Gastroesophageal reflux disease and idiopathic pulmonary fibrosis risk: A mendelian randomization study

Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with unknown etiology and treatment options for it were limited. Whether Gastroesophageal reflux disease (GERD) could affect the occurrence of IPF remains unclear.

Methods: Using available data from FINNGEN and IEU OpenGWAS, we performed Two-sample mendelian randomization (MR) to explore the causal relationship between GERD and IPF.

Results: Using 65 GERD-related SNPs, we found the association between GERD and the risk of IPF was not statistically significant with IVW approach (OR = 1.20, 95% CI = 0.84-1.70, p = .32), MR-Egger regression (OR = 1.65, 95% CI = 0.19-14.43, p = .65) and weighted median approaches (OR = 1.44, 95% CI = 0.94-2.23, p = .09). However, heterogeneity was observed with MR-Egger (p = .001) and IVW (p = .001) analysis. Similar results were obtained with MR-PRESSO (global heterogeneity test p value <.01). After removing one outlier (rs9636202), with weighted median method, we found GERD increased the risk of IPF (OR 1.55, 95% CI: 1.01-2.36, p = .045) while not with the IVW (OR: 1.27, 95% CI: 0.91-1.78, p = .16) and MR-Egger method (OR: 2.01, 95% CI: 0.26-15.8, p = .51). Hence, we set a stricter instrument p value threshold to a level of <1 × 10⁻⁸, there was no statistical significance with MR estimates. Additionally, there was no directional pleiotropy observed (intercept = −0.01; SE = 0.036. p = .772). To validate causal effect of GERD on IPF, we identified three SNPs (rs79348626, rs12759463 and rs4269485) from another GWAS data that were significantly associated with GERD independently. The analysis showed no evidence of causality between GERD and IPF using the IVW method (OR = 0.91, 95% CI = 0.42-1.97, p = .814), MR-Egger regression (OR = 0.43, 95% CI = 0.06-3.07, p = .553) and weighted median approaches (OR = 0.90, 95% CI = 0.36-2.27, p = 0 0.819).

Conclusions: Our analysis using MR does not support GERD could significantly increase the incidence of IPF, which suggests that treating GERD cannot reduce the risk of developing IPF.

Keywords

idiopathic pulmonary fibrosis Mendelian randomization study gastroesophageal reflux disease

Introduction

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease with an unknown etiology and usually happens in elderly people. Its radiological and pathological features are consistent with usual interstitial pneumonia (UIP).¹ Generally, the patients present as dyspnea and gradual deterioration of lung function with acute exacerbation occurring during the course of disease. The prognosis of IPF is poor and median survival time was only 3.8 years since diagnosis in people over 65 years old.^1–3 Epithelial-Mesenchymal Transition (EMT) plays an important role during dysfunctional epithelial regeneration and may be major pathogenic driver in IPF.^4,5 Besides, a mendelian randomization study showed that high level of IL-14 had a causal relationship with the increased risk of IPF.⁶ In addition, the treatments for IPF were limited, up to now only two drugs, pirfenidone and nintedanib, have evidence-based medical support that they can slow down the rate of decay of lung function but cannot improve the mortality of IPF.^7,8 Therefore, explore potential risk of IPF is important, which could possibly improve the prognosis of this tricky disease.

