Major depressive disorder (MDD) and psychostimulant use disorder (PUD) are common, disabling psychopathologies that pose a major public health burden. They share a common behavioral phenotype: deficits in inhibitory control (IC). However, whether this is underpinned by shared neurobiology remains unclear. In this meta-analytic study, we aimed to define and compare brain functional alterations during IC tasks in MDD and PUD.

We conducted a systematic literature search on IC task-based functional magnetic resonance imaging studies in MDD and PUD (cocaine or methamphetamine use disorder) in PubMed, Web of Science, and Scopus. We performed a quantitative meta-analysis using seed-based d mapping to define common and distinct neurofunctional abnormalities.

We identified 14 studies comparing IC-related brain activation in a total of 340 MDD patients with 303 healthy controls (HCs), and 11 studies comparing 258 PUD patients with 273 HCs. MDD showed disorder-differentiating hypoactivation during IC tasks in the median cingulate/paracingulate gyri relative to PUD and HC, whereas PUD showed disorder-differentiating hypoactivation relative to MDD and HC in the bilateral inferior parietal lobule. In conjunction analysis, hypoactivation in the right inferior/middle frontal gyrus was common to both MDD and PUD.

The transdiagnostic neurofunctional alterations in prefrontal cognitive control regions may underlie IC deficits shared by MDD and PUD, whereas disorder-differentiating activation abnormalities in midcingulate and parietal regions may account for their distinct features associated with disturbed goal-directed behavior.

Anhedonia, a transdiagnostic feature common to both Major Depressive Disorder (MDD) and Schizophrenia (SCZ), is characterized by abnormalities in hedonic experience. Previous studies have used machine learning (ML) algorithms without focusing on disorder-specific characteristics to independently classify SCZ and MDD. This study aimed to classify MDD and SCZ using ML models that integrate components of hedonic processing.

We recruited 99 patients with MDD, 100 patients with SCZ, and 113 healthy controls (HC) from four sites. The patient groups were allocated to distinct training and testing datasets. All participants completed a modified Monetary Incentive Delay (MID) task, which yielded features categorized into five hedonic components, two reward consequences, and three reward magnitudes. We employed a stacking ensemble model with SHapley Additive exPlanations (SHAP) values to identify key features distinguishing MDD, SCZ, and HC across binary and multi-class classifications.

The stacking model demonstrated high classification accuracy, with Area Under the Curve (AUC) values of 96.08% (MDD versus HC) and 91.77% (SCZ versus HC) in the main dataset. However, the MDD versus SCZ classification had an AUC of 57.75%. The motivation reward component, loss reward consequence, and high reward magnitude were the most influential features within respective categories for distinguishing both MDD and SCZ from HC (p < 0.001). A refined model using only the top eight features maintained robust performance, achieving AUCs of 96.06% (MDD versus HC) and 95.18% (SCZ versus HC).

The stacking model effectively classified SCZ and MDD from HC, contributing to understanding transdiagnostic mechanisms of anhedonia.

Major depressive disorder (MDD) is a disabling psychiatric condition in which physical activity provides clinical benefits. While exercise effectively alleviates depressive symptoms, its biological mechanisms remain unclear.

This systematic review investigated the neurobiological effects of physical exercise on biomarkers in adults with MDD through randomized controlled trials, including studies assessing exercise interventions and reporting data on their biological effects.

A total of 30 studies, including 2194 participants, were included, examining the effects of physical exercise on various biological systems in patients with MDD. Exercise interventions had mixed effects on inflammatory markers, including interleukins, C-reactive protein, and tumor necrosis factor-α, suggesting a potential but inconsistent anti-inflammatory role. Neurotrophic factors, such as brain-derived neurotrophic factor showed promise as biomarkers of treatment response, but their role in clinical improvements remained inconclusive. Findings for the stress-response system, including cortisol and monoaminergic systems, primarily involving serotonin and dopamine, were limited and variable. Exercise demonstrated potential benefits in reducing oxidative stress and enhancing β-endorphin levels, although these effects were not consistently observed.

This systematic review adopted a broader perspective than prior studies, exploring less-studied biological systems and identifying several limitations in the included studies, including small sample sizes, varying methodologies, and a predominant focus on biochemical markers. Future research should prioritize larger, standardized trials and particularly employ omics approaches to better understand the biological mechanisms underlying the effects of exercise in MDD. The findings highlight the complexity of exercise’s biological effects and emphasize the need for further research to clarify its mechanisms.

