The association between Helicobacter pylori infection and pancreatic diseases: a Mendelian Randomization study

The association between Helicobacter pylori infection and pancreatic diseases: a 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 Article The association between Helicobacter pylori infection and pancreatic diseases: a Mendelian Randomization study Mengjia Zhu, Dian Zhang, Angli Chen, Xinjie Wang, Weiling Hu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3866393/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 Object: The relationship between Helicobacter pylori and pancreatic diseases remains a subject of controversy. Our study aims to investigate the association between Helicobacter pylori infection and pancreatic cancer as well as pancreatitis. Methods In this study, we employed the two-sample Mendelian randomization (MR) method to assess the causal relationship between anti-Helicobacter pylori antibody levels and the occurrence of pancreatic cancer and pancreatitis. The primary analytical approach was determined to be the inverse variance-weighted (IVW) analysis under a fixed-effects model. To ensure the reliability of our study findings, we conducted multiple sensitivity analyses. Results Our research reveals a significant correlation between elevated levels of anti-Helicobacter pylori outer membrane protein (OMP) and a reduced risk of alcohol-induced chronic pancreatitis (ACP) (OR, 0.654; 95% CI, 0.508–0.841; p < 0.05). Multivariable Mendelian randomization (MR) analysis indicates that C-reactive protein (CRP), as opposed to monocyte chemoattractant protein-1 (MCP-1), peptic ulcers, gastric ulcers, and duodenal ulcers, mediates the causal relationship between Helicobacter pylori infection and alcoholic chronic pancreatitis (ACP). Furthermore, our study findings exhibit no evidence of heterogeneity or pleiotropy. Conclusion The two-sample Mendelian randomization (MR) analysis reveals a causal relationship between anti-Helicobacter pylori OMP levels and ACP. Further investigations are warranted to elucidate and validate these findings. Biological sciences/Cancer Biological sciences/Microbiology Health sciences/Gastroenterology Health sciences/Risk factors anti-Helicobacter pylori antibodies levels pancreatic cancer pancreatitis causal association Mendelian randomization Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction Pancreatic cancer (PC) remains a significant burden on global health, characterized by high malignancy and poor prognosis. In 2017, there were a total of 441,000 cases of PC globally, and the risk of pancreatic cancer increases with age. The five-year survival rate for PC is approximately around 10% 1 . The mortality risk of PC also rises with age, and as global health conditions improve, leading to increased life expectancy, the overall incidence of PC may also rise 2 . Research has indicated that risk factors for PC include smoking 3 , diabetes 4 , BMI 5 , alcohol consumption 6 , pancreatitis 7 , allergies 8 , and genetic factors 9 . Due to the lack of typical clinical manifestations and diagnostic methods, PC is often diagnosed at an advanced stage, leading to poor treatment outcomes and a dismal prognosis. Therefore, implementing appropriate early diagnosis and screening strategies can offer surgical opportunities and early treatment for PC patients. Currently, common diagnostic methods for PC include CT, MRI, ERCP, MRCP, endoscopic ultrasound, among others 10 . Recently, many researchers have been dedicated to identifying new biomarkers for diagnosing PC. CA199 is widely used as a biomarker for monitoring PC 11 . Furthermore, the role of the tumor microbiome in the occurrence, development, and metastasis of PC has been identified by researchers. The tumor microbiome might potentially serve as a novel biomarker for predicting PC and revealing new therapeutic approaches 12 . Pancreatitis, serving as a predominant cause for hospitalization in gastrointestinal-related illnesses, exhibits a profound correlation between its incidence, mortality rates, and socioeconomic burden 13 . Pancreatitis cases are predominantly linked to digestive proteases within the pancreas, and both local and systemic inflammatory responses play crucial roles in the progression and severity of pancreatitis 14 . Risk factors for acute pancreatitis (AP) include gallstones, alcohol abuse, smoking, and type 2 diabetes 15 . In the context of chronic pancreatitis (CP), prolonged alcohol consumption and smoking are considered the primary risk factors 16 . Patients with CP typically manifest abdominal pain, yet targeted guidelines for managing CP-related pain are lacking. Consequently, the conventional approach involves employing the three-step ladder for cancer pain management. Additional pain relief modalities encompass endoscopic stone extraction and celiac plexus block procedures 17 . Studies have identified that autophagy dysregulation may contribute to the onset of pancreatic inflammation, offering a potential avenue for exploring novel therapeutic interventions 18 . The interplay between these factors underscores the complexity of pancreatitis, necessitating comprehensive strategies for its diagnosis, management, and potential avenues for therapeutic innovation. Helicobacter pylori (H. pylori) infection remains a significant human health concern, capable of eliciting gastritis, duodenal ulcers, gastric cancer, and various digestive or non-digestive disorders 19 . It has been discovered that H. pylori infection is associated with neurological and autoimmune diseases such as stroke, Alzheimer's disease, multiple sclerosis (MS), Parkinson's disease (PD), and Guillain-Barré syndrome (GBS) 20 . The primary pathogenic factors of H. pylori infection include Vacuolating cytotoxin A (VacA) and Cytotoxin-associated gene A (CagA). Other serum antibodies associated with H. pylori include IgG, GroEL, Urea, Catalase, outer membrane proteins (OMP) 21 . The causal relationship between H. pylori infection and pancreatic cancer is still debated. Some studies suggest an increased risk of pancreatic cancer with H. pylori infection 22 , while others indicate a lack of significant correlation between H. pylori infection and the incidence of pancreatic cancer 23 . Currently, the evidence linking H. pylori to pancreatic diseases is limited, necessitating further investigation to elucidate the relationship between H. pylori and pancreatic disorders. In Mendelian Randomization (MR), the relationship between exposure and outcome can be explored through the selection of Single Nucleotide Polymorphisms (SNPs) 24 . The core concept of MR involves leveraging naturally occurring genetic variations (SNPs) as "randomized experiments" to mimic the random allocation of exposure factors in nature, thereby mitigating biases caused by confounding factors. Through MR studies, we can circumvent some common confounding issues prevalent in traditional observational research. This is because genetic variations occur randomly within organisms and are not influenced by environmental factors. This allows researchers to assess the causal relationship more reliably between exposure factors and specific outcomes without concerns about interference from confounding factors. To the best of our knowledge, there is currently no Mendelian Randomization study investigating the relationship between serum Helicobacter pylori antibody levels and the occurrence of pancreatic cancer and pancreatitis. Therefore, we employed a two-sample Mendelian Randomization approach to examine whether Helicobacter pylori infection might increase or decrease the risk of pancreatic cancer or pancreatitis. 2. Method 2.1 Mendelian randomization design: Figure 1 illustrates the overall process of Mendelian randomization. To assess the relationship between serum antibodies against H. pylori and the risk of pancreatic cancer and pancreatitis, we conducted MR analysis. In determining the instrumental variable (IV) for MR, three core assumptions are made 25 : (a) the relevance assumption, positing a strong correlation between genetic variations and exposure; (b) the independence assumption, asserting the absence of confounding factors associated with genetic variations; and (c) the exclusion restriction, stipulating that gene polymorphisms are unrelated to the outcome in the presence of exposure and other confounding factors. To further evaluate the effectiveness of the instrumental variable, the F-statistic for each SNP was calculated using the formula: F = \({R}^{2}*\frac{(N-2)}{1-{R}^{2}}\) where \({R}^{2}\) represents the proportion of exposure variance explained by each genetic variant, N is the number of individuals in each sample 26 . A F-statistic less than 10 indicates weak IVs insufficient to mitigate the potential bias impact 27 . 