Longitudinal Changes in Structural Connectivity in Young People at High Genetic Risk for Bipolar Disorder

Transdiagnostic white matter controllability deficits across patients with affective and anxiety spectrum disorders

BACKGROUND

Affective and anxiety disorders including major depression disorder (MDD), post-traumatic stress disorder (PTSD), and social anxiety disorder (SAD) are characterized by network dysconnectivity. Network controllability quantifies the capability of specific brain regions to impact functional dynamics based on the underlying structural connectome. This study aimed to investigate transdiagnostic and illness-specific network controllability alterations across these three disorders.

MATERIALS AND METHODS

The study enrolled 233 currently untreated and non-comorbid subjects, including 68 MDD patients, 51 PTSD patients, 46 SAD patients, and 68 healthy controls (HCs). White matter network controllability was compared among the four groups, and its associations with symptom severity and duration of untreated illness were evaluated.

RESULTS

Compared with HCs, patients with PTSD, MDD and SAD exhibited reduced average controllability in the somatomotor, subcortical, and default mode network, notably in brain regions such as the superior frontal gyrus, postcentral gyrus, paracentral gyrus, pallidum, posterior cingulate, and putamen. MDD and SAD patients exhibited reduced average controllability in the left lateral occipital gyrus and bilateral accumbens. SAD patients showed reduced average controllability in the dorsal attention network. These controllability changes did not correlate with illness duration or symptom severity.

LIMITATIONS

The cross-sectional design limits causal inference, and adjusting for age and sex differences may not completely eliminate their influence on the results.

CONCLUSION

The present study revealed shared and specific alterations of network controllability in MDD, PTSD, and SAD, suggesting reduced ability of specific brain regions/networks in driving the brain system into different functional states across these disorders.

Enhancing Early Diagnosis of Bipolar Disorder in Adolescents Through Multimodal Neuroimaging

BACKGROUND

Bipolar disorder (BD), a severe neuropsychiatric condition, often appears during adolescence. Traditional diagnostic methods, which primarily rely on clinical interviews and single-modal magnetic resonance imaging (MRI) techniques, may have limitations in accuracy. This study aimed to improve adolescent BD diagnosis by integrating behavioral assessments with multimodal MRI. We hypothesized that this combination would enhance diagnostic accuracy for at-risk adolescents.

METHODS

A retrospective cohort of 309 participants, including patients with BD, offspring of patients with BD (with and without subthreshold symptoms), non-BD offspring with subthreshold symptoms, and healthy control participants, was analyzed. Behavioral attributes were integrated with MRI features from T1-weighted, resting-state functional MRI, and diffusion tensor imaging. Three diagnostic models were developed using GLMNET multinomial regression: a clinical diagnosis model based on behavioral attributes, an MRI-based model, and a comprehensive model integrating both datasets.

RESULTS

The comprehensive model achieved a prediction accuracy of 0.83 (95% CI, 0.72-0.92), significantly higher than the clinical (0.75) and MRI-based (0.65) models. Validation with an external cohort showed high accuracy (0.89, area under the curve = 0.95). Structural equation modeling revealed that clinical diagnosis (β = 0.487, p < .0001), parental BD history (β = -0.380, p < .0001), and global function (β = 0.578, p < .0001) significantly affected brain health, while psychiatric symptoms showed only a marginal influence (β = -0.112, p = .056).

CONCLUSIONS

This study highlights the value of integrating multimodal MRI with behavioral assessments for early diagnosis in at-risk adolescents. Combining neuroimaging enables more accurate patient subgroup distinctions, facilitating timely interventions and improving health outcomes. Our findings suggest a paradigm shift in BD diagnostics, advocating for incorporating advanced imaging techniques in routine evaluations.

Reconfiguration of brain network dynamics in bipolar disorder: a hidden Markov model approach

Bipolar disorder (BD) is a neuropsychiatric disorder characterized by severe disturbance and fluctuation in mood. Dynamic functional connectivity (dFC) has the potential to more accurately capture the evolving processes of emotion and cognition in BD. Nevertheless, prior investigations of dFC typically centered on larger time scales, limiting the sensitivity to transient changes. This study employed hidden Markov model (HMM) analysis to delve deeper into the moment-to-moment temporal patterns of brain activity in BD. We utilized resting-state functional magnetic resonance imaging (rs-fMRI) data from 43 BD patients and 51 controls to evaluate the altered dynamic spatiotemporal architecture of the whole-brain network and identify unique activation patterns in BD. Additionally, we investigated the relationship between altered brain dynamics and structural disruption through the ridge regression (RR) algorithm. The results demonstrated that BD spent less time in a hyperconnected state with higher network efficiency and lower segregation. Conversely, BD spent more time in anticorrelated states featuring overall negative correlations, particularly among pairs of default mode network (DMN) and sensorimotor network (SMN), DMN and insular-opercular ventral attention networks (ION), subcortical network (SCN) and SMN, as well as SCN and ION. Interestingly, the hypoactivation of the cognitive control network in BD may be associated with the structural disruption primarily situated in the frontal and parietal lobes. This study investigated the dynamic mechanisms of brain network dysfunction in BD and offered fresh perspectives for exploring the physiological foundation of altered brain dynamics.

