Dynamic functional hippocampal markers of residual depressive symptoms in euthymic bipolar disorder

Residual subjective depressive symptoms and resilience in patients with bipolar disorder

BACKGROUND

Residual symptoms experienced by patients with bipolar disorder (BD) is a risk factor for illness relapse/recurrence, and these symptoms are associated with a lower quality of life. Resilience allows patients to cope with stress effectively and acts as a protective factor against relapse. Therefore, this study aimed to determine the relationship between resilience and residual subjective depressive symptoms in euthymic patients with BD.

METHODS

A total of 49 euthymic patients with BD completed the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR) and the Connor-Davidson Resilience Scale (CD-RISC). Hierarchical multiple regression analysis was performed to investigate the association between QIDS-SR and CD-RISC scores.

RESULTS

The mean Clinical Global Impression for BD (CGI-BP) and QIDS-SR scores were 1.3 ± 0.5 and 8.0 ± 5.8, respectively. Although clinically stable according to objective assessment using the CGI-BP, patients with BD experienced residual subjective depressive symptoms. After adjusting for demographic and clinical characteristics, CD-RISC scores could predict QIDS-SR scores significantly in a hierarchical multiple regression. The association between CD-RISC and QIDS-SR scores did not differ according to CGI-BP scores.

LIMITATIONS

The clinical status was objectively evaluated using the CGI-BP alone. This was a cross-sectional study with a relatively small number of patients with BD, complicating the determination of the exact causal relationship between residual depressive symptoms and resilience.

CONCLUSION

Higher levels of resilience appears to be associated with lower subjective residual depressive symptoms in euthymic patients with BD. Resilience could play a protective role against the residual subjective depressive symptoms experienced by clinically stable patients with BD.

Limbic-Sensorimotor Tug of War for the Hippocampus: Dynamic Functional Connectivity as a Transdiagnostic Vulnerability Marker in Offspring of Emotion Dysregulation Patients

BACKGROUND

Emotion dysregulation (ED) is a key transdiagnostic symptom in several psychiatric disorders such as borderline personality disorder (BPD), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD). These disorders, here defined as ED disorders (EDD), share similarities in symptoms, comorbidity, and heritability, emphasizing the importance of a transdiagnostic approach to identify markers of vulnerability to EDD in high-risk populations, such as EDD patients' offspring (EDDoff). The hippocampus, central to ED, exhibits alterations across EDD.

METHODS

We employed a state-of-the-art approach (micro-co-activation patterns, μCAPs) to study the transdiagnostic dynamic functional connectivity (dFC) of hippocampal subregions from resting-state functional MRI of 201 participants (74 EDD patients, 57 EDDoff, 70 controls). μCAPs provide a data-driven differentiation within the seed region.

RESULTS

DFC between the sensorimotor network (SMN) and the hippocampal body was lower in EDD patients (pFDR=0.0002) and EDDoff (pFDR=0.01) compared to controls, with EDDoff displaying an intermediate pattern between EDD patients and controls. dFC between the limbic network (LN) and the hippocampal head was higher in EDD patients than in controls (pFDR=0.01) and in EDDoff (pFDR=0.01). A negative correlation was found between ED and SMN (pFDR=0.01), suggesting increasing ED with decreasing SMN dFC with the hippocampus.

CONCLUSIONS

Increased dFC between the hippocampal head and the LN, at the expense of the SMN, may represent a marker of disease in EDD patients. Lower dFC between the SMN and the hippocampal body may represent a marker of vulnerability to EDD in EDDoff, correlating with ED. Such a transdiagnostic construct represents a clinically relevant target for early interventions aimed at reducing vulnerability to EDD in high-risk populations.

Hippocampal temporal dynamics and spatial heterogeneity unveil vulnerability markers in the offspring of bipolar patients

OBJECTIVES

Bipolar disorder (BD) is a highly heritable disorder characterized by emotion dysregulation and recurrent oscillations between mood states. Despite the proven efficacy of early interventions, vulnerability markers in high-risk individuals are still lacking. BD patients present structural alterations of the hippocampus, a pivotal hub of emotion regulation networks composed of multiple subregions with different projections. However, the hippocampal dynamic functional connectivity (dFC) in BD remains unclear. We aim to investigate whether the dFC of hippocampal subdivisions differentiates BD patients, offspring of BD patients (BDoff), and healthy controls (HC); and whether it correlates with symptoms differently between these groups.

METHODS

We studied for the first time the dFC of the hippocampus through a cutting-edge micro-co-activation patterns (μCAPs) analysis of resting-state functional MRI data of 97 subjects (26 BD, 18 BDoff, 53 HC). μCAPs allow a data-driven differentiation within the seed region.

