Abstract
Two primary chitinases have been identified in humans – acid mammalian chitinase (AMCase) and chitotriosidase (CHIT1). Mammalian chitinases have been observed to affect the host’s immune response. The aim of this study was to test for association between genetic variation in the chitinases and phenotypes related to Chronic Obstructive Pulmonary Disease (COPD). Polymorphisms in the chitinase genes were selected based on previous associations with respiratory diseases. Polymorphisms that were associated with lung function level or rate of decline in the Lung Health Study (LHS) cohort were analyzed for association with COPD affection status in four other COPD case-control populations. Chitinase activity and protein levels were also related to genotypes. In the Caucasian LHS population, the baseline forced expiratory volume in one second (FEV1) was significantly different between the AA and GG genotypic groups of the AMCase rs3818822 polymorphism. Subjects with the GG genotype had higher AMCase protein and chitinase activity compared with AA homozygotes. For CHIT1 rs2494303, a significant association was observed between rate of decline in FEV1 and the different genotypes. In the African American LHS population, CHIT1 rs2494303 and AMCase G339T genotypes were associated with rate of decline in FEV1. Although a significant effect of chitinase gene alleles was found on lung function level and decline in the LHS, we were unable to replicate the associations with COPD affection status in the other COPD study groups.
Keywords: Chronic Obstructive Pulmonary Disease, chitinase, polymorphism, lung function
INTRODUCTION
Chitin is the second most abundant polysaccharide found in nature and functions as a major structural component in fungi, crustaceans, and insects, but not in mammals. Chitinases are enzymes characterized by their ability to hydrolytically cleave chitin. In mammals, two primary chitinases have been identified – acid mammalian chitinase (AMCase) and chitotriosidase (CHIT1). In addition to their ability to cleave either inhaled or ingested exogenous chitin, mammalian chitinases have been observed to affect the host’s immune response (Lee 2009). Recent studies have shown an association between the chitinase family of proteins and inflammatory lung diseases. For instance, high levels of AMCase in the lung were observed in a mouse model of asthma (Zhu 2004). CHIT1 levels were elevated in the bronchoalveolar lavage fluid of smokers with chronic obstructive pulmonary disease (COPD) (Létuvé 2010). A chitinase-like protein, commonly known as YKL-40, has also been discovered in mammals. Unlike AMCase and CHIT1, YKL-40 binds chitin polymers but lacks the active site residues necessary for cleavage. Nevertheless, genetic variants in the gene have been shown to influence levels of the protein and susceptibility to asthma (Chupp 2007; Ober 2008). In addition, elevated levels of this protein in the lung have been found in patients with COPD (Létuvé 2008). Moreover, studies show that chitin has the ability to recruit and activate immune cells that are involved in the development of COPD, suggesting an important role of chitinases and chitinase-like proteins in the disease (Lee 2008).
Although these studies suggest the involvement of chitinase and chitinase-like proteins in COPD, the underlying mechanism remains to be determined. It is possible that the presence of chitinase may result in changes to the immune response, which could lead to more frequent exacerbations and ultimately increased rate of decline in lung function. COPD is a lung disease characterized by airflow limitation that is not fully reversible. Smoking is a key causal factor in the disease, however, only a fraction of all smokers develop COPD, suggesting a genetic susceptibility (Khoury 1985). Therefore, the aim of this study was to test for association between genetic variation in the chitinases and phenotypes related to COPD. Polymorphisms in the genes encoding the chitinase and chitinase-like proteins were assayed to determine their association with lung function phenotypes in smokers. We hypothesized that these gene variants affect the baseline levels and rate of decline of lung function of smokers with mild-moderate COPD.
MATERIALS AND METHODS
Study participants
The participants in the primary analysis included in the present study were from the NHLBI-sponsored Lung Health Study (LHS) cohort previously described in detail (Connett 1993). Briefly, the participants were all smokers with evidence of lung function impairment. Lung function at the start of the study was measured as forced expiratory volume in 1 second (FEV1) as a percentage of predicted value. The change in lung function, measured as change in FEV1 per year over a five-year period, was the main outcome measure of the LHS. Of the 5887 total participants in the cohort, DNA samples and phenotypic data were available for 4344 subjects. Informed consent was obtained from all participants and this study received the approval of the Providence Health Care Research Ethics Board. Table 1 provides the characteristics of the LHS participants (Caucasians = 4123; African-Americans = 164; Other = 48). The single nucleotide polymorphisms (SNPs) that showed association with COPD in the LHS cohort were examined in four case-control cohorts, in which genome-wide association study data were available: (1) a case-control population from Norway (GenKOLS), (2) the National Emphysema Treatment Trial (NETT) cases and Normative Aging Study (NAS) controls, (3) the COPD cases and smoking controls of the ECLIPSE study (protocol number SCO104960) (Vestbo 2008), and (4) the first 1000 COPDGene study subjects (Table 2). Details of these populations have been previously described (Cho 2010; Cho 2011).
Table 1.
