Cortical and subcortical gray matter alterations in first-episode drug-naïve adolescents with major depressive disorder

Functional and structural alterations in different durations of untreated illness in the frontal and parietal lobe in major depressive disorder

Major depressive disorder (MDD) is one of the most disabling illnesses that profoundly restricts psychosocial functions and impairs quality of life. However, the treatment rate of MDD is surprisingly low because the availability and acceptability of appropriate treatments are limited. Therefore, identifying whether and how treatment delay affects the brain and the initial time point of the alterations is imperative, but these changes have not been thoroughly explored. We investigated the functional and structural alterations of MDD for different durations of untreated illness (DUI) using regional homogeneity (ReHo) and voxel-based morphometry (VBM) with a sample of 125 treatment-naïve MDD patients and 100 healthy controls (HCs). The MDD patients were subgrouped based on the DUI, namely, DUI ≤ 1 M, 1 < DUI ≤ 6 M, 6 < DUI ≤ 12 M, and 12 < DUI ≤ 48 M. Subgroup comparison (MDD with different DUIs) was applied to compare ReHo and grey matter volume (GMV) extracted from clusters of regions with significant differences (the pooled MDD patients relative to HCs). Correlations and mediation effects were analysed to estimate the relationships between the functional and structural neuroimaging changes and clinical characteristics. MDD patients exhibited decreased ReHo in the left postcentral gyrus and precentral gyrus and reduced GMV in the left middle frontal gyrus and superior frontal gyrus relative to HCs. The initial functional abnormalities were detected after being untreated for 1 month, whereas this duration was 3 months for GMV reduction. Nevertheless, a transient increase in ReHo was observed after being untreated for 3 months. No significant differences were discovered between HCs and MDD patients with a DUI less than 1 month or among MDD patients with different DUIs in either ReHo or GMV. Longer DUI was related to reduced ReHo with GMV as mediator in MDD patients. We identified disassociated functional and anatomical alterations in treatment-naïve MDD patients at different time points in distinct brain regions at the early stage of the disease. Additionally, we also discovered that GMV mediated the relationship between a longer DUI and diminished ReHo in MDD patients, disclosing the latent deleterious and neuro-progressive implications of DUI on both the structure and function of the brain and indicating the necessity of early treatment of MDD.

Vulnerable brain regions in adolescent major depressive disorder: A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis

BACKGROUND

Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated.

AIM

To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation (ALE) meta-analysis.

METHODS

We performed a comprehensive literature search through July 12, 2023, for studies investigating brain functional changes in adolescent MDD patients. We utilized regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) analyses. We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls (HCs) using ALE.

RESULTS

Ten studies (369 adolescent MDD patients and 313 HCs) were included. Combining the ReHo and ALFF/fALFF data, the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs (voxel size: 648 mm3, P < 0.05), and no brain region exhibited increased activity. Based on the ALFF data, we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients (voxel size: 736 mm3, P < 0.05), with no regions exhibiting increased activity.

CONCLUSION

Through ALE meta-analysis, we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients, increasing our understanding of the neuropathology of affected adolescents.

Gray matter biomarkers for major depressive disorder and manic disorder using logistic regression

The study investigates morphometric changes using surface-based measures and logistic regression in Major depressive-disorder (MDD) and Manic-disorder patients as compared to controls. MDD (n = 21) and manic (n = 20) subjects were recruited from psychiatric clinics, along with 19 healthy-controls from local population, after structured and semi-structured clinical interview (DSM-IV, brief Psychotic-Rating Scale (BPRS), Young Mania Rating Scale (YMRS), Hamilton depression rating scale (HDRS), cognitive function by postgraduate Institute Battery of Brain Dysfunction (PGIBBD)). Using 3D T1-weighted images, gray matter (GM) cortical thickness and GM-based morphometric signatures (using logistic regression) were compared among MDD, manic disorder and controls using analysis of covariance (ANCOVA). No significant difference was found between the MDD and manic disorder patients. When compared to controls, cortical thinning was observed in bilateral rostral middle frontal gyrus and parsopercularis, right lateral occipital cortex, right lingual gyrus in MDD; and bilateral rostral middle frontal and superior frontal gyrus, right middle temporal gyrus, left supramarginal and left precentral gyrus in Manic disorders. Logistic regression analysis exhibited GM cortical thinning in the bilateral parsopercularis, right lateral occipital cortex and lingual gyrus in MDD; and bilateral rostral middle, superior frontal gyri, right middle temporal gyrus in Manic with a sensitivity and specificity of 85.7 % and 94.7 % and 90.0 % and 94.7 %, respectively in comparison with controls. Both groups exhibited GM loss in bilateral rostral middle frontal gyrus brain regions compared to controls. Multivariate analysis revealed common changes in GM in MDD and manic disorders associated with mood temperament, but differences when compared to controls.

