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Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease
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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9876837/ https://www.ncbi.nlm.nih.gov/pubmed/36711310 http://dx.doi.org/10.1016/j.heliyon.2022.e12202 |
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author | Afzal, Muhammad Alharbi, Khalid Saad Alzarea, Sami I. Alyamani, Najiah M. Kazmi, Imran Güven, Emine |
author_facet | Afzal, Muhammad Alharbi, Khalid Saad Alzarea, Sami I. Alyamani, Najiah M. Kazmi, Imran Güven, Emine |
author_sort | Afzal, Muhammad |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9876837 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-98768372023-01-27 Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease Afzal, Muhammad Alharbi, Khalid Saad Alzarea, Sami I. Alyamani, Najiah M. Kazmi, Imran Güven, Emine Heliyon Research Article 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. Elsevier 2022-12-16 /pmc/articles/PMC9876837/ /pubmed/36711310 http://dx.doi.org/10.1016/j.heliyon.2022.e12202 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Research Article Afzal, Muhammad Alharbi, Khalid Saad Alzarea, Sami I. Alyamani, Najiah M. Kazmi, Imran Güven, Emine Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease |
title | Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease |
title_full | Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease |
title_fullStr | Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease |
title_full_unstemmed | Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease |
title_short | Revealing genetic links of Type 2 diabetes that lead to the development of Alzheimer’s disease |
title_sort | revealing genetic links of type 2 diabetes that lead to the development of alzheimer’s disease |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9876837/ https://www.ncbi.nlm.nih.gov/pubmed/36711310 http://dx.doi.org/10.1016/j.heliyon.2022.e12202 |
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