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.

Age Trajectories of the Structural Connectome in Child and Adolescent Offspring of Individuals With Bipolar Disorder or Schizophrenia

Background

Offspring of parents with severe mental illness (e.g., bipolar disorder or schizophrenia) are at elevated risk of developing psychiatric illness owing to both genetic predisposition and increased burden of environmental stress. Emerging evidence indicates a disruption of brain network connectivity in young offspring of patients with bipolar disorder and schizophrenia, but the age trajectories of these brain networks in this high-familial-risk population remain to be elucidated.

Methods

A total of 271 T1-weighted and diffusion-weighted scans were obtained from 174 offspring of at least 1 parent diagnosed with bipolar disorder (n = 74) or schizophrenia (n = 51) and offspring of parents without severe mental illness (n = 49). The age range was 8 to 23 years; 97 offspring underwent 2 scans. Anatomical brain networks were reconstructed into structural connectivity matrices. Network analysis was performed to investigate anatomical brain connectivity.

Results

Offspring of parents with schizophrenia had differential trajectories of connectivity strength and clustering compared with offspring of parents with bipolar disorder and parents without severe mental illness, of global efficiency compared with offspring of parents without severe mental illness, and of local connectivity compared with offspring of parents with bipolar disorder.

Conclusions

The findings of this study suggest that familial high risk of schizophrenia is related to deviations in age trajectories of global structural connectome properties and local connectivity strength.

Aberrant brain network topology in youth with a familial risk for bipolar disorder: a task-based fMRI connectome study

BACKGROUND

Youth with a family history of bipolar disorder (BD) may be at increased risk for mood disorders and for developing side effects after antidepressant exposure. The neurobiological basis of these risks remains poorly understood. We aimed to identify biomarkers underlying risk by characterizing abnormalities in the brain connectome of symptomatic youth at familial risk for BD.

METHODS

Depressed and/or anxious youth (n = 119, age = 14.9 ± 1.6 years) with a family history of BD but no prior antidepressant exposure and typically developing controls (n = 57, age = 14.8 ± 1.7 years) received functional magnetic resonance imaging (fMRI) during an emotional continuous performance task. A generalized psychophysiological interaction (gPPI) analysis was performed to compare their brain connectome patterns, followed by machine learning of topological metrics.

RESULTS

High-risk youth showed weaker connectivity patterns that were mainly located in the default mode network (DMN) (network weight = 50.1%) relative to controls, and connectivity patterns derived from the visual network (VN) constituted the largest proportion of aberrant stronger pairs (network weight = 54.9%). Global local efficiency (Elocal, p = .022) and clustering coefficient (Cp, p = .029) and nodal metrics of the right superior frontal gyrus (SFG) (Elocal: p < .001; Cp: p = .001) in the high-risk group were significantly higher than those in healthy subjects, and similar patterns were also found in the left insula (degree: p = .004; betweenness: p = .005; age-by-group interaction, p = .038) and right hippocampus (degree: p = .003; betweenness: p = .003). The case-control classifier achieved a cross-validation accuracy of 78.4%.

CONCLUSIONS

Our findings of abnormal connectome organization in the DMN and VN may advance mechanistic understanding of risk for BD. Neuroimaging biomarkers of increased network segregation in the SFG and altered topological centrality in the insula and hippocampus in broader limbic systems may be used to target interventions tailored to mitigate the underlying risk of brain abnormalities in these at-risk youth.

A Preliminary Study of Brain Developmental Features of Bipolar Disorder Familial Risk and Subthreshold Symptoms

BACKGROUND

Risk for bipolar disorder (BD) is increased among individuals with a family history or subthreshold mood symptoms. However, the brain structural developments associated with these BD risks remain unknown.

METHODS

This longitudinal cohort study examined the brain gray matter volume (GMV) developmental features of familial and symptomatic risks for BD and their associations with participants' global function levels. We recruited unaffected BD offspring with (n = 26, 14 female, mean ± SD age = 14.9 ± 2.9 years) or without (n = 35, 19 female, age = 15.3 ± 2.7 years) subthreshold manic or depressive symptoms and unaffected non-BD offspring with (n = 49, 30 female, age = 14.5 ± 2.2 years) or without (n = 68, 37 female, age = 15.0 ± 2.3 years) symptoms. The offspring had no mood disorder diagnosis prior to the study. The average follow-up duration was 2.63 ± 1.63 years.

