Abnormal structural covariance network in major depressive disorder: Evidence from the REST-meta-MDD project

Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices. Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations. VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network. Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.

BackgroundIt is difficult to make a precise diagnosis to distinguish patients with Major Depressive Disorder (MDD) from patients with Bipolar Depressive Disorder (current depressive episode, BD). This study will explore the difference in time perception between MDD and BD using a temporal bisection task.MethodsIn this temporal bisection task, 30 MDD patients, 30 BD patients, and 30 healthy controls (HC) had to categorize a signal duration, between 400 and 1600 milliseconds (ms), as either short or long. A repeated measurement analysis of variance with 3 (subject type) × 7 (time interval) was performed on the long response ratio with Bonferroni correction for multiple comparisons. Origin software was used to calculate the subjective bisection point (BP), difference limen (DL), and Weber ratio (WR). The Hamilton Depression Rating Scale for depression-17 was used to assess depressive symptoms in the patients.ResultsThe data showed that the interaction effect between subject type and duration was significant (F(6,498) = 4.656, p <0.001, η2p = 0.101). At 400 ms, and the long response of the MDD group was greater than HC group (p<0.017, Bonferroni-corrected). At 1200, 1400 and 1600 ms, the long response of BD group is smaller than HC group, (p<0.017, Bonferroni-corrected). The one-way ANOVA revealed significant difference among the HC, MDD and BD groups in the BP values WR values, F(2, 81) = 3.462, p = 0.036 vs. F(2, 81) = 3.311, p = 0.042. Post-hoc tests showed that the value of BP in the MDD group was less than BD group (p = 0.027) and the value of BP in the MDD group was less than HC group (p = 0.027), while there was not significant difference of BP values between BD group and HC group. The WR values in MDD group larger than the HC group (p = 0.022).LimitationsSeverity of depression not divided and analyzed according to the Hamilton Depression Rating Scale score.ConclusionThe time perception of the MDD and BD groups was different from that of the HC group, they overestimated short time periods. Compared with the BD group, the MDD group had a smaller time bisector, and these patients felt that time passed more slowly. The time sensitivity of MDD group and BD group were less than the HC group. However, there was no statistical difference in time sensitivity between the MDD and BD groups.

Response to Dr Fried & Dr Kievit, and Dr Malhi et al.

Executive function impairments, particularly in inhibition and cognitive flexibility/shifting, are core features of major depressive disorder (MDD) yet marked interindividual heterogeneity has hindered the identification of reliable brain-based biomarkers. This study aimed to use individualized structural covariance networks (SCNs) analysis, a novel approach reflecting interregional covariation within subjects to characterize the individual differences in brain architecture related to inhibition and shifting ability in first-episode drug-naïve (FEDN) MDD patients. Individualized SCNs were constructed for 283 patients and 81 healthy controls (HCs) using the Brainnetome Atlas, combining probability density estimation and Kullback-Leibler divergence based on regional gray matter volumes. Global and nodal topological properties were estimated. In both MDD and HCs, inhibition-shifting was significantly associated with global and local efficiency and small-worldness. In MDD group, the betweenness centrality of middle frontal gyrus, precentral gyrus, and inferior temporal gyrus were associated with poorer inhibition-shifting, and those of thalamus, cingulate gyrus and inferior frontal gyrus were associated with better inhibition-shifting function. No significant associations between inhibition-shifting and nodal centrality were observed in HCs. These results suggest recruitment of thalamo-cingulate regions in compensation for frontal-temporal organizations affecting inhibition-shifting in FEDN MDD. The individual SCNs may help identify biomarkers for specific executive function in MDD.

