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

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cris.lastimport.scopus2024-02-12T19:59:39Z
dc.abstract.enThe 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. © 2018, The Author(s).
dc.affiliationUniwersytet Warszawski
dc.contributor.authorKursa, Miron
dc.contributor.authorStanescu, A.
dc.contributor.authorShiga, M.
dc.contributor.authorAbdallah, E.B.
dc.contributor.authorVogel, R.
dc.contributor.authorAmadoz, A.
dc.contributor.authorAghababazadeh, F.A.
dc.contributor.authorPandey, G.
dc.contributor.authorHenao, R.
dc.contributor.authorYu, X.
dc.contributor.authorSieberts, S.K.
dc.contributor.authorMcClain, M.T.
dc.contributor.authorAydın, Z.
dc.contributor.authorChiu, C.
dc.contributor.authorYu, T.
dc.contributor.authorTian, C.
dc.contributor.authorSuprun, M.
dc.contributor.authorXie, L.
dc.contributor.authorTomalin, L.E.
dc.contributor.authorNordling, T.E.M.
dc.contributor.authorLiang, X.
dc.contributor.authorAhsen, M.E.
dc.contributor.authorYeung, K.Y.
dc.contributor.authorJahandideh, S.
dc.contributor.authorAlmugbel, R.
dc.contributor.authorSharma, R.
dc.contributor.authorSharma, A.
dc.contributor.authorStojkovic, I.
dc.contributor.authorKlén, R.
dc.contributor.authorSingla, D.
dc.contributor.authorSchwikowski, B.
dc.contributor.authorMangravite, L.M.
dc.contributor.authorGinsburg, G.S.
dc.contributor.authorSuomi, T.
dc.contributor.authorWoods, C.W.
dc.contributor.authorTsalik, E.L.
dc.contributor.authorElo, L.L.
dc.contributor.authorRibeiro, T.
dc.contributor.authorRazzaq, M.
dc.contributor.authorSaghapour, E.
dc.contributor.authorRoux, O.
dc.contributor.authorObradovic, Z.
dc.contributor.authorRahman, M.M.
dc.contributor.authorPak, C.
dc.contributor.authorSarhadi, S.
dc.contributor.authorSaini, H.
dc.contributor.authorSato, H.
dc.contributor.authorLu, P.
dc.contributor.authorBurkhart, J.G.
dc.contributor.authorLi, Q.
dc.contributor.authorMahmoudian, M.
dc.contributor.authorMao, W.
dc.contributor.authorMagnin, M.
dc.contributor.authorTalla, A.
dc.contributor.authorFourati, S.
dc.contributor.authorNikolayeva, I.
dc.contributor.authorMiannay, B.
dc.contributor.authorHidalgo, M.R.
dc.contributor.authorHe, D.
dc.contributor.authorInoue, K.
dc.contributor.authorHou, J.
dc.contributor.authorGuziolowski, C.
dc.contributor.authorFlinta, C.
dc.contributor.authorŁopuszyński, Michał
dc.contributor.authorJi, J.
dc.contributor.authorJaakkola, M.K.
dc.contributor.authorKumar, S.
dc.contributor.authorKumar, R.
dc.contributor.authorCokelaer, T.
dc.contributor.authorDhanda, S.K.
dc.contributor.authorCubuk, C.
dc.contributor.authorFaux, T.
dc.contributor.authorDopazo, J.
dc.contributor.authorFeng, Y.
dc.contributor.authorBongen, E.
dc.contributor.authorBleakley, K.
dc.contributor.authorBucher, P.
dc.contributor.authorBorzacchielo, D.
dc.contributor.authorBhalla, S.
dc.contributor.authorChow, R.D.
dc.contributor.authorChaudhary, K.
dc.contributor.authorCarbonell-Caballero, J.
dc.contributor.authorChodavarapu, P.
dc.contributor.authorChinesta, F.
dc.date.accessioned2024-01-24T17:29:41Z
dc.date.available2024-01-24T17:29:41Z
dc.date.copyright2018-10-24
dc.date.issued2018
dc.description.accesstimeAT_PUBLICATION
dc.description.financeNie dotyczy
dc.description.versionFINAL_PUBLISHED
dc.description.volume9
dc.identifier.doi10.1038/S41467-018-06735-8
dc.identifier.issn2041-1723
dc.identifier.urihttps://repozytorium.uw.edu.pl//handle/item/101501
dc.identifier.weblinkhttps://www.nature.com/articles/s41467-018-06735-8
dc.languageeng
dc.pbn.affiliationcomputer and information sciences
dc.relation.ispartofNature Communications
dc.relation.pages4418
dc.rightsCC-BY
dc.sciencecloudnosend
dc.subject.enheme gene expression infectivity metabolism molecular analysis respiratory disease viral disease virus ab initio calculation adult Article controlled study crowdsourcing female gene expression human human experiment Human respiratory syncytial virus infection sensitivity Influenza A virus (H1N1) Influenza A virus (H3N2) male molecular dynamics molecular signature nonhuman normal human prediction Rhinovirus virus infection Rhinovirus Rice stripe virus
dc.titleA crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection
dc.typeJournalArticle
dspace.entity.typePublication