Ketamine: Mechanisms and Relevance to Treatment of Depression.

Major depressive disorder (MDD) is a leading cause of suicide in the world. Monoamine-based antidepressant drugs are a primary line of treatment for this mental disorder, although the delayed response and incomplete efficacy in some patients highlight the need for improved therapeutic approaches. Over the past two decades, ketamine has shown rapid onset with sustained (up to several days) antidepressant effects in patients whose MDD has not responded to conventional antidepressant drugs. Recent preclinical studies have started to elucidate the underlying mechanisms of ketamine's antidepressant properties. Herein, we describe and compare recent clinical and preclinical findings to provide a broad perspective of the relevant mechanisms for the antidepressant action of ketamine.

Shared genetic effect of kidney function on bipolar and major depressive disorders: a large-scale genome-wide cross-trait analysis.

BACKGROUND: Epidemiological studies have revealed a significant association between impaired kidney function and certain mental disorders, particularly bipolar disorder (BIP) and major depressive disorder (MDD). However, the evidence regarding shared genetics and causality is limited due to residual confounding and reverse causation. METHODS: In this study, we conducted a large-scale genome-wide cross-trait association study to investigate the genetic overlap between 5 kidney function biomarkers (eGFRcrea, eGFRcys, blood urea nitrogen (BUN), serum urate, and UACR) and 2 mental disorders (MDD, BIP). Summary-level data of European ancestry were extracted from UK Biobank, Chronic Kidney Disease Genetics Consortium, and Psychiatric Genomics Consortium. RESULTS: Using LD score regression, we found moderate but significant genetic correlations between kidney function biomarker traits on BIP and MDD. Cross-trait meta-analysis identified 1 to 19 independent significant loci that were found shared among 10 pairs of 5 kidney function biomarkers traits and 2 mental disorders. Among them, 3 novel genes: SUFU, IBSP, and PTPRJ, were also identified in transcriptome-wide association study analysis (TWAS), most of which were observed in the nervous and digestive systems (FDR < 0.05). Pathway analysis showed the immune system could play a role between kidney function biomarkers and mental disorders. Bidirectional mendelian randomization analysis suggested a potential causal relationship of kidney function biomarkers on BIP and MDD. CONCLUSIONS: In conclusion, the study demonstrated that both BIP and MDD shared genetic architecture with kidney function biomarkers, providing new insights into their genetic architectures and suggesting that larger GWASs are warranted.

Scn1a haploinsufficiency in the prefrontal cortex engages to cognitive impairment and depressive phenotype.

Altered development and function of the prefrontal cortex (PFC) during adolescence is implicated in the origin of mental disorders. Deficits in the GABAergic system prominently contribute to these alterations. Nav1.1 is a voltage-gated Na+ channel critical for normal GABAergic activity. Here, we studied the role of Nav1.1 in PFC function and its potential relationship with the aetiology of mental disorders. Dysfunction of Nav1.1 activity in the medial PFC (mPFC) of adolescent mice enhanced the local excitation/inhibition ratio, resulting in epileptic activity, cognitive deficits and depressive-like behaviour in adulthood, along with a gene expression profile linked to major depressive disorder (MDD). Additionally, it reduced extracellular serotonin concentration in the dorsal raphe nucleus and brain-derived neurotrophic factor expression in the hippocampus, two MDD-related brain areas beyond the PFC. We also observed alterations in oscillatory activity and impaired hippocampal-mPFC coherence during sleep. Finally, we found reduced expression levels of SCN1A, the gene encoding Nav1.1, in post-mortem PFC samples from human MDD subjects. Collectively, our results provide a novel mechanistic framework linking adolescence-specific alterations in Nav1.1 function in the PFC to the pathogenesis of epilepsy and comorbidities such as cognitive impairment and depressive disorders.

Impaired visual-motor functional connectivity in first-episode medication-naïve patients with major depressive disorder.