Characteristics of the Lung Health Study participants
| Characteristic | Male | Female | Total |
|---|---|---|---|
| Number of participants | 2736 | 1608 | 4344 |
| Age (mean ± SD), years | 48.4 ± 6.9 | 48.7 ± 6.5 | 48.5 ± 6.8 |
| Smoking history (mean ± SD), pack-yearsa | 42.4 ± 19.3 | 35.9 ± 15.9 | 40.0 ± 18.4 |
| Baseline FEV1 post-bronchodilator (mean ± SD), % predictedb | 78.63 ± 9.12 | 78.24 ± 9.11 | 78.48 ± 9.12 |
| FEV1 post-bronchodilator rate of decline (mean ± SD), % predicted/yearc | −0.906 ± 1.75 | −1.083 ± 1.92 | −0.972 ± 1.81 |
Number packs of cigarettes smoked per day × number of years of smoking.
Lung function at the start of the study measured as forced expiratory volume in 1 second (FEV1).
Mean change in lung function per year over a five-year period measured as forced expiratory volume in 1 second (FEV1).
Table 2.
Characteristics of each case-control replication study group
| Characteristic | COPDGene | ECLIPSE | NETT/NAS | GenKOLs | ||||
|---|---|---|---|---|---|---|---|---|
| Cases | Controls | Cases | Controls | Cases | Controls | Cases | Controls | |
| Number of participants | 499 | 501 | 1764 | 178 | 373 | 435 | 863 | 808 |
| Age (mean ± SD), years | 64.77 (8.12) |
60.2 (8.66) |
63.63 (7.10) |
57.48 (9.44) |
67.47 (5.78) |
69.8 (7.49) |
65.53 (10.03) |
55.62 (9.71) |
| Smoking history (mean ± SD), pack-yearsa | 54.76 (26.69) |
38.87 (21.07) |
50.29 (27.42) |
32.11 (24.84) |
66.43 (30.68) |
40.66 (27.85) |
31.98 (18.46) |
19.66 (13.58) |
| FEV1 (mean ± SD), % predictedb | 48.73 (18.41) |
97.98 (11.32) |
47.63 (15.62) |
107.83 (13.56) |
28.12 (7.38) |
99.97 (13.2) |
50.63 (17.44) |
94.91 (9.24) |
| Sex (% Male) | 49.5% | 50.1% | 67.0% | 57.9% | 63.8% | 100% | 60.1% | 50.1% |
Number packs of cigarettes smoked per day × number of years of smoking.
Lung function measured as forced expiratory volume in 1 second (FEV1).
Gene variants
The SNPs in the chitinase and chitinase-like genes in this study were selected based on previous associations with respiratory diseases. Table 3 shows a brief description of the polymorphisms. SNP rs3818822 in the CHIA gene (which encodes for the AMCase protein) has been previously associated with asthma in a case-control study from Germany (Bierbaum 2005). Another SNP in the CHIA gene, G339T, has also been previously associated with asthma among African American subjects in several populations (Seibold 2009). A 24-bp duplication in exon 10 in the CHIT1 gene results in aberrant splicing leading to the deletion of 87 nucleotides, producing an inactive form of the protein due to the lack of 29 amino acids. This polymorphism has been associated with reduced chitinase activity in the lungs of smokers (Seibold 2008). The CHI3L1 gene encodes the YKL-40 protein. SNP rs4950928 in CHI3L1 has been associated with asthma in both a Hutterite population and outbred populations as well as with serum levels of the protein (Ober 2008).
Table 3.
Description of the polymorphisms studied
| Gene | Protein | SNP | Allele change |
Location/amino acid change |
Clinical Association |
|---|---|---|---|---|---|
| CHIA | Acid mammalian chitinase | rs3818822 G339T |
G => A G => T |
Gly102 => Arg Arg61 => Met |
Associated with asthma (Bierbaum 2005; Seibold 2009) |
| CHIT1 | Chitotriosidase | rs2494303 | C => A | Intron | High linkage disequilibrium with 24-bp duplication that was associated with reduced chitinase activity in the lungs of smokers (Seibold 2008) |
| CHI3L1 | YKL-40 | rs4950928 | C => G | 5’ untranslated region | Associated with asthma (Ober 2008) |
Tag SNP selection for the 24 bp duplication in CHIT1
To select a SNP that acts as a surrogate for the 24 bp duplication in the CHIT1 gene, 44 Coriell samples (Coriell Institute for Medical Research, Camden, NJ, USA) were genotyped for the duplication. The 24 bp duplication in the CHIT1 gene was assayed using electrophoresis on a 2 % agarose gel of an amplification product containing the duplication site. The region containing the duplication was amplified using a PCR cocktail that included 5 ng of genomic DNA, 0.2 µM primers, 0.2 mM dNTPs, 1.5 µL PCR buffer (Invitrogen), and 0.2 µL Taq DNA polymerase (5U/µL). PCR cycling conditions were as follows: 95°C for 15 min, 40 cycles of 95°C for 15 s, 60°C for 15 s, 72°C for 15 s, and a final extension at 72°C for 10 min. The results were compared with genotype data from SNPs within 100 kb of the duplication using the International HapMap Project database (http://hapmap.ncbi.nlm.nih.gov, accessed on February 18, 2010). Linkage disequilibrium was calculated using the CubeX algorithm (Gaunt 2007).
Genotyping
DNA from blood samples of the LHS subjects was whole genome amplified using the REPLI-g Mini Kit (Qiagen, Mississauga, ON, Canada) prior to genotyping. Genotyping was performed using commercially available TaqMan assays (Applied Biosystems, Foster City, CA, USA). The assays used are as follows: assay ID for rs3818822 = C_25984541_20; G339T = AHXOFUG; rs2494303 = C_424861_10; rs4950928 = C_27832042_10. For each assay, 5 ng of DNA was used for allelic discrimination.
