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From expression pattern to genetic association in asthma and asthma-related phenotypes

BMC Research Notes volume 5, Article number: 630 (2012) Cite this article

Abstract

Background

Asthma is a complex disease characterized by hyperresponsiveness, obstruction and inflammation of the airways. To date, several studies using different approaches as candidate genes approach, genome wide association studies, linkage analysis and genomic expression leaded to the identification of over 300 genes involved in asthma pathophysiology. Combining results from two studies of genomic expression, this study aims to perform an association analysis between genes differently expressed in bronchial biopsies of asthmatics compared to controls and asthma-related phenotypes using the same French-Canadian Caucasian population.

Results

Before correction, 31 of the 85 genes selected were associated with at least one asthma-related phenotype. We found four genes that survived the correction for multiple testing. The rs11630178 in aggrecan gene (AGC1) is associated with atopy (p=0.0003) and atopic asthma (p=0.0001), the rs1247653 in the interferon alpha-inducible protein 6 (IFI6), the rs1119529 in adrenergic, alpha-2A-, receptor (ADRA2A) and the rs13103321 in the alcohol dehydrogenase 1B (class I), beta polypeptide (ADH1B), are associated with asthma (p=0.019; 0.01 and 0.002 respectively).

Conclusion

To our knowledge, this is the first time those genes are associated with asthma and related traits. Consequently, our study confirms that genetic and expression studies are complementary to identify new candidate genes and to investigate their role to improve the comprehension of the complexity of asthma pathophysiology.

Background

Asthma is a complex disease which is characterized by hyperresponsiveness, obstruction and inflammation of the airways and is modulated by the interaction of genetic and environmental factors[1]. The appearance of an immune response and of a remodeling process, which implicates structural and inflammatory cells, dictates the development, the severity and the chronicity of asthma[2]. Atopy, which also shows a genetic component, is characterized by the excessive production of immunoglobulin E in response to environmental allergens and is an important risk factor of asthma[3]. Using candidate genes approach, genome wide association studies, linkage analysis or genomic expression, studies of the last decades revealed that the pathophysiology of asthma is related with more than 300 genes[4, 5]. Indeed, several studies showed that microarrays are a relevant tool to highlight genes that are implicated in the different processes occurring during asthma.[6, 7] This study aims firstly to demonstrate that expression and genetic association studies complement each other and secondly to test the hypothesis that differences in the expression of several genes identified in the studies of Laprise et al.[8] and Chamberland et al.[9] could be caused by genetic variants. To achieve this, we combined the results of Laprise et al. and Chamberland et al. and performed association analysis between the differently expressed genes and asthma-related phenotypes in the family sample of Saguenay–Lac-St-Jean (SLSJ). The present study identified four significantly associated genes, which are the aggrecan gene (AGC1) the interferon alpha-inducible protein 6 (IFI6), the adrenergic, alpha-2A-, receptor (ADRA2A) and the alcohol dehydrogenase 1B (class I), beta polypeptide (ADH1B).

Methods

Selection of genes

The selection of genes was made according to the results of two previous studies of Laprise et al. and Chamberland et al.[8, 9]. Both studies included bronchial biopsies from four asthmatic subjects and four controls (from the Respiratory Health Network biobank of the Fonds de la recherche du Québec en santé (FRQS)) and aimed to identify differently expressed genes related to asthma. The study of Laprise et al. (Series GSE15823 on GEO) used the U95Av2 array and a t-test with Bonferroni correction with a fold change threshold of 2.0, whereas Chamberland et al. (Series GSE41649 on GEO) used the U133A array and Smyth’s moderated t-test with a fold change threshold of 1.8 as selection criteria. Both of them had a signification level at 0.05. Those two studies allowed to identify a total of 100 differently expressed genes and classified them in 13 functional groups (see Table1).

Table 1 Differently expressed genes in two microarrays studies using bronchial tissues of asthmatic and control subjects
Full size table

For the present study, some of the 100 genes were not considered for the following reasons: 1) in the first functional group named immune signaling molecules (Table1), 9 genes (CX3CR1, IL7R, CD14, SFRP1, ALOX15, NOS2A, IL2RB, NQO1 and IL1R2) were already included in previous studies and consequently removed for the present study[10–12]; 2) no SNP for the SDF1, COROA1 and SFN genes were available in the Illumina 610KQuad array (genome wide data used for the present study); 3) the TRA@ and TRB@ regions were not included in the present study as they identify loci and contained several genes and 4) no reference sequence was available for the IGHM gene. Consequently, a total of 85 genes were included in this genetic association study.

