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Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis

Variants associated with Parkinson’s disease (PD) have generally a small effect size and, therefore, large sample sizes or targeted analyses are required to detect significant associations in a whole exome sequencing (WES) study. Here, we used protein-protein interaction (PPI) information on 36 gene...

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Autores principales: Siitonen, Ari, Kytövuori, Laura, Nalls, Mike A., Gibbs, Raphael, Hernandez, Dena G., Ylikotila, Pauli, Peltonen, Markku, Singleton, Andrew B., Majamaa, Kari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906405/
https://www.ncbi.nlm.nih.gov/pubmed/31827228
http://dx.doi.org/10.1038/s41598-019-55479-y
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author Siitonen, Ari
Kytövuori, Laura
Nalls, Mike A.
Gibbs, Raphael
Hernandez, Dena G.
Ylikotila, Pauli
Peltonen, Markku
Singleton, Andrew B.
Majamaa, Kari
author_facet Siitonen, Ari
Kytövuori, Laura
Nalls, Mike A.
Gibbs, Raphael
Hernandez, Dena G.
Ylikotila, Pauli
Peltonen, Markku
Singleton, Andrew B.
Majamaa, Kari
author_sort Siitonen, Ari
collection PubMed
description Variants associated with Parkinson’s disease (PD) have generally a small effect size and, therefore, large sample sizes or targeted analyses are required to detect significant associations in a whole exome sequencing (WES) study. Here, we used protein-protein interaction (PPI) information on 36 genes with established or suggested associations with PD to target the analysis of the WES data. We performed an association analysis on WES data from 439 Finnish PD subjects and 855 controls, and included a Finnish population cohort as the replication dataset with 60 PD subjects and 8214 controls. Single variant association (SVA) test in the discovery dataset yielded 11 candidate variants in seven genes, but the associations were not significant in the replication cohort after correction for multiple testing. Polygenic risk score using variants rs2230288 and rs2291312, however, was associated to PD with odds ratio of 2.7 (95% confidence interval 1.4–5.2; p < 2.56e-03). Furthermore, an analysis of the PPI network revealed enriched clusters of biological processes among established and candidate genes, and these functional networks were visualized in the study. We identified novel candidate variants for PD using a gene prioritization based on PPI information, and described why these variants may be involved in the pathogenesis of PD.
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spelling pubmed-69064052019-12-13 Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis Siitonen, Ari Kytövuori, Laura Nalls, Mike A. Gibbs, Raphael Hernandez, Dena G. Ylikotila, Pauli Peltonen, Markku Singleton, Andrew B. Majamaa, Kari Sci Rep Article Variants associated with Parkinson’s disease (PD) have generally a small effect size and, therefore, large sample sizes or targeted analyses are required to detect significant associations in a whole exome sequencing (WES) study. Here, we used protein-protein interaction (PPI) information on 36 genes with established or suggested associations with PD to target the analysis of the WES data. We performed an association analysis on WES data from 439 Finnish PD subjects and 855 controls, and included a Finnish population cohort as the replication dataset with 60 PD subjects and 8214 controls. Single variant association (SVA) test in the discovery dataset yielded 11 candidate variants in seven genes, but the associations were not significant in the replication cohort after correction for multiple testing. Polygenic risk score using variants rs2230288 and rs2291312, however, was associated to PD with odds ratio of 2.7 (95% confidence interval 1.4–5.2; p < 2.56e-03). Furthermore, an analysis of the PPI network revealed enriched clusters of biological processes among established and candidate genes, and these functional networks were visualized in the study. We identified novel candidate variants for PD using a gene prioritization based on PPI information, and described why these variants may be involved in the pathogenesis of PD. Nature Publishing Group UK 2019-12-11 /pmc/articles/PMC6906405/ /pubmed/31827228 http://dx.doi.org/10.1038/s41598-019-55479-y Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Siitonen, Ari
Kytövuori, Laura
Nalls, Mike A.
Gibbs, Raphael
Hernandez, Dena G.
Ylikotila, Pauli
Peltonen, Markku
Singleton, Andrew B.
Majamaa, Kari
Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
title Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
title_full Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
title_fullStr Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
title_full_unstemmed Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
title_short Finnish Parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
title_sort finnish parkinson’s disease study integrating protein-protein interaction network data with exome sequencing analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6906405/
https://www.ncbi.nlm.nih.gov/pubmed/31827228
http://dx.doi.org/10.1038/s41598-019-55479-y
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