Insulin resistance, clinical presentation and resistance to selective serotonin and noradrenaline reuptake inhibitors in major depressive disorder.

BACKGROUND: The understanding of mechanisms underlying non-response to antidepressants is limited. The latest data highlights the role of insulin resistance (IR) in major depressive disorder (MDD) pathophysiology, presentation, and treatment efficacy. This work aimed to assess IR in MDD and explore the relationships between IR, MDD presentation and non-response to selective serotonin and noradrenaline reuptake inhibitors (SNRI). METHODS: 67 MDD individuals: 36 responsive (MDD T[+]), 31 non-responsive (MDD T[-]) to SNRI and 30 healthy controls were recruited. The treatment response criteria were: Clinical Global Impression Scale-Improvement score of 1 or 2 after ≥ 8 weeks of treatment. Participants were assessed by physician and self-report tools measuring depression, anhedonia, anxiety, bipolarity, sleep quality. Blood samples were collected to assess fasting glucose and insulin levels and calculate HOMA-IR (homeostasis model assessment of insulin resistance). RESULTS: MDD T[-] vs. MDD T[+] had significantly higher body mass index, insulin levels, and HOMA-IR. MDD T[-] presented higher levels of depressed mood, appetite/weight changes, loss of interest, energy, overall depressive symptoms, and sleep impairment; some evaluations suggested higher anhedonia and anxiety in MDD T[-] vs. MDD T[+]. Insulin and IR were weakly but significantly correlated with the severity of psychomotor symptoms, energy level, thoughts of death/suicide, self-criticism, appetite/weight, depressed mood symptoms, sleep problems. IR was weakly but significantly correlated with anhedonia. CONCLUSION: IR appears to be linked to depressive symptoms characteristic of the "metabolic" MDD subtype, such as psychomotor changes, energy level, anhedonia, sleep problems, appetite/weight changes, state and trait anxiety, sleep quality, and non-response to SNRI.

Bioinformatics and systems biology approach to identify the pathogenetic link of neurological pain and major depressive disorder.

Neurological pain (NP) is always accompanied by symptoms of depression, which seriously affects physical and mental health. In this study, we identified the common hub genes (Co-hub genes) and related immune cells of NP and major depressive disorder (MDD) to determine whether they have common pathological and molecular mechanisms. NP and MDD expression data was downloaded from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (Co-DEGs) for NP and MDD were extracted and the hub genes and hub nodes were mined. Co-DEGs, hub genes, and hub nodes were analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Finally, the hub nodes, and genes were analyzed to obtain Co-hub genes. We plotted Receiver operating characteristic (ROC) curves to evaluate the diagnostic impact of the Co-hub genes on MDD and NP. We also identified the immune-infiltrating cell component by ssGSEA and analyzed the relationship. For the GO and KEGG enrichment analyses, 93 Co-DEGs were associated with biological processes (BP), such as fibrinolysis, cell composition (CC), such as tertiary granules, and pathways, such as complement, and coagulation cascades. A differential gene expression analysis revealed significant differences between the Co-hub genes ANGPT2, MMP9, PLAU, and TIMP2. There was some accuracy in the diagnosis of NP based on the expression of ANGPT2 and MMP9. Analysis of differences in the immune cell components indicated an abundance of activated dendritic cells, effector memory CD8+ T cells, memory B cells, and regulatory T cells in both groups, which were statistically significant. In summary, we identified 6 Co-hub genes and 4 immune cell types related to NP and MDD. Further studies are needed to determine the role of these genes and immune cells as potential diagnostic markers or therapeutic targets in NP and MDD.

Relationship between serum inflammatory cytokines and suicide risk in patients with major depressive disorder.

