Abstract
Large-scale brain bulk-RNAseq studies identified molecular pathways implicated in Alzheimer’s disease (AD), however these findings can be confounded by cellular composition changes in bulk-tissue. To identify cell intrinsic gene expression alterations of individual cell types, we designed a bioinformatics pipeline and analyzed three AD and control bulk-RNAseq datasets of temporal and dorsolateral prefrontal cortex from 685 brain samples. We detected cell-proportion changes in AD brains that are robustly replicable across the three independently assessed cohorts. We applied three different algorithms including our in-house algorithm to identify cell intrinsic differentially expressed genes in individual cell types (CI-DEGs). We assessed the performance of all algorithms by comparison to single nucleus RNAseq data. We identified consensus CI-DEGs that are common to multiple brain regions. Despite significant overlap between consensus CI-DEGs and bulk-DEGs, many CI-DEGs were absent from bulk-DEGs. Consensus CI-DEGs and their enriched GO terms include genes and pathways previously implicated in AD or neurodegeneration, as well as novel ones. We demonstrated that the detection of CI-DEGs through computational deconvolution methods is promising and highlight remaining challenges. These findings provide novel insights into cell-intrinsic transcriptional changes of individual cell types in AD and may refine discovery and modeling of molecular targets that drive this complex disease.
Highlights
Alzheimer’s disease (AD) is a neurodegenerative disease that affects ~ 5.7 million patients with annual cost of more than $230 billion in the US [1]
Cellular composition in three brain cohorts from two brain regions We analyzed three cohorts each consisting of postmortem brains from AD and control subjects (Table S1), namely the Rush Religious Orders Study and Memory and Aging Project dorsolateral prefrontal cortex (DLPFC) [7, 8], Mayo Clinic temporal cortex (TCX-Mayo) [4, 12], and Mount Sinai VA Medical Center Brain Bank temporal cortex (TCX-MSBB) [18]
We identified consensus cellintrinsic transcriptional alterations (CI-Differentially expressed genes (DEGs)) in AD, which are conserved across cohorts and brain regions
Summary
Alzheimer’s disease (AD) is a neurodegenerative disease that affects ~ 5.7 million patients with annual cost of more than $230 billion in the US [1]. Transcriptome-wide expression levels have been analyzed from bulk brain tissue of hundreds. We expect that identifying cell-intrinsic differentially expressed genes (CI-DEGs) of individual CNS cell types will reveal novel insights into the genes and pathways that could potentially identify drug targets and lead to AD therapeutics. This approach circumvents the influence of cell-composition changes that can impact disease associated DEGs obtained from bulk tissue transcriptome analysis. There exist large-scale bulk brain RNAseq datasets [5, 8, 12], which can be leveraged to identify CI-DEGs through analytic deconvolution of bulk tissue expression into signals of individual cell types by using cell proportions or their proxies [13, 14]
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