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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...

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Autores principales: Maselli, Francesca, D’Antona, Salvatore, Utichi, Mattia, Arnaudi, Matteo, Castiglioni, Isabella, Porro, Danilo, Papaleo, Elena, Gandellini, Paolo, Cava, Claudia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2023
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.
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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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