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

Minghui Wang(Icahn School of Medicine at Mount Sinai), Noam D. Beckmann(Icahn School of Medicine at Mount Sinai), Panos Roussos(Allen Institute for Brain Science), Erming Wang(Icahn School of Medicine at Mount Sinai), Xianxiao Zhou(Icahn School of Medicine at Mount Sinai), Qian Wang(Icahn School of Medicine at Mount Sinai), Ming Chen(Icahn School of Medicine at Mount Sinai), Ryan Neff(Icahn School of Medicine at Mount Sinai), Weiping Ma(Icahn School of Medicine at Mount Sinai), John F. Fullard(Allen Institute for Brain Science), Mads E. Hauberg(Allen Institute for Brain Science), Jaroslav Bendl(Allen Institute for Brain Science), Mette A. Peters(Sage Bionetworks), Ben Logsdon(Sage Bionetworks), Pei Wang(Icahn School of Medicine at Mount Sinai), Milind Mahajan(Icahn School of Medicine at Mount Sinai), Lara M. Mangravite(Sage Bionetworks), Eric B. Dammer(Emory University), Duc M. Duong(Emory University), James J. Lah(Emory University), Nicholas T. Seyfried(Emory University), Allan I. Levey(Emory University), Joseph D. Buxbaum(Allen Institute for Brain Science), Michelle E. Ehrlich(Icahn School of Medicine at Mount Sinai), Sam Gandy(The King's College), Pavel Katsel(The King's College), Vahram Haroutunian(The King's College), Eric E. Schadt(Icahn School of Medicine at Mount Sinai), Bin Zhang(Icahn School of Medicine at Mount Sinai)
Scientific Data
September 11, 2018
Cited by 599Open Access
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Abstract

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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