RESULTS

dFC between the hippocampal body and a somatomotor-μCAP was lower both in BD patients (p-valueFDR:0.00015) and in BDoff (p-valueFDR:0.020) than in HC. Inversely, dFC between the hippocampal head and a limbic-μCAP was higher in BD patients than in HC (p-valueFDR: 0.005). Furthermore, the correlations between a frontoparietal-μCAP and both depression and emotion dysregulation symptoms were significantly higher in BD than HC (p-valueFDR <0.02).

CONCLUSION

Overall, we observed alterations of large-scale functional brain networks associated with decreased cognitive control flexibility and disrupted somatomotor, saliency, and emotion processing in BD. Interestingly, BDoff presented an intermediate phenotype between BD and HC, suggesting that dFC of hippocampal subregions might represent a marker of vulnerability to BD.

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.

Manic Residual Symptoms Also Deserve Attention: A Symptom Network Analysis of Residual Symptoms in Bipolar Disorder

Background

Lots of patients with bipolar disorder (BD) continue to have residual symptoms after treatment in their remission, BD exhibits intricate characteristics and transformation patterns in its residual symptoms, residual symptoms of different polarities and degrees can mix with and transform to each other. There is a need for further investigation of BD as a comprehensive multivariate disease system. The current research lacks network analyses focusing on BD's residual and subsyndromal symptoms.

Methods

242 patients were included with bipolar disorder in remission. We compared demographic data and differences in symptoms between populations with and without residual symptoms using t-tests and chi-square tests, with FDR applied for multiple comparison correction. Logistic regression was used to identify influencing factors for residual symptoms. Symptom networks were compared by network analysis to analyze the relationships between different types of residual symptoms.

Results

Depressive residual symptoms (N=111) were more common than manic residual symptoms (n=29) in the patients included. The comparison between two groups with and without residual symptoms shows no difference in demographic data and medical history information. The main influencing factors related to residual symptoms were time from diagnosis to first treatment (OR=0.88), the first(OR=1.51) and second (OR=17.1)factors of the Mood Disorder Questionnaire (MDQ), the Quick Inventory of Depressive Symptomatology Self-Report (QIDS)(OR=5.28), the psychological(OR=0.68) and environment (OR=1.53) subscale of the World Health Organization Quality of Life Short Form (WHOQOL-BREF). There was a significant difference in network structure between the groups with and without residual symptoms (network invariance difference=0.4, p =0.025). At the same time, there was no significant difference between the groups with and without depressive residual symptoms. However, the symptom network in patients with depressive residual symptoms is more loosely structured than in those without, with symptoms exhibiting weaker interconnections. When there is no depressive or manic residual symptom, it can still form a symptom network and cause an impact on social function.

Conclusion

This study underscores the complexity of bipolar disorder's residual symptoms. Although it primarily manifests as loosely structured depressive residual symptoms, manic residual symptoms should not be ignored. Future research should explore network-based interventions targeting specific symptom clusters or connections to improve residual symptom management and patient outcomes.

The influence of accelerated brain aging on coactivation pattern dynamics in Parkinson's disease

Aging is widely acknowledged as the primary risk factor for brain degeneration, with Parkinson's disease (PD) tending to follow accelerated aging trajectories. We aim to investigate the impact of structural brain aging on the temporal dynamics of a large-scale functional network in PD. We enrolled 62 PD patients and 32 healthy controls (HCs). The level of brain aging was determined by calculating global and local brain age gap estimates (G-brainAGE and L-brainAGE) from structural images. The neural network activity of the whole brain was captured by identifying coactivation patterns (CAPs) from resting-state functional images. Intergroup differences were assessed using the general linear model. Subsequently, a spatial correlation analysis between the L-brainAGE difference map and CAPs was conducted to uncover the anatomical underpinnings of functional alterations. Compared to HCs (-3.73 years), G-brainAGE was significantly higher in PD patients (+1.93 years), who also exhibited widespread elevation in L-brainAGE. G-brainAGE was correlated with disease severity and duration. PD patients spent less time in CAPs involving activated default mode and the fronto-parietal network (DMN-FPN), as well as the sensorimotor and salience network (SMN-SN), and had a reduced transition frequency from other CAPs to the DMN-FPN and SMN-SN CAPs. Furthermore, the pattern of localized brain age acceleration showed spatial similarities with the SMN-SN CAP. Accelerated structural brain aging in PD adversely affects brain function, manifesting as dysregulated brain network dynamics. These findings provide insights into the neuropathological mechanisms underlying neurodegenerative diseases and imply the possibility of interventions for modifying PD progression by slowing the brain aging process.

