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Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease

BACKGROUND: Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration. METHODS: A gene co-expression network was constructe...

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Autores principales: Lancour, Daniel, Dupuis, Josée, Mayeux, Richard, Haines, Jonathan L., Pericak-Vance, Margaret A., Schellenberg, Gerard C., Crovella, Mark, Farrer, Lindsay A., Kasif, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7469336/
https://www.ncbi.nlm.nih.gov/pubmed/32878640
http://dx.doi.org/10.1186/s13195-020-00674-7
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author Lancour, Daniel
Dupuis, Josée
Mayeux, Richard
Haines, Jonathan L.
Pericak-Vance, Margaret A.
Schellenberg, Gerard C.
Crovella, Mark
Farrer, Lindsay A.
Kasif, Simon
author_facet Lancour, Daniel
Dupuis, Josée
Mayeux, Richard
Haines, Jonathan L.
Pericak-Vance, Margaret A.
Schellenberg, Gerard C.
Crovella, Mark
Farrer, Lindsay A.
Kasif, Simon
author_sort Lancour, Daniel
collection PubMed
description BACKGROUND: Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration. METHODS: A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD. RESULTS: We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10(−3)) and HSPA2 (FDR p = 0.245). CONCLUSIONS: Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach.
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spelling pubmed-74693362020-09-03 Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease Lancour, Daniel Dupuis, Josée Mayeux, Richard Haines, Jonathan L. Pericak-Vance, Margaret A. Schellenberg, Gerard C. Crovella, Mark Farrer, Lindsay A. Kasif, Simon Alzheimers Res Ther Research BACKGROUND: Identifying and understanding the functional role of genetic risk factors for Alzheimer disease (AD) has been complicated by the variability of genetic influences across brain regions and confounding with age-related neurodegeneration. METHODS: A gene co-expression network was constructed using data obtained from the Allen Brain Atlas for multiple brain regions (cerebral cortex, cerebellum, and brain stem) in six individuals. Gene network analyses were seeded with 52 reproducible (i.e., established) AD (RAD) genes. Genome-wide association study summary data were integrated with the gene co-expression results and phenotypic information (i.e., memory and aging-related outcomes) from gene knockout studies in Drosophila to generate rankings for other genes that may have a role in AD. RESULTS: We found that co-expression of the RAD genes is strongest in the cortical regions where neurodegeneration due to AD is most severe. There was significant evidence for two novel AD-related genes including EPS8 (FDR p = 8.77 × 10(−3)) and HSPA2 (FDR p = 0.245). CONCLUSIONS: Our findings indicate that AD-related risk factors are potentially associated with brain region-specific effects on gene expression that can be detected using a gene network approach. BioMed Central 2020-09-02 /pmc/articles/PMC7469336/ /pubmed/32878640 http://dx.doi.org/10.1186/s13195-020-00674-7 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lancour, Daniel
Dupuis, Josée
Mayeux, Richard
Haines, Jonathan L.
Pericak-Vance, Margaret A.
Schellenberg, Gerard C.
Crovella, Mark
Farrer, Lindsay A.
Kasif, Simon
Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease
title Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease
title_full Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease
title_fullStr Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease
title_full_unstemmed Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease
title_short Analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with Alzheimer disease
title_sort analysis of brain region-specific co-expression networks reveals clustering of established and novel genes associated with alzheimer disease
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7469336/
https://www.ncbi.nlm.nih.gov/pubmed/32878640
http://dx.doi.org/10.1186/s13195-020-00674-7
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