Genetic variation in the Toll-like receptor signaling pathway is associated with childhood asthma

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involvement that is often observed in patients with EGID and by the fact that only a few biopsy specimens were collected at different instances.1,4 We propose that the gastrointestinal symptoms and eosinophilic intestinal inflammation observed in this patient were caused by immune hypersensitivity to pollen allergens and cross-reaction with food allergens (possibly PR-10 proteins). Indeed, the boy’s symptoms were greatly reduced after PR-10 protein–containing fruits and vegetables were eliminated from his diet and returned on 2 occasions after challenge with fresh apple (at 10.3 years and 14.7 years), when eosinophilic esophagitis was detected on biopsy specimen analysis. Moreover, his symptoms recurred not only during the pollen season but also repetitively over the first 2 years of immunotherapy at a fixed time interval after the shots. Furthermore, ELISA excluded IgE-mediated allergic reactivity to thaumatin-like proteins and lipid transfer proteins (see Fig E1 in this article’s Online Repository at www. jacionline.org). Consequently, this case indicates that immune crossreactivity to PR-10 proteins from pollen and from plant food can cause more than just OAS. Similar findings have been shown in patients with allergies to Api g 1, Dau c 1, or Gly m 4; allergies to Mal d 1 have been associated with atopic dermatitis.5,6 Another study reported seasonal exacerbation of symptoms, which appeared to be induced by pollen allergy, in a patient with eosinophilic esophagitis.7 In analysis of PBMCs collected from the patient during immunotherapy, incubation with Bet v 1 and Phl p 1 resulted in continuous production of IL-5 and IL-13 at levels comparable with those observed when cells were stimulated with Der p 1 and Der p 2. However, stimulation of the PBMCs with Bet v 1 and Phl p 1 also led to increasing production of IFN-g over time, which was not observed when the cells were stimulated with Der p 1 and Der p 2. This indicates that immunotherapy caused a switch from TH2 cell to TH1 cell preponderance.8 On the other hand, in this case IL-10 and IL-17 did not seem to be involved. IgG4 levels against rBet v 1 increased greatly during immunotherapy; this is a mechanism by which immunotherapy has been proposed to reduce antigen-specific TH2-type hypersensitivity.8 In this patient the observed increase in sIgG4 levels and a gradual decrease in sIgE levels to rBet v 1 greatly reduced the ratio of sIgE-rBet v 1 to sIgG4-rBet v 1, from 40 at the start of immunotherapy to 1.5 at the end. The reductions observed in respiratory allergic symptoms were likely to result from SCIT with pollen allergen.8 However, we cannot assume that the SCIT reduced the gastrointestinal symptoms based only on a single case; further studies are needed to reproduce these findings in larger groups of patients. Short-lived resolution of symptoms related to apple ingestion has been described in other patients with pollen or food allergies who received immunotherapy.9 On the basis of this case, we propose that immune crossreactivity to pollen and food allergens could cause inflammatory gastrointestinal disease with features of at least intermittent tissue eosinophilia. PR-10 protein–containing foods could be involved in these disorders, which might therefore be treated with immunotherapies that contain pollen allergens. Further studies are needed to evaluate this model. Liliane De Swert, MDa Genevi eve Veereman, MD, PhDb Merima Bublin, PhDc

Heimo Breiteneder, PhDc Ellen Dilissen, BScd Eugene Bosmans, PhDe Caroline Mattelaer, MDf Dominique Bullens, MD, PhDg From aPediatric Allergy, Department of Pediatrics, UZ Gasthuisberg Leuven, Leuven, Belgium; bKindergastroenterologie UZ Brussels, Brussels, Belgium; cthe Department of Pathophysiology and Allergy Research, Medical University of Vienna, Vienna, Austria; dthe Laboratory of Clinical Immunology, Department of Microbiology and Immunology, K.U. Leuven, Leuven, Belgium; eAML, Antwerp, Belgium; fthe Department of Pathology, ZNA, Antwerp, Belgium; and gthe Laboratory of Pediatric Immunology, Department of Microbiology and Immunology, K.U. Leuven, Leuven, Belgium. E-mail: [email protected]. D.B. is the recipient of a senior researcher fellowship from the Fund for Scientific Research Vlaanderen (FWO). Disclosure of potential conflict of interest: C. Mattelaer has received consultancy fees from Histogenex NV and is employed by ZNA Hospital Antwerp. D. Bullens has received research support from the Fund for Scientific Research, senior research fund, MSD, and FWO, Flanders and has received lecture fees and travel expenses from Stallergenes. The rest of the authors declare that they have no relevant conflicts of interest.

