A bidirectional two-sample Mendelian randomization using the gut microbiota to reveal potential therapeutic targets for acute pancreatitis

A bidirectional two-sample Mendelian randomization using the gut microbiota to reveal potential therapeutic targets for acute pancreatitis | 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 Article A bidirectional two-sample Mendelian randomization using the gut microbiota to reveal potential therapeutic targets for acute pancreatitis Lin He, Haojun Luo, Yu Li, Jing Lu, Jinzhi Li, Li Peng, Yan Xu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4444933/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: Numerous studies have indicated a correlation between the gut microbiota (GM) and acute pancreatitis (AP), yet the precise causal relationship between them remains ambiguous. Methods: A two-sample Mendelian randomization (MR) study was conducted utilizing aggregated data from genome-wide association studies (GWASs) of 471 taxa (11 phyla, 19 orders, 24 orders, 62 families, 146 genera, and 209 species) and AP patients. Various methods, including inverse variance weighting (IVW), MR‒Egger, weighted medians, simple mode, and weighted mode, were employed to assess the causal association between the GM and AP. Sensitivity analyses were conducted utilizing Cochran's Q test, MR-Egger regression intercept analysis, and MR-PRESSO, followed by reverse MR analysis to evaluate the potential reverse causality between AP and GM. Results: Three gut microbial taxa were found to have significant associations with acute pancreatitis (AP). The inverse variance weighted (IVW) results revealed that Coprobacillus (OR 1.19, 95% CI 1.01 to 1.40, p=0.035) and Holdemania sp900120005 (OR 1.18, 95% CI 1.02 to 1.35, p=0.023) were identified as risk factors for the development of AP, while Megamonas (OR: 0.87, 95% CI: 0.77 to 0.98, p=0.023) was found to be a protective factor against the occurrence of AP. A thorough sensitivity analysis confirmed the reliability of our findings. Reverse Mendelian randomization (MR) analysis did not indicate any causal relationship between AP and the gut microbiota (GM). Conclusions: This study revealed a complex causal relationship between 3 GM taxa and AP, providing new evidence for the development of AP from a genetic perspective. Gut microbiota mendelian randomization causal effect genetic acute pancreatitis Figures Figure 1 Figure 2 Figure 3 1. Introduction Acute pancreatitis (AP) is a common acute abdominal illness with an annual incidence ranging between 13 and 45 per 100,000 individuals, with approximately 20–30% of cases classified as severe acute pancreatitis (SAP) and posing a potential threat to life [ 1 , 2 ]. There are several factors that can speed up the progression of pancreatitis. Previous research indicates that excessive alcohol consumption or the presence of gallstones accounts for approximately 80% of cases of acute pancreatitis [ 3 ]. As the global prevalence of acute pancreatitis rises, it has become evident that a significant proportion of cases remain idiopathic [ 4 ]. Thus, there is an urgent need for further investigation into the underlying pathogenic mechanisms of the disease. The gut microbiota is a critical factor in the maintenance of homeostasis [ 5 ], impacting various physiological functions such as metabolism and immune response through interactions with the host organism [ 6 , 7 ]. Dysbiosis in the gut microbiota, characterized by an imbalance in microbial acquisition and composition, has been linked to the development of metabolic and inflammatory diseases [ 8 , 9 ]. Emerging research suggests a correlation between gut microbiota dysbiosis and conditions such as hepatitis, coronary heart disease, diabetes, and pancreatitis [ 10 – 13 ]. Li et al. demonstrated in a mouse model of hypertriglyceridemic pancreatitis (HTGP) that gut microbiota colonization resulted in the recruitment of neutrophils and enhanced formation of neutrophil extracellular traps (NETs), ultimately exacerbating pancreatic injury and systemic inflammation [ 14 ]. Furthermore, Wang et al. discovered that lactulose alters the gut microbiota composition and stimulates the production of short-chain fatty acids, consequently mitigating the advancement of pancreatitis [ 15 ]. However, the specific regulatory mechanisms of gut microbes in pancreatitis remain to be elucidated. In the field of genetic epidemiology, Mendelian randomization (MR) is utilized as a method for investigating the unprejudiced influence of genetic variations on diseases [ 16 ]. The assignment of genotypes for single nucleotide polymorphisms (SNPs) is done randomly at conception in order to mitigate residual confounding [ 17 ]. A recent study by Wang et al. has begun to investigate the potential causal relationship between gut microbiota and AP [ 18 ]. Nevertheless, due to the constraints imposed by the small sample size of gut microbiota, there remain numerous unexplored avenues for research. In this research, we utilized genome-wide association study (GWAS) summary statistics from a study of 471 gut microbiota taxa that was recently published [ 19 ] to investigate the potential causal relationship between gut microbiota and acute pancreatitis (AP), with the goal of offering novel insights into the pathogenesis of AP. 2. Material & methods 2.1. Two-sample MR design In order to investigate the potential causal association between acute pancreatitis and gut microbiota, a two-sample Mendelian randomization (MR) study was carried out. The study adhered to three key assumptions commonly required in MR studies: (i) the instrumental variables (IVs) used must exhibit a strong association with the exposure factors, (ii) the IVs must be independent of any potential confounding factors, and (iii) the IVs must be exclusively linked to the outcomes being studied. The study procedure is outlined in Fig. 1 . Utilization of publicly available data negated the need for ethical approval in this analysis. 2.2. Data sources Genome-wide association study (GWAS) data from the FINRISK 2002 (FR02) study was utilized to examine the human gut microbiota as an exposure variable. The study encompassed 5959 participants, comprising both men and women aged 25 to 74 years in Finland. A total of 471 distinct Genome Taxonomy Database (GTDB) taxa were identified, encompassing 11 phyla, 19 orders, 24 classes, 62 families, 146 genera, and 209 species [ 19 ]. Comprehensive summary statistics of microbial taxa displaying genome-wide significant associations can be accessed through the NHGRI-EBI GWAS Catalog ( https://www.ebi.ac.uk/gwas/ ) spanning from accession GCST90032172 to GCST90032644. The GWAS summary data for Acute Pancreatitis (GWAS ID: ebi-a-GCST90018789) is available from the IEU open GWAS project ( https://gwas.mrcieu.ac.uk/ ), encompassing 3,798 cases and 476,104 controls. Ethical approval was not required for this study as all data utilized was publicly accessible. 