Reduced grey matter volume in frontal and temporal areas in depression: contributions from voxel-based morphometry study

Scientific psychiatry within technical reach

This is an invited commentary on the paper by Zou et al, accepted for publication in World Journal of Psychiatry. It reflects the findings of the authors in the broader context of the search for scientifically sound and evidence based nomothetic system for diagnosis and treatment in psychiatry, with a special focus on the application of translational neuroimaging in that effort.

Neurofind: using deep learning to make individualised inferences in brain-based disorders

Within precision psychiatry, there is a growing interest in normative models given their ability to parse heterogeneity. While they are intuitive and informative, the technical expertise and resources required to develop normative models may not be accessible to most researchers. Here we present Neurofind, a new freely available tool that bridges this gap by wrapping sound and previously tested methods on data harmonisation and advanced normative models into a web-based platform that requires minimal input from the user. We explain how Neurofind was developed, how to use the Neurofind website in four simple steps ( www.neurofind.ai ), and provide exemplar applications. Neurofind takes as input structural MRI images and outputs two main metrics derived from independent normative models: (1) Outlier Index Score, a deviation score from the normative brain morphology, and (2) Brain Age, the predicted age based on an individual's brain morphometry. The tool was trained on 3362 images of healthy controls aged 20-80 from publicly available datasets. The volume of 101 cortical and subcortical regions was extracted and modelled with an adversarial autoencoder for the Outlier index model and a support vector regression for the Brain age model. To illustrate potential applications, we applied Neurofind to 364 images from three independent datasets of patients diagnosed with Alzheimer's disease and schizophrenia. In Alzheimer's disease, 55.2% of patients had very extreme Outlier Index Scores, mostly driven by larger deviations in temporal-limbic structures and ventricles. Patients were also homogeneous in how they deviated from the norm. Conversely, only 30.1% of schizophrenia patients were extreme outliers, due to deviations in the hippocampus and pallidum, and patients tended to be more heterogeneous than controls. Both groups showed signs of accelerated brain ageing.

Identifying major depressive disorder based on cerebral blood flow and brain structure: An explainable multimodal learning study

Magnetic resonance imaging (MRI) offers non-invasive assessments of brain structure and function for analyzing brain disorders. With the increasing accumulation of multimodal MRI data in recent years, integrating information from various modalities has become an effective strategy for improving the detection of brain disorders. This study focuses on identifying major depressive disorder (MDD) by using arterial spin labeling (ASL) perfusion MRI in conjunction with structural MRI data. We collected ASL and structural MRI data from 260 participants, including 169 MDD patients and 91 healthy controls. We developed an explainable fusion method to identify MDD, utilizing cerebral blood flow (CBF) data from ASL perfusion MRI and brain tissue volumes from structural MRI. The fusion model, which integrates multimodal data, demonstrated superior predictive performance for MDD. By combining MRI regional volumes with CBF data, we achieved more effective results than using each modality independently. Additionally, we analyzed feature importance and interactions to explain the fusion model. We identified fourteen important features, comprising eight regional volumes and six regional CBF measures, that played a crucial role in the identification of MDD. Furthermore, we found three feature interactions among the important features and seven interactions between structural and functional features, which were particularly prominent in the model. The results of this study suggest that the fusion learning approach, which integrates ASL and structural MRI data, is effective in detecting MDD. Moreover, the study demonstrates that the model explanation method can reveal key features that influence the decisions of models, as well as potential interactions among these key features or between functional and structural features in identifying MDD.

Depressive symptoms are linked to age-specific neuroanatomical and cognitive variations

Depression is a heterogeneous disorder, both in terms of patient symptomatology and in patient sociodemographic factors. Here, we examine the contribution of age to this heterogeneity, by characterizing the associations of depressive symptoms with cognitive performance and brain structure across the lifespan. We analyzed data from the Cambridge Centre for Aging Neuroscience (Cam-CAN) cohort (N = 2591, age 18-99). A subset of this cohort (N = 647) underwent structural MRI. Depressive symptoms were measured using the Hospital Anxiety and Depression Scale. Cognitive assessments were performed using The Addenbrooke's Cognitive Examination Revised. Generalized linear models were employed to examine the relationship between depressive symptoms and cognitive performance. Statistical parametric mapping explored age-dependent associations between depressive symptoms and grey matter volume. Cognitive performance was associated with a significant age by depression by cognitive domain interaction, indicating that older individuals with more depressive symptoms had a lower cognitive performance, particularly in the fluency domain. Structural MRI revealed preferential depression-related reduction in grey matter volume in the left and right hippocampi in older adults. By contrast, in younger adults, depressive symptoms were more strongly associated with grey matter volume reduction in the left superior frontal gyrus and left middle frontal gyrus. Collectively, these findings indicate that the associations of depression with cognitive performance and brain structure are age-dependent, suggesting that the pathophysiological mechanisms underlying depression may differ between young and older adults. Recognizing these differences will support the development of better diagnostic tools and therapeutic interventions for depression across the lifespan.

Neuroanatomical substrates of depression in dementia with Lewy bodies and Alzheimer's disease

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) are often associated with depressive symptoms from the prodromal stage. The aim of the present study was to investigate the neuroanatomical correlates of depression in prodromal to mild DLB patients compared with AD patients. Eighty-three DLB patients, 37 AD patients, and 18 healthy volunteers were enrolled in this study. Depression was evaluated with the Mini International Neuropsychiatric Interview (MINI), French version 5.0.0. T1-weighted three-dimensional anatomical images were acquired for all participants. Regression and comparison analyses were conducted using a whole-brain voxel-based morphometry (VBM) approach on the grey matter volume (GMV). DLB patients presented a significantly higher mean MINI score than AD patients (p = 0.004), 30.1% of DLB patients had clinical depression, and 56.6% had a history of depression, while 0% of AD patients had clinical depression and 29.7% had a history of depression. VBM regression analyses revealed negative correlations between the MINI score and the GMV of right prefrontal regions in DLB patients (p < 0.001, uncorrected). Comparison analyses between DLB patients taking and those not taking an antidepressant mainly highlighted a decreased GMV in the bilateral middle/inferior temporal gyrus (p < 0.001, uncorrected) in treated DLB patients. In line with the literature, our behavioral analyses revealed higher depression scores in DLB patients than in AD patients. We also showed that depressive symptoms in DLB are associated with decreased GMV in right prefrontal regions. Treated DLB patients with long-standing depression would be more likely to experience GMV loss in the bilateral middle/inferior temporal cortex. These findings should be taken into account when managing DLB patients.

Disruptive and complementary effects of depression symptoms on spontaneous brain activity in the subcortical vascular mild cognitive impairment

Background

Although depression symptoms are commonly reported in patients with subcortical vascular mild cognitive impairment (svMCI), their impact on brain functions remains largely unknown, with diagnoses mainly dependent on behavioral assessments.

Methods

In this study, we analyzed resting-state fMRI data from a cohort of 34 svMCI patients, comprising 18 patients with depression symptoms (svMCI+D) and 16 patients without (svMCI-D), along with 34 normal controls (NC). The study used the fraction of the amplitude of low-frequency fluctuations (fALFF), resting-state functional connectivity, correlation analyses, and support vector machine (SVM) techniques.

Results

The fALFF of the right cerebellum (CERE.R) differed among the svMCI+D, svMCI-D, and NC groups. Specifically, the regional mean fALFF of CERE. R was lower in svMCI-D patients compared to NC but higher in svMCI+D patients compared to svMCI-D patients. Moreover, the adjusted fALFF of CERE. R showed a significant correlation with Montreal Cognitive Assessment (MOCA) scores in svMCI-D patients. The fALFF of the right orbital part of the superior frontal gyrus was significantly correlated with Hamilton Depression Scale scores in svMCI+D patients, whereas the fALFF of the right postcingulate cortex (PCC.R) showed a significant correlation with MOCA scores in svMCI-D patients. Furthermore, RSFC between PCC. R and right precuneus, as well as between CERE. R and the right lingual gyrus (LING.R), was significantly reduced in svMCI-D patients compared to NC. In regional analyses, the adjusted RSFC between PCC. R and PreCUN. R, as well as between CERE. R and LING. R, was decreased in svMCI-D patients compared to NC but increased in svMCI+D patients compared to svMCI-D. Further SVM analyses achieved good performances, with an area under the curve (AUC) of 0.82 for classifying svMCI+D, svMCI-D, and NC; 0.96 for classifying svMCI+D and svMCI-D; 0.82 for classifying svMCI+D and NC; and 0.92 for classifying svMCI-D and NC.

