Major depressive disorder

Glucocorticoid receptor signaling in the brain and its involvement in cognitive function

The hypothalamic-pituitary-adrenal axis regulates the secretion of glucocorticoids in response to environmental challenges. In the brain, a nuclear receptor transcription factor, the glucocorticoid receptor, is an important component of the hypothalamic-pituitary-adrenal axis's negative feedback loop and plays a key role in regulating cognitive equilibrium and neuroplasticity. The glucocorticoid receptor influences cognitive processes, including glutamate neurotransmission, calcium signaling, and the activation of brain-derived neurotrophic factor-mediated pathways, through a combination of genomic and non-genomic mechanisms. Protein interactions within the central nervous system can alter the expression and activity of the glucocorticoid receptor, thereby affecting the hypothalamic-pituitary-adrenal axis and stress-related cognitive functions. An appropriate level of glucocorticoid receptor expression can improve cognitive function, while excessive glucocorticoid receptors or long-term exposure to glucocorticoids may lead to cognitive impairment. Patients with cognitive impairment-associated diseases, such as Alzheimer's disease, aging, depression, Parkinson's disease, Huntington's disease, stroke, and addiction, often present with dysregulation of the hypothalamic-pituitary-adrenal axis and glucocorticoid receptor expression. This review provides a comprehensive overview of the functions of the glucocorticoid receptor in the hypothalamic-pituitary-adrenal axis and cognitive activities. It emphasizes that appropriate glucocorticoid receptor signaling facilitates learning and memory, while its dysregulation can lead to cognitive impairment. This provides clues about how glucocorticoid receptor signaling can be targeted to overcome cognitive disability-related disorders.

Investigating causal relationships between gene expression and major depressive disorder via brain bulk-tissue and cell type-specific eQTL: A Mendelian randomization and Bayesian colocalization study

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent psychiatric disorder with complex genetic underpinnings. While genome-wide association studies (GWAS) have identified multiple risk loci, pinpointing causal genes within the human brain remains challenging, particularly given the regulatory complexity across different cell types.

METHODS

We performed summary data-based MR (SMR) and Bayesian colocalization analyses by integrating bulk-tissue eQTL data from 888 individuals with single-cell eQTL datasets from 192 donors representing major brain cell types (excitatory and inhibitory neurons, astrocytes, microglia, oligodendrocytes, OPCs/COPs, endothelial cells, and pericytes). GWAS summary statistics for MDD (170,756 cases and 329,443 controls) were used to assess the causal impact of gene expression. Sensitivity analyses, including the heterogeneity in dependent instruments (HEIDI) test and Steiger filtering, ensured robust inference.

RESULTS

In bulk tissue analyses, five genes (BTN3A2, SLC12A5, AREL1, GMPPB, and ZNF660) emerged as having robust causal evidence for MDD, displaying consistent MR signals and strong colocalization. Cell type-specific analyses revealed additional candidate genes in excitatory neurons (FLOT1, AL450423.1), astrocytes (AL121821.1), and oligodendrocytes (YLPM1, COP1).

CONCLUSION

Our integrative approach reveals that causal gene expression profiles differ markedly between bulk-tissue and specific brain cell types, emphasizing cellular heterogeneity in MDD pathogenesis and informing precision therapeutic strategies. These findings underscore the necessity of considering cell type-specific gene regulation when developing therapeutic interventions for MDD.

Specific expression and common potential therapeutic drugs in different brain regions of major depressive disorder patients: bioinformatics analysis

Major depressive disorder (MDD) is a prevalent and debilitating mental health condition characterized by persistent feelings of sadness and loss of interest. Despite its high prevalence, the underlying molecular mechanisms remain poorly understood. This study aims to elucidate the gene expression differences across distinct brain regions in MDD patients, identify potential diagnostic and therapeutic targets, and establish predictive models using bioinformatics approaches. Whole-transcriptome sequencing data from three different human brain regions were obtained from five datasets (GSE54564, GSE54571, GSE54572, GSE54567, GSE54568) in the GEO database. Gene symbol preprocessing was conducted using the XIANTAO platform. Differentially expressed genes (DEGs) were identified between MDD samples and controls using the R package "limma." Protein-protein interaction (PPI) networks were constructed using STRING and visualized in Cytoscape. Core genes were identified via CytoHubba using three algorithms (MCC, DEGREE, EPC). Receiver operating characteristic (ROC) curve analysis was performed to evaluate the prognostic value of core genes. LASSO regression was employed to enhance prediction accuracy and interpretability of machine learning models. Potential therapeutic drugs were predicted using the Comparative Toxicogenomics Database (CTD). In total, 342 DEGs related to the amygdala, 76 DEGs related to the anterior cingulate cortex, and 64 DEGs related to the dorsolateral prefrontal cortex were identified (p < 0.05, |logFC| > 0.15). Key diagnostic genes included COX5A and SST for the amygdala; CTSG, IL18RAP, LMO2, and MS4A7 for the anterior cingulate cortex; and VGF for the dorsolateral prefrontal cortex. The machine learning models demonstrated high predictive accuracy with AUC values of 0.776 for the amygdala, 0.928 for the anterior cingulate cortex, and 0.867 for the dorsolateral prefrontal cortex. Potential therapeutic drugs included dorsomorphin and trichostatin A. Gene set enrichment analysis (GSEA) revealed significant pathways such as oxidative phosphorylation in the amygdala, TYROBP microglial network in the anterior cingulate cortex, and MAPK signaling pathway in the dorsolateral prefrontal cortex. This study provides a comprehensive bioinformatics analysis of gene expression differences across brain regions in MDD patients. The identified core genes and pathways offer valuable insights into disease mechanisms and potential therapeutic targets, paving the way for future clinical applications.

Association between hikikomori (social withdrawal) and depression in Korean young adults

BACKGROUND

Major depressive disorder (MDD) is a prevalent mental illness, particularly affecting women. The World Health Organization projects that by 2030, MDD will be the leading cause of disease burden. The phenomenon of hikikomori-initially observed in Japan-is increasingly associated with depression, a key risk factor for which is social isolation. This study analyzed the impact of social withdrawal on depression among South Korean young adults, focusing on (1) the relation between withdrawal duration and causes, and (2) its effect on depression severity.

METHODS

Data from the 2022 Korean Youth Survey, including 14,966 participants aged 19-34, were used. Depression levels were assessed using the Patient Health Questionnaire-9 (PHQ-9), and multiple logistic regression was conducted to examine the association between hikikomori behavior and depression.

RESULTS

The reference group for all analyses was youth who were not socially withdrawn. The association between hikikomori and depression was statistically significant for the two sexes (males: OR: 2.25, 95 % CI: 1.60-3.19; females: OR: 2.34, 95 % CI: 1.63-3.36). Household size influenced depression risk among hikikomori, and sex differences were observed in social withdrawal's effect on suicide risk.

CONCLUSION

This study highlights the link between hikikomori and depression in South Korean youth, with sex-specific differences in depression and suicide risk, suggesting the need for tailored mental health programs. Future research should explore the long-term effects of prolonged social withdrawal through longitudinal studies and conduct cross-cultural comparisons of hikikomori.

Recurrent major depression, employment and transitions to unemployment and disability benefits

This study assesses the effects of recurrent major depression on employment and transitions to unemployment and disability benefits. Examining this issue is essential for designing timely interventions aimed to sustain individuals' employment. We rely on register data of a sample of individuals initially employed-a 2% sample of employees representative of French private-sector employees-followed up to eight years before and eight years after the year of diagnosis, aged between 20 and 60 years, over the period 2000-2015. We estimate that recurrent major depression persistently decreases the likelihood of being employed by 35 percentage points and annual earnings by 51%, and leads to increase the probability of long absence by 47 percentage points and the probability of permanent disability benefit recipiency by 33 percentage points. The effect sizes are similar between men and women. We find differences between age groups. For young and middle-aged individuals, recurrent major depression implies a decrease in employment rates, an increase in unemployment benefit rates and a persistent increase in disability benefit recipiency rates. Many young ill individuals remain attached to the labor market but experience unemployment and a large decline in annual earnings. For older individuals, recurrent major depression leads to a larger decrease in employment rates and a greater increase in disability benefit recipiency rates, compared to younger individuals. We conclude that differentiated policies tailored to age groups might be developed to support the employment of individuals with recurrent major depression.

Kynurenine pathway metabolites predict antianhedonic effects of electroconvulsive therapy in patients with treatment-resistant depression

BACKGROUND

Electroconvulsive therapy (ECT) is a rapid and effective antianhedonic treatment for treatment-resistant depression (TRD). Whether this effect is related to kynurenine (KYN) pathway metabolites lacks evidence, so we examined if the changes in these metabolites can serve as potential biomarkers for the antianhedonic effects of ECT.

METHODS

In this single-arm clinical trial, sixty patients diagnosed with TRD received a series of eight ECT treatments and provided blood samples. Antianhedonic effects were measured by items 1 (apparent sadness), 2 (reported sadness), 6 (concentration difficulties), 7 (lassitude) and 8 (inability to feel) of the Montgomery-Åsberg Depression Rating Scale (MADRS). Serum tryptophan (TRP), KYN, kynurenic acid (KYNA) concentration, KYN/TRP ratio and KYNA/KYN ratio, were measured at baseline and after ECT sessions 2, 4, 6 and 8.

RESULTS

Anhedonia responders had higher TRP levels (after ECT session 8) and lower KYNA levels (after ECT sessions 4 and 6) than non-responders (all p's < 0.05). Anhedonia remitters had a lower KYNA/KYN ratio (after ECT sessions 2, 6) and lower KYN/TRP ratio (after ECT sessions 8) compared to non-remitters (all p's < 0.05). The reduction in anhedonia scores after ECT session 2 were related to the reduction of KYN levels from baseline to ECT session 2 (r = 0.3, p = 0.049). TRP, KYN levels and KYN/TRP ratios predicted antianhedonic efficacy for ECT (TRP: β = 1.6, p = 0.029; KYN: β = -2.4, p = 0.033; KYN/TRP ratio: β = 1.9, p = 0.027).