Diagnosis of Major Depressive Disorder Using Machine Learning Based on Multisequence MRI Neuroimaging Features

BACKGROUND

Previous studies have found qualitative structural and functional brain changes in major depressive disorder (MDD) patients. However, most studies ignored the complementarity of multisequence MRI neuroimaging features and cannot determine accurate biomarkers.

PURPOSE

To evaluate machine-learning models combined with multisequence MRI neuroimaging features to diagnose patients with MDD.

STUDY TYPE

Prospective.

SUBJECTS

A training cohort including 111 patients and 90 healthy controls (HCs) and a test cohort including 28 patients and 22 HCs.

FIELD STRENGTH/SEQUENCE

A 3.0 T/T1-weighted imaging, resting-state functional MRI with echo-planar sequence, and single-shot echo-planar diffusion tensor imaging.

ASSESSMENT

Recruitment and integration were used to reflect the dynamic changes of functional networks, while gray matter volume and fractional anisotropy were used to reflect the changes in the morphological and anatomical network. We then fused features with significant differences in functional, morphological, and anatomical networks to evaluate a random forest (RF) classifier to diagnose patients with MDD. Furthermore, a support vector machine (SVM) classifier was used to verify the stability of neuroimaging features. Linear regression analyses were conducted to investigate the relationships among multisequence neuroimaging features and the suicide risk of patients.

STATISTICAL TESTS

The comparison of functional network attributes between patients and controls by two-sample t-test. Network-based statistical analysis was used to identify structural and anatomical connectivity changes between MDD and HCs. The performance of the model was evaluated by receiver operating characteristic (ROC) curves.

RESULTS

The performance of the RF model integrating multisequence neuroimaging features in the diagnosis of depression was significantly improved, with an AUC of 93.6%. In addition, we found that multisequence neuroimaging features could accurately predict suicide risk in patients with MDD (r = 0.691).

DATA CONCLUSION

The RF model fusing functional, morphological, and anatomical network features performed well in diagnosing patients with MDD and provided important insights into the pathological mechanisms of MDD.

EVIDENCE LEVEL

1.

TECHNICAL EFFICACY

Stage 2.

In vivo analyses reveal hippocampal subfield volume reductions in adolescents with schizophrenia, but not with major depressive disorder

BACKGROUND

Adult studies have reported atypicalities in the hippocampus and subfields in patients with schizophrenia (SCZ) and major depressive disorder (MDD). Both affective and psychotic disorders typically onset in adolescence, when human brain develops rapidly and shows increased susceptibility to adverse environments. However, few in vivo studies have investigated whether hippocampus subfield abnormalities occur in adolescence and whether they differ between SCZ and MDD cases.

METHODS

We recruited 150 adolescents (49 SCZ patients, 67 MDD patients, and 34 healthy controls) and obtained their structural images. We used FreeSurfer to automatically segment hippocampus into 12 subfields and analyzed subfield volumetric differences between groups by analysis of covariance, covarying for age, sex, and intracranial volume. Composite measures by summing subfield volumes were further compared across groups and analyzed in relation to clinical characteristic.

RESULTS

SCZ adolescents showed significant volume reductions in subfields of CA1, molecular layer, subiculum, parasubiculum, dentate gyrus and CA4 than healthy controls, and almost significant reductions, as compared to the MDD group, in left molecular layer, dentate gyrus, CA2/3 and CA4. Composite analyses showed smaller volumes in SCZ group than in healthy controls in all bilateral composite measures, and reduced volumes in comparison to MDD group in all left composite measures only.

CONCLUSIONS

SCZ adolescents exhibited both hippocampal subfield and composite volumes reduction, and also showed greater magnitude of deviance than those diagnosed with MDD, particularly in core CA regions. These results indicate a hippocampal disease process, suggesting a potential intervention marker of early psychotic patients and risk youths.