Potential effect of missense polymorphism in the CHIA gene
To determine the potential effect of the missense polymorphism, rs3818822 (Gly102Arg), we used the SIFT and PolyPhen algorithms (http://sift.jcvi.org and http://genetics.bwh.harvard.edu/pph/), programs that predict the consequence of a polymorphism based on sequence homology and the physical properties of the amino acids.
AMCase protein levels
SDS-PAGE for AMCase in bronchoalveolar lavage (BAL) fluid had been previously performed (Seibold 2008) and using these data AMCase protein levels in BAL were examined between the GG (n = 18) and AG (n = 5) genotypes (subjects with AA genotype were not available).
Chitinase activity
To determine the effect of rs3818822 on chitinase activity, we used data from a chitinase activity assay that was previously performed (Seibold 2008). Chitinase activity levels were examined between the GG (n = 33) and AG/AA (AG = 9; AA = 1) genotypes.
Statistical analyses
Agreement of the genotype distributions with Hardy-Weinberg equilibrium in the LHS samples was assessed using a χ2 goodness-of-fit analysis. The LHS subjects were then stratified into Caucasian and African American populations for further analyses (other ethnicities were excluded due to small sample sizes). The two outcomes used were mean baseline and rate of decline of post-bronchodilator FEV1, expressed as a percent of predicted value. Statistical analyses were performed by multivariate linear regression analysis. Age, sex, and smoking history (pack-years) were adjusted for when performing association analyses to determine the influence of each gene variant on the outcomes. The JMP 5.1 statistical software package (SAS Institute Inc., Cary, NC, USA) was used for analysis of the relationship between the genetic variants and the measures of lung function in the LHS. Analysis of the additive model in the LHS data was done using the SimHap package (Carter 2008). For the AMCase protein levels and chitinase activity analyses, an unpaired 2-tailed student’s t-test with Welch correction was performed. A p-value < 0.05 was considered significant.
RESULTS
Analysis of Hardy-Weinberg equilibrium
All four SNPs were in Hardy-Weinberg equilibrium (rs3818822, p-value = 0.625; G339T, p-value = 0.663; rs2494303, p-value = 0.996; rs4950928, p-value = 0.995).
CHIA polymorphism rs3818822
Genotyping of rs3818822 was successful for 4025 LHS subjects (3879 Caucasians; 129 African Americans; 17 Hispanics excluded). In the Caucasian population, there was a significant decrease in baseline lung function associated with the AA genotype compared with the GG genotype (p = 0.0291). The AA genotype was associated with almost 3 % decrease in baseline FEV1 compared with the GG + AG genotypes combined (p = 0.0285). No significant association was observed in the African American population, as shown in Table 4. Furthermore, no significant association was observed with rate of decline of FEV1. An association study of this SNP was then performed in the four case-control populations; however no significant associations were observed (Table 5).
Table 4.
Genotype frequencies of chitinase polymorphisms in the LHS cohort and their associations with lung function
| Caucasians | ||||||||||
| Gene | Polymorphism | Genotype | N | Baseline FEV1a | P value |
P value Additive model |
N | Rate of FEV1 Declineb | P value |
P value Additive model |
| CHIA | rs3818822 | GG | 3112 (80%) | 78.64 ± 0.16 | Reference | 0.3124 | 3407 (82%) | −0.96 ± 0.03 | Reference | 0.6681 |
| AG | 715 (18%) | 78.61 ± 0.35 | 0.0521 | 709 (17%) | −1.01 ± 0.07 | 0.7526 | ||||
| AA | 51 (1%) | 76.01 ± 1.10 | 0.0291 | 49 (1%) | −0.94 ± 0.21 | 0.8993 | ||||
| CHIA | G339T | GG | 2493 (76%) | 78.40 ± 0.18 | Reference | 0.8344 | 2448 (76%) | −0.97 ± 0.04 | Reference | 0.6766 |
| GT | 728 (22%) | 78.52 ± 0.34 | 0.7279 | 715 (22%) | −1.05 ± 0.07 | 0.2743 | ||||
| TT | 58 (2%) | 78.01 ± 1.16 | 0.8179 | 54 (2%) | −0.83 ± 0.24 | 0.4065 | ||||
