Gut Microbiota, Circulating Cytokines and Eosinophilic Esophagitis: A Comprehensive Mendelian Randomization Study

Gut Microbiota, Circulating Cytokines and Eosinophilic Esophagitis: A Comprehensive Mendelian Randomization Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Gut Microbiota, Circulating Cytokines and Eosinophilic Esophagitis: A Comprehensive Mendelian Randomization Study Ruoyu Ji, Yuxiang Zhi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6635236/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Observational studies have reported the correlation between gut microbiota, cytokines and eosinophilic esophagitis (EoE), but the underlying causal relationship remains largely unclear. Methods : We used the Mendelian randomization approach based on large-scale genome-wide association study datasets to evaluate the causal relationship between gut microbiota and EoE, and to identify whether cytokines play a mediating role. We applied the inverse variance weighted method as the primary analysis followed by several sensitivity analyses. Results : We identified five bacterial taxa at various levels and two cytokines which exerted a positive casual effect on EoE. Eight bacterial taxa and one cytokine were found to have a protective effect on EoE. Cytokines did not act as mediating factors from gut microbiota to EoE. Reversely, EoE altered the composition of microbiome and levels of circulating cytokines. Sensitivity analyses confirmed the robustness of primary results. Conclusions : Gut microbiota and cytokines were causally associated with EoE, and cytokines did not play a mediating role in the pathway from gut microbiota to EoE. Eosinophilic esophagitis cytokines gut microbiota Mendelian randomization causality Figures Figure 1 Figure 2 Figure 3 1 Introduction Eosinophilic esophagitis (EoE) is a chronic T helper (Th) 2 cell immune-mediated upper gastrointestinal (GI) disease characterized by esophageal dysfunction clinically and eosinophilic infiltration in the esophageal mucosa pathologically[ 1 ]. The incidence of EoE is estimated to range from 5–10 cases per 100,000 and is still increasing worldwide. EoE has become the main cause of dysphagia among children and young adults[ 2 ]. The pathogenesis of EoE is complicated. Skewed immune response and defective barrier function are key elements involved in the occurrence and development of EoE[ 3 , 4 ]. Accumulated evidence has supported a role for the microbiome in modulating local immune response and epithelial barrier function to a variety of atopic diseases[ 5 – 7 ] and chronic esophageal diseases[ 8 , 9 ], including EoE[ 10 , 11 ]. The translocation of microbiota activates local immune cells, with a subsequent release of pathogenic cytokines, leading to epithelial inflammation in EoE. EoE alters GI microecology and in turn causes further dysbiosis in gut microbiota and local immunity[ 12 ]. We assumed that both gut microbiota and cytokines can affect the development of EoE, where cytokines may act as a mediating factor in the pathway from microbiome dysbiosis to EoE. The cross-sectional or case-control design of published studies limits the identification of the underlying causal relationship. Although randomized trials may solve this issue theoretically, the usage of bacteria strains and cytokines as interventions is no doubt infeasible. Mendelian randomization (MR) is an approach that uses the unique properties of genotype to investigate causal relationships, which offers the advantage of minimizing bias caused by confounding factors and reverse causality[ 13 , 14 ]. Here, we performed a comprehensive bi-directional MR analysis to explore the causality between the gut microbiota, circulating cytokines and EoE, and to identify whether cytokines act as a mediating factor from microbiota to EoE. 2 Materials and methods Study design This MR study is composed of three domains as demonstrated in Fig. 1 , including the bi-directional causality between gut microbiota and EoE (Part A), bi-directional causality between cytokines and EoE (Part B) and mediation analysis of cytokines in the pathway from gut microbiota to EoE (Part C). We utilized single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs). Three assumptions need to be fulfilled in a compelling MR study: (1) the IVs are closely associated with the exposure factors; (2) IVs are not associated with confounding factors; (3) IVs do not affect the outcome directly, and it can only affect outcome via the exposure[ 15 ]. Data Source Genetic variants of gut microbiota were obtained from the largest and most widely used genome-wide association studies (GWAS) dataset generated by the international MiBioGen consortium[ 16 ]. This large-scale GWAS analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals of predominantly European ancestry. Setting genus as the lowest taxonomic level, data of 211 taxa (9 phyla, 16 classes, 20 orders, 35 families and 131 genera, including unknown taxa) were reported. The genetic statistics for cytokines were obtained from a GWAS analyzing 41 circulating cytokines based on 8,337 individuals of European ancestry[ 17 ]. Genetic variants of EoE originated from a meta-analysis of GWAS (ID GCST90027899). The study included 1,930 patients with EoE and 13,634 controls of European ancestry. The diagnosis of EoE was both clinically and pathologically confirmed[ 18 ]. All studies were approved by the corresponding ethics committee and informed consents were collected from all participants. There is no participant overlapping among the three datasets. Selection of IVs The thresholds were set as P < 1×10 − 5 and P < 5×10 − 6 to filter SNPs strongly correlated with gut microbiota and cytokines at the locus-wide significance[ 19 , 20 ]. We then performed a linkage disequilibrium clumping and removed SNPs with r 2 ≥ 0.001 and clump distance ≤ 10,000 kb. All selected SNPs were required to have a minor allele frequency (MAF) > 1% and an F-statistic > 10. F-statistic which represents instrument strength is calculated using the formula \(\:F=\frac{{R}^{2}\times\:(N-1-k)}{(1-{R}^{2})\times\:K}\:\) , where R 2 is the proportion of variability in the exposure explained by IVs, N is the sample size and K is the number of IVs [ 21 , 22 ]. We also searched through the PhenoScanner GWAS database ( http://phenoscanner.medschl.cam.ac.uk ) and removed previously reported SNPs (if existed) associated with the outcome under a genome-wide significance threshold of P<5×10 −8 [ 23 ]. In the reverse MR, the significant threshold was set as P < 5×10 − 8 to filter IVs strongly correlated with EoE. MR analyses Two-sample bi-directional analysis MR analyses were performed by using the TwoSampleMR R package and a series of ancillary packages in the R software (Version 4.2.1)[ 24 ]. Only bacteria taxa (Forward, Part A) and cytokines (Forward, Part B) with three and more related SNPs were included in formal analyses, we excluded unknown bacterial taxa due to a lack of clinical significance. We used the random-effect inverse variance weighted (IVW) method as the primary analysis[ 25 ]. We used MR-Egger (MRE) and weighted median (WM) methods to test the robustness of primary results[ 25 , 26 ]. Estimates of individual SNP-exposure correlation versus SNP-outcome correlation were visualized by scattered plots. Mediation analysis Through the two-sample bi-directional analyses (Part A&B), we included bacterial taxa and cytokines with significant causal effects on EoE in further mediation analysis (Part C). We explored whether selected bacterial taxa had a causal effect on selected cytokines, and if so, we would perform multiple MR analysis to identify whether cytokines act as mediation factors in the pathway from gut microbiota to EoE. Sensitivity analysis The Egger intercept was utilized to examine pleiotropic effect. If a significant pleiotropic effect was detected, the MR pleiotropy residual sum and outlier (MR-PRESSO) method was used to identify the source of pleiotropy[ 27 ]. Heterogeneity was assessed using Cochrane’s Q test and was intuitively shown by the leave-one-out analysis[ 24 ]. When significant heterogeneity existed, the MR-Radial method was used to explore the source of heterogeneity and the sensitivity analysis was then performed by removing the identified outlier [ 28 , 29 ]. 