Helicobacter pylori infection is associated with fecal biomarkers of environmental enteric dysfunction but not with the nutritional status of children living in Bangladesh

RESEARCH ARTICLE Helicobacter pylori infection is associated with fecal biomarkers of environmental enteric dysfunction but not with the nutritional status of children living in Bangladesh Shah Mohammad FahimID 1 *, Subhasish Das 1 , Md. Amran Gazi 1 , Md. Ashraful AlamID 1 , Md. Mehedi Hasan 1 , Md. Shabab Hossain 1 , Mustafa Mahfuz 1,2 , M Masudur Rahman 3 , Rashidul Haque 4 , Shafiqul Alam Sarker 1 , Ramendra Nath Mazumder 1☯ , Tahmeed Ahmed 1,5,6☯ 1Nutrition and Clinical Services Division, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh, 2Faculty of Medicine and Life Sciences, University of Tampere, Finland, 3Department of Gastroenterology, Sheikh Russel National Gastro Liver Institute & Hospital, Dhaka, Bangladesh, 4Infectious Diseases Division, International Centre for Diarrheal Disease Research, Bangladesh (icddr,b), Dhaka, Bangladesh, 5Department of Global Health, University of Washington, Seattle, Washington, United States of America, 6James P. Grant School of Public Health, BRAC University, Dhaka, Bangladesh ☯These authors contributed equally to this work. *[email protected] Abstract Background Because Helicobacter pylori (H.pylori) infection and Environmental Enteric Dysfunction (EED) follow a similar mode of transmission, there can be a complex interplay between H. pylori infection and EED, both of which can influence childhood growth. We sought to investigate the factors associated with H.pylori infection and identify its relationship with the fecal biomarkers of EED including Myeloperoxidase (MPO), Neopterin (NEO), Calprotectin, Reg1B and Alpha-1 antitrypsin (AAT), and nutritional status of the children. Methodology Data from an on-going community-based nutrition intervention study was used for this analysis. Total 319 children aged between 12–18 months were evaluated at enrolment and at the end of a 90-day nutrition intervention. Multivariable linear regression with generalized estimating equations was done to examine the association of H.pylori infection with stool biomarker of EED and nutritional status of the children. Principal findings One-fifth of the participants had H.pylori infection at both the time points, with 13.8% overall persistence. Children living in crowded households had higher odds of being infected by H. pylori (AOR = 2.02; 95% CI = 1.02, 4.10; p-value = 0.045). At enrolment, 60%, 99%, 69% and 85% of the stool samples were elevated compared to the reference values set for MPO, PLOS NEGLECTED TROPICAL DISEASES PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 1 / 18 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Fahim SM, Das S, Gazi M.A, Alam M.A, Hasan M.M, Hossain M.S, et al. (2020) Helicobacter pylori infection is associated with fecal biomarkers of environmental enteric dysfunction but not with the nutritional status of children living in Bangladesh. PLoS Negl Trop Dis 14(4): e0008243. https://doi.org/10.1371/journal. pntd.0008243 Editor: Zulfiqar A. Bhutta, The Hospital for Sick Children, CANADA Received: October 18, 2019 Accepted: March 23, 2020 Published: April 23, 2020 Peer Review History: PLOS recognizes the benefits of transparency in the peer review process; therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. The editorial history of this article is available here: https://doi.org/10.1371/journal.pntd.0008243 Copyright: ©2020 Fahim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. NEO, AAT and Calprotectin in the non-tropical western countries. The proportions reduced to 52%, 99%, 67%, and 77% for the same biomarkers after the nutrition intervention. Infection with H.pylori had significant positive association with fecal AAT concentrations (Coefficient = 0.26; 95% CI = 0.02, 0.49; p-value = 0.03) and inverse relationship with Reg1B concentrations measured in the stool samples (Coefficient = -0.32; 95% CI = -0.59, -0.05; pvalue = 0.02). However, H.pylori infection was not associated with the indicators of childhood growth. Conclusions The study findings affirmed that the acquisition and persistence of H.pylori infection in the early years of life may exert an adverse impact on intestinal health, induce gut inflammation and result in increased intestinal permeability. Author summary Infection with H.pylori, a substantial public health burden in the tropical countries, follows the similar mode of transmission analogous to Environmental Enteric Dysfunction (EED). There can be a complex interplay between H.pylori infection and EED–both of which can influence childhood growth–but the definite role of H.pylori infection contributing to EED and subsequent growth failure is poorly understood. In this study, the authors present data from an ongoing community-based nutrition intervention study and investigated the factors associated with H.pylori infection and identify its relationship with fecal biomarkers of EED and indicators of the nutritional status of the children hailing from a resource-poor urban settlement. They demonstrated the acquisition and persistence of H.pylori infection during early childhood. The study results also corroborate that infection with H.pylori had significant positive association with fecal Alpha-1 antitrypsin concentrations and an inverse relationship with Reg1B concentrations measured in stool samples of the children. The findings revealed in this study may contribute to a better understanding of the role of H.pylori infection in contributing to EED as well