Background: Studies have shown that increased inflammatory cytokines are associated with suicide risk, but the relationship between suicide risk and inflammatory cytokines is not clear. This study aimed to investigate the relationship between specific inflammatory markers and suicide risk in patients with MDD. Methods: This is a cross-sectional study. Firstly, we measured and compared psychological characteristics and 10 peripheral inflammatory cytokines in 130 MDD patients and 130 healthy controls(HC). Secondly, MDD patients were divided into 4 groups according to the severity of suicide risk for comparison between groups. Finally, multiple linear regression analysis was used to explore the predictors of suicide risk. Results: We found that the group with higher suicide risk had higher levels of IL-6, CRP, TNF-α, CXCL-2, and IFN-γ, and lower levels of IL-2 and IL-8 (all p<0.01). However, we found no difference in CRP between MIS and LS groups (p=0.337). Regression models were well-fitted. IL-2,IL-8 negatively predicted suicide risk (all p<0.05),IL-6,CRP,TNF-α,CXCL-2, and IFN-γ can positively predict the risk of suicide (all p<0.05). Limitations: This study employed a self-assessment scale. Conclusions: The higher the levels of IL-6, CRP, TNF-α, CXCL-2, and IFN-γ and the lower the levels of IL-2 and IL-8 of MDD patients, the higher the risk of suicide.

Microglial circ-UBE2K exacerbates depression by regulating parental gene UBE2K via targeting HNRNPU.

Background: Knowledge about the pathogenesis of depression and treatments for this disease are lacking. Epigenetics-related circRNAs are likely involved in the mechanism of depression and have great potential as treatment targets, but their mechanism of action is still unclear. Methods: Circular RNA UBE2K (circ-UBE2K) was screened from peripheral blood of patients with major depressive disorder (MDD) and brain of depression model mice through high-throughput sequencing. Microinjection of circ-UBE2K overexpression lentivirus and adeno-associated virus for interfering with microglial circ-UBE2K into the mouse hippocampus was used to observe the role of circ-UBE2K in MDD. Sucrose preference, forced swim, tail suspension and open filed tests were performed to evaluate the depressive-like behaviors of mice. Immunofluorescence and Western blotting analysis of the effects of circ-UBE2K on microglial activation and immune inflammation. Pull-down-mass spectrometry assay, RNA immunoprecipitation (RIP) test and fluorescence in situ hybridization (FISH) were used to identify downstream targets of circ-UBE2K/ HNRNPU (heterogeneous nuclear ribonucleoprotein U) axis. Results: In this study, through high-throughput sequencing and large-scale screening, we found that circ-UBE2K levels were significantly elevated both in the peripheral blood of patients with MDD and in the brains of depression model mice. Functionally, circ-UBE2K-overexpressing mice exhibited worsened depression-like symptoms, elevated brain inflammatory factor levels, and abnormal microglial activation. Knocking down circ-UBE2K mitigated these changes. Mechanistically, we found that circ-UBE2K binds to heterogeneous nuclear ribonucleoprotein U (HNRNPU) to form a complex that upregulates the expression of the parental gene ubiquitin conjugating enzyme E2 K (UBE2K), leading to abnormal microglial activation and neuroinflammation and promoting the occurrence and development of depression. Conclusions: The findings of the present study revealed that the expression of circUBE2K, which combines with HNRNPU to form the circUBE2K/HNRNPU complex, is increased in microglia after external stress, thus regulating the expression of the parental gene UBE2K and mediating the abnormal activation of microglia to induce neuroinflammation, promoting the development of MDD. These results indicate that circ-UBE2K plays a newly discovered role in the pathogenesis of depression.

Utilization and outcomes of transcranial magnetic stimulation and usual care for MDD in a large group psychiatric practice.