CONCLUSION

This preliminary study found that ECT treatment significantly improved anhedonia symptoms in TRD patients and this improvement was related to biomarker changes in the KYN pathway.

Major-depressive-disorder-associated dysregulation of ZBTB7A in orbitofrontal cortex promotes astrocyte-mediated stress susceptibility

Heightened activity in the orbitofrontal cortex (OFC), a brain region that contributes to motivation, emotion, and reward-related decision-making, is a key clinical feature of major depressive disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unclear. Here, we performed cell-type-specific profiling of human OFC and unexpectedly mapped MDD-linked epigenomic features (including genetic risk variants) to non-neuronal cells, revealing significant glial dysregulation in this region. Characterization of MDD-specific chromatin loci further identified ZBTB7A-a transcriptional regulator of astrocyte reactivity-as an important mediator of MDD-related alterations. In rodent models, we found that Zbtb7a induction in astrocytes is both necessary and sufficient to drive stress-mediated behavioral deficits, cell-type-specific transcriptional/epigenomic signatures, and aberrant OFC astrocyte-neuronal communication in male mice-an established MDD risk factor. These findings thus highlight essential roles for astrocytes in OFC-mediated stress susceptibility and identify ZBTB7A as a critical and therapeutically relevant regulator of MDD-related OFC dysfunction.

Social determinants of health and their impact on depression in family caregivers of those with dementia: The importance of intermediary determinants

INTRODUCTION

Dementia family caregivers face a significant burden due to the progressive nature of the disease, which places them at high risk for depression. Because a lack of information is available on the social determinants of health that impact depression, this study investigated this relationship.

METHODS

This study was a secondary data analysis using the 2017 National Health and Aging Trends Study (NHATS) Round 11 and the National Study of Caregiving (NSOC) Round 4, which included a nationally representative sample of American older adults and their family caregivers. Weighted multivariate logistic regression models were used for data analysis.

RESULTS

Among 528 family caregivers of persons living with dementia, ≈15.9% had depression. The final logistic regression model showed that intermediary determinants, such as living with a spouse/partner or utilizing a caregiver training program, lowered the likelihood of depression.

DISCUSSION

Health care professionals should pay greater attention to these individuals, and caregiver training programs should be made widely accessible and available.

HIGHLIGHTS

Approximately 15.9% of dementia family caregivers had depression. Family caregivers who were married or living with a partner were less likely to have depression. Family caregivers involved in caregiving training programs were less likely to have depression.

Optimism moderates the relationship between inflammatory polygenic risk and major depressive disorder in U.S. Military veterans

OBJECTIVES

Major depressive disorder (MDD) is a leading cause of disability, and chronic inflammation is a contributing factor to its onset and progression. This study examined the relationship between genetic predisposition to inflammation and MDD risk in a nationally representative sample of U.S. military veterans, as well as psychosocial moderators of this association.

METHODS

A composite polygenic risk score (PRS) for inflammatory biomarkers was derived from the UK Biobank and examined in relation to a positive MDD screen in 1,660 European-American veterans. The analysis adjusted for known correlates of inflammation and MDD, including medical conditions and cumulative trauma burden.

RESULTS

Each standard deviation increase in the inflammatory PRS was associated with more than two-fold increased odds of screening positive for MDD (OR = 2.51, 95% CI = 1.39-4.54). Interaction analyses revealed that optimism moderated this association; among those in the highest PRS tertile, individuals with high optimism were more than 30 times less likely to screen positive for MDD compared to those with low optimism (0.7% vs. 22.6%). Pathway-based analyses identified enrichment of immune- and brain-related gene sets, highlighting potential biological mechanisms linking inflammation and MDD.

CONCLUSIONS

Findings suggest genetic risk for inflammation contributes to MDD vulnerability and that optimism may buffer this risk.

Bootstrap inference and machine learning reveal core differential plasma metabolic connectome signatures in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) involves molecular alterations and pathway dysregulation. Metabolic interconnections are crucial for normal functioning, yet current analysis focuses on individual pathways or biomarkers, overlooking intricate metabolic biomarker interactions.

METHODS

Plasma metabolomic data from 182,053 UK Biobank participants [9425 MDD, and 172,628 healthy controls (HC)] were used to construct metabolic correlation networks through bootstrap inference analysis (bootstrap step size: 1000, 3000, 5000, 7000, 9000; n = 1000 times/size). Differential core metabolic network signatures between MDD and HC were identified by machine learning, followed by metabolic pathway analysis. Various deep learning and machine learning models were employed to differentiate MDD from HC groups using the identified network features and baseline characteristics.

RESULTS

The MDD metabolic network showed marked reorganization, with a sparser and more streamlined network structure compared to controls (p < 0.05 for both Vnet-edge and Vnet-node). Analysis of the core network in MDD revealed four key altered pathways, with linoleic acid metabolism being the most influential (p < 0.01, impact = 0.29). An extreme gradient boosting model combining network signatures and baseline features achieved 73 % accuracy, and an AUROC of 0.82 in differentiating MDD from HC groups.

CONCLUSIONS

This large-scale, metabolomic connectome analysis revealed consistent dysregulated metabolic network features in MDD, providing a robust and distinguishable framework compared to controls. The MDD network exhibits distinct connectivity patterns, particularly within linoleic acid metabolism. Integrating metabolomics as networks, rather than isolated markers, offers a promising approach for elucidating MDD pathophysiology and identifying diagnostic biomarkers.

Running therapy improves clinical symptoms but not functional network connectivity in individuals with affective disorders

OBJECTIVES

Running therapy has been shown to be efficacious for depression and anxiety disorders. However, little is known about the effects of running therapy on functional brain connectivity.

METHODS

We used resting-state functional MRI scans from 25 individuals with an affective disorder that performed 16 weeks running therapy as part of the MOod Treatment with Antidepressants or Running (MOTAR) study. Using an atlas-based approach we investigated therapy-induced changes in connectivity and topology of several functional systems, e.g. the default-mode and salience networks. We additionally performed a case-control analysis using the pre-treatment scans of affective disorder patients (N = 50) and matched healthy controls (N = 66).

RESULTS

Running therapy significantly improved depressive (Inventory of Depressive Symptoms; IDS) and anxiety (Beck's Anxiety Inventory; BAI) symptoms after 16 weeks (IDS: Z = -4.13, P < 0.001, BAI: Z = -2.87, P = 0.003), but it had no significant effect on functional connectivity or network topology. The case-control analyses at baseline also did not reveal any between-group differences.

CONCLUSION

We conclude that there were either no functional abnormalities to improve or the effects of 16 weeks running therapy may be too subtle to impact (global) network communication of functional systems and may be limited to changes in localized brain regions. Discrepancies between our case-control results and that of previous literature are interpreted in light of methodological and clinical heterogeneity.

A data-centric and interpretable EEG framework for depression severity grading using SHAP-based insights

BACKGROUND

Major Depressive Disorder is a leading cause of disability worldwide. An accurate assessment of depression severity is critical for diagnosis, treatment planning, and monitoring, yet current clinical tools are largely subjective, relying on self-report and clinician judgment via traditional assessment scales. EEG has emerged as a promising, non-invasive modality for capturing neural correlates of depression. However, most EEG-based machine learning diagnostic studies focus on boosting classification accuracy through complex algorithms and small, homogenous datasets. These black-box approaches often yield results that are difficult to interpret and poorly generalizable, making clinical translation impractical. Therefore there remains a critical need for models that are not only accurate but also transparent, robust, and grounded in the physiological properties of the data itself.

METHODS

We proposed a data-centric, interpretable framework for EEG-based depression severity grading. A hybrid feature selection method was used, combining p-value and SHapley Additive exPlanations (SHAP) methods to select features that are both independently significant and jointly informative. The system was trained and evaluated on a large-scale, multi-site resting-state EEG dataset, using random forest for both classification and regression tasks. The SHAP method, an explainable artificial intelligence technique, is also used post-hoc to infer the key electrophysiological features and key brain regions associated with MDD mechanism to further increase interpretability.

RESULTS

The proposed system achieved 74.5% (95% CI [70.97%, 78.80%], p < 0.001) ten-fold classification accuracy and a correlation coefficient of 0.56 (95% CI [0.407, 0.683], p < 0.001) for severity estimation. SHAP analysis identified consistent, clinically meaningful EEG features, particularly in the left parietal-occipital lobe. Through in-depth SHAP value analysis, we identified critical disease-related brain areas in the left occipital and parietal lobes, along with key features including relative beta power in the left parietal lobe, time-domain features at the parietal midline, 1/f intercept, left occipital relative beta power, and global brain alpha energy.

CONCLUSION

This study proposes a data-centric, interpretable depression grading system built on large-scale, multi-center EEG data, using simple models and hybrid feature selection to emphasize explainability, generalizability and data fidelity. By shifting the focus from algorithmic complexity to data transparency and feature-level insight, the model offers a practical and trustworthy path toward real-world mental health assessment.

Effect of combined oral contraceptive use on verbal memory function in healthy women

PURPOSE

Female sex hormones as well as the synthetic hormones contained within combined oral contraceptives (COCs) may influence emotional and cognitive functioning including learning and memory; however, findings are inconsistent. We here present the largest study to date investigating the effect of COC use on verbal memory in healthy women.

METHODS

COC use and verbal memory scores were available from the CIMBI database for 205 healthy women in the reproductive age. We assessed if verbal memory and affective bias differed between COC users and non-users. In a subgroup of natural cycling women in the follicular phase, we assessed if verbal memory was associated with plasma estradiol levels.

RESULTS

We found no statistically significant group differences in either overall memory performance (p = 0.16) or affective memory bias (p = 0.18) between COC users and non-users, although there was a trend suggesting COC users may exhibit slightly better recall for short-term (p = 0.09) and long-term task (p = 0.08) conditions. Similarly, COC users tended to have slightly better overall memory compared with women in the follicular phase (p = 0.05). Follicular phase plasma estradiol levels were not associated with verbal memory.

