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Computational Interrogation of Early Signatures of Environmental Enteropathy

Sana Syed of the University of Virginia in the U.S. together with Imran Nisar of Aga Khan University in Pakistan will utilize metabolic modeling of patient-derived ‘omics data from pre-existing maternal and pediatric cohorts to identify new biomarkers and therapeutic targets for environmental enteropathy (EE), which is associated with impaired childhood growth and development and vaccine responses. They will leverage a computational, flux-balance analysis-based approach to analyze large transcriptomic and proteomic datasets from pregnant mothers and infants with EE to identify disease-associated metabolic signatures. The signatures derived from pregnant mothers might precede the development of EE and reveal pharmaceutical targets for prevention. They will also develop a duodenal enteroid cell culture model derived from biopsies of children with EE to test whether the identified infant-derived metabolic signatures can be disrupted with existing pharmacological agents as potential new treatments.

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