Skip to main content
PMC home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2011 Mar 1.
Published in final edited form as: J Allergy Clin Immunol. 2010 Mar;125(3):754–757.e2. doi: 10.1016/j.jaci.2009.12.995

Polymorphisms of Chitinases are not Associated with Asthma

Ann Chen Wu 1,2,3, Jessica Lasky-Su 4, Christine A Rogers 5, Barbara J Klanderman 3, Augusto Litonjua 3,4,6
PMCID: PMC2844863  NIHMSID: NIHMS171318  PMID: 20226308

Short Summary

Despite the potential role of chitinases and chitinase-like proteins in the pathogenesis of asthma, variants in their respective genes are not associated with asthma, changes in lung physiology or allergy-related phenotypes in Caucasian children.

Keywords: chitinase, chitinase-like protein, CHIA, CHIT1, CHI13L1, YKL-40, AMCase, SNPs, asthma

To the Editor:

One of the most exciting findings recently in the pathophysiology of asthma is that mammalian chitinases may play an important role in the pathogenesis of asthma. Some researchers hypothesize that mammalian chitinases and a chitinase homologue may contribute to the pathogenesis of type 2 helper immune responses which play an important role in asthma.1, 2 Chitinases are enzymes that cleave chitin, a polysaccharide that is present in fungal cells, crustaceans, insects, and parasitic nematodes.3 Although chitin does not exist in humans, two chitinases, acidic mammalian chitinase (AMCase, CHIA) and chitotriosidase (CHIT1), have been described in humans.3 A third protein, chitinase-like protein YKL-40 (also known as human cartilage glycoprotein 39 [HCgp-39] and chitinase 3-like 1) also appears to be important in asthma.1

The objectives of this study were to assess whether single nucleotide polymorphisms (SNPs) in CHIT1, CHIA, and CHI3L1 and one CHIT1 duplication are associated with asthma, changes in lung physiology that are associated with asthma, or allergy-related phenotypes. We used data from the Childhood Asthma Management Program (CAMP), a multi-center trial that enrolled children between the ages of five and 12 years with mild to moderate persistent asthma and their parents.4 Subjects were followed every two to four months for four years in order to study the long-term use of the budesonide, nedocromil, and placebo.4

SNPs in CHIT1, CHIA, and CHI3L1 (see figures E1-3 for linkage disequilibrium plots) were genotyped using the Infinium HumanHap550 genotyping at Illumina (San Diego, CA). Genotyping quality was evaluated using the program PLINK (V1.01). SNPs with low Illumina gencall scores, poor completion rates, or four or more parent-offspring genotyped inconsistencies were dropped. Using the Basic Local Alignment Search Tool (BLAST), SNPs were further limited to those whose flanking sequences were reliably mapped to unique autosomal locations in the hg17 reference genome sequence. The CHIT1 fragment analysis5 was performed utilizing the Applied Biosystems (AB) 3100 Genetic Analyzer platform. Primers CHIT1_A1FGTCTGGATGAGGGGGTATCG-FAM and CHIT1 A1RGTTTCTTCCCTGCACAGGTCAGCTATC were used to PCR amplify the region containing the 24-bp duplication, and peaks were analyzed with AB GeneMapper software. Genotyping completion rate was 94%.

FBAT-PC is a method that has the ability to use genetic data from family members to assess associations between a disease phenotype and a gene allele, while maximizing the genetic information when multiple phenotypes are tested.6 We performed association analyses for each SNP and each phenotype using the FBAT-PC approach. FBAT-PC uses principal components analysis to construct an overall phenotype that amplifies the trait heritability by aggregating the genetic components of all measurements into a single univariate phenotype with maximal heritability.6

After the univariate phenotype is generated at each SNP, FBAT-PC uses a screening procedure to select the SNPs to be tested using a univariate quantitative FBAT statistic, the FBAT-PC statistic. For each SNP, the power to detect the association with the generated univariate phenotype is calculated, a group of SNPs with their associated phenotypes are selected based on the power to detect a genetic association, and then the FBAT-PC statistic is calculated on the SNPs and their associated phenotypes. In the analysis for this study, the additive genetic model was used and a minimum of 20 informative families were required. We utilized an FBAT approach with generalized estimating equations (FBAT-GEE)7 for our outcomes which were assessed at one time point.

Power calculations were conducted using the FBAT Power Calculator (HelixTree version 6.4.2, 2008; See online repository Table E1). Assuming a significance level of 0.05, we had ≥80% power to detect an association between each SNP and a single continuous measure for a heritability of ≥ 4%. We had greater power to detect smaller effect sizes for our outcomes with repeated measures. For example, we had ≥80% power to detect an association for a heritability of ≥4% for the outcomes FEV1 and FEV1 percent predicted which had 16 repeated measures.