CONCLUSIONS

We found no support for COC use to negatively impact verbal memory, if anything COC users tended to perform better than natural cycling women in follicular phase; however, this could be influenced by a healthy user bias. In conclusion, these findings highlight that women who tolerate COCs well should not be concerned about potential adverse effects on memory.

Alterations of serum metabolic profile in major depressive disorder: A case-control study in the Chinese population

BACKGROUND

Major depressive disorder (MDD) is characterized by persistent depressed mood and cognitive symptoms. This study aimed to discover biomarkers for MDD, explore its pathological mechanisms, and examine the associations of the identified biomarkers with clinical and psychological variables.

AIM

To discover candidate biomarkers for MDD identification and provide insight into the pathological mechanism of MDD.

METHODS

The current study adopted a single-center cross-sectional case-control design. Serum samples were obtained from 100 individuals diagnosed with MDD and 97 healthy controls (HCs) aged between 18 to 60 years. Metabolomics was performed on an Ultimate 3000 UHPLC system coupled with Q-Exactive MS (Thermo Scientific). The online software Metaboanalyst 6.0 was used to process and analyze the acquired raw data of peak intensities from the instrument.

RESULTS

The study included 100 MDD patients and 97 HCs. Metabolomic profiling identified 35 significantly different metabolites (e.g., cortisol, sebacic acid, and L-glutamic acid). Receiver operating characteristic curve analysis highlighted 8-HETE, 10-HDoHE, cortisol, 12-HHTrE, and 10-hydroxydecanoic acid as top diagnostic biomarkers for MDD. Significant correlations were found between metabolites (e.g., some lipids, steroids, and amino acids) and clinical and psychological variables.

CONCLUSION

Our study reported metabolites (some lipids, steroids, amino acids, carnitines, and alkaloids) responsible for discriminating MDD patients and HCs. This metabolite profile may enable the development of a laboratory-based diagnostic test for MDD. The mechanisms underlying the association between psychological or clinical variables and differential metabolites deserve further exploration.

Non-aversive handling in laboratory animals and its effects on depressive-like and anxiety-related behaviors: A scoping review

Stress is an adaptive response to environmental demands, but increased intensity and frequency can lead to impaired adaptive functions. Stress is considered a risk factor for Major Depressive Disorder, a multifactorial disorder that often coexists with anxiety. Picking up laboratory mice by the tail is the most common method for animal capture and may create background stress. Non-aversive handling (NAH) includes capturing the animal with the help of a tunnel or by capturing the animal with cupped hands. Given the importance of stress-induced models in the investigation of depressive-like and anxiety-related behaviors, we conducted a literature review to investigate the current knowledge on the behavioral effects of NAH in laboratory animals. While the ability of NAH to counteract depressive-like behavior has yielded mixed results, its ability to induce anxiolytic-like effects in mice has been confirmed by several studies. Some of the studies also investigated the impact of NAH on stress-related molecules (e.g. corticosterone) and physiological parameters (i.e. adrenal gland mass and body weight). The anxiolytic-like effect elicited by NAH seems to be well established in the literature, but little is known about the biochemical pathways underlying it and its antidepressant potential.

Neuroimaging studies of acupuncture for depressive disorder: a systematic review of published papers from 2014 to 2024

Background

Several neuroimaging studies have confirmed that acupuncture can elicit alterations in brain networks and regions associated with depressive disorder (DD). This review provides an overview of the methodologies and results of neuroimaging investigations into the efficacy of acupuncture in treating DD, with the intention of guiding future research objectives.

Methods

Neuroimaging studies of acupuncture for DD being published between February 2, 2014 and February 2, 2024, were gathered from PubMed, Cochrane Library, EMBASE, Web of Science, China National Knowledge Infrastructure, Chongqing VIP Database, WanFang Database, and Chinese Biomedical Literature Database. The methodological quality of the studies was assessed utilizing the Risk of Bias 2.0 and Risk of Bias in Non-Randomized Studies of Interventions tools. Following a qualitative analysis of the studies, relevant information regarding acupuncture interventions and brain imaging data was extracted.

Results

A total of 26 studies met the inclusion criteria. These studies featured a combined sample size of 1138 participants. All studies employed magnetic resonance imaging. Our findings indicate that acupuncture can affect neural activity in the cingulate gyrus, precuneus, insula, prefrontal lobe, etc. The neuroimaging results of most DD patients were correlated with the Hamilton Rating Scale for Depression scores.

Conclusions

The results of the current study indicate that acupuncture treatment may have a regulatory effect on the abnormal functioning of neural regions and networks in individuals diagnosed with DD. These networks are predominantly localized within various brain regions, including the default mode network, limbic system, emotion regulation and cognitive network, reward network, central executive network, salience network, and sensorimotor network. It is essential to conduct additional high-quality and multimodal neuroimaging research to expand upon these findings and elucidate the mechanisms by which acupuncture impacts patients with DD.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero/, identifier CRD42023400557.

Schizophrenia, bipolar disorder and major depressive disorder are probably not risk factors for cardiovascular disease: A Mendelian randomized study

BACKGROUND

Individuals with severe mental illnesses (SMI) like schizophrenia, bipolar disorder (BD), and major depressive disorder (MDD) have an increased risk for cardiovascular diseases (CVD), but the causal relationship remains unclear.

METHODS

Mendelian randomization (MR) was used to investigate the potential causal relationship between SMI and CVD and its five subtypes of disease, coronary heart disease, myocardial infarction, stroke, heart failure, and atrial fibrillation. Subsequently, the MR results of SMI with CVD and its subtypes were meta-analyzed separately. To assess the robustness of the findings, Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis were used. Select single nucleotide polymorphisms (SNPs) related to SMI and CVD and their five subtypes (coronary heart disease, myocardial infarction, stroke, heart failure, and atrial fibrillation). Use univariable Mendelian randomization (UVMR) and multivariate Mendelian randomization (MVMR) to assess the causal relationship between these conditions. Conduct a meta-analysis of the MR results of SMI and CVD and their subtypes. Use MR mediation analysis to evaluate the mediating effect of BMI between BD and CVD. Use Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis to enhance the robustness of the study.

RESULTS

MR analyses have revealed correlations between schizophrenia and BD with CVD and their subtypes in certain datasets. No significant evidence of an association between MDD and CVD or its subtypes was observed in our MR analyses. After MVMR and MR meta-analysis, no basis for genetically predicted SMI increasing CVD and their subtypes was found. The MR mediation analysis showed that the reduced risk of certain CVDs in BD was partially related to BMI to some extent.

CONCLUSION

Our MR study did not provide conclusive evidence for a causal association between genetic predisposition to SMI and CVD. Based on the available evidence, it would be more appropriate to consider SMI as potential risk markers for CVD and its subtypes rather than definitive risk factors.

Microglial cannabinoid receptor 2 and epigenetic regulation: Implications for the treatment of depression

Depression, often stress-induced, is closely related to neuroinflammation, in which microglia, the brain's immune cells, are the leading players. Microglia shift between a quiescent and an active state, promoting both pro- and anti-inflammatory responses. Cannabinoid type 2 (CB2) receptor encoded by the CNR2 gene is a key player to modulate inflammatory activity. CB2 receptor is highly controlled at the epigenetic level, especially in response to stressful stimuli, positioning it between stress, neuroinflammation, and depression. The following review addresses how epigenetic regulation of CNR2 expression affects depression and the dissection, further, of molecular pathways driving neuroinflammation-related depressive states. The present study emphasizes the therapeutic potential of CB2 receptor agonists that selectively interact with activated microglia and opens a new avenue for the treatment of depression associated with neuroinflammation. The review, therefore, provides a framework of underlying mechanisms for developing novel therapeutic strategies that focus on relieving symptoms by modulating the neuroinflammatory response. Finally, this review underlines the possibilities of therapeutic interventions taking into account CB2 receptors in combating depression.

Blood lipid profiles and mood disorders: A principal component analysis of UK Biobank data reveals distinct associations with depression and bipolar disorder

BACKGROUND

Growing evidence suggests that lipid metabolism may play a crucial role in mood disorder pathophysiology, and the correlation between blood lipids and mood disorder remains further clarified.

METHODS

This prospective, population-based cohort study utilized data from the UK Biobank. The study included 268,098 and 292,121 participants who had never been diagnosed with depression or bipolar disorder and who had complete data at both the baseline and follow-up points. A principal component analysis (PCA) was conducted on seven blood lipids, and the first three principal components (PCs) were derived. Cox regression analysis was employed to examine the correlation between the risk of mood disorders and the PCs. Multiplicative interaction and sensitivity analyses were also conducted. The relationship between blood lipids and neurological biomarkers was explored using Spearman's analysis.

RESULTS

PC1, primarily reflecting levels of Apolipoprotein B (ApoB), cholesterol, and low-density lipoprotein cholesterol (LDL-C), showed a protective effect against depression, with HRs of 0.98 (95 % CI: 0.96,1.00) in the fully adjusted Cox regression model. In contrast, PC2, characterized by opposite loadings for triglycerides and high-density lipoprotein cholesterol (HDLC), was positively associated with the risk of depression and bipolar disorder.(HR = 1.03,95 % CI: 1.01,1.06; HR = 1.11, 95 % CI: 1.01,1.23). Increased PC2 level was related to a significant increase in bipolar disorder risk among participants with high genetic risk (genetic risk score > 90 %, HR = 1.22, 95 % CI: 1.02,1.46). Complicated correlations between blood lipids and serum neuroproteins were detected.

CONCLUSION

These findings suggest complex associations between blood lipid profiles and the risk of depression and bipolar disorder.

An Increase of Adropin Can Predict Depression Improvement

Objectives Depression is characterized by a lack of energy, social withdrawal, and fatigue, and it is also associated with increased inflammation in the brain. Some studies suggest that adropin may have anti-inflammatory effects and could reduce the inflammatory processes contributing to depression.

METHODS

We included 54 newly diagnosed patients experiencing their first episode of depression and 56 healthy volunteers in this study. The participants with depression were divided into three subgroups based on DSM-5 and BDI-II criteria. The focus of the study was to compare adropin levels between depressive patients and healthy volunteers, as well as to monitor changes in adropin levels after six months of treatment for depressive patients.

