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Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease
To better understand DNA methylation in Alzheimer’s disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388493/ https://www.ncbi.nlm.nih.gov/pubmed/35982059 http://dx.doi.org/10.1038/s41467-022-32475-x |
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author | C. Silva, Tiago Young, Juan I. Zhang, Lanyu Gomez, Lissette Schmidt, Michael A. Varma, Achintya Chen, X. Steven Martin, Eden R. Wang, Lily |
author_facet | C. Silva, Tiago Young, Juan I. Zhang, Lanyu Gomez, Lissette Schmidt, Michael A. Varma, Achintya Chen, X. Steven Martin, Eden R. Wang, Lily |
author_sort | C. Silva, Tiago |
collection | PubMed |
description | To better understand DNA methylation in Alzheimer’s disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 − 0.770, P-value = 2.78 × 10(−5)). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery. |
format | Online Article Text |
id | pubmed-9388493 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93884932022-08-20 Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease C. Silva, Tiago Young, Juan I. Zhang, Lanyu Gomez, Lissette Schmidt, Michael A. Varma, Achintya Chen, X. Steven Martin, Eden R. Wang, Lily Nat Commun Article To better understand DNA methylation in Alzheimer’s disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 − 0.770, P-value = 2.78 × 10(−5)). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery. Nature Publishing Group UK 2022-08-18 /pmc/articles/PMC9388493/ /pubmed/35982059 http://dx.doi.org/10.1038/s41467-022-32475-x Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article C. Silva, Tiago Young, Juan I. Zhang, Lanyu Gomez, Lissette Schmidt, Michael A. Varma, Achintya Chen, X. Steven Martin, Eden R. Wang, Lily Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease |
title | Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease |
title_full | Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease |
title_fullStr | Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease |
title_full_unstemmed | Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease |
title_short | Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease |
title_sort | cross-tissue analysis of blood and brain epigenome-wide association studies in alzheimer’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9388493/ https://www.ncbi.nlm.nih.gov/pubmed/35982059 http://dx.doi.org/10.1038/s41467-022-32475-x |
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