Functional Connectivity of the Anterior Cingulate Cortex and the Right Anterior Insula Differentiates between Major Depressive Disorder, Bipolar Disorder and Healthy Controls

Neuroimaging Changes in the Sensorimotor Network and Visual Network in Bipolar Disorder and Their Relationship with Genetic Characteristics

Objective: Patients with bipolar disorder (BD) may exhibit common and significant changes in brain activity across different networks. Our aim was to investigate the changes in functional connectivity (FC) within different brain networks in BD, as well as their neuroimaging homogeneity, heterogeneity, and genetic variation. Methods: In this study, we analyzed the seed points and whole-brain FC of the sensorimotor network (SMN) and visual network (VN) in 83 healthy controls (HCs) and 77 BD patients, along with their genetic neuroimaging associations. Results: The results showed that, compared to HCs, BD patients exhibited abnormal FC in the SMN and VN brain regions. However, after three months of treatment, there were no significant differences in SMN and VN FC in the brain regions of the patients compared to pre-treatment levels. Enrichment analysis indicated that genes associated with changes in FC were shared among different SMN seed points, but no shared genes were found among VN seed points. Conclusions: In conclusion, changes in SMN FC may serve as a potential neuroimaging marker in BD patients. Our genetic neuroimaging association analysis may help to comprehensively understand the molecular mechanisms underlying FC changes in BD patients.

Altered local spontaneous activity and functional connectivity density in major depressive disorder patients with anhedonia

OBJECTIVE

The purpose of this study was to investigate the alterations of intrinsic brain function in major depressive disorder (MDD) patients with and without anhedonia based on whole-brain level by using two novel measures, four-dimensional spatial-temporal consistency of local neural activity (FOCA) and local functional connectivity density (lFCD).

METHODS

A total of 26 MDD patients with anhedonia (MDD-WA), 29 MDD patients without anhedonia (MDD-WoA), and 30 healthy controls (HCs) were recruited and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scanning and intrinsic brain function was explored by FOCA and lFCD. A two-sample t-test was conducted to explore FOCA and lFCD differences between MDD patients and HCs, then analysis of covariance (ANCOVA) and post hoc tests were performed to obtain brain regions with significant differences among three groups. Finally, the diagnostic performance of FOCA and lFCD values with significant inter-group difference was evaluated using receiver operating characteristic (ROC) curves.

RESULTS

Compared to HCs, MDD patients showed decreased FOCA in the right cuneus (CUN) and left postcentral gyrus (PoCG), as well as diminished lFCD in the right CUN and left calcarine fissure and surrounding cortex (CAL). Interestingly, the MDD-WA group was more likely to exhibit decreased FOCA in the left PoCG and reduced lFCD in the left CAL after consideration for the effect of anhedonia in MDD patients. The MDD-WA group further showed increased FOCA in the bilateral caudate (CAU) and right ventral anterior nucleus (VA) when comparing to HCs. Additionally, as compared with MDD-WoA group, the MDD-WA group presented decreased FOCA in the right middle occipital gyrus (MOG), which was also negatively associated with the severity of anhedonia in MDD patients. Finally, FOCA values of the right MOG exhibited excellent discriminant validity in differentiating MDD-WA from MDD-WoA, and the other individual or combined indices of FOCA or lFCD values in the aforementioned distinct brain regions presented significant utility in distinguishing between MDD or MDD-WA and HCs.

CONCLUSIONS

The present findings suggest that aberrant intrinsic brain function in the left CAL, left PoCG, bilateral CAU, right VA, and, especially the right MOG may be associated with anhedonia in patients with MDD. Altered FOCA in the right MOG may have the potential to be a diagnostic neuroimaging biomarker for MDD patients with anhedonia.

Unearthing the hidden links: Investigating the functional connectivity between amygdala subregions and brain networks in bipolar disorder through resting-state fMRI

Introduction

Bipolar disorder is a multifaceted psychiatric condition characterized by fluctuating activity levels and dysfunctional mood states, oscillating between manic and depressive episodes. These mood disturbances are accompanied by persistent functional and cognitive impairments, even during periods of euthymia. Prior studies have underscored the critical role of amygdala activity in the pathophysiology of bipolar disorder. This research aims to utilize resting-state functional Magnetic Resonance Imaging (rs-fMRI) to explore the functional modifications in the six sub-regions that compose the amygdala of individuals diagnosed with bipolar disorder.