Psychiatric manifestations in moyamoya disease: more than a puff of smoke? a systematic review and a case-reports meta-analysis

Introduction

Moyamoya disease (MMD) is a life-threatening condition characterized by stenosis of intracranial arteries. Despite the frequency and the impact of psychiatric symptoms on the long-term prognosis and quality of life of MMD patients, no systematic review on this topic exists.

Methods

This systematic review and meta-analysis included 41 studies (29 being case reports), from PubMed, Scopus, Embase until 27/3/2023, on MMD patients exhibiting psychiatric symptoms.

Results

Despite a fair average quality of the articles, quantitative synthesis through logistic regression was possible only for case reports, due to heterogeneity between the other studies. Psychosis, the most frequent psychiatric symptom reported in case reports, was more frequent in MMD patients with left hemisphere involvement. Neurological symptoms occurrence increased the odds of MMD diagnosis preceding psychiatric symptoms. Psychiatric symptoms are highly prevalent in MMD patients and are relatively often the only presenting symptoms.

Discussion

We discuss the diagnostic, therapeutic, and prognostic implications of recognizing and characterizing specific psychiatric symptoms in MMD, outlining preliminary guidelines for targeted pharmacological and psychotherapeutic interventions. Lastly, we outline future research and clinical perspectives, striving to enhance the oft-overlooked psychiatric care for MMD patients and to ameliorate their long-term outcome.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42023406303.

Inflammation and emotion regulation: a narrative review of evidence and mechanisms in emotion dysregulation disorders

Emotion dysregulation (ED) describes a difficulty with the modulation of which emotions are felt, as well as when and how these emotions are experienced or expressed. It is a focal overarching symptom in many severe and prevalent neuropsychiatric diseases, including bipolar disorders (BD), attention deficit/hyperactivity disorder (ADHD), and borderline personality disorder (BPD). In all these disorders, ED can manifest through symptoms of depression, anxiety, or affective lability. Considering the many symptomatic similarities between BD, ADHD, and BPD, a transdiagnostic approach is a promising lens of investigation. Mounting evidence supports the role of peripheral inflammatory markers and stress in the multifactorial aetiology and physiopathology of BD, ADHD, and BPD. Of note, neural circuits that regulate emotions appear particularly vulnerable to inflammatory insults and peripheral inflammation, which can impact the neuroimmune milieu of the central nervous system. Thus far, few studies have examined the link between ED and inflammation in BD, ADHD, and BPD. To our knowledge, no specific work has provided a critical comparison of the results from these disorders. To fill this gap in the literature, we review the known associations and mechanisms linking ED and inflammation in general, and clinically, in BD, ADHD, and BD. Our narrative review begins with an examination of the routes linking ED and inflammation, followed by a discussion of disorder-specific results accounting for methodological limitations and relevant confounding factors. Finally, we critically discuss both correspondences and discrepancies in the results and comment on potential vulnerability markers and promising therapeutic interventions.

Effects of Exercise on Functional Recovery in Patients with Bipolar Depression: A Study Protocol for a Randomized Controlled Trial

Treatment of bipolar disorder is prone to prolongation despite various treatments, including medication. The efficacy of exercise treatment (i.e., interventions involving physical exercise and sports intervention) for major depressive disorders has been reported for depressive symptoms, cognitive function, and sleep disturbances. However, its efficacy for bipolar disorder has yet to be established. We designed a randomized, controlled, double-blind clinical trial that includes 100 patients with bipolar disorder aged 20-65 years. This will be a cluster-randomized, two-group trial that will be conducted in ten psychiatric hospitals. The hospitals will be randomly assigned to an exercise intervention + treatment as usual (exercise) group or a placebo exercise intervention (stretching) + treatment as usual (control) group. Patients will be assessed using an extensive battery of clinical tests, physical parameters, sleep status, biological parameters (cytokines, neurotrophic factors), and genetic parameters (DNA and RNA) at baseline after a 6-week intervention period, at 10-week follow-up, and at 6-month follow-up. This innovative study may provide important evidence for the effectiveness of exercise in the treatment of bipolar depression based on clinical, biological, genetic, and physiological markers.