Sample

The sample comprises 253 asthmatic probands and their family members (a total of 1284 subjects) from SLSJ, a region of the province of Quebec, Canada (see Table2). This French-Canadian population is known for its founder effect and has wide conserved chromosomal regions, which can facilitate the identification of genes associated with complex traits[13]. In this family collection, 47% present asthma, 53% present atopy, and 34% have asthma and atopy and this sample has been well described in previous publications[14, 15]. Phenotypes were defined following the American Thoracic Society’s criteria[16]. Asthma was defined if the subject had an asthma diagnosis by a physician or if he showed a positive methacholine provocation test (PC20 > 8 mg/ml) combined with asthma-related symptoms. Atopy was defined as a positive response (wheal diameter ≥ 3 mm at 10 min) for at least one allergen to the skin prick test. Atopic asthma was defined as a combination of both asthma and atopy. This research project was reviewed and approved by the institutional ethic committee of the Université du Québec à Chicoutimi. The written informed consent for participation in the study was obtained from participants or, where participants are children, from a parent.

Table 2 Clinical characteristics of the French-Canadian family study
Full size table

Genotyping

The sample used in the present study was genotyped using Illumina 610KQuad array (Illumina, San Diego, USA) at the Centre National de Génotypage (CNG, Evry, France)[17]. A total of 1217 SNPs that are located in a ± 10 kb area from the 85 selected genes and fulfilling the following quality control criteria were considered in the analyses: call rate ≥ 95%, minor allele frequency ≥ 5%, Hardy-Weinberg equilibrium p value ≥ 5% and Mendelian errors ≤ 1%. Genotypes were extracted from the genome wide association study (GWAS) data using PLINK software (http://pngu.mgh.harvard.edu/∼purcell/plink/, version 1.07).

Statistical analyses

To identify associations between SNPs and asthma-related phenotypes, transmission disequilibrium was analyzed using the Family-Based Association Tests software (FBAT) (version 2.0.3,http://www.biostat.harvard.edu/∼fbat/default.thml). SNP associations were investigated under an additive genetic model and with the empirical variance estimator “-e” to account for the inclusion of multiple affected family members[18]. All the associations of SNPs obtained had to survive a multiple test correction for the number of independent tagSNPs[19] and the number of independent phenotypes, which was identified as two using a matrix spectral decomposition (matSpD) (http://gump.qimr.edu.au/general/daleN/matSpD/).

Results

For the analyses, a total of 1217 SNPs located in the 85 studied genes were tested individually for association with asthma, atopy, and atopic asthma. Before correction, 95 SNPs located in 30 genes (CD19COL11A1, MUC2, COL2A1, AGC1, FBLN, HLA-DPB1, MS4A1, CEACAM5, IGHG1, IGLA, PTPRC, IFI6, SYK, CTSC, PSMA6, SPINK5, KLRC3, ADRA2A, CLCA2, KCNJ16, CYBA, ZNF38, ITGB2, C7, ALDH3A1, FA2H, ADH1B, PIK3R1 and TNC) were associated with asthma-related phenotypes (data not shown, see Additional file1).

After correction for independent tagSNPs and phenotypes, four SNPs in the AGC1, IFI6, ADRA2A and ADH1B genes remained associated (see Table3). The rs11630178 in the AGC1 gene is associated with atopy (p=0.0003) and atopic asthma (p=0.0001), the rs1247653 located in the IFI6 gene (p=0.019), the rs1119529 in the ADRA2A gene (p=0.009) and the rs13103321 in the ADH1B gene (p=0.002), are associated with asthma.

