Aim: To identify key genes linking glucose variability (GV) and inflammatory pathways in diabetes.

Methods: Text mining-based reconstruction and analysis of the gene networks associated with GV and low-grade inflammation in diabetes were performed by the ANDSystem ( . Key elements of the networks were identified by the highest value of cross-talk centrality (CTC) and cross-talk specificity (CTS) . A comparative analysis of two networks was applied to identify genes that are up- or down-regulated by glucose fluctuations and involve in the inflammatory pathways.

Results: We revealed sixty one genes related to GV and inflammation (Table) . Based on CTC values, TP53, TNF, NFKB1, IL1B, IL6, CASP3, MMP2, MMP9, TGFB1, and VEGFA were identified as the principal hubs in the gene network of inflammation that are regulated by GV. The UCP2, GPX1, SOD2, ANGPT2, GLP1R, HGF, SPP1, MAPK9, TIMP1, and MMP1 genes demonstrated the highest CTS values.

Conclusions: The obtained results improve the understanding of the molecular mechanisms of the proinflammatory effect of GV in diabetes. The role of the identified molecules as key drivers of GV-induced inflammation needs further experimental verification.


O.V.Saik: None. V.Klimontov: None.


Russian Science Foundation (20-15-00057)

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