
==== Front
World Allergy Organ J
World Allergy Organ J
The World Allergy Organization Journal
1939-4551
World Allergy Organization

S1939-4551(24)00091-7
10.1016/j.waojou.2024.100960
100960
Full Length Article
Mendelian randomization study of childhood asthma and chronic obstructive pulmonary disease in European and East Asian population☆
Fan Guo Zhen PhD a
Chen Ke Yang MD b
Liu Xiao Meng MD c
Qu Zheng Hai MD quzhenghai@163.com
a⁎
a Department of Pediatrics, The Affiliated Hospital of Qingdao University, Qingdao, China
b First Clinical Medical College of Anhui Medical University, Hefei, China
c Department of Hospital Infection Management, The Affiliated Hospital of Qingdao University, Qingdao, China
⁎ Corresponding author. quzhenghai@163.com
24 8 2024
9 2024
24 8 2024
17 9 10096025 4 2024
30 7 2024
6 8 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Objective

The present study aimed to explore the potential causal relationship between childhood asthma and chronic obstructive pulmonary disease (COPD) in European and East Asian populations with Mendelian randomization (MR) analysis.

Methods

Based on summary data from genome-wide association studies, single nucleotide polymorphisms (SNPs) associated with childhood asthma were used as instrumental variables. The MR analysis employed the inverse variance weighting, MR-Egger regression and weighted median method to estimate the causal effect between childhood asthma and COPD in European and East Asian populations. Cochran's Q test, MR-PRESSO method and MR-Egger intercept were used to detect heterogeneity, outliers and horizontal pleiotropy, respectively. Leave-one-out analysis applied to assess the effect of removing individual SNP on the estimate of causal association.

Results

The MR analysis showed no genetic causal relationship between childhood asthma and COPD. The results of Cochran's Q test, MR-PRESSO and MR-Egger regression indicated the absence of heterogeneity, outliers and horizontal pleiotropy, respectively. Leave-one-out analysis showed no significant difference in the statistical results after exclusion of single SNPs.

Conclusions

The MR analysis revealed that there is no causal relationship between childhood asthma and COPD at the genetic level in both European and East Asian populations. Additionally, due to the presence of shared confounding factors and pathogenic genes, further research is needed to comprehensively assess the relationship between childhood asthma and COPD.

Keywords

Childhood asthma
Chronic obstructive pulmonary disease
East Asian population
European population
Mendelian randomization
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pmcIntroduction

Asthma serves as a common respiratory disease in childhood and exhibits a range of typical symptoms, including cough, recurrent wheezing, chest distress and shortness of breath.1,2 Based on the research data from global burden of disease, approximately 22 million children had asthma, and 12.9 thousand children died from the disease in 2019.3 Among them, the age-standardized incidence rates of asthma among children aged 1–4, 5–9, 10–14, and 15–19 years were 44.2%, 28.4%, 16.7%, and 10.7%, respectively; the mortality rates were 47.4%, 13.2%, 16.4%, and 23%, respectively. This indicates that the incidence and mortality rates are higher among children aged 1–4, which may be related to a higher likelihood of genetic defects in this age group. Although inhaled corticosteroids could help to relieve asthma symptoms, serious complications and rapid lung function decline may occur among certain children with persistent asthma.3,4

Chronic obstructive pulmonary disease (COPD), characterized by incompletely reversible airflow limitation, is a heterogeneous disorder triggered by small airway disease and parenchymal destruction.5 According to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) definition, chronic obstructive pulmonary disease (COPD) can be classified into 4 groups: A (low symptoms, low risk), B (high symptoms, low risk), C (low symptoms, high risk), and D (high symptoms, high risk).5 In 2017, approximately 544.9 million people worldwide suffered from chronic respiratory diseases; among them, COPD accounted for about 55% with a rise of 6% since 1990.6 According to the prediction, COPD will develop into the third principal reason for dying worldwide by 2030.7 The main risk factors for COPD are genetics and inhalation exposure, but host traits like atopy and bronchial hyperresponsiveness could impair lung growth in childhood, thereby increasing susceptibility to COPD in adulthood.5,8 In the early 1960s, Orie et al9 put forward the Dutch Hypothesis: asthma, chronic bronchitis, and emphysema should be considered as distinct manifestations of the same disease, with both host and environmental factors play major roles in this process. A retrospective study from Japan enrolling 300 COPD patients and 400 controls indicated that the prevalence of childhood asthma in the COPD patients was 6.3%, higher than that in the control group (2.4%).10 In Aberdeen, Tagiyeva et al11 followed-up 330 schoolchildren for a 50-year period, and found that childhood asthma increased the risk of developing COPD (odds ratio = 6.37). However, a prospective study from Melbourne, Tai et al12 recruited 346 asthmatic children from age 6 to 7 followed until 50 and discovered that 15 of 34 children with severe asthma had COPD at age 50, 4 of 66 children with intermittent asthma had COPD at age 50; moreover, intermittent asthmatic children had no increased hazard for developing COPD by multivariate analysis. The causal relationship between childhood asthma and COPD is still unclear so far.

