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

Fourati, Slim and Talla, Aarthi and Mahmoudian, Mehrad and Burkhart, Joshua G. and Klén, Riku and Henao, Ricardo and Yu, Thomas and Aydın, Zafer and Yeung, Ka Y. and Ahsen, Mehmet E. and Almugbel, Reem and Jahandideh, Samad and Liang, Xiao and Nordling, Torbjörn E.M. and Shiga, Motoki and Stanescu, Ana and Vogel, Robert and Pandey, Gaurav and Chiu, Christopher and McClain, Micah T. and Woods, Christopher W. and Ginsburg, Geoffrey S. and Elo, Laura L. and Tsalik, Ephraim L. and Mangravite, Lara M. and Sieberts, Solveig K. and Abdallah, Emna B. and Aghababazadeh, Farnoosh A. and Amadoz, Alicia and Bhalla, Sherry and Bleakley, Kevin and Bongen, Erika and Borzacchielo, Domenico and Bucher, Philipp and Carbonell-Caballero, Jose and Chaudhary, Kumardeep and Chinesta, Francisco and Chodavarapu, Prasad and Chow, Ryan D. and Cokelaer, Thomas and Cubuk, Cankut and Dhanda, Sandeep K. and Dopazo, Joaquin and Faux, Thomas and Feng, Yang and Flinta, Christofer and Guziolowski, Carito and He, Di and Hidalgo, Marta R. and Hou, Jiayi and Inoue, Katsumi and Jaakkola, Maria K. and Ji, Jiadong and Kumar, Ritesh and Kumar, Sunil and Kursa, Miron B. and Li, Qian and Lu, Pengcheng and Magnin, Morgan and Mao, Weiguang and Miannay, Bertrand and Nikolayeva, Iryna and Obradovic, Zoran and Pak, Chi and Rahman, Mohammad M. and Razzaq, Misbah and Ribeiro, Tony and Roux, Olivier and Saghapour, Ehsan and Saini, Harsh and Sarhadi, Shamim and Sato, Hiroki and Schwikowski, Benno and Sharma, Alokanand and Sharma, Ronesh and Singla, Deepak and Stojkovic, Ivan and Suomi, Tomi and Suprun, Maria and Tian, Chengzhe and Tomalin, Lewis E. and Xie, Lei and Yu, Xiang and Łopuszyński, Michał (2018) A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection. Nature Communications, 9 (1). NA. ISSN NA

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    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.

    Item Type: Journal Article
    Subjects: Q Science > Q Science (General)
    Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Engineering and Physics
    Depositing User: Ms Shalni Sanjana
    Date Deposited: 15 Feb 2019 15:11
    Last Modified: 15 Feb 2019 15:11
    URI: http://repository.usp.ac.fj/id/eprint/11336
    UNSPECIFIED

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