2.3. Genetic instruments selection In order to establish the veracity of the causal association between gut microbiota and acute pancreatitis, adherence to rigorous quality control measures is imperative during the identification of suitable instrumental variables. (i)The selection criteria employed included the selection of SNPs linked to each taxa with a significance level of p < 1.0 × 10 − 5 ,thereby reducing the impact of sample size limitations and providing greater flexibility in terms of the nature of the exploratory study[ 21 ]. (ii) When evaluating the linkage disequilibrium (LD) between single nucleotide polymorphisms (SNPs), data from the European samples of the 1,000 Genome Project were utilized as a reference. Among SNPs with an R 2 value less than 0.001 (using a clustering window size of 10,000 kb), only those with the most statistically significant p-values were retained. (iii) Our Mendelian randomization (MR) analyses excluded palindromic SNPs with intermediate allele frequencies. (iv) The formula F=(R 2 /(R 2 -1))×((N-K-1)/K) was employed to identify instrumental variables (IVs) with F values exceeding 10, thereby eliminating potential biases associated with weak IVs. 2.4. Statistical analysis Mendelian randomization (MR) analysis was employed to ascertain potential causal relationships between 471 gut microbiota taxa and acute pancreatitis. Our analysis utilized five methods, namely inverse variance weighting (IVW), MR-Egger, weighted median, weighted mode, and simple mode techniques. In instances of discordant findings, IVW was prioritized as the primary outcome [ 22 ]. Heterogeneity was assessed and reported based on Cochran's Q test. MR Egger and MR-PRESSO tests were conducted to assess horizontal pleiotropy, with a p-value greater than 0.05 indicating the absence of horizontal pleiotropy [ 23 , 24 ]. In order to investigate potential sources of heterogeneity and assess the robustness of findings, a leave-one-out sensitivity analysis was employed. To examine the causal association between acute pancreatitis and various bacterial species, a reverse Mendelian randomization study was conducted, with pancreatitis as the exposure and gut microbes as the outcome variable. All statistical analyses were performed utilizing R version 4.3.2 and the TwoSampleMR R packages. 3. Results 3.1 Two-sample Mendelian randomization A causal relationship between three gut microbiota taxa and AP was established through a rigorous quality control process, resulting in the identification of 87 independent SNPs. The mean F-statistics value for these gut microbiota taxa was 22.74, all exceeding the threshold of 10, indicating minimal susceptibility to weak instrumental bias (Supplementary Table S1 ). This study provides evidence supporting the association between specific gut microbiota taxa and AP. While a correlation was identified, it did not retain significance after undergoing multiple testing correction using the False Discovery Rate (FDR) method (pFDR = 0.0001). Nevertheless, the results did show nominal significance when the p-value was < 0.05. 3.2 Causal effects of gut microbiota on AP In this study, we conducted a screening of three gut microbiota to assess their correlation with acute pancreatitis (AP) using the inverse variance weighted (IVW) method. Our analysis revealed that Coprobacillus (OR: 1.19, 95% CI: 1.01–1.40, p = 0.035) and Holdemania sp900120005 (OR: 1.18, 95% CI: 1.02–1.35, p = 0.023) were associated with an increased risk of AP, while Megamonas (OR: 0.87, 95% CI: 0.77–0.98, p = 0.023) showed a negative correlation with AP. Additionally, the results obtained from the other four Mendelian randomization analysis methods were consistent with those from the IVW method (Table 1 ). Table 1 MR results of causal links between gut microbiota and acute pancreatitis (p < 1 × 10 − 5 ). Bacterial taxa Nsnp Method Beta SE P-value OR(CI) F-statistic Coprobacillus 21 IVW 0.17 0.08 0.035 1.19 (1.01–1.40) 23.16 Coprobacillus 21 MR Egger 0.14 0.18 0.460 1.15 (0.80–1.63) Coprobacillus 21 Weighted median 0.17 0.12 0.152 1.18 (0.94–1.48) Coprobacillus 21 Simple mode 0.29 0.23 0.217 1.33 (0.86–2.07) Coprobacillus 21 Weighted mode 0.28 0.21 0.209 1.32(0.87-2.00) Holdemania sp900120005 19 IVW 0.16 0.07 0.023 1.18(1.02–1.35) 22.89 Holdemania sp900120005 19 MR Egger 0.09 0.20 0.646 1.10(0.74–1.63) Holdemania sp900120005 19 Weighted median 0.20 0.10 0.036 1.23(1.01–1.49) Holdemania sp900120005 19 Simple mode 0.26 0.18 0.159 1.30(0.92–1.85) Holdemania sp900120005 19 Weighted mode 0.26 0.18 0.164 1.29(0.91–1.82) Megamonas 46 IVW -0.14 0.06 0.023 0.87(0.77–0.98) 22.50 Megamonas 46 MR Egger -0.11 0.12 0.342 0.89(0.71–1.12) Megamonas 46 Weighted median -0.12 0.09 0.157 0.88(0.74–1.05) Megamonas 46 Simple mode -0.16 0.17 0.352 0.86(0.62–1.18) Megamonas 46 Weighted mode -0.12 0.14 0.417 0.89(0.68–1.17) MR, Mendelian randomization; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval, IVW, inverse variance weighted. 3.3 Sensitivity analysis The analyses of Rucker's Q statistic and Cochran's Q statistic indicated that there was no significant heterogeneity among the three gut microbiota and AP (p > 0.05). Furthermore, the MR-Egger regression test for intercept revealed no evidence of horizontal pleiotropy (p > 0.05) (Table 2 ). Through a "leave-one-out" sensitivity analysis, the robustness and reliability of our conclusion were confirmed (Fig. 2 – 3 ). Additionally, the MR-PRESSO global test did not detect any horizontal pleiotropy (Supplementary Table S2 ). Table 2 Sensitivity analysis between gut microbiome and acute pancreatitis Exposure Heterogeneity Horizontal pleiotropy Rucker’s Q MR-Egger P-value Cochran’s Q IVW P-value Egger-intercept MR-Egger SE P-value Coprobacillus 16.153 0.647 16.212 0.703 0.005 0.021 0.810 Holdemania sp900120005 19.637 0.293 19.788 0.344 0.008 0.021 0.722 Megamonas 52.715 0.173 52.833 0.197 -0.004 0.013 0.756 MR, Mendelian randomization; SE, standard error; IVW, inverse variance weighted. 3.4 Reverse MR analysis Inverse MR analysis was conducted on three gut microbiota in this study. The findings indicated a lack of statistically significant association between acute pancreatitis and the three gut microbiota, as demonstrated in Supplementary Table S3 . 4. Discussion In recent years, there has been a notable increase in the incidence of acute pancreatitis [ 25 ], with the risk of severe cases continuing to rise [ 26 ]. While factors such as gallstones, hyperlipidemia, and alcohol consumption are recognized as common etiologic factors [ 27 , 28 ], a significant proportion of acute pancreatitis cases lack clear identifiable causes in clinical practice [ 29 ]. Recent research has increasingly highlighted the interconnected relationship between gut microbes and acute pancreatitis. Christoph et al. conducted a study involving 420 patients with acute pancreatitis, identifying a notable association between 16 gut microbiota and the severity of systemic inflammatory response syndrome [ 30 ]. Liu et al. demonstrated the potential therapeutic effects of gut microbiota-derived nicotinamide mononucleotide in alleviating acute pancreatitis through the activation of pancreatic SIRT3 signalling [ 31 ]. Li et al. observed that fecal microbiota transplantation (FMT) reactivates intestinal NLRP3 inflammatory vesicles, exacerbating disease in antibiotic treated (Abx) and germ-free (GF) mice [ 32 ]. Nevertheless, the precise relationship between AP and GM remains uncertain due to the small sample size of observational studies and the numerous confounding variables. This study utilized two-sample Mendelian randomization analysis to investigate the