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Association between PTCH1 gene polymorphisms and chronic obstructive pulmonary disease susceptibility in a Chinese Han population: a case-control study

Kang, Xi1,2,3; Guo, Ting1,2,3; Liu, Lyu1,2,3; Ding, Shui-Zi1,2,3; Lei, Cheng1,2,3; Luo, Hong1,2,3

Editor(s): Wei., Pei-Fang

Author Information
doi: 10.1097/CM9.0000000000000858

Abstract

Introduction

Chronic obstructive pulmonary disease (COPD) is a major chronic respiratory disease characterized by incompletely reversible airflow obstruction accompanied by airway mucus accumulation, chronic inflammation, and airway remodeling.[1,2] According to the prediction of the Global Burden of Disease Study, COPD could be the fifth leading cause of morbidity and the third leading cause of mortality worldwide in the near future.[3] Tobacco smoking is the primary risk factor for COPD in the general population and it is estimated that approximately 10% to 20% of smokers ultimately develop the disease[4,5]; furthermore, long-term exposure to biomass fuel smoke is another important cause of COPD in developing countries. However, individual variation in response to the same risk factor suggests a role of genetic predisposition in the development and progression of COPD; therefore, identification of the genetic factors associated with COPD could aid in its diagnosis and treatment.

The Hedgehog (Hh) signaling pathway plays an essential role in lung branching morphogenesis and embryonic development.[6,7] Patched 1 (PTCH1) is a 12-pass transmembrane receptor for the Hh protein, and the binding of PTCH1 and Hh protein relieves the inhibition of Smoothened, resulting in the induction of the downstream signaling and transcriptional changes in the target genes. As a member of the Hh signaling pathway, PTCH1 encoded by the PTCH1 (OMIN 601, 309) which is located in chromosome 9q22, was shown to participate in multiple signaling mechanisms, including lung organogenesis and response to injury,[8] and PTCH1 mutations have been previously shown to be associated with the risk of COPD in the population of European descent.[9] However, given the huge difference in the genetic background between European and Asian people, studies on PTCH1 single-nucleotide polymorphisms (SNPs), which can influence gene expression and determine distinct phenotypic traits,[10] should be also conducted in Asian countries.

In China, the association between PTCH1 SNPs and COPD susceptibility has not been reported. Therefore, in this study, we aimed to investigate whether SNPs in the PTCH1 gene were related to the development of COPD in a Chinese Han population.

Methods

Ethical approval

This study was conducted in accordance with the principles of Declaration of Helsinki. The study protocol was reviewed and approved by the Ethics Committee of the Second Xiangya Hospital of Central South University, Changsha, China (No. NSFC: 2017-013). Written informed consent was provided by all participants in this study.

Study population

All participants in this study were of Han ethnicity and lived in Hunan Province, China. Patients diagnosed with stable COPD at the Second Xiangya Hospital of Central South University (Changsha, China) between May 2012 and May 2016 were consecutively recruited. Patients with a history of other respiratory diseases including bronchial asthma, pulmonary tuberculosis, interstitial lung disease, or lung cancer, and known Alpha-1-antitrypsin deficiency were excluded from this study. The control group consisted of healthy volunteers. Physical conditions of these participants were assessed by the same physicians, and we chose the controls with normal lung function, no lung-related diseases or chronic diseases. The diagnosis of COPD was confirmed according to the criteria of the Global Initiative for Chronic Obstructive Lung Disease.[11] All subjects were required to donate 4 mL peripheral blood. A questionnaire about demographic data, basic characteristics, and other information was collected from all subjects. Sample size was calculated based on type I error of 0.05 (α value), a power of 90% (1 − β value) and a case-control ratio of 1:1 using PASS 11.0 software (NCSS LCC, Kaysville, UT, USA). Based on these assumptions, 251 cases and 251 controls enabled us to detect a minimum odds ratio of 2.0. Considering SNP minor allele frequency, this study finally recruited 296 cases and 300 control groups.

