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Published ahead of print on May 25, 2006, doi:10.1165/rcmb.2006-0084OC
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American Journal of Respiratory Cell and Molecular Biology. Vol. 35, pp. 488-495, 2006
© 2006 American Thoracic Society
DOI: 10.1165/rcmb.2006-0084OC

Association of TNF Haplotypes with Asthma, Serum IgE Levels, and Correlation with Serum TNF-{alpha} Levels

Shilpy Sharma, Amit Sharma, Sarvesh Kumar, Surendra K. Sharma and Balaram Ghosh

Molecular Immunogenetics Laboratory, Institute of Genomics and Integrative Biology, Delhi; Department of Medicine, All India Institute of Medical Sciences, Delhi, India

Correspondence and requests for reprints should be addressed to Dr. Balaram Ghosh, Molecular Immunogenetics Laboratory, Institute of Genomics and Integrative Biology, Mall Road, Delhi-110007, India. E-mail: bghosh{at}igib.res.in


   Abstract
Top
 Abstract
Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
Both biochemical and genetic evidence have implicated the genes for TNF-{alpha} (TNFA) and lymphotoxin-{alpha} (LTA) in atopic asthma. Here, we report for the first time the association of their genotypes and haplotypes with atopic asthma in Indian populations. We genotyped seven single nucleotide polymorphisms, encompassing the two genes, in patients and control subjects in two independent cohorts. Serum TNF-{alpha} levels of selected individuals were measured and correlated with genotypes and haplotypes. The A allele of the TNFA–863C > A polymorphism was associated with reduced risk of asthma (P = 0.002 and 0.007 in Cohorts A and B, respectively), reduced TsIgE levels (P = 0.0024 and P = 0.0029 in Cohorts A and B, respectively), and reduced serum TNF-{alpha} levels (P < 0.05). A marginal association was also observed for LTA_NcoI polymorphism with asthma and TsIgE levels. Furthermore, analysis using HAPLO. STATS showed significant differences in the major haplotype frequencies (> 3%) between patients and control subjects (P = 0.002 and P = 0.006 for Cohorts A and B, respectively). Individually, the haplotype GATCCG was the most frequent in patients (P = 0.0029 and P = 0.0025 for Cohorts A and B, respectively), and was associated with high TsIgE and serum TNF-{alpha} levels, whereas AACACG was the most frequent in the control subjects (P = 0.0032 and P = 0.022 for Cohorts A and B, respectively), and was associated with low TsIgE and serum TNF-{alpha} levels. We also report here that the C > A substitution at position –863 of the TNFA influences the binding of nuclear proteins in electrophoretic mobility shift assay experiments. Thus, the TNFA–863C > A polymorphism in the promoter region of TNFA may influence TNF-{alpha} expression and affect TsIgE levels and susceptibility to asthma.

Key Words: asthma • haplotype • Indian population • LTA • TNF-{alpha}


   Introduction
Top
 Abstract
 Introduction
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 
TNF, classically considered to belong to T helper (Th) 1 profile, is among the preformed mediators released from mast cell (1). Elevated levels of TNF-{alpha} have been detected in sputum, bronchoalveolar lavage (BAL), and biopsy samples from patients with asthma (2). In addition, inhalation of TNF-{alpha} has been shown to cause airway hyperresponsiveness and increased sputum neutrophil counts in healthy volunteers (2). Lymphotoxin-{alpha} (LTA; alternative names: TNF-beta, TNFB), on the other hand, has roles in lymphocyte homing, formation of spleen and lymph nodes (3), B-cell proliferation, and IgE synthesis (4). LTA production is also differentially regulated in B cells from atopic and nonatopic donors of Italian origin (5).

The genes for TNF-{alpha} (TNFA) and LTA (TNFB), members of the TNF family, are located on chromosome 6p21.3, within the human major histocompatibility complex cluster, a region shown to be linked to atopic asthma by several genome-wide linkage studies (6–8). Both case-control and family-based studies performed in populations of diverse origin have shown that TNF polymorphisms and haplotypes are associated with asthma (6, 8–10). Particularly, the TNFA–308G > A promoter polymorphism has been reported to be associated with asthma (6, 10–14), increased bronchial hyperreactivity (15), and childhood asthma and wheezing (16, 17) in many independent studies. The A allele was shown to be associated with elevated TNF-{alpha} transcriptional activity in a B-cell line and with increased TNF levels in stimulated human white blood cells (6). The NcoI polymorphism (LTA_NcoI), present in intron 1 of LTA, has also been studied extensively (6, 18), and has been found to influence the level of LTA secretion (19). On the other hand, various other studies failed to show any association of TNF polymorphisms with asthma (6).