Mendelian randomization (MR) analysis, widely used to causal inference in epidemiology, utilizes genetic variation as an instrumental variable to establish a model and text the causation between exposure factors and diseases.13, 14, 15 MR analysis is viewed as less likely to be affected by environmental confounding factors when compared with observational studies, due to its application of genetic information as the random source of exposure variation.13,16 Nevertheless, to our knowledge, the MR study on association with childhood asthma and COPD was barely reported. In this context, the present study aimed to explore the potential causal relationship between childhood asthma and COPD in European and East Asian population with MR analysis.

Methods

Study design

In the present study, single nucleotide polymorphisms (SNPs) associated with childhood asthma were used as instrumental variables to investigate the potential causal relationship between childhood asthma and COPD. MR analysis must satisfy the following three core hypotheses:14 (1) genetic variation served as strongly associated with exposure (childhood asthma); (2) genetic variation was not related to confounders; (3) genetic variation affected the outcome (COPD) only through exposure (childhood asthma) (Fig. 1). We utilized data from published genome-wide association studies (GWAS) to perform the MR analysis. As each study received institutional approval from the respective ethical review board, no further ethical approval was required.Fig. 1 Mendelian randomization model of childhood asthma and COPD

Fig. 1

Instrumental variables selection

In this study, the GWAS summary data stemmed out of the Integrative Epidemiology Unit (IEU) GWAS database (https://gwas.mrcieu.ac.uk/) and the GWAS catalog website (https://www.ebi.ac.uk/gwas/).

GWAS data for childhood asthma in European population (GWAS ID: ebi-a-GCST007800) were acquired through the IEU GWAS database, including 13,962 cases and 300,671 non-cases (Table 1). Single nucleotide polymorphisms (SNPs) with genome-wide significance (P < 5 × 10−8) had been screened from GAWS data; in order to avoid the linkage disequilibrium (LD) affecting the analysis results, the r2 threshold was set as 0.001 and the distance was set as 10000 kb; via the website PhenoScanner (http://www.phenoscanner.medschl.cam.ac.uk/) to exclude SNPs associated with other phenotypes. In addition, the F statistic served as calculated to evaluate whether the selected instrumental variables had weak instrumental variable bias.17 The calculation formula is as follows: F = R2(N − K − 1)/K(1 − R2); among them, “N” represents the sample size of the exposure database, “K” refers to the number of SNPs, and “R2” denotes the proportion of genetic variation explained by SNPs in the exposure database. The formula for calculating R2 is as follows: R2 = 2 × EAF × (1 − EAF) × β2; among them, EAF denotes effect allele frequency, and β2 represents the effect size of the allele. F statistic greater than 10 suggest a low probability of bias resulting from weak instrumental variables.17Table 1 GWAS data information in MR analysis

Table 1Disease	GWAS ID	Population	Samples size (case/control)	Sources	Years	
Childhood asthma	ebi-a-GCST007800	European	314,633 (13,962/300,671)	IEU GWAS database	2019	
Childhood asthma	GCST90018675	East Asian	162,350 (547/161,803)	GWAS catalog website	2021	
COPD	finn-b-J10_COPD	European	193,638 (6915/186,723)	IEU GWAS database	2021	
COPD	bbj-a-103	East Asian	204,907 (3315/201,592)	IEU GWAS database	2019	

GWAS data for childhood asthma in East Asian population (GWAS ID: GCST90018675) stemmed from the GWAS catalog website, including 547 cases and 161,803 non-cases (Table 1). In general, SNPs with a P-value less than 5 × 10−8 serve as considered to be genome-wide significant. However, since none of the SNPs in this data met the condition, a lower threshold with a P-value less than 5 × 10−6 was chosen for analysis.18 The remaining screening criteria were the same as described above.