Abnormal voxel-wise whole-brain functional connectivity in first-episode, drug-naïve adolescents with major depression disorder

Major depression disorder (MDD) is one of the most common psychiatric disorders. Previous studies have demonstrated structural and functional abnormalities in adult depression. However, the neurobiology of adolescent depression has not been fully understood. The aim of this study was to investigate the intrinsic dysconnectivity pattern of voxel-level whole-brain functional networks in first-episode, drug-naïve adolescents with MDD. Resting-state functional magnetic resonance imaging data were acquired from 66 depressed adolescents and 47 matched healthy controls. Voxel-wise degree centrality (DC) analysis was performed to identify voxels that showed altered whole-brain functional connectivity (FC) with other voxels. We further conducted seed-based FC analysis to investigate in more detail the connectivity patterns of the identified DC changes. The relationship between altered DC and clinical variables in depressed adolescents was also analyzed. Compared with controls, depressed adolescents showed lower DC in the bilateral hippocampus, left superior temporal gyrus and right insula. Seed-based analysis revealed that depressed adolescents, relative to controls, showed hypoconnectivity between the hippocampus to the medial prefrontal regions and right precuneus. Furthermore, the DC values in the bilateral hippocampus were correlated with the Hamilton Depression Rating Scale score and duration of disease (all P < 0.05, false discovery rate corrected). Our study indicates abnormal intrinsic dysconnectivity patterns of whole-brain functional networks in drug-naïve, first-episode adolescents with MDD, and abnormal DC in the hippocampus may affect the association of prefrontal-hippocampus circuit. These findings may provide new insights into the pathophysiology of adolescent-onset MDD.

An MRI-based morphometric and structural covariance network study of Brazilian adolescents stratified by depression risk

OBJECTIVE

To explore differences in regional cortical morphometric structure between adolescents at risk for depression or with current depression.

METHODS

We analyzed cross-sectional structural neuroimaging data from a sample of 150 Brazilian adolescents classified as low-risk (n=50) or high-risk for depression (n=50) or with current depression (n=50) through a vertex-based approach with measurements of cortical volume, surface area and thickness. Differences between groups in subcortical volumes and in the organization of networks of structural covariance were also explored.

RESULTS

No significant differences in brain structure between groups were observed in whole-brain vertex-wise cortical volume, surface area or thickness. Also, no significant differences in subcortical volume were observed between risk groups. In relation to the structural covariance network, there was an indication of an increase in the hippocampus betweenness centrality index in the high-risk group network compared to the low-risk and current depression group networks. However, this result was only statistically significant when applying false discovery rate correction for nodes within the affective network.

CONCLUSION

In an adolescent sample recruited using an empirically based composite risk score, no major differences in brain structure were detected according to the risk and presence of depression.

Gray matter alterations in adolescent major depressive disorder and adolescent bipolar disorder

BACKGROUND

Gray matter volume (GMV) alterations in several emotion-related brain areas are implicated in mood disorders, but findings have been inconsistent in adolescents with major depressive disorder (MDD) or bipolar disorder (BD).

METHODS

We conducted a comprehensive meta-analysis of 35 region-of-interest (ROI) and 18 whole-brain voxel-based morphometry (VBM) MRI studies in adolescent MDD and adolescent BD, and indirectly compared the results in the two groups. The effects of age, sex, and other demographic and clinical scale scores were explored using meta-regression analysis.

RESULTS

In the ROI meta-analysis, right putamen volume was decreased in adolescents with MDD, while bilateral amygdala volume was decreased in adolescents with BD compared to healthy controls (HC). In the whole-brain VBM meta-analysis, GMV was increased in right middle frontal gyrus and decreased in left caudate in adolescents with MDD compared to HC, while in adolescents with BD, GMV was increased in left superior frontal gyrus and decreased in limbic regions compared with HC. MDD vs BD comparison revealed volume alteration in the prefrontal-limbic system.

LIMITATION

Different clinical features limit the comparability of the samples, and small sample size and insufficient clinical details precluded subgroup analysis or meta-regression analyses of these variables.

CONCLUSIONS

Distinct patterns of GMV alterations in adolescent MDD and adolescent BD could help to differentiate these two populations and provide potential diagnostic biomarkers.

