Combinatorial panel with endophenotypes from multilevel information of diffusion tensor imaging and lipid profile as predictors for depression.

OBJECTIVE: Clinical heterogeneity in major depressive disorder likely reflects the range of etiology and contributing factors in the disorder, such as genetic risk. Identification of more refined subgroups based on biomarkers such as white matter integrity and lipid-related metabolites could facilitate precision medicine in major depressive disorder. METHODS: A total of 148 participants (15 genetic high-risk participants, 57 patients with first-episode major depressive disorder and 76 healthy controls) underwent diffusion tensor imaging and plasma lipid profiling. Alterations in white matter integrity and lipid metabolites were identified in genetic high-risk participants and patients with first-episode major depressive disorder. Then, shared alterations between genetic high-risk and first-episode major depressive disorder were used to develop an imaging x metabolite diagnostic panel for genetically based major depressive disorder via factor analysis and logistic regression. A fivefold cross-validation test was performed to evaluate the diagnostic panel. RESULTS: Alterations of white matter integrity in corona radiata, superior longitudinal fasciculus and the body of corpus callosum and dysregulated unsaturated fatty acid metabolism were identified in both genetic high-risk participants and patients with first-episode major depressive disorder. An imaging x metabolite diagnostic panel, consisting of measures for white matter integrity and unsaturated fatty acid metabolism, was identified that achieved an area under the receiver operating characteristic curve of 0.86 and had a significantly higher diagnostic performance than that using either measure alone. And cross-validation confirmed the adequate reliability and accuracy of the diagnostic panel. CONCLUSION: Combining white matter integrity in corpus callosum, superior longitudinal fasciculus and corona radiata, and unsaturated fatty acid profile may improve the identification of genetically based endophenotypes in major depressive disorder to advance precision medicine strategies.

Transdiagnostic time-varying dysconnectivity across major psychiatric disorders.

Dynamic functional connectivity (DFC) analysis can capture time-varying properties of connectivity. However, studies on large samples using DFC to investigate transdiagnostic dysconnectivity across schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD) are rare. In this study, we used resting-state functional magnetic resonance imaging and a sliding-window method to study DFC in a total of 610 individuals (150 with SZ, 100 with BD, 150 with MDD, and 210 healthy controls [HC]) at a single site. Using k-means clustering, DFCs were clustered into three functional connectivity states: one was a more frequent state with moderate positive and negative connectivity (State 1), and the other two were less frequent states with stronger positive and negative connectivity (State 2 and State 3). Significant 4-group differences (SZ, BD, MDD, and HC groups; q < .05, false-discovery rate [FDR]-corrected) in DFC were nearly only in State 1. Post hoc analyses (q < .05, FDR-corrected) in State 1 showed that transdiagnostic dysconnectivity patterns among SZ, BD and MDD featured consistently decreased connectivity within most networks (the visual, somatomotor, salience and frontoparietal networks), which was most obvious in both range and extent for SZ. Our findings suggest that there is more common dysconnectivity across SZ, BD and MDD than we previously expected and that such dysconnectivity is state-dependent, which provides new insights into the pathophysiological mechanism of major psychiatric disorders.

A neuroimaging-based precision medicine framework for depression.

BACKGROUND: Symptom-based diagnostic criteria of depression leads to notorious heterogeneity and subjectivity. METHODS: The study was conducted in two stages at two sites: development of a neuroimaging-based subtyping and precise repetitive transcranial magnetic stimulation (rTMS) strategy for depression at Center 1 and its clinical application at Center 2. Center 1 identified depression subtypes and subtype-specific rTMS targets based on amplitude of low frequency fluctuation (ALFF) in a cohort of 238 major depressive disorder patients and 66 healthy controls (HC). Subtypes were identified using a Gaussian Mixture Model, and subtype-specific rTMS targets were selected based on dominant brain regions prominently differentiating depression subtypes from HC. Subsequently, one classifier was employed and 72 hospitalized, depressed youths at Center 2 received two-week precise rTMS. MRI and clinical assessments were obtained at baseline, midpoint, and treatment completion for evaluation. RESULTS: Two neuroimaging subtypes of depression, archetypal and atypical depression, were identified based on distinct frontal-posterior functional imbalance patterns as measured by ALFF. The dorsomedial prefrontal cortex was identified as the rTMS target for archetypal depression, and the occipital cortex for atypical depression. Following precise rTMS, ALFF alterations were normalized in both archetypal and atypical depressed youths, corresponding with symptom response of 90.00% in archetypal depression and 70.73% in atypical depression. CONCLUSIONS: A precision medicine framework for depression was developed based on objective neurobiomarkers and implemented with promising results, actualizing a subtyping-treatment-evaluation closed loop in depression. Future randomized controlled trials are warranted.

Three major psychiatric disorders share specific dynamic alterations of intrinsic brain activity.

BACKGROUND: Increasing evidence suggests that major psychiatric disorders, including major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ) share biological, neuropsychological and clinical features, despite the criteria for their respective diagnoses being different. Neuroimaging studies have shown disrupted 'static' neural connectivity in these disorders. However, the changes in brain dynamics across the three psychiatric disorders remain unknown. METHODS: We aim to examine the connections and divergencies of the dynamic amplitude of low-frequency fluctuation (dALFF) in MDD, BD and SZ. In total, 901 participants [MDD, 229; BD, 146; SZ, 142; and healthy controls (HCs), 384] received resting-state functional magnetic resonance imaging. The dALFF was calculated using sliding-window analysis and compared across three psychiatric disorders. RESULTS: We found significant increases of dALFF in the right fusiform, right hippocampus, right parahippocampal in participants with MDD, BD and SZ compared to HC. We also found specific increased dALFF changes in caudate and left thalamus for SZ and BD and decreased dALFF changes in calcarine and lingual for SZ and MDD. CONCLUSION: Our study found significant intrinsic brain activity changes in the limbic system and primary visual area in MDD, BD, and SZ, which indicates these areas disruptions are core neurobiological features shared among three psychiatric disorders. Meanwhile, our findings also indicate that specific alterations in MDD, BD, and SZ provide neuroimaging evidence for the differential diagnosis of the three mental disorders.

Brain Functional and Structural Alterations in Women With Bipolar Disorder and Suicidality.

Objective: Suicide is the leading cause of death from bipolar disorder (BD). At least 25-50% of the patients with BD will attempt suicide, with suicide rates much higher in women patients than in men. It is crucial to explore the potential neural mechanism underlying suicidality in women with BD, which will lead to understanding and detection of suicidality and prevent death and injury from suicide. Methods: Brain function and structure were measured by amplitude of low-frequency fluctuation (ALFF) and gray matter volume (GMV) in 155 women [30 women with BD and a history of suicidality, 50 women with BD without suicidality, and 75 healthy controls (HC)]. The differences in ALFF and GMV across the BD with suicidality, BD without suicidality, and HC groups were investigated. Results: BD with suicidality showed significantly increased ALFF in the left and right cuneus compared with BD without suicidality and HC groups. Moreover, the GMV in the left lateral prefrontal cortex and left cuneus in BD with suicidality were significantly lower than those in BD without suicidality and HC groups, while the GMV of the right ventral prefrontal cortex was significantly decreased in both BD with and without suicidality groups. Conclusions: This study, combining functional and structural neuroimaging techniques, may help to identify specific pathophysiological changes in women with BD and suicidality. Increased ALFF and less GMV in cuneus might represent the neuroimaging features of suicidality in women with BD. Investigating this potential neuromarker for suicidality in women with BD may lead to the ability to prevent suicidality.

Increased Amygdala-Paracentral Lobule/Precuneus Functional Connectivity Associated With Patients With Mood Disorder and Suicidal Behavior.

Mood disorder patients have greater suicide risk than members of the general population, but how suicidal behavior relates to brain functions has not been fully elucidated. This study investigated how functional connectivity (FC) values between the right/left amygdala and the whole brain relate to suicidal behavior in patients with mood disorder. The participants in this study were 100 mood disorder patients with suicidal behavior (SB group), 120 mood disorder patients with non-suicidal behavior (NSB group), and 138 age- and gender-matched healthy controls (HC group). Whole-brain FC values among the three groups were compared using an analysis of covariance (ANCOVA). Compared to the NSB and HC groups, increased FC values in the right amygdala-bilateral paracentral lobule/precuneus circuit were observed in the SB group (Bonferroni-corrected, p < 0.017). The FC values in the NSB group did not differ significantly from those in the HC group (Bonferroni-corrected, p > 0.017). Moreover, there were no significant differences in FC values between mood disorder patients with suicide attempt (SA group) and mood disorder patients with suicidal ideation (SI group), while the FC values between the right amygdala and bilateral paracentral lobule/precuneus in the SA group were higher than the mean in the SI group. These findings suggest that right amygdala-paracentral lobule/precuneus dysfunction has an important role in patients with mood disorder and suicidal behavior.