Du Lei

Background: The migraine spectrum exhibits substantial clinical heterogeneity, encompassing pain-dominant, vertigo-dominant, and pain-vertigo overlapping manifestations, as represented here by migraine without aura (MwoA), a clinically defined adult vertigo-dominant recurrent vestibular phenotype (hereafter, BPV group), and vestibular migraine (VM), respectively. However, the shared and symptom-preferential functional network alterations and their underlying molecular characteristics across these clinical phenotypes remain poorly understood, hindering individualized precision interventions. Methods: Resting-state fMRI data were acquired from 106 patients within the migraine spectrum (16 BPV, 61 MwoA, and 29 VM) and 39 healthy controls (HC). An edge-centric connectome framework was applied to identify overlapping network communities, and regional functional diversity was quantified using normalized entropy. Gene expression profiles and neurotransmitter receptor/transporter maps were integrated to identify molecular patterns spatially associated with aberrant functional diversity. Results: All patient groups showed significant functional diversity alterations in the ventral attention network and left precuneus that correlated with symptom severity. MwoA and VM exhibited divergent functional diversity in sensorimotor regions but shared associations with serotonergic maps; BPV and VM shared cerebellar increases associated with gamma-aminobutyric acid type A receptor distribution. VM further exhibited reduced functional diversity in the thalamus and insula, with molecular associations involving genetic homeostasis and glial cell processes. Conclusions: Across the migraine spectrum, these distinct clinical phenotypes share network abnormalities related to higher-order attentional regulation, while the pain-containing and vertigo-containing phenotypes exhibit preferential alterations involving pain processing and vestibular regulation, respectively, with the pain-vertigo overlapping phenotype further showing additional abnormalities involving multimodal sensory integration and molecular homeostatic processes. This study delineates shared and symptom-preferential neural signatures across pain-dominant, vertigo-dominant, and pain–vertigo overlapping clinical phenotypes, providing new insights for individualized clinical assessment and precision interventions.

Major depressive disorder with suicidal ideation (MDD-SI) is associated with a high risk of mortality. The specific longitudinal alterations in brain structural networks associated with SI remain unclear. We aimed to identify treatment-related topological reorganization in patients with MDD, with and without SI. This longitudinal study leveraged graph theory and structural MRI to analyze brain network changes in 101 MDD patients (66 MDD-SI, 35 MDD-nSI) and 41 healthy controls (HC). Network properties were evaluated before and after 2 weeks of clinical treatment, with global and nodal metrics calculated to track topological reorganization. Subsequently, group × time interaction analyses were conducted to characterize treatment-specific trajectories of brain network evolution. We identified SI-specific structural connectome alterations, characterized by increased network regularization and topological deficits in the posterior cingulate gyrus (PCG), insula, and hippocampus. Longitudinal analysis revealed that nodal centrality in the PCG and insula was significantly associated with SI severity. Crucially, a significant longitudinal interaction effect was observed in the PCG. Our findings underscore the important role of the PCG in the structural network recovery of MDD-SI. The topological changes of the PCG may provide insight into the neurobiological mechanisms underlying suicide-related pathophysiology and treatment response in MDD-SI.

Major depressive disorder (MDD) is highly prevalent among adolescents, but its neurobiological mechanisms remain unclear. Neuroimaging studies have shown cortical abnormalities in MDD, and emerging evidence suggests that trace elements may impact brain structure. This study aimed to investigate the association between urinary element concentrations and cortical alterations in adolescent MDD. Structural magnetic resonance imaging (sMRI) was conducted on 190 adolescents with MDD and 123 healthy controls (HCs), measuring cortical volume, cortical thickness, and urinary metal concentrations. Partial correlation analyses examined the associations between differential elements and cortical features, while mediation analyses tested whether cortical changes mediated the effects of elements on symptom severity. Furthermore, nine supervised machine learning models were trained using differential cortical and element features, and model performance was evaluated using cross-validation and stacking ensembles. The results revealed significant reductions in cortical volume in the left lateral orbitofrontal cortex (LLOF), left medial orbitofrontal cortex (LMOF), left rostral middle frontal gyrus (LRMFG), and left frontal pole (LFP), as well as reduced cortical thickness in the right pars triangularis (RPTRI), right pars orbitalis (RPORB), and right medial orbitofrontal cortex (RMOF) in adolescents with MDD compared with HCs. Urinary copper (Cu) levels were negatively correlated with LFP volume and positively associated with both depressive and anxiety symptom severity. In machine learning classification, the stacking ensemble demonstrated the best overall performance, indicating the discriminative value of combined cortical and urinary element features in distinguishing adolescents with MDD from HCs. This study suggests that trace elements, particularly Cu, are linked to structural brain alterations and symptom severity in adolescent MDD. The integration of neuroimaging and element data enhances predictive modeling and offers new insights into the pathophysiology of MDD.

