Gene expression profiling in blood from cerebral malaria patients and mild malaria patients living in Senegal

• Main Authors: Alassane Thiam (Author), Michel Sanka (Author), Rokhaya Ndiaye Diallo (Author), Magali Torres (Author), Babacar Mbengue (Author), Nicolas Fernandez Nunez (Author), Fatou Thiam (Author), Gora Diop (Author), Geneviève Victorero (Author), Catherine Nguyen (Author), Alioune Dieye (Author), Pascal Rihet (Author)
• Format: Book
• Published: BMC, 2019-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 10.1186/s12920-019-0599-z; 1755-8794
• Keywords: Transcriptome; Gene expression profiling; Cerebral malaria; Mild malaria; Internal medicine; RC31-1245; Genetics; QH426-470
• Source: BMC Medical Genomics, Vol 12, Iss 1, Pp 1-15 (2019)

Abstract Background Plasmodium falciparum malaria remains a major health problem in Africa. The mechanisms of pathogenesis are not fully understood. Transcriptomic studies may provide new insights into molecular pathways involved in the severe form of the disease. Methods Blood transcriptional levels were assessed in patients with cerebral malaria, non-cerebral malaria, or mild malaria by using microarray technology to look for gene expression profiles associated with clinical status. Multi-way ANOVA was used to extract differentially expressed genes. Network and pathways analyses were used to detect enrichment for biological pathways. Results We identified a set of 443 genes that were differentially expressed in the three patient groups after applying a false discovery rate of 10%. Since the cerebral patients displayed a particular transcriptional pattern, we focused our analysis on the differences between cerebral malaria patients and mild malaria patients. We further found 842 differentially expressed genes after applying a false discovery rate of 10%. Unsupervised hierarchical clustering of cerebral malaria-informative genes led to clustering of the cerebral malaria patients. The support vector machine method allowed us to correctly classify five out of six cerebral malaria patients and six of six mild malaria patients. Furthermore, the products of the differentially expressed genes were mapped onto a human protein-protein network. This led to the identification of the proteins with the highest number of interactions, including GSK3B, RELA, and APP. The enrichment analysis of the gene functional annotation indicates that genes involved in immune signalling pathways play a role in the occurrence of cerebral malaria. These include BCR-, TCR-, TLR-, cytokine-, FcεRI-, and FCGR- signalling pathways and natural killer cell cytotoxicity pathways, which are involved in the activation of immune cells. In addition, our results revealed an enrichment of genes involved in Alzheimer's disease. Conclusions In the present study, we examine a set of genes whose expression differed in cerebral malaria patients and mild malaria patients. Moreover, our results provide new insights into the potential effect of the dysregulation of gene expression in immune pathways. Host genetic variation may partly explain such alteration of gene expression. Further studies are required to investigate this in African populations.