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Population genealogy resource shows evidence of familial clustering for Alzheimer disease
OBJECTIVE: To show the potential of a resource consisting of a genealogy of the US record linked to National Veterans Health Administration (VHA) patient data for investigation of the genetic contribution to health-related phenotypes, we present an analysis of familial clustering of VHA patients dia...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6089693/ https://www.ncbi.nlm.nih.gov/pubmed/30109265 http://dx.doi.org/10.1212/NXG.0000000000000249 |
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author | Cannon-Albright, Lisa Anne Dintelman, Sue Maness, Tim Cerny, Johni Thomas, Alun Backus, Steven Farnham, James Michael Teerlink, Craig Carl Contreras, Jorge Kauwe, John S.K. Meyer, Laurence J. |
author_facet | Cannon-Albright, Lisa Anne Dintelman, Sue Maness, Tim Cerny, Johni Thomas, Alun Backus, Steven Farnham, James Michael Teerlink, Craig Carl Contreras, Jorge Kauwe, John S.K. Meyer, Laurence J. |
author_sort | Cannon-Albright, Lisa Anne |
collection | PubMed |
description | OBJECTIVE: To show the potential of a resource consisting of a genealogy of the US record linked to National Veterans Health Administration (VHA) patient data for investigation of the genetic contribution to health-related phenotypes, we present an analysis of familial clustering of VHA patients diagnosed with Alzheimer disease (AD). METHODS: Patients with AD were identified by the International Classification of Diseases code. The Genealogical Index of Familiality method was used to compare the average relatedness of VHA patients with AD with expected relatedness. Relative risks for AD were estimated in first- to fifth- degree relatives of patients with AD using population rates for AD. RESULTS: Evidence for significant excess relatedness and significantly elevated risks for AD in relatives was observed; multiple pedigrees with a significant excess of VHA patients with AD were identified. CONCLUSIONS: This analysis of AD shows the nascent power of the US Veterans Genealogy Resource, in early stages, to provide evidence for familial clustering of multiple phenotypes, and shows the utility of this VHA genealogic resource for future genetic studies. |
format | Online Article Text |
id | pubmed-6089693 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Wolters Kluwer |
record_format | MEDLINE/PubMed |
spelling | pubmed-60896932018-08-14 Population genealogy resource shows evidence of familial clustering for Alzheimer disease Cannon-Albright, Lisa Anne Dintelman, Sue Maness, Tim Cerny, Johni Thomas, Alun Backus, Steven Farnham, James Michael Teerlink, Craig Carl Contreras, Jorge Kauwe, John S.K. Meyer, Laurence J. Neurol Genet Article OBJECTIVE: To show the potential of a resource consisting of a genealogy of the US record linked to National Veterans Health Administration (VHA) patient data for investigation of the genetic contribution to health-related phenotypes, we present an analysis of familial clustering of VHA patients diagnosed with Alzheimer disease (AD). METHODS: Patients with AD were identified by the International Classification of Diseases code. The Genealogical Index of Familiality method was used to compare the average relatedness of VHA patients with AD with expected relatedness. Relative risks for AD were estimated in first- to fifth- degree relatives of patients with AD using population rates for AD. RESULTS: Evidence for significant excess relatedness and significantly elevated risks for AD in relatives was observed; multiple pedigrees with a significant excess of VHA patients with AD were identified. CONCLUSIONS: This analysis of AD shows the nascent power of the US Veterans Genealogy Resource, in early stages, to provide evidence for familial clustering of multiple phenotypes, and shows the utility of this VHA genealogic resource for future genetic studies. Wolters Kluwer 2018-08-01 /pmc/articles/PMC6089693/ /pubmed/30109265 http://dx.doi.org/10.1212/NXG.0000000000000249 Text en Copyright © 2018 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (http://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits downloading and sharing the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. |
spellingShingle | Article Cannon-Albright, Lisa Anne Dintelman, Sue Maness, Tim Cerny, Johni Thomas, Alun Backus, Steven Farnham, James Michael Teerlink, Craig Carl Contreras, Jorge Kauwe, John S.K. Meyer, Laurence J. Population genealogy resource shows evidence of familial clustering for Alzheimer disease |
title | Population genealogy resource shows evidence of familial clustering for Alzheimer disease |
title_full | Population genealogy resource shows evidence of familial clustering for Alzheimer disease |
title_fullStr | Population genealogy resource shows evidence of familial clustering for Alzheimer disease |
title_full_unstemmed | Population genealogy resource shows evidence of familial clustering for Alzheimer disease |
title_short | Population genealogy resource shows evidence of familial clustering for Alzheimer disease |
title_sort | population genealogy resource shows evidence of familial clustering for alzheimer disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6089693/ https://www.ncbi.nlm.nih.gov/pubmed/30109265 http://dx.doi.org/10.1212/NXG.0000000000000249 |
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