Structural dysconnectivity in offspring of individuals with bipolar disorder: The effect of co-existing clinical-high-risk for bipolar disorder

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.

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.

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.

Increased grey matter volumes in the temporal lobe and its relationship with cognitive functioning in euthymic patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodic mood dysregulation, although a significant portion of patients suffer persistent cognitive impairment during euthymia. Previous magnetic resonance imaging (MRI) research suggests BD patients may have accelerated brain aging, observed as lower grey matter volumes. How these neurostructural alterations are related to the cognitive profile of BD is unclear.

METHODS

We aim to explore this relationship in euthymic BD patients with multimodal structural neuroimaging. A sample of 27 euthymic BD patients and 24 healthy controls (HC) underwent structural grey matter MRI and diffusion-weighted imaging (DWI). BD patient's cognition was also assessed. FreeSurfer algorithms were used to obtain estimations of regional grey matter volumes. White matter pathways were reconstructed using TRACULA, and four diffusion metrics were extracted. ANCOVA models were performed to compare BD patients and HC values of regional grey matter volume and diffusion metrics. Global brain measures were also compared. Bivariate Pearson correlations were explored between significant brain results and five cognitive domains.

RESULTS

Euthymic BD patients showed higher ventricular volume (F(1, 46) = 6.04; p = 0.018) and regional grey matter volumes in the left fusiform (F(1, 46) = 15.03; pFDR = 0.015) and bilateral parahippocampal gyri compared to HC (L: F(1, 46) = 12.79, pFDR = 0.025/ R: F(1, 46) = 15.25, pFDR = 0.015). Higher grey matter volumes were correlated with greater executive function (r = 0.53, p = 0.008).

LIMITATIONS

We evaluated a modest sample size with concurrent pharmacological treatment.

CONCLUSIONS

Higher medial temporal volumes in euthymic BD patients may be a potential signature of brain resilience and cognitive adaptation to a putative illness neuroprogression. This knowledge should be integrated into further efforts to implement imaging into BD clinical management.

Integrity of cerebellar tracts associated with the risk of bipolar disorder

This study examined the structural brain differences across individuals of different BD stages and the risks of developing bipolar disorder (BD) associated with these brain differences. A total of 221 participants who were recruited from the Guangzhou Brain Hospital and the community were categorized into four groups: NC (healthy control) (N = 77), high risk (HR) (N = 42), ultra-high risk (UHR) (N = 38), and bipolar disorder (BD) (N = 64) based on a list of criteria. Their demographics, clinical characteristics, and diffusion magnetic resonance imaging (dMRI) data were collected. ANCOVA results showed that the HR group had significantly reduced mean diffusivity (MD) (p = 0.043) and radial diffusivity (RD) (p = 0.039) of the left portico-ponto-cerebellar tracts when compared with the BD group. Moreover, logistic regression results showed that the specific diffusivity measures of cerebellar tracts (e.g., cortico-ponto-cerebellar tract), particularly the RD and MD revealed differences between groups at different BD stages after controlling for the covariates. The findings suggested that specific diffusivity (RD and MD) of cerebellar tracts (e.g., cortico-ponto-cerebellar tract) revealed differences between groups at different BD stages which is helpful in detecting the trajectory changes in BD syndromes in the early stages of BD, particularly when the BD syndromes start from HR stage.

Differentiating white matter measures that protect against vs. predispose to bipolar disorder and other psychopathology in at-risk youth

Bipolar disorder (BD) is highly heritable. Identifying objective biomarkers reflecting pathophysiological processes predisposing to, versus protecting against BD, can help identify BD risk in offspring of BD parents. We recruited 21 BD participants with a first-degree relative with BD, 25 offspring of BD parents, 27 offspring of comparison parents with non-BD psychiatric disorders, and 32 healthy offspring of healthy parents. In at-risk groups, 23 had non-BD diagnoses and 29, no Axis-I diagnoses(healthy). Five at-risk offspring who developed BD post scan(Converters) were included. Diffusion imaging(dMRI) analysis with tract segmentation identified between-group differences in the microstructure of prefrontal tracts supporting emotional regulation relevant to BD: forceps minor, anterior thalamic radiation(ATR), cingulum bundle(CB), and uncinate fasciculus(UF). BD participants showed lower fractional anisotropy (FA) in the right CB (anterior portion) than other groups (q < 0.05); and in bilateral ATR (posterior portion) versus at-risk groups (q < 0.001). Healthy, but not non-BD, at-risk participants showed significantly higher FA in bilateral ATR clusters than healthy controls (qs < 0.05). At-risk groups showed higher FA in these clusters than BD participants (qs < 0.05). Non-BD versus healthy at-risk participants, and Converters versus offspring of BD parents, showed lower FA in the right ATR cluster (qs < 0.05). Low anterior right CB FA in BD participants versus other groups might result from having BD. High bilateral ATR FA in at-risk groups, and in healthy at-risk participants, versus healthy controls might protect against BD/other psychiatric disorders. Absence of elevated right ATR FA in non-BD versus healthy at-risk participants, and in Converters versus non-converter offspring of BD parents, might lower protection against BD in at-risk groups.