6%, P = .06) were marginally significantly different between case and
control groups, occurring less frequently in the cases. Haplotype TAC was the
most common, with Hap-frequencies of 24.1%.
Haplotype GGT was the most uncommon in CD case (3.9%) and control (3.3%)
subjects, but occurred at equal frequencies in both (Hap-frequencies of 3.6%, P> .05). Haplotypes GAC, GAT, and TGC occurred at
equal frequencies in CD patients and control subjects (P> .05).There were also significant associations between these haplotypes
for UC cases as compared with control subjects (χ2 = 46.3, df = 7, P < .0001). For the three marker haplotypes (rs1061622, rs1061624, and rs3397), the
frequencies of haplotypes of GGC (9.1% versus 3.1%, P < .0001), TAC (17.9% versus
27.7%, P = .005), TAT (17.0% versus 6.4%, P = .006), and TGT (11.2% versus 23.6%, P = .0007)
were significantly different between case and control subjects. Haplotype TAC
was the most common in UC cases (Hap-frequency of 27.8%, P = .005), whereas haplotype
GGT was the most uncommon in UC patients and control subjects, with frequencies
of 3.6% and 3.3%, respectively (Hap-frequency = 3.4%, P = .53). The frequencies of GAC and TGC were lower
and the frequency of GAT higher in UC patients than control subjects, but there
was no statistically significant difference between them.


## 3.1. Haplotype Analysis

Table6 summarizes the results of haplotype analysis of the three TNFRSF1B
SNPs (rs1061622, rs1061624, and
rs3397). Haplotype frequencies were estimated, and association analyses were
performed with respect to CD and UC in New Zealand IBD patients and Caucasian
controls. A score for each haplotype
(Hap-score) was calculated and P-value also calculated for the significance of
each Hap-score. A positive hap-score implies that the haplotype occurs more
frequently in the CD or UC case group than control subjects. A global P-value
tests the overall association between haplotypes and the response.Table 6
Haplotype analysis of three-SNP TNFRSF1B haplotype in IBD status in New Zealand IBD patients and
Caucasians.
HaplotypeCase
frequencyControl
frequencyHap frequencyHap-scoreP-valueGlobal score statisticsCDThree
SNPs TNFRSF1B region
(rs1061622,
rs1061624, rs3397)GAC0.0570.1010.075−1.55.12χ2 = 29.9, df =
7,
P =
.0001GAT0.0480.0500.0510.09.93GGC0.0910.0310.0642.78.005GGT0.0390.0330.0360.77.44TAC0.2100.2770.241−1.88.06TAT0.1720.0640.1223.29.001TGC0.2380.2090.2240.16.88TGT0.1450.2360.186−1.90.06UCThree
SNPs TNFRSF1B region
(rs1061622,
rs1061624, rs3397)GAC0.0670.1010.078−0.92.36χ2 = 46.3, df = 7, P < .0001GAT0.0570.0500.0560.43.67GGC0.0910.0310.0673.32<.0001GGT0.0360.0330.0340.63.53TAC0.1790.2770.278−2.81.005TAT0.1700.0640.1282.76.006TGC0.2890.2090.2591.75.08TGT0.1120.2360.159−3.40.0007There was a significant difference between these haplotypes for CD
patients and control subjects (χ2 = 29.9, df = 7, P = .0001). In the three SNPs (rs1061622, rs1061624, and rs3397) in
CD, the frequencies of haplotypes of GGC (9.1% for case versus 3.1% for control
group, P = .005) and TAT (17.2% versus 6.4%, P = .001) were significantly different, with
haplotypes GGC and TAT occurring more in CD cases than the control group. TAC (21.0% versus 27.7%, P = .06) and TGT (14.5%
versus 23.6%, P = .06) were marginally significantly different between case and
control groups, occurring less frequently in the cases. Haplotype TAC was the
most common, with Hap-frequencies of 24.1%.
Haplotype GGT was the most uncommon in CD case (3.9%) and control (3.3%)
subjects, but occurred at equal frequencies in both (Hap-frequencies of 3.6%, P> .05). Haplotypes GAC, GAT, and TGC occurred at
equal frequencies in CD patients and control subjects (P> .05).There were also significant associations between these haplotypes
for UC cases as compared with control subjects (χ2 = 46.3, df = 7, P < .0001). For the three marker haplotypes (rs1061622, rs1061624, and rs3397), the
frequencies of haplotypes of GGC (9.1% versus 3.1%, P < .0001), TAC (17.9% versus
27.7%, P = .005), TAT (17.0% versus 6.4%, P = .006), and TGT (11.2% versus 23.6%, P = .0007)
were significantly different between case and control subjects. Haplotype TAC
was the most common in UC cases (Hap-frequency of 27.8%, P = .005), whereas haplotype
GGT was the most uncommon in UC patients and control subjects, with frequencies
of 3.6% and 3.3%, respectively (Hap-frequency = 3.4%, P = .53). The frequencies of GAC and TGC were lower
and the frequency of GAT higher in UC patients than control subjects, but there
was no statistically significant difference between them.