Insular-associated causal network of structural covariance evaluating progressive gray matter changes in major depressive disorder

BACKGROUND

Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD).

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.

Gray matter volume reduction in orbitofrontal cortex correlated with plasma glial cell line-derived neurotrophic factor (GDNF) levels within major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a severe mental disorder characterized by reduced gray matter volume (GMV). To date, the pathogenesis of MDD remains unclear, but neurotrophic factors play an essential role in the pathophysiological alterations of MDD during disease development. In particular, plasma glial cell line-derived neurotrophic factor (GDNF) has been suggested as a potential biomarker that may be associated with disease activity and neurological progression in MDD. Our study investigated whether plasma GDNF levels in MDD patients and healthy controls (HCs) are correlated with GMV alterations.

METHODS

We studied 54 MDD patients and 48 HCs. The effect of different diagnoses on whole-brain GMV was investigated using ANOVA (Analysis of Variance). The threshold of significance was p < 0.05, and Gaussian random-field (GRF) correction for error was used. All analyses were controlled for covariates such as ethnicity, handedness, age, and gender that could affect GMV.

RESULT

Compared with the HC group, the GMV in the MDD group was significantly reduced in the right inferior orbitofrontal cortex (OFC), and plasma GDNF levels were significantly higher in the MDD group than in the HC group. In the right inferior OFC, the GDNF levels were positively correlated with GMV reduction in the MDD group, whereas in the HC group, a negative correlation was observed between GDNF levels and GMV reduction.

CONCLUSION

Although increased production of GDNF in MDD may help repair neural damage in brain regions associated with brain disease, its repairing effects may be interfered with and hindered by underlying neuroinflammatory processes.

Severity related neuroanatomical and spontaneous functional activity alteration in adolescents with major depressive disorder

Background

Major depressive disorder (MDD) is a disabling and severe psychiatric disorder with a high rate of prevalence, and adolescence is one of the most probable periods for the first onset. The neurobiological mechanism underlying the adolescent MDD remains unexplored.

Methods

In this study, we examined the cortical and subcortical alterations of neuroanatomical structures and spontaneous functional activation in 50 unmedicated adolescents with MDD vs. 39 healthy controls through the combined structural and resting-state functional magnetic resonance imaging.

Results

Significantly altered regional gray matter volume was found at broader frontal-temporal-parietal and subcortical brain areas involved with various forms of information processing in adolescent MDD. Specifically, the increased GM volume at the left paracentral lobule and right supplementary motor cortex was significantly correlated with depression severity in adolescent MDD. Furthermore, lower cortical thickness at brain areas responsible for visual and auditory processing as well as motor movements was found in adolescent MDD. The lower cortical thickness at the superior premotor subdivision was positively correlated with the course of the disease. Moreover, higher spontaneous neuronal activity was found at the anterior cingulum and medial prefrontal cortex, and this hyperactivity was also negatively correlated with the course of the disease. It potentially reflected the rumination, impaired concentration, and physiological arousal in adolescent MDD.

Conclusion

The abnormal structural and functional findings at cortico-subcortical areas implied the dysfunctional cognitive control and emotional regulations in adolescent depression. The findings might help elaborate the underlying neural mechanisms of MDD in adolescents.

Altered spontaneous brain activity in major depressive disorder: An activation likelihood estimation meta-analysis

BACKGROUND

Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD.

METHODS

A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3.

RESULTS

25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm³, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm³, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions.

CONCLUSION

Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD.

Personalized Diagnosis and Treatment for Neuroimaging in Depressive Disorders

Depressive disorders are highly heterogeneous in nature. Previous studies have not been useful for the clinical diagnosis and prediction of outcomes of major depressive disorder (MDD) at the individual level, although they provide many meaningful insights. To make inferences beyond group-level analyses, machine learning (ML) techniques can be used for the diagnosis of subtypes of MDD and the prediction of treatment responses. We searched PubMed for relevant studies published until December 2021 that included depressive disorders and applied ML algorithms in neuroimaging fields for depressive disorders. We divided these studies into two sections, namely diagnosis and treatment outcomes, for the application of prediction using ML. Structural and functional magnetic resonance imaging studies using ML algorithms were included. Thirty studies were summarized for the prediction of an MDD diagnosis. In addition, 19 studies on the prediction of treatment outcomes for MDD were reviewed. We summarized and discussed the results of previous studies. For future research results to be useful in clinical practice, ML enabling individual inferences is important. At the same time, there are important challenges to be addressed in the future.

