Evaluation of serum MIP-1ß and MCP-2 levels in major depressive disorder: A case-control study.

BACKGROUND: Major depressive disorder (MDD) is a common and debilitating mental illness characterized by persistent feelings of sadness, hopelessness, and a lack of interest in daily activities. The objective of this study was to investigate whether levels of macrophage inflammatory protein-1ß (MIP-1ß) and macrophage chemoattractant protein-2 (MCP-2) in the blood were associated with the pathophysiology and development of MDD compared to healthy controls (HCs). METHODS: This case-control study was conducted involving 50 MDD patients and 38 HCs. We performed a comprehensive assessment to match age, sex, BMI, and socio-demographic profile between the groups. The study excluded participants with chronic infection, inflammatory diseases, coexisting psychiatric disorder, history of liver and kidney diseases, and individuals who are under antipsychotic medications. A professional psychiatrist diagnosed MDD patients and evaluated HCs based on the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) criteria. The severity of depression was assessed using the Hamilton Depression (Ham-D) rating scale. Commercially available enzyme-linked immunosorbent assay (ELISA) kits were used to quantify the serum MIP-1ß and MCP-2 levels. RESULTS: The results indicated elevated serum MIP-1ß levels (207.73±24.24 pg/ml) in MDD patients compared to HCs (58.77±9.14 pg/ml). This difference in concentration is positively correlated with severity of disease symptoms (r = 0.451; p<0.001). Similarly, the levels of MCP-2 were found to be elevated in patients compared to controls (143.61±19.92 vs. 56.84±4.02 pg/ml; p = 0.003), with a positive correlation with the Ham-D scores (r = 0.373; p = 0.004). CONCLUSION: According to this study, elevated levels of MIP-1ß and MCP-2 may be associated with the pathophysiology and development of MDD. These increased serum MIP-1ß and MCP-2 levels could be used as risk assessment tools for MDD. The present findings urge further research and the development of therapeutic and diagnostic approaches for depression.

Sex differences in correlates of suicide attempts in Chinese Han first-episode and drug-naïve major depressive disorder with comorbid subclinical hypothyroidism: A cross-sectional study.

BACKGROUND: This study aimed to investigate sex differences in risk factors for suicide attempts in first-episode and drug naive (FEDN) major depressive disorder (MDD) with comorbid subclinical hypothyroidism (SCH). METHODS: A total of 1034 FEDN MDD patients with comorbid SCH were enrolled. The Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), and Positive and Negative Syndrome Scale (PANSS) positive subscale were used to assess patients' symptoms. Thyroid hormone levels and metabolic parameters were measured. RESULTS: MDD patients with SCH had a significantly higher risk of suicide attempts than those without SCH (25.4% vs. 12.2%). Logistic regression showed that HAMA score, thyroid stimulating hormone (TSH) levels, and thyroid peroxidase antibody (TPOAb) levels were significantly associated with an increased risk for suicide attempts in both male and female MDD patients comorbid SCH, while low-density lipoprotein cholesterol (LDL-C) was significantly associated with an increased risk for suicide attempts only in male patients, HAMD score and systolic blood pressure were significantly associated with an increased risk for suicide attempts only in female patients. CONCLUSION: SCH comorbidities may increase suicide attempts in MDD patients. Our results showed significant sex differences in clinical and metabolic factors associated with suicide attempts among FEDN MDD patients with comorbid SCH, highlighting appropriate sex-based preventive interventions are needed.

Non-linear relationship between TSH and psychotic symptoms on first episode and drug naïve major depressive disorder patients: a large sample sized cross-sectional study in China.

INTRODUCTION: Psychotic depression (PD) is characterized by the co-occurrence of emotional dysfunction and psychotic symptoms such as delusions and hallucinations with poor clinical outcomes. TSH may involve in the development of PD. This study aims to explore relationship between TSH and PD. METHODS: A total of 1718 outpatients diagnosed as FEDN MDD were recruited in this study. The relationship between PD and TSH was evaluated using multivariable binary logistic regression analysis. To assess the presence of non-linear associations, a two-piecewise linear regression model was employed. Furthermore, interaction and stratified analyses were conducted with respect to sex, education, marital status, comorbid anxiety, and suicide attempt. RESULTS: Multivariable logistic regression analysis revealed that TSH was positively associated with the risk of PD after adjusting for confounders (OR = 1.26, 95% CI: 1.11 to 1.43; p < 0.05). Smoothing plots showed a nonlinear relationship between TSH and PD, with the inflection point of TSH being 4.94 mIU/L. On the right of the inflection point, for each unit increase in serum TSH level on the right side of the inflection point, the probability of PD increased substantially by 47% (OR = 1.47, 95% CI: 1.25 to 1.73, p < 0.001), while no significant association was observed on the left side of the inflection point (OR = 0.87, 95% CI: 0.67 to 1.14, p = 0.32). CONCLUSION: Our investigation showed a nonlinear TSH-PD relationship in FEDN MDD patients, thus contributing to effective intervention strategies for psychotic symptoms in depression patients.