2.2 Data sources: We obtained genome-wide association study (GWAS) summary statistics for H. pylori IgG, GroEL, OMP, Urea, VacA, Catalase, and CagA antibodies levels from the publicly available data repository maintained by the European Bioinformatics Institute (EBI) at https://gwas.mrcieu.ac.uk/ . The GWAS summary data for pancreatic cancer were sourced from a study conducted by Sakaue S et al. in 2021, encompassing a cohort of 476,245 European male and female individuals 28 . Data pertaining to alcohol-induced acute pancreatitis (AAP), acute pancreatitis (AP), alcohol-induced chronic pancreatitis (ACP), and chronic pancreatitis (CP) were retrieved from the Finnen database. Summary data for C-reactive protein (CRP), monocyte chemoattractant protein-1 (MCP-1), peptic ulcers (PU), gastric ulcers (GU), and duodenal ulcers (DU) were extracted from Genome-Wide Association Studies (GWAS). Refer to Table 1 for detailed information on the data sources. Table 1 Details of the GWAS data in this study. Exposure/Outcome Consortium Population Sample size Web source Anti-Helicobacter pylori IgG levels NA European 4683 https://gwas.mrcieu.ac.uk/datasets/ieu-b-4905/ Helicobacter pylori GroEL antibody levels NA European 2716 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006913/ Helicobacter pylori OMP antibody levels NA European 2640 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006914/ Helicobacter pylori UREA antibody levels NA European 2251 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006915/ Helicobacter pylori VacA antibody levels NA European 1571 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006916/ Helicobacter pylori Catalase antibody levels NA European 1558 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006912/ Helicobacter pylori CagA antibody levels NA European 985 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006911/ pancreatic cancer NA European 476245 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90018893/ Acohol-induced acute pancreatitis FinnGen European NA https://gwas.mrcieu.ac.uk/datasets/finn-b-ALCOPANCACU/ Acute pancreatitis FinnGen European NA https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_ACUTPANC/ Alcohol-induced chronic pancreatitis FinnGen European NA https://gwas.mrcieu.ac.uk/datasets/finn-b-ALCOPANCCHRON/ Chronic pancreatitis FinnGen European NA https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_CHRONPANC/ C-reactive protein NA European 204402 https://gwas.mrcieu.ac.uk/datasets/ieu-b-35/ monocyte chemoattractant protein 1 NA European 21758 https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90012007/ peptic ulcer NA European 361194 https://gwas.mrcieu.ac.uk/datasets/ukb-d-K11_GASTRODUOULC/ gastric ulcer NA European 361194 https://gwas.mrcieu.ac.uk/datasets/ukb-d-K25/ duodenal ulcer NA European 361194 https://gwas.mrcieu.ac.uk/datasets/ukb-d-K26/ 2.3 Selection and validation of SNPs: We employed a significance threshold of p < 5 × 10 − 6 to identify SNPs. At the genome-wide significance level (p < 5 × 10 − 6 ), the number of Single Nucleotide Polymorphisms (SNPs) ranged from 4 to 15. Effective MR analysis necessitates the absence of linkage disequilibrium between specific SNPs (r 2 < 0.001) 29 . Additionally, we computed the F-statistic using the aforementioned formula, considering F < 10 as indicative of weak instrumental variables (IVs). Detailed SNP data can be found in the supplementary table. 2.4 Statistical analysis: Through the two-sample Mendelian Randomization (MR) approach, we elucidated causal and reverse causal relationships between H. pylori infection and both pancreatic cancer and pancreatitis. Our primary MR analyses employed the multiplicative random-effects inverse-variance weighted (IVW) method, chosen for its precision in estimation under the assumption of the validity of all single nucleotide polymorphisms (SNPs) as instruments. To enhance result robustness, supplementary analyses were performed, which included IVW under the random effects model, weighted median, and MR-Egger. Detection of pleiotropic bias was taken into account, and significance was indicated if the MR-Egger intercept yielded a p-value below 0.05 30 . Additionally, we employed the MR-PRESSO method to identify outliers before MR estimate computation. MR-PRESSO effectively identified and excluded abnormal SNPs (outliers), enabling an assessment of potential horizontal pleiotropy and testing for differences in results before and after correction 31 . To evaluate result sensitivity, we implemented the leave-one-out method, systematically excluding one SNP at a time to explore whether a single SNP with a substantial horizontal pleiotropic effect could influence MR estimates. Cochran's Q was computed in this study to assess heterogeneity introduced by various SNPs. In the realm of multivariable Mendelian randomization (MR), we amalgamated serum Helicobacter pylori antibody levels with instrumental variables (IVs) for CRP, MCP-1, PU, and their subtypes (GU and DU). This fusion aimed to elucidate their mediating role in the causal relationship between Helicobacter pylori infection and pancreatic diseases. The R package "TwosampleMR" and "MendelianRandomization" was employed for the execution of the MR analyses. 3. Result 3.1 The association between H. pylori outer membrane proteins (OMP) antibody levels and pancreatic diseases. Following meticulous selection, we included 9 or 10 Single Nucleotide Polymorphisms (SNPs) with p-values < 5*10^-6, detailed information can be found in the supplementary table. According to the Inverse Variance Weighted (IVW) analysis under fixed effects, there is a significant association between Helicobacter pylori antibody OMP levels and ACP (OR, 0.654; 95% CI, 0.508–0.841; p < 0.05). Similar results were obtained in the Weighted Median analysis (OR, 0.631; 95% CI, 0.447–0.891; p < 0.05). However, MR-Egger analysis failed to yield such results (OR, 0.920; 95% CI, 0.398–2.127; p = 0.852) (Fig. 2 ). Figure 3 A vividly illustrates the inverse relationship, showing a decrease in the risk of ACP with an elevation in Helicobacter pylori antibody OMP levels. Figure 3 C displays downward slopes for different algorithms, suggesting a decline in the incidence of ACP with an increase in Helicobacter pylori antibody OMP levels. To ensure the reliability of the results, we conducted sensitivity analyses. MR-PRESSO analysis revealed no outliers, and we employed a leave-one-out study to assess the robustness of the results. The stepwise exclusion of each SNP and the subsequent calculation of the remaining SNP effects are depicted in Fig. 3 B, demonstrating minimal changes in the overall error lines, all positioned to the left of zero. Furthermore, to examine study heterogeneity, Cochran's Q test yielded a p-value of 0.679 for MR-Egger and 0.698 for IVW. Figure 3 D shows the funnel diagram. Overall, this study exhibits no heterogeneity (Table 2 ). Tests for pleiotropy also indicated the absence of horizontal pleiotropy in this study (Table 2 ). Table2: Pleiotropy and heterogeneity between OMP and alcohol-induced chronic pancreatitis (ACP). exposure heterogeneity Pleiotropy MR Egger IVW MR-Egger intercept se P-value Q P-value Q P-value ieu-b-4905 Anti-Helicobacter pylori IgG levels 8.422 0.588 9.714 0.556 0.068 0.060 0.282 ebi-a-GCST90006914 Helicobacter pylori OMP antibody levels 3.985 0.679 4.690 0.698 -0.067 0.079 0.433 ebi-a-GCST90006915 Helicobacter pylori UREA antibody levels 5.474 0.706 6.735 0.665 0.073 0.065 0.294 ebi-a-GCST90006916 Helicobacter pylori VacA antibody levels 13.809 0.244 13.858 0.310 0.011 0.053 0.846 ebi-a-GCST90006912 Helicobacter pylori Catalase antibody levels 8.830 0.183 8.920 0.258 -0.015 0.060 0.813 ebi-a-GCST90006911 Helicobacter pylori CagA antibody levels 3.016 0.933 3.886 0.919 0.053 0.057 0.378 3.2 The association between other H.pylri antibodies levels and pancreatic diseases. We also applied MR analysis to investigate the relationships between serum H. pylori IgG, GroEL, Urea, VacA, CagA, and Catalase antibodies with PC, AAP, AP, ACP, and CP. We did not find any significant associations between IgG and PC (OR, 1.027; 95% CI, 0.815–1.295; p = 0.820), AAP (OR, 1.239; 95% CI, 0.815–1.883; p = 0.316), AP (OR, 1.058; 95% CI, 0.923–1.212; p = 0.418), ACP (OR, 1.022; 95% CI, 0.806–1.296; p = 0.860), and CP (OR, 1.000; 95% CI, 0.797–1.255; p = 0.998) (Fig. 4 ). Similarly, GroEL showed no significant correlation with PC, AAP, AP, ACP, and CP (Fig. 4 ). Figures 5 and 6 depict the relationships between Urea, VacA, CagA, Catalase, and PC, AAP, AP, ACP, and CP. Different algorithms demonstrated no significant associations between these exposures and outcomes. 3.3 CRP mediates the causal effects of Helicobacter pylori infection on ACP in MVMR. To elucidate the potential mediating mechanisms underlying the causal relationship between Helicobacter pylori infection and ACP, we conducted MVMR analyses by integrating instrumental variables (IVs) for OMP and CRP (Fig. 7 ). The MVMR study, utilizing the IVW method, revealed a dissipation of the observed association between OMP and ACP (OR = 1.067, 95% CI = 0.774–1.472, P = 0.691). Consistent results were obtained using MR-Egger and Lasso methods in alignment with the IVW method. However, when merging IVs for OMP and MCP-1, the IVW analysis exhibited a persistent association between OMP and ACP (OR = 0.633, 95% CI = 0.495–0.808, P < 0.001). MR-Egger and Lasso methods yielded congruent outcomes. Similarly, the combined analysis of OMP with IVs for PU, GU, and DU using IVW demonstrated an enduring causal relationship between OMP and ACP (PU: OR = 0.677, 95% CI = 0.530–0.865, P = 0.002; GU: OR = 0.609, 95% CI = 0.470–0.788, P < 0.001; DU: OR = 0.704, 95% CI = 0.555–0.892, P = 0.004). MR-Egger and Lasso methods corroborated these findings consistently. 