In a study published in PLoS Biology last month, Dr. Yashar Zeighami and collaborators compared the way genes are expressed in different brain diseases to see if they could identify patterns that would help classify and compare the diseases. They found that genes associated with brain diseases have unique patterns of expression that reflect both where they are in the brain and what type of cells they are in. These patterns can be used to group diseases together based on similarities in their gene expression. The study identified five main groups of diseases, such as tumors, neurodegenerative diseases, and psychiatric illnesses. By studying these gene expression patterns, researchers hope to gain a better understanding of brain diseases and potentially discover new relationships between them.
Dr. Zeighami and his colleagues explored the transcriptomic patterns of risk genes associated with 40 common human brain diseases. These patterns reflect both anatomical and cell type relationships, providing a molecular-based signature for each disease. Through the analysis of brain-wide transcriptomic patterns, the diseases can be compared and aggregated based on the similarity of their signatures.
The study identified 5 major transcriptional patterns representing tumor-related, neurodegenerative, psychiatric and substance abuse, and 2 mixed groups of diseases affecting basal ganglia and hypothalamus.
“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.” — Dr. Yashar Zeighami, lead author
Further analysis of diseases with enriched expression in cortex showed a cell type expression gradient separating neurodegenerative, psychiatric, and substance abuse diseases, with unique excitatory cell type expression differentiating psychiatric diseases, notably autism, schizophrenia, and bipolar disorder (figure).
Most disease risk genes were found to act in common cell types through mapping of homologous cell types between mouse and human. However, these genes exhibited species-specific expression in those types while preserving similar phenotypic classification within species.
These findings provide a molecular-based strategy for classifying and comparing diseases, potentially identifying novel disease relationships. They also offer insight into the structural and cellular transcriptomic relationships of disease risk genes in the adult brain. Overall, gene activity analysis has the potential to revolutionize our understanding and treatment of brain diseases. By providing more detailed information about the underlying biology of these diseases, this approach can help to develop more effective and personalized treatments for patients.
Read the full article here in Open Access: “A comparison of anatomic and cellular transcriptome structures across 40 human brain diseases” by Yashar Zeighami et al. PLOS Biology