REFERENCES 1. Rothenberg ME. Eosinophilic gastrointestinal disorders. J Allergy Clin Immunol 2004;113:11-28. 2. Fernandez-Rivas M, Bolhaar S, Gonzalez-Mancebo E, Asero R, van Leeuwen A, Bohle B, et al. Apple allergy across Europe: how allergen sensitization profiles determine the clinical expression of allergies to plant foods. J Allergy Clin Immunol 2006;118:481-8. 3. Peterson CGB, Eklund E, Taha Y, Raab Y, Carlson M. A new method for the quantification of neutrophil and eosinophil cationic proteins in feces: establishment of normal levels and clinical application in patients with inflammatory bowel disease. Am J Gastroenterol 2002;97:1755-62. 4. Khan S. Eosinophilic gastroenteritis. Best Pract Res Clin Gastroenterol 2005;19: 177-98. 5. Bohle B. The impact of pollen-related food allergens on pollen allergy. Allergy 2007;62:3-10. 6. Kleine-Tebbe J, Wangorsch A, Vogel L, Crowell DN, Haustein UF, Vieths S. Severe oral allergy syndrome and anaphylactic reactions caused by a Bet v 1-related PR-10 protein in soybean, SAM22. J Allergy Clin Immunol 2002;110:797-804. 7. Fogg MI, Ruchelli E, Spergel JM. Pollen and eosinophilic esophagitis. J Allergy Clin Immunol 2003;112:796-7. 8. Shamji MH, Durham SR. Mechanisms of immunotherapy to aeroallergens. Clin Exp Allergy 2011;41:1235-46. 9. Webber CM, England RW. Oral allergy syndrome: a clinical, diagnostic and therapeutic challenge. Ann Allergy Asthma Immunol 2010;104:109-10. http://dx.doi.org/10.1016/j.jaci.2012.10.057

Genetic variation in the Toll-like receptor signaling pathway is associated with childhood asthma To the Editor: Diverse microbial exposures in early life seem to have protective effects on atopy and asthma.1 Toll-like receptors (TLRs) can sense a wide range of pathogen-associated molecular patterns from the environment and are capable of mounting immune reactions. TLRs act through complex intracellular signaling cascades: myeloid differentiation primary response gene-88 (MyD88)–dependent and MyD88-independent mechanisms and AKT pathways contribute to the plasticity of the immune response (Fig 1, A, and see Fig E1 in this article’s Online Repository at www. jacionline.org). In addition, the TLR signaling network is controlled by various regulatory receptors and intracellular signaling modulators. Systematic analyses of TLR genes have previously shown that common genetic polymorphisms in the TLR4 and

