bioRxivBioinformaticsPreprint
Transcriptional Profiles Analysis of COVID-19 and Malaria Patients Reveals Potential Biomarkers in Children
Nzungize LambertiD, Jonas Arnaud Kengne-OuafoiD, Rissy M. Wesonga, Umuhoza Diane, Ken Murithi, Peter Kimani, Olaitan Igbagbo AweiD, Allissa DillmaniD
Abstract
The clinical presentation overlap between malaria and COVID-19 poses special challenges for rapid diagnosis in febrile children. In this study, we collected RNA-seq data of children with malaria and COVID-19 infection from the public databases as raw data in fastq format paired end files. A group of six, five and two biological replicates of malaria, COVID-19 and healthy donors respectively were used for the study. We conducted differential gene expression analysis to visualize differences in the expression profiles. Using edgeR, we explored particularly gene expression levels in different phenotype groups and found that 1084 genes and 2495 genes were differentially expressed in the malaria samples and COVID-19 samples respectively when compared to healthy controls. The highly expressed gene in the COVID-19 group we found CD151 gene which is facilitates in T cell proliferation, while in the malaria group, among the highly expressed gene we identified GBP5 gene which involved in inflammatory response and response to bacterium. By comparing both malaria and COVID-19 infections, the overlap of 62 differentially expressed genes patterns were identified. Among them, three genes (ENSG00000234998, H2AC19 and TXNDC5) were highly upregulated in both infections. Strikingly, we observed 13 genes such as HBQ1, HBM, SLC7A5, SERINC2, ATP6V0C, ST6GALNAC4, RAD23A, PNPLA2, GAS2L1, TMEM86B, SLC6A8, UBALD1, RNF187 were downregulated in children with malaria and uniquely upregulated in children with COVID-19, thus may be further validated as potential biomarkers to delineate COVID-19 from malaria-related febrile infection. The hemoglobin complexes and lipid metabolism biological pathways are highly expressed in both infections. Our study provided new insights for further investigation of the biological pattern in hosts with malaria and COVID-19 coinfection.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- approach: statistical model
- Citations
- 17
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