BACKGROUND: General psychiatrists' practice standards vary regarding when to implement transcranial magnetic stimulation (TMS) for care of patients with major depressive disorder (MDD). Furthermore, few studies have examined real-world utilization and clinical outcomes of TMS. This study analyzed data from a large, multi-site psychiatric practice to evaluate utilization and outcomes of TMS as well as usual care (UC) for patients with MDD. METHODS: Depression outcomes for TMS and UC among adult patients at a multi-site psychiatric group practice were examined in this retrospective cohort analysis. Patients with a primary diagnosis of MDD, PHQ-9 ≥ 10, and a visit in November 2020 with 6-month follow-up were included and categorized into the TMS or UC cohorts. RESULTS: Of 1,011 patients with qualifying PHQ-9 at the baseline visit, 9% (89) received a full course of TMS, and 583 patients receiving UC met study inclusion criteria (339 patients were excluded due to lacking a 6-month follow-up visit or receiving esketamine during the study period). The TMS cohort had higher baseline PHQ-9 than UC (17.9 vs. 15.5, p < .001) and had failed more medication trials (≥ 4 vs. 3.1, p < .001). Mean PHQ-9 decreased by 5.7 points (SD = 6.7, p < .001) in the TMS cohort and by 4.2 points (SD = 6.4, p < .001) in the UC cohort over the study period. Among patients who had failed four or more antidepressant medications, PHQ-9 decreased by 5.8 points in the TMS cohort (SD = 6.7, p < .001) and by 3.2 points in the UC cohort (SD = 6.3, p < .001). CONCLUSIONS: TMS utilization was low, despite TMS showing significant real-world clinical benefits. Future research should examine and address barriers to wider adoption of TMS into routine patient care for patients with treatment-resistant MDD. Wider adoption including routine use of TMS in less treatment-resistant patients will allow statistical comparisons of outcomes between TMS and UC populations that are difficult to do when TMS is underutilized.

Risk of major depressive increases with increasing frequency of alcohol drinking: a bidirectional two-sample Mendelian randomization analysis.

Introduction: A growing body of evidence suggests that alcohol use disorders coexist with depression. However, the causal relationship between alcohol consumption and depression remains a topic of controversy. Methods: We conducted a two-sample two-way Mendelian randomization analysis using genetic variants associated with alcohol use and major depressive disorder from a genome-wide association study. Results: Our research indicates that drinking alcohol can reduce the risk of major depression (odds ratio: 0.71, 95% confidence interval: 0.54~0.93, p = 0.01), while increasing the frequency of drinking can increase the risk of major depression (odds ratio: 1.09, 95% confidence interval: 1.00~1.18, p = 0.04). Furthermore, our multivariate MR analysis demonstrated that even after accounting for different types of drinking, the promoting effect of drinking frequency on the likelihood of developing major depression still persists (odds ratio: 1.13, 95% confidence interval: 1.04~1.23, p = 0.005). Additionally, mediation analysis using a two-step MR approach revealed that this effect is partially mediated by the adiposity index, with a mediated proportion of 37.5% (95% confidence interval: 0.22 to 0.38). Discussion: In this study, we found that alcohol consumption can alleviate major depression, while alcohol intake frequency can aggravate it.These findings have important implications for the development of prevention and intervention strategies targeting alcohol-related depression.

Assessing the associations of 1,400 blood metabolites with major depressive disorder: a Mendelian randomization study.