Therefore, it is imperative to identify polymorphisms and haplotypes in these genes that may predispose individuals to asthma in ethnically diverse populations, such as the Indian population. Here, we selected polymorphisms that have previously been used in studies evaluating the roles of TNF single nucleotide polymorphisms (SNPs) in various diseases. Our goal was to establish the association of these polymorphisms, both individually and at the haplotype level, with asthma and its associated quantitative trait, total serum IgE (TsIgE). We also attempted to correlate the polymorphisms within the TNFA gene with its level in serum. Here, we report that the A allele of the TNFA–863C > A polymorphism was associated with reduced risk of asthma, reduced TsIgE levels, and reduced serum TNF-{alpha} levels (P < 0.05). By constructing six-locus haplotypes, we identified GATCCG and AACACG as risk and protective haplotypes, respectively, for asthma. Interestingly, the risk haplotype was correlated with high serum TNF-{alpha} levels, whereas the protective haplotype was correlated with low serum TNF-{alpha} levels. The functional significance of the TNFA–863C > A polymorphism was investigated using electrophoretic mobility shift assay (EMSA). Interestingly, we observed that the C > A substitution at this position alters the binding of nuclear proteins. Its implication in the expression of TNF-{alpha} is discussed.


   MATERIALS AND METHODS
Top
 Abstract
 Introduction
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 References
 
Subjects
Unrelated patients with mild to moderate atopic asthma were recruited from various collaborating hospitals of Northern (Cohort A: n = 246) and Western India (Cohort B, n = 238) (Table 1). Ethical approval was obtained from the institutional review board of each hospital. A full verbal explanation was provided to all patients, who gave informed consent and participated in this study. The diagnosis of asthma was based on physician assessment that followed the guidelines of the National Asthma Education and Prevention Program (Expert Panel Report 2) (20). In the initial screening, subjects with self-reported history of breathlessness and wheezing were considered; however, only individuals with a family history of asthma/atopy were included in the final study. A detailed questionnaire was designed to include the clinical history, details of environmental factors, the geographic region of origin, and migration status of the participants (21). Patients had to satisfy at least two of the following criteria: (1) two or more episodes of wheezing and shortness of breath during the past year; (2) presence of bronchial hyperresponsiveness (FEV1 < 70% at the time of attack) and reversibility of wheezing and dyspnea, as documented by an inhalant bronchodialator–induced improvement of more than 15% (using albuterol/salbutamol); (3) hospitalization for asthma anytime in life; and (4) asthma therapy (Table 1). Atopy was defined as the presence of an immediate skin reaction (equal to or greater than histamine [3 mm diameter]) to 1 or more of 15 common environmental allergens used for the skin prick test. TsIgE levels were determined for all individuals using ELISA (21), except for a few individuals (< 10%) where sera were not available.


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  		TABLE 1. DEMOGRAPHIC PROFILE OF PATIENT AND THE CONTROL GROUPS

 
Healthy volunteers (referred to as normal control subjects) (n = 252 and 224 in Cohorts A and B, respectively) were recruited from the general population who answered negatively to a screening questionnaire for respiratory symptoms and/or history of allergic diseases. TsIgE levels were determined for all the control samples recruited for the study; however, pulmonary function test (FEV1 > 90%) and skin prick test were performed in > 63% of the control population, wherever consent was obtained. Individuals having a history of smoking and parasitic/helminthic infestations (as determined from the clinical histories) in the past 2 yr were excluded from the study.

The samples used in this study were collected from individuals on the basis of their family history, origin, and migration status; thus, the error due to stratification is minimized (Table 1). The genetic homogeneity between the two groups was also established by genotyping multiple microsatellite markers, as yet unlinked to asthma or related atopic disorders (21, 22). The panel of unlinked markers tested included: D20S117, D6S1574, D20S196, D6S470, D12S368, D16S404, D6S446, D16S3136, D6S441, D8S264, D8S258, D8S1771, D8S285, D8S260, D8S270, D8S1784, D8S514, D8S284, D8S272, D5S406, D5S416, D5S419, D5S426, D5S418, D5S407, D5S647, D5S424, D5S641, D5S428, D5S2027, D5S471, D5S2115, D5S436, D5S422, D5S408, D6S281, D6S308, D6S264, and D6S287.

