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Analysis of the association of ANO3/MUC15, COL4A4, RRBP1, and KLK1 polymorphisms with COPD susceptibility in the Kashi population

Abstract

Objective

Chronic obstructive pulmonary disease (COPD) is a complex, multifactorial, polygenic disease. The rate of occurrence of COPD in the Kashi population (Uyghur) is significantly higher than that observed nationwide. The identification of COPD-related genes in the Chinese Uyghur population could provide useful insights that could help us understand this phenomenon. Our previous whole-exome sequencing study of three Uyghur families with COPD demonstrated that 72 mutations in 55 genes might be associated with COPD; these included rs15783G > A in the anoctamin 3 (ANO3) gene/mucin 15 (MUC15) gene, rs1800517G > A in the collagen type IV alpha 4 chain (COL4A4) gene, rs11960G > A in the ribosome binding protein 1 (RRBP1) gene, and rs5516C > G in the kallikrein 1 (KLK1) gene. This case–control study aimed to further validate the association of the four mutations with COPD in the Chinese Uyghur population.

Methods

Sanger sequencing was used for the genotyping of four polymorphisms (ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516) in 541 unrelated Uyghur COPD patients and 534 Uyghur healthy controls. We then conducted stratified analyses based on the smoking status and airflow limitation severity, to explore the correlation between selected gene polymorphisms and COPD.

Results

ANO3/MUC15 rs15783 and KLK1 rs5516 polymorphisms could significantly reduce COPD risk (p < 0.05), but COL4A4 rs1800517 and RRBP1 rs11960 polymorphisms were not correlated with COPD in the entire population. In a stratified analysis of smoking status, non-smokers with the ANO3/MUC15 rs15783G/G genotype (OR = 0.63, p = 0.032) or COL4A4 rs1800517 allele G (OR = 0.80, p = 0.023) had a reduced risk of COPD. Smokers with the RRBP1 rs11960A/G genotype had a lower risk of COPD (OR = 0.41, p = 0.025). The KLK1 rs5516G > C polymorphism was associated with a decreased risk of COPD (OR < 1, p < 0.05), irrespective of the smoking status of individuals. No significant association with COPD severity was observed in individuals with these four polymorphisms (p > 0.05).

Conclusion

We identified four previously unreported mutations (ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516) that might decrease the COPD risk in individuals with different smoking statuses in the Chinese Uyghur population. Our findings provide new light for the genetic risk factors associated with the occurrence of COPD.

Peer Review reports

Introduction

Chronic obstructive pulmonary disease (COPD) is characterized by persistent respiratory symptoms and airflow limitations [1], which are correlated with higher morbidity and mortality worldwide [2]. Cigarette smoking (CS) is the leading environmental risk factor for COPD; yet, even among heavy smokers, less than 50% develop COPD during their lifetime [3]. Epidemiologic studies have consistently shown that people who have never smoked might develop chronic airflow limitations [4]. In addition, during our previous epidemiological investigation in Kashi (Xinjiang, China), three three-generation families had presented with COPD [5]. The mechanisms responsible for the occurrence of these phenomena are unclear, but could depend at least partially on the genetic makeup of individuals. The epidemiolog ical investigation also showed that the rate of occurrence of COPD in Chinese Uighurs whose age was above 40 years in Kashi was 17.01% [5] and was significantly higher than that observed nationwide [6]. The identification of COPD-related genes in the Chinese Uyghur population could provide useful insights that could help us understand this phenomenon.

Protein-coding genes constitute only ~ 1% of the human genome but harbor 85% of all mutations and significantly influence the occurrence of disease-related traits; thus, whole-exome sequencing (WES) can be used to obtain relevant insights into diverse human diseases [7]. Therefore, we performed WES on eight people with COPD and one healthy person from three Uyghur families with COPD in Kashi to screen for the susceptibility genes and polymorphisms related to COPD [8]. WES facilitated the identification of 72 single nucleotide variants (SNVs) of 55 genes, including g.26565254G > A (rs15783G > A, NC_000011.10) in the anoctamin 3 (ANO3) gene/mucin 15 (MUC15) gene, g.227051116G > A (rs1800517G > A, NC_000002.12) in the collagen type IV alpha 4 chain (COL4A4) gene, g.17619712G > A (rs11960G > A, NC_000020.11) in the ribosome binding protein 1 (RRBP1) gene, and g.50820217C > G (rs5516C > G, NC_000019.10) in the kallikrein 1 (KLK1) gene [8] (Fig. 1 and Additional files 1, 2, 3 and 4). Notably, the WES study evaluated only one healthy control as a reference; the screened 72 SNVs might include SNVs found in healthy people. Hence, it was necessary to verify the relationship between these 72 SNVs and COPD in a case–control study. Moreover, although scholars have found that several gene polymorphisms might be related to COPD susceptibility [9, 10], the correlation between polymorphisms of the four genes (ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516) and COPD risk is still poorly understood. Therefore, a case–control study of 1075 individuals (541 COPD patients and 534 healthy subjects) recruited from the same population was conducted, to evaluate the correlation between four selected SNVs and COPD risk. Furthermore, the correlations between the four selected SNVs and both clinical and functional parameters were explored. We found that the ANO3/MUC15, KLK1, COL4A4, and RRBP1 polymorphisms were closely associated with a decreased risk of COPD in individuals with different smoking statuses. The four SNVs were not found to be correlated with COPD severity after a stratified analysis based on airflow limitation severity. Our findings would provide further insights into the mechanism of occurrence of COPD.

