Abstract

Whereas meta-analytical data highlight abnormal frontocortical macrostructure (thickness/surface area/volume) in Major Depressive Disorder (MDD), the underlying microstructural processes remain uncharted, due to the use of conventional MRI scanners and acquisition techniques. We uniquely combined Ultra-High Field MRI at 7.0 Tesla with Quantitative Imaging to map intracortical myelin (proxied by longitudinal relaxation time T1) and iron concentration (proxied by transverse relaxation time T2*), microstructural processes deemed particularly germane to cortical macrostructure. Informed by meta-analytical evidence, we focused specifically on orbitofrontal and rostral anterior cingulate cortices among adult MDD patients (N = 48) and matched healthy controls (HC; N = 10). Analyses probed the association of MDD diagnosis and clinical profile (severity, medication use, comorbid anxiety disorders, childhood trauma) with aforementioned microstructural properties. MDD diagnosis (p’s < 0.05, Cohen’s D = 0.55–0.66) and symptom severity (p’s < 0.01, r = 0.271–0.267) both related to decreased intracortical myelination (higher T1 values) within the lateral orbitofrontal cortex, a region tightly coupled to processing negative affect and feelings of sadness in MDD. No relations were found with local iron concentrations. These findings allow uniquely fine-grained insights on frontocortical microstructure in MDD, and cautiously point to intracortical demyelination as a possible driver of macroscale cortical disintegrity in MDD.

Details

Title
Quantitative MRI at 7-Tesla reveals novel frontocortical myeloarchitecture anomalies in major depressive disorder
Author
Heij, Jurjen 1 ; van der Zwaag, Wietske 2 ; Knapen, Tomas 1 ; Caan, Matthan W. A. 3 ; Forstman, Birte 4 ; Veltman, Dick J. 5 ; van Wingen, Guido 6 ; Aghajani, Moji 7   VIAFID ORCID Logo 

 Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands (GRID:grid.458380.2) (ISNI:0000 0004 0368 8664); NIN, Department of Computational Cognitive Neuroscience and Neuroimaging, Amsterdam, The Netherlands (GRID:grid.419918.c) (ISNI:0000 0001 2171 8263); Vrije Universiteit Amsterdam, Department of Experimental and Applied Psychology, Amsterdam, The Netherlands (GRID:grid.12380.38) (ISNI:0000 0004 1754 9227) 
 Spinoza Centre for Neuroimaging, Amsterdam, The Netherlands (GRID:grid.458380.2) (ISNI:0000 0004 0368 8664); NIN, Department of Computational Cognitive Neuroscience and Neuroimaging, Amsterdam, The Netherlands (GRID:grid.419918.c) (ISNI:0000 0001 2171 8263) 
 Amsterdam UMC, Location University of Amsterdam, Department of Biomedical Engineering and Physics, Amsterdam, The Netherlands (GRID:grid.509540.d) (ISNI:0000 0004 6880 3010) 
 University of Amsterdam, Department of Brain & Cognition, Amsterdam, The Netherlands (GRID:grid.7177.6) (ISNI:0000 0000 8499 2262) 
 Amsterdam UMC, Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands (GRID:grid.509540.d) (ISNI:0000 0004 6880 3010) 
 Amsterdam UMC, Location University of Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands (GRID:grid.509540.d) (ISNI:0000 0004 6880 3010) 
 Amsterdam UMC, Location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam, The Netherlands (GRID:grid.509540.d) (ISNI:0000 0004 6880 3010); Leiden University, Institute of Education and Child Studies, Section Forensic Family & Youth Care, Leiden, The Netherlands (GRID:grid.5132.5) (ISNI:0000 0001 2312 1970) 
Pages
262
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
21583188
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3070126598
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.