Serum TNF-{alpha} Level Measurement
TNF-{alpha} levels in serum were determined by OPTEIA ELISA kit (BD Biosciences, San Jose, CA), per the manufacturer's instructions.

PCR Amplification and Genotyping
Genomic DNA was genotyped for polymorphisms in the TNFA and LTA genes using the respective primers (as shown in Table E1 in the online supplement). The TNFA–1031T > C (–1211T > C), TNFA–863C > A (–1043C > A), TNFA–857T > C (–1037T > C), TNFA–308G > A (–488G > A), and the two non-synonymous SNPs in the LTA gene (His51Pro [rs3093543] and Thr60Asn [rs1041981]) were studied using SNaPshot ddNTP Primer Extension Kit (Applied Biosystems, Foster City, CA). The LTA_NcoI polymorphism was assessed using NcoI restriction endonuclease digestion. The genotyping procedures are detailed in the online supplement.

Statistical Analysis
The allele frequencies were calculated and agreement with Hardy-Weinberg equilibrium was tested using a {chi}2 goodness-of-fit test for each locus. The differences in allele frequencies and genotype distribution of each polymorphism between the patients and control subjects was evaluated by using a 2 x 2 contingency {chi}2 test with 1 degree of freedom (df), and the odds ratios (OR) were calculated with 95% confidence intervals (CIs). Because there is no single best measure of linkage disequilibrium (LD) under all possible situations, pair-wise LD among the 7 SNPs in the control population was measured by complementary measures, D' and r2 by using the software EMLD (available online at: http://request.mdacc.tmc.edu/~qhuang/Software/pub.htm). D' is inversely biased with the sample size, and the degree of bias is greater for the SNPs with lower allele frequencies (23). On the other hand, r2 is highly dependent upon allele frequency. ANOVA was performed to test the effect of these polymorphisms and of disease status on TsIgE levels and serum TNF-{alpha} levels.

Haplotypes for each individual were inferred using two different statistical software packages—HAPLO.STATS version 1.2.2 (24) and PHASE version 2.0.2 (25). The software HAPLO.STATS computes scores to evaluate the association of a trait (disease status) with haplotypes when the linkage phase is unknown. We used HAPLO.STATS to compute the global statistic (which allows the testing of the significance of the association of all haplotypes) and a global P value in the patients and the control subjects using the haplo.cc option in the software. In addition, it also provides the haplotype-specific statistic (Hap-Score), which allows the comparison of each haplotype with a common selected haplotype, with the respective ORs and CIs. The haplotypes with a frequency less than 3% were later dropped from the test to include only the major haplotypes in the analysis by setting the haplo.min.count parameter to 25 for the final analysis. In addition, the primary difference in the haplotype frequencies obtained by PHASE was compared using clump22 software with 10,00,000 Monte-Carlo simulations (26).

Cell Culture
Human umbilical vein endothelial cells were isolated from human umbilical cord after mild trypsinization (27). Briefly, the cells were grown in M199 medium supplemented with 20% heat-inactivated FCS, 2 mM L-glutamine, 100 U/ml penicillin, 100 µg/ml streptomycin, 0.25 µg/ml amphotericin, endothelial cell growth factor (50 µg/ml), and heparin (5 U/ml). At confluence, the cells were subcultured using 0.05% trypsin–0.01 M EDTA solution and used between passages three and four for EMSA.

Preparation of Nuclear Extracts
The nuclear extracts were prepared from endothelial cells, as previously described (27) and stored at –80°C in small aliquots. The protein concentration in the extracts was estimated using the bicinchoninic acid method (27).