Fig. 1
figure 1

The physical location of MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516 (Genes, NCBI Homo sapiens Annotation Release)

Materials and methods

Experimental subjects

Individuals included 541 Uyghur unrelated COPD patients and 534 Uyghur healthy controls were consecutively recruited from the First people’s Hospital of Kashi during the period from 2018 to 2019. The age of all the participants was > 40 years. Spirometry (Cosmed, Rome, Italy) was performed for all subjects. COPD was diagnosed in accordance with the diagnostic criteria outlined by the global initiative for chronic obstructive lung disease (GOLD), which specified that the post-bronchodilator forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) should be < 70% [1]. Baseline characteristics and classical COPD risk factors were recorded. None of the subjects were diagnosed with a history of atopy and an α1-antitrypsin deficiency. Additional inclusion and exclusion criteria for the participants were described by Gong et al. [11].

Informed written consent was obtained from all subjects. This study was carried out with the approval (Approval details: Kuai Shen Yan No. 70) of the Ethics Committee of the First People's Hospital of Kashi. Five milliliters of peripheral blood samples were obtained from each of the 1075 participants for DNA extraction and transferred to BD Vacutainer ® EDTA-K2 blood collection tubes for DNA extraction.

Target gene sequencing

Genomic DNA samples were extracted from the peripheral blood using the Genomic DNA purification Kit (TIANGEN BIOTECH (BEIJING) CO.,LTD, China), in accordance with the manufacturer's instructions. The NanoDrop 2000 (Thermo Fisher Scientific, Waltham, MA, USA) was used to measure the concentration and quality of extracted DNA. The four SNVs (ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516) were genotyped via Sanger sequencing using a custom-by-design 48-Plex SNPscan Kit (Center for Genetic & Genomic Analysis, Genesky Biotechnologies Inc., Shanghai, China) [8]. The ABI3730XL (Applied Biosystems, USA) sequenator and GeneMapper 4.1 (Applied Biosystems, USA) were adopted to analyze the polymorphisms.

Statistical analysis

SPSS 18.0 statistical software (SPSS Inc., Chicago, IL, U.S.A.) was used for statistical analysis. Quantitative data were presented as means ± standard deviations (SD) for normally distributed values or medians plus interquartile ranges for non-normally distributed data. Categorical variables were described in terms of the count (%). Pearson's chi-squared test was used to compare the differences in gender, smoking status, smoking index (SI), wood consumption, and coal consumption. The differences in age and body mass index (BMI) between different groups were assessed using an independent sample t-test, after quantile–quantile (QQ) plots demonstrated that these data showed an approximately normal distribution. FEV1%, FEV1/FVC, and annual household income values that did not conform to the normal distribution were calculated using the Mann–Whitney U test. Fisher's exact test was used to assess the variations in all the SNVs frequencies by assessing the Hardy–Weinberg equilibrium (HWE). Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated to determine the association between the selected SNVs and COPD risk using logistic regression analysis, with adjustments for age, gender, and BMI. Using PLINK software (version 2.0), the effects attributable to single nucleotide polymorphisms (SNPs) were fitted under five models of inheritance, i.e., the additive, codominant, dominant, recessive, and allele models. The stratified model was applied for subgroup analysis after taking the smoking status and pulmonary function of participants into consideration. We used p < 0.05 as the cut-off value for determining statistical significance.

Results

Characteristics of the study population

The clinical characteristics and spirometry data of 1075 participants in the case–control study have been provided in Table 1. A total of 541 COPD patients (280 male and 261 female) and 534 controls (234 male and 300 female) were included in the study. There was no significant difference between COPD cases and controls in terms of wood consumption, coal consumption, and annual household income (p > 0.05). The differences between the two groups with regard to age, gender, BMI, smoking status, smoking index, FEV1%, and FEV1/FVC were statistically significant (p < 0.05). Within the COPD population, 150, 292, 82, and 17 patients had mild disease (FEV1 ≥ 80% predicted), moderate disease (50% ≤ FEV1 < 80% predicted), severe disease (30% ≤ FEV1 < 50% predicted), and very severe disease (FEV1 < 30% predicted), respectively.

Table 1 General characteristics of COPD patients and healthy subjects

Genotype analyses of COPD risk

Four SNVs (ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516) of target genes were successfully genotyped in the case–control study. The call success rate was more than 99%. Genotype distributions of the above SNVs were in accordance with Hardy–Weinberg equilibrium predictions (p > 0.05) (Table 2).

