Exposure of Early Growth Traits Genetics and Childhood Disorders is Causally Associated with the Gallbladder Outcomes: A Mendelian Randomization study

Exposure of Early Growth Traits Genetics and Childhood Disorders is Causally Associated with the Gallbladder Outcomes: 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 Research Article Exposure of Early Growth Traits Genetics and Childhood Disorders is Causally Associated with the Gallbladder Outcomes: A Mendelian Randomization study Ahmed Arslan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6234473/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 Gallstone disease has wide-spread prevalence with up to 20% world population is impacted. However, the causal relationship(s) between gallbladder disease traits and early growth trait and childhood disorders is not established yet. Therefore, with two-sample mendelian randomization (MR) settings, we explored the causal association between three gallbladder traits and 30 early growth traits and childhood disorders. A causal effect between the gallbladder diseases such as gallstones and traits including childhood BMI, childhood aggression was identified. Additionally, with mediation analyses we also identified 18 phenotypes that could mediate harmful effects of early growth traits on gallbladder complications. Together, early growth traits and childhood disorders causally impact gallbladder disease phenotypes and proper management of early growth health could possibility reduce gallbladder complications in adults. Statistical Epidemiology Epidemiology Figures Figure 1 Figure 2 What is already known on this topic Gallbladder complications impacting large number of people worldwide but the casual effects of early growth traits and childhood disorders such as childhood BMI are largely unknown. The mendelian randomization method uses genetic variants as instruments to estimate causal effect of exposure on outcome. What this study adds – Withmediation based mendelian randomization, evidence support the potential of early growth traits and childhood phenotypes including childhood BMI, childhood aggression causally effects the increased adulthood gallbladder complications including gallstones, gallbladder inflammation with and without the presence of gallstones. Introduction The diseases of childhood and adolescence are categorized as non-communicable disease such as obesity, allergies, and psychiatric diseases. The burden of these diseases cumulatively impacts individuals, families, and whole societies ( 1 ). Additionally, the early exposure to the diseases might persists throughout the life and results in the poor health condition as adult or an aged individual ( 2 ). Of example, the childhood obesity is associated with the adulthood cardiovascular diseases ( 3 ). Likewise, low birth weight has been shown to be associated with a number of later-life disorders including respiratory, cardiovascular, and psychological diseases ( 4 – 6 ). The childhood psychiatric disorders extend to life-long adolescence and adulthood mental illness such as schizophrenia ( 7 ). The persistence of childhood and adolescent traits and disorders throughout the later life suggest investigating their etiology might provide new prevention tools for later life health adversaries. Moreover, the identification of specific genetic variants, operating pathways could indicate efficient drug targets and help in eliminating the adverse effects. The gallstone disease or gallstones (cholelithiasis) is characterized by the presence of crystal deposits of bilirubin, bile and cholesterol within the gallbladder or biliary tree. The gallstones are among the most common causes of hospitalizations in the world ( 8 ). With high disease prevalence, it is estimated that 70% population between the age of 20 to 74 years of the United States have developed gallstones ( 9 ) whereas 20% European population have the disease. The main causes include metabolic dysfunction such as diabetes, high saturated fats, sugar rich diet, dyslipidemia, obesity, insulin resistance, and lower fiber diet. The lack of exercise, sudden weight loss and/or prolonged fasting featuring in lowering of gallstone movement and increasing biliary cholesterol secretion ( 10 , 11 ). The hormonal (estrogen) levels have been shown to influence bile cholesterol and contribute to the decrease mobility of gallbladder ( 12 ). The sex and inheritance also play their role, as women are more susceptible to gallstone disease compared to men whereas gallstones developed in up to 30% cases with the family disease history ( 13 ). A role of early growth trait genetics has not been assessed in the formation of adult life gallstones and related traits. The identification of the gallstone pathways that mediated and regulated by genetic markers of early growth genetics may ameliorate risk stratification in the general and high-risk population. The proposed framework may help in the development of better medications against gallstones and related disorders. Here we setup a two-sample MR experiment to test if a causal relationship of genetic determinants for gallstones (cholelithiasis), gallbladder inflammation (cholecystitis) and gallbladder inflammation without the presence of stones (acalculous cholecystitis) exits with that of genetics of 30 different childhood traits and phenotypes. Followed by a series of mediation analyses, which suggested 18 phenotypes mediating the causal effects of early growth traits and childhood disorders on gallbladder functions. Together, the results suggested that the early growth traits have an impact on the gallbladder disease and traits, and the impact is mediated by lifelong changes in various factors. Method and material Study design : We planned a two-phase MR study (Fig. 1 ). In the first phase, we identified a casual association of genetic markers of early growth traits and childhood disorders (EGTCD) with three gallbladder disease traits including cholelithiasis (gallstones), cholecystitis (inflammation of gallbladder) and acalculous cholecystitis (cholecystitis without gallstones). In the second phase, we performed a two-step MR study to identify mediating effects of candidate mediators on the casual association between the EGTCD and gallbladder disease traits. The MR study design included three parameters: first, the genetic associations of instruments must follow conventional threshold (p < 5e-08); second, genetic instruments must be independent of confounders and finally the instruments must affect the outcomes exclusively through the risk factors. Data sources The study was retrieved from the publicly available GWAS summary stats datasets; therefore, no specific ethical approval was required to perform the study. The summary of the data and sample size are provided in the Table S1. Exposure data We selected 30 childhood traits and childhood disorders as exposure phenotypes. The comprehensive phenotypes list includes genome-wide association (GWAS) summary statistic data of 6 phenotypes of birth weight, 6 phenotypes of gestational period weight, two phenotypes of gestation duration, two phenotypes of birth/delivery, three phenotypes of early-, pre-, post-term birth, 6 phenotypes of placental weight, childhood sleep duration, childhood aggression, childhood behavioral problems, Tanner stage, childhood (age 6–10 year) body-mass index (BMI), and two phenotypes of head circumference (infant − 6–30 months age and at birth). More specifically, the data for weight gain during the gestation period (28 weeks) were generated by meta-analyzing the GWAS data for total gestational weight gain (GWG), early (difference between pre-early upto 20 weeks) and late (difference between 20 to 28 weeks) GWG for both mother and offspring ( 14 ). The weight at birth included GWAS summary