Selection and genotyping of tag SNPs

SNPs from the region of PTCH1 were extracted from HapMap database with minor allele frequency of 5% or above in Chinese Han population in Hunan. Genomic DNA samples from 30 controls were collected to select tag SNPs. The tag SNPs were identified using the tagger program in Haploview 4.2 (https://www.broadinstitute.org/haploview/haploview) based on the 1000 Genomes database (http://www.internationalgenome.org/) and linkage disequilibrium (LD) analysis.

Genomic DNA was extracted from peripheral blood of every participant using DNeasy blood and tissue kit (Qiagen, Valencia, CA, USA) according to the manufacturer's instructions as we have described,[12] and DNA concentration was measured using a NanoDrop 2000 (Thermo Scientific, Fitchburg, WI, USA). Tag SNPs were genotyped with the SNPseq assay, an efficient multiple gene region enrichment/next generation sequencing-based assay by Genesky Biotechnologies, Inc. (Shanghai, China). D′ value was used to evaluate the LD for each pair of SNPs. D′ value equaling to 0.8 or above indicated that the related tag SNPs formed one block.[13,14]

Statistical analysis

SPSS software version 19.0 (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. Distribution of normality for the continuous variables was assessed by Kolmogorov-Smirnov test. Continuous variables with normal distribution were presented as mean ± standard deviation and analyzed with Student's t test and those with non-normal distribution were expressed as median (interquartile range) and analyzed with Mann-Whitney U test. Categorical variables were expressed as counts (percentages) and compared using the Chi-squared test or Fisher's exact test as appropriate. Hardy-Weinberg equilibrium was tested for each of the SNPs. Odds ratios (ORs) and 95% confidence interval (95% CI) were calculated to assess the associations between PTCH1 SNPs and COPD risk in the four models using logistic regression analysis. Genotypic model analysis (co-dominant, dominant recessive, and log-additive) was performed by SNPStats software (Catalan Institute of Oncology, Barcelona, Spain).[15] LD, haplotype construction, and genetic associations at polymorphism loci were estimated using Haploview software version 4.2 (Dr Mark Daly's laboratory, Massachusetts Institute of Technology/Harvard Broad Institute, Cambridge, MA, USA) and SHEsis software platform (http://www.nhgg.org/analysis/).[14]P values less than 0.05 were considered to indicate statistical significance.

Results

Study population characteristics

A total of 596 subjects from China were included in this study, including 296 cases (244 males) and 300 controls (251 males). Table 1 summarizes the basic clinical characteristics of the patients and healthy volunteers. There were no significant differences in the gender, body mass index, predicted percentage of forced expiratory volume in 1 s (FEV1% predicted) and smoking status between the COPD and the control groups (all P > 0.05). However, patients with COPD were significantly older than controls (67.1 ± 8.8 vs. 54.9 ± 9.6 years, t = 3.215, P < 0.001).

Table 1
Table 1:
Characteristics of the COPD and control group.

Allele analysis of COPD susceptibility

In total, we identified 28 SNPs in PTCH1 genes of all subjects [Supplementary Table 1, http://links.lww.com/CM9/A233], but only three SNP variants, including the “A” allele of rs28491365 (OR: 1.388, 95% CI: 1.055–1.827, P = 0.018) and “G” alleles of rs10512248 (OR: 1.299, 95% CI: 1.021–1.653, P = 0.033) and rs28705285 (OR: 1.359, 95% CI: 1.024–1.803, P = 0.033) were found to be significantly associated with the risk of COPD development [Table 2]. All the 28 SNPs from controls were in Hardy-Weinberg equilibrium. The call rate of all SNPs was above 97%.

Table 2
Table 2:
Allele frequencies in cases and controls and their associations with COPD (positive loci).

Genotypic model analysis of COPD susceptibility

In this study, we performed logistic regression analysis to analyze the associations between the 28 SNPs and COPD risk using four genetic models (co-dominant, dominant, recessive, and log-additive). Crude analysis revealed that the “T/T” genotype of rs34695652 was associated with a decreased COPD risk under the recessive model (OR: 0.550, 95% CI: 0.350–0.860, P < 0.001). After adjusting for age, gender, and smoking status, the “T/T” rs34695652 genotype was confirmed to significantly decrease the risk of COPD in the recessive model (OR: 0.490, 95% CI: 0.270–0.880, P = 0.010), indicating that the rs34695652 polymorphism may protect against COPD development. No associations between the other SNPs and COPD were revealed in the recessive model.