4. Discussion Historical animal experiments have suggested that Helicobacter pylori infection may lead to microcirculatory disturbances in acute pancreatitis, thereby exacerbating the severity of ischemic pancreatitis 32 . Additionally, in a case-control study encompassing 40 patients each with chronic alcoholic pancreatitis, alcoholic cirrhosis, and asymptomatic non-drinking individuals, endoscopic examinations and biopsies were conducted to assess Helicobacter pylori infection. Surprisingly, no association was found between Helicobacter pylori infection and the occurrence of chronic alcoholic pancreatitis. Conversely, individuals with Helicobacter pylori-negative severe chronic gastritis were more prevalent in cases of chronic alcoholic pancreatitis 33 . Elevated levels of CRP serve as a predictive indicator for AP, with a concomitant increase in CRP values corresponding to a diminished prognosis for AP 34 . In individuals with CP, the serum levels of CRP are notably elevated compared to the levels observed in the serum of healthy individuals 35 . However, no studies have demonstrated serum CRP levels in ACP patients. Contrary to these findings, our study reveals a significant correlation between serum levels of anti-Helicobacter pylori OMP and ACP. As serum anti-Helicobacter pylori OMP levels increase, the risk of developing ACP decreases. Further MVMR analysis indicates that CRP mediates the causal relationship between OMP and ACP. Consequently, our conclusion posits that OMP serves as a protective factor against ACP, and this process is mediated through a signal transduction pathway facilitated by CRP. This finding contrasts with the conclusions drawn from previous case-control studies, and potential reasons for this discrepancy may include the following. Firstly, our study only identified an association between OMP and ACP, while several other serum anti-Helicobacter pylori antibodies showed no correlation with ACP. The reasons for this discrepancy require further investigation. Secondly, the case-control study mentioned earlier was published in 1998, and the authors detected Helicobacter pylori infection through gastric biopsy specimens, whereas we utilized serum anti-Helicobacter pylori antibody levels. This difference in methodology may contribute to the disparities in our conclusions. Furthermore, the analytical approach of the Mendelian Randomization study closely resembles a randomized controlled trial, allowing for the elimination of confounding factors, which might explain our findings associating OMP with ACP. Lastly, differences in diet and lifestyle among the populations studied could also be contributing factors. Previous studies have suggested an association between PC risk and Helicobacter pylori seropositivity in individuals with non-O blood type, while no such correlation was observed in individuals with blood type O 36 . In contrast, a meta-analysis in 2022 indicated an increased incidence of PC associated with Helicobacter pylori infection, but there was no link between CagA/VacA-positive Helicobacter pylori infection and PC 37 . However, an analysis of anti-Hp-IgG (Helicobacter pylori-specific antibodies), Hp-IgM (Helicobacter pylori antibodies), and CagA-Hp-IgG (antibodies against Helicobacter pylori cytotoxin-associated protein A) revealed that infection with CagA-positive Helicobacter pylori strains is one of the risk factors for PC 38 . Additionally, several potential mechanisms associated with PC include physiological changes related to Helicobacter pylori-induced gastritis, such as increased gastric secretion of gastrin and alterations in somatostatin (reduced somatostatin cell numbers in the gastric antrum) 39 40 . Moreover, factors such as increased DNA synthesis due to bacterial overgrowth, elevated formation of N-nitroso compounds, and chronic inflammation may independently contribute to the carcinogenic process 41 42 . It is noteworthy that, despite previous research suggesting a link between Helicobacter pylori and PC, our Mendelian Randomization study did not find a correlation between Helicobacter pylori infection and PC. This discrepancy could be attributed to differences in study populations, study designs, or other unconsidered factors. Therefore, further research is still required to elucidate the relationship between Helicobacter pylori and PC. Regarding the controversy surrounding the relationship between Helicobacter pylori and PC or pancreatitis, we posit several potential explanations. Firstly, many previous observational studies lack prospective, randomized, and blinded designs, making them susceptible to confounding factors and selection bias, thereby compromising the reliability of the study outcomes. Secondly, the diverse diagnostic criteria for Helicobacter pylori infection pose a challenge. Presently, the primary non-invasive method for diagnosing Helicobacter pylori infection is the urea breath test. Past research, including our Mendelian Randomization study, has predominantly employed serum levels of anti-Helicobacter pylori antibodies to investigate their association with pancreatic diseases, introducing a potential limitation to the methodology. Lastly, disparities in age, gender, ethnicity, dietary habits, socioeconomic status, and other factors may contribute to the existing controversies. In our study, we employed the MR approach. Similar to a randomized controlled trial (RCT) where participants are randomly assigned to experimental or control groups, MR studies randomize individuals based on the influence of one or more genetic variants on risk factors. This randomization helps determine whether carriers of these genetic variations have different disease risk compared to non-carriers. Unlike other observational studies, MR addresses issues of reverse causation. Given the high global prevalence of H. pylori infection, establishing whether there is a correlation between H. pylori infection and PC, or pancreatitis is crucial for early prevention and intervention. Our findings suggest a potential association between H. pylori infection and ACP, with serum H. pylori OMP antibody levels reducing the risk of ACP. This study provides valuable insights for future directions in the prevention, diagnosis, and treatment of ACP. In conclusion, the relationship between H. pylori infection and pancreatic diseases remains an area that necessitates extensive foundational experiments and randomized controlled trials for refinement. However, our study identified OMP as a protective factor against ACP. This discovery opens up new avenues for the future treatment of alcohol-induced chronic pancreatitis. 5. Conclusions Our study is designed to examine the relationship between H. pylori infection and PC as well as pancreatitis. Utilizing MR methodology, our research establishes the association between H. pylori infection and ACP. Declarations Conflict of interest: All authors declare no conflict of interest. Author Contribution Conceptualization, MJZ and WLH.; writing—original draft preparation, MJZ and DZ; writing, DZ and ALC; review and editing, XJW, ALC and MJZ.; manuscript polishing, MJZ; supervision, WLH. All authors have read and agreed to the published version of the manuscript. 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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-3866393","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":268619770,"identity":"445d4190-be62-48d1-afac-5a45bb5733a2","order_by":0,"name":"Mengjia Zhu","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mengjia","middleName":"","lastName":"Zhu","suffix":""},{"id":268619771,"identity":"058c3403-d465-4254-86ca-5e6fc7e86a2d","order_by":1,"name":"Dian Zhang","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital","correspondingAuthor":false,"prefix":"","firstName":"Dian","middleName":"","lastName":"Zhang","suffix":""},{"id":268619773,"identity":"91c67c5a-a6cb-4e1e-938d-76c76696e9ce","order_by":2,"name":"Angli Chen","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital","correspondingAuthor":false,"prefix":"","firstName":"Angli","middleName":"","lastName":"Chen","suffix":""},{"id":268619776,"identity":"52cb6733-7c3d-45c0-9d72-774648425447","order_by":3,"name":"Xinjie Wang","email":"","orcid":"","institution":"Sir Run Run Shaw Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xinjie","middleName":"","lastName":"Wang","suffix":""},{"id":268619778,"identity":"fdde74a0-1f0c-4819-b342-392de92a4818","order_by":4,"name":"Weiling Hu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYBACAxCRUCDBwMDeAOYwNhCnxQCohecAKVrApEQCmElYi7lEjuGDBwYWefKRzx8U8zDYyG44wPzsAT4tljNyjA2ADis2vJ2QYMzDkGa84QCbuQFeh93I3SYB1JK4cXbCAaCWw4kbDvCwSRDQsv0HWMvMgw1ALf+J0rINFGKJ8yWYGYBaDhCh5cz7z2CHbeBJYzCcY5BsPPMwmxl+LcfTEj/+qKhLnN9+/JnBmwo72b7jzc/wakHoPcDAZgCOIGai1AOBfAMD8wNiFY+CUTAKRsHIAgDH00hw40Ma8gAAAABJRU5ErkJggg==","orcid":"","institution":"Zhejiang University","correspondingAuthor":true,"prefix":"","firstName":"Weiling","middleName":"","lastName":"Hu","suffix":""}],"badges":[],"createdAt":"2024-01-15 12:05:48","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3866393/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3866393/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":50016197,"identity":"a9855880-e94f-4e99-9a98-fe703c59b13b","added_by":"auto","created_at":"2024-01-23 06:43:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":156252,"visible":true,"origin":"","legend":"\u003cp\u003eThree crucial hypotheses of the Mendelian randomization study. SNPs, single-nucleotide polymorphisms; H. pylori, Helicobacter pylori.\u003cstrong\u003e Assumption1:\u003c/strong\u003e The IVs are robustly associated with exposures.\u003cstrong\u003e Assumption2:\u003c/strong\u003e The IVs are not associated with confounders.