Method

The study encompassed 80 participants, bifurcated into two groups: 40 individuals with bipolar disorder and 40 healthy controls. Each group comprised an equal gender distribution of 20 females and 20 males, ranging in age from 21 to 50 years. Using rs-fMRI, we examined the functional connectivity within six amygdala sub-regions across eight regional functional networks.

Results

Comparative analysis between the control group and the bipolar patients revealed that all six amygdala sub-regions demonstrated connectivity with the eight functional brain networks. Notable similarities and disparities were observed in the connectivity patterns between the bipolar group and controls, particularly within the amygdala's sub-regions and other brain networks. The most significant functional connectivity alterations were found with the salience network and the default mode network. Additionally, alterations in the functional connectivity between the amygdala, sensory-motor, and visual networks were noted in bipolar patients.

Conclusion

The study's findings highlight the distinct patterns of resting-state functional connectivity of the amygdala and various brain networks in differentiating bipolar patients from healthy controls. These variations suggest the existence of multiple pathophysiological mechanisms contributing to emotional dysregulation in bipolar disorder.

Factors Associated with the Development of Depression and the Influence of Obesity on Depressive Disorders: A Narrative Review

Depression affects several aspects of life, including socioeconomic status, relationships, behavior, emotions, and overall health. The etiology of depression is complex and influenced by various factors, with obesity emerging as a significant contributor. This narrative review aims to investigate the factors associated with the development of depression, with a particular focus on the role of obesity. The literature search was conducted on PubMed, Embase, and PsycINFO from May to July 2024. The review highlights the impact of environmental and socioeconomic conditions; lifestyle choices, including physical activity and dietary habits; stress; traumatic experiences; neurotransmitter imbalances; medical and psychological conditions; hormone fluctuations; and epigenetic factors on depression. A key emphasis is placed on the inflammatory processes linked to obesity, which may drive the bidirectional relationship between obesity and depression. The findings suggest that obesity is associated with an increased risk of depression, potentially due to chronic inflammation, neurochemical dysregulation, and the emotional and social challenges related to weight stigma and obesity management. Understanding these interconnected factors is important for developing targeted interventions to address both obesity and depression, leading to improved quality of life for those affected.

Integrated analysis of transcriptional changes in major depressive disorder: Insights from blood and anterior cingulate cortex

Background

Major depressive disorder (MDD) was involved in widely transcriptional changes in central and peripheral tissues. While, previous studies focused on single tissues, making it difficult to represent systemic molecular changes throughout the body. Thus, there is an urgent need to explore the central and peripheral biomarkers with intrinsic correlation.

Methods

We systematically retrieved gene expression profiles of blood and anterior cingulate cortex (ACC). 3 blood datatsets (84 MDD and 88 controls) and 6 ACC datasets (100 MDD and 100 controls) were obtained. Differential expression analysis, RobustRankAggreg (RRA) analysis, functional enrichment analysis, immune associated analysis and protein-protein interaction networks (PPI) were integrated. Furthermore, the key genes were validated in an independent ACC dataset (12 MDD and 15 controls) and a cohort with 120 MDD and 117 controls.

Results

Differential expression analysis identified 2211 and 2021 differential expressed genes (DEGs) in blood and ACC, respectively. RRA identified 45 and 25 robust DEGs in blood and ACC based on DEGs, and all of them were closely associated with immune cells. Functional enrichment results showed both the robust DEGs in blood and ACC were enriched in humoral immune response. Furthermore, PPI identified 8 hub DEGs (CD79A, CD79B, CD19, MS4A1, PLP1, CLDN11, MOG, MAG) in blood and ACC. Independent ACC dataset showed the area under the curve (AUC) based on these hub DEGs was 0.77. Meanwhile, these hub DEGs were validated in the serum of MDD patients, and also showed a promising diagnostic power.

Conclusions

The biomarker panel based on hub DEGs yield a promising diagnostic efficacy, and all of these hub DEGs were strongly correlated with immunity. Humoral immune response may be the key link between the brain and blood in MDD, and our results may provide further understanding for MDD.

