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Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci
Neurodegenerative diseases (ND) are heterogeneous disorders of the central nervous system that share a chronic and selective process of neuronal cell death. A computational approach to investigate shared genetic and specific loci was applied to 5 different ND: Amyotrophic lateral sclerosis (ALS), Al...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651457/ https://www.ncbi.nlm.nih.gov/pubmed/38022694 http://dx.doi.org/10.1016/j.csbj.2023.10.031 |
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author | Maselli, Francesca D’Antona, Salvatore Utichi, Mattia Arnaudi, Matteo Castiglioni, Isabella Porro, Danilo Papaleo, Elena Gandellini, Paolo Cava, Claudia |
author_facet | Maselli, Francesca D’Antona, Salvatore Utichi, Mattia Arnaudi, Matteo Castiglioni, Isabella Porro, Danilo Papaleo, Elena Gandellini, Paolo Cava, Claudia |
author_sort | Maselli, Francesca |
collection | PubMed |
description | Neurodegenerative diseases (ND) are heterogeneous disorders of the central nervous system that share a chronic and selective process of neuronal cell death. A computational approach to investigate shared genetic and specific loci was applied to 5 different ND: Amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), Multiple sclerosis (MS), and Lewy body dementia (LBD). The datasets were analyzed separately, and then we compared the obtained results. For this purpose, we applied a genetic correlation analysis to genome-wide association datasets and revealed different genetic correlations with several human traits and diseases. In addition, a clumping analysis was carried out to identify SNPs genetically associated with each disease. We found 27 SNPs in AD, 6 SNPs in ALS, 10 SNPs in PD, 17 SNPs in MS, and 3 SNPs in LBD. Most of them are located in non-coding regions, with the exception of 5 SNPs on which a protein structure and stability prediction was performed to verify their impact on disease. Furthermore, an analysis of the differentially expressed miRNAs of the 5 examined pathologies was performed to reveal regulatory mechanisms that could involve genes associated with selected SNPs. In conclusion, the results obtained constitute an important step toward the discovery of diagnostic biomarkers and a better understanding of the diseases. |
format | Online Article Text |
id | pubmed-10651457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-106514572023-10-21 Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci Maselli, Francesca D’Antona, Salvatore Utichi, Mattia Arnaudi, Matteo Castiglioni, Isabella Porro, Danilo Papaleo, Elena Gandellini, Paolo Cava, Claudia Comput Struct Biotechnol J Research Article Neurodegenerative diseases (ND) are heterogeneous disorders of the central nervous system that share a chronic and selective process of neuronal cell death. A computational approach to investigate shared genetic and specific loci was applied to 5 different ND: Amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), Multiple sclerosis (MS), and Lewy body dementia (LBD). The datasets were analyzed separately, and then we compared the obtained results. For this purpose, we applied a genetic correlation analysis to genome-wide association datasets and revealed different genetic correlations with several human traits and diseases. In addition, a clumping analysis was carried out to identify SNPs genetically associated with each disease. We found 27 SNPs in AD, 6 SNPs in ALS, 10 SNPs in PD, 17 SNPs in MS, and 3 SNPs in LBD. Most of them are located in non-coding regions, with the exception of 5 SNPs on which a protein structure and stability prediction was performed to verify their impact on disease. Furthermore, an analysis of the differentially expressed miRNAs of the 5 examined pathologies was performed to reveal regulatory mechanisms that could involve genes associated with selected SNPs. In conclusion, the results obtained constitute an important step toward the discovery of diagnostic biomarkers and a better understanding of the diseases. Research Network of Computational and Structural Biotechnology 2023-10-21 /pmc/articles/PMC10651457/ /pubmed/38022694 http://dx.doi.org/10.1016/j.csbj.2023.10.031 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Maselli, Francesca D’Antona, Salvatore Utichi, Mattia Arnaudi, Matteo Castiglioni, Isabella Porro, Danilo Papaleo, Elena Gandellini, Paolo Cava, Claudia Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
title | Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
title_full | Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
title_fullStr | Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
title_full_unstemmed | Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
title_short | Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
title_sort | computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10651457/ https://www.ncbi.nlm.nih.gov/pubmed/38022694 http://dx.doi.org/10.1016/j.csbj.2023.10.031 |
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