Crude analysis under the dominant model showed that T/G-G/G genotype of rs10512248 (OR: 1.450, 95% CI: 1.040–2.010, P = 0.020), T/A-A/A genotype of rs28491365 (OR: 1.470, 95% CI: 1.060−2.050, P = 0.020), A/C-C/C genotype of rs28469297 (OR: 1.400, 95% CI: 1.010−1.940, P = 0.040), and T/G-G/G genotype of rs28705285 (OR: 1.420, 95% CI: 1.020−1.990, P = 0.030) were significantly associated with an increased risk of COPD. Furthermore, rs10512248 (OR: 1.310, 95% CI: 1.020–1.670, P = 0.030), rs28491365 (OR: 1.380, 95% CI: 1.050–1.810, P = 0.021), and rs28705285 (OR: 1.350, 95% CI: 1.020–1.790, P = 0.030) were significantly associated with COPD under the log-additive model. However, after adjustment for age, gender, and smoking status, no correlations between these SNPs and COPD were revealed by logistic regression analysis [Table 3]. There were no statistically significant associations between the other 23 SNPs and COPD risk [Supplementary Table 2, http://links.lww.com/CM9/A233].

Table 3
Table 3:
Genotypic model analysis of relationships between SNPs and COPD.

Haplotype and LD association analysis

As shown in Figure 1, seven LD blocks including 19 SNPs with D′ = 1 were detected. Analysis of the association between haplotypes and COPD by Pearson's Chi-squared test revealed that two SNPs, rs28504650 and rs10512248, formed four haplotypes: CG, CT, TG, and TT. After adjustment for age, gender, and smoking status, only the CG haplotype was found to be related to an increased risk of COPD (OR: 6.364, 95% CI: 1.220–33.292, P = 0.028) [Table 4]. Furthermore, another pair of SNPs, rs113154802 and rs28705285, formed three haplotypes: CG, CT, and TT; among them, the CG haplotype was found to be significantly associated with the COPD risk by crude analysis (OR: 1.335, 95% CI: 1.010–1.770, P = 0.044), but the association was not confirmed after adjustment for age, gender, and smoking status (OR: 1.354, 95% CI: 0.956–1.918, P = 0.087). Results of haplotype analysis for the other SNPs are shown in Supplementary Table 3, http://links.lww.com/CM9/A233.

Figure 1
Figure 1:
The haplotype block map constructed by candidate single-nucleotide polymorphisms in PTCH1.
Table 4
Table 4:
Haplotype frequencies of PTCH1 gene polymorphisms and the associations with COPD risk.

Discussion

In this case-control study, we evaluated the associations between COPD and 28 selected SNPs of the PTCH1 gene in a Chinese Han population from Hunan province. The results indicated that three SNPs, rs10512248, rs28491365, and rs28705285, were associated with an increased risk of COPD, whereas one SNP, rs34695652 was correlated with a decreased risk of the disease.

Previous studies have shown that the Hh signaling pathway is involved in the origin of several pathological conditions such as cancer and Hirschsprung disease,[6,7,16,17] and plays a key role in embryogenesis, including pulmonary branch formation and lung development.[18–20] PTCH1 is a key signaling molecule in the Hh signaling pathway, which binds to Hh ligands, thus activating the Hh cascade. The Hh signaling pathway is implicated in the COPD development, which is consistent with a genome-wide association studies showing that SNPs rs16909898, rs16909859, and rs10512249 in the PTCH1 gene were significantly associated with pulmonary function in European population.[21] Another study revealed that rs10512248 was correlated with FEV1 and forced vital capacity.[9] Furthermore, it was shown that PTCH1 was a negative regulator of Hh pathway and the expression of the PTCH1 protein was increased in the airway epithelium of patients with COPD.[22] These findings together with our results suggest that PTCH1 is related to COPD pathogenesis and may be a causal gene in the disease development.