The perceptual dysfunctions have been fundamental causes of cognitive and emotional problems in patients with major depressive disorder. However, visual system impairment in depression has been underexplored. Here, we explored functional connectivity in a large cohort of first-episode medication-naïve patients with major depressive disorder (n = 190) and compared it with age- and sex-matched healthy controls (n = 190). A recently developed individual-oriented approach was applied to parcellate the cerebral cortex into 92 regions of interest using resting-state functional magnetic resonance imaging data. Significant reductions in functional connectivities were observed between the right lateral occipitotemporal junction within the visual network and 2 regions of interest within the sensorimotor network in patients. The volume of right lateral occipitotemporal junction was also significantly reduced in major depressive disorder patients, indicating that this visual region is anatomically and functionally impaired. Behavioral correlation analysis showed that the reduced functional connectivities were significantly associated with inhibition control in visual-motor processing in patients. Taken together, our data suggest that functional connectivity between visual network and sensorimotor network already shows a significant reduction in the first episode of major depressive disorder, which may interfere with the inhibition control in visual-motor processing. The lateral occipitotemporal junction may be a hub of disconnection and may play a role in the pathophysiology of major depressive disorder.

Reading language of the eyes in female depression.

Aberrations in non-verbal social cognition have been reported to coincide with major depressive disorder. Yet little is known about the role of the eyes. To fill this gap, the present study explores whether and, if so, how reading language of the eyes is altered in depression. For this purpose, patients and person-by-person matched typically developing individuals were administered the Emotions in Masked Faces task and Reading the Mind in the Eyes Test, modified, both of which contained a comparable amount of visual information available. For achieving group homogeneity, we set a focus on females as major depressive disorder displays a gender-specific profile. The findings show that facial masks selectively affect inferring emotions: recognition of sadness and anger are more heavily compromised in major depressive disorder as compared with typically developing controls, whereas the recognition of fear, happiness, and neutral expressions remains unhindered. Disgust, the forgotten emotion of psychiatry, is the least recognizable emotion in both groups. On the Reading the Mind in the Eyes Test patients exhibit lower accuracy on positive expressions than their typically developing peers, but do not differ on negative items. In both depressive and typically developing individuals, the ability to recognize emotions behind a mask and performance on the Reading the Mind in the Eyes Test are linked to each other in processing speed, but not recognition accuracy. The outcome provides a blueprint for understanding the complexities of reading language of the eyes within and beyond the COVID-19 pandemic.

Uncovering the power of neurofeedback: a meta-analysis of its effectiveness in treating major depressive disorders.

Neurofeedback, a non-invasive intervention, has been increasingly used as a potential treatment for major depressive disorders. However, the effectiveness of neurofeedback in alleviating depressive symptoms remains uncertain. To address this gap, we conducted a comprehensive meta-analysis to evaluate the efficacy of neurofeedback as a treatment for major depressive disorders. We conducted a comprehensive meta-analysis of 22 studies investigating the effects of neurofeedback interventions on depression symptoms, neurophysiological outcomes, and neuropsychological function. Our analysis included the calculation of Hedges' g effect sizes and explored various moderators like intervention settings, study designs, and demographics. Our findings revealed that neurofeedback intervention had a significant impact on depression symptoms (Hedges' g = -0.600) and neurophysiological outcomes (Hedges' g = -0.726). We also observed a moderate effect size for neurofeedback intervention on neuropsychological function (Hedges' g = -0.418). As expected, we observed that longer intervention length was associated with better outcomes for depressive symptoms (ß = -4.36, P < 0.001) and neuropsychological function (ß = -2.89, P = 0.003). Surprisingly, we found that shorter neurofeedback sessions were associated with improvements in neurophysiological outcomes (ß = 3.34, P < 0.001). Our meta-analysis provides compelling evidence that neurofeedback holds promising potential as a non-pharmacological intervention option for effectively improving depressive symptoms, neurophysiological outcomes, and neuropsychological function in individuals with major depressive disorders.

Sex differences in aberrant functional connectivity of three core networks and subcortical networks in medication-free adolescent-onset major depressive disorder.

