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A comparison of anatomic and cellular transcriptome structures across 40 human brain diseases
Journal article   Open access   Peer reviewed

A comparison of anatomic and cellular transcriptome structures across 40 human brain diseases

Yashar G. Zeighami, Trygve E. A. Bakken, Thomas Nickl-Jockschat, Zeru Peterson, Anil G. S. Jegga, Jeremy A. Miller, Jay Schulkin, Alan C. Evans, Ed S. Lein and Michael Hawrylycz
PLoS biology, Vol.21(4), e3002058
04/20/2023
DOI: 10.1371/journal.pbio.3002058
PMCID: PMC10118126
PMID: 37079537
url
https://doi.org/10.1371/journal.pbio.3002058View
Published (Version of record) Open Access

Abstract

Genes associated with risk for brain disease exhibit characteristic expression patterns that reflect both anatomical and cell type relationships. Brain-wide transcriptomic patterns of disease risk genes provide a molecular-based signature, based on differential co-expression, that is often unique to that disease. Brain diseases can be compared and aggregated based on the similarity of their signatures which often associates diseases from diverse phenotypic classes. Analysis of 40 common human brain diseases identifies 5 major transcriptional patterns, representing tumor-related, neurodegenerative, psychiatric and substance abuse, and 2 mixed groups of diseases affecting basal ganglia and hypothalamus. Further, for diseases with enriched expression in cortex, single-nucleus data in the middle temporal gyrus (MTG) exhibits a cell type expression gradient separating neurodegenerative, psychiatric, and substance abuse diseases, with unique excitatory cell type expression differentiating psychiatric diseases. Through mapping of homologous cell types between mouse and human, most disease risk genes are found to act in common cell types, while having species-specific expression in those types and preserving similar phenotypic classification within species. These results describe structural and cellular transcriptomic relationships of disease risk genes in the adult brain and provide a molecular-based strategy for classifying and comparing diseases, potentially identifying novel disease relationships.
Biochemistry & Molecular Biology Biology Life Sciences & Biomedicine Life Sciences & Biomedicine - Other Topics Science & Technology

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