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TLR2 system, as well as TLR7, TLR8, and TLR9, are associated with asthma.1 However, regulatory and intracellular molecules involved in TLR signaling have not been analyzed comprehensively for genetic variations and their effects on asthma development. We selected 41 genes from currently known TLR-mediated signaling cascades (Fig 1, A, and see Table E1 in this article’s Online Repository at www.jacionline.org). These genes spanned approximately 2 Mb in length of genomic sequence and harbored 1405 single nucleotide polymorphisms (SNPs) covered by 375 tagging blocks identified by means of linkage disequilibrium with a minor allele frequency of greater than 5% in the HapMap (CEU) population. Association with asthma was analyzed in a genome-wide association dataset consisting of 651 asthmatic patients and 652 control subjects of German and Austrian origin (see the supplementary text section in this article’s Online Repository at www.jacionline.org). After successful atopy testing and data quality control, we had 468 atopic asthmatic patients and 98 nonatopic asthmatic patients against 408 nonatopic nonasthmatic control subjects for phenotype stratification. The SNPs were genotyped with the Illumina HumanHap300Chip (n 5 169; Illumina, San Diego, Calif) or matrix-assisted laser desorption/ionization time of flight mass spectroscopy (n 5 19) or were imputed (n 5 187). Three SNPs (rs2440134, rs4114291, and rs1323288) could not be genotyped by using any method, and 1 SNP, rs17433909, was monomorphic in our population. Logistic regression analyses were performed to model the additive effects of 371 SNPs with asthma and subphenotypes (atopic and nonatopic asthma). We accounted for multiple testing in a ranking algorithm considering P values, odds ratios (ORs), and multiple testing by using following formula:

h  n i Score 5½2logðPmin Þ3½ORmax 3 11 ; N where Pmin is the smallest P value, ORmax is the strongest OR, n is the number of associated tagging SNP, and N is the total number of tagging SNPs in the gene. Subsequently, clustering of the associated genes on a virtual pathway map was performed by using a systems biology approach. Our analyses revealed that 147 SNPs tagged by 31 studied SNPs were significantly associated with asthma at a P value of less than .05 (see Fig E2 in this article’s Online Repository at www. jacionline.org). The power of our study was between greater than 90% and greater than 60% to detect asthma associations of ORs of 1.5 (maximum OR found) and ORs of 1.3 (median OR of detected associations) at a significance level of .05 for SNPs with a minor allele frequency of 10% or greater.3 The association of almost 10% (31/371) of the investigated SNPs and more than 45% (19/41) of the genes with asthma suggests a relevant contribution of genetic variability in the TLR pathway to asthma susceptibility. Asthma-associated tagging SNPs are located in 19 genes of the TLR signaling pathway (see Table E2 and Fig E2 in this article’s Online Repository at www.jacionline.org). Ranking and subsequent correction for multiple testing resulted in a progressive shift in individual P value–based ranks of the genes (see Fig E3 in this article’s Online Repository at www.jacionline.org). IL-1 receptor–associated kinase 1 (IRAK1), mitogen-activated protein kinase kinase (MKK3), extracellular signal–regulated kinase 2 (ERK2), inhibitor of nuclear factor kB kinase subunit ε (IKBKE), and mitogen-activated protein kinase/extracellular signal–