as alteration of gut function in the early years of life. Introduction Infection with Helicobacter pylori (H.pylori) has emerged as a substantial public health burden over the past couple of decades [1]. The infection is highly prevalent in low-income countries and affects more than half of the global population [2]. The organism is obtained mostly by oral ingestion and induces chronic inflammation of the underlying gastric mucosa [3,4]. The pathology is associated with diarrheal diseases, malnutrition and subsequent growth failure in children [5–8]. Evidence suggests that H.pylori infection is primarily acquired at the early years of life and can persist for a long period of time [9–11]. Infection acquired in the early age induces malabsorption and implicates in growth retardation [8]. The prevalence of the infection varies from around 10% to over 80% in children living in different regions of the world [12]. A birth cohort study, conducted in Bangladesh, showed that 50–60% of Bangladeshi children had the H.pylori infection by 2 years of their age [13]. Epidemiologic studies demonstrated that first two years of life is critical for growth [14] as well as for the acquisition of H. PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 2 / 18 Data Availability Statement: All relevant data are within the manuscript and its Supporting Information files. Funding: This protocol is supported by the Bill and Melinda Gates Foundation under its Global Health Program. Project investment ID is OPP1136751. (https://www.gatesfoundation.org/How-We-Work/ Quick-Links/GrantsDatabase/Grants/2015/11/ OPP1136751). The funders had no role in the study design; collection, analysis, and interpretation of data; preparation, review, or approval of the manuscript; and decision to submit and publication of the manuscript. Competing interests: The authors have declared that no competing interests exist. pylori infection [15]. Consistent with those reports, many recent studies have exhibited the association of growth impairment with H.pylori infection, especially among those living in resource poor settings [8,16–18]. Conversely, H.pylori has also been found to be linked with improved nutritional status in children, although the mechanism has not yet been elucidated [16,19]. There is also evidence of having no relationship between infection with H.pylori and nutritional status of younger children [20]. The definite role of H.pylori on nutritional status of children is paradoxical and the findings are “mixed-bag”. However, H.pylori infection can induce inflammatory responses as well as production of pro-inflammatory cytokines, and leads to malabsorption of essential nutrients [8]. Infection with H.pylori may also predisposes to multiple enteric pathogens resulting is altered intestinal health and function [8,21]. Environmental Enteric Dysfunction (EED), an asymptomatic small intestinal pathology, has been implicated in linear growth failure of children less than two years of age [14,22]. EED is characterized by persistent immune activation, gut inflammation and altered intestinal permeability resulting from chronic exposure to intestinal pathogens and frequent enteric infections [23–25]. The overall negative impact of EED on child growth and development, especially in their early years of life, is now well established [22,26]. The condition has been described in the scientific literature since 1960s, but still there is no definite criteria to diagnose the ailment [22]. EED can be diagnosed through small intestinal biopsy which is considered to be the gold standard but difficult to perform in children owing to the invasiveness of the procedure [27]. However, several biomarkers have been tested as markers of EED and found to be associated with features of EED in previous studies [28–30]. Stool biomarkers including Myeloperoxidase (MPO), Neopterin (NEO), Calprotectin, Reg1B, and Alpha-1 antitrypsin (AAT) are the non-invasive alternatives proposed for the assessment of EED [27,31]. MPO, Calprotectin, and NEO indicate intestinal inflammation, whereas AAT is a useful marker of enteric protein loss as well as intestinal permeability [32]. Reg1B is a newly proposed marker which points to epithelial tissue injury and subsequent repair in the small intestine [33]. EED is attributable to microbial contamination of food and water associated with poor sanitation and hygiene [34,35]. Since H.pylori infection also follows the similar mode of transmission, there can be a complex interplay between the acquisition of H.pylori infection, EED and impaired growth in the first two years of life. Prior studies showed that H.pylori infection induces gastritis and results in protein losing enteropathy with evidence of resolution of the enteropathy by eradication of the infection [36,37]. To that end, we hypothesized that H.pylori infections may contribute to and exacerbate EED and subsequent growth failure in children. But till date, no attempt was made to investigate the definite role of H.pylori infection contributing to EED and subsequent growth failure in children less than two years of age. Given the high prevalence of both H.pylori infection as well as EED in this patient population, investigation into how each condition influences the other and patient outcomes is of high importance. Therefore, we sought to investigate the factors associated with H.pylori infection and identify its relationship with fecal biomarkers of EED and indicators of the nutritional status of the children hailing from a resource-poor urban settlement in Dhaka, Bangladesh. Methods Ethics