Aberrant brain regional homogeneity in first-episode drug-naïve patients with major depressive disorder: A voxel-wise meta-analysis

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Gut proinflammatory bacteria is associated with abnormal functional connectivity of hippocampus in unmedicated patients with major depressive disorder

Accumulating evidence has revealed the gut bacteria dysbiosis and brain hippocampal functional and structural alterations in major depressive disorder (MDD). However, the potential relationship between the gut microbiota and hippocampal function alterations in patients with MDD is still very limited. Data of resting-state functional magnetic resonance imaging were acquired from 44 unmedicated MDD patients and 42 demographically matched healthy controls (HCs). Severn pairs of hippocampus subregions (the bilateral cornu ammonis [CA1-CA3], dentate gyrus (DG), entorhinal cortex, hippocampal-amygdaloid transition area, and subiculum) were selected as the seeds in the functional connectivity (FC) analysis. Additionally, fecal samples of participants were collected and 16S rDNA amplicon sequencing was used to identify the altered relative abundance of gut microbiota. Then, association analysis was conducted to investigate the potential relationships between the abnormal hippocampal subregions FC and microbiome features. Also, the altered hippocampal subregion FC values and gut microbiota levels were used as features separately or together in the support vector machine models distinguishing the MDD patients and HCs. Compared with HCs, patients with MDD exhibited increased FC between the left hippocampus (CA2, CA3 and DG) and right hippocampus (CA2 and CA3), and decreased FC between the right hippocampal CA3 and bilateral posterior cingulate cortex. In addition, we found that the level of proinflammatory bacteria (i.e., Enterobacteriaceae) was significantly increased, whereas the level of short-chain fatty acids producing-bacteria (i.e., Prevotellaceae, Agathobacter and Clostridium) were significantly decreased in MDD patients. Furthermore, FC values of the left hippocampal CA3- right hippocampus (CA2 and CA3) was positively correlated with the relative abundance of Enterobacteriaceae in patients with MDD. Moreover, altered hippocampal FC patterns and gut microbiota level were considered in combination, the best discrimination was obtained (AUC = 0.92). These findings may provide insights into the potential role of gut microbiota in the underlying neuropathology of MDD patients.

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.

A three-dimensional model of neural activity and phenomenal-behavioral patterns

How phenomenal experience and behavior are related to neural activity in physiology and psychopathology represents a fundamental question in neuroscience and psychiatry. The phenomenal-behavior patterns may be deconstructed into basic dimensions, i.e., psychomotricity, affectivity, and thought, which might have distinct neural correlates. This work provides a data overview on the relationship of these phenomenal-behavioral dimensions with brain activity across physiological and pathological conditions (including major depressive disorder, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, anxiety disorders, addictive disorders, Parkinson's disease, Tourette syndrome, Alzheimer's disease, and frontotemporal dementia). Accordingly, we propose a three-dimensional model of neural activity and phenomenal-behavioral patterns. In this model, neural activity is organized into distinct units in accordance with connectivity patterns and related input/output processing, manifesting in the different phenomenal-behavioral dimensions. (1) An external neural unit, which involves the sensorimotor circuit/brain's sensorimotor network and is connected with the external environment, processes external inputs/outputs, manifesting in the psychomotor dimension (processing of exteroception/somatomotor activity). External unit hyperactivity manifests in psychomotor excitation (hyperactivity/hyperkinesia/catatonia), while external unit hypoactivity manifests in psychomotor inhibition (retardation/hypokinesia/catatonia). (2) An internal neural unit, which involves the interoceptive-autonomic circuit/brain's salience network and is connected with the internal/body environment, processes internal inputs/outputs, manifesting in the affective dimension (processing of interoception/autonomic activity). Internal unit hyperactivity manifests in affective excitation (anxiety/dysphoria-euphoria/panic), while internal unit hypoactivity manifests in affective inhibition (anhedonia/apathy/depersonalization). (3) An associative neural unit, which involves the brain's associative areas/default-mode network and is connected with the external/internal units (but not with the environment), processes associative inputs/outputs, manifesting in the thought dimension (processing of ideas). Associative unit hyperactivity manifests in thought excitation (mind-wandering/repetitive thinking/psychosis), while associative unit hypoactivity manifests in thought inhibition (inattention/cognitive deficit/consciousness loss). Finally, these neural units interplay and dynamically combine into various neural states, resulting in the complex phenomenal experience and behavior across physiology and neuropsychiatric disorders.

Does Baseline Cognitive Function Predict the Reduction Rate in HDRS-17 Total Scores in First-Episode, Drug-Naïve Patients with Major Depressive Disorder?