\u003cstrong\u003eAssumption3:\u003c/strong\u003e The IVs can only induce outcomes through exposures.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/28ce8eb3f95f49e894812820.png"},{"id":50016654,"identity":"5ba01633-0827-4bf7-a0c3-95c0dd801303","added_by":"auto","created_at":"2024-01-23 06:51:15","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":144177,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations of anti-H. pylori OMP levels with pancreatic diseases\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/06c51f796f3621f74b3f5f76.png"},{"id":50016199,"identity":"295f0118-14c1-4cfd-9c55-976d697ea66a","added_by":"auto","created_at":"2024-01-23 06:43:15","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":158763,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot (A), sensitivity analysis (B), scatter plot (C), and funnel plot (D) of the effect of anti-H. pylori OMP levels on Acohol-induced chronic pancreatitis.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/32cedcb75c182badfee43eb1.png"},{"id":50016198,"identity":"7a16ec1d-7f0c-4c18-af19-79bb24d8dfab","added_by":"auto","created_at":"2024-01-23 06:43:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":210703,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations of anti-H. pylori IgG (A) and GroEL (B) levels with pancreatic diseases.\u003c/p\u003e","description":"","filename":"figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/780a36ed4660a370ff6308d2.png"},{"id":50016204,"identity":"6b709297-8c8b-40d1-ba89-a0b7eb850041","added_by":"auto","created_at":"2024-01-23 06:43:15","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":200175,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations of anti-H. pylori UREA (A) and VacA (B) levels with pancreatic diseases.\u003c/p\u003e","description":"","filename":"figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/0d2ca371fdf56d1c03891a9e.png"},{"id":50016655,"identity":"a3f82546-14cd-4294-8de1-992b1c69d61e","added_by":"auto","created_at":"2024-01-23 06:51:15","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":203802,"visible":true,"origin":"","legend":"\u003cp\u003eAssociations of anti-H. pylori Catalase (A) and CagA (B) levels with pancreatic diseases.\u003c/p\u003e","description":"","filename":"figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/e0ab45779ecd0e4ddbeb3f9e.png"},{"id":50016201,"identity":"c7472a92-e207-4319-aa81-01b8971b44d4","added_by":"auto","created_at":"2024-01-23 06:43:15","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":167864,"visible":true,"origin":"","legend":"\u003cp\u003eMVMR analyses by integrating instrumental variables (IVs) for OMP and CRP, MCP-1, PU, GU, DU.\u003c/p\u003e","description":"","filename":"figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/6171e578ce2952ec10492dca.png"},{"id":51993369,"identity":"928ac1db-77fa-49a0-8db0-52cd74e95ca8","added_by":"auto","created_at":"2024-03-05 05:05:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1582100,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/528924c7-8e1e-4ba3-8884-aed4eff03678.pdf"},{"id":50016203,"identity":"95b54a8d-7474-4b39-90e5-62c1a26876d2","added_by":"auto","created_at":"2024-01-23 06:43:15","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":88574,"visible":true,"origin":"","legend":"","description":"","filename":"supplementtable.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3866393/v1/b489133f2d0f0735498ee922.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The association between Helicobacter pylori infection and pancreatic diseases: a Mendelian Randomization study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePancreatic cancer (PC) remains a significant burden on global health, characterized by high malignancy and poor prognosis. In 2017, there were a total of 441,000 cases of PC globally, and the risk of pancreatic cancer increases with age. The five-year survival rate for PC is approximately around 10%\u003csup\u003e1\u003c/sup\u003e. The mortality risk of PC also rises with age, and as global health conditions improve, leading to increased life expectancy, the overall incidence of PC may also rise \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Research has indicated that risk factors for PC include smoking \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, diabetes \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, BMI \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, alcohol consumption \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, pancreatitis \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, allergies \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, and genetic factors \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Due to the lack of typical clinical manifestations and diagnostic methods, PC is often diagnosed at an advanced stage, leading to poor treatment outcomes and a dismal prognosis. Therefore, implementing appropriate early diagnosis and screening strategies can offer surgical opportunities and early treatment for PC patients. Currently, common diagnostic methods for PC include CT, MRI, ERCP, MRCP, endoscopic ultrasound, among others \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Recently, many researchers have been dedicated to identifying new biomarkers for diagnosing PC. CA199 is widely used as a biomarker for monitoring PC \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Furthermore, the role of the tumor microbiome in the occurrence, development, and metastasis of PC has been identified by researchers. The tumor microbiome might potentially serve as a novel biomarker for predicting PC and revealing new therapeutic approaches\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePancreatitis, serving as a predominant cause for hospitalization in gastrointestinal-related illnesses, exhibits a profound correlation between its incidence, mortality rates, and socioeconomic burden \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Pancreatitis cases are predominantly linked to digestive proteases within the pancreas, and both local and systemic inflammatory responses play crucial roles in the progression and severity of pancreatitis \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Risk factors for acute pancreatitis (AP) include gallstones, alcohol abuse, smoking, and type 2 diabetes \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. In the context of chronic pancreatitis (CP), prolonged alcohol consumption and smoking are considered the primary risk factors \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Patients with CP typically manifest abdominal pain, yet targeted guidelines for managing CP-related pain are lacking. Consequently, the conventional approach involves employing the three-step ladder for cancer pain management. Additional pain relief modalities encompass endoscopic stone extraction and celiac plexus block procedures \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Studies have identified that autophagy dysregulation may contribute to the onset of pancreatic inflammation, offering a potential avenue for exploring novel therapeutic interventions \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The interplay between these factors underscores the complexity of pancreatitis, necessitating comprehensive strategies for its diagnosis, management, and potential avenues for therapeutic innovation.\u003c/p\u003e \u003cp\u003eHelicobacter pylori (H. pylori) infection remains a significant human health concern, capable of eliciting gastritis, duodenal ulcers, gastric cancer, and various digestive or non-digestive disorders \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. It has been discovered that H. pylori infection is associated with neurological and autoimmune diseases such as stroke, Alzheimer's disease, multiple sclerosis (MS), Parkinson's disease (PD), and Guillain-Barr\u0026eacute; syndrome (GBS) \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The primary pathogenic factors of H. pylori infection include Vacuolating cytotoxin A (VacA) and Cytotoxin-associated gene A (CagA). Other serum antibodies associated with H. pylori include IgG, GroEL, Urea, Catalase, outer membrane proteins (OMP) \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The causal relationship between H. pylori infection and pancreatic cancer is still debated. Some studies suggest an increased risk of pancreatic cancer with H. pylori infection \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, while others indicate a lack of significant correlation between H. pylori infection and the incidence of pancreatic cancer \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Currently, the evidence linking H. pylori to pancreatic diseases is limited, necessitating further investigation to elucidate the relationship between H. pylori and pancreatic disorders.