Gastroesophageal reflux disease (GERD) is a prevalent condition especially in European and North American populations. Bretagne et al⁹ reported that about 31.3% French used to have typical symptoms of GERD. The prevalence of GERD in the U.S population is estimated to range from 18.1% to 27.8%.¹⁰ Asian people also have high morbidity of GERD, Fujiwara et al¹¹ showed that about 17.9% Japanese had GERD. In IPF patients, there has been reported to have higher morbidity of GERD. Mays et al¹² found 44% IPF patients were diagnosed with GERD, while age matching group was only 19%. Therefore, we speculated there were correlation between GERD and IPF, persistent existing of GERD could contribute to the occurrence of IPF. In vivo studies, Chen et al¹³ found that in GERD rat models expression level of TGF-β1, Type I collagen and connective tissue growth factor were up-regulated in lung tissues and the rats usually had more severe fibrosis extent. Kouki et al¹⁴ revealed that dogs afflicted with IPF exhibited elevated levels of total bile acid in both saliva and bronchoalveolar lavage fluid, surpassing those observed in their healthy counterparts. Hence, micro-aspiration may potentially exert a pivotal role in the occurrence and progression of GERD, while mitigating micro-aspiration could potentially attenuate the incidence rate and development of IPF, so the correlation between GERD and IPF has confirmed, but the causal relationship between need further explored¹⁵

Exploring etiology of a disease is usually associated with its prognosis. The key treatment of GERD is to block-up micro-aspiration, which includes lifestyle modifications, intervention with anti-acid drugs (AAT) and laparoscopic anti-reflux surgery. There were several studies focusing on whether AAT or laparoscopic anti-reflux surgery could slow down progress and improve the prognosis of IPF, but the results were controversial. Retrospective studies¹⁶ and a meta-analysis¹⁷ both revealed that treatment of GERD can improve prognosis in patients with IPF. However, the study of Kreuter et al¹⁸ suggested that use of AAT in patients with IPF could not improve prognosis and in the contrary increased the risk of severe infection. Raghu et al¹⁹ revealed that laparoscopic anti-reflux surgery could not decrease mortality in IPF patients. However, in observational studies, research results are often interfered by various confounding factors so as to make etiological explanations unreliable. Therefore, the exploration of the relationship between disease risk and outcome necessitates the implementation of novel methodological studies.

Mendelian randomization (MR) was first described by Katan,²⁰ The underlying principle of this concept is that distinct genotypes give rise to diverse phenotypes (Figure 1).²¹ By simulating the impact of exposure characteristics on a disease, the association between genotype and disease can be elucidated. The estimated effect between genotype and disease remains untainted by confounding factors that could potentially induce reverse causal associations, as alleles adhere to the principle of random allocation during gamete formation. Therefore, this method has an incomparable advantage over observational studies in causal inference.

Figure 1.

Mendelian randomization design, adopted from Jareebi (2024).²¹

We conducted this study to investigate the impact of GERD on the risk of developing IPF in a MR design. By utilizing genetic variants associated with GERD as instrumental variables, we aimed to clarify if there is potential causal relationship between GERD and the development of IPF, ultimately providing novel insights into this hypothesis.

Methods

GWAS summary data collection and IVs selection

Mendelian randomization (MR) analysis with R software (version 4.2.2) and the TwoSampleMR package was applied in our original research. It encompassed collecting genetic data for the exposures and their corresponding outcomes. To ensure compatibility, we performed data harmonization to align alleles across two distinct datasets to facilitate MR analysis. We conducted MR analyses from both the IEU OpenGWAS and FINNGEN datasets. A significance threshold of p < .05 was applied, with a primary emphasis on employing the inverse variance weighted (IVW) method, weighted median approach, and MR-Egger methods. Additionally, we employed MR-PRESSO and leave-one-out analysis to identify and address any potential bias caused by horizontal pleiotropy or a single SNP.

We searched for relevant genome-wide association studies (GWAS) data on FINNGEN (https://www.finngen.fi/en)²² and IEU OpenGWAS (https://gwas.mrcieu.ac.uk/),^23–25 selecting genetic variants significantly associated with GERD as instrumental variables (IVs) in our MR design (see Figure 2). Two representative GERD-related GWASs were included in our study. The first GWAS was downloaded from IEU OpenGWAS(ebi-a-GCST90000514) as test set, and the second was extracted from FINNGEN (K11_REFLUX) as validation set. The IVs identified in the test set are referred to as IV-1, while those identified in the validation set are referred to as IV-2 (Table 1).