RESULTS

Initial measurements showed no significant differences in standard laboratory parameters or adropin levels between the depression and control groups. However, adropin and vitamin D levels increased in the group of depressive patients during the six-month follow-up.

CONCLUSIONS

Our research indicates that adropin plays a significant role in the development of depression and may influence the effectiveness of depression treatments.

Neurometabolite Changes After Transcranial Photobiomodulation in Major Depressive Disorder: A Randomized Controlled Trial Investigating Dose-Dependent Effects

Background: Transcranial photobiomodulation (t-PBM) is a promising non-invasive therapy for Major Depressive Disorder (MDD). MDD is associated with altered brain metabolism, including changes in N-acetylaspartate (NAA), choline (Cho), and creatine (Cr). This study assessed the effects of varying t-PBM doses on neurometabolite levels in the dorsolateral prefrontal cortex (dlPFC) and their correlations with clinical outcomes. Methods: In this randomized, sham-controlled, cross-over study, 33 adults with MDD received one session of t-PBM at low, medium, and high doses and a sham treatment. Proton magnetic resonance spectroscopy (1H-MRS) measured NAA, Cho, and Cr pre- and post-treatment. Clinical outcomes were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Symptoms of Depression Questionnaire (SDQ). Statistical analyses included paired t-tests or Wilcoxon signed-rank tests for neurometabolite changes, and linear mixed-effects regression models for t-PBM dose, neurometabolites, and time effects. Results: NAA levels increased significantly (7.52 ± 0.777 to 8.12 ± 1.05 mmol/L for one session; 7.36 ± 0.85 to 7.85 ± 0.68 mmol/L across all sessions); however, these changes were not associated with specific t-PBM doses or sham. No significant changes were observed for Cho and Cr levels. Positive correlations were found between Cho levels and MADRS scores (r = 0.59, p = 0.017), and negative correlations between Cr levels and SDQ scores at the medium dose (r = -0.91, p = 0.011). Conclusions: While NAA levels increased, and correlations between neurometabolites and clinical outcomes were observed, these findings do not suggest a specific effect of t-PBM. Larger randomized controlled trials with optimized dosing protocols, extended follow-up, and advanced spectroscopy are needed to clarify the neurometabolic therapeutic potential of t-PBM in MDD.

Effects of Ninjin'yoeito and physical exercise on serum corticosterone and hippocampal BDNF/proBDNF and neuroinflammation in post-stroke depression in rats

BACKGROUND

Ninjin'yoeito (NYT), a traditional Japanese Kampo medicine, improves the depression and anxiety in humans and animals, rendering it a novel therapeutic option for post-stroke depression (PSD). Furthermore, physical exercise is an important nonpharmacological therapy for major depressive disorder. The components of NYT or exercise exert antidepressant effects through the increased expression of neurotrophic factors and reduced neuroinflammation in the brain. However, the mechanisms underlying the antidepressant effects of NYT and exercise in PSD remain unclear. Therefore, we examined the effects of NYT and physical exercise in a rat model of PSD.

METHODS

Rats were divided into five groups: PSD, PSD with NYT, PSD with exercise (Ex), PSD with NYT and exercise (NYT + Ex), and control (sham). PSD was induced by the microinjection of endothelin-1 into the left medial prefrontal cortex and chronic unpredictable mild stress 3 days per week. A diet containing 3% NYT was administered to rats one day after stroke induction. Exercise was conducted using a motorized treadmill for three days per week, starting three days after the stroke. The therapeutic interventions lasted for four weeks. Serum corticosterone levels, depression-like behavior, and hippocampal pathophysiology, including the expression of brain-derived neurotrophic factor (BDNF), precursor BDNF (proBDNF), doublecortin (DCX), NeuN, glial cell activation, and tumor necrosis factor-α (TNF-α), were examined.

RESULTS

Serum corticosterone levels were lower in the treatment group than those in the PSD group. Notably, serum corticosterone levels were significantly lower in the NYT group than those in the PSD group. BDNF expression in the CA1 region was significantly higher in the Ex group than that in the PSD group. The NYT + Ex group showed a significantly higher hippocampal BDNF/proBDNF ratio than the other groups. DCX and NeuN expression levels were significantly higher in the NYT + Ex group than those in the NYT and PSD groups. Hippocampal glial cell activation and TNF-α expression increased in the PSD group and decreased in the intervention groups.

CONCLUSIONS

NYT ameliorates serum corticosterone levels and hippocampal neuroinflammation in PSD. Additionally, this study suggested that NYT, together with exercise therapy, may improve neurogenesis, the BDNF/proBDNF ratio, and neuroinflammation in the hippocampus in PSD.

CLINICAL TRIAL NUMBER

Not applicable.

Neuroimaging correlates of psychological resilience: an Open Science systematic review and meta-analysis

Introduction

While risk factors have been identified for numerous psychiatric disorders, many individuals exposed to these risk factors do not develop psychopathology. A growing neuroimaging literature has sought to find structural and functional brain features that confer psychological resilience against developing psychiatric disorders.

Methods

We conducted a systematic review and meta-analysis of neuroimaging studies associated with psychological resilience. Searches of Pubmed, Embase, Web of Science and PsychInfo yielded 2,658 potentially relevant articles published 2000-2021. Of these, we identified 154 human neuroimaging articles which provided anatomical coordinates of regions promoting resilience against psychiatric disorders including PTSD (44% of articles), schizophrenia (18%), major depressive disorder (14%) and bipolar disorder (12%).

Results

Meta-analysis conducted in GingerALE identified three regions as promoting psychological resilience across disorders (cluster-level FWE p < 0.05): left amygdala, right amygdala, and anterior cingulate.

Discussion

We additionally introduce a novel framework for conducting systematic reviews and meta-analyses that is compliant with best practices of Open Science: our publicly viewable systematic review was curated and annotated using the open-source reference manager Zotero, with customizable Python scripts for extracting curated data for meta-analyses. Our methodological pipeline not only permits independent replication of our findings but also supports customization for future neuroimaging meta-analyses.

Machine learning approaches for classifying major depressive disorder using biological and neuropsychological markers: A meta-analysis

Traditional diagnostic methods for major depressive disorder (MDD), which rely on subjective assessments, may compromise diagnostic accuracy. In contrast, machine learning models have the potential to classify and diagnose MDD more effectively, reducing the risk of misdiagnosis associated with conventional methods. The aim of this meta-analysis is to evaluate the overall classification accuracy of machine learning models in MDD and examine the effects of machine learning algorithms, biomarkers, diagnostic comparison groups, validation procedures, and participant age on classification performance. As of September 2024, a total of 176 studies were ultimately included in the meta-analysis, encompassing a total of 60,926 participants. A random-effects model was applied to analyze the extracted data, resulting in an overall classification accuracy of 0.825 (95 % CI [0.810; 0.839]). Convolutional neural networks significantly outperformed support vector machines (SVM) when using electroencephalography and magnetoencephalography data. Additionally, SVM demonstrated significantly better performance with functional magnetic resonance imaging data compared to graph neural networks and gaussian process classification. The sample size was negatively correlated to classification accuracy. Furthermore, evidence of publication bias was also detected. Therefore, while this study indicates that machine learning models show high accuracy in distinguishing MDD from healthy controls and other psychiatric disorders, further research is required before these findings can be generalized to large-scale clinical practice.

Differences in baseline and dynamic plasma/saliva endocrine and linear/non-linear heart measures between patients with major depression and closely-matched healthy subjects: A 3-day combined overnight dexamethasone/metyrapone challenge study

BACKGROUND

Major depressive disorder (MDD) has been consistently associated with hypothalamic-pituitary-adrenal (HPA)-axis and autonomic nervous system (ANS) (re-)activity abnormalities, however, often with conflicting results.

METHODS

This study offers a concurrent multi-measure assessment of both HPA-axis and ANS activity and reactivity over 3 days to better characterize baseline and dynamic neuroendocrine alterations in MDD accounting for multiple individual factors. We therefore investigated group differences between 20 unmedicated MDD patients and 20 carefully-matched healthy controls (HC) by simultaneously assessing morning plasma (CORT, ACTH, copeptin) and awakening response saliva (CORT, DHEA, DHEA-s) endocrine measures, as well as multiple linear and non-linear measures of resting heart rate (HR) and its variability (HRV), before (baseline, day 1) and after a successive overnight metyrapone (HPA-axis stimulation, day 2) and dexamethasone (HPA-axis suppression, day 3) pharmaco-endocrine challenge, controlling for childhood trauma (CT) history.

RESULTS

Statistically significant group differences emerged only for baseline plasma CORT and ACTH levels (MDD > HC) and resting HR in all 3 days. No differences were found in dynamic plasma levels and all saliva endocrine measures, as well as all HRV measures. Baseline HR was the only significant predictor for MDD diagnosis.

CONCLUSIONS

Our detailed baseline and dynamic neuroendocrine comparison using closely matched HC indicates fewer neuroendocrine alterations in MDD than expected. These results challenge prior findings and support the importance of exact matching when investigating neuroendocrine biomarkers, as previously reported findings may rely on unaccounted individual but not group differences.

Anxiety, depressive and insomnia symptoms among patients with depression: a network perspective

BACKGROUND

The aim of this study was to utilize network analysis to explore the interconnections among anxiety, depressive, and insomnia symptoms in depressed patients in China.

METHODS

The study included two surveys, the baseline survey was conducted from May 18, 2020 to June 18, 2020, and the follow-up survey was conducted 5 months later. A total of 4476 patients completed the baseline survey, and 1877 of them completed the follow-up survey. Depression symptoms were evaluated using the 9-item Patient Health Questionnaire-9 (PHQ-9), anxiety symptoms were evaluated using the 7-item Generalized Anxiety Disorder (GAD-7), and insomnia symptoms were evaluated using the 7-item Insomnia Severity Index (ISI). The centrality indices are utilized in the network analysis, and using Network Comparison Test (NCT) to evaluate the differences between the network structures at two different time points.