Systemic inflammation, oxidative damage and neurocognition predict telomere length in a transdiagnostic sample stratified by global DNA methylation levels.

Epigenetic mechanisms contribute to the maintenance of both type 2 diabetes mellitus (T2DM) and psychiatric disorders. Emerging evidence suggests that molecular pathways and neurocognitive performance regulate epigenetic dynamics in these disorders. The current combined and transdiagnostic study investigated whether inflammatory, oxidative stress, adhesion molecule, neurocognitive and functional performance are significant predictors of telomere dynamics in a sample stratified by global DNA methylation levels. Peripheral blood inflammation, oxidative stress and adhesion molecule biomarkers and neurocognitive function were assessed twice over a 1-year period in 80 individuals, including 16 with schizophrenia (SZ), 16 with bipolar disorder (BD), 16 with major depressive disorder (MDD), 15 with T2DM, and 17 healthy controls (HCs). Leukocyte telomere length (LTL) was measured by qRT-PCR using deoxyribonucleic acid (DNA) extracted from peripheral blood samples. A posteriori, individuals were classified based on their global methylation score (GMS) at baseline into two groups: the below-average methylation (BM) and above-average methylation (AM) groups. Hierarchical and k-means clustering methods, mixed one-way analysis of variance and linear regression analyses were performed. Overall, the BM group showed a significantly higher leukocyte telomere length (LTL) than the AM group at both time points (p = 0.02; η2p = 0.06). Moreover, the BM group had significantly lower levels of tumor necrosis factor alpha (TNF-α) (p = 0.03; η2p = 0.06) and C-reactive protein (CRP) (p = 0.03; η2p = 0.06) than the AM group at the 1-year follow-up. Across all participants, the regression models showed that oxidative stress (reactive oxygen species [ROS]) (p = 0.04) and global cognitive score [GCS] (p = 0.02) were significantly negatively associated with LTL, whereas inflammatory (TNF-α) (p = 0.04), adhesion molecule biomarkers (inter cellular adhesion molecule [ICAM]) (p = 0.009), and intelligence quotient [IQ] (p = 0.03) were significantly positively associated with LTL. Moreover, the model predictive power was increased when tested in both groups separately, explaining 15.8% and 28.1% of the LTL variance at the 1-year follow-up for the AM and BM groups, respectively. Heterogeneous DNA methylation in individuals with T2DM and severe mental disorders seems to support the hypothesis that epigenetic dysregulation occurs in a transdiagnostic manner. Our results may help to elucidate the interplay between epigenetics, molecular processes and neurocognitive function in these disorders. DNA methylation and LTL are potential therapeutic targets for transdiagnostic interventions to decrease the risk of comorbidities.

Decoding the inflammatory signature of the major depressive episode: insights from peripheral immunophenotyping in active and remitted condition, a case-control study.