Major depressive disorder demonstrated sex differences in prevalence and symptoms, which were more pronounced during adolescence. Yet, research on sex-specific brain network characteristics in adolescent-onset major depressive disorder remains limited. This study investigated sex-specific and nonspecific alterations in resting-state functional connectivity of three core networks (frontoparietal network, salience network, and default mode network) and subcortical networks in adolescent-onset major depressive disorder, using seed-based resting-state functional connectivity in 50 medication-free patients with adolescent-onset major depressive disorder and 56 healthy controls. Irrespective of sex, compared with healthy controls, adolescent-onset major depressive disorder patients showed hypoconnectivity between bilateral hippocampus and right superior temporal gyrus (default mode network). More importantly, we further found that females with adolescent-onset major depressive disorder exhibited hypoconnectivity within the default mode network (medial prefrontal cortex), and between the subcortical regions (i.e. amygdala, striatum, and thalamus) with the default mode network (angular gyrus and posterior cingulate cortex) and the frontoparietal network (dorsal prefrontal cortex), while the opposite patterns of resting-state functional connectivity alterations were observed in males with adolescent-onset major depressive disorder, relative to their sex-matched healthy controls. Moreover, several sex-specific resting-state functional connectivity changes were correlated with age of onset, sleep disturbance, and anxiety in adolescent-onset major depressive disorder with different sex. These findings suggested that these sex-specific resting-state functional connectivity alterations may reflect the differences in brain development or processes related to early illness onset, underscoring the necessity for sex-tailored diagnostic and therapeutic approaches in adolescent-onset major depressive disorder.

Elevated BICD2 DNA methylation in blood of major depressive disorder patients and reduction of depressive-like behaviors in hippocampal Bicd2-knockdown mice.

Major depressive disorder (MDD) is a prevalent and devastating mental illness. To date, the diagnosis of MDD is largely dependent on clinical interviews and questionnaires and still lacks a reliable biomarker. DNA methylation has a stable and reversible nature and is likely associated with the course and therapeutic efficacy of complex diseases, which may play an important role in the etiology of a disease. Here, we identified and validated a DNA methylation biomarker for MDD from four independent cohorts of the Chinese Han population. First, we integrated the analysis of the DNA methylation microarray (n = 80) and RNA expression microarray data (n = 40) and identified BICD2 as the top-ranked gene. In the replication phase, we employed the Sequenom MassARRAY method to confirm the DNA hypermethylation change in a large sample size (n = 1,346) and used the methylation-sensitive restriction enzymes and a quantitative PCR approach (MSE-qPCR) and qPCR method to confirm the correlation between DNA hypermethylation and mRNA down-regulation of BICD2 (n = 60). The results were replicated in the peripheral blood of mice with depressive-like behaviors, while in the hippocampus of mice, Bicd2 showed DNA hypomethylation and mRNA/protein up-regulation. Hippocampal Bicd2 knockdown demonstrates antidepressant action in the chronic unpredictable mild stress (CUMS) mouse model of depression, which may be mediated by increased BDNF expression. Our study identified a potential DNA methylation biomarker and investigated its functional implications, which could be exploited to improve the diagnosis and treatment of MDD.

Multiscale neural signatures of major depressive, anxiety, and stress-related disorders.

The extent of shared and distinct neural mechanisms underlying major depressive disorder (MDD), anxiety, and stress-related disorders is still unclear. We compared the neural signatures of these disorders in 5,405 UK Biobank patients and 21,727 healthy controls. We found the greatest case­control differences in resting-state functional connectivity and cortical thickness in MDD, followed by anxiety and stress-related disorders. Neural signatures for MDD and anxiety disorders were highly concordant, whereas stress-related disorders showed a distinct pattern. Controlling for cross-disorder genetic risk somewhat decreased the similarity between functional neural signatures of stress-related disorders and both MDD and anxiety disorders. Among cases and healthy controls, reduced within-network and increased between-network frontoparietal and default mode connectivity were associated with poorer cognitive performance (processing speed, attention, associative learning, and fluid intelligence). These results provide evidence for distinct neural circuit function impairments in MDD and anxiety disorders compared to stress disorders, yet cognitive impairment appears unrelated to diagnosis and varies with circuit function.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response.

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study.

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

Adenylate cyclase 3: a potential genetic link between obesity and major depressive disorder.

Obesity and major depressive disorder (MDD) are both significant health issues that have been increasing in prevalence and are associated with multiple comorbidities. Obesity and MDD have been shown to be bidirectionally associated, and they are both influenced by genetics and environmental factors. However, the molecular mechanisms that link these two diseases are not yet fully understood. It is possible that these diseases are connected through the actions of the cAMP/protein kinase A (PKA) pathway. Within this pathway, adenylate cyclase 3 (Adcy3) has emerged as a key player in both obesity and MDD. Numerous genetic variants in Adcy3 have been identified in humans in association with obesity. Rodent knockout studies have also validated the importance of this gene for energy homeostasis. Furthermore, Adcy3 has been identified as a top candidate gene and even a potential blood biomarker for MDD. Adcy3 and the cAMP/PKA pathway may therefore serve as an important genetic and functional link between these two diseases. In this mini-review, we discuss the role of both Adcy3 and the cAMP/PKA pathway, including specific genetic mutations, in both diseases. Understanding the role that Adcy3 mutations play in obesity and MDD could open the door for precision medicine approaches and treatments for both diseases that target this gene.