Mood and microbes: a comprehensive review of intestinal microbiota's impact on depression

Depression is considered a multifaceted and intricate mental disorder of growing concern due to its significant impact on global health issues. The human gut microbiota, also known as the "second brain," has an important role in the CNS by regulating it through chemical, immunological, hormonal, and neurological processes. Various studies have found a significant bidirectional link between the brain and the gut, emphasizing the onset of depression therapies. The biological and molecular processes underlying depression and microbiota are required, as the bidirectional association may represent a novel study. However, profound insights into the stratification and diversity of the gut microbiota are still uncommon. This article investigates the emerging evidence of a bacterial relationship between the gut and the brain's neurological system and its potential pathogenicity and relevance. The interplay of microbiota, immune system, nervous system neurotransmitter synthesis, and neuroplasticity transitions is also widely studied. The consequences of stress, dietary fibers, probiotics, prebiotics, and antibiotics on the GB axis are being studied. Multiple studies revealed the processes underlying this axis and led to the development of effective microbiota-based drugs for both prevention and treatment. Therefore, the results support the hypothesis that gut microbiota influences depression and provide a promising area of research for an improved knowledge of the etiology of the disease and future therapies.

The Cerebellum's Role in Affective Disorders: The Onset of Its Social Dimension

Major Depressive Disorder (MDD) and Bipolar Disorder (BD) are the most frequent mental disorders whose indeterminate etiopathogenesis spurs to explore new aetiologic scenarios. In light of the neuropsychiatric symptoms characterizing Cerebellar Cognitive Affective Syndrome (CCAS), the objective of this narrative review is to analyze the involvement of the cerebellum (Cbm) in the onset of these conditions. It aims at detecting the repercussions of the Cbm activities on mood disorders based on its functional subdivision in vestibulocerebellum (vCbm), pontocerebellum (pCbm) and spinocerebellum (sCbm). Despite the Cbm having been, for decades, associated with somato-motor functions, the described intercellular pathways, without forgiving the molecular impairment and the alteration in the volumetric relationships, make the Cbm a new important therapeutic target for MDD and BD. Given that numerous studies have showed its activation during mnestic activities and socio-emotional events, this review highlights in the Cbm, in which the altered external space perception (vCbm) is strictly linked to the cognitive-limbic Cbm (pCbm and sCbm), a crucial role in the MDD and BD pathogenesis. Finally, by the analysis of the cerebellar activity, this study aims at underlying not only the Cbm involvement in affective disorders, but also its role in social relationship building.

Degeneracy and disordered brain networks in psychiatric patients using multivariate structural covariance analyzes

INTRODUCTION

In this study, we applied multivariate methods to identify brain regions that have a critical role in shaping the connectivity patterns of networks associated with major psychiatric diagnoses, including schizophrenia (SCH), major depressive disorder (MDD) and bipolar disorder (BD) and healthy controls (HC). We used T1w images from 164 subjects: Schizophrenia (n = 17), bipolar disorder (n = 25), major depressive disorder (n = 68) and a healthy control group (n = 54).

METHODS

We extracted regions of interest (ROIs) using a method based on the SHOOT algorithm of the SPM12 toolbox. We then performed multivariate structural covariance between the groups. For the regions identified as significant in t term of their covariance value, we calculated their eigencentrality as a measure of the influence of brain regions within the network. We applied a significance threshold of p = 0.001. Finally, we performed a cluster analysis to determine groups of regions that had similar eigencentrality profiles in different pairwise comparison networks in the observed groups.

RESULTS

As a result, we obtained 4 clusters with different brain regions that were diagnosis-specific. Cluster 1 showed the strongest discriminative values between SCH and HC and SCH and BD. Cluster 2 had the strongest discriminative value for the MDD patients, cluster 3 - for the BD patients. Cluster 4 seemed to contribute almost equally to the discrimination between the four groups.

DISCUSSION

Our results suggest that we can use the multivariate structural covariance method to identify specific regions that have higher predictive value for specific psychiatric diagnoses. In our research, we have identified brain signatures that suggest that degeneracy shapes brain networks in different ways both within and across major psychiatric disorders.