Table 1 provides the baseline demographic characteristics measured in our study population of 422 children. None of the polymorphisms were associated with asthma after Bonferroni correction. We found no associations between the SNPs and the total number of hospitalizations and ED visits over four years (Table 2). The results were not significantly different after adjusting for age, gender, and treatment group.

TABLE 1.

Demographics

N=422 Mean [SD] or Percent (n)
Age in years [SD] (range) 8.7 [2.1] (5.2-13.2)
Treatment group
 Budesonide 28% (118)
 Nedocromil 29% (122)
 Placebo 43% (182)
Gender, n=422
 Male 63% (266)
 Female 37% (156)
Weight at baseline (kg), n = 419 31.87 [10.56]
Height at baseline (cm), n = 417 132.45 [13.50]
Total number of hospitalization and ED
visits over 4 year period, n=422
 0 69% (291)
 1 14% (60)
 2 7% (31)
 3 or more 9.5% (40)
Baseline PreFEV1, n=421 1.694 [0.473]
Baseline Bronchodilator Response, n = 421 0.104 [0.098]
Baseline FEV1 percent predicted, n = 416 93.370 [13.954]
Baseline lnPC20, n = 420 0.025 [1.153]
Baseline Log10 IgE, n = 417 2.616 [0.671]
Baseline Log10 Eosinophil count, n = 414 2.561 [0.488]
Open in a new tab

TABLE 2.

FBAT-PC Results from the SNPs using the PBAT Power Screen

Unadjusted FBAT-PC p-value*
Gene Marker Minor
Allele
Frequency		 Number of
Informative
Families		 pre-
FEV1 		BDR ln
PC20 		log10Eos log10IgE Total number
of
hospitalizations
and ED visits
CHIT 1 rs4950934 0.108 161 0.036 0.526 0.879 0.221 0.715 0.144
rs2486953 0.473 341 0.403 0.483 0.080 0.175 0.084 0.646
rs2486954 0.196 251 0.233 0.570 0.590 0.776 0.117 0.299
rs12141375 0.197 252 0.221 0.621 0.573 0.774 0.107 0.282
rs4950936 0.474 341 0.443 0.524 0.083 0.170 0.121 0.640
rs4950937 0.280 276 0.697 0.854 0.752 0.089 0.699 0.668
rs872583 0.195 253 0.262 0.728 0.694 0.796 0.050 0.239
rs1417149 0.471 340 0.441 0.609 0.079 0.106 0.096 0.679
rs3831317** 0.174 273 0.913 0.693 0.799 0.490 0.420 0.922
rs2486958 0.492 340 0.570 0.753 0.102 0.935 0.872 0.591
rs1556854 0.485 341 0.516 0.697 0.087 0.560 0.815 0.556
rs2486959 0.174 235 0.263 0.775 0.837 0.702 0.244 0.265
rs946257 0.309 290 0.387 0.913 0.372 0.860 0.325 0.951
rs2486068 0.171 234 0.275 0.875 0.724 0.868 0.223 0.253
rs2297950 0.308 289 0.456 0.886 0.676 0.746 0.233 0.984
rs2486070 0.171 233 0.312 0.840 0.702 0.799 0.209 0.269
rs3766537 0.192 241 0.218 0.148 0.842 0.117 0.106 0.957
rs1417150 0.467 331 0.781 0.970 0.177 0.237 0.077 0.305
rs2486072 0.353 323 0.703 0.533 0.784 0.471 0.098 0.844
rs12747110 0.014 28 0.774 0.567 0.427 0.405 0.896 0.798
rs2494287 0.128 177 0.149 0.937 0.348 0.602 0.529 0.999
CHIA rs4240529 0.283 222 0.256 0.622 0.538 0.594 0.331 0.589
rs4272622 0.190 167 0.126 0.900 0.369 0.018 0.049 0.178
rs11102233 0.258 208 0.052 0.839 0.101 0.167 0.466 0.550
rs12401737 0.460 264 0.979 0.078 0.764 0.992 0.028 0.172
rs10857871 0.212 188 0.847 0.514 0.787 0.493 0.091 0.146
rs3806448 0.481 261 0.844 0.293 0.891 0.930 0.527 0.666
rs10494132 0.221 208 0.449 0.263 0.378 0.234 0.257 0.072
rs3806446 0.450 270 0.590 0.651 0.868 0.891 0.510 0.331
rs7411387 0.401 239 0.978 0.319 0.775 0.018 0.018 0.064
rs11584291 0.313 243 0.940 0.502 0.691 0.144 0.191 0.636
rs4240530 0.288 245 0.533 0.779 0.777 0.060 0.213 0.758
rs12127313 0.136 149 0.487 0.477 0.625 0.870 0.261 0.214
rs10494133 0.143 159 0.188 0.417 0.528 0.036 0.039 0.362
rs3818822 0.101 124 0.547 0.714 0.592 0.395 0.930 0.906
rs12034576 0.326 242 0.567 0.007 0.610 0.860 0.566 0.524
rs10494134 0.463 269 0.058 0.000 0.204 0.807 0.631 0.805
rs2275253 0.288 236 0.603 0.692 0.577 0.028 0.501 0.751
rs2275254 0.396 261 0.679 0.011 0.400 0.493 0.645 0.718
rs2256721 0.286 225 0.708 0.764 0.593 0.050 0.432 0.787
rs2820093 0.102 126 0.663 0.857 0.515 0.457 0.716 0.877
rs2282290 0.469 267 0.576 0.119 0.767 0.077 0.253 0.268
rs12034177 0.328 241 0.562 0.007 0.597 0.858 0.558 0.534
rs10776724 0.454 262 0.815 0.232 0.958 0.088 0.560 0.156
rs12137697 0.128 141 0.840 0.724 0.594 0.935 0.075 0.105
CH13L1 rs7542294 0.145 168 0.953 0.616 0.171 0.985 0.257 0.797
rs880633 0.485 254 0.130 0.436 0.007 0.560 0.272 0.903
rs10399805 0.126 149 0.448 0.999 0.047 0.757 0.060 0.192
rs946261 0.401 252 0.200 0.687 0.010 0.811 0.291 0.970
Open in a new tab
*