Prediction of anxious depression using multimodal neuroimaging and machine learning.

Anxious depression is a common subtype of major depressive disorder (MDD) associated with adverse outcomes and severely impaired social function. It is important to clarify the underlying neurobiology of anxious depression to refine the diagnosis and stratify patients for therapy. Here we explored associations between anxiety and brain structure/function in MDD patients. A total of 260 MDD patients and 127 healthy controls underwent three-dimensional T1-weighted structural scanning and resting-state functional magnetic resonance imaging. Demographic data were collected from all participants. Differences in gray matter volume (GMV), (fractional) amplitude of low-frequency fluctuation ((f)ALFF), regional homogeneity (ReHo), and seed point-based functional connectivity were compared between anxious MDD patients, non-anxious MDD patients, and healthy controls. A random forest model was used to predict anxiety in MDD patients using neuroimaging features. Anxious MDD patients showed significant differences in GMV in the left middle temporal gyrus and ReHo in the right superior parietal gyrus and the left precuneus than HCs. Compared with non-anxious MDD patients, patients with anxious MDD showed significantly different GMV in the left inferior temporal gyrus, left superior temporal gyrus, left superior frontal gyrus (orbital part), and left dorsolateral superior frontal gyrus; fALFF in the left middle temporal gyrus; ReHo in the inferior temporal gyrus and the superior frontal gyrus (orbital part); and functional connectivity between the left superior temporal gyrus(temporal pole) and left medial superior frontal gyrus. A diagnostic predictive random forest model built using imaging features and validated by 10-fold cross-validation distinguished anxious from non-anxious MDD with an AUC of 0.802. Patients with anxious depression exhibit dysregulation of brain regions associated with emotion regulation, cognition, and decision-making, and our diagnostic model paves the way for more accurate, objective clinical diagnosis of anxious depression.

Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI.

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future.

Dysregulation of circadian clock gene expression patterns in a treatment-resistant animal model of depression.

Circadian rhythm (CR) disturbances are among the most commonly observed symptoms during major depressive disorder, mostly in the form of disrupted sleeping patterns. However, several other measurable parameters, such as plasma hormone rhythms and differential expression of circadian clock genes (ccgs), are also present, often referred to as circadian phase markers. In the recent years, CR disturbances have been recognized as an essential aspect of depression; however, most of the known animal models of depression have yet to be evaluated for their eligibility to model CR disturbances. In this study, we investigate the potential of adrenocorticotropic hormone (ACTH)-treated animals as a disease model for research in CR disturbances in treatment-resistant depression. For this purpose, we evaluate the changes in several circadian phase markers, including plasma concentrations of corticosterone, ACTH, and melatonin, as well as gene expression patterns of 13 selected ccgs at 3 different time points, in both peripheral and central tissues. We observed no impact on plasma corticosterone and melatonin concentrations in the ACTH rats compared to vehicle. However, the expression pattern of several ccgs was affected in the ACTH rats compared to vehicle. In the hippocampus, 10 ccgs were affected by ACTH treatment, whereas in the adrenal glands, 5 ccgs were affected and in the prefrontal cortex, hypothalamus and liver 4 ccgs were regulated. In the blood, only 1 gene was affected. Individual tissues showed changes in different ccgs, but the expression of Bmal1, Per1, and Per2 were most generally affected. Collectively, the results presented here indicate that the ACTH animal model displays dysregulation of a number of phase markers suggesting the model may be appropriate for future studies into CR disturbances.

Multiple integrated social stress induces depressive-like behavioral and neural adaptations in female C57BL/6J mice.