3 Results 3.1 Causal relationship between gut microbiota and EoE (Part A) SNPs selections In the forward analysis, 100 SNPs of nine phyla, 155 SNPs of 15 classes, 173 SNPs of 19 orders, 237 SNPs of 30 families and 400 SNPs of 74 genera were selected as IVs. In the reverse analysis, 10 independent SNPs correlated with EoE were filtered. The F statistics of the IVs were all over 10, indicating no evidence of weak instrument bias. Details of selected IVs were demonstrated in Table S1 and Table S2 . Forward analyses Primary results were detailed in Table S3 . The phylum Tenericutes was causally associated with EoE (IVW, odds ratio [OR] = 1.41, 95% confidence interval [CI]: 1.00-1.99, P = 0.047), while MRE (OR = 2.08, 95% CI: 0.67–6.42) and WM (OR = 1.51, 95% CI: 0.97–2.37) methods revealed a non-significant result (Fig. 2 A). At the class level, the class Mollicutes exerted a causal effect on EoE (OR = 1.43, 95% CI: 1.03–1.97, P = 0.033). Results of MRE (OR = 1.28; 95% CI, 0.48–3.43) and WM (OR = 1.53; 95% CI, 0.99–2.38) both suggested a positive but non-significant relationship (Fig. 2 B). At the order level, the order Bacteroidales was genetically correlated with EoE (OR = 2.00, 95% CI: 1.33–3.01, P < 0.001; MRE, OR = 1.78; 95% CI, 1.28–6.04; WM, OR = 1.89; 95% CI, 1.05–3.39, Fig. 2 C), while Desulfovibrionales (IVW, OR = 0.57, 95% CI: 0.33–0.98, P = 0.040; MRE, OR = 0.19; 95% CI, 0.07–0.49; WM, OR = 0.44; 95% CI, 0.25–0.77, Fig. 2 D) and Pasteurellales (IVW, OR = 0.74, 95% CI: 0.56–0.98, P = 0.037; MRE, OR = 0.57, 95% CI: 0.29–1.10; WM, OR = 0.70, 95% CI, 0.49-1.00, Fig. 2 E) showed a protective effect on EoE. The family Pasteurellaceae demonstrated a protective effect on EoE in both IVW (OR = 0.75, 95% CI: 0.56–0.99, P = 0.045) and MRE (OR = 0.47, 95% CI: 0.23–0.94) analyses, but not by the WM method (OR = 0.70, 95% CI: 0.48–1.02, Fig. 2 F). At the genus level, Eisenbergiella (IVW, OR = 1.81, 95% CI: 1.16–2.85, P = 0.009; MRE, OR = 1.13, 95% CI: 0.06–20.45; WM, OR = 1.90, 95% CI: 1.09–3.30) and Lachnospiraceae_FCS020_group (IVW, OR = 1.71, 95% CI: 1.04–2.83, P = 0.034; MRE, OR = 4.41, 95% CI: 1.44–13.48; WM, OR = 1.96, 95% CI: 0.99–3.86) yielded a positive causal effect on EoE, while the Anaerotruncus (IVW, OR = 0.23, 95% CI: 0.06–0.85, P = 0.027; MRE, OR = 0.03, 95% CI: 0.00-16.47; WM, OR = 0.26, 95% CI: 0.08–0.82), Coprococcus_1 (IVW, OR = 0.41, 95% CI: 0.23–0.73, P = 0.002; MRE, OR = 0.50, 95% CI: 0.12–2.32; WM, OR = 0.47, 95% CI: 0.22–1.02), Haemophilus (IVW, OR = 0.65, 95% CI: 0.45–0.92, P = 0.015; MRE, OR = 0.41, 95% CI: 0.16–1.04; WM, OR = 0.58, 95% CI: 0.37–0.90), Oxalobacter (IVW, OR = 0.75, 95% CI: 0.60–0.92, P = 0.006; MRE, OR = 0.55, 95% CI: 0.25–1.21; WM, OR = 0.77, 95% CI: 0.58–1.01) and Subdoligranulum (IVW, OR = 0.54, 95% CI: 0.30–0.99, P = 0.045; MRE, OR = 0.51, 95% CI: 0.01–25.66; WM, OR = 0.54, 95% CI: 0.24–1.21) demonstrated a protective effect on EoE (Fig. 2 G-M). Reverse analyses Primary results of the reverse analysis were detailed in Table S4 . EoE led to an increased abundance of the genus Eubacterium_nodatum_group (IVW, OR = 1.17, 95% CI: 1.07–1.27, P = 0.002; MRE, OR = 1.08, 95% CI: 0.20–1.96; WM, OR = 1.16, 95% CI: 1.06–1.26, Figure S1 A), but was causally associated with the depletion of family Pasteurellaceae (IVW, OR = 0.95, 95% CI: 0.90-1.00, P = 0.042; MRE, OR = 1.08, 95% CI: 0.72–1.44; WM, OR = 0.96, 95% CI: 0.90–1.01, Figure S1 B), family Ruminococcaceae (IVW, OR = 0.97, 95% CI: 0.93-1.00, P = 0.042; MRE, OR = 0.96, 95% CI: 0.92-1.00; WM, OR = 1.03, 95% CI: 0.81–1.24, Figure S1 C), genus Ruminococcaceae_UCG003 (IVW, OR = 0.96, 95% CI: 0.92–0.99, P = 0.025; MRE, OR = 1.01, 95% CI: 0.72–1.31; WM, OR = 0.95, 95% CI: 0.91-1.00, Figure S1 D), genus Coprococcus_1 (IVW, OR = 0.96, 95% CI: 0.93-1.00, P = 0.039; MRE, OR = 0.90, 95% CI: 0.66–1.14; WM, OR = 0.95, 95% CI: 0.91-1.00, Figure S1 E) and genus Faecalibacterium (IVW, OR = 0.96, 95% CI: 0.93-1.00, P = 0.033; MRE, OR = 0.94, 95% CI: 0.73–1.16; WM, OR = 0.96, 95% CI: 0.92-1.00, Figure S1 F). Sensitivity analyses In the forward MR (Table S5, Figure S2 ), a significant heterogeneity and pleiotropic effect regarding the estimates of the order Desulfovibrionales were detected by the Cochrane’s Q test (Q value = 17.44, P = 0.026) and the intercept of Egger regression (Egger intercept = 0.095, P = 0.040), respectively. The MR-PRESSO (P = 0.044) and MR-Radial (P = 0.026) methods further confirmed this result and identified the rs9928243 as the outlier. The sensitivity analysis was then performed after excluding the outlier, the protective effect became more significant as expected (IVW, OR = 0.46, 95% CI: 0.32–0.68, P < 0.001). In the reverse MR, no heterogeneity or pleiotropic effect was detected (Table S5, Figure S3 ). 3.2 Causal relationship between cytokines and EoE (Part B) SNPs selections In the forward analysis, 414 SNPs of 41 cytokines with MAF > 1% and F-statistic > 10 were screened as IVs (Table S6). In the reverse analysis, 10 independent SNPs correlated with EoE were filtered (Table S2 ). Forward analyses Among 41 cytokines (Table S7), the interleukin (IL)-12p70 (IVW, OR = 1.17, 95% CI: 1.03–1.31, P = 0.028; MRE, OR = 1.09, 95% CI: 0.86–1.31; WM, OR = 1.18, 95% CI: 1.02–1.34, Fig. 3 A) and IL-16 (IVW, OR = 1.13, 95% CI: 1.02–1.23, P = 0.028; MRE, OR = 1.11, 95% CI: 0.94–1.27; WM, OR = 1.13, 95% CI: 0.99–1.27, Fig. 3 B) exerted a positive casual effect on EoE, while the monokine induced by interferon-γ (MIG) demonstrated a protective effect on EoE (IVW, OR = 0.82, 95% CI: 0.69–0.95, P = 0.002; MRE, OR = 0.82, 95% CI: 0.94–1.27; WM, OR = 0.89, 95% CI: 0.73–1.05, Fig. 3 C),. Reverse analyses Reversely, EoE contributed to a declined level of cutaneous T-cell attracting chemokine (CTACK, IVW, OR = 0.91, 95% CI: 0.84–0.98, P = 0.008; MRE, OR = 0.87, 95% CI: 0.52–1.21; WM, OR = 0.93, 95% CI: 0.84–1.02). No other significant result was revealed (Table S8). Sensitivity analyses The sensitivity analyses detected no significant heterogeneity or pleiotropic effect was detected in bidirectional results (Table S9). 3.3 Mediation analysis (Part C) We assumed that cytokines play a potential mediating role in the pathway from gut microbiota to EoE. We evaluated the casual relationship between bacterial taxa and cytokines with significant causal effects on EoE, and no significant causality was revealed (Table S10). Therefore, there was no suggestive evidence that cytokines are mediators between gut microbiota and EoE. 4 Discussion Despite the close correlation between gut microbiota and EoE, whether the alteration in microbiome is a cause or consequence of EoE is largely unclear. Recent publishment of EoE GWAS enabled us to use the genetic approach to identify the underlying causal relationship[ 18 ]. Using publicly available GWAS summary statistics, results of our two-sample MR analysis identified several bacterial taxa of various levels, which had significant causal relation with EoE. At the genus level, our findings indicate a positive causal effect of Eisenbergiella and Lachnospiraceae_FCS020_group on EoE. Despite a lack of direct and straightforward mechanism to explain how Eisenbergiella increases the risk of EoE, this genus has been linked with the risk of moderate to severe asthma and the severity of allergic rhinitis by previous studies[ 30 , 31 ], suggesting its pathogenic role in atopic diseases. The Lachnospiraceae_FCS020_group is a rare member of the family Lachnospiraceae. Lachnospiraceae is a core gut microbiome and plays a controversial role in human health and diseases. In inflammatory bowel disease (IBD), some genera exert a beneficial effect via butyrogenesis, while others harmful genera disrupt the mucus layer and promote bacterial translocation [ 32 ]. We speculated that the overgrowth of Lachnospiraceae_FCS020_group may trigger inflammation in the GI tract by attenuating the beneficial effect from other butyrate-producing genera of the Lachnospiraceae. On the other hand, several genera including Subdoligranulum , Oxalobacter, Coprococcs_1, Anaerotruncus and Haemophilus were found to have a protective effect on EoE. The depletion of Subdoligranulum in infants around the age of weaning is correlated with children’s food allergy which is a main trigger or EoE[ 4 , 30 ]. Further mice experiment indicated that bacteriotherapy using Subdoligranulum and Clostridiales species suppress food allergy via a regulatory T cell MyD88/RORγt pathway[ 30 ]. Oxalobacter species maintain host oxalate homeostasis, with protection against oxalate-induced toxicity. The disruption of oxalate homeostasis is correlated with the development of multiple auto-immune diseases[ 33 ]. Genus Coprococcus and Anaerotruncus are butyrate-producing bacteria. As the metabolite of probiotics, butyrate plays an essential role in inhibiting GI inflammation and maintaining epithelial