Table 2 Basic information and allele frequencies among all SNVs

To identify whether the polymorphisms of these genes were related to COPD susceptibility, we analyzed five genetic models (additive, codominant, dominant, recessive, and allele) that were adjusted for age, gender, and BMI (Table 3). The results showed that the ANO3/MUC15 rs15783G > A and KLK1 rs5516C > G polymorphisms were correlated with a decreased risk of COPD (p < 0.05). Individuals with the ANO3/MUC15 rs15783 G/G genotype had a reduced risk of COPD, as shown by the results obtained with the codominant model (OR = 0.67, p = 0.038) and recessive model (OR = 0.67, p = 0.021). The KLK1 rs5516 C/C genotype was associated with a decreased risk of COPD under the codominant model (OR = 0.62, p = 0.042) and recessive model (OR = 0.62, p = 0.039). No significant association was observed for other SNVs.

Table 3 Analysis of genotypes of ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516

Stratified analysis of rs15783G > A, rs1800517G > A, rs11960G > A, and rs5516C > G in the case–control study based on smoking status

COPD is a complex disease that is likely influenced by environmental factors, multiple genes, and gene-by-smoking/environmental interactions [12, 13]. To investigate whether the association between these four variants and COPD risk differed between smokers and non-smokers, we conducted a subgroup analysis (Table 4).

Table 4 Analysis of genotypes of all SNVs among non-smoker and smoker group

We found that ANO3/MUC15 rs15783 and COL4A4 rs1800517 polymorphisms were only related to an altered risk of COPD in non-smokers (p < 0.05). Individuals with the ANO3/MUC15 rs15783 G/G genotype had a reduced risk in the codominant (OR = 0.63, p = 0.032) and recessive (OR = 0.63, p = 0.017) models. Another COL4A4 rs1800517G > A polymorphism also played a protective role in non-smokers, and carriers of the minor allele (G) had a lower risk for COPD, based on the results for the allele (OR = 0.80, p = 0.023) and additive (OR = 0.80, p = 0.025) models. Additionally, the COL4A4 rs1800517 G/G genotype was also associated with a decreased risk of COPD in the codominant (OR = 0.64, p = 0.026) and dominant (OR = 0.72, p = 0.039) models.

The RRBP1 rs11960G > A played a protective role in smokers (p < 0.05). The RRBP1 rs11960 A/G genotype was associated with a decreased risk of COPD, based on the results obtained with the codominant (OR = 0.41, p = 0.025) and dominant (OR = 0.40, p = 0.018) models. The RRBP1 rs11960G > A SNV fitted the additive model, and a significantly decreased risk of COPD was observed in the presence of a “G” allele (OR = 0.62, p = 0.041).

We observed that the KLK1 rs5516C > G polymorphism influenced COPD risk in both smokers and non-smokers in different genetic models. The results of the stratified analyses for the recessive model (OR = 0.60, p = 0.046) indicated that the KLK1 rs5516 C/C genotype was associated with a decreased risk of COPD in non-smoking participants. However, we also found that the KLK1 rs5516 polymorphism was strongly related to COPD risk in smoking participants, while carriers of the G/C genotype were at lower risk for COPD, based on the results obtained with the codominant (OR = 0.39, p = 0.007) and dominant (OR = 0.41, p = 0.007) models. The KLK1 rs5516C > G SNV fitted the additive model, and was observed to be associated with a significantly decreased risk of COPD in the presence of a "C" allele (OR = 0.56, p = 0.024).

Stratified analysis of rs15783G > A, rs1800517G > A, rs11960G > A, and rs5516C > G based on COPD severity in the case–control study

Using a logistic regression model, we investigated the association of ANO3/MUC15, COL4A4, RRBP1, and KLK1 genotype distributions and disease severity based on lung function, using a cutoff limit of FEV1 = 50% predicted. As shown in Table 5, no significant correlation was found between the genotype distribution of ANO3/MUC15 rs15783G > A, COL4A4 rs1800517G > A, RRBP1 rs11960G > A, and KLK1 rs5516C > G polymorphisms and airflow limitation severity (p > 0.05).

Table 5 Analysis of genotypes of all SNVs at different FEV1 predicted values in COPD patients

Discussion

COPD is a heterogeneous and complex disease, and the genetic composition of an individual could significantly determine susceptibility [3,4,5]. We first screened four mutations, namely, ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516, which were identified to be associated with COPD via a WES analysis of a cluster of three COPD families. The results of association analysis for these four SNVs indicated that the ANO3/MUC15 rs15783 and KLK1 rs5516 polymorphisms were associated with COPD susceptibility in the entire population. Further, upon performing stratified analysis, we found that the ANO3/MUC15, KLK1, COL4A4, and RRBP1 polymorphisms were closely associated with a reduced risk of COPD in individuals with different smoking statuses, but were not related to disease severity.

The ANO3/MUC15 rs15783, COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516 are non-synonymous variants (via NCBI database: https://www.ncbi.nlm.nih.gov/). Three of the 4 SNVs (COL4A4 rs1800517, RRBP1 rs11960, and KLK1 rs5516) are exonic SNPs and correspond to a missense substitution. Only SNV rs15783 occurs in the overlapping genes ANO3 and MUC15; it occurs as an intronic SNP in ANO3 (intron 13 of NM_031418.2 transcript) and exonic SNP in MUC15, and corresponds to a missense substitution (Thr > Ile) at position 229 in the MUC15 isoform b [14]. The enrichment analyses of the Gene Ontology (GO) database (http://www.geneontology.org) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway (https://www.genome.jp/kegg) indicated that the four genes did not occur in the same KEGG metabolic pathway. In addition, protein interaction network analysis using the STRING database (https://string-db.org/) showed that these proteins did not interact with each other in any manner.