3,4-methylenedioxymethamphetamine (MDMA)-assisted therapy (MDMA-AT) has shown promising safety and efficacy in phase 3 studies of post-traumatic stress disorder, but has not been investigated for a primary diagnosis of major depressive disorder (MDD).

We aimed to explore the proof of principle and safety as a first study with MDMA-AT for MDD, and to provide preliminary efficacy data.

Twelve participants (7 women, 5 men) with moderate to severe MDD received MDMA in 2 open-label sessions 1 month apart, along with psychotherapy before, during and after the MDMA sessions, between January 2023 and May 2024. The primary outcome measure was mean change in Montgomery–Asberg Depression Rating Scale (MADRS), and the secondary outcome measure was mean change in functional impairment as measured with the Sheehan Disability Scale (SDS), both from baseline to 8 weeks following the second MDMA session. We used descriptive statistics and the two-tailed Wilcoxon signed-rank test to compare baseline and outcome scores. Repeated measures were analysed by a mixed-effects model.

Baseline MADRS was 29.6 (s.d. 4.9). Feasibility was demonstrated with sufficient recruitment and retention. MADRS scores were significantly reduced post treatment compared with baseline (mean difference –19.3, s.e. 2.4, CI –14.8 to –23.8, P < 0.001). SDS scores significantly decreased from baseline (mean difference –11.7, s.e. 2.2, CI –7.5 to –15.9, P = 0.001). There were no adverse events of special interest, and no unexpected or serious adverse events.

The study met the primary objectives of safety and feasibility, and provided indications of efficacy for MDMA-AT for MDD. Further studies with a randomised design are required to confirm these findings.

EudraCT no. 2021-000805-26.

Compelling evidence claims that gut microbial dysbiosis may be causally associated with major depressive disorder (MDD), with a particular focus on Alistipes. However, little is known about the potential microbiota–gut–brain axis mechanisms by which Alistipes exerts its pathogenic effects in MDD.

We collected data from 16S rDNA amplicon sequencing, untargeted metabolomics, and multimodal brain magnetic resonance imaging from 111 MDD patients and 102 healthy controls. We used multistage linked analyses, including group comparisons, correlation analyses, and mediation analyses, to explore the relationships between the gut microbiome (Alistipes), fecal metabolome, brain imaging, and behaviors in MDD.

Gut microbiome analysis demonstrated that MDD patients had a higher abundance of Alistipes relative to controls. Partial least squares regression revealed that the increased Alistipes was significantly associated with fecal metabolome in MDD, involving a range of metabolites mainly enriched for amino acid, vitamin B, and bile acid metabolism pathways. Correlation analyses showed that the Alistipes-related metabolites were associated with a wide array of brain imaging measures involving gray matter morphology, spontaneous brain function, and white matter integrity, among which the brain functional measures were, in turn, associated with affective symptoms (anxiety and anhedonia) and cognition (sustained attention) in MDD. Of more importance, further mediation analyses identified multiple significant mediation pathways where the brain functional measures in the visual cortex mediated the associations of metabolites with behavioral deficits.

Our findings provide a proof of concept that Alistipes and its related metabolites play a critical role in the pathophysiology of MDD through the microbiota–gut–brain axis.

Major depressive disorder (MDD) is a leading cause of disability worldwide. Investigating early-stage alterations in cerebral intrinsic activity among drug-naive patients may enhance our understanding of MDD’s neurobiological mechanisms and contribute to early diagnosis and intervention.

To examine alterations in the amplitude of low-frequency fluctuation (ALFF) in first-episode, drug-naive MDD individuals and explore associations between ALFF changes and clinical parameters, including depression severity and illness duration.

A total of 30 first-episode, drug-naive MDD individuals (mean illness duration 14 weeks) and 52 healthy controls were included in this study. Resting-state functional magnetic resonance imaging was used to obtain whole-brain ALFF measurements. Voxel-based ALFF maps were compared between MDD and healthy control groups using a two-sample t-test. Simple regression analysis was performed to assess associations between ALFF and clinical measures, including Hamilton Rating Scale for Depression (HAMD) scores and illness duration.