Purpose

Major depressive disorder (MDD) is associated with worse cognitive functioning. We aim to examine the association between baseline cognitive functioning and the reduction rate in HDRS-17 total scores and to highlight the predictors of the reduction rate in HDRS-17 total scores in MDD with first-episode, drug-naïve (FED) patients.

Patients and Methods

Ninety FED patients were recruited consecutively and evaluated using the 17-item Hamilton Depression Rating Scale (HDRS-17), the 14-item Hamilton Anxiety Scale (HAMA-14), the Functioning Assessment Short Test (FAST) and the MATRICS Consensus Cognitive Battery (MCCB) at baseline and again at week 8.

Results

Eighty-four FED patients completed the study. Comparison showed that response group had significantly higher T scores in TMT-A, BACS-SC, WMS-III, BVMT-R, MSCEI and CPT-IP, but showed significantly lower scores in FAST total scores including autonomy, occupational functioning, cognitive functioning, interpersonal relationship than non- response group (all p's< 0.05). Partial correlation analysis also found that the reduction rate in HDRS-17 total scores could be negatively associated with autonomy, cognitive functioning and interpersonal relationship domains as well as total FAST scores, also was further positively associated with T-scores of BACS-SC, CPT-IP and MSCEI in MCCB, even when accounting for potential confounders. Furthermore, the levels of cognitive function domain, autonomy domain in FAST, and BACS-SC, CPT-IP in MCCB may predict the reduction rate in HDRS-17 total scores in FED patients (all p's< 0.05).

Conclusion

Our findings underscore significant correlations between baseline functioning and the reduction rate in HDRS-17 total scores in FED patients. Moreover, better baseline cognitive function, autonomy, speed of processing and attention/vigilance are more likely to predict patients' response to antidepressant treatment, indicating pre-treatment better cognitive functioning may be predictors to treatment response in FED.

Lifetime Exposure to Depression and Neuroimaging Measures of Brain Structure and Function

Importance

Despite decades of neuroimaging studies reporting brain structural and functional alterations in depression, discrepancies in findings across studies and limited convergence across meta-analyses have raised questions about the consistency and robustness of the observed brain phenotypes.

Objective

To investigate the associations between 6 operational criteria of lifetime exposure to depression and functional and structural neuroimaging measures.

Design, Setting, and Participants

This cross-sectional study analyzed data from a UK Biobank cohort of individuals aged 45 to 80 years who were enrolled between January 1, 2014, and December 31, 2018. Participants included individuals with a lifetime exposure to depression and matched healthy controls without indications of psychosis, mental illness, behavior disorder, and disease of the nervous system. Six operational criteria of lifetime exposure to depression were evaluated: help seeking for depression; self-reported depression; antidepressant use; depression definition by Smith et al; hospital International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes F32 and F33; and Composite International Diagnostic Interview Short Form score. Six increasingly restrictive depression definitions and groups were defined based on the 6 depression criteria, ranging from meeting only 1 criterion to meeting all 6 criteria. Data were analyzed between January and October 2022.

Main Outcomes and Measures

Functional measures were calculated using voxel-wise fractional amplitude of low-frequency fluctuation (fALFF), global correlation (GCOR), and local correlation (LCOR). Structural measures were calculated using gray matter volume (GMV).

Results

The study included 20 484 individuals with lifetime depression (12 645 females [61.7%]; mean [SD] age, 63.91 [7.60] years) and 25 462 healthy controls (14 078 males [55.3%]; mean [SD] age, 65.05 [7.8] years). Across all depression criteria, individuals with lifetime depression displayed regionally consistent decreases in fALFF, LCOR, and GCOR (Cohen d range, -0.53 [95% CI, -0.88 to -0.15] to -0.04 [95% CI, -0.07 to -0.01]) but not in GMV (Cohen d range, -0.47 [95 % CI, -0.75 to -0.12] to 0.26 [95% CI, 0.15-0.37]). Hospital ICD-10 diagnosis codes F32 and F33 (median [IQR] difference in effect sizes, -0.14 [-0.17 to -0.11]) and antidepressant use (median [IQR] difference in effect sizes, -0.12 [-0.16 to -0.10]) were criteria associated with the most pronounced alterations.

Conclusions and Relevance

Results of this cross-sectional study indicate that lifetime exposure to depression was associated with robust functional changes, with a more restrictive depression definition revealing more pronounced alterations. Different inclusion criteria for depression may be associated with the substantial variation in imaging findings reported in the literature.

Association between gaming disorder and regional homogeneity in highly involved male adult gamers: A pilot resting-state fMRI study

BACKGROUND

Gaming behavior can induce cerebral changes that may be related to the neurobiological features of gaming disorder (GD). Additionally, individuals with higher levels of depression or impulsivity are more likely to experience GD. Therefore, the present pilot study explored potential neurobiological correlates of GD in the context of depression and impulsivity, after accounting for video gaming behavior.

