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dc.creatorTziastoudi M., Cholevas C., Theoharides T.C., Stefanidis I.en
dc.date.accessioned2023-01-31T10:21:34Z
dc.date.available2023-01-31T10:21:34Z
dc.date.issued2022
dc.identifier10.3390/ijms23010020
dc.identifier.issn16616596
dc.identifier.urihttp://hdl.handle.net/11615/80240
dc.description.abstractThe latest meta-analysis of genome-wide linkage studies (GWLS) identified nine cytogenetic locations suggestive of a linkage with diabetic nephropathy (DN) due to type 1 diabetes mellitus (T1DM) and seven locations due to type 2 diabetes mellitus (T2DM). In order to gain biological insight about the functional role of the genes located in these regions and to prioritize the most significant genetic loci for further research, we conducted a gene ontology analysis with an over representation test for the functional annotation of the protein coding genes. Protein analysis through evolutionary relationships (PANTHER) version 16.0 software and Cytoscape with the relevant plugins were used for the gene ontology analysis, and the overrepresentation test and STRING database were used for the construction of the protein network. The findings of the over-representation test highlight the contribution of immune related molecules like immunoglobulins, cytokines, and chemokines with regard to the most overrepresented protein classes, whereas the most enriched signaling pathways include the VEGF signaling pathway, the Cadherin pathway, the Wnt pathway, the angiogenesis pathway, the p38 MAPK pathway, and the EGF receptor signaling pathway. The common section of T1DM and T2DM results include the significant over representation of immune related molecules, and the Cadherin and Wnt signaling pathways that could constitute potential therapeutic targets for the treatment of DN, irrespective of the type of diabetes. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.en
dc.language.isoenen
dc.sourceInternational Journal of Molecular Sciencesen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85121380889&doi=10.3390%2fijms23010020&partnerID=40&md5=54550e9c938ee2c109acec9b86d1e20a
dc.subjectcadherinen
dc.subjectepidermal growth factor receptoren
dc.subjectgonadorelin receptoren
dc.subjectArticleen
dc.subjectbioinformaticsen
dc.subjectcytogeneticsen
dc.subjectcytokine signalingen
dc.subjectdiabetic nephropathyen
dc.subjectDNA bindingen
dc.subjectgene locusen
dc.subjectgenetic susceptibilityen
dc.subjecthumanen
dc.subjectinsulin dependent diabetes mellitusen
dc.subjectmeta analysisen
dc.subjectnon insulin dependent diabetes mellitusen
dc.subjectsignal transductionen
dc.subjectVEGF signalingen
dc.subjectWnt signalingen
dc.subjectbiologyen
dc.subjectcomplicationen
dc.subjectdiabetic nephropathyen
dc.subjectgene expression regulationen
dc.subjectgene regulatory networken
dc.subjectgenetic association studyen
dc.subjectgenetic predispositionen
dc.subjectgeneticsen
dc.subjectmolecular geneticsen
dc.subjectproceduresen
dc.subjectComputational Biologyen
dc.subjectDiabetes Mellitus, Type 1en
dc.subjectDiabetes Mellitus, Type 2en
dc.subjectDiabetic Nephropathiesen
dc.subjectGene Expression Regulationen
dc.subjectGene Regulatory Networksen
dc.subjectGenetic Association Studiesen
dc.subjectGenetic Predisposition to Diseaseen
dc.subjectHumansen
dc.subjectMolecular Sequence Annotationen
dc.subjectMDPIen
dc.titleMeta-analysis and bioinformatics detection of susceptibility genes in diabetic nephropathyen
dc.typejournalArticleen


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