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

TLDR

Alzheimer’s disease affects half of Americans over 85, is universally fatal after about a decade of progressive cognitive decline, and although GWAS have identified ~33 risk genes, these loci explain only a minority of cases and provide limited predictive or mechanistic insight. The study aimed to generate a large, matched multi‑omics dataset from AD and control brains to uncover novel molecular mechanisms underlying the disease. Whole‑genome, whole‑exome, transcriptome, and proteome data were collected from 364 post‑mortem brains across multiple regions, with rigorous quality control, and linked to detailed clinical and pathophysiological information. Both raw and processed datasets are publicly available on the Synapse platform.

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.