The primary objective of the project is to generate a systems-level view of human milk in the context of healthy mothers and their term infants. The study uses biospecimens and clinical data from the <a href="https://milkresearch.umn.edu/mothers-and-infants-linked-healthy-growth-milk-study">Mothers and Infants LinKed for Healthy Growth Study (MILk Study)</a>, a prospective observational cohort of approximately 500 exclusively breastfeeding women and their infants who are followed to 6 months of age. The project focuses on mature milk samples collected at 1 month postpartum and infant gut microbiome samples collected at 1 and 6 months of age. Specific Aim 1 is to identify maternal genetic and clinical factors that shape human milk gene expression. Using bulk and single-cell RNA sequencing of the milk cell pellet and genotypes from maternal DNA, we will identify novel genetic determinants of the milk transcriptome and assess potential modification of these genetic associations by gestational weight gain, diet, and other clinical factors. Specific Aim 2 is to describe key features of the normative human milk biosystem and their interactions with one another. Specifically, machine learning techniques will be used to characterize interaction networks and correlational structures among the following features of human milk: transcriptomics, microbiomes, oligosaccharides, metabolomics, lipidomics, and milk macronutrient composition. Specific Aim 3 is to establish how the milk biosystem is related to variation in infant gut microbiomes and health. dbGaP will house the maternal genotype and milk transcriptomics data.The infant microbiome sequence data are associated with BioProject <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1019702">PRJNA1019702</a>.

MILK-Omics: Systems Biology of Human Milk and Its Links to Maternal and Infant Health

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