Transcriptomics Improves Brain Disease Classification

Glowing Brain Slice Over Blue Background. Concept For Neurological Diseases, Tumors And Brain Surgery
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A better way to characterize neurologic disorders with transcriptomics has been described in a new study. A team examined disease transcriptomes—the set of RNA transcripts from affected brain regions—for 40 different brain diseases—and found they could classify brain diseases into five primary groups based on where disease-risk genes were active in the brain.

The study was published in PLOS Biology this week. The lead author is Yashar Zeighami at McGill University.

Neurologic conditions are a major cause of death and disability worldwide, accounting for about 33 deaths per 100,000 worldwide. These diseases are largely grouped into cerebrovascular, neurodegenerative, movement related, psychiatric disorders, developmental and congenital disorders, substance abuse disorders, brain tumors, and a set of other brain-related diseases.

This team’s work shows that comparing the transcriptomes related to different brain diseases can clarify mechanisms underlying the diseases, and why certain conditions are comorbid. This approach also found new relationships among diseases, which could have an impact on clinical treatment options.

“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,” says Zeighami.

Classifying brain diseases is difficult because many have multiple genetic and environmental risk factors. In addition, the symptoms of many brain diseases overlap. For example, Parkinson’s disease and Lewy body dementia are both neurodegenerative disorders presenting with muscle tremors and rigidity. They also share some similar cognitive and behavioral symptoms.

As a result of these overlaps, misdiagnoses occur that can impact patient care. Neurodegenerative, movement-related, and psychiatric neurologic disorders are the most difficult to diagnose both because of the overlap in symptoms and the fact that these change over time.

This team found they could classify brain diseases into five primary groups based on where disease-risk genes were active in the brain and in which cell types. These types were: tumor-related, neurodegenerative, psychiatric and substance abuse, and two mixed groups of diseases affecting basal ganglia and hypothalamus.

They write, “Transcriptomic relationships at a mesoscale, intermediate between the larger brain structures (e.g., cortex, hypothalamus) and those at cellular resolution, provide a framework and starting point for classifying broad disease associations in comparison with common phenotypic grouping.”

Starting with the Allen Human Brain Atlas ( they studied anatomic patterning and differential expression of the transcriptional patterns in the adult neurotypical brain of genes for 40 brain-related disorders across 104 structures from cortex, hippocampus, amygdala, basal ganglia, epithalamus, thalamus, ventral thalamus, hypothalamus, mesencephalon, cerebellum, pons, pontine nuclei, myelencephalon, ventricles, and white matter.

In addition to confirming known relationships among diseases, disease transcriptome analysis was able to find previously unknown relationships among diseases.

In one example: language development disorders, obsessive-compulsive disorder, and temporal lobe epilepsy were all classified into group 3, meaning that despite their very different symptoms, their corresponding genes are active in the same brain regions and in the same cell types.

The team noted that, “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.”

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