Widespread reductions in gray matter volume in depression

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

Abnormality in Peripheral and Brain Iron Contents and the Relationship with Grey Matter Volumes in Major Depressive Disorder

Major depressive disorder (MDD) is a prevalent mental illness globally, yet its etiology remains largely elusive. Recent interest in the scientific community has focused on the correlation between the disruption of iron homeostasis and MDD. Prior studies have revealed anomalous levels of iron in both peripheral blood and the brain of MDD patients; however, these findings are not consistent. This study involved 95 MDD patients aged 18-35 and 66 sex- and age-matched healthy controls (HCs) who underwent 3D-T1 and quantitative susceptibility mapping (QSM) sequence scans to assess grey matter volume (GMV) and brain iron concentration, respectively. Plasma ferritin (pF) levels were measured in a subset of 49 MDD individuals and 41 HCs using the Enzyme-linked immunosorbent assay (ELISA), whose blood data were simultaneously collected. We hypothesize that morphological brain changes in MDD patients are related to abnormal regulation of iron levels in the brain and periphery. Multimodal canonical correlation analysis plus joint independent component analysis (MCCA+jICA) algorithm was mainly used to investigate the covariation patterns between the brain iron concentration and GMV. The results of "MCCA+jICA" showed that the QSM values in bilateral globus pallidus and caudate nucleus of MDD patients were lower than HCs. While in the bilateral thalamus and putamen, the QSM values in MDD patients were higher than in HCs. The GMV values of these brain regions showed a significant positive correlation with QSM. The GMV values of bilateral putamen were found to be increased in MDD patients compared with HCs. A small portion of the thalamus showed reduced GMV values in MDD patients compared to HCs. Furthermore, the region of interest (ROI)-based comparison results in the basal ganglia structures align with the outcomes obtained from the "MCCA+jICA" analysis. The ELISA results indicated that the levels of pF in MDD patients were higher than those in HCs. Correlation analysis revealed that the increase in pF was positively correlated with the iron content in the left thalamus. Finally, the covariation patterns obtained from "MCCA+jICA" analysis as classification features effectively differentiated MDD patients from HCs in the support vector machine (SVM) model. Our findings indicate that elevated peripheral ferritin in MDD patients may disrupt the normal metabolism of iron in the brain, leading to abnormal changes in brain iron levels and GMV.

Bidirectional associations between perinatal allopregnanolone and depression severity with postpartum gray matter volume in adult women

BACKGROUND

Perinatal depression (PND) is a debilitating condition affecting maternal well-being and child development. Allopregnanolone (ALLO) is important to perinatal neuroplasticity, however its relationship with depression severity and postpartum structural brain volume is unknown.

METHOD

We examined perinatal temporal dynamics and bidirectional associations between ALLO and depression severity and the association between these variables and postpartum gray matter volume, using a random intercept cross-lagged panel model.

RESULTS

We identified a unidirectional predictive relationship between PND severity and ALLO concentration, suggesting greater depression severity early in the perinatal period may contribute to subsequent changes in ALLO concentration (β = 0.26, p = 0.009), while variations in ALLO levels during the perinatal period influences the development and severity of depressive symptoms later in the postpartum period (β = 0.38, p = 0.007). Antepartum depression severity (Visit 2, β = 0.35, p = 0.004), ALLO concentration (Visit 2, β = 0.37, p = 0.001), and postpartum depression severity (Visit 3, β = 0.39, p = 0.031), each predicted the right anterior cingulate volume. Antepartum ALLO concentration (Visit 2, β = 0.29, p = 0.001) predicted left suborbital sulcus volume. Antepartum depression severity (Visit 1, β = 0.39, p = 0.006 and Visit 2, β = 0.48, p < 0.001) predicted the right straight gyrus volume. Postpartum depression severity (Visit 3, β = 0.36, p = 0.001) predicted left middle-posterior cingulate volume.

CONCLUSION

These results provide the first evidence of bidirectional associations between perinatal ALLO and depression severity with postpartum gray matter volume.

Age exacerbates the negative effect of depression on executive functioning in racial and ethnic minorities

Age and depression may interact to produce a "double jeopardy" for cognitive impairment, and executive functioning, in cognitively unimpaired aging. Few studies have considered middle age or the ethnoracial diversity of subjects, despite evidence of more severe cognitive outcomes in historically minoritized people. In this pilot study, we investigated the impact of age on depression-related cognitive impairment and the underlying brain volumes in middle-aged non-Hispanic White adults (116), and Hispanic and Black adults (60), with a total number of 176 adults. The result shows a significant interaction between age and depression for executive functioning, specifically for middle-aged Hispanic and Black adults, but not non-Hispanic White adults. Prefrontal cortex volumes, which were reduced in the Black and Hispanic compared to the non-Hispanic White adults, partially mediated the relationship between depression level and executive functioning, across age and ethnoracial group. Collectively, these results suggest that the negative impact of depression on executive functioning and Prefrontal cortex volumes integrity may be exacerbated by age and that historically minoritized people may be particularly sensitive to this double jeopardy.

Unraveling the causal relationships between depression and brain structural imaging phenotypes: A bidirectional Mendelian Randomization study

BACKGROUND

Previous studies have revealed structural brain abnormalities in individuals with depression, but the causal relationship between depression and brain structure remains unclear.

METHODS

A genetic correlation analysis was conducted using summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 1,265 brain structural imaging-derived phenotypes (IDPs, N = 33,224). Subsequently, a bidirectional two-sample Mendelian Randomization (MR) approach was employed to explore the causal relationships between depression and the IDPs that showed genetic correlations with depression. The main MR results were obtained using the inverse variance weighted (IVW) method, and other MR methods were further employed to ensure the reliability of the findings.

RESULTS

Ninety structural IDPs were identified as being genetically correlated with depression and were included in the MR analyses. The IVW MR results indicated that reductions in the volume of several brain regions, including the bilateral subcallosal cortex, right medial orbitofrontal cortex, and right middle-posterior part of the cingulate cortex, were causally linked to an increased risk of depression. Additionally, decreases in surface area of the right middle temporal visual area, right middle temporal cortex, right inferior temporal cortex, and right middle-posterior part of the cingulate cortex were causally associated with a heightened risk of depression. Validation and sensitivity analyses supported the robustness of these findings. However, no evidence was found for a causal effect of depression on structural IDPs.

CONCLUSIONS

Our findings reveal the causal influence of specific brain structures on depression, providing evidence to consider brain structural changes in the etiology and treatment of depression.

Modeling brain sex in the limbic system as phenotype for female-prevalent mental disorders

BACKGROUND

Sex differences exist in the prevalence and clinical manifestation of several mental disorders, suggesting that sex-specific brain phenotypes may play key roles. Previous research used machine learning models to classify sex from imaging data of the whole brain and studied the association of class probabilities with mental health, potentially overlooking regional specific characteristics.