potential causal relationship between two sets of samples, utilizing the most recent genome-wide association study data on 471 gut microbiota taxa as exposures. The analysis was conducted from a genetic perspective, revealing a significant causal relationship between three specific gut microbiota taxa (Coprobacillus, Holdemania sp900120005, Megamonas) and acute pancreatitis (AP). These findings offer novel therapeutic targets for the treatment of AP. Imbalances in the gut microbiota have been closely associated with abnormal lipid metabolism and obesity [ 33 ]. Recent research has identified an overexpression of Coprobacillus in mice fed a high-fat diet, which may contribute to an increase in colon cancer multiplicity. However, treatment with non-steroidal anti-inflammatory drugs has been shown to significantly reduce these effects, potentially reversing some of the consequences of chronic obesity and tumor diversity [ 34 ]. Elena et al. observed a cumulative effect of a high-fat diet in 3xtg mice, wherein an increase in Coprobacillus abundance was concomitant with the overexpression of inflammatory metabolites such as unsaturated fatty acids, ketone bodies, lactate, and TMAO [ 35 ]. It is noteworthy that high lipid metabolism is significantly implicated in the pathogenesis of acute pancreatitis [ 36 , 37 ]. Furthermore, the presence of Coprobacillus has been identified in various non-infectious inflammatory diseases [ 38 ]. The onset of acute pancreatitis (AP) is commonly associated with aseptic inflammation resulting from pancreatic tissue damage caused by excessive production of pancreatic enzymes, leading to self-digestion [ 39 ]. Nevertheless, Zhang et al. observed that baicalin administration decreased the expression of immune-related genes, such as Th1 and Th17, ameliorated intestinal inflammation, and promoted the proliferation of Coprobacillus in a murine model of high-dose antibiotic-induced intestinal inflammation [ 40 ]. This paradoxical outcome may be attributed to the disruption of microbial homeostasis in the initial gut environment caused by the extensive administration of antibiotics, leading to varying levels of mutations in the gut microbiota, thereby highlighting the diversity of Coprobacillus. Our research has revealed that Coprobacillus functions as a pathogenic bacterium that could potentially exacerbate the development of acute pancreatitis. Holdemania sp900120005 belongs to Holdemania. Holdemania is a pathogenic bacterium that has been found in various environments and poses a potential threat to human health [ 41 ]. Studies have shown an elevated presence of Holdemania in inflammatory and psychiatric disorders, indicating its pathogenic nature [ 42 – 44 ]. In a study conducted by Bjørkhaug et al., the impact of alcohol on gut microbiota functioning was investigated by comparing 24 patients with alcohol overdose to 18 control subjects. The study revealed an increased expression of Holdemania in the alcohol overdose group, with no significant association observed with short-chain fatty acids (SCFA) [ 45 ]. Notably, alcohol is recognized as a primary causative agent in acute pancreatitis [ 46 , 47 ]. Furthermore, Raimondi et al. demonstrated the involvement of Holdemania in mucin degradation, a crucial component of the intestinal barrier, with excessive degradation potentially exacerbating the systemic inflammatory response [ 48 ]. These findings suggest a potential mediating role of Holdemania in the relationship between alcohol consumption and acute pancreatitis. Megamonas, a genus of beneficial bacteria belonging to the Firmicutes phylum [ 49 ], is involved in the metabolism of the organism through the fermentation of carbohydrates to produce short-chain fatty acids (SCFA) [ 50 ]. These SCFAs, such as acetate, propionate, and butyrate, are essential for maintaining intestinal homeostasis [ 51 , 52 ]and have been shown to have significant anti-inflammatory effects in various inflammatory diseases [ 53 – 55 ]. Jing et al. demonstrated that supplementation with short-chain fatty acids (SCFA) led to the down-regulation of the NF-κB signaling pathway, resulting in decreased inflammation and improved neural tissue function [ 56 ]. In a separate study, Li et al. observed that oral anticoagulants (OACs) altered the composition of gut microbiota, specifically increasing the abundance of Megamonas and decreasing pro-inflammatory colonies in patients with atrial fibrillation (AF). This shift in microbiota was associated with reduced thrombosis and highlighted the potential modulatory role of Megamonas in abnormal lipid metabolism [ 57]. In conclusion, our findings reinforce the aforementioned conclusions and identify novel therapeutic targets for the management of acute pancreatitis. Recent studies have highlighted a potential causal link between gut microbiota and AP [ 58,59]. However, due to the small sample size in previous research, further investigation is warranted. This study aims to delve deeper into this relationship by analyzing 471 updated gut microbiota samples, thus enhancing the reliability of our findings. This study is subject to several limitations. While our research aligns with the MR hypothesis, it does not definitively establish a weak tool bias. Additionally, our findings would benefit from validation through additional experimental studies. 5. Conclusions In conclusion, our study has identified a notable causal association between three specific intestinal microbiota and acute pancreatitis (AP), thereby contributing novel insights into the genetic basis of AP pathogenesis. Declarations Data availability statement This study analysed publicly available datasets. The primary summary statistics for the gut microbiome can be accessed through the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas/) spanning from accession GCST90032172 to GCST90032644, and the AP dataset is accessible at https://gwas.mrcieu.ac.uk/. Ethics approval and consent to participate Ethical approval was obtained for all included original GWASs, which did not violate any of the ethical requirements. Author contributions LH conceived the study, conducted the data analysis, and authored the manuscript. HJL and YL contributed to the experimental design and participated in the revision of the manuscript. JL, JZL, LP,and YX provided valuable assistance in the data analysis. HL was involved in the design of the experimental methods and provided critical review and editing of the manuscript. All authors contributed to the article and approved the submitted version. Acknowledgements The authors thank the participants of all GWAS cohorts included in the present work and the investigators of the FINRISK 2002 and IEU open GWAS project initiatives for sharing the GWAS summary statistics. 10. Funding This research was supported by the National Natural Science Foundation of China (82072938) and the Sichuan Provincial Administration of Traditional Chinese Medicine Project (2023MS511). 11. Conflicts of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest. References Guo X. Y., Xiao F., Li J, et al.. (2019). Exosomes and pancreatic diseases: status, challenges, and hopes. 