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Background: Most patients with the major depressive disorder (MDD) have varying degrees of impaired social functioning, and functional improvement often lags behind symptomatic improvement. However, it is still unclear if certain neurobiological factors underlie the deficits of social function in MDD. The aim of this study was to investigate the biomarkers of social function in MDD using structural magnetic resonance imaging (MRI). Methods: 3T anatomical MRI was obtained from 272 subjects including 46 high-functioning (high-SF, Sheehan Disability Scale (SDS) rating < 18) and 63 low-functioning (low-SF, SDS score ≥ 18) patients with MDD and 163 healthy controls (HC). Voxel-based morphometry (VBM) was employed to locate brain regions with grey matter (GM) volume differences in relation to social function in MDD. Regions showing GM differences in relation to social function at baseline were followed up longitudinally in a subset of 38 patients scanned after 12-week treatment. Results: Volume of right parahippocampal gyrus (rPHG) was significantly reduced in low-SF patients with MDD when compared to high-SF ones (FDR-corrected p < 0.05). Over 12 weeks of follow-up, though SF improved overall, the high and low-SF subgroups continued to differ in their SF, but had no progressive changes in PHG volume. Limitations: Limited functional assessment, high drop-out rate and median-based grouping method. Conclusions: Greater GM volume (GMV) of the rPHG may mark better social function in patients with MDD.

Background This study aimed to explore subtypes of treatment-resistant depression (TRD). Methods Latent class analysis (LCA) was performed on clinical and demographic data collected from 375 patients with TRD. Clinical variables were compared across subtypes. Treatment outcomes across subtypes of TRD were compared separately for those within each subtype with anxiety (those with a HRSD-17 anxiety/somatization factor score ≥ 7) and those without anxiety. LCA subtypes were compared using Cochran's and Mantel–Haenszel χ2 test, respectively. Unordered multinomial logistic regression was used to assess clinical correlates of TRD subtypes. Results Three categories were detected: severe depression (66%), moderate depression with anxiety (9%) and mild depression with anxiety/somatization (25%). Gender, age, age at first onset, family monthly income, number of hospitalizations, HRSD-17 and clinical global impression-severity (CGI) scores were significantly different across the three groups. Remission rates were significantly different among anxious cases with severe (43.75%), moderate (22.73%) and mild (26.25%) depression subtypes. Compared to cases in the mild depression group, those in the severe depression group had a greater likelihood of being male, having a later age of first onset, higher numbers of hospitalization, higher HRSD-17 and CGI total scores, and lower family income. Those in the moderate depression group were more likely to be male and have lower family income than those in the mild depression group. Limitations Representative bias, relatively small sample size, unbalanced group size and incomplete indicator variables might have a negative effect on the validity and generalization of the findings. Conclusions Depression severity could be a basis for subtype classification of patients with TRD. The classification of latent class of TRD observed in our study was similar to the structure found in MDD. Longitudinal research into the stability of the latent structure of TRD across illness course is merited as is research into treatment outcomes for TRD subtypes.

Somatic symptoms are prevalent in patients with major depressive disorder (MDD) and often associated with a high risk of suicide. However, which somatic symptoms display as significant risk factors for suicidal ideation (SI) is still poorly understood in MDD.Two thousand and seventeen Chinese patients with first-episode MDD from the National Survey on Symptomatology of Depression were included in this study. A doctor-rating assessment questionnaire was constructed to evaluate depression related somatic symptoms, and stepwise logistic regression analysis was performed to explore the relationship between somatic symptoms and SI.Our results showed a high prevalence of current SI in first-episode MDD (50.87%), while no significant gender differences (53.32% vs. 49.26%, P = 0.076) were observed. In addition, patients who have more somatic symptoms would be at the higher risk to elicit SI, and stepwise logistic regression analysis indicated that age (β = -0.020, P 0.001), Pre-verbal physical complaints (β = 0.356, P = 0.001), Sensory system complaints (β = 0.707, P = 0.000), Other pain conditions (β = 0.434, P 0.001), Late insomnia (β = 0.267, P = 0.008), Hypersomnia (β = 0.936, P 0.001), Weight loss (β = 0.272, P = 0.006), Hyposexuality (β = 0.513, P = P 0.001) were strongly associated with current SI in first-episode Chinese major depression.Somatic symptoms are strongly associated with SI in first-episode MDD. It is suggestive for clinicians to show concerns for patients' somatic symptoms in practice.