Major depressive disorder (MDD) is highly heterogeneous, with marked individual differences in clinical presentation and neurobiology, which may obscure identification of structural brain abnormalities in MDD. To explore this, we used normative modeling to index regional patterns of variability in cortical thickness (CT) across individual patients. To use normative modeling in a large dataset from the ENIGMA MDD consortium to obtain individualised CT deviations from the norm (relative to age, sex and site) and examine the relationship between these deviations and clinical characteristics. A normative model adjusting for age, sex and site effects was trained on 35 CT measures from FreeSurfer parcellation of 3,181 healthy controls (HC) from 34 sites (40 scanners). Individualised z-score deviations from this norm for each CT measure were calculated for a test set of 2,119 HC and 3,645 individuals with MDD. For each individual, each CT z-score was classified as being within the normal range (95% of individuals) or within the extreme range (2.5% of individuals with the thinnest or thickest cortices). Z-score deviations of CT measures of MDD individuals as estimated from a normative model based on HC. Z-score distributions of CT measures were largely overlapping between MDD and HC (minimum 92%, range 92-98%), with overall thinner cortices in MDD. 34.5% of MDD individuals, and 30% of HC individuals, showed an extreme deviation in at least one region, and these deviations were widely distributed across the brain. There was high heterogeneity in the spatial location of CT deviations across individuals with MDD: a maximum of 12% of individuals with MDD showed an extreme deviation in the same location. Extreme negative CT deviations were associated with having an earlier onset of depression and more severe depressive symptoms in the MDD group, and with higher BMI across MDD and HC groups. Extreme positive deviations were associated with being remitted, of not taking antidepressants and less severe symptoms. Our study illustrates a large heterogeneity in the spatial location of CT abnormalities across patients with MDD and confirms a substantial overlap of CT measures with HC. We also demonstrate that individualised extreme deviations can identify protective factors and individuals with a more severe clinical picture.

Unidirectionally affected causal connectivity of cortico-limbic-cerebellar circuit by structural deficits in drug-naive major depressive disorder

Several lines of evidence support the involvement of transcriptomic and epigenetic mechanisms in the brain structural deficits of major depressive disorder (MDD) separately. However, research in these two areas has remained isolated. In this study, we proposed an integrative strategy that combined neuroimaging, brain-wide gene expression, and peripheral DNA methylation data to investigate the genetic basis of gray matter abnormalities in MDD. The MRI T1-weighted images and Illumina 850 K DNA methylation microarrays were obtained from 269 patients and 416 healthy controls, and brain-wide transcriptomic data were collected from Allen Human Brain Atlas. The between-group differences in gray matter volume (GMV) and differentially methylated CpG positions (DMPs) were examined. The genes with their expression patterns spatially related to GMV changes and genes with DMPs were overlapped and selected. Using principal component regression, the associations between DMPs in overlapped genes and GMV across individual patients were investigated, and the region-specific correlations between methylation status and gene expression were examined. We found significant associations between the decreased GMV and DMPs methylation status in the anterior cingulate cortex, inferior frontal cortex, and fusiform face cortex regions. These DMPs genes were primarily enriched in the neurodevelopmental and synaptic transmission process. There was a significant negative correlation between DNA methylation and gene expression in genes associated with GMV changes of the frontal cortex in MDD. Our findings suggest that GMV abnormalities in MDD may have a transcriptomic and epigenetic basis. This imaging-transcriptomic-epigenetic integrative analysis provides spatial and biological links between cortical morphological deficits and peripheral epigenetic signatures in MDD.

Identifying Subgroups of Major Depressive Disorder Using Brain Structural Covariance Networks and Mapping of Associated Clinical and Cognitive Variables