EMSA
In vitro binding reactions between 32P-end labeled double-stranded oligonucleotides, as described below, and nuclear extracts were performed in a total volume of 20 µl, containing 2 µl of 10x binding buffer (12 mM HEPES, 50 mM NaCl, 10 mM TrisCl [pH 7.5], 10% glycerol, 1 mM EDTA, and 1 mM DTT), 1 µl of 1.0 µg/µl poly dI-dC (Sigma, St. Louis, MO), and 10 µg of nuclear protein. This reaction was allowed to proceed at 25–28°C for 30 min before the addition of 2 µl of nondenaturing loading buffer (0.2% bromophenol blue, 20% glycerol). The samples were electrophoresed on 1.5-mm-thick 6% polyacrylamide gel using Tris-glycine buffer (pH 8.5), and visualized by autoradiography. 32P-end labeled double-stranded oligonucleotides TNFA–863C (5'-ACCCCCCCTTAACGAAGACA-3' and 5'-TGTCTTCGTTAAGGGGGGGT-3') and TNFA–863A (5'-ACCCCCACTTAACGAAGACA-3' and 5'-TGTCTTCGTTAAGTGGGGGT-3') were synthesized and used for the assay.


   RESULTS
Top
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 References
 
The physical distance between the LTA and TNFA genes is around 13 kb on chromosome 6p21 (Figure 1A). To explore the association between SNPs in these genes and asthma in the Indian population, we genotyped seven SNPs in the patients and control subjects in two independent cohorts (Cohorts A and B). Because the LD patterns were similar in the two cohorts (data not shown), the control samples from both the cohorts were combined for the LD analysis. As seen in Figure 1B, the LTA_NcoI variant was in complete LD with the LTA_His51Pro mutation (D' = 1.00; r2 = 1.00), so, for all further analysis, LTA_NcoI SNP was used. In addition, partial LD was observed between the TNFA–1031T > C and TNFA–863C > A polymorphisms (D' = 0.75 and r2 = 0.54; Figure 1B).


Figure 1
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  		Figure 1. (A) The schematic representation of the TNF genes (TNFA and LTA) on chromosome 6 with SNP locations (marked with arrow heads). The dark boxes denote exons, whereas the white boxes denote the 5' and 3' untranslated regions. (B) Pairwise LD for all two-way comparisons among the seven polymorphisms investigated in the TNF gene cluster with control individuals.

 
Association of TNF Polymorphisms with Asthma
The distribution of genotype frequencies for all the polymorphisms investigated was consistent with Hardy-Weinberg expectations in the patient and control groups of both cohorts (P > 0.05), except the TNFA–863C > A polymorphism, which deviated marginally from Hardy-Weinberg expectations in the patient population of Cohort A (P = 0.035). Individually, allele A of TNFA–863C > A was found to be protective (OR < 1) and, hence, negatively associated with asthma (P = 0.002 and 0.007 in Cohorts A and B, respectively) (Table 2). This significance was retained even after Bonferroni correction (raw P values were multiplied by 6; P = 0.012 and 0.014 for Cohorts A and B, respectively). At the level of genotypes, an increase in risk was observed when CA was changed to CC for this polymorphism (Table 2). In addition, a marginally significant association was also observed for the TNFA–308G > A and LTA_NcoI SNPs (Table2) at both the allelic and the genotypic levels (P < 0.05 in both cohorts).


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  		TABLE 2. DISTRIBUTION OF ALLELE AND GENOTYPE FREQUENCIES FOR THE TNF SNPS IN TWO COHORTS STUDIED

 
Association of TNF Polymorphisms with Total Serum IgE Levels
TsIgE values were found to follow a log normal distribution in both the cohorts. When the patients and control subjects were compared with respect to log total serum IgE values, a highly significant difference was obtained (F-ratio = 25.14, df = 1, P < 0.0001 for Cohort A, and F-ratio = 75.90, df = 1, P < 0.0001 for Cohort B, respectively).

The genetic effect of TNF polymorphisms was also tested on the total TsIgE levels, and a strong association was observed for the TNFA–863C > A polymorphism (Cohort A: F-ratio = 6.22, df = 2, P = 0.0024; Cohort B: F-ratio = 6.02, df = 2, P = 0.0029), whereas a marginally significant association was detected with respect to the LTA_NcoI (Cohort A: F-ratio = 3.6, df = 2, P = 0.029; Cohort B: F-ratio = 4.18, df = 2, P = 0.017) and TNFA–1031T > C polymorphism (Cohort A: F-ratio = 3.47, df = 2, P = 0.03; Cohort B: F-ratio = 3.53, df = 2, P = 0.03) (Table 3). These investigations were performed in patients with asthma (case-only association study).


