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

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.

Interleukin 9 alterations linked to alzheimer disease in african americans

“…Brain IL4RA and KIT Profiles in African Americans Support Th9 Polarization in AD Finally, we sought to replicate our findings in a separate clinicopathologic cohort of NC, MCI, and AD cases. 24 Proteomic analysis in the Mount Sinai cohort (26 African Americans, 180 Caucasians) did not detect IL-9 or any of the proteins in its network, consistent with our and others' experience that only abundant proteins are reproducibly detected using an untargeted approach. 28 Brain transcriptomic analysis on 7 genes previously implicated in the IL-9 network showed SPI1 (encoding PU.1, p = 0.030) to positively correlate with plaque burden independent of race, consistent with the brain IHC results from Emory for FIGURE 3: Immunohistochemistry of protein markers related to Th9 in postmortem brain tissue.…”

“…For comparison with an independent cohort, the publicly available proteomic and gene expression dataset from the Mount Sinai cohort (New York, NY) was analyzed because of its inclusion of African Americans (n = 26) and Caucasians (n = 180) with NC, MCI, and AD. 24 Because detailed plaque density was available, we performed linear regression analysis to examine whether race modified the relationship between neuritic plaque density and IL-9-related genes (including SPI1 for PU.1, IL4RA, IL33, TGFBR2, STAT6, SMAD3, and OX40 genes associated with Th9 differentiation; and KIT as a mast cell receptor; IL9 and TPSAB1 [for mast cell tryptase beta] mRNA were not detected). As TGFBR2 and IL4RA expression levels were already log-transformed, the ratio of TGFBR2 to IL4RA was calculated by deriving the difference between logtransformed values.…”

Molecular Networks and Key Regulators of the Dysregulated Neuronal System in Alzheimer’s Disease

“…This unique collection of multi-Omic LOAD data in tandem with the integrative network biology approaches allowed us to: 1) identify functional pathways dysregulated in LOAD with respect to multiple cognitive/neuropathological outcomes, 2) uncover and prioritize intrinsic co-expressed gene modules across a spectrum of disease stages of LOAD, 3) construct Bayesian probabilistic causal gene regulatory networks by integrating expression quantitative trait loci (eQTLs), transcription factor (TF) and gene expression data, 4) infer the key network hub genes driving key pathways of LOAD, and 5) validate the top ranked novel driver gene by characterizing its functional roles across human induced pluripotent stem cell (hiPSC)-derived neurons and fly models of LOAD ( Fig. 1A).. 6 The MSBB-AD cohort included 364 human brains accessed from the Mount Sinai/JJ Peters VA Medical Center Brain Bank 8,10,11 . The age at the time of death (AOD) of the present population ranged from 61 to 108 years, with a mean and standard deviation (s.d.)…”

“…1A). Details about the demographics of the study sample as well as data generation and quality control (QC) have been described previously 10 . Expanded details regarding the preprocessing of the RNA-seq data, including sample filtering, normalization and covariate correction, are provided in Supplementary Information (SI) (Fig.…”

Accumulated degeneration of transcriptional regulation contributes to disease development and detrimental clinical outcomes of Alzheimer’s disease

“…cognitive score and braak stages. Among them, approximately 61% were diagnosed as having pathological AD or probable AD (see Figure S1 for detailed clinical information) [27] . Specifically, 869 brainexpressed TFs were selected to study their regulatory status among these subjects (see Methods for detail).…”