MDD individuals exhibited significantly increased ALFF in the dorsal anterior cingulate cortex and vermal subregion V3 of the cerebellum. Additionally, ALFF in the right dorsolateral prefrontal cortex was negatively correlated with HAMD scores (r = –0.591, P < 0.001). However, no significant association was found between ALFF and illness duration.

This study demonstrates early-stage ALFF alterations in drug-naive MDD patients, particularly in brain regions implicated in cognitive and emotional regulation. These findings suggest potential neuroimaging biomarkers for the early diagnosis and intervention of MDD.

Major depressive disorder (MDD) is a complex and heterogeneous disorder, and this heterogeneity poses a significant challenge for advancing precision medicine in patients with MDD. MRI-based subtyping analysis has been widely employed to address the heterogeneity of MDD patients. In this study, we investigated the subtypes of first-episode and drug-naive (FEDN) MDD patients based on the individualized structural covariance network (IDSCN).

In this study, we used T1-weighted anatomical images of 164 FEDN MDD patients and 164 healthy controls from the REST-meta-MDD consortium. The IDSCN of participants was obtained using the network template perturbation method. Subtypes of FEDN MDD were identified using k-means clustering analysis, and differences in neuroimaging findings and clinical symptoms between the identified subtypes were compared using two-sample t-tests.

This study identified two subtypes of FEDN MDD: subtype 1 (n = 117) and subtype 2 (n = 47) by characterizing 10 edges that were significantly altered in at least 5% of patients (i.e., 8 patients) in the IDSCN. Compared with subtype 2, subtype 1 had significantly higher anxiety symptom scores, stronger structural covariance edges in 9 edges within the thalamus, and a significantly reduced gray matter volume (GMV) in the frontal and parietal regions, and in the thalamus.

Our results suggest that patients with FEDN MDD can be classified into two different subtypes based on their IDSCN, providing an important reference for personalized treatment and precision medicine for patients with FEDN MDD.

Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), but initial outcomes can be modest.

To compare SSRI dose optimisation with four alternative second-line strategies in MDD patients unresponsive to an SSRI.

Of 257 participants, 51 were randomised to SSRI dose optimisation (SSRI-Opt), 46 to lithium augmentation (SSRI+Li), 48 to nortriptyline combination (SSRI+NTP), 55 to switch to venlafaxine (VEN) and 57 to problem-solving therapy (SSRI+PST). Primary outcomes were week-6 response/remission rates, assessed by blinded evaluators using the 17-item Hamilton Depression Rating Scale (HDRS-17). Changes in HDRS-17 scores, global improvement and safety outcomes were also explored. EudraCT No. 2007-002130-11.

Alternative second-line strategies led to higher response (28.2% v. 14.3%, odds ratio = 2.36 [95% CI 1.0–5.6], p = 0.05) and remission (16.9% v. 12.2%, odds ratio = 1.46, [95% CI 0.57–3.71], p = 0.27) rates, with greater HDRS-17 score reductions (−2.6 [95% CI −4.9 to −0.4], p = 0.021]) than SSRI-Opt. Significant/marginally significant effects were only observed in both response rates and HDRS-17 decreases for VEN (odds ratio = 2.53 [95% CI 0.94–6.80], p = 0.067; HDRS-17 difference: −2.7 [95% CI −5.5 to 0.0], p = 0.054) and for SSRI+PST (odds ratio = 2.46 [95% CI 0.92 to 6.62], p = 0.074; HDRS-17 difference: −3.1 [95% CI −5.8 to −0.3], p = 0.032). The SSRI+PST group reported the fewest adverse effects, while SSRI+NTP experienced the most (28.1% v. 75%; p < 0.01), largely mild.

Patients with MDD and insufficient response to SSRIs would benefit from any other second-line strategy aside from dose optimisation. With limited statistical power, switching to venlafaxine and adding psychotherapy yielded the most consistent results in the DEPRE'5 study.

Difficult-to-treat depression (DTD) is a common clinical challenge for major depressive disorder and bipolar disorders. Electro convulsive therapy (ECT) has proven to be one of the most effective treatments for this condition. Although several studies have investigated individually the clinical factors associated with the DTD response, the role of their interplay in the clinical response to ECT remains unknown. In the present study, we aimed to characterize the network of symptoms in DTD, evaluate the effects of ECT on the interrelationship of depressive symptoms, and identify the network characteristics that could predict the clinical response.