| CHIT1 | rs2494303 | CC | 2328 (65%) | 78.32 ± 0.18 | Reference | 0.0605 | 2328 (65%) | −1.02 ± 0.04 | Reference | 0.7693 |
| AC | 1128 (31%) | 78.99 ± 0.27 | 0.6554 | 1128 (31%) | −0.88 ± 0.05 | 0.0021 | ||||
| AA | 132 (4%) | 79.13 ± 0.82 | 0.5729 | 132 (4%) | −1.35 ± 0.16 | 0.0121 | ||||
| CHI3L1 | rs4950928 | CC | 2466 (64%) | 78.52 ± 0.18 | Reference | 0.3671 | 2420 (64%) | −0.98 ± 0.04 | Reference | 0.6294 |
| CG | 1216 (32%) | 78.75 ± 0.25 | 0.9689 | 1193 (32%) | −0.95 ± 0.05 | 0.971 | ||||
| GG | 145 (4%) | 78.84 ± 0.76 | 0.67 | 144 (4%) | −0.94 ± 0.15 | 0.8293 | ||||
| African Americans | ||||||||||
| Gene | Polymorphism | Genotype | N | Baseline FEV1a | P value |
P value Additive model |
N | Rate of FEV1 Declineb | P value |
P value Additive model |
| CHIA | rs3818822 | GG | 84 (65%) | 76.87 ± 1.05 | Reference | 0.7405 | 83 (64%) | −1.25 ± 0.28 | Reference | 0.1490 |
| AG | 43 (33%) | 76.40 ± 1.27 | 0.8731 | 42 (33%) | −0.53 ± 0.39 | 0.1476 | ||||
| AA | 2 (2%) | 74.30 ± 4.90 | Excluded | 2 (2%) | −0.53 ± 0.55 | Excluded | ||||
| CHIA | G339T | GG | 85 (75%) | 76.25 ± 1.00 | Reference | 0.5498 | 83 (74%) | −0.92 ± 0.24 | Reference | 0.0348 |
| GT | 24 (21%) | 76.31 ± 1.89 | 0.2096 | 24 (21%) | −0.71 ± 0.42 | 0.005 | ||||
| TT | 5 (4%) | 80.44 ± 3.73 | 0.169 | 5 (4%) | −4.89 ± 3.28 | 0.0005 | ||||
| CHIT1 | rs2494303 | CC | 108 (87%) | 76.50 ± 0.87 | Reference | 0.7211 | 108 (87%) | −0.82 ± 0.21 | Reference | 0.0222 |
| AC | 15 (12%) | 78.18 ± 2.26 | 0.6923 | 15 (12%) | −2.57 ± 1.14 | 0.0075 | ||||
| AA | 1 (1%) | 62.3 | Excluded | 1 (1%) | −0.35 | Excluded | ||||
| CHI3L1 | rs4950928 | CC | 52 (43%) | 75.92 ± 1.45 | Reference | 0.5775 | 52 (43%) | −0.93 ± 0.48 | Reference | 0.3990 |
| CG | 52 (43%) | 76.60 ± 1.23 | 0.8456 | 52 (43%) | −0.98 ± 0.21 | 0.6813 | ||||
| GG | 17 (14%) | 77.54 ± 2.02 | 0.5864 | 16 (13%) | −1.54 ± 0.39 | 0.3694 | ||||
Lung function at the start of the study measured as forced expiratory volume in 1 second (FEV1) % of predicted (± standard error).
Mean change in lung function per year over a five-year period measured as FEV1 % of predicted (± standard error).
Table 5.
Genetic association of CHIT1 and CHIA SNPs with COPD affection status in each COPD case-control study
| Gene | Polymorphism | Genotype | COPDGene Effect (SE) P-value |
ECLIPSE Effect (SE) P-value |
NETT/NAS Effect (SE) P-value |
GenKOLs Effect (SE) P-value |
Meta- Analysis Effect (SE) P-value |
Meta-Analysis Additive Model Effect (SE) P-value |
|---|---|---|---|---|---|---|---|---|
| CHIT1 | rs2494303 | CC | Reference | Reference | Reference | Reference | Reference | 0.05 (0.06) 0.42 |
| AC | −0.16 (0.36) 0.67 |
0.13 (0.41) 0.74 |
0.54 (0.45) 0.22 |
−0.16 (0.30) 0.60 |
0.02 (0.18) 0.92 |
|||
| AA | 0.06 (0.15) 0.69 |
0.00 (0.18) 0.99 |
0.08 (0.19) 0.69 |
0.15 (0.13) 0.25 |
0.08 (0.08) 0.28 |
|||
| CHIA | rs3818822 | GG | Reference | Reference | Reference | Reference | Reference | −0.07 (0.08) 0.41 |
| AG | −1.14 (0.70) 0.10 |
0.09 (0.77) 0.91 |
0.63 (0.73) 0.39 |
0.80 (0.83) 0.33 |
0.02 (0.38) 0.96 |
|||
| AA | −0.33 (0.17) 0.05 |
0.03 (0.03) 0.91 |
0.03 (0.23) 0.77 |
−0.01 (0.15) 0.94 |
−0.08 (0.09) 0.36 |
CHIA polymorphism G339T
Genotyping of G339T was successful for 3407 LHS subjects (3280 Caucasians; 114 African Americans; 13 Hispanics excluded). This variant was associated with the rate of decline of FEV1 in African American subjects (p = 0.0021). As shown in Table 4, a slower rate of decline in lung function was associated with the GT genotype compared with the GG genotype (p = 0.0050). The TT genotype was associated with a significant increase in rate of decline in lung function compared to the GG genotype (p = 0.0005). This result remained significant (p = 0.008) after Bonferroni correction for multiple comparisons (4 SNPs and 4 outcomes). No significant association of the SNP was detected with baseline FEV1 or rate of decline of FEV1 in the Caucasian population.