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  		TABLE 3. LOG TsIgE LEVELS WITH RESPECT TO DIFFERENT GENOTYPES AND HAPLOTYPES OF TNF GENES*

 
Association of TNF Haplotypes with Asthma and Total Serum IgE Levels
Using six SNPs in the TNFA and LTA genes, haplotype frequencies were estimated using the software HAPLO.STATS. A highly significant difference was observed in the haplotypes frequencies between the patients and the control subjects (global-stat = 51.87, df = 14, P = 0.000003 in Cohort A, and global-stat = 47.12, df = 13, P = 0.000009 in Cohort B, respectively). Similarly, when the major haplotypes (frequency > 3%) were included in the analysis, a highly significant difference was observed in the haplotype frequencies between the patients and the control subjects (globat-stat = 22.13, df = 7, P = 0.002 for Cohort A, and global-stat = 19.9, df = 7, P = 0.006 for Cohort B, respectively) (Figure 2).


Figure 2
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  		Figure 2. The frequency distribution of the major haplotypes (frequency >= 3%) of the TNFA and LTA genes in patients and unrelated control subjexts in Cohorts A and B, respectively. The haplotypes were plotted on the x-axis and their respective relative frequencies (%) on the y-axis. Dark gray bars, patient A; diagonally hatched bars, control A; cross-hatched bars, patient B; light gray bars, control B.

 
Individually, the haplotype GATCCG was the most frequent in the patient population (Figure 2). The odds of patients rather than control subjects having the haplotype GATCCG was 1.50, with CI = 0.97–2.33 (Hap-Score = 2.97, P = 0.0029) and 1.61 with CI = 1.15–2.24 (Hap-Score = 3.02, P = 0.0025) in Cohorts A and B, respectively. These results remained significant even after Bonferroni correction (number of major haplotypes = 7; raw P values multiplied by 7; PA = 0.020 and PB = 0.018 respectively). These results suggest that the haplotype GATCCG is an important risk/susceptibility haplotype and is positively associated with asthma in the Indian population.

On the other hand, the haplotype distribution in the patients and control subjects identified AACACG as the most frequent haplotype in the control population (Figure 2). The odds of patients, rather than control subjects, having the haplotype AACACG was 0.65, with CI = 0.42–0.99 (Hap-Score = –2.94, P = 0.0032), and 0.73, with CI = 0.49–1.10 (Hap-Score = –2.29, P = 0.022) in Cohorts A and Cohort B, respectively. However, only the results in Cohort A remained significant after Bonferroni correction (number of major haplotypes = 7; raw P values multiplied by 7; PA = 0.022). These results suggest that the haplotype AACACG is an important protective haplotype in Cohort A (but not in Cohort B), and is negatively associated with asthma.

Another statistical software, PHASE, was also used to validate these results. Because the counts per haplotype were very low, Clump22 with 10,000,000 Monte-Carlo simulations was used. Haplotype frequencies showed highly significant differences between the patients and control subjects (normal (T1) {chi}2 = 79.08, df = 21, P = 0.000000, and maximum (T4) {chi}2 = 43.68, P = 0.000001 for Cohort A; normal (T1) {chi}2 = 63.77, df = 20, P = 0.000002 and maximum (T4) {chi}2 = 30.32, P = 0.0001 for Cohort B, respectively).

As HAPLO.STATS is limited to not providing diplotype data while analyzing quantitative traits, such as TsIgE levels, the diplotypes were constructed by PHASE and used for the analysis. In the patient-only analysis, the risk haplotype (GATCCG) was weakly associated with TsIgE level (Cohort A: F-ratio = 3.17, df = 2, P = 0.047; and Cohort B: F-ratio = 3.58, df = 2, P = 0.03). The individuals homozygous for this haplotype had higher TsIgE levels as compared with the individuals heterozygous for the haplotype (Table 3). On the other hand, the protective haplotype, AACACG, was associated with lower TsIgE levels in both cohorts (Cohort A: F-ratio = 6.19, df = 2, P = 0.002; and Cohort B: F-ratio = 4.27, df = 2, P = 0.015).

