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Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN)
The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10400428/ https://www.ncbi.nlm.nih.gov/pubmed/37429916 http://dx.doi.org/10.1038/s41593-023-01359-8 |
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author | McKay, Nicole S. Gordon, Brian A. Hornbeck, Russ C. Dincer, Aylin Flores, Shaney Keefe, Sarah J. Joseph-Mathurin, Nelly Jack, Clifford R. Koeppe, Robert Millar, Peter R. Ances, Beau M. Chen, Charles D. Daniels, Alisha Hobbs, Diana A. Jackson, Kelley Koudelis, Deborah Massoumzadeh, Parinaz McCullough, Austin Nickels, Michael L. Rahmani, Farzaneh Swisher, Laura Wang, Qing Allegri, Ricardo F. Berman, Sarah B. Brickman, Adam M. Brooks, William S. Cash, David M. Chhatwal, Jasmeer P. Day, Gregory S. Farlow, Martin R. la Fougère, Christian Fox, Nick C. Fulham, Michael Ghetti, Bernardino Graff-Radford, Neill Ikeuchi, Takeshi Klunk, William Lee, Jae-Hong Levin, Johannes Martins, Ralph Masters, Colin L. McConathy, Jonathan Mori, Hiroshi Noble, James M. Reischl, Gerald Rowe, Christopher Salloway, Stephen Sanchez-Valle, Raquel Schofield, Peter R. Shimada, Hiroyuki Shoji, Mikio Su, Yi Suzuki, Kazushi Vöglein, Jonathan Yakushev, Igor Cruchaga, Carlos Hassenstab, Jason Karch, Celeste McDade, Eric Perrin, Richard J. Xiong, Chengjie Morris, John C. Bateman, Randall J. Benzinger, Tammie L. S. |
author_facet | McKay, Nicole S. Gordon, Brian A. Hornbeck, Russ C. Dincer, Aylin Flores, Shaney Keefe, Sarah J. Joseph-Mathurin, Nelly Jack, Clifford R. Koeppe, Robert Millar, Peter R. Ances, Beau M. Chen, Charles D. Daniels, Alisha Hobbs, Diana A. Jackson, Kelley Koudelis, Deborah Massoumzadeh, Parinaz McCullough, Austin Nickels, Michael L. Rahmani, Farzaneh Swisher, Laura Wang, Qing Allegri, Ricardo F. Berman, Sarah B. Brickman, Adam M. Brooks, William S. Cash, David M. Chhatwal, Jasmeer P. Day, Gregory S. Farlow, Martin R. la Fougère, Christian Fox, Nick C. Fulham, Michael Ghetti, Bernardino Graff-Radford, Neill Ikeuchi, Takeshi Klunk, William Lee, Jae-Hong Levin, Johannes Martins, Ralph Masters, Colin L. McConathy, Jonathan Mori, Hiroshi Noble, James M. Reischl, Gerald Rowe, Christopher Salloway, Stephen Sanchez-Valle, Raquel Schofield, Peter R. Shimada, Hiroyuki Shoji, Mikio Su, Yi Suzuki, Kazushi Vöglein, Jonathan Yakushev, Igor Cruchaga, Carlos Hassenstab, Jason Karch, Celeste McDade, Eric Perrin, Richard J. Xiong, Chengjie Morris, John C. Bateman, Randall J. Benzinger, Tammie L. S. |
author_sort | McKay, Nicole S. |
collection | PubMed |
description | The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case–control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual’s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of ‘sporadic’ AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers. |
format | Online Article Text |
id | pubmed-10400428 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-104004282023-08-05 Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) McKay, Nicole S. Gordon, Brian A. Hornbeck, Russ C. Dincer, Aylin Flores, Shaney Keefe, Sarah J. Joseph-Mathurin, Nelly Jack, Clifford R. Koeppe, Robert Millar, Peter R. Ances, Beau M. Chen, Charles D. Daniels, Alisha Hobbs, Diana A. Jackson, Kelley Koudelis, Deborah Massoumzadeh, Parinaz McCullough, Austin Nickels, Michael L. Rahmani, Farzaneh Swisher, Laura Wang, Qing Allegri, Ricardo F. Berman, Sarah B. Brickman, Adam M. Brooks, William S. Cash, David M. Chhatwal, Jasmeer P. Day, Gregory S. Farlow, Martin R. la Fougère, Christian Fox, Nick C. Fulham, Michael Ghetti, Bernardino Graff-Radford, Neill Ikeuchi, Takeshi Klunk, William Lee, Jae-Hong