Growth stunting in children with EED linked with duodenal microbiota, enteropathy
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Investigators observed a relationship between growth stunting and small intestinal microbiota components and enteropathy in children with environmental enteric dysfunction.
This demonstrated the possible need for therapies that would target microbial contributions to environmental enteric dysfunction.
“The microbial community of the small intestine remains a ‘terra incognita,’ and its relationship to the pathogenesis of gut barrier dysfunction, enteropathy, and stunting has been largely unexplored,” Robert Y. Chen, MD, PhD, from Edison Family Center for Genome Sciences and Systems Biology, the Center for Gut Microbiome and Nutrition Research at Washington University School of Medicine, and colleagues wrote. “Our results emphasize the need for techniques for performing imaging and sampling of the small intestine that are less invasive than those currently available in routine practice.”
The study included 110 children (mean age, 18 months) from an urban slum in Dhaka, Bangladesh, with linear growth stunting and who had not improved with a nutritional benefit. Chen and colleagues performed an endoscopy in 80 children with biopsy-confirmed environmental enteric dysfunction and had plasma and duodenal samples available. Investigators then obtained and quantified levels of 4,077 plasma proteins and 2,619 proteins in duodenal biopsy samples. They used culture-independent methods to determine the levels of bacterial strains in microbiota from duodenal aspirate. Additionally, they obtained 21 plasma samples and 27 fecal samples from healthy age-matched children.
Results showed the absolute levels of 14 taxa were negatively associated with linear growth (length-for-age z score, r = –0.49; P = .003) and positively associated with duodenal proteins in immunoinflammatory responses.
“The representation of these 14 duodenal taxa in fecal microbiota was significantly different from that in samples obtained from healthy children (P < .001 by permutational multivariate analysis of variance),” Chen and colleagues wrote.
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