barrier integrity[ 34 , 35 ]. The protective effect of the genus Haemophilus on EoE is in contrary to some of the results of previous studies[ 12 ]. Haemophilus in the respiratory tract activates IL-6 signaling pathway and therefore induces chronic airway inflammation[ 36 ]. However, several studies have confirmed the role of IL-6 in promoting homeostasis and rapid tissue-protective responses in the gut[ 37 , 38 ], which partially explains the protective effect of Haemophilus on EoE. To date, bacteriotherapy has been attempted in the treatment of atopic diseases[ 39 – 41 ] and IBD[ 42 ], and some clinical trials has accomplished satisfactory outcomes. Therefore, identifications of bacteria with a protective effect on EoE may help with the follow-up development of bacteriotherapy for EoE. We further explored the causality of cytokines on EoE and examined whether they play a mediating role between gut microbiota and EoE. Our results suggested that a higher circulating level of IL-12p70 and IL-16 levels is casually related to an increased risk of EoE. IL-16 is involved in CD4 + cell recruitment and further enhances the expression of Th2 cytokines[ 43 ], which has been identified as a potential biomarker in allergic diseases like atopic dermatitis[ 44 , 45 ]. IL-12p70 is the dimeric form of IL-12 which binds to the IL-12 receptor and initiates the downstream signaling pathways. IL-12 induces intestinal inflammation and is a key target in the treatment of IBD[ 46 ], which is another chronic immune-mediated GI disease sharing overlapping pathogenesis with EoE. However, results of mediation analyses did not support the mediating effect of cytokines. To our knowledge, this is the first MR study to assess the causal effect of gut microbiome and cytokines on EoE. The exposure data originated from the large-scale and widely used GWAS of human gut microbiome and circulating cytokines. The EoE dataset was obtained from a high-quality GWAS meta-analysis with an appropriate case-control ratio of 1:7, avoiding the bias caused by extremely unbalanced case-control ratio[ 47 ]. In the creation of IVs, we excluded SNPs with potential linkage disequilibrium and weak strengths. To validate the credibility of our results, we employed various MR methods. Generally, a consistency of OR values among the three MR methods is observed. Additionally, sensitivity analyses detected small heterogeneity and pleiotropy of primary results, confirming the robustness of our findings. Inevitably, our study has limitations. Populations in all GWAS datasets are predominantly European, limiting the direct generalization of our findings to other ethnic populations. Since the GWAS of gut microbiome only provided summary data to the genus level, we were unable to further the analysis at the species level, which is underlined and feasible in the era of metagenomic sequencing. The GWAS data of EoE were generated based on children and adolescents. Though there is no evidence for the difference in genetic variants between pediatric and adult EoE patients, selection bias could not be fully excluded. Further research is warranted to resolve the above issues. 5 Conclusion This MR study identified bacteria that were causally associated with EoE at various taxonomic levels. Bacteria exerting a protective effect on EoE might be targets forfurther bacteriotherapy. Also, several cytokines causally correlated to EoE were revealed, but they seemed not to act as a mediating factor between gut microbiota and EoE. EoE reversely altered gut microbiome composition and levels of circulating cytokines. Of note, MR studies only generate evidence for causality from the genetic perspective rather than establishing causality straightforwardly. Further studies focusing on underlying mechanisms are still needed. Abbreviations EoE: eosinophilic esophagitis; MR: Mendelian randomization; GWAS: genome wide association study; IV: instrumental variable; Th: T helper; GI: gastrointestinal; SNP: single nucleotide polymorphism; IVW: inverse variance weighted; MRE: MR-Egger; WM: weighted median; OR: odds ratio; CI: confidence interval; MR-PRESSO: MR pleiotropy residual sum and outlier; IL: interleukin; MIG: monokine induced by interferon-γ; IBD: inflammatory bowel disease. Declarations Data availability statement: The original contributions are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors. Author contributions: Ruoyu Ji contributed to study design, data collection, data processing, data analysis and wrote the manuscript draft. Yuxiang Zhi contributed to the initiation of the study, study design, and reviewed the manuscript draft. Both authors contributed to the interpretation of results and approved the final manuscript. Ethics Statement : This study is performed based on publicly available data. Ethical approval was granted for all the original studies included. No individual‑level data were generated. Therefore, the ethics approval was waived by the Ethics Committee of Peking Union Medical College Hospital. Funding support: CAMS Innovation Fund for Medical Sciences (grant number, CIFMS 2021-I2M-1-003) and Beijing Natural Science Foundation (grant number L222082). Consent for publication: Not applicable Disclosure of potential conflict of interest: The authors declare that they have no relevant conflicts of interest. Acknowledgments: None. References Liacouras, C.A., et al., Eosinophilic esophagitis: updated consensus recommendations for children and adults. 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Kuhn, K.A., et al., IL-6 stimulates intestinal epithelial proliferation and repair after injury. PLoS One, 2014. 9 (12): p. e114195. Yan, Y., et al., Interleukin-6 produced by enteric neurons regulates the number and phenotype of microbe-responsive regulatory T cells in the gut. Immunity, 2021. 54 (3): p. 499-513.e5. Nakatsuji, T., et al., Development of a human skin commensal microbe for bacteriotherapy of atopic dermatitis and use in a phase 1 randomized clinical trial. Nat Med, 2021. 27 (4): p. 700-709. Gong, J.Q., et al., Skin colonization by Staphylococcus aureus in patients with eczema and atopic dermatitis and relevant combined topical therapy: a double-blind multicentre randomized controlled trial. Br J Dermatol, 2006. 155 (4): p. 680-7. Helin, T., S. Haahtela, and T. Haahtela, No effect of oral treatment with an intestinal bacterial strain, Lactobacillus rhamnosus (ATCC 53103), on birch-pollen allergy: a placebo-controlled double-blind study. Allergy, 2002. 57 (3): p. 243-6. Liu, J., et al., Mucoadhesive probiotic backpacks with ROS nanoscavengers enhance the bacteriotherapy for inflammatory bowel diseases. Sci Adv, 2022. 8 (45): p. eabp8798. Li, C., et al., Interleukin-16 aggravates ovalbumin-induced allergic inflammation by enhancing Th2 and Th17 cytokine production in a mouse model. Immunology, 2019. 157 (3): p. 257-267. Frezzolini, A., et al., Circulating interleukin 16 (IL-16) in children with atopic/eczema dermatitis syndrome (AEDS): a novel serological marker of disease activity. Allergy, 2002. 57 (9): p. 815-20. Angelova-Fischer, I., et al., Significance of interleukin-16, macrophage-derived chemokine, eosinophil cationic protein and soluble E-selectin in reflecting disease activity of atopic dermatitis--from laboratory parameters to clinical scores. Br J Dermatol, 2006. 154 (6): p. 1112-7. Verstockt, B., et al., IL-12 and IL-23 pathway inhibition in inflammatory bowel disease. Nat Rev Gastroenterol Hepatol, 2023. 20 (7): p. 433-446. Zhou, W., et al., Efficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies. Nat Genet, 2018. 50 (9): p. 1335-1341. Additional Declarations No competing interests reported. Supplementary Files FigureS1.jpg Figure S1. Scatter plots of MR analyses evaluating the causal effect of EoE on genus Eubacterium_nodatum_group (A), family Pasteurellaceae (B), family Ruminococcaceae (C), genus Ruminococcaceae_UCG003 (D), genus Coprococcus_1 (E) and genus Faecalibacterium (F). MR, Mendelian randomization; EoE, eosinophilic esophagitis; SNP, single nucleotide polymorphism. FigureS2.jpg Figure S2 Results of leave-one-out sensitivity analyses for evaluating the causal effect of plylum Tenericutes (A), class Mollicutes (B), order Bacteroidales (C), order Desulfovibrionales (D), order Pasteurellales (E), family Pasteurellaceae (F), genus Anaerotruncus (G), genus Coprococcus1 (H), genus Eisenbergiella (I), genus Haemophilus (J), genus LachnospiraceaeFCS020group (K), genus Oxalobacter (L) and genus Subdoligranulum (M) on EoE. MR, Mendelian randomization; EoE, eosinophilic esophagitis. FigureS3.jpg Figure S3. Results of leave-one-out sensitivity analyses for evaluating the causal effect of EoE on genus Eubacterium_nodatum_group (A), family Pasteurellaceae (B), family Ruminococcaceae (C), genus Ruminococcaceae_UCG003 (D), genus Coprococcus_1 (E) and genus Faecalibacterium (F). MR, Mendelian randomization; EoE, eosinophilic esophagitis. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6635236","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456123994,"identity":"156b74d5-730b-49fe-9098-1a002249a59a","order_by":0,"name":"Ruoyu Ji","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences and Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Ruoyu","middleName":"","lastName":"Ji","suffix":""},{"id":456123995,"identity":"112b7dbe-145e-4774-966f-5d717b14174e","order_by":1,"name":"Yuxiang Zhi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIiWNgGAWjYDCCAxAqgQ1MAjE/M/PhBwS0MDagaJFsZ0szIEoLXMDgPI+CBD4dfMebnz/4uKcuj08ix0ziQc0du82HeRgMGGpsonFpkTxzzLBxxjO2YjaJHGODhGPPkrcd5j3wgOFYWm4DDi0GN3IYm3kO8CS2SeQYPkhgO5xsdpgvwYCx4TAhLRIgLQYHEv4dTjZu5jGQIEKLAcSWxLbDdgbMBLSA/DJzxoGExDaeZ8UGiX2HEyQOAwM5AY9fgCH24MOHA3WJ89uTt0n++HbYnr//8OEHH2pscGpBAIEEMJUIVplAUDkI8B8AU/ZEKR4Fo2AUjIIRBQDcj2HQZYQjjAAAAABJRU5ErkJggg==","orcid":"","institution":"Chinese Academy of Medical Sciences and Peking Union Medical College","correspondingAuthor":true,"prefix":"","firstName":"Yuxiang","middleName":"","lastName":"Zhi","suffix":""}],"badges":[],"createdAt":"2025-05-10 14:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6635236/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6635236/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82682549,"identity":"1cc7f3d0-2f72-4369-8925-c62bff58a609","added_by":"auto","created_at":"2025-05-14 06:10:46","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":410550,"visible":true,"origin":"","legend":"\u003cp\u003eStudy overview. This study is composed of three domains, including a bi-directional MR analysis between gut microbiota and EoE (Part A), a bi-directional MR analysis between cytokines and EoE (Part B) and a mediation analysis of cytokines in the pathway from gut microbiota to EoE (Part C). The IVs in forward analyses were selected with a locus-wide significance. The IVs in reverse analyses were selected with a genome-wide significance. GWAS, genome wide association study; EoE, eosinophilic esophagitis; IVs, instrumental variables; MR, Mendelian randomization.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/01345be57d4746eb7d0c5834.jpg"},{"id":82681665,"identity":"1c9a851a-f399-49bf-972a-8219aacda9cd","added_by":"auto","created_at":"2025-05-14 06:02:46","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1622257,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of MR analyses evaluating the causal effect of plylum \u003cem\u003eTenericutes\u003c/em\u003e (A), class \u003cem\u003eMollicutes\u003c/em\u003e(B), order \u003cem\u003eBacteroidales\u003c/em\u003e (C), order \u003cem\u003eDesulfovibrionales\u003c/em\u003e (D), order \u003cem\u003ePasteurellales \u003c/em\u003e(E), family \u003cem\u003ePasteurellaceae\u003c/em\u003e (F), genus \u003cem\u003eAnaerotruncus \u003c/em\u003e(G), genus \u003cem\u003eCoprococcus1 \u003c/em\u003e(H), genus \u003cem\u003eEisenbergiella\u003c/em\u003e (I), genus \u003cem\u003eHaemophilus\u003c/em\u003e(J), genus \u003cem\u003eLachnospiraceaeFCS020group\u003c/em\u003e (K), genus \u003cem\u003eOxalobacter\u003c/em\u003e (L) and genus \u003cem\u003eSubdoligranulum\u003c/em\u003e (M) on EoE. MR, Mendelian randomization; EoE, eosinophilic esophagitis.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/e4de0392f9db510e535fd333.jpg"},{"id":82681663,"identity":"8f7cd411-7da7-47ba-89eb-6b1a86a61ac6","added_by":"auto","created_at":"2025-05-14 06:02:46","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":345368,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of MR analyses evaluating the causal effect of IL-12p70 (A), IL-16 (B) and MIG (C) on EoE. MR, Mendelian randomization; IL, interleukin; MIG: monokine induced by interferon-γ; EoE, eosinophilic esophagitis.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/79006a29afc4e7ec9c50a552.jpg"},{"id":83071602,"identity":"7149fef4-7523-4dca-a59c-25fff78b78b8","added_by":"auto","created_at":"2025-05-19 16:38:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3143919,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/5627de27-b873-44e8-aed3-326108d7673f.pdf"},{"id":82681659,"identity":"e1cda7ef-a7f5-4ff9-a269-3a01b371a93b","added_by":"auto","created_at":"2025-05-14 06:02:46","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":504136,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S1. Scatter plots of MR analyses evaluating the causal effect of EoE on genus \u003cem\u003eEubacterium_nodatum_group \u003c/em\u003e(A), family \u003cem\u003ePasteurellaceae \u003c/em\u003e(B), family \u003cem\u003eRuminococcaceae\u003c/em\u003e (C), genus\u003cem\u003eRuminococcaceae_UCG003\u003c/em\u003e (D), genus \u003cem\u003eCoprococcus_1\u003c/em\u003e (E) and genus \u003cem\u003eFaecalibacterium \u003c/em\u003e(F). MR, Mendelian randomization; EoE, eosinophilic esophagitis; SNP, single nucleotide polymorphism.\u003c/p\u003e","description":"","filename":"FigureS1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/5031ef6db7cece3890932785.jpg"},{"id":82681660,"identity":"224c8f4b-7cdd-4e36-b082-25797dd3b2a5","added_by":"auto","created_at":"2025-05-14 06:02:46","extension":"jpg","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1884439,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S2 Results of leave-one-out sensitivity analyses for evaluating the causal effect of plylum \u003cem\u003eTenericutes\u003c/em\u003e(A), class \u003cem\u003eMollicutes\u003c/em\u003e (B), order \u003cem\u003eBacteroidales\u003c/em\u003e (C), order \u003cem\u003eDesulfovibrionales\u003c/em\u003e(D), order \u003cem\u003ePasteurellales \u003c/em\u003e(E), family \u003cem\u003ePasteurellaceae\u003c/em\u003e (F), genus \u003cem\u003eAnaerotruncus \u003c/em\u003e(G), genus \u003cem\u003eCoprococcus1 \u003c/em\u003e(H), genus \u003cem\u003eEisenbergiella\u003c/em\u003e (I), genus \u003cem\u003eHaemophilus\u003c/em\u003e(J), genus \u003cem\u003eLachnospiraceaeFCS020group\u003c/em\u003e (K), genus \u003cem\u003eOxalobacter\u003c/em\u003e (L) and genus \u003cem\u003eSubdoligranulum\u003c/em\u003e(M) on EoE. MR, Mendelian randomization; EoE, eosinophilic esophagitis.\u003c/p\u003e","description":"","filename":"FigureS2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/f032c3a5ec27331d9d18f1a5.jpg"},{"id":82681668,"identity":"10386a07-e2a8-41d7-b150-d3a165540e92","added_by":"auto","created_at":"2025-05-14 06:02:46","extension":"jpg","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":437899,"visible":true,"origin":"","legend":"\u003cp\u003eFigure S3. Results of leave-one-out sensitivity analyses for evaluating the causal effect of EoE on genus \u003cem\u003eEubacterium_nodatum_group \u003c/em\u003e(A), family \u003cem\u003ePasteurellaceae \u003c/em\u003e(B), family \u003cem\u003eRuminococcaceae\u003c/em\u003e (C), genus\u003cem\u003eRuminococcaceae_UCG003\u003c/em\u003e (D), genus \u003cem\u003eCoprococcus_1\u003c/em\u003e (E) and genus \u003cem\u003eFaecalibacterium \u003c/em\u003e(F). MR, Mendelian randomization; EoE, eosinophilic esophagitis.\u003c/p\u003e","description":"","filename":"FigureS3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/966b1c132dbd83ffe5cd26c4.jpg"},{"id":82681666,"identity":"9f91c625-0398-4433-acd8-9842823fc6d2","added_by":"auto","created_at":"2025-05-14 06:02:46","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":287860,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6635236/v1/844e38f74d66e4805aef5575.