Table 3 Associated SNPs after correction with asthma-related phenotypes
Full size table

Discussion

This study aimed to demonstrate that gene expression studies may lead to the identification of genetic determinants. Indeed, although all expression differences cannot be explained by a genetic variant, it is possible that differential expression is related to a SNP in a regulatory region or in the promoter[20]. As the genotypes for the SLSJ family study were available from the GWAS data, we investigated the association of SNPs located in genes that are differently expressed in bronchial biopsies of atopic asthmatics compared to controls from two previous publications and asthma-related phenotypes[8, 9]. We showed that four genes are genetically associated with asthma or asthma-related phenotypes (the AGC1 gene associated with atopy and atopic asthma, the IFI6, ADRA2A and ADH1B genes associated with asthma).

Like the majority of asthma associated SNPs, the variants associated in the present study are located in introns[20]. Although, mutations located in an intron may lead to the suppression of critical steps (such as the binding of splicing factors or DNA polymerase) and to the abolition or creation of a binding site causing alteration in gene expression[21].

The AGC1 gene, located in the chromosomal region 15q26, is coding for the aggrecan, a major component of the extracellular matrix of the cartilage that binds with tenascins[22]. More specifically, it binds to the type C tenascins that are upregulated in acute and chronic inflammatory diseases[23]. In asthmatic subjects, there is an abnormal deposition of tenascin C on the basal membrane, which leads to a decrease of the airway lumen[24]. Tenascin C is implicated in allergies and increases during seasonal atopic asthma[25]. Three SNPs in the tenascin C gene, including a coding SNP (GLN/1978/ARG), were associated with atopy in our study before correction (data not shown). The implication of the tenascin C in the atopic mechanisms supports its association with atopy and atopic asthma phenotypes in our study, but this gene was also associated with asthma in other studies[26]. In the literature, the AGC1 gene was mostly associated with skeleton and spinal cord diseases[27, 28].

The IFI6 gene is located on the chromosome 1 and codes for an interferon-induced protein that regulates the apoptosis process. This gene is involved in the treatment of myeloma and other malignancy diseases by its antiapoptotic activity[29]. There is no function established for this gene in respiratory disorder except for its implication in tract infection caused by the respiratory syncytial virus (RSV)[30]. As RSV leads to the inflammation of the epithelium in affected patients and as a previous GWAS demonstrated that genes implicated in the epithelial function are strongly associated with asthma[17], the IFI6 gene could play a role in asthma through the modulation of the epithelium structure.

The ADRA2A gene, mapped on the 10q23 chromosomal region, codes for the A subtype of the adrenergic g protein-coupled receptors family. This family plays a role in the regulation of neurotransmitters, the production of normal neurons, and is implicated in the cardiovascular and the central nervous systems[31]. The B subtype of the receptor is known to be a biomarker in asthma and its agonists are used as therapeutic molecules as bronchoconstriction regulators[32, 33]. Several studies associated SNPs in the ADRA2B gene with asthma and atopic diseases[34–37]. In the respiratory system, the activation of the adrenergic alpha-2A-receptor regulates the recovery of the cholinergic outflow to the airways in response to repeated allergen exposition and also leads to the release of proinflammatory cytokines[32, 38]. This gene is also involved in the regulation of mood, response to stress, anxiety and autonomic function[39, 40]. Consequently, interactions between physiological factors and emotions may modulate the severity and the symptoms of asthma at least partially through the ADRA2A gene.

The ADH1B gene is located on the long arm of the chromosome 4 and codes for the beta unit of class I alcohol dehydrogenase. This enzyme catalyzes the oxidation of alcohol to acetaldehyde[41]. SNPs in the alcohol dehydrogenase and the acetaldehyde dehydrogenase genes are involved in alcohol-induced hypersensitivity[42, 43]. Moreover, the inhalation of acetaldehyde (alcohol) and a fast metabolism of ethanol can lead to a bronchoconstriction in asthmatic subjects[44]. Therefore, the ADH1B gene seems to be involved in an increase of airway obstruction in asthma by its effects on the alcohol metabolism.

Conclusion

The association analysis on genes differently expressed in microarray studies of bronchial biopsies obtained from asthmatic and control subjects allowed confirming the association of four new genes to asthma and/or allergy. The known functions of these genes suggest that they could play a significant role in the pathogenesis of asthma. On the 100 genes identified as differently expressed in the Laprise et al. and Chamberland et al. studies, the combination of the four association studies performed by our team associated 9 genes after correction for multiple testing (9%). This study illustrates the potential of combining studies of expression and association in order to increase our understanding of the biology of complex traits, and more specifically to identify gene and biological pathways relevant to asthma.