Data sources of COPD

GWAS data for COPD in European population (GWAS ID: finn-b-J10_COPD) came from the IEU GWAS database, including 6915 cases and 186,723 non-cases (Table 1). GWAS data for COPD in East Asian population (GWAS ID: bbj-a-103) were acquired through the IEU GWAS database, including 3315 cases and 201,592 non-cases (Table 1).

MR and statistical analysis

Two-sample MR analysis. Two-sample MR analysis was performed using R software (version 4.3.0) and the “TwoSampleMR” package (version 0.5.6). This MR analysis mainly employed the inverse variance weighting (IVW) method to estimate the causal effect between childhood asthma and COPD. In addition, the MR-Egger regression and the weighted median (WM) method had been used to supplement the IVW results. The IVW method serves as widely considered the gold standard for MR analysis:19,20 it estimates the causal effect of each tool SNP with the Wald ratio method, followed by a weighted summary analysis; the IVW method could provide unbiased effect estimates if there is no horizontal pleiotropy. Unlike the IVW method, MR-Egger could estimate mean instrumental variable pleiotropy through intercept magnitude, but the results tend to be of low precision.21 When the proportion of invalid instrumental variables reaches 50%, the WM method continues to provide estimates of the causal effect.22

Heterogeneity. Cochran's Q statistic is calculated by IVW and MR-Egger regression, and P > 0.05 represents no significant heterogeneity.23 In case of heterogeneity among instrumental variables, the analysis results will be based on the random effects IVW model; whereas IVW model with fixed effects will be employed if heterogeneity serve as absent.24

Pleiotropy analysis. The MR-PRESSO method tested potential pleiotropy and excluded outliers.22 The intercept term in MR-Egger regression is used to examine horizontal pleiotropic bias of included SNPs: if the intercept has close to zero, it indicates the absence of horizontal pleiotropy in the instrumental variables.25

Sensitivity analysis. Leave-one-out analysis can be employed to assess the effect of removing individual SNP on the estimate of causal association, and P > 0.05 after excluding a SNP indicates that the SNP has no significant impact on the results.15

Statistical analysis. The MR results were expressed as odds ratio (OR) and 95% confidence interval (CI), and a significance level of α = 0.05 (two-sided).

Results

Childhood asthma and COPD in European population

After excluding 59 SNPs related to confounding factors (such as eosinophil count and lymphocyte count), 41 SNPs associated with childhood asthma in European population (P < 5 × 10−8, LD r2 < 0.001) were finally included as instrumental variables. The F statistic calculated for a single SNP ranged from 7864.54 to 442078.96 (F > 10), and indicated that this study was unlikely to be affected by weak instrumental variables bias. Details of the 59 SNPs and 41 SNPs are shown in Supplementary Table 1 and Supplementary Table 2, respectively.

Based on the IVW results from fixed effects model (OR = 1.00, 95% CI: 0.99–1.01, P = 0.57), no significant causal association was found between childhood asthma and COPD in European population. In addition, the MR-Egger (OR = 1.03, 95% CI: 0.95–1.12, P = 0.46) and WM (OR = 1.00, 95% CI: 0.99–1.01, P = 0.95) method also showed no genetic causal relationship between childhood asthma and COPD (Table 2, Fig. 2A). The results of Cochran's Q, MR-PRESSO and MR-Egger text are displayed in Table 3. There was no significant heterogeneity among SNPs according to the finds of Cochran's Q test (MR-Egger, P = 0.17; IVW, P = 0.17). Therefore, this study mainly used the fixed effects IVW model for causal inference. The MR-PRESSO test also did not identify any pleiotropy or outliers (P = 0.18). No significant horizontal pleiotropy was found in this MR analysis on the basis of MR-Egger results (intercept = −0.03, P = 0.42). The leave-one-out analysis indicated that no single SNP had a significant effect on the robustness of the results (Fig. 3A). The forest plots and funnel plots on childhood asthma and COPD in European population are demonstrated in Supplementary Figs. 1A and 2A.Table 2 Mendelian randomization (MR) results between childhood asthma and COPD

Table 2Population	IVW	MR-Egger	WM	
OR (95% CI)	P	OR (95% CI)	P	OR (95% CI)	P	
European	1.00 (0.99, 1.01)	0.57	1.03 (0.95, 1.12)	0.46	1.00 (0.99, 1.01)	0.95	
East Asian	1.05 (0.97, 1.15)	0.25	1.18 (0.74, 1.88)	0.56	1.05 (0.95, 1.15)	0.36	

