Dataset Information

Disentangling Microbial Mediators of Malnutrition: Modeling Environmental Enteric Dysfunction.

ABSTRACT: Environmental enteric dysfunction (EED) (also referred to as environmental enteropathy) is a subclinical chronic intestinal disorder that is an emerging contributor to early childhood malnutrition. EED is common in resource-limited settings, and is postulated to consist of small intestinal injury, dysfunctional nutrient absorption, and chronic inflammation that results in impaired early child growth attainment. Although there is emerging interest in the hypothetical potential for chemical toxins in the environmental exposome to contribute to EED, the propensity of published data, and hence the focus of this review, implicates a critical role of environmental microbes. Early childhood malnutrition and EED are most prevalent in resource-limited settings where food is limited, and inadequate access to clean water and sanitation results in frequent gastrointestinal pathogen exposures. Even as overt diarrhea rates in these settings decline, silent enteric infections and faltering growth persist. Furthermore, beyond restricted physical growth, EED and/or enteric pathogens also associate with impaired oral vaccine responses, impaired cognitive development, and may even accelerate metabolic syndrome and its cardiovascular consequences. As these potentially costly long-term consequences of early childhood enteric infections increasingly are appreciated, novel therapeutic strategies that reverse damage resulting from nutritional deficiencies and microbial insults in the developing small intestine are needed. Given the inherent limitations in investigating how specific intestinal pathogens directly injure the small intestine in children, animal models provide an affordable and controlled opportunity to elucidate causal sequelae of specific enteric infections, to differentiate consequences of defined nutrient deprivation alone from co-incident enteropathogen insults, and to correlate the resulting gut pathologies with their functional impact during vulnerable early life windows.

SUBMITTER: Bartelt LA

PROVIDER: S-EPMC6477186 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Disentangling Microbial Mediators of Malnutrition: Modeling Environmental Enteric Dysfunction.

Bartelt Luther A LA Bolick David T DT Guerrant Richard L RL

Cellular and molecular gastroenterology and hepatology 20190107 3

Environmental enteric dysfunction (EED) (also referred to as environmental enteropathy) is a subclinical chronic intestinal disorder that is an emerging contributor to early childhood malnutrition. EED is common in resource-limited settings, and is postulated to consist of small intestinal injury, dysfunctional nutrient absorption, and chronic inflammation that results in impaired early child growth attainment. Although there is emerging interest in the hypothetical potential for chemical toxins ...[more]

PMID: 30630118

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Project description:BackgroundEcological interactions among microorganisms are fundamental for ecosystem function, yet they are mostly unknown or poorly understood. High-throughput-omics can indicate microbial interactions through associations across time and space, which can be represented as association networks. Associations could result from either ecological interactions between microorganisms, or from environmental selection, where the association is environmentally driven. Therefore, before downstream analysis and interpretation, we need to distinguish the nature of the association, particularly if it is due to environmental selection or not.ResultsWe present EnDED (environmentally driven edge detection), an implementation of four approaches as well as their combination to predict which links between microorganisms in an association network are environmentally driven. The four approaches are sign pattern, overlap, interaction information, and data processing inequality. We tested EnDED on networks from simulated data of 50 microorganisms. The networks contained on average 50 nodes and 1087 edges, of which 60 were true interactions but 1026 false associations (i.e., environmentally driven or due to chance). Applying each method individually, we detected a moderate to high number of environmentally driven edges-87% sign pattern and overlap, 67% interaction information, and 44% data processing inequality. Combining these methods in an intersection approach resulted in retaining more interactions, both true and false (32% of environmentally driven associations). After validation with the simulated datasets, we applied EnDED on a marine microbial network inferred from 10 years of monthly observations of microbial-plankton abundance. The intersection combination predicted that 8.3% of the associations were environmentally driven, while individual methods predicted 24.8% (data processing inequality), 25.7% (interaction information), and up to 84.6% (sign pattern as well as overlap). The fraction of environmentally driven edges among negative microbial associations in the real network increased rapidly with the number of environmental factors.ConclusionsTo reach accurate hypotheses about ecological interactions, it is important to determine, quantify, and remove environmentally driven associations in marine microbial association networks. For that, EnDED offers up to four individual methods as well as their combination. However, especially for the intersection combination, we suggest using EnDED with other strategies to reduce the number of false associations and consequently the number of potential interaction hypotheses. Video abstract.

Project description:OBJECTIVES:Environmental enteric dysfunction (EED) may inhibit growth and development in low- and middle-income countries, but available assessment methodologies limit its study. In rural Bangladesh, we measured EED using the widely used lactulose mannitol ratio (L:M) test and a panel of intestinal and systemic health biomarkers to evaluate convergence among biomarkers and describe risk factors for EED. METHODS:In 539 18-month-old children finishing participation in a randomized food supplementation trial, serum, stool, and urine collected after lactulose and mannitol dosing were analyzed for biomarkers of intestinal absorption, inflammation, permeability and repair, and systemic inflammation. EED scores for each participant were developed using principal component analysis and partial least squares regression. Associations between scores and L:M and with child sociodemographic and health characteristics were evaluated using regression analysis. RESULTS:EED prevalence (L:M?>?0.07) was 39.0%; 60% had elevated acute phase proteins (C-reactive protein >5 mg/L or ?-1 acid glycoprotein >100 mg/dL). Correlations between intestinal biomarkers were low, with the highest between myeloperoxidase and ?-1 antitrypsin (r?=?0.33, P?<?0.01), and biomarker values did not differ by supplementation history. A 1-factor partial least squares model with L:M as the dependent variable explained only 8.6% of L:M variability. In adjusted models, L:M was associated with child sex and socioeconomic status index, whereas systemic inflammation was predicted mainly by recent illness, not EED. CONCLUSIONS:Impaired intestinal health is widespread in this setting of prevalent stunting, but a panel of serum and stool biomarkers demonstrated poor agreement with L:M. Etiologies of intestinal and systemic inflammation are likely numerous and complex in resource-poor settings, underscoring the need for a better case definition with corresponding diagnostic methods to further the study of EED.

Dataset Information

Disentangling Microbial Mediators of Malnutrition: Modeling Environmental Enteric Dysfunction.

Publications

Disentangling Microbial Mediators of Malnutrition: Modeling Environmental Enteric Dysfunction.

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