Depression is a prevalent and incapacitating condition with a significant impact on global morbidity and mortality. Although the immune system's role in its pathogenesis is increasingly recognized, there is a lack of comprehensive understanding regarding the involvement of innate and adaptive immune cells. To address this gap, we conducted a multicenter case-control study involving 121 participants matched for sex and age. These participants had either an active (or current) major depressive episode (MDE) (39 cases) or a remitted MDE (40 cases), including individuals with major depressive disorder or bipolar disorder. We compared these 79 patients to 42 healthy controls (HC), analyzing their immunological profiles. In blood samples, we determined the complete cell count and the monocyte subtypes and lymphocyte T-cell populations using flow cytometry. Additionally, we measured a panel of cytokines, chemokines, and neurotrophic factors in the plasma. Compared with HC, people endorsing a current MDE showed monocytosis (p = 0.001), increased high-sensitivity C-reactive protein (p = 0.002), and erythrocyte sedimentation rate (p = 0.003), and an altered proportion of specific monocyte subsets. CD4 lymphocytes presented increased median percentages of activation markers CD69+ (p = 0.007) and exhaustion markers PD1+ (p = 0.013) and LAG3+ (p = 0.014), as well as a higher frequency of CD4+CD25+FOXP3+ regulatory T cells (p = 0.003). Additionally, patients showed increased plasma levels of sTREM2 (p = 0.0089). These changes are more likely state markers, indicating the presence of an ongoing inflammatory response during an active MDE. The Random Forest model achieved remarkable classification accuracies of 83.8% for MDE vs. HC and 70% for differentiating active and remitted MDE. Interestingly, the cluster analysis identified three distinct immunological profiles among MDE patients. Cluster 1 has the highest number of leukocytes, mainly given by the increment in lymphocyte count and the lowest proinflammatory cytokine levels. Cluster 3 displayed the most robust inflammatory pattern, with high levels of TNFα, CX3CL1, IL-12p70, IL-17A, IL-23, and IL-33, associated with the highest level of IL-10, as well as ß-NGF and the lowest level for BDNF. This profile is also associated with the highest absolute number and percentage of circulating monocytes and the lowest absolute number and percentage of circulating lymphocytes, denoting an active inflammatory process. Cluster 2 has some cardinal signs of more acute inflammation, such as elevated levels of CCL2 and increased levels of proinflammatory cytokines such as IL-1ß, IFNγ, and CXCL8. Similarly, the absolute number of monocytes is closer to a HC value, as well as the percentage of lymphocytes, suggesting a possible initiation of the inflammatory process. The study provides new insights into the immune system's role in MDE, paving the ground for replication prospective studies targeting the development of diagnostic and prognostic tools and new therapeutic targets.

Graph convolutional network with attention mechanism improve major depressive depression diagnosis based on plasma biomarkers and neuroimaging data.

BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking. METHODS: In this study, blood samples from 100 MDD and 100 HC were analyzed, along with MRI images from 46 MDD and 49 HC. Here, we devised a novel algorithm, integrating graph neural networks and attention modules, for MDD diagnosis based on inflammatory cytokines, neurotrophic factors, and Orexin A levels in the blood samples. Model performance was assessed via accuracy and F1 value in 3-fold cross-validation, comparing with 9 traditional algorithms. We then applied our algorithm to a dataset containing both the aforementioned protein quantifications and neuroimages, evaluating if integrating neuroimages into the model improves performance. RESULTS: Compared to HC, MDD showed significant alterations in plasma protein levels and gray matter volume revealed by MRI. Our new algorithm exhibited superior performance, achieving an F1 value and accuracy of 0.9436 and 94.08 %, respectively. Integration of neuroimaging data enhanced our novel algorithm's performance, resulting in an improved F1 value and accuracy, reaching 0.9543 and 95.06 %. LIMITATIONS: This single-center study with a small sample size requires future evaluations on a larger test set for improved reliability. CONCLUSIONS: In comparison to traditional machine learning models, our newly developed MDD diagnostic model exhibited superior performance and showed promising potential for inclusion in routine clinical diagnosis for MDD.

Inflammation and immune system pathways as biological signatures of adolescent depression-the IDEA-RiSCo study.

The biological mechanisms underlying the onset of major depressive disorder (MDD) have predominantly been studied in adult populations from high-income countries, despite the onset of depression typically occurring in adolescence and the majority of the world's adolescents living in low- and middle-income countries (LMIC). Taking advantage of a unique adolescent sample in an LMIC (Brazil), this study aimed to identify biological pathways characterizing the presence and increased risk of depression in adolescence, and sex-specific differences in such biological signatures. We collected blood samples from a risk-stratified cohort of 150 Brazilian adolescents (aged 14-16 years old) comprising 50 adolescents with MDD, 50 adolescents at high risk of developing MDD but without current MDD, and 50 adolescents at low risk of developing MDD and without MDD (25 females and 25 males in each group). We conducted RNA-Seq and pathway analysis on whole blood. Inflammatory-related biological pathways, such as role of hypercytokinemia/hyperchemokinemia in the pathogenesis of influenza (z-score = 3.464, p < 0.001), interferon signaling (z-score = 2.464, p < 0.001), interferon alpha/beta signaling (z-score = 3.873, p < 0.001), and complement signaling (z-score = 2, p = 0.002) were upregulated in adolescents with MDD compared with adolescents without MDD independently from their level of risk. The up-regulation of such inflammation-related pathways was observed in females but not in males. Inflammatory-related pathways involved in the production of cytokines and in interferon and complement signaling were identified as key indicators of adolescent depression, and this effect was present only in females.