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Cancer 144 (11), 2728–2745. doi: 10.1002/ijc.32007 Morrison DJ, Preston T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes. 2016 May 3;7(3):189-200. doi: 10.1080/19490976.2015.1134082. Epub 2016 Mar 10. Martin-Gallausiaux C, Marinelli L, et al. SCFA: mechanisms and functional importance in the gut. Proc Nutr Soc. 2021 Feb;80(1):37-49. doi: 10.1017/S0029665120006916. Epub 2020 Apr 2. Wang F, Qian F, Zhang Q,et al. The reduced SCFA-producing gut microbes are involved in the inflammatory activation in Kawasaki disease. Front Immunol. 2023 Jun 15;14:1124118. doi: 10.3389/fimmu.2023.1124118. Nogal A, Asnicar F, Vijay A, et al. Genetic and gut microbiome determinants of SCFA circulating and fecal levels, postprandial responses and links to chronic and acute inflammation. Gut Microbes. 2023 Jan-Dec;15(1):2240050. doi: 10.1080/19490976.2023.2240050. Zahedi E, Sadr SS, Sanaeierad A,et al. Chronic acetyl-L-carnitine treatment alleviates behavioral deficits and neuroinflammation through enhancing microbiota derived-SCFA in valproate model of autism. Biomed Pharmacother. 2023 Jul;163:114848. doi: 10.1016/j.biopha.2023.114848. Epub 2023 May 8. Jing Y, Yang D, Bai F,et al. Spinal cord injury-induced gut dysbiosis influences neurological recovery partly through short-chain fatty acids. NPJ Biofilms Microbiomes. 2023 Dec 14;9(1):99. doi: 10.1038/s41522-023-00466-5. Li W, Li C, Ren C, et al. Bidirectional effects of oral anticoagulants on gut microbiota in patients with atrial fibrillation. Front Cell Infect Microbiol. 2023 Mar 24;13:1038472. doi: 10.3389/fcimb.2023.1038472. Yan C, Bao J, Jin J. Exploring the interplay of gut microbiota, inflammation, and LDL-cholesterol: a multiomics Mendelian randomization analysis of their causal relationship in acute pancreatitis and non-alcoholic fatty liver disease. J Transl Med. 2024 Feb 19;22(1):179. doi: 10.1186/s12967-024-04996-0. Wang K, Qin X, et al. Causal link between gut microbiota and four types of pancreatitis: a genetic association and bidirectional Mendelian randomization study. Front Microbiol. 2023 Nov 23;14:1290202. doi: 10.3389/fmicb.2023.1290202. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTableS1.xlsx Table S1. Instrument Variables for main gut microbiota taxa. SupplementaryTableS2.xlsx Table S2. MR-PRESSO analysis for the association between gut microbiota and acute pancreatitis. SupplementaryTableS3.xlsx Table S3. Reverse MR analysis for the causal effect of acute pancreatitis on gut microbiota. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-4444933","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":317931466,"identity":"17097df3-cb0c-4422-b9dc-b496f889504a","order_by":0,"name":"Lin He","email":"","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"He","suffix":""},{"id":317931467,"identity":"1a42abab-68b2-4ebf-a830-ee4baf4dae35","order_by":1,"name":"Haojun Luo","email":"","orcid":"","institution":"The Second Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haojun","middleName":"","lastName":"Luo","suffix":""},{"id":317931468,"identity":"4239ab00-01c5-4897-b451-bf3b968eed8c","order_by":2,"name":"Yu Li","email":"","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Li","suffix":""},{"id":317931469,"identity":"03d88122-2aa0-43ce-b77f-21832cd9a444","order_by":3,"name":"Jing Lu","email":"","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Lu","suffix":""},{"id":317931470,"identity":"8c27017a-4911-458d-9dc7-19554ffb4d10","order_by":4,"name":"Jinzhi Li","email":"","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":false,"prefix":"","firstName":"Jinzhi","middleName":"","lastName":"Li","suffix":""},{"id":317931471,"identity":"e58024fa-118d-416b-a4f5-2b4b642b6a84","order_by":5,"name":"Li Peng","email":"","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Peng","suffix":""},{"id":317931472,"identity":"e73ba92e-7b75-488c-8613-8c512515cea8","order_by":6,"name":"Yan Xu","email":"","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Xu","suffix":""},{"id":317931473,"identity":"9a3b8614-f42d-4b77-b40e-e45d4331561b","order_by":7,"name":"Hang Liu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYBACAxDxwICBsYG9sfHhB6K1JIC08BxuNpYgXgsDUItEepsADzFazNnPHn6RUHBYdsPNh20MEgx2croNBLRY9uSlWSQYHDbecDux7UEBQ7Kx2QFCDjuQY2YA1JII1NJuIMFwIHEbQS3n30C13DzYJsFDlJYbOcYPwFpuMBKt5Y0ZMJDTjWeeSQQGsgExfjmfY/zhwx9r2b7jxx8+/FBhJ0dQCxCwgSNQAazSgLByEGAGJxP5BuJUj4JRMApGwQgEAAFhS/Nx96WsAAAAAElFTkSuQmCC","orcid":"","institution":"People’s Hospital of Deyang City","correspondingAuthor":true,"prefix":"","firstName":"Hang","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-05-19 15:39:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4444933/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4444933/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":59293151,"identity":"3edc83c2-60a8-4c74-a7c9-5ff957bcbf53","added_by":"auto","created_at":"2024-06-28 19:00:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":190717,"visible":true,"origin":"","legend":"\u003cp\u003eOverview of the Mendelian randomization framework used to investigate the causal effect of the gut microbiota on acute pancreatitis.\u003c/p\u003e","description":"","filename":"Fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/324e0c2f6a04f98519ddb6f0.png"},{"id":59292349,"identity":"2a371967-a931-42a9-adcb-7316cc75830c","added_by":"auto","created_at":"2024-06-28 18:52:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":98256,"visible":true,"origin":"","legend":"\u003cp\u003e“Leave-one-out” analysis. The red lines are the analysis results of random effects IVW. (A) Coprobacillus and acute pancreatitis; (B) Holdemania sp900120005 and acute pancreatitis; (C) Megamonas and acute pancreatitis;\u003c/p\u003e","description":"","filename":"Fig.2.png","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/636a3fb4fd201b14db0c8e28.png"},{"id":59293152,"identity":"bc4f9e69-0624-4bd7-888e-448532164816","added_by":"auto","created_at":"2024-06-28 19:00:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":122582,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots of the MR analyses for the association of three gut microbiota taxa and the risk of AP. (A) Causal effect of Coprobacillus on AP; (B) Causal effect of Holdemania sp900120005 on AP; (C) Causal effect of Megamonas on AP;\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/3d2a6bb38ed298b40a467455.png"},{"id":71522930,"identity":"abd5c6f2-d079-4ca8-b3c6-afde290759cd","added_by":"auto","created_at":"2024-12-16 12:01:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":922502,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/c3b69afd-a8a6-4dc5-a24e-6b7ac65bec56.pdf"},{"id":59292351,"identity":"5e828888-46d4-4ebc-a8a5-aa12eda72fea","added_by":"auto","created_at":"2024-06-28 18:52:44","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33213,"visible":true,"origin":"","legend":"\u003cp\u003eTable S1. Instrument Variables for main gut microbiota taxa.\u003c/p\u003e","description":"","filename":"SupplementaryTableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/83ef144a4a2158ea9cdb714e.xlsx"},{"id":59293494,"identity":"28d92b72-46ca-41fd-a1e9-7e09a0c13092","added_by":"auto","created_at":"2024-06-28 19:08:44","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10144,"visible":true,"origin":"","legend":"\u003cp\u003eTable S2. MR-PRESSO analysis for the association between gut microbiota and acute pancreatitis.