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Study highlights major factors in shaping cross-disorder cortical abnormalities

Published on 10/08/22 at 09:50am

The study began by constructing maps of cortical abnormalities from thirteen neurodevelopmental, neurological, and psychiatric disorders. These maps came from 21,000 participants and 26,000 controls.

 

The study compared multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), and global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability), to cortical maps. This found a relationship between molecular vulnerability and white-matter architecture, and the cortical disorder profiles.

 

This study was the first to research the shared contributions of molecular and connectomic vulnerabilities to brain disorders in a multi-disorder framework. It allowed them to “systematically relate the effect of disease to multiple scales of organisation.” The study also states that:

 

“By taking a cross-modal and cross-disorder approach we reveal that, despite different clinical presentation and label, there exists some commonality across diseases including predictors that are ubiquitously important as well as interplay between local vulnerability and network structure.”

 

However, they acknowledge that in such a large-scale study, there is some obscurity in the inter-subject variability of the disorders, such as age and disease severity. To remedy this, they conducted supplementary analyses in which cortical disorder profiles were stratified by these variables. Differences were found in the strength of the contributions from molecular and connectomic influences. For example, molecular predictors become less powerful, and connectomic predictors more so, as Parkinson’s disease progresses.

 

The study also highlighted the need for further research into the subject of cross-disorder brain abnormalities, offering a focus in the direction of looking at disruptions in white-matter pathways instead of cortical thickness.

James Spargo

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