bioRxivDevelopmental BiologyPreprint
Development of the Early Childhood Duodenum across Ancestry, Geography and Environment
Joshua de Sousa CasaliD, Krishnan RaghunathaniD, Chelsea Asare, Abigail Plone, Nazanin MoradinasabiD, Junaid IqbaliD, Lianna WoodiD, Elsy M. NgwaiD, Xia Chen, S. Fisher Rhoads, Clara BaekiD, Dur-e Shahwar, Neha S. Dhaliwal, Madison Wong, Max Garrity-Janger, Lily GilletteiD, Stephanie Regis, Fatima Zulqarnain, Asra Usmani, Jason D. Boisvert, Casey R. Johnson, Jackson Larlee, Michael D. Anderson, Daniel ZeveiD, Elisa Saint-Denis, , Jay R. ThiagarajahiD
Abstract
During early childhood, the proximal small intestinal mucosa plays a central role in growth, metabolism, immune priming, and neuronal development. Yet the cellular architecture and environmental responsiveness of the human small intestinal mucosa during this period remain poorly defined. Here, we generate a comprehensive cellular and spatial map of the duodenum from 87 children aged 6 months to 13 years, representing diverse ancestries and geographic contexts. This atlas integrates single-cell transcriptomic and spatial profiling with data on diet, social drivers of health, and environmental exposures. Using these data, we define mucosal cellular composition and chart its developmental trajectory in early childhood. Comparative analyses of children residing in the United States (US) and Pakistan reveal a differentiated enterocyte subset expressing the aquaglyceroporin, AQP10 (AQP10+ enterocyte), that is enriched in children from the US. We show that emergence of this enterocyte state depends on lipid exposure to intestinal stem cells and correlates with dietary fat intake. We also identify a previously-undescribed thyrotropin-releasing hormone (TRH+) enteroendocrine cell and provide evidence for a local endocrine-epithelial-lymphocyte circuit. Our work establishes a detailed framework for pediatric duodenal mucosal development and illuminates how intestinal cellular dynamics are shaped by age and environment.
- organism: human
- assay: scRNA-seq
- assay: spatial transcriptomics
- research focus: cell type annotation
- research focus: trajectory inference
- approach: statistical model
- Citations
- 1
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