SNP rs10512248 and rs28491365 identified in our study are located in intronic regions, which in most cases are not involved in protein synthesis and are considered as “junk DNA.” However, some studies indicate that introns can participate in gene expression at multiple levels in mammals; thus, regulatory elements in the intron region were shown to directly affect transcription.[23,24] Therefore, we speculate that the SNP (rs10512248 and rs28491365) could be involved in the pathogenesis of COPD through regulation of PTCH1 expression. The other identified SNPs rs28705285 and rs34695652 are located in 5′ flanking region and our results indicate that they are significantly associated with an increased and decreased risk of COPD, respectively.

Thus, our study provides a new insight into the effect of common mutations in the PTCH1 gene on the susceptibility to COPD in the Chinese Han population, presenting further evidence of PTCH1 involvement in the disease pathogenesis. To the best of our knowledge, this is the first report about the association between PTCH1 polymorphisms and the COPD risk in the Chinese population. However, the functional changes caused by PTCH1 mutations are not fully understood and the obtained results need to be confirmed in future studies on the role of the PTCH1 gene in COPD.

Our study had several intrinsic limitations. First, we could not confirm the interaction between genetic polymorphisms and environmental risk factors such as tobacco smoking which significantly increases the susceptibility to COPD, because our sample size was not sufficient. Studies involving a larger number of participants should be conducted in the future to explore the association between PTCH1 polymorphisms and the smoking status of patients with COPD. Second, the molecular mechanism underlying the association of COPD with PTCH1 polymorphisms was not clarified. After statistical adjustment, the significance of the association was not confirmed for some SNPs. Analysis of a higher number of loci is needed to verify the results of this study. In our study, the age difference was statistically significant between the two groups, however, we did not perform age-stratified analysis due to limited sample size

In summary, we identified, for the first time, three loci (rs10512248, rs28491365, and rs28705285) positively associated and one locus (rs34695652) negatively associated with COPD susceptibility in a Chinese Han population. This information should contribute to understanding of the COPD pathogenesis and provide a foundation for further research into the correlation between the PTCH1 gene and the COPD risk in different populations, thus promoting the development of new therapeutic strategies for this disease.

Acknowledgements

The authors are grateful to all individuals for participating in this study.

Funding

This work was supported by grants from the National Natural Science Foundation of China (Nos. 81470202, 81570288, and 81900002) and Central South University Clinical Data System for Pulmonary Inflammatory Diseases.

Conflicts of interest

None.

