HLX1 gene variants influence the development of childhood asthma

Article Outline

• Abstract
• Methods
  • Population description for association studies
  • Resequencing and mutation screening
  • Genotyping
  • Luciferase assay
  • Electrophoretic mobility shift assay
  • Statistical analysis
• Results
  • Mutation screening and polymorphism identification in the HLX1 gene
  • HLX1 SNP selection for genotyping
  • Association studies with selected HLX1 SNPs
  • HLX1 SNP selection for functional studies
  • Promoter polymorphism–dependent HLX1 gene expression analysis
  • Transcription factor binding analysis of HLX1 promoter polymorphisms
• Discussion
• Acknowledgment
• Fig E1. 
• Table E1. 
• Table E2. 
• Table E3. 
• Table E4. 
• Table E5. 
• References
• Copyright

Background

Major transcription factors controlling T_H1 and T_H2 development, such as T-box transcription factor and GATA3, might be centrally involved in asthma and atopic diseases. Only recently, the homeobox transcription factor H.20-like homeobox 1 (HLX1), interacting closely with T-box transcription factor, has been identified as an important regulator of T_H1 differentiation and suppressor of T_H2 commitment.

Objective

We investigated whether genetic variations in the HLX1 gene exist and whether these could affect the development of childhood asthma.

Methods

The HLX1 gene was resequenced in 80 chromosomes. Associations between identified polymorphisms, asthma, and atopic diseases were investigated in German children (total n = 3099) from the cross-sectional International Study of Asthma and Allergy in Childhood phase II. Functional properties of polymorphisms were studied by using luciferase reporter gene assays and electrophoretic mobility shift assays in T cells. All statistical analyses were performed with SAS/Genetics software (SAS Institute, Inc, Cary, NC).

Results

Nineteen polymorphisms were identified in the HLX1 gene, and 2 tagging single nucleotide polymorphisms representing 7 polymorphisms were associated with childhood asthma in our study population. Two promoter polymorphisms, C−1407T and C−742G, contained in 1 tagging block were associated with asthma (odds ratio, 1.44; 95% CI, 1.11-1.86; P = .0061), significantly decrease promoter transactivation, and disrupt specificity protein–transcription factor binding in in vitro experiments.

Conclusions

Our data suggest that polymorphisms in the HLX1 gene increase the risk for childhood asthma. On the cellular level, altered binding of specificity protein–transcription factors to the HLX1 promoter and subsequent changes in HLX1 gene expression might contribute to these effects.

Key words: HLX1, asthma, association study, genetic analysis, functional promoter analysis

Abbreviations used: HLX1, H.20-like homeobox 1, EMSA, Electrophoretic mobility shift assay, LD, Linkage disequilibrium, MAF, Minor allele frequency, OR, Odds ratio, SNP, Single nucleotide polymorphism, SP, Specificity protein, T-bet, T-box transcription factor, UTR, Untranslated region

Asthma and allergy are common diseases during childhood, but the underlying mechanisms are still not well understood. However, the involvement of T cell–regulated inflammation and T_H2-associated cytokine expression in the development and perpetuation of these diseases is undisputed.¹, ² Signature transcription factors, such as the T cell–specific T-box transcription factor (T-bet) and the GATA binding protein 3 (GATA3), control T_H1 and T_H2 development from naive T_H cells and might thus be centrally involved in the development of allergy and asthma. Although GATA3 induces T_H2 development associated with the secretion of IL-4, IL-5, and IL-13,³ T-bet is responsible for the activation and maintenance of T_H1 development by inducing IFN-γ production.⁴ However, T-bet is only capable of inducing maximal IFN-γ release in cooperation with a second transcription factor, the homeobox transcription factor HLX1 (H.20-like homeobox 1), which itself is regulated by T-bet.⁵ In combination, T-bet and HLX1 actively suppress T_H2 commitment. HLX1 downregulates the IL-4 receptor α expression in naive CD4 T cells.⁶ Furthermore, T-bet and HLX1 have the unique ability to revert T_H2 cell commitment of T_H cells already expressing T_H2 cytokines.⁵

Thus it was speculated that genetic alterations in T_H1/T_H2 signature transcription factors might lead to a deregulation of immune responses and have considerable effect on the development of atopic diseases. Indeed, results of recent studies had identified common variants in the gene encoding T-bet that were associated with asthma in some,⁷, ⁸, ⁹ but not all, studies.¹⁰, ¹¹ Considering the close interaction between T-bet and HLX1, we hypothesized that genetic alterations in HLX1 might also contribute to the pathogenesis of asthma. Therefore we investigated whether genetic variations in the HLX1 gene exist that could affect the development of allergic diseases and asthma in a cross-sectional study population of German children (total n = 3099).