RESULTS

Network analysis revealed that the central symptom value was ISI5 ("Interfere with your daily functioning") in the baseline networks and ISI4 ("Worried/distressed") in the follow-up networks, the symptom with the bridge symptom value in both networks was PHQ9-3 ("Sleep"). The NCT results revealed no significant differences in edge weights and global strength among participants who completed both baseline and follow-up surveys.

CONCLUSIONS

Our results suggest that central symptom (e.g., "Interfere with your daily functioning","Worried/distressed") and bridge symptom PHQ9-3 ("Sleep") can be prioritized as a target for intervention and treatment in patients with depression.

Altered proteomics in brain extracellular vesicles from depressed individuals who died by suicide implicates synaptic processes

BACKGROUND

Major depressive disorder (MDD) is a common and debilitating disorder whose molecular neurobiology remains unclear. Extracellular vesicles (EVs) are small vesicles that are released by cells and are involved in intercellular communication. They carry bioactive molecules, such as proteins, that reflect the state of their cell of origin. In this study, we sought to investigate the proteomic cargo of brain EVs from depressed individuals as compared to EVs from matched neurotypical individuals. In addition, we investigated how the EV proteomic cargo compares to the proteomic profile of bulk tissue.

METHODS

Using mass spectrometry and label-free quantification, we investigated the EV and bulk tissue protein profile from anterior cingulate cortex samples from 86 individuals. We performed differential expression analysis to compare cases and controls, followed by in silico analysis to determine potential implicated functions of dysregulated proteins.

RESULTS

Extracellular vesicles display distinct proteomic profiles compared to bulk tissue. Differential expression analysis showed that 70 proteins were differentially packaged in EVs in MDD, while there was no significant difference in protein levels between groups in bulk tissue. In silico analysis points to a strong role of these differential EV proteins in synaptic functions.

CONCLUSION

To our knowledge, this is the first study to profile EV proteins in depression, providing novel information to better understand the pathophysiology of MDD. This work paves the way for discovering new therapeutic targets for MDD and prompts more investigations into EVs in MDD and other psychiatric disorders.

Stress Accelerates Depressive-Like Behavior through Increase of SPNS2 Expression in Tg2576 Mice

To investigate the relationship between depression and AD, water avoidance stress (WAS) was induced for 10 days in both Tg2576 mice and wild-type (WT) mice. After WAS, memory function and depressive-like behavior were investigated in Tg2576 mice. Tg2576 WAS mice exhibited more depressive-like behaviors than WT WAS and Tg2576 control (CON) mice. Strikingly, Tg2576 CON mice showed more depressive-like behaviors than WT mice. Moreover, corticosterone and phospho-glucocorticoid receptor (p-GR) levels were also higher in Tg2576 WAS mice in comparison to Tg2576 CON mice. Spinster homologue 2 (SPNS2) is a member of non-ATP-dependent transporter. The role of SPNS2 was widely known as a sphingosine-1-phosphate (S1P) transporter, which export intracellular S1P from cells. Using GEO database to analyze SPNS2 gene expression changes in patients with AD and depression, we show that SPNS2 gene expression correlates with AD and depression. Interestingly, Tg2576 WAS mice displayed significantly increased levels of SPNS2 w1hen compared to Tg2576 CON counterparts. SPNS2 levels were also higher in Tg2576 CON mice in comparison with WT CON mice. Remarkably, we found a decrease in S1P brain levels and an increase in S1P serum levels of Tg2576 WAS mice in comparison with Tg2576 CON mice. Accordingly, WAS induced group further decreased S1P levels in the brains. However, the level in the serum further increased in comparison with non-induced group. Therefore, these results suggest that AD and depression could be associated, and that Tg2576 transgenic mice are more susceptible to stress-induced depression through the release of S1P by SPNS2 up-regulation.

11,12-Diacetyl-Carnosol Ameliorates Depression-Like Behaviors and Memory Dysfunction in CUMS Mouse Model via Inhibiting HMGB1-Mediated Neuroinflammation

BACKGROUNDS

11,12-Diacetyl-carnosol (DACA), a derivative of carnosol, exhibits significant anti-inflammatory and antioxidant properties. However, its antidepressant effects and underlying mechanisms remain unclear. High mobility group box 1 protein (HMGB1)-mediated inflammatory responses and associated neurofunctional impairments play a crucial role in the pathogenesis of depression. This study aimed to investigate whether DACA exerts anti-inflammatory and antidepressant effects and whether its mechanisms involve the HMGB1/NF-κB/NLRP3 signaling pathway.

METHODS

(1) A depression model was established in mice through 6 weeks of chronic unpredictable mild stress (CUMS). From the 4th week of stimulation, the treatment group received DACA for 3 weeks. (2) BV2 cells were stimulated with LPS+ATP, and the treatment group was cultured in DACA medium for 24 h. (3) Supernatants from BV2 cells were used to culture primary neurons. To confirm the critical role of HMGB1 in DACA's antidepressant effects, CUMS-stressed mice were treated with glycyrrhizin (GZA) or the DACA+GZA combination. Depressive-like behaviors were evaluated using the sucrose preference test (SPT), open field test (OFT), tail suspension test (TST), forced swim test (FST), and Morris water maze (MWM). Hippocampal microglial cell and primary neuron morphology were assessed by immunofluorescence, and dendritic spine density in hippocampal neurons was examined using Golgi staining. IL-6 and TNF-α concentrations in mouse serum and BV2 supernatant were measured by ELISA. Western blotting was used to detect protein expressions of HMGB1, NF-κB p65, p-NF-κB p65, NLRP3, and IL-1β in the hippocampus and BV2 cells.

RESULTS

CUMS-exposed mice showed decreased sucrose preference, increased immobility in TST and FST, prolonged escape latency in MWM, and reduced crossings. Microglial activation and upregulation of HMGB1, NF-κB p65, p-NF-κB p65, NLRP3, and IL-1β were observed in both CUMS-stressed mice and LPS+ATP-induced BV2 cells, with reduced dendritic spine density in the hippocampus. DACA significantly reversed these phenomena. The effects of DACA were comparable to those of GZA treatment, and no changes were observed with the DACA+GZA combination.

CONCLUSION

The HMGB1/NF-κB/NLRP3 signaling pathway is involved in DACA's therapeutic effects on depression.

Azetukalner, a Novel KV7 Potassium Channel Opener, in Adults With Major Depressive Disorder: A Randomized Clinical Trial

Importance

Available antidepressants provide inadequate therapeutic responses in many patients with major depressive disorder (MDD), highlighting a substantial unmet need.

Objective

To evaluate the efficacy and safety of azetukalner, a novel, potent KV7 potassium channel opener, in participants with MDD.

Design, Setting, and Participants

X-NOVA was a multicenter, proof-of-concept, phase 2, randomized, double-blind, parallel-group, placebo-controlled clinical trial that evaluated azetukalner in participants (adults aged ≥18 to ≤65 years) with moderate to severe MDD in a current depressive episode. Participants were enrolled between April 2022 and October 2023, and data analysis occurred from January 2023 to January 2024.

Intervention

Participants were randomized (1:1:1) to 10 mg of azetukalner, 20 mg of azetukalner, or placebo orally once daily with food for 6 weeks, with a 4-week follow-up. Concomitant antidepressant medications were not permitted.

Main Outcomes and Measures

The primary efficacy end point was change in Montgomery-Åsberg Depression Rating Scale (MADRS) score at week 6. Secondary end points included change from baseline at week 6 in the Snaith-Hamilton Pleasure Scale (SHAPS) and Beck Anxiety Inventory. Exploratory end points included change in the Hamilton Depression Rating Scale, 17-Item (HAM-D17) score and change in MADRS at week 1. Frequency and severity of treatment-emergent adverse events (TEAEs) were recorded.

Results

Altogether, 168 participants were randomized (56 to placebo, 56 to 10 mg of azetukalner, and 56 to 20 mg of azetukalner); mean (SD) age was 47.2 (13.6) years, and 111 participants (66.5%) were female. The modified intent-to-treat and safety populations consisted of 164 and 167 participants, respectively. The mean (SE) reduction in MADRS scores from baseline to week 6 was -13.90 (1.41) points with placebo, -15.61 (1.34) points with 10 mg of azetukalner, and -16.94 (1.45) points with 20 mg of azetukalner; the mean (SE) reduction with 20 mg of azetukalner vs placebo was clinically meaningful but not statistically significant (-3.04 points; 95% CI, -7.04 to 0.96 points; P = .14) at week 6, while significant at week 1 (-2.66 points; 95% CI, -5.30 to -0.03 points; P = .047). The mean (SE) reduction in HAM-D17 from baseline to week 6 was significantly greater with 20 mg of azetukalner vs placebo (-13.3 [1.1] vs -10.2 [1.0] points; P = .04). The mean (SE) reduction in SHAPS scores from baseline to week 6 was significantly greater with 20 mg of azetukalner vs placebo (-7.77 [0.87] vs -5.30 [0.85] points; P = .046). Similar rates of discontinuation due to TEAEs were reported across groups.

Conclusions and Relevance

In this randomized clinical trial of azetukalner, preliminary findings supported its further clinical development for the treatment of MDD and anhedonia.

Trial Registration

ClinicalTrials.gov Identifier: NCT05376150.

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning

BACKGROUND

Early diagnosis of depression is crucial, and speech-based early diagnosis of depression is promising, but insufficient data and lack of theoretical support make it difficult to be applied. Therefore, it is valuable to combine psychiatric theories, collect speech recognition data for depression, and develop a practicable recognition method for depression.

METHODS

In this study, 24 patients with major depressive disorders (MDDs) and 36 healthy controls (HCs) were recruited to participate in a multi-task speech experiment. Descriptive statistics and tests of variance were used to analyze subjects' personality and speech changes. Subsequently, the speech task with the most depressive cues was explored using the Bidirectional Long - Short Term Memory (Bi-LSTM) algorithm, on which a personality-assisted multitasking deep model, i.e., multi-task attentional temporal convolutional network model (TCN-MTA).