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eGut Microbiota, Circulating Cytokines and Eosinophilic Esophagitis: A Comprehensive Mendelian Randomization Study\u003c/p\u003e","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eEosinophilic esophagitis (EoE) is a chronic T helper (Th) 2 cell immune-mediated upper gastrointestinal (GI) disease characterized by esophageal dysfunction clinically and eosinophilic infiltration in the esophageal mucosa pathologically[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The incidence of EoE is estimated to range from 5\u0026ndash;10 cases per 100,000 and is still increasing worldwide. EoE has become the main cause of dysphagia among children and young adults[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The pathogenesis of EoE is complicated. Skewed immune response and defective barrier function are key elements involved in the occurrence and development of EoE[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Accumulated evidence has supported a role for the microbiome in modulating local immune response and epithelial barrier function to a variety of atopic diseases[\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and chronic esophageal diseases[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], including EoE[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The translocation of microbiota activates local immune cells, with a subsequent release of pathogenic cytokines, leading to epithelial inflammation in EoE. EoE alters GI microecology and in turn causes further dysbiosis in gut microbiota and local immunity[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. We assumed that both gut microbiota and cytokines can affect the development of EoE, where cytokines may act as a mediating factor in the pathway from microbiome dysbiosis to EoE. The cross-sectional or case-control design of published studies limits the identification of the underlying causal relationship. Although randomized trials may solve this issue theoretically, the usage of bacteria strains and cytokines as interventions is no doubt infeasible.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) is an approach that uses the unique properties of genotype to investigate causal relationships, which offers the advantage of minimizing bias caused by confounding factors and reverse causality[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Here, we performed a comprehensive bi-directional MR analysis to explore the causality between the gut microbiota, circulating cytokines and EoE, and to identify whether cytokines act as a mediating factor from microbiota to EoE.\u003c/p\u003e"},{"header":"2 Materials and methods","content":"\u003cp\u003e \u003cb\u003eStudy design\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis MR study is composed of three domains as demonstrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, including the bi-directional causality between gut microbiota and EoE (Part A), bi-directional causality between cytokines and EoE (Part B) and mediation analysis of cytokines in the pathway from gut microbiota to EoE (Part C). We utilized single-nucleotide polymorphisms (SNPs) as instrumental variables (IVs). Three assumptions need to be fulfilled in a compelling MR study: (1) the IVs are closely associated with the exposure factors; (2) IVs are not associated with confounding factors; (3) IVs do not affect the outcome directly, and it can only affect outcome via the exposure[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eData Source\u003c/b\u003e \u003c/p\u003e \u003cp\u003eGenetic variants of gut microbiota were obtained from the largest and most widely used genome-wide association studies (GWAS) dataset generated by the international MiBioGen consortium[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This large-scale GWAS analyzed genome-wide genotypes and 16S fecal microbiome data from 18,340 individuals of predominantly European ancestry. Setting genus as the lowest taxonomic level, data of 211 taxa (9 phyla, 16 classes, 20 orders, 35 families and 131 genera, including unknown taxa) were reported. The genetic statistics for cytokines were obtained from a GWAS analyzing 41 circulating cytokines based on 8,337 individuals of European ancestry[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Genetic variants of EoE originated from a meta-analysis of GWAS (ID GCST90027899). The study included 1,930 patients with EoE and 13,634 controls of European ancestry. The diagnosis of EoE was both clinically and pathologically confirmed[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. All studies were approved by the corresponding ethics committee and informed consents were collected from all participants. There is no participant overlapping among the three datasets.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSelection of IVs\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe thresholds were set as P\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e and P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e to filter SNPs strongly correlated with gut microbiota and cytokines at the locus-wide significance[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. We then performed a linkage disequilibrium clumping and removed SNPs with r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026ge;\u0026thinsp;0.001 and clump distance\u0026thinsp;\u0026le;\u0026thinsp;10,000 kb. All selected SNPs were required to have a minor allele frequency (MAF)\u0026thinsp;\u0026gt;\u0026thinsp;1% and an F-statistic\u0026thinsp;\u0026gt;\u0026thinsp;10. F-statistic which represents instrument strength is calculated using the formula \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:F=\\frac{{R}^{2}\\times\\:(N-1-k)}{(1-{R}^{2})\\times\\:K}\\:\\)\u003c/span\u003e\u003c/span\u003e, where R\u003csup\u003e2\u003c/sup\u003e is the proportion of variability in the exposure explained by IVs, N is the sample size and K is the number of IVs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We also searched through the PhenoScanner GWAS database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://phenoscanner.medschl.cam.ac.uk\u003c/span\u003e\u003cspan address=\"http://phenoscanner.medschl.cam.ac.uk\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and removed previously reported SNPs (if existed) associated with the outcome under a genome-wide significance threshold of P\u0026lt;5\u0026times;10\u003csup\u003e\u0026minus;8\u003c/sup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In the reverse MR, the significant threshold was set as P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e to filter IVs strongly correlated with EoE.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMR analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eTwo-sample bi-directional analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eMR analyses were performed by using the TwoSampleMR R package and a series of ancillary packages in the R software (Version 4.2.1)[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Only bacteria taxa (Forward, Part A) and cytokines (Forward, Part B) with three and more related SNPs were included in formal analyses, we excluded unknown bacterial taxa due to a lack of clinical significance. We used the random-effect inverse variance weighted (IVW) method as the primary analysis[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. We used MR-Egger (MRE) and weighted median (WM) methods to test the robustness of primary results[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Estimates of individual SNP-exposure correlation versus SNP-outcome correlation were visualized by scattered plots.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMediation analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThrough the two-sample bi-directional analyses (Part A\u0026amp;B), we included bacterial taxa and cytokines with significant causal effects on EoE in further mediation analysis (Part C). We explored whether selected bacterial taxa had a causal effect on selected cytokines, and if so, we would perform multiple MR analysis to identify whether cytokines act as mediation factors in the pathway from gut microbiota to EoE.