Background and objectives: Major Depressive Disorder (MDD) is one of the most prevalent and debilitating health conditions worldwide. Previous studies have reported a link between metabolic dysregulation and MDD. However, evidence for a causal relationship between blood metabolites and MDD is lacking. Methods: Using a two-sample bidirectional Mendelian randomization analysis (MR), we assessed the causal relationship between 1,400 serum metabolites and Major Depressive Disorder (MDD). The Inverse Variance Weighted method (IVW) was employed to estimate the causal association between exposures and outcomes. Additionally, MR-Egger regression, weighted median, simple mode, and weighted mode methods were used as supplementary approaches for a comprehensive appraisal of the causality between blood metabolites and MDD. Pleiotropy and heterogeneity tests were also conducted. Lastly, the relevant metabolites were subjected to metabolite function analysis, and a reverse MR was implemented to explore the potential influence of MDD on these metabolites. Results: After rigorous screening, we identified 34 known metabolites, 13 unknown metabolites, and 18 metabolite ratios associated with Major Depressive Disorder (MDD). Among all metabolites, 33 were found to have positive associations, and 32 had negative associations. The top five metabolites that increased the risk of MDD were the Arachidonate (20:4n6) to linoleate (18:2n6) ratio, LysoPE(18:0/0:0), N-acetyl-beta-alanine levels, Arachidonate (20:4n6) to oleate to vaccenate (18:1) ratio, Glutaminylglutamine, and Threonine to pyruvate ratio. Conversely, the top five metabolites that decreased the risk of MDD were N6-Acetyl-L-lysine, Oleoyl-linoleoyl-glycerol (18:1 to 18:2) [2] to linoleoyl-arachidonoyl-glycerol (18:2 to 20:4) [2] ratio, Methionine to phosphate ratio, Pregnanediol 3-O-glucuronide, and 6-Oxopiperidine-2-carboxylic acid. Metabolite function enrichment was primarily concentrated in pathways such as Bile Acid Biosynthesis (FDR=0.177), Glutathione Metabolism (FDR=0.177), Threonine, and 2-Oxobutanoate Degradation (FDR=0.177). In addition, enrichment was noted in pathways like Valine, Leucine, and Isoleucine Biosynthesis (p=0.04), as well as Ascorbate and Aldarate Metabolism (p=0.04). Discussion: Within a pool of 1,400 blood metabolites, we identified 34 known metabolites and 13 unknown metabolites, as well as 18 metabolite ratios associated with Major Depressive Disorder (MDD). Additionally, three functionally enriched groups and two metabolic pathways were selected. The integration of genomics and metabolomics has provided significant insights for the screening and prevention of MDD.

Exploring the potential of drug repurposing for treating depression.

Researchers are interested in drug repurposing or drug repositioning of existing pharmaceuticals because of rising costs and slower rates of new medication development. Other investigations that authorized these treatments used data from experimental research and off-label drug use. More research into the causes of depression could lead to more effective pharmaceutical repurposing efforts. In addition to the loss of neurotransmitters like serotonin and adrenaline, inflammation, inadequate blood flow, and neurotoxins are now thought to be plausible mechanisms. Because of these other mechanisms, repurposing drugs has resulted for treatment-resistant depression. This chapter focuses on therapeutic alternatives and their effectiveness in drug repositioning. Atypical antipsychotics, central nervous system stimulants, and neurotransmitter antagonists have investigated for possible repurposing. Nonetheless, extensive research is required to ensure their formulation, effectiveness, and regulatory compliance.

Sleep disturbances and incident risk of major depressive disorder in a population-based cohort.

Sleep disturbances are well-known symptoms of major depressive disorder (MDD). However, the prospective risk of MDD in the presence of sleep disturbances in a general population-based cohort is not well known. This study investigated associations between both polysomnography (PSG)-based or subjective sleep features and incident MDD. Participants representative of the general population who had never had MDD completed sleep questionnaires (n = 2000) and/or underwent PSG (n = 717). Over 8 years' follow-up, participants completed psychiatric interviews enabling the diagnosis of MDD. Survival Cox models were used to analyze associations between sleep features and MDD incidence. A higher Epworth Sleepiness Scale and presence of insomnia symptoms were significantly associated with a higher incidence of MDD (hazard ratio [HR] [95 % confidence interval (CI)]: 1.062 [1.022-1.103], p = 0.002 and 1.437 [1.064-1.940], p = 0.018, respectively). Higher density of rapid eye movements in rapid eye movement (REM) sleep was associated with a higher incidence of MDD in men (HR 1.270 [95 % CI 1.064-1.516], p = 0.008). In women, higher delta power spectral density was associated with a lower MDD incidence (HR 0.674 [95 % CI 0.463-0.981], p = 0.039). This study confirmed the associations between subjective and objective sleep features and the incidence of MDD in a large community dwelling cohort.

Cognitive Behavioral Therapy and Hypnosis in the Treatment of Major Depressive Disorder: A Randomized Control Trial.