METHODS

We here investigated if a regionally constrained model of brain volumetric imaging data may provide estimates that are more sensitive to mental health than whole brain-based estimates. Given its known role in emotional processing and mood disorders, we focused on the limbic system. Using two different cohorts of healthy subjects, the Human Connectome Project and the Queensland Twin IMaging, we investigated sex differences and heritability of brain volumes of limbic structures compared to non-limbic structures, and subsequently applied regionally constrained machine learning models trained solely on limbic or non-limbic features. To investigate the biological underpinnings of such models, we assessed the heritability of the obtained sex class probability estimates, and we investigated the association with major depression diagnosis in an independent clinical sample. All analyses were performed both with and without controlling for estimated total intracranial volume (eTIV).

RESULTS

Limbic structures show greater sex differences and are more heritable compared to non-limbic structures in both analyses, with and without eTIV control. Consequently, machine learning models performed well at classifying sex based solely on limbic structures and achieved performance as high as those on non-limbic or whole brain data, despite the much smaller number of features in the limbic system. The resulting class probabilities were heritable, suggesting potentially meaningful underlying biological information. Applied to an independent population with major depressive disorder, we found that depression is associated with male-female class probabilities, with largest effects obtained using the limbic model. This association was significant for models not controlling for eTIV whereas in those controlling for eTIV the associations did not pass significance correction.

CONCLUSIONS

Overall, our results highlight the potential utility of regionally constrained models of brain sex to better understand the link between sex differences in the brain and mental disorders.

Consensus Paper: Cerebellum and Ageing

Given the key roles of the cerebellum in motor, cognitive, and affective operations and given the decline of brain functions with aging, cerebellar circuitry is attracting the attention of the scientific community. The cerebellum plays a key role in timing aspects of both motor and cognitive operations, including for complex tasks such as spatial navigation. Anatomically, the cerebellum is connected with the basal ganglia via disynaptic loops, and it receives inputs from nearly every region in the cerebral cortex. The current leading hypothesis is that the cerebellum builds internal models and facilitates automatic behaviors through multiple interactions with the cerebral cortex, basal ganglia and spinal cord. The cerebellum undergoes structural and functional changes with aging, being involved in mobility frailty and related cognitive impairment as observed in the physio-cognitive decline syndrome (PCDS) affecting older, functionally-preserved adults who show slowness and/or weakness. Reductions in cerebellar volume accompany aging and are at least correlated with cognitive decline. There is a strongly negative correlation between cerebellar volume and age in cross-sectional studies, often mirrored by a reduced performance in motor tasks. Still, predictive motor timing scores remain stable over various age groups despite marked cerebellar atrophy. The cerebello-frontal network could play a significant role in processing speed and impaired cerebellar function due to aging might be compensated by increasing frontal activity to optimize processing speed in the elderly. For cognitive operations, decreased functional connectivity of the default mode network (DMN) is correlated with lower performances. Neuroimaging studies highlight that the cerebellum might be involved in the cognitive decline occurring in Alzheimer's disease (AD), independently of contributions of the cerebral cortex. Grey matter volume loss in AD is distinct from that seen in normal aging, occurring initially in cerebellar posterior lobe regions, and is associated with neuronal, synaptic and beta-amyloid neuropathology. Regarding depression, structural imaging studies have identified a relationship between depressive symptoms and cerebellar gray matter volume. In particular, major depressive disorder (MDD) and higher depressive symptom burden are associated with smaller gray matter volumes in the total cerebellum as well as the posterior cerebellum, vermis, and posterior Crus I. From the genetic/epigenetic standpoint, prominent DNA methylation changes in the cerebellum with aging are both in the form of hypo- and hyper-methylation, and the presumably increased/decreased expression of certain genes might impact on motor coordination. Training influences motor skills and lifelong practice might contribute to structural maintenance of the cerebellum in old age, reducing loss of grey matter volume and therefore contributing to the maintenance of cerebellar reserve. Non-invasive cerebellar stimulation techniques are increasingly being applied to enhance cerebellar functions related to motor, cognitive, and affective operations. They might enhance cerebellar reserve in the elderly. In conclusion, macroscopic and microscopic changes occur in the cerebellum during the lifespan, with changes in structural and functional connectivity with both the cerebral cortex and basal ganglia. With the aging of the population and the impact of aging on quality of life, the panel of experts considers that there is a huge need to clarify how the effects of aging on the cerebellar circuitry modify specific motor, cognitive, and affective operations both in normal subjects and in brain disorders such as AD or MDD, with the goal of preventing symptoms or improving the motor, cognitive, and affective symptoms.

Roles of the medial and lateral orbitofrontal cortex in major depression and its treatment

We describe evidence for dissociable roles of the medial and lateral orbitofrontal cortex (OFC) in major depressive disorder (MDD) from structure, functional activation, functional connectivity, metabolism, and neurochemical systems. The reward-related medial orbitofrontal cortex has lower connectivity and less reward sensitivity in MDD associated with anhedonia symptoms; and the non-reward related lateral OFC has higher functional connectivity and more sensitivity to non-reward/aversive stimuli in MDD associated with negative bias symptoms. Importantly, we propose that conventional antidepressants act to normalize the hyperactive lateral (but not medial) OFC to reduce negative bias in MDD; while other treatments are needed to operate on the medial OFC to reduce anhedonia, with emerging evidence suggesting that ketamine may act in this way. The orbitofrontal cortex is the key cortical region in emotion and reward, and the current review presents much new evidence about the different ways that the medial and lateral OFC are involved in MDD.

Identifying two distinct neuroanatomical subtypes of first-episode depression using heterogeneity through discriminative analysis

BACKGROUND

Neurobiological heterogeneity in depression remains largely unknown, leading to inconsistent neuroimaging findings.

METHODS

Here, we adopted a novel proposed machine learning method ground on gray matter volumes (GMVs) to investigate neuroanatomical subtypes of first-episode treatment-naïve depression. GMVs were obtained from high-resolution T1-weighted images of 195 patients with first-episode, treatment-naïve depression and 78 matched healthy controls (HCs). Then we explored distinct subtypes of depression by employing heterogeneity through discriminative analysis (HYDRA) with regional GMVs as features.

RESULTS

Two prominently divergent subtypes of first-episode depression were identified, exhibiting opposite structural alterations compared with HCs but no different demographic features. Subtype 1 presented widespread increased GMVs mainly located in frontal, parietal, temporal cortex and partially located in limbic system. Subtype 2 presented widespread decreased GMVs mainly located in thalamus, cerebellum, limbic system and partially located in frontal, parietal, temporal cortex. Subtype 2 had smaller TIV and longer illness duration than Subtype 1. And TIV in Subtype 1 was positively correlated with age of onset while not in Subtype 2, probably implying the different potential neuropathological mechanisms.

LIMITATIONS

Despite results obtained in this study were validated by employing another brain atlas, the conclusions were acquired from a single dataset.

CONCLUSIONS

This study revealed two distinguishing neuroanatomical subtypes of first-episode depression, which provides new insights into underlying biological mechanisms of the heterogeneity in depression and might be helpful for accurate clinical diagnosis and future treatment.

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.