statement The research protocol of this study (protocol no.: PR-16007) was approved by the Institutional Review Board of the International Center for Diarrheal Disease Research, Bangladesh (icddr, b), and written informed consent was obtained from the parents or legal guardians. PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 3 / 18 Study design, site and population Data from the Bangladesh Environmental Enteric Dysfunction (BEED) study was used to conduct this analysis. In brief, the BEED study is an ongoing community-based nutrition intervention study that is being conducted in the Mirpur area, a suburb located in the capital city of Bangladesh. In this study, children aged between 12 to 18 months either stunted [length-forage z score (LAZ) <2] or at risk of stunting [LAZ = −1 to −2] are being enrolled for an intervention for 90 feeding days. The enrolled children receive an egg, 150 ml of whole milk, micronutrient sprinkles and nutritional counseling daily for 6 days in a week. A total of 319 children living in the slums of Mirpur area were included in this analysis. We included only those children who completed the nutrition intervention, and had data in both the time points–at enrollment and at the end of nutrition intervention. Exclusion criteria for enrollment in BEED study are: severe acute malnutrition, severe anemia, tuberculosis, presence of any congenital anomaly or deformity, suffering from diarrhoea or history of persistent diarrhoea in the preceding month, another family member already enrolled in the BEED study, and presence of any severe or chronic disease. The methodology of BEED study has been published previously [38]. Data collection Field staff collected the socio-economic and household information of the participants from the parents or caregivers at enrollment. Anthropometry was measured by the trained field staff following standard operating procedures (SOPs) based on the manuals of WHO and CDC [39, 40]. In order to ensure the consistency of an anthropometric measurement from one rater to another, we provided refresher’s training to the field staff and estimated intra-class correlation coefficient (ICC) periodically every three months. Such training results in significant improvement of raters pertaining to anthropometric measurements at field site with a coefficient more than 0.9 for each of the scales. Indicators of nutritional status such as length-for-age z (LAZ), weight-for-age z (WAZ), and weight-for-height z (WHZ) scores were calculated using WHO anthropometry software. Blood and non-diarrheal stool samples were collected at baseline and after completion of 90-day nutrition intervention. Stool samples were obtained without using any fixative and frozen at −70˚C until analysis. Laboratory analysis All the laboratory assays were carried out at icddr,b in Dhaka, Bangladesh. Blood samples were collected and centrifuged for 10 minutes at 4000 rotation per minute to separate the plasma. Aliquots were immediately stored at -80˚C till analysis. The inflammatory markers including high sensitivity CRP (Immundiagnostik, Bensheim, Germany) and AGP (Alpco, Salem, NH, USA) were analyzed from the plasma samples. Fecal biomarkers including AAT (Biovendor, Chandler, North Carolina), NEO (GenWay Biotech, San Diego, California), Reg1B (TechLab, Blacksburg, Virginia), Calprotectin (BU ¨HLMANN fCAL, Scho¨nenbuch, Switzerland), and MPO (Alpco, Salem, New Hampshire) were measured in the stool samples using kits available for enzyme-linked immunosorbent assay (ELISA) following the instructions given by the manufacturers. Calibration curves were used to quantify the levels of each biomarker. In this study, fecal antigen test for H.pylori was employed to detect the H.pylori in the stool samples. This is a well-recognized non-invasive technique for the detection of H.pylori infection in the children [41]. Stool was analyzed for H.pylori antigen through ELISA using Amplified IDEIA™ Hp StAR™(OXOID Limited, Hampshire, United Kingdom). Dual wavelength of 450/630 nm was used following the instruction of the manufacturer. PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 4 / 18 Variables used in this analysis We used H.pylori infection as the exposure variable. It was a binary categorical variable categorized based on the absorbance values derived from the stool ELISA results. Stool specimens with absorbance values �0.15 were considered positive and specimens with absorbance values <0.15 were considered negative for infection with H.pylori. Fecal biomarkers (e.g. MPO, NEO, Calprotectin, REG1B and AAT) and the indicators of nutritional status (e.g. LAZ, WAZ, and WHZ) were the outcome variables in our analyses. The covariates such as treatment of drinking water, source of drinking water, source of cooking water, hand washing practice after toilet, hand washing practice after helping the child to defecate, hand washing practice before cooking, separate space for kitchen, animal exposure at households, educational status of mothers and heads of households, and crowded living conditions were categorical variables. Crowded living condition was defined if more than 4 household members sleep in a single room[42]. Markers of systemic inflammation (e.g. CRP and AGP) were also included as covariates in this analysis (see the list of variables in S1 Table). We also divided the children enrolled in this study into four groups based on their infection with H.pylori and created a categorical variable–H.pylori infection status. The categories of the variable are: a) children who had infection at enrollment but got cleared by the