RESULTS

At baseline, we found significant interactive effects of familial risk and subthreshold symptoms that indicated that the symptomatic offspring exhibited markedly large GMV in the brain affective and cognitive circuitries. During follow-up, the combined group of BD offspring (symptomatic and nonsymptomatic) displayed a more accelerated GMV decrease than BD nonoffspring in the hippocampus and anterior cingulate cortex. In contrast, the combined group of symptomatic participants (offspring and nonoffspring) displayed a slower GMV decrease than nonsymptomatic participants in the ventromedial prefrontal cortex. Larger GMV at baseline and accelerated GMV decrease during follow-up prospectively and longitudinally predicted positive global function changes. All results survived multiple testing correction.

CONCLUSIONS

These findings indicated that familial and symptomatic risks of BD are associated with distinct brain structural developments and unraveled key brain developmental features of particularly vulnerable high-risk individuals to subsequent functional deterioration.

Common and distinct neural correlates of emotional processing in individuals at familial risk for major depressive disorder and bipolar disorder: A comparative meta-analysis

Individuals at familial risk for mood disorders exhibit deficits in emotional processing and associated brain dysfunction prior to illness onset. However, such brain-behavior abnormalities related to familial predisposition remain poorly understood. To investigate robust abnormal functional activation patterns during emotional processing in unaffected at-risk relatives of patients with major depressive disorder (UAR-MDD) and bipolar disorder (UAR-BD), we performed a meta-analysis of task-based functional magnetic resonance imaging studies using Seed-based d Mapping (SDM) toolbox. Common and distinct patterns of abnormal functional activation between UAR-MDD and UAR-BD were detected via conjunction and differential analyses. A total of 17 studies comparing 481 UAR and 670 healthy controls (HC) were included. Compared with HC, UAR-MDD exhibited hyperactivation in the parahippocampal gyrus, amygdala and cerebellum, while UAR-BD exhibited parahippocampal hyperactivation and hypoactivation in the striatum and middle occipital gyrus (MOG). Conjunction analysis revealed shared hyperactivated PHG in both groups. Differential analysis indicated that the activation patterns of amygdala and MOG significantly differed between UAR-MDD and UAR-BD. These findings provide novel insights into common and distinct neural phenotypes for familial risk and associated risk mechanisms in MDD and BD, which may have implications in guiding precise prevention strategies tailored to the family context.

Cerebellar morphological differences and associations with extrinsic factors in bipolar disorder type I

BACKGROUND

The neural underpinnings of bipolar disorder (BD) remain poorly understood. The cerebellum is ideally positioned to modulate emotional regulation circuitry yet has been understudied in BD. Literature suggests differences in cerebellar activity and metabolism in BD, however findings on structural differences remain contradictory. Potential reasons include combining BD subtypes, small sample sizes, and potential moderators such as genetics, adverse childhood experiences (ACEs), and pharmacotherapy.

METHODS

We collected 3 T MRI scans from participants with (N = 131) and without (N = 81) BD type I, as well as blood and questionnaires. We assessed differences in cerebellar volumes and explored potentially influential factors.

RESULTS

The cerebellar cortex was smaller bilaterally in participants with BD. Polygenic propensity score did not predict any cerebellar volumes, suggesting that non-genetic factors may have greater influence on the cerebellar volume difference we observed in BD. Proportionate cerebellar white matter volumes appeared larger with more ACEs, but this may result from reduced ICV. Time from onset and symptom burden were not associated with cerebellar volumes. Finally, taking sedatives was associated with larger cerebellar white matter and non-significantly larger cortical volume.

LIMITATIONS

This study was cross-sectional, limiting interpretation of possible mechanisms. Most of our participants were White, which could limit the generalizability. Additionally, we did not account for potential polypharmacy interactions.

CONCLUSIONS

These findings suggest that external factors, such as sedatives and childhood experiences, may influence cerebellum structure in BD and may mask underlying differences. Accounting for such variables may be critical for consistent findings in future studies.

Preventive interventions for individuals at risk of developing bipolar disorder: A systematic review and meta-analysis

BACKGROUND

This systematic review and meta-analysis aimed to explore whether early interventions can reduce affective symptoms and have long-term benefits among individuals at risk of bipolar disorder (BD).

METHODS

The PubMed, Embase, and Web of Science databases were searched. The primary outcome was continuous symptom scores before and after treatment. Random effects meta-analyses were conducted for each outcome arm studied and pooled mean difference estimates were calculated.

