Cargando…
Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data
Alzheimer’s disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease’s causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer’s Pr...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330278/ https://www.ncbi.nlm.nih.gov/pubmed/30666269 http://dx.doi.org/10.3389/fgene.2018.00653 |
_version_ | 1783386936421908480 |
---|---|
author | Hao, Sicheng Wang, Rui Zhang, Yu Zhan, Hui |
author_facet | Hao, Sicheng Wang, Rui Zhang, Yu Zhan, Hui |
author_sort | Hao, Sicheng |
collection | PubMed |
description | Alzheimer’s disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease’s causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer’s Project (IGAP), many disease-associated genes have been identified; however, we do not have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways. We integrated GWAS summary data from IGAP and five different expression-level data by using the transcriptome-wide association study method and identified 15 disease-causal genes under strict multiple testing (α < 0.05), and four genes are newly identified. We identified an additional 29 potential disease-causal genes under a false discovery rate (α < 0.05), and 21 of them are newly identified. Many genes we identified are also associated with an autoimmune disorder. |
format | Online Article Text |
id | pubmed-6330278 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63302782019-01-21 Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data Hao, Sicheng Wang, Rui Zhang, Yu Zhan, Hui Front Genet Genetics Alzheimer’s disease (AD) is the most common cause of dementia. It is the fifth leading cause of death among elderly people. With high genetic heritability (79%), finding the disease’s causal genes is a crucial step in finding a treatment for AD. Following the International Genomics of Alzheimer’s Project (IGAP), many disease-associated genes have been identified; however, we do not have enough knowledge about how those disease-associated genes affect gene expression and disease-related pathways. We integrated GWAS summary data from IGAP and five different expression-level data by using the transcriptome-wide association study method and identified 15 disease-causal genes under strict multiple testing (α < 0.05), and four genes are newly identified. We identified an additional 29 potential disease-causal genes under a false discovery rate (α < 0.05), and 21 of them are newly identified. Many genes we identified are also associated with an autoimmune disorder. Frontiers Media S.A. 2019-01-07 /pmc/articles/PMC6330278/ /pubmed/30666269 http://dx.doi.org/10.3389/fgene.2018.00653 Text en Copyright © 2019 Hao, Wang, Zhang and Zhan. http://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 Hao, Sicheng Wang, Rui Zhang, Yu Zhan, Hui Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data |
title | Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data |
title_full | Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data |
title_fullStr | Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data |
title_full_unstemmed | Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data |
title_short | Prediction of Alzheimer’s Disease-Associated Genes by Integration of GWAS Summary Data and Expression Data |
title_sort | prediction of alzheimer’s disease-associated genes by integration of gwas summary data and expression data |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330278/ https://www.ncbi.nlm.nih.gov/pubmed/30666269 http://dx.doi.org/10.3389/fgene.2018.00653 |
work_keys_str_mv | AT haosicheng predictionofalzheimersdiseaseassociatedgenesbyintegrationofgwassummarydataandexpressiondata AT wangrui predictionofalzheimersdiseaseassociatedgenesbyintegrationofgwassummarydataandexpressiondata AT zhangyu predictionofalzheimersdiseaseassociatedgenesbyintegrationofgwassummarydataandexpressiondata AT zhanhui predictionofalzheimersdiseaseassociatedgenesbyintegrationofgwassummarydataandexpressiondata |