The Journal of infectious diseases · 2017
Genetic Profiling and Comorbidities of Zika Infection.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Moni Mohammad Ali, Lio' Pietro
Аннотация
BACKGROUND: The difficulty in distinguishing infection by Zika virus (ZIKV) from other flaviviruses is a global health concern, particularly given the high risk of neurologic complications (including Guillain-Barré syndrome [GBS]) with ZIKV infection.
METHODS: We developed quantitative frameworks to compare and explore infectome, diseasome, and comorbidity of ZIKV infections. We analyzed gene expression microarray and RNA-Seq data from ZIKV, West Nile fever (WNF), chikungunya, dengue, yellow fever, Japanese encephalitis virus, GBS, and control datasets. Using neighborhood-based benchmarking and multilayer network topology, we constructed relationship networks based on the Online Mendelian Inheritance in Man database and our identified significant genes.
RESULTS: ZIKV infections showed dysregulation in expression of 929 genes. Forty-seven genes were highly expressed in both ZIKV and dengue infections. However, ZIKV shared <15 significant transcripts with other flavivirus infections. Notably, dysregulation of MAFB and SELENBP1 was common to ZIKV, dengue, and GBS infection; ATF5, TNFAIP3, and BAMB1 were common to ZIKV, dengue, and WNF; and NAMPT and PMAlP1 were common to ZIKV, GBS, and WNF. Phylogenetic, ontologic, and pathway analyses showed that ZIKV infection most resembles dengue fever.
CONCLUSIONS: We have developed methodologies to investigate disease mechanisms and predictions for infectome, diseasome, and comorbidities quantitatively, and identified particular similarities between ZIKV and dengue infections.
METHODS: We developed quantitative frameworks to compare and explore infectome, diseasome, and comorbidity of ZIKV infections. We analyzed gene expression microarray and RNA-Seq data from ZIKV, West Nile fever (WNF), chikungunya, dengue, yellow fever, Japanese encephalitis virus, GBS, and control datasets. Using neighborhood-based benchmarking and multilayer network topology, we constructed relationship networks based on the Online Mendelian Inheritance in Man database and our identified significant genes.
RESULTS: ZIKV infections showed dysregulation in expression of 929 genes. Forty-seven genes were highly expressed in both ZIKV and dengue infections. However, ZIKV shared <15 significant transcripts with other flavivirus infections. Notably, dysregulation of MAFB and SELENBP1 was common to ZIKV, dengue, and GBS infection; ATF5, TNFAIP3, and BAMB1 were common to ZIKV, dengue, and WNF; and NAMPT and PMAlP1 were common to ZIKV, GBS, and WNF. Phylogenetic, ontologic, and pathway analyses showed that ZIKV infection most resembles dengue fever.
CONCLUSIONS: We have developed methodologies to investigate disease mechanisms and predictions for infectome, diseasome, and comorbidities quantitatively, and identified particular similarities between ZIKV and dengue infections.