RESULTS

Statistical analyses of speech duration showed that the fable reading, neutral stimulus, and negative stimulus tasks had significant differences on subjects' speech duration, and the negative stimulus task had significant differences between the depressed and control groups (p < 0.001, 0.03, 0.04). Notably, the Big Five personality emotional stability scores were significantly different between the depressed and control groups (0.03). Depression was best identified using Bi-LSTM in negative (Youden index = 0.44) and positive stimulus speech (Youden index = 0.42). Further, the specificity of 0.72 and sensitivity of 0.87 for recognizing depression in negative stimulus speech using our proposed TCN-MTA outperforms existing methods.

LIMITATIONS

The sample size enrolled in this study is higher than the minimum sample size calculated through G-Power 3.1, but the sample size in this study is still small.

CONCLUSION

The proposed deep learning-based personality-assisted multitasking method could accurately recognize major depression, which demonstrated the potential of the method based on the fusion of specialized theories and artificial intelligence.

Emotion regulation repertoires predict the risk of major depressive disorder

BACKGROUND

Few studies explored emotion regulation (ER) repertoires (the tendency to utilize multiple ER strategies in different contexts) in patients with major depressive disorder (MDD). It remains unclear to what extent ER repertoires can assess the risk of MDD and other psychiatric disorders.

METHOD

Three subsamples including 1397 non-clinical individuals, 135 MDD patients, and 127 healthy controls (HCs) were combined to explore ER repertoires. We further built classifiers of ER repertoires to distinguish MDD patients from HCs, and additionally examined its performance based on published studies (total N = 4918).

RESULTS

Adaptive, average, maladaptive, and intensely maladaptive repertoires were identified. The classifier based on ER repertoires effectively distinguished MDD patients from HCs, demonstrating an AUC of 0.803 (SD = 0.067). Additionally, the classifier exhibited discriminatory power for various psychopathologies in published studies, including depression, anxiety, eating disorders, PTSD, and personality disorders (AUC: 0.616-0.779).

LIMITATIONS

Future studies should investigate the longitudinal influence of ER repertoires on the development of psychopathologies.

CONCLUSIONS

Our findings suggest that an individual's ER repertoire is a critical psychopathological risk that can serve as a valuable indicator for assessing risk and imply the potential utility of reforming ER repertoire.

Peripheral protein inflammatory biomarkers in bipolar disorder and major depressive disorder: A systematic review and meta-analysis

OBJECTIVES

Bipolar disorder (BD) and major depressive disorder (MDD) are mood disorders. The most frequent clinical presentation of BD and MDD is depression, which contributes to high rates of misdiagnosis between disorders. To support diagnostic discrimination and therapeutic stratification, we aim to perform a systematic review and meta-analysis evaluating peripheral protein inflammatory biomarkers between BD and MDD, with a focus on the depressive state.

METHODS

We conducted a literature search on PubMed, PsycInfo and Embase with no year/language restrictions. Original studies including human participants with a BD or MDD diagnosis which directly compared levels of peripheral protein inflammatory biomarkers between groups were included. A random effects meta-analysis was performed.

RESULTS

35 studies were included in the systematic review. 9 studies were included in the meta-analysis. The meta-analysis showed IL-7 (p < 0.01) levels were significantly decreased in BD, and IL-9 (p < 0.01), CCL3 (p = 0.03), CCL4 (p = 0.01), CCL5 (p = 0.02) and CCL11 (p = 0.04) levels were significantly increased in BD.

LIMITATIONS

High heterogeneity and limited dataset size restricted our meta-analysis to a small subset of biomarkers and limited our exploration of the effects of moderator variables.

CONCLUSION

This study found differences in IL-7, IL-9, CCL3, CCL4, CCL5 and CCL11 between BD and MDD in a depressive state. These findings support the notion that inflammation is associated with mood disorder pathophysiology, particularly with respect to T-cell network dysregulation. Further studies can assist in better understanding differences between disorders and work towards clinical applications.

Cross-cultural adaptation and psychometric evaluation of the urdu version of the morisky, greene, and levine medication adherence scale (MGLS-4) for major depressive disorder patients

In Pakistan, Major depressive disorder (MDD) contributes significantly to the mental health burden. It is crucial to understand patients' medication adherence status for developing a strategy for improving adherence and treatment outcomes. Therefore, a valid and reliable tool in the local Urdu language is required. The Morisky, Greene, and Levine Medication Adherence Scale (MGLS-4) is a reliable, valid and straightforward instrument to assess medication-taking behavior. The valid and reliable Urdu translation of MGLS-4 can fill this gap within the local context. Therefore, the present study aims to validate the Urdu Morisky, Green and Levine Adherence Scale (UMGLS-4) for MDD patients. This was a quantitative, cross-sectional validation study for Pakistani MDD patients. Reliability was measured using Cronbach's α and for test-retest reliability intraclass correlation coefficient (ICC) was calculated. Validity was assessed through face validity, content validity, construct validity, and convergent validity with the Drug Attitude Inventory (DAI-10). Descriptive and inferential statistical analyses were carried out to demonstrate adherence level and statistical significance, respectively. Linear regression was applied to find the association between the UGMLS-4 score and demographic characteristics. The UMGLS-4 demonstrated high reliability (Cronbach's α = 0.829) and a significant strong ICC (x = 0.601, p < 0.01) was detected. Exploratory factor analysis (EFA) revealed a single-factor structure explaining 66.084% of the variance. Confirmatory factor analysis (CFA) confirmed good model fit (GFI = 0.950, AGFI = 0.920, NFI = 0.930, RMSEA = 0.050, SRMSR = 0.055). Medication adherence was observed to be high in 39.1% of patients, moderate in 28.6%, and poor in 32.3%. Significant associations were found between adherence scores and gender, educational attainment, and occupational status (p < 0.005) with education predicting adherence (B = 0.301, p < 0.000), indicating the scale's robustness in detecting adherence variations among Urdu-speaking MDD patients. The UMGLS-4 is a reliable and valid tool for assessing medication adherence in Pakistani MDD patients, effectively capturing adherence variations across demographic variables.

The occurrence of and risk factors for depressive symptomatology in myocarditis survivors: a cross-sectional survey-based study using machine learning

Background

The frequency and impact of depressive symptoms in myocarditis survivors are poorly understood.

Objectives

We conducted a cross-sectional study to identify risk factors and the relative importance of each for predicting clinically significant depressive symptomatology in myocarditis survivors.

Methods

Participants completed an electronic survey assessing sociodemographic, general health, and myocarditis-related variables, as well as self-reported cardiac symptoms and personal and family mental health history. Participants also completed the Center for Epidemiologic Studies Depression Scale (CES-D), Beck Anxiety Inventory (BAI), revised Impact of Events Scale (IES-R), and other validated measures of social support, quality of life, resiliency, childhood adversity, treatment distress, and somatic symptom burden. Clinically significant depressive symptomatology was defined as a CES-D total score ≥ 16. We used supervised machine learning to examine which and how well psychosocial and other types of variables predicted clinically significant depressive symptomatology in myocarditis survivors. Finally, we calculated the variable importance for each variable from the trained models and examined the rank ordering of predictors.

Results

Ninety-six of 113 respondents (85.0%) with complete survey data were included in the analyses. Forty-three (44.8%) respondents had clinically significant depressive symptomatology. When predicting depressive symptomatology, random forests achieved a mean AUC of 0.91 (95% CI 0.87-0.95) and a significantly higher accuracy than that of the null information rate (0.84 vs 0.55, p < 0.005), with correspondingly high sensitivity (0.84) and specificity (0.85). Emotional wellbeing, quality of life, history of depression, anxiety, and resilience were the top predictors in variable importance analyses, ahead of self-reported cardiovascular symptoms, other myocarditis-related variables, and family history of depression.

Conclusions

Myocarditis survivors are at high risk for clinically significant depressive symptomatology. Psychosocial factors that are measurable in routine practice may be more predictive of significant depressive symptomatology than demographics, family history, or self-reported cardiovascular symptoms.

Repetitive transcranial magnetic stimulation: an effective treatment for resistant depressive episodes in the elderly

OBJECTIVES

To evaluate the effectiveness of repetitive transcranial magnetic stimulation (rTMS) in older (≥60 years) versus younger (<60 years) patients with treatment-resistant depression (TRD), and to determine whether age affects clinical outcomes in a naturalistic clinical setting.

METHOD

A retrospective analysis was conducted on 272 patients with TRD treated with rTMS at a tertiary psychiatric hospital. Depression severity was assessed at baseline, end-of-treatment (V1), and one-month follow-up (V2) using the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Beck Depression Inventory (BDI). Response (≥50% MADRS reduction) and remission (MADRS ≤10) rates were calculated. Repeated measures ANOVA and logistic regression were used to examine the influence of age and treatment protocol.

RESULTS

Both age groups showed significant improvement in depressive symptoms. Older adults had higher remission rates at V1 (36% vs. 23%, p = 0.033), although this difference was no longer significant at V2. No interaction between age and protocol was observed. Female sex was the only significant predictor of remission at V2 (OR = 14.25, p = 0.021). Sensitivity analyses treating age as a continuous variable yielded consistent findings.

CONCLUSION

rTMS is an effective treatment for TRD in both older and younger adults. Older patients respond comparably to younger ones, challenging concerns about age-related reductions in neuromodulation efficacy. These findings support the use of rTMS in late-life depression without major protocol adjustments and underscore the need for future studies examining personalized treatment parameters and psychosocial moderators of response.

