Differences in resting-state functional magnetic resonance regional homogeneity and fractional amplitude of low-frequency fluctuations between early adult depressed patients with non-suicidal self-injury and suicide attempts.

Using machine learning to reveal two distinct neuroanatomical subtypes of first-episode, drug-naïve major depressive disorder: Evidence from the REST-meta-MDD project.

Biological subtypes of cognitive impairment in first-episode medication-naïve MDD linking individualized functional connectome, cognition, and symptom.

Depression imposes severe psychological, social, and economic burdens, with its manifestations varying significantly across age groups. Adolescent major depressive disorder (MDD) presents unique challenges and remains poorly understood at the molecular level. This study aims to apply a multiomic approach to characterize peripheral transcriptional changes in adolescent MDD. Peripheral blood samples were collected from 180 MDD patients and 99 healthy controls (HC) for bulk RNA sequencing, with a subset of 4 MDD patients and 4 HC undergoing single-cell sequencing. We further explored the effect of drug therapy on transcriptional variations based on participants' histories of antidepressant use. The EPIC analysis and flow cytometry were employed to predict and confirm the peripheral immune cell proportions within subgroups. Finally, the Connectivity Map platform identified potential drugs for adolescent MDD. Bulk analyses revealed widespread transcriptional downregulation of immune-related genes, including key inflammatory regulators (e.g., NFKBIA, JUN, and JUND). Single-cell profiling localized the strongest alterations to monocytes, with additional changes in T cells and neutrophils. Notably, comparisons between adolescent and adult MDD showed distinct expression patterns of immune-related genes (e.g., NFKBIA, TNF, IL-12A, CCL2, and CX3CR1) and pathways (e.g., the C-type lectin receptor signaling pathway, IL-17 signaling pathway, natural killer cell-mediated cytotoxicity, and toll-like receptor signaling pathway). The similar transcriptional profiles between drug-naïve and drug-treated adolescents indicated that monoamine-based antidepressants might not be associated with the normalization of peripheral immune dysregulation in adolescent MDD. Finally, the Connectivity Map analysis highlighted several compound classes, including tubulin-associated inhibitors, that may counteract the observed transcriptional pattern. These findings define a suppressed peripheral immune profile in adolescent MDD, and show limited modification of peripheral immune dysregulation by current treatments. Our study highlights the need for therapeutic strategies that more directly target the immune-related biological changes observed in depressed adolescents.

Sleep-architecture signatures for differential diagnosis of schizophrenia, bipolar, and major depressive disorders: A polysomnography-based multinomial modeling study.

Rich-club connections dynamics are associated with long-term outcomes in major depressive disorder.

Temporal interference stimulation (TIS) for major depressive disorder: right lingual gyrus as a predictor.

Anhedonia is a core feature of major depressive disorder (MDD), yet links between peripheral molecular signatures and cortical network architecture remain poorly defined. We enrolled 210 participants, including 56 unmedicated MDD patients with high-anhedonia (HA), 61 with low-anhedonia (LA), and 93 healthy controls (HC). Morphometric similarity networks (MSNs) from structural MRI were compared between HA and LA. MSNs index individual-level network organization by quantifying inter-regional morphometric similarity. Regional MSN patterns were linked to Allen Human Brain Atlas using Spearman correlations with spin tests and a multi-K stability screen. Whole-blood RNA-seq (n = 199) was integrated with MSN features via sparse partial least squares-canonical correlation (sPLS-C), with key blood analyses repeated after leukocyte-composition adjustment. Gene Ontology over-representation and MAGMA gene-level analyses provided pathway context. HA showed greater MSN integration than LA, particularly within default-mode and somatomotor networks. MSN maps were negatively correlated with dopamine-transporter and kappa-opioid-receptor densities. Imaging-derived gene associations were enriched for regulation of Toll-like-receptor-3 signaling. In blood, sPLS-C revealed coupling between MSN features and a transcriptomic signature enriched for T-cell activation/differentiation and lymphocyte-apoptosis pathways. After composition adjustment, the pre-specified blood signature did not differ between HA and LA, indicating that between-group differences were largely composition-driven. As supportive genetic context, over-representation on MAGMA FDR-significant genes suggested protocadherin-mediated homophilic adhesion. Peripheral immune-redox pathway enrichment aligns with anhedonia-related cortical network alterations, whereas between-group blood differences are chiefly composition-driven. Adjusting for blood-cell composition is essential, this multimodal framework nominates immune-modulatory/redox targets and synaptic-adhesion biology for precision stratification and intervention.