Figure 2.

Workflow of Mendelian randomization study revealing causality from GERD on IPF.

Table 1.

Association of the instrumental SNPs with GRED and IPF among IV1 and IV2.

SNP	Effect alleles	Other alleles	Beta	SE	p Value	IV
rs10010963	T	C	−0.0269803	0.00494665	4.92E-08	IV1
rs1011407	G	A	−0.0420618	0.00735917	1.09E-08	IV1
rs10133111	A	G	0.0417875	0.00650789	1.35E-10	IV1
rs1021363	G	A	−0.031217	0.00502204	5.10E-10	IV1
rs11762636	A	C	−0.0514827	0.00625598	1.88E-16	IV1
rs11953061	T	C	0.0281599	0.00508694	3.10E-08	IV1
rs12204714	T	C	−0.028817	0.00499422	7.92E-09	IV1
rs12357321	A	G	0.0317159	0.00523077	1.33E-09	IV1
rs12453010	T	C	0.0296967	0.00493315	1.75E-09	IV1
rs12967855	G	A	−0.0365451	0.00513354	1.09E-12	IV1
rs12997558	A	G	0.0278184	0.00502214	3.04E-08	IV1
rs13107325	T	C	0.0701443	0.00918312	2.20E-14	IV1
rs1334297	A	G	−0.0387984	0.00545512	1.14E-12	IV1
rs13409451	G	A	−0.0277081	0.00493183	1.93E-08	IV1
rs1431196	G	A	0.0324197	0.00486448	2.65E-11	IV1
rs1479405	T	C	0.0314843	0.0051514	9.85E-10	IV1
rs1510719	C	T	−0.0388844	0.00494701	3.84E-15	IV1
rs1596747	G	A	0.0310869	0.00480742	1.00E-10	IV1
rs1716171	T	C	0.0383981	0.00590382	7.83E-11	IV1
rs1883842	G	T	0.0308332	0.00536826	9.27E-09	IV1
rs1937450	G	T	0.0315845	0.00484484	7.07E-11	IV1
rs2023878	T	C	−0.0362846	0.00611913	3.04E-09	IV1
rs2043539	A	G	0.0272058	0.00486485	2.24E-08	IV1
rs215614	A	G	−0.0328541	0.00497715	4.08E-11	IV1
rs2164300	T	C	−0.0264751	0.00482677	4.13E-08	IV1
rs2240326	A	G	−0.0471681	0.00481335	1.13E-22	IV1
rs2396133	G	A	0.0293547	0.00481787	1.11E-09	IV1
rs2396766	A	G	0.0322057	0.00481878	2.34E-11	IV1
rs2734839	T	C	−0.0283478	0.00492778	8.79E-09	IV1
rs2744961	T	C	0.0292007	0.00501549	5.81E-09	IV1
rs2782641	A	G	0.0270882	0.00494583	4.33E-08	IV1
rs2815749	G	A	0.0388767	0.0060216	1.07E-10	IV1
rs2834005	C	T	0.0296997	0.0051734	9.42E-09	IV1
rs324769	T	C	−0.0267699	0.00483328	3.05E-08	IV1
rs329122	A	G	−0.0289529	0.00488358	3.05E-09	IV1
rs3766823	A	G	0.0393599	0.00638545	7.09E-10	IV1
rs3793577	G	A	0.0270309	0.00484976	2.49E-08	IV1
rs3828917	T	G	0.0671113	0.0120054	2.27E-08	IV1
rs3863241	T	C	0.0324982	0.00481521	1.49E-11	IV1
rs4300861	T	C	0.0307132	0.00494886	5.43E-10	IV1
rs4382592	G	T	−0.0302679	0.00525091	8.20E-09	IV1
rs4713692	T	C	−0.0276128	0.00498634	3.07E-08	IV1
rs569356	G	A	−0.037919	0.00690971	4.07E-08	IV1
rs6711584	A	G	0.0322545	0.00483974	2.66E-11	IV1
rs6722661	A	G	−0.0322543	0.00500354	1.15E-10	IV1
rs7032155	A	C	0.02775	0.00491358	1.63E-08	IV1
rs7241572	A	G	0.0365511	0.00597464	9.49E-10	IV1
rs7527682	G	A	−0.026684	0.00482174	3.13E-08	IV1
rs7541875	G	A	0.0273972	0.00484976	1.61E-08	IV1
rs7600261	T	C	0.0338034	0.00522051	9.47E-11	IV1
rs7612999	A	G	0.0305231	0.00559546	4.90E-08	IV1
rs761777	G	A	0.0345341	0.00554469	4.71E-10	IV1
rs7675588	A	C	−0.0335228	0.00595438	1.80E-08	IV1
rs7685686	G	A	−0.0279222	0.00489191	1.14E-08	IV1
rs773109	A	G	−0.0380572	0.00510213	8.71E-14	IV1
rs7942368	T	C	−0.0339683	0.00591917	9.54E-09	IV1
rs903678	A	G	0.0277378	0.00508463	4.89E-08	IV1
rs9372625	A	G	−0.037727	0.0049537	2.62E-14	IV1
rs9373363	G	A	−0.0326836	0.00555966	4.13E-09	IV1
rs9396740	A	G	−0.031493	0.0055587	1.47E-08	IV1
rs942065	A	G	0.0307384	0.00500925	8.45E-10	IV1
rs9529055	A	G	0.0266604	0.00481637	3.11E-08	IV1
rs9615905	T	C	0.0275657	0.0048378	1.21E-08	IV1
rs9636202	A	G	−0.035044	0.00547191	1.51E-10	IV1
rs9940128	A	G	0.0332513	0.00486305	8.06E-12	IV1
rs12759463	G	A	−0.0498746	0.00977648	3.369926e-07	IV2
rs4269485	G	A	−0.0511240	0.00982180	1.938338e-07	IV2
rs79348626	A	G	0.1823770	0.03547430	2.731315e-07	IV2