A stress-sensitive frontostriatal circuit supporting effortful reward-seeking behavior

Effort valuation-a process for selecting actions based on the anticipated value of rewarding outcomes and expectations about the work required to obtain them-plays a fundamental role in decision-making. Effort valuation is disrupted in chronic stress states and is supported by the anterior cingulate cortex (ACC), but the circuit-level mechanisms by which the ACC regulates effort-based decision-making are unclear. Here, we show that ACC neurons projecting to the nucleus accumbens (ACC-NAc) play a critical role in effort valuation behavior in mice. Activity in ACC-NAc cells integrates both reward- and effort-related information, encoding a reward-related signal that scales with effort requirements and is necessary for supporting future effortful decisions. Chronic corticosterone exposure reduces motivation, suppresses effortful reward-seeking, and disrupts ACC-NAc signals. Together, our results delineate a stress-sensitive ACC-NAc circuit that supports effortful reward-seeking behavior by integrating reward and effort signals and reinforcing effort allocation in the service of maximizing reward.

PGAM5 knockout causes depressive-like behaviors in mice via ATP deficiency in the prefrontal cortex

INTRODUCTION

Major depressive disorder (MDD) affects about 17% population in the world. Although abnormal energy metabolism plays an important role in the pathophysiology of MDD, however, how deficiency of adenosine triphosphate (ATP) products affects emotional circuit and what regulates ATP synthesis are still need to be elaborated.

AIMS

Our study aimed to investigate how deficiency of PGAM5-mediated depressive behavior.

RESULTS

We firstly discovered that PGAM5 knockout (PGAM5-/- ) mice generated depressive-like behaviors. The phenotype was reinforced by the observation that chronic unexpected mild stress (CUMS)-induced depressive mice exhibited lowered expression of PGAM5 in prefrontal cortex (PFC), hippocampus (HIP), and striatum. Next, we found, with the using of functional magnetic resonance imaging (fMRI), that the functional connectivity between PFC reward system and the PFC volume were reduced in PGAM5-/- mice. PGAM5 ablation resulted in the loss of dendritic spines and lowered density of PSD95 in PFC, but not in HIP. Finally, we found that PGAM5 ablation led to lowered ATP concentration in PFC, but not in HIP. Coimmunoprecipitation study showed that PGAM5 directly interacted with the ATP F1 F0 synthase without influencing the interaction between ATP F1 F0 synthase and Bcl-xl. We then conducted ATP administration to PGAM5-/- mice and found that ATP could rescue the behavioral and neuronal phenotypes of PGAM5-/- mice.

CONCLUSIONS

Our findings provide convincing evidence that PGAM5 ablation generates depressive-like behaviors via restricting neuronal ATP production so as to impair the number of neuronal spines in PFC.

Examining the relationship between anxiety and regional brain volumes in the National Alzheimer's Coordinating Center uniform, imaging, and biomarker datasets

Anxiety has been associated with a greater risk of Alzheimer's disease (AD). Existing research has identified structural differences in regional brain tissue in participants with anxiety, but results have been inconsistent. We sought to determine the association between anxiety and regional brain volumes, and the moderation effect of APOE ε4. Using data from participants in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set, with complete imaging (MRI) and biomarker data (n = 1533), multiple linear regression estimated the adjusted effect of anxiety on 30 structural MRI regions. The moderation effect of APOE ε4 on the relation between structural MRI regions and anxiety was assessed as was the moderation effect of cognitive status. False discovery rate was used to adjust for multiple comparisons. After controlling for intracranial volume, age, sex, years of education, race, Hispanic ethnicity, and cognitive status, seven MRI regions demonstrated lower volumes among participants with anxiety: total cerebrum gray matter volume, right hippocampus volume, hippocampal volume (total), right and left frontal lobe cortical gray matter volume, and right and total temporal lobe cortical gray matter volume. Findings suggest that anxiety is associated with significant atrophy in multiple brain regions, with corresponding ventricular enlargement. Future research should investigate if anxiety-related changes to brain morphology contribute to greater AD risk.

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.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Impact of Stress on Brain Morphology: Insights into Structural Biomarkers of Stress-related Disorders

Exposure to acute and chronic stress has a broad range of structural effects on the brain. The brain areas commonly targeted in the stress response models include the hippocampus, the amygdala, and the prefrontal cortex. Studies in patients suffering from the so-called stress-related disorders -embracing post-traumatic stress, major depressive and anxiety disorders- have fairly replicated animal models of stress response -particularly the neuroendocrine and the inflammatory models- by finding alterations in different brain areas, even in the early neurodevelopment. Therefore, this narrative review aims to provide an overview of structural neuroimaging findings and to discuss how these studies have contributed to our knowledge of variability in response to stress and the ulterior development of stress-related disorders. There are a gross number of studies available but neuroimaging research of stress-related disorders as a single category is still in its infancy. Although the available studies point at particular brain circuitries involved in stress and emotion regulation, the pathophysiology of these abnormalities -involving genetics, epigenetics and molecular pathways-, their relation to intraindividual stress responses -including personality characteristics, self-perception of stress conditions…-, and their potential involvement as biomarkers in diagnosis, treatment prescription and prognosis are discussed.

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.

Decreased cortical gyrification in major depressive disorder

BACKGROUND

Early neurodevelopmental deviations, such as abnormal cortical folding patterns, are candidate biomarkers of major depressive disorder (MDD). We aimed to investigate the association of MDD with the local gyrification index (LGI) in each cortical region at the whole-brain level, and the association of the LGI with clinical characteristics of MDD.

METHODS

We obtained T1-weighted images from 234 patients with MDD and 215 healthy controls (HCs). The LGI values from 66 cortical regions in the bilateral hemispheres were automatically calculated according to the Desikan-Killiany atlas. We compared the LGI values between the MDD and HC groups using analysis of covariance, including age, sex, and years of education as covariates. The association between the clinical characteristics and LGI values was investigated in the MDD group.

RESULTS

Compared with HCs, patients with MDD showed significantly decreased LGI values in the cortical regions, including the bilateral ventrolateral and dorsolateral prefrontal cortices, medial and lateral orbitofrontal cortices, insula, right rostral anterior cingulate cortex, and several temporal and parietal regions, with the largest effect size in the left pars triangularis (Cohen's f2 = 0.361; p = 1.78 × 10-13). Regarding the association of clinical characteristics with LGIs within the MDD group, recurrence and longer illness duration were associated with increased gyrification in several occipital and temporal regions, which showed no significant difference in LGIs between the MDD and HC groups.

CONCLUSIONS

These findings suggest that the LGI may be a relatively stable neuroimaging marker associated with MDD predisposition.