## 4. Discussion

The present results show that carrying a single variant allele in TNFRSF1B c.676T> C, 1663A > G, or
1690T > C has no significant effect on the overall risk of either CD or
UC. However, the risk of certain
phenotypes is affected by either of the latter two variant alleles. More
striking, however, is the effect of
carrying certain haplotypes, and specific combinations may either increase or
decrease the risk of either CD or UC in the New Zealand Caucasian population,
with strong statistical significance.TNFRSF1B is the main
TNF receptor found on circulating T cells [14]. The gene contains 10 exons,
spanning around 26 kb of genomic DNA and encoding 415 amino acids [14].
Cysteine-rich extracellular regions, comprising three to six disulfide-linked
domains, are considered to be important for ligand binding and are expressed
by several different cell types [29]. The protein produced by the gene forms a
heterocomplex with the product of TNFRSF1A,
leading to recruitment of two antiapoptotic proteins c-IAP1 and c-IAP2, both
of which possess E3 ubiquitin ligase activity. c-IAP1 has been suggested to
potentiate TNF-a induced apoptosis through the ubiquitination and degradation
of TNF-receptor-associated factor 2, which produces antiapoptotic signals. We
have previously shown that TNF-alpha polymorphisms may contribute significantly
to the risk of certain IBD phenotypes in the New Zealand
population [9]. The present data augment the previous
conclusion, that variant alleles associated with this pathway are important for
IBD risk in this population.There are limited data on the functionality
of the various SNPs in this gene. However,
the 676 T> G polymorphism replaces a methionine by an arginine, and is functional, as the cytotoxic activity is
increased [30]. The variant polymorphism
has been previously associated with susceptibility to familial rheumatoid
arthritis (RA) [20] and systemic lupus erythematosus (SLE) [21]. However,
association studies have suggested that the other SNPs considered in the
present study might be in linkage with a functional SNP, even if not themselves
functional [22, 23, 31]. Perhaps even more relevant to patients with IBD is
that associations have recently been demonstrated between a two allele
haplotypes and responses to IFB in Japanese CD patients [28, 32].Kawasaki et
al. [31] reported no association between the variant SNP at position 676
and the risk of either form of IBD in their Japanese database. These data are
consistent with our own findings in the present study. However, these data do
not agree with other observations in a European Caucasian population [23] which
associated TNFRSF1B with
clinical CD phenotypes. They studied a well-phenotyped cohort of 205 patients
with CD and 106 controls to associate the variant SNP at this position with
increased risk of CD (P = .034), but decreased risk with UC or with the need
for surgery. We suggest that the previous European consortium data had
insufficient power to conclusively decide a negative result.It is of some interest that we have associated differences in the
risk of certain IBD phenotypes with variant alleles in the other two SNPs
considered (1663A> G, or 1690T > C). A Japanese study considered 124 patients with CD, 106
patients with UC, and 111 unrelated healthy controls [22] for these same two
SNPs, while Waschke et al. [23] studied
the first but not the second in their European Caucasian group. Neither of
these previous reports demonstrated a statistically significant difference in
carrying either of the variant alleles. We note, however, that in the Japanese
population but not in European groups [23], C appears to be the major allele at
position 1493.Although Sashio et al. [22] reported only minor effects on
IBD risk associated with carrying any single variant allele, they found a
significant difference (odds ratio of 2.13) in carrier frequency for haplotype
AT (1466A, 1493T) between CD patients and the controls. These differences were most significant in CD
patients with either internal or external fistula, and/or who responded poorly
to nutritional, medical, or surgical therapy. Similar haplotype effects are
recorded in the present study. However, we are currently unable to find a
convincing explanation of the converse data for UC.Although the region containing this gene has not emerged
from recent whole genome association studies as a lead candidate in CD (WTCCC,
2007; Barrett et al. 2008) it is of interest that two of the genes consistently
appearing important are closely related to the present gene. The protein
product of TNFAIP3 (TNF-alpha- induced protein 3) inhibits TNF-alpha-induced
NFkB-dependent gene expression by interfering with transactivation signals. Markers
with lower levels of significance in these studies include one within TNFSF15
(tumour necrosis factor superfamily, member 15). Taken together, the present
data add support to an important role for TNF-alpha and related molecules in CD
susceptibility and progression.



---

*Source: 591704-2009-05-03.xml*