Arbovirus epidemiology in pregnant women in Pernambuco state, Brazil

Abstract

The mosquito-borne Zika flavivirus (ZIKV) causes a mild or asymptomatic dengue-like disease that usually lasts two to seven days. Symptoms may include fever, headache and rash that are often either unrecognized or misdiagnosed as dengue, West Nile fever (WNF), chikungunya or other viral infections. ZIKV infection may also be associated with a risk for development of neurologic complications including Guillain-Barré syndrome (GBS). Zika infection is often associated to infectome, diseasome and comorbidity.Methods & Materials: We present a quantitative framework to compare and explore infectome, diseasome and comorbidity of Zika infection. We have analysed several gene expression microarray data from Zika, WNF, chikungunya, dengue, other flaviviruses and GBS, with respect to healthy and control data sets.Results: The differential gene expression profiling of ZIKV infection shows that a large number of genes (1197 genes) are statistically dysregulated. We also observed that 47 genes are commonly highly expressed between ZIKV and dengue infections. However, ZIKV shares only 12, 15 and 10 significant genes with chikungunya, WNF and GBS respectively. Notably, one significant gene SELENBP1 is commonly dysregulated among ZIKV, Dengue and GBS, 2 significant genes AF5 and BAMB1 are commonly dysregulated among ZIKV, Dengue and WNF and 2 significant genes NAMPT and PMAlP1 are commonly dysregulated among ZIKV, GBS and WNF. By using neighbourhood based benchmark and multi layer network topology methods, we have built infectome, diseasome and comorbidity relationships network based on the OMIM and our identified significant genes. Then based on the gene expression, PPI and signalling pathways data, we investigate the infectome, diseasome and comorbidity association among the Zika, chikungunya, WNS, dengue infections and GBS.Conclusion: Here, we describe the infectome and diseasome of ZIKV with dengue, chikungunya, WNS and GBS. We believe that our results will be important for comprehensive modelling and analysis of the systems level properties associated to Zika virus infections, molecular association analysis of these five symtomatic and pathological similar infections and disorders and for translational medicine aims. Our methods and pipeline will be useful for advancing our current knowledge on disease mechanism and predicting infectome, diseasome and disease comorbidities in a quantitative way.