Helicobacter pylori infection is involved in development of diverse gastro-pathologies. Our aim is to investigate potential signature of cytokines-chemokine levels (IL-17A, IL-1β, and CXCL-8) in H. pylori-infected patients and their impact on immune response in both corpus and antrum. Multivariate level analysis with machine learning model were carried out using cytokines/chemokine levels of infected Moroccan patients. In addition, Geo dataset was used to run enrichment analysis following CXCL-8 upregulation. Our analysis showed that combination of cytokines-chemokine levels allowed prediction of positive H. pylori density score with <5% of miss-classification error, with fundus CXCL-8 being the most important variable for this discrimination. Furthermore, CXCL-8 dependent expression profile was mainly associated to IL6/JAK/STAT3 signaling in the antrum, interferons alpha and gamma responses in the corpus and commonly induced transcriptional /proliferative activities. To conclude, CXCL-8 level might be a signature of Moroccan H. pylori-infected patients and an inducer of regional-dependent immune response at the gastric level. Larger trials must be carried out to validate the relevance of these results for diverse populations.
Keywords: Artificial intelligence model; Bioinformatics; CXCL-8; Gastric regionalization; H. pylori; Immune response.
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