Effect of duloxetine on changes in serum proinflammatory cytokine levels in patients with major depressive disorder.

OBJECTIVE: Accumulating evidence supports the idea that inflammation may contribute to the pathophysiology of major depressive disorder (MDD). Duloxetine, a serotonin-norepinephrine reuptake inhibitor, exhibits anti-inflammatory effects both in vitro and in vivo. In this study, we investigated the impact of duloxetine on changes in serum proinflammatory cytokine levels among individuals diagnosed with MDD. METHODS: A cohort of 23 drug-naïve individuals diagnosed with MDD and 23 healthy controls were included in this study. The severity of depressive symptoms was evaluated using the 24-item Hamilton Depression Scale (HAMD-24). A panel of 7 proinflammatory cytokines, including interleukin-1ß (IL-1ß), IL-2, IL-6, IL-8, IL-12, tumor necrosis factor-α (TNF-α), and interferon-γ (IFN-γ), were quantified using multiplex Luminex assays. The levels of serum cytokines in healthy controls and patients with MDD were compared at baseline. All patients received duloxetine at a dosage range of 40-60 mg/day for a duration of 4 weeks. The HAMD-24 scores and serum cytokine levels were compared before and after duloxetine treatment. RESULTS: Compared with healthy controls, patients with MDD had significantly greater levels of IL-2, IL-6, IL-8, IL-12, TNF-α, and IFN-γ (P < 0.05). Moreover, there was a significant decrease in HAMD-24 scores observed pre- and post-treatment (t = 13.161, P < 0.001). Furthermore, after 4 weeks of treatment, the serum levels of IL-8 (t = 3.605, P = 0.002), IL-12 (t = 2.559, P = 0.018), and IFN-γ (t = 3.567, P = 0.002) decreased significantly. However, there were no significant differences in other cytokines, including IL-1ß, IL-2, IL-6, and TNF-α, before and after treatment (P > 0.05). CONCLUSIONS: These findings present compelling evidence, potentially for the first time, indicating that duloxetine treatment may effectively reduce the serum concentrations of IL-8, IL-12, and IFN-γ in individuals diagnosed with MDD. However, the precise mechanisms underlying this effect remain unclear and warrant further investigation.

Can the DEX/CRH test or markers of oxidative stress distinguish work-related stress from major depressive disorder and normal controls?

Hypothalamic-pituitary-adrenal (HPA)-axis hyperactivity measured by the combined dexamethasone-CRH test (DEX-CRH test) has been found in patients with major depressive disorder (MDD), whereas hypoactivity has been found in patients with work-related stress. We aimed to investigate the DEX-CRH test as a biomarker to distinguish between MDD and work-related stress (exhaustion disorder - ED). We hypothesized that there would be lower cortisol and ACTH response in participants with ED compared to MDD and healthy controls (HC). Also, we explored if the cortisol response of those patients interacted with robust markers of oxidative stress. Thirty inpatients with MDD and 23 outpatients with ED were recruited. Plasma cortisol and ACTH were sampled during a DEX-CRH test. The main outcome measure, area under the curve (AUC) for cortisol and ACTH, was compa-red between MDD vs. ED participants and a historical HC group. Secondary markers of oxidative stress urinary 8-oxodG and 8-oxoGuo; quality of sleep and psychometrics were obtained. Cortisol concentrations were higher in MDD and ED participants compared to HC, and no differences in AUC cortisol and ACTH were found between ED vs. MDD. Compared to ED, MDD participants had higher stress symptom severity and a lower sense of well-being. No differences in oxidative stress markers or quality of sleep between the groups were found. The result indicates that the patients with ED, like patients with MDD, are non-suppressors in DEX-CRH test and not hypocortisolemic as suggested.

The impact of major depressive disorder on glycaemic control in type 2 diabetes: a longitudinal cohort study using UK Biobank primary care records.

