Environmental enteric dysfunction includes a broad spectrum of inflammatory responses and epithelial repair processes (RT-PCR)

Environmental enteric dysfunction (EED), a chronic diffuse inflammation of the small intestine, is associated with stunting in children in the developing world. The pathobiology of EED is poorly understood because of the lack of a method to elucidate the host response. This study utilized a novel microarray method to interrogate the host transcriptome in feces in Malawian children with EED. Our data showed that the children studied had a range of %L values, consistent a spectrum of EED from normal to severe. We identified 12 transcripts associated with the severity of EED, including chemokines that stimulate T-cell proliferation, Fc fragments of multiple immunoglobulin families, interferon-induced proteins, activators of neutrophils and B-cells, and mediators that dampen cellular responses to hormones. EED associated transcripts mapped to pathways related to cell adhesion, and responses to a broad spectrum of viral, bacterial and parasitic microbes and enhanced phagocytosis. Several mucins, regulatory factors and protein kinases associated with the maintenance of the mucous layer were expressed less in children with EED than normal children. In conclusion, EED represents the focused activation of elements of the immune system and is associated with widespread intestinal barrier disruption. The differentially expressed transcripts may be explored as potential biomarkers. This study was carried out, firstly using Affymetrix Human Transcriptome Array 2.0 (HTA2.0, data have already been deposited in the GEO database: GSE74681) to profile the transcriptome of the host stool RNAs in 259 subjects, and then using droplet digital PCR (ddPCR) assays to validate the microarray data in terms of signal correlation. The ddPCR assay was done for a total of 60 genes in 25 - 236 (median 67) of the 258 RNA samples per RNA availability (1 of 259 samples [stool_080B] was not used for any of the 60 assays due to lack of availability). The data of the first 42 assays (genes) in the matrix sheets were used in Figure 4 for signal correlation analysis, and the data of the rest 18 assays (genes) were used in Table 4 for validation of 18 significant genes identified in biological pathway analysis.