Gestation and breastfeeding in schistosomotic mothers differently modulate the immune response of adult offspring to postnatal Schistosoma mansoni infection

Schistosoma mansoni antigens in the early life alter homologous and heterologous immunity during postnatal infections. We evaluate the immunity to parasite antigens and ovalbumin (OA) in adult mice born/suckled by schistosomotic mothers. Newborns were divided into: born (BIM), suckled (SIM) or born/suckled (BSIM) in schistosomotic mothers, and animals from noninfected mothers (control). When adults, the mice were infected and compared the hepatic granuloma size and cellularity. Some animals were OA + adjuvant immunised. We evaluated hypersensitivity reactions (HR), antibodies levels (IgG1/IgG2a) anti-soluble egg antigen and anti-soluble worm antigen preparation, and anti-OA, cytokine production, and CD4+FoxP3+T-cells by splenocytes. Compared to control group, BIM mice showed a greater quantity of granulomas and collagen deposition, whereas SIM and BSIM presented smaller granulomas. BSIM group exhibited the lowest levels of anti-parasite antibodies. For anti-OA immunity, immediate HR was suppressed in all groups, with greater intensity in SIM mice accompanied of the remarkable level of basal CD4+FoxP3+T-cells. BIM and SIM groups produced less interleukin (IL)-4 and interferon (IFN)-g. In BSIM, there was higher production of IL-10 and IFN-γ, but lower levels of IL-4 and CD4+FoxP3+T-cells. Thus, pregnancy in schistosomotic mothers intensified hepatic fibrosis, whereas breastfeeding diminished granulomas in descendants. Separately, pregnancy and breastfeeding could suppress heterologous immunity; however, when combined, the responses could be partially restored in infected descendants.

Pathway analysis for identification of potential biomarkers in severe cutaneous drug hypersensitivity reactions

Purpose: To construct a cluster model or a gene signature for Stevens-Johnson syndrome (SJS) using pathways analysis in order to identify some potential biomarkers that may be used for early detection of SJS and epidermal necrolysis (TEN) manifestations. Methods: Gene expression profiles of GSE12829 were downloaded from Gene Expression Omnibus database. A total of 193 differentially expressed genes (DEGs) were obtained. We applied these genes to geneMANIA database, to remove ambiguous and duplicated genes, and after that, characterized the gene expression profiles using geneMANIA, DAVID, REACTOME, STRING and GENECODIS which are online software and databases. Results: Out of 193 genes, only 91 were used (after removing the ambiguous and duplicated genes) for topological analysis. It was found by geneMANIA database search that majority of these genes were coexpressed yielding 84.63 % co-expression. It was found that ten genes were in Physical interactions comprising almost 14.33 %. There were < 1 % pathway and genetic interactions with values of 0.97 and 0.06 %, respectively. Final analyses revealed that there are two clusters of gene interactions and 13 genes were shown to be in evident relationship of interaction with regards to hypersensitivity. Conclusion: Analysis of differential gene expressions by topological and database approaches in the current study reveals 2 gene network clusters. These genes are CD3G, CD3E, CD3D, TK1, TOP2A, CDK1, CDKN3, CCNB1, and CCNF. There are 9 key protein interactions in hypersensitivity reactions and may serve as biomarkers for SJS and TEN. Pathways related gene clusters has been identified and a genetic model to predict SJS and TEN early incidence using these biomarker genes has been developed.