Statistical Analyses

The IPF GWAS summary data was extracted from FINNGEN(IPF), which are publicly available, include over 20 million SNPs from 1812 IPF cases and 338784 controls. Our study analyzed 129,080 GERD cases and 473,524 controls and results showed that there were 65 single-nucleotide polymorphisms (SNPs) significantly associated with GERD (p < 5 × 10⁻⁸; linkage disequilibrium [LD] r² < 0.001). Details of the 65 SNPs can be found in (Table 1). The average F-statistics was 38.92, which supported our instruments’ ability to accurately predict IPF (Table 2).

Table 2.

Summary of the causal effects of each trait on IPF via different MR methods.

	IV1		IV2
Number of SNPs	65		3
MR-Egger	OR (95%CI)	1.65 (0.19, 14.4)	0.43 (0.06 3.07)
	p value	0.65	0.55
Weighted median	OR (95%CI)	1.45 (0.94, 2.23)	0.90 (0.36.2.27)
	p value	0.09	0.82
IVW	OR (95%CI)	1.20 (0.84, 1.70)	0.91 (0.42, s1.97)
	p value	0.32	0,81
F		38.92	26.52

The validation set extracted from FINNGEN (K11_REFLUX), using data from 22867 GERD and 292,256 control cases. To increase the number of SNPs associated with GERD, we used a more lenient threshold (p < 5 × 10⁻⁷) and evaluated LD (r² < 0.001). This resulted in the identification of three SNPs (rs79348626, rs12759463 and rs4269485). The average F-statistics was 26.52 (Table 1-2).

