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Quantitative MRI maps of human neocortex explored using cell type-specific gene expression analysis.

Luke J Edwards1, Peter McColgan1,2, Saskia Helbling1,3

  • 1Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, DE, Germany.

Cerebral Cortex (New York, N.Y. : 1991)
|December 15, 2022
PubMed
Summary
This summary is machine-generated.

Quantitative magnetic resonance imaging (qMRI) parameters correlate with specific neocortical cell types. This finding links qMRI to brain cytoarchitecture and cell distribution, advancing its use as a biomarker.

Keywords:
hMRIisocortexmagnetic resonance imagingmyelinrelaxometry

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Area of Science:

  • Neuroimaging
  • Neuroscience
  • Biomarker Discovery

Background:

  • Quantitative magnetic resonance imaging (qMRI) provides reproducible parameter maps but their biological substrates in the human neocortex are not well understood.
  • The complex cellular architecture of the neocortex presents challenges in linking qMRI metrics to specific cell types.

Purpose of the Study:

  • To investigate the associations between qMRI parameters (longitudinal relaxation rate R1, effective transverse relaxation rate R2*, and magnetization transfer saturation MTsat) and neocortical cell types in the human brain.
  • To explore the relationship between qMRI parameters and cell-type-specific gene expression data at 3T and 7T.

Main Methods:

  • Compared spatial distributions of qMRI parameters (R1, R2*, MTsat) with gene expression data from the Allen Human Brain Atlas.
  • Integrated gene expression data enriched in specific human brain cell types (neurons, astrocytes, endothelial cells, microglia, oligodendrocytes).
  • Analyzed MRI data acquired at both 3 Tesla (3T) and 7 Tesla (7T) to account for magnetic field strength dependency.

Main Results:

  • All qMRI parameters significantly covaried with genes enriched in GABAergic and glutamatergic neurons, indicating association with cytoarchitecture.
  • qMRI parameters showed significant covariation with genes enriched in astrocytes, endothelial cells, microglia, and oligodendrocytes/oligodendrocyte precursor cells, with specific associations varying by cell type and field strength.
  • R2* at 3T and R1 at 7T correlated with astrocytes; R1 and MTsat at 3T correlated with endothelial cells and microglia; R1 at 7T correlated with oligodendrocytes.

Conclusions:

  • qMRI parameters are associated with the distribution of major neocortical cell types, including neurons, astrocytes, endothelial cells, microglia, and oligodendrocytes.
  • These findings support the potential of qMRI parameters as in vivo biomarkers for specific cell types within the human neocortex.
  • The study highlights the utility of combining qMRI with gene expression data to bridge the gap between imaging metrics and biological substrates.