stats meta-data of four traits, own birth weight (BW), offspring BW, fetal effect and maternal effect ( 15 ). Own birth weight represents individual's own genetic effect on their birth weight, the material genetic effect on offspring BW is encoded as offspring BW. Whereas the individual's own genetic effect adjusted for correlated maternal genotype and mother's genetic effect adjusted for correlated offspring's genotypes are termed as fetal effect and maternal effect, respectively ( 15 ). The childhood BMI study meta-analyzed genotyping data from 26 studies containing the samples (N = 39620) of age 6–10 years old ( 16 ). The data for maternal (excluding 23andme data) on the gestation duration (spontaneous deliveries), pre-term delivery ( 294 days) were retrieved ( 17 ). For fetal genetic effects on gestation duration, the meta-data from two consortia namely early growth genetics (EGG) consortium and the Lundbeck foundation initiative for integrative psychiatric research (iPSYCH) for the traits including early pre-term (< 34 gestation weeks), pre-term (< 37 gestation weeks) and post-term (≥ 42 gestation weeks) deliveries were included in the MR analyses ( 18 ). The GWAS meta-analysis-based summary data for Tanner Stage, a measure of sexual maturation, was obtained for boys (age 12.6-15years) and girls (age 10.5–12.5years) ( 19 ). The GWAS summary data for combined sex meta-analysis were used in our MR analysis. The placental weight summary datasets for fetal effect, material and paternal effect were included ( 20 ), the GWAS for fetal effect, material effect and paternal effect on placental weight were adjusted for sex and gestation duration and second set of GWAS datasets were adjusted for sex only. For the sleep duration, the meta-data from GWAS on children of ages from 7–11, were obtained from the study which surveyed parents to answer, “How many hours does your child sleep per day including naps?” ( 21 ). The childhood aggression phenotype data utilized from a study meta-analyzing big cohorts of two developmental stages (early childhood, age from 3–7 years and middle childhood, age from 8-15years). The meta-analyses based on the phenotypic data obtained from parents’ awareness of their child's behavior and filling the survey questionnaire form ( 22 ). The childhood psychiatric/behavioral problems, data obtained from the study combining data on school going children (age 5–13 years) from 20 cohorts ( 23 ). The data obtained from the parent-rated questionnaire and includes traits such as depressive symptoms, anxiety, autism spectrum disorder, intelligence, years of schooling, smoking and more, complete list of traits is reported elsewhere ( 23 ). Lastly, the head circumference (HC) data were reported for the children with age between 6 and 30 months old (infant) and at birth ( 24 ). The GWAS summary stats consist of meta-analysis of 26 studies for infant children and 21 studies of at birth HC genome-wide associations. For Further details about the sample size, number of SNPs, and references are reported in Table S1. Selection of instrumental variables (IVs) To qualify SNPs as instrumental variables (IVs) or instruments they need to follow well established criteria. The SNPs need to be strongly associated with the exposure (conventionally pval < 5e-08, however, to ensure the sufficient number of SNPs we used a liberal value 5e-05 ( 25 )). The candidate IVs must show a certain level of independence from other SNPs that could be assess by linkage disequilibrium (LD) with parameter (r 2 < 0.0001 within 10kb distance). The exposure and outcome datasets need to be harmonized in order to assign effect value to the same allele as well as avoiding palindromic SNPs. The strength of qualified IVs can further be assessed by the F statistics with commonly used threshold of F statistics > 10 ensures sufficiently strong IVs to conduct MR analysis. Outcome data We utilized GWAS summary data from three different gallbladder traits [Table S1] as outcomes. For the gallstone disease, the data was consisting of the meta-analysis of the 43639 cases and 506798 controls from UK biobank and FinnGen consortia ( 26 ). The cases were recruited based on the diagnostic codes such as ICT10, primary care, and UKB self-reported cases. Those individual with diagnostic codes for gallstone disease and patients treating for the gallstone diseases were included in the final cases for the study. The individuals with no gallstone disease diagnostic codes or treatment were considered as controls. For cholecystitis, the GWAS summary data included 4052 cases and 482432 controls from UK biobank. The cases were defined based on the diagnostic code (K81) and controls were the individuals without the code ( 27 ). For the third and final trait considered in the study i.e., cholecystitis without cholelithiasis, the data consisting of 2650 cases and 453698 controls of European ancestry. The individuals with the code PheCode 574.3 were considered as cases for cholecystitis without cholelithiasis phenotype ( 28 ). Mediator phenotypes: We surveyed broader range of traits to find potential mediators of exposure to outcome pathways. The GWAS summary statistic data of 585 traits were retrieved and formatted, more detailed can be found in Table S1. To qualify a trait as a mediator of the pathway, we developed the following strategy. In the two-sample MR, the trait act as outcome must be associated strongly (IVW p ≤ 0.05) to the EGTCD phenotype in the first MR step. Before moving to the second step of two-step MR, the strongly associated traits to the EGTCD must not show bidirectional MR trend. In second step, the trait acts an exposure has same beta direction and show strong association (IVW p ≤ 0.05) with the gallbladder trait as outcome. Together, a trait to be considered as a mediator must have a strong association both as outcome (first step) and as exposure (second step) without showing bidirectional MR in the first step to eliminate possible confounding effect. Statistical analysis Two-sample MR To assess the casual relationship between the EGTCD and gallbladder traits, we employed four effective MR methods including MR Egger, weighted mode, weighted median and random-effect inverse- variance weighted (IVW). The primary MR estimate as obtained from IVW, which allows the casual effect estimates based on the meta-analysis of individual estimates without the need of individual-level data ( 29 ). For the consistency point of view, we compared with IVW results with the other approaches, MR Egger, weighted mode, weighted median, used in our MR analyses. To correct for pleiotropy and assess heterogeneity, we performed sensitivity analyses which included pleiotropy tests (i.e. MR Egger intercept test, MR-PRESSO distortion test( 30 , 31 ) and leave-one-out test) and heterogeneity tests (global test MR-PRESSO (MR pleiotropy residual sum and outlier) and Cochrane’s Q test). Mediation Analysis The mediation assessment from the EGTCD to gallbladder traits were performed with two-step MR. In this, first the casual effect was estimated between the EGTCD and mediator phenotypes (β E−M ). Next, the mediators that showed statistically significant casual association in first step were selected for second step. In step-two, the casual effect between mediators and gallbladder traits were estimated (β M−O ). The proportion of mediation was calculated with the product method where two βs were multiplied and divided by total β from GATD trait on gallbladder outcomes. For all the two-sample MR, MR-PRESSO and two-step MR calculations, Two-sample MR r package was used (version 0.5.7) in the custom codes: https://github.com/AhmedArslan/MRsimplify . The significance results were determined with the pvalue ≤ 0.05 and results are presented in β coefficient, S.E., pvalue along with