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Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2
Alzheimer’s disease (AD) is a neurodegenerative disease that is clinically characterized by progressive cognitive decline. More than 200 pathogenic mutations have been identified in amyloid-β precursor protein (APP), presenilin 1 (PSEN1) and presenilin 2 (PSEN2). Additionally, common and rare varian...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236786/ https://www.ncbi.nlm.nih.gov/pubmed/32087291 http://dx.doi.org/10.1016/j.nbd.2020.104817 |
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author | Hsu, Simon Pimenova, Anna A. Hayes, Kimberly Villa, Juan A. Rosene, Matthew J. Jere, Madhavi Goate, Alison M. Karch, Celeste M. |
author_facet | Hsu, Simon Pimenova, Anna A. Hayes, Kimberly Villa, Juan A. Rosene, Matthew J. Jere, Madhavi Goate, Alison M. Karch, Celeste M. |
author_sort | Hsu, Simon |
collection | PubMed |
description | Alzheimer’s disease (AD) is a neurodegenerative disease that is clinically characterized by progressive cognitive decline. More than 200 pathogenic mutations have been identified in amyloid-β precursor protein (APP), presenilin 1 (PSEN1) and presenilin 2 (PSEN2). Additionally, common and rare variants occur within APP, PSEN1, and PSEN2 that may be risk factors, protective factors, or benign, non-pathogenic polymorphisms. Yet, to date, no single study has carefully examined the effect of all of the variants of unknown significance reported in APP, PSEN1 and PSEN2 on Aβ isoform levels in vitro. In this study, we analyzed Aβ isoform levels by ELISA in a cell-based system in which each reported pathogenic and risk variant in APP, PSEN1, and PSEN2 was expressed individually. In order to classify variants for which limited family history data is available, we have implemented an algorithm for determining pathogenicity using available information from multiple domains, including genetic, bioinformatic, and in vitro analyses. We identified 90 variants of unknown significance and classified 19 as likely pathogenic mutations. We also propose that five variants are possibly protective. In defining a subset of these variants as pathogenic, individuals from these families may eligible to enroll in observational studies and clinical trials. |
format | Online Article Text |
id | pubmed-7236786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-72367862021-06-01 Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 Hsu, Simon Pimenova, Anna A. Hayes, Kimberly Villa, Juan A. Rosene, Matthew J. Jere, Madhavi Goate, Alison M. Karch, Celeste M. Neurobiol Dis Article Alzheimer’s disease (AD) is a neurodegenerative disease that is clinically characterized by progressive cognitive decline. More than 200 pathogenic mutations have been identified in amyloid-β precursor protein (APP), presenilin 1 (PSEN1) and presenilin 2 (PSEN2). Additionally, common and rare variants occur within APP, PSEN1, and PSEN2 that may be risk factors, protective factors, or benign, non-pathogenic polymorphisms. Yet, to date, no single study has carefully examined the effect of all of the variants of unknown significance reported in APP, PSEN1 and PSEN2 on Aβ isoform levels in vitro. In this study, we analyzed Aβ isoform levels by ELISA in a cell-based system in which each reported pathogenic and risk variant in APP, PSEN1, and PSEN2 was expressed individually. In order to classify variants for which limited family history data is available, we have implemented an algorithm for determining pathogenicity using available information from multiple domains, including genetic, bioinformatic, and in vitro analyses. We identified 90 variants of unknown significance and classified 19 as likely pathogenic mutations. We also propose that five variants are possibly protective. In defining a subset of these variants as pathogenic, individuals from these families may eligible to enroll in observational studies and clinical trials. 2020-02-19 2020-06 /pmc/articles/PMC7236786/ /pubmed/32087291 http://dx.doi.org/10.1016/j.nbd.2020.104817 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) ). |
spellingShingle | Article Hsu, Simon Pimenova, Anna A. Hayes, Kimberly Villa, Juan A. Rosene, Matthew J. Jere, Madhavi Goate, Alison M. Karch, Celeste M. Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 |
title | Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 |
title_full | Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 |
title_fullStr | Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 |
title_full_unstemmed | Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 |
title_short | Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2 |
title_sort | systematic validation of variants of unknown significance in app, psen1 and psen2 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236786/ https://www.ncbi.nlm.nih.gov/pubmed/32087291 http://dx.doi.org/10.1016/j.nbd.2020.104817 |
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