\u003c/p\u003e","description":"","filename":"SupplementaryTableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/73738ec8aa0fccd2108747f8.xlsx"},{"id":59292354,"identity":"c1b6b912-4396-4e39-bd47-00fc56325744","added_by":"auto","created_at":"2024-06-28 18:52:44","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":10580,"visible":true,"origin":"","legend":"\u003cp\u003eTable S3. Reverse MR analysis for the causal effect of acute pancreatitis on gut microbiota.\u003c/p\u003e","description":"","filename":"SupplementaryTableS3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4444933/v1/cb06d4770a4592a96eb867b9.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A bidirectional two-sample Mendelian randomization using the gut microbiota to reveal potential therapeutic targets for acute pancreatitis","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAcute pancreatitis (AP) is a common acute abdominal illness with an annual incidence ranging between 13 and 45 per 100,000 individuals, with approximately 20\u0026ndash;30% of cases classified as severe acute pancreatitis (SAP) and posing a potential threat to life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. There are several factors that can speed up the progression of pancreatitis. Previous research indicates that excessive alcohol consumption or the presence of gallstones accounts for approximately 80% of cases of acute pancreatitis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. As the global prevalence of acute pancreatitis rises, it has become evident that a significant proportion of cases remain idiopathic [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Thus, there is an urgent need for further investigation into the underlying pathogenic mechanisms of the disease.\u003c/p\u003e \u003cp\u003eThe gut microbiota is a critical factor in the maintenance of homeostasis [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], impacting various physiological functions such as metabolism and immune response through interactions with the host organism [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Dysbiosis in the gut microbiota, characterized by an imbalance in microbial acquisition and composition, has been linked to the development of metabolic and inflammatory diseases [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Emerging research suggests a correlation between gut microbiota dysbiosis and conditions such as hepatitis, coronary heart disease, diabetes, and pancreatitis [\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Li et al. demonstrated in a mouse model of hypertriglyceridemic pancreatitis (HTGP) that gut microbiota colonization resulted in the recruitment of neutrophils and enhanced formation of neutrophil extracellular traps (NETs), ultimately exacerbating pancreatic injury and systemic inflammation [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, Wang et al. discovered that lactulose alters the gut microbiota composition and stimulates the production of short-chain fatty acids, consequently mitigating the advancement of pancreatitis [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, the specific regulatory mechanisms of gut microbes in pancreatitis remain to be elucidated.\u003c/p\u003e \u003cp\u003eIn the field of genetic epidemiology, Mendelian randomization (MR) is utilized as a method for investigating the unprejudiced influence of genetic variations on diseases [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The assignment of genotypes for single nucleotide polymorphisms (SNPs) is done randomly at conception in order to mitigate residual confounding [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A recent study by Wang et al. has begun to investigate the potential causal relationship between gut microbiota and AP [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Nevertheless, due to the constraints imposed by the small sample size of gut microbiota, there remain numerous unexplored avenues for research. In this research, we utilized genome-wide association study (GWAS) summary statistics from a study of 471 gut microbiota taxa that was recently published [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] to investigate the potential causal relationship between gut microbiota and acute pancreatitis (AP), with the goal of offering novel insights into the pathogenesis of AP.\u003c/p\u003e"},{"header":"2. Material \u0026 methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Two-sample MR design\u003c/h2\u003e \u003cp\u003eIn order to investigate the potential causal association between acute pancreatitis and gut microbiota, a two-sample Mendelian randomization (MR) study was carried out. The study adhered to three key assumptions commonly required in MR studies: (i) the instrumental variables (IVs) used must exhibit a strong association with the exposure factors, (ii) the IVs must be independent of any potential confounding factors, and (iii) the IVs must be exclusively linked to the outcomes being studied. The study procedure is outlined in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Utilization of publicly available data negated the need for ethical approval in this analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data sources\u003c/h2\u003e \u003cp\u003eGenome-wide association study (GWAS) data from the FINRISK 2002 (FR02) study was utilized to examine the human gut microbiota as an exposure variable. The study encompassed 5959 participants, comprising both men and women aged 25 to 74 years in Finland. A total of 471 distinct Genome Taxonomy Database (GTDB) taxa were identified, encompassing 11 phyla, 19 orders, 24 classes, 62 families, 146 genera, and 209 species [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Comprehensive summary statistics of microbial taxa displaying genome-wide significant associations can be accessed through the NHGRI-EBI GWAS Catalog (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/gwas/\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/gwas/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) spanning from accession GCST90032172 to GCST90032644. The GWAS summary data for Acute Pancreatitis (GWAS ID: ebi-a-GCST90018789) is available from the IEU open GWAS project (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), encompassing 3,798 cases and 476,104 controls. Ethical approval was not required for this study as all data utilized was publicly accessible.