Local dynamic spontaneous brain activity changes in first-episode, treatment-naïve patients with major depressive disorder and their associated gene expression profiles

Abstract

Background Major depressive disorder (MDD) is a common debilitating disorder characterized by impaired spontaneous brain activity, yet little is known about its alterations in dynamic properties and the molecular mechanisms associated with these changes. Methods Based on the resting-state functional MRI data of 65 first-episode, treatment-naïve patients with MDD and 66 healthy controls, we compared dynamic regional homogeneity (dReHo) of spontaneous brain activity between the two groups, and we investigated gene expression profiles associated with dReHo alterations in MDD by leveraging transcriptional data from the Allen Human Brain Atlas and weighted gene co-expression network analysis. Results Compared with healthy controls, patients with MDD consistently showed reduced dReHo in both fusiform gyri and in the right temporal pole and hippocampus. The expression profiles of 16 gene modules were correlated with dReHo alterations in MDD. These gene modules were enriched for various biological process terms, including immune, synaptic signalling, ion channels, mitochondrial function and protein metabolism, and were preferentially expressed in different cell types. Conclusions Patients with MDD have reduced dReHo in brain areas associated with emotional and cognitive regulation, and these changes may be related to complex polygenetic and polypathway mechanisms.

Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

“…Third, Fisher’s r -to- z transformation was applied for all DFC maps to improve the normality of the correlation distribution. Finally, the SD map across time windows was calculated in each subject to characterize the changes in individual ROI-to-whole-brain DFC, which is a commonly used metric in previous DFC studies ( Falahpour et al, 2016 ; Kaiser et al, 2016 ; Harlalka et al, 2019 ; Xue et al, 2020 ).…”

Classification of Obsessive-Compulsive Disorder Using Distance Correlation on Resting-State Functional MRI Images

“…The data were preprocessed by using the Statistical Parametric Mapping toolbox (SPM12, https://www.fil.ion.ucl.ac.uk/spm ) and the Data Processing Assistant for Resting-State fMRI (DPARSF version 4.4, http://rfmri.org/dpabi ; Shenas et al, 2013 , 2014 ). Image preprocessing consisted of: (1) removing first the 10-time points; (2) slicing timing correction; (3) realigning the time series of the images for each subject; (4) T1-weighted individual structural images by coregistered to the mean functional image; (5) the transformed structural images by segmented into gray matter, white matter, and cerebrospinal fluid; (6) based on these segmented images, using diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) (Ashburner, 2007 ) tool to estimate the normalization parameters from individual native space to the Montreal Neurological Institute (MNI) space (Xue et al, 2020 ); (7) the functional imaging data normalized to the MNI space by using these normalization parameters and resampling at 3 mm 3 × 3 mm 3 × 3 mm 3 ; (8) nuisance covariate regression (head motion parameters, white matter signal, and cerebrospinal fluid signal); (9) spatial smoothing with a 4-mm full-width half-maximum isotropic Gaussian kernel; (10) band-pass filtering (0.01–0.08 Hz); and (11) micro-head-motion correction according to framewise displacement (FD) by replacing the rs-fMRI volume with FD > 0.5 mm (nearest neighbor interpolation).…”

Altered Variability and Concordance of Dynamic Resting-State Functional Magnetic Resonance Imaging Indices in Patients With Major Depressive Disorder and Childhood Trauma

“…Regarding aberrant variability, Zhao, Lei and colleagues reported significantly decreased dynamic ALFF (dALFF) in the emotion network in depressed patients ( Zhao et al, 2021 ). Xue et al (2020) observed a consistently decreased dynamic regional homogeneity (dReHo) in patients with MDD in both fusiform gyri, the right temporal pole, and the hippocampus relative to healthy controls. Additionally, Zhang et al (2022) revealed the relationship between brain dynamic working patterns and chronic stress in adolescent MDD using the dynamic functional connectivity (FC) method.…”

“…A number of studies have captured the temporal dynamic patterns of intrinsic brain activity using the sliding window method. Evidence has indicated that aberrant variability and concordance of resting-state functional magnetic resonance imaging (R-fMRI) indices are related to the mechanisms underlying MDD ( Hutchison et al, 2013 ; Allen et al, 2014 ; Xue et al, 2020 ). Regarding aberrant variability, Zhao, Lei and colleagues reported significantly decreased dynamic ALFF (dALFF) in the emotion network in depressed patients ( Zhao et al, 2021 ).…”