\u003c/p\u003e \u003cp\u003e \u003cb\u003eSensitivity analysis\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe Egger intercept was utilized to examine pleiotropic effect. If a significant pleiotropic effect was detected, the MR pleiotropy residual sum and outlier (MR-PRESSO) method was used to identify the source of pleiotropy[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Heterogeneity was assessed using Cochrane\u0026rsquo;s Q test and was intuitively shown by the leave-one-out analysis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. When significant heterogeneity existed, the MR-Radial method was used to explore the source of heterogeneity and the sensitivity analysis was then performed by removing the identified outlier [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Causal relationship between gut microbiota and EoE (Part A)\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSNPs selections\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the forward analysis, 100 SNPs of nine phyla, 155 SNPs of 15 classes, 173 SNPs of 19 orders, 237 SNPs of 30 families and 400 SNPs of 74 genera were selected as IVs. In the reverse analysis, 10 independent SNPs correlated with EoE were filtered. The F statistics of the IVs were all over 10, indicating no evidence of weak instrument bias. Details of selected IVs were demonstrated in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eForward analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePrimary results were detailed in Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e. The phylum \u003cem\u003eTenericutes\u003c/em\u003e was causally associated with EoE (IVW, odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.41, 95% confidence interval [CI]: 1.00-1.99, P\u0026thinsp;=\u0026thinsp;0.047), while MRE (OR\u0026thinsp;=\u0026thinsp;2.08, 95% CI: 0.67\u0026ndash;6.42) and WM (OR\u0026thinsp;=\u0026thinsp;1.51, 95% CI: 0.97\u0026ndash;2.37) methods revealed a non-significant result (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). At the class level, the class \u003cem\u003eMollicutes\u003c/em\u003e exerted a causal effect on EoE (OR\u0026thinsp;=\u0026thinsp;1.43, 95% CI: 1.03\u0026ndash;1.97, P\u0026thinsp;=\u0026thinsp;0.033). Results of MRE (OR\u0026thinsp;=\u0026thinsp;1.28; 95% CI, 0.48\u0026ndash;3.43) and WM (OR\u0026thinsp;=\u0026thinsp;1.53; 95% CI, 0.99\u0026ndash;2.38) both suggested a positive but non-significant relationship (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). At the order level, the order \u003cem\u003eBacteroidales\u003c/em\u003e was genetically correlated with EoE (OR\u0026thinsp;=\u0026thinsp;2.00, 95% CI: 1.33\u0026ndash;3.01, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; MRE, OR\u0026thinsp;=\u0026thinsp;1.78; 95% CI, 1.28\u0026ndash;6.04; WM, OR\u0026thinsp;=\u0026thinsp;1.89; 95% CI, 1.05\u0026ndash;3.39, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), while \u003cem\u003eDesulfovibrionales\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.57, 95% CI: 0.33\u0026ndash;0.98, P\u0026thinsp;=\u0026thinsp;0.040; MRE, OR\u0026thinsp;=\u0026thinsp;0.19; 95% CI, 0.07\u0026ndash;0.49; WM, OR\u0026thinsp;=\u0026thinsp;0.44; 95% CI, 0.25\u0026ndash;0.77, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD) and \u003cem\u003ePasteurellales\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.74, 95% CI: 0.56\u0026ndash;0.98, P\u0026thinsp;=\u0026thinsp;0.037; MRE, OR\u0026thinsp;=\u0026thinsp;0.57, 95% CI: 0.29\u0026ndash;1.10; WM, OR\u0026thinsp;=\u0026thinsp;0.70, 95% CI, 0.49-1.00, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE) showed a protective effect on EoE. The family \u003cem\u003ePasteurellaceae\u003c/em\u003e demonstrated a protective effect on EoE in both IVW (OR\u0026thinsp;=\u0026thinsp;0.75, 95% CI: 0.56\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.045) and MRE (OR\u0026thinsp;=\u0026thinsp;0.47, 95% CI: 0.23\u0026ndash;0.94) analyses, but not by the WM method (OR\u0026thinsp;=\u0026thinsp;0.70, 95% CI: 0.48\u0026ndash;1.02, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). At the genus level, \u003cem\u003eEisenbergiella\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;1.81, 95% CI: 1.16\u0026ndash;2.85, P\u0026thinsp;=\u0026thinsp;0.009; MRE, OR\u0026thinsp;=\u0026thinsp;1.13, 95% CI: 0.06\u0026ndash;20.45; WM, OR\u0026thinsp;=\u0026thinsp;1.90, 95% CI: 1.09\u0026ndash;3.30) and \u003cem\u003eLachnospiraceae_FCS020_group\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;1.71, 95% CI: 1.04\u0026ndash;2.83, P\u0026thinsp;=\u0026thinsp;0.034; MRE, OR\u0026thinsp;=\u0026thinsp;4.41, 95% CI: 1.44\u0026ndash;13.48; WM, OR\u0026thinsp;=\u0026thinsp;1.96, 95% CI: 0.99\u0026ndash;3.86) yielded a positive causal effect on EoE, while the \u003cem\u003eAnaerotruncus\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.23, 95% CI: 0.06\u0026ndash;0.85, P\u0026thinsp;=\u0026thinsp;0.027; MRE, OR\u0026thinsp;=\u0026thinsp;0.03, 95% CI: 0.00-16.47; WM, OR\u0026thinsp;=\u0026thinsp;0.26, 95% CI: 0.08\u0026ndash;0.82), \u003cem\u003eCoprococcus_1\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.41, 95% CI: 0.23\u0026ndash;0.73, P\u0026thinsp;=\u0026thinsp;0.002; MRE, OR\u0026thinsp;=\u0026thinsp;0.50, 95% CI: 0.12\u0026ndash;2.32; WM, OR\u0026thinsp;=\u0026thinsp;0.47, 95% CI: 0.22\u0026ndash;1.02), \u003cem\u003eHaemophilus\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.65, 95% CI: 0.45\u0026ndash;0.92, P\u0026thinsp;=\u0026thinsp;0.015; MRE, OR\u0026thinsp;=\u0026thinsp;0.41, 95% CI: 0.16\u0026ndash;1.04; WM, OR\u0026thinsp;=\u0026thinsp;0.58, 95% CI: 0.37\u0026ndash;0.90), \u003cem\u003eOxalobacter\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.75, 95% CI: 0.60\u0026ndash;0.92, P\u0026thinsp;=\u0026thinsp;0.006; MRE, OR\u0026thinsp;=\u0026thinsp;0.55, 95% CI: 0.25\u0026ndash;1.21; WM, OR\u0026thinsp;=\u0026thinsp;0.77, 95% CI: 0.58\u0026ndash;1.01) and \u003cem\u003eSubdoligranulum\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.54, 95% CI: 0.30\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.045; MRE, OR\u0026thinsp;=\u0026thinsp;0.51, 95% CI: 0.01\u0026ndash;25.66; WM, OR\u0026thinsp;=\u0026thinsp;0.54, 95% CI: 0.24\u0026ndash;1.21) demonstrated a protective effect on EoE (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eG-M).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eReverse analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003ePrimary results of the reverse analysis were detailed in Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e. EoE led to an increased abundance of the genus \u003cem\u003eEubacterium_nodatum_group\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;1.17, 95% CI: 1.07\u0026ndash;1.27, P\u0026thinsp;=\u0026thinsp;0.002; MRE, OR\u0026thinsp;=\u0026thinsp;1.08, 95% CI: 0.20\u0026ndash;1.96; WM, OR\u0026thinsp;=\u0026thinsp;1.16, 95% CI: 1.06\u0026ndash;1.26, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eA), but was causally associated with the depletion of family \u003cem\u003ePasteurellaceae\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.95, 95% CI: 0.90-1.00, P\u0026thinsp;=\u0026thinsp;0.042; MRE, OR\u0026thinsp;=\u0026thinsp;1.08, 95% CI: 0.72\u0026ndash;1.44; WM, OR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.90\u0026ndash;1.01, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eB), family \u003cem\u003eRuminococcaceae\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.97, 95% CI: 0.93-1.00, P\u0026thinsp;=\u0026thinsp;0.042; MRE, OR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.92-1.00; WM, OR\u0026thinsp;=\u0026thinsp;1.03, 95% CI: 0.81\u0026ndash;1.24, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eC), genus \u003cem\u003eRuminococcaceae_UCG003\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.92\u0026ndash;0.99, P\u0026thinsp;=\u0026thinsp;0.025; MRE, OR\u0026thinsp;=\u0026thinsp;1.01, 95% CI: 0.72\u0026ndash;1.31; WM, OR\u0026thinsp;=\u0026thinsp;0.95, 95% CI: 0.91-1.00, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eD), genus \u003cem\u003eCoprococcus_1\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.93-1.00, P\u0026thinsp;=\u0026thinsp;0.039; MRE, OR\u0026thinsp;=\u0026thinsp;0.90, 95% CI: 0.66\u0026ndash;1.14; WM, OR\u0026thinsp;=\u0026thinsp;0.95, 95% CI: 0.91-1.00, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eE) and genus \u003cem\u003eFaecalibacterium\u003c/em\u003e (IVW, OR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.93-1.00, P\u0026thinsp;=\u0026thinsp;0.033; MRE, OR\u0026thinsp;=\u0026thinsp;0.94, 95% CI: 0.73\u0026ndash;1.16; WM, OR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.92-1.00, Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSensitivity analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the forward MR (Table S5, Figure \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e), a significant heterogeneity and pleiotropic effect regarding the estimates of the order \u003cem\u003eDesulfovibrionales\u003c/em\u003e were detected by the Cochrane\u0026rsquo;s Q test (Q value\u0026thinsp;=\u0026thinsp;17.44, P\u0026thinsp;=\u0026thinsp;0.026) and the intercept of Egger regression (Egger intercept\u0026thinsp;=\u0026thinsp;0.095, P\u0026thinsp;=\u0026thinsp;0.040), respectively. The MR-PRESSO (P\u0026thinsp;=\u0026thinsp;0.044) and MR-Radial (P\u0026thinsp;=\u0026thinsp;0.026) methods further confirmed this result and identified the rs9928243 as the outlier. The sensitivity analysis was then performed after excluding the outlier, the protective effect became more significant as expected (IVW, OR\u0026thinsp;=\u0026thinsp;0.46, 95% CI: 0.32\u0026ndash;0.68, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the reverse MR, no heterogeneity or