BACKGROUND: This study evaluates longitudinal associations between glycaemic control, measured by mean and within-patient variability of glycated haemaglobin (HbA1c) levels, and major depressive disorder (MDD) in individuals with type 2 diabetes (T2D), focusing on the timings of these diagnoses. METHODS: In UK Biobank, T2D was defined using self-report and linked health outcome data, then validated using polygenic scores. Repeated HbA1c measurements (mmol/mol) over the 10 years following T2D diagnosis were outcomes in mixed effects models, with disease duration included using restricted cubic splines. Four MDD exposures were considered: MDD diagnosis prior to T2D diagnosis (pre-T2D MDD), time between pre-T2D MDD diagnosis and T2D, new MDD diagnosis during follow-up (post-T2D MDD) and time since post-T2D MDD diagnosis. Models with and without covariate adjustment were considered. RESULTS: T2D diagnostic criteria were robustly associated with T2D polygenic scores. In 11,837 T2D cases (6.9 years median follow-up), pre-T2D MDD was associated with a 0.92 increase in HbA1c (95% CI: [0.00, 1.84]), but earlier pre-T2D MDD diagnosis correlated with lower HbA1c. These pre-T2D MDD effects became non-significant after covariate adjustment. Post-T2D MDD individuals demonstrated increasing HbA1c with years since MDD diagnosis ( ß = 0.51 , 95% CI: [0.17, 0.86]). Retrospectively, across study follow-up, within-patient variability in HbA1c was 1.16 (95% CI: 1.13-1.19) times higher in post-T2D MDD individuals. CONCLUSIONS: The timing of MDD diagnosis is important for understanding glycaemic control in T2D. Poorer control was observed in MDD diagnosed post-T2D, highlighting the importance of depression screening in T2D, and closer monitoring for individuals who develop MDD after T2D.

Gender-related alterations of serum trace elements and neurometabolism in the anterior cingulate cortex of patients with major depressive disorder.

BACKGROUND: It is widely known that sex differences have a significant impact on patients with major depressive disorder (MDD). This study aims to evaluate the sex-related connection between serum trace elements and changes in neurometabolism in the anterior cingulate cortex (ACC) of MDD patients. METHODS: 109 untreated MDD patients and 59 healthy controls underwent proton magnetic resonance spectroscopy (1H-MRS) under resting conditions. We measured metabolic ratios in the ACC from both sides. Additionally, venous blood samples were taken from all participants to detect calcium (Ca), phosphorus, magnesium (Mg), copper (Cu), ceruloplasmin (CER), zinc (Zn), and iron (Fe) levels. We performed association and interaction analyses to explore the connections between the disease and gender. RESULTS: In individuals with MDD, the Cu/Zn ratio increased, while the levels of Mg, CER, Zn and Fe decreased. Male MDD patients had lower Cu levels, while female patients had an increased Cu/Zn ratio. We observed significant gender differences in Cu, CER and the Cu/Zn ratio in MDD. Male patients showed a reduced N-acetyl aspartate (NAA)/phosphocreatine + creatine (PCr + Cr) ratio in the left ACC. The NAA/PCr + Cr ratio decreased in the right ACC in patients with MDD. In the left ACC of male MDD patients, the Cu/Zn ratio was inversely related to the NAA/PCr + Cr ratio, and Fe levels were negatively associated with the GPC + PC/PCr + Cr ratio. CONCLUSIONS: Our findings highlight gender-specific changes in Cu homeostasis among male MDD patients. The Cu/Zn ratio and Fe levels in male MDD patients were significantly linked to neurometabolic alterations in the ACC.

MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach.

BACKGROUND: Major depressive disorder (MDD) is notably underdiagnosed and undertreated due to its complex nature and subjective diagnostic methods. Biomarker identification would help provide a clearer understanding of MDD aetiology. Although machine learning (ML) has been implemented in previous studies to study the alteration of microRNA (miRNA) levels in MDD cases, clinical translation has not been feasible due to the lack of interpretability (i.e. too many miRNAs for consideration) and stability. METHODS: This study applied logistic regression (LR) model to the blood miRNA expression profile to differentiate patients with MDD (n = 60) from healthy controls (HCs, n = 60). Embedded (L1-regularised logistic regression) feature selector was utilised to extract clinically relevant miRNAs, and optimized for clinical application. RESULTS: Patients with MDD could be differentiated from HCs with the area under the receiver operating characteristic curve (AUC) of 0.81 on testing data when all available miRNAs were considered (which served as a benchmark). Our LR model selected miRNAs up to 5 (known as LR-5 model) emerged as the best model because it achieved a moderate classification ability (AUC = 0.75), relatively high interpretability (feature number = 5) and stability (ϕ̂Z=0.55) compared to the benchmark. The top-ranking miRNAs identified by our model have demonstrated associations with MDD pathways involving cytokine signalling in the immune system, the reelin signalling pathway, programmed cell death and cellular responses to stress. CONCLUSION: The LR-5 model, which is optimised based on ML design factors, may lead to a robust and clinically usable MDD diagnostic tool.