Functional Correlation of TNFA Polymorphisms with Serum Levels of TNF-{alpha}
To find any functional correlation between TNFA polymorphisms and its expression in the serum, we measured TNF-{alpha} levels in serum of 113 unrelated individuals using ELISA, as described in MATERIALS AND METHODS. The TNFA–1031T > C and TNFA–863C > A polymorphisms were found to influence TNF-{alpha} levels in the serum (F-ratio = 7.0, df = 2, P = 0.0014; and F-ratio = 6.47, df = 2, P = 0.0022, respectively). The presence of TNFA–1031C and TNFA–863A alleles seem to be associated with lower TNF-{alpha} levels (Table 4).


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  		TABLE 4. SERUM TNF-{alpha} LEVELS IN CONTEXT OF DIFFERENT TNF GENOTYPES AND HAPLOTYPES

 
Furthermore, when haplotypes (counts >= 2) were analyzed for TNF-{alpha} levels, a significant difference was observed (F-ratio = 2.90, df = 6, P = 0.01). As seen in Table 4, the individuals homozygous for the protective haplotype AACACG had the lower TNF-{alpha} levels when compared with individuals homozygous for the risk/susceptibility haplotype GATCCG.

Allele-Specific Binding of Nuclear Protein to the TNFA–863C > A Polymorphic Site
To test the effect of –863C > A substitution in the interaction with nuclear proteins, we performed EMSA using nuclear extracts derived from human umbilical vein endothelial cells (known to induce TNF-{alpha} upon stimulation [28]) and oligonucleotides containing C or A variant, as detailed in MATERIALS AND METHODS. Distinct differences were observed in the binding of the 20-bp DNA fragments containing either the –863C or the –863A variant of the TNFA promoter (Figure 3A). Two distinct DNA–protein complexes (complex A and complex B) were detected for the –863C probe (lanes 8 and 9, Figure 3A), whereas, –863A probe failed to form any appreciable amount of these complexes (lanes 2–6, Figure 3A). The specificity of these complexes was tested using 150-fold excess of the unlabeled C probe (lane 10, Figure 3A) and an irrelevant AP-1 oligo (lane 12, Figure 2A). The unlabeled C probe inhibited the formation of these complexes, whereas irrelevant AP-1 oligo was unable to do the same. Moreover, competition experiments using increasing concentrations of the unlabeled A probe demonstrated an inability to inhibit the formation of the complexes formed with the C probe (lanes 3–6, Figure 3B). In contrast, the unlabeled C probe, even with 40-fold excess, was able to inhibit the complex formation (lane 8, Figure 3B). Therefore, the A variant is neither able to bind to nuclear proteins nor to inhibit the binding of these proteins with the C variant.


Figure 3
Figure 3
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  		Figure 3. Analysis of differential binding of nuclear proteins to the A and C allele of TNFA–863C > A polymorphism by EMSA, as described in the MATERIALS AND METHODS. Nuclear extracts prepared from LPS-induced human umbilical vein endothelial cells were incubated with 32P–end labeled, double-stranded oligonucleotides representing the A and C variants. (A) Lanes 1–6 show interaction with the A allele, whereas lanes 7–12 show interaction with the C allele. Lanes 1 and 7 represent free probe without the nuclear extract; lanes 5, 11, 6, and 12 represent the complexes formed when the nuclear extract was preincubated with NF-{kappa}B oligo and an irrelevant AP-1 oligo, respectively. (B) Lane 1 represent free probe without the nuclear extract, whereas in lanes 3–6, the DNA–protein complexes were preincubated with increasing concentrations of the unlabeled A probe, and in lanes 7–10 the DNA–protein complexes were preincubated with increasing concentrations of the unlabeled C probe. Lanes 11 and 12 represent the complexes formed when the nuclear extract was preincubated with increasing concentrations of the NF-{kappa}B oligo.

 
As proposed in an earlier study, the region containing the –863C > A substitution (–869 to –850) overlaps with a nuclear factor-{kappa}B (NF-{kappa}B) binding site (25). We tested this hypothesis by performing competition experiments with unlabeled NF-{kappa}B oligo. Interestingly, even 150-fold excess of NF-{kappa}B oligo was unable to inhibit the binding of nuclear proteins with the C variant (lane 11, Figure 2A; lanes 11–12, Figure 2B), indicating that this region might not contain any overlapping NF-{kappa}B sites. Taken together, these results indicate that there are specific DNA-binding proteins interacting in this segment of the TNFA promoter, and that these interactions are substantially altered due to the C > A substitution at position –863.


