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Understanding the transcriptional (dys)regulation in progressive supranuclear palsy
Author(s) -
Min Yuhao,
Wang Xue,
Reddy Joseph S.,
Nguyen Thuy,
Malphrus Kimberly G.,
Crook Julia E.,
Carrasquillo Minerva M.,
Dickson Dennis W,
Allen Mariet,
ErtekinTaner Nilufer
Publication year - 2021
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.050985
Subject(s) - transcriptome , progressive supranuclear palsy , biology , endophenotype , gene expression , gene , computational biology , cell type , proteome , neuroscience , gene regulatory network , genetics , cell , atrophy , cognition
Background Progressive Supranuclear Palsy (PSP) is an incurable, neurodegenerative parkinsonian disorder characterized by tau proteinopathy in multiple brain cell types. We previously reported global gene expression changes associated with neuropathologic endophenotypes in PSP. In this study, we expanded this work to brain RNA sequence (RNAseq) transcriptome data from two independent cohorts and assessed both bulk and analytically deconvoluted transcriptome integrated with other omics data from humans and mice to discover dysregulated genes and networks in PSP. Method Transcriptome was measured in 408 temporal cortex samples from two independent cohorts of PSP and control brains, all of which had quantitative neuropathology scores. Differentially expressed genes (DEG) were identified using both bulk and analytically deconvoluted transcriptome for each brain cell type. Weighted Gene Co‐expression Network Analysis (WGCNA) was used to construct modules, which were annotated for enrichment of Gene Ontology terms and cell type markers. We sought validations using a multitude of complementary datasets, including PSP GWAS, eQTL, proteome data and tau transgenic mouse models. Results There were 22,560 genes detected in both cohorts of which 1,709 were significantly differentially expressed. Among the DEGs, 721 genes also had nominal associations with one or more neuropathology endophenotypes. Additionally, 104 of the bulk DEGs were also differentially expressed in one of the brain cell types, i.e. were cell‐intrinsic DEGs (CI‐DEGs). There were 23 co‐expression network modules, 10 of which were enriched for brain cell type markers; 8 of these also demonstrated enrichment of CI‐DEGs of the corresponding cell‐type. Importantly, 3 of these 8 modules also associated with PSP diagnosis. The most significant modules were enriched for oligodendrocyte and astrocyte genes and CI‐DEGs. Most notably, we identified one module with enrichment of oligodendrocyte gene markers that are likewise downregulated in PSP. This module was also enriched with myelin gene expression changes identified in oligodendrocyte CI‐DEGs. Conclusion The expression profile of PSP brain changes in a cell‐specific manner. Astrocyte and oligodendrocyte gene expression appears most impacted in PSP. Our findings implicate novel genes and pathways which underlie disease risk and neuropathology in PSP and may serve as novel therapeutic and biomarker targets.