\u003c/p\u003e \u003cp\u003eIn Mendelian Randomization (MR), the relationship between exposure and outcome can be explored through the selection of Single Nucleotide Polymorphisms (SNPs) \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. The core concept of MR involves leveraging naturally occurring genetic variations (SNPs) as \"randomized experiments\" to mimic the random allocation of exposure factors in nature, thereby mitigating biases caused by confounding factors. Through MR studies, we can circumvent some common confounding issues prevalent in traditional observational research. This is because genetic variations occur randomly within organisms and are not influenced by environmental factors. This allows researchers to assess the causal relationship more reliably between exposure factors and specific outcomes without concerns about interference from confounding factors. To the best of our knowledge, there is currently no Mendelian Randomization study investigating the relationship between serum Helicobacter pylori antibody levels and the occurrence of pancreatic cancer and pancreatitis. Therefore, we employed a two-sample Mendelian Randomization approach to examine whether Helicobacter pylori infection might increase or decrease the risk of pancreatic cancer or pancreatitis.\u003c/p\u003e"},{"header":"2. Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Mendelian randomization design:\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the overall process of Mendelian randomization. To assess the relationship between serum antibodies against H. pylori and the risk of pancreatic cancer and pancreatitis, we conducted MR analysis. In determining the instrumental variable (IV) for MR, three core assumptions are made \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e: (a) the relevance assumption, positing a strong correlation between genetic variations and exposure; (b) the independence assumption, asserting the absence of confounding factors associated with genetic variations; and (c) the exclusion restriction, stipulating that gene polymorphisms are unrelated to the outcome in the presence of exposure and other confounding factors. To further evaluate the effectiveness of the instrumental variable, the F-statistic for each SNP was calculated using the formula:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eF\u003c/em\u003e =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}*\\frac{(N-2)}{1-{R}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}\\)\u003c/span\u003e\u003c/span\u003erepresents the proportion of exposure variance explained by each genetic variant, N is the number of individuals in each sample \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. A F-statistic less than 10 indicates weak IVs insufficient to mitigate the potential bias impact \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Data sources:\u003c/h2\u003e \u003cp\u003eWe obtained genome-wide association study (GWAS) summary statistics for H. pylori IgG, GroEL, OMP, Urea, VacA, Catalase, and CagA antibodies levels from the publicly available data repository maintained by the European Bioinformatics Institute (EBI) at \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. The GWAS summary data for pancreatic cancer were sourced from a study conducted by \u003cem\u003eSakaue S\u003c/em\u003e et al. in 2021, encompassing a cohort of 476,245 European male and female individuals \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Data pertaining to alcohol-induced acute pancreatitis (AAP), acute pancreatitis (AP), alcohol-induced chronic pancreatitis (ACP), and chronic pancreatitis (CP) were retrieved from the Finnen database. Summary data for C-reactive protein (CRP), monocyte chemoattractant protein-1 (MCP-1), peptic ulcers (PU), gastric ulcers (GU), and duodenal ulcers (DU) were extracted from Genome-Wide Association Studies (GWAS). Refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for detailed information on the data sources.\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\u003eDetails of the GWAS data in this study.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure/Outcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsortium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWeb source\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnti-Helicobacter pylori IgG levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ieu-b-4905/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ieu-b-4905/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelicobacter pylori GroEL antibody levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006913/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006913/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelicobacter pylori OMP antibody levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006914/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006914/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelicobacter pylori UREA antibody levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006915/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006915/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelicobacter pylori VacA antibody levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006916/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006916/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelicobacter pylori Catalase antibody levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006912/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006912/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHelicobacter pylori CagA antibody levels\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006911/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90006911/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epancreatic cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e476245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90018893/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90018893/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcohol-induced acute pancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/finn-b-ALCOPANCACU/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/finn-b-ALCOPANCACU/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute pancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/finn-b-K11_ACUTPANC/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_ACUTPANC/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol-induced chronic pancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/finn-b-ALCOPANCCHRON/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/finn-b-ALCOPANCCHRON/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic pancreatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/finn-b-K11_CHRONPANC/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/finn-b-K11_CHRONPANC/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e204402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ieu-b-35/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ieu-b-35/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emonocyte chemoattractant protein 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90012007/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90012007/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epeptic ulcer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e361194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ukb-d-K11_GASTRODUOULC/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ukb-d-K11_GASTRODUOULC/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egastric ulcer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e361194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ukb-d-K25/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ukb-d-K25/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eduodenal ulcer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e361194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/datasets/ukb-d-K26/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/datasets/ukb-d-K26/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Selection and validation of SNPs:\u003c/h2\u003e \u003cp\u003eWe employed a significance threshold of p\u0026thinsp;\u0026lt;\u0026thinsp;5 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e to identify SNPs. At the genome-wide significance level (p\u0026thinsp;\u0026lt;\u0026thinsp;5 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e), the number of Single Nucleotide Polymorphisms (SNPs) ranged from 4 to 15. Effective MR analysis necessitates the absence of linkage disequilibrium between specific SNPs (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Additionally, we computed the F-statistic using the aforementioned formula, considering F\u0026thinsp;\u0026lt;\u0026thinsp;10 as indicative of weak instrumental variables (IVs). Detailed SNP data can be found in the supplementary table.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis:\u003c/h2\u003e \u003cp\u003eThrough the two-sample Mendelian Randomization (MR) approach, we elucidated causal and reverse causal relationships between H. pylori infection and both pancreatic cancer and pancreatitis. Our primary MR analyses employed the multiplicative random-effects inverse-variance weighted (IVW) method, chosen for its precision in estimation under the assumption of the validity of all single nucleotide polymorphisms (SNPs) as instruments. To enhance result robustness, supplementary analyses were performed, which included IVW under the random effects model, weighted median, and MR-Egger. Detection of pleiotropic bias was taken into account, and significance was indicated if the MR-Egger intercept yielded a p-value below 0.05 \u003csup\u003e30\u003c/sup\u003e. Additionally, we employed the MR-PRESSO method to identify outliers before MR estimate computation. MR-PRESSO effectively identified and excluded abnormal SNPs (outliers), enabling an assessment of potential horizontal pleiotropy and testing for differences in results before and after correction \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. To evaluate result sensitivity, we implemented the leave-one-out method, systematically excluding one SNP at a time to explore whether a single SNP with a substantial horizontal pleiotropic effect could influence MR estimates. Cochran's Q was computed in this study to assess heterogeneity introduced by various SNPs. In the realm of multivariable Mendelian randomization (MR), we amalgamated serum Helicobacter pylori antibody levels with instrumental variables (IVs) for CRP, MCP-1, PU, and their subtypes (GU and DU). This fusion aimed to elucidate their mediating role in the causal relationship between Helicobacter pylori infection and pancreatic diseases. The R package \"TwosampleMR\" and \"MendelianRandomization\" was employed for the execution of the MR analyses.