Conclusion

The study revealed disruptive effects of cognitive impairment, along with both disruptive and complementary effects of depression symptoms on spontaneous brain activity in svMCI. Moreover, these findings suggest that the identified features might serve as potential biomarkers for distinguishing between svMCI+D, svMCI-D, and NC, thereby guiding clinical treatments such as transcranial magnetic stimulation for svMCI.

Towards New Methodology for Cross-Validation of Clinical Evaluation Scales and Functional MRI in Psychiatry

Objective biomarkers have been a critical challenge for the field of psychiatry, where diagnostic, prognostic, and theranostic assessments are still based on subjective narratives. Psychopathology operates with idiographic knowledge and subjective evaluations incorporated into clinical assessment inventories, but is considered to be a medical discipline and, as such, uses medical intervention methods (e.g., pharmacological, ECT; rTMS; tDCS) and, therefore, is supposed to operate with the language and methods of nomothetic networks. The idiographic assessments are provisionally "quantified" into "structured clinical scales" to in some way resemble nomothetic measures. Instead of fostering data merging and integration, this approach further encapsulates the clinical psychiatric methods, as all other biological tests (molecular, neuroimaging) are performed separately, only after the clinical assessment has provided diagnosis. Translational cross-validation of clinical assessment instruments and fMRI is an attempt to address the gap. The aim of this approach is to investigate whether there exist common and specific neural circuits, which underpin differential item responses to clinical self-rating scales during fMRI sessions in patients suffering from the two main spectra of mental disorders: schizophrenia and major depression. The current status of this research program and future implications to promote the development of psychiatry as a medical discipline are discussed.

Hypergraph Structural Information Aggregation Generative Adversarial Networks for Diagnosis and Pathogenetic Factors Identification of Alzheimer's Disease With Imaging Genetic Data

Alzheimer's disease (AD) is a neurodegenerative disease with profound pathogenetic causes. Imaging genetic data analysis can provide comprehensive insights into its causes. To fully utilize the multi-level information in the data, this article proposes a hypergraph structural information aggregation model, and constructs a novel deep learning method named hypergraph structural information aggregation generative adversarial networks (HSIA-GANs) for the automatic sample classification and accurate feature extraction. Specifically, HSIA-GAN is composed of generator and discriminator. The generator has three main functions. First, vertex graph and edge graph are constructed based on the input hypergraph to present the low-order relations. Second, the low-order structural information of hypergraph is extracted by the designed vertex convolution layers and edge convolution layers. Finally, the synthetic hypergraph is generated as the input of the discriminator. The discriminator can extract the high-order structural information directly from hypergraph through vertex-edge convolution, fuse the high and low-order structural information, and finalize the results through the full connection (FC) layers. Based on the data acquired from AD neuroimaging initiative, HSIA-GAN shows significant advantages in three classification tasks, and extracts discriminant features conducive to better disease classification.

The effect of the Yara smartphone application on anxiety, sleep quality, and suicidal thoughts in patients with major depressive disorder in Iran: a randomized controlled trial

BACKGROUND

Depression is one of the most common mental disorders that leads to anxiety, sleep disturbances, and suicidal thoughts. Due to the high cost of treatment and the reluctance of many patients to seek medical help, major depressive disorder (MDD) is becoming more prevalent. Therefore, alternative methods like smartphone applications can help prevent and improve depression symptoms. The present study aimed to determine the effect of the newly developed Yara smartphone application on anxiety, sleep quality, and suicidal thoughts in patients with MDD.

METHODS

This randomized controlled trial with a pretest-posttest design was conducted on Iranian patients with MDD in 2022. Sixty-four patients were recruited using convenience sampling and randomly assigned to two control and intervention groups. The intervention was conducted using the Yara smartphone application for three months. Data were collected using the Spielberger State-Trait Anxiety Inventory (STAI), Pittsburgh Sleep Quality Index (PSQI), and Beck Scale for Suicidal Ideation (BSSI). Data were first entered into IBM SPSS Statistics for Windows, version 22 (IBM Corp., Armonk, N.Y., USA) and then analyzed using descriptive and analytical statistics.

RESULTS

There was no statistically significant difference in the mean score of anxiety and sleep quality between the intervention and control groups before the intervention (p ≥ .05). However, this difference in the mean score of anxiety and sleep quality was statistically significant in the two groups after the intervention (p < .05). The results showed no statistically significant difference in the mean score of suicidal thoughts between the two groups before and after the intervention (p ≥ .05). The use of the Yara smartphone application had a significant positive effect on anxiety and sleep quality in depressed patients (p < .001). At the same time, it had no significant effect on suicidal thoughts (p ≥ .05).

CONCLUSION

Considering the positive effect of using the Yara smartphone application on reducing anxiety and improving sleep quality in depressed patients, this application can help alleviate the problems of depressed patients alongside existing treatment methods. Thus, this application is recommended for this group of patients in psychiatric clinics and departments. The Yara application's effectiveness was not approved on suicidal thoughts in this study so that further investigation would be necessary.

TRIAL REGISTRATION

Iranian Registry of Clinical Trial approval code (IRCT# IRCT20131112015390N7).

Elevated VCAM-1 levels in peripheral blood are associated with brain structural and functional alterations in major depressive disorder

BACKGROUND

Vascular cell adhesion molecule-1 (VCAM-1) is a well-known biomarker of endothelial activation. This study aimed to determine whether changes in peripheral VCAM-1 levels occurred in major depressive disorder (MDD) patients and explored immune-brain interactions based on neuroimaging.

METHODS

This study included 165 subjects (80 healthy controls [HCs] and 85 MDD patients). Of them, 133 underwent magnetic resonance imaging. VCAM-1 was measured using a commercially available Enzyme-Linked Immunosorbent Assay kit following the manufacturer's instructions. The gray matter volume (GMV) and surface-based functional connectivity (FC) were calculated based on Schaefer parcellation 400 parcels.

RESULTS

Compared with the HCs, MDD patients exhibited significantly higher level of VCAM-1. The correlation analysis showed that VCAM-1 had a significant negative correlation with GMV of the right medial frontal cortex (MFC) and postcentral (PostCG). The mediation analyses showed that VCAM-1 mediated the association between group and GMV of PostCG and the FC of left ventral prefrontal cortex (vPFC) with right inferior parietal lobe (IPL).

CONCLUSIONS

This study showed that a high level of VCAM-1 was associated to the decreased GMV in the right MFC and PostCG, and mediated the FC of the left vPFC with right IPL. These findings suggested that VCAM-1 might contribute to the etiology of MDD by influencing brain structure and function.

LIMITATIONS

The cross-sectional design makes it difficult to determine the causal relationship and dynamic effect among VCAM-1, brain structure/function features, and depressive symptoms.

Gender differences in brain region activation during verbal fluency task as detected by fNIRS in patients with depression

BACKGROUND

Gender plays a role in the mechanisms of depression, but fewer studies have focused on gender differences in the abnormal activation of brain regions when patients perform specific cognitive tasks.

METHODS

A total of 110 major depressive disorder (MDD) patients and 106 healthy controls were recruited. The relative change in oxygen-haemoglobin (oxy-Hb) concentration during the verbal fluency task were measured by a 52-channel near-infra-red spectroscopy (NIRS) system. Differences in brain region activation between patients and healthy controls and between genders of depression patients were compared.

RESULTS

MDD patients demonstrated significantly decreased [oxy-Hb] changes in the right inferior frontal gyrus (p = 0.043) compared to healthy controls. A marked increase in leftward functional language lateralisation in the inferior frontal gyrus was observed in the MDD group in contrast to the HC group (p = 0.039). Furthermore, female patients in the MDD group exhibited significant reductions in [oxy-Hb] changes in the right frontal region (specifically, the superior and middle frontal gyrus; p = 0.037) compared with male patients.

CONCLUSIONS

Gender impacts depression-related brain activation during cognitive tasks, potentially influencing depression's pathogenesis.

Negative association between DNA methylation in brain-derived neurotrophic factor exon VI and left superior parietal gyrification in major depressive disorder

OBJECTIVE

We have recently reported significantly higher DNA methylation in brain-derived neurotrophic factor (BDNF) exon VI in major depressive disorder (MDD). This study aimed to investigated cortical changes and their associations with DNA methylations in BDNF exon VI in MDD.

METHODS

Data of 93 patients with MDD and 59 controls were involved in statistics. General linear regressions (GLM) were performed to analyze thickness and gyrification changes in MDD and their association with DNA methylation in BDNF exon VI in patients with MDD and controls.

RESULTS

Significantly decreased cortical thickness (CT) in left lateral orbitofrontal cortex (LOFC), left superior temporal lobe (ST) and right frontal pole (FP) and decreased local gyrification index (lGI) in left superior parietal lobe (SP) were found in MDD. The associations between DNA methylation in 3 CpG sites in BDNF exon VI and lGI in left SP were significantly different in patients and controls. DNA methylations in BDNF132 (β = -0.359, P < 0.001), BDNF137 (β = -0.214, P = 0.032), and BDNF151 (β = -0.223, P = 0.025) were significantly negatively associated with lGI in left SP in MDD.