CHIT1 polymorphism rs2494303
SNP rs2494303 was found to be in perfect linkage disequilibrium with the 24 bp duplication (r2=1) and was chosen for further study. Subsequently, 281 LHS participants who had been previously genotyped for the duplication were genotyped for rs2494303 to validate the level of linkage disequilibrium with the duplication. We confirmed the strong linkage disequilibrium between the 24 bp duplication and rs2494303 (D’ = 1.0, r2 = 0.974) and this SNP was used to genotype the remaining LHS samples. Genotyping of rs2494303 was successful for 3802 subjects (3661 Caucasians; 126 African Americans; 15 Hispanics excluded). The variant was strongly associated with rate of decline of FEV1 in the Caucasian population (p = 0.0083). In particular, a decrease in rate of lung function decline was associated with the AC genotype (heterozygous for duplication) compared to the CC genotype (p = 0.0021). Conversely, a faster rate of decline in lung function was associated with the AA genotype (homozygous for duplication) compared with the CC genotype, as shown in Table 4 (p = 0.0121). In the African American population, the AC genotype was associated with a faster rate of decline in lung function compared with the CC genotype (p = 0.0075). No significant associations were observed with baseline FEV1 in either population. An association study of this SNP was then performed in the four case-control populations; however no significant associations with casecontrol status (Table 5) or FEV1 levels (data not shown) were observed.
CHI3L1 polymorphism rs4950928
Genotyping of rs4950928 was successful for 3966 LHS subjects (3829 Caucasians; 121 African Americans; 16 Hispanics excluded). We did not detect any association of the rs4950928 polymorphism with baseline FEV1 or rate of decline of FEV1 in either population.
Potential effect of missense polymorphism rs3818822
The CHIA gene variant rs3818822 is a missense polymorphism that results in a glycine to arginine change. The SIFT and PolyPhen algorithms predicted that the glycine to arginine substitution may damage protein function due to its close contact with the functional site and the distinct changes in charge and hydrophobicity which could potentially affect folding of the protein.
AMCase protein levels
AMCase protein levels were examined between subjects with the GG and AG genotypes for rs3818822. It was determined that subjects with the GG genotype had higher BAL AMCase protein by over 2.4-fold compared with subjects who had the AG genotype, as shown in Figure 1A (p = 0.0209).
Figure 1.
(A) Effect of rs3818822 on bronchoalveolar lavage AMCase protein levels (± SEM) in subjects with the GG genotype (n = 18) and the AG genotype (n = 5); * P < 0.05 compared with the GG genotype. (B) Effect of rs3818822 on bronchoalveolar lavage chitinase activity (± SEM) in subjects with the GG genotype (n = 33) and the AG/AA genotypes (n = 10); * P < 0.05 compared with the GG genotype.
Chitinase activity
Chitinase activity was determined in subjects with GG and AG/AA genotypes for rs3818822. As shown in Figure 1B, it was found that subjects with the GG genotype had a higher BAL chitinase activity by over 4-fold compared with subjects who had the AG/AA genotypes (p = 0.0475).
DISCUSSION
CHIA codes for the human acid mammalian chitinase. In this study we showed that the CHIA gene variant rs3818822 was significantly associated with baseline FEV1 in the LHS cohort. Specifically, smokers with the AA genotype had a lower baseline FEV1 compared to smokers with GG genotype and GG + AG genotypes combined. Previously, this SNP has been associated with asthma in adults and children, with the G allele associated with protection against asthma (Bierbaum 2005). The rs3818822 gene variant is a missense polymorphism that results in an amino acid change, Gly102Arg. This variation is located in close proximity to the AMCase active site. However, the functional effect of rs3818822 has yet to be examined. Our hypothesis that the Gly102Arg substitution may affect the functionality of the AMCase protein is supported by in silico analysis using the SIFT and PolyPhen algorithms which predicted the polymorphism to be detrimental to the function of the protein. Furthermore, this study has found that the GG genotype was associated with higher AMCase protein levels and chitinase activity in BAL.
A previous study has documented that a splice variant of the AMCase protein is detectable in the lung; however, this variant is lacking exon 6, which contains the conserved active site residues required for enzymatic activity of the protein (Seibold 2008). Since rs3818822 is located near the active site, one can postulate that the Arg102 isoform may have a similar effect as the splice variant described in the previous study, i.e., result in a lack of catalytic activity of the protein. It is important to note, however, that the chitin-binding domain is located in exon 12, away from the active site. Thus, one can suggest that if the Arg102 isoform conserves its ability to bind chitin, the AMCase-chitin binding complex may act as a “chi-lectin” to modulate the immune response. It is possible that the complex stimulates pro-inflammatory responses, leading to lung function impairment in COPD. The idea of chitin as a potential immunological adjuvant has been explored in previous studies (Da Silva 2010). An alternative hypothesis is that the Gly102Arg change alters the tertiary structure of the protein and thus modifies chitin binding, despite being located far from the chitin-binding domain in the amino acid sequence. Further research is needed to differentiate between these hypotheses. Nonetheless, our present study shows a genetic association between an AMCase polymorphism and level of lung function in the LHS cohort.
The fact that the rs3818822 gene variant was associated with baseline FEV1 but not rate of decline in FEV1 suggests that AMCase may not contribute to the progression of lung function decline, but rather may have a role in lung development or early impairment of lung function. A comparison with a matched cohort of healthy subjects is required to complement this observation. The other CHIA gene variant examined was the G339T located in the fourth exon. This study illustrated that this SNP is associated with the rate of decline in FEV1 in African Americans. The minor T allele of this SNP was found to be associated with protection against asthma among African American subjects (Seibold 2009). The presence of a single T allele was shown to be associated with a slower rate of decline in lung function compared with the GG genotype. The effect was not consistent in subjects with the TT genotype, however the sample size (n = 5) was low in this analysis.