Major depressive disorder (MDD) is frequently accompanied by self-harm behaviors, including non-suicidal self-injury (NSSI) and suicide attempts (SA), which are important risk factors for suicide and poor clinical outcomes. Although neuroimaging studies have identified structural brain abnormalities related to suicidal behaviors in MDD, the neurobiological distinctions between NSSI and SA remain poorly understood. In particular, few studies have simultaneously compared MDD patients with NSSI, MDD patients with SA, and MDD patients without self-harm behaviors. Therefore, this study aimed to investigate gray matter volume (GMV) alterations and their associations with clinical symptoms in early adulthood (aged 18-30 years) MDD patients using voxel-based morphometry (VBM). A total of 54 MDD patients with NSSI (MDD/NSSI), 68 MDD patients without NSSI (sMDD), 50 MDD patients with SA (MDD/SA), and 66 healthy controls (HCs) were included. VBM was used to examine GMV differences using high-resolution T1-weighted MRI scans. Age, sex, education, and intracranial volume were included as covariates. One-way ANOVA with Gaussian random field (GRF) correction was performed, followed by post-hoc t-tests. Correlations between GMV and clinical measures of depression (HAMD), anxiety (HAMA), and suicide risk (NGASR) were assessed. Significant GMV differences were observed in the superior/middle frontal gyrus, superior frontal gyrus, bilateral caudate, superior/middle temporal gyrus, and middle cingulate gyrus (voxel-level p < 0.001, GRF corrected p < 0.05). Post-hoc analyses showed reduced GMV in the MDD/SA group compared with the MDD/NSSI group in several regions. However, supplementary GLM analyses indicated that NSSI-related characteristics showed more consistent independent associations with regional GMV, whereas SA history was not independently associated with GMV in any examined region. Correlations between GMV and clinical measures did not survive FDR correction. MDD patients with NSSI and SA may exhibit distinct patterns of gray matter alterations; however, these differences likely reflect clinical heterogeneity across self-harm subgroups rather than SA-specific structural abnormalities. Supplementary analyses further suggest that NSSI-related characteristics show stronger independent associations with GMV than SA history. These findings highlight the importance of distinguishing self-harm subtypes in the neurobiological characterization of MDD. All results should be interpreted cautiously given the cross-sectional design and the lack of robust associations after multiple-comparison correction. Not applicable.

The structural and functional connectivity of the brain network is a combination of complex connections and interconnections among neurons of different brain regions. Analysis of these connectivity patterns provides a representation of the mental health of an individual, including major depressive disorder (MDD). MDD analysis with Electroencephalogram (EEG) has increasingly focused on characterizing alterations in brain connectivity patterns. The dynamic complexities in the functional connectivity of the brain and its intricate interconnections have posed significant challenges in effectively utilizing EEG data and machine learning techniques to extract meaningful information for accurate MDD diagnosis. This paper proposes the use of a graph convolutional neural network (GCNN) for MDD classification and analysis while discovering the dynamic functional connectivity involved through scalp EEG recordings. The connectivity graph was obtained using spectral coherence of resting-state and task-based EEG recordings. This paper makes three key contributions: it proposes a novel GCNN model with a unique graph representation for EEG data that integrates domain knowledge of brain regions with data-driven functional relationships without relying on explicit spatial geometry; it conducts extensive evaluation using two distinct scalp- EEG datasets and identifies effective frequency bands and brain region markers associated with MDD. The proposed method demonstrates strong performance in classifying MDD patients and healthy individuals, achieving an AUROC of 93% for dataset 1 and 71% for dataset 2. The study found consistent identification of neurophysiologically relevant biomarkers across both datasets, including dominant activity in the left prefrontal, left frontoparietal and right prefrontal regions, along with contributions from delta, theta, and alpha frequency bands. In contrast, the lower beta band has only a minimal influence compared to the others.