A network analysis of clinical and demographic data from 154 patients with DTD was performed to compare longitudinally the patterns of relationships among depressive symptoms after ECT treatment. Furthermore, we estimated the network structure at baseline associated with a greater clinical improvement (≥80% reduction at Montgomery–Åsberg Depression Rating Scale total score).

ECT modulated the network of depressive symptoms, with increased strength of the global network (p = 0.03, Cohen’s d = −0.98, 95% confidence interval = [−1.07, −0.88]). The strength of the edges between somatic symptoms (appetite and sleep) and cognitive-emotional symptoms (tension, lassitude, and pessimistic thoughts) was also increased. A stronger negative relationship between insomnia and pessimistic thoughts was associated with a greater improvement after ECT. Concentration difficulties and apparent sadness showed the greatest centrality.

In conclusion, ECT treatment may affect not only the severity of the symptoms but also their relationship; this may contribute to the response in DTD.

Heterogeneous symptoms in major depression contribute to unsuccessful antidepressant treatment, termed treatment-resistant depression (TRD). Psychometric network modeling conceptualizes depression as interplay of symptoms with potential benefits for treatment; however, a knowledge gap exists regarding networks in TRD.

Symptoms from 1,385 depressed patients, assessed by the Montgomery-Åsberg-depression rating scale (MADRS) as part of the “TRD-III” cohort of the multinational research consortium “Group for the Studies of Resistant Depression,” were used for Gaussian graphical network modeling. Networks were estimated for two timepoints, pretreatment and posttreatment, after the establishment of outcomes response, non-response, and TRD. Applying the network-comparison test, edge weights, and symptom centrality was assessed by bootstrapping. Applying the network-comparison test, outcome groups were compared cross-sectionally and longitudinally regarding the networks’ global strength, invariance, and centrality.

Pretreatment networks did not differ in global strength, but outcome groups showed distinct symptom connections. For both response and TRD, global strength was reduced posttreatment, leading to significant differences between each pair of networks posttreatment. Sadness, lassitude, inability-to-feel, and pessimistic thoughts ranked most centrally in unfavorable outcomes, while reduced-appetite and suicidal thoughts were more densely connected in response. Connections between central symptoms increased in strength following unsuccessful treatment, particularly regarding links involving pessimistic thoughts in TRD.

Treatment reduced global network strength across outcome groups. However, distinct symptom networks were found in patients showing response to treatment, non-response, and TRD. More easily targetable symptoms such as reduced-appetite were central to networks in patients with response, while pessimistic thoughts may be a key symptom upholding disease burden in TRD.

Many studies have highlighted the detrimental effect of childhood maltreatment (CM) on depression severity and the course of illness in major depressive disorder (MDD). Yet our understanding of how CM influences the dynamic symptom change throughout a patient’s trajectory remains limited. Hence, we investigated the impact of CM on depression severity in MDD with a focus on various treatment phases during inpatient treatment and after discharge (1 or 2 years later) and validated findings in a real-world setting.

We used longitudinal data from a cohort study sample (n = 567) and a clinical routine sample (n = 438). CM was measured with the Childhood Trauma Questionnaire (CTQ), and depression severity was assessed using Beck’s Depression Inventory (BDI). The long-term clinical trajectory was assessed using the Life Chart Interview.

Our analyses revealed that CM significantly increased depression severity before, during, and after inpatient therapy in both samples. Although CM was associated with higher depression severity at the beginning of inpatient treatment and lower remission rates upon discharge, no discernible impact of CM was evident on the relative change in symptoms over time during inpatient treatment. CM consistently predicted higher relapse rates and lower rates of full remission after discharge during long-term follow-up in both samples.

Our findings affirm the link between CM and the development of more severe and persistent clinical trajectories within real-world clinical settings. Furthermore, conventional psychiatric treatments may not lead to comparable outcomes for individuals with a history of CM, underscoring the necessity for tailored therapeutic interventions.

The relationship between emotional symptoms and cognitive impairments in major depressive disorder (MDD) is key to understanding cognitive dysfunction and optimizing recovery strategies. This study investigates the relationship between subjective and objective cognitive functions and emotional symptoms in MDD and evaluates their contributions to social functioning recovery.