The results were not significantly different even after adjusting for age, gender, treatment group.

**

rs3831317 is a 24-bp duplication in CHIT1.

Although there is increasing evidence that chitinases play a role in asthma, our analysis suggests that variation in chitinase genes are not associated with asthma. Our study found no associations between SNPs in the genes of CHIT1, CHIA, and CHI3L1 and any of the outcomes studied: asthma, changes in lung physiology, or allergy-related phenotypes in subjects with mild to moderate asthma. Another strength of our study was the use of repeated measures of the asthma- and allergy-related phenotypes using a family-based design that accounts for these repeated measures, thus providing greater power to detect associations than a single measurement of the outcome.

Our finding that SNPs in CHIT1 and CHI3L1 are not associated with asthma is consistent with the findings of other studies.8, 9 On the other hand, our study findings are in contrast to previous studies that found that polymorphisms in CHIA are associated with asthma and IgE levels10, 11 and a previous study that concluded that CHI3L1 is associated with asthma.12 One potential reason for the discrepant findings may be that the studies that found positive associations used a case-control design, did not evaluate for population stratification, or did not adjust for multiple testing. Alternatively, environmental exposures in our cohort interacting with these genes may be different than in other cohorts.

Despite the strengths of our study, we were limited by our relatively small sample size of 422 subjects. Nevertheless, our power calculations suggest we had adequate power to detect small to moderate effect sizes.

The human chitinases and chitinase-like proteins have received attention in recent years because of their potential role in the pathogenesis of asthma. Nevertheless, polymorphisms in CHIT1, CHIA, and CHI3L1 are not associated with asthma, changes in lung physiology, or allergy-related phenotypes, suggesting that the effects of variation in these genes alone are weak without the appropriate environmental exposure.

Supplementary Material

01
02
03

ACKNOWLEDGMENTS

We thank Brooke Schuemann, MPH for her assistance with preparation of the phenotype data. We thank all subjects for their ongoing participation in this study. We acknowledge the CAMP investigators and research team, supported by NHLBI, for collection of CAMP Genetic Ancillary Study data. All work on data collected from the CAMP Genetic Ancillary Study was conducted at Channing Laboratory of the Brigham and Women's Hospital under appropriate CAMP policies and human subject's protections. CAMP is supported by U01 HL076419, U01 HL65899, P01 HL083069, and T32 HL07427 from the National Heart, Lung, and Blood Institute, National Institutes of Health.

Support: The Childhood Asthma Management Program is supported by contracts NO1-HR-16044, 16045, 16046, 16047, 16048, 16049, 16050, 16051, and 16052 with the National Heart, Lung, and Blood Institute and General Clinical Research Center grants M01RR00051, M01RR0099718-24, M01RR02719-14, and RR00036 from the National Center for Research Resources. This work was also supported by U01 HL65899. Dr. Litonjua is supported by R01 AI056230.