Back to Article Outline

Methods 

Population description for association studies 

The cross-sectional International Study of Asthma and Allergy in Childhood phase II was performed with the same standardized and validated study tools in Munich and Dresden.¹² The prevalence of asthma and allergies in 5629 schoolchildren ages 9 to 11 years was assessed based on self-administered questionnaires and objective measurements, such as lung function tests, skin prick tests, and serum IgE measurements. Descriptive demographics are shown in Table E1 (available in this article's Online Repository at www.jacionline.org).

Children whose parents reported a physician's diagnosis of asthma (at least once) or of spastic or asthmatic bronchitis (at least twice) in a self-administered questionnaire were classified as having asthma. Children's classification of hay fever or atopic dermatitis was based on a parental report of a physician's diagnosis of the respective diseases.

The sensitivity to 6 common aeroallergens (Dermatophagoides pteronyssinus, Dermatophagoides farinae, Alternaria tenuis, cat dander, and mixed grass and tree pollen) was assessed by means of skin prick testing with standardized extracts and lancets (ALK-Abelló, Hørsholm, Denmark). A child was considered atopic if a wheal reaction of 3 mm or greater occurred to 1 or more specific allergens after subtraction of the negative control's wheal size. Total serum IgE levels were measured by using the Immulite System (DPC Biermann, Bad Nauheim, Germany). All children of German origin with DNA and serum IgE measurements available were included in this analysis (n = 3099). Written informed consent was obtained from all parents of children included in the study. All study methods were approved by the appropriate ethics committees.

Resequencing and mutation screening 

Twenty-two overlapping fragments were designed to investigate all exons and introns to cover 7919 bp of continuous sequence in and around the HLX1 gene. Additionally, 1934 bp upstream (based on the first ATG of exon 1) and 1155 bp downstream of exon 4 were sequenced, thereby including the 5′ untranslated region (UTR) and 3′UTR. Gene fragments of interest were amplified by means of PCR with specific primers (see Table E2 in this article's Online Repository at www.jacionline.org). Primers were designed with the NetPrimer software and obtained from Metabion GmbH (Planegg-Martinsried, Germany). PCR was carried out on standard cyclers (Eppendorf GmbH, Eppendorf, Germany) in a total volume of 50 μL with 60 ng of genomic DNA, a primer concentration of 0.25 μL each, 0.2 mmol/L of each deoxyribonucleoside triphosphate, and 0.8 U of Taq DNA Polymerase. PCR fragments were sequenced in 80 chromosomes from 40 unrelated randomly selected German adult volunteers by using an ABI 3730 sequencer (Applied Biosystems, Lincoln, Calif).

Genotyping 

Genomic DNA was extracted from whole blood by using a standard salting-out method.¹³ To minimize the use of genomic DNA in further analyses, a modified primer extension preamplification¹⁴ or alternatively the GenomiPhi procedure (Amersham Biosciences, Freiburg, Germany) were applied for random DNA before amplification. DNA samples were genotyped by using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (Sequenom, Inc, San Diego, Calif). PCR assays and associated extension reactions were designed by using the SpectroDESIGNER software (Sequenom, Inc). All amplification and extension reaction conditions have been previously described,¹⁵ and specific primers are shown in Table E3 (available in this article's Online Repository at www.jacionline.org). Primer extension products were loaded onto a 384-element chip with a nanoliter pipetting system (SpectroCHIP, SpectroJet, Sequenom) and analyzed by using a MassARRAY mass spectrometer (Bruker Daltonik GmbH, Bremen, Germany). The resulting mass spectra were analyzed for peak identification with the SpectroTYPER RT 2.0 software (Sequenom, Inc). For quality control, Hardy-Weinberg calculations were performed to ensure that each marker was within the expected allelic population equilibrium.

Luciferase assay 

Jurkat T cells obtained from the German Collection of Microorganisms and Cell Cultures (Braunschweig, Germany) were seeded in a 96-well plate at a density of 8 × 10⁴ cells per well. The next day, cells were transfected with 35 ng of pGL3 plasmids, expressing a luciferase gene under the control of the HLX1 promoter containing wild-type or polymorphic alleles at positions C−1407T, C−742G, or both together with 15 ng of pRL-TK Renilla reporter plasmid (Promega, Madison, Wis) for normalization of transfection efficiency and cell viability. Xtreme Gene Q was used as transfection reagent, according to the manufacturer's protocol (Roche, Mannheim, Germany). Eight hours after transfection, medium was exchanged with medium containing various concentrations of ionomycin (2 or 50 ng/mL) or medium alone. After 18 hours' incubation, cells were washed in PBS and lysed in 1× passive lysis buffer (Promega). The dual luciferase assay was performed according to the manufacturer's instructions (Promega) by using a Genios Pro luminometer (Tecan, Bubendorf, Switzerland).