CONCLUSION

The negative association between BDNF exon VI methylation and lGI in left SP might imply a potential epigenetic marker associated with cortical gyrification reduction in patients with MDD.

Altered gray matter volume and functional connectivity in lung cancer patients with bone metastasis pain

Bone metastasis pain (BMP) is a severe chronic pain condition. Our previous studies on BMP revealed functional brain abnormalities. However, the potential effect of BMP on brain structure and function, especially gray matter volume (GMV) and related functional networks, have not yet been clearly illustrated. Voxel-based morphometry and functional connectivity (FC) analysis methods were used to investigate GMV and intrinsic FC differences in 45 right-handed lung cancer patients with BMP(+), 37 lung cancer patients without BMP(-), and 45 healthy controls (HCs). Correlation analysis was performed thereafter with all clinical variables by Pearson correlation. Compared to HCs, BMP(+) group exhibited decreased GMV in medial frontal gyrus (MFG) and right middle temporal gyrus (MTG). Compared with BMP(-) group, BMP(+) group exhibited reduced GMV in cerebelum_6_L and left lingual gyrus. However, no regions with significant GMV differences were found between BMP(-) and HCs groups. Receiver operating characteristic analysis indicated the potential classification power of these aberrant regions. Correlation analysis revealed that GMV in the right MTG was positively associated with anxiety in BMP(+) group. Further FC analysis demonstrated enhanced interactions between MFG/right MTG and cerebellum in BMP(+) patients compared with HCs. These results showed that BMP was closely associated with cerebral alterations, which may induce the impairment of pain moderation circuit, deficits in cognitive function, dysfunction of emotional control, and sensorimotor processing. These findings may provide a fresh perspective and further neuroimaging evidence for the possible mechanisms of BMP. Furthermore, the role of the cerebellum in pain processing needs to be further investigated.

Cross‐Validation of Paranoid and Depressive Scales: Results From Functional MRI Group Independent Component Analysis

Objective: Based on earlier research, we hypothesized that patient response to diagnostically relevant items (paranoid (DP) and depressive (DS)) from clinical self‐assessment scale (PD‐S) could be cross‐validated when performed simultaneously with task‐based fMRI, resulting in specific and common neural circuit activations in response to the PDS items. In the current study, we tried to overcome one of the limitations of our previous research, namely, the lack of a healthy control (HC) group. Thus, our aim was to investigate the possible differences between patients with schizophrenia (SCZ) and depression and HCs using independent component analysis.

Methods: A total of 72 subjects participated in this study, including 21 HCs, 26 patients with SCZ, and 25 patients with major depressive episode (DEP). Patients were scanned on a 3Т MRI system using a functional MRI task representing statements from DP‐DS scale and diagnostically neutral (DN) statements. The data were processed using group independent component analysis for fMRI toolbox (GIFT).

Results: Five components were identified as task‐related, but only three of them were found to demonstrate statistical difference between SCZ, DEP, and HC, namely, components 6, 7, and 9. The contrast between SCZ and HC was presented by Component 6 (cingulate gyrus and basal ganglia), which exhibited significant difference when comparing all three active conditions. On the other hand, SCZ and DEP group differences were presented by Component 7 for DS‐DN comparison (frontoparietal network and superior temporal gyrus) and Component 9 (medial frontal gyrus, precuneus, angular gyrus, and among others) which highlighted preferential processing related to the DP‐DN and the DS‐DP comparison.

Conclusion: Our results demonstrate differences in brain circuits processing preferentially diagnostic stimuli across the three groups. Those circuits involve mainly networks of cognitive and affective functioning, which provides insights in their role for pathophysiology of SCZ and DEP. This evidence fosters the theory of transdisciplinary validation, where neurobiological measure such as functional MRI is determined as external validity operation for the diagnostic assessment scales. This can facilitate the use of clinical evaluation methods as proxy measures of brain functions.

Gray matter abnormalities in patients with major depressive disorder and social anxiety disorder: a voxel-based meta-analysis

BACKGROUND

Major depressive and social anxiety disorders have a high comorbidity rate and similar cognitive patterns. However, their unique and shared neuroanatomical characteristics have not been fully identified.

METHODS

Voxel-based morphometric studies comparing gray matter volume between patients with major depressive disorder/social anxiety disorder and healthy controls were searched using 4 electronic databases from the inception to March 2022. Stereotactic data were extracted and subsequently tested for convergence and differences using activation likelihood estimation. In addition, based on the result of the meta-analysis, behavioral analysis was performed to assess the functional roles of the regions affected by major depressive disorder and/or social anxiety disorder.

RESULTS

In total, 34 studies on major depressive disorder with 2873 participants, and 10 studies on social anxiety disorder with 1004 subjects were included. Gray matter volume conjunction analysis showed that the right parahippocampal gyrus region, especially the amygdala, was smaller in patients compared to healthy controls. The contrast analysis of major depressive disorder and social anxiety disorder revealed lower gray matter volume in the right lentiform nucleus and medial frontal gyrus in social anxiety disorder and lower gray matter volume in the left parahippocampal gyrus in major depressive disorder. Behavioral analysis showed that regions with lower gray matter volume in social anxiety disorder are strongly associated with negative emotional processes.

CONCLUSIONS

The shared and unique patterns of gray matter volume abnormalities in patients with major depressive and social anxiety disorder may be linked to the underlying neuropathogenesis of these mental illnesses and provide potential biomarkers. PROSPERO registration number: CRD42021277546.

Altered fractional amplitude of low-frequency fluctuations in the superior temporal gyrus: a resting-state fMRI study in anxious depression

BACKGROUND

Anxious depression, which is a common subtype of major depressive disorder, has distinct clinical features from nonanxious depression. However, little is known about the neurobiological characteristics of anxious depression. In this study, we explored resting-state regional brain activity changes between anxious depression and nonanxious depression.

METHOD

Resting-state functional magnetic resonance (rs-fMRI) imaging data were collected from 60 patients with anxious depression, 38 patients with nonanxious depression, and 60 matched healthy controls (HCs). One-way analysis of variance was performed to compare the whole-brain fractional amplitude of low-frequency fluctuation (fALFF) in the three groups. The correlation between the fALFF values and the clinical measures was examined.

RESULTS

Compared with those of HCs, the fALFF values in the left superior temporal gyrus (STG) in patients with anxious depression were significantly increased, while the fALFF values in the left middle temporal gyrus (MTG), left STG, and right STG in patients with nonanxious depression were significantly increased. Patients with anxious depression showed reduced fALFF values in the right STG compared with patients with nonanxious depression (p < 0.001, corrected). Within the anxious depression group, fALFF value in the right STG was positively correlated with the cognitive disturbance score (r = 0.36, p = 0.005 corrected).

CONCLUSION

The bilateral STG and left MTG, which are related to the default mode network, appear to be key brain regions in nonanxious depression, while the right STG plays an essential role in the neuropathological mechanism of anxious depression.

Sex effects on differentiating patients with major depressive disorder from bipolar disorder in depressive state: A fMRI study with follow-up

BACKGROUND

Bipolar disorder (BD) is difficult to discriminate from major depressive disorder (MDD) before the appearance of mania or hypomania. This study was designed to identify whether patients with MDD and those who converted to BD are distinguishable using dynamic amplitude low-frequency fluctuations (dALFF) and describe the sex effects on the identification of the two disorders.

METHODS

We compared the dALFF values of 35 BD patients who converted from MDD during the 2-year follow-up, 99 MDD patients, and 130 healthy controls (HCs) using two-way ANOVA. Pearson's correlation was used to compare dALFF in dysfunctional brain regions and clinical characteristics.

RESULTS

A main effect of diagnosis was discovered in the frontal and occipital gyrus. For the main effect of sex, both the left middle occipital gyrus and the medial part of the superior frontal gyrus had higher dALFF values in males compared to females. An interaction of sex and diagnosis effect was observed in the right precentral gyrus. Male MDD patients exhibited a higher dALFF value than male BD patients. Additionally, we discovered a higher dALFF value in females than in males in BD patients. WCST scores were positively associated with dALFF values in the frontal and occipital gyrus in MDD patients. Meanwhile, dALFF values in the occipital gyrus positively correlated with WCST in female MDD patients only.

LIMITATION

Most of the participants were on medication and the sample size was small.

CONCLUSIONS

Our study is the first to find the non-neglectable role of sex effects in differentiating BD and MDD at an early stage.