Effects of tianeptine on mTORC1-mediated neuronal autophagy in primary rat hippocampal neurons under nutrient deprivation

The aim of this study was to investigate the effects of the antidepressant tianeptine on the mechanistic target of rapamycin complex 1(mTORC1)-mediated autophagy pathway in primary hippocampal neurons exposed to B27-deprived conditions. When primary hippocampal neurons were treated with tianeptine at doses of 1, 10, 50, and 100 µM for 3 days under B27-deprived conditions, we observed that it activated autophagy and increased the formation of autophagosomes through the upregulation of autophagic proteins, including autophagy-activating kinase 1 (ULK1), Beclin 1, LC3B-II/I, and p62. And at a concentration of 100 µM tianeptine, the decrease in mTORC1 phosphorylation induced by B27 deprivation was significantly reversed. Changes in the expression of autophagic proteins induced by B27 deprivation were reversed by tianeptine treatment in a concentration-dependent manner, and tianeptine significantly reduced the increase in LC3B membrane number induced by B27 deprivation, an effect that was blocked by pretreatment with rapamycin. In conclusion, tianeptine attenuated the activity of mTORC1-mediated autophagy in primary rat hippocampal neurons under B27-deprived conditions. These results may suggest a novel mechanism by which tianeptine may affect autophagy in neurons.

Brain connectivity and transcriptional changes induced by rTMS in first-episode major depressive disorder

Repetitive transcranial magnetic stimulation (rTMS) is a widely utilized non-invasive brain stimulation technique with demonstrated efficacy in treating major depressive disorder (MDD). However, the mechanisms underlying its therapeutic effects, particularly in modulating neural connectivity and influencing gene expression, remain incompletely understood. In this study, we investigated the voxel-wise degree centrality (DC) induced by 10 Hz rTMS targeting the left dorsolateral prefrontal cortex, as well as their associations with transcriptomic data from the Allen Human Brain Atlas. The results indicated that the active treatment significantly reduced clinical symptoms and increased DC in the left superior medial frontal gyrus, left middle occipital gyrus, and right anterior cingulate cortex. Partial least squares regression analysis revealed that genes associated with DC alternations were enriched biological processes related to neural plasticity and synaptic connectivity. Furthermore, protein-protein interaction (PPI) analysis identified key hub genes, including SCN1A, SNAP25, and PVALB, whose expression levels were positively correlated with DC changes. Notably, SCN1A emerged as a significant predictor on DC changes. These findings suggest that rTMS may exert its therapeutic effects in MDD by modulating specific molecular pathways and neural networks, providing valuable insights into its mechanisms of action.

Neuroinflammation and stress-induced pathophysiology in major depressive disorder: mechanisms and therapeutic implications

Major depressive disorder (MDD) is one of the most common mental health conditions, characterized by pervasive and persistent low mood, low self-esteem, and a loss of interest or pleasure in activities that are typically enjoyable. Despite decades of research into the etiology and pathophysiological mechanisms of depression, the therapeutic outcomes for many individuals remain less than expected. A promising new area of research focuses on stress-induced neuroinflammatory processes, such as the excessive activation and crosstalk of microglia and astrocytes in the central nervous system under stress, as well as elevated levels of pro-inflammatory cytokines, which are closely linked to the onset and progression of depression. This review summarizes the mechanisms through which neuroinflammation induces or promotes the development of depression, and also highlights the effective roles of small molecules with anti-inflammatory activity in the treatment of MDD. Understanding the specific mechanisms through which stress-induced neuroinflammation further impacts depression, and using technologies such as single-cell RNA sequencing to elucidate the specific subtypes and interactions of microglia and astrocytes in depression, is of great importance for developing more effective therapeutic strategies for MDD.

Dissecting the genetic association between abnormal sperm parameters and depression: a transcriptome-wide analysis of 157 participants

PURPOSE

Depression often occurs in the males with semen abnormalities. Evidence suggested a genetic correlation between depression and the pathogenesis of abnormal sperm parameters, whereas the mechanisms remained unclear.

METHODS

Genomic datasets of major depressive disorder (MDD) and abnormal sperm parameters were obtained from the Gene Expression Omnibus database. After screening the datasets, differentially expressed genes (DEGs) were identified. GO and pathway enrichment analyses, a protein-protein interaction network, and receiver operator characteristic curve analysis were conducted. Then, MDD-related DEGs (MDRGs), the external validation, immunological, and translational regulation analysis were performed. Moreover, tissue expression of MDRGs was explored.

RESULTS

A total of 249 overlapped MDRGs were discovered in the MDD and abnormal sperm parameters gene sets. MDRGs had a tight relationship with adhesion-associated and PI3 K-Akt-associated biological signaling. The protein-protein interaction module showed the enriched pathways involved in neuron differentiation and cell adhesion. Drug prediction revealed ten pharmacologic candidates. Finally, two hub MDRGs were identified and validated with good diagnostic values. Immunological and translational results showed three closely correlated kinds of CD8 + T lymphocytes, neutrophils, and macrophages, 19 transcription factor-MDRGs, and 71 miRNA-MDRGs interactions. Furthermore, expression signatures of Carnosine Dipeptidase 2 (CNDP2) and Galectin 3 Binding Protein (LGALS3BP) were displayed in cortex and testis.

CONCLUSION

Our study discovered the genetic profiles in abnormal sperm parameters and MDD and elucidated enriched pathways and molecular associations between hub genes and immune infiltration. These findings provide novel insights into the common pathogenesis of both diseases as well as the potential biomarkers for MDD-associated abnormal sperm parameters.

The Effects of Psychosocial Risk Factors and Severity of Abuse on the Development of Depressive Symptoms in Sexually Abused Turkish Youth

Depression in sexually abused youth has a complex etiology involving various mechanisms related to adverse familial psychosocial factors and the severity of childhood sexual abuse (CSA). This study aimed to identify mediating mechanisms between CSA severity, adverse familial psychosocial factors and depressive symptoms in Turkish children and adolescents who have experienced sexual abuse. The files of 340 CSA cases, aged 6-18, who applied to the forensic outpatient clinic between 2014-2020 were retrospectively evaluated. Psychiatric diagnoses were made according to Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Depressive symptoms were evaluated through clinical examinations and Children's Depression Inventory (CDI). Sexual abuse severity was measured with the Sexual Abuse Severity Score (SASS) algorithm based on the information obtained from files. Both intrafamilial violence (IFV) (B = 2.67, 95%CI [0.56-4.77]) and chaotic family environment (CFE) (B = 2.57, 95%CI [0.43-4.72]) had significant effects on CDI scores under significant and full-mediating effects of verbal/physical coercion (B = 1.16, 95%CI [0.17-2.81] for IFV→CDI; B = 1.44, 95%CI [0.24-3.34] for CFE→CDI) and qualitative severity of sexual abuse (B = 0.91, 95%CI [0.17-2.06] for IFV→CDI; B = 1.04, 95%CI [0.14-2.44] for CFE→CDI). However, total SASS had no significant mediation in the relationship between adverse familial psychosocial factors and CDI scores. These findings provide evidence that both IFV and CFE appear to have significant associations with depressive symptoms, within the significant mediating roles of both verbal/physical coercion and qualitative severity of sexual abuse.

Efficacy and tolerability of antidepressants in individuals suffering from physical conditions and depressive disorders: network meta-analysis

BACKGROUND

Antidepressants are effective for depression, but most evidence excludes individuals with comorbid physical conditions.

AIMS

To assess antidepressants' efficacy and tolerability in individuals with depression and comorbid physical conditions.

METHODS

Systematic review and network meta-analysis of randomised controlled trials (RCTs). Co-primary outcomes were efficacy on depressive symptoms and tolerability (participants dropping out because of adverse events). Bias was assessed with the Cochrane Risk-of-Bias 2 tool and certainty of estimates with the Confidence in Network Meta-Analysis approach. A study protocol was registered in advance (https://osf.io/9cjhe/).

RESULTS

Of the 115 included RCTs, 104 contributed to efficacy (7714 participants) and 82 to tolerability (6083 participants). The mean age was 55.7 years and 51.9% of participants were female. Neurological and cardiocirculatory conditions were the most represented (26.1% and 18.3% of RCTs, respectively). The following antidepressants were more effective than placebo: imipramine, nortriptyline, amitriptyline, desipramine, sertraline, paroxetine, citalopram, fluoxetine, escitalopram, mianserin, mirtazapine and agomelatine, with standardised mean differences ranging from -1.01 (imipramine) to -0.34 (escitalopram). Sertraline and paroxetine were effective for the largest number of ICD-11 disease subgroups (four out of seven). In terms of tolerability, sertraline, imipramine and nortriptyline were less tolerated than placebo, with relative risks ranging from 1.47 (sertraline) to 3.41 (nortriptyline). For both outcomes, certainty of evidence was 'low' or 'very low' for most comparisons.

CONCLUSION

Antidepressants are effective in individuals with comorbid physical conditions, although tolerability is a relevant concern. Selective serotonin reuptake inhibitors (SSRIs) have the best benefit-risk profile, making them suitable as first-line treatments, while tricyclics are highly effective but less tolerated than SSRIs and placebo.

Improved recognition memory and reduced inflammation following β-caryophyllene treatment in the Wistar-Kyoto rodent model of treatment-resistant depression

Persistent low mood, anxiety and cognitive deficits are common symptoms of depression and highly efficacious treatments that address symptoms including cognitive dysfunction are still required. β-caryophyllene (BCP) is a terpene with anti-inflammatory and pro-cognitive properties; however, its efficacy on cognition in depression remains unclear. This study aimed to investigate acute and chronic BCP treatment effects on cognitive, depressive- and anxiety-like behaviours, and inflammation in male and female Wistar-Kyoto (WKY) rats, a rodent model of treatment-resistant depression. Rats were administered either BCP (50 mg/kg) or vehicle (control). Open field (OFT), social interaction, sucrose preference, novel object recognition (NOR) and elevated plus maze (EPM) tests were conducted after acute (1 h) and chronic (2 weeks) treatment. Peripheral plasma inflammatory cytokine levels were examined. BCP acutely increased locomotor activity in the OFT but did not improve social interaction, whereas chronic BCP prevented increased latency to first interaction in females (not males). BCP did not improve sucrose preference or prevent anxiety-like behaviours in the EPM. BCP significantly increased novel object discrimination in the NOR test in male and female WKY rats and reduced cytokine levels after chronic treatment. This study shows for the first time that chronic BCP treatment improved recognition memory and exerted anti-inflammatory properties in a rodent model of depressive-like behaviours. BCP did not significantly improve anxiety-like behaviours, social interaction or anhedonia in WKY rats of either sex. These findings demonstrate the pro-cognitive effects of BCP in a rodent model of treatment-resistant depression worthy of further investigation.