Age exacerbates the negative effect of depression on executive functioning in racial and ethnic minorities

Age and depression may interact to produce a "double jeopardy" for cognitive impairment, and executive functioning, in cognitively unimpaired aging. Few studies have considered middle age or the ethnoracial diversity of subjects, despite evidence of more severe cognitive outcomes in historically minoritized people. In this pilot study, we investigated the impact of age on depression-related cognitive impairment and the underlying brain volumes in middle-aged non-Hispanic White adults (116), and Hispanic and Black adults (60), with a total number of 176 adults. The result shows a significant interaction between age and depression for executive functioning, specifically for middle-aged Hispanic and Black adults, but not non-Hispanic White adults. Prefrontal cortex volumes, which were reduced in the Black and Hispanic compared to the non-Hispanic White adults, partially mediated the relationship between depression level and executive functioning, across age and ethnoracial group. Collectively, these results suggest that the negative impact of depression on executive functioning and Prefrontal cortex volumes integrity may be exacerbated by age and that historically minoritized people may be particularly sensitive to this double jeopardy.

The neural basis underlying female vulnerability to depressive disorders

Depressive disorders are more prevalent and severe in women; however, our knowledge of the underlying factors contributing to female vulnerability to depression remains limited. Additionally, females are notably underrepresented in studies seeking to understand the mechanisms of depression. Various animal models of depression have been devised, but only recently have females been included in research. In this comprehensive review, we aim to describe the sex differences in the prevalence, pathophysiology, and responses to drug treatment in patients with depression. Subsequently, we highlight animal models of depression in which both sexes have been studied, in the pursuit of identifying models that accurately reflect female vulnerability to depression. We also introduce explanations for the neural basis of sex differences in depression. Notably, the medial prefrontal cortex and the nucleus accumbens have exhibited sex differences in previous studies. Furthermore, other brain circuits involving the dopaminergic center (ventral tegmental area) and the serotonergic center (dorsal raphe nucleus), along with their respective projections, have shown sex differences in relation to depression. In conclusion, our review covers the critical aspects of sex differences in depression, with a specific focus on female vulnerability in humans and its representation in animal models, including the potential underlying mechanisms. Employing suitable animal models that effectively represent female vulnerability would benefit our understanding of the sex-dependent pathophysiology of depression.

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning

Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physical health. Nowadays, a DD diagnosis mainly relies on the experience of clinical psychiatrists and subjective scales, lacking objective, accurate, practical, and automatic diagnosis technologies. Recently, electroencephalogram (EEG) signals have been widely applied for DD diagnosis, but mainly with high-density EEG, which can severely limit the efficiency of the EEG data acquisition and reduce the practicability of diagnostic techniques. The current study attempts to achieve accurate and practical DD diagnoses based on combining frontal six-channel electroencephalogram (EEG) signals and deep learning models. To this end, 10 min clinical resting-state EEG signals were collected from 41 DD patients and 34 healthy controls (HCs). Two deep learning models, multi-resolution convolutional neural network (MRCNN) combined with long short-term memory (LSTM) (named MRCNN-LSTM) and MRCNN combined with residual squeeze and excitation (RSE) (named MRCNN-RSE), were proposed for DD recognition. The results of this study showed that the higher EEG frequency band obtained the better classification performance for DD diagnosis. The MRCNN-RSE model achieved the highest classification accuracy of 98.48 ± 0.22% with 8-30 Hz EEG signals. These findings indicated that the proposed analytical framework can provide an accurate and practical strategy for DD diagnosis, as well as essential theoretical and technical support for the treatment and efficacy evaluation of DD.

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.

Identification of structural brain alterations in adolescents with depressive symptomatology

INTRODUCTION

Depressive symptoms can emerge as early as childhood and may lead to adverse situations in adulthood. Studies have examined structural brain alternations in individuals with depressive symptoms, but findings remain inconclusive. Furthermore, previous studies have focused on adults or used a categorical approach to assess depression. The current study looks to identify grey matter volumes (GMV) that predict depressive symptomatology across a clinically concerning sample of adolescents.

METHODS

Structural MRI data were collected from 338 clinically concerning adolescents (mean age = 15.30 SD=2.07; mean IQ = 101.01 SD=12.43; 132 F). Depression symptoms were indexed via the Mood and Feelings Questionnaire (MFQ). Freesurfer was used to parcellate the brain into 68 cortical regions and 14 subcortical regions. GMV was extracted from all 82 brain areas. Multiple linear regression was used to look at the relationship between MFQ scores and region-specific GMV parameter. Follow up regressions were conducted to look at potential effects of psychiatric diagnoses and medication intake.

RESULTS

Our regression analysis produced a significant model (R2 = 0.446, F(86, 251) = 2.348, p < 0.001). Specifically, there was a negative association between GMV of the left parahippocampal (B = -0.203, p = 0.005), right rostral anterior cingulate (B = -0.162, p = 0.049), and right frontal pole (B = -0.147, p = 0.039) and a positive association between GMV of the left bank of the superior temporal sulcus (B = 0.173, p = 0.029). Follow up analyses produced results proximal to the main analysis.

CONCLUSIONS

Altered regional brain volumes may serve as biomarkers for the development of depressive symptoms during adolescence. These findings suggest a homogeneity of altered cortical structures in adolescents with depressive symptoms.

Consistent functional abnormalities in patients with postpartum depression

Postpartum depression (PPD) is a common public health concern. A wide range of functional abnormalities in various brain regions have been reported in fMRI studies on PPD, however, a consistent functional changing pattern is still lacking. Herein, we obtained functional Magnetic Resonance Imaging (fMRI) data from 52 patients with PPD and 24 healthy postpartum women (HPW). Functional indexes (low-frequency fluctuation, degree centrality, and regional homogeneity) were calculated and compared among these groups to explore the functional changing patterns of PPD. Then, correlation analyses were performed to investigate the relationship between changed functional indexes and clinical measurements in the PPD. Finally, support vector machine (SVM) was performed to test whether these abnormal features can be used to distinguish PPD from HPW. As a result, we identified significantly and consistently functional changing pattern characterizing by increased functional activity in the left inferior occipital gyrus and decreased functional activity right anterior cingulate cortex in the PPD as compared to HPW. These functional values in the right anterior cingulate cortex were significantly correlated with depression symptoms in the PPD, and can be used as features to distinguish PPD from HPW. In conclusion, our results suggested that the right anterior cingulate cortex could be served as a functional neuro-imaging biomarker for PPD, which might be used as a potential target for neuro-modulation.

Cortical and cerebellar structural correlates of cognitive-motor integration performance in females with and without persistent concussion symptoms

INTRODUCTION

Fifteen percent of individuals who sustain a concussion develop persistent concussion symptoms (PCS). Recent literature has demonstrated atrophy of the frontal, parietal, and cerebellar regions following acute concussive injury. The frontoparietal-cerebellar network is essential for the performance of visuomotor transformation tasks requiring cognitive-motor integration (CMI), important for daily function.

PURPOSE

We investigated cortical and subcortical structural differences and how these differences are associated with CMI performance in those with PCS versus healthy controls.

METHODS

Twenty-six age-matched  female participants (13 PCS, 13 healthy) completed four visuomotor tasks.  Additionally, MR-images were analyzed for cortical thickness and volume, and cerebellar lobule volume.