Lateralized grey matter volume changes in adolescents versus adults with major depression: SDM-PSI meta-analysis

The current study is the first meta-analysis to examine grey matter volume (GMV) changes in adolescents and across the lifespan in major depressive disorder (MDD). Seed-based d mapping-with permutation of subject images (SDM-PSI) has advantages over previous coordinate-based meta-analytical methods (CBMA), such as reducing bias (via the MetaNSUE algorithm) and including non-statistically significant unreported effects. SDM-PSI was used to analyze 105 whole-brain GMV voxel-based morphometry (VBM) studies comparing 6,530 individuals with MDD versus 6,821 age-matched healthy controls (HC). A laterality effect was observed in which adults with MDD showed lower GMV than adult HC in left fronto-temporo-parietal structures (superior temporal gyrus, insula, Rolandic operculum, and inferior frontal gyrus). However, these abnormalities were not statistically significant for adolescent MDD versus adolescent HC. Instead, adolescent MDD showed lower GMV than adult MDD in right temporo-parietal structures (angular gyrus and middle temporal gyrus). These regional differences may be used as potential biomarkers to predict and monitor treatment outcomes as well as to choose the most effective treatments in adolescents versus adults. Finally, due to the paucity of youth, older adult, and longitudinal studies, future studies should attempt to replicate these GMV findings and examine whether they correlate with treatment response and illness severity.

Sex-specific association between prenatal androgenization (second-to-fourth digit length ratio) and frontal brain volumes in adolescents

Prenatal androgenization associates sex-dependently with behavior and mental health in adolescence and adulthood, including risk-taking, emotionality, substance use, and depression. However, still little is known on how it affects underlying neural correlates, like frontal brain control regions. Thus, we tested whether prenatal androgen load is sex-dependently related to frontal cortex volumes in a sex-balanced adolescent sample. In a cross-sectional magnetic resonance imaging study, we examined 61 adolescents (28 males, 33 females; aged 14 or 16 years) and analyzed associations of frontal brain region volumes with the second-to-fourth digit length ratio (2D:4D), an established marker for prenatal androgenization, using voxel-based morphometry in a region-of-interest approach. Lower 2D:4D (indicative of higher prenatal androgen load) correlated significantly with smaller volumes of the right anterior cingulate cortex (r-ACC; β = 0.45) in male adolescents and with larger volumes of the left inferior frontal gyrus orbital part (l-IFGorb; β = - 0.38) in female adolescents. The regression slopes of 2D:4D on the r-ACC also differed significantly between males and females. The study provides novel evidence that prenatal androgenization may influence the development of the frontal brain in a sex- and frontal brain region-specific manner. These effects might contribute to the well-known sex differences in risk-taking, emotionality, substance use, and depression. Future research is needed to elucidate the role of prenatal androgenization within the biopsychosocial model.

Allergen induces depression-like behavior in association with altered prefrontal-hippocampal circuit in male rats

Allergic asthma is a common chronic inflammatory condition associated with psychiatric comorbidities. Notably depression, correlated with adverse outcomes in asthmatic patients. Peripheral inflammation's role in depression has been shown previously. However, evidence regarding the effects of allergic asthma on the medial prefrontal cortex (mPFC)-ventral hippocampus (vHipp) interactions, an important neurocircuitry in affective regulation, is yet to be demonstrated. Herein, we investigated the effects of allergen exposure in sensitized rats on the immunoreactivity of glial cells, depression-like behavior, brain regions volume, as well as activity and connectivity of the mPFC-vHipp circuit. We found that allergen-induced depressive-like behavior was associated with more activated microglia and astrocytes in mPFC and vHipp, as well as reduced hippocampus volume. Intriguingly, depressive-like behavior was negatively correlated with mPFC and hippocampus volumes in the allergen-exposed group. Moreover, mPFC and vHipp activity were altered in asthmatic animals. Allergen disrupted the strength and direction of functional connectivity in the mPFC-vHipp circuit so that, unlike normal conditions, mPFC causes and modulates vHipp activity. Our results provide new insight into the underlying mechanism of allergic inflammation-induced psychiatric disorders, aiming to develop new interventions and therapeutic approaches for improving asthma complications.

Brain structural abnormalities in adult major depressive disorder revealed by voxel- and source-based morphometry: evidence from the REST-meta-MDD Consortium

BACKGROUND

Neuroimaging studies on major depressive disorder (MDD) have identified an extensive range of brain structural abnormalities, but the exact neural mechanisms associated with MDD remain elusive. Most previous studies were performed with voxel- or surface-based morphometry which were univariate methods without considering spatial information across voxels/vertices.

METHODS

Brain morphology was investigated using voxel-based morphometry (VBM) and source-based morphometry (SBM) in 1082 MDD patients and 990 healthy controls (HCs) from the REST-meta-MDD Consortium. We first examined group differences in regional grey matter (GM) volumes and structural covariance networks between patients and HCs. We then compared first-episode, drug-naïve (FEDN) patients, and recurrent patients. Additionally, we assessed the effects of symptom severity and illness duration on brain alterations.

RESULTS

VBM showed decreased GM volume in various regions in MDD patients including the superior temporal cortex, anterior and middle cingulate cortex, inferior frontal cortex, and precuneus. SBM returned differences only in the prefrontal network. Comparisons between FEDN and recurrent MDD patients showed no significant differences by VBM, but SBM showed greater decreases in prefrontal, basal ganglia, visual, and cerebellar networks in the recurrent group. Moreover, depression severity was associated with volumes in the inferior frontal gyrus and precuneus, as well as the prefrontal network.

CONCLUSIONS

Simultaneous application of VBM and SBM methods revealed brain alterations in MDD patients and specified differences between recurrent and FEDN patients, which tentatively provide an effective multivariate method to identify potential neurobiological markers for depression.

Chronic stress, neuroinflammation, and depression: an overview of pathophysiological mechanisms and emerging anti-inflammatories

In a subset of patients, chronic exposure to stress is an etiological risk factor for neuroinflammation and depression. Neuroinflammation affects up to 27% of patients with MDD and is associated with a more severe, chronic, and treatment-resistant trajectory. Inflammation is not unique to depression and has transdiagnostic effects suggesting a shared etiological risk factor underlying psychopathologies and metabolic disorders. Research supports an association but not necessarily a causation with depression. Putative mechanisms link chronic stress to dysregulation of the HPA axis and immune cell glucocorticoid resistance resulting in hyperactivation of the peripheral immune system. The chronic extracellular release of DAMPs and immune cell DAMP-PRR signaling creates a feed forward loop that accelerates peripheral and central inflammation. Higher plasma levels of inflammatory cytokines, most consistently interleukin IL-1β, IL-6, and TNF-α, are correlated with greater depressive symptomatology. Cytokines sensitize the HPA axis, disrupt the negative feedback loop, and further propagate inflammatory reactions. Peripheral inflammation exacerbates central inflammation (neuroinflammation) through several mechanisms including disruption of the blood-brain barrier, immune cellular trafficking, and activation of glial cells. Activated glial cells release cytokines, chemokines, and reactive oxygen and nitrogen species into the extra-synaptic space dysregulating neurotransmitter systems, imbalancing the excitatory to inhibitory ratio, and disrupting neural circuitry plasticity and adaptation. In particular, microglial activation and toxicity plays a central role in the pathophysiology of neuroinflammation. Magnetic resonance imaging (MRI) studies most consistently show reduced hippocampal volumes. Neural circuitry dysfunction such as hypoactivation between the ventral striatum and the ventromedial prefrontal cortex underlies the melancholic phenotype of depression. Chronic administration of monoamine-based antidepressants counters the inflammatory response, but with a delayed therapeutic onset. Therapeutics targeting cell mediated immunity, generalized and specific inflammatory signaling pathways, and nitro-oxidative stress have enormous potential to advance the treatment landscape. Future clinical trials will need to include immune system perturbations as biomarker outcome measures to facilitate novel antidepressant development. In this overview, we explore the inflammatory correlates of depression and elucidate pathomechanisms to facilitate the development of novel biomarkers and therapeutics.

Structural and functional features of treatment-resistant depression: A systematic review and exploratory coordinate-based meta-analysis of neuroimaging studies

OBJECTIVES

A third of people suffering from major depressive disorder do not experience a significant improvement in their symptoms even after adequate treatment with two different antidepressant medications. This common condition, termed treatment-resistant depression (TRD), severely affects the quality of life of millions of people worldwide, causing long-lasting interpersonal problems and social costs. Given its epidemiological and clinical relevance and the little consensus on whether the neurobiological underpinnings of TRD differ from treatment-sensitive depression (TSD), we sought to highlight the convergent morphometric and functional neuroimaging correlates of TRD.