References

  1. Maddox L, Schwartz DA: The pathophysiology of asthma. Annu Rev Med. 2002, 53: 477-498. 10.1146/annurev.med.53.082901.103921.

    PubMed  CAS  Article  Google Scholar 

  2. Elias JA, Zhu Z, Chupp G, Homer RJ: Airway remodeling in asthma. J Clin Invest. 1999, 104: 1001-1006. 10.1172/JCI8124.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  3. Johansson SG, Hourihane JO, Bousquet J, Bruijnzeel-Koomen C, Dreborg S, Haahtela T, Kowalski ML, Mygind N, Ring J, van Cauwenberge P: A revised nomenclature for allergy. Allergy. 2001, 56: 813-824. 10.1034/j.1398-9995.2001.t01-1-00001.x.

    PubMed  CAS  Article  Google Scholar 

  4. Madore AM, Laprise C: Immunological and genetic aspects of asthma and allergy. J Asthma Allergy. 2010, 3: 107-121.

    PubMed  CAS  PubMed Central  Google Scholar 

  5. Lee SH, Park JS, Park CS: The search for genetic variants and epigenetics related to asthma. Allergy Asthma Immunol Res. 2011, 3: 236-244. 10.4168/aair.2011.3.4.236.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  6. Izuhara K, Saito H: Microarray-based identification of novel biomarkers in asthma. Allergol Int. 2006, 55: 361-367. 10.2332/allergolint.55.361.

    PubMed  CAS  Article  Google Scholar 

  7. Butte A: The use and analysis of microarray data. Nat Rev Drug Discov. 2002, 1: 951-960. 10.1038/nrd961.

    PubMed  CAS  Article  Google Scholar 

  8. Laprise C, Sladek R, Ponton A, Bernier MC, Hudson TJ, Laviolette M: Functional classes of bronchial mucosa genes that are differentially expressed in asthma. BMC Genomics. 2004, 5: 21-10.1186/1471-2164-5-21.

    PubMed  PubMed Central  Article  Google Scholar 

  9. Chamberland A, Madore A-M, Tremblay K, Laviolette M, Laprise C: A comparison of two sets of microarray experiments to define allergic asthma expression pattern. Exp Lung Res. 2009, 35: 399-410. 10.1080/01902140902745174.

    PubMed  Article  Google Scholar 

  10. Tremblay K, Daley D, Chamberland A, Lemire M, Montpetit A, Laviolette M, Musk AW, James AL, Chan-Yeung M, Becker A: Genetic variation in immune signaling genes differentially expressed in asthmatic lung tissues. J Allergy Clin Immunol. 2008, 122: 529-536. 10.1016/j.jaci.2008.05.049. e517

    PubMed  CAS  Article  Google Scholar 

  11. Tremblay K, Lemire M, Provost V, Pastinen T, Renaud Y, Sandford AJ, Laviolette M, Hudson TJ, Laprise C: Association study between the CX3CR1 gene and asthma. Genes Immun. 2006, 7: 632-639. 10.1038/sj.gene.6364340.

    PubMed  CAS  Article  Google Scholar 

  12. Morin A, Brook JR, Duchaîne C, Laprise C: Association Study of Genes Associated to Asthma in a Specific Environment, in an Asthma Familial Collection Located in a Rural Area Influenced by Different Industries. Int J Environ Res Public Health. 2012, 9: 2620-2635. 10.3390/ijerph9082620.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  13. Heyer E, Tremblay M, Desjardins B: Seventeenth-century European origins of hereditary diseases in the Saguenay population (Quebec, Canada). Hum Biol. 1997, 69: 209-225.

    PubMed  CAS  Google Scholar 

  14. Poon AH, Laprise C, Lemire M, Montpetit A, Sinnett D, Schurr E, Hudson TJ: Association of vitamin D receptor genetic variants with susceptibility to asthma and atopy. Am J Respir Crit Care Med. 2004, 170: 967-973. 10.1164/rccm.200403-412OC.