We investigated whether adding hypnosis to CBT (CBTH) improved treatment outcomes for MDD with a two-armed, parallel-treated, randomized-controlled trial using anonymous self-report and clinician-blinded assessments. Expectancy, credibility, and attitude to hypnosis were also examined. Participants (n = 66) were randomly allocated to 10-weekly sessions of group-based CBT or CBTH. LMM analyses of ITT and Completer data at post-treatment, six-month and 12-month follow-up showed that both treatments were probably efficacious but we did not find significant differences between them. Analyses of remission and response to treatment data revealed that the CBTH Completer group significantly outperformed CBT at 12-month follow-up (p = .011). CBTH also displayed significantly higher associations between credibility, expectancy and mood outcomes up to 12-month follow-up (all p < .05 or better), while attitude to hypnosis showed one significant association (r = -0.57, p < .05). These results suggest that hypnosis shows promise as an adjunct in the treatment of MDD but a larger sample size is required to fully test its merits.

Comparative analysis of resting-state EEG functional connectivity in depression and obsessive-compulsive disorder.

Major depressive disorder (MDD) and obsessive-compulsive disorder (OCD) are psychiatric disorders that often co-occur. We aimed to investigate whether their high comorbidity could be traced not only by clinical manifestations, but also at the level of functional brain activity. In this paper, we examined the differences in functional connectivity (FC) at the whole-brain level and within the default mode network (DMN). Resting-state EEG was obtained from 43 controls, 26 OCD patients, and 34 MDD patients. FC was analyzed between 68 cortical sources, and between-group differences in the 4-30 Hz range were assessed via the Network Based Statistic method. The strength of DMN intra-connectivity was compared between groups in the theta, alpha and beta frequency bands. A cluster of 67 connections distinguished the OCD, MDD and control groups. The majority of the connections, 8 of which correlated with depressive symptom severity, were found to be weaker in the clinical groups. Only 3 connections differed between the clinical groups, and one of them correlated with OCD severity. The DMN strength was reduced in the clinical groups in the alpha and beta bands. It can be concluded that the high comorbidity of OCD and MDD can be traced at the level of FC.

Assessing the Relationship Between Vitiligo and Major Depressive Disorder Severity: Cross-Sectional Study.

BACKGROUND: Vitiligo, a common dermatological disorder in Saudi Arabia, is associated with significant psychological impacts. This study explores the relationship between vitiligo and the severity of major depressive disorder (MDD), highlighting the broader implications on mental health among affected individuals. OBJECTIVE: We aim to assess the prevalence and predictors of depression among adult patients with vitiligo, and to examine the relationship between MDD severity and vitiligo. METHODS: Using a cross-sectional design, the research used the vitiligo area severity index and the Patient Health Questionnaire-9 to measure the extent of vitiligo and depression severity, respectively. This study involved 340 diagnosed patients with vitiligo from various health care settings. Logistic and ordinal regression analysis were applied to evaluate the impact of sociodemographic variables and vitiligo types on MDD severity. RESULTS: The prevalence of MDD was 58.8% (200/340) of participants. Depression severity varied notably: 18.2% (62/340) of patients experienced mild depression, 17.9% (61/340) moderate, 11.8% (40/340) moderately severe, and 10.9% (37/340) severe depression. Female patients had higher odds of severe depression than male patients (adjusted odds ratio [aOR] 3.14, 95% CI 1.93-5.1; P<.001). Age was inversely related to depression severity, with patients aged older than 60 years showing significantly lower odds (aOR 0.1, 95% CI 0.03-0.39; P<.001). Lower income was associated with higher depression severity (aOR 10.2, 95% CI 3.25-31.8; P<.001). Vitiligo types also influenced depression severity; vulgaris (aOR 5.3, 95% CI 2.6-10.9; P<.001) and acrofacial vitiligo (aOR 2.8, 95% CI 1.5-5.1; P<.001) were significantly associated with higher depression levels compared to focal vitiligo. CONCLUSIONS: The findings suggest that vitiligo contributes to an increased risk of severe depression, highlighting the need for integrated dermatological and psychological treatment approaches to address both the physical and mental health aspects of the disease.

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis.

