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Identification of Parkinson’s Disease-Causing Genes via Omics Data

Parkinson’s disease (PD) is the second most frequent neurogenic disease after Alzheimer’s disease. The clinical manifestations include mostly motor disorders, such as bradykinesia, myotonia, and static tremors. Since the cause of this pathological features remain unclear, there is currently no radic...

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Autores principales: Cui, Xinran, Xu, Chen, Zhang, Liyuan, Wang, Yadong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355633/
https://www.ncbi.nlm.nih.gov/pubmed/34394198
http://dx.doi.org/10.3389/fgene.2021.712164
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author Cui, Xinran
Xu, Chen
Zhang, Liyuan
Wang, Yadong
author_facet Cui, Xinran
Xu, Chen
Zhang, Liyuan
Wang, Yadong
author_sort Cui, Xinran
collection PubMed
description Parkinson’s disease (PD) is the second most frequent neurogenic disease after Alzheimer’s disease. The clinical manifestations include mostly motor disorders, such as bradykinesia, myotonia, and static tremors. Since the cause of this pathological features remain unclear, there is currently no radical treatment for PD. Environmental and genetic factors are thought to contribute to the pathology of PD. To identify the genetic factors, some studies employed the Genome-Wide Association Studies (GWAS) method and detected certain genes closely related to PD. However, the functions of these gene mutants in the development of PD are unknown. Combining GWAS and expression Quantitative Trait Loci (eQTL) analysis, the biological meaning of mutation could be explained to some extent. Therefore, the present investigation used Summary data-based Mendelian Randomization (SMR) analysis to integrate of two PD GWAS datasets and four eQTL datasets with the objective of identifying casual genes. Using this strategy, we found six Single Nucleotide Polymorphism (SNP) loci which could cause the development of PD through altering the susceptibility gene expression, and three risk genes: Synuclein Alpha (SNCA), Mitochondrial Poly(A) Polymerase (MTPAP), and RP11-305E6.4. We proved the accuracy of results through case studies and inferred the functions of these genes in PD. Overall, this study provides insights into the genetic mechanism behind PD, which is crucial for the study of the development of this disease and its diagnosis and treatment.
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spelling pubmed-83556332021-08-12 Identification of Parkinson’s Disease-Causing Genes via Omics Data Cui, Xinran Xu, Chen Zhang, Liyuan Wang, Yadong Front Genet Genetics Parkinson’s disease (PD) is the second most frequent neurogenic disease after Alzheimer’s disease. The clinical manifestations include mostly motor disorders, such as bradykinesia, myotonia, and static tremors. Since the cause of this pathological features remain unclear, there is currently no radical treatment for PD. Environmental and genetic factors are thought to contribute to the pathology of PD. To identify the genetic factors, some studies employed the Genome-Wide Association Studies (GWAS) method and detected certain genes closely related to PD. However, the functions of these gene mutants in the development of PD are unknown. Combining GWAS and expression Quantitative Trait Loci (eQTL) analysis, the biological meaning of mutation could be explained to some extent. Therefore, the present investigation used Summary data-based Mendelian Randomization (SMR) analysis to integrate of two PD GWAS datasets and four eQTL datasets with the objective of identifying casual genes. Using this strategy, we found six Single Nucleotide Polymorphism (SNP) loci which could cause the development of PD through altering the susceptibility gene expression, and three risk genes: Synuclein Alpha (SNCA), Mitochondrial Poly(A) Polymerase (MTPAP), and RP11-305E6.4. We proved the accuracy of results through case studies and inferred the functions of these genes in PD. Overall, this study provides insights into the genetic mechanism behind PD, which is crucial for the study of the development of this disease and its diagnosis and treatment. Frontiers Media S.A. 2021-07-28 /pmc/articles/PMC8355633/ /pubmed/34394198 http://dx.doi.org/10.3389/fgene.2021.712164 Text en Copyright © 2021 Cui, Xu, Zhang and Wang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Cui, Xinran
Xu, Chen
Zhang, Liyuan
Wang, Yadong
Identification of Parkinson’s Disease-Causing Genes via Omics Data
title Identification of Parkinson’s Disease-Causing Genes via Omics Data
title_full Identification of Parkinson’s Disease-Causing Genes via Omics Data
title_fullStr Identification of Parkinson’s Disease-Causing Genes via Omics Data
title_full_unstemmed Identification of Parkinson’s Disease-Causing Genes via Omics Data
title_short Identification of Parkinson’s Disease-Causing Genes via Omics Data
title_sort identification of parkinson’s disease-causing genes via omics data
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8355633/
https://www.ncbi.nlm.nih.gov/pubmed/34394198
http://dx.doi.org/10.3389/fgene.2021.712164
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