Abstract
BackgroundChildhood undernutrition remains a significant global health challenge accounting for over half of all under 5 child mortality. Moderate acute malnutrition (MAM), which leads to wasting [weight-for-length z-scores (WLZ) between − 2 and − 3], affects 33 million children under 5 globally and more than 2 million in Bangladesh alone. We have previously reported that acute malnutrition in this population is associated with gut microbiota immaturity, and in a small, 1-month pre-proof-of-concept (POC) study demonstrated that a microbiota-directed complementary food formulation (MDCF-2) was able to repair this immaturity, promote weight gain and increase plasma biomarkers and mediators of healthy growth. Here we describe the design controlled feeding study that tests whether MDCF-2 exhibits superior efficacy (ponderal growth, host biomarkers of a biological state) than a conventional Ready-to-use Supplementary Food (RUSF) in children with MAM over intervention period of 3 months.MethodsTwo separate cohorts of 12–18-month-old children will be enrolled: 124 with primary MAM, and 124 with MAM after having been treated for severe acute malnutrition (post-SAM MAM). We have established several field sites in an urban slum located in the Mirpur district of Dhaka, Bangladesh and at a rural site, Kurigram in the north of Bangladesh. The two groups of children receiving MDCF-2 and RUSF will be compared at baseline (pre-intervention), after 1 month, at the end of intervention (3 months), 1 month after cessation of intervention, and every 6 months thereafter for 4 years.DiscussionThis study will determine whether daily, controlled administration of MDCF-2 for 3 months provides superior improvements in weight gain, microbiota repair, and elevated levels of key plasma biomarkers/mediators of healthy growth compared to the control RUSF formulation. The pathogenesis of MAM is poorly defined and there are currently no WHO-approved treatments; results from the current study of children with primary MAM and post-SAM MAM will shed light on the effects of the gut microbiota on childhood growth/development and will provide a knowledge base that may help improve complementary feeding practices.Trial registrationThe primary MAM and post-SAM MAM trials are registered in Clintrials.gov (NCT04015999 and NCT04015986, registered on July 11, 2019, retrospectively registered).
Highlights
Childhood undernutrition remains a significant global health challenge accounting for over half of all under 5 child mortality
Moderate acute malnutrition (MAM), a major global health problem, is defined as wasting and/or mid-upper-arm circumference (MUAC) greater or equal to 115 mm and less than 125 mm
Using the 15 ecogroup taxa, we found that Bangladeshi children with MAM and Severe acute malnutrition (SAM) have impaired gut community development; this perturbation is worse in children with MAM compared to SAM and is not repaired by currently available nutritional interventions, which are not designed based on knowledge and/or consideration of gut microbial community development [6]
Summary
Children will be screened and enrolled through household surveys by Field Research Assistants (FRAs) following pre-specified inclusion criteria (see Table 1 for inclusion/exclusion criteria) For those who meet the enrollment criteria, a full description of the purpose of the study will be provided, including the number and type of biological samples to be collected. We have established a Food Processing Laboratory at the Mirpur and Kurigram field sites in order to freshly prepare the MDCF-2 and RUSF formulations each day prior to their distribution on that day to study participants. In the stabilization phase of the post-SAM MAM trial, each child will be managed according to WHO/icddr,b guidelines [7] This protocol includes programmed feeding, micronutrient supplementation, judicious rehydration, broad spectrum antibiotic treatment and prompt recognition and management of complications. A variety of computational tools, including those that allow for feature reduction [6, 10], will be applied to these multi-omic datasets to identify significant correlations between components of the microbiota/microbiome, proteome, metabolome and clinical parameters
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