    PubMed  Article  Google Scholar 

  15. Begin P, Tremblay K, Daley D, Lemire M, Claveau S, Salesse C, Kacel S, Montpetit A, Becker A, Chan-Yeung M: Association of urokinase-type plasminogen activator with asthma and atopy. Am J Respir Crit Care Med. 2007, 175: 1109-1116. 10.1164/rccm.200607-1012OC.

    PubMed  CAS  Article  Google Scholar 

  16. Society AT: ATS statement–Snowbird workshop on standardization of spirometry. Ann Rev Respir Dis. 1979, 119: 831-838.

    Google Scholar 

  17. Moffatt MF, Gut IG, Demenais F, Strachan DP, Bouzigon E, Heath S, von Mutius E, Farrall M, Lathrop M, Cookson WO: A large-scale, consortium-based genomewide association study of asthma. N Engl J Med. 2010, 363: 1211-1221. 10.1056/NEJMoa0906312.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  18. Lake SL, Blacker D, Laird NM: Family-based tests of association in the presence of linkage. Am J Hum Genet. 2000, 67: 1515-1525. 10.1086/316895.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  19. Nyholt DR: A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am J Hum Genet. 2004, 74: 765-769. 10.1086/383251.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  20. Lomelin D, Jorgenson E, Risch N: Human genetic variation recognizes functional elements in noncoding sequence. Genome Res. 2010, 20: 311-319. 10.1101/gr.094151.109.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  21. Bowen H, Kelly A, Lee T, Lavender P: Control of cytokine gene transcription in Th1 and Th2 cells. Clin Exp Allergy. 2008, 38: 1422-1431. 10.1111/j.1365-2222.2008.03067.x.

    PubMed  CAS  Article  Google Scholar 

  22. Day JM, Olin AI, Murdoch AD, Canfield A, Sasaki T, Timpl R, Hardingham TE, Aspberg A: Alternative splicing in the aggrecan G3 domain influences binding interactions with tenascin-C and other extracellular matrix proteins. J Biol Chem. 2004, 279: 12511-12518.

    PubMed  CAS  Article  Google Scholar 

  23. Midwood K, Sacre S, Piccinini AM, Inglis J, Trebaul A, Chan E, Drexler S, Sofat N, Kashiwagi M, Orend G: Tenascin-C is an endogenous activator of Toll-like receptor 4 that is essential for maintaining inflammation in arthritic joint disease. Nat Med. 2009, 15: 774-780. 10.1038/nm.1987.

    PubMed  CAS  Article  Google Scholar 

  24. Laitinen A, Altraja A, Kämpe M, Linden M, Virtanen I, Laitinen LA: Tenascin is increased in airway basement membrane of asthmatics and decreased by an inhaled steroid. Am J Respir Crit Care Med. 1997, 156: 951-958.

    PubMed  CAS  Article  Google Scholar 

  25. Amin K, Ludviksdottir D, Janson C, Nettelbladt O, Bjornsson E, Roomans GM, Boman G, Seveus L, Venge P: Inflammation and structural changes in the airways of patients with atopic and nonatopic asthma. BHR Group. Am J Respir Crit Care Med. 2000, 162: 2295-2301.

    PubMed  CAS  Article  Google Scholar 

  26. Matsuda A, Hirota T, Akahoshi M, Shimizu M, Tamari M, Miyatake A, Takahashi A, Nakashima K, Takahashi N, Obara K: Coding SNP in tenascin-C Fn-III-D domain associates with adult asthma. Hum Mol Genet. 2005, 14: 2779-2786. 10.1093/hmg/ddi311.

    PubMed  CAS  Article  Google Scholar 

  27. Spector TD, MacGregor AJ: Risk factors for osteoarthritis: genetics. Osteoarthr Cartil. 2004, 12 (Suppl A): S39-44.

    PubMed  Article  Google Scholar 

  28. Ryder JJ, Garrison K, Song F, Hooper L, Skinner J, Loke Y, Loughlin J, Higgins JP, MacGregor AJ: Genetic associations in peripheral joint osteoarthritis and spinal degenerative disease: a systematic review. Ann Rheum Dis. 2008, 67: 584-591.