Brain morphometry and connectivity differs between adolescent- and adult-onset major depressive disorder

BACKGROUND

Early-onset (EO) major depressive disorder (MDD) patients experience more depressive episodes and an increased risk of relapse. Thus, on a neurobiological level, adult EO patients might display brain structure and function different from adult-onset (AO) patients.

METHODS

A total of 103 patients (66 females) underwent magnetic resonance imaging. Structural measures of gray matter volume (GMV) and functional connectivity networks during resting state were compared between EO (≤19 years) and AO groups. Four residual major depression symptoms, mood, anxiety, insomnia, and somatic symptoms, were correlated with GMV between groups.

RESULTS

We found comparatively increased GMV in the EO group, namely the medial prefrontal and insular cortex, as well as the anterior hippocampus. Functional networks in EO patients showed a comparatively weaker synchronization of the left hippocampus with the adjacent amygdala, and a stronger integration with nodes in the contralateral prefrontal cortex and supramarginal gyrus. Volumetric analysis of depression symptoms associated the caudate nuclei with symptoms of insomnia, and persisting mood symptoms with the right amygdala, while finding no significant clusters for somatic and anxiety symptoms.

CONCLUSIONS

The study highlights the important role of the hippocampus and the prefrontal cortex in EO patients as part of emotion-regulation networks. Results in EO patients demonstrated subcortical volume changes irrespective of sleep and mood symptom recovery, which substantiates adolescence as a pivotal developmental phase for MDD. Longitudinal studies are needed to differentiate neural recovery trajectories while accounting for age of onset.

Distinguish bipolar and major depressive disorder in adolescents based on multimodal neuroimaging: Results from the Adolescent Brain Cognitive Development study®

Background

Major depressive disorder and bipolar disorder in adolescents are prevalent and are associated with cognitive impairment, executive dysfunction, and increased mortality. Early intervention in the initial stages of major depressive disorder and bipolar disorder can significantly improve personal health.

Methods

We collected 309 samples from the Adolescent Brain Cognitive Development study, including 116 adolescents with bipolar disorder, 64 adolescents with major depressive disorder, and 129 healthy adolescents, and employed a support vector machine to develop classification models for identification. We developed a multimodal model, which combined functional connectivity of resting-state functional magnetic resonance imaging and four anatomical measures of structural magnetic resonance imaging (cortical thickness, area, volume, and sulcal depth). We measured the performances of both multimodal and single modality classifiers.

Results

The multimodal classifiers showed outstanding performance compared with all five single modalities, and they are 100% for major depressive disorder versus healthy controls, 100% for bipolar disorder versus healthy control, 98.5% (95% CI: 95.4–100%) for major depressive disorder versus bipolar disorder, 100% for major depressive disorder versus depressed bipolar disorder and the leave-one-site-out analysis results are 77.4%, 63.3%, 79.4%, and 81.7%, separately.

Conclusions

The study shows that multimodal classifiers show high classification performances. Moreover, cuneus may be a potential biomarker to differentiate major depressive disorder, bipolar disorder, and healthy adolescents. Overall, this study can form multimodal diagnostic prediction workflows for clinically feasible to make more precise diagnose at the early stage and potentially reduce loss of personal pain and public society.

Heterogeneous alterations in thalamic subfields in major depression disorder

BACKGROUND

It is well known that the thalamus is not a unitary and homogeneous entity but a complex and highly connected archeocortical structure. Although many neuroimaging studies have reported alterations in the thalamus in major depressive disorder (MDD), the structural alterations in thalamic subfields remain unclear. This study aimed to investigate changes in gray matter volume (GMV) in thalamic subfields in MDD patients.

METHODS

The present study included structural images of 848 MDD patients and 794 age-matched normal controls (NC) from 17 study sites of the REST-meta-MDD consortium. We performed voxel-based morphometric analyses to calculate the GMV in the entire thalamus and its subfields using three different automated anatomical labeling atlases and subsequently compared the differences between first-episode drug-naïve major depressive disorder (FEDN), recurrent major depressive disorder (RMDD), and NC groups. We also evaluated the relationships between thalamic GMV and clinical symptoms in MDD patients.