METHODS

Using resting-state functional magnetic resonance imaging (fMRI), a cross-sectional study was conducted with 35 highly involved male adult gamers to examine potential associations between GD severity and regional homogeneity (ReHo) in the entire brain. A mediation model was used to test the role of ReHo in the possible links between depression/impulsivity and GD severity.

RESULTS

Individuals with greater GD severity showed increased ReHo in the right Heschl's gyrus and decreased ReHo in the right hippocampus (rHip). Furthermore, depression and impulsivity were negatively correlated with ReHo in the rHip, respectively. More importantly, ReHo in the rHip was found to mediate the associations between depression/impulsivity and GD.

CONCLUSIONS

These preliminary findings suggest that GD severity is related to ReHo in brain regions associated with learning/memory/mood and auditory function. Higher levels of depression or impulsivity may potentiate GD through the functional activity of the hippocampus. Our findings advance our understanding of the neurobiological differences behind GD symptoms in highly involved gamers.

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.

Role of SNAP-25 MnlI variant in impaired working memory and brain functions in attention deficit/hyperactivity disorder

INTRODUCTION

Attention deficit/hyperactivity disorder (ADHD) is a hereditary neurodevelopmental disorder characterized by working memory (WM) deficits. The MnlI variant (rs3746544) of the synaptosomal-associated protein 25 (SNAP-25) gene is associated with ADHD. In this study, we investigated the role and underlying mechanism of SNAP-25 MnlI variant in cognitive impairment and brain functions in boys with ADHD.

METHOD

We performed WM capacity tests using the fourth version of the Wechsler Intelligence Scale for Children (WISC-IV) and regional homogeneity (ReHo) analysis for the resting-state functional magnetic resonance imaging data of 56 boys with ADHD divided into two genotypic groups (TT homozygotes and G-allele carriers). Next, Spearman's rank correlation analysis between the obtained ReHo values and the WM index (WMI) calculated for each participant.

RESULTS

Compared with G-allele carrier group, there were higher ReHo values for the left medial prefrontal cortex (mPFC) and higher WM capacity in TT homozygote group. Contrary to TT homozygote group, the WM capacity was negatively correlated with the peak ReHo value for the left mPFC in G-allele carrier group.

CONCLUSION

These findings suggest that SNAP-25 MnlI variant may underlie cognitive and brain function impairments in boys with ADHD, thus suggesting its potential as a new target for ADHD treatment.

Altered brain regional homogeneity is associated with depressive symptoms in COVID-19

BACKGROUND

COVID-19 is an infectious disease that has spread worldwide in 2020, causing a severe pandemic. In addition to respiratory symptoms, neuropsychiatric manifestations are commonly observed, including chronic fatigue, depression, and anxiety. The neural correlates of neuropsychiatric symptoms in COVID-19 are still largely unknown.

METHODS

A total of 79 patients with COVID-19 (COV) and 17 healthy controls (HC) underwent 3 T functional magnetic resonance imaging at rest, as well as structural imaging. Regional homogeneity (ReHo) was calculated. We also measured depressive symptoms with the Patient Health Questionnaire (PHQ-9), anxiety using the General Anxiety Disorder 7-item scale, and fatigue with the Multidimension Fatigue Inventory.

RESULTS

In comparison with HC, COV showed significantly higher depressive scores. Moreover, COV presented reduced ReHo in the left angular gyrus, the right superior/middle temporal gyrus and the left inferior temporal gyrus, and higher ReHo in the right hippocampus. No differences in gray matter were detected in these areas. Furthermore, we observed a negative correlation between ReHo in the left angular gyrus and PHQ-9 scores and a trend toward a positive correlation between ReHo in the right hippocampus and PHQ-9 scores.

LIMITATIONS

Heterogeneity in the clinical presentation in COV, the different timing from the first positive molecular swab test to the MRI, and the cross-sectional design of the study limit the generalizability of our findings.

CONCLUSIONS

Our results suggest that COVID-19 infection may contribute to depressive symptoms via a modulation of local functional connectivity in cortico-limbic circuits.

The alterations of brain functional connectivity networks in major depressive disorder detected by machine learning through multisite rs-fMRI data

BACKGROUND

The current diagnosis of major depressive disorder (MDD) is mainly based on the patient's self-report and clinical symptoms. Machine learning methods are used to identify MDD using resting-state functional magnetic resonance imaging (rs-fMRI) data. However, due to large site differences in multisite rs-fMRI data and the difficulty of sample collection, most of the current machine learning studies use small sample sizes of rs-fMRI datasets to detect the alterations of functional connectivity (FC) or network attribute (NA), which may affect the reliability of the experimental results.