end of study, b) who acquired new infection during the study, c) children who remained infected at enrollment and at the end of nutrition intervention, and d) who remained non-infected in both the time points. Statistical analyses Demographic and socio-economic characteristics were described by frequency with proportions for categorical variables, mean with standard deviation for symmetric continuous variables and median with inter-quartile ranges (IQR) for asymmetric continuous data. T-test, Wilcoxon rank-sum test and Pearson’s chi-square test were applied to compare the baseline characteristics between the stunted and at risk of stunting children. The univariate Pearson’s chi-square test was used to measure the differences in the prevalence of H.pylori infection both in stunted and at risk of stunting children at both the time points. We have identified the factors associated with H.pylori infection in non-diarrheal stool samples during enrollment using logistic regression model. Variables were assessed individually and were included in the multivariable logistic regression model if the p-value was found <0.2 in bivariate analysis. Education of household head was included in the model because of its previously reported association with the H.pylori infection in children [16,42]. Additionally, the model was adjusted for age, sex, and nutritional status of the enrolled participants at enrolment. Stool concentrations of all the fecal biomarkers (AAT, Reg1B, MPO, Calprotectin and NEO) were log-transformed. We then examined the association between H.pylori infection and stool biomarker concentrations and subsequently the association between H.pylori infection and indicators of nutritional status (LAZ, WAZ, and WLZ) of the children using multivariable linear regression with generalized estimating equations (GEE). In both the analyses, the family was Gaussian, identity was the link function and the correlation matrix was unstructured. The correlation matrix was selected based on the lowest quasi-likelihood under independence model criterion (QIC) value. Multicollinearity among the independent variables was checked for all the models using variance inflation factor (VIF) values. At first, bivariate analysis was done to explore the unadjusted effect of the variables on the outcomes using individual GEE model. Variables were included in the multivariable models if the p-value was found <0.2 in the bivariate analyses. In addition, all the estimates were adjusted for age and sex of the enrolled participants. We also performed multivariable linear regression analysis to test the association between H.pylori infection status and biomarker values at the end of nutrition PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 5 / 18 intervention. The biomarker values were log-transformed prior to analysis and the models were adjusted for age, sex, and nutritional status of the children at enrollment. Herein, we considered the children who remained non-infected as the reference group. A complete case analysis was applied for all the analyses and statistical significance was defined as a two-sided pvalue<0.05. The statistical analyses were conducted using R version 3.5.1 (https://www.rproject.org, Foundation for Statistical Computing, Vienna, Austria) software. Results A total of 319 children were included in this analysis. Among them 154 were stunted and 165 were at risk of being stunted children. The mean (±SD) age of the children was 14.5 (±2.1) months and 47.3% of the enrolled children were male. Almost 80% of the mothers received formal education. Water treatment rate was higher in the families of the children who are at risk of being stunted compared to the families of stunted children and it was found statistically significant (p = 0.047). The living condition of stunted children was more crowded than that of their peers. Compared to their counterparts, stunted children were more exposed to animals at the household level. The monthly family income of the stunted children was lower than that of at risk of stunting children. Table 1 describes the baseline characteristics of the enrolled children. Prevalence of H.pylori infection The prevalence of infection with H.pylori at enrollment and at the end of nutrition intervention for both the stunted and at risk of being stunted children is presented in Fig 1. Although the proportion of H.pylori positivity was higher in the stool samples of the stunted children compared to at risk of stunting children at both the time points, the difference was not statistically significant (p-value>0.05). The prevalence was lower at enrollment compared to that of at the end of nutrition intervention, but it was not statistically different (p-value>0.05). The prevalence of persistent H.pylori infection as defined by the positivity of H.pylori infection at both the time points was 13.8% in this cohort of children (Fig 1). Persistence of H.pylori infection was more frequent in stunted children (15.6%) compared to at risk of being stunted children (12.1%). Here again, the difference was not found statistically significant (p-value>0.05). Distribution of fecal biomarkers in the stool samples Overall, the fecal biomarker levels were much higher in the study participants compared to that of the standard in the non-tropical countries where the reference values for MPO, NEO, AAT and Calprotectin are <2,000 ng/mL, <70 nmol/L, <0.27 mg/g, <200 μg/g, respectively [43]. At enrolment, 60%, 99%, 69% and 85% of the stool samples were elevated compared to the reference values set for MPO, NEO, AAT and Calprotectin in the