To the Editor: Achalasia of cardia (AC) is a primary esophageal motility disorder characterized by impaired relaxation of the lower esophageal sphincter (LES) and irregular peristalsis of the esophageal body, with clinical symptoms including dysphagia, regurgitation, chest pain, and weight loss.1 It has been shown that inhibitory myenteric neurons in LES specimens from patients with AC are reduced or even absent, suggesting that AC may be a neurodegenerative disease of the esophageal myenteric plexus.1 Despite extensive research, the exact etiology of AC remains unclear. Commonly accepted potential etiopathogenesis models include genetic predisposition, viral infection, and autoimmune-related mechanisms.1 The relationship between AC and eosinophilic esophagitis (EoE), a immune-mediated esophageal motility abnormality characterized by endoscopic biopsies with ≥15 eosinophils per high-powered field after excluding other causes of esophageal eosinophilia, is an old but still inconclusive topic.2 Recent studies have revealed potential associations between AC and other allergic diseases.3,4 However, there is a lack of large-scale prospective studies and causal inference analyses to establish definitive evidence. Supplementary Figure 1, https://links.lww.com/CM9/C853 illustrates the overall design of this study. We aimed to investigate the associations between incident AC and three major allergic disorders, including asthma, allergic rhinitis (AR), and atopic dermatitis (AD), using population-based cohort data. Furthermore, we leveraged available summary-level genome-wide association study (GWAS) datasets to systematically examine the causal relationships between AC and EoE, as well as the three aforementioned allergic diseases through univariable Mendelian randomization (UVMR) and multivariable Mendelian randomization (MVMR) methods. In the observational study section, we utilized individual-level data from a large-scale UK Biobank (UKB) cohort, comprising over 500,000 middle-aged and elderly British participants recruited from 2006 to 2010. The UKB study was approved by the North West Multicenter Research Ethics Committee (No. 11/NW/0382), and all participants provided informed consent through electronic signature. This research was conducted under UK Biobank application No. 96511. We obtained summary-level GWAS data for AC from the FinnGen Consortium (https://r9.finngen.fi/. Accessed 21 Nov, 2023). Based on data from the discharge and cause of death registry, the phenotype of AC was determined by coordinating the ICD 8th, 9th, and 10th edition codes (ICD-10 codes: K22.0; or ICD-8/9 codes: 5300). Individuals with esophageal, stomach, and duodenal diseases were excluded from the control group. Covariates adjusted in GWAS analysis of FinnGen included sex, age, 10 genetic principal components, and genotyping batch. Details of GWAS data for allergy-related traits from multiple European cohorts can be found in Supplementary Methods and Supplementary Tables 1 and 2, https://links.lww.com/CM9/C853. All GWAS data used in the study were obtained from publicly available databases, and there were no issues requiring additional ethical approval or informed consent. In the participant selection process of UKB, we initially excluded participants who had been diagnosed with AC before the consent time (n = 112) and those with prevalent gastroesophageal reflux disease, gastrointestinal cancer, esophageal stricture, dyskinesia of the esophagus, or other esophagitis at the time of recruitment (n = 34,505). Additionally, participants of non-White or unknown ethnicity were also excluded (n = 52,499). All medical conditions mentioned in the exclusion criteria were determined based on self-reported disease history or International Classification of Diseases 10th revision (ICD-10) coded diagnosis, with the Field ID of 20002 and 41270, respectively. Ethnicity was self-reported through a touchscreen questionnaire in Field 21000. Ultimately, a total of 415,300 participants were included in the main analysis. Baseline characteristics were compared using Student’s t test or chi-square test as appropriate. Cox proportional hazards regression models were applied to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations between allergic diseases and incident AC, with sequential adjustments for potential confounders. For Mendelian randomization analyses, odds ratios (ORs) and 95% CIs were used to estimate causal effects. The inverse-variance weighted (IVW) method was applied as the primary approach, complemented by weighted median, MR-Egger regression, MR-robust adjusted profile score, maximum likelihood, and MR-pleiotropy residual sum and outlier (MR-PRESSO) analyses. Heterogeneity, horizontal pleiotropy and leave-one-out sensitivity analyses were performed to evaluate the robustness of the findings. All statistical tests were two-sided, and a P value <0.05 was considered statistically significant. Analyses were conducted using R software version 4.3.0 (R Core Team, Vienna, Austria) with the “survival”, “TwoSampleMR”, “mr.raps”, and “MendelianRandomization” packages. Baseline characteristics between participants with and without AC during the follow-up in the UKB cohort were summarized in Supplementary Table 3, https://links.lww.com/CM9/C853. Among the 415,300 participants included in the primary analysis, the average age was 56.61 ± 8.04 years, with 226,148 (54.45%) being females. At baseline, 48,132 (11.59%) participants had prevalent asthma, 23,330 (5.62%) participants had prevalent AR, and 10,932 (2.63%) participants had prevalent AD. During a median follow-up period of 13.64 years, 210 individuals were diagnosed with AC. Compared with those without an AC diagnosis during the follow-up, AC patients had a higher average age at recruitment (mean age: 58.54 years vs. 56.61 years; P <0.001). As shown in Figure 1A, none of asthma (HR, 1.28; 95% CI, 0.87–1.88; P = 0.214), AR (HR, 1.36; 95% CI, 0.82–2.26; P = 0.237), or AD (HR, 1.27; 95% CI, 0.60–2.69; P = 0.540) significantly affected the risk of incident AC in Model 1. The results remained consistent after adjusting for the other two exposures in Model 2 and further adjusting for age, gender, body mass index, smoking status, alcohol drinking status, education level, and Townsend Deprivation Index in Model 