Gender differences in plasma S100B levels of patients with major depressive disorder.

BACKGROUND: Low concentrations of S100B have neurotrophic effects and can promote nerve growth and repair, which plays an essential role in the pathophysiological and histopathological alterations of major depressive disorder (MDD) during disease development. Studies have shown that plasma S100B levels are altered in patients with MDD. In this study, we investigated whether the plasma S100B levels in MDD differ between genders. METHODS: We studied 235 healthy controls (HCs) (90 males and 145 females) and 185 MDD patients (65 males and 120 females). Plasma S100B levels were detected via multifactor assay. The Mahalanobis distance method was used to detect the outliers of plasma S100B levels in the HC and MDD groups. The Kolmogorov-Smirnov test was used to test the normality of six groups of S100B samples. The Mann-Whitney test and Scheirer-Ray-Hare test were used for the comparison of S100B between diagnoses and genders, and the presence of a relationship between plasma S100B levels and demographic details or clinical traits was assessed using Spearman correlation analysis. RESULTS: All individuals in the HC group had plasma S100B levels that were significantly greater than those in the MDD group. In the MDD group, males presented significantly higher plasma S100B levels than females. In the male group, the plasma S100B levels in the HC group were significantly higher than those in the MDD group, while in the female group, no significant difference was found between the HC and MDD groups. In the male MDD subgroup, there was a positive correlation between plasma S100B levels and years of education. In the female MDD subgroup, there were negative correlations between plasma S100B levels and age and suicidal ideation. CONCLUSIONS: In summary, plasma S100B levels vary with gender and are decreased in MDD patients, which may be related to pathological alterations in glial cells.

Association of anhedonia with brain-derived neurotrophic factor and interleukin-10 in major depressive disorder.

BACKGROUND: Anhedonia, a core symptom of major depressive disorder (MDD), manifests in two forms: anticipatory and consummatory, reflecting a diminished capacity to anticipate or enjoy pleasurable activities. Prior studies suggest that brain-derived neurotrophic factor (BDNF) and interleukin-10 (IL-10) may play key roles in the emergence of anhedonia in MDD. The specific relationships between these biomarkers and the two forms of anhedonia remain unclear. This study investigated the potential links between BDNF, IL-10, and both forms of anhedonia in MDD patients. METHODS: This study included 43 participants diagnosed with MDD and 58 healthy controls. It involved detailed assessments of depression and anxiety levels, anticipatory and consummatory pleasure, cognitive functions, and a broad spectrum of plasma biomarkers, such as C-reactive protein, various interleukins, and BDNF. Using partial correlation, variables related to pleasant experiences were identified. Stepwise multiple linear regression analysis was applied to pinpoint the independent predictors of anhedonia in the MDD group. RESULTS: Demographically, both groups were comparable in terms of age, sex, body mass index, educational year, and marital status. Individuals with MDD displayed markedly reduced levels of anticipatory and consummatory pleasure, higher anxiety, and depression scores compared to healthy controls. Additionally, cognitive performance was notably poorer in the MDD group. These patients also had lower plasma diamine oxidase levels. Analysis linked anhedonia to impaired delayed memory. Regression results identified IL-10 and BDNF as independent predictors of anticipatory and consummatory anhedonia, respectively. CONCLUSION: These findings demonstrate that anticipatory and consummatory anhedonia are influenced by independent factors, thereby providing critical insights into the distinct neuroimmunological mechanisms that underlie various forms of anhedonia. Clinicl Trial Registration Number: NCT03790085.

Alterations in plasma endocannabinoid concentrations among individuals with major depression treated with electroconvulsive therapy.

The role of the endocannabinoid system (ECS) in depression and suicidality has recently emerged. The purpose of the study was to identify changes in plasma endocannabinoid concentrations of several endocannabinoids and correlate them with depressive symptoms and suicidality in patients with severe major depression undergoing electroconvulsive therapy (ECT). The study included 17 patients that were evaluated in four visits at different stages of therapy. At each visit depression, anxiety and suicidality symptoms were assessed and blood samples collected. Several endocannabinoid concentrations increased following six sessions of ECT, as 2-AG (p < 0.05) and LEA (p < 0.01), and following twelve sessions of ECT, as 2-AG (p < 0.05), AEA (p < 0.05), LEA (p < 0.05) and DH-Gly (p < 0.05). Endocannabinoids also correlated with symptoms of depression, anxiety and suicidality at baseline and at the sixth ECT session. Finally, we found one endocannabinoid, l-Gly, that differentiated between remitted and not-remitted patients at the seventh and thirteenth ECT sessions (p < 0.05). Our findings suggest that depression is markedly related to imbalance of the endocannabinoid system, and further regulated by ECT. Plasma endocannabinoids could be promising biomarkers for detection of depression response and remission.