non-tropical western countries. The proportions reduced to 52%, 99%, 67%, and 77% for the same biomarkers after the nutrition intervention. In a recent study, the median values of fecal Reg1B concentration was found 30.8 and 16.5 μg/mL in the children of Bangladesh and Peru, respectively [44]. We have observed much higher concentrations of Reg1B compared to those findings in the stool samples of the children enrolled in this study. The median (IQR) concentration of Reg1B was 57.7 (31.1, 89.3) μg/mL at enrollment and it decreased to 48.3 (17.4, 82.6) μg/mL at the end of nutrition intervention. However, all the fecal biomarker values were reduced significantly after the 90-day nutrition intervention (p-value <0.05). At both the time points, the concentrations of MPO, AAT and Calprotectin were higher in the stool samples of the H.pylori infected children. But only the difference in fecal AAT concentrations between infected and non-infected children at enrolment was found statistically significant (p-value = 0.04). Fecal NEO and Reg1B concentrations were lower in H.pylori PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 6 / 18 infected children, which was found statistically insignificant at enrollment but significant only for Reg1B at the end of nutrition intervention (p-value = 0.01). There was no statistically significant difference in the fecal biomarker concentrations of children with persistent infection compared to those without persistent infection (p-value>0.05). Factors associated with H.pylori infection Multivariable logistic regression model demonstrated that children living in crowded households had higher odds of being infected by H.pylori (AOR = 2.02; 95% CI = 1.02, 4.10; pvalue = 0.045) in this cohort after controlling for the age, sex, nutritional status at enrollment, mother’s education, education received by household head, and water treatment. No other socio-demographic factor demonstrated any statistically significant association with the H. Pylori infection (Table 2). Association of H.pylori infection with the fecal biomarkers of EED Table 3 showed the association of H.pylori infection with the fecal biomarkers of EED. No significant association was observed between the infection and fecal levels of MPO, NEO, and Table 1. Descriptive characteristics of the stunted and at risk of being stunted children at enrollment. Variables Stunted (n = 154) At risk of stunting (n = 165) Total (N = 319) p-value Socio-demographic variables Age in month, mean (SD) 14.6 (2.1) 14.4 (2.0) 14.5 (2.1) 0.39 Gender (Male), n (%) 88 (57.1%) 63 (38.2%) 151 (47.3%) 0.001 LAZ, mean (SD) -2.9 (0.7) -1.6 (0.3) -2.2 (0.8) <0.001 WAZ, mean (SD) -2.3 (0.8) -1.4 (0.7) -1.8 (0.9) <0.001 WHZ, mean (SD) -1.1 (0.8) -0.87 (0.9) -0.98 (0.9) 0.01 Mothers received education, n (%) 120 (77.9%) 131 (79.4%) 251 (78.7%) 0.75 Household head received education, n (%) 98 (68.1%) 117 (74.5%) 215 (71.4%) 0.22 Water treatment, n (%) 84 (54.5%) 108 (65.5%) 192 (60.2%) 0.047 Separate space for kitchen, n (%) 124 (80.5%) 145 (87.9%) 269 (84.3%) 0.07 Always wash hand before cooking, n (%) 14 (9.1%) 24 (14.6%) 38 (11.9%) 0.13 Always wash hand after toilet, n (%) 103 (66.9%) 126 (76.4%) 229 (71.8%) 0.06 Always wash hand after child defecation, n (%) 85 (55.2%) 99 (60%) 184 (57.7%) 0.39 Improved toilet, n (%) 99 (64.3%) 108 (65.5%) 207 (64.9%) 0.83 Crowded living conditions, n (%) 43 (27.9%) 31 (18.8%) 74 (23.2%) 0.05 Animal exposure in household, n (%) 15 (9.9%) 8 (4.9%) 23 (7.3%) 0.09 Monthly family income (USD)�, mean (SD) 167.3 (84.1) 190.6 (117.3) 179.4 (103.1) 0.04 Markers of systemic inflammation CRP (mg/l), median (IQR) 1.2 (0.4, 3.2) 1.0 (0.6, 4.1) 1.1 (0.5, 3.6) 0.69 AGP (mg/dl), median (IQR) 96.3 (70.8, 127.6) 85.1 (64.1, 122.5) 92.6 (66.5, 125.6) 0.11 Fecal biomarkers of EED MPO (ng/mL), median (IQR) 2740.5 (1457.2, 5505.2) 2266.0 (1427.0, 4758.0) 2438.0 (1434.0, 5398.0) 0.27 NEO (nmol/L), median (IQR) 2902.0 (1907.0, 4269.0) 3226.0 (1732.0, 5149.0) 3068.0 (1850.0, 4548.0) 0.26 AAT (mg/g), median (IQR) 0.46 (0.23, 0.68) 0.47 (0.25, 0.64) 0.46 (0.24, 0.67) 0.97 Calprotectin (μg/g), median (IQR) 524.2 (266.2, 1025.5) 672.4 (327.9, 1074.8) 598.3 (300.1, 1041.5) 0.09 Reg1B (μg/mL), median (IQR) 62.2 (33.4, 91.7) 51.9 (30.8, 85.1) 57.7 (31.4, 89.3) 0.31 �1 USD = 84.21 BDT was used as conversion rate https://doi.org/10.1371/journal.pntd.0008243.t001 PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 7 / 18 Calprotectin, both in bivariate and multivariable analysis using GEE. However, H.pylori infection was significantly associated with the fecal concentrations of AAT (Coefficient = 0.26; 95% CI = 0.02, 0.49; p-value = 0.03) after adjusting for age, sex, nutritional status at enrollment, mother’s education, crowded living conditions, water treatment, hand washing practice of mother after toilet, CRP, and AGP. A statistically significant negative association was observed between H.pylori infection and fecal concentrations of REG1B (Coefficient = -0.32; 95% CI = Fig 1. Prevalence of Helicobacter pylori infection in children living in Bangladesh https://doi.org/10.1371/journal.pntd.0008243.g001 Table 2. Factors associated with Helicobacter pylori infection in children during enrollment. Variables OR (95% CI) p-value AOR (95% CI) p-value Age 1.11 (0.96, 1.27) 0.16 1.08 (0.93, 1.26) 0.29 Sex (female) 0.68 (0.38, 1.21) 0.19 0.62 (0.33, 1.17) 0.14 Nutritional status (At risk of stunting) 0.92 (0.52, 1.64) 0.78 1.24 (0.66, 2.33) 0.51 Crowding (>4 people sleep per room) 1.94 (1.04, 3.64) 0.04 2.02 (1.02, 4.10) 0.045 Mother received education 0.55 (0.29, 