their 95% confidence interval (C.I.). Results Causal relationship between the EGTCD and gallbladder traits Using two-sample MR settings, we obtained harmful associations between early growth traits and disorders, and gallbladder disease traits including gallstone disease, gallbladder inflammation and gallbladder inflammation without the presence of gallstones [Table S2]. More specifically, for increased gallstone disease: the childhood BMI (β (IVW) = 0.09, 95% CI = 0.0054 to 0.222, p = 7.42e-06), childhood aggression (β (IVW) = 0.14, 95% CI = 0.041 to 0.254, p = 0.006), and fetal genetic effect on preterm birth (β (IVW) = 0.002, 95% CI = 0.002 to 0.254, p = 0.03) were significantly associated [Fig. 2 ]. For decreased gallstone disease: individual's own genetic effect (fetal effect) on their birth weight (β (IVW) = -0.08, 95% CI = -0.16 to -0.003, p = 0.04) and fetal birth weight (β (IVW) = -0.09, 95% CI = 0.002 to 0.254, p = 0.01) showed statistical casual associations. For increased gallbladder inflammation trait: childhood BMI (β (IVW) = 0.108, 95% CI = 0.055 to 0.14, p = 0.03), late gestation total weight gain (maternal) (β (IVW) = 0.131, 95% CI = 0.008 to 0.025, p = 0.03) were causally associated whereas for decreased gallbladder inflammation, total weight gain (offspring) (β (IVW) = -0.11, 95% CI = -0.22 to -0.006, p = 0.03) and gestation duration (maternal GWAS) (β (IVW) = -0.17, 95% CI = -0.03 to -0.034, p = 0.003) were significantly associated. Finally, for the phenotype of decreased gallbladder inflammation without the presence of gallstones: fetal birth weight (β (IVW) = -0.18, 95% CI = -0.01 to 0.14, p = 0.04) and gestation duration (maternal GWAS) (β (IVW) = -0.104, 95% CI = -0.018 to -0.023, p = 0.01) showed casual association whereas no phenotype showed significant association with increased gallbladder inflammation without the presence of gallstones. For all the analyses, the strong strength of genetic instruments was showed by the F statistics (F > 10). The sensitivity analyses reflected that there is heterogeneity between exposure and outcomes phenotypes however not appreciable pleiotropy was overserved among them. Also, reflected by the symmetry observed in the funnel plots [Fig. S1]. Few genetic instruments can exert more impact than others that can destabilize the MR prediction, in leave-one-out plot we did not observe such instruments that significantly influence the causal relationship assessment [Fig S1]. Mediator traits identification and effects With the two-step MR settings, first we identified mediators from a large selection of traits that showed significant association with the EGTCD. In second step, we identified mediators from the first step with same direction of effect size (beta value) that did not show bidirectional MR trend and showed significant causal association with gallbladder traits. By doing so, we identified 9, 4 and 4 significantly associated mediators for childhood BMI, preterm delivery (fetal effect) and childhood aggression with gallstones, respectively. For gallbladder inflammation, we identified 5, 1, and 3 potential mediators for childhood BMI, preterm delivery (fetal effect) and childhood aggression, respectively. For inflammation without gallstones, 4, 2, and 1 phenotype showed significant mediation trends [Table S3]. The sensitivity analyses showed that the mediation results obtained with IVW method were reliable. Mediation analysis The phenotypes of mood swings (4.1%), high-density lipoprotein (HDL) levels (9.06%), apolipoprotein A levels (7.5%), shortness of breath walking on level ground - UKB data field 4717 (9.6%), insulin-like growth factor 1 (IGF1) levels (3.6%), alcohol drinker status previous - UKB data field 20117_1 (3.3%), Pain in joint - PheCode 745 (2.2%) and treatment or medication use of paracetamol - UKB data field 20003_2038460150 (4.6%), are mediating the casual effects of childhood BMI on gallstones. The casual effects of childhood BMI on gallbladder inflammation were found mediated by mood swings (5.8%), high-density lipoprotein (HDL) levels (13.0%), apolipoprotein A levels (8.9%) and shortness of breath walking on level ground - UKB data field 4717 (11.4%). Whereas the phenotypes of mood swings (4.5%), high-density lipoprotein (HDL) levels (18.2%), apolipoprotein A levels (15.4%) and Illnesses of mother: Diabetes (UKB data field 20110_9 (11.3%) were shown to mediate effects of childhood BMI on gallbladder inflammation without the presence of gallstones. The causal effects of preterm delivery (fetal effect) on gallstones were found to be mediated by the traits including calculus of bile duct - PheCode 574.2 (13.2%), meat consumers - UKB data field 103000 (1.58%), and mouth or teeth dental problems loose teeth - UKB data field 6149_4 (1.1%). For the effects of preterm delivery (fetal effect) on gallbladder inflammation and gallbladder inflammation without the presence of gallstones, we identified mediators namely calculus of bile duct - PheCode 574.2 (11%), and calculus of bile duct - PheCode 574.2 (16.3%), functional disorders of bladder - PheCode 596.5 (2.8%), respectively. The mediation traits including sugar or foods drinks containing sugar - UKB data field 6144_4 (11.5%), smoking status: current - UKB data field 20116_2 (13.1%), acute pancreatitis - PheCode 577.1 (37.75%), alcohol drinker status: previous - UKB data field 20117_1 (8.57%), heart failure (5.2%), and other disorders of biliary tract - PheCode 575.8 (28.57%) were identified as potential mediators of causal effects of childhood aggression on gallstones. The sugar or foods drinks containing sugar - UKB data field 6144_4 (14.5%), heart failure (11.5%) and acute pancreatitis - PheCode 577.1 (29.59%) were found to be mediating phenotypes between childhood aggression on gallbladder inflammation. The acute pancreatitis - PheCode 577.1 (40.8%) mediated the effects of childhood aggression on gallbladder inflammation without the presence of gallstones. Discussion In this study, we evaluated the causal effect of early growth traits and childhood disorders on gallstone traits. Our stable results, obtained by utilizing the GWAS summary stats data, MR framework and sensitivity analyses, indicated that the EGTCD causally effecting the adult age gallbladder phenotypes. To our knowledge, the impact of early growth traits and disorders on gallbladder traits have not suggested in a MR study, previously. Age independent body weight is a major risk factor for gallstones formation. Additionally, rapid fluctuation in body weight especially rapid weight loss could increase gallstone formation risk. Moreover, a longitudinal study focusing on adults (N = 4106) suggested that an increased BMI is a risk factor for gallstone diseases ( 32 ) with females are at disease risk more than men. The gallstone complications in children and adolescents have been implicated by childhood obesity or overweight ( 33 , 34 ). Here we suggested the gallbladder complications including cholelithiasis and cholecystitis could be impacted by the presence of higher body mass index value in children between the age of 6–10 years. We suspect causal association of childhood BMI with gallstone complications predispose formation of adulthood gallbladder complications in later age. Therefore, later life events such as rapid weight loss or further weight gain, medication, HDL, alcohol drinking could contribute to the complications. However, future research would further strengthen this observation. Childhood aggression includes traits from difficult temperament to directed aggression towards a person or a thing ( 35 ). The early age behavioral problems have been associated with gastrointestinal issues including constipation and stomach pain. Whereas no research on the childhood aggression and gallstones have been reported. Here