METHODS

Multisite rs-fMRI data were used to increase the size of the sample, and then we extracted the functional connectivity (FC) and network attribute (NA) features from 1611 rs-fMRI data (832 patients with MDD (MDDs) and 779 healthy controls (HCs)). ComBat algorithm was used to harmonize the data variances caused by the multisite effect, and multivariate linear regression was used to remove age and sex covariates. Two-sample t-test and wrapper-based feature selection methods (support vector machine recursive feature elimination with cross-validation (SVM-RFECV) and LightGBM's "feature_importances_" function) were used to select important features. The Shapley additive explanations (SHAP) method was used to assign the contribution of features to the best classification effect model.

RESULTS

The best result was obtained from the LinearSVM model trained with the 136 important features selected by SVMRFE-CV. In the nested five-fold cross-validation (consisting of an outer and an inner loop of five-fold cross-validation) of 1611 data, the model achieved the accuracy, sensitivity, and specificity of 68.90 %, 71.75 %, and 65.84 %, respectively. The 136 important features were tested in a small dataset and obtained excellent classification results after balancing the ratio between patients with depression and HCs.

CONCLUSIONS

The combined use of FC and NA features is effective for classifying MDDs and HCs. The important FC and NA features extracted from the large sample dataset have some generalization performance and may be used as a reference for the altered brain functional connectivity networks in MDD.

Treatment Response Prediction for Major Depressive Disorder Patients via Multivariate Pattern Analysis of Thalamic Features

Antidepressant treatment, as an important method in clinical practice, is not suitable for all major depressive disorder (MDD) patients. Although magnetic resonance imaging (MRI) studies have found thalamic abnormalities in MDD patients, it is not clear whether the features of the thalamus are suitable to serve as predictive aids for treatment responses at the individual level. Here, we tested the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional ALFF (fALFF) of the thalamus using multivariate pattern analysis (MVPA). A total of 74 MDD patients and 44 healthy control (HC) subjects were recruited. Thirty-nine MDD patients and 35 HC subjects underwent scanning twice. Between the two scanning sessions, patients in the MDD group received selective serotonin reuptake inhibitor (SSRI) treatment for 3-month, and HC group did not receive any treatment. Gaussian process regression (GPR) was trained to predict the percentage decrease in the Hamilton Depression Scale (HAMD) score after treatment. The percentage decrease in HAMD score after SSRI treatment was predicted by building GPRs trained with baseline thalamic data. The results showed significant correlations between the true percentage of HAMD score decreases and predictions (p < 0.01, r² = 0.11) in GPRs trained with GMD. We did not find significant correlations between the true percentage of HAMD score decreases and predictions in GMV (p = 0.16, r² = 0.00), ALFF (p = 0.125, r² = 0.00), and fALFF (p = 0.485, r² = 0.10). Our results suggest that GMD of the thalamus has good potential as an aid in individualized treatment response predictions of MDD patients.

Functional MRI in major depressive disorder: A review of findings, limitations, and future prospects

Objective diagnosis and prognosis in major depressive disorder (MDD) remains a challenge due to the absence of biomarkers based on physiological parameters or medical tests. Numerous studies have been conducted to identify functional magnetic resonance imaging‐based biomarkers of depression that either objectively differentiate patients with depression from healthy subjects, predict personalized treatment outcome, or characterize biological subtypes of depression. While there are some findings of consistent functional biomarkers, there is still lack of robust data acquisition and analysis methodology. According to current findings, primarily, the anterior cingulate cortex, prefrontal cortex, and default mode network play a crucial role in MDD. Yet, there are also less consistent results and the involvement of other regions or networks remains ambiguous. We further discuss image acquisition, processing, and analysis limitations that might underlie these inconsistencies. Finally, the current review aims to address and discuss possible remedies and future opportunities that could improve the search for consistent functional imaging biomarkers of depression. Novel acquisition techniques, such as multiband and multiecho imaging, and neural network‐based cleaning approaches can enhance the signal quality in limbic and frontal regions. More comprehensive analyses, such as directed or dynamic functional features or the identification of biological depression subtypes, can improve objective diagnosis or treatment outcome prediction and mitigate the heterogeneity of MDD. Overall, these improvements in functional MRI imaging techniques, processing, and analysis could advance the search for biomarkers and ultimately aid patients with MDD and their treatment course.

Subregion-specific, modality-dependent and timescale-sensitive hippocampal connectivity alterations in patients with first-episode, drug-naïve major depression disorder

BACKGROUND

Despite accumulating evidence for the hippocampus as a key dysfunctional node in major depressive disorder (MDD), previous findings are controversial possibly due to heterogeneous and small clinical samples, complicated hippocampal structure, and different imaging modalities and analytical methods.

