A graph theory neuroimaging approach to distinguish the depression of bipolar disorder from major depressive disorder in adolescents and young adults

Exploring Behavioural Patterns in Youth Predisposed to Bipolar Disorder and the Role of Interpersonal Trauma Using the Adolescent Brain Cognitive Development (ABCD) Dataset

INTRODUCTION

Bipolar disorder (BD) is a severe, persistent disorder that causes functional impairment. Besides heritability, environmental factors, such as traumatic experience, impact the development of BD. Little is known about the early developmental signs of this disorder; therefore, this study aims to look at the impact of interpersonal trauma on the early developmental signs of BD. Specifically, differences in psychopathological behaviours were investigated between (1) at-risk children and controls and (2) at-risk children who experienced an interpersonal traumatic event and those who did not.

METHODS

Using the Adolescent Brain Cognitive Development (ABCD) dataset, participants with a first-degree relative with BD were identified (Nat-risk = 625) and matched on sex and age to a control group (Ncontrol = 625). The Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS) was used to assess interpersonal trauma and psychopathological symptoms. The trauma (Ntrauma = 198) and no-trauma sub-groups (Nno-trauma = 428) were built from the at-risk population. Group comparison was conducted on depressive, manic and anxiety symptoms.

RESULTS

Compared to controls, at-risk children exhibited a significantly greater number of manic symptoms at baseline and 2-year follow-up, and anxiety symptoms at follow-up. No significant differences were found between the trauma and no-trauma groups at either baseline or follow-up.

DISCUSSION

These results confirm the presence of early symptoms in at-risk children, in line with the staging model of BD. Extended longitudinal research is needed to further investigate the potential specific role of trauma on its early behavioural patterns.

The impact of obsessive-compulsive personality disorder on obsessive-compulsive disorder: clinical outcomes in the context of bipolarity

Obsessive-compulsive disorder (OCD) is characterized by obsessions and compulsions that significantly impair functioning. Obsessive-compulsive personality disorder (OCPD) co-occurs in 17-45% of OCD patients, worsening outcomes across multiple domains. Therefore, we aimed to study the impact of OCPD in more detail by analyzing selected comorbidities, emotional aspects, and sociodemographic data. This study assessed 78 OCD patients (average age 44.9 years, 34.61% OCPD), using Y-BOCS, BABS, BPAQ, BIS-11, YMRS, HDRS-17, and ASEX. Patients with comorbid OCPD had significantly worse outcomes in symptom severity (Y-BOCS = 0.0006), treatment duration (p = 0.0127), insight (BABS, p = 0.0185), aggression (p = 0.0266), impulsivity (p = 0.0469), depression (HDRS, p = 0.0178), mania (YMRS, p = 0.0003), and sexual dysfunction (ASEX, p = 0.008). OCPD was more prevalent in unemployed individuals (p = 0.046) and older patients (p = 0.009). No significant differences were found regarding gender, education, or relationship status. Obsessions and compulsions, such as contamination (p = 0.025), somatic (p = 0.018), ruminations (p = 0.003), and obsessional slowness (p = 0.007), were more common in the OCPD group. In the group with OCPD, aggression and OCD severity were correlated with increased levels of depression, which can be considered potential correlates of bipolarity in the relationship between OCD and OCPD. In conclusion, OCPD significantly worsens clinical outcomes in OCD across emotional, behavioral, and functional dimensions.

Towards a neurodevelopmental model of bipolar disorder: a critical review of trait- and state-related functional neuroimaging in adolescents and young adults

Neurodevelopmental mechanisms are increasingly implicated in bipolar disorder (BD), highlighting the importance of their study in young persons. Neuroimaging studies have demonstrated a central role for frontotemporal corticolimbic brain systems that subserve processing and regulation of emotions, and processing of reward in adults with BD. As adolescence and young adulthood (AYA) is a time when fully syndromal BD often emerges, and when these brain systems undergo dynamic maturational changes, the AYA epoch is implicated as a critical period in the neurodevelopment of BD. Functional magnetic resonance imaging (fMRI) studies can be especially informative in identifying the functional neuroanatomy in adolescents and young adults with BD (BDAYA) and at high risk for BD (HR-BDAYA) that is related to acute mood states and trait vulnerability to the disorder. The identification of early emerging brain differences, trait- and state-based, can contribute to the elucidation of the developmental neuropathophysiology of BD, and to the generation of treatment and prevention targets. In this critical review, fMRI studies of BDAYA and HR-BDAYA are discussed, and a preliminary neurodevelopmental model is presented based on a convergence of literature that suggests early emerging dysfunction in subcortical (e.g., amygdalar, striatal, thalamic) and caudal and ventral cortical regions, especially ventral prefrontal cortex (vPFC) and insula, and connections among them, persisting as trait-related features. More rostral and dorsal cortical alterations, and bilaterality progress later, with lateralization, and direction of functional imaging findings differing by mood state. Altered functioning of these brain regions, and regions they are strongly connected to, are implicated in the range of symptoms seen in BD, such as the insula in interoception, precentral gyrus in motor changes, and prefrontal cortex in cognition. Current limitations, and outlook on the future use of neuroimaging evidence to inform interventions and prevent the onset of mood episodes in BDAYA, are outlined.