we showed that childhood aggression is casually associated with the gallstone formation. Previous studies on the maternal weight gain during pregnancy have shown later life child health implications ( 36 ). These complications include diabetes and obesity, here we shown that maternal weight gain during the late adage of pregnancy has causal association with gallbladder inflammation. Here we suggest a contribution to the later age onset on gallbladder inflammation in individuals born to mother who gain weight in the later stage of their pregnancy. The duration of gestation period and fetal birth weight showed reverse casual association with gallbladder inflammation and gallbladder inflammation without gallstones. Previous studies have shown the preterm birth have association with the long-term adverse health impacts including diabetes, blood pressure as well as neurodevelopmental and psychiatric disorders ( 36 ). A reverse causality of gestation duration and gallbladder inflammation suggest a decreased risk of developing gallbladder inflammation in later life, which is novel and interesting finding. On which future studies would reflect how gestation duration and fetal birth weight impact gallbladder inflammation traits. There can be many limitations to our study. The study was performed with the two-sample MR method which is a robust framework to assess the causal association between exposure and outcome phenotypes. The residual pleiotropy and sample-size are to major limitations that would not be addressed with the present framework, however with the advancement of additional MR methods and bigger cohorts would certainly contribute to eliminate such constrains in future studies. Additionally, we replied on samples from one ancestry which could not reflects the causal associations from different ancestries, future studies should also consider including different ancestries. In conclusion, we performed an exposure and outcome phenotypes MR analysis and identified casual associations of gallstones, gallbladder inflammation as well as gallbladder inflammation without the presence of gallstones with early growth traits and childhood traits including childhood BMI, childhood aggression, gestation period, fetal weight at birth and material weight gain during pregnancy. These novel insights into the etiology of gallstone disease traits should contribute to the better understanding of the role of studied exposures in gallbladder functions. Declarations Competing interests: There are no competing interests for any author. Ethical approval: The study was retrieved from the publicly available GWAS summary stats datasets; therefore, no specific ethical approval was required to perform the study. 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Hepatology 58(6):2133–2141 Krawczyk M, Kułaga Z, Niewiadomska O, Jankowska I, Lebensztejn D, Więcek S et al (2023) Are children with gallstone disease more overweight? Results of a matched case-control analysis. Clin Res Hepatol Gastroenterol 47(8):102204 Koebnick C, Smith N, Black MH, Porter AH, Richie BA, Hudson S et al (2012) Pediatric obesity and gallstone disease. J Pediatr Gastroenterol Nutr 55(3):328–333 Reebye P (2005) Aggression during early years - infancy and preschool. Can Child Adolesc Psychiatr Rev 14(1):16–20 Leddy MA, Power ML, Schulkin J (2008) The impact of maternal obesity on maternal and fetal health. Rev Obstet Gynecol 1(4):170–178 Additional Declarations The authors declare no competing interests. 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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-6234473","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":429423072,"identity":"32c1f27f-22e4-4c20-90ba-0597574cb261","order_by":0,"name":"Ahmed Arslan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4ElEQVRIiWNgGAWjYDACCSDmATHYgfgDg0UCWIQ4LcwMDIwzGCRI1MLMQ4wW/tndiQ/eMNjlyzczP3ts2yaRxyDdfAC/JXfObjacw5BsueEwm7lxbptEMYPMsQT81tzI3SbNw8BsYMDMYCYN1JLYIJFjgFeH/I3c7b95GOoN5JvZv0lbgrXkf8CrxQBoC9DXhw0YDvOYSTNCbMHvLsMbuZsl5xgcNzA4zFMm2XNOophN5hh+h8ndyN344U1FtYF8e/s2iR9lNnn80s0P8FsDcR4Sm40I9aNgFIyCUTAKCAAA2Pc9g9M4kgYAAAAASUVORK5CYII=","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Ahmed","middleName":"","lastName":"Arslan","suffix":""}],"badges":[],"createdAt":"2025-03-15 19:20:39","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6234473/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6234473/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78725473,"identity":"2b6575fe-3efc-481a-acd1-d3016bc564d5","added_by":"auto","created_at":"2025-03-18 06:05:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":73466,"visible":true,"origin":"","legend":"\u003cp\u003eStudy flowchart. In the phase 1, first the IVs of early growth traits and disorders were used to perform two-sample MR to identify causal effects on gallbladder traits. Next, in a two-step MR, the mediators were identified that potentially mediate (without bidirectional MR denoted by cross symbol) the effects of early growth traits and disorders on gallbladder functions.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6234473/v1/a05f08263890886266d2196b.png"},{"id":78725467,"identity":"0074a2d2-4c97-4707-97f7-ceccd32ca256","added_by":"auto","created_at":"2025-03-18 06:05:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":739059,"visible":true,"origin":"","legend":"\u003cp\u003eCausal effects of early growth traits with gallbladder disease traits.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-6234473/v1/c2f048635d80ef9c7dbf25ad.png"},{"id":78726292,"identity":"e758c955-1185-4940-983f-bafda1f50d49","added_by":"auto","created_at":"2025-03-18 06:21:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1204064,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6234473/v1/0fddfa9d-7b59-4a71-b72a-a8f64f498b04.pdf"},{"id":78725465,"identity":"8caf8a6d-e527-446d-a79c-25f12c899456","added_by":"auto","created_at":"2025-03-18 06:05:20","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":21264,"visible":true,"origin":"","legend":"","description":"","filename":"TableS.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6234473/v1/8ff858c1c2dd5031016eb263.xlsx"},{"id":78725474,"identity":"995a6a7a-ca7b-49dd-806e-f129f039d4bb","added_by":"auto","created_at":"2025-03-18 06:05:21","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":9547358,"visible":true,"origin":"","legend":"","description":"","filename":"FigureS1.docx","url":"https://assets-eu.researchsquare.com/files/rs-6234473/v1/d92389d9cc7a041c9e4c5d91.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eExposure of Early Growth Traits Genetics and Childhood Disorders is Causally Associated with the Gallbladder Outcomes: A Mendelian Randomization study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"What is already known on this topic ","content":"\u003cp\u003eGallbladder complications impacting large number of people worldwide but the casual effects of early growth traits and childhood disorders such as childhood BMI are largely unknown.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe mendelian randomization method uses genetic variants as instruments to estimate causal effect of exposure on outcome.