Fig. 2 Scatter plots of the association between childhood asthma and COPD. (A) Childhood asthma and COPD in European population; (B) Childhood asthma and COPD in East Asian population

Fig. 2

Table 3 The result of Cochran's Q, MR-PRESSO and MR-Egger text

Table 3Population	Cochran's Q	MR-PRESSO	MR-Egger	
MR-Egger (Q statistic, P)	IVW (Q statistic, P)	RSSobs	P	intercept	P	
European	(47.43, 0.17)	(48.23, 0.17)	50.51	0.18	−0.03	0.42	
East Asian	(1.03, 0.60)	(1.28, 0.73)	2.32	0.76	−0.04	0.67	

Fig. 3 Leave-one-out plots of childhood asthma and COPD. (A) Childhood asthma and COPD in European population; (B) Childhood asthma and COPD in East Asian population

Fig. 3

Childhood asthma and COPD in East Asian population

Upon exclusion of 1 SNP associated with confounding factors (eosinophil count), the study included the 4 SNPs (P < 5 × 10−6, LD r2 < 0.001) as instrumental variables for childhood asthma in East Asian population (Supplementary Table 1, Supplementary Table 3). The F-values for individual SNP ranged between 6831.32 and 8119.83, and suggested an absence of weak instrumental variables bias.

The fixed effects IVW model demonstrated no causal relationship between childhood asthma and COPD in East Asian population (OR = 1.05, 95% CI: 0.97–1.15, P = 0.25), which was consistent with the results of MR-Egger (OR = 1.18, 95% CI: 0.74–1.88, P = 0.56) and WM (OR = 1.05, 95% CI: 0.95, 1.15, P = 0.36) (Table 2, Fig. 2B). There was no significant heterogeneity observed among the instrumental variables as demonstrated by the Cochran's Q test (MR-Egger, P = 0.60; IVW, P = 0.73); neither MR-Egger regression (intercept = −0.04, P = 0.67) nor MR-PRESSO (P = 0.76) revealed significant horizontal pleiotropy (Table 3). Leave-one-out analysis showed no significant difference in the statistical results after exclusion of SNP one by one (Fig. 3B). The forest plots and funnel plots on childhood asthma and COPD in East Asian population are presented in Supplementary Figs. 1B and 2B.

Discussion

This study employed MR analysis to investigate the association between childhood asthma and COPD in European and East Asian population. We utilized three different analytical approaches (IVW, MR-Egger and WM) for MR analysis, and the results consistently showed no significant causal relationship between childhood asthma and COPD. All the instrumental variables were screened by PhenoScanner database to exclude confounding factors, and their F statistics were greater than 10. No significant heterogeneity or pleiotropy was found among the instrumental variables. In addition, a single SNP did not affect the robustness of the results through leave-one-out sensitivity analysis. As such, the outcomes of this MR analysis exhibit a high degree of reliability.

In recent years, there has been a progressively escalating interest in COPD, particularly in its relationship with childhood asthma. Several previous studies have reported a close association between childhood asthma and COPD. A retrospective study from New Zealand found that among COPD patients defined by GOLD criteria, 19% of them had a history of childhood asthma; in multivariate regression analysis, childhood asthma was the strongest risk factor for COPD (OR = 5.2).26 In another retrospective study recruited 10,199 non-Hispanic whites or African Americans with a history of smoking, Hayden et al27 indicated that compared to the control group, individuals with a history of childhood asthma exhibited significant reductions in lung function indicators, including FEV1, FVC, and FEV1/FVC; additionally, they had a 3.42-fold increased risk of developing COPD. Based on the data from 11 articles encompassing 48,657 individuals, a meta-analysis by Ali et al28 showed that children with asthma had 3.0 times higher likelihood of developing COPD in adulthood compared to children without asthma; moreover, the association between childhood asthma and adult COPD was greater in studies with random sampling than in studies with continuous sampling. Lung function is an important indicator for assessing the risk of developing COPD in children with asthma as adults. Follow-up studies on the lung function of children with asthma have shown that childhood asthma can affect lung function development, leading to reduced FEV1 in early adulthood and increasing the risk of COPD later in life.11,29 Additionally, the Childhood Asthma Management Program (CAMP) cohort study tracked lung function changes in 684 children aged 5 to 12 with mild-to-moderate persistent asthma until they were around 30 years old.30 It found that persistent asthma in childhood and the resulting reduction in FEV1 can increase the risk of irreversible airway obstruction and even COPD in adulthood. However, it is worth noting that many previous studies have predominantly based on observational epidemiology, which is prone to influence by sample restrictions and confounding factors, leading to false causal associations and making it impossible to determine the causal relationship between the two. In order to address this limitation, the present study employed MR analysis to investigate the causal relationship between childhood asthma and COPD. Our findings indicated no genetic causal relationship between childhood asthma and COPD, suggesting that the clinically observed associations may be attributed to similar underlying mechanisms of pathogenesis.