References

1. Hogg JC, McDonough JE, Sanchez PG, Cooper JD, Coxson HO, Elliott WM, et al. Micro-computed tomography measurements of peripheral lung pathology in chronic obstructive pulmonary disease. Proc Am Thorac Soc 2009; 6:546549. doi: 10.1513/pats.200905-029DS.
2. Pauwels RA, Rabe KF. Burden and clinical features of chronic obstructive pulmonary disease (COPD). Lancet 2004; 364:613620. doi: 10.1016/S0140-6736(04)16855-4.
3. Murray CJ, Lopez AD. Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet 1997; 349:14981504. doi: 10.1016/S0140-6736(96)07492-2.
4. Weiss ST. Lung function and airway diseases. Nat Genet 2010; 42:1416. doi: 10.1038/ng0110-14.
5. Fletcher C, Peto R. The natural history of chronic airflow obstruction. Br Med J 1977; 1:16451648. doi: 10.1136/bmj.1.6077.1645.
6. Watkins DN, Berman DM, Burkholder SG, Wang B, Beachy PA, Baylin SB. Hedgehog signalling within airway epithelial progenitors and in small-cell lung cancer. Nature 2003; 422:313317. doi: 10.1038/nature01493.
7. Krause A, Xu Y, Joh J, Hubner R, Gess A, Ilic T, et al. Overexpression of sonic Hedgehog in the lung mimics the effect of lung injury and compensatory lung growth on pulmonary Sca-1 and CD34 positive cells. Mol Ther 2010; 18:404412. doi: 10.1038/mt.2009.229.
8. Kogerman P, Krause D, Rahnama F, Kogerman L, Undén AB, Zaphiropoulos PG, et al. Alternative first exons of PTCH1 are differentially regulated in vivo and may confer different functions to the PTCH1 protein. Oncogene 2002; 21:60076016. doi: 10.1038/sj.onc.1205865.
9. Obeidat M, Hao K, Bossé Y, Nickle DC, Nie Y, Postma DS, et al. Molecular mechanisms underlying variations in lung function: a systems genetics analysis. Lancet Respir Med 2015; 3:782795. doi: 10.1016/S2213-2600(15)00380-X.
10. Hindorff LA, Sethupathy P, Junkins HA, Ramos EM, Mehta JP, Collins FS, et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc Natl Acad Sci U S A 2009; 106:93629367. doi: 10.1073/pnas.0903103106.
11. Vestbo J, Hurd SS, Agustí AG, Jones PW, Vogelmeier C, Anzueto A, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2013; 187:347365. doi: 10.1164/rccm.201204-0596PP.
12. Luo H, Xie L, Wang SZ, Chen JL, Huang C, Wang J, et al. Duplication of 8q12 encompassing CHD7 is associated with a distinct phenotype but without duane anomaly. Eur J Med Genet 2012; 55:646649. doi: 10.1016/j.ejmg.2012.07.006.
13. Teramoto S, Ishii T, Yamamoto H, Yamaguchi Y, Matsuse T. Xenobiotic enzymes and genetics of COPD. Chest 2005; 127:408409. doi: 10.1378/chest.127.1.408.
14. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005; 21:263265. doi: 10.1093/bioinformatics/bth457.
15. Solé X, Guinó E, Valls J, Iniesta R, Moreno V. SNPStats: a web tool for the analysis of association studies. Bioinformatics 2006; 22:19281929. doi: 10.1093/bioinformatics/btl268.
16. Chuang PT, Kawcak T, McMahon AP. Feedback control of mammalian Hedgehog signaling by the Hedgehog-binding protein, Hip1, modulates Fgf signaling during branching morphogenesis of the lung. Genes Dev 2003; 17:342347. doi: 10.1101/gad.1026303.
17. Wang Y, Wang J, Pan W, Zhou Y, Xiao Y, Zhou K, et al. Common genetic variations in Patched1 (PTCH1) gene and risk of Hirschsprung disease in the Han Chinese population. PLoS One 2013; 8:e75407doi: 10.1371/journal.pone.0075407.
18. Teglund S, Toftgård R. Hedgehog beyond medulloblastoma and basal cell carcinoma. Biochim Biophys Acta 2010; 1805:181208. doi: 10.1016/j.bbcan.2010.01.003.
19. Ngan ES, Garcia-Barceló MM, Yip BH, Poon HC, Lau ST, Kwok CK, et al. Hedgehog/Notch-induced premature gliogenesis represents a new disease mechanism for Hirschsprung disease in mice and humans. J Clin Invest 2011; 121:34673478. doi: 10.1172/JCI43737.
20. Li X, Howard TD, Moore WC, Ampleford EJ, Li H, Busse WW, et al. Importance of hedgehog interacting protein and other lung function genes in asthma. J Allergy Clin Immunol 2011; 127:14571465. doi: 10.1016/j.jaci.2011.01.056.
21. Hancock DB, Eijgelsheim M, Wilk JB, Gharib SA, Loehr LR, Marciante KD, et al. Meta-analyses of genome-wide association studies identify multiple loci associated with pulmonary function. Nat Genet 2010; 42:4552. doi: 10.1038/ng.500.
22. Tam A, Hughes M, McNagny KM, Obeidat M, Hackett TL, Leung JM, et al. Hedgehog signaling in the airway epithelium of patients with chronic obstructive pulmonary disease. Sci Rep 2019; 9:3353doi: 10.1038/s41598-019-40045-3.
23. Shaul O. How introns enhance gene expression. Int J Biochem Cell Biol 2017; 91:145155. doi: 10.1016/j.biocel.2017.06.016.
24. De Conti L, Baralle M, Buratti E. Exon and intron definition in pre-mRNA splicing. Wiley Interdiscip Rev RNA 2013; 4:4960. doi: 10.1002/wrna.1140.
Keywords:

PTCH1; Chronic obstructive pulmonary disease; Gene polymorphism; Case-control study; Single-nucleotide polymorphisms

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