Two-sample MR

After standardizing the effect alleles in the IVs and FINNGEN(IPF), we used IVW, weighted median and MR-Egger to calculate MR estimates. If these approaches yielded inconsistent results, we would set a stricter instrument p value threshold.²⁶ We used the IVW approach to detect heterogeneity (Cochran Q-derived p < .05) and checked for directional pleiotropy using the MR-Egger regression intercept (p < .05 indicated its presence).²⁷ In addition, we utilized MR-PRESSO and leave-one-out analysis to detect and correct for horizontal pleiotropy or any potential bias caused by a single SNP.^28,29 These analyses were conducted in R (version 4.2.2).

Outcomes

The findings are concisely summarized and visually presented (Figure 3).

Figure 3.

Odds ratio plot for causal effect of GERD on IPF.

Causal effect from GERD to IPF

Using 65 GERD-related SNPs, we found the potential causal effect of GERD on the risk of IPF was not statistically significant from the IVW approach (OR = 1.20, 95% CI = 0.84-1.70, p = .32), MR-Egger regression (OR = 1.65, 95% CI = 0.19-14.43, p = .65) and weighted median approaches (OR = 1.44, 95% CI = 0.94-2.23, p = .09) (Figure 4). However, there was heterogeneity observed using MR-Egger regression (p value derived from Cochran Q-test = 0.001) and IVW methods (p = .001). A similar result was also obtained with MR-PRESSO (global heterogeneity test p value <.01). After removing one outlier (rs9636202), we re-applied MR methods to assess the relationship between GRED and IPF. With weighted median method, we found that GERD significantly increased the risk of IPF (OR 1.55, 95% CI: 1.01-2.36, p = .045). However, when using the IVW (OR: 1.27, 95% CI: 0.91-1.78, p = .16) and MR-Egger approach (OR: 2.01, 95% CI: 0.26-15.8, p = .51), opposing results were observed which showed inconsistency with our findings from the Weighted median method. To address this inconsistency, we tightened the instrument p value threshold to a more stringent level of <1 × 10⁻⁸ and used a set of only forty-two SNPs as instrumental tools. As a result, the MR estimates did not reach statistical significance using IVW (OR = 1.26, 95% CI = 0.84-1.87, p = .26), MR-Egger regression (OR = 0.63, 95% CI = 0.04-9.74, p = .74) and weighted median approaches (OR = 1.48, 95% CI = 0.90-2.45, p = .12), indicating that a genetically predicted increase in GERD was not significantly associated with IPF risk. Additionally, there was no directional pleiotropy observed (intercept = −0.01; SE = 0.036. p = .772). The leave-one-out analysis showed that no single SNP against the overall effect (Figure S1). Furthermore, the funnel plot indicating no pleiotropy (Figure S2).

Figure 4.

Scatter plots of the association of GERD and IPF.

Validation causal effect from GERD to IPF

We identified three SNPs (rs79348626, rs12759463 and 4269485) that were significantly associated with GERD independently. However, our analysis showed no evidence of causality between GERD and IPF using the IVW method (OR = 0.91, 95% CI = 0.42-1.97, p = .814), MR-Egger regression (OR = 0.43, 95% CI = 0.06-3.07, p = .553) and weighted median approaches (OR = 0.90, 95% CI = 0.36-2.27, p = 0 0.819) (Figure S3). There is no significant heterogeneity present via analysis with MR-Egger (p = .545) and IVW methods (p = .595).

Discussion

We used two-sample MR to evaluate the association between GERD and IPF. Overall, we did not find strong evidence to support that GERD increases IPF risk, which was opposite to previous studies.^30–32

Until now, the relationship between GERD and IPF has remained controversial.^15,33,34 Most published studies were retrospective, making it difficult to determine causality. Some diagnosed cases of GERD and undiagnosed subclinical GERD may potentially contribute to the development of IPF; however, it remains uncertain whether GERD can accurately predict the onset or prognosis of IPF. Moreover, previous observational studies were susceptible to confounding risk factors.^33,35 In our study, we established causality using MR methods and avoided bias through improved study design. The utilization of two sets of genetic instruments unveiled no causal association between GERD and IPF incidence, in line with recent high-quality investigations. Khor et al³⁶ indicated that the use of antacid medication or anti-reflux surgery did not improve prognosis in patients with IPF, even if they did not have confirmed diagnosis of GERD. Similarly, a study conducted by the Australia IPF Registry found no significant impact on longer-term outcomes from either antacid therapy or GERD symptoms.³⁷ In a study based on large populations, it showed that using PPIs did not lower the risk of death or hospitalization for patients with IPF.³⁸ These studies suggest that treating GERD may not be as helpful for IPF as previously thought and is only conditionally recommended in treatment guidelines.