METHODS

We collected structural and resting-state functional MRI data from 100 first-episode, drug-naïve MDD patients and 99 healthy controls. A subset of the participants (34 patients and 33 controls) also completed a battery of neuropsychological tests and childhood trauma questionnaires. Seed-based morphological and functional (static and dynamic) connectivity were calculated for ten hippocampal subregions, followed by analyses of dynamic functional connectivity states (k-means clustering), connectivity cross-modality relationships (cosine similarity), and connectivity associations with clinical and neuropsychological variables (Spearman correlation).

RESULTS

Between-group comparisons revealed abnormal hippocampal connectivity in the patients that depended on 1) hippocampal subdivisions: the cornu ammonis (CA) was the most seriously affected subregion, in particular the right CA1 for functional connectivity alterations; 2) imaging modality: morphological connectivity revealed seldom and sporadic alterations with different lobes, while functional connectivity identified numerous and convergent alterations with prefrontal regions; and 3) time scale: dynamic functional connectivity was more sensitive than static functional connectivity, in particular in revealing alterations between the right CA1 and contralateral prefrontal cortex. Among the 34 patients, functional connectivity alterations of the CA1 were related to the history of childhood trauma in the patients.

LIMITATIONS

Only a subset of the patients completed the neuropsychological tests, which may cause underestimation of cognitive relevance of hippocampal connectivity alterations.

CONCLUSIONS

Disrupted hippocampal CA1 functional connectivity plays key roles in the pathophysiology of MDD and may act as a potential diagnostic biomarker for the disease.

Combined rs-fMRI study on brain functional imaging and mechanism of RAGE-DAMPs of depression: Evidence from MDD patients to chronic stress-induced depression models in cynomolgus monkeys and mice

More and more evidence show that major depressive disorder (MDD) is closely related to inflammation caused by chronic stress, which seriously affects human physical and mental health. However, the inflammatory mechanism of depression and its effect on brain function have not been clarified. Based on resting-state functional magnetic resonance imaging (rs-fMRI), we investigated change of brain functional imaging and the inflammatory mechanism of damage-related molecular patterns (DAMPs)-receptor of advanced glycation protein end product (RAGE) in MDD patients and depressive-like cynomolgus monkeys and mice models induced by chronic stress. The regional homogeneity (ReHo) and functional connectivity (FC) were analyzed using MATLAB and SPM12 software. We detected the expression of DAMPs-RAGE pathway-related proteins and mRNA in MDD peripheral blood and in serum and brain tissue of cynomolgus monkeys and mice. Meanwhile, RAGE gene knockout mice, RAGE inhibitor, and overexpression of AVV9RAGE adeno-associated virus were used to verify that RAGE is a reliable potential biomarker of depression. The results showed that the ReHo value of prefrontal cortex (PFC) in MDD patients and depressive-like cynomolgus monkeys was decreased. Then, the PFC was used as a seed point, the FC of ipsilateral and contralateral PFC were weakened in depressive-like mice. At the same time, qPCR showed that RAGE and HMGB1 mRNA were upregulated and S100β mRNA was downregulated. The expression of RAGE-related inflammatory protein in PFC of depressive-like monkeys and mice were consistent with that in peripheral blood of MDD patients. Moreover, the results were confirmed in RAGE-/- mice, injection of FPS-ZM1, and overexpression of AAV9RAGE in mice. To sum up, our findings enhance the evidence that chronic stress-PFC-RAGE are associated with depression. These results attempt to establish the links between brain functional imaging, and molecular targets among different species will help to reveal the pathophysiological mechanism of depression from multiple perspectives.

Individualized diagnosis of major depressive disorder via multivariate pattern analysis of thalamic sMRI features

BACKGROUND

Magnetic resonance imaging (MRI) studies have found thalamic abnormalities in major depressive disorder (MDD). Although there are significant differences in the structure and function of the thalamus between MDD patients and healthy controls (HCs) at the group level, it is not clear whether the structural and functional features of the thalamus are suitable for use as diagnostic prediction aids at the individual level. Here, we were to test the predictive value of gray matter density (GMD), gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and fractional amplitude of low-frequency fluctuations (fALFF) in the thalamus using multivariate pattern analysis (MVPA).

METHODS

Seventy-four MDD patients and 44 HC subjects were recruited. The Gaussian process classifier (GPC) was trained to separate MDD patients from HCs, Gaussian process regression (GPR) was trained to predict depression scores, and Multiple Kernel Learning (MKL) was applied to explore the contribution of each subregion of the thalamus.