Elevated thyroid stimulating hormone and metabolic syndrome risk in patients with first-episode and drug-naïve major depressive disorder: a large-scale cross-sectional study.

BACKGROUND: Metabolic syndrome (MetS) is common in major depressive disorder (MDD), but its relationship with thyroid hormones remains unclear. We aimed to examine the association of thyroid hormones and MetS in first-episode drug-naïve (FEDN) MDD patients. METHODS: We recruited 1718 unmedicated MDD patients in this cross-sectional study. MetS was defined based on the 2004 Chinese Diabetes Society Criteria. Serum thyroid hormones including free thyroxine (FT4), free triiodothyronine (FT3), thyroid-stimulating hormone (TSH), thyroid peroxidase antibodies (TPOAb), and anti-thyroglobulin (TGAb) were examined. We used the logistic regression model to determine risk factors for MetS and examined the performance of the regression model by using the Area Under the Curve (AUC). In addition, we performed the trend test to test whether the results were robust. RESULTS: The prevalence of MetS in unmedicated MDD patients was 34.4%. MDD patients with MetS had higher levels of serum TSH, TGAb, and TPOAb (all P < 0.001). Concurrently, serum TSH levels were independent risk factors for MetS in MDD patients (OR:1.49, 95%CI: 1.40-1.58), which could also distinguish MDD patients with and without MetS (AUC was 0.77). Additionally, in the trend test, the results also indicated a similar trend when TSH was used as a categorical variable (P for trend < 0.001). CONCLUSIONS: This study suggests that TSH levels were independent risk factors for MetS in FEDN MDD patients (OR:1.49). The examination of thyroid function may contribute to the early detection of MetS.

Elevated SCN11A concentrations associated with lower serum lipid levels in patients with major depressive disorder.

The pathogenesis of major depressive disorder (MDD) involves lipid metabolism. Our earlier research also revealed that MDD patients had much lower total cholesterol (TC) concentrations than healthy controls (HCs). However, it is still unclear why TC decreased in MDD. Here, based on the Ingenuity Knowledge Base's ingenuity pathway analysis, we found that sodium voltage-gated channel alpha subunit 11A (SCN11A) might serve as a link between low lipid levels and MDD. We analyzed the TC levels and used ELISA kits to measure the levels of SCN11A in the serum from 139 MDD patients, and 65 HCs to confirm this theory and explore the potential involvement of SCN11A in MDD. The findings revealed that TC levels were considerably lower and SCN11A levels were remarkably increased in MDD patients than those in HCs, while they were significantly reversed in drug-treatment MDD patients than in drug-naïve MDD patients. There was no significant difference in SCN11A levels among MDD patients who used single or multiple antidepressants, and selective serotonin reuptake inhibitors or other antidepressants. Pearson correlation analysis showed that the levels of TC and SCN11A were linked with the Hamilton Depression Rating Scales score. A substantial association was also found between TC and SCN11A. Moreover, a discriminative model made up of SCN11A was discovered, which produced an area under a curve of 0.9571 in the training set and 0.9357 in the testing set. Taken together, our findings indicated that SCN11A may serve as a link between low lipid levels and MDD, and showed promise as a candidate biomarker for MDD.

Gut microbiota and inflammatory factor characteristics in major depressive disorder patients with anorexia.