1.05) 0.07 0.62 (0.28, 1.37) 0.24 Household head received education 0.71 (0.38, 1.34) 0.29 0.99 (0.47, 2.13) 0.99 Treatment of water 0.66 (0.37, 1.18) 0.16 0.88 (0.46, 1.67) 0.69 https://doi.org/10.1371/journal.pntd.0008243.t002 PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 8 / 18 -0.59, -0.05; p-value = 0.02) after adjustment for age, sex, nutritional status at enrollment, mother’s education, and hand washing practice of mother after defecating the child. We observed statistically significant association between H.pylori infection status and biomarkers of EED at the end of nutrition intervention (Table 4). The multivariable linear regression analyses showed that children who were infected at enrolment had significantly higher fecal concentrations of AAT (p-value = 0.03), MPO (p-value = 0.01), and calprotectin (pvalue = 0.02) at the end of nutrition intervention compared to the children who remained non-infected. Children who acquired infection during study (p-value = 0.03) and who remained infected in the both the time points (p-value = 0.006) had significantly lower concentrations of fecal Reg1B compared to the reference group. Fecal NEO concentration was significantly lower (p-value <0.001) in children who acquired infection during the study in comparison to the children who had no infection at all. Table 3. Association of Helicobacter pylori infection with the fecal biomarkers of EED using GEE ¶ . Variables AAT, mg/g MPO, ng/mL NEO, nmol/L Calprotectin, μg/g Reg1B, μg/mL Age in days -0.004(-0.05, 0.04) -0.02 (-0.07, 0.03) -0.05 (-0.10, -0.001)�-0.02 (-0.07, 0.04) -0.08 (-0.13, -0.02)� Sex (female) -0.14 (-0.34, 0.06) 0.12 (-0.09, 0.33) 0.03 (-0.18, 0.24) -0.02 (-0.20, 0.25) 0.12 (-0.10, 0.35) Nutritional status (At risk of stunting) -0.07 (-0.27, 0.13) -0.02 (-0.24, 0.19) 0.06 (-0.15, 0.28) -0.10 (-0.33, 0.12) -0.03 (-0.25, 0.20) Mothers received education 0.19 (-0.06, 0.45) 0.20 (-0.07, 0.47) 0.29 (0.01, 0.56)� Water treatment 0.01 (-0.22, 0.23) Separate space for kitchen -0.24 (-0.56, 0.08) Animal exposure in household -0.42 (-0.84, -0.002) Always wash hand after child defecation -0.14 (-0.39, 0.11) -0.18 (-0.45, 0.09) Always wash hand after toilet 0.21 (-0.03, 0.45) 0.26 (0.02, 0.49)�-0.01 (-0.27, 0.29) -0.02 (-0.31, 0.28) Crowding -0.09 (-0.33, 0.15) 0.15 (-0.10, 0.40) CRP 0.01 (-0.01, 0.03) 0.02 (-0.01, 0.04) -0.03 (-0.05, -0.01)�0.01 (-0.01, 0.04) AGP 0.001 (-0.001, 0.003) 0.001 (-0.001, 0.003) 0.003 (0.0003, 0.005)� Helicobacter pylori infection 0.26 (0.02, 0.49)�0.14 (-0.11, 0.39) -0.02 (-0.26, 0.23) -0.07 (-0.34, 0.20) -0.32 (-0.59, -0.05)� ¶ Each column represents an individual model. The adjusted coefficient with 95% confidence interval (CI) has been reported. The asterisk (�) denotes the statistical significance with a p-value <0.05. Abbreviations used: AAT, alpha-1 antitrypsin; MPO, myeloperoxidase; NEO, neopterin; CRP, C-reactive protein; AGP, Alpha-1-acid glycoprotein. https://doi.org/10.1371/journal.pntd.0008243.t003 Table 4. Association of Helicobacter pylori infection status with the fecal biomarkers of EED using multivariable linear regression analysis ¶ . Variables AAT, mg/g MPO, ng/mL NEO, nmol/L Calprotectin, μg/g Reg1B, μg/mL Age in days -0.03 (-0.09, 0.03) -0.04 (-0.08, 0.01) -0.08 (-0.14, -0.02) �-0.05 (-0.11, 0.01) -0.11 (-0.19, -0.03) � Sex (female) -0.11(-0.31, 0.09) -0.003 (-0.20, 0.19) 0.16 (-0.04, 0.36) -0.12 (-0.36, 0.12) 0.08 (-0.23, 0.39) Nutritional status (At risk of stunting) -0.19(-0.39, 0.01) 0.05(-0.15, 0.25) -0.08 (-0.28, 0.12) 0.03 (-0.21, 0.27) -0.06 (-0.39, 0.27) Helicobacter pylori infection status (Ref: non-infected) Infected at enrolment 0.58(0.05, 1.11) �0.67 (0.16, 1.18) �0.19 (-0.32, 0.70) 0.73 (0.10, 1.36) �0.11 (-0.73, 0.95) Infected acquired during study 0.33(-0.04, 0.70) 0.30(-0.07, 0.67) -0.72 (-1.09, -0.35) �0.29 (-0.14, 0.72) -0.68 (-1.27, -0.10) � Remained infected -0.09(-0.38, 0.20) 0.14(-0.15, 0.43) -0.09 (-0.38, 0.20) 0.27 (-0.08, 0.62) -0.67 (-1.14, -0.20) � ¶ Multivariable linear regression was applied considering the biomarker values at the end of nutrition intervention as the outcome variables. Each column represents an individual model. Biomarker values were log-transformed prior to analysis. Adjusted coefficient values with 95% CI have been reported in the table. The asterisk (�) sign indicates the statistical significance. https://doi.org/10.1371/journal.pntd.0008243.t004 PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 9 / 18 28. Uddin MI, Islam S, Nishat NS, Hossain M, Rafique TA, Rashu R, et al. Biomarkers of environmental enteropathy are positively associated with immune responses to an oral cholera vaccine in Bangladeshi children. PLoS neglected tropical diseases. 2016; 10(11). 29. McCormick BJ, Lee GO, Seidman JC, Haque R, Mondal D, Quetz J, et al. Dynamics and trends in fecal biomarkers of gut function in children from 1–24 months in the MAL-ED study. The American journal of tropical medicine and hygiene. 2017; 96(2):465–72. https://doi.org/10.4269/ajtmh.16-0496 PMID: 27994110 30. George CM, Oldja L, Biswas S, Perin J, Lee GO, Kosek M, et al. Geophagy is associated with environmental enteropathy and stunting in children in rural Bangladesh. The American journal of tropical medicine and hygiene. 2015; 92(6):1117–24. https://doi.org/10.4269/ajtmh.14-0672 PMID: 25918214 31. Iqbal NT, Sadiq K, Syed S, Akhund T, Umrani F, Ahmed S, et al. Promising Biomarkers of Environmental Enteric Dysfunction: A Prospective Cohort study in Pakistani Children. Scientific reports. 