RESULTS

The primary findings were as follows: [1] The balanced accuracy of the GPC trained with thalamic GMD was 96.59% (P < 0.001). The accuracy of the GPC trained with thalamic GMV was 93.18% (P < 0.001). The correlation between Hamilton Depression Scale (HAMD) score targets and predictions in the GPR trained with GMD was 0.90 (P < 0.001, r2 = 0.82), and in the GPR trained with GMV, the correlation between HAMD score targets and predictions was 0.89 (P < 0.001, r2 = 0.79). [2] The models trained with ALFF and fALFF in the thalamus failed to discriminate MDD patients from HC participants. [3] The MKL model showed that the left lateral prefrontal thalamus, the right caudal temporal thalamus, and the right sensory thalamus contribute more to the diagnostic classification.

CONCLUSIONS

The results suggested that GMD and GMV, but not functional indicators of the thalamus, have good potential for the individualized diagnosis of MDD. Furthermore, the thalamus shows the heterogeneity in the structural features of thalamic subregions for predicting MDD. To our knowledge, this is the first study to focus on the thalamus for the prediction of MDD using machine learning methods at the individual level.

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.

Altered local connectivity in chronic pain: A voxel-wise meta-analysis of resting-state functional magnetic resonance imaging studies

BACKGROUND

A number of studies have used regional homogeneity (ReHo) to depict local functional connectivity in chronic pain (CP). However, the findings from these studies were mixed and inconsistent.

METHODS

A computerized literature search will be performed in PubMed, Web of Science, Embase, China National Knowledge Infrastructure (CNKI), WanFang, and SinoMed databases until June 15, 2019 and updated on March 20, 2020. This protocol will follow the Preferred Reporting Items for Systematic review and Meta-Analysis Protocols (PRISMA-P). The Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software will be used for this voxel-wise meta-analysis.

RESULTS

This meta-analysis will identify the most consistent ReHo alterations in CP.

CONCLUSIONS

To our knowledge, this will be the first voxel-wise meta-analysis that integrates ReHo findings in CP. This meta-analysis will offer the quantitative evidence of ReHo alterations that characterize brain local functional connectivity of CP.

PROSPERO REGISTRATION NUMBER

CRD42019148523.

Altered Whole-Brain Functional Networks in Drug-Naïve, First-Episode Adolescents With Major Depression Disorder

BACKGROUND

Neuroimaging studies have demonstrated disrupted brain functional networks in major depression disorder (MDD); however, alterations to whole-brain networks specifically associated with adolescent MDD remain poorly understood.

PURPOSE

To investigate the topological architecture of intrinsic brain functional networks in drug-naïve, first-episode adolescent MDD patients using graph theoretical analysis.

STUDY TYPE

Prospective.

SUBJECTS

In all, 109 adolescent MDD patients and 70 healthy control subjects.

FIELD STRENGTH/SEQUENCES

3.0T; gradient-echo echo-planar imaging sequence.

ASSESSMENT

After the construction of whole-brain functional networks by thresholding partial correlation matrices of 90 brain regions, we calculated the topological properties (eg, small-world, efficiency, and nodal centrality) using graph theoretical analysis.

STATISTICAL TESTS

A chi-squared test was used to compare the gender-ratio difference, and a two-sample t-test was used in the comparison of age. We compared network measures between the two groups using nonparametric permutation tests. Exploratory partial correlation analyses were used to determine the relationships between the topological metrics showing significant between-group differences and the clinical variables for adolescent MDD patients.

RESULTS

Small-world architecture in brain functional networks was identified for both the MDD and control groups. However, depressed adolescents exhibited lower characteristic path length, normalized characteristic path length and clustering coefficient, and higher global efficiency than controls (false discovery rate [FDR] q < 0.05). Compared with controls, depressed adolescents exhibited increased nodal centralities in the default mode regions, including the right anterior cingulate and paracingulate gyri, left posterior cingulate gyrus, right superior frontal gyrus (medial part), bilateral hippocampus, and bilateral parahippocampal gyrus, and decreased nodal centralities in the orbitofrontal, temporal, and occipital regions (FDR q < 0.05).

DATA CONCLUSION

This study indicated that drug-naïve, first-episode adolescent MDD patients exhibit disruptions in whole-brain functional networks.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 2 J. MAGN. RESON. IMAGING 2020;52:1790-1798.

Adjunct ketamine treatment of depression in treatment-resistant schizophrenia patients is unsatisfactory in pilot and secondary follow-up studies

OBJECTIVE

To investigate the effects of adjunct ketamine treatment on chronic treatment-resistant schizophrenia patients with treatment-resistant depressive symptoms (CTRS-TRD patients), including alterations in brain function.

METHODS

Intravenous ketamine (0.5 mg/kg body weight) was administered to CTRS-TRD patients over a 1-hr period on days 1, 4, 7, 10, 13, 16, 19, 22, and 25 of our initial pilot study. This treatment method was subsequently repeated 58 days after the start of the pilot study for a secondary follow-up study. Calgary Depression Scale for Schizophrenia (CDSS), Positive and Negative Syndrome Scale (PANSS), and regional homogeneity (ReHo) results were used to assess treatment effects and alterations in brain function throughout the entire duration of our studies.