Electrophoretic mobility shift assay 

Nuclear extract was prepared from 14 × 10⁶ unstimulated Jurkat T cells, as previously described.¹⁶ Nuclear extracts were placed in aliquots and stored at −80°C. The protein concentration of nuclear extract was determined by using the bicinchoninic acid kit (Pierce, Rockford, Ill). Electrophoretic mobility shift assays (EMSAs) were performed by using 31-bp oligonucleotides carrying wild-type or polymorphic alleles at positions −1407 and −742 (C−1407T: 5′-ACCACGCAGCTCCTC [C/T] TGCAACCAG GCCCAA-3′; C−742G: 5′-CCTGTGATCAAC [C/G] CTCCTTGCCCCGTGG-3′). As controls, oligonucleotides were used that contain a known specificity protein (SP) binding site (5′-ATTCGATCGGGGCGGGGCGAGC-3¹⁷) or an unrelated binding site (position −1127/−1097 of the IL13 5′-flanking region: 5′-GGACTTCTAGGAAAACGAGGGAAGAGCAGGA-3^′18). Annealing of the complementary oligonucleotide pairs was carried out in 10 mmol/L Tris Cl (pH 8), 1 mmol/L EDTA, and 100 mmol/L NaCl by boiling the samples for 5 minutes and cooling slowly to 37°C. Purified double-stranded probes (100 ng) were end-labeled with γ[³²P]–adenosine triphosphate (250 μCi) with T4 polynucleotide kinase (New England Biolabs, Ipswich, Mass). Free radioactivity was removed with mini Quick Spin Oligo Columns (Roche, Mannheim, Germany). For EMSA experiments, each binding reaction (20 μL) contained 5 μg of nuclear extract, 1× binding buffer (10 mmol/L Tris Cl [pH 8], 1 mmol/L EDTA, 0.1 mmol/L β-mercaptoethanol), and 1 μg/reaction poly(dI-dC)–poly(dI-dC) and was adjusted for a final concentration of 80 mmol/L NaCl and 4% glycerol. The respective ³²P-labeled protein/DNA complexes were resolved on a 5% polyacrylamide gel and run for 6 hours at 18 to 22 mA with 0.5× Tris-borate-EDTA buffer at 4°C. All EMSA experiments were performed under the described conditions by using probes either carrying the wild-type or polymorphic alleles.

Statistical analysis 

Linkage disequilibrium (LD) patterns were assessed by using Haploview software.¹⁹ Deviations from Hardy-Weinberg equilibrium were analyzed by using the χ² test, with expected frequencies derived from allele frequencies. Association between single nucleotide polymorphisms (SNPs) and dichotomous outcomes were tested by using χ² tests. As a reference group for every phenotype, children without the phenotype were used, irrespective of the other phenotypes. Reference groups for atopic or nonatopic asthma were also nonasthmatic subjects. The dominant model showed the best fit for the HLX1 data. Results of the dominant model are reported, resulting in P values for Pearson χ² tests, odds ratios (ORs), and 95% CIs. Logistic regression analysis was used to calculate adjusted ORs, and P values of the Wald test are reported in adjusted analyses (see Table E4 in this article's Online Repository at www.jacionline.org). Haplotype frequencies were estimated by using the EM algorithm, and haplotypes with frequencies of greater than 0.03 were analyzed with haplotype trend regressions, in which the estimated probabilities of the haplotypes are modeled in logistic regression as independent variables.²⁰

A Bonferroni correction was used for every phenotype of each tagging SNP to check for multiple testing in the single-SNP analyses of the pooled population (n = 3099). Haplotype analyses were corrected for the number of common haplotypes. Additionally, a homogeneity analyses was performed in 2 different populations (Dresden, n = 1940; Munich, n = 1159) to validate the effects observed for tagging SNPs. All tests were 2-sided, and the differences were considered significant at a P value of .05 or less. Calculations were carried out with SAS (9.1.3) and SAS/Genetics software (SAS Institute, Inc, Cary, NC).

Transcription factor binding site analysis was performed with MatInspector²¹ and Alibaba 2.1²² software.

Back to Article Outline

Results 

Mutation screening and polymorphism identification in the HLX1 gene 

By using overlapping PCR fragments, the complete length of the HLX1 gene, including all exons, introns, and flanking regions, was sequenced in 40 adult volunteers of German origin. Nineteen SNPs with minor allele frequencies (MAFs) of at least 3% were identified in the region of the HLX1 gene (Table I), whereof 3 (A-1663G, C-796A, and C+3958T) polymorphisms were previously not described and submitted to the public SNP databases (dbSNP). Six polymorphisms were found in the promoter region, 3 in the 5′UTR, 5 in the intronic region, and 1 in the 3′UTR. Four SNPs were located in the coding region, of which 3 resulted in a putative amino acid change in the HLX1 protein.

