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A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease
Alzheimer’s disease (AD) is a looming public health disaster with limited interventions. Alzheimer’s is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecul...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104800/ https://www.ncbi.nlm.nih.gov/pubmed/37059743 http://dx.doi.org/10.1038/s41597-023-02057-7 |
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author | Merrihew, Gennifer E. Park, Jea Plubell, Deanna Searle, Brian C. Keene, C. Dirk Larson, Eric B. Bateman, Randall Perrin, Richard J. Chhatwal, Jasmeer P. Farlow, Martin R. McLean, Catriona A. Ghetti, Bernardino Newell, Kathy L. Frosch, Matthew P. Montine, Thomas J. MacCoss, Michael J. |
author_facet | Merrihew, Gennifer E. Park, Jea Plubell, Deanna Searle, Brian C. Keene, C. Dirk Larson, Eric B. Bateman, Randall Perrin, Richard J. Chhatwal, Jasmeer P. Farlow, Martin R. McLean, Catriona A. Ghetti, Bernardino Newell, Kathy L. Frosch, Matthew P. Montine, Thomas J. MacCoss, Michael J. |
author_sort | Merrihew, Gennifer E. |
collection | PubMed |
description | Alzheimer’s disease (AD) is a looming public health disaster with limited interventions. Alzheimer’s is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing. |
format | Online Article Text |
id | pubmed-10104800 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101048002023-04-16 A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease Merrihew, Gennifer E. Park, Jea Plubell, Deanna Searle, Brian C. Keene, C. Dirk Larson, Eric B. Bateman, Randall Perrin, Richard J. Chhatwal, Jasmeer P. Farlow, Martin R. McLean, Catriona A. Ghetti, Bernardino Newell, Kathy L. Frosch, Matthew P. Montine, Thomas J. MacCoss, Michael J. Sci Data Data Descriptor Alzheimer’s disease (AD) is a looming public health disaster with limited interventions. Alzheimer’s is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing. Nature Publishing Group UK 2023-04-14 /pmc/articles/PMC10104800/ /pubmed/37059743 http://dx.doi.org/10.1038/s41597-023-02057-7 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 | Data Descriptor Merrihew, Gennifer E. Park, Jea Plubell, Deanna Searle, Brian C. Keene, C. Dirk Larson, Eric B. Bateman, Randall Perrin, Richard J. Chhatwal, Jasmeer P. Farlow, Martin R. McLean, Catriona A. Ghetti, Bernardino Newell, Kathy L. Frosch, Matthew P. Montine, Thomas J. MacCoss, Michael J. A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease |
title | A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease |
title_full | A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease |
title_fullStr | A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease |
title_full_unstemmed | A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease |
title_short | A peptide-centric quantitative proteomics dataset for the phenotypic assessment of Alzheimer’s disease |
title_sort | peptide-centric quantitative proteomics dataset for the phenotypic assessment of alzheimer’s disease |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10104800/ https://www.ncbi.nlm.nih.gov/pubmed/37059743 http://dx.doi.org/10.1038/s41597-023-02057-7 |
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