Household Food Insecurity Alters Gut Microbiome Composition and Enriches Sutterella in Ethiopian Schoolchildren.

Beta diversity analysis revealed a significant shift in gut microbiome composition between food-secure and food-insecure children.

• Fecal samples were collected from 57 school-aged children in Ethiopia.
• Microbial profiles were established using 16S rRNA amplicon paired-end sequencing.
• Bray-Curtis dissimilarity analysis with PERMANOVA yielded p < 0.05.
• Food security status was assessed using the Household Food Insecurity Access Scale (HFIAS).

Alpha diversity did not differ significantly across food security status groups.

• Wilcoxon p > 0.05 for alpha diversity comparisons.
• This finding indicates that overall species richness and evenness were not meaningfully altered by food insecurity status.
• The sample included 57 school-aged children in Ethiopia.

Individual HFIAS questions used as proxies for dietary deprivation were each associated with significant changes in microbial composition.

• Three specific dietary deprivation proxies were examined: limited dietary variety, consumption of disliked foods, and reduced meal size.
• Each was associated with significant changes in microbial composition (PERMANOVA; all q < 0.05).
• These component-specific analyses provided more granular insight than the composite food insecurity variable alone.

Sutterella was consistently identified as significantly more abundant among food-insecure participants across multiple analytical approaches.

• In the composite HFI model, Sutterella enrichment showed q = 0.11.
• In component-specific models using individual HFIAS questions as proxies, Sutterella enrichment showed q < 0.05.
• Differential abundance analyses consistently identified Sutterella across all models tested.
• Sutterella enrichment was observed in food-insecure children specifically.

A microbial feature-based machine learning model accurately predicted food security status, with Sutterella as the top predictive feature.

• The machine learning model achieved an AUC of 0.81.
• Sutterella emerged as the top predictive feature in the model.
• The model was trained on microbial composition data from 57 Ethiopian schoolchildren.
• This finding suggests that gut microbial composition encodes information about a child's food security status.

The study investigated household food insecurity (HFI) as both a composite variable and through individual HFIAS questions as specific proxies for dietary deprivation.

• The Household Food Insecurity Access Scale (HFIAS) was used to assess food insecurity.
• HFI was analyzed both as a composite variable and broken down into individual component questions.
• Individual questions examined included limited dietary variety, consumption of disliked foods, and reduced meal size.
• The study design aimed to capture different dimensions of dietary deprivation separately.