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regulated kinase kinase (MEK1) emerged as the top 5 genes associated with asthma in our analyses (Figs 1, B, and 2). These genes clustered to the MyD88-dependent mitogen-activated protein kinase (MAPK) pathway. The strongest signal was observed from the p38-MAPK and ERK1/2 pathways. A second group of associations clustered to regulatory genes (TOLL-interacting protein [TOLLIP], single immunoglobulin and Toll-IL-1 receptor domain receptor [SIGIRR], IRAKM, and IL-1 receptor–like 1 [IL1RL1]). Association signal clustering for atopic asthma was distinct from nonatopic asthma, only partially overlapping (Fig 2). For atopic asthma, IRAK1, IRAKM, receptor-interacting protein 1 (RIP1), Jun N-terminal kinase 2 (JNK2), and MKK6 were the top 5 ranked genes and IRAK1, SIGIRR, TNF receptor–associated factor (TRAF6), MKK6, and TAK-1 binding protein (TAB2) for nonatopic asthma (Fig 1, C and D). SNP rs1059703 in IRAK1 exhibits one of the strongest P values (.0063) and a high OR (1.423) for asthma. Because all known IRAK1 SNPs localize in a single linkage disequilibrium block, the effect of this gene during multiple testing correction and ranking might have been inflated (see Fig E3). IRAK1 is an intracellular mediator of TLR signaling with kinase activity and contributes to activation of nuclear factor kB and interferon-regulatory factors 5 and 7 by means of ligand-stimulated phosphorylation.2 IRAK1-deficient macrophages show cross-tolerance after primary exposure to lipo-teichoic acid (LTA) and lipo-polysaccharides (LPS) (ligands to TLR2 and TLR4), which affects cytokine production, suggesting a central role of IRAK1 in TLR-mediated immune responses.3 In a previous study on asthma, SNP rs1059701 in IRAK1 showed interaction with rs2907749 in NOD1 and rs6001585 in TAB1.4 A novel association between MAPK pathway genes (MKK3 and ERK2) and asthma was found in this study, whereas functional involvement of ERK-1/2 and the p38-MAPK pathway in asthma has been suggested previously.5 SNPs in IL1RL1 (rs1420101, rs1921622, and rs13431828) were previously associated with asthma, atopy, and eosinophil counts.6,7 All these SNPs were associated with atopic asthma in our population, but only rs1921622 was associated with asthma irrespective of atopy status. The SNPs rs4074794 in SIGIRR and rs2701652 in IRAKM associated with asthma in our population but not in a Japanese study.8 SNPs in Toll–IL-1 receptor domain containing adaptor protein 1 (TIRAP) and MyD88, linking TLRs to intracellular signaling molecules, were associated with atopic and nonatopic asthma in our study. SNPs in genes related to the MyD88-independent pathway showed a stronger association with nonatopic asthma, whereas genetic susceptibility to atopic asthma seems to be mediated through SNPs in MyD88-related genes (Fig 1). This specific clustering of association signals could relate to causal differences in TLR-related intracellular signaling in patients with atopic and nonatopic asthma (alternatively, associations by chance caused by smaller sample size in subgroup analyses cannot be ruled out). TLR2 (along with its dimeric partners TLR1 and TLR6), TLR5, TLR7, and TLR9 signal through the MyD88-dependent pathway, whereas TLR3 signals exclusively through the MyD88independent pathway. TLR4 can signal through MyD88dependent, as well as MyD88-independent, pathways (Fig 1, A). On stimulation with respective microbial stimuli, each of these TLRs can induce the production of specific cytokines. In dendritic cells TLR2 activation resulted in a cytokine response dominated by IL-8, IL-10, and IL-23. TLR3 ligands led to

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FIG 1. Overview of the TLR signaling network and clustering of polymorphisms in genes associated with asthma, atopic asthma, and nonatopic asthma. A, TLRs activate 3 signaling cascades through the MyD88dependent pathway through IRAK1-IRAK4 complexes, the MyD88-independent pathway through TRIF adapter, and the alternate AKT pathway through Rac1 adapters and are modulated by several regulatory factors (Green receptor/box) at the surface and in the intracellular compartment. B-D, Clustering of genes associated with asthma (Fig 1, B), atopic asthma (Fig 1, C), and nonatopic asthma (Fig 1, D). The clustering corresponds to the ranks of respective genes (red 5 ranks 1-5, orange 5 ranks 6-10, yellow 5 ranks 11-19).

production of IL-10 and IL-15, and TLR4 stimulation showed a significant overlap with both TLR2 and TLR3 effects.9 These patterns in cytokine production correlate with the overlap of the signaling pathways used by these receptors. Thus, together with previous results, our findings suggest that different TLR signaling mechanisms might be involved in the

pathogenesis of atopic and nonatopic asthma. Post–genome-wide association study analyses of existing datasets with pathway approaches might be a promising way of identifying novel asthma susceptibility loci, adding to the missing heritability of asthma. However, further replications and functional validations of these findings will be necessary.