RESULTS

No statistically significant group differences were found in CMI performance. However, those with PCS demonstrated a significantly thicker and larger precuneus, and significantly smaller cerebellar lobules (VIIIa, VIIIb, X) compared to controls. When groups were combined, volumes of both the cerebellar lobules and cortical regions were associated with CMI task performance.

CONCLUSION

The lack of behavioral differences combined with the structural differences may reflect a compensatory mechanism for those with PCS. In addition, this study highlights the effectiveness of CMI tasks in estimating the structural integrity of the frontoparietal-cerebellar network and is among the first to demonstrate structural correlates of PCS.

The Relationships Among Metal Homeostasis, Mitochondria, and Locus Coeruleus in Psychiatric and Neurodegenerative Disorders: Potential Pathogenetic Mechanism and Therapeutic Implications

While alterations in the locus coeruleus-noradrenergic system are present during early stages of neuropsychiatric disorders, it is unclear what causes these changes and how they contribute to other pathologies in these conditions. Data suggest that the onset of major depressive disorder and schizophrenia is associated with metal dyshomeostasis that causes glial cell mitochondrial dysfunction and hyperactivation in the locus coeruleus. The effect of the overactive locus coeruleus on the hippocampus, amygdala, thalamus, and prefrontal cortex can be responsible for some of the psychiatric symptoms. Although locus coeruleus overactivation may diminish over time, neuroinflammation-induced alterations are presumably ongoing due to continued metal dyshomeostasis and mitochondrial dysfunction. In early Alzheimer's and Parkinson's diseases, metal dyshomeostasis and mitochondrial dysfunction likely induce locus coeruleus hyperactivation, pathological tau or α-synuclein formation, and neurodegeneration, while reduction of glymphatic and cerebrospinal fluid flow might be responsible for β-amyloid aggregation in the olfactory regions before the onset of dementia. It is possible that the overactive noradrenergic system stimulates the apoptosis signaling pathway and pathogenic protein formation, leading to further pathological changes which can occur in the presence or absence of locus coeruleus hypoactivation. Data are presented in this review indicating that although locus coeruleus hyperactivation is involved in pathological changes at prodromal and early stages of these neuropsychiatric disorders, metal dyshomeostasis and mitochondrial dysfunction are critical factors in maintaining ongoing neuropathology throughout the course of these conditions. The proposed mechanistic model includes multiple pharmacological sites that may be targeted for the treatment of neuropsychiatric disorders commonly.

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.

Effects of a probiotic add-on treatment on fronto-limbic brain structure, function, and perfusion in depression: Secondary neuroimaging findings of a randomized controlled trial

BACKGROUND

Probiotics are suggested to improve depressive symptoms via the microbiota-gut-brain axis. We have recently shown a beneficial clinical effect of probiotic supplementation in patients with depression. Their underlying neural mechanisms remain unknown.

METHODS

A multimodal neuroimaging approach including diffusion tensor imaging, resting-state functional MRI, and arterial spin labeling was used to investigate the effects of a four-weeks probiotic supplementation on fronto-limbic brain structure, function, and perfusion and whether these effects were related to symptom changes.

RESULTS

Thirty-two patients completed both imaging assessments (18 placebo and 14 probiotics group). Probiotics maintained mean diffusivity in the left uncinate fasciculus, stabilized it in the right uncinate fasciculus, and altered resting-state functional connectivity (rsFC) between limbic structures and the temporal pole to a cluster in the precuneus. Moreover, a cluster in the left superior parietal lobule showed altered rsFC to the subcallosal cortex, the left orbitofrontal cortex, and limbic structures after probiotics. In the probiotics group, structural and functional changes were partly related to decreases in depressive symptoms.

LIMITATIONS

This study has a rather small sample size. An additional follow-up MRI session would be interesting for seeing clearer changes in the relevant brain regions as clinical effects were strongest in the follow-up.

CONCLUSION

Probiotic supplementation is suggested to prevent neuronal degeneration along the uncinate fasciculus and alter fronto-limbic rsFC, effects that are partly related to the improvement of depressive symptoms. Elucidating the neural mechanisms underlying probiotics' clinical effects on depression provide potential targets for the development of more precise probiotic treatments.

Gene Expression has Distinct Associations with Brain Structure and Function in Major Depressive Disorder

Major depressive disorder (MDD) is associated with structural and functional brain abnormalities. MDD as well as brain anatomy and function are influenced by genetic factors, but the role of gene expression remains unclear. Here, this work investigates how cortical gene expression contributes to structural and functional brain abnormalities in MDD. This work compares the gray matter volume and resting-state functional measures in a Chinese sample of 848 MDD patients and 749 healthy controls, and these case-control differences are then associated with cortical variation of gene expression. While whole gene expression is positively associated with structural abnormalities, it is negatively associated with functional abnormalities. This work observes the relationships of expression levels with brain abnormalities for individual genes, and found that transcriptional correlates of brain structure and function show opposite relations with gene dysregulation in postmortem cortical tissue from MDD patients. This work further identifies genes that are positively or negatively related to structural abnormalities as well as functional abnormalities. The MDD-related genes are enriched for brain tissue, cortical cells, and biological pathways. These findings suggest that distinct genetic mechanisms underlie structural and functional brain abnormalities in MDD, and highlight the importance of cortical gene expression for the development of cortical abnormalities.

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

BACKGROUND

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

OBJECTIVE

This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis.

METHODS

The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information.

RESULTS

With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum.

CONCLUSIONS

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

Convergent molecular and structural neuroimaging signatures of first-episode depression

BACKGROUND

Convergent studies have demonstrated morphological abnormalities in various brain regions in depression patients. However, the molecular underpinnings of the structural impairments remain largely unknown, despite a pressing need for treatment targets and mechanisms. Here, we investigated the gray matter volume (GMV) alteration in patients with depression and its underlying molecular architecture.

METHODS

We recruited 195 first-episode, treatment-naïve depression patients and 78 gender-, age-, and education level-matched healthy controls (HCs) who underwent high-resolution T1-weighted magnetic resonance scans. Voxel-based morphometry (VBM) was adopted to calculate the GMV differences between two groups. Then we analyzed the spatial correlation between depression-induced alteration in GMV and density maps of 10 receptors/transporters deriving from prior molecular imaging in healthy people.

RESULTS

Compared to HCs, the depression group had significantly increased GMV in the left ventral portions of the ventral medial prefrontal cortex, parahippocampal gyrus, amygdala, the right superior parietal lobule and precuneus while decreased GMV in the bilateral hippocampus extending to the thalamus and cerebellum. The GMV alteration introduced by depression was spatially correlated with serotonin receptors (5-HT1a, 5-HT1b, and 5-HT2a), dopamine receptors (D1 and D2) and GABAergic receptor (GABAa) densities.

LIMITATIONS

The conclusions drawn in this study were obtained from a single dataset.

CONCLUSIONS

This study reveals abnormal GMV alteration and provides a series of neurotransmitters receptors possibly related to GMV alteration in depression, which facilitates an integrative understanding of the molecular mechanism underlying the structural abnormalities in depression and may provide clues to new treatment strategies.