METHODS

We systematically reviewed the published literature on structural and resting-state functional neuroimaging of TRD compared to TSD and healthy controls (HC) and performed exploratory coordinate-based meta-analyses (CBMA) of significant results separately for each modality and multimodally ("all-effects"). CBMAs were also performed for each direction and combining both directions of group contrasts.

RESULTS

Out of the initial 1929 studies, only eight involving 555 participants (189 patients with TRD, 156 with TSD, and 210 HC) were included. In all-effects CBMA, precentral/superior frontal gyrus showed a significant difference between TRD and HC. Functional and structural imaging meta-analyses did not yield statistically significant results. A marginally significant cluster of altered intrinsic activity was found between TRD and HC in the cerebellum/pons.

CONCLUSIONS

Frontal, cerebellar, and brainstem functions can be involved in the pathophysiology of TRD. However, the design and heterogeneity of the (scarce) published literature hinder the generalizability of the findings.

Progressive brain structural abnormality in depression assessed with MR imaging by using causal network analysis

BACKGROUND

As a neuroprogressive illness, depression is accompanied by brain structural abnormality that extends to many brain regions. However, the progressive structural alteration pattern remains unknown.

METHODS

To elaborate the progressive structural alteration of depression according to illness duration, we recruited 195 never-treated first-episode patients with depression and 130 healthy controls (HCs) undergoing T1-weighted MRI scans. Voxel-based morphometry method was adopted to measure gray matter volume (GMV) for each participant. Patients were first divided into three stages according to the length of illness duration, then we explored stage-specific GMV alterations and the causal effect relationship between them using causal structural covariance network (CaSCN) analysis.

RESULTS

Overall, patients with depression presented stage-specific GMV alterations compared with HCs. Regions including the hippocampus, the thalamus and the ventral medial prefrontal cortex (vmPFC) presented GMV alteration at onset of illness. Then as the illness advanced, others regions began to present GMV alterations. These results suggested that GMV alteration originated from the hippocampus, the thalamus and vmPFC then expanded to other brain regions. The results of CaSCN analysis revealed that the hippocampus and the vmPFC corporately exerted causal effect on regions such as nucleus accumbens, the precuneus and the cerebellum. In addition, GMV alteration in the hippocampus was also potentially causally related to that in the dorsolateral frontal gyrus.

CONCLUSIONS

Consistent with the neuroprogressive hypothesis, our results reveal progressive morphological alteration originating from the vmPFC and the hippocampus and further elucidate possible details about disease progression 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.

Gray and white matter abnormalities in major depressive disorder patients and its associations with childhood adversity

OBJECTIVE

Early life stress of childhood adversity (CA) may result in major depressive disorder (MDD) by sensitizing individuals to proximal stressors in life events. The neurobiological changes that underlie adult depression may result from the absence of proper care and supervision of caregivers. We aimed to find both gray and white matter abnormalities in MDD patients, who reported the experiences of CA.

METHODS

The present study examined cortical alterations in 54 patients with MDD and 167 healthy controls (HCs) using voxel-based morphology and fractional anisotropy (FA) tract-based spatial statistics (TBSS). Both patients and HCs were administered the self-questionnaire clinical scale (the Korean translation of the Childhood Trauma Questionnaire CTQK). Pearson's correlation analysis was performed to find the associations between FA and CTQK.

RESULTS

The MDD group showed a significant decrease in gray matter (GM) in the left rectus at both the cluster and peak levels after family-wise error correction. The TBSS results showed significantly reduced FA in widespread regions, including the corpus callosum (CC), superior corona radiata, cingulate gyrus, and superior longitudinal fasciculus. The CA was negatively correlated with the FA in CC and crossing pontine tract.

CONCLUSION

Our findings demonstrated GM atrophy and white matter (WM) connectivity changes in patients with MDD. The major findings of the widespread FA reduction in WM provided the evidence of brain alterations in MDD. We further propose that the WM would be vulnerable to emotional, physical, and sexual abuse in early childhood during the brain development.

Associations between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential indicators in major depressive disorder

Background

This study aimed to investigate the correlations between abnormal spontaneous neural activity measured with fractional amplitude of low-frequency fluctuations (fALFF) and clinical variables, eye movements, and event-related potential indicators in patients with major depressive disorder (MDD).

Methods

We recruited 42 patients with MDD and 42 healthy controls (HCs) and collected their clinical variables, eye movement, event-related potential, and resting-state functional magnetic resonance imaging (rs-fMRI) data. The fALFF, support vector machine (SVM), and correlation analysis were used to analyze the data.

Results

The results of the study showed that the fALFF values of the sensorimotor network, including the right middle temporal gyrus, right cerebellar Crus2, left occipital gyrus, and left middle temporal gyrus, were significantly higher compared to HCs. Correlation analysis showed that the abnormal fALFF value of the right cerebellar Crus2 was inversely correlated with the active coping scores of the Simplified Coping Style Questionnaire in the patients (r = -0.307, p = 0.048). No correlation was observed between abnormal fALFF values and other clinical symptoms, neuropsychological tests, eye movements, and event-related potential-related indicators in patients with MDD. fALFF values in the left middle temporal gyrus could be used to distinguish patients with MDD from HCs with an accuracy of 78.57%.

Conclusions

Patients with MDD exhibited enhanced spontaneous neural activity in the sensorimotor network. No associations were found between abnormal spontaneous neural activity and clinical variables, eye movements, and event-related potential related indicators in MDD.

Shared and differential fractional amplitude of low-frequency fluctuation patterns at rest in major depressive disorders with or without sleep disturbance

Objective

Sleep disturbances (SD) are commonly found in patients with major depressive disorder (MDD). This study aims to explore the influence of SD symptoms on clinical characteristics in patients with MDD and to investigate the shared and distinct fractional amplitude of low-frequency fluctuation (fALFF) patterns in these patients with or without SD symptoms.

Methods

Twenty-four MDD patients with SD symptoms (Pa_s), 33 MDD patients without SD symptoms (Pa_ns) and 32 healthy controls (HCs) were included in this study. The fALFF and correlation analyses were applied to analyze the features of imaging and clinical data.

Results

Pa_s showed more severe anxiety and depression than Pa_ns. Compared with Pa_ns, Pa_s exhibited increased fALFF value in the left precuneus. Patients shared abnormal fALFF in the frontal-occipital brain regions. There was a positive correlation between fALFF values of the left precuneus and sleep disturbance scores (r = 0.607, p = 0.0000056734) in all patients in addition to a negative correlation between fALFF values of the left MOG/cuneus and HAMD-17 total scores (r = -0.595, p = 0.002141) in Pa_s. The receiver operating characteristic (ROC) results of the fALFF could be used to discriminate Pa_s from Pa_ns with a specificity of 72.73% and a sensitivity of 70.83%.

Conclusion

Pa_s displayed more serious anxiety and depression symptoms. Patients shared abnormal fALFF in the frontal-occipital brain regions, which may be a common characteristic for MDD. And increased fALFF value in the left precuneus might be a specific neuroimaging feature of MDD patients with SD symptoms.

A voxel-based meta-analysis comparing medication-naive patients of major depression with treated longer-term ill cases

Structural neuroimaging studies have identified brain areas implicated in the pathogenesis of major depressive disorder (MDD). However, findings have been inconsistent, potentially due to variable illness duration and effects of antidepressant treatment. Using a meta-analytic approach, we compared gray matter (GM) volumes in patients grouped by medication status (naïve and treated) and illness duration (early course and long-term ill) to identify potential treatment and illness duration effects on brain structure. A total of 70 studies were included, including 3682 patients and 3469 controls. The pooled analysis found frontal, temporal and limbic regions with decreased GM volume in MDD patients. Additional analyses indicated that larger GM volume in the right striatum and smaller GM volume in the right precuneus are likely to be associated with drug effects, while smaller GM volume in the right temporal gyrus may correlate with longer illness duration. Similar GM decreases in bilateral medial frontal cortex between patient subgroups suggest that this alteration may persist over the course of illness and drug treatment.

A novel generation adversarial network framework with characteristics aggregation and diffusion for brain disease classification and feature selection

Imaging genetics provides unique insights into the pathological studies of complex brain diseases by integrating the characteristics of multi-level medical data. However, most current imaging genetics research performs incomplete data fusion. Also, there is a lack of effective deep learning methods to analyze neuroimaging and genetic data jointly. Therefore, this paper first constructs the brain region-gene networks to intuitively represent the association pattern of pathogenetic factors. Second, a novel feature information aggregation model is constructed to accurately describe the information aggregation process among brain region nodes and gene nodes. Finally, a deep learning method called feature information aggregation and diffusion generative adversarial network (FIAD-GAN) is proposed to efficiently classify samples and select features. We focus on improving the generator with the proposed convolution and deconvolution operations, with which the interpretability of the deep learning framework has been dramatically improved. The experimental results indicate that FIAD-GAN can not only achieve superior results in various disease classification tasks but also extract brain regions and genes closely related to AD. This work provides a novel method for intelligent clinical decisions. The relevant biomedical discoveries provide a reliable reference and technical basis for the clinical diagnosis, treatment and pathological analysis of disease.