    PubMed  CAS  Article  Google Scholar 

  29. Cheriyath V, Glaser KB, Waring JF, Baz R, Hussein MA, Borden EC: G1P3, an IFN-induced survival factor, antagonizes TRAIL-induced apoptosis in human myeloma cells. J Clin Invest. 2007, 117: 3107-3117. 10.1172/JCI31122.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  30. Zhao D, Peng D, Li L, Zhang Q, Zhang C: Inhibition of G1P3 expression found in the differential display study on respiratory syncytial virus infection. Virol J. 2008, 5: 114-10.1186/1743-422X-5-114.

    PubMed  PubMed Central  Article  Google Scholar 

  31. Hein L, Kobilka BK: Adrenergic receptor signal transduction and regulation. Neuropharmacology. 1995, 34: 357-366. 10.1016/0028-3908(95)00018-2.

    PubMed  CAS  Article  Google Scholar 

  32. Wilson CG, Akhter S, Mayer CA, Kc P, Balan KV, Ernsberger P, Haxhiu MA: Allergic lung inflammation affects central noradrenergic control of cholinergic outflow to the airways in ferrets. J Appl Physiol. 2007, 103: 2095-2104. 10.1152/japplphysiol.01182.2006.

    PubMed  CAS  Article  Google Scholar 

  33. Rosethorne EM, Turner RJ, Fairhurst RA, Charlton SJ: Efficacy is a contributing factor to the clinical onset of bronchodilation of inhaled beta(2)-adrenoceptor agonists. Naunyn Schmiedebergs Arch Pharmacol. 2010, 382: 255-263. 10.1007/s00210-010-0533-6.

    PubMed  CAS  Article  Google Scholar 

  34. Limsuwan T, Thakkinstian A, Verasertniyom O, Vanichapuntu M, Attia J, Janwityanujit S, Nantiruj K: Possible protective effects of the Glu27 allele of beta2-adrenergic receptor polymorphism in Thai asthmatic patients. Asian Pac J Allergy Immunol. 2010, 28: 107-114.

    PubMed  CAS  Google Scholar 

  35. Qiu YY, Zhang XL, Qin Y, Yin KS, Zhang DP: Beta(2)-adrenergic receptor haplotype/polymorphisms and asthma susceptibility and clinical phenotype in a Chinese Han population. Allergy Asthma Proc. 2010, 31: 91-97. 10.2500/aap.2010.31.3371.

    PubMed  Article  Google Scholar 

  36. Hur GY, Park HJ, Lee HY, Koh DH, Lee BJ, Choi GS, Kim SH, Ye YM, Park HS: Association of beta-adrenergic receptor polymorphism with work-related symptoms in workers exposed to wheat flour. Yonsei Med J. 2011, 52: 488-494. 10.3349/ymj.2011.52.3.488.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  37. Chung LP, Waterer G, Thompson PJ: Pharmacogenetics of beta2 adrenergic receptor gene polymorphisms, long-acting beta-agonists and asthma. Clin Exp Allergy. 2011, 41: 312-326. 10.1111/j.1365-2222.2011.03696.x.

    PubMed  CAS  Article  Google Scholar 

  38. Leong J, Zhou M, Jacob A, Wang P: Aging-related hyperinflammation in endotoxemia is mediated by the alpha2A-adrenoceptor and CD14/TLR4 pathways. Life Sci. 2010, 86: 740-746. 10.1016/j.lfs.2010.03.009.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  39. Bertolino M, Vicini S, Gillis R, Travagli A: Presynaptic alpha2-adrenoceptors inhibit excitatory synaptic transmission in rat brain stem. Am J Physiol. 1997, 272: G654-661.

    PubMed  CAS  Google Scholar 

  40. Boehm S: Presynaptic alpha2-adrenoceptors control excitatory, but not inhibitory, transmission at rat hippocampal synapses. J Physiol. 1999, 519 (Pt 2): 439-449.

    PubMed  CAS  PubMed Central  Article  Google Scholar 

  41. Edenberg HJ: The genetics of alcohol metabolism: role of alcohol dehydrogenase and aldehyde dehydrogenase variants. Alcohol Res Health. 2007, 30: 5-13.