Anhedonia, a core symptom of adolescent depression, is often difficult to assess, the 14-item Anhedonia Scale for Adolescents (ASA) was developed to address this need. This study aimed to evaluate the reliability and validity of the ASA among healthy and depressed adolescents in China. In Study 1, a large community sample of 1,448 adolescents (female = 855; mean age = 14.61 years) from middle schools across eastern, western, and central China were recruited between October 2022 to April 2023 to evaluate the psychometric properties of the ASA in general population. To validate the factor structure, confirmatory factor analysis was employed. Internal consistency (Cronbach's α) and test-retest reliability at six-month intervals (Intraclass Correlation Coefficient, ICC) were also assessed. In Study 2, a clinical sample of 168 adolescents with major depressive disorder (MDD), 121 with subthreshold depression (SD), and 149 healthy controls (HC) were recruited between April 2023 to April 2024, to examine the construct validity, discriminative ability, and clinical applicability and divergent validity of the ASA. One-way analyses of variance (ANOVAs) were conducted to analysis the group difference. In Study 1, validity assessments confirmed that a three-factor model - (1) Enjoyment, Excitement, Emotional Flattening; (2) Enthusiasm, Connection, Purpose; (3) Effort, Motivation, Drive-provided a good fit. Reliability assessments demonstrated strong internal consistency (Cronbach's α = 0.733 to 0.883) and test-retest reliability (ICC = 0.749). In study 2, the ASA exhibited acceptable reliability and validity within the MDD group. Crucially, ANOVA results revealed significant group differences in ASA scores, with MDD patients scoring the highest, followed by SD groups, and then HCs (MDD > SD >HC, ps < 0.001), demonstrating strong discriminative ability. These results indicate that the ASA demonstrates acceptable construct validity, reliability, discriminative ability and shows promise as a useful tool for assessing anhedonia in Chinese adolescents for both research and clinical settings with Chinese adolescents.

Intrinsic excitation-inhibition imbalance in major depressive disorder.

Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) due to overlapping clinical syndromes. Although numerous studies have investigated biomarkers to differentiate these two disorders, no clinically applicable differential diagnostic panel has been established. Notably, sex-specific differences play a critical role in this context. Females are more prone to experience depressive episodes and exhibit more pronounced immune-inflammatory dysregulation, which further increases the risk of misdiagnosis. This study aimed to explore whether C-reactive protein (CRP)-based stratified modeling of routinely available biochemical parameters could improve discriminative performance in reproductive-age women. A total of 502 female patients of reproductive age were enrolled, including 263 with BD and 239 with MDD, grouped according to CRP levels. Fourteen clinical biochemical indexes were compared: white blood cells (WBC), platelets, uric acid (UA), direct bilirubin (DBIL), indirect bilirubin (IBIL), glutamic oxaloacetic transaminase (GOT), lactate dehydrogenase (LDH), prealbumin, triglycerides, low-density lipoproteins (LDL), testosterone, free triiodothyronine (FT3), free tetraiodothyronine (FT4) and thyroid stimulating hormone (TSH). Binary logistic regression analysis was employed to develop predictive models for distinguishing BD from MDD. Model performance was assessed using the area under the receiver operating characteristic (ROC) curve (AUC), and the holistic model was internally validated with 10-fold cross-validation. In the Normal-CRP group, BD patients had higher levels of WBC, IBIL, GOT, LDH, and FT4, and lower DBIL, prealbumin, and triglycerides compared to MDD patients. In the high CRP group, BD patients had higher IBIL and LDH, and lower DBIL (p < 0.05). Five predictive models were constructed. The Holistic model yielded an apparent AUC of 0.805 (cross-validated mean AUC: 0.808), the High-Risk model (3 ≤ CRP <5 mg/L) achieved an AUC of 0.887, and the High-CRP model (CRP ≥ 5 mg/L) had an AUC of 0.929. Detailed results for the Low-Risk and Normal-CRP models are available in the Supplementary Material. The CRP-stratified models demonstrated promising discriminative performance, with the highest AUC observed in the High-CRP model. These results suggest that CRP-based stratification may serve as an exploratory approach to aid differential diagnosis in women of reproductive age. Given their limited sample sizes, the High-Risk and High-CRP models were considered exploratory approaches and were not internally validated. The CRP-based stratified models are still in the exploratory phase and require external validation to confirm their clinical applicability.