Diagnostic value of structural, functional and effective connectivity in bipolar disorder

INTRODUCTION

The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS.

RESULTS

A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria.

DISCUSSION

Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network. Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.

Effects of one night of sleep deprivation on whole brain intrinsic connectivity distribution using a graph theory neuroimaging approach

Neuroimaging studies have revealed disturbances in brain functional connectivity (FC) after one night of sleep deprivation (SD). These researches explored the alterations of FC using classical regions of interest (ROI)-based analysis or functional connectivity density. However, these methods need for a priori information about the selected ROIs and a specific correlation threshold to define a connection between two ROIs or voxels, which may bring inconsistent results. In the present study, we adopted a data-driven, whole brain voxel-based graph-theoretical approach, intrinsic connectivity distribution (ICD) analysis, to examine changes of brain connectivity after SD in 52 normal young subjects without any prior knowledge. The cross-hemisphere ICD (ch-ICD) analysis was also performed to discover the effect of SD on cerebral lateralization. We found that sleep-deprived subjects showed significant reduced ICD in default mode network (DMN) and limbic network, and increased ICD in sensorimotor network. Furthermore, after SD, the ICD in the right precuneus showed significant correlation with psychomotor vigilance test (PVT) performance following the stepwise regression analysis after Bonferroni correction (ICD = 0.43 - 0.62∗10 % fast reaction time + 0.31∗the standard deviation of reaction time, p = 0.0012). Follow-up seed-based FC analyses in the right precuneus revealed decreased FC to regions in DMN, visual network, ventral attentional network and frontal-parietal network. Nevertheless, no striking difference of ch-ICD was found following SD. In conclusion, these findings suggested that DMN, especially precuneus may be hubs of FC disturbances associated with vigilance after SD, and may provide new insights into the intervention for SD.

Deficits in prefrontal metabotropic glutamate receptor 5 are associated with functional alterations during emotional processing in bipolar disorder

BACKGROUND

Elucidating biological mechanisms contributing to bipolar disorder (BD) is key to improved diagnosis and treatment development. With converging evidence implicating the metabotropic glutamate receptor 5 (mGlu5) in the pathology of BD, here, we therefore test the hypothesis that recently identified deficits in mGlu5 are associated with functional brain differences during emotion processing in BD.

METHODS

Positron emission tomography (PET) with [18F]FPEB was used to measure mGlu5 receptor availability and functional imaging (fMRI) was performed while participants completed an emotion processing task. Data were analyzed from 62 individuals (33 ± 12 years, 45 % female) who completed both PET and fMRI, including individuals with BD (n = 18), major depressive disorder (MDD: n = 20), and psychiatrically healthy comparisons (HC: n = 25).

RESULTS

Consistent with some prior reports, the BD group displayed greater activation during fear processing relative to MDD and HC, notably in right lateralized frontal and parietal brain regions. In BD, (but not MDD or HC) lower prefrontal mGlu5 availability was associated with greater activation in bilateral pre/postcentral gyri and cuneus during fear processing. Furthermore, greater prefrontal mGlu5-related brain activity in BD was associated with difficulties in psychomotor function (r≥0.904, p≤0.005) and attention (r≥0.809, p≤0.028).

LIMITATIONS

The modest sample size is the primary limitation.

CONCLUSIONS

Deficits in prefrontal mGlu5 in BD were linked to increased cortical activation during fear processing, which in turn was associated with impulsivity and attentional difficulties. These data further implicate an mGlu5-related mechanism unique to BD. More generally these data suggest integrating PET and fMRI can provide novel mechanistic insights.

Distinct global brain connectivity alterations in depressed adolescents with subthreshold mania and the relationship with processing speed: Evidence from sBEAD Cohort

BACKGROUND

Bipolar disorder (BD) is a progressive condition. Investigating the neuroimaging mechanisms in depressed adolescents with subthreshold mania (SubMD) facilitates the early identification of BD. However, the global brain connectivity (GBC) patterns in SubMD patients, as well as the relationship with processing speed before the onset of full-blown BD, remain unclear.

METHODS

The study involved 72 SubMD, 77 depressed adolescents without subthreshold mania (nSubMD), and 69 gender- and age-matched healthy adolescents (HCs). All patients underwent a clinical follow-up ranging from six to twelve months. We calculated the voxel-based graph theory analysis of the GBC map and conducted the TMT-A test to measure the processing speed.