RESULTS

Between day 7 and day 14 of the first treatment, CDSS scores were reduced by 63.8% and PANSS scores were reduced by 30.04%. In addition, ReHo values increased in the frontal, temporal, and parietal lobes. However, by day 21, depressive symptoms relapsed. During the second treatment period, CDSS and PANSS scores exhibited no significant differences compared to baseline between day 58 and day 86. On day 65, ReHo values were higher in the temporal, frontal, and parietal lobes. However, on day 79, the increase in ReHo values completely disappeared.

CONCLUSIONS

Depressive symptoms in CTRS-TRD patients were alleviated with adjunct ketamine treatment for only 1 week during the first treatment period. Moreover, after 1 month, the antidepressant effects of ketamine on CTRS-TRD patients completely disappeared. Correspondingly, ReHo alterations induced by ketamine in the CTRS-TRD patients were not maintained for more than 3 weeks. These pilot findings indicate that adjunct ketamine treatment is not satisfactory for CTRS-TRD patients.

Meta-analysis of cortical thickness abnormalities in medication-free patients with major depressive disorder

Alterations in cortical thickness have been identified in major depressive disorder (MDD), but findings have been variable and inconsistent. To date, no reliable tools have been available for the meta-analysis of surface-based morphometric (SBM) studies to effectively characterize what has been learned in previous studies, and drug treatments may have differentially impacted findings. We conducted a comprehensive meta-analysis of magnetic resonance imaging (MRI) studies that explored cortical thickness in medication-free patients with MDD, using a newly developed meta-analytic mask compatible with seed-based d mapping (SDM) meta-analytic software. We performed the meta-regression to explore the effects of demographics and clinical characteristics on variation in cortical thickness in MDD. Fifteen studies describing 529 patients and 586 healthy controls (HCs) were included. Medication-free patients with MDD, relative to HCs, showed a complex pattern of increased cortical thickness in some areas (posterior cingulate cortex, ventromedial prefrontal cortex, and anterior cingulate cortex) and decreased cortical thickness in others (gyrus rectus, orbital segment of the superior frontal gyrus, and middle temporal gyrus). Most findings in the whole sample analysis were confirmed in a meta-analysis of studies recruiting medication-naive patients. Using the new mask specifically developed for SBM studies, this SDM meta-analysis provides evidence for regional cortical thickness alterations in MDD, mainly involving increased cortical thickness in the default mode network and decreased cortical thickness in the orbitofrontal and temporal cortex.

Volumetric Deficit Within the Fronto-Limbic-Striatal Circuit in First-Episode Drug Naïve Patients With Major Depression Disorder

Background: Depression is a major psychiatric disorder and the leading cause of disability worldwide. Previous evidence suggested certain pattern of structural alterations were induced by major depression disorder (MDD) with heterogeneity due to patients' clinical characteristics and proposed that early impairment of fronto-limbic-striatal circuit was involved. Yet the hypothesis couldn't be replicated fully. Accordingly, this study aimed to validate this hypothesis in a new set of first-episode, drug naïve MDD patients and further explore the neuroimaging biomarker of illness severity using whole-brain voxel-based morphometry (VBM). Materials and Methods: A total of 93 participants, 30 patients with first-episode medication-naïve MDD, and 63 healthy controls were enrolled in the study. VBM was applied to analyze differences in the gray matter volume (GMV) between these two groups. The correlation between the GMV of the identified brain regions and the severity of clinical symptoms quantified by the Hamilton Depression Scale (HAMD) was further conducted in the post-hoc analysis to confirm the role of GMV structural alteration in clinical symptoms. Results: Our results revealed that the brain gray matter volume of the prefrontal lobe, limbic system, striatum, cerebellum, temporal lobe, and bilateral lingual gyri were significantly decreased in MDD patients compared with healthy controls. Besides, the HAMD scores were negatively correlated with GMV of the right insula and positively correlated with that of the right lingual gyrus. Conclusions: Our findings provide robust evidence that gray matter structural abnormalities within the prefronto-limbic-striatal circuit are implicated in the pathophysiology of MDD at an early stage without confounding influence of medication status. Besides, our data suggest that the cerebellum, lingual gyrus, and fusiform gyrus should also be integrated into the brain alterations in MDD. Future synthesis of individual neuroimaging studies and more advanced statistical analysis comparing subfields of the aforementioned regions are warranted to further shed light on the neurobiology of the disease and assist in the diagnosis of this burdensome disorder.