BackgroundMajor depressive disorder (MDD) is known to be characterized by altered brain functional connectivity (FC) patterns. However, whether and how the features of dynamic FC would change in patients with MDD are unclear. In this study, we aimed to characterize dynamic FC in MDD using a large multi-site sample and a novel dynamic network-based approach.MethodsResting-state functional magnetic resonance imaging (fMRI) data were acquired from a total of 460 MDD patients and 473 healthy controls, as a part of the REST-meta-MDD consortium. Resting-state dynamic functional brain networks were constructed for each subject by a sliding-window approach. Multiple spatio-temporal features of dynamic brain networks, including temporal variability, temporal clustering and temporal efficiency, were then compared between patients and healthy subjects at both global and local levels.ResultsThe group of MDD patients showed significantly higher temporal variability, lower temporal correlation coefficient (indicating decreased temporal clustering) and shorter characteristic temporal path length (indicating increased temporal efficiency) compared with healthy controls (corrected p < 3.14×10−3). Corresponding local changes in MDD were mainly found in the default-mode, sensorimotor and subcortical areas. Measures of temporal variability and characteristic temporal path length were significantly correlated with depression severity in patients (corrected p < 0.05). Moreover, the observed between-group differences were robustly present in both first-episode, drug-naïve (FEDN) and non-FEDN patients.ConclusionsOur findings suggest that excessive temporal variations of brain FC, reflecting abnormal communications between large-scale bran networks over time, may underlie the neuropathology of MDD.

BackgroundResting state functional connectivity analysis has a potential to unearth the putative neuronal underpinnings of various disorders of the brain. Major depressive disorder (MDD) has been regarded as a disorder arising out alterations in functional networks in the brain.Aims & ObjectivesThere is paucity of literature on resting state functional MRI (Rs-fMRI) in major depressive disorder (MDD), especially from the Indian subcontinent. The purpose of our study was to elucidate the differences in Rs-fMRI connectivity between MDD patients and age and gender matched healthy controls (HC).MethodIn this prospective single-institute based study, the patients were recruited consecutively based on Hamilton depression rating scale (HAM-D). Age and gender matched healthy controls were also recruited. Rs-fMRI and anatomical MRI images were acquired for all the subjects (MDD and HC group) and subsequent analysis was done using the CONN toolbox. A total of 49 subjects were included in the final analysis (MDD = 28 patients, HC = 21 healthy controls). HAM-D score was noted to be 24.4±4.8 in the MDD group. There was no significant difference between MDD and HC groups as far as age, gender, employment status and level of education is concerned. Region-of-interest based analysis of Rs-fMRI data showed a significantly lower connectivity between the left insula and left nucleus accumbens and between left paracingulate gyrus and bilateral posterior middle temporal gyri in MDD group as compared to HC group.ResultsA total of 49 subjects were included in the final analysis (MDD = 28 patients, HC = 21 healthy controls). HAM-D score was noted to be 24.4±4.8 in the MDD group. There was no significant difference between MDD and HC groups as far as age, gender, employment status and level of education is concerned. Region-of-interest based analysis of Rs-fMRI data showed a significantly lower connectivity between the left insula and left nucleus accumbens and between left paracingulate gyrus and bilateral posterior middle temporal gyri in MDD group as compared to HC group.Discussion & ConclusionsThere is reduced connectivity between certain key regions of the brain in MDD patients, i.e., between the left insular cortex and left nucleus accumbens and between left paracingulate gyrus and bilateral posterior middle temporal gyrus. These findings could explain the basis of clinical features of MDD such as anhedonia, rumination of thoughts, reduced visuo-spatial comprehension, reduced language function and response to external stimuli.

Major depressive disorder (MDD) is a psychiatric disorder with a relatively limited response to treatment. It is necessary to better understand the neuroanatomical mechanisms of structural networks. The current study recruited 181 first-onset, untreated adult MDD patients: slight MDD (SD, N = 23), moderate MDD (MD, N = 77), Heavy MDD (HD, N = 81) groups; along with a healthy control group (HC, N = 81) with matched general clinical data. FreeSurfer was used to preprocess T1 images for gray matter volume (GMV), and the default mode network (DMN) and the execution control network (ECN) were analyzed by structural covariance network (SCN). Present study found that the GMV of brain regions reduced with the severity of the disease. Specifically, the GMV of the left anterior cingulate gyrus (ACC.L) is negatively correlated with MDD severity. In addition, the SCN connectivity of the whole-brain network increases with the increase of severity in MDD. ACC.L is a key brain region with increased connectivity between the left orbitofrontal in DMN and between the right orbitofrontal in ECN, which leads to damage to the balance of neural circuits. Patients with smaller GMV of ACC.L are more likely to develop severe MDD, and as a key region in both networks which have distinct structural network models in DMN and ECN. MDD patients with different severity have different neuroimaging changes in DMN and ECN.