BACKGROUND: Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings. OBJECTIVE: This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts. METHODS: Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score. RESULTS: Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (ß=-93.61, P<.001), increased sleep variability (ß=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: ß=0.55, P=.001; sleep offset: ß=1.12, P<.001; M10 onset: ß=0.73, P=.003; HR acrophase: ß=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (ß of PHQ-8 × spring = -31.51, P=.002) and summer (ß of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (ß of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer. CONCLUSIONS: Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

TanhReLU -based convolutional neural networks for MDD classification.

Major Depression Disorder (MDD), a complex mental health disorder, poses significant challenges in accurate diagnosis. In addressing the issue of gradient vanishing in the classification of MDD using current data-driven electroencephalogram (EEG) data, this study introduces a TanhReLU-based Convolutional Neural Network (CNN). By integrating the TanhReLU activation function, which combines the characteristics of the hyperbolic tangent (Tanh) and rectified linear unit (ReLU) activations, the model aims to improve performance in identifying patterns associated with MDD while alleviating the issue of model overfitting and gradient vanishing. Experimental results demonstrate promising outcomes in the task of MDD classification upon the publicly available EEG data, suggesting potential clinical applications.

Using Alternative Definitions of Controls to Increase Statistical Power in GWAS.

Genome-wide association studies (GWAS) are often underpowered due to small effect sizes of common single nucleotide polymorphisms (SNPs) on phenotypes and extreme multiple testing thresholds. The most common approach for increasing statistical power is to increase sample size. We propose an alternative strategy of redefining case-control outcomes into ordinal case-subthreshold-asymptomatic variables. While maintaining the clinical case threshold, we subdivide controls into two groups: individuals who are symptomatic but do not meet the clinical criteria for diagnosis (subthreshold) and individuals who are effectively asymptomatic. We conducted a simulation study to examine the impact of effect size, minor allele frequency, population prevalence, and the prevalence of the subthreshold group on statistical power to detect genetic associations in three scenarios: a standard case-control, an ordinal, and a case-asymptomatic control analysis. Our results suggest the ordinal model consistently provides the greatest statistical power while the case-control model the least. Power in the case-asymptomatic control model reflects the case-control or ordinal model depending on the population prevalence and size of the subthreshold category. We then analyzed a major depression phenotype from the UK Biobank to corroborate our simulation results. Overall, the ordinal model improves statistical power in GWAS consistent with increasing the sample size by approximately 10%.

Neurodevelopmental signature of a transcriptome-based polygenic risk score for depression.

Disentangling the molecular underpinnings of major depressive disorder (MDD) is necessary for identifying new treatment and prevention targets. The functional impact of depression-related transcriptomic changes on the brain remains relatively unexplored. We recently developed a novel transcriptome-based polygenic risk score (tPRS) composed of genes transcriptionally altered in MDD. Here, we sought to investigate effects of tPRS on brain structure in a developmental cohort (Adolescent Brain Cognitive Development study; n = 5124; 2387 female) at baseline (9-10 years) and 2-year follow-up (11-12 years). We tested associations between tPRS and Freesurfer-derived measures of cortical thickness, cortical surface area, and subcortical volume. Across the whole sample, higher tPRS was significantly associated with thicker left posterior cingulate cortex at both baseline and 2-year follow-up. In females only, tPRS was associated with lower right hippocampal volume at baseline and 2-year follow-up, and lower right pallidal volume at baseline. Furthermore, regional subcortical volume significantly mediated an indirect effect of tPRS on depressive symptoms in females at both timepoints. Conversely, tPRS did not have significant effects on cortical surface area. These findings suggest the existence of a sex-specific neurodevelopmental signature associated with shifts towards a more depression-like brain transcriptome, and highlight novel pathways of developmentally mediated MDD risk.

Higher levels of plasma Adrenocorticotropic hormone (ACTH) are associated with lower suicidal ideation in depressed patients compared to controls and suicide attempters, independently from depression severity.

