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Uncovering the Dynamics of Immune Cell Populations in the First Week of Life: The Interplay of Neutrophils and Breastfeeding

GSE275823 Homo sapiens Expression profiling by high throughput sequencing 178 samples 2024/10/01 GPL16791
Summary
The first few days of life are characterized by rapid external and internal changes that require rapid host adaptations. Despite growing evidence of the impact of this period on an individual’s lifelong health trajectory, this period remains largely uncharted. To decipher key factors associated with changes in peripheral blood cell composition we conducted a stringently standardized, high-throughput immune phenotyping investigation on 796 newborns across diverse settings (The Gambia, West Africa and Papua New Guinea, Australasia) in the framework of a Human Immunology Project Consortium study. Samples were collected twice from each newborn during the first week of life and analyzed via high throughput flow cytometry with an unbiased automated gating algorithm to capture cell compositional changes at an unprecedented level of detail. We found that immune cell composition in peripheral blood changes along patterns highly conserved across populations and environments. Changes with age/day of life were most pronounced in the innate myeloid compartment. While there was minimal impact of sex, season of birth, mother’s age or origin (i.e., environmental and genetic background), breastfeeding and vaccination were strongly associated with increase in cell counts of peripheral blood neutrophils and monocytes. Our results may suggest a possible association of initiation of breastfeeding with changes in immune ontogeny, and thus possibly host immune-mediated protection from infection. These data begin to outline a specific window of opportunity for interventions that can deliberately direct immune ontogeny.
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NCBI GEO page ↗ Paper (PMID 42225675) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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