CHIT1 encodes for the human chitinase, chitotriosidase. Unlike AMCase, this chitinase has previously been implicated in COPD. It was observed that CHIT1 is responsible for chitinolytic activity in the lung and is elevated in the lungs of patients with COPD (Létuvé 2010). Furthermore, the 24-bp duplication allele results in a nonfunctional protein and is associated with a lack of CHIT1 activity (Seibold 2008). In this study we found an association between a genetic variant in CHIT1 and the rate of change in lung function. Smokers in the LHS cohort who were homozygous for a SNP which is in linkage disequilibrium with the duplication had a faster rate of decline in FEV1. This implies that smokers without a functional isoform of CHIT1 may develop a faster rate of decline of their lung function. Thus, the study suggests an active form CHIT1 may be protective against rapid disease progression in smokers who develop COPD. This duplication has been examined in coronary artery disease and asthma, however no association was found (Piras 2007).
CHI3L1 encodes for the chitinase-like protein, YKL-40. The rs4950928 gene variant was shown to be associated with reduced lung function in asthmatics, as well as with schizophrenia (Ober 2008; Zhao 2007); however, in this study we found no significant association with the level or rate of decline in lung function in smokers who had mild/moderate COPD. Since all of the participants in the LHS were smokers, it is possible that this strong environmental factor may have overwhelmed the effect of the rs4950928 polymorphism. This SNP is located in the core promoter of CHI3L1, within the binding site for the MYC and MAX transcription factors. The G allele is known to disrupt binding of these transcription factors, resulting in reduced transcription and lower mRNA levels, thus reducing levels of the YKL-40 protein (Zhao 2007).
Even though we were not able to replicate these associations with COPD affection status in four COPD case-control populations, we were able to demonstrate genetic association of chitinase polymorphisms with measures of baseline lung function and lung function decline in the COPD patients from the LHS cohort. One can suggest that the associations in the LHS represent false positive results; however a limited number of polymorphism were tested. The inconsistent results may be a result of the different demographics of the cohorts involved; for instance, the LHS participants were considerably younger than the subjects in the other cohorts. It is possible that the chitinase polymorphisms are risk factors early in the pathogenesis of COPD but their influence could be more difficult to detect in the later stages of the disease when the cumulative level of exposure to environmental factors (such as cigarette smoke) is larger. Another potential explanation for these results is that chitinase polymorphisms could influence lung function decline and/or severity in COPD subjects without influencing overall COPD susceptibility.
In the LHS, the associations of CHIA G339T with rate of decline of FEV1 in the African Americans and CHIT1 rs2494303 with rate of decline of FEV1 in the Caucasians demonstrated that the values for heterozygotes were significantly lower (or greater) than those for both homozygous classes. As there is no obvious biological rationale for this observation, these data must be viewed with caution until replicated in independent data sets.
Chitin has been shown to act as an immunological adjuvant by stimulating the production of various cytokines and chemokines (Lee 2008). This suggests that chitinases such as CHIT1 may play a role in modulating the local and/or circulating concentration of chitins in the body and regulating the immune response to this common polysaccharide. Theoretically, when exogenous chitin from sources such as fungi or dust mites is present in the lungs, CHIT1 acts by cleaving chitin which subsequently could prevent chitin from stimulating immune responses. Therefore, one can speculate that without active CHIT1, an accumulation of chitin may be present in the lungs which could initiate an exaggerated pro-inflammatory response. This in turn could contribute to lung inflammation and ultimately to the onset and progression of COPD. Prior studies that have shown associations with chitinases and lung function were among subjects with asthma. The differences observed in this study may be due to the different disease mechanisms between asthma and COPD. The method by which smoking causes the activation of chitinases is unclear. One hypothesis is that chitin particles are inhaled in tobacco smoke, due to fungal infection of the tobacco leaf (Verweij 2000) and this may initiate the action of chitinases in the lungs.
In this study we have demonstrated genetic associations between chitinase gene variants and lung function level and rate of decline in COPD patients from the LHS. In addition, a functional effect of the rs3818822 polymorphism on AMCase levels and activity was demonstrated. Although a significant effect of chitinase gene alleles was found in the LHS, we were not able to replicate the associations with COPD affection status in other COPD study populations. Therefore, we propose that chitinases may play a role in COPD disease risk in specific populations; however, more research is warranted to further clarify the precise function of chitinases in lung disease.
ACKNOWLEDGEMENTS
This work was supported by grants from the Canadian Institutes of Health Research and National Institutes of Health Grant 5R01HL064068-04. The Lung Health Study was supported by contract N01-HR-46002 from the Division of Lung Diseases of the National Heart, Lung, and Blood Institute. LA is the recipient of a UBC Four Year Doctoral Fellowship and an AllerGen NCE Inc. Canadian Allergy and Immune Diseases Training Award. AJS is the recipient of a Canada Research Chair in genetics and a Michael Smith Foundation for Health Research Senior Scholar Award.