Common and distinct abnormal frontal-limbic system structural and functional patterns in patients with major depression and bipolar disorder

The present study investigated the usefulness of evaluating the existence of volume reduction in brain regions using voxel-based morphometry (VBM) to dissociate major depressive disorder (MDD) from bipolar disorder (BD). This study enrolled 92 individuals with MDD, 32 individuals with BD, and 43 healthy controls (HCs). We focused on gray matter volume (GMV) of the subgenual anterior cingulate cortex (sgACC), subcallosal area (SCA), and hippocampus. The degree of volume reduction in these brain regions was calculated as the z score, and the differences of z scores in these regions were investigated among the MDD, BD, and HC groups. We then performed a receiver operating characteristic curve analysis to dissociate the individuals with MDD and BD from the HCs based on the z scores in the GMV of these brain regions. While there were no significant differences in the z scores of the hippocampus among the three groups, the z score of the sgACC was significantly higher in the MDD group than in the BD and HC groups, and the SCA z score was significantly higher in the MDD and BD groups than in the HC group. Our findings suggest that VBM evaluation of GMV reduction in the sgACC may be useful as an objective adjunctive tool to distinguish between MDD and BD.

BackgroundSustained attention deficits were reported more significant in patients with major depressive disorder (MDD) than in healthy controls (HCs), and are pivotal in both the development and aggravation of depression. Childhood trauma is also common in MDD and the exposure to childhood trauma may impede sustained attention and increase the treatment resistance in MDD. However, the underlying neuro-mechanisms link the childhood trauma to sustained attention deficits in MDD remain unclear.MethodsWe collected resting-state functional magnetic resonance imaging data, and measured childhood trauma severity using the Childhood Trauma Questionnaire and sustained attention using the Continuous Performance Test, Identical Pairs version. After excluding subjects with significant head movement, 45 MDDs and 54 HCs were included in the analysis. We compared fractional amplitude of low-frequency fluctuation (fALFF) between the groups, conducted whole-brain correlation analysis between the fALFF and sustained attention in the MDD group, and defined significant regions as the regions of interest for the seed-to-whole brain functional connectivity (FC) analysis. We further performed mediation analyses to investigate the relationships among the childhood trauma, fALFF and FC values, and the level of sustained attention in the MDD group.ResultsCompared with HCs, MDDs exhibited higher fALFF in the right middle frontal gyrus and left inferior frontal gyrus, and lower fALFF in the bilateral insular cortex, left medial orbital superior frontal gyrus and left angular gyrus (ANG.L). Whole-brain correlation analysis showed that impaired sustained attention was associated with increased fALFF in the left postcentral gyrus (PoCG.L), and FC of PoCG.L-left precentral gyrus (PreCG.L) and ANG.L-right superior temporal gyrus (STG.R) in the MDD group. Furthermore, mediation analyses showed that the fALFF in PoCG.L, and FC of PoCG.L-PreCG.L and ANG.L-STG.R mediated the relationship between the childhood trauma and sustained attention in the MDD group.ConclusionThe fALFF in PoCG.L, and FC of PoCG.L-PreCG.L and ANG.L-STG.R might be potential neural substrate in the association between the childhood trauma and poor sustained attention in the MDDs, and might serve as potential intervention targets for the treatment of sustained attention deficits in MDDs with childhood trauma history.

Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD). This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis. The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information. With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum. This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.