Table I. Description of HLX1 polymorphisms and their respective position within the gene, rs numbers, allele frequencies, LD, tagging SNPs, genotyping call rates in percentages, and the P value for a deviation from Hardy-Weinberg equilibrium in 1940 children from Dresden

Call R%, Genotyping call rates in percentage; HWE, Hardy-Weinberg equilibrium.

HLX1 SNP selection for genotyping 

The LDs between polymorphisms showing an MAF of at least 3% were calculated to identify tagging SNPs for the genotyping of the HLX1 gene (Fig 1). Based on the screening population of 80 chromosomes, 5 major LD blocks with r² values of 0.8 or greater were observed, whereas 5 SNPs could not be attributed to any LD block in the screening population. These 5 SNPs (C−1407T, C−796A, C−742G, C−559T, and G+4447A) and 1 tagging SNP per LD block (C−1486G, T+346C, G+2256A, T+3183A, and C+3958T) were genotyped in a cross-sectional study population of 1940 children from Dresden, and LD was reassessed (see Fig E1 in this article's Online Repository at www.jacionline.org). In this larger population one of the SNPs (C−796A) was too infrequent to further qualify as an SNP (with an MAF of 2%), whereas all other SNPs could be assigned to one of the 5 previously defined LD blocks (Table I). Tagging SNPs for the 5 LD blocks (all exceeding an MAF of 10%) were then genotyped in the second part of the study population (n = 1159 from Munich).

• 
  • View Large Image
  • Download to PowerPoint

• Fig 1. 

  Structure of the HLX1 gene on chromosome 1q41 and the LD (r² plot) between the HLX1 polymorphisms (MAF >3%) identified in the screening population (n = 40). Color code for the LD plot is produced by using Haploview software: white (r² = 0), shades of gray (0 < r² < 1), and black (r² = 1).

Association studies with selected HLX1 SNPs 

HLX1-tagging SNPs representing blocks 2 and 3 showed significant associations with asthma in the cross-sectional study population of children from Dresden and Munich (n = 3099, Table II). The polymorphic allele of SNP T+346C, tagging block 3 and leading to a putative amino acid change in exon 1, was protective against the development of asthma (OR, 0.73; 95% CI, 0.56-0.95; P = .0172), whereas the minor allele of SNP C−1407T, representing block 2, significantly increased the risk of asthma (OR, 1.44; 95% CI, 1.11-1.86; P = .0061). For both SNPs, these effects were slightly stronger for nonatopic asthma. The effect for C−1407T stays also significant after correction for multiple testing in the pooled sample. In addition, the homogeneity analyses demonstrated that the observed effects of both polymorphisms show the same trends in Munich and Dresden (see Table E5 in this article's Online Repository at www.jacionline.org).

Table II. Associations between HLX1 tagging SNPs and asthma (divided into atopic and nonatopic asthma), atopic dermatitis, hay fever, and atopy

Associations are given in terms of ORs (95% CIs) for dominant effects in the pooled cross-sectional study population (pooled population, total n = 3099). Significant associations are shown in boldface.

Furthermore, the polymorphism at position C−1486G, representing block 1, resulted in a borderline protective effect concerning nonatopic asthma (OR, 0.64; 95% CI, 0.41-1.00; P = .0502). No significant associations with other atopic phenotypes, such as atopic dermatitis, hay fever, or atopy, were observed.

Next, haplotype analyses with the HLX1 region were conducted (Table III). The haplotype H_b (C-C-C-G-T) showed a borderline significant protective effect against asthma (OR, 0.64; 95% CI, 0.40-1.00; P = .052). The haplotype H_c (C-T-T-A-T) significantly increased asthma risk (OR, 1.86; 95% CI, 1.21-2.87; P = .005).

Table III. Estimated haplotype frequencies in the pooled cross-sectional study population (total n = 3099) built of the 5 tagging SNPs (C−1486G, C−1407T, T+346C, G+2256A, and T+3183A) and association tests for individual haplotypes with asthma

P values, ORs, and 95% CIs are shown by haplotype trend regression (HTR). Significant associations are shown in boldface.

