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

Authors :
Yashar Zeighami
Trygve E. Bakken
Thomas Nickl-Jockschat
Zeru Peterson
Anil G. Jegga
Jeremy A. Miller
Jay Schulkin
Alan C. Evans
Ed S. Lein
Michael Hawrylycz
Source :
PLoS Biology, Vol 21, Iss 4 (2023)
Publication Year :
2023
Publisher :
Public Library of Science (PLoS), 2023.

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. Analysis of the transcription patterns of risk genes for human brain disease reveals characteristic expression signatures across brain anatomy; these can be used to compare and aggregate diseases, providing associations that often differ from conventional phenotypic classification.

Subjects

Subjects :
Biology (General)
QH301-705.5

Details

Language :
English
ISSN :
15449173 and 15457885
Volume :
21
Issue :
4
Database :
Directory of Open Access Journals
Journal :
PLoS Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.fb8faf585b084c3aa95ebfe9b0ed7a4b
Document Type :
article