Prolonged exposure to CS might increase the total burden attributable to environmental factors such as genetic predisposition, which might increase the risk of COPD sufficiently and cause COPD [12, 13], especially in individuals with high levels of susceptibility. In the present study, we first demonstrated that the ANO3/MUC15 rs15783 and COL4A4 rs1800517 SNVs were associated with a reduced risk of COPD in non-smokers. Notably, smokers did not have a significantly altered risk of COPD, regardless of the genetic model, compared to non-smokers. This suggests that the G/G genotype of ANO3/MUC15 rs15783 and allele G of COL4A4 rs1800517 might exhibit only a weak protective effect against COPD in non-smokers; this protective relationship would be reversed if non-smokers carrying protective mutations at these two loci were affected by CS. Here, the RRBP1 rs11960 polymorphism was also first shown to be associated with COPD susceptibility in smokers; an individual with allele G could have a significantly reduced risk of COPD. Interestingly, we observed that this protective effect of RRBP1 rs11960 could be observed only in those carrying heterozygous mutations. In addition, we found that the risk of COPD was decreased in smokers with the KLK1 rs5516 G/C genotype and non-smokers with the rs5516 C/C variant, though individuals with different smoking statuses were affected by homozygous and heterozygous mutations.

COPD manifests as persistent airflow obstruction. Although mucus and other epithelial secretions of the airway play a critical role in protecting the lung during acute injury, impaired mucus clearance after chronic mucus hyperproduction causes airway obstruction, infection, and inflammation, which contribute to morbidity in common pulmonary disorders, including chronic obstructive pulmonary disease and asthma [15]. ANO3 (also known as TMEM16C) belongs to the TMEM16 family encoding predicted membrane proteins that are involved in the functioning of intracellular calcium-activated chloride channels (CaCCs). These proteins perform many important functions in cell physiology, including the facilitation of fluid secretion from acinar cells of secretory glands, regulation of neuronal excitability, and regulation of smooth muscle contraction [16]. Although limited information is available regarding the function of TMEM16C in COPD pathology, another anoctamin (TMEM16A) has been shown to be involved in CaCC-based mechanisms resulting in excessive mucus secretion and airway smooth muscle contraction during inflammatory airway disease [17]. The process of GO annotation of genes related to TMEM16A and TMEM16C includes genes that facilitate intracellular CaCC activity, suggesting that TMEM16C might also be involved in the pathophysiological mechanism of occurrence of COPD, via the regulation of mucus secretion or airway smooth muscle contraction. However, studies on ANO3 have mainly focused on genetic dystonia [18]. MUC15 (Mucin 15, cell surface associated) belongs to the family of mucin genes, which encode large epithelial glycoproteins that are major constituents of the mucus that covers the surfaces of epithelial tissues and provides a physical barrier that protects the underlying epithelium [19]. MUC15 is a highly glycosylated protein exhibiting the structural features observed in other inline membrane mucins [20]. Therefore, we hypothesized that MUC15 might play a key role in the occurrence and development of COPD. However, studies on the correlation between MUC15 and human disease mainly focus on malignant tumors [21], and its correlation with COPD is still poorly understood. We showed that ANO3/MUC15 rs15783 might act as a protective factor against COPD. It should be noted that both ANO3 and MUC15, which are affected by the SNV rs15783, may be related to COPD; thus, ANO3/MUC15 rs15783 SNV is highly likely to alter the risk of COPD.

COL4A4 encodes one of the six subunits of type IV collagen, the major structural component of basement membranes that majorly contribute to the strength of the blood-gas barrier (BGB) [22]. The BGB (also known as the alveolar-capillary barrier) is the key functional element of the lung, and serves as the site of oxygen and carbon dioxide exchange between distal airspaces and the pulmonary vasculature [23]. A recent animal (mouse and chick) study found that type IV collagen plays a key role during alveolar morphogenesis and is critical for the proper formation of the BGB and the process of septation [22]. COPD is characterized by persistent respiratory symptoms and airflow limitations caused by airway and/or alveolar abnormalities that are influenced by a host of factors, including abnormal lung development [1]. An impaired microvascular barrier also has been observed in COPD patients [24, 25]. Meanwhile, it has been reported that type IV collagen is important for maintaining the integrity of the vascular basement membrane [26]. The important role of type IV collagen in the alveolar sphere and pulmonary vascular basement membrane structure suggests that a mutation in COL4A4 might contribute to COPD occurrence. Although COL4A4 is widely expressed in both kidney (RPKM 5.3) and lung (RPKM 4.3) tissues (via NCBI database: https://www.ncbi.nlm.nih.gov/), previous studies have mainly focused on COL4A4 expression in the glomerular basement membrane [27, 28]. The specific role of COL4A4 in COPD development remains unknown. Our study has shown for the first time that COL4A4 rs1800517 allele G may act as a protective factor against COPD. We speculated that the COL4A4 rs1800517 SNV might prevent the occurrence of COPD as it affects basement membrane components in the lung tissue.