HLX1 SNP selection for functional studies 

Taken together, association results suggested that HLX1 LD blocks 2 (C−1407T, C−742G, T−429G, C+3958T, and G+4447A) and 3 (T+346C and C+1562G) might play a role in the pathogeneses of asthma. Functional studies were needed to discriminate those SNPs within the respective LD blocks responsible for the observed effects because the LD was too strong to further dissect the origin of effects by association studies. Within block 2, associated with a significant increase in asthma risk, 2 SNPs (C−1407T and C−742G) were located in the promoter region, 1 in the 5′UTR (T−429G), 1 in intron 3 (C+3958T), and 1 synonymous SNP in exon 4 (G+4447A). Based on the position of these SNPs, we first thought to determine whether the 2 promoter SNPs might lead to a change in HLX1 gene expression.

Promoter polymorphism–dependent HLX1 gene expression analysis 

Luciferase reporter constructs were generated with 1.8 kb of HLX1 proximal promoter, carrying either wild-type or polymorphic alleles at positions C−1407T, C−742G, or both. These constructs were transfected into the human T-cell line, and polymorphism-dependent effects on promoter activity were studied after mitogen stimulation (ionomycin) by using luciferase reporter assays. As indicated in Fig 2, the presence of these polymorphic promoter alleles led to a significant decrease in promoter transactivation after stimulation with 50 ng of ionomycin in vitro, each by itself (P = .003 and .006) and in combination (P = .0002). These data suggested that both SNPs in block 2 influence HLX1 promoter activity independently but with synergistic effects. Thus we then thought to determine the mechanisms by which these changes in promoter activity can occur.

• 
  • View Large Image
  • Download to PowerPoint

• Fig 2. 

  The polymorphisms C−1407T and C−742G reduce HLX1 promoter activity in Jurkat T cells. Jurkat T cells transiently transfected with 1.8-kb HLX1 promoter reporter constructs carrying the wild-type (wt) or respective polymorphic sequences (n = 3) are shown. Cells were left unstimulated or stimulated with ionomycin and harvested after 18 hours. ^∗P < .05, ^∗∗P < .01, and ^∗∗∗P < .001, Student t test.

Transcription factor binding analysis of HLX1 promoter polymorphisms 

In silico transcription factor binding analyses with MatInspector and Alibaba Web-based bioinformatic tools were conducted that predicted SNP-dependent alterations of SP transcription factor binding at position −1407. Next, EMSAs were performed for both promoter loci. Radioactively labeled 31mer oligonucleotides, either carrying the wild-type or the polymorphic allele, at the respective positions were used and incubated with nuclear extracts from unstimulated Jurkat T cells (Fig 3). Antibody supershift experiments were performed to specifically identify transcription factors within observed DNA protein complexes to confirm the specificity of protein competition experiments. EMSA experiments at both promoter positions (–1407 and –742) revealed strong and significant differences in allele-specific transcription factor binding of SP transcription factors. Although SP transcription factor family members did constitutively bind to the respective wild-type alleles (C-1407 and C-742), this binding was almost completely abolished in the presence of the polymorphic allele (–1407T and –742G). These results suggest that altered SP binding at these promoter positions occurs, which might explain the differences in gene expression observed in luciferase reporter studies.

• 
  • View Large Image
  • Download to PowerPoint

• Fig 3. 

  Allele-specific transcription factor binding analyses within the HLX1 promoter in nuclear extracts from Jurkat T cells. EMSA probes carrying wild-type (WT) or polymorphic (PO) allele for C−1407T (left) and C−742G (right). DNA-protein interaction patterns for wild-type (lanes 1 and 14) and polymorphic alleles (lanes 2 and 15) show the formation of 5 specific complexes in wild-type probes only. All 5 complexes are abrogated by competition with 100-fold molar excess of cold oligos (lane 3 and lane 16) and with SP consensus sites (lanes 5 and 18). Specific antibodies for the SP transcription factor family (SP1, SP3, and SP4) supershift specific complexes (lanes 8-12 and 21-25), indicating the presence of the respective SP proteins in the complexes.

Back to Article Outline

Discussion 

In this study we resequenced the HLX1 gene locus and identified novel polymorphisms in the gene. Haplotype structure was assessed, and genotyping was performed accordingly, identifying associations between HLX1 SNPs and asthma in a large study population of 3099 German children. When promoter polymorphisms positively associated with the development of asthma were studied functionally, significant differences in promoter transactivation on ionomycin stimulation were observed, potentially because of significantly reduced binding of SP transcription factors in the presence of polymorphic alleles in the HLX1 promoter.

Although previous genetic studies investigating the role of transcription factors involved in the T_H1/T_H2 differentiation and the development of asthma were focused on T-bet (T_H1)⁷, ⁸, ⁹, ¹⁰, ¹¹ and GATA3 (T_H2) only,²³, ²⁴ our data suggest that genetic HLX1 variants might also influence asthma. Until now, no systematic screening for polymorphisms in the HLX1 gene has been carried out. Thus we resequenced the complete gene locus in 80 chromosomes. It is very unlikely that frequent mutations/polymorphisms in that region were missed by using this comprehensive approach. By using a pragmatic genotyping strategy based on haplotype tagging SNPs, it can be assumed that all relevant genetic information of the locus has been captured by our association analysis.