Levin, Johannes Martins, Ralph Masters, Colin L. McConathy, Jonathan Mori, Hiroshi Noble, James M. Reischl, Gerald Rowe, Christopher Salloway, Stephen Sanchez-Valle, Raquel Schofield, Peter R. Shimada, Hiroyuki Shoji, Mikio Su, Yi Suzuki, Kazushi Vöglein, Jonathan Yakushev, Igor Cruchaga, Carlos Hassenstab, Jason Karch, Celeste McDade, Eric Perrin, Richard J. Xiong, Chengjie Morris, John C. Bateman, Randall J. Benzinger, Tammie L. S. Nat Neurosci Resource The Dominantly Inherited Alzheimer Network (DIAN) is an international collaboration studying autosomal dominant Alzheimer disease (ADAD). ADAD arises from mutations occurring in three genes. Offspring from ADAD families have a 50% chance of inheriting their familial mutation, so non-carrier siblings can be recruited for comparisons in case–control studies. The age of onset in ADAD is highly predictable within families, allowing researchers to estimate an individual’s point in the disease trajectory. These characteristics allow candidate AD biomarker measurements to be reliably mapped during the preclinical phase. Although ADAD represents a small proportion of AD cases, understanding neuroimaging-based changes that occur during the preclinical period may provide insight into early disease stages of ‘sporadic’ AD also. Additionally, this study provides rich data for research in healthy aging through inclusion of the non-carrier controls. Here we introduce the neuroimaging dataset collected and describe how this resource can be used by a range of researchers. Nature Publishing Group US 2023-07-10 2023 /pmc/articles/PMC10400428/ /pubmed/37429916 http://dx.doi.org/10.1038/s41593-023-01359-8 Text en © The Author(s) 2023 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 | Resource McKay, Nicole S. Gordon, Brian A. Hornbeck, Russ C. Dincer, Aylin Flores, Shaney Keefe, Sarah J. Joseph-Mathurin, Nelly Jack, Clifford R. Koeppe, Robert Millar, Peter R. Ances, Beau M. Chen, Charles D. Daniels, Alisha Hobbs, Diana A. Jackson, Kelley Koudelis, Deborah Massoumzadeh, Parinaz McCullough, Austin Nickels, Michael L. Rahmani, Farzaneh Swisher, Laura Wang, Qing Allegri, Ricardo F. Berman, Sarah B. Brickman, Adam M. Brooks, William S. Cash, David M. Chhatwal, Jasmeer P. Day, Gregory S. Farlow, Martin R. la Fougère, Christian Fox, Nick C. Fulham, Michael Ghetti, Bernardino Graff-Radford, Neill Ikeuchi, Takeshi Klunk, William Lee, Jae-Hong Levin, Johannes Martins, Ralph Masters, Colin L. McConathy, Jonathan Mori, Hiroshi Noble, James M. Reischl, Gerald Rowe, Christopher Salloway, Stephen Sanchez-Valle, Raquel Schofield, Peter R. Shimada, Hiroyuki Shoji, Mikio Su, Yi Suzuki, Kazushi Vöglein, Jonathan Yakushev, Igor Cruchaga, Carlos Hassenstab, Jason Karch, Celeste McDade, Eric Perrin, Richard J. Xiong, Chengjie Morris, John C. Bateman, Randall J. Benzinger, Tammie L. S. Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) |
title | Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) |
title_full | Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) |
title_fullStr | Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) |
title_full_unstemmed | Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) |
title_short | Positron emission tomography and magnetic resonance imaging methods and datasets within the Dominantly Inherited Alzheimer Network (DIAN) |
title_sort | positron emission tomography and magnetic resonance imaging methods and datasets within the dominantly inherited alzheimer network (dian) |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10400428/ https://www.ncbi.nlm.nih.gov/pubmed/37429916 http://dx.doi.org/10.1038/s41593-023-01359-8 |
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