BACKGROUND: This study aimed to explore the gut microbiota and inflammatory factor characteristics in major depressive disorder (MDD) patients with anorexia and to analyze the correlation between gut microbiota and inflammatory factors, anorexia, and HAMD scores. METHODS: 46 MDD patients and 46 healthy controls (HC) were included in the study. The 46 MDD patients were divided into two groups according to whether they had anorexia:20 MDD without anorexia (MDA0 group) and 26 MDD with anorexia (MDA1 group). We used the Hamilton Depression Scale-24 (HAMD-24) to evaluate the depression status of all participants and 16 S ribosomal RNA (16 S rRNA)sequencing to evaluate the composition of the gut microbiota. Inflammatory factors in peripheral blood such as C-reactive protein (CRP) were detected using enzyme-linked immunosorbent assay (ELISA). Spearman's correlation analysis was used to evaluate the correlation between gut microbiota and inflammatory factors, HAMD scores, and anorexia. RESULTS: 1). CRP was significantly higher in the MDA0, MDA1, than HC. 2). An analysis of α-diversity shows: the Simpson and Pielou indices of the HC group are higher than the MDA1 group (P < 0.05). 3). The ß-diversity analysis shows differences in the composition of microbial communities between the MDA0, MDA1, and HC group. 4). A correlation analysis showed that Blautia positively correlated with anorexia, HAMD scores, and CRP level, whereas Faecalibacterium, Bacteroides, Roseburia, and Parabacteroides negatively correlated with anorexia, HAMD scores, and CRP level. 5). The receiver operating characteristic (ROC) curve was drawn using the differential bacterial genera between MDD patients with or without anorexia as biomarkers to identify whether MDD patients were accompanied with anorexia, and its area under curve (AUC) was 0.85. The ROC curve was drawn using the differential bacterial genera between MDD patients with anorexia and healthy controls as biomarkers to diagnose MDD patients with anorexia, with its AUC was 0.97. CONCLUSION: This study suggested that MDD patients with anorexia had a distinct gut microbiota compared to healthy individuals, with higher level of CRP. Blautia was more abundant in MDD patients with anorexia and positively correlated with CRP, HAMD scores, and anorexia. The gut microbiota might have influenced MDD and anorexia through the inflammatory factor CRP.

U-shaped association between fasting blood glucose and suicide attempts in Chinese patients with first-episode drug-naïve major depressive disorder.

BACKGROUND: Evidence regarding the relationship between fasting blood glucose (FBG) and suicide attempts (SA) in patients with major depressive disorder (MDD) was limited. Therefore, the objective of this research was to investigate whether FBG was independently related to SA in Chinese patients with first-episode drug-naïve (FEDN) MDD after adjusting for other covariates. METHODS: The present study was a cross-sectional study. A total of 1718 participants (average age: 34.9 ± 12.4 years, 65.8% females) with FEDN MDD were involved in a hospital in China from September 2016 to December 2018. Multiple logistic regression analysis and smooth curve fitting were used to estimate the association between FBG and the risk of SA. The threshold effect was examined by the two-piecewise linear regression model. Interaction and stratified analyses were conducted according to sex, education, marital status, comorbid anxiety, and psychotic symptoms. RESULTS: The prevalence of SA in patients with FEDN MDD was 20.1%. The result of fully adjusted binary logistic regression showed FBG was positively associated with the risk of SA (odds ratio (OR) = 1.62, 95% CI: 1.13-2.32). Smoothing plots also revealed a nonlinear relationship between FBG and SA, with the inflection point of FBG being 5.34 mmol/l. The effect sizes and the confidence intervals on the left and right sides of the inflection point were 0.53 (0.32-0.88, P = 0.014) and 1.48 (1.04-2.10, P = 0.030), respectively. CONCLUSIONS: A U-shaped relationship between FBG and SA in FEDN MDD patients was found, with the lowest risk of SA at a FBG of 5.34 mmol/l, indicating that both the lower and higher FBG levels may lead to an increased risk of SA.

AI algorithm combined with RNA editing-based blood biomarkers to discriminate bipolar from major depressive disorders in an external validation multicentric cohort.

Bipolar disorder (BD) is a leading cause of disability worldwide, as it can lead to cognitive and functional impairment and premature mortality. The first episode of BD is usually a depressive episode and is often misdiagnosed as major depressive disorder (MDD). Growing evidence indicates that peripheral immune activation and inflammation are involved in the pathophysiology of BD and MDD. Recently, by developing a panel of RNA editing-based blood biomarkers able to discriminate MDD from depressive BD, we have provided clinicians a new tool to reduce the misdiagnosis delay observed in patients suffering from BD. The present study aimed at validating the diagnostic value of this panel in an external independent multicentric Switzerland-based cohort of 143 patients suffering from moderate to major depression. The RNA-editing based blood biomarker (BMK) algorithm developped allowed to accurately discriminate MDD from depressive BD in an external cohort, with high accuracy, sensitivity and specificity values (82.5 %, 86.4 % and 80.8 %, respectively). These findings further confirm the important role of RNA editing in the physiopathology of mental disorders and emphasize the possible clinical usefulness of the biomarker panel for optimization treatment delay in patients suffering from BD.