In these analyses 2 LD blocks genotyped by tagging SNPs C−1407T and T+346C were significantly associated with asthma, nonatopic asthma, or both in the study population. Asthma risk increased in the presence of polymorphisms from LD block 2, represented by tagging SNP C−1407T, and effects were similar for atopic and nonatopic forms of asthma. In contrast, the polymorphic C allele of SNP T+346C representing block 3 decreased asthma risk. This effect was stronger in nonatopic asthma. Interestingly, no significant associations with other atopic diseases or atopic sensitization were found, even though no mutually exclusive reference groups were used in the analysis. Thus it can be speculated that the effects of genetic variants of HLX1 observed with asthma might not act through intermediate steps of atopic sensitization but rather have a more direct effect on asthma-specific mechanisms independent of atopy. Potentially, it is the absence of the T_H1 signal and not the increase of the T_H2 signal that induces asthma. This phenomenon is not new and has been observed previously for other asthma genes. For example, IL-13 influences total serum IgE levels but also has IgE-independent effects on asthma development directly related to pulmonary inflammation and airway smooth muscle cells.²⁵ How HLX1 polymorphisms influence asthma development is not yet clear. To better understand these mechanisms, we started to dissect HLX1 SNP function in this study.

The 2 tagging SNPs associated with asthma in this study represent 5 (C−1407T) and 2 (T+346C) SNPs in their respective LD blocks. Each of these SNPs can putatively be causal for the signals observed with the respective tagging SNPs. Because LD in block 2 (C−1407T) is extremely high (r² ≥ 0.98), almost every individual is either wild-type or polymorphic at all 5 SNP loci at the same time. Thus dissection of function on a population level is impossible, and other methods had to be used. Of the 5 SNPs in block 2, 2 SNPs were located in the promoter region, 1 in the 5′UTR, 1 in intron 3, and 1 synonymous SNP in exon 4. Of all these SNPs in block 2, the 2 promoter SNPs seemed the most likely candidates to influence HLX1 function because of their position in a putative regulatory region.

Indeed, both SNPs lead to a decrease in promoter activity, as shown by luciferase gene expression studies. Interestingly, this effect might be due to the loss of transcription factor binding of the same transcription factors in both loci in the presence of the respective polymorphic alleles. −1407T and −742G lead to an almost complete loss of SP transcription factor binding in both regions.

Members of the SP transcription factor family share a highly conserved DNA binding domain, which is able to recognize GC- or GT-rich motifs frequently existing in various promoters.²⁶ Although these factors show a high homology to each other, they exhibit different functional properties.²⁶ SP1 generally induces promoter activity, whereas SP3 is a bifunctional regulator, either activating or suppressing transcription by inhibiting the stimulatory role of SP1.²⁷, ²⁸ Because SP1 and SP3 compete for the same binding sites, the ratio of SP1 and SP3 is a critical determinant of the influence of SP response elements on transcriptional activity.²⁶ A similar situation was recently described for the polymorphic CD14 promoter site, a gene that is also involved in IgE regulation and the development of atopy.¹⁷ In that case the polymorphic allele also reduces the binding of transcription factors of the SP family and enhances gene expression, thereby influencing the development of atopy.¹⁷

Although the first functional results evaluating the promoter SNPs in block 2 are promising and suggestive, a number of questions remain. How decreased HLX1 expression might increase asthma risk is unclear, and a number of intermediate steps need to be studied further in the process from HLX1 gene expression to disease development. Ex vivo studies need to confirm our in vitro results. Furthermore, also less likely to be causative for the observed effects, a function of the remaining 3 SNPs in block 2 cannot be excluded yet. Also, in the study reported here, no functional characterizations of SNPs in block 3 have yet been performed. Obviously these polymorphisms must be evaluated in future studies. In particular, polymorphism T+346C, located in exon 1, which leads to an amino acid change from serine to proline, requires further attention. Analyses investigating putative synergistic effects between polymorphisms in HLX1 and the gene encoding T-bet are currently ongoing.

Taken together, the functional studies thus far performed for 2 promoter polymorphisms associated with an increased asthma risk at the population level indeed suggest that these polymorphisms alter transcription factor binding sites and expression levels of the HLX1 gene. Thus HLX1 might not only be important for T_H1 cell differentiation, but genetic variants in this T-bet–associated gene might also modify the development of asthma.

Back to Article Outline

We thank Tanja Kaacksteen and Ilona Dahmen for expert technical assistance. This work is part of the PhD thesis of Kathrin Suttner and part of the MD thesis of Isabell Ruoss.

