Dynamic molecular changes during the first week of human life follow a robust developmental trajectory View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2019-12

AUTHORS

Amy H. Lee, Casey P. Shannon, Nelly Amenyogbe, Tue B. Bennike, Joann Diray-Arce, Olubukola T. Idoko, Erin E. Gill, Rym Ben-Othman, William S. Pomat, Simon D. van Haren, Kim-Anh Lê Cao, Momoudou Cox, Alansana Darboe, Reza Falsafi, Davide Ferrari, Daniel J. Harbeson, Daniel He, Cai Bing, Samuel J. Hinshaw, Jorjoh Ndure, Jainaba Njie-Jobe, Matthew A. Pettengill, Peter C. Richmond, Rebecca Ford, Gerard Saleu, Geraldine Masiria, John Paul Matlam, Wendy Kirarock, Elishia Roberts, Mehrnoush Malek, Guzmán Sanchez-Schmitz, Amrit Singh, Asimenia Angelidou, Kinga K. Smolen, , Ryan R. Brinkman, Al Ozonoff, Robert E. W. Hancock, Anita H. J. van den Biggelaar, Hanno Steen, Scott J. Tebbutt, Beate Kampmann, Ofer Levy, Tobias R. Kollmann

ABSTRACT

Systems biology can unravel complex biology but has not been extensively applied to human newborns, a group highly vulnerable to a wide range of diseases. We optimized methods to extract transcriptomic, proteomic, metabolomic, cytokine/chemokine, and single cell immune phenotyping data from <1 ml of blood, a volume readily obtained from newborns. Indexing to baseline and applying innovative integrative computational methods reveals dramatic changes along a remarkably stable developmental trajectory over the first week of life. This is most evident in changes of interferon and complement pathways, as well as neutrophil-associated signaling. Validated across two independent cohorts of newborns from West Africa and Australasia, a robust and common trajectory emerges, suggesting a purposeful rather than random developmental path. Systems biology and innovative data integration can provide fresh insights into the molecular ontogeny of the first week of life, a dynamic developmental phase that is key for health and disease. More... »

PAGES

1092

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41467-019-08794-x

    DOI

    http://dx.doi.org/10.1038/s41467-019-08794-x

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1112706410

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/30862783


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