Background
Methods/Design
General study design/recruitment
Inclusion and non-inclusion criteria
Inclusion criteria | Exclusion criteria |
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ᅟ•ᅟChildren between the age of 24 and 60 months ᅟ•ᅟGeneral health status allowing for the tests to be performed | •ᅟHIV positive test at inclusion •ᅟSigns of respiratory distress (≥40/min) •ᅟFever (≥ 38.5 °C) •ᅟInfectious diarrhoea with mucus or blood •ᅟAntibiotics taken in the 2 weeks prior to inclusion •ᅟRenutrition regime taken in the 6 months prior to inclusion •ᅟSeptic shock •ᅟVomiting •ᅟAcute malnutrition (WHZ ≤ − 2) |
Recruitment procedures
Madagascar
CAR
Variables collected
Anthropometric measurements
Biological measurements and tests performed
Developing a better diagnostic test for pediatric environmental enteropathy
Candidate biomarkers | Pathophysiological change measured | Sample type needed for analysis |
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Lactitol-mannitol test | Intestinal permeability | Urine |
Citrulline | Villous atrophy | Blood |
α anti-trypsin | Altered intestinal barrier | Faeces |
Calprotectin | Mucosal inflammation | Faeces |
C reactive protein (CRP) | Systemic inflammation | Blood |
Endotoxine (circulating LPS) | Bacterial leakage into the systemic circuit (intestinal permeability) | Faeces |
Immunoglobulines | Adaptive immune response | Blood, faeces, duodenal aspirates |
Small intestinal bacterial overgrowth | Too important bacterial load in the small intestine | Duodenal aspirates |
Specific bacteria or eukaryotes | Disturbances in the gut ecosystem | Faeces, duodenal and gastric aspirates |
Specific bile acid profiles | Disturbances in the gut ecosystem | Faeces, duodenal and gastric aspirates |
Understanding the broader environment of children with PEE
Aspect addressed
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Reasoning
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Methods used
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Study site
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Statistical considerations
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Social relations, political and economic conditions of children | Stunting and PEE are linked to poverty. Specific political economic conditions and social relations appear to be drivers of these two syndromes. | Participant-observations Open-ended interviews focusing on life histories, family histories, specific practices of social interactions, hygiene and feeding of children GPS mapping of major points in neighborhoods (food, contamination, play areas, waste disposal, etc.) | Bangui & Antananarivo | 30 families with a stunted child/ child with PEE and 30 families with a non-stunted child per country or until exhaustion. Data analysis using “grounded theory” approach |
Risk factors | To date, very little is known about the actual risk factors for PEE, a fact that hampers developing evidence-based prevention strategies. | Standardized questionnaire about the general health status of children, nutrition, family composition, hygiene and mother’s pregnancy Biological data on micronutrient deficiencies, inflammation, parasite load | Bangui & Antananarivo | Hypothesizing a PEE prevalence of 75% in controls [57, 80] and 85% in cases, to show an odds ratio of 4.8 a power of 80% and a two-sided α = 0.05, an expected proportion of exposed controls of 32%, a sample size of 30 stunted children and 100 non-stunted controls is needed. Accounting for 10% of secondary exclusion, the required sample size is 34 stunted children and 111 non-stunted control children. |
Diagnostic test | To date, the reference test for PEE, the lactitol-mannitol gut permeability test, is difficult and costly to perform in low-income settings. Further, gut permeability is a non-specific aspect of any inflammatory disease of the intestine. Efforts are therefore needed as to find other, more specific and easier to use biomarkers of the syndrome. The lactitol-mannitol gut permeability test is therefore an imperfect test. | Measurement of a given set of nine different biomarkers Sensitivity/Specificity testing against the reference test and latent model of the different markers. | Bangui & Antananarivo | Sample size was calculated based on the formula provided by Beam et al. [92] for matched-groups diagnostic study. Assuming a sensitivity and specificity of 80% for the candidate biomarker, respectively (the sensitivity and specificity of the imperfect reference test were estimated to be respectively 90 and 80%), with a power of 80%, a probability of disagreement of 0.18 between the two test, an assumed secondary exclusion of 10%, the total estimated sample size is of 128 children, 64 with PEE and 64 without PEE. With an estimated PEE prevalence of 85% among the stunted children and 75% among the non-stunted controls [80], 75 stunted children and 256 non-stunted controls have to be included, hence a total of 331 children. |
Asymptomatic enteropathogen carriage | It is well established that diarrhea and undernutrition complement each other in a deleterious vicious circle, however, the prevalence of PEE seems higher among the pediatric population than the prevalence of recurrent/chronic diarrhea [11, 80]. The degree of overlap between these two entities remains unclear. To date, data on possible links between asymptomatic pathogen carriage and stunting remain scarce. The MAL-ED consortium found a relation between asymptomatic enteropathogen carriage and stunting, which likely is mediated through systemic inflammation [100]. It is likely that other pathogens might also contribute to PEE in subclinical infections. | qPCR on a given list of enteric pathogens (bacteria, viruses and parasites) Microscopy for parasites | Bangui & Antananarivo | Based on earlier studies in Antananarivo [103] and Bangui [104, 105] we assume a prevalence of roughly 10% of any asymptomatic microorganism carriage, among children. To show an odds ratio of 3 between stunting and any asymptomatic pathogen carriage, with an asymptomatic pathogen carriage prevalence of 10% in non- stunted children [105], a power of 80% and a two-sided α = 0.05, a sample size of 97 stunted children and 97 non-stunted controls are to be recruited. To show an odds ratio of 3 between the carriage of a given parasite and PEE, with a pathogen prevalence of 10% in non-PEE children, a power of 80% and a two-sided α = 0.05, a sample size of 97 PEE children and 97 non-PEE controls are to be recruited. Assuming a PEE prevalence of 85% among the stunted children and 75% among the non-stunted controls [80], 115 stunted children and 380 non-stunted controls are to be recruited to assess the association between nutritional status and PEE. With a secondary exclusion of 10%, this sums to a total of 475 non-stunted children and 144 stunted children for each country. The analysis will be performed pooled on both countries as to have enough sample size. |