   DISCUSSION
Top
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
References
 
To elucidate the role of TNF-{alpha}/LTA in asthma pathogenesis, we genotyped known polymorphisms in these two genes. As there is evidence for transcriptional regulation of TNFA gene expression, we concentrated on promoter polymorphisms, non-synonymous variants, and polymorphisms already linked to TNF levels.

Our data presented here strongly suggest that polymorphisms and haplotypes in these two genes are associated with asthma in the Indian population. Interestingly, the A allele of the TNFA–863C > A polymorphism was associated with reduced risk of asthma, reduced TsIgE levels (Table 3), and reduced serum TNF-{alpha} levels (Table 4). In addition, because a moderate level of LD exists between the TNFA–1031 and TNFA–863 polymorphisms (D' = 0.75, r2 = 0.55), the TNFA–1031 polymorphism was also shown to affect the TsIgE (Table 3) and serum TNF-{alpha} levels (Table 4). A marginal association was also observed for LTA_NcoI polymorphism with asthma (Table 2) and TsIgE levels (Table 3). The minor G allele for this SNP was associated with higher TsIgE levels (Table 3). Our results are supported by an earlier study, in which the GG genotype for this locus was associated with increased IgE levels in females (10). It is important to note that the TsIgE levels in the control subjects recruited in our study were higher than those of the western population(s), as also observed previously (22).

Although we obtained marginal significance for TNFA–308 SNP with asthma in both our cohorts, when analysis was performed with respect to serum IgE and serum TNF-{alpha} levels, no association was observed. A recent study performed in the North- Indian population also reported a marginal association between the TNFA–308 SNP and seasonal and late-onset asthma; however, no attempts were made to correlate TNFA–308 SNP with TsIgE and serum TNF-{alpha} levels (11). It is also evident from the study by Knight and colleagues that the TNFA–308 SNP does not regulate TNF levels, and is not likely to be the functionally important SNP, as previously hypothesized (29).

To further supplement our understanding of the contributions of these genetic variants to asthma, we constructed six-locus haplotypes and studied their distribution in the patient and the control populations. The haplotype GATCCG was identified as the risk/susceptibility haplotype, whereas AACACG was identified as the protective haplotype. In addition, the risk haplotype was associated with increased TsIgE and serum TNF-{alpha} levels, whereas the protective haplotype was associated with lower TsIgE and serum TNF-{alpha} levels. Our results are supported by a study performed with a Japanese population (9), which reported an increased transmission of the C allele of the TNFA–857C > T polymorphism and the TNFA–1031T_–863C_–857C haplotype to children with asthma. In addition, individuals homozygous for this haplotype had the highest TNF-{alpha} levels as compared with other individuals. The TNFA–308 SNP was not detected in that Japanese population (9). It is to be noted that our risk haplotype (GATCCG) is an expanded haplotype in comparison to their TNFA–1031T_–863C_–857C haplotype. Our results are also supported by a study performed in Korean patients with asthma (10). That study revealed marginally significant differences in the total IgE levels corresponding to the different genotypes for LTA_NcoI polymorphism and the extended haplotype (ht-1, similar to our risk haplotype GATCCG) formed using the polymorphisms in the TNF genes (10).

Another study conducted in the Japanese population performed haplotype analysis of a 100-kb region spanning the TNF-LTA genes (8). The workers identified the LTA_–753G > A polymorphism and its associated haplotypes to be significantly associated with asthma (8). However, they failed to find association with the TNFA–863C > A polymorphism. Our results are supported by another study in whites (6), in which there was an increase in transmission of LTA NcoI_G/TNFA–308G haplotype. Knight and colleagues have identified functionally important LTA/TNF haplotypes, and have correlated them with allele-specific transcription of LTA in lymphoblastoid cell lines (29). However, our risk/susceptibility haplotype (GATCCG) and two other major haplotypes (AACCCG and AATACG) were absent in their analysis. Detailed analysis of LTA polymorphisms and their effect on the transcription of LTA gene in the Indian population remains to be undertaken in the future.