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Genetic instruments selection\u003c/h2\u003e \u003cp\u003eIn order to establish the veracity of the causal association between gut microbiota and acute pancreatitis, adherence to rigorous quality control measures is imperative during the identification of suitable instrumental variables. (i)The selection criteria employed included the selection of SNPs linked to each taxa with a significance level of p\u0026thinsp;\u0026lt;\u0026thinsp;1.0 \u0026times; 10 \u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e ,thereby reducing the impact of sample size limitations and providing greater flexibility in terms of the nature of the exploratory study[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. (ii) When evaluating the linkage disequilibrium (LD) between single nucleotide polymorphisms (SNPs), data from the European samples of the 1,000 Genome Project were utilized as a reference. Among SNPs with an R\u003csup\u003e2\u003c/sup\u003e value less than 0.001 (using a clustering window size of 10,000 kb), only those with the most statistically significant p-values were retained. (iii) Our Mendelian randomization (MR) analyses excluded palindromic SNPs with intermediate allele frequencies. (iv) The formula F=(R\u003csup\u003e2\u003c/sup\u003e/(R\u003csup\u003e2\u003c/sup\u003e-1))\u0026times;((N-K-1)/K) was employed to identify instrumental variables (IVs) with F values exceeding 10, thereby eliminating potential biases associated with weak IVs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical analysis\u003c/h2\u003e \u003cp\u003eMendelian randomization (MR) analysis was employed to ascertain potential causal relationships between 471 gut microbiota taxa and acute pancreatitis. Our analysis utilized five methods, namely inverse variance weighting (IVW), MR-Egger, weighted median, weighted mode, and simple mode techniques. In instances of discordant findings, IVW was prioritized as the primary outcome [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Heterogeneity was assessed and reported based on Cochran's Q test. MR Egger and MR-PRESSO tests were conducted to assess horizontal pleiotropy, with a p-value greater than 0.05 indicating the absence of horizontal pleiotropy [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In order to investigate potential sources of heterogeneity and assess the robustness of findings, a leave-one-out sensitivity analysis was employed. To examine the causal association between acute pancreatitis and various bacterial species, a reverse Mendelian randomization study was conducted, with pancreatitis as the exposure and gut microbes as the outcome variable. All statistical analyses were performed utilizing R version 4.3.2 and the TwoSampleMR R packages.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Two-sample Mendelian randomization\u003c/h2\u003e \u003cp\u003eA causal relationship between three gut microbiota taxa and AP was established through a rigorous quality control process, resulting in the identification of 87 independent SNPs. The mean F-statistics value for these gut microbiota taxa was 22.74, all exceeding the threshold of 10, indicating minimal susceptibility to weak instrumental bias (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). This study provides evidence supporting the association between specific gut microbiota taxa and AP. While a correlation was identified, it did not retain significance after undergoing multiple testing correction using the False Discovery Rate (FDR) method (pFDR\u0026thinsp;=\u0026thinsp;0.0001). Nevertheless, the results did show nominal significance when the p-value was \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Causal effects of gut microbiota on AP\u003c/h2\u003e \u003cp\u003eIn this study, we conducted a screening of three gut microbiota to assess their correlation with acute pancreatitis (AP) using the inverse variance weighted (IVW) method. Our analysis revealed that Coprobacillus (OR: 1.19, 95% CI: 1.01\u0026ndash;1.40, p\u0026thinsp;=\u0026thinsp;0.035) and Holdemania sp900120005 (OR: 1.18, 95% CI: 1.02\u0026ndash;1.35, p\u0026thinsp;=\u0026thinsp;0.023) were associated with an increased risk of AP, while Megamonas (OR: 0.87, 95% CI: 0.77\u0026ndash;0.98, p\u0026thinsp;=\u0026thinsp;0.023) showed a negative correlation with AP. Additionally, the results obtained from the other four Mendelian randomization analysis methods were consistent with those from the IVW method (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMR results of causal links between gut microbiota and acute pancreatitis (p\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBacterial taxa\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNsnp\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR(CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF-statistic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoprobacillus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.19 (1.01\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e23.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoprobacillus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.15 (0.80\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoprobacillus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.18 (0.94\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoprobacillus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.33 (0.86\u0026ndash;2.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoprobacillus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.32(0.87-2.00)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoldemania sp900120005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.18(1.02\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e22.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoldemania sp900120005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.646\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.10(0.74\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoldemania sp900120005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.23(1.01\u0026ndash;1.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoldemania sp900120005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.30(0.92\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoldemania sp900120005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.29(0.91\u0026ndash;1.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMegamonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.87(0.77\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e22.50\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMegamonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.89(0.71\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMegamonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted median\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.88(0.74\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMegamonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSimple mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.86(0.62\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMegamonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.89(0.68\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eMR, Mendelian randomization; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence interval, IVW, inverse variance weighted.