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

BACKGROUND

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

METHODS

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

RESULT

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

CONCLUSION

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

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.

Neighborhood Beauty and the Brain in Older Japanese Adults

People have a preference for, and feel better in, beautiful natural environments. However, there are no epidemiological studies on the association between neighborhood beauty and neuroimaging measures. We aimed to determine association between neighborhood beauty and regional brain volume. Participants were 476 community-dwelling older adults from the Neuron to Environmental Impact across Generations (NEIGE) study. Subjective neighborhood beauty was assessed through participants’ perception of beautiful scenery within 1 km of their home. Objective measures of neighborhood indicators (green spaces, blue spaces, and plant diversity) within 1 km of participants’ homes were obtained using a geographic information system. Volumes of brain regions associated with experience of beauty were measured using magnetic resonance imaging. We estimated associations between neighborhood beauty and regional brain volume using linear regression. Of the participants, 42% rated their neighborhoods as very beautiful, and 17% rated them as not at all beautiful. Higher subjective neighborhood beauty was associated with larger bilateral medial orbitofrontal cortex and insula volumes (all p for trend < 0.01). Brain volume was not associated with objective neighborhood measures. Subjective neighborhood beauty was associated with brain regions related to rewards and decision making, suggesting that these brain regions underpin the perception of neighborhood beauty.

Common and unique neural activities in subclinical depression and major depressive disorder indicate the development of brain impairments in different depressive stages

BACKGROUND

Subclinical depression (SD) and major depressive disorder (MDD) can be considered as the early and late stages of depression, but the characteristics of intrinsic neural activity in different depressive stages are largely unknown.

METHODS

Twenty-six SD, 36 MDD subjects and 33 well-matched healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Voxel-wise regional homogeneity (ReHo) was analyzed to explore the alterations of intrinsic neural activity, and machine learning classification based on ReHo features was performed to assess potential performance for diagnostic classification.

RESULTS

Common alterations of ReHo in both SD and MDD groups were found in the bilateral middle temporal gyrus and the left middle occipital gyrus. Opposite alterations in SD and MDD groups were found in the right superior cerebellum. Moreover, increased ReHo in the bilateral precuneus was only found in MDD, while increased ReHo in the right middle frontal gyrus and precentral gyrus were unique to SD. The distinct ReHo values correctly identified SD, MDD, and HC by linear support vector machine (SVM) with an accuracy of 77.89 %, which further verified the discrimination ability of altered ReHo in these brain regions.

LIMITATION

The sample size is relatively small.

CONCLUSION

Common and unique ReHo alterations provided insights into the development of brain impairments in depression, and helped to understand the pathophysiology of SD and MDD.

Hyperconnectivity and altered interactions of a nucleus accumbens network in post-stroke depression

Post-stroke depression is a common complication of stroke. To date, no consistent locus of injury is associated with this complication. Here, we probed network dynamics and structural alterations in post-stroke depression in four functional circuits linked to major depressive disorder and a visual network, which served as a control network. Forty-four participants with recent stroke (mean age = 69.03, standard deviation age = 8.59, age range = 51–86 and gender: female = 10) and 16 healthy volunteers (mean age = 71.53, standard deviation age = 10.62, age range = 51–84 and gender: female = 11) were imaged with 3-Tesla structural, diffusion and resting-state functional MRI. The Geriatric Depression Scale was administered to measure depression severity. Associations between depression severity and functional connectivity were investigated within networks seeded from nucleus accumbens, amygdala, dorsolateral prefrontal cortex and primary visual cortex. In addition, the default mode network was identified by connectivity with medial prefrontal cortex and posterior cingulate cortex. Circuits that exhibited altered activity associated with depression severity were further investigated by extracting within-network volumetric and microstructural measures from structural images. In the stroke group, functional connectivity within the nucleus accumbens-seeded network (left hemisphere: P = 0.001; and right hemisphere: P = 0.004) and default mode network (cluster one: P &lt; 0.001; and cluster two: P &lt; 0.001) correlated positively with depressive symptoms. Normal anticorrelations between these two networks were absent in patients with post-stroke depression. Grey matter volume of the right posterior cingulate cortex (Pearson correlation coefficient = −0.286, P = 0.03), as well as microstructural measures in the posterior cingulate cortex (right: Pearson correlation coefficient = 0.4, P = 0.024; and left: Pearson correlation coefficient = 0.3, P = 0.048), right medial prefrontal cortex (Pearson correlation coefficient = 0.312, P = 0.039) and the medial forebrain bundle (Pearson correlation coefficient = 0.450, P = 0.003), a major projection pathway interconnecting the nucleus accumbens-seeded network and linking to medial prefrontal cortex, were associated with depression severity. Depression after stroke is marked by reduced mutual inhibition between functional circuits involving nucleus accumbens and default mode network as well as volumetric and microstructural changes within these networks. Aberrant network dynamics present in patients with post-stroke depression are therefore likely to be influenced by secondary, pervasive alterations in grey and white matter, remote from the site of injury.

Neural activity changes in first-episode, drug-naïve patients with major depressive disorder after transcutaneous auricular vagus nerve stimulation treatment: A resting-state fMRI study

Introduction

Major depressive disorder (MDD) is a disease with prominent individual, medical, and economic impacts. Drug therapy and other treatment methods (such as Electroconvulsive therapy) may induce treatment-resistance and have associated side effects including loss of memory, decrease of reaction time, and residual symptoms. Transcutaneous auricular vagus nerve stimulation (taVNS) is a novel and non-invasive treatment approach which stimulates brain structures with no side-effects. However, it remains little understood whether and how the neural activation is modulated by taVNS in MDD patients. Herein, we used the regional homogeneity (ReHo) to investigate the brain activity in first-episode, drug-naïve MDD patients after taVNS treatment.

Materials and methods

Twenty-two first-episode, drug-naïve MDD patients were enrolled in the study. These patients received the first taVNS treatment at the baseline time, and underwent resting-state MRI scanning twice, before and after taVNS. All the patients then received taVNS treatments for 4 weeks. The severity of depression was assessed by the 17-item Hamilton Depression Rating Scale (HAMD) at the baseline time and after 4-week’s treatment. Pearson analysis was used to assess the correlation between alterations of ReHo and changes of the HAMD scores. Two patients were excluded due to excessive head movement, two patients lack clinical data in the fourth week, thus, imaging analysis was performed in 20 patients, while correlation analysis between clinical and imaging data was performed in only 18 patients.

Results

There were significant differences in the ReHo values in first-episode, drug-naïve MDD patients between pre- or post- taVNS. The primary finding is that the patients exhibited a significantly lower ReHo in the left/right median cingulate cortex, the left precentral gyrus, the left postcentral gyrus, the right calcarine cortex, the left supplementary motor area, the left paracentral lobule, and the right lingual gyrus. Pearson analysis revealed a positive correlation between changes of ReHo in the right median cingulate cortex/the left supplementary motor area and changes of HAMD scores after taVNS.