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWhat this study adds –\u0026nbsp;\u003c/strong\u003eWithmediation based mendelian randomization, evidence support the potential of early growth traits and childhood phenotypes including childhood BMI, childhood aggression causally effects the increased adulthood gallbladder complications including gallstones, gallbladder inflammation with and without the presence of gallstones. \u0026nbsp;\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe diseases of childhood and adolescence are categorized as non-communicable disease such as obesity, allergies, and psychiatric diseases. The burden of these diseases cumulatively impacts individuals, families, and whole societies (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Additionally, the early exposure to the diseases might persists throughout the life and results in the poor health condition as adult or an aged individual (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Of example, the childhood obesity is associated with the adulthood cardiovascular diseases (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Likewise, low birth weight has been shown to be associated with a number of later-life disorders including respiratory, cardiovascular, and psychological diseases (\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). The childhood psychiatric disorders extend to life-long adolescence and adulthood mental illness such as schizophrenia (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The persistence of childhood and adolescent traits and disorders throughout the later life suggest investigating their etiology might provide new prevention tools for later life health adversaries. Moreover, the identification of specific genetic variants, operating pathways could indicate efficient drug targets and help in eliminating the adverse effects.\u003c/p\u003e \u003cp\u003eThe gallstone disease or gallstones (cholelithiasis) is characterized by the presence of crystal deposits of bilirubin, bile and cholesterol within the gallbladder or biliary tree. The gallstones are among the most common causes of hospitalizations in the world (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). With high disease prevalence, it is estimated that 70% population between the age of 20 to 74 years of the United States have developed gallstones (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) whereas 20% European population have the disease. The main causes include metabolic dysfunction such as diabetes, high saturated fats, sugar rich diet, dyslipidemia, obesity, insulin resistance, and lower fiber diet. The lack of exercise, sudden weight loss and/or prolonged fasting featuring in lowering of gallstone movement and increasing biliary cholesterol secretion (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The hormonal (estrogen) levels have been shown to influence bile cholesterol and contribute to the decrease mobility of gallbladder (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). The sex and inheritance also play their role, as women are more susceptible to gallstone disease compared to men whereas gallstones developed in up to 30% cases with the family disease history (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA role of early growth trait genetics has not been assessed in the formation of adult life gallstones and related traits. The identification of the gallstone pathways that mediated and regulated by genetic markers of early growth genetics may ameliorate risk stratification in the general and high-risk population. The proposed framework may help in the development of better medications against gallstones and related disorders. Here we setup a two-sample MR experiment to test if a causal relationship of genetic determinants for gallstones (cholelithiasis), gallbladder inflammation (cholecystitis) and gallbladder inflammation without the presence of stones (acalculous cholecystitis) exits with that of genetics of 30 different childhood traits and phenotypes. Followed by a series of mediation analyses, which suggested 18 phenotypes mediating the causal effects of early growth traits and childhood disorders on gallbladder functions. Together, the results suggested that the early growth traits have an impact on the gallbladder disease and traits, and the impact is mediated by lifelong changes in various factors.\u003c/p\u003e"},{"header":"Method and material","content":"\u003cp\u003e \u003cem\u003eStudy design\u003c/em\u003e: We planned a two-phase MR study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In the first phase, we identified a casual association of genetic markers of early growth traits and childhood disorders (EGTCD) with three gallbladder disease traits including cholelithiasis (gallstones), cholecystitis (inflammation of gallbladder) and acalculous cholecystitis (cholecystitis without gallstones). In the second phase, we performed a two-step MR study to identify mediating effects of candidate mediators on the casual association between the EGTCD and gallbladder disease traits. The MR study design included three parameters: first, the genetic associations of instruments must follow conventional threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;5e-08); second, genetic instruments must be independent of confounders and finally the instruments must affect the outcomes exclusively through the risk factors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData sources\u003c/strong\u003e \u003cp\u003eThe study was retrieved from the publicly available GWAS summary stats datasets; therefore, no specific ethical approval was required to perform the study. The summary of the data and sample size are provided in the Table S1.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExposure data\u003c/strong\u003e \u003cp\u003eWe selected 30 childhood traits and childhood disorders as exposure phenotypes. The comprehensive phenotypes list includes genome-wide association (GWAS) summary statistic data of 6 phenotypes of birth weight, 6 phenotypes of gestational period weight, two phenotypes of gestation duration, two phenotypes of birth/delivery, three phenotypes of early-, pre-, post-term birth, 6 phenotypes of placental weight, childhood sleep duration, childhood aggression, childhood behavioral problems, Tanner stage, childhood (age 6\u0026ndash;10 year) body-mass index (BMI), and two phenotypes of head circumference (infant \u0026minus;\u0026thinsp;6\u0026ndash;30 months age and at birth).\u003c/p\u003e \u003c/p\u003e \u003cp\u003eMore specifically, the data for weight gain during the gestation period (28 weeks) were generated by meta-analyzing the GWAS data for total gestational weight gain (GWG), early (difference between pre-early upto 20 weeks) and late (difference between 20 to 28 weeks) GWG for both mother and offspring (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). The weight at birth included GWAS summary stats meta-data of four traits, own birth weight (BW), offspring BW, fetal effect and maternal effect (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Own birth weight represents individual's own genetic effect on their birth weight, the material genetic effect on offspring BW is encoded as offspring BW. Whereas the individual's own genetic effect adjusted for correlated maternal genotype and mother's genetic effect adjusted for correlated offspring's genotypes are termed as fetal effect and maternal effect, respectively (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). The childhood BMI study meta-analyzed genotyping data from 26 studies containing the samples (N\u0026thinsp;=\u0026thinsp;39620) of age 6\u0026ndash;10 years old (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). The data for maternal (excluding 23andme data) on the gestation duration (spontaneous deliveries), pre-term delivery (\u0026lt;\u0026thinsp;259 days), and post-term delivery (\u0026gt;\u0026thinsp;294 days) were retrieved (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). For fetal genetic effects on gestation duration, the meta-data from two consortia namely early growth genetics (EGG) consortium and the Lundbeck foundation initiative for integrative psychiatric research (iPSYCH) for the traits including early pre-term (\u0026lt;\u0026thinsp;34 gestation weeks), pre-term (\u0026lt;\u0026thinsp;37 gestation weeks) and post-term (\u0026ge;\u0026thinsp;42 gestation weeks) deliveries were included in the MR analyses (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The GWAS meta-analysis-based summary data for Tanner Stage, a measure of sexual maturation, was obtained for boys (age 12.6-15years) and girls (age 10.5\u0026ndash;12.5years) (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). The GWAS summary data for combined sex meta-analysis were used in our MR analysis. The placental weight summary datasets for fetal effect, material and paternal effect were included (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), the GWAS for fetal effect, material effect and paternal effect on placental weight were adjusted for sex and gestation duration and second set of GWAS datasets were adjusted for sex only. For the sleep duration, the meta-data from GWAS on children of ages from 7\u0026ndash;11, were obtained from the study which surveyed parents to answer, \u0026ldquo;How many hours does your child sleep per day including naps?