    PubMed  PubMed Central  Google Scholar 

  42. Linneberg A, Fenger RV, Husemoen LL, Vidal C, Vizcaino L, Gonzalez-Quintela A: Immunoglobulin E sensitization to cross-reactive carbohydrate determinants: epidemiological study of clinical relevance and role of alcohol consumption. Int Arch Allergy Immunol. 2010, 153: 86-94. 10.1159/000301583.

    PubMed  CAS  Article  Google Scholar 

  43. Linneberg A, Gonzalez-Quintela A, Vidal C, Jorgensen T, Fenger M, Hansen T, Pedersen O, Husemoen LL: Genetic determinants of both ethanol and acetaldehyde metabolism influence alcohol hypersensitivity and drinking behaviour among Scandinavians. Clin Exp Allergy. 2010, 40: 123-130.

    PubMed  CAS  Article  Google Scholar 

  44. Myou S, Fujimura M, Bando T, Saito M, Matsuda T: Aerosolized acetaldehyde, but not ethanol, induces histamine-mediated bronchoconstriction in guinea-pigs. Clin Exp Allergy. 1994, 24: 140-143. 10.1111/j.1365-2222.1994.tb00210.x.

    PubMed  CAS  Article  Google Scholar 

  45. Daley D, He J-Q, Akhabir L, Stefanowicz D, Becker AB, Chan-Yeung M, Tripp B, Zamar D, Bossé Y, Kozyrskyj AL: Associations of genetic polymorphisms in innate immunity genes with asthma and asthma-related phenotypes. J Allergy Clin Immunol. in press

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Acknowledgments

The authors thank all the families for their valuable participation to this study. Catherine Laprise is the chair holder of the Canada Research Chair for genetic determinants in asthma and is responsible for the Inflammation and remodeling strategic group of the Respiratory Health Network of the Fonds de la recherche du Québec en santé (FRQS), and member of AllerGen NCE Inc. (the Allergy, Genes and Environment Network), a national multidisciplinary research network. This work was supported by the European Commission as part of GABRIEL (a multidisciplinary study to identify the genetic and environmental causes of asthma in the European Community) contract number 018996 under the Integrated Program LSH-2004-1.2.5-1 Post genomic approaches to understand the molecular basis of asthma aiming at a preventive or therapeutic control.

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Authors and Affiliations

  1. Département des sciences fondamentales, Université du Québec à Chicoutimi, 555 boulevard de l’Université, Chicoutimi, Saguenay, Québec, G7H 2B1, Canada

    Vanessa T Vaillancourt & Catherine Laprise

  2. Institut de cardiologie et de pneumologie de l’Hôpital Laval, Université Laval, 2725, chemin Sainte-Foy, Québec, G1V 4G5, Canada

    Martine Bordeleau & Michel Laviolette

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  1. Vanessa T Vaillancourt
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  2. Martine Bordeleau
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Correspondence to Catherine Laprise.

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The authors declare that they have no competing interests.

Authors' contributions

VTV performed the analysis and drafted the manuscript. MB performed a part of the analysis and contributed to the draft of the manuscript. ML contributed to the collection of the samples and to the design of the study for the microarrays. CL designed and directed the study as well as supervised and revised the manuscript. All authors read and approved the final manuscript.

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13104_2012_1923_MOESM1_ESM.pdf

Additional file 1:Table: S1 Acrobat reader (.pdf) http://get.adobe.com/fr/reader/. Association before correction with asthma related phenotypes. This table lists all the associations before correction in the 85 studied genes for the three studied phenotypes, which are asthma, atopy and atopic asthma. The table also contains the number of tested SNPs, alleles and frequencies, Z scores and corrected threshold for each association with p≤0.05. (PDF 160 KB)

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Vaillancourt, V.T., Bordeleau, M., Laviolette, M. et al. From expression pattern to genetic association in asthma and asthma-related phenotypes. BMC Res Notes 5, 630 (2012). https://doi.org/10.1186/1756-0500-5-630

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Keywords

  • Asthma
  • Atopy
  • Atopic asthma
  • Microarrays
  • Association study
  • Expression profile
  • AGC1
  • ADRA2A
  • IFI6
  • ADH1B

BMC Research Notes

ISSN: 1756-0500

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