pleiotropic effect was detected (Table S5, Figure \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Causal relationship between cytokines and EoE (Part B)\u003c/h2\u003e \u003cp\u003e \u003cb\u003eSNPs selections\u003c/b\u003e \u003c/p\u003e \u003cp\u003eIn the forward analysis, 414 SNPs of 41 cytokines with MAF\u0026thinsp;\u0026gt;\u0026thinsp;1% and F-statistic\u0026thinsp;\u0026gt;\u0026thinsp;10 were screened as IVs (Table S6). In the reverse analysis, 10 independent SNPs correlated with EoE were filtered (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eForward analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAmong 41 cytokines (Table S7), the interleukin (IL)-12p70 (IVW, OR\u0026thinsp;=\u0026thinsp;1.17, 95% CI: 1.03\u0026ndash;1.31, P\u0026thinsp;=\u0026thinsp;0.028; MRE, OR\u0026thinsp;=\u0026thinsp;1.09, 95% CI: 0.86\u0026ndash;1.31; WM, OR\u0026thinsp;=\u0026thinsp;1.18, 95% CI: 1.02\u0026ndash;1.34, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eA) and IL-16 (IVW, OR\u0026thinsp;=\u0026thinsp;1.13, 95% CI: 1.02\u0026ndash;1.23, P\u0026thinsp;=\u0026thinsp;0.028; MRE, OR\u0026thinsp;=\u0026thinsp;1.11, 95% CI: 0.94\u0026ndash;1.27; WM, OR\u0026thinsp;=\u0026thinsp;1.13, 95% CI: 0.99\u0026ndash;1.27, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) exerted a positive casual effect on EoE, while the monokine induced by interferon-γ (MIG) demonstrated a protective effect on EoE (IVW, OR\u0026thinsp;=\u0026thinsp;0.82, 95% CI: 0.69\u0026ndash;0.95, P\u0026thinsp;=\u0026thinsp;0.002; MRE, OR\u0026thinsp;=\u0026thinsp;0.82, 95% CI: 0.94\u0026ndash;1.27; WM, OR\u0026thinsp;=\u0026thinsp;0.89, 95% CI: 0.73\u0026ndash;1.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003eC),.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eReverse analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003eReversely, EoE contributed to a declined level of cutaneous T-cell attracting chemokine (CTACK, IVW, OR\u0026thinsp;=\u0026thinsp;0.91, 95% CI: 0.84\u0026ndash;0.98, P\u0026thinsp;=\u0026thinsp;0.008; MRE, OR\u0026thinsp;=\u0026thinsp;0.87, 95% CI: 0.52\u0026ndash;1.21; WM, OR\u0026thinsp;=\u0026thinsp;0.93, 95% CI: 0.84\u0026ndash;1.02). No other significant result was revealed (Table S8).\u003c/p\u003e \u003cp\u003e \u003cb\u003eSensitivity analyses\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe sensitivity analyses detected no significant heterogeneity or pleiotropic effect was detected in bidirectional results (Table S9).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Mediation analysis (Part C)\u003c/h2\u003e \u003cp\u003eWe assumed that cytokines play a potential mediating role in the pathway from gut microbiota to EoE. We evaluated the casual relationship between bacterial taxa and cytokines with significant causal effects on EoE, and no significant causality was revealed (Table S10). Therefore, there was no suggestive evidence that cytokines are mediators between gut microbiota and EoE.\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eDespite the close correlation between gut microbiota and EoE, whether the alteration in microbiome is a cause or consequence of EoE is largely unclear. Recent publishment of EoE GWAS enabled us to use the genetic approach to identify the underlying causal relationship[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Using publicly available GWAS summary statistics, results of our two-sample MR analysis identified several bacterial taxa of various levels, which had significant causal relation with EoE.\u003c/p\u003e \u003cp\u003eAt the genus level, our findings indicate a positive causal effect of \u003cem\u003eEisenbergiella\u003c/em\u003e and \u003cem\u003eLachnospiraceae_FCS020_group\u003c/em\u003e on EoE. Despite a lack of direct and straightforward mechanism to explain how \u003cem\u003eEisenbergiella\u003c/em\u003e increases the risk of EoE, \u003cem\u003ethis genus\u003c/em\u003e has been linked with the risk of moderate to severe asthma and the severity of allergic rhinitis by previous studies[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], suggesting its pathogenic role in atopic diseases. The \u003cem\u003eLachnospiraceae_FCS020_group\u003c/em\u003e is a rare member of the family \u003cem\u003eLachnospiraceae. Lachnospiraceae\u003c/em\u003e is a core gut microbiome and plays a controversial role in human health and diseases. In inflammatory bowel disease (IBD), some genera exert a beneficial effect via butyrogenesis, while others harmful genera disrupt the mucus layer and promote bacterial translocation [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. We speculated that the overgrowth of \u003cem\u003eLachnospiraceae_FCS020_group\u003c/em\u003e may trigger inflammation in the GI tract by attenuating the beneficial effect from other butyrate-producing genera of the \u003cem\u003eLachnospiraceae.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eOn the other hand, several genera including \u003cem\u003eSubdoligranulum\u003c/em\u003e, \u003cem\u003eOxalobacter, Coprococcs_1, Anaerotruncus\u003c/em\u003e and \u003cem\u003eHaemophilus\u003c/em\u003e were found to have a protective effect on EoE. The depletion of \u003cem\u003eSubdoligranulum\u003c/em\u003e in infants around the age of weaning is correlated with children\u0026rsquo;s food allergy which is a main trigger or EoE[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Further mice experiment indicated that bacteriotherapy using \u003cem\u003eSubdoligranulum\u003c/em\u003e and \u003cem\u003eClostridiales\u003c/em\u003e species suppress food allergy via a regulatory T cell MyD88/RORγt pathway[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. \u003cem\u003eOxalobacter\u003c/em\u003e species maintain host oxalate homeostasis, with protection against oxalate-induced toxicity. The disruption of oxalate homeostasis is correlated with the development of multiple auto-immune diseases[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Genus \u003cem\u003eCoprococcus\u003c/em\u003e and \u003cem\u003eAnaerotruncus\u003c/em\u003e are butyrate-producing bacteria. As the metabolite of probiotics, butyrate plays an essential role in inhibiting GI inflammation and maintaining epithelial barrier integrity[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The protective effect of the genus \u003cem\u003eHaemophilus\u003c/em\u003e on EoE is in contrary to some of the results of previous studies[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. \u003cem\u003eHaemophilus\u003c/em\u003e in the respiratory tract activates IL-6 signaling pathway and therefore induces chronic airway inflammation[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. However, several studies have confirmed the role of IL-6 in promoting homeostasis and rapid tissue-protective responses in the gut[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], which partially explains the protective effect of \u003cem\u003eHaemophilus\u003c/em\u003e on EoE. To date, bacteriotherapy has been attempted in the treatment of atopic diseases[\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and IBD[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], and some clinical trials has accomplished satisfactory outcomes. Therefore, identifications of bacteria with a protective effect on EoE may help with the follow-up development of bacteriotherapy for EoE.\u003c/p\u003e \u003cp\u003eWe further explored the causality of cytokines on EoE and examined whether they play a mediating role between gut microbiota and EoE. Our results suggested that a higher circulating level of IL-12p70 and IL-16 levels is casually related to an increased risk of EoE. IL-16 is involved in CD4\u0026thinsp;+\u0026thinsp;cell recruitment and further enhances the expression of Th2 cytokines[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e], which has been identified as a potential biomarker in allergic diseases like atopic dermatitis[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. IL-12p70 is the dimeric form of IL-12 which binds to the IL-12 receptor and initiates the downstream signaling pathways. IL-12 induces intestinal inflammation and is a key target in the treatment of IBD[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], which is another chronic immune-mediated GI disease sharing overlapping pathogenesis with EoE. However, results of mediation analyses did not support the mediating effect of cytokines.