Despite women representing most of those affected by major depression, preclinical studies have focused almost exclusively on male subjects, partially due to a lack of ideal animal paradigms. As the persistent need regarding the sex balance of neuroscience research and female-specific pathology of mental disorders surges, the establishment of natural etiology-based and systematically validated animal paradigms for depression with female subjects becomes an urgent scientific problem. This study aims to establish, characterize, and validate a "Multiple Integrated Social Stress (MISS)" model of depression in female C57BL/6J mice by manipulating and integrating daily social stressors that females are experiencing. Female C57BL/6J mice randomly experienced social competition failure in tube test, modified vicarious social defeat stress, unescapable overcrowding stress followed by social isolation on each day, for ten consecutive days. Compared with their controls, female MISS mice exhibited a relatively decreased preference for social interaction and sucrose, along with increased immobility in the tail suspension test, which could last for at least one month. These MISS mice also exhibited increased levels of blood serum corticosterone, interleukin-6 L and 1ß. In the pharmacological experiment, MISS-induced dysfunctions in social interaction, sucrose preference, and tail suspension tests were amended by systematically administrating a single dose of sub-anesthetic ketamine, a rapid-onset antidepressant. Compared with controls, MISS females exhibited decreased c-Fos activation in their anterior cingulate cortex, prefrontal cortex, nucleus accumbens and some other depression-related brain regions. Furthermore, 24 h after the last exposure to the paradigm, MISS mice demonstrated a decreased center zone time in the open field test and decreased open arm time in the elevated plus-maze test, indicating anxiety-like behavioral phenotypes. Interestingly, MISS mice developed an excessive nesting ability, suggesting a likely behavioral phenotype of obsessive-compulsive disorder. These data showed that the MISS paradigm was sufficient to generate pathological profiles in female mice to mimic core symptoms, serum biochemistry and neural adaptations of depression in clinical patients. The present study offers a multiple integrated natural etiology-based animal model tool for studying female stress susceptibility.

Acceptability of psilocybin-assisted group therapy in patients with cancer and major depressive disorder: Qualitative analysis.

BACKGROUND: The present study explored the acceptability of psilocybin-assisted group therapy from the perspective of patients with cancer and depression who participated in a clinical trial assessing the safety and efficacy of this novel intervention. METHODS: Guided by the conceptual framework of acceptability, the authors conducted semi-structured interviews with participants of the psilocybin trial. Data were analyzed using template and thematic analyses. RESULTS: Participants' (n = 28) perspectives on the acceptability of the group and simultaneous sessions was generally positive, both in terms of safety and efficacy: first, the groups contributed to increase participants' sense of safety and preparedness as they were engaging in the therapy; and second, the groups fostered a sense of connection and of belonging, which served to enrich and deepen the meaning of participants' experience, ultimately opening a dimension of self-transcendence and compassion. Other subthemes related to factors influencing the acceptability of the group approach included: 1) the importance of the therapeutic framework, 2) the complementary value of individual sessions, 3) disruptive factors related to the group and/or simultaneous setting, and 4) opportunities and challenges related to group size and how to structure interactions. CONCLUSIONS: This study enhances understanding of what promotes acceptability of the psilocybin-assisted therapy group model for the treatment of MDD in cancer patients. PLAIN LANGUAGE SUMMARY: We conducted exit interviews with participants of a phase 2 trial of psilocybin-assisted therapy (PAT) conducted in a community cancer center, to assess the acceptability of a novel psilocybin delivery model combining simultaneous individual therapy and group sessions. Our findings support the acceptability of this intervention and suggest that in addition to being feasible, it might also enhance participants' perceived safety and efficacy compared to uniquely individual or group delivery models of PAT. Our analysis highlights critical factors conditioning acceptability and suggests new ways PAT may be scaled and integrated into cancer care.

Psilocybin-assisted group therapy in patients with cancer diagnosed with a major depressive disorder.