Introduction: Suicidal ideation, an important risk factor for suicide attempts, has an unclear neurobiological basis and is potentially linked to the dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis and immune-inflammatory systems. While inflammatory markers have been associated with suicide attempts and, to a lower extent suicidal ideation, the data on the role of a stress-response system is less robust, with most studies carried out with cortisol showing inconsistent results. The present study extends on the previous studies implicating stress-response and immune-inflammatory systems in suicidal thoughts and behaviours, focusing on the associations of several stress-response (adrenocorticotropic hormone (ACTH), cortisol, and dehydroepiandrosterone (DHEA)) and immune-inflammatory (C-reactive protein (CRP),interle ukin-6 (IL-6), and tumour necrosis factor-alpha (TNF-alpha)) with suicidal ideation severity in recent suicide attempters, patients with major depressive disorder, and non-psychiatric controls. Methods: This observational study included 156 adults from three Vilnius hospitals, recruited into one of the three groups in equal parts: recent suicide attempters, patients with major depressive disorder in current depressive episode, and non-psychiatric controls. Measures included the Hamilton Depression Rating Scale (HDRS-17) and the Beck Scale for Suicide Ideation/Suicide Severity Index (BSS/SSI), alongside sociodemographic data, alcohol, tobacco use, and morning blood samples, measuring plasma ACTH, cortisol, DHEA, CRP, and IL-6. Data were analysed with non-parametric tests, Kendall's tau correlation, and multivariate linear regression adjusted for confounders. Results: We found a negative correlation between the plasma ACTH levels and suicidal ideation severity (tau = -0.130, p = 0.033), which was driven by the patients with major depressive disorder (tau = -0.237, p = 0.031). Suicidal ideation severity was also negatively correlated with TNF-alpha (tau = -0.231; p < 0.001), positively correlated with IL-6 (tau = 0.154, p = 0.015), and CRP levels (tau = 0.153, p = 0.015), but no differences were observed in group-stratified analyses. The association between plasma ACTH levels and suicidal ideation severity in patients with major depressive disorder remained robust to adjustment for major confounders (adjusted for age, sex, education years, body mass index, smoking status, plasma CRP and PEth concentration (measuring chronic alcohol exposure), and antidepressant use) in the linear regression model (t = -2.71, p = 0.011), as well as additionally adjusting for depression severity (t = -2.99, p = 0.006). Discussion: The present study shows an association between plasma ACTH levels and suicidal ideation severity in patients with major depressive disorder, robust to adjustment for antidepressant use and depression severity. This finding highlights the potential role of ACTH, in elucidating the effects of stress and mental health disorders. Our findings underscore the importance of the HPA axis in the diagnosis and treatment of suicidal ideation in major depressive disorder and invite further research on interventions targeting this pathway.

An association study of m6A methylation with major depressive disorder.

OBJECTIVE: To find the relationship between N6-methyladenosine (m6A) genes and Major Depressive Disorder (MDD). METHODS: Differential expression of m6A associated genes between normal and MDD samples was initially identified. Subsequent analysis was conducted on the functions of these genes and the pathways they may affect. A diagnostic model was constructed using the expression matrix of these differential genes, and visualized using a nomogram. Simultaneously, an unsupervised classification method was employed to classify all patients based on the expression of these m6A associated genes. Following this, common differential genes among different clusters were computed. By analyzing the functions of the common differential expressed genes among clusters, the role of m6A-related genes in the pathogenesis of MDD patients was elucidated. RESULTS: Differential expression was observed in ELAVL1 and YTHDC2 between the MDD group and the control group. ELAVL1 was associated with comorbid anxiety in MDD patients. A linear regression model based on these two genes could accurately predict whether patients in the GSE98793 dataset had MDD and could provide a net benefit for clinical decision-making. Based on the expression matrix of ELAVL1 and YTHDC2, MDD patients were classified into three clusters. Among these clusters, there were 937 common differential genes. Enrichment analysis was also performed on these genes. The ssGSEA method was applied to predict the content of 23 immune cells in the GSE98793 dataset samples. The relationship between these immune cells and ELAVL1, YTHDC2, and different clusters was analyzed. CONCLUSION: Among all the m6A genes, ELAVL1 and YTHDC2 are closely associated with MDD, ELAVL1 is related to comorbid anxiety in MDD. ELAVL1 and YTHDC2 have opposite associations with immune cells in MDD.