\u0026rdquo; (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The childhood aggression phenotype data utilized from a study meta-analyzing big cohorts of two developmental stages (early childhood, age from 3\u0026ndash;7 years and middle childhood, age from 8-15years). The meta-analyses based on the phenotypic data obtained from parents\u0026rsquo; awareness of their child's behavior and filling the survey questionnaire form (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). The childhood psychiatric/behavioral problems, data obtained from the study combining data on school going children (age 5\u0026ndash;13 years) from 20 cohorts (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The data obtained from the parent-rated questionnaire and includes traits such as depressive symptoms, anxiety, autism spectrum disorder, intelligence, years of schooling, smoking and more, complete list of traits is reported elsewhere (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Lastly, the head circumference (HC) data were reported for the children with age between 6 and 30 months old (infant) and at birth (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). The GWAS summary stats consist of meta-analysis of 26 studies for infant children and 21 studies of at birth HC genome-wide associations. For Further details about the sample size, number of SNPs, and references are reported in Table S1.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSelection of instrumental variables (IVs)\u003c/strong\u003e \u003cp\u003eTo qualify SNPs as instrumental variables (IVs) or instruments they need to follow well established criteria. The SNPs need to be strongly associated with the exposure (conventionally pval\u0026thinsp;\u0026lt;\u0026thinsp;5e-08, however, to ensure the sufficient number of SNPs we used a liberal value 5e-05 (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)). The candidate IVs must show a certain level of independence from other SNPs that could be assess by linkage disequilibrium (LD) with parameter (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001 within 10kb distance). The exposure and outcome datasets need to be harmonized in order to assign effect value to the same allele as well as avoiding palindromic SNPs. The strength of qualified IVs can further be assessed by the F statistics with commonly used threshold of F statistics\u0026thinsp;\u0026gt;\u0026thinsp;10 ensures sufficiently strong IVs to conduct MR analysis.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eOutcome data\u003c/strong\u003e \u003cp\u003eWe utilized GWAS summary data from three different gallbladder traits [Table S1] as outcomes. For the gallstone disease, the data was consisting of the meta-analysis of the 43639 cases and 506798 controls from UK biobank and FinnGen consortia (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). The cases were recruited based on the diagnostic codes such as ICT10, primary care, and UKB self-reported cases. Those individual with diagnostic codes for gallstone disease and patients treating for the gallstone diseases were included in the final cases for the study. The individuals with no gallstone disease diagnostic codes or treatment were considered as controls. For cholecystitis, the GWAS summary data included 4052 cases and 482432 controls from UK biobank. The cases were defined based on the diagnostic code (K81) and controls were the individuals without the code (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). For the third and final trait considered in the study i.e., cholecystitis without cholelithiasis, the data consisting of 2650 cases and 453698 controls of European ancestry. The individuals with the code PheCode 574.3 were considered as cases for cholecystitis without cholelithiasis phenotype (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e).\u003c/p\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMediator phenotypes:\u003c/h2\u003e \u003cp\u003eWe surveyed broader range of traits to find potential mediators of exposure to outcome pathways. The GWAS summary statistic data of 585 traits were retrieved and formatted, more detailed can be found in Table S1. To qualify a trait as a mediator of the pathway, we developed the following strategy. In the two-sample MR, the trait act as outcome must be associated strongly (IVW p\u0026thinsp;\u0026le;\u0026thinsp;0.05) to the EGTCD phenotype in the first MR step. Before moving to the second step of two-step MR, the strongly associated traits to the EGTCD must not show bidirectional MR trend. In second step, the trait acts an exposure has same beta direction and show strong association (IVW p\u0026thinsp;\u0026le;\u0026thinsp;0.05) with the gallbladder trait as outcome. Together, a trait to be considered as a mediator must have a strong association both as outcome (first step) and as exposure (second step) without showing bidirectional MR in the first step to eliminate possible confounding effect.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003e \u003cstrong\u003eTwo-sample MR\u003c/strong\u003e \u003cp\u003eTo assess the casual relationship between the EGTCD and gallbladder traits, we employed four effective MR methods including MR Egger, weighted mode, weighted median and random-effect inverse- variance weighted (IVW). The primary MR estimate as obtained from IVW, which allows the casual effect estimates based on the meta-analysis of individual estimates without the need of individual-level data (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). For the consistency point of view, we compared with IVW results with the other approaches, MR Egger, weighted mode, weighted median, used in our MR analyses. To correct for pleiotropy and assess heterogeneity, we performed sensitivity analyses which included pleiotropy tests (i.e. MR Egger intercept test, MR-PRESSO distortion test(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e) and leave-one-out test) and heterogeneity tests (global test MR-PRESSO (MR pleiotropy residual sum and outlier) and Cochrane\u0026rsquo;s Q test).\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMediation Analysis\u003c/strong\u003e \u003cp\u003eThe mediation assessment from the EGTCD to gallbladder traits were performed with two-step MR. In this, first the casual effect was estimated between the EGTCD and mediator phenotypes (β\u003csub\u003eE\u0026minus;M\u003c/sub\u003e). Next, the mediators that showed statistically significant casual association in first step were selected for second step. In step-two, the casual effect between mediators and gallbladder traits were estimated (β\u003csub\u003eM\u0026minus;O\u003c/sub\u003e). The proportion of mediation was calculated with the product method where two βs were multiplied and divided by total β from GATD trait on gallbladder outcomes.