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sensitivity analysis\u003c/h2\u003e \u003cp\u003eThe analyses of Rucker's Q statistic and Cochran's Q statistic indicated that there was no significant heterogeneity among the three gut microbiota and AP (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Furthermore, the MR-Egger regression test for intercept revealed no evidence of horizontal pleiotropy (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Through a \"leave-one-out\" sensitivity analysis, the robustness and reliability of our conclusion were confirmed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Additionally, the MR-PRESSO global test did not detect any horizontal pleiotropy (Supplementary Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSensitivity analysis between gut microbiome and acute pancreatitis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eHeterogeneity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eHorizontal pleiotropy\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRucker\u0026rsquo;s Q\u003c/p\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCochran\u0026rsquo;s Q\u003c/p\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEgger-intercept\u003c/p\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoprobacillus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.810\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHoldemania sp900120005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.788\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMegamonas\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eMR, Mendelian randomization; SE, standard error; IVW, inverse variance weighted.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Reverse MR analysis\u003c/h2\u003e \u003cp\u003eInverse MR analysis was conducted on three gut microbiota in this study. The findings indicated a lack of statistically significant association between acute pancreatitis and the three gut microbiota, as demonstrated in Supplementary Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn recent years, there has been a notable increase in the incidence of acute pancreatitis [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e], with the risk of severe cases continuing to rise [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. While factors such as gallstones, hyperlipidemia, and alcohol consumption are recognized as common etiologic factors [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], a significant proportion of acute pancreatitis cases lack clear identifiable causes in clinical practice [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Recent research has increasingly highlighted the interconnected relationship between gut microbes and acute pancreatitis. Christoph et al. conducted a study involving 420 patients with acute pancreatitis, identifying a notable association between 16 gut microbiota and the severity of systemic inflammatory response syndrome [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Liu et al. demonstrated the potential therapeutic effects of gut microbiota-derived nicotinamide mononucleotide in alleviating acute pancreatitis through the activation of pancreatic SIRT3 signalling [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Li et al. observed that fecal microbiota transplantation (FMT) reactivates intestinal NLRP3 inflammatory vesicles, exacerbating disease in antibiotic treated (Abx) and germ-free (GF) mice [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Nevertheless, the precise relationship between AP and GM remains uncertain due to the small sample size of observational studies and the numerous confounding variables.\u003c/p\u003e \u003cp\u003eThis study utilized two-sample Mendelian randomization analysis to investigate the potential causal relationship between two sets of samples, utilizing the most recent genome-wide association study data on 471 gut microbiota taxa as exposures. The analysis was conducted from a genetic perspective, revealing a significant causal relationship between three specific gut microbiota taxa (Coprobacillus, Holdemania sp900120005, Megamonas) and acute pancreatitis (AP). These findings offer novel therapeutic targets for the treatment of AP.\u003c/p\u003e \u003cp\u003eImbalances in the gut microbiota have been closely associated with abnormal lipid metabolism and obesity [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Recent research has identified an overexpression of Coprobacillus in mice fed a high-fat diet, which may contribute to an increase in colon cancer multiplicity. However, treatment with non-steroidal anti-inflammatory drugs has been shown to significantly reduce these effects, potentially reversing some of the consequences of chronic obesity and tumor diversity [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Elena et al. observed a cumulative effect of a high-fat diet in 3xtg mice, wherein an increase in Coprobacillus abundance was concomitant with the overexpression of inflammatory metabolites such as unsaturated fatty acids, ketone bodies, lactate, and TMAO [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. It is noteworthy that high lipid metabolism is significantly implicated in the pathogenesis of acute pancreatitis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Furthermore, the presence of Coprobacillus has been identified in various non-infectious inflammatory diseases [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The onset of acute pancreatitis (AP) is commonly associated with aseptic inflammation resulting from pancreatic tissue damage caused by excessive production of pancreatic enzymes, leading to self-digestion [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Nevertheless, Zhang et al. observed that baicalin administration decreased the expression of immune-related genes, such as Th1 and Th17, ameliorated intestinal inflammation, and promoted the proliferation of Coprobacillus in a murine model of high-dose antibiotic-induced intestinal inflammation [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. This paradoxical outcome may be attributed to the disruption of microbial homeostasis in the initial gut environment caused by the extensive administration of antibiotics, leading to varying levels of mutations in the gut microbiota, thereby highlighting the diversity of Coprobacillus. Our research has revealed that Coprobacillus functions as a pathogenic bacterium that could potentially exacerbate the development of acute pancreatitis.\u003c/p\u003e \u003cp\u003eHoldemania sp900120005 belongs to Holdemania. Holdemania is a pathogenic bacterium that has been found in various environments and poses a potential threat to human health [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Studies have shown an elevated presence of Holdemania in inflammatory and psychiatric disorders, indicating its pathogenic nature [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. In a study conducted by Bj\u0026oslash;rkhaug et al., the impact of alcohol on gut microbiota functioning was investigated by comparing 24 patients with alcohol overdose to 18 control subjects. The study revealed an increased expression of Holdemania in the alcohol overdose group, with no significant association observed with short-chain fatty acids (SCFA) [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Notably, alcohol is recognized as a primary causative agent in acute pancreatitis [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Furthermore, Raimondi et al. demonstrated the involvement of Holdemania in mucin degradation, a crucial component of the intestinal barrier, with excessive degradation potentially exacerbating the systemic inflammatory response [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. These findings suggest a potential mediating role of Holdemania in the relationship between alcohol consumption and acute pancreatitis.