Genetic Profiling and Comorbidities of Zika Infection

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.

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.

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.

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.