\u003c/p\u003e \u003c/p\u003e \u003cp\u003eFor all the two-sample MR, MR-PRESSO and two-step MR calculations, Two-sample MR r package was used (version 0.5.7) in the custom codes: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/AhmedArslan/MRsimplify\u003c/span\u003e\u003cspan address=\"https://github.com/AhmedArslan/MRsimplify\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe significance results were determined with the pvalue\u0026thinsp;\u0026le;\u0026thinsp;0.05 and results are presented in β coefficient, S.E., pvalue along with their 95% confidence interval (C.I.).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eCausal relationship between the EGTCD and gallbladder traits\u003c/h2\u003e \u003cp\u003eUsing two-sample MR settings, we obtained harmful associations between early growth traits and disorders, and gallbladder disease traits including gallstone disease, gallbladder inflammation and gallbladder inflammation without the presence of gallstones [Table S2]. More specifically, for increased gallstone disease: the childhood BMI (β\u003csub\u003e(IVW)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.09, 95% CI\u0026thinsp;=\u0026thinsp;0.0054 to 0.222, p\u0026thinsp;=\u0026thinsp;7.42e-06), childhood aggression (β\u003csub\u003e(IVW)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.14, 95% CI\u0026thinsp;=\u0026thinsp;0.041 to 0.254, p\u0026thinsp;=\u0026thinsp;0.006), and fetal genetic effect on preterm birth (β\u003csub\u003e(IVW)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.002, 95% CI\u0026thinsp;=\u0026thinsp;0.002 to 0.254, p\u0026thinsp;=\u0026thinsp;0.03) were significantly associated [Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e]. For decreased gallstone disease: individual's own genetic effect (fetal effect) on their birth weight (β\u003csub\u003e(IVW)\u003c/sub\u003e = -0.08, 95% CI = -0.16 to -0.003, p\u0026thinsp;=\u0026thinsp;0.04) and fetal birth weight (β\u003csub\u003e(IVW)\u003c/sub\u003e = -0.09, 95% CI\u0026thinsp;=\u0026thinsp;0.002 to 0.254, p\u0026thinsp;=\u0026thinsp;0.01) showed statistical casual associations. For increased gallbladder inflammation trait: childhood BMI (β\u003csub\u003e(IVW)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.108, 95% CI\u0026thinsp;=\u0026thinsp;0.055 to 0.14, p\u0026thinsp;=\u0026thinsp;0.03), late gestation total weight gain (maternal) (β\u003csub\u003e(IVW)\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.131, 95% CI\u0026thinsp;=\u0026thinsp;0.008 to 0.025, p\u0026thinsp;=\u0026thinsp;0.03) were causally associated whereas for decreased gallbladder inflammation, total weight gain (offspring) (β\u003csub\u003e(IVW)\u003c/sub\u003e = -0.11, 95% CI = -0.22 to -0.006, p\u0026thinsp;=\u0026thinsp;0.03) and gestation duration (maternal GWAS) (β\u003csub\u003e(IVW)\u003c/sub\u003e = -0.17, 95% CI = -0.03 to -0.034, p\u0026thinsp;=\u0026thinsp;0.003) were significantly associated. Finally, for the phenotype of decreased gallbladder inflammation without the presence of gallstones: fetal birth weight (β\u003csub\u003e(IVW)\u003c/sub\u003e = -0.18, 95% CI = -0.01 to 0.14, p\u0026thinsp;=\u0026thinsp;0.04) and gestation duration (maternal GWAS) (β\u003csub\u003e(IVW)\u003c/sub\u003e = -0.104, 95% CI = -0.018 to -0.023, p\u0026thinsp;=\u0026thinsp;0.01) showed casual association whereas no phenotype showed significant association with increased gallbladder inflammation without the presence of gallstones. For all the analyses, the strong strength of genetic instruments was showed by the F statistics (F\u0026thinsp;\u0026gt;\u0026thinsp;10). The sensitivity analyses reflected that there is heterogeneity between exposure and outcomes phenotypes however not appreciable pleiotropy was overserved among them. Also, reflected by the symmetry observed in the funnel plots [Fig. S1]. Few genetic instruments can exert more impact than others that can destabilize the MR prediction, in leave-one-out plot we did not observe such instruments that significantly influence the causal relationship assessment [Fig S1].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMediator traits identification and effects\u003c/h3\u003e\n\u003cp\u003eWith the two-step MR settings, first we identified mediators from a large selection of traits that showed significant association with the EGTCD. In second step, we identified mediators from the first step with same direction of effect size (beta value) that did not show bidirectional MR trend and showed significant causal association with gallbladder traits. By doing so, we identified 9, 4 and 4 significantly associated mediators for childhood BMI, preterm delivery (fetal effect) and childhood aggression with gallstones, respectively. For gallbladder inflammation, we identified 5, 1, and 3 potential mediators for childhood BMI, preterm delivery (fetal effect) and childhood aggression, respectively. For inflammation without gallstones, 4, 2, and 1 phenotype showed significant mediation trends [Table S3]. The sensitivity analyses showed that the mediation results obtained with IVW method were reliable.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMediation analysis\u003c/h2\u003e \u003cp\u003eThe phenotypes of mood swings (4.1%), high-density lipoprotein (HDL) levels (9.06%), apolipoprotein A levels (7.5%), shortness of breath walking on level ground - UKB data field 4717 (9.6%), insulin-like growth factor 1 (IGF1) levels (3.6%), alcohol drinker status previous - UKB data field 20117_1 (3.3%), Pain in joint - PheCode 745 (2.2%) and treatment or medication use of paracetamol - UKB data field 20003_2038460150 (4.6%), are mediating the casual effects of childhood BMI on gallstones. The casual effects of childhood BMI on gallbladder inflammation were found mediated by mood swings (5.8%), high-density lipoprotein (HDL) levels (13.0%), apolipoprotein A levels (8.9%) and shortness of breath walking on level ground - UKB data field 4717 (11.4%). Whereas the phenotypes of mood swings (4.5%), high-density lipoprotein (HDL) levels (18.2%), apolipoprotein A levels (15.4%) and Illnesses of mother: Diabetes (UKB data field 20110_9 (11.3%) were shown to mediate effects of childhood BMI on gallbladder inflammation without the presence of gallstones.\u003c/p\u003e \u003cp\u003eThe causal effects of preterm delivery (fetal effect) on gallstones were found to be mediated by the traits including calculus of bile duct - PheCode 574.2 (13.2%), meat consumers - UKB data field 103000 (1.58%), and mouth or teeth dental problems loose teeth - UKB data field 6149_4 (1.1%). For the effects of preterm delivery (fetal effect) on gallbladder inflammation and gallbladder inflammation without the presence of gallstones, we identified mediators namely calculus of bile duct - PheCode 574.2 (11%), and calculus of bile duct - PheCode 574.2 (16.3%), functional disorders of bladder - PheCode 596.5 (2.8%), respectively.\u003c/p\u003e \u003cp\u003eThe mediation traits including sugar or foods drinks containing sugar - UKB data field 6144_4 (11.5%), smoking status: current - UKB data field 20116_2 (13.1%), acute pancreatitis - PheCode 577.1 (37.75%), alcohol drinker status: previous - UKB data field 20117_1 (8.57%), heart failure (5.2%), and other disorders of biliary tract - PheCode 575.8 (28.57%) were identified as potential mediators of causal effects of childhood aggression on gallstones. The sugar or foods drinks containing sugar - UKB data field 6144_4 (14.5%), heart failure (11.5%) and acute pancreatitis - PheCode 577.1 (29.59%) were found to be mediating phenotypes between childhood aggression on gallbladder inflammation. The acute pancreatitis - PheCode 577.1 (40.8%) mediated the effects of childhood aggression on gallbladder inflammation without the presence of gallstones.