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first MR study to assess the causal effect of gut microbiome and cytokines on EoE. The exposure data originated from the large-scale and widely used GWAS of human gut microbiome and circulating cytokines. The EoE dataset was obtained from a high-quality GWAS meta-analysis with an appropriate case-control ratio of 1:7, avoiding the bias caused by extremely unbalanced case-control ratio[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. In the creation of IVs, we excluded SNPs with potential linkage disequilibrium and weak strengths. To validate the credibility of our results, we employed various MR methods. Generally, a consistency of OR values among the three MR methods is observed. Additionally, sensitivity analyses detected small heterogeneity and pleiotropy of primary results, confirming the robustness of our findings. Inevitably, our study has limitations. Populations in all GWAS datasets are predominantly European, limiting the direct generalization of our findings to other ethnic populations. Since the GWAS of gut microbiome only provided summary data to the genus level, we were unable to further the analysis at the species level, which is underlined and feasible in the era of metagenomic sequencing. The GWAS data of EoE were generated based on children and adolescents. Though there is no evidence for the difference in genetic variants between pediatric and adult EoE patients, selection bias could not be fully excluded. Further research is warranted to resolve the above issues.\u003c/p\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eThis MR study identified bacteria that were causally associated with EoE at various taxonomic levels. Bacteria exerting a protective effect on EoE might be targets forfurther bacteriotherapy. Also, several cytokines causally correlated to EoE were revealed, but they seemed not to act as a mediating factor between gut microbiota and EoE. EoE reversely altered gut microbiome composition and levels of circulating cytokines. Of note, MR studies only generate evidence for causality from the genetic perspective rather than establishing causality straightforwardly. Further studies focusing on underlying mechanisms are still needed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEoE: eosinophilic esophagitis; MR: Mendelian randomization; GWAS: genome wide association study; IV: instrumental variable; Th: T helper; GI: gastrointestinal; SNP: single nucleotide polymorphism; IVW: inverse variance weighted; MRE: MR-Egger; WM: weighted median; OR: odds ratio; CI: confidence interval; MR-PRESSO: MR pleiotropy residual sum and outlier; IL: interleukin; MIG: monokine induced by interferon-γ; IBD: inflammatory bowel disease.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement:\u0026nbsp;\u003c/strong\u003eThe original contributions are included in the article/Supplementary Material. Further inquiries can be directed to the corresponding authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eRuoyu Ji contributed to study design, data collection, data processing, data analysis and wrote the manuscript draft. Yuxiang Zhi contributed to the initiation of the study, study design, and reviewed the manuscript draft. Both authors contributed to the interpretation of results and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e: This study is performed based on publicly available data. Ethical\u003c/p\u003e\n\u003cp\u003eapproval was granted for all the original studies included. No individual‑level data were generated. Therefore, the ethics approval was waived by the Ethics Committee of Peking Union Medical College Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding support:\u0026nbsp;\u003c/strong\u003eCAMS Innovation Fund for Medical Sciences (grant number, CIFMS 2021-I2M-1-003) and Beijing Natural Science Foundation (grant number L222082).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure of potential conflict of interest:\u003c/strong\u003e The authors declare that they have no relevant conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eNone.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eLiacouras, C.A., et al., \u003cem\u003eEosinophilic esophagitis: updated consensus recommendations for children and adults.\u003c/em\u003e J Allergy Clin Immunol, 2011. \u003cstrong\u003e128\u003c/strong\u003e(1): p. 3-20.e6; quiz 21-2.\u003c/li\u003e\n \u003cli\u003eDellon, E.S. and I. 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Haahtela, \u003cem\u003eNo effect of oral treatment with an intestinal bacterial strain, Lactobacillus rhamnosus (ATCC 53103), on birch-pollen allergy: a placebo-controlled double-blind study.\u003c/em\u003e Allergy, 2002. \u003cstrong\u003e57\u003c/strong\u003e(3): p. 243-6.\u003c/li\u003e\n \u003cli\u003eLiu, J., et al., \u003cem\u003eMucoadhesive probiotic backpacks with ROS nanoscavengers enhance the bacteriotherapy for inflammatory bowel diseases.\u003c/em\u003e Sci Adv, 2022. \u003cstrong\u003e8\u003c/strong\u003e(45): p. eabp8798.\u003c/li\u003e\n \u003cli\u003eLi, C., et al., \u003cem\u003eInterleukin-16 aggravates ovalbumin-induced allergic inflammation by enhancing Th2 and Th17 cytokine production in a mouse model.\u003c/em\u003e Immunology, 2019. \u003cstrong\u003e157\u003c/strong\u003e(3): p. 257-267.\u003c/li\u003e\n \u003cli\u003eFrezzolini, A., et al., \u003cem\u003eCirculating interleukin 16 (IL-16) in children with atopic/eczema dermatitis syndrome (AEDS): a novel serological marker of disease activity.\u003c/em\u003e Allergy, 2002. \u003cstrong\u003e57\u003c/strong\u003e(9): p. 815-20.\u003c/li\u003e\n \u003cli\u003eAngelova-Fischer, I., et al., \u003cem\u003eSignificance of interleukin-16, macrophage-derived chemokine, eosinophil cationic protein and soluble E-selectin in reflecting disease activity of atopic dermatitis--from laboratory parameters to clinical scores.\u003c/em\u003e Br J Dermatol, 2006. \u003cstrong\u003e154\u003c/strong\u003e(6): p. 1112-7.\u003c/li\u003e\n \u003cli\u003eVerstockt, B., et al., \u003cem\u003eIL-12 and IL-23 pathway inhibition in inflammatory bowel disease.\u003c/em\u003e Nat Rev Gastroenterol Hepatol, 2023. \u003cstrong\u003e20\u003c/strong\u003e(7): p. 433-446.\u003c/li\u003e\n \u003cli\u003eZhou, W., et al., \u003cem\u003eEfficiently controlling for case-control imbalance and sample relatedness in large-scale genetic association studies.\u003c/em\u003e Nat Genet, 2018. \u003cstrong\u003e50\u003c/strong\u003e(9): p. 1335-1341.\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Eosinophilic esophagitis, cytokines, gut microbiota, Mendelian randomization, causality","lastPublishedDoi":"10.21203/rs.3.rs-6635236/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6635236/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Observational studies have reported the correlation between gut microbiota, cytokines and eosinophilic esophagitis (EoE), but the underlying causal relationship remains largely unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We used the Mendelian randomization approach based on large-scale genome-wide association study datasets to evaluate the causal relationship between gut microbiota and EoE, and to identify whether cytokines play a mediating role. We applied the inverse variance weighted method as the primary analysis followed by several sensitivity analyses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: We identified five bacterial taxa at various levels and two cytokines which exerted a positive casual effect on EoE. Eight bacterial taxa and one cytokine were found to have a protective effect on EoE. Cytokines did not act as mediating factors from gut microbiota to EoE. Reversely, EoE altered the composition of microbiome and levels of circulating cytokines. Sensitivity analyses confirmed the robustness of primary results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Gut microbiota and cytokines were causally associated with EoE, and cytokines did not play a mediating role in the pathway from gut microbiota to EoE.\u003c/p\u003e","manuscriptTitle":"Gut Microbiota, Circulating Cytokines and Eosinophilic Esophagitis: A Comprehensive Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-14 06:02:41","doi":"10.21203/rs.3.rs-6635236/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1b377c81-b5a4-4000-a92a-368f1ee6d615","owner":[],"postedDate":"May 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-11T03:32:49+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-14 06:02:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6635236","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6635236","identity":"rs-6635236","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}