Association between intestinal bacterial carriage, biomarkers of environmental enteric dysfunction, and stunting in rural Malawian children

Ethical considerations

The MORDOR trial was conducted in accordance with the Declaration of Helsinki. It was approved by the London School of Hygiene and Tropical Medicine Ethics Committee (UK) (reference number 6500) and the College of Medicine Research Ethics Committee (Malawi) (P.02/14/1521). Information and consent forms were translated into local languages (Yao and Chichewa) prior to their approval by the local ethics committee. Consent was first obtained at the community level through discussions with the village chief and community elders who then verbally indicated whether the community was willing to participate. Written, informed consent (by thumbprint or signature) was then obtained from the parent or legal guardian of each child for inclusion before they participated in the study. All parents and guardians were informed of their freedom to withdraw their child from the study at any time without a requirement to give a reason(s).

Study design

This study made use of fecal samples, and demographic and anthropometry data gathered during a baseline assessment of the prevalence of carriage of macrolide resistant enteropathogens undertaken as part of a multi-country randomized controlled trial named “MORDOR” (NCT02047981). The trial study design and protocol have been previously published^13,14. Briefly, a total of 1,090 children residing in 30 clusters within the Mangochi district were enrolled into the baseline survey. All enrolled children were aged 1 to 59 months and weighed at least 3.8kg. Sample and data collection took place between May and July 2015. Details of fecal sample collection have been described in previous studies^15,16. This study is based off the first named author’s PhD thesis¹⁷.

Laboratory methods

Total, genomic DNA was isolated from 250mg fecal sample using the commercially available PowerSoil DNA Isolation Kit (MO BIO Laboratories Inc, Carlsbad, CA, now a part of Qiagen, Germany). As a quality control measure, DNA yield was quantified in 10% of samples using the Qubit dsDNA HS assay kit (Invitrogen, CA, USA). Endpoint qPCR was performed to detect the presence of the following bacteria: Akkermensia muciniphila, Bifidobacterium longum Dorea formicigenerans, and Faecalibacterium prausnitzii. Each PCR reaction used a 1:10 diluted DNA sample to negate any unwanted effects of high DNA yield. The qPCR was performed using a Rotorgene-Q instrument (Qiagen, Hilden, Germany) where samples were run in a 72-well rotor format. The qPCR assays were designed and performed using the microbial DNA qPCR assay platform (Qiagen). The total volume of a single PCR reaction was 12.5µl and each reaction contained 6.25µl of microbial qPCR master mix (Qiagen), a commercial microbial DNA qPCR assay containing primers (10µM), and a 5’-hydrolysis probe (5 µM) targeting the bacterial 16S rRNA gene and 3µl template DNA in an aqueous solution. A no template control and a microbial DNA positive control (Qiagen) were included on each run. Thermal cycling conditions for the assay were 95°C for 10 minutes followed by 40 cycles of 95°C for 15 seconds and 60°C for 2 minutes. The endpoint qPCR results were classified as positive or negative using a method by Pickering et al.,¹⁸

To quantify fecal biomarkers of EED, commercially available enzyme-linked immunosorbent assay (ELISA) kits for MPO (Immundiagnostik, Germany), AAT (Immundiagnostik), and NEO (Genway, CA, USA) were used for the quantification of each biomarker¹⁶.

Height/length measurements

The SECA Leicester height measure (Chasmors Ltd., UK) was used to measure height for children who were ≥2 years of age and able to stand whereas the SECA 417 infantometer (Chasmors Ltd.) was used to measure recumbent length for children who were <2 years of age or unable to stand unaided. Both height and length were measured to within 0.1 cm. All measurements were taken in triplicate by field nurses.

Statistical analysis

To describe the prevalence of carriage of defined bacteria, the proportions of fecal samples with a positive qPCR result for each of the defined bacteria were calculated. The biomarkers of EED were assessed individually or were combined to form a composite EED score as described by Kosek et al.,¹¹ with minor modifications as detailed elsewhere¹⁶. The distribution of the biomarkers of EED was determined using the median (IQR) concentration of the fecal biomarkers. Published cut-off values for each of the three biomarkers^11,19 were used to determine proportions of fecal samples with elevated biomarkers. The World Health Organization (WHO) 2006 Child Growth Standards were used for the calculation of height-for-age Z (HAZ) scores²⁰. Participants with out-of-range HAZ scores, (>6 or <-6) were not included in the subsequent analyses as such scores are biologically implausible. HAZ scores were used in analyses as continuous variables or categorized into not stunted or stunted, defined as having a Z score of <-2. Fisher’s exact or Pearson’s chi-square tests were used to explore associations between bacterial carriage and sex, age, biomarkers of EED, and stunting. Age and sex adjusted regression models were also used to explore the relationship between bacterial carriage, biomarkers of EED, and stunting.