Small intestinal bacterial overgrowth (SIBO) | Impaired small intestinal barrier functions – possibly also impaired digestive and nutrient transport functions - seem to be largely caused by the stable constitution of small intestinal bacterial overgrowth (SIBO) [50, 106] causing local and systemic endotoxemia, thus excessive local and systemic inflammation [83]. SIBO is prevalent in shanty towns in many places [50, 83, 107, 108] and it is therefore likely that SIBO might have a role in PEE. | Culture of duodenal samples (SIBO > 105 bacteria/ml of aspirate) | Bangui & Antananarivo | SIBO analysis can, for ethical reasons, only be performed on stunted children. In the context of this study, 400 stunted children (200 severely stunted and 200 moderately stunted) will be recruited and aspirated. We therefore could not estimate a sample size, but will analyze all collected samples and compare the moderately to the severely malnourished children estimating the power retrospectively (exploratory analysis): |
Microbial composition of the gastrointestinal tract (primary objective) | It has long been speculated that the microbiota might be changed in PEE. However, to date, only a single study in fecal samples was performed, showing changes in the gut microbiota of PEE children compared to their healthy controls [48]. One of the strengths of AFRIBIOTA is its capacity to collect samples in their most relevant location, particularly the collection of duodenal fluid in affected children, which will allow studying the microbiota composition at the location where disease takes place. | Amplicon sequencing (16S, 18S, ITS) IgA targeted bacterial fraction (BugFacs) Metagenomics | Bangui & Antananarivo | We estimate at least 100 samples per categories and per country are required (effect size unknown, convenience sampling). |
Bile salt profiles | Primary bile acids are crucial players in fat absorption. They are transformed into secondary bile acids by the resident gut microbiota. Bile acids are shaping the microbiota by promoting the growth of bile acid-metabolizing bacteria and by inhibiting the growth of bile-sensitive bacteria. In a recent study, serum bile acid profiles were changed in PEE children [90]. | Mass spectrometry analysis | Bangui & Antananarivo | We estimate at least 100 samples per categories and per country are required (effect size unknown, convenience sampling). |
Mucosal immune system | To date, while it is increasingly clear that mucosal immune dysfunction is linked to stunted growth [109], there is little knowledge on how PEE affects the immune system of the small intestine. Campbell et al. showed that PEE leads to an increased presence of T-cells in the lamina propria and the epithelium of the small intestine of children with PEE [45, 46]. Brown et al. showed that in a weaned mouse model for PEE, the presence of NK T cells in the gut was increased [26]. In humans, it is highly challenging to analyze the mucosal immune system. As specific immune cells release specific cytokines, we will assess the presence or absence of individual cytokines. | Cytokine/Chemokines/Growth Hormone profiling Immunoglobulin profiling | Bangui & Antananarivo | We estimate at least 100 samples per categories and per country are required (effect size unknown, convenience sampling). |
Systemic immune system | In the context of chronic enteropathy, the ratio of circulating TH17 to Treg cells is increased [109, 110]. To date, nothing is known about the circulating cell populations in PEE. We therefore analyze the circulating cell populations of children with chronic undernutrition and/or PEE. We will use five eight-color antibody panels as well as cytokine and immunoglobulin profiling in order to quantify and characterize the major leukocyte populations and their secreted immune molecules. | Cytokine/Chemokines/Growth hormone profiling Immunoglobulin profiling Flow cytometry (B-cells, NK-cells, monocytes and the different subsets of CD4+ T-cells (TH1, TH2, TH17 and Treg) [68]. | Bangui (cytokine/immunoglobulin profiling) & Antananarivo (cytokine/immunoglobulin profiling and flow cytometry) | We estimate at least 100 samples per categories and per country are required (effect size unknown, convenience sampling). |
Mounting of immune responses | Vaccines are performing less well in the developing world than in industrialized countries [59]. We hypothesize that this is due to changes in immune homeostasis and abrogated immune responses as a result of PEE, an association that was previously shown in a few studies [55, 93, 110, 111]. In low-income settings, there is widespread absence of trustworthy vaccine records. Therefore, we aim at using an alternative approach, the TruCulture stimulation system (Myriad). This allows investigating the immune response of children in vitro [69]. Stimuli selected include LPS (gram negative bacteria), Poly I:C (double stranded RNA viruses) and staphylococcal enterotoxin B (SEB) (T-cells). These stimuli were selected as they represent the two groups of pathogens that cause the most orally contracted infections in small children and target the T-cell response implicated in PEE pathophysiology [26, 46]. | TruCulture system (Myriad)/ Cytokine/Chemokines/Growth hormone profiling [69] | Antananarivo | We estimate at least 100 samples per categories and per country are required (effect size unknown, convenience sampling). |
Psychomotor development of children | Changes in the microbiota and its metabolites have been associated since several years with brain development (“gut-brain axis”) [112]. Recent reports also reported helminth carriage and associated microbiota changes as one of the risk factors of delayed psychomotor development [113]. Considering the role these entities play in PEE, it is therefore likely that PEE is associated with psychomotor delays [114]. | Adapted version of the ASQ3 test | Antananarivo | For the psychometric analysis internal consistency (Cronbach’s alpha), test-retest, and inter-rater (Kappa statistics with expert child development specialist) are performed. Validity of the tool is measured using the Pearson product moment test and factor analysis (FA). For association with PEE, we estimate to required at least 100 samples per category (effect size unknown) |