A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

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, Emna Ben Abdallah, Farnoosh Abbas Aghababazadeh, Alicia AmadozSherry Bhalla, Kevin Bleakley, Erika Bongen, Domenico Borzacchielo, Philipp Bucher, Jose Carbonell-Caballero, Kumardeep Chaudhary, Francisco Chinesta, Prasad Chodavarapu, Ryan D. Chow, Thomas Cokelaer, Cankut Cubuk, Sandeep Kumar Dhanda, Joaquin Dopazo, Thomas Faux, Yang Feng, Christofer Flinta, Carito Guziolowski, Di He, Marta R. Hidalgo, Jiayi Hou, Katsumi Inoue, Maria K. Jaakkola, Jiadong Ji, Ritesh Kumar, Sunil Kumar, Miron Bartosz Kursa, Qian Li, Michał Łopuszyński, Pengcheng Lu, Morgan Magnin, Weiguang Mao, Bertrand Miannay, Iryna Nikolayeva, Zoran Obradovic, Chi Pak, Mohammad M. Rahman, Misbah Razzaq, Tony Ribeiro, Olivier Roux, Ehsan Saghapour, Harsh Saini, Shamim Sarhadi, Hiroki Sato, Benno Schwikowski, Alok Sharma, Ronesh Sharma, Deepak Singla, Ivan Stojkovic, Tomi Suomi, Maria Suprun, Chengzhe Tian, Lewis E. Tomalin, Lei Xie, Xiang Yu, 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

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.
Original languageEnglish (US)
JournalNature Communications
Volume9
Issue number1
DOIs
StatePublished - Dec 1 2018
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Chemistry(all)
  • Physics and Astronomy(all)

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