Volumes of hippocampal subfields suggest a continuum between schizophrenia, major depressive disorder and bipolar disorder

Objective

There is considerable debate as to whether the continuum of major psychiatric disorders exists and to what extent the boundaries extend. Converging evidence suggests that alterations in hippocampal volume are a common sign in psychiatric disorders; however, there is still no consensus on the nature and extent of hippocampal atrophy in schizophrenia (SZ), major depressive disorder (MDD) and bipolar disorder (BD). The aim of this study was to verify the continuum of SZ - BD - MDD at the level of hippocampal subfield volume and to compare the volume differences in hippocampal subfields in the continuum.

Methods

A total of 412 participants (204 SZ, 98 MDD, and 110 BD) underwent 3 T MRI scans, structured clinical interviews, and clinical scales. We segmented the hippocampal subfields with FreeSurfer 7.1.1 and compared subfields volumes across the three diagnostic groups by controlling for age, gender, education, and intracranial volumes.

Results

The results showed a gradual increase in hippocampal subfield volumes from SZ to MDD to BD. Significant volume differences in the total hippocampus and 13 of 26 hippocampal subfields, including CA1, CA3, CA4, GC-ML-DG, molecular layer and the whole hippocampus, bilaterally, and parasubiculum in the right hemisphere, were observed among diagnostic groups. Medication treatment had the most effect on subfields of MDD compared to SZ and BD. Subfield volumes were negatively correlated with illness duration of MDD. Positive correlations were found between subfield volumes and drug dose in SZ and MDD. There was no significant difference in laterality between diagnostic groups.

Conclusion

The pattern of hippocampal volume reduction in SZ, MDD and BD suggests that there may be a continuum of the three disorders at the hippocampal level. The hippocampus represents a phenotype that is distinct from traditional diagnostic strategies. Combined with illness duration and drug intervention, it may better reflect shared pathophysiology and mechanisms across psychiatric disorders.

Dynamic functional hippocampal markers of residual depressive symptoms in euthymic bipolar disorder

OBJECTIVES

Bipolar disorder (BD) is a severe, chronic, affective disorder characterized by recurrent switching between mood states, psychomotor and cognitive symptoms, which can linger in euthymic states as residual symptoms. Hippocampal alterations may play a key role in the neural processing of BD symptoms. However, its dynamic functional connectivity (dFC) remains unclear. Therefore, the present study explores hippocampal dFC in relation to BD symptoms.

METHODS

We assessed hippocampus-based dFC coactivation patterns (CAPs) on resting-state fMRI data of 25 euthymic BD patients and 25 age- and sex-matched healthy controls (HC).

RESULTS

Bilateral hippocampal dFC with somatomotor networks (SMN) was reduced in BD, compared to HC, while at the same time dFC between the left hippocampus and midcingulo-insular salience system (SN) was higher in BD. Correlational analysis between CAPs and clinical scores revealed that dFC between the bilateral hippocampus and the default-like network (DMN) correlated with depression scores in BD. Furthermore, pathological hyperconnectivity between the default mode network (DMN) and SMN and the frontoparietal network (FPN) was modulated by the same depression scores in BD.

CONCLUSIONS

Overall, we observed alterations of large-scale functional brain networks associated with decreased flexibility in cognitive control, salience detection, and emotion processing in BD. Additionally, the present study provides new insights on the neural architecture underlying a self-centered perspective on the environment in BD patients. dFC markers may improve detection, treatment, and follow-up of BD patients and of disabling residual depressive symptoms in particular.

Machine Learning Prediction of Estimated Risk for Bipolar Disorders Using Hippocampal Subfield and Amygdala Nuclei Volumes

The pathophysiology of bipolar disorder (BD) remains mostly unclear. Yet, a valid biomarker is necessary to improve upon the early detection of this serious disorder. Patients with manifest BD display reduced volumes of the hippocampal subfields and amygdala nuclei. In this pre-registered analysis, we used structural MRI (n = 271, 7 sites) to compare volumes of hippocampus, amygdala and their subfields/nuclei between help-seeking subjects divided into risk groups for BD as estimated by BPSS-P, BARS and EPIbipolar. We performed between-group comparisons using linear mixed effects models for all three risk assessment tools. Additionally, we aimed to differentiate the risk groups using a linear support vector machine. We found no significant volume differences between the risk groups for all limbic structures during the main analysis. However, the SVM could still classify subjects at risk according to BPSS-P criteria with a balanced accuracy of 66.90% (95% CI 59.2-74.6) for 10-fold cross-validation and 61.9% (95% CI 52.0-71.9) for leave-one-site-out. Structural alterations of the hippocampus and amygdala may not be as pronounced in young people at risk; nonetheless, machine learning can predict the estimated risk for BD above chance. This suggests that neural changes may not merely be a consequence of BD and may have prognostic clinical value.