Conclusion

The decreased ReHo were found after taVNS. The sensorimotor, limbic and visual-related brain regions may play an important role in understanding the underlying neural mechanisms and be the target brain regions in the further therapy.

The neuroanatomy of social trust predicts depression vulnerability

Trust attitude is a social personality trait linked with the estimation of others’ trustworthiness. Trusting others, however, can have substantial negative effects on mental health, such as the development of depression. Despite significant progress in understanding the neurobiology of trust, whether the neuroanatomy of trust is linked with depression vulnerability remains unknown. To investigate a link between the neuroanatomy of trust and depression vulnerability, we assessed trust and depressive symptoms and employed neuroimaging to acquire brain structure data of healthy participants. A high depressive symptom score was used as an indicator of depression vulnerability. The neuroanatomical results observed with the healthy sample were validated in a sample of clinically diagnosed depressive patients. We found significantly higher depressive symptoms among low trusters than among high trusters. Neuroanatomically, low trusters and depressive patients showed similar volume reduction in brain regions implicated in social cognition, including the dorsolateral prefrontal cortex (DLPFC), dorsomedial PFC, posterior cingulate, precuneus, and angular gyrus. Furthermore, the reduced volume of the DLPFC and precuneus mediated the relationship between trust and depressive symptoms. These findings contribute to understanding social- and neural-markers of depression vulnerability and may inform the development of social interventions to prevent pathological depression.

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).

Evaluation of brain structure and metabolism in currently depressed adults with a history of childhood trauma

Structural differences in the dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), hippocampus, and amygdala were reported in adults who experienced childhood trauma; however, it is unknown whether metabolic differences accompany these structural differences. This multimodal imaging study examined structural and metabolic correlates of childhood trauma in adults with major depressive disorder (MDD). Participants with MDD completed the Childhood Trauma Questionnaire (CTQ, n = 83, n = 54 female (65.1%), age: 30.4 ± 14.1) and simultaneous positron emission tomography (PET)/magnetic resonance imaging (MRI). Structure (volume, n = 80, and cortical thickness, n = 81) was quantified from MRI using Freesurfer. Metabolism (metabolic rate of glucose uptake) was quantified from dynamic ¹⁸F-fluorodeoxyglucose (FDG)-PET images (n = 70) using Patlak graphical analysis. A linear mixed model was utilized to examine the association between structural/metabolic variables and continuous childhood trauma measures while controlling for confounding factors. Bonferroni correction was applied. Amygdala volumes were significantly inversely correlated with continuous CTQ scores. Specifically, volumes were lower by 7.44 mm³ (95% confidence interval [CI]: -12.19, -2.68) per point increase in CTQ. No significant relationship was found between thickness/metabolism and CTQ score. While longitudinal studies are required to establish causation, this study provides insight into potential consequences of, and therefore potential therapeutic targets for, childhood trauma in the prevention of MDD. This work aims to reduce heterogeneity in MDD studies by quantifying neurobiological correlates of trauma within MDD. It further provides biological targets for future interventions aimed at preventing MDD following trauma. To our knowledge, this is the first simultaneous positron emission tomography (PET) and magnetic resonance imaging (MRI) study to assess both structure and metabolism associated with childhood trauma in adults with MDD.

Correlation between cognitive deficits and dorsolateral prefrontal cortex functional connectivity in first-episode depression

INTRODUCTION

Although depression is commonly accompanied by cognitive deficits, the underlying mechanism remains unclear. One possibility is that such deficits are related to abnormal brain network connections. The purpose of this study was thus to investigate changes in brain functional connectivity (FC) in depression and its relationship with cognitive deficits.

METHODS

We enrolled 37 first-episode MDD patients and 53 matched healthy controls (HC). All participants completed clinical and neurocognitive assessments and underwent resting-state functional MRI. Seed-based analysis was used to define the dorsolateral prefrontal cortex (DLPFC) and FC analysis was then performed. We used bias correlation to analyze the correlation between FC and clinical and neurocognitive scores.

RESULTS

MDD patients showed increased FC of the right DLPFC with the left inferior temporal gyrus, left cuneus, right inferior frontal gyrus, right anterior cingulate cortex, left BA39, right angular gyrus, right precuneus, left middle frontal gyrus, and right precentral gyrus. MDD patients also showed stronger FC in the left thalamus and reduced FC between the left superior occipital gyrus and left DLPFC seed region. Interestingly, increased FC was related to disease severity (with the right precentral gyrus) and social cognitive dysfunction (with the right angular gyrus) in MDD patients.

LIMITATIONS

The sample size was relatively small and it is unclear how age may influence FC changes in patients with depression.

CONCLUSIONS

These findings support changes in FC of the DLPFC in early MDD patients related to cognitive function. FC is a potential biomarker for the diagnosis of MDD.

Microstructural deficits of the thalamus in major depressive disorder

Macroscopic structural abnormalities in the thalamus and thalamic circuits have been implicated in the neuropathology of major depressive disorder. However, cytoarchitectonic properties underlying these macroscopic abnormalities remain unknown. Here, we examined systematic deficits of brain architecture in depression, from structural brain network organization to microstructural properties. A multi-modal neuroimaging approach including diffusion, anatomical and quantitative MRI was used to examine structural-related alternations in 56 patients with depression compared with 35 age- and sex-matched controls. The seed-based probabilistic tractography showed multiple alterations of structural connectivity within a set of subcortical areas and their connections to cortical regions in patients with depression. These subcortical regions included the putamen, thalamus and caudate, which are predominantly involved in the limbic-cortical-striatal-pallidal-thalamic network. Structural connectivity was disrupted within and between large-scale networks, including the subcortical network, default-mode network and salience network. Consistently, morphometric measurements, including cortical thickness and voxel-based morphometry, showed widespread volume reductions of these key regions in patients with depression. A conjunction analysis identified common structural alternations of the left orbitofrontal cortex, left putamen, bilateral thalamus and right amygdala across macro-modalities. Importantly, the microstructural properties, longitudinal relaxation time of the left thalamus was increased and inversely correlated with its grey matter volume in patients with depression. Together, this work to date provides the first macro–micro neuroimaging evidence for the structural abnormalities of the thalamus in patients with depression, shedding light on the neuropathological disruptions of the limbic-cortical-striatal-pallidal-thalamic circuit in major depressive disorder. These findings have implications in understanding the abnormal changes of brain structures across the development of depression.