The COPDGene® project is supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, Novartis, Pfizer, and Sunovion. The COPDGene® project is also supported by the National Heart, Lung, and Blood Institute contracts R01HL089856 and R01HL089897. The members of the COPDGene® study group include: Ann Arbor VA: Jeffrey Curtis, MD (PI), Ella Kazerooni, MD (RAD). Baylor College of Medicine, Houston, TX: Nicola Hanania, MD, MS (PI), Philip Alapat, MD, Venkata Bandi, MD, Kalpalatha Guntupalli, MD, Elizabeth Guy, MD, Antara Mallampalli, MD, Charles Trinh, MD (RAD), Mustafa Atik, MD. Brigham and Women’s Hospital, Boston, MA: Dawn DeMeo, MD, MPH (Co-PI), Craig Hersh, MD, MPH (Co-PI), George Washko, MD, Francine Jacobson, MD, MPH (RAD). Columbia University, New York, NY: R. Graham Barr, MD, DrPH (PI), Byron Thomashow, MD, John Austin, MD (RAD). Duke University Medical Center, Durham, NC: Neil MacIntyre, Jr., MD (PI), Lacey Washington, MD (RAD), H Page McAdams, MD (RAD). Fallon Clinic, Worcester, MA: Richard Rosiello, MD (PI), Timothy Bresnahan, MD (RAD). Health Partners Research Foundation, Minneapolis, MN: Charlene McEvoy, MD, MPH (PI), Joseph Tashjian, MD (RAD). Johns Hopkins University, Baltimore, MD: Robert Wise, MD (PI), Nadia Hansel, MD, MPH, Robert Brown, MD (RAD), Gregory Diette, MD. Los Angeles Biomedical Research Institute at Harbor UCLA Medical Center, Los Angeles, CA: Richard Casaburi, MD (PI), Janos Porszasz, MD, PhD, Hans Fischer, MD, PhD (RAD), Matt Budoff, MD. Michael E. DeBakey VAMC, Houston, TX: Amir Sharafkhaneh, MD (PI), Charles Trinh, MD (RAD), Hirani Kamal, MD, Roham Darvishi, MD. Minneapolis VA: Dennis Niewoehner, MD (PI), Tadashi Allen, MD (RAD), Quentin Anderson, MD (RAD), Kathryn Rice, MD. Morehouse School of Medicine, Atlanta, GA: Marilyn Foreman, MD, MS (PI), Gloria Westney, MD, MS, Eugene Berkowitz, MD, PhD (RAD). National Jewish Health, Denver, CO: Russell Bowler, MD, PhD (PI), Adam Friedlander, MD, David Lynch, MB (RAD), Joyce Schroeder, MD (RAD), John Newell, Jr., MD (RAD). Temple University, Philadelphia, PA: Gerard Criner, MD (PI), Victor Kim, MD, Nathaniel Marchetti, DO, Aditi Satti, MD, A. James Mamary, MD, Robert Steiner, MD (RAD), Chandra Dass, MD (RAD). University of Alabama, Birmingham, AL: William Bailey, MD (PI), Mark Dransfield, MD (Co-PI), Hrudaya Nath, MD (RAD). University of California, San Diego, CA: Joe Ramsdell, MD (PI), Paul Friedman, MD (RAD) University of Iowa, Iowa City, IA: Geoffrey McLennan, MD, PhD (PI), Edwin JR van Beek, MD, PhD (RAD), Brad Thompson, MD (RAD), Dwight Look, MD. University of Michigan, Ann Arbor, MI: Fernando Martinez, MD (PI), MeiLan Han, MD, Ella Kazerooni, MD (RAD). University of Minnesota, Minneapolis, MN: Christine Wendt, MD (PI), Tadashi Allen, MD (RAD). University of Pittsburgh, Pittsburgh, PA: Frank Sciurba, MD (PI), Joel Weissfeld, MD, MPH, Carl Fuhrman, MD (RAD), Jessica Bon, MD. University of Texas Health Science Center at San Antonio, San Antonio, TX: Antonio Anzueto, MD (PI), Sandra Adams, MD, Carlos Orozco, MD, Mario Ruiz, MD (RAD). Administrative Core: James Crapo, MD (PI), Edwin Silverman, MD, PhD (PI), Barry Make, MD, Elizabeth Regan, MD, Sarah Moyle, MS, Douglas Stinson. Genetic Analysis Core: Terri Beaty, PhD, Barbara Klanderman, PhD, Nan Laird, PhD, Christoph Lange, PhD, Michael Cho, MD, Stephanie Santorico, PhD, John Hokanson, MPH, PhD, Dawn DeMeo, MD, MPH, Nadia Hansel, MD, MPH, Craig Hersh, MD, MPH, Jacqueline Hetmanski, MS, Tanda Murray. Imaging Core: David Lynch, MB, Joyce Schroeder, MD, John Newell, Jr., MD, John Reilly, MD, Harvey Coxson, PhD, Philip Judy, PhD, Eric Hoffman, PhD, George Washko, MD, Raul San Jose Estepar, PhD, James Ross, MSc, Rebecca Leek, Jordan Zach, Alex Kluiber, Jered Sieren, Heather Baumhauer, Verity McArthur, Dzimitry Kazlouski, Andrew Allen, Tanya Mann, Anastasia Rodionova. PFT QA Core, LDS Hospital, Salt Lake City, UT: Robert Jensen, PhD. Biological Repository, Johns Hopkins University, Baltimore, MD: Homayoon Farzadegan, PhD, Stacey Meyerer, Shivam Chandan, Samantha Bragan. Data Coordinating Center and Biostatistics, National Jewish Health, Denver, CO: James Murphy, PhD, Douglas Everett, PhD, Carla Wilson, MS, Ruthie Knowles, Amber Powell, Joe Piccoli, Maura Robinson, Margaret Forbes, Martina Wamboldt. Epidemiology Core, University of Colorado School of Public Health, Denver, CO: John Hokanson, MPH, PhD, Marci Sontag, PhD, Jennifer Black-Shinn, MPH, Gregory Kinney, MPH.
The Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study (clinicaltrials.govidentifier NCT00292552; GSK code SCO104960) is funded by GlaxoSmithKline. Principal investigators and centers participating in the ECLIPSE study (NCT00292552): Bulgaria: Y. Ivanov (Pleven), and K. Kostov (Sofia); Canada: J. Bourbeau (Montreal, QC), M. Fitzgerald (Vancouver, BC), P. Hernandez (Halifax, NS), K. Killian (Hamilton, ON), R. Levy (Vancouver, BC), F. Maltais (Montreal, QC), and D. O’Donnell (Kingston, ON); Czech Republic: J. Krepelka (Prague); Denmark: J. Vestbo (Hvidovre); the Netherlands: E. Wouters (Horn and Maastricht); New Zealand: D. Quinn (Wellington); Norway: P. Bakke (Bergen); Slovenia: M. Kosnik (Golnik); Spain: A. Agustı´ (Palma de Mallorca), and J. Sauleda (Palma de Mallorca); Ukraine: Y. Feschenko (Kiev), V. Gavrisyuk (Kiev), N. Monogarova (Donetsk), and L. Yashina (Kiev); UK: P. Calverley (Liverpool), D. Lomas (Cambridge), W. MacNee (Edinburgh), D. Singh (Manchester), and J. Wedzicha (London); and USA: A. Anzueto (San Antonio, TX), S. Braman (Providence, RI), R. Casaburi (Torrance CA), B. Celli (Boston, MA), G. Giessel (Richmond, VA), M. Gotfried (Phoenix, AZ), G. Greenwald (Rancho Mirage, CA), N. Hanania (Houston, TX), D. Mahler (Lebanon, NH), B. Make (Denver, CO), S. Rennard (Omaha, NE), C. Rochester (New Haven, CT), P. Scanlon (Rochester, MN), D. Schuller (Omaha, NE), F. Sciurba (Pittsburgh, PA), A. Sharafkhaneh (Houston, TX), T. Siler (St Charles, MO), E. Silverman (Boston, MA), A. Wanner (Miami, FL), R. Wise (Baltimore, MD), and R. ZuWallack (Hartford, CT). Steering committee: H. Coxson (Vancouver, Canada); L. Edwards (GlaxoSmithKline, Research Triangle Park, NC, USA); K. Knobil (cochair; GlaxoSmithKline, Research Triangle Park, NC, USA); D. Lomas (Cambridge, UK); W. MacNee (Edinburgh, UK); E. Silverman (Boston, MA, USA); R. Tal-Singer (GlaxoSmithKline, King of Prussia, PA, USA); J. Vestbo (co-chair; Hvidovre, Denmark); and J. Yates (GlaxoSmithKline, Research Triangle Park, NC, USA). Scientific committee: A. Agustı´ (Barcelona, Spain); P. Calverley (Liverpool, UK); B. Celli (Boston, MA, USA); C. Crim (GlaxoSmithKline, Research Triangle Park, NC, USA); B. Miller (GlaxoSmithKline, King of Prussia, PA, USA); W. MacNee (chair; Edinburgh, UK); S. Rennard (Omaha, NE, USA); R. Tal-Singer (GlaxoSmithKline, King of Prussia, PA, USA); E. Wouters (Horn, Maastricht, the Netherlands); and J. Yates (GlaxoSmithKline, Research Triangle Park, NC, USA).
The National Emphysema Treatment Trial (NETT) was supported by the National Heart, Lung, and Blood Institute contracts N01HR76101, N01HR76102, N01HR76103, N01HR76104, N01HR76105, N01HR76106, N01HR76107, N01HR76108, N01HR76109, N01HR76110, N01HR76111, N01HR76112, N01HR76113, N01HR76114, N01HR76115, N01HR76116, N01HR76118, and N01HR76119. The NETT was also supported by the Centers for Medicare and Medicaid Services and the Agency for Healthcare Research and Quality. Co-investigators in the NETT Genetics Ancillary Study also include J. Benditt, G. Criner, M. DeCamp, P. Diaz, M. Ginsburg, L. Kaiser, M. Katz, M. Krasna, N. MacIntyre, R. McKenna, F. Martinez, Z. Mosenifar, J. Reilly, A. Ries, P. Scanlon, F. Sciurba, and J. Utz.
The Normative Aging Study is supported by the Cooperative Studies Program/ Epidemiology Research and Information Center (ERIC) of the US Department of Veterans Affairs and is a component of the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Boston, Massachusetts.
The Norway GenKOLS study (Genetics of Chronic Obstructive Lung Disease, GSK code RES11080) is funded by GlaxoSmithKline.
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