Interestingly, the A allele of the TNFA–863C > A polymorphism correlated with reduced serum TNF-{alpha} levels (Table 4). Our genetic results are supported by results from our EMSA studies, which indicate that the –863C > A polymorphism strongly influences the specific binding of nuclear protein(s), with stronger binding occurring in the C allele (Figure 3A). It is noteworthy that this polymorphism is situated at the border of a 10-bp sequence, which shows considerable similarity with the consensus sequence of the NF-{kappa}B p50 binding site. However, competition experiments indicated that a 150-fold excess of unlabeled NF-{kappa}B oligo was unable to abolish the binding of nuclear proteins with the –863C variant. Thus, the sequence contained in the oligonucleotide (positions –869 to –850) may not contain any NF-{kappa}B binding site. It is, therefore, likely that the C variant promotes the binding of nuclear factors other than NF-{kappa}B to the TNF-{alpha} gene promoter, which may lead to an increase in TNF-{alpha} expression. However, this proposition needs to be confirmed in the future. Also, the possibility that other mutations, linked to TNFA–863C > A polymorphism, may influence the expression of TNF-{alpha} cannot be excluded.

Previous in vivo studies of the TNFA–863C > A polymorphism have yielded a confusing picture (30–32). The A allele has been reported to be associated with elevated TNF production by peripheral blood mononuclear cells stimulated with concanavalin A (32). In contrast, no effect of this polymorphism was seen in chloramphenicol acetyl transferase reporter gene assays when TNF-{alpha} transcription was analyzed in vitro in T- and B-cell lines (33). Moreover, the A allele has been associated with a marked decrease in the basal rate of TNF-{alpha} transcription in vitro in HepG2 cells (30). Our results are similar to those of the latter study, where the A allele was associated with a decreased basal transcription rate and with significantly lower serum TNF-{alpha} levels in a well-defined group of apparently healthy, middle-aged men of Swedish origin (30). However, another study using adenoviral reporter assay, showed contradictory results, in which the C variant was shown to bind to p50-p50 homodimer, and was associated with reduction of LPS-inducible gene expression in primary human monocytes (31). In contrast, studies by Skoog and colleagues were unable to demonstrate an allele-specific response in LPS-induced transfection experiments using the TNFA–863C > A constructs, thereby negating the presence of an inducible NF-{kappa}B site (30). It is also to be noted that, in the adenoviral reporter experiments (31), the concentration of p50-p50 homodimer was much greater than the normal physiologic concentration and, therefore, may not represent the exact function of this site.

Because asthma is a complex disorder, we conducted a case–control study here that could provide better indications on promising loci (21). These leads can be further tested using a well controlled, family-based study. Moreover, the additional unlinked regions used as controls (21), and validation of our results in another independent cohort, only added more confidence to our results.

In summary, this is the first study from the Indian subcontinent identifying risk and protective genotypes and haplotypes in the TNF gene cluster, which are associated with asthma and TsIgE and serum TNF-{alpha} levels. The EMSA data presented here also indicate that the TNFA–863C > A polymorphism in the promoter region of the TNFA gene influences TNF-{alpha} expression directly/indirectly, and thus may affect TsIgE levels and susceptibility to asthma. However, the identification and characterization of the nuclear proteins binding to this region of the promoter remain to be undertaken.


   Acknowledgments
 
The authors thank their collaborating physicians for help in sample collection. They also thank all patients and healthy volunteers for participating in this study, and acknowledge Mr. Rajshekhar Chatterjee, Ms. Mamta Sharma, Ms. Jyotsna Batra, Mr. Amrendra Gupta, Ms. Deepti Mann, and Dr. U. Mabalirajan for their help. Shilpy Sharma, Amit Sharma, and Sarvesh Kumar acknowledge the Council for Scientific and Industrial Research, Government of India, for their fellowship.


   Footnotes
 
This work was supported by the Council for Scientific and Industrial Research (Task Force project SMM0006), India.

This article has an online supplement, which is accessible from this issue's table of contents at www.atsjournals.org

Originally Published in Press as DOI: 10.1165/rcmb.2006-0084OC on May 25, 2006

Conflict of Interest Statement: None of the authors has a financial relationship with a commercial entity that has an interest in the subject of this manuscript.

Received in original form February 24, 2006

Accepted in final form May 8, 2006


   References
Top
 Abstract
 Introduction
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 References
 

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