3.Figure 1: Association between allergic diseases (traits) and risk of achalasia of cardia. (A) Association between allergic diseases and risk of achalasia of cardia. *Model 1: Univariable model without adjustment. †Model 2: Cox model adjusted for other two allergic diseases for each exposure. ‡Model 3: Further adjusted for gender, age, body mass index, smoking status, alcohol drinking status, education level, and Townsend deprivation index. (B) Forest plot of the causal associations between allergy-related traits and achalasia of cardia. AC: Achalasia of cardia; CI: Confidence interval; HR: Hazard ratio; MR: Mendelian Randomization; MVMR: Multivariable MR; OR: Odds ratio; Ref: Reference; SNP: Single nucleotide polymorphisms; UVMR: Univariable MR.Harmonized data for UVMR were detailed in Supplementary Tables 4–6, https://links.lww.com/CM9/C853. As illustrated in Figure 1B, Supplementary Figure 2, and Supplementary Tables 7 and 8, https://links.lww.com/CM9/C853, the forward UVMR analysis did not yield significant causal effects for any of the allergy-related traits on AC, with P values over 0.05. In reverse UVMR analysis, the effects of AC on asthma, AR, and AD also showed insignificant results. Notably, we observed an association between AC as the exposure and EoE as the outcome (IVW OR, 1.095; 95% CI, 1.003–1.194; P = 0.042). After applying the penalized IVW method to reduce the weight of abnormal single nucleotide polymorphisms (SNPs), similar conclusions were also drawn. All bidirectional UVMR results successfully passed Cochran’s Q test and the MR-Egger intercept test, suggesting negligible heterogeneity and horizontal pleiotropy Supplementary Table 9, https://links.lww.com/CM9/C853. When combined allergic diseases were analyzed as the exposure, MR PRESSO detected one outlier SNP (rs1289273) and significant horizontal pleiotropy (PGlobal = 0.025). However, the outlier had little impact on the main MR results (PDistortion = 0.848) Supplementary Table 9, https://links.lww.com/CM9/C853. After removing the outlier SNP, no pleiotropy was further reported (PGlobal = 0.141), and the IVW results remained similar Supplementary Table 7, https://links.lww.com/CM9/C853. In addition, leave-one-out analyses showed no single SNP disproportionately affected the overall MR results Supplementary Figures 3 and 4, https://links.lww.com/CM9/C853. Harmonized data for MVMR were displayed in Supplementary Table 10, https://links.lww.com/CM9/C853. Results from MVMR-IVW indicated that liability to each allergic disorder did not affect the risk of AC, which was further supported by the MVMR-Egger method. These findings were consistent with the prior UVMR results, and both heterogeneity and pleiotropy tests provided satisfying results Supplementary Table 11, https://links.lww.com/CM9/C853. We also calculated the bias caused by potential sample overlap and the minimum detectable OR at 80% power for each MR analysis Supplementary Tables 12–13, https://links.lww.com/CM9/C853. In the present study, we evaluated the associations between AC and allergic diseases, including EoE, asthma, AR, and AD. Results from Cox regression based on the UKB cohort demonstrated that allergic diseases did not exert significant effects on the risk of incident AC in both unadjusted and adjusted models. These findings were further supported by forward UVMR and MVMR analyses, demonstrating that any allergy-related features had no causal effect on AC. Results from reverse MR indicated that AC could lead to a 9.5% increase in the risk of EoE, but no evidence was found for similar risks in other allergic diseases. This study leveraged the UKB dataset, which offers unique advantages due to its substantial sample size and standardized protocols for data collection and follow-up. Additionally, the utilization of the MR approach explained the associations between AC and allergy-related traits from a genetic epidemiology perspective, which is believed to effectively mitigate confounding bias, reverse causality, and recall bias. There are also some limitations of this study. First, the study population was restricted to the European population in the observational study and MR analysis, which limited the generalizability of our findings. Additionally, the UKB cohort predominantly consisted of middle-aged and elderly individuals, necessitating caution regarding allergic diseases and AC issues among teenagers and younger adults. Baseline data from UKB were self-reported, and recall bias may be introduced during data collection. Second, we failed to retrieve data from UKB with the definition of “eosinophilic esophagitis”, resulting in the lack of analysis of the direct association between EoE and AC in the prospective study. Furthermore, AC can be divided into three subtypes based on esophageal manometry, while there were no available data on the subtype of AC. Third, despite utilizing the largest existing GWAS datasets, the scarcity of AC and EoE cases (both of which were relatively rare diseases) resulted in a limited number of statistically significant SNPs, thus weakening the efficacy of MR analysis. In other words, we must acknowledge that our study is likely to be underpowered to detect subtle effects, and these findings are just preliminary. Taken together, through prospective cohort studies and MR analysis, this study did not provide evidence to suggest a direct causal relationship between AC and three outra-esophageal allergic diseases, namely, asthma, AR, and AD. Although genetically estimated AC was linked to an increased risk of EoE, the reverse association was not observed. This study proposed that considering AC as an allergy-driven disease may be untenable from the viewpoint of causal inference. Previous studies, including comorbidity-based case reports, histological staining, and population cohort studies, have suggested a potential association between AC and EoE, and proposed possible pathophysiological rationales to explain this phenomenon.2 The present study preliminarily proposed that AC may increase the risk of EoE from a causal inference perspective. Future research with larger sample sizes and more refined methodologies is necessary to more accurately elucidate the complex relationship between AC and EoE. Conflicts of interest None.
Li et al. (Mon,) studied this question.