Structural disconnection-based prediction of poststroke depression

Poststroke depression (PSD) is a common complication of stroke. Brain network disruptions caused by stroke are potential biological determinants of PSD but their conclusive roles are unavailable. Our study aimed to identify the strategic structural disconnection (SDC) pattern for PSD at three months poststroke and assess the predictive value of SDC information. Our prospective cohort of 697 first-ever acute ischemic stroke patients were recruited from three hospitals in central China. Sociodemographic, clinical, psychological and neuroimaging data were collected at baseline and depression status was assessed at three months poststroke. Voxel-based disconnection-symptom mapping found that SDCs involving bilateral temporal white matter and posterior corpus callosum, as well as white matter next to bilateral prefrontal cortex and posterior parietal cortex, were associated with PSD. This PSD-specific SDC pattern was used to derive SDC scores for all participants. SDC score was an independent predictor of PSD after adjusting for all imaging and clinical-sociodemographic-psychological covariates (odds ratio, 1.25; 95% confidence interval, 1.07, 1.48; P = 0.006). Split-half replication showed the stability and generalizability of above results. When added to the clinical-sociodemographic-psychological prediction model, SDC score significantly improved the model performance and ranked the highest in terms of predictor importance. In conclusion, a strategic SDC pattern involving multiple lobes bilaterally is identified for PSD at 3 months poststroke. The SDC score is an independent predictor of PSD and may improve the predictive performance of the clinical-sociodemographic-psychological prediction model, providing new evidence for the brain-behavior mechanism and biopsychosocial theory of PSD.

Functional and structural brain differences in bipolar disorder: a multimodal meta-analysis of neuroimaging studies

BACKGROUND

Numerous studies of resting-state functional imaging and voxel-based morphometry (VBM) have revealed differences in specific brain regions of patients with bipolar disorder (BD), but the results have been inconsistent.

METHODS

A whole-brain voxel-wise meta-analysis was conducted on resting-state functional imaging and VBM studies that compared differences between patients with BD and healthy controls using Seed-based d Mapping with Permutation of Subject Images software.

RESULTS

A systematic literature search identified 51 functional imaging studies (1842 BD and 2190 controls) and 83 VBM studies (2790 BD and 3690 controls). Overall, patients with BD displayed increased resting-state functional activity in the left middle frontal gyrus, right inferior frontal gyrus (IFG) extending to the right insula, right superior frontal gyrus and bilateral striatum, as well as decreased resting-state functional activity in the left middle temporal gyrus extending to the left superior temporal gyrus and post-central gyrus, left cerebellum, and bilateral precuneus. The meta-analysis of VBM showed that patients with BD displayed decreased VBM in the right IFG extending to the right insula, temporal pole and superior temporal gyrus, left superior temporal gyrus extending to the left insula, temporal pole, and IFG, anterior cingulate cortex, left superior frontal gyrus (medial prefrontal cortex), left thalamus, and right fusiform gyrus.

CONCLUSIONS

The multimodal meta-analyses suggested that BD showed similar patterns of aberrant brain activity and structure in the insula extending to the temporal cortex, fronto-striatal-thalamic, and default-mode network regions, which provide useful insights for understanding the underlying pathophysiology of BD.

Pathological fear, anxiety and negative affect exhibit distinct neurostructural signatures: evidence from psychiatric neuroimaging meta-analysis

Internalizing disorders encompass anxiety, fear and depressive disorders, which exhibit overlap at both conceptual and symptom levels. Given that a neurobiological evaluation is lacking, we conducted a Seed-based D-Mapping comparative meta-analysis including coordinates as well as original statistical maps to determine common and disorder-specific gray matter volume alterations in generalized anxiety disorder (GAD), fear-related anxiety disorders (FAD, i.e., social anxiety disorder, specific phobias, panic disorder) and major depressive disorder (MDD). Results showed that GAD exhibited disorder-specific altered volumes relative to FAD including decreased volumes in left insula and lateral/medial prefrontal cortex as well as increased right putamen volume. Both GAD and MDD showed decreased prefrontal volumes compared to controls and FAD. While FAD showed less robust alterations in lingual gyrus compared to controls, this group presented intact frontal integrity. No shared structural abnormalities were found. Our study is the first to provide meta-analytic evidence for distinct neuroanatomical abnormalities underlying the pathophysiology of anxiety-, fear-related and depressive disorders. These findings may have implications for determining promising target regions for disorder-specific neuromodulation interventions (e.g. transcranial magnetic stimulation or neurofeedback).

Altered frequency-specific/universal amplitude characteristics of spontaneous brain oscillations in patients with bipolar disorder

The human brain is a dynamic system with intrinsic oscillations in spontaneous neural activity. Whether the dynamic characteristics of these spontaneous oscillations are differentially altered across different frequency bands in patients with bipolar disorder (BD) remains unclear. This study recruited 65 patients with BD and 85 healthy controls (HCs). The entire frequency range of resting-state fMRI data was decomposed into four frequency intervals. Two-way repeated-measures ANCOVA was employed to detect frequency-specific/universal alterations in the dynamic oscillation amplitude in BD. The patients were then divided into two subgroups according to their mood states to explore whether these alterations were independent of their mood states. Finally, other window sizes, step sizes, and window types were tested to replicate all analyses. Frequency-specific abnormality of the dynamic oscillation amplitude was detected within the posterior medial parietal cortex (centered at the precuneus extending to the posterior cingulate cortex). This specific profile indicates decreased amplitudes in the lower frequency bands (slow-5/4) and no amplitude changes in the higher frequency bands (slow-3/2) compared with HCs. Frequency-universal abnormalities of the dynamic oscillation amplitude were also detectable, indicating increased amplitudes in the thalamus and left cerebellum anterior lobe but decreased amplitudes in the medial superior frontal gyrus. These alterations were independent of the patients' mood states and replicable across multiple analytic and parametric settings. In short, frequency-specific/universal amplitude characteristics of spontaneous oscillations were observed in patients with BD. These abnormal characteristics have important implications for specific functional changes in BD from multiple frequency and dynamic perspectives.

Shared and specific characteristics of regional cerebral blood flow and functional connectivity in unmedicated bipolar and major depressive disorders

BACKGROUND

Identifying brain similarities and differences between bipolar disorder (BD) and major depressive disorder (MDD) can help us better understand their pathophysiological mechanisms and develop more effective treatments. However, the features of whole-brain regional cerebral blood flow (CBF) and intrinsic functional connectivity (FC) underlying BD and MDD have not been directly compared.

METHODS

Eighty-eight unmedicated BD II depression patients, 95 unmedicated MDD patients, and 96 healthy controls (HCs) underwent three-dimensional arterial spin labeling (3D ASL) and resting-state functional MRI (rs-fMRI). The functional properties of whole brain CBF and seed-based resting-state FC further performed based on those regions with changed CBF were analyzed between the three groups.

RESULTS

The patients with BD and MDD showed commonly increased CBF in the left posterior lobe of the cerebellum and the left middle temporal gyrus (MTG) compared with HCs. The CBF of the left MTG was positively associated with 24-items Hamilton Depression Rating Scale scores in MDD patients. Decreased FC between the left posterior lobe of the cerebellum and the left inferior frontal gyrus (IFG) was observed only in patients with BD compared with HCs.

CONCLUSION

Patients with BD and those with MDD shared common features of CBF in the posterior lobe of the cerebellum and the MTG. The altered posterior lobe of the cerebellum-IFG FC can be considered as a potential biomarker for the differentiation of patients with BD from those with MDD.

Morphological brain changes between active and inactive phases of thyroid associated ophthalmopathy: a voxel-based morphometry study

AIM

To explore the morphological brain changes among active thyroid-associated ophthalmopathy (TAO) patients, inactive TAO patients and healthy controls and to investigate the neuropathological relationship of TAO using magnetic resonance imaging (MRI) data.

METHODS

In this observational case-control study, we included 35 inactive TAO patients, 37 active TAO patients and 23 healthy controls. Voxel-based morphometry (VBM) analysis was conducted to evaluate the gray matter volume (GMV) changes among groups, and the correlations between GMV alterations and clinical parameters in active and inactive TAO groups were investigated.

