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The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease

Alzheimer’s disease (AD) affects half the US population over the age of 85 and is universally fatal following an average course of 10 years of progressive cognitive disability. Genetic and genome-wide association studies (GWAS) have identified about 33 risk factor genes for common, late-onset AD (LO...

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Autores principales: Wang, Minghui, Beckmann, Noam D., Roussos, Panos, Wang, Erming, Zhou, Xianxiao, Wang, Qian, Ming, Chen, Neff, Ryan, Ma, Weiping, Fullard, John F., Hauberg, Mads E., Bendl, Jaroslav, Peters, Mette A., Logsdon, Ben, Wang, Pei, Mahajan, Milind, Mangravite, Lara M., Dammer, Eric B., Duong, Duc M., Lah, James J., Seyfried, Nicholas T., Levey, Allan I., Buxbaum, Joseph D., Ehrlich, Michelle, Gandy, Sam, Katsel, Pavel, Haroutunian, Vahram, Schadt, Eric, Zhang, Bin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132187/
https://www.ncbi.nlm.nih.gov/pubmed/30204156
http://dx.doi.org/10.1038/sdata.2018.185
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author Wang, Minghui
Beckmann, Noam D.
Roussos, Panos
Wang, Erming
Zhou, Xianxiao
Wang, Qian
Ming, Chen
Neff, Ryan
Ma, Weiping
Fullard, John F.
Hauberg, Mads E.
Bendl, Jaroslav
Peters, Mette A.
Logsdon, Ben
Wang, Pei
Mahajan, Milind
Mangravite, Lara M.
Dammer, Eric B.
Duong, Duc M.
Lah, James J.
Seyfried, Nicholas T.
Levey, Allan I.
Buxbaum, Joseph D.
Ehrlich, Michelle
Gandy, Sam
Katsel, Pavel
Haroutunian, Vahram
Schadt, Eric
Zhang, Bin
author_facet Wang, Minghui
Beckmann, Noam D.
Roussos, Panos
Wang, Erming
Zhou, Xianxiao
Wang, Qian
Ming, Chen
Neff, Ryan
Ma, Weiping
Fullard, John F.
Hauberg, Mads E.
Bendl, Jaroslav
Peters, Mette A.
Logsdon, Ben
Wang, Pei
Mahajan, Milind
Mangravite, Lara M.
Dammer, Eric B.
Duong, Duc M.
Lah, James J.
Seyfried, Nicholas T.
Levey, Allan I.
Buxbaum, Joseph D.
Ehrlich, Michelle
Gandy, Sam
Katsel, Pavel
Haroutunian, Vahram
Schadt, Eric
Zhang, Bin
author_sort Wang, Minghui
collection PubMed
description Alzheimer’s disease (AD) affects half the US population over the age of 85 and is universally fatal following an average course of 10 years of progressive cognitive disability. Genetic and genome-wide association studies (GWAS) have identified about 33 risk factor genes for common, late-onset AD (LOAD), but these risk loci fail to account for the majority of affected cases and can neither provide clinically meaningful prediction of development of AD nor offer actionable mechanisms. This cohort study generated large-scale matched multi-Omics data in AD and control brains for exploring novel molecular underpinnings of AD. Specifically, we generated whole genome sequencing, whole exome sequencing, transcriptome sequencing and proteome profiling data from multiple regions of 364 postmortem control, mild cognitive impaired (MCI) and AD brains with rich clinical and pathophysiological data. All the data went through rigorous quality control. Both the raw and processed data are publicly available through the Synapse software platform.
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spelling pubmed-61321872018-09-17 The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease Wang, Minghui Beckmann, Noam D. Roussos, Panos Wang, Erming Zhou, Xianxiao Wang, Qian Ming, Chen Neff, Ryan Ma, Weiping Fullard, John F. Hauberg, Mads E. Bendl, Jaroslav Peters, Mette A. Logsdon, Ben Wang, Pei Mahajan, Milind Mangravite, Lara M. Dammer, Eric B. Duong, Duc M. Lah, James J. Seyfried, Nicholas T. Levey, Allan I. Buxbaum, Joseph D. Ehrlich, Michelle Gandy, Sam Katsel, Pavel Haroutunian, Vahram Schadt, Eric Zhang, Bin Sci Data Data Descriptor Alzheimer’s disease (AD) affects half the US population over the age of 85 and is universally fatal following an average course of 10 years of progressive cognitive disability. Genetic and genome-wide association studies (GWAS) have identified about 33 risk factor genes for common, late-onset AD (LOAD), but these risk loci fail to account for the majority of affected cases and can neither provide clinically meaningful prediction of development of AD nor offer actionable mechanisms. This cohort study generated large-scale matched multi-Omics data in AD and control brains for exploring novel molecular underpinnings of AD. Specifically, we generated whole genome sequencing, whole exome sequencing, transcriptome sequencing and proteome profiling data from multiple regions of 364 postmortem control, mild cognitive impaired (MCI) and AD brains with rich clinical and pathophysiological data. All the data went through rigorous quality control. Both the raw and processed data are publicly available through the Synapse software platform. Nature Publishing Group 2018-09-11 /pmc/articles/PMC6132187/ /pubmed/30204156 http://dx.doi.org/10.1038/sdata.2018.185 Text en Copyright © 2018, The Author(s) http://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/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
spellingShingle Data Descriptor
Wang, Minghui
Beckmann, Noam D.
Roussos, Panos
Wang, Erming
Zhou, Xianxiao
Wang, Qian
Ming, Chen
Neff, Ryan
Ma, Weiping
Fullard, John F.
Hauberg, Mads E.
Bendl, Jaroslav
Peters, Mette A.
Logsdon, Ben
Wang, Pei
Mahajan, Milind
Mangravite, Lara M.
Dammer, Eric B.
Duong, Duc M.
Lah, James J.
Seyfried, Nicholas T.
Levey, Allan I.
Buxbaum, Joseph D.
Ehrlich, Michelle
Gandy, Sam
Katsel, Pavel
Haroutunian, Vahram
Schadt, Eric
Zhang, Bin
The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
title The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
title_full The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
title_fullStr The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
title_full_unstemmed The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
title_short The Mount Sinai cohort of large-scale genomic, transcriptomic and proteomic data in Alzheimer's disease
title_sort mount sinai cohort of large-scale genomic, transcriptomic and proteomic data in alzheimer's disease
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6132187/
https://www.ncbi.nlm.nih.gov/pubmed/30204156
http://dx.doi.org/10.1038/sdata.2018.185
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