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Asthma Rank 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

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Genes IRAK1 MKK3 ERK2 IKBKE Mek1 TOLLIP JNK2 SIGIRR TAB2 TAB1 AKT1 IRF3 IRAKM RIP1 TAK1 TRAM1 NFKB1 IL1RL1 MKK4

Highest OR (L95-U95) 0.70 (0.55-0.90) 1.28 (1.10-1.50) 1.22 (1.05-1.42) 0.68 (0.51-0.91) 1.33 (1.00-1.76) 0.82 (0.70-0.96) 1.42 (1.07-1.87) 0.77 (0.62-0.95) 0.82 (0.70-0.95) 0.83 (0.71-0.97) 0.77 (0.61-0.98) 0.79 (0.64-0.97) 1.24 (1.04-1.47) 1.38 (1.03-1.84) 1.30 (1.03-1.64) 1.37 (1.01-1.86) 0.68 (0.47-1.00) 0.84 (0.72-0.99) 1.25 (1.00-1.55)

Atopic asthma Smallest P-value 0.006 0.002 0.010 0.010 0.025 0.009 0.014 0.014 0.009 0.022 0.030 0.026 0.015 0.029 0.026 0.045 0.048 0.031 0.047

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Genes IRAK1 IRAKM RIP1 JNK2 MKK6 MKK3 IL1RL1 IRF7 NFKB1 TIRAP IRF3 Mek1 AKT1

Highest OR (L95-U95) 0.73 (0.54-0.99) 0.53 (0.31-0.90) 1.49 (1.04-2.12) 0.78 (0.65-0.94) 0.55 (0.31-0.95) 1.27 (1.05-1.53) 0.79 (0.65-0.96) 0.74 (0.56-0.98) 0.61 (0.39-0.97) 1.65 (1.01-2.69) 0.76 (0.59-0.98) 1.25 (1.02-1.53) 1.25 (1.01-1.55)

Non-atopic asthma Smallest P-value 0.042 0.019 0.012 0.010 0.029 0.014 0.015 0.029 0.034 0.045 0.031 0.032 0.037

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Genes IRAK1 SIGIRR TRAF6 MKK6 TAB2 IRAK4 MyD88 IKBKE RIP1 TRAM1 P38 JNK1 JNK2 AP1

Highest OR (L95-U95) 0.50 (0.28-0.86) 0.54 (0.35-0.85) 0.65 (0.46-0.90) 2.29 (1.23-4.25) 0.63 (0.46-0.86) 0.42 (0.20-0.89) 2.07 (1.10-3.90) 1.47 (1.08-1.98) 1.85 (1.05-3.25) 1.75 (1.02-3.01) 1.67 (1.03-2.72) 1.60 (1.03-2.48) 1.51 (1.04-2.20) 0.68 (0.46-1.00)

Smallest P-value 0.013 0.008 0.009 0.009 0.004 0.024 0.024 0.013 0.034 0.043 0.039 0.038 0.030 0.049

FIG 2. Ranking of genes associated with asthma and subphenotypes. Among the associated SNPs of the genes, the smallest P value and the highest OR within the 95% CI (L95-U95) are shown. From the significantly associated genes, the risk alleles are illustrated against respective genes, and color codes used in clustering are shown.