Atypical subcortical involvement in emotional face processing in major depressive disorder with and without comorbid social anxiety

Previous research on major depressive disorder (MDD) has largely focused on cognitive biases and abnormalities in cortico-limbic circuitry during emotional face processing. However, it remains unclear whether these abnormalities start at early perceptual stages via subcortical pathways and how comorbid social anxiety influences this process. Here, we investigated subcortical mechanisms in emotional face processing using a psychophysical method that measures monocular advantage (i.e., superior discrimination performance when two stimuli are presented to the same eye than to different eyes). Participants included clinical patients diagnosed with MDD (n = 32), patients with MDD comorbid with social anxiety (comorbid MDD-SAD, n = 32), and a control group of healthy participants (HC, n = 32). We assessed monocular advantage across different emotions (neutral, sad, angry) and among groups. Results indicated that individuals with MDD showed a stronger monocular advantage for sad expressions compared to neutral and angry expressions. In contrast, HC and comorbid MDD-SAD groups showed a greater monocular advantage for neural over negative expressions. Cross-group comparisons revealed that MDD group had a stronger monocular advantage for sad expressions than both HC and comorbid MDD-SAD groups. Additionally, self-reported depressive symptoms were positively correlated with monocular advantage for sad expressions, while social anxiety symptoms were negatively correlated with monocular advantage for negative expressions. These findings suggest atypical early perceptual processing of sadness in individuals with MDD via subcortical mechanisms, with comorbid social anxiety potentially counteracting this effect. This study may inform novel interventions targeting sensory processing and expand beyond cognitive bias modification.

Hospitalizations for depressive disorders in Ecuador: An eight-year nationwide analysis of trends and demographic insights

BACKGROUND

Sociodemographic characteristics and limited mental health care access may contribute to higher depression rates in low- and middle-income countries. This study aimed to analyze nationwide depressive disorder hospitalizations in Ecuador.

METHODS

We assessed the sociodemographic characteristics, severity, recurrence, and duration of hospitalizations for depressive disorders. The dataset used is publicly available on the Ecuadorian National Institute of Statistics and Censuses website. Multivariable multinomial logistic regression was performed to calculate adjusted relative risk ratios (aRRR).

RESULTS

14,586 hospitalizations were analyzed during 2015-2022. There was a significant increase in depressive disorders hospitalizations, from 9.41 cases per 100,000 inhabitants in 2015 to 13.9 in 2022. Females accounted for 65.7 % of hospital admissions. Depressive disorder hospitalizations had a mean age of 33.43 years. Severe depressive disorders without psychotic symptoms had the highest average hospitalization rate during 2015-2022 with 3.53 cases per 100,000 inhabitants. Individuals aged 20-29 years (aRRR 1.68, 95 % CI 1.27-2.22) and those aged 30-39 years (aRRR 1.81, 95 % CI 1.32-2.47) had higher probabilities of hospitalization for severe depressive disorder without psychotic symptoms. Patients with severe depression with or without psychotic symptoms were more likely of being hospitalized for seven or more days. Ethnic minorities were less likely to be hospitalized for severe depressive disorder without psychotic symptoms.

CONCLUSION

These findings highlight the increasing rates of depressive disorders in low- and middle-income countries such as Ecuador and emphasize the necessity for public health strategies focused on vulnerable groups.

Association of the GRIK4 rs1954787 polymorphism with clinical response in antidepressant-treated depressed patients: results from a prospective cohort and meta-analysis

Major Depressive Disorder (MDD) is the leading cause of disability worldwide. Genetic factors influence the effect of its main treatment option, antidepressant drugs (ATD). The GRIK4 rs1954787(T>C) genetic polymorphism was associated with response following 1-3 months of ATD treatment in some studies, but not others. We aimed to analyze its association with clinical outcomes in a cohort of 6-month ATD-treated patients and meta-analysis. Clinical data were obtained at baseline and after 1 (M1), 3 (M3), and 6 (M6) months of ATD treatment in 390 patients of the METADAP cohort. Mixed-effects models were used to assess the association of the GRIK4 rs1954787 polymorphism with the Hamilton Depression Rating Scale (HDRS) score and response and remission rates across time. Meta-analyses of ATD treatment response were performed with previously meta-analyzed data and METADAP. Compared to C allele carriers at M3 (n = 200), TT homozygotes at M3 (n = 66) had higher HDRS scores (coef = 3.37, 95% CI [1.30-5.54], Padj = 0.0046) and lower remission rates (OR = 0.36, 95% CI [0.16-0.76], Padj = 0.029). At M6, greater differences between TT homozygotes (n = 53) and C allele carriers (n = 152) were observed for HDRS scores (coef = 4.68, 95% CI [2.17-7.18], Padj = 0.00091) and remission rates (OR = 0.26, 95% CI [0.12-0.54], Padj = 0.0016). Meta-analyses of response were significant when comparing C vs T alleles (OR = 1.31, 95% CI [1.06-1.62], P = 0.014) and CC vs TT genotypes (OR = 1.63, 95% CI [1.10-2.38], P = 0.019). Altogether, our results support an association of the GRIK4 rs1954787(T>C) polymorphism with clinical improvement following ATD treatment. This association should be further assessed in other longitudinal studies. Its position within the glutamatergic system may help in understanding the mechanism of ATD action.

Genetic correlation, pleiotropic loci and shared risk genes between major depressive disorder and gastrointestinal tract disorders

BACKGROUND

Major depressive disorder (MDD) is associated with gastrointestinal tract (GIT) disorders, while genetic correlation, pleiotropic loci and shared risk genes remain to be explored.

METHODS

Leveraging genome-wide association study statistics for MDD (n = 170,756), peptic ulcer disease (PUD; n = 16,666), gastroesophageal reflux disease (GORD; n = 54,854), PUD and/or GORD and/or medications (PGM; n = 90,175), irritable bowel syndrome (IBS; n = 28,518), and inflammatory bowel disease (IBD; n = 7045), we determined global and local genetic correlations, identified pleiotropic loci, performed gene-level evaluations, and inferred causal associations using bidirectional Mendelian randomization.

RESULTS

We found global correlation of MDD with PUD (rg = 0.444, P = 3.135 × 10-24), GORD (rg = 0.459, P = 2.568 × 10-65), PGM (rg = 0.498, P = 6.094 × 10-114), IBS (rg = 0.621, P = 2.483 × 10-63), and IBD (rg = 0.171, P = 1.824 × 10-5). We identified 12 locally correlated regions between MDD and GIT disorders except for IBD, and one shared region (chr11:111985737-113,103,996) for PGM, GORD, and IBS. We found one pleiotropic locus for PUD, 12 for GORD, 30 for PGM, eight for IBS, and seven for IBD, and five shared loci (rs138786869, rs2284189, rs3130063, rs35789010, rs7568369) for GORD and PGM. We respectively observed 14 and 20 overlapping genes for MDD-GORD and MDD-PGM. We showed genetic liabilities to GORD, PGM, and IBS causally increase MDD risk, while all reverse causalities are significant.

CONCLUSIONS

Our work identifies genetic architectures shared between MDD and GIT disorders, contributes genetic insights to understand depression in the context of gut-brain interactions, and provides potential targets to treat gastrointestinal symptoms in depressive patients.

Ghrelin in Depression: A Promising Therapeutic Target

Depression is a widespread disease affecting over 300 million individuals of various ethnicities and socioeconomic backgrounds globally. It frequently strikes early in life and becomes a chronic or recurring lifelong illness. Out of the various hypotheses for the pathophysiology of depression, the gut-brain axis and stress hypothesis are the ones that need to be researched, as psychological stress impairs one or more pathways of the brain-gut axis and is likely to cause brain-gut axis dysfunction and depression. A dysfunctional reciprocal gut-brain relationship may contribute to many diseases, including inflammatory disorders, abnormal stress responses, impaired behavior, and metabolic changes. The hormone ghrelin is a topic of interest concerning the gut-brain axis as it interacts with the gut-brain axis indirectly via the central nervous system or via crossing the blood-brain barrier. Ghrelin release is also affected by the gut microbes, which has also been discussed in the review. This review elaborates on Ghrelin's role in depression and its effect on various aspects like neurogenesis, HPA axis, and neuroinflammation. Furthermore, this review focuses on ghrelin as a potential target for alleviation of depressive symptoms.

The Neural Association Between Symptom and Cognition in Major Depressive Disorder: A Network Control Theory Study

Major depressive disorder (MDD) is characterized by intercorrelated clinical symptoms and cognitive deficits, whose neural mechanisms in relation to these disturbances remain unclear. To elucidate this, we applied the relatively new approach of Network Control Theory (NCT), which considers how network topology informs brain dynamics based on white matter connectivity data. We used the NCT parameter of average controllability (AC) to assess the potential control that brain network nodes have on brain-state transitions associated with clinical and cognitive symptoms in MDD. DTI and high-resolution T1-weighted anatomical imaging were performed on 170 MDD patients (mean age 31.6 years; 72 males, 98 females) and 137 healthy controls (HC; mean age 33.4 years; 64 males, 73 females). We used an NCT approach to compare AC between the groups. We then performed partial Spearman's rank correlation and moderation/mediation analyses for AC and cognition and clinical symptom scores. Compared with HC, MDD patients had lower AC in the left precuneus and superior parietal lobule and higher AC in the right precentral gyrus (preCG) and superior frontal gyrus (SFG), predominantly in the default-mode, somatomotor, and attention networks. In the HC group, AC of right preCG was positively associated with processing speed. While in the MDD group, AC of right SFG was negatively associated with memory function and also negatively moderated the association between memory and anxiety symptoms. The current study highlighted that the altered brain controllability may provide a novel understanding of the neural substrate underlying cognitive control in MDD. Disrupted control of right SFG during state transitions may partially explain the variable relationship between memory and anxiety symptoms in MDD.