The advances in the Internet and related technologies may lead to changes in professional roles of psychiatrists and psychotherapists. The application of artificial intelligence (AI) and electronic measurement-based care (eMBC) in the treatment of depressive disorder has addressed more interest. AI could play a role in population health management and patient administration as well as assist physicians to make a decision in the real-world clinical practice. The eMBC strengthens MBC through web/mobile devices and telephone consulting services, to monitor disease progression, and customizes the MBC interface in electronic medical record systems (EMRs).

BackgroundInflammation that is mediated by microglia activation plays an important role in the pathogenesis of depression. Microglia activation can lead to an increase in the levels of proinflammatory cytokines, including TNF-α, which leads to neuronal apoptosis in the specific neural circuits of some brain regions, abnormal cognition and treatment-resistant depression (TRD). Protein kinase C (PKC) is a key regulator of the microglia activation process. We assume that the abnormality in PKC might result in abnormal microglia activation, neuronal apoptosis, significant changes in emotional and cognitive neural circuits, and TRD. In the current study, we plan to target at the PKC signal pathway to improve the TRD treatment outcome.Methods and analysisThis is a 12-week, ongoing, randomised, placebo-controlled trial. Patients with TRD (N=180) were recruited from Shanghai Mental Health Center, Shanghai Jiao Tong University. Healthy control volunteers (N=60) were recruited by advertisement. Patients with TRD were randomly assigned to ‘escitalopram+golimumab (TNF-α inhibitor)’, ‘escitalopram+calcium tablet+vitamin D (PKC activator)’ or ‘escitalopram+placebo’ groups. We define the primary outcome as changes in the 17-item Hamilton Depression Rating Scale (HAMD-17). The secondary outcome is defined as changes in anti-inflammatory effects, cognitive function and quality of life.DiscussionThis study might be the first randomised, placebo-controlled trial to target at the PKC signal pathway in patients with TRD. Our study might help to propose individualised treatment strategies for depression.Trial registration numberThe trial protocol is registered with ClinicalTrials.gov under protocol ID 81930033 and ClinicalTrials.gov ID NCT04156425.

It has been suggested that inflammation is involved in the pathophysiology of depression. As tissue-specific macrophages in the central nervous system (CNS), microglia play an important role in neuroinflammation. Resident microglia become activated towards the pro-inflammatory (M1) phenotype or the anti-inflammatory (M2) phenotype during neuroinflammation. In the CNS, neurons report to microglia regarding their statuses and can regulate microglial activation, while microglia also modulate neuronal activities, including neuroplasticity. The molecular mechanisms underlying the communication between microglia and neurons, which include intracellular and extracellular signalling pathways, might be complex and of great importance for new research on the pathogenesis of depression. The present review aims to discuss the common cellular and molecular mechanisms for microglial activation and aberrant neuroplasticity in depression and the role of these processes in the pathogenesis of depression.

Background Suicide risk is greatly increased in depression. Detection of those at risk is clinically important. Hence, this study aimed to evaluate the prevalence and identify independent risk factors associated with suicidal ideation (SI) in a widespread symptomatology within and outside DSM framework. Methods This study was part of the National Survey on Symptomatology of Depression (NSSD) which was designed to investigate the magnitude of symptoms of current major depressive episode in China. Stepwise multivariable logistic regression was performed to examine the independent risk factors for SI, including variables that are statistically significant in univariate analysis. Receiver operating characteristic (ROC) was used to evaluate the performance of the regression model. Results A total of 3275 patients (1293 males and 1982 females) were included in our analysis. Of these, 1750 patients (53.4%) had SI. Independent risk predictors included crying (P = 0.000; odds ratio = 1.827), helplessness (P = 0.000; odds ratio = 1.514), worthlessness (P = 0.001; odds ratio = 1.359), hopelessness (P = 0.000; odds ratio = 1.805), unusually restless (P = 0.005; odds ratio = 1.276), self-harm (P = 0.000; odds ratio = 3.385), mood-incongruent psychosis (P = 0.000; odds ratio = 2.782), feeling losing control of oneself (P = 0.009; odds ratio = 1.352), hypersomnia (P = 0.000; odds ratio = 1.805), sensory system complaints (P = 0.000; odds ratio = 1.546), derealization (P = 0.006; odds ratio = 1.580), guilt (P = 0.002; odds ratio = 1.332), suicidal attempts (P = 0.000; odds ratio = 2.841), male gender (P = 0.001; odds ratio = 0.756), the total course of depression (P = 0.010; odds ratio = 1.003) in the regression model. In addition, the areas under the curve of the ROC and the accuracy for the regression model were 0.80 and 0.76, respectively. Conclusions This study provided an effective risk model for SI in MDD and indicated that all these factors in our model allow better the employment of preventative measures.