RESULTS

Active TAO patients showed significantly increased GMV in the right inferior frontal gyrus, left superior frontal gyrus (SFG), orbital superior frontal gyrus, orbital middle frontal gyrus, precuneus and postcentral gyrus compared with controls and significantly increased GMV in the right middle temporal gyrus, left SFG and precuneus compared with the inactive TAO group. No significant differences were observed between the inactive TAO group and healthy controls. Notably, the receiver operating characteristic (ROC) curve analysis demonstrated altered GMV among groups and significantly (p<0.001) differentiated active TAO from inactive TAO and healthy controls. In addition, the mean GMV in precuneus and postcentral gyrus were significantly associated with clinical parameters in active TAO.

CONCLUSION

Our findings suggested the localized GMV alterations among groups were associated with the pathophysiology of TAO and served as a potential discriminative pattern to detect clinical phases of TAO at the individual level. The altered brain morphometry may suggest a corresponding process of self-repair and remodeling of the brain structure as the disease progresses in TAO.

Gray Matter Volume Abnormality in Chronic Pain Patients With Depressive Symptoms: A Systemic Review and Meta-Analysis of Voxel-Based Morphometry Studies

Background

Gray matter volume (GMV) alteration in specific brain regions has been widely regarded as one of the most important neuroplasticity features in chronic pain patients with depressive symptoms (CP-D). However, the consistent and significant results were still lacking. Thus, further exploration was suggested to be performed.

Objectives

This study aimed to comprehensively collect the voxel-based morphometry (VBM) studies on GMV alteration between CP-D and healthy controls (HCs). And a systemic review and meta-analysis were made to explore the characteristic brain regions in chronic pain and depression comorbidity.

Methods

Search of PubMed, MEDLINE, Web of Science, and Cochrane Library databases updated to July 13, 2021. The altered GMV between CP-D and HCs in VBM studies was included in this meta-analysis. In total, 18 studies (20 datasets) and 1320 participants (520 patients and 800 HCs) were included. The significant coordinate information (x, y, z) reported in standard space and the effect size (t-value or z-score) were extracted and analyzed by anisotropic effect size-signed differential mapping (AES-SDM) 5.15 software.

Results

According to the main analysis results, CP-D showed significant and consistent increased GMV in the left hippocampus (HIP. L) and decreased GMV in the medial part of the left superior frontal gyrus (SFG. L, BA 10) compared to HCs. Subgroup analysis showed significant decreased GMV in the medial orbital part of SFG.R (BA 10) in neuropathic pain, as well as significant increased GMV in the right parahippocampal gyrus (PHG.R, BA 35), left hippocampus (HIP.L, BA 20), and right middle frontal gyrus (MFG.R) in musculoskeletal pain. Furthermore, meta-regression showed a positive relationship between the decreased GMV in the medial part of SFG.L and the percentage of female patients.

Conclusion

GMV abnormality in specific brain areas (e.g., HIP.L and SFG) was robust and reproducible, which could be significantly involved in this comorbidity disease. The findings in this study may be a valuable reference for future research.

Systematic Review Registration

[www.crd.york.ac.uk/prospero/].

Abnormal Fractional Amplitude of Low Frequency Fluctuation Changes in Patients With Dry Eye Disease: A Functional Magnetic Resonance Imaging Study

Purpose

To investigate spontaneous brain activity in patients with dry eye (DE) and healthy control (HC) using the fractional amplitude of low frequency fluctuation (fALFF) technique with the aim of elucidating the relationship between the clinical symptoms of DE and changes in brain function.

Material and Methods

A total of 28 patients with DE and 28 matched healthy volunteers (10 males and 18 females in each group) were enrolled. Resting-state functional magnetic resonance imaging scans were performed in both groups. Then all subjects were required to complete a comprehensive Hospital Anxiety and Depression Scale (HADS). Receiver operating characteristic (ROC) curve analysis was used to evaluate the differences in fALFF values between the two groups and their diagnostic value. Linear correlations between HADS and fALFF values in different brain regions of DE patients were analyzed using the Pearson correlation coefficient.

Results

Patients with DE had significantly higher fALFF values in the left calcarine sulcus (CS) than the HC group, while fALFF values in the bilateral middle frontal gyrus (MFG) and right MFG/right inferior frontal gyrus (IFG) were significantly lower in DE patients than in HC group. fALFF values had a high diagnostic value for differentiating patients with DE from the HC group (P &lt; 0.001). Right MFG and right MFG/IFG were significantly correlated with HADS values.

Conclusion

Our study found that DE mainly involved functional disorders in the brain areas of the left CS, bilateral MFG and right MFG/right IFG, which helped us to find possible clinical features of DE disease and reflected the potential pathological mechanism of DE.

Association of DNA Methylation of the NLRP3 Gene with Changes in Cortical Thickness in Major Depressive Disorder

The Nod-like receptor pyrin containing 3 (NLRP3) inflammasome has been reported to be a convergent point linking the peripheral immune response induced by psychological stress and neuroinflammatory processes in the brain. We aimed to identify differences in the methylation profiles of the NLRP3 gene between major depressive disorder (MDD) patients and healthy controls (HCs). We also investigated the correlation of the methylation score of loci in NLRP3 with cortical thickness in the MDD group using magnetic resonance imaging (MRI) data. A total of 220 patients with MDD and 82 HCs were included in the study, and genome-wide DNA methylation profiling of the NLRP3 gene was performed. Among the total sample, 88 patients with MDD and 74 HCs underwent T1-weighted structural MRI and were included in the neuroimaging–methylation analysis. We identified five significant differentially methylated positions (DMPs) in NLRP3. In the MDD group, the methylation scores of cg18793688 and cg09418290 showed significant positive or negative correlations with cortical thickness in the occipital, parietal, temporal, and frontal regions, which showed significant differences in cortical thickness between the MDD and HC groups. Our findings suggest that NLRP3 DNA methylation may predispose to depression-related brain structural changes by increasing NLRP3 inflammasome-related neuroinflammatory processes in MDD.

False dogmas in mood disorders research: Towards a nomothetic network approach

The current understanding of major depressive disorder (MDD) and bipolar disorder (BD) is plagued by a cacophony of controversies as evidenced by competing schools to understand MDD/BD. The DSM/ICD taxonomies have cemented their status as the gold standard for diagnosing MDD/BD. The aim of this review is to discuss the false dogmas that reign in current MDD/BD research with respect to the new, data-driven, machine learning method to model psychiatric illness, namely nomothetic network psychiatry (NNP). This review discusses many false dogmas including: MDD/BD are mind-brain disorders that are best conceptualized using a bio-psycho-social model or mind-brain interactions; mood disorders due to medical disease are attributable to psychosocial stress or chemical imbalances; DSM/ICD are the gold standards to make the MDD/BD diagnosis; severity of illness should be measured using rating scales; clinical remission should be defined using threshold values on rating scale scores; existing diagnostic BD boundaries are too restrictive; and mood disorder spectra are the rule. In contrast, our NNP models show that MDD/BD are not mind-brain or psycho-social but systemic medical disorders; the DSM/ICD taxonomies are counterproductive; a shared core, namely the reoccurrence of illness (ROI), underpins the intertwined recurrence of depressive and manic episodes and suicidal behaviors; mood disorders should be ROI-defined; ROI mediates the effects of nitro-oxidative stress pathways and early lifetime trauma on the phenome of mood disorders; severity of illness and treatment response should be delineated using the NNP-derived causome, pathway, ROI and integrated phenome scores; and MDD and BD are the same illness.

Alteration of cortical functional networks in mood disorders with resting-state electroencephalography

Studies comparing bipolar disorder (BD) and major depressive disorder (MDD) are scarce, and the neuropathology of these disorders is poorly understood. This study investigated source-level cortical functional networks using resting-state electroencephalography (EEG) in patients with BD and MDD. EEG was recorded in 35 patients with BD, 39 patients with MDD, and 42 healthy controls (HCs). Graph theory-based source-level weighted functional networks were assessed via strength, clustering coefficient (CC), and path length (PL) in six frequency bands. At the global level, patients with BD and MDD showed higher strength and CC, and lower PL in the high beta band, compared to HCs. At the nodal level, compared to HCs, patients with BD showed higher high beta band nodal CCs in the right precuneus, left isthmus cingulate, bilateral paracentral, and left superior frontal; however, patients with MDD showed higher nodal CC only in the right precuneus compared to HCs. Although both MDD and BD patients had similar global level network changes, they had different nodal level network changes compared to HCs. Our findings might suggest more altered cortical functional network in patients with BD than in those with MDD.

