A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection
Tekijät: Slim Fourati, Aarthi Talla, Mehrad Mahmoudian, Joshua G. Burkhart, Riku Klén, Ricardo Henao, Thomas Yu, Zafer Aydın, Ka Yee Yeung, Mehmet Eren Ahsen, Reem Almugbel, Samad Jahandideh, Xiao Liang, Torbjörn E.M. Nordling, Motoki Shiga, Ana Stanescu, Robert Vogel, The Respiratory Viral DREAM Challenge Consortium, Gaurav Pandey, Christopher Chiu, Micah T. McClain, Christopher W. Woods, Geoffrey S. Ginsburg, Laura L. Elo, Ephraim L. Tsalik, Lara M. Mangravite, Solveig K. Sieberts
Kustantaja: NATURE PUBLISHING GROUP
Julkaisuvuosi: 2018
Journal: Nature Communications
Tietokannassa oleva lehden nimi: NATURE COMMUNICATIONS
Lehden akronyymi: NAT COMMUN
Artikkelin numero: ARTN 4418
Vuosikerta: 9
Aloitussivu: 1
Lopetussivu: 11
Sivujen määrä: 11
ISSN: 2041-1723
DOI: https://doi.org/10.1038/s41467-018-06735-8
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/36583381
The response to respiratory viruses varies substantially between individuals, and there are currently no known molecular predictors from the early stages of infection. Here we conduct a community-based analysis to determine whether pre- or early post-exposure molecular factors could predict physiologic responses to viral exposure. Using peripheral blood gene expression profiles collected from healthy subjects prior to exposure to one of four respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV), as well as up to 24 h following exposure, we find that it is possible to construct models predictive of symptomatic response using profiles even prior to viral exposure. Analysis of predictive gene features reveal little overlap among models; however, in aggregate, these genes are enriched for common pathways. Heme metabolism, the most significantly enriched pathway, is associated with a higher risk of developing symptoms following viral exposure. This study demonstrates that pre-exposure molecular predictors can be identified and improves our understanding of the mechanisms of response to respiratory viruses.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
