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Lukacsovich D, O’Shea D, Huang H, Zhang W, Young J, Chen XS, Dietrich ST, Kunkle B, Martin E, Wang L. MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease. Database (Oxford) 2024; 2024:baae061. [PMID: 39028752 PMCID: PMC11259044 DOI: 10.1093/database/baae061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 05/08/2024] [Accepted: 07/03/2024] [Indexed: 07/21/2024]
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.
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Affiliation(s)
- David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Deirdre O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami, Miller School of Medicine, 7700 W Camino Real, Boca Raton, FL 33433, USA
| | - Hanchen Huang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Juan Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, 1475 NW 12th Ave, Miami, FL 33136, USA
| | - Sven-Thorsten Dietrich
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Eden Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, 1475 NW 12th Ave, Miami, FL 33136, USA
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Lukacsovich D, O’Shea D, Huang H, Zhang W, Young JI, Steven Chen X, Dietrich ST, Kunkle B, Martin ER, Wang L. MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.04.23299412. [PMID: 38105943 PMCID: PMC10723513 DOI: 10.1101/2023.12.04.23299412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledge base containing manually curated summary statistics from 97 published tables in 37 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels - at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD (https://miami-ad.org/) facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD.
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Affiliation(s)
- David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Deirdre O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Boca Raton, FL, 33433
| | - Hanchen Huang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I. Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Sven-Thorsten Dietrich
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Eden R. Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
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Cava C, D'Antona S, Maselli F, Castiglioni I, Porro D. From genetic correlations of Alzheimer's disease to classification with artificial neural network models. Funct Integr Genomics 2023; 23:293. [PMID: 37682415 PMCID: PMC10491691 DOI: 10.1007/s10142-023-01228-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Revised: 08/30/2023] [Accepted: 09/03/2023] [Indexed: 09/09/2023]
Abstract
Sporadic Alzheimer's disease (AD) is a complex neurological disorder characterized by many risk loci with potential associations with different traits and diseases. AD, characterized by a progressive loss of neuronal functions, manifests with different symptoms such as decline in memory, movement, coordination, and speech. The mechanisms underlying the onset of AD are not always fully understood, but involve a multiplicity of factors. Early diagnosis of AD plays a central role as it can offer the possibility of early treatment, which can slow disease progression. Currently, the methods of diagnosis are cognitive testing, neuroimaging, or cerebrospinal fluid analysis that can be time-consuming, expensive, invasive, and not always accurate. In the present study, we performed a genetic correlation analysis using genome-wide association statistics from a large study of AD and UK Biobank, to examine the association of AD with other human traits and disorders. In addition, since hippocampus, a part of cerebral cortex could play a central role in several traits that are associated with AD; we analyzed the gene expression profiles of hippocampus of AD patients applying 4 different artificial neural network models. We found 65 traits correlated with AD grouped into 9 clusters: medical conditions, fluid intelligence, education, anthropometric measures, employment status, activity, diet, lifestyle, and sexuality. The comparison of different 4 neural network models along with feature selection methods on 5 Alzheimer's gene expression datasets showed that the simple basic neural network model obtains a better performance (66% of accuracy) than other more complex methods with dropout and weight regularization of the network.
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Affiliation(s)
- Claudia Cava
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy.
- Department of Science, Technology and Society, University School for Advanced Studies IUSS Pavia, Palazzo del Broletto, Piazza Della Vittoria 15, 27100, Pavia, Italy.
| | - Salvatore D'Antona
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy
| | - Francesca Maselli
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy
| | - Isabella Castiglioni
- Department of Physics "Giuseppe Occhialini", University of Milan-Bicocca Piazza Dell'Ateneo Nuovo, 20126, Milan, Italy
| | - Danilo Porro
- Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), Via F. Cervi 93, Segrate-Milan, 20090, Milan, Italy
- NBFC, National Biodiversity Future Center, 90133, Palermo, Italy
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