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 The association between H. pylori outer membrane proteins (OMP) antibody levels and pancreatic diseases.\u003c/h2\u003e \u003cp\u003eFollowing meticulous selection, we included 9 or 10 Single Nucleotide Polymorphisms (SNPs) with p-values\u0026thinsp;\u0026lt;\u0026thinsp;5*10^-6, detailed information can be found in the supplementary table. According to the Inverse Variance Weighted (IVW) analysis under fixed effects, there is a significant association between Helicobacter pylori antibody OMP levels and ACP (OR, 0.654; 95% CI, 0.508\u0026ndash;0.841; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Similar results were obtained in the Weighted Median analysis (OR, 0.631; 95% CI, 0.447\u0026ndash;0.891; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). However, MR-Egger analysis failed to yield such results (OR, 0.920; 95% CI, 0.398\u0026ndash;2.127; p\u0026thinsp;=\u0026thinsp;0.852) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA vividly illustrates the inverse relationship, showing a decrease in the risk of ACP with an elevation in Helicobacter pylori antibody OMP levels. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC displays downward slopes for different algorithms, suggesting a decline in the incidence of ACP with an increase in Helicobacter pylori antibody OMP levels. To ensure the reliability of the results, we conducted sensitivity analyses. MR-PRESSO analysis revealed no outliers, and we employed a leave-one-out study to assess the robustness of the results. The stepwise exclusion of each SNP and the subsequent calculation of the remaining SNP effects are depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, demonstrating minimal changes in the overall error lines, all positioned to the left of zero. Furthermore, to examine study heterogeneity, Cochran's Q test yielded a p-value of 0.679 for MR-Egger and 0.698 for IVW. Figure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD shows the funnel diagram. Overall, this study exhibits no heterogeneity (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Tests for pleiotropy also indicated the absence of horizontal pleiotropy in this study (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable2: Pleiotropy and heterogeneity between OMP and alcohol-induced chronic pancreatitis (ACP).\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" style=\"width: 36.2237%;\"\u003e\n \u003cp\u003eexposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 18.2995%;\"\u003e\n \u003cp\u003eheterogeneity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 27.125%;\"\u003e\n \u003cp\u003ePleiotropy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.1029%;\"\u003e\n \u003cp\u003eMR Egger\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 9.1029%;\"\u003e\n \u003cp\u003eIVW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 10.9797%;\"\u003e\n \u003cp\u003eMR-Egger intercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 3.8476%;\"\u003e\n \u003cp\u003ese\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 7.625%;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003eQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003eQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.8566%;\"\u003e\n \u003cp\u003eieu-b-4905\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3671%;\"\u003e\n \u003cp\u003eAnti-Helicobacter pylori IgG levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e8.422\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.588\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e9.714\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.556\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9797%;\"\u003e\n \u003cp\u003e0.068\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.8476%;\"\u003e\n \u003cp\u003e0.060\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.625%;\"\u003e\n \u003cp\u003e0.282\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.8566%;\"\u003e\n \u003cp\u003eebi-a-GCST90006914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3671%;\"\u003e\n \u003cp\u003eHelicobacter pylori OMP antibody levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e3.985\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.679\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e4.690\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.698\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9797%;\"\u003e\n \u003cp\u003e-0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.8476%;\"\u003e\n \u003cp\u003e0.079\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.625%;\"\u003e\n \u003cp\u003e0.433\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.8566%;\"\u003e\n \u003cp\u003eebi-a-GCST90006915\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3671%;\"\u003e\n \u003cp\u003eHelicobacter pylori UREA antibody levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e5.474\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.706\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e6.735\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.665\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9797%;\"\u003e\n \u003cp\u003e0.073\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.8476%;\"\u003e\n \u003cp\u003e0.065\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.625%;\"\u003e\n \u003cp\u003e0.294\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.8566%;\"\u003e\n \u003cp\u003eebi-a-GCST90006916\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3671%;\"\u003e\n \u003cp\u003eHelicobacter pylori VacA antibody levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e13.809\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.244\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e13.858\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.310\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9797%;\"\u003e\n \u003cp\u003e0.011\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.8476%;\"\u003e\n \u003cp\u003e0.053\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.625%;\"\u003e\n \u003cp\u003e0.846\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.8566%;\"\u003e\n \u003cp\u003eebi-a-GCST90006912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3671%;\"\u003e\n \u003cp\u003eHelicobacter pylori Catalase antibody levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e8.830\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.183\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e8.920\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.258\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9797%;\"\u003e\n \u003cp\u003e-0.015\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.8476%;\"\u003e\n \u003cp\u003e0.060\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.625%;\"\u003e\n \u003cp\u003e0.813\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12.8566%;\"\u003e\n \u003cp\u003eebi-a-GCST90006911\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23.3671%;\"\u003e\n \u003cp\u003eHelicobacter pylori CagA antibody levels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e3.016\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.933\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5983%;\"\u003e\n \u003cp\u003e3.886\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 4.5045%;\"\u003e\n \u003cp\u003e0.919\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10.9797%;\"\u003e\n \u003cp\u003e0.053\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 3.8476%;\"\u003e\n \u003cp\u003e0.057\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.625%;\"\u003e\n \u003cp\u003e0.378\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 The association between other H.pylri antibodies levels and pancreatic diseases.\u003c/h2\u003e \u003cp\u003eWe also applied MR analysis to investigate the relationships between serum H. pylori IgG, GroEL, Urea, VacA, CagA, and Catalase antibodies with PC, AAP, AP, ACP, and CP. We did not find any significant associations between IgG and PC (OR, 1.027; 95% CI, 0.815\u0026ndash;1.295; p\u0026thinsp;=\u0026thinsp;0.820), AAP (OR, 1.239; 95% CI, 0.815\u0026ndash;1.883; p\u0026thinsp;=\u0026thinsp;0.316), AP (OR, 1.058; 95% CI, 0.923\u0026ndash;1.212; p\u0026thinsp;=\u0026thinsp;0.418), ACP (OR, 1.022; 95% CI, 0.806\u0026ndash;1.296; p\u0026thinsp;=\u0026thinsp;0.860), and CP (OR, 1.000; 95% CI, 0.797\u0026ndash;1.255; p\u0026thinsp;=\u0026thinsp;0.998) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Similarly, GroEL showed no significant correlation with PC, AAP, AP, ACP, and CP (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Figures\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and \u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e depict the relationships between Urea, VacA, CagA, Catalase, and PC, AAP, AP, ACP, and CP. Different algorithms demonstrated no significant associations between these exposures and outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 CRP mediates the causal effects of Helicobacter pylori infection on ACP in MVMR.