Application of Mass Multivariate Analysis on Neuroimaging Data Sets for Precision Diagnostics of Depression

We used the Mass Multivariate Method on structural, resting-state, and task-related fMRI data from two groups of patients with schizophrenia and depression in order to define several regions of significant relevance to the differential diagnosis of those conditions. The regions included the left planum polare (PP), the left opercular part of the inferior frontal gyrus (OpIFG), the medial orbital gyrus (MOrG), the posterior insula (PIns), and the parahippocampal gyrus (PHG). This study delivered evidence that a multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnoses. Structural, resting-state, or task-related functional MRI modalities cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity combining clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.

Hyperconnectivity between the posterior cingulate and middle frontal and temporal gyrus in depression: Based on functional connectivity meta-analyses

Disrupted whole-brain resting-state functional connectivity (RSFC) of the posterior cingulate (PCC) has been highlighted to associate with cognitive and affective dysfunction in major depressive disorder (MDD). However, prior findings showed certain inconsistency about the RSFC of the PCC in MDD. This study aims to investigate the aberrant RSFC of the PCC in MDD using anisotropic effect-size version of seed-based d mapping (AES-SDM). Web of Science and PubMed were searched for studies investigating PCC-based RSFC in MDD. A total of 17 studies, involving 804 patients and 724 healthy controls (HCs), fit our selection criteria. Additionally, to seek for the link between functional and structural differences, we did a meta-analysis on the studies in conjunction with voxel-based morphology (VBM) analysis. The PCC showed higher RSFC with the left middle temporal gyrus (MTG) and the right middle frontal gyrus (MFG), and lower RSFC with the left superior frontal gyrus (SFG) and the left precuneus in patients with MDD than HCs. Moreover, the meta-regression analysis revealed a negative correlation between the FC alteration of the right MFG with the PCC and depression severity. Notably, the left MTG and the left MFG demonstrated gray matter deviations in conjunction analysis. Our results indicated that the aberrant RSFC between the PCC and brain regions sub-serving cognitive control and emotional regulation in patients with MDD. And such functional alterations may have structural basis. These findings may underlie the mechanisms of deficits in cognitive control and emotional regulation of MDD.

Imaging correlates of depression in progressive supranuclear palsy

Depression is highly common in Progressive Supranuclear Palsy (PSP) and is a meaningful determinant of quality of life. However, neurobiological and neuroimaging correlates of this neuropsychiatric disturbance in PSP patients are still unknown. In this study, we aimed to investigate the topographical distribution of morphometric changes associated with depression in PSP patients using cortical thickness. Forty patients with PSP were evaluated at baseline with clinical rating scales and MRI scans. Based on the response to the 15-item Geriatric Depression Scale we identified 21 PSP patients with depression (GDS-15 score ≥ 5) and 19 PSP patients without depression (GDS-15 score < 5). In vertex-wise analysis, comparison of cortical thickness between PSP patients with and without depression was performed using a general linear model. PSP patients with depressions showed reduced cortical thickness in temporo-parieto-occipital areas, more pronounced in the right hemisphere. These findings propose neurobiological conceptualizations of depression in PSP as being associated with a multiregional pattern of morphometric grey matter reduction.

Habenular Involvement in Response to Subcallosal Cingulate Deep Brain Stimulation for Depression

The habenula (Hb) is a small, evolutionarily conserved epithalamic structure implicated in functions such as reward and mood regulation. Prior imaging work suggests that Hb's structural and functional properties may relate to treatment response in depression and other mood disorders. We used multimodal MRI techniques to investigate the potential involvement of Hb in response to subcallosal cingulate area deep brain stimulation (SCC-DBS) for treatment-resistant mood disorders. Using an automated segmentation technique, we compared Hb volume at baseline and at a subsequent post-operative timepoint (4.4 ± 3.0 years after surgery) in a cohort of 32 patients who received SCC-DBS. Clinical response to treatment (≥50% decrease in HAMD-17 from baseline to 12 months post-operation) was significantly associated with longitudinal Hb volume change: responders tended to have increased Hb volume over time, while non-responders showed decreased Hb volume (t = 2.4, p = 0.021). We additionally used functional MRI (fMRI) in a subcohort of SCC-DBS patients (n = 12) to investigate immediate within-patient changes in Hb functional connectivity associated with SCC-DBS stimulation. Active DBS was significantly associated with increased Hb connectivity to several prefrontal and corticolimbic regions (TFCE-adjusted p _Bonferroni < 0.0001), many of which have been previously implicated in the neurocircuitry of depression. Taken together, our results suggest that Hb may play an important role in the antidepressant effect of SCC-DBS.

Relationship between depression, prefrontal creatine and grey matter volume

BACKGROUND

Depression and low mood are leading contributors to disability worldwide. Research indicates that clinical depression may be associated with low creatine concentrations in the brain and low prefrontal grey matter volume. Because subclinical depression also contributes to difficulties in day-to-day life, understanding the neural mechanisms of depressive symptoms in all individuals, even at a subclinical level, may aid public health.

METHODS

Eighty-four young adult participants completed the Depression, Anxiety and Stress Scale (DASS) to quantify severity of depression, anxiety and stress, and underwent 1H-Magnetic Resonance Spectroscopy of the medial prefrontal cortex and structural magnetic resonance imaging (MRI) to determine whole-brain grey matter volume.

RESULTS/OUTCOMES

DASS depression scores were negatively associated (a) with concentrations of creatine (but not other metabolites) in the prefrontal cortex and (b) with grey matter volume in the right superior medial frontal gyrus. Medial prefrontal creatine concentrations and right superior medial frontal grey matter volume were positively correlated. DASS anxiety and DASS stress scores were not related to prefrontal metabolite concentrations or whole-brain grey matter volume.

CONCLUSIONS/INTERPRETATIONS

This study provides preliminary evidence from a representative group of individuals who exhibit a range of depression levels that prefrontal creatine and grey matter volume are negatively associated with depression. While future research is needed to fully understand this relationship, these results provide support for previous findings, which indicate that increasing creatine concentrations in the prefrontal cortex may improve mood and well-being.

Effective Connectivity between Major Nodes of the Limbic System, Salience and Frontoparietal Networks Differentiates Schizophrenia and Mood Disorders from Healthy Controls

This study was conducted to examine whether there are quantitative or qualitative differences in the connectome between psychiatric patients and healthy controls and to delineate the connectome features of major depressive disorder (MDD), schizophrenia (SCZ) and bipolar disorder (BD), as well as the severity of these disorders. Toward this end, we performed an effective connectivity analysis of resting state functional MRI data in these three patient groups and healthy controls. We used spectral Dynamic Causal Modeling (spDCM), and the derived connectome features were further subjected to machine learning. The results outlined a model of five connections, which discriminated patients from controls, comprising major nodes of the limbic system (amygdala (AMY), hippocampus (HPC) and anterior cingulate cortex (ACC)), the salience network (anterior insula (AI), and the frontoparietal and dorsal attention network (middle frontal gyrus (MFG), corresponding to the dorsolateral prefrontal cortex, and frontal eye field (FEF)). Notably, the alterations in the self-inhibitory connection of the anterior insula emerged as a feature of both mood disorders and SCZ. Moreover, four out of the five connectome features that discriminate mental illness from controls are features of mood disorders (both MDD and BD), namely the MFG→FEF, HPC→FEF, AI→AMY, and MFG→AMY connections, whereas one connection is a feature of SCZ, namely the AMY→SPL connectivity. A large part of the variance in the severity of depression (31.6%) and SCZ (40.6%) was explained by connectivity features. In conclusion, dysfunctions in the self-regulation of the salience network may underpin major mental disorders, while other key connectome features shape differences between mood disorders and SCZ, and can be used as potential imaging biomarkers.

Cognitive impairment and depression: Meta-analysis of structural magnetic resonance imaging studies

Longitudinal comorbidity of depression and cognitive impairment has been reported by number of epidemiological studies but the underlying mechanisms explaining the link between affective problems and cognitive decline are not very well understood. Imaging studies have typically investigated patients with major depressive disorder (MDD) and mild cognitive impairment (MCI) separately and thus have not identified a structural brain signature common to these conditions that may illuminate potentially targetable shared biological mechanisms. We performed a meta-analysis of. 48 voxel-based morphometry (VBM) studies of individuals with MDD, MCI, and age-matched controls and demonstrated that MDD and MCI patients had shared volumetric reductions in a number of regions including the insula, superior temporal gyrus (STG), inferior frontal gyrus, amygdala, hippocampus, and thalamus. We suggest that the shared volumetric reductions in the insula and STG might reflect communication deficits and infrequent participation in mentally or socially stimulating activities, which have been described as risk factors for both MCI and MDD. We also suggest that the disease-specific structural changes might reflect the disease-specific symptoms such as poor integration of emotional information, feelings of helplessness and worthlessness, and anhedonia in MDD. These findings could contribute to better understanding of the origins of MDD-MCI comorbidity and facilitate development of early interventions.