Ramesh Chandra Pandey, MSa Sven Michel, MSca Riccardina Tesse, MDa Aristea Binia, PhDa Michaela Schedel, PhDa Liming Liang, PhDb Norman Klopp, PhDc,d Andre Franke, PhDe Andrea von Berg, MDf Albrecht Bufe, MDg Ernst Rietschel, MDh Andrea Heinzmann, MDi Otto Laub, MDj Burkhard Simma, MDk Thomas Frischer, MDl Jon Genuneit, MDm Thomas Illig, PhDc,d Michael Kabesch, MDa,n From athe Department of Pediatric Pneumology, Allergy and Neonatology, Hannover Medical School, Hannover, Germany; bthe Department of Epidemiology, Harvard School of Public Health, Boston, Mass; cthe Research Unit of Molecular Epidemiology, Helmholtz Centre Munich, Neuherberg, Germany; dHannover Unified Biobank, Hannover Medical School, Hannover, Germany; ethe Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Kiel, Germany; fthe Research Institute for the Prevention of Allergic Diseases, Children’s Department, Marien-Hospital, Wesel, Germany; gthe Department of Experimental Pneumology, Ruhr-University, Bochum, Germany; hUniversity Children’s Hospital, University of Cologne, Cologne, Germany; iUniversity Children’s Hospital, Albert Ludwigs University, Freiburg, Germany; jKinder- und Jugendarztpraxis Laub, Rosenheim, Germany; kChildren’s Department, University Teaching Hospital, Landeskrankenhaus Feldkirch, Feldkirch, Austria; lUniversity Children’s Hospital Vienna, Vienna, Austria; mthe Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; and nUniversity Children’s Hospital Regensburg (KUNO), Department of Pediatric Pneumology and Allergy, Regensburg, Germany. This work was funded by the German ministry of education and research (BMBF) as part of the National Genome Research Network (NGFN), with grant NGFN 01GS0810, and by the European Commission as part of the GABRIEL (a multidisciplinary study to identify the genetic and environmental causes of asthma in the European Community), contract no. 018996 under the Integrated Program LSH-2004-1.2.5-1. R.C.P. is supported by a research fellowship from the GRK1441 (Allergy) program of Deutsche Forschungsgemeinschaft (DFG) and was supported by the PhD program ‘‘Molecular Medicine,’’ Hannover Biomedical Research School (HBRS). Disclosure of potential conflict of interest: A. von Berg has received payment for lectures from the Nestle Nutrition Institute. E. Rietschel is on the board and has received

payment for lectures from Merck Sharpe & Dohme. T. Frischer has received payment for lectures from Abbott. M. Kabesch has received grants from the European Union, the German Ministry of Education and Research, and the German Research Foundation and has received payment for lectures from the European Respiratory Society, the European Academy of Allergology and Clinical Immunology, the American Thoracic Society, Novartis, and GlaxoSmithKline. The rest of the authors declare that they have no relevant conflicts of interest.

REFERENCES 1. Tesse R, Pandey RC, Kabesch M. Genetic variations in toll-like receptor pathway genes influence asthma and atopy. Allergy 2011;66:307-16. 2. Ringwood L, Li L. The involvement of the interleukin-1 receptor-associated kinases (IRAKs) in cellular signaling networks controlling inflammation. Cytokine 2008;42: 1-7. 3. Albrecht V, Hofer TP, Foxwell B, Frankenberger M, Ziegler-Heitbrock L. Tolerance induced via TLR2 and TLR4 in human dendritic cells: role of IRAK-1. BMC Immunol 2008;9:69. 4. Reijmerink NE, Bottema RW, Kerkhof M, Gerritsen J, Stelma FF, Thijs C, et al. TLR-related pathway analysis: novel gene-gene interactions in the development of asthma and atopy. Allergy 2010;65:199-207. 5. Gerthoffer WT, Singer CA. MAPK regulation of gene expression in airway smooth muscle. Respir Physiol Neurobiol 2003;137:237-50. 6. Gudbjartsson DF, Bjornsdottir US, Halapi E, Helgadottir A, Sulem P, Jonsdottir GM, et al. Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction. Nat Genet 2009;41:342-7. 7. Savenije OE, Kerkhof M, Reijmerink NE, Brunekreef B, de Jongste JC, Smit HA, et al. Interleukin-1 receptor-like 1 polymorphisms are associated with serum IL1RL1-a, eosinophils, and asthma in childhood. J Allergy Clin Immunol 2011; 127:750-6.e5. 8. Nakashima K, Hirota T, Obara K, Shimizu M, Jodo A, Kameda M, et al. An association study of asthma and related phenotypes with polymorphisms in negative regulator molecules of the TLR signaling pathway. J Hum Genet 2006;51: 284-91. 9. Re F, Strominger JL. Heterogeneity of TLR-induced responses in dendritic cells: from innate to adaptive immunity. Immunobiology 2004;209:191-8. Available online December 28, 2012. http://dx.doi.org/10.1016/j.jaci.2012.10.061

Somatic D816V KIT mutation in a case of adult-onset familial mastocytosis To the Editor: Familial occurrence of mastocytosis is unusual.1 Most of the clustered cases were pediatric cutaneous mastocytosis without