TY - JOUR
T1 - A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection
AU - The Respiratory Viral DREAM Challenge Consortium
AU - Fourati, Slim
AU - Talla, Aarthi
AU - Mahmoudian, Mehrad
AU - Burkhart, Joshua G.
AU - Klén, Riku
AU - Henao, Ricardo
AU - Yu, Thomas
AU - Aydın, Zafer
AU - Yeung, Ka Yee
AU - Ahsen, Mehmet Eren
AU - Almugbel, Reem
AU - Jahandideh, Samad
AU - Liang, Xiao
AU - Nordling, Torbjörn E.M.
AU - Shiga, Motoki
AU - Stanescu, Ana
AU - Vogel, Robert
AU - Abdallah, Emna Ben
AU - Aghababazadeh, Farnoosh Abbas
AU - Amadoz, Alicia
AU - Bhalla, Sherry
AU - Bleakley, Kevin
AU - Bongen, Erika
AU - Borzacchielo, Domenico
AU - Bucher, Philipp
AU - Carbonell-Caballero, Jose
AU - Chaudhary, Kumardeep
AU - Chinesta, Francisco
AU - Chodavarapu, Prasad
AU - Chow, Ryan D.
AU - Cokelaer, Thomas
AU - Cubuk, Cankut
AU - Dhanda, Sandeep Kumar
AU - Dopazo, Joaquin
AU - Faux, Thomas
AU - Feng, Yang
AU - Flinta, Christofer
AU - Guziolowski, Carito
AU - He, Di
AU - Hidalgo, Marta R.
AU - Hou, Jiayi
AU - Inoue, Katsumi
AU - Jaakkola, Maria K.
AU - Ji, Jiadong
AU - Kumar, Ritesh
AU - Kumar, Sunil
AU - Kursa, Miron Bartosz
AU - Li, Qian
AU - Łopuszyński, Michał
AU - Lu, Pengcheng
N1 - Publisher Copyright:
© 2018, The Author(s).
PY - 2018/12/1
Y1 - 2018/12/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85055459624&partnerID=8YFLogxK
U2 - 10.1038/s41467-018-06735-8
DO - 10.1038/s41467-018-06735-8
M3 - Article
C2 - 30356117
AN - SCOPUS:85055459624
SN - 2041-1723
VL - 9
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 4418
ER -