Back to Article Outline

Fig E1. 

• 
  • View Large Image
  • Download to PowerPoint

• LD (r² plot) between HLX1 single and tagging SNPs (representing blocks 1, 2, 3, 4, and 5) genotyped in the Dresden population (n = 1940). Color code for the LD plot is produced by using Haploview: white (r² = 0), shades of gray (0 < r² < 1), and black (r² = 1).

Back to Article Outline

Table E1. 

Descriptive characterization of the International Study of Asthma and Allergy in Childhood phase II study population comparing all genotyped German children included in this analysis (n = 3099)

Back to Article Outline

Table E2. 

Description of the primers used for PCR amplification and sequencing of the HLX1 gene

Back to Article Outline

Table E3. 

Description of the primers used for genotyping of the HLX1 gene in the Dresden and Munich populations

Back to Article Outline

Table E4. 

Comparison of unadjusted and adjusted analyses (adjusted for sex and environmental tobacco smoke exposure)

Values are presented as ORs (95% CIs) and P values, as shown, and adjusted for sex and environmental tobacco smoke. Current environmental smoke exposure was defined as any current environmental tobacco smoke exposure at the age of 9 to 11 years, according to the information derived from parental questionnaires. Significant associations are shown in boldface.

Back to Article Outline

Table E5. 

Associations between HLX1-tagging SNPs and asthma (divided into atopic and non atopic asthma) and atopy in the homogeneity analysis

Associations are given in terms of ORs (95% CIs) for dominant effects in the pooled population (MD; total n = 3099) and in the single populations from Dresden (D; n = 1940) and Munich (M; n = 1159). Significant associations are shown in boldface.