Endoplasmic reticulum stress (ERS) can be attributed to the improper folding or conformation (misfolded protein) of proteins, which can interfere with the normal physiological functions of the cell [29]. The unfolded protein response (UPR) is a mechanism by which cells control ER protein homeostasis [30]. RRBP1 was originally identified as a ribosome-binding protein located on the rough endoplasmic reticulum, and was majorly involved in regulating the secretion of intracellular proteins and alleviation of ERS [31,32,33]. ERS can be strongly induced by cigarette smoke extracts [34]. Several studies have indicated that the inhibition of ERS can largely ameliorate CS-induced airway inflammation and emphysema through the suppression of inflammation, apoptosis, and oxidative stress, via the blocking of ERS [34,35,36,37]. ERS has been implicated in COPD [38], while RRBP1 is associated with the regulation of UPR; however, the role of RRBP1 in COPD development is unclear. Here, the RRBP1 rs11960 polymorphism was first shown to be a protective factor in smokers. Therefore, we speculated that RRBP1 might potentially exhibit protective effects against COPD by inhibiting CS-induced ERS.

A characteristic pathologic feature of COPD is a protease-antiprotease imbalance [39]. KLK1 is one of the important regulatory genes contributing to a protease-antiprotease imbalance, and is essential for the pathogenesis of COPD. Previous studies have shown that the uncontrolled activity of KLK1 can lead to the direct proteolytic cleavage of the pro-epidermal growth factor, release of mature epidermal growth factor, and subsequent activation of epidermal growth factor receptor (EGFR), thereby resulting in metaplasia and excessive mucus secretion in individuals with airway diseases [40]. In addition, EGFR activation was also related to the pathologic phenotypes of epithelial cells in smokers [41]. Upon exposure to the reactive oxygen species derived from cigarette smoke or endogenous sources, the up-regulation of KLK1 activity leads to the degradation of the hyaluronic acid (HA) occurring on airway epithelial cells [42], subsequently weakening the limiting effect of the proteolytic activity of HA [43]. The KLK1 rs5516 polymorphism influences susceptibility of multiple diseases and conditions, including aortic aneurysm [44], thoracic aortic dissection [45], SLE with nephritis [46], and essential hypertension [47]. To date, this is the first study to demonstrate that KLK1 rs5516 SNV might be associated with COPD susceptibility.

We used a combination of whole-exome and targeted sequencing to search for novel genetic characteristics of COPD in the Chinese Uighur population. To our knowledge, we are the first to report the association between the four SNVs and COPD risk. However, several limitations are associated with our study. First, our population verification process is based on the ethnic characteristics of individuals from Kashi, i.e., the Uyghur population. Therefore, the results are not representative of other ethnic groups. Second, the sample size of the subgroup of smokers was small; hence, our findings need to be confirmed in studies with a larger sample size of smokers. In addition, although polymorphisms of four genes identified in this study might be associated with lower prevalence of COPD, the specific role of these genes in COPD pathogenesis is unclear. Additional investigations, including multi-omics approaches and functional studies are needed, to further determine disease causality and biological mechanisms of action of these genes.

Conclusion

The present study identified four previously unreported mutations that were associated with COPD susceptibility in individuals with different smoking statuses. The ANO3/MUC15 rs15783G > A and COL4A4 rs1800517G > A polymorphisms had protective effects on non-smokers, while the RRBP1 rs11960G > A polymorphism had protective effects on smokers. The KLK1 rs5516C > G polymorphism was associated with a decreased risk of COPD, irrespective of whether the individual was a smoker or non-smoker. Our findings provide new insights regarding the contribution of the genetic makeup of an individual to COPD pathogenesis in a Chinese Uyghur population.

Availability of data and materials

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

COPD:

Chronic obstructive pulmonary disease

ANO3/MUC15 :

Anoctamin 3/Mucin 15

COL4A4 :

Collagen type IV Alpha 4 chain

KLK1 :

Kallikrein 1

RRBP1 :

Ribosome binding protein 1

CS:

Cigarette smoking

WES:

Whole-exome sequencing

SNVs:

Single nucleotide variants

GOLD:

Global initiative for chronic obstructive lung disease

FEV1:

Forced expiratory volume in 1 s

FVC:

Forced vital capacity

BMI:

Body mass index

SNP:

Single nucleotide polymorphism

MAF:

Minor allele frequency

HWE:

Hardy–Weinberg equilibrium

QQ:

Quantile–quantile

SD:

Standard deviation

ORs:

Odds ratios

CIs:

Confidence intervals

CaCCs:

Calcium-activated chloride channels

GO:

Gene ontology

BGB:

Blood-gas barrier

ERS:

Endoplasmic reticulum stress

UPR:

The unfolded protein response

EGFR:

Epidermal growth factor receptor

NIV:

Noninvasive ventilation

SABA:

Short-acting beta2-agonist

SAMA:

Short-acting muscarinic antagonist

LABA:

Long-acting beta2-agonist

LAMA:

Long-acting muscarinic antagonist

ICS:

Inhaled corticosteroids

LTRA:

Leukotriene receptor antagonist

References

  1. Vogelmeier CF, Criner GJ, Martinez FJ, Anzueto A, Barnes PJ, Bourbeau J, Celli BR, Chen R, Decramer M, Fabbri LM, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive lung disease 2017 report. GOLD executive summary. Am J Respir Crit Care Med. 2017;195(5):557–82.