Background Childhood trauma (CT) is a major risk factor for adolescent major depressive disorder (MDD), yet its neurobiological underpinnings and longitudinal treatment effects remain poorly characterized. Methods Leveraging graph theory and resting-state fMRI, we analyzed in 343 adolescents with MDD aged 10 − 18 years, including 211 with a history of childhood trauma (MDD-CT) and 106 without childhood trauma (MDD-NCT), as well as 149 healthy controls. Machine learning models were applied to baseline functional network data to distinguish between treatment responders and non-responders. Results We identified CT-associated functional connectome disruptions marked by increased network randomness and topological deficits in default mode network (DMN) hubs (left parahippocampal gyrus, posterior cingulate gyrus, temporal pole). Longitudinal neuroimaging revealed post-treatment normalization of these abnormalities, particularly in the left precuneus and amygdala, paralleling symptom improvement. Machine learning models using baseline connectomes predicted antidepressant response with 82% accuracy. Conclusion Our findings establish CT-driven connectome disturbances in adolescent MDD, map dynamic network reorganization to therapeutic recovery, and position functional connectivity as a clinically actionable biomarker. This work bridges neurobiological mechanisms of trauma-related depression with precision treatment strategies, offering a path toward biomarker-guided interventions.

Background: Major depressive disorder (MDD) and bipolar disorder (BD) commonly emerge during adolescence, a critical stage of brain development. Characterizing their shared and distinct neurobiological features is essential for early differential diagnosis. Methods: In this study, we investigated adolescents with major depressive disorder (MDD) ( n = 48), bipolar disorder (BD) ( n = 37), and healthy controls( n = 40). We acquired diffusion tensor imaging (DTI) data and applied a combined framework of graph-theoretical analysis and fixel-based analysis (FBA). We reconstructed structural networks using deterministic tractography and calculated global and nodal graph metrics. We then used FBA to measure fiber density (FD), fiber cross-section (FC), and combined FDC across major white matter tracts. We tested group differences and examined correlations with clinical severity after multiple-comparison correction. Results: Global graph metrics did not differ across groups, whereas nodal alterations were observed in regions assigned to the default mode, salience, and central executive networks, with disorder specific patterns. Fixel based analysis indicated widespread tract involvement in major depressive disorder but more circumscribed abnormalities in bipolar disorder, particularly in the corpus callosum and fornix. Several metrics were associated with symptom severity. Conclusions: These findings suggest disorder-related alterations in nodal topological properties and fiber-specific microstructure in adolescent MDD and BD, providing insight into the neurobiological basis of mood symptoms during this developmental stage. While these structural features may assist future efforts in differential characterization or individualized risk assessment, their potential clinical utility requires further validation. Clinical trial number: Not applicable.

Background: Bipolar I disorder (BD) is associated with reduced white matter microstructural integrity in the uncinate fasciculus (UF), a primary fiber tract connecting frontolimbic systems. Although familial history for BD, attention‐deficit/hyperactivity disorder (ADHD), and psychostimulants are important risk factors implicated in BD pathoetiology, their impact on UF microstructure remains poorly understood. Methods: This diffusion tensor imaging study investigated UF microstructural integrity prior to and following 12 weeks of psychostimulant treatment in ADHD youth with (‘high‐risk’, HR) and without (‘low‐risk’, LR) a first‐degree relative with BD. Healthy controls were included for comparative purposes. LR youth received 12‐week open‐label mixed amphetamine salts‐extended release (MAS‐XR), and HR youth were randomized to either MAS‐XR or placebo (PLA). Bilateral UF fractional anisotropy (FA) and axial diffusivity (AD) were assessed using automated fiber quantification. Results: A total of 137 participants were included in the analyses. At baseline, there were no significant group differences in bilateral UF microstructural metrics. Following 12‐week MAS‐XR treatment, significant group‐by‐time interactions were found for left UF FA and AD between HR‐MAS and LR‐MAS, as well as for left UF FA between HR‐MAS and HR‐PLA. Specifically, left UF FA and UF AD decreased significantly in HR‐MAS but remained unchanged in LR‐MAS and HR‐PLA groups. At week 12, left UF FA was lower in HR‐MAS relative to HC but not in LR‐MAS or HR‐PLA. Segment‐wise analyses further revealed that UF microstructural changes in the HR‐MAS group were localized to the anterior segments. Conclusions: These results suggest that HR‐ADHD youth are uniquely vulnerable to reductions in left UF microstructural integrity following psychostimulant treatment, suggesting potential relevance to BD pathoprogression.