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Dynamic molecular changes during the first week of human life follow a robust developmental trajectory
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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6414553/ https://www.ncbi.nlm.nih.gov/pubmed/30862783 http://dx.doi.org/10.1038/s41467-019-08794-x |
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author | Lee, Amy H. Shannon, Casey P. Amenyogbe, Nelly Bennike, Tue B. Diray-Arce, Joann Idoko, Olubukola T. Gill, Erin E. Ben-Othman, Rym Pomat, William S. van Haren, Simon D. Cao, Kim-Anh Lê Cox, Momoudou Darboe, Alansana Falsafi, Reza Ferrari, Davide Harbeson, Daniel J. He, Daniel Bing, Cai Hinshaw, Samuel J. Ndure, Jorjoh Njie-Jobe, Jainaba Pettengill, Matthew A. Richmond, Peter C. Ford, Rebecca Saleu, Gerard Masiria, Geraldine Matlam, John Paul Kirarock, Wendy Roberts, Elishia Malek, Mehrnoush Sanchez-Schmitz, Guzmán Singh, Amrit Angelidou, Asimenia Smolen, Kinga K. Brinkman, Ryan R. Ozonoff, Al Hancock, Robert E. W. van den Biggelaar, Anita H. J. Steen, Hanno Tebbutt, Scott J. Kampmann, Beate Levy, Ofer Kollmann, Tobias R. |
author_facet | Lee, Amy H. Shannon, Casey P. Amenyogbe, Nelly Bennike, Tue B. Diray-Arce, Joann Idoko, Olubukola T. Gill, Erin E. Ben-Othman, Rym Pomat, William S. van Haren, Simon D. Cao, Kim-Anh Lê Cox, Momoudou Darboe, Alansana Falsafi, Reza Ferrari, Davide Harbeson, Daniel J. He, Daniel Bing, Cai Hinshaw, Samuel J. Ndure, Jorjoh Njie-Jobe, Jainaba Pettengill, Matthew A. Richmond, Peter C. Ford, Rebecca Saleu, Gerard Masiria, Geraldine Matlam, John Paul Kirarock, Wendy Roberts, Elishia Malek, Mehrnoush Sanchez-Schmitz, Guzmán Singh, Amrit Angelidou, Asimenia Smolen, Kinga K. Brinkman, Ryan R. Ozonoff, Al Hancock, Robert E. W. van den Biggelaar, Anita H. J. Steen, Hanno Tebbutt, Scott J. Kampmann, Beate Levy, Ofer Kollmann, Tobias R. |
author_sort | Lee, Amy H. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6414553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-64145532019-03-14 Dynamic molecular changes during the first week of human life follow a robust developmental trajectory Lee, Amy H. Shannon, Casey P. Amenyogbe, Nelly Bennike, Tue B. Diray-Arce, Joann Idoko, Olubukola T. Gill, Erin E. Ben-Othman, Rym Pomat, William S. van Haren, Simon D. Cao, Kim-Anh Lê Cox, Momoudou Darboe, Alansana Falsafi, Reza Ferrari, Davide Harbeson, Daniel J. He, Daniel Bing, Cai Hinshaw, Samuel J. Ndure, Jorjoh Njie-Jobe, Jainaba Pettengill, Matthew A. Richmond, Peter C. Ford, Rebecca Saleu, Gerard Masiria, Geraldine Matlam, John Paul Kirarock, Wendy Roberts, Elishia Malek, Mehrnoush Sanchez-Schmitz, Guzmán Singh, Amrit Angelidou, Asimenia Smolen, Kinga K. Brinkman, Ryan R. Ozonoff, Al Hancock, Robert E. W. van den Biggelaar, Anita H. J. Steen, Hanno Tebbutt, Scott J. Kampmann, Beate Levy, Ofer Kollmann, Tobias R. Nat Commun Article 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. Nature Publishing Group UK 2019-03-12 /pmc/articles/PMC6414553/ /pubmed/30862783 http://dx.doi.org/10.1038/s41467-019-08794-x Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lee, Amy H. Shannon, Casey P. Amenyogbe, Nelly Bennike, Tue B. Diray-Arce, Joann Idoko, Olubukola T. Gill, Erin E. Ben-Othman, Rym Pomat, William S. van Haren, Simon D. Cao, Kim-Anh Lê Cox, Momoudou Darboe, Alansana Falsafi, Reza Ferrari, Davide Harbeson, Daniel J. He, Daniel Bing, Cai Hinshaw, Samuel J. Ndure, Jorjoh Njie-Jobe, Jainaba Pettengill, Matthew A. Richmond, Peter C. Ford, Rebecca Saleu, Gerard Masiria, Geraldine Matlam, John Paul Kirarock, Wendy Roberts, Elishia Malek, Mehrnoush Sanchez-Schmitz, Guzmán Singh, Amrit Angelidou, Asimenia Smolen, Kinga K. Brinkman, Ryan R. Ozonoff, Al Hancock, Robert E. W. van den Biggelaar, Anita H. J. Steen, Hanno Tebbutt, Scott J. Kampmann, Beate Levy, Ofer Kollmann, Tobias R. Dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
title | Dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
title_full | Dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
title_fullStr | Dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
title_full_unstemmed | Dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
title_short | Dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
title_sort | dynamic molecular changes during the first week of human life follow a robust developmental trajectory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6414553/ https://www.ncbi.nlm.nih.gov/pubmed/30862783 http://dx.doi.org/10.1038/s41467-019-08794-x |
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