Previous research has found that asthma and COPD may share common pathological mechanisms. Both asthma and COPD involve varying degrees of airway epithelial damage. Whether it is allergens or cigarette smoke, they both primarily enter the body through the airways. Research has shown that allergens, interleukin (IL)-13, or IL-33 regulates the release of IL-25 from airway epithelial cells by inhibiting mechanistic target of rapamycin (MTOR) and inducing autophagy, leading to airway epithelial cell damage and TH2 inflammatory response in asthma.31 In the airway epithelial cells from COPD patients and the lungs of mice induced by cigarette smoke, the expression of MTOR decreased significantly; MTOR may inhibit cigarette smoke-induced inflammation and emphysema by regulating autophagy, apoptosis and necroptosis.32 Furthermore, Lai et al33 have studied data from COPD patients and cigarette smoke-induced mice models and found that smoke exposure governed IL-17A production in airway epithelial cells via histone deacetylase (HDAC) 2, subsequently influencing airway inflammation and remodeling in COPD. In the case of asthma, allergens or house dust mite can also induce airway epithelial damage through the HDAC2-IL17A pathway, thereby regulating airway inflammation.34 In recent years, the role of eosinophils in the pathogenesis of asthma and COPD has attracted significant attention. Studies have shown that compared to healthy controls, asthma patients have a significantly increased density of eosinophils in the airway walls; furthermore, the increase in eosinophils is closely associated with airway hyperreactivity and airway inflammation in asthma.35 Kolsum et al36 compared the clinical data of COPD patients with high blood eosinophils (≥250/μL) and low blood eosinophils (<150/μL), and found that the former had higher eosinophil counts in sputum, bronchoalveolar lavage fluid and bronchial submucosa, which indicated that eosinophils were related to airway inflammation. In addition, with the advancement of genetic research technology, some common candidate genes related to asthma and COPD have been identified through candidate gene analysis, including ADAM 33, GSTM 1, GSTP1, IL 13, TGFb, and TNF.37 Although our study did not identify a causal relationship between childhood asthma and COPD, there was an association observed in previous clinical observations between the two conditions, which could potentially be attributed to shared pathogenic mechanisms and pathogenic genes.

This study has several strengths. To our knowledge, MR studies on the causal relationship between childhood asthma and COPD were seldom reported. MR studies can mitigate the interference of confounding factors and reverse causality. Additionally, this study integrates GWAS data from European and East Asian population, allowing for a more precise assessment of the causal relationship across different ethnicities. However, this study also has certain limitations. Firstly, the GWAS data in the study were aggregated results, lacking individual data, and cannot be stratified by gender, age smoking history, atopy status, disease duration, FEV1 level, reversibility level, FEV1/FVC ratio and other factors. Secondly, the sample size in the databases used for this study was relatively modest in comparison to the broader human population. Lastly, genetic-level investigations could be susceptible to the influence of ethnicity, and further research is needed to validate the extrapolation of the results.

Conclusions

The MR analysis revealed that there is no causal relationship between childhood asthma and COPD at the genetic level in both European and East Asian populations. Additionally, due to the presence of shared confounding factors and pathogenic genes, further research is needed to comprehensively assess the relationship between childhood asthma and COPD.

Abbreviations

COPD, Chronic obstructive pulmonary disease; GWAS, genome-wide association studies; IEU, Integrative Epidemiology Unit; IVW, inverse variance weighting; LD, linkage disequilibrium; MR, Mendelian randomization; MTOR, mechanistic target of rapamycin; SNPs, single nucleotide polymorphisms; WM, weighted median.

Declaration of competing interest

None.

Appendix A Supplementary data

The following is the Supplementary data to this article:Multimedia component 1

Multimedia component 1

☆ Full list of author information is available at the end of the article

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.waojou.2024.100960.
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