Impact of sex differences on the association between clinical predictors and electroconvulsive therapy outcomes: results from the Dutch ECT Consortium (DEC).

Chronic somatic pain (CSP) and major depressive disorder (MDD) frequently co-occur and are associated with poor prognosis. However, the neural circuit mechanisms underlying the modulation of MDD pathology by CSP remain unclear. This case-control study included 129 participants who underwent fNIRS during a verbal fluency task (VFT) and at rest. Participants were divided into three groups (n = 43 each): MDD patients with comorbid CSP (MDD + CSP), MDD patients without CSP (MDD-CSP), and healthy controls (HC). This study aimed to identify CSP-specific neural signatures and examine their mediating role between pain and depression. Compared with HC, all MDD patients exhibited reduced activation in the bilateral frontopolar cortex during the task. A key finding was that, relative to both HC and the MDD-only group, the comorbid group showed selectively lower activation in the right-hemispheric Broca's homologue (RH-Broca) (p = 0.003). Pain intensity was negatively correlated with RH-Broca activation (p < 0.001). Mediation analysis revealed a bidirectional mediating effect of RH-Broca activation on the pain-depression relationship: it mediated both the pathway from pain to depression (indirect effect β = 1.17, 95% CI: 0.66-1.71) and the pathway from depression to pain (indirect effect β = 0.13, 95% CI: 0.08-0.18). At rest, the comorbid group displayed hyperactivation in the right frontopolar cortex, whereas the MDD-only group showed alterations in small-world network properties. Selective hypoactivation in the right-hemispheric language network, particularly in the RH-Broca, is closely associated with the comorbidity of chronic somatic pain and major depressive disorder and may contribute to their mutual exacerbation. These findings support the view that the RH-Broca serves as a putative neural node connecting pain and depressive symptoms, potentially forming a bidirectional loop in comorbid patients. This neural circuit may represent a promising target for neuromodulation therapy in patients with MDD comorbid with CSP.

Altered perivascular water diffusivity links childhood trauma and major depressive disorder: A multimodal integration of cognition, neuroimaging, and transcriptomics.

Shifts in the brain sex continuum in major depressive disorder: Evidence for a persistent neurobiological marker.

Bipolar disorder (BD) and major depressive disorder (MDD) are severe and chronic mood disorders which impairs the psychosocial functioning of patients. Besides manic or hypomanic episodes, many patients with BD also experience depressive episodes similar to those seen in MDD, suggesting the similarities and differences between the two diseases. However, the shared and distinct abnormalities of gene expression and cellular function in the brain underlying the disorders remain to be elucidated. Here we analyzed publicly available single-nucleus and bulk RNA expression datasets of postmortem brain samples from BD patients, MDD patients, and healthy donors. For single-nucleus gene expression profiling of postmortem orbitofrontal cortex (OFC), differential abundance testing, differential gene expression analysis and gene set enrichment analysis performed on each cell type showed abnormal gene expression profiles in both neuronal and non-neuronal cells. Cell-cell communication inference revealed the dysfunction of parvalbumin interneurons, as well as enhanced interactions among certain subtypes of neurons, in both diseases. Gene co-expression network analysis identified the overall alterations in both diseases, as well as the differences in co-expression modules between BD and MDD. Compared to MDD, most neurons in BD exhibited particularly downregulated expression of modules related to translation and mitochondrial ATP production. Transcription factor network analysis revealed the regulatory relationships among the modules. Further analyses of two additional datasets supported the main findings of the postmortem OFC analyses. Overall, our findings clarified the molecular mechanisms underlying BD and MDD, which highlight distinct molecular pathways that may inform therapeutic strategies for mood disorders.

Source-level EEG dysconnectivity in drug-naïve patients with major depressive disorder: Bridging neural oscillations with potential neuroelectrophysiological markers.

Sex-specific cognitive profiles and correlations with dimensional symptoms in first-episode major depressive disorder.