Mohammad Ali Moni1, Pietro Lio'2. 1. Garvan Institute of Medical Research, University of New South Wales, Sydney,Australia. 2. Computer Laboratory, University of Cambridge,United Kingdom.
Abstract
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.
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.
Authors: Utpala Nanda Chowdhury; Shamim Ahmad; M Babul Islam; Salem A Alyami; Julian M W Quinn; Valsamma Eapen; Mohammad Ali Moni Journal: PLoS One Date: 2021-05-06 Impact factor: 3.240
Authors: M Babul Islam; Utpala Nanda Chowdhury; Zulkar Nain; Shahadat Uddin; Mohammad Boshir Ahmed; Mohammad Ali Moni Journal: Comput Biol Med Date: 2021-07-23 Impact factor: 4.589
Authors: Md Habibur Rahman; Silong Peng; Xiyuan Hu; Chen Chen; Md Rezanur Rahman; Shahadat Uddin; Julian M W Quinn; Mohammad Ali Moni Journal: Int J Environ Res Public Health Date: 2020-02-06 Impact factor: 3.390
Authors: Md Nasim Haidar; M Babul Islam; Utpala Nanda Chowdhury; Md Rezanur Rahman; Fazlul Huq; Julian M W Quinn; Mohammad Ali Moni Journal: IET Syst Biol Date: 2020-04 Impact factor: 1.615