    Article  CAS  PubMed  Google Scholar 

  2. Collaborators GBDCoD. Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the global burden of disease study 2016. Lancet. 2017;390(10100):1151–210.

    Article  Google Scholar 

  3. Rennard SI, Vestbo J. COPD: the dangerous underestimate of 15%. Lancet. 2006;367(9518):1216–9.

    Article  PubMed  Google Scholar 

  4. Ruvuna L, Sood A. Epidemiology of chronic obstructive pulmonary disease. Clin Chest Med. 2020;41(3):315–27.

    Article  PubMed  Google Scholar 

  5. Li L, Zhong X, Zheng A, JianKun C, Budukadeer AA, Aini P, Tuerxun M, Yasen M, Ma T, Ren J, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in Kashi region, Northwestern China. Int J Chron Obstr Pulm Dis. 2021;16:655–63.

    Article  Google Scholar 

  6. Wang C, Xu J, Yang L, Xu Y, Zhang X, Bai C, Kang J, Ran P, Shen H, Wen F, et al. Prevalence and risk factors of chronic obstructive pulmonary disease in China (the China pulmonary health [CPH] study): a national cross-sectional study. Lancet. 2018;391(10131):1706–17.

    Article  PubMed  Google Scholar 

  7. Choi M, Scholl UI, Ji W, Liu T, Tikhonova IR, Zumbo P, Nayir A, Bakkaloglu A, Ozen S, Sanjad S, et al. Genetic diagnosis by whole exome capture and massively parallel DNA sequencing. Proc Natl Acad Sci U S A. 2009;106(45):19096–101.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Xu J, Li L, Ren J, Zhong X, Xie C, Zheng A, Abudukadier A, Tuerxun M, Zhang S, Tang L, et al. Whole-exome sequencing implicates the USP34 rs777591A > G intron variant in chronic obstructive pulmonary disease in a Kashi cohort. Front Cell Dev Biol. 2021;9: 792027.

    Article  PubMed  Google Scholar 

  9. Busch R, Hobbs BD, Zhou J, Castaldi PJ, McGeachie MJ, Hardin ME, Hawrylkiewicz I, Sliwinski P, Yim JJ, Kim WJ, et al. Genetic association and risk scores in a chronic obstructive pulmonary disease meta-analysis of 16,707 subjects. Am J Respir Cell Mol Biol. 2017;57(1):35–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Silverman EK. Genetics of COPD. Annu Rev Physiol. 2020;82:413–31.

    Article  CAS  PubMed  Google Scholar 

  11. Gong H, Ren J, Xu J, Zhong X, Abudureheman Z, Yilamujiang S, Xie C, Ma T, Li F, Tang L, et al. SMAD3 rs36221701 T>C polymorphism impacts COPD susceptibility in the Kashi population. Gene. 2022;808: 145970.

    Article  CAS  PubMed  Google Scholar 

  12. Su J, Ye Q, Zhang D, Zhou J, Tao R, Ding Z, Lu G, Liu J, Xu F. Joint association of cigarette smoking and PM2.5 with COPD among urban and rural adults in regional China. BMC Pulm Med. 2021;21(1):87.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Postma DS, Bush A, van den Berge M. Risk factors and early origins of chronic obstructive pulmonary disease. Lancet. 2015;385(9971):899–909.

    Article  PubMed  Google Scholar 

  14. Dizier MH, Margaritte-Jeannin P, Madore AM, Esparza-Gordillo J, Moffatt M, Corda E, Monier F, Guilloud-Bataille M, Franke A, Weidinger S, et al. The ANO3/MUC15 locus is associated with eczema in families ascertained through asthma. J Allergy Clin Immunol. 2012;129(6):1547–53.

    Article  CAS  PubMed  Google Scholar 

  15. Boucher RC. Muco-obstructive lung diseases. N Engl J Med. 2019;380(20):1941–53.

    Article  CAS  PubMed  Google Scholar 

  16. Le SC, Yang H. Structure-function of TMEM16 ion channels and lipid scramblases. Adv Exp Med Biol. 2021;1349:87–109.

    Article  PubMed  Google Scholar 

  17. Zhou-Suckow Z, Duerr J, Hagner M, Agrawal R, Mall MA. Airway mucus, inflammation and remodeling: emerging links in the pathogenesis of chronic lung diseases. Cell Tissue Res. 2017;367(3):537–50.