2018; 8 (1):2966. https://doi.org/10.1038/s41598-018-21319-8 PMID: 29445110 32. Fahim SM, Das S, Sanin KI, Gazi MA, Mahfuz M, Islam MM, et al. Association of Fecal Markers of Environmental Enteric Dysfunction with Zinc and Iron Status among Children at First Two Years of Life in Bangladesh. The American journal of tropical medicine and hygiene. 2018; 99(2):489–94. https://doi. org/10.4269/ajtmh.17-0985 PMID: 29893201 33. Syed S, Ali A, Duggan C. Environmental enteric dysfunction in children: a review. Journal of pediatric gastroenterology and nutrition. 2016; 63(1):6. https://doi.org/10.1097/MPG.0000000000001147 PMID: 26974416 34. Owino V, Ahmed T, Freemark M, Kelly P, Loy A, Manary M, et al. Environmental enteric dysfunction and growth failure/stunting in global child health. Pediatrics. 2016; 138(6):e20160641. https://doi.org/ 10.1542/peds.2016-0641 PMID: 27940670 35. Etheredge AJ, Manji K, Kellogg M, Tran H, Liu E, McDonald CM, et al. Markers of Environmental Enteric Dysfunction Are Associated With Neurodevelopmental Outcomes in Tanzanian Children. Journal of pediatric gastroenterology and nutrition. 2018; 66(6):953–9. https://doi.org/10.1097/MPG. 0000000000001978 PMID: 29613921 36. Hill ID, Sinclair-Smith C, Lastovica A, Bowie M, Emms M. Transient protein losing enteropathy associated with acute gastritis and campylobacter pylori. Archives of disease in childhood. 1987; 62 (12):1215–9. https://doi.org/10.1136/adc.62.12.1215 PMID: 3435155 37. Landzberg BR, Pochapin MB. Protein-losing enteropathy and gastropathy. Current treatment options in gastroenterology. 2001; 4(1):39–49. https://doi.org/10.1007/s11938-001-0045-z PMID: 11177680 38. Mahfuz M, Das S, Mazumder RN, Rahman MM, Haque R, Bhuiyan MMR, et al. Bangladesh environmental enteric dysfunction (BEED) study: protocol for a community-based intervention study to validate non-invasive biomarkers of environmental enteric dysfunction. BMJ open. 2017; 7(8):e017768. https:// doi.org/10.1136/bmjopen-2017-017768 PMID: 28801442 39. Organization WH. Physical status: The use of and interpretation of anthropometry, Report of a WHO Expert Committee. 1995. 40. Control CfD, Prevention. National Health and Nutrition Examination Survey (NHANES) anthropometry procedures manual; 2009. USA: CDC. 2012. 41. Oderda G, Rapa A, Ronchi B, Lerro P, Pastore M, Staiano A, et al. Detection of Helicobacter pylori in stool specimens by non-invasive antigen enzyme immunoassay in children: multicentre Italian study. Bmj. 2000; 320(7231):347–8. https://doi.org/10.1136/bmj.320.7231.347 PMID: 10657328 42. Jafri W, Yakoob J, Abid S, Siddiqui S, Awan S, Nizami S. Helicobacter pylori infection in children: population-based age-specific prevalence and risk factors in a developing country. Acta Paediatrica. 2010; 99(2):279–82. https://doi.org/10.1111/j.1651-2227.2009.01542.x PMID: 19839955 43. Naylor C, Lu M, Haque R, Mondal D, Buonomo E, Nayak U, et al. Environmental enteropathy, oral vaccine failure and growth faltering in infants in Bangladesh. EBioMedicine. 2015; 2(11):1759–66. https:// doi.org/10.1016/j.ebiom.2015.09.036 PMID: 26870801 44. Peterson KM, Buss J, Easley R, Yang Z, Korpe PS, Niu F, et al. REG1B as a predictor of childhood stunting in Bangladesh and Peru–. The American of Clinical Nutrition. 2013; 97(5):1129–33. 45. Amieva M, Peek RM Jr. Pathobiology of Helicobacter pylori–induced gastric cancer. Gastroenterology. 2016; 150(1):64–78. https://doi.org/10.1053/j.gastro.2015.09.004 PMID: 26385073 46. Cover TL. Helicobacter pylori diversity and gastric cancer risk. MBio. 2016; 7(1):e01869–15. https://doi. org/10.1128/mBio.01869-15 PMID: 26814181 47. Hu Y, Wan JH, Li XY, Zhu Y, Graham D, Lu NH. Systematic review with meta-analysis: the global recurrence rate of Helicobacter pylori. Alimentary pharmacology & therapeutics. 2017; 46(9):773–9. 48. Wangda S, Richter JM, Kuenzang P, Wangchuk K, Choden T, Tenzin K, et al. Epidemiology of Helicobacter pylori infection in asymptomatic schoolchildren in Bhutan. Helicobacter. 2017; 22(6):e12439. PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 16 / 18 49. O’ryan ML, Lucero Y, Rabello M, Mamani N, Salinas AM, Peña A, et al. Persistent and transient Helicobacter pylori infections in early childhood. Clinical Infectious Diseases. 2015; 61(2):211–8. https://doi. org/10.1093/cid/civ256 PMID: 25838286 50. Kayali S, Manfredi M, Gaiani F, Bianchi L, Bizzarri B, Leandro G, et al. Helicobacter pylori, transmission routes and recurrence of infection: state of the art. Acta Bio Medica Atenei Parmensis. 2018; 89(8S):72–6. https://doi.org/10.23750/abm.v89i8-S.7947 PMID: 30561421 51. Mamishi S, Eshaghi H, Mahmoudi S, Bahador A, Hosseinpour Sadeghi R, Najafi M, et al. Intrafamilial transmission of Helicobacter pylori: genotyping of faecal samples. British journal of biomedical science. 2016; 73(1):38–43. https://doi.org/10.1080/09674845.2016.1150666 PMID: 27182676 52. Sarker SA, Rahman MM, Mahalanabis D, Bardhan PK, Hildebrand P, Beglinger C, et al. Prevalence ofHelicobacter pylori infection in infants and family contacts in a poor Bangladesh community. Digestive diseases and sciences. 1995; 40(12):2669–72. https://doi.org/10.1007/bf02220458 PMID: 8536529 53. Kienesberger S, Perez-Perez GI, Olivares AZ, Bardhan P, Sarker SA, Hasan KZ, et al. When is Helicobacter pylori acquired in populations in developing countries? A birth-cohort study in Bangladeshi children. Gut microbes. 2018:1–12. 54. Bhuiyan TR, Qadri F, Saha A, Svennerholm A-M. Infection by Helicobacter pylori in Bangladeshi children from birth to two years: relation to blood group, nutritional status, and seasonality. The Pediatric infectious disease journal. 