Abbreviations

AMCase, CHIA

Acid mammalian chitinase

BDR

Bronchodilator response

CAMP

Childhood Asthma Management Program

CHIT1

Chitotiosidase

FBAT-PC

Family-Based Association Test-Principal Components

FEV1

Forced Expiratory Volume in 1 second

GEE

General Estimating Equations

PC20

Concentration that provoked a 20% decrease from post-diluent FEV1

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  • 1.Chupp GL, Lee CG, Jarjour N, Shim YM, Holm CT, He S, et al. A chitinase-like protein in the lung and circulation of patients with severe asthma. N Engl J Med. 2007;357:2016–27. doi: 10.1056/NEJMoa073600. [DOI] [PubMed] [Google Scholar]
  • 2.Zhu Z, Zheng T, Homer RJ, Kim YK, Chen NY, Cohn L, et al. Acidic mammalian chitinase in asthmatic Th2 inflammation and IL-13 pathway activation. Science. 2004;304:1678–82. doi: 10.1126/science.1095336. [DOI] [PubMed] [Google Scholar]
  • 3.Boot RG, Blommaart EF, Swart E, Ghauharali-van der Vlugt K, Bijl N, Moe C, et al. Identification of a novel acidic mammalian chitinase distinct from chitotriosidase. J Biol Chem. 2001;276:6770–8. doi: 10.1074/jbc.M009886200. [DOI] [PubMed] [Google Scholar]
  • 4.Long-term effects of budesonide or nedocromil in children with asthma The Childhood Asthma Management Program Research Group. N Engl J Med. 2000;343:1054–63. doi: 10.1056/NEJM200010123431501. [DOI] [PubMed] [Google Scholar]
  • 5.Seibold MA, Donnelly S, Solon M, Innes A, Woodruff PG, Boot RG, et al. Chitotriosidase is the primary active chitinase in the human lung and is modulated by genotype and smoking habit. J Allergy Clin Immunol. 2008;122:944–50. doi: 10.1016/j.jaci.2008.08.023. e3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Lasky-Su J, Biederman J, Doyle AE, Wilens T, Monuteaux M, Smoller JW, et al. Family based association analysis of statistically derived quantitative traits for drug use in ADHD and the dopamine transporter gene. Addict Behav. 2006;31:1088–99. doi: 10.1016/j.addbeh.2006.03.013. [DOI] [PubMed] [Google Scholar]
  • 7.Lange C, Silverman EK, Xu X, Weiss ST, Laird NM. A multivariate family-based association test using generalized estimating equations: FBAT-GEE. Biostatistics. 2003;4:195–206. doi: 10.1093/biostatistics/4.2.195. [DOI] [PubMed] [Google Scholar]
  • 8.Bierbaum S, Superti-Furga A, Heinzmann A. Genetic polymorphisms of chitotriosidase in Caucasian children with bronchial asthma. Int J Immunogenet. 2006;33:201–4. doi: 10.1111/j.1744-313X.2006.00597.x. [DOI] [PubMed] [Google Scholar]
  • 9.Sohn MH, Lee JH, Kim KW, Kim SW, Lee SH, Kim KE, et al. Genetic variation in the promoter region of chitinase 3-like 1 is associated with atopy. Am J Respir Crit Care Med. 2009;179:449–56. doi: 10.1164/rccm.200809-1422OC. [DOI] [PubMed] [Google Scholar]
  • 10.Bierbaum S, Nickel R, Koch A, Lau S, Deichmann KA, Wahn U, et al. Polymorphisms and haplotypes of acid mammalian chitinase are associated with bronchial asthma. Am J Respir Crit Care Med. 2005;172:1505–9. doi: 10.1164/rccm.200506-890OC. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Chatterjee R, Batra J, Das S, Sharma SK, Ghosh B. Genetic association of acidic mammalian chitinase with atopic asthma and serum total IgE levels. J Allergy Clin Immunol. 2008;122:202–8. doi: 10.1016/j.jaci.2008.04.030. 8 e1-7. [DOI] [PubMed] [Google Scholar]
  • 12.Ober C, Tan Z, Sun Y, Possick JD, Pan L, Nicolae R, et al. Effect of variation in CHI3L1 on serum YKL-40 level, risk of asthma, and lung function. N Engl J Med. 2008;358:1682–91. doi: 10.1056/NEJMoa0708801. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

01
NIHMS171318-supplement-01.tif (319.3KB, tif)
02
NIHMS171318-supplement-02.tif (332.3KB, tif)
03
NIHMS171318-supplement-03.tif (112.2KB, tif)

RESOURCES