RESULTS

Compared to NC, the FEDN patients showed increased GMV in thalamic subfields but not in the entire thalamus, while RMDD patients showed no significant alterations in GMV in the entire thalamus and its subfields. Moreover, the mean GMV in the right anterior thalamus and left anteroventral thalamus in RMDD patients were mildly positively correlated with the Hamilton Anxiety Rating Scale scores.

LIMITATIONS

The main limitations are a single-modal analysis based on T1-weighted MR images and a cross-sectional design.

CONCLUSIONS

Our findings suggest that FEDN and RMDD patients show heterogeneous alterations across thalamic subfields, which may help us understand the pathophysiological mechanisms of MDD.

Altered resting-state functional connectivity of the right precuneus and cognition between depressed and non-depressed schizophrenia

The study investigated the resting-state functional connectivity (FC) and cognitive changes in patients with depressed schizophrenia(DS) and non-depressed schizophrenia(NDS). Eighty patients with first-episode schizophrenia and 50 healthy controls (HC) were included to conduct resting-state fMRI. All participants completed MATRICS Consensus Cognitive Battery (MCCB). The right precuneus was selected as the seed in whole-brain FC analysis. Our results showed the cognitive function (All MCCB dimensions) of all schizophrenia patients were worse than HC, but no differences were found between DS and NDS. The DS had decreased FC than NDS between the right precuneus and left middle cingulate gyrus, left cerebellum, right cerebellum. The DS had increased FC than HC between the right precuneus and temporal lobe, occipital lobe, and decreased FC between the right precuneus and left cerebellum. However, the NDS had increased FC than HC between the right precuneus and left cerebellum, right cerebellum, temporal lobe, occipital lobe, left superior parietal lobule. Correlation analysis showed that FC between the right precuneus and occipital lobe was negatively correlated with visual learning in DS and with social cognition in NDS. Our results suggest DS and NDS patients have different patterns of FC, and their FC changes correlate with different domains of cognition.

Alterations in the Occipital Cortex of Drug-Naïve Adults With Major Depressive Disorder: A Surface-Based Analysis of Surface Area and Cortical Thickness

OBJECTIVE

Advances in surface-based morphometric methods have allowed researchers to separate cortical volume into cortical thickness (CTh) and surface area (SA). Although CTh alterations in major depressive disorder (MDD) have been observed in numerous studies, few studies have described significant SA alterations. Our study aimed to measure patients' SAs and to compare it with their CTh to examine whether SA exhibits alteration patterns that differ from those of CTh in drug-naïve patients with MDD.

METHODS

A total of 71 drug-naïve MDD patients and 111 healthy controls underwent structural magnetic resonance imaging, and SA and CTh were analyzed between the groups.

RESULTS

We found a smaller SA in the left superior occipital gyrus (L-SOG) in drug-naïve patients with MDD. In the CTh analysis, the bilateral fusiform gyrus, left middle occipital gyrus, left temporal superior gyrus, and right posterior cingulate showed thinner cortices in patients with MDD, while the CTh of the bilateral SOG, right straight gyrus, right posterior cingulate, and left lingual gyrus were increased.

CONCLUSION

Compared with the bilateral occipito-temporal changes in CTh, SA alterations in patients with MDD were confined to the L-SOG. These findings may improve our understanding of the neurobiological mechanisms of SA alteration in relation to MDD.

The Association Between Resting State Functional Connectivity and the Trait of Impulsivity and Suicidal Ideation in Young Depressed Patients With Suicide Attempts

Suicide is a leading cause of death among youth and is strongly associated with major depressive disorder (MDD). However, the neurobiological underpinnings of suicidal behaviour and the identification of risk for suicide in young depressed patients are not yet well-understood. In this study, we used a seed-based correlation analysis to investigate the differences in resting-state functional connectivity (RSFC) in depressed youth with or without a history of suicide attempts and healthy controls (HCs). Suicidal attempters (ATT group, n = 35), non-suicide attempters (NAT group, n = 18), and HCs exhibited significantly different RSFC patterns with the left superior prefrontal gyrus (L-SFG) and left middle prefrontal gyrus (L-MFG) serving as the regions of interest (ROIs). The ATT group showed decreased RSFC of the left middle frontal gyrus with the left superior parietal gyrus compared to the NAT and HC groups. Decreased RSFC between the left superior frontal gyrus and the right anterior cingulate cortex (rACC) was found in the ATT group compared to the NAT and HC groups. Furthermore, the left prefrontal-parietal connectivity was associated with suicidal ideation and levels of impulsivity, but RSFC of the left prefrontal cortex with the rACC was correlated exclusively with impulsivity levels and was not related to suicidal ideation in the ATT group. Our results demonstrated that altered RSFC of the prefrontal-parietal and prefrontal-rACC regions was associated with suicide attempts in depressed youth, and state-related deficits in their interconnectivity may contribute to traits, such as cognitive impairments and impulsivity to facilitate suicidal acts. Our findings suggest that the neural correlates of suicidal behaviours might be dissociable from those related to the severity of current suicidal ideation. Neural circuits underlying suicide attempts differ from those that underlie suicidal ideation.