Although our findings suggest that there is no direct link between GERD and IPF incidence, whether GERD contributes to the progression of IPF remains unknown. The presence of gastric contents in the lungs has been demonstrated in mouse studies to be associated with the development of pulmonary fibrosis. This intricate process involves a multitude of molecules that actively contribute to the progression of fibrosis, encompassing TGF-β, basic fibroblast growth factor, vascular endothelial growth factor, and connective tissue growth factor.^39,40 In IPF patients, several studies found that pepsin was exist in the bronchoalveolar lavage fluid (BALF). This could result in acute exacerbation of IPF.^41–44 Additionally, children with GERD had more pepsin compare to healthy controls in their tracheal fluid.^45,46 Furthermore, pepsin was not present in the tracheal fluid of children who did not have GERD or respiratory symptoms.⁴⁷

Our study possesses several notable strengths. Firstly, we were able to emulate randomized controlled trials within observational settings through the utilization of MR. MR studies effectively circumvent confounding bias as SNPs are randomly assigned at conception and offer a cost-effective approach. In comparison to other observational studies, MR holds the advantage of mitigating reverse causation. Using MR method. Besides, our findings suggest that AAT and laparoscopic anti-reflux surgery may not be necessary for IPF treatment. Instead, more attention should be given to exploring the pathogenesis of IPF in relation to GERD.

Meanwhile, there are also some limitations. The data used in all GWASs came from European populations, it remains to be seen whether our findings apply to other populations. Secondly, it is important to recognize the diversity among IPF patients, it is possible that GERD may be a causal factor for a specific type of IPF. More comprehensive studies including subgroups of IPF should be considered in the future. In addition, we have tested the MR assumptions using different methods, although the results were broadly consistent, there was inevitably some residual uncertainty. Besides, the calculation and justification of the sample size selected for this study were not done in this study. Finally, it should be noted that the SNP size of the validation data set was small in our study.

Conclusion

Findings of our MR study not support a causal effect between GERD and IPF, which highlight we need to search and control for other candidate risk factors of IPF.

Supplemental Material

Supplemental Material - Gastroesophageal reflux disease and idiopathic pulmonary fibrosis risk: A mendelian randomization study

Supplemental Material for Gastroesophageal reflux disease and idiopathic pulmonary fibrosis risk: A mendelian randomization study by Minjie Lin, Junjie Wang, Jie Wei, Yu Yao, Cheng Tang, Wenfang Jin, Weihong Yuan and Yanling Lv in European Journal of Inflammation.

Supplemental Material

Supplemental Material - Gastroesophageal reflux disease and idiopathic pulmonary fibrosis risk: A mendelian randomization study

Supplemental Material

Supplemental Material - Gastroesophageal reflux disease and idiopathic pulmonary fibrosis risk: A mendelian randomization study

Footnotes

Authors’ contribution

YLL, WHY and MJL contributed to the conception, methodology design, and writing of the manuscript. JW, YY, CT, JJW and WFJ took responsibilities for data abstraction and accuracy of data analysis. All authors are guarantors of this work.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was funded by National Natural Science Foundation of China, grant number 82203561.

ORCID iD

Minjie Lin

Data availability statement

All data generated or analyses in this study are included in this article. Further enquiries can be directed to the corresponding author.*

Supplemental Material

Supplemental material for this article is available online.

Abbreviations

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