\u003c/p\u003e \u003cp\u003eMegamonas, a genus of beneficial bacteria belonging to the Firmicutes phylum [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], is involved in the metabolism of the organism through the fermentation of carbohydrates to produce short-chain fatty acids (SCFA) [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. These SCFAs, such as acetate, propionate, and butyrate, are essential for maintaining intestinal homeostasis [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]and have been shown to have significant anti-inflammatory effects in various inflammatory diseases [\u003cspan additionalcitationids=\"CR54\" citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Jing et al. demonstrated that supplementation with short-chain fatty acids (SCFA) led to the down-regulation of the NF-κB signaling pathway, resulting in decreased inflammation and improved neural tissue function [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In a separate study, Li et al. observed that oral anticoagulants (OACs) altered the composition of gut microbiota, specifically increasing the abundance of Megamonas and decreasing pro-inflammatory colonies in patients with atrial fibrillation (AF). This shift in microbiota was associated with reduced thrombosis and highlighted the potential modulatory role of Megamonas in abnormal lipid metabolism [ 57]. In conclusion, our findings reinforce the aforementioned conclusions and identify novel therapeutic targets for the management of acute pancreatitis.\u003c/p\u003e \u003cp\u003eRecent studies have highlighted a potential causal link between gut microbiota and AP [ 58,59]. However, due to the small sample size in previous research, further investigation is warranted. This study aims to delve deeper into this relationship by analyzing 471 updated gut microbiota samples, thus enhancing the reliability of our findings.\u003c/p\u003e \u003cp\u003eThis study is subject to several limitations. While our research aligns with the MR hypothesis, it does not definitively establish a weak tool bias. Additionally, our findings would benefit from validation through additional experimental studies.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn conclusion, our study has identified a notable causal association between three specific intestinal microbiota and acute pancreatitis (AP), thereby contributing novel insights into the genetic basis of AP pathogenesis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study analysed publicly available datasets. The primary summary statistics for the gut microbiome can be accessed through the NHGRI-EBI GWAS Catalog (https://www.ebi.ac.uk/gwas/) spanning from accession GCST90032172 to GCST90032644, and the AP dataset is accessible at https://gwas.mrcieu.ac.uk/.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained for all included original GWASs, which did not violate any of the ethical requirements.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLH conceived the study, conducted the data analysis, and authored the manuscript. HJL and YL contributed to the experimental design and participated in the revision of the manuscript. JL, JZL, LP,and YX provided valuable assistance in the data analysis. HL was involved in the design of the experimental methods and provided critical review and editing of the manuscript. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the participants of all GWAS cohorts included in the present work and the investigators of the FINRISK 2002 and IEU open GWAS project initiatives for sharing the GWAS summary statistics.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003e10. Funding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the National Natural Science Foundation of China (82072938) and the Sichuan Provincial Administration of Traditional Chinese Medicine Project (2023MS511).\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003e11. Conflicts of interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGuo X. Y., Xiao F., Li J, et al.. (2019). Exosomes and pancreatic diseases: status, challenges, and hopes. Int. J. Biol. Sci. 15, 1846\u0026ndash;1860. doi: 10.7150/ijbs.35823\u003c/li\u003e\n\u003cli\u003eYadav D., Lowenfels A. B. The epidemiology of pancreatitis and pancreatic cancer. Gastroenterology. 2013;144(6):1252\u0026ndash;1261. doi: 10.1053/j.gastro.2013.01.068.\u003c/li\u003e\n\u003cli\u003eAcute pancreatitis: a review. Mederos MA, Reber HA, Girgis MD. JAMA. 2021;325:382\u0026ndash;390. \u003c/li\u003e\n\u003cli\u003eBaron TH, DiMaio CJ, Wang AY, Morgan KA. 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Front Microbiol. 2023 Nov 23;14:1290202. doi: 10.3389/fmicb.2023.1290202. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Gut microbiota, mendelian randomization, causal effect, genetic, acute pancreatitis","lastPublishedDoi":"10.21203/rs.3.rs-4444933/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4444933/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Numerous studies have indicated a correlation between the gut microbiota (GM) and acute pancreatitis (AP), yet the precise causal relationship between them remains ambiguous.\u003c/p\u003e\n\u003cp\u003eMethods: A two-sample Mendelian randomization (MR) study was conducted utilizing aggregated data from genome-wide association studies (GWASs) of 471 taxa (11 phyla, 19 orders, 24 orders, 62 families, 146 genera, and 209 species) and AP patients. Various methods, including inverse variance weighting (IVW), MR‒Egger, weighted medians, simple mode, and weighted mode, were employed to assess the causal association between the GM and AP. Sensitivity analyses were conducted utilizing Cochran's Q test, MR-Egger regression intercept analysis, and MR-PRESSO, followed by reverse MR analysis to evaluate the potential reverse causality between AP and GM.\u003c/p\u003e\n\u003cp\u003eResults: Three gut microbial taxa were found to have significant associations with acute pancreatitis (AP). The inverse variance weighted (IVW) results revealed that Coprobacillus (OR 1.19, 95% CI 1.01 to 1.40, p=0.035) and Holdemania sp900120005 (OR 1.18, 95% CI 1.02 to 1.35, p=0.023) were identified as risk factors for the development of AP, while Megamonas (OR: 0.87, 95% CI: 0.77 to 0.98, p=0.023) was found to be a protective factor against the occurrence of AP. A thorough sensitivity analysis confirmed the reliability of our findings. Reverse Mendelian randomization (MR) analysis did not indicate any causal relationship between AP and the gut microbiota (GM).\u003c/p\u003e\n\u003cp\u003eConclusions: This study revealed a complex causal relationship between 3 GM taxa and AP, providing new evidence for the development of AP from a genetic perspective.\u003c/p\u003e","manuscriptTitle":"A bidirectional two-sample Mendelian randomization using the gut microbiota to reveal potential therapeutic targets for acute pancreatitis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-28 18:52:39","doi":"10.21203/rs.3.rs-4444933/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":"879c9d91-06fc-428e-bcaa-7e4733297351","owner":[],"postedDate":"June 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-12-16T11:53:48+00:00","versionOfRecord":[],"versionCreatedAt":"2024-06-28 18:52:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4444933","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4444933","identity":"rs-4444933","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}