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we evaluated the causal effect of early growth traits and childhood disorders on gallstone traits. Our stable results, obtained by utilizing the GWAS summary stats data, MR framework and sensitivity analyses, indicated that the EGTCD causally effecting the adult age gallbladder phenotypes. To our knowledge, the impact of early growth traits and disorders on gallbladder traits have not suggested in a MR study, previously.\u003c/p\u003e \u003cp\u003eAge independent body weight is a major risk factor for gallstones formation. Additionally, rapid fluctuation in body weight especially rapid weight loss could increase gallstone formation risk. Moreover, a longitudinal study focusing on adults (N\u0026thinsp;=\u0026thinsp;4106) suggested that an increased BMI is a risk factor for gallstone diseases (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e) with females are at disease risk more than men. The gallstone complications in children and adolescents have been implicated by childhood obesity or overweight (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Here we suggested the gallbladder complications including cholelithiasis and cholecystitis could be impacted by the presence of higher body mass index value in children between the age of 6\u0026ndash;10 years. We suspect causal association of childhood BMI with gallstone complications predispose formation of adulthood gallbladder complications in later age. Therefore, later life events such as rapid weight loss or further weight gain, medication, HDL, alcohol drinking could contribute to the complications. However, future research would further strengthen this observation. Childhood aggression includes traits from difficult temperament to directed aggression towards a person or a thing (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The early age behavioral problems have been associated with gastrointestinal issues including constipation and stomach pain. Whereas no research on the childhood aggression and gallstones have been reported. Here we showed that childhood aggression is casually associated with the gallstone formation.\u003c/p\u003e \u003cp\u003ePrevious studies on the maternal weight gain during pregnancy have shown later life child health implications (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). These complications include diabetes and obesity, here we shown that maternal weight gain during the late adage of pregnancy has causal association with gallbladder inflammation. Here we suggest a contribution to the later age onset on gallbladder inflammation in individuals born to mother who gain weight in the later stage of their pregnancy.\u003c/p\u003e \u003cp\u003eThe duration of gestation period and fetal birth weight showed reverse casual association with gallbladder inflammation and gallbladder inflammation without gallstones. Previous studies have shown the preterm birth have association with the long-term adverse health impacts including diabetes, blood pressure as well as neurodevelopmental and psychiatric disorders (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). A reverse causality of gestation duration and gallbladder inflammation suggest a decreased risk of developing gallbladder inflammation in later life, which is novel and interesting finding. On which future studies would reflect how gestation duration and fetal birth weight impact gallbladder inflammation traits.\u003c/p\u003e \u003cp\u003eThere can be many limitations to our study. The study was performed with the two-sample MR method which is a robust framework to assess the causal association between exposure and outcome phenotypes. The residual pleiotropy and sample-size are to major limitations that would not be addressed with the present framework, however with the advancement of additional MR methods and bigger cohorts would certainly contribute to eliminate such constrains in future studies. Additionally, we replied on samples from one ancestry which could not reflects the causal associations from different ancestries, future studies should also consider including different ancestries.\u003c/p\u003e \u003cp\u003eIn conclusion, we performed an exposure and outcome phenotypes MR analysis and identified casual associations of gallstones, gallbladder inflammation as well as gallbladder inflammation without the presence of gallstones with early growth traits and childhood traits including childhood BMI, childhood aggression, gestation period, fetal weight at birth and material weight gain during pregnancy. These novel insights into the etiology of gallstone disease traits should contribute to the better understanding of the role of studied exposures in gallbladder functions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests:\u003c/h2\u003e \u003cp\u003eThere are no competing interests for any author.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval:\u003c/strong\u003e \u003cp\u003eThe study was retrieved from the publicly available GWAS summary stats datasets; therefore, no specific ethical approval was required to perform the study.\u003c/p\u003e \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGlobal Burden of Disease Pediatrics Collaboration, Kyu HH, Pinho C, Wagner JA, Brown JC, Bertozzi-Villa A et al (2016) Global and National Burden of Diseases and Injuries Among Children and Adolescents Between 1990 and 2013: Findings From the Global Burden of Disease 2013 Study. 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Can Child Adolesc Psychiatr Rev 14(1):16\u0026ndash;20\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeddy MA, Power ML, Schulkin J (2008) The impact of maternal obesity on maternal and fetal health. Rev Obstet Gynecol 1(4):170\u0026ndash;178\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Université Libre de Bruxelles","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":"","lastPublishedDoi":"10.21203/rs.3.rs-6234473/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6234473/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGallstone disease has wide-spread prevalence with up to 20% world population is impacted. However, the causal relationship(s) between gallbladder disease traits and early growth trait and childhood disorders is not established yet. Therefore, with two-sample mendelian randomization (MR) settings, we explored the causal association between three gallbladder traits and 30 early growth traits and childhood disorders. A causal effect between the gallbladder diseases such as gallstones and traits including childhood BMI, childhood aggression was identified. Additionally, with mediation analyses we also identified 18 phenotypes that could mediate harmful effects of early growth traits on gallbladder complications. Together, early growth traits and childhood disorders causally impact gallbladder disease phenotypes and proper management of early growth health could possibility reduce gallbladder complications in adults.\u003c/p\u003e","manuscriptTitle":"Exposure of Early Growth Traits Genetics and Childhood Disorders is Causally Associated with the Gallbladder Outcomes: A Mendelian Randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-18 06:05:16","doi":"10.21203/rs.3.rs-6234473/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":"6a5cd761-38b5-4782-9113-d6c9a6a8a6b7","owner":[],"postedDate":"March 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":45739704,"name":"Statistical Epidemiology"},{"id":45739705,"name":"Epidemiology"}],"tags":[],"updatedAt":"2025-03-18T06:05:16+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-18 06:05:16","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6234473","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6234473","identity":"rs-6234473","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}