RESULTS

Compared to HCs and nSubMD, SubMD patients displayed distinctive GBC index patterns: GBC index decreased in the right Medial Superior Frontal Gyrus (SFGmed.R)/Superior Frontal Gyrus (SFG) while increased in the right Precuneus and left Postcentral Gyrus. Both patient groups showed increased GBC index in the right Inferior Temporal Gyrus. An increased GBC value in the right Supplementary Motor Area was exclusively observed in the nSubMD-group. There were opposite changes in the GBC index in SFGmed.R/SFG between two patient groups, with an AUC of 0.727. Additionally, GBC values in SFGmed.R/SFG exhibited a positive correlation with TMT-A scores in SubMD-group.

LIMITATIONS

Relatively shorter follow-up duration, medications confounding, and modest sample size.

CONCLUSION

These findings suggest that adolescents with subthreshold BD have specific impairments patterns at the whole brain connectivity level associated with processing speed impairments, providing insights into early identification and intervention strategies for BD.

Resting-state fMRI network efficiency as a mediator in the relationship between the glymphatic system and cognitive function in obstructive sleep apnea hypopnea syndrome: Insights from a DTI-ALPS investigation

INTRODUCTION

Obstructive sleep apnea hypopnea syndrome (OSAHS) is associated with cognitive impairment and physiological complications, necessitating further understanding of its mechanisms. This study investigates the relationship between glymphatic system function, brain network efficiency, and cognitive impairment in OSAHS patients using diffusion tensor image analysis along the perivascular space (DTI-ALPS) and resting-state fMRI.

MATERIALS AND METHODS

This study included 31 OSAHS patients and 34 age- and gender-matched healthy controls (HC). All participants underwent GE 3.0T magnetic resonance imaging (MRI) with diffusion tensor image (DTI) and resting-state fMRI scans. The DTI-ALPS index and brain functional networks were assessed. Differences between groups and correlations with clinical characteristics were analyzed. Additionally, the mediating role of brain network efficiency was explored. Finally, receiver operating characteristics (ROC) analysis assessed diagnostic performance.

RESULTS

OSAHS patients had significantly lower ALPS-index (1.268 vs. 1.431, p < 0.0001) and moderate negative correlation with Apnea Hypopnea Index (AHI) (r = -0.389, p = 0.031), as well as moderate positive correlation with Montreal Cognitive Assessment (MoCA) (r = 0.525, p = 0.002). Moreover, global efficiency (Eg) of the brain network was positively correlated with the ALPS-index and MoCA scores in OSAHS patients (r = 0.405, p = 0.024; r = 0.56, p = 0.001, respectively). Furthermore, mediation analysis showed that global efficiency partially mediated the impact of glymphatic system dysfunction on cognitive impairment in OSAHS patients (indirect effect = 4.58, mediation effect = 26.9 %). The AUROC for identifying OSAHS and HC was 0.80 (95 % CI 0.69 to 0.91) using an ALPS-index cut-off of 1.35.

CONCLUSIONS

OSAHS patients exhibit decreased ALPS-index, indicating impaired glymphatic system function. Dysfunction of the glymphatic system can affect cognitive function in OSAHS by disrupting brain functional network, suggesting a potential underlying pathological mechanism. Additionally, preliminary findings suggest that the ALPS-index may offer promise as a potential indicator for OSAHS.

Common and distinct functional brain network abnormalities in adolescent, early-middle adult, and late adult major depressive disorders

BACKGROUND

The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis.

METHODS

The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12-17 years old; 411 early-middle adults, 18-54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively.

RESULTS

We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs.

CONCLUSIONS

To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD.

Predicting depressed and elevated mood symptomatology in bipolar disorder using brain functional connectomes

BACKGROUND

The study is aimed to identify brain functional connectomes predictive of depressed and elevated mood symptomatology in individuals with bipolar disorder (BD) using the machine learning approach Connectome-based Predictive Modeling (CPM).

METHODS

Functional magnetic resonance imaging data were obtained from 81 adults with BD while they performed an emotion processing task. CPM with 5000 permutations of leave-one-out cross-validation was applied to identify functional connectomes predictive of depressed and elevated mood symptom scores on the Hamilton Depression and Young Mania rating scales. The predictive ability of the identified connectomes was tested in an independent sample of 43 adults with BD.

RESULTS

CPM predicted the severity of depressed [concordance between actual and predicted values (r = 0.23, pperm (permutation test) = 0.031) and elevated (r = 0.27, pperm = 0.01) mood. Functional connectivity of left dorsolateral prefrontal cortex and supplementary motor area nodes, with inter- and intra-hemispheric connections to other anterior and posterior cortical, limbic, motor, and cerebellar regions, predicted depressed mood severity. Connectivity of left fusiform and right visual association area nodes with inter- and intra-hemispheric connections to the motor, insular, limbic, and posterior cortices predicted elevated mood severity. These networks were predictive of mood symptomatology in the independent sample (r ⩾ 0.45, p = 0.002).