Cortical Thickness Changes in Chronic Ketamine Users

Background: Previous studies have examined the effects of long-term ketamine use on gray matter volume. But it is unclear whether chronic ketamine use alters cortical thickness and whether cortical thickness changes in chronic ketamine users are associated with cognitive deficits observed in chronic ketamine users. Methods: Here, 28 chronic ketamine users and 30 healthy controls (HCs) were recruited. Cortical morphometry based on Computational Anatomy Toolbox (CAT12) was used to measure cortical thickness. Cognitive performance was measured by MATRICS Consensus Cognitive Battery (MCCB). Two-sample t-test was used to assess differences in cortical thickness and cognitive performance between the two groups. Partial correlation analysis was used for assessing correlations between cortical thickness changes and clinical characteristics, cognitive performance in chronic ketamine users. Results: Chronic ketamine users exhibited significantly reduced cortical thickness in frontal, parietal, temporal, and occipital lobes compared to HC [false discovery rate (FDR) corrected at p < 0.05]. In chronic ketamine users, the average quantity (g) of ketamine use/day was negatively correlated with cortical thickness in the left superior frontal gyrus (SFG), right caudal middle frontal gyrus (MFG), and right paracentral lobule. The frequency of ketamine use (days per week) was negatively correlated with cortical thickness in the left isthmus cingulate cortex. Duration of ketamine use (month) was negatively correlated with cortical thickness in the left precentral gyrus. The chronic ketamine users showed significantly poorer cognitive performance on the working memory (P = 0.009), visual learning (P = 0.009), speed of processing (P < 0.000), and Matrics composite (P = 0.01). There was no correlation between scores of domains of MCCB and reduced cortical thickness. Conclusion: The present study observed reduced cortical thickness in multiple brain areas, especially in the prefrontal cortex (PFC) in chronic ketamine users. Dose, frequency, and duration of ketamine use was negatively correlated with cortical thickness of some brain areas. Our results suggest that chronic ketamine use may lead to a decrease of cortical thickness. But the present study did not observe any correlation between reduced cortical thickness and decreased cognitive performance in chronic ketamine users.

Bifrontal electroconvulsive therapy changed regional homogeneity and functional connectivity of left angular gyrus in major depressive disorder

Electroconvulsive therapy (ECT) is a rapid and effective treatment for MDD. However, the mechanism of ECT for MDD has not been clarified. In this study, we used resting-state functional magnetic resonance imaging (rs-fMRI) to explore the mechanism of ECT. Two groups of subjects were recruited: healthy controls (HCs) and MDD patients who received bifrontal ECT. MDD patients and HCs underwent rs-fMRI scans and clinical assessments (Hamilton Depression Rating Scale, Rey-Auditory Verbal Learning Test (RAVLT), and the verbal fluency test). Regional homogeneity (ReHo) and functional connectivity were evaluated for the analysis of rs-fMRI data. The results showed that ReHo values in the left angular gyrus (LAG) significantly increased in MDD patients after ECT, and the functional connectivity of the LAG with bilateral inferior temporal gyrus, bilateral middle frontal gyrus, left superior frontal gyrus, left middle temporal gyrus, left precuneus, left posterior cingulate gyrus, and right angular gyrus was found to be strengthened after ECT. The scores of delayed recall trial in the RAVLT of MDD patients were related to the functional connectivity of the LAG with the left inferior temporal gyrus and the left posterior cingulate gyrus. It indicated LAG palyed an important role in the mechanism of ECT in MDD.

ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.