\u003c/h2\u003e \u003cp\u003eTo elucidate the potential mediating mechanisms underlying the causal relationship between Helicobacter pylori infection and ACP, we conducted MVMR analyses by integrating instrumental variables (IVs) for OMP and CRP (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). The MVMR study, utilizing the IVW method, revealed a dissipation of the observed association between OMP and ACP (OR\u0026thinsp;=\u0026thinsp;1.067, 95% CI\u0026thinsp;=\u0026thinsp;0.774\u0026ndash;1.472, P\u0026thinsp;=\u0026thinsp;0.691). Consistent results were obtained using MR-Egger and Lasso methods in alignment with the IVW method. However, when merging IVs for OMP and MCP-1, the IVW analysis exhibited a persistent association between OMP and ACP (OR\u0026thinsp;=\u0026thinsp;0.633, 95% CI\u0026thinsp;=\u0026thinsp;0.495\u0026ndash;0.808, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). MR-Egger and Lasso methods yielded congruent outcomes. Similarly, the combined analysis of OMP with IVs for PU, GU, and DU using IVW demonstrated an enduring causal relationship between OMP and ACP (PU: OR\u0026thinsp;=\u0026thinsp;0.677, 95% CI\u0026thinsp;=\u0026thinsp;0.530\u0026ndash;0.865, P\u0026thinsp;=\u0026thinsp;0.002; GU: OR\u0026thinsp;=\u0026thinsp;0.609, 95% CI\u0026thinsp;=\u0026thinsp;0.470\u0026ndash;0.788, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; DU: OR\u0026thinsp;=\u0026thinsp;0.704, 95% CI\u0026thinsp;=\u0026thinsp;0.555\u0026ndash;0.892, P\u0026thinsp;=\u0026thinsp;0.004). MR-Egger and Lasso methods corroborated these findings consistently.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eHistorical animal experiments have suggested that Helicobacter pylori infection may lead to microcirculatory disturbances in acute pancreatitis, thereby exacerbating the severity of ischemic pancreatitis \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Additionally, in a case-control study encompassing 40 patients each with chronic alcoholic pancreatitis, alcoholic cirrhosis, and asymptomatic non-drinking individuals, endoscopic examinations and biopsies were conducted to assess Helicobacter pylori infection. Surprisingly, no association was found between Helicobacter pylori infection and the occurrence of chronic alcoholic pancreatitis. Conversely, individuals with Helicobacter pylori-negative severe chronic gastritis were more prevalent in cases of chronic alcoholic pancreatitis \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Elevated levels of CRP serve as a predictive indicator for AP, with a concomitant increase in CRP values corresponding to a diminished prognosis for AP\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. In individuals with CP, the serum levels of CRP are notably elevated compared to the levels observed in the serum of healthy individuals\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. However, no studies have demonstrated serum CRP levels in ACP patients. Contrary to these findings, our study reveals a significant correlation between serum levels of anti-Helicobacter pylori OMP and ACP. As serum anti-Helicobacter pylori OMP levels increase, the risk of developing ACP decreases. Further MVMR analysis indicates that CRP mediates the causal relationship between OMP and ACP. Consequently, our conclusion posits that OMP serves as a protective factor against ACP, and this process is mediated through a signal transduction pathway facilitated by CRP. This finding contrasts with the conclusions drawn from previous case-control studies, and potential reasons for this discrepancy may include the following.\u003c/p\u003e \u003cp\u003eFirstly, our study only identified an association between OMP and ACP, while several other serum anti-Helicobacter pylori antibodies showed no correlation with ACP. The reasons for this discrepancy require further investigation. Secondly, the case-control study mentioned earlier was published in 1998, and the authors detected Helicobacter pylori infection through gastric biopsy specimens, whereas we utilized serum anti-Helicobacter pylori antibody levels. This difference in methodology may contribute to the disparities in our conclusions. Furthermore, the analytical approach of the Mendelian Randomization study closely resembles a randomized controlled trial, allowing for the elimination of confounding factors, which might explain our findings associating OMP with ACP. Lastly, differences in diet and lifestyle among the populations studied could also be contributing factors.\u003c/p\u003e \u003cp\u003ePrevious studies have suggested an association between PC risk and Helicobacter pylori seropositivity in individuals with non-O blood type, while no such correlation was observed in individuals with blood type O \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. In contrast, a meta-analysis in 2022 indicated an increased incidence of PC associated with Helicobacter pylori infection, but there was no link between CagA/VacA-positive Helicobacter pylori infection and PC \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, an analysis of anti-Hp-IgG (Helicobacter pylori-specific antibodies), Hp-IgM (Helicobacter pylori antibodies), and CagA-Hp-IgG (antibodies against Helicobacter pylori cytotoxin-associated protein A) revealed that infection with CagA-positive Helicobacter pylori strains is one of the risk factors for PC \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. Additionally, several potential mechanisms associated with PC include physiological changes related to Helicobacter pylori-induced gastritis, such as increased gastric secretion of gastrin and alterations in somatostatin (reduced somatostatin cell numbers in the gastric antrum) \u003csup\u003e39 40\u003c/sup\u003e. Moreover, factors such as increased DNA synthesis due to bacterial overgrowth, elevated formation of N-nitroso compounds, and chronic inflammation may independently contribute to the carcinogenic process \u003csup\u003e41 42\u003c/sup\u003e. It is noteworthy that, despite previous research suggesting a link between Helicobacter pylori and PC, our Mendelian Randomization study did not find a correlation between Helicobacter pylori infection and PC. This discrepancy could be attributed to differences in study populations, study designs, or other unconsidered factors. Therefore, further research is still required to elucidate the relationship between Helicobacter pylori and PC.\u003c/p\u003e \u003cp\u003eRegarding the controversy surrounding the relationship between Helicobacter pylori and PC or pancreatitis, we posit several potential explanations. Firstly, many previous observational studies lack prospective, randomized, and blinded designs, making them susceptible to confounding factors and selection bias, thereby compromising the reliability of the study outcomes. Secondly, the diverse diagnostic criteria for Helicobacter pylori infection pose a challenge. Presently, the primary non-invasive method for diagnosing Helicobacter pylori infection is the urea breath test. Past research, including our Mendelian Randomization study, has predominantly employed serum levels of anti-Helicobacter pylori antibodies to investigate their association with pancreatic diseases, introducing a potential limitation to the methodology. Lastly, disparities in age, gender, ethnicity, dietary habits, socioeconomic status, and other factors may contribute to the existing controversies.\u003c/p\u003e \u003cp\u003eIn our study, we employed the MR approach. Similar to a randomized controlled trial (RCT) where participants are randomly assigned to experimental or control groups, MR studies randomize individuals based on the influence of one or more genetic variants on risk factors. This randomization helps determine whether carriers of these genetic variations have different disease risk compared to non-carriers. Unlike other observational studies, MR addresses issues of reverse causation. Given the high global prevalence of H. pylori infection, establishing whether there is a correlation between H. pylori infection and PC, or pancreatitis is crucial for early prevention and intervention. Our findings suggest a potential association between H. pylori infection and ACP, with serum H. pylori OMP antibody levels reducing the risk of ACP. This study provides valuable insights for future directions in the prevention, diagnosis, and treatment of ACP.\u003c/p\u003e \u003cp\u003eIn conclusion, the relationship between H. pylori infection and pancreatic diseases remains an area that necessitates extensive foundational experiments and randomized controlled trials for refinement. However, our study identified OMP as a protective factor against ACP. This discovery opens up new avenues for the future treatment of alcohol-induced chronic pancreatitis.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eOur study is designed to examine the relationship between H. pylori infection and PC as well as pancreatitis. Utilizing MR methodology, our research establishes the association between H. pylori infection and ACP.