    Article  CAS  PubMed  Google Scholar 

  18. Lange LM, Junker J, Loens S, Baumann H, Olschewski L, Schaake S, Madoev H, Petkovic S, Kuhnke N, Kasten M, et al. Genotype-phenotype relations for isolated dystonia genes: MDSGene systematic review. Mov Disord. 2021;36(5):1086–103.

    Article  CAS  PubMed  Google Scholar 

  19. Ma J, Rubin BK, Voynow JA. Mucins, Mucus, and Goblet Cells. Chest. 2018;154(1):169–76.

    Article  PubMed  Google Scholar 

  20. Pallesen LT, Berglund L, Rasmussen LK, Petersen TE, Rasmussen JT. Isolation and characterization of MUC15, a novel cell membrane-associated mucin. Eur J Biochem. 2002;269(11):2755–63.

    Article  CAS  PubMed  Google Scholar 

  21. Zhang S, Zhang W, Xiao Y, Qin T, Yue Y, Qian W, Shen X, Ma Q, Wang Z. Targeting MUC15 protein in cancer: molecular mechanisms and therapeutic perspectives. Curr Cancer Drug Targets. 2020;20(9):647–53.

    Article  PubMed  CAS  Google Scholar 

  22. Loscertales M, Nicolaou F, Jeanne M, Longoni M, Gould DB, Sun Y, Maalouf FI, Nagy N, Donahoe PK. Type IV collagen drives alveolar epithelial-endothelial association and the morphogenetic movements of septation. BMC Biol. 2016;14:59.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Leiby KL, Raredon MSB, Niklason LE. Bioengineering the blood-gas barrier. Compr Physiol. 2020;10(2):415–52.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Harris B, Klein R, Jerosch-Herold M, Hoffman EA, Ahmed FS, Jacobs DR Jr, Klein BE, Wong TY, Lima JA, Cotch MF, et al. The association of systemic microvascular changes with lung function and lung density: a cross-sectional study. PLoS ONE. 2012;7(12): e50224.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kyomoto Y, Kanazawa H, Tochino Y, Watanabe T, Asai K, Kawaguchi T. Possible role of airway microvascular permeability on airway obstruction in patients with chronic obstructive pulmonary disease. Respir Med. 2019;146:137–41.

    Article  PubMed  Google Scholar 

  26. Thomsen MS, Birkelund S, Burkhart A, Stensballe A, Moos T. Synthesis and deposition of basement membrane proteins by primary brain capillary endothelial cells in a murine model of the blood-brain barrier. J Neurochem. 2017;140(5):741–54.

    Article  CAS  PubMed  Google Scholar 

  27. Storey H, Savige J, Sivakumar V, Abbs S, Flinter FA. COL4A3/COL4A4 mutations and features in individuals with autosomal recessive alport syndrome. J Am Soc Nephrol. 2013;24(12):1945–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Guo L, Li D, Dong S, Wan D, Yang B, Huang Y. Mutation analysis of COL4A3 and COL4A4 genes in a Chinese autosomal-dominant Alport syndrome family. J Genet. 2017;96(2):389–92.

    Article  CAS  PubMed  Google Scholar 

  29. Oakes SA, Papa FR. The role of endoplasmic reticulum stress in human pathology. Annu Rev Pathol. 2015;10:173–94.

    Article  CAS  PubMed  Google Scholar 

  30. Read A, Schroder M. The unfolded protein response: an overview. Biology (Basel). 2021;10(5):384.

    CAS  Google Scholar 

  31. Savitz AJ, Meyer DI. Identification of a ribosome receptor in the rough endoplasmic reticulum. Nature. 1990;346(6284):540–4.

    Article  CAS  PubMed  Google Scholar 

  32. Tsai HY, Yang YF, Wu AT, Yang CJ, Liu YP, Jan YH, Lee CH, Hsiao YW, Yeh CT, Shen CN, et al. Endoplasmic reticulum ribosome-binding protein 1 (RRBP1) overexpression is frequently found in lung cancer patients and alleviates intracellular stress-induced apoptosis through the enhancement of GRP78. Oncogene. 2013;32(41):4921–31.

    Article  CAS  PubMed  Google Scholar 

  33. Wang W, Wang M, Xiao Y, Wang Y, Ma L, Guo L, Wu X, Lin X, Zhang P. USP35 mitigates endoplasmic reticulum stress-induced apoptosis by stabilizing RRBP1 in non-small cell lung cancer. Mol Oncol. 2021;16(7):1572–90.

  34. Wang HL, Chen FQ, Wu LJ. Ephedrine ameliorates chronic obstructive pulmonary disease (COPD) through restraining endoplasmic reticulum (ER) stress in vitro and in vivo. Int Immunopharmacol. 2022;103: 107842.

