Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer's disease

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dc.authorscopusid26645391400
dc.authorscopusid57205146162
dc.authorscopusid57217185560
dc.authorscopusid57218370621
dc.authorscopusid54796632400
dc.authorscopusid57203489662
dc.contributor.authorAfzal, Muhammad
dc.contributor.authorAlharbi, K.S.
dc.contributor.authorAlzarea, S.I.
dc.contributor.authorAlyamani, N.M.
dc.contributor.authorKazmi, I.
dc.contributor.authorGüven, E.
dc.date.accessioned2023-07-26T11:51:19Z
dc.date.available2023-07-26T11:51:19Z
dc.date.issued2023
dc.departmentDÜ, Mühendislik Fakültesi, Biyomedikal Mühendisliği Bölümüen_US
dc.description.abstractBackground: A factor leading to Alzheimer's Disease (AD), portrayed by peripheral insulin resistance, is Type 2 diabetes mellitus (T2D). The likelihood of T2D cases would be at boosted danger in alternating AD cases has severe social consequences. Several genes have been detected via gene expression profiling or different techniques; despite the consideration of the utility of numerous of these genes stays insufficient. Methods: This project is designed to uncover the mutual genomics motifs between AD and T2D via non-negative matrix factorization (NMF) of differentially expressed genes (DEGs) of T2D Mellitus of human cortical neurons of the neurovascular unit gene expression data. A rank factorization value is calculated by employing the combination of the NMF model with the unit invariant knee (UIK) point method. The metagenes are further determined by remarking the enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment tools. In this study, the most highly expressed genes of metagenes are subjected to protein-protein interaction (PPI) network study to discover the most significant biomarkers of T2D Mellitus in the ageing brain. Results: We screened the most important shared genes (CDKN1A, COL22A1, EIF4A, GFAP, SLC1A1, and VIM) and essential human molecular pathways that motivate these diseases. The study aimed to validate the most significant hub genes using network-based methods which detected the corresponding relationship between AD and T2D. Conclusions: Using in silico tools, the computational pipeline has broadly examined transformed pathways and discovered promising biomarkers and drug targets. We validated the most significant hub genes using network-based methods which detected the corresponding relationship between AD and T2D. These consequences on brain cells hypothetically reserve to diabetic Alzheimer's so-called type 3 diabetes (T3D) and may offer promising methodologies for curative intrusion. © 2022 The Author(s)en_US
dc.description.sponsorshipDeanship of Scientific Research, University of Jordan, DSR: DSR2022-RG-0150en_US
dc.description.sponsorshipMuhammad Afzal was supported by the Deanship of Scientific Research at Jouf University [ DSR2022-RG-0150 ].en_US
dc.description.sponsorshipThis research work was funded by the Deanship of Scientific Reseacrh at Jouf University [DSR2022-RG-0150].en_US
dc.identifier.doi10.1016/j.heliyon.2022.e12202
dc.identifier.issn2405-8440
dc.identifier.issue1en_US
dc.identifier.pmid36711310en_US
dc.identifier.scopus2-s2.0-85149764764en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.heliyon.2022.e12202
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12536
dc.identifier.volume9en_US
dc.identifier.wosWOS:000968577300001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorGüven, E.
dc.language.isoenen_US
dc.publisherElsevier Ltden_US
dc.relation.ispartofHeliyonen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectAgeing brainen_US
dc.subjectAlzheimer's diseaseen_US
dc.subjectDifferential expressionen_US
dc.subjectNeovascular uniten_US
dc.subjectType 2 diabetes mellitusen_US
dc.titleRevealing genetic links of Type 2 diabetes that lead to the development of Alzheimer's diseaseen_US
dc.typeArticleen_US

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