Personalized Diagnosis and Treatment for Neuroimaging in Depressive Disorders

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

Training intervention effects on cognitive performance and neuronal plasticity—A pilot study

Studies suggest that people suffering from chronic pain may have altered brain plasticity, along with altered functional connectivity between pain-processing brain regions. These may be related to decreased mood and cognitive performance. There is some debate as to whether physical activity combined with behavioral therapy (e.g. cognitive distraction, body scan) may counteract these changes. However, underlying neuronal mechanisms are unclear. The aim of the current pilot study with a 3-armed randomized controlled trial design was to examine the effects of sensorimotor training for nonspecific chronic low back pain on (1) cognitive performance; (2) fMRI activity co-fluctuations (functional connectivity) between pain-related brain regions; and (3) the relationship between functional connectivity and subjective variables (pain and depression). Six hundred and sixty two volunteers with non-specific chronic low back pain were randomly allocated to a unimodal (sensorimotor training), multidisciplinary (sensorimotor training and behavioral therapy) intervention, or to a control group within a multicenter study. A subsample of patients (n = 21) from one study center participated in the pilot study presented here. Measurements were at baseline, during (3 weeks, M2) and after intervention (12 weeks, M4 and 24 weeks, M5). Cognitive performance was measured by the Trail Making Test and functional connectivity by MRI. Pain perception and depression were assessed by the Von Korff questionnaire and the Hospital and Anxiety. Group differences were calculated by univariate and repeated ANOVA measures and Bayesian statistics; correlations by Pearson's r. Change and correlation of functional connection were analyzed within a pooled intervention group (uni-, multidisciplinary group). Results revealed that participants with increased pain intensity at baseline showed higher functional connectivity between pain-related brain areas used as ROIs in this study. Though small sample sizes limit generalization, cognitive performance increased in the multimodal group. Increased functional connectivity was observed in participants with increased pain ratings. Pain ratings and connectivity in pain-related brain regions decreased after the intervention. The results provide preliminary indication that intervention effects can potentially be achieved on the cognitive and neuronal level. The intervention may be suitable for therapy and prevention of non-specific chronic low back pain.

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.

Abnormal brain gray matter volume in patients with major depressive disorder: Associated with childhood trauma?

BACKGROUND

Patients with major depressive disorders (MDD) have abnormalities in the frontal-limbic structures of the brain. Childhood trauma is a risk factor for both structural brain alterations and MDD. However, the relationships among the three have not been confirmed.

METHODS

Sixty-four patients with MDD and sixty-one healthy controls (HC) were checked by using MRI, the Hamilton Depression Scale (HAMD) and Childhood Trauma Questionnaire (CTQ). Voxel-based morphometry (VBM) was used to compare gray matter volume (GMV) differences between the two groups. Moreover, partial correlation and mediation analyses were conducted to test for potential associations between CTQ scores, different GMV, and clinical variables.

RESULTS

Compared to the HC group, the MDD patients showed decreased GMV in the right middle frontal gyrus (rMFG) and right precentral gyrus (rPreCG). In the patient group, reduced GMV in rMFG was associated with CTQ scores (r = -0.30, P = 0.019) and HAMD scores (r = -0.53, P < 0.001). Finally, in the patient group, mediation analysis revealed that the indirect effect of rMFG GMV in CTQ scores and HAMD scores was 0.115 and the proportion of indirect effect to total effect was 23.86%.

LIMITATIONS

This study used a cross-sectional collection, and it is unclear whether at the longitudinal level the brain GMV mediates the relationship between childhood trauma and depression.

CONCLUSIONS

Abnormalities in the frontal GMV were presented in the MDD patients. It is possible that childhood traumatic experiences cause inefficient GMV and ultimately lead to an increased susceptibility to depression.

Neural correlates of affective control regions induced by common therapeutic strategies in major depressive disorders: An activation likelihood estimation meta-analysis study

In major depressive disorder (MDD), not only the pathophysiology of this disease is unknown but also the mechanisms of clinical efficacy across its therapeutic strategies are unclear. Although neuroimaging studies adopted activation likelihood estimation (ALE) approach to identify the convergent abnormalities of human brain in the MDD patients, the common alterations after antidepressant therapies were not summarized. Thus, we extracted the coordinates of brain regions in the MDD patients that showed differences in resting-state function, gray matter morphometry, and task-evoked neuronal responses after therapies. The ALE algorithm (GingerALE2.0.3) was employed in all 53 studies (64 experiments with 1406 MDD patients). Consistent results across treatment therapies were reported in the affective control network, including the bilateral thalamus, bilateral amygdala/parahippocampal gyrus, right anterior cingulate cortex/middle frontal gyrus, and right insular cortex/claustrum. Only electroconvulsive therapy partially replicated above findings. Our results indicate the antidepressant therapies efficiently influence core structures of the affective control network, which might be the underlying mechanism of remission in depression and provides potential targets for further treatment strategies.

A deep learning-based multisite neuroimage harmonization framework established with a traveling-subject dataset

The accumulation of multisite large-sample MRI datasets collected during large brain research projects in the last decade has provided critical resources for understanding the neurobiological mechanisms underlying cognitive functions and brain disorders. However, the significant site effects observed in imaging data and their derived structural and functional features have prevented the derivation of consistent findings across multiple studies. The development of harmonization methods that can effectively eliminate complex site effects while maintaining biological characteristics in neuroimaging data has become a vital and urgent requirement for multisite imaging studies. Here, we propose a deep learning-based framework to harmonize imaging data obtained from pairs of sites, in which site factors and brain features can be disentangled and encoded. We trained the proposed framework with a publicly available traveling subject dataset from the Strategic Research Program for Brain Sciences (SRPBS) and harmonized the gray matter volume maps derived from eight source sites to a target site. The proposed framework significantly eliminated intersite differences in gray matter volumes. The embedded encoders successfully captured both the abstract textures of site factors and the concrete brain features. Moreover, the proposed framework exhibited outstanding performance relative to conventional statistical harmonization methods in terms of site effect removal, data distribution homogenization, and intrasubject similarity improvement. Finally, the proposed harmonization network provided fixable expandability, through which new sites could be linked to the target site via indirect schema without retraining the whole model. Together, the proposed method offers a powerful and interpretable deep learning-based harmonization framework for multisite neuroimaging data that can enhance reliability and reproducibility in multisite studies regarding brain development and brain disorders.

Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank

Depression is assessed in various ways in research, with large population studies often relying on minimal phenotyping. Genetic results suggest clinical diagnoses and self-report measures of depression show some core similarities, but also important differences. It is not yet clear how neuroimaging associations depend on levels of phenotyping. We studied 39,300 UK Biobank imaging participants (20,701 female; aged 44.6 to 82.3 years, M = 64.1, SD = 7.5) with structural neuroimaging and lifetime depression data. Past depression phenotypes included a single-item self-report measure, an intermediate measure of 'probable' lifetime depression, derived from multiple questionnaire items relevant to a history of depression, and a retrospective clinical diagnosis according to DSM-IV criteria. We tested (i) associations between brain structural measures and each depression phenotype, and (ii) effects of phenotype on these associations. Depression-brain structure associations were small (β < 0.1) for all phenotypes, but still significant after FDR correction for many regional metrics. Lifetime depression was consistently associated with reduced white matter integrity across phenotypes. Cortical thickness showed negative associations with Self-reported Depression in particular. Phenotype effects were small across most metrics, but significant for cortical thickness in most regions. We report consistent effects of lifetime depression in brain structural measures, including reduced integrity of thalamic radiations and association fibres. We also observed significant differences in associations with cortical thickness across depression phenotypes. Although these results did not relate to level of phenotyping as expected, effects of phenotype definition are still an important consideration for future depression research.