Volume 13, Issue 4 (2023)
JMBS 2023, 13(4): 0-0 |
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sadeghi M, Safari S. Exploring signature genes and pathways in Alzheimer’s disease by network based analysis of Hippocampus transcriptome data. JMBS 2023; 13 (4)
URL: http://biot.modares.ac.ir/article-22-59783-en.html
URL: http://biot.modares.ac.ir/article-22-59783-en.html
1- Semnan University , mehdisadeghi@semnan.ac.ir
2- Semnan University
2- Semnan University
Abstract: (1191 Views)
Background and Objectives: Alzheimer’s disease is the most common neurodegenerative disease and the memory impairment is the main prominent symptom of this disease. The hippocampus of the brain, is the first region that undergoes changes in Alzheimer’s. Systems biology tools such as high-throughput techniques, enable us to explore signature genes involved in disease initiation and advancement which can be considered as new therapeutic and diagnostic candidates in complex diseases like Alzheimer’s.
Methods: A total of 85 samples obtained from the hippocampus of the brain of healthy individuals and individuals with Alzheimer’s were selected from two datasets. Differential expression analysis was performed independently for both datasets and the results were integrated. Genes with the same expression pattern in the two datasets were used to construct a gene-gene network using the STRING database. The obtained network analysis was performed to detect key genes associated with the disease.
Results: In this study, 73 genes with the same expression pattern were found in the two datasets. The obtained network analysis led to the identification of SNAP25, UNC13A, SYN2 and AMPH as key genes connected with Alzheimer’s disease.
Conclusion: The role of the reported key genes in endocytosis, neurotransmitters release and synaptic vesicle cycle facilitate proper functioning of memory. Expressional changes and mutations in each of these genes effect other pathways and lead to Alzheimer’s. Thus, the key genes reported in this study, can be considered as potential markers in developing diagnostic and therapeutic methods for Alzheimer’s.
Methods: A total of 85 samples obtained from the hippocampus of the brain of healthy individuals and individuals with Alzheimer’s were selected from two datasets. Differential expression analysis was performed independently for both datasets and the results were integrated. Genes with the same expression pattern in the two datasets were used to construct a gene-gene network using the STRING database. The obtained network analysis was performed to detect key genes associated with the disease.
Results: In this study, 73 genes with the same expression pattern were found in the two datasets. The obtained network analysis led to the identification of SNAP25, UNC13A, SYN2 and AMPH as key genes connected with Alzheimer’s disease.
Conclusion: The role of the reported key genes in endocytosis, neurotransmitters release and synaptic vesicle cycle facilitate proper functioning of memory. Expressional changes and mutations in each of these genes effect other pathways and lead to Alzheimer’s. Thus, the key genes reported in this study, can be considered as potential markers in developing diagnostic and therapeutic methods for Alzheimer’s.
Keywords: Alzheimer’s disease, High-throughput techniques, Gene expression profile, Transcriptome analysis, Gene-gene network
Article Type: Original Research |
Subject:
Biological system
Received: 2022/02/22 | Accepted: 2022/06/29 | Published: 2023/11/19
Received: 2022/02/22 | Accepted: 2022/06/29 | Published: 2023/11/19
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