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Related Concept Videos

Brain Imaging01:14

Brain Imaging

282
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
282

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Imaging Transcriptomics of Brain Disorders.

Aurina Arnatkeviciute1, Ben D Fulcher2, Mark A Bellgrove1

  • 1Turner Institute for Brain and Mental Health, School of Psychological Science, Monash University, Melbourne, Victoria, Australia.

Biological Psychiatry Global Open Science
|November 3, 2022
PubMed
Summary
This summary is machine-generated.

Neuroimaging combined with gene expression atlases reveals brain disorder mechanisms. This approach links spatial gene variations to brain changes in development and neurodegeneration, aiding disease research.

Keywords:
Brain imagingConnectomeGene expressionNeurodegenerationNeurodevelopmentPsychiatric disorders

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Area of Science:

  • Neuroscience
  • Genomics
  • Brain Imaging

Background:

  • Noninvasive neuroimaging quantifies brain structure and function but offers indirect measures of pathology.
  • Gene expression atlases provide a new avenue for understanding the molecular basis of brain phenotypes.

Purpose of the Study:

  • To provide an overview of imaging transcriptomics methods.
  • To outline the application of these methods in understanding neurodevelopmental, adult, and neurodegenerative brain disorders.
  • To explore the link between gene expression and neuroimaging phenotypes.

Main Methods:

  • Integration of noninvasive neuroimaging data with anatomically comprehensive gene expression atlases.
  • Analysis of spatial variations in gene expression in relation to brain structure and function.
  • Utilizing ex vivo patient brain data and modeling studies to investigate disease mechanisms.

Main Results:

  • Spatial gene expression variations correlate with normative brain maturation and neurodegeneration.
  • Transcriptional correlates of disorder-related neuroimaging phenotypes align with ex vivo findings.
  • Gene expression patterns influence regional vulnerability and disease spread in neurodegeneration.

Conclusions:

  • Imaging transcriptomics offers a powerful framework for evaluating pathophysiological hypotheses in brain disorders.
  • Transcriptional atlases are valuable for testing molecular mechanisms underlying neuroimaging changes.
  • This approach enhances our understanding of the molecular drivers of brain diseases.