Baseline characteristics of participants

The baseline survey of prevalence of carriage of macrolide resistant enteropathogens enrolled 1,090 children, of which only 709 (65%) returned fecal samples. Of the 709 fecal samples, 613 fecal samples had sufficient volume for the analyses of intestinal bacterial carriage while 523 of the 613 fecal samples had sufficient remaining volume for the analyses of fecal biomarkers of EED. Characteristics of all children who were included in the final analyses of this study and those not included are shown in Table 1. Participant sex was comparable between all participants who were not included the analyses and those included in the bacterial carriage and EED biomarker analyses whilst differences were seen for age and height between children included in the analyses of bacterial carriage and EED biomarkers and all participants not included in the analyses.

Prevalence of bacterial carriage and biomarker distribution

F. prausnitzii was the most prevalent bacterium, appearing in 98% of the samples (Table 2). D. formicigenerans was present in 79% of the samples, A. muciniphila was found in 43% of the samples, and B. longum was present in just over one third of the fecal samples. Fecal samples were stratified by sex and age to compare bacterial carriage. There was no difference in the prevalence of F. prausnitzii, B. longum and A. muciniphila between male and female children, however, a higher proportion of fecal samples from male children were positive for D. formicigenerans compared to the female children (Table 2). B. longum was most prevalent in fecal samples from the youngest age group while D. formicigenerans, F. prausnitzii, and A. muciniphila were more prevalent in the older children (Table 2).

Of the 523 fecal samples that were available for the measurement of fecal biomarkers of EED, 488 had sufficient sample volume for MPO ELISA, 421 for NEO, and 495 for AAT. Four hundred and twenty one samples had results for all the three markers. A larger proportion of children [77% (324/421)] had elevated NEO levels relative to published reference values (NEO <=70 nmol/L, AAT <=0.27 mg/g and MPO <=2000 ng/ml)^11,19. Approximately, one third of the children had elevated MPO levels and levels of fecal AAT were elevated in 16% of the children (Table 3). The comparison of biomarker concentrations by sex did not show any differences in MPO and AAT concentrations; however, NEO concentration was higher in female children compared to male children (Table 3). There were significant differences in biomarker distribution among the five age groups. Median fecal concentration for all the three biomarkers was higher in younger children compared to older children (Table 3).

Association between bacterial intestinal carriage and biomarkers of EED

Logistic regression analysis examining the relationship between bacterial carriage and biomarker concentration did not find any association between fecal carriage of A. muciniphila or F. prausnitzii and any of the three individual biomarkers of EED. However, fecal carriage of B. longum was associated with increased odds of having elevated biomarker concentrations (vs normal concentrations), whilst fecal samples that were positive for D. formicigenerans were 70% less likely to have elevated MPO concentration (Table 4).

B. longum carriage in children younger than 24 months was associated with fecal concentrations of MPO and NEO but not in the older children (Table 5). Elevated MPO concentration was found in fecal samples of children aged between 0-12 months who were positive for B. longum while children aged between 12-24 months who were positive for B. longum were more likely to have elevated NEO concentration. D. formicigenerans carriage was not associated with any individual biomarker in any of the age groups (Table 6).

Bacterial carriage and composite EED score were analyzed by age and sex adjusted logistic regression. Composite EED scores were categorized into low and high scores centered around the mean score (1.73). B. longum, but not the other three bacteria species, was associated with the composite EED score. Fecal samples that were positive for B. longum were more likely to have a high composite EED score (Table 7).

Bacterial carriage and biomarkers of EED were not associated with stunting

Height measurements and demographic (age and sex) data were available for all participants whose fecal samples were assayed for bacterial carriage (n=613) and 488 of those whose samples were assayed for individual biomarkers of EED. For the complete data set, mean (SD) HAZ score was -1.6 (1.5) with 38% (229/607) of the children stunted. There was no relationship between bacterial carriage and HAZ or stunting. Similarly, none of the individual EED biomarkers or the composite EED score were associated with HAZ or stunting (Table 8).

Underlying data

Figshare: Association between intestinal bacterial carriage, biomarkers of environmental enteric dysfunction and stunting in rural Malawian children.

https://doi.org/10.6084/m9.figshare.20178065.v1³⁶

This project contains the following underlying data:

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).