Effects of Chaihu-Shugan-San capsule for psychogenic erectile dysfunction: Study protocol of a randomized placebo-controlled trial

BACKGROUND

Erectile dysfunction (ED) affects many adult men worldwide. Many studies on the brain of psychogenic ED have shown significant cerebral functional changes and reduced volume of gray matter and white matter microstructural alterations in widespread brain regions. Chaihu-Shugan-San (CHSGS) capsule has been used to treat ED from the 20th century in China. However, clinical research of CHSGS capsule in the treatment of ED was lack. We design this study to evaluate the efficacy and safety of CHSGS capsule in the treatment of patients suffering from psychogenic ED. Furthermore, we also aim to provide a new evidence as well as an innovation of the clinical treatment in psychogenic ED.

METHODS

This study is designed as a multi-center, 3-arms, randomized trial. From the perspective of psychogenic ED, we will divide patients into 3 groups, which are placebo group, tadalafil group and CHSGS group. One hundred thirty-five patients will be randomly allocated to receive placebo, CHSGS capsule or tadalafil oral pharmacotherapy. After the period of 4-week treatment, the outcome of primary assessment changes in the brain MRI, IIEF-5, EHS, and QEQ total scores from baseline. Secondary assessments include the SEAR, HAMA-14, HAMD-17 scores, response rate of the patients and their partners.

DISCUSSION

We designed this study based on previous research about psychogenic erectile dysfunction (ED). This study will provide objective evidences to evaluate the effects of CHSGS capsule as an adjuvant treatment for psychogenic ED.

TRIAL REGISTRATION NUMBER

chictr.org.cn, ChiCTR-IOR-1800018301.

Differing Spontaneous Brain Activity in Healthy Adults with Two Different Body Constitutions: A Resting-State Functional Magnetic Resonance Imaging Study

Traditional Chinese medicine (TCM) practitioners assess body constitution (BC) as a treatment basis for maintaining body homeostasis. We investigated patterns in spontaneous brain activity in different BC groups using resting-state functional magnetic resonance imaging (rsfMRI) and determined the relationship between these patterns and quality of life (QOL). Thirty-two healthy individuals divided into two groups (body constitution questionnaire (BCQ)-gentleness [BCQ-G] and BCQ-deficiency [BCQ-D]) based on the body constitution questionnaire (BCQ) underwent rsfMRI to analyze regional homogeneity (ReHo) and the amplitude of low-frequency fluctuation (ALFF). The World Health Organization Quality of Life Instruments (brief edition) scale was used to evaluate the QOL. The BCQ-G group (n = 18) had significantly greater ReHo values in the right postcentral gyrus and lower ALFF values in the brainstem than the BCQ-D group (n = 14). In the BCQ-D group, decreased ReHo of the postcentral gyrus correlated with better physiological functioning; increased ALFF in the brainstem correlated with poor QOL. BCQ-subgroup analysis revealed a nonsignificant correlation between ReHo and Yang deficiency/phlegm and stasis (Phl & STA). Nonetheless, the BCQ-D group showed a positive correlation between ALFF and Phl & STA in the parahippocampus. This study identified differences between BCQ-G and BCQ-D types of healthy adults based on the rsfMRI analysis. The different BCQ types with varied brain endophenotypes may elucidate individualized TCM treatment strategies.

Abnormal coupling among spontaneous brain activity metrics and cognitive deficits in major depressive disorder

BACKGROUND

A variety of functional metrics derived from resting-state functional magnetic resonance imaging (rs-fMRI) have been employed to explore spontaneous brain activity changes in major depressive disorder (MDD) and have enjoyed significant success in unraveling the neurobiological mechanisms underlying this disorder. However, it is unclear whether spatial and temporal coupling relationships among these rs-fMRI metrics are altered in MDD.

METHODS

50 patients with MDD and 36 well-matched healthy controls underwent rs-fMRI scans. A dynamic analysis was applied to compute multiple frequently used metrics including fractional amplitude of low frequency fluctuations, regional homogeneity, voxel-mirrored homotopic connectivity, degree centrality and global signal connectivity. Kendall's W was used to calculate volume-wise (across voxels) and voxel-wise (across time windows) concordance among these metrics. Inter-group differences in the concordance and their associations with clinical and cognitive variables were tested.

RESULTS

Compared to healthy controls, patients with MDD showed decreased whole gray matter volume-wise concordance. Despite similar spatial distributions, quantitative comparison analysis revealed that MDD patients exhibited reduced voxel-wise concordance in multiple cortical and subcortical regions. Moreover, the lower concordance was associated with worse performances in prospective memory and sustained attention in the MDD group.

LIMITATIONS

The study design of fairly modest sample size did not allow us to perform a full analysis of the potential effects of medication and illness duration.

CONCLUSIONS

Our findings suggest that spatial and temporal decoupling of multiple resting-state brain activity metrics may help elucidate the neural mechanisms of cognitive deficits in depression.