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of interest:\u003c/h2\u003e \u003cp\u003eAll authors declare no conflict of interest.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, MJZ and WLH.; writing\u0026mdash;original draft preparation, MJZ and DZ; writing, DZ and ALC; review and editing, XJW, ALC and MJZ.; manuscript polishing, MJZ; supervision, WLH. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eData availability statement:\u003c/h2\u003e \u003cp\u003eAll the information provided in the article are available.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eThe global, regional, and national burden of pancreatic cancer and its attributable risk factors in 195 countries and territories, 1990\u0026ndash;2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet Gastroenterol Hepatol 2019;4:934\u0026ndash;947.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlein AP. Pancreatic cancer: a growing burden. Lancet Gastroenterol Hepatol 2019;4:895\u0026ndash;896.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIodice S, Gandini S, Maisonneuve P, et al. Tobacco and the risk of pancreatic cancer: a review and meta-analysis. 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Chronic pancreatitis. Nat Rev Dis Primers 2017;3:17060.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh VK, Yadav D, Garg PK. Diagnosis and Management of Chronic Pancreatitis: A Review. Jama 2019;322:2422\u0026ndash;2434.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGukovskaya AS, Gukovsky I, Alg\u0026uuml;l H, et al. Autophagy, Inflammation, and Immune Dysfunction in the Pathogenesis of Pancreatitis. Gastroenterology 2017;153:1212\u0026ndash;1226.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu Y, Murray GK, Byrne EM, et al. GWAS of peptic ulcer disease implicates Helicobacter pylori infection, other gastrointestinal disorders and depression. Nat Commun 2021;12:1146.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGravina AG, Zagari RM, De Musis C, et al. Helicobacter pylori and extragastric diseases: A review. World J Gastroenterol 2018;24:3204\u0026ndash;3221.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEl Hafa F, Wang T, Ndifor VM, et al. Association between Helicobacter pylori antibodies determined by multiplex serology and gastric cancer risk: A meta-analysis. Helicobacter 2022;27:e12881.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGuo Y, Liu W, Wu J. Helicobacter pylori infection and pancreatic cancer risk: A meta-analysis. J Cancer Res Ther 2016;12:C229-c232.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang J, Zagai U, Hallmans G, et al. Helicobacter pylori infection, chronic corpus atrophic gastritis and pancreatic cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort: A nested case-control study. Int J Cancer 2017;140:1727\u0026ndash;1735.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith GD, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol 2004;33:30\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSekula P, Del Greco MF, Pattaro C, et al. Mendelian Randomization as an Approach to Assess Causality Using Observational Data. J Am Soc Nephrol 2016;27:3253\u0026ndash;3265.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalmer TM, Lawlor DA, Harbord RM, et al. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 2012;21:223\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 2011;40:755\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakaue S, Kanai M, Tanigawa Y, et al. A cross-population atlas of genetic associations for 220 human phenotypes. Nat Genet 2021;53:1415\u0026ndash;1424.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbecasis GR, Altshuler D, Auton A, et al. A map of human genome variation from population-scale sequencing. Nature 2010;467:1061\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 2015;44:512\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerbanck M, Chen CY, Neale B, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet 2018;50:693\u0026ndash;698.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWarzecha Z, Dembiński A, Ceranowicz P, et al. Deleterious effect of Helicobacter pylori infection on the course of acute pancreatitis in rats. Pancreatology 2002;2:386\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManes G, Dominguez-Mu\u0026ntilde;oz JE, Hackelsberger A, et al. Prevalence of Helicobacter pylori infection and gastric mucosal abnormalities in chronic pancreatitis. Am J Gastroenterol 1998;93:1097\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePuolakkainen P, Valtonen V, Paananen A, et al. C-reactive protein (CRP) and serum phospholipase A2 in the assessment of the severity of acute pancreatitis. Gut 1987;28:764\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreer JB, Greer P, Sandhu BS, et al. Nutrition and Inflammatory Biomarkers in Chronic Pancreatitis Patients. Nutr Clin Pract 2019;34:387\u0026ndash;399.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRisch HA, Yu H, Lu L, et al. ABO blood group, Helicobacter pylori seropositivity, and risk of pancreatic cancer: a case-control study. J Natl Cancer Inst 2010;102:502\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu W, Zhou X, Yin M, et al. The relationship between Helicobacter pylori and pancreatic cancer: a meta-analysis. Transl Cancer Res 2022;11:2810\u0026ndash;2822.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAi F, Hua X, Liu Y, et al. Preliminary study of pancreatic cancer associated with Helicobacter pylori infection. Cell Biochem Biophys 2015;71:397\u0026ndash;400.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTham TC, Chen L, Dennison N, et al. Effect of Helicobacter pylori eradication on antral somatostatin cell density in humans. Eur J Gastroenterol Hepatol 1998;10:289\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLarsson LI. Developmental biology of gastrin and somatostatin cells in the antropyloric mucosa of the stomach. Microsc Res Tech 2000;48:272\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRisch HA. Etiology of pancreatic cancer, with a hypothesis concerning the role of N-nitroso compounds and excess gastric acidity. J Natl Cancer Inst 2003;95:948\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDobrila-Dintinjana R, Vanis N, Dintinjana M, et al. Etiology and oncogenesis of pancreatic carcinoma. Coll Antropol 2012;36:1063\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\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":"anti-Helicobacter pylori antibodies levels, pancreatic cancer, pancreatitis, causal association, Mendelian randomization","lastPublishedDoi":"10.21203/rs.3.rs-3866393/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3866393/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObject:\u003c/h2\u003e \u003cp\u003eThe relationship between Helicobacter pylori and pancreatic diseases remains a subject of controversy. Our study aims to investigate the association between Helicobacter pylori infection and pancreatic cancer as well as pancreatitis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, we employed the two-sample Mendelian randomization (MR) method to assess the causal relationship between anti-Helicobacter pylori antibody levels and the occurrence of pancreatic cancer and pancreatitis. The primary analytical approach was determined to be the inverse variance-weighted (IVW) analysis under a fixed-effects model. To ensure the reliability of our study findings, we conducted multiple sensitivity analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur research reveals a significant correlation between elevated levels of anti-Helicobacter pylori outer membrane protein (OMP) and a reduced risk of alcohol-induced chronic pancreatitis (ACP) (OR, 0.654; 95% CI, 0.508\u0026ndash;0.841; p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Multivariable Mendelian randomization (MR) analysis indicates that C-reactive protein (CRP), as opposed to monocyte chemoattractant protein-1 (MCP-1), peptic ulcers, gastric ulcers, and duodenal ulcers, mediates the causal relationship between Helicobacter pylori infection and alcoholic chronic pancreatitis (ACP). Furthermore, our study findings exhibit no evidence of heterogeneity or pleiotropy.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe two-sample Mendelian randomization (MR) analysis reveals a causal relationship between anti-Helicobacter pylori OMP levels and ACP. Further investigations are warranted to elucidate and validate these findings.\u003c/p\u003e","manuscriptTitle":"The association between Helicobacter pylori infection and pancreatic diseases: a Mendelian Randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-23 06:43:10","doi":"10.21203/rs.3.rs-3866393/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":"d92705d6-28ed-4982-82c2-88515ac328df","owner":[],"postedDate":"January 23rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":28297096,"name":"Biological sciences/Cancer"},{"id":28297097,"name":"Biological sciences/Microbiology"},{"id":28297098,"name":"Health sciences/Gastroenterology"},{"id":28297099,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-03-05T05:05:20+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-23 06:43:10","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3866393","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3866393","identity":"rs-3866393","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}