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Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia

Proxy phenotypes allow for the utilization of genetic data from large population cohorts to analyze late-onset diseases by using parental diagnoses as a proxy for genetic disease risk. Proxy phenotypes based on parental diagnosis status have been used in previous studies to identify common variants...

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Autores principales: Wightman, Douglas P., Savage, Jeanne E., de Leeuw, Christiaan A., Jansen, Iris E., Posthuma, Danielle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9905079/
https://www.ncbi.nlm.nih.gov/pubmed/36750708
http://dx.doi.org/10.1038/s41598-023-29108-8
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author Wightman, Douglas P.
Savage, Jeanne E.
de Leeuw, Christiaan A.
Jansen, Iris E.
Posthuma, Danielle
author_facet Wightman, Douglas P.
Savage, Jeanne E.
de Leeuw, Christiaan A.
Jansen, Iris E.
Posthuma, Danielle
author_sort Wightman, Douglas P.
collection PubMed
description Proxy phenotypes allow for the utilization of genetic data from large population cohorts to analyze late-onset diseases by using parental diagnoses as a proxy for genetic disease risk. Proxy phenotypes based on parental diagnosis status have been used in previous studies to identify common variants associated with Alzheimer’s disease. As of yet, proxy phenotypes have not been used to identify genes associated with Alzheimer’s disease through rare variants. Here we show that a proxy Alzheimer’s disease/dementia phenotype can capture known Alzheimer’s disease risk genes through rare variant aggregation. We generated a proxy Alzheimer’s disease/dementia phenotype for 148,508 unrelated individuals of European ancestry in the UK biobank in order to perform exome-wide rare variant aggregation analyses to identify genes associated with proxy Alzheimer’s disease/dementia. We identified four genes significantly associated with the proxy phenotype, three of which were significantly associated with proxy Alzheimer’s disease/dementia in an independent replication cohort consisting of 197,506 unrelated individuals of European ancestry in the UK biobank. All three of the replicated genes have been previously associated with clinically diagnosed Alzheimer’s disease (SORL1, TREM2, and TOMM40/APOE). We show that proxy Alzheimer’s disease/dementia can be used to identify genes associated with Alzheimer’s disease through rare variant aggregation.
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spelling pubmed-99050792023-02-08 Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia Wightman, Douglas P. Savage, Jeanne E. de Leeuw, Christiaan A. Jansen, Iris E. Posthuma, Danielle Sci Rep Article Proxy phenotypes allow for the utilization of genetic data from large population cohorts to analyze late-onset diseases by using parental diagnoses as a proxy for genetic disease risk. Proxy phenotypes based on parental diagnosis status have been used in previous studies to identify common variants associated with Alzheimer’s disease. As of yet, proxy phenotypes have not been used to identify genes associated with Alzheimer’s disease through rare variants. Here we show that a proxy Alzheimer’s disease/dementia phenotype can capture known Alzheimer’s disease risk genes through rare variant aggregation. We generated a proxy Alzheimer’s disease/dementia phenotype for 148,508 unrelated individuals of European ancestry in the UK biobank in order to perform exome-wide rare variant aggregation analyses to identify genes associated with proxy Alzheimer’s disease/dementia. We identified four genes significantly associated with the proxy phenotype, three of which were significantly associated with proxy Alzheimer’s disease/dementia in an independent replication cohort consisting of 197,506 unrelated individuals of European ancestry in the UK biobank. All three of the replicated genes have been previously associated with clinically diagnosed Alzheimer’s disease (SORL1, TREM2, and TOMM40/APOE). We show that proxy Alzheimer’s disease/dementia can be used to identify genes associated with Alzheimer’s disease through rare variant aggregation. Nature Publishing Group UK 2023-02-07 /pmc/articles/PMC9905079/ /pubmed/36750708 http://dx.doi.org/10.1038/s41598-023-29108-8 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wightman, Douglas P.
Savage, Jeanne E.
de Leeuw, Christiaan A.
Jansen, Iris E.
Posthuma, Danielle
Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
title Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
title_full Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
title_fullStr Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
title_full_unstemmed Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
title_short Rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
title_sort rare variant aggregation in 148,508 exomes identifies genes associated with proxy dementia
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9905079/
https://www.ncbi.nlm.nih.gov/pubmed/36750708
http://dx.doi.org/10.1038/s41598-023-29108-8
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