| Literature DB >> 30025542 |
Pascale Vonaesch1, Rindra Randremanana2, Jean-Chrysostome Gody3, Jean-Marc Collard4, Tamara Giles-Vernick5, Maria Doria1, Inès Vigan-Womas6, Pierre-Alain Rubbo7, Aurélie Etienne2, Emilson Jean Andriatahirintsoa8, Nathalie Kapel9, Eric Brown10, Kelsey E Huus10, Darragh Duffy11, B Brett Finlay10, Milena Hasan12, Francis Allen Hunald13, Annick Robinson14, Alexandre Manirakiza15, Laura Wegener-Parfrey16, Muriel Vray5, Philippe J Sansonetti17.
Abstract
BACKGROUND: Globally one out of four children under 5 years is affected by linear growth delay (stunting). This syndrome has severe long-term sequelae including increased risk of illness and mortality and delayed psychomotor development. Stunting is a syndrome that is linked to poor nutrition and repeated infections. To date, the treatment of stunted children is challenging as the underlying etiology and pathophysiological mechanisms remain elusive. We hypothesize that pediatric environmental enteropathy (PEE), a chronic inflammation of the small intestine, plays a major role in the pathophysiology of stunting, failure of nutritional interventions and diminished response to oral vaccines, potentially via changes in the composition of the pro- and eukaryotic intestinal communities. The main objective of AFRIBIOTA is to describe the intestinal dysbiosis observed in the context of stunting and to link it to PEE. Secondary objectives include the identification of the broader socio-economic environment and biological and environmental risk factors for stunting and PEE as well as the testing of a set of easy-to-use candidate biomarkers for PEE. We also assess host outcomes including mucosal and systemic immunity and psychomotor development. This article describes the rationale and study protocol of the AFRIBIOTA project.Entities:
Keywords: Biomarkers; Central African Republic; Child development; Immunology; Madagascar; Medical anthropology; Microbiota; Pediatric environmental enteropathy; Risk factors; Stunting
Mesh:
Year: 2018 PMID: 30025542 PMCID: PMC6053792 DOI: 10.1186/s12887-018-1189-5
Source DB: PubMed Journal: BMC Pediatr ISSN: 1471-2431 Impact factor: 2.125
Fig. 1Scheme depicting the different entities underlying or being affected by pediatric environmental enteropathy (PEE). Underlying causes are colored in orange, physiological changes in red and consequences in green
Inclusion and exclusion criteria
| Inclusion criteria | Exclusion criteria |
|---|---|
| ᅟ•ᅟChildren between the age of 24 and 60 months | •ᅟHIV positive test at inclusion |
Fig. 2Recruitment Schema of the AFRIBIOTA project
Fig. 3Framework of the different interacting entities being associated with stunting and pediatric environmental enteropathy (PEE). Data collected for each entity in the context of the AFRIBIOTA project is indicated in red. Interactions in between the different entities are indicated with arrows. The child’s macro-environment is influencing all other entities
Aspects of PEE and stunting studied by the AFRIBIOTA study group
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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 | Bangui & Antananarivo | 30 families with a stunted child/ child with PEE and 30 families with a non-stunted child per country or until exhaustion. |
| 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 | Bangui & Antananarivo | Hypothesizing a PEE prevalence of 75% in controls [ |
| 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 | Bangui & Antananarivo | Sample size was calculated based on the formula provided by Beam et al. [ |
| 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 [ | qPCR on a given list of enteric pathogens (bacteria, viruses and parasites) | Bangui & Antananarivo | Based on earlier studies in Antananarivo [ |
| 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) [ | 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 [ | Amplicon sequencing (16S, 18S, ITS) | 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 [ | 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 [ | Cytokine/Chemokines/Growth Hormone 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 [ | Cytokine/Chemokines/Growth hormone profiling | 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 [ | TruCulture system (Myriad)/ Cytokine/Chemokines/Growth hormone profiling [ | 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”) [ | 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). |
Fig. 4Schema of the biomarker analysis performed in AFRIBIOTA. Features assessed are indicated in black, measurements performed within the context of AFRIBIOTA in blue
Candidate biomarkers for environmental enteropathy
| Candidate biomarkers | Pathophysiological change measured | Sample type needed for analysis |
|---|---|---|
| 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 |