Suicide risk in patients with a current depressive episode during the COVID-19 pandemic.

Introduction: The prevalence of major depressive disorder (MDD) increased during the COVID-19 pandemic. Data on suicidality in these patients during the pandemic period remain scarce. The aim of the study was to determine the prevalence and variables associated with serious suicide risk in Russian inpatients with MDD during the COVID-19 pandemic. Methods: A cross-sectional cohort study with consecutive sampling was conducted from January 1, 2021 to December 31, 2021. All patients completed the Mini International Neuropsychiatric Interview (M.I.N.I.) (including the suicidality module), the Beck Depression Inventory, and the State-Trait Anxiety Inventory, and underwent a semi-structured interview to collect relevant demographic and clinical data. Effect sizes for all independent variables and covariates were calculated using partial eta-squared (ηp2). Results: Of the 6757 patients with non-psychotic mental disorders assessed, 1605 (23.7%) had MDD confirmed by the M.I.N.I., of whom 17.8% were at serious risk for suicide according to the M.I.N.I. suicidality module. Factors independently associated with serious suicide risk in Russian inpatients with MDD during the pandemic were younger age (ηp2 = 0.021), greater severity of depression (0.038), higher state anxiety (0.003), and nonsuicidal self-injury (NSSI) (0.066). The same variables, except for state anxiety, were independently associated with suicide risk in the subgroup of MDD patients previously infected with SARS-CoV2. Conclusion: In the COVID-19 pandemic, the proportion of patients with MDD at serious risk of suicide was similar to pre-pandemic data. No associations were found between suicidality in patients with MDD and COVID-related factors. Younger age, greater severity of depression, and especially NSSI were the most significant risk factors for suicide in patients with MDD during the COVID-19 pandemic.

Subjective and objective cognitive functioning in untreated late-life depression: An exploration centered on comorbid generalized anxiety disorder.

BACKGROUND: Late-Life Depression (LLD) is a prevalent mental health disorder that is often accompanied by cognitive impairments. The objective of this study is to investigate the influence of coexisting Generalized Anxiety Disorder (GAD) on both subjective and objective cognitive abilities in untreated LLD individuals. METHODS: A total of 77 participants aged 60 years and above were recruited for this study, comprising 31 individuals with Major Depressive Disorder (LLD group), 46 with MDD and coexisting Generalized Anxiety Disorder (LLDA group), and 54 healthy controls (HC). Prior to the study, all patients had abstained from psychotropic medication for a minimum of two weeks. Comprehensive neuropsychological assessments were administered to all participants. RESULTS: The LLDA group exhibited substantial disparities in memory, attention, processing speed,executive function,overall cognitive functioning, and subjective cognitive functioning when compared to the HC group. The LLD group displayed deficits in memory, SCWT-W in attention, SCWT-C in processing speed,overall cognitive functioning, and subjective cognitive functioning in comparison to the healthy controls. Although the LLD group achieved lower average scores in executive function, TMTA in processing speed, and DSST in attention than the HC group, no significant distinctions were identified between these groups in these domains. Linear regression analysis unveiled that anxiety symptoms had a significant impact on subjective cognitive deficits among MDD patients, but exhibited a milder influence on objective cognitive performance. After adjusting for the severity of depression, anxiety symptoms were found to affect TMTA in processing speed and subjective cognitive functioning in LLD patients. CONCLUSION: Late-Life Depression (LLD) exhibits pervasive cognitive impairments, particularly in individuals with generalized anxiety disorder, presenting a crucial target for future therapeutic interventions. Among elderly individuals with depression, anxiety symptoms significantly impact subjective cognitive functioning, suggesting its potential utility in distinguishing between depression-associated cognitive decline and pre-dementia conditions.