2009; 28(2):79–85. https://doi.org/10.1097/INF.0b013e31818a5d9d PMID: 19116602 55. Salih BA. Helicobacter pylori infection in developing countries: the burden for how long? Saudi journal of gastroenterology: official journal of the Saudi Gastroenterology Association. 2009; 15(3):201. 56. Ding Z, Zhao S, Gong S, Li Z, Mao M, Xu X, et al. Prevalence and risk factors of Helicobacter pylori infection in asymptomatic Chinese children: a prospective, cross-sectional, population-based study. Alimentary pharmacology & therapeutics. 2015; 42(8):1019–26. 57. Campbell RK, Schulze KJ, Shaikh S, Mehra S, Ali H, Wu L, et al. Biomarkers of environmental enteric dysfunction among children in rural Bangladesh. Journal of pediatric gastroenterology and nutrition. 2017; 65(1):40–6. https://doi.org/10.1097/MPG.0000000000001557 PMID: 28644348 58. Fahim SM, Das S, Sanin KI, Gazi MA, Mahfuz M, Islam MM, et al. Association of Fecal Markers of Environmental Enteric Dysfunction with Zinc and Iron Status among Children at First Two Years of Life in Bangladesh. The American journal of tropical medicine and hygiene. 2018. 59. Harper KM, Mutasa M, Prendergast AJ, Humphrey J, Manges AR. Environmental enteric dysfunction pathways and child stunting: A systematic review. PLoS neglected tropical diseases. 2018; 12(1): e0006205. https://doi.org/10.1371/journal.pntd.0006205 PMID: 29351288 60. De Serres F, Blanco I. Role of alpha-1 antitrypsin in human health and disease. Journal of internal medicine. 2014; 276(4):311–35. https://doi.org/10.1111/joim.12239 PMID: 24661570 61. Campbell RK, Schulze K, Shaikh S, Mehra S, Ali H, Wu L, et al. Biomarkers of environmental enteric dysfunction among children in rural Bangladesh. Journal of pediatric gastroenterology and nutrition. 2017; 65(1):40. https://doi.org/10.1097/MPG.0000000000001557 PMID: 28644348 62. Lima AA, Leite AM, Moura AF, Lima NL, Oria RB, Soares AM, et al., editors. Risk factors, gut function biomarkers and growth deficit associated with environmental enteropathy and malnutrition: The casecontrol mal-ed study in Fortaleza, Ceara, Brazil. American Journal of Tropical Medicine and Hygiene; 2015: AMER SOC TROP MED & HYGIENE 8000 WESTPARK DR, STE 130, MCLEAN, VA 22101 USA. 63. Badov D, Lambert J, Finlay M, Balazs N. Helicobacter pylori as a pathogenic factor in Menetrier’s disease. The American journal of gastroenterology. 1998; 93(10):1976. https://doi.org/10.1111/j.15720241.1998.00347.x PMID: 9772069 64. Sullivan P, Thomas J, Eastham E, Lunn P, Neale G. Helicobacter pylori and protein losing enteropathy. Archives of disease in childhood. 1990; 65(3):332. 65. Lekmeechai S, Su Y-C, Brant M, Alvarado-Kristensson M, Vallstro ¨m A, Obi I, et al. Helicobacter pylori outer membrane vesicles protect the pathogen from reactive oxygen species of the respiratory burst. Frontiers in microbiology. 2018;9. https://doi.org/10.3389/fmicb.2018.00009 66. Chmiela M, Walczak N, Rudnicka K. Helicobacter pylori outer membrane vesicles involvement in the infection development and Helicobacter pylori-related diseases. Journal of biomedical science. 2018; 25(1):78. https://doi.org/10.1186/s12929-018-0480-y PMID: 30409143 67. Yui S, Nakatani Y, Mikami M. Calprotectin (S100A8/S100A9), an inflammatory protein complex from neutrophils with a broad apoptosis-inducing activity. Biological and Pharmaceutical Bulletin. 2003; 26 (6):753–60. https://doi.org/10.1248/bpb.26.753 PMID: 12808281 68. Vaos G, Kostakis ID, Zavras N, Chatzemichael A. The role of calprotectin in pediatric disease. BioMed research international. 2013;2013. PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 17 / 18 69. Papamichael K, Konstantopoulos P, Mantzaris GJ. Helicobacter pylori infection and inflammatory bowel disease: is there a link? World journal of gastroenterology: WJG. 2014; 20(21):6374. https://doi. org/10.3748/wjg.v20.i21.6374 PMID: 24914359 70. van Beelen Granlund A, Østvik AE, Brenna Ø, Torp SH, Gustafsson BI, Sandvik AK. REG gene expression in inflamed and healthy colon mucosa explored by in situ hybridisation. Cell and tissue research. 2013; 352(3):639–46. https://doi.org/10.1007/s00441-013-1592-z PMID: 23519454 71. Easley R, Peterson K, Haque R, Petri W, Lyerly D, Buss J. Reg1B and malnutrition in Bangladeshi children. Age (in years). 1:5. 72. Dror G, Muhsen K. Helicobacter pylori infection and children’s growth: an overview. Journal of pediatric gastroenterology and nutrition. 2016; 62(6):e48–e59. https://doi.org/10.1097/MPG.0000000000001045 PMID: 26628446 73. Kalach N, Bontems P, Raymond J. Helicobacter pylori infection in children. Helicobacter. 2017; 22: e12414. 74. Pacifico L, Osborn JF, Tromba V, Romaggioli S, Bascetta S, Chiesa C. Helicobacter pylori infection and extragastric disorders in children: a critical update. World Journal of Gastroenterology: WJG. 2014; 20 (6):1379. https://doi.org/10.3748/wjg.v20.i6.1379 PMID: 24587617 75. O ¨zc¸ay F, Demir H, O ¨zen H, Gu¨rakan F, Saltik IN, Yu¨ce A, et al. Normal growth in young children with Helicobacter pylori infection. Journal of pediatric gastroenterology and nutrition. 2002; 35(1):102. https://doi.org/10.1097/00005176-200207000-00024 PMID: 12142822 76. Chiu N-C, Lin C-Y, Chi H, Yeung C-Y, Ting W-H, Chan W-T, et al. Helicobacter pylori infection is not associated with failure to thrive: a case control study. Therapeutics and clinical risk management. 2017; 13:273. https://doi.org/10.2147/TCRM.S123148 PMID: 28260914 PLOS NEGLECTED TROPICAL DISEASES Helicobacter pylori, EED and growth in children PLOS Neglected Tropical Diseases | https://doi.org/10.1371/journal.pntd.0008243 April 23, 2020 18 / 18