ArticleHeliyon2023
Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer's disease.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- Glycation in Alzheimer's Disease and Type 2 Diabetes: The Prospect of Dual Drug Approaches for Therapeutic Interventions.Molecular neurobiology · 2025Review
- Identification of MicroRNA Drug Targets for Alzheimer's and Diabetes Mellitus Using Network Medicine.Current Alzheimer research · 2025Article
- Aronia Melanocarpa Elliot Anthocyanins Inhibits Alcoholic Liver Disease by Activation of α7nAChR.Plant foods for human nutrition (Dordrecht, Netherlands) · 2024Article
- Alzheimer's Disease as Type 3 Diabetes: Understanding the Link and Implications.International journal of molecular sciences · 2024Review
- A review and analysis of key biomarkers in Alzheimer's disease.Frontiers in neuroscience · 2024Review
- Identification of the Shared Gene Signatures Between Alzheimer's Disease and Diabetes-Associated Cognitive Dysfunction by Bioinformatics Analysis Combined with Biological Experiment.Journal of Alzheimer's disease : JAD · 2024Article
- Decision of the Optimal Rank of a Nonnegative Matrix Factorization Model for Gene Expression Data Sets Utilizing the Unit Invariant Knee Method: Development and Evaluation of the Elbow Method for Rank Selection.JMIR bioinformatics and biotechnology · 2023Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.