BACKGROUND: Depression is common in patients with cancer and is associated with lower treatment adherence and reduced quality of life. Antidepressants and psychotherapy have limited success in improving depression among patients with cancer. This study explored the safety, feasibility, and efficacy of psilocybin-assisted therapy in patients with cancer and major depressive disorder. METHODS: This phase 2, open-label trial enrolled patients with curable and noncurable cancer and major depressive disorder at a single community oncology practice site. A single 25-mg dose of psilocybin was administered simultaneously to cohorts of three to four participants with individual (4.25 hours in 1:1 therapist-to-patient ratio) and group therapeutic support (3.75 hours) before, during, and after psilocybin administration. Outcomes included depression severity, anxiety, pain, demoralization, and disability. RESULTS: Thirty participants completed the study. No psilocybin-related serious adverse events occurred; treatment-related adverse events (e.g., nausea, headache) were generally mild and expected. There were no laboratory or electrocardiogram abnormalities. No suicidality was reported. Efficacy was suggested with a robust reduction in depression severity scores from baseline to posttreatment of 19.1 points (95% CI, 22.3 to -16.0; p < .0001) by week 8. Eighty percent of participants demonstrated a sustained response to psilocybin treatment; 50% showed full remission of depressive symptoms at week 1, which was sustained for 8 weeks. CONCLUSIONS: Psilocybin-assisted therapy in group cohort administration was safe and feasible in patients with cancer and depression. Efficacy was suggested based on clinically meaningful reductions in depressive symptoms. The novel, group-oriented format, compact delivery time, community cancer center setting, and one-to-one therapist-to-patient ratio could also add to therapeutic gains and efficiency of administration. TRIAL REGISTRATION: NCT04593563. PLAIN LANGUAGE SUMMARY: Depression is common in patients with cancer and associated with lower treatment adherence, reduced quality of life, and limited response to antidepressants and psychotherapy. We conducted a phase 2 trial to study a single dose of psilocybin administered in a group therapy setting with one-to-one therapist-to-participant psychological support to patients with curable and noncurable cancer and major depressive disorder. Findings of the study showed safety (no treatment-related serious adverse events or suicidality) with psilocybin and suggested efficacy, with a significant reduction in depression severity scores from baseline to posttreatment. Further investigation is warranted.

Differences in resting-state brain activity in first-episode drug-naïve major depressive disorder patients with and without suicidal ideation.

Despite altered brain activities being associated with suicidal ideation (SI), the neural correlates of SI in major depressive disorder (MDD) have remained elusive. We enrolled 82 first-episode drug-naïve MDD patients including 41 with SI and 41 without SI, as well as 41 healthy controls (HCs). Resting-state functional and structural MRI data were collected. The measures of fractional amplitude of low-frequency fluctuation (fALFF) and grey matter volume (GMV) were calculated and compared. Compared with HCs, patients with SI exhibited increased fALFF values in the right rectus gyrus and left medial superior frontal gyrus, middle frontal gyrus and precuneus. Decreased GMV in the right parahippocampal gyrus, insula and middle occipital gyrus and increased GMV in the left superior frontal gyrus were detected in patients with SI. In addition, patients without SI demonstrated increased fALFF values in the right superior frontal gyrus and decreased fALFF values in the right postcentral gyrus. Decreased GMV in the left superior frontal gyrus, right medial superior frontal gyrus, opercular part of inferior frontal gyrus, postcentral gyrus, fusiform gyrus and increased left supplementary motor area, superior occipital gyrus, right anterior cingulate gyrus and superior temporal gyrus were revealed in patients with SI. Moreover, in comparison with patients without SI, increased fALFF values were identified in the left precuneus of patients with SI. However, no significant differences were found in GMV between patients with and without SI. These findings might be helpful for finding neuroimaging markers predicting individual suicide risk and detecting targeted brain regions for effective early interventions.

Classification of MDD using a Transformer classifier with large-scale multisite resting-state fMRI data.

Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide with high recurrence rate. Identifying MDD patients, particularly those with recurrent episodes with resting-state fMRI, may reveal the relationship between MDD and brain function. We proposed a Transformer-Encoder model, which utilized functional connectivity extracted from large-scale multisite rs-fMRI datasets to classify MDD and HC. The model discarded the Transformer's Decoder part, reducing the model's complexity and decreasing the number of parameters to adapt to the limited sample size and it does not require a complex feature selection process and achieves end-to-end classification. Additionally, our model is suitable for classifying data combined from multiple brain atlases and has an optional unsupervised pre-training module to acquire optimal initial parameters and speed up the training process. The model's performance was tested on a large-scale multisite dataset and identified brain regions affected by MDD using the Grad-CAM method. After conducting five-fold cross-validation, our model achieved an average classification accuracy of 68.61% on a dataset consisting of 1611 samples. For the selected recurrent MDD dataset, the model reached an average classification accuracy of 78.11%. Abnormalities were detected in the frontal gyri and cerebral cortex of MDD patients in both datasets. Furthermore, the identified brain regions in the recurrent MDD dataset generally exhibited a higher contribution to the model's performance.