The Prospective Cohort Study of Depression in China (PROUD) involved 1,376 MDD patients, who underwent 8 weeks of antidepressant monotherapy with assessments at baseline, week 8, and week 52. Measures included the Hamilton Depression Rating Scale (HAMD-17), Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR16), Chinese Brief Cognitive Test (C-BCT), Perceived Deficits Questionnaire for Depression-5 (PDQ-D5), and Sheehan Disability Scale (SDS). Cross-lagged panel modeling (CLPM) was used to analyze temporal relationships.

Depressive symptoms and cognitive measures demonstrated significant improvement over 8 weeks (p < 0.001). Baseline subjective cognitive dysfunction predicted depressive symptoms at week 8 (HAMD-17: β = 0.190, 95% CI: 0.108–0.271; QIDS-SR16: β = 0.217, 95% CI: 0.126–0.308). Meanwhile, baseline depressive symptoms (QIDS-SR16) also predicted subsequent subjective cognitive dysfunction (β = 0.090, 95% CI: 0.003-0.177). Recovery of social functioning was driven by improvements in depressive symptoms (β = 0.384, p < 0.0001) and subjective cognition (β = 0.551, p < 0.0001), with subjective cognition contributing more substantially (R2 = 0.196 vs. 0.075).

Subjective cognitive dysfunction is more strongly associated with depressive symptoms and plays a significant role in social functioning recovery, highlighting the need for targeted interventions addressing subjective cognitive deficits in MDD.

Despite advances in antiretroviral treatment (ART), human immunodeficiency virus (HIV) can detrimentally affect everyday functioning. Neurocognitive impairment (NCI) and current depression are common in people with HIV (PWH) and can contribute to poor functional outcomes, but potential synergies between the two conditions are less understood. Thus, the present study aimed to compare the independent and combined effects of NCI and depression on everyday functioning in PWH. We predicted worse functional outcomes with comorbid NCI and depression than either condition alone.

PWH enrolled at the UCSD HIV Neurobehavioral Research Program were assessed for neuropsychological performance, depression severity (≤minimal, mild, moderate, or severe; Beck Depression Inventory-II), and self-reported everyday functioning.

Participants were 1,973 PWH (79% male; 66% racial/ethnic minority; Age: M = 48.6; Education: M = 13.0, 66% AIDS; 82% on ART; 42% with NCI; 35% BDI>13). ANCOVA models found effects of NCI and depression symptom severity on all functional outcomes (ps < .0001). With NCI and depression severity included in the same model, both remained significant (ps < .0001), although the effects of each were attenuated, and yielded better model fit parameters (i.e., lower AIC values) than models with only NCI or only depression.

Consistent with prior literature, NCI and depression had independent effects on everyday functioning in PWH. There was also evidence for combined effects of NCI and depression, such that their comorbidity had a greater impact on functioning than either alone. Our results have implications for informing future interventions to target common, comorbid NCI and depressed mood in PWH and thus reduce HIV-related health disparities.

The antidepressant mechanism of electroconvulsive therapy (ECT) remains not clearly understood. This study aimed to detect the changes in gray matter volume (GMV) in patients with major depressive disorder (MDD) caused by ECT and exploratorily analyzed the potential functional mechanisms.

A total of 24 patients with MDD who underwent eight ECT sessions were included in the study. Clinical symptom assessments and MRI scans were conducted and compared. Using whole-brain micro-array measurements provided by the Allen Human Brain Atlas (AHBA), regional gene expression profiles were calculated. The differential gene PLS1 was obtained through Partial Least Squares (PLS) regression analysis, and PLS1 was divided into positive contribution (PLS1+) and negative contribution (PLS1−) genes. Through gene function enrichment analysis, the functional pathways and cell types of PLS1 enrichment were identified.

Gray matter volume (GMV) in the somatosensory and motor cortices, occipital cortex, prefrontal cortex, and insula showed an increasing trend after ECT, while GMV in the temporal cortex, posterior cingulate cortex, and orbitofrontal cortex decreased. PLS1 genes were enriched in synapse- and cell-related biological processes and cellular components (such as ‘pre- and post-synapse’, ‘synapse organization’ etc.). A large number of genes in the PLS1+ list were involved in neurons (inhibitory and excitatory), whereas PLS1− genes were significantly involved in Astrocytes (Astro) and Microglia (Micro).

This study established a link between treatment-induced GMV changes and specific functional pathways and cell types, which suggests that ECT may exert its effects through synapse-associated functional and affect neurons and glial cells.