    Article  CAS  PubMed  Google Scholar 

  35. Tang F, Ling C. Curcumin ameliorates chronic obstructive pulmonary disease by modulating autophagy and endoplasmic reticulum stress through regulation of SIRT1 in a rat model. J Int Med Res. 2019;47(10):4764–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Wang Y, Wu ZZ, Wang W. Inhibition of endoplasmic reticulum stress alleviates cigarette smoke-induced airway inflammation and emphysema. Oncotarget. 2017;8(44):77685–95.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Li X, Michaeloudes C, Zhang Y, Wiegman CH, Adcock IM, Lian Q, Mak JCW, Bhavsar PK, Chung KF. Mesenchymal stem cells alleviate oxidative stress-induced mitochondrial dysfunction in the airways. J Allergy Clin Immunol. 2018;141(5):1634–45.

  38. Naiel S, Tat V, Padwal M, Vierhout M, Mekhael O, Yousof T, Ayoub A, Abed S, Dvorkin-Gheva A, Ask K. Protein misfolding and endoplasmic reticulum stress in chronic lung disease: Will cell-specific targeting be the key to the cure? Chest. 2020;157(5):1207–20.

    Article  CAS  PubMed  Google Scholar 

  39. Stockley RA. Neutrophils and protease/antiprotease imbalance. Am J Respir Crit Care Med. 1999;160(5 Pt 2):S49-52.

    Article  CAS  PubMed  Google Scholar 

  40. Casalino-Matsuda SM, Monzon ME, Forteza RM. Epidermal growth factor receptor activation by epidermal growth factor mediates oxidant-induced goblet cell metaplasia in human airway epithelium. Am J Respir Cell Mol Biol. 2006;34(5):581–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Shaykhiev R, Zuo WL, Chao I, Fukui T, Witover B, Brekman A, Crystal RG. EGF shifts human airway basal cell fate toward a smoking-associated airway epithelial phenotype. Proc Natl Acad Sci U S A. 2013;110(29):12102–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Casalino-Matsuda SM, Monzon ME, Conner GE, Salathe M, Forteza RM. Role of hyaluronan and reactive oxygen species in tissue kallikrein-mediated epidermal growth factor receptor activation in human airways. J Biol Chem. 2004;279(20):21606–16.

    Article  CAS  PubMed  Google Scholar 

  43. Forteza R, Casalino-Matsuda SM, Monzon ME, Fries E, Rugg MS, Milner CM, Day AJ. TSG-6 potentiates the antitissue kallikrein activity of inter-alpha-inhibitor through bikunin release. Am J Respir Cell Mol Biol. 2007;36(1):20–31.

    Article  CAS  PubMed  Google Scholar 

  44. Zhang Y, Huang H, Ma Y, Sun Y, Wang G, Tang L. Association of the KLK1 rs5516 G allele and the ACE D allele with aortic aneurysm and atherosclerotic stenosis. Medicine (Baltimore). 2016;95(44): e5120.

    Article  CAS  Google Scholar 

  45. Zhang Y, Huang H, Ma Y, Sun Y, Wang G, Tang L. Analysis of KLK1 polymorphism (rs5516) in patients with abdominal aortic aneurysm or thoracic aortic dissection. J Cardiovasc Surg (Torino). 2018;59(2):293–6.

    Google Scholar 

  46. Liu K, Li QZ, Delgado-Vega AM, Abelson AK, Sanchez E, Kelly JA, Li L, Liu Y, Zhou J, Yan M, et al. Kallikrein genes are associated with lupus and glomerular basement membrane-specific antibody-induced nephritis in mice and humans. J Clin Invest. 2009;119(4):911–23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Jiang S, Hsu YH, Venners SA, Zhang Y, Xing H, Wang X, Xu X. Effects of protein coding polymorphisms in the kallikrein 1 gene on baseline blood pressure and antihypertensive response to irbesartan in Chinese hypertensive patients. J Hum Hypertens. 2011;25(5):327–33.

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank all the volunteers who participated in this study. We appreciate the linguistic assistance provided by TopEdit (www.topeditsci.com) during the preparation of this manuscript.

Funding

This study was supported by the Xinjiang Uygur Autonomous Natural Science Foundation of China under Grant (2017D01C016) and Tianshan Youth Project of Xinjiang Uyghur Autonomous Region (2019Q143).

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Authors and Affiliations

Authors

Contributions

LT and XZ drafted the work or revised it critically for important content; LT, XZ, MT, TM, JR, CX, AZ, AA and PA performed the experiments and collected data; LT, HG and SY analyzed the data; LT and HG prepared the figures and tables; LL conceived and designed the experiments. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Li Li.

Ethics declarations

Ethics approval and consent to participate

This study has been performed in compliance with the Declaration of Helsinki. This study was approved by the Ethics Committee of the First People's Hospital of Kashi. Informed consent was obtained from patients or their family members.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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Supplementary Information

Additional file 1

. The uncropped image details of the location of SNV rs5516.

Additional file 2

. The uncropped image details of the location of SNV rs11960.

Additional file 3

. The uncropped image details of the location of SNV rs15783.

Additional file 4

. The uncropped image details of the location of SNV rs1800517.

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Tang, L., Zhong, X., Gong, H. et al. Analysis of the association of ANO3/MUC15, COL4A4, RRBP1, and KLK1 polymorphisms with COPD susceptibility in the Kashi population. BMC Pulm Med 22, 178 (2022). https://doi.org/10.1186/s12890-022-01975-3

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