Gene expression changes in mammalian hosts during schistosomiasis: a review

Abstract

Schistosomiasis affects over 250 million people worldwide with an estimated mortality of more than 200,000 deaths per year in sub-Saharan Africa. Efforts to control schistosomiasis in the affected areas have mainly relied on mass administration of praziquantel, which kills adult but not immature worms of all Schistosoma species. Mammalian hosts respond differently to Schistosoma infection with some being more susceptible than others, which is associated with risk factors such as sociodemographic, epidemiological, immunological and/or genetic. Host genetic factors play a major role in influencing molecular processes in response to schistosomiasis as shown in gene expression studies. These studies highlight gene profiles expressed at different time points of infection using model animals. Immune function related genes; cytokines (Th1 and Th17) are upregulated earlier in infection and Th2 upregulated later indicating a mixed Th1/Th2 response. However, Th1 response has been shown to be sustained in S. japonicum infection. Immune mediators such as matrix metalloproteinases (Mmps) and tissue inhibitors of matrix metalloproteinases (Timps) are expressed later in the infection and these are linked to wound healing and fibrosis. Downregulation of metabolic associated genes is recorded in later stages of infection. Most mammalian host gene expression studies have been done using rodent models, with fewer in larger hosts such as bovines and humans. The majority of these studies have focused on S. japonicum infections and less on S. haematobium and S. mansoni infections (the two species that cause most global infections). The few human schistosomiasis gene expression studies so far have focused on S. japonicum and S. haematobium infections and none on S. mansoni, as far as we are aware. This highlights a paucity of gene expression data in humans, specifically with S. mansoni infection. This data is important to understand the disease pathology, identify biomarkers, diagnostics and possible drug targets.