CONCLUSIONS

This study identified distributed functional connectomes predictive of depressed and elevated mood severity in BD. Connectomes subserving emotional, cognitive, and psychomotor control predicted depressed mood severity, while those subserving emotional and social perceptual functions predicted elevated mood severity. Identification of these connectome networks may help inform the development of targeted treatments for mood symptoms.

Differentiation between bipolar disorder and major depressive disorder in adolescents: from clinical to biological biomarkers

Background

Mood disorders are very common among adolescents and include mainly bipolar disorder (BD) and major depressive disorder (MDD), with overlapping depressive symptoms that pose a significant challenge to realizing a rapid and accurate differential diagnosis in clinical practice. Misdiagnosis of BD as MDD can lead to inappropriate treatment and detrimental outcomes, including a poorer ultimate clinical and functional prognosis and even an increased risk of suicide. Therefore, it is of great significance for clinical management to identify clinical symptoms or features and biological markers that can accurately distinguish BD from MDD. With the aid of bibliometric analysis, we explore, visualize, and conclude the important directions of differential diagnostic studies of BD and MDD in adolescents.

Materials and methods

A literature search was performed for studies on differential diagnostic studies of BD and MDD among adolescents in the Web of Science Core Collection database. All studies considered for this article were published between 2004 and 2023. Bibliometric analysis and visualization were performed using the VOSviewer and CiteSpace software.

Results

In total, 148 publications were retrieved. The number of publications on differential diagnostic studies of BD and MDD among adolescents has been generally increasing since 2012, with the United States being an emerging hub with a growing influence in the field. Boris Birmaher is the top author in terms of the number of publications, and the Journal of Affective Disorders is the most published journal in the field. Co-occurrence analysis of keywords showed that clinical characteristics, genetic factors, and neuroimaging are current research hotspots. Ultimately, we comprehensively sorted out the current state of research in this area and proposed possible research directions in future.

Conclusion

This is the first-ever study of bibliometric and visual analyses of differential diagnostic studies of BD and MDD in adolescents to reveal the current research status and important directions in the field. Our research and analysis results might provide some practical sources for academic scholars and clinical practice.

Common and unique alterations of functional connectivity in major depressive disorder and bipolar disorder

OBJECTIVE

Major depressive disorder (MDD) and bipolar disorder (BD) are considered whole-brain disorders with some common clinical and neurobiological features. It is important to investigate neural mechanisms to distinguish between the two disorders. However, few studies have explored the functional dysconnectivity between the two disorders from the whole brain level.

METHODS

In this study, 117 patients with MDD, 65 patients with BD, and 116 healthy controls completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Both edge-based network construction and large-scale network analyses were applied.

RESULTS

Results found that both the BD and MDD groups showed decreased FC in the whole brain network. The shared aberrant network across patients involves the visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and ventral attention network (VAN), which is related to the processing of external stimuli. The default mode network (DMN) and the limbic network (LN) abnormalities were only found in patients with MDD. Furthermore, results showed the highest decrease in edges of patients with MDD in between-network FC in SMN-VN, whereas in VAN-VN of patients with BD.

CONCLUSIONS

Our findings indicated that both MDD and BD are extensive abnormal brain network diseases, mainly aberrant in those brain networks correlated to the processing of external stimuli, especially the attention network. Specific altered functional connectivity also was found in MDD and BD groups, respectively. These results may provide possible trait markers to distinguish the two disorders.

Brain Hemispheric Asymmetry in Schizophrenia and Bipolar Disorder

BACKGROUND

This study aimed to compare brain asymmetry in patients with schizophrenia (SCZ), bipolar disorder (BPD), and healthy controls to test whether asymmetry patterns could discriminate and set boundaries between two partially overlapping severe mental disorders.

METHODS

We applied a fully automated voxel-based morphometry (VBM) approach to assess structural brain hemispheric asymmetry in magnetic resonance imaging (MRI) anatomical scans in 60 participants (SCZ = 20; BP = 20; healthy controls = 20), all right-handed and matched for gender, age, and education.

RESULTS

Significant differences in gray matter asymmetry were found between patients with SCZ and BPD, between SCZ patients and healthy controls (HC), and between BPD patients and HC. We found a higher asymmetry index (AI) in BPD patients when compared to SCZ in Brodmann areas 6, 11, and 37 and anterior cingulate cortex and an AI higher in SCZ patients when compared to BPD in the cerebellum.

CONCLUSION

Our study found significant differences in brain asymmetry between patients with SCZ and BPD. These promising results could be translated to clinical practice, given that structural brain changes detected by MRI are good candidates for exploration as biological markers for differential diagnosis, besides helping to understand disease-specific abnormalities.