RESULTS

The search identified 10 controlled studies involving 425 participants and 6 single-arm studies involving 90 participants. For controlled trials, meta-analysis showed that the interventions led to greater reduction in clinical global score than placebo (standardized mean differences (SMD) = -0.96, 95 % CI:-1.32, -0.60), and supported a long-term longitudinal effect for pharmacotherapy (SMD = -0.42, 95 % CI: -0.79, -0.05). For single-arm trials, both pharmacotherapy and psychotherapy showed efficacy for depressive symptoms, while pharmacotherapy only showed efficacy for hypomania symptoms (effect size (ES) = -9.16, 95 % CI:-11.29, -7.04). Discontinuation of pharmacotherapy due to adverse effects did not show a difference.

LIMITATIONS

The primary limitations are the small number of RCTs and the influence of medication dosage.

CONCLUSIONS

Based on the limited available data, early interventions show efficacy for individuals at risk of BD. Psychological therapy might be more beneficial for depressive symptoms and have long-term benefits for hypomania. Pharmacotherapy may be appropriate in situations of severe hypomanic symptoms and the poor functioning. Large, well-designed, double-blind -controlled trials are needed to make solid conclusions about the efficacy of early interventions.

Polygenic Scores and Onset of Major Mood or Psychotic Disorders Among Offspring of Affected Parents

OBJECTIVE

Family history is an established risk factor for mental illness. The authors sought to investigate whether polygenic scores (PGSs) can complement family history to improve identification of risk for major mood and psychotic disorders.

METHODS

Eight cohorts were combined to create a sample of 1,884 participants ages 2-36 years, including 1,339 offspring of parents with mood or psychotic disorders, who were prospectively assessed with diagnostic interviews over an average of 5.1 years. PGSs were constructed for depression, bipolar disorder, anxiety, attention deficit hyperactivity disorder (ADHD), schizophrenia, neuroticism, subjective well-being, p factor, and height (as a negative control). Cox regression was used to test associations between PGSs, family history of major mental illness, and onsets of major mood and psychotic disorders.

RESULTS

There were 435 onsets of major mood and psychotic disorders across follow-up. PGSs for neuroticism (hazard ratio=1.23, 95% CI=1.12-1.36), schizophrenia (hazard ratio=1.15, 95% CI=1.04-1.26), depression (hazard ratio=1.11, 95% CI=1.01-1.22), ADHD (hazard ratio=1.10, 95% CI=1.00-1.21), subjective well-being (hazard ratio=0.90, 95% CI=0.82-0.99), and p factor (hazard ratio=1.14, 95% CI=1.04-1.26) were associated with onsets. After controlling for family history, neuroticism PGS remained significantly positively associated (hazard ratio=1.19, 95% CI=1.08-1.31) and subjective well-being PGS remained significantly negatively associated (hazard ratio=0.89, 95% CI=0.81-0.98) with onsets.

CONCLUSIONS

Neuroticism and subjective well-being PGSs capture risk of major mood and psychotic disorders that is independent of family history, whereas PGSs for psychiatric illness provide limited predictive power when family history is known. Neuroticism and subjective well-being PGSs may complement family history in the early identification of persons at elevated risk.

Hippocampal cingulum white matter increases over time in young people at high genetic risk for bipolar disorder

BACKGROUND

Bipolar disorder (BD) is a strongly familial psychiatric disorder associated with white matter (WM) brain abnormalities. It is unclear whether such abnormalities are present in relatives without BD, and little is known about WM trajectories in those at increased genetic risk.

METHODS

Diffusion magnetic resonance imaging (dMRI) data were acquired at baseline and after two years in 91 unaffected individuals with a first-degree relative with bipolar disorder (HR), and 85 individuals with no family history of mental illness (CON). All participants were aged between 12 and 30 years at baseline. We examined longitudinal change in Fractional Anisotropy (FA) using tract-based spatial statistics (TBSS).

RESULTS

Compared to the CON group, HR participants showed a significant increase in FA in the right cingulum (hippocampus) (CGH) over a two-year period (p < .05, FDR corrected). This effect was more pronounced in HR individuals without a lifetime diagnosis of a mood disorder than those with a mood disorder.

LIMITATIONS

While our study is well powered to achieve the primary objectives, our sub-group analyses were under powered.

CONCLUSIONS

In one of the very few longitudinal neuroimaging studies of young people at high risk for BD, this study reports novel evidence of atypical white matter development in HR individuals in a key cortico-limbic tract involved in emotion regulation. Our findings also suggest that this different white matter developmental trajectory may be stronger in HR individuals without affective psychopathology. As such, increases in FA in the right CGH of HR participants may be a biomarker of resilience to mood disorders.