Deciphering cellular transcriptional alterations in Alzheimer’s disease brains

Molecular Neurodegeneration

Joseph S. Reddy¹  Julia E. Crook¹  Yan W. Asmann¹  Xue Wang¹  Zachary S. Quicksall¹  Shaoyu Li²  Kimberly G. Malphrus³  Minerva M. Carrasquillo³  Sarah J. Lincoln³  Dennis W. Dickson³  Thuy T. Nguyen³  Mariet Allen³  Troy P. Carnwath³  Tulsi A. Patel³  Nilüfer Ertekin-Taner⁴ 

[1] Department of Health Sciences Research, Mayo Clinic Florida, Jacksonville, FL, USA;Department of Mathematics and Statistics, University of North Carolina at Charlotte, Charlotte, NC, USA;Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA;Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA;Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, USA;

关键词: Alzheimer’s disease;    Gene expression;    Transcriptome;    RNA sequencing;    Deconvolution;    Cell-specific gene expression;    Neurodegeneration;    Bioinformatics;   

DOI  :  10.1186/s13024-020-00392-6

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY