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Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking. Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11–93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity. Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes. These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder. [ABSTRACT FROM AUTHOR]

Background: Bipolar I disorder (BD‐I) is associated with a high risk of suicide attempt; however, the neural circuit dysfunction that confers suicidal vulnerability in individuals with this disorder remains largely unknown. Resting‐state functional magnetic resonance imaging (rs‐fMRI) allows non‐invasive mapping of brain functional connectivity. The current study used an unbiased voxel‐based graph theory analysis of rs‐fMRI to investigate the intrinsic brain networks of BD‐I patients with and without suicide attempt. Methods: A total of 30 BD‐I patients with suicide attempt (attempter group), 82 patients without suicide attempt (non‐attempter group), and 67 healthy controls underwent rs‐fMRI scan, and then global brain connectivity (GBC) was computed as the sum of connections of each voxel with all other gray matter voxels in the brain. Results: Compared with the non‐attempter group, we found regional differences in GBC values in emotion‐encoding circuits, including the left superior temporal gyrus, bilateral insula/rolandic operculum, and right precuneus (PCu)/cuneus in the bipolar disorder (BD) attempter group, and these disrupted hub‐like regions displayed fair to good power in distinguishing attempters from non‐attempters among BD‐I patients. GBC values of the right PCu/cuneus were positively correlated with illness duration and education in the attempter group. Conclusions: Our results indicate that abnormal connectivity patterns in emotion‐encoding circuits are associated with the increasing risk of vulnerability to suicide attempt in BD patients, and global dysconnectivity across these emotion‐encoding circuits might serve as potential biomarkers for classification of suicide attempt in BD patients. [ABSTRACT FROM AUTHOR]

Functional connectome studies have revealed widespread connectivity alterations in major depressive disorder (MDD). However, the low frequency bandpass filtering (0.01–0.08 Hz or 0.01–0.1 Hz) in most studies have impeded our understanding on whether and how these alterations are affected by frequency of interest. Here, we performed frequency-resolved (0.01–0.06 Hz, 0.06–0.16 Hz and 0.16–0.24 Hz) connectome analyses using a large-sample resting-state functional MRI dataset of 1002 MDD patients and 924 healthy controls from seven independent centers. We reported significant frequency-dependent connectome alterations in MDD in left inferior parietal, inferior temporal, precentral, and fusiform cortices and bilateral precuneus. These frequency-dependent connectome alterations are mainly derived by abnormalities of medium- and long-distance connections and are brain network-dependent. Moreover, the connectome alteration of left precuneus in high frequency band (0.16–0.24 Hz) is significantly associated with illness duration. Multisite harmonization model only removed linear site effects. Neurobiological underpinning of alterations in higher frequency (0.16–0.24 Hz) should be further examined by combining fMRI data with respiration, heartbeat and blood flow recordings in future studies. These results highlight the frequency-dependency of connectome alterations in MDD and the benefit of examining connectome alteration in MDD under a wider frequency band. • FCS in the low frequency band (0.01-0.06 Hz) is highly reproducible, and is more sensitive to MDD alterations. • Frequency-resolved FCS alterations of MDD consisted by altered medium-/long-distance, inter-network functional connections. • FCS alterations of MDD in higher frequency are associated with illness duration. [ABSTRACT FROM AUTHOR]

Abstract Resting-state functional MRI (R-fMRI) studies have demonstrated widespread alterations in brain function in patients with major depressive disorder (MDD). However, a clear and consistent conclusion regarding a repeatable pattern of MDD-relevant alterations is still limited due to the scarcity of large-sample, multisite datasets. Here, we address this issue by including a large R-fMRI dataset with 1434 participants (709 patients with MDD and 725 healthy controls) from five centers in China. Individual functional activity maps that represent very local to long-range connections are computed using the amplitude of low-frequency fluctuations, regional homogeneity and distance-related functional connectivity strength. The reproducibility analyses involve different statistical strategies, global signal regression, across-center consistency, clinical variables, and sample size. We observed significant hypoactivity in the orbitofrontal, sensorimotor, and visual cortices and hyperactivity in the frontoparietal cortices in MDD patients compared to the controls. These alterations are not affected by different statistical analysis strategies, global signal regression and medication status and are generally reproducible across centers. However, these between-group differences are partially influenced by the episode status and the age of disease onset in patients, and the brain-clinical variable relationship exhibits poor cross-center reproducibility. Bootstrap analyses reveal that at least 400 subjects in each group are required to replicate significant alterations (an extent threshold of P <.05 and a height threshold of P <.001) at 50% reproducibility. Together, these results highlight reproducible patterns of functional alterations in MDD and relevant influencing factors, which provides crucial guidance for future neuroimaging studies of this disorder. Highlights • Significant hypoactivity in primary regions and orbitofrontal regions in MDD. • Significant hyperactivity in frontoparietal cortices in MDD. • Functional alterations are not affected by statistical method and medication statue. • Correlations between brain and clinics have a poor across-center reproducibility. • At least 400 subjects in each group are needed to replicate significant alterations. [ABSTRACT FROM AUTHOR]