Back to Article Outline

References 

1. Robinson DS, Hamid Q, Ying S, Tsicopoulos A, Barkans J, Bentley AM, et al. Predominant TH2-like bronchoalveolar T-lymphocyte population in atopic asthma. N Engl J Med. 1992;326:298–304
   • View In Article
   • MEDLINE
   • CrossRef
2. Neurath MF, Finotto S, Glimcher LH. The role of Th1/Th2 polarization in mucosal immunity. Nat Med. 2002;8:567–573
   • View In Article
   • MEDLINE
   • CrossRef
3. Zheng W, Flavell RA. The transcription factor GATA-3 is necessary and sufficient for Th2 cytokine gene expression in CD4 T cells. Cell. 1997;89:587–596
   • View In Article
   • MEDLINE
   • CrossRef
4. Szabo SJ, Kim ST, Costa GL, Zhang X, Fathman CG, Glimcher LH. A novel transcription factor, T-bet, directs Th1 lineage commitment. Cell. 2000;100:655–669
   • View In Article
   • MEDLINE
   • CrossRef
5. Mullen AC, Hutchins AS, High FA, Lee HW, Sykes KJ, Chodosh LA, et al. Hlx is induced by and genetically interacts with T-bet to promote heritable T(H)1 gene induction. Nat Immunol. 2002;3:652–658
   • View In Article
   • MEDLINE
6. Mikhalkevich N, Becknell B, Caligiuri MA, Bates MD, Harvey R, Zheng WP. Responsiveness of naive CD4 T cells to polarizing cytokine determines the ratio of Th1 and Th2 cell differentiation. J Immunol. 2006;176:1553–1560
   • View In Article
   • MEDLINE
7. Akahoshi M, Obara K, Hirota T, Matsuda A, Hasegawa K, Takahashi N, et al. Functional promoter polymorphism in the TBX21 gene associated with aspirin-induced asthma. Hum Genet. 2005;117:16–26
   • View In Article
   • MEDLINE
   • CrossRef
8. Raby BA, Hwang ES, Van Steen K, Tantisira K, Peng S, Litonjua A, et al. T-bet polymorphisms are associated with asthma and airway hyperresponsiveness. Am J Respir Crit Care Med. 2006;173:64–70
   • View In Article
   • MEDLINE
   • CrossRef
9. Munthe-Kaas MC, Carlsen KH, Haland G, Devulapalli CS, Gervin K, Egeland T, et al. T cell-specific T-box transcription factor haplotype is associated with allergic asthma in children. J Allergy Clin Immunol. 2008;121:51–56
   • View In Article
   • Abstract
   • Full Text
   • Full-Text PDF (212 KB)
   • CrossRef
10. Chung HT, Kim LH, Park BL, Lee JH, Park HS, Choi BW, et al. Association analysis of novel TBX21 variants with asthma phenotypes. Hum Mutat. 2003;22:257
    • View In Article
    • CrossRef
11. Ylikoski E, Kinos R, Sirkkanen N, Pykalainen M, Savolainen J, Laitinen LA, et al. Association study of 15 novel single-nucleotide polymorphisms of the T-bet locus among Finnish asthma families. Clin Exp Allergy. 2004;34:1049–1055
    • View In Article
    • MEDLINE
    • CrossRef
12. Weiland SK, von Mutius E, Hirsch T, Duhme H, Fritzsch C, Werner B, et al. Prevalence of respiratory and atopic disorders among children in the East and West of Germany five years after unification. Eur Respir J. 1999;14:862–870
    • View In Article
    • MEDLINE
    • CrossRef
13. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res. 1988;16:1215
    • View In Article
    • MEDLINE
14. Zhang L, Cui X, Schmitt K, Hubert R, Navidi W, Arnheim N. Whole genome amplification from a single cell: implications for genetic analysis. Proc Natl Acad Sci U S A. 1992;89:5847–5851
    • View In Article
    • MEDLINE
    • CrossRef
15. Schedel M, Carr D, Klopp N, Woitsch B, Illig T, Stachel D, et al. A signal transducer and activator of transcription 6 haplotype influences the regulation of serum IgE levels. J Allergy Clin Immunol. 2004;114:1100–1105
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (194 KB)
    • CrossRef
16. Schedel M, Pinto LA, Schaub B, Rosenstiel P, Cherkasov D, Cameron L, et al. IRF-1 gene variations influence IgE regulation and atopy. Am J Respir Crit Care Med. 2008;177:613–621
    • View In Article
    • CrossRef
17. LeVan TD, Bloom JW, Bailey TJ, Karp CL, Halonen M, Martinez FD, et al. A common single nucleotide polymorphism in the CD14 promoter decreases the affinity of Sp protein binding and enhances transcriptional activity. J Immunol. 2001;167:5838–5844
    • View In Article
    • MEDLINE
18. Cameron L, Webster RB, Strempel JM, Kiesler P, Kabesch M, Ramachandran H, et al. Th2 cell-selective enhancement of human IL13 transcription by IL13-1112C>T, a polymorphism associated with allergic inflammation. J Immunol. 2006;177:8633–8642
    • View In Article
    • MEDLINE
19. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–265
    • View In Article
    • MEDLINE
    • CrossRef
20. Zaykin DV, Westfall PH, Young SS, Karnoub MA, Wagner MJ, Ehm MG. Testing association of statistically inferred haplotypes with discrete and continuous traits in samples of unrelated individuals. Hum Hered. 2002;53:79–91
    • View In Article
    • MEDLINE
    • CrossRef
21. Quandt K, Frech K, Karas H, Wingender E, Werner T. MatInd and MatInspector: new fast and versatile tools for detection of consensus matches in nucleotide sequence data. Nucleic Acids Res. 1995;23:4878–4884
    • View In Article
    • MEDLINE
22. Grabe N. AliBaba2: context specific identification of transcription factor binding sites. In Silico Biol. 2002;2(suppl):S1–S15
    • View In Article
    • MEDLINE
23. Pykalainen M, Kinos R, Valkonen S, Rydman P, Kilpelainen M, Laitinen LA, et al. Association analysis of common variants of STAT6, GATA3, and STAT4 to asthma and high serum IgE phenotypes. J Allergy Clin Immunol. 2005;115:80–87
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (155 KB)
    • CrossRef
24. Huebner M, Kim DY, Ewart S, Karmaus W, Sadeghnejad A, Arshad SH. Patterns of GATA3 and IL13 gene polymorphisms associated with childhood rhinitis and atopy in a birth cohort. J Allergy Clin Immunol. 2008;121:408–414
    • View In Article
    • Abstract
    • Full Text
    • Full-Text PDF (367 KB)
    • CrossRef
25. Wills-Karp M, Luyimbazi J, Xu X, Schofield B, Neben TY, Karp CL, et al. Interleukin-13: central mediator of allergic asthma. Science. 1998;282:2258–2261
    • View In Article
    • MEDLINE
    • CrossRef
26. Suske G. The Sp-family of transcription factors. Gene. 1999;238:291–300
    • View In Article
    • MEDLINE
    • CrossRef
27. Birnbaum MJ, van Wijnen AJ, Odgren PR, Last TJ, Suske G, Stein GS, et al. Sp1 trans-activation of cell cycle regulated promoters is selectively repressed by Sp3. Biochemistry. 1995;34:16503–16508
    • View In Article
    • MEDLINE
    • CrossRef
28. Prowse DM, Bolgan L, Molnar A, Dotto GP. Involvement of the Sp3 transcription factor in induction of p21Cip1/WAF1 in keratinocyte differentiation. J Biol Chem. 1997;272:1308–1314
    • View In Article
    • MEDLINE
    • CrossRef