Unipolar Depressed Patients Research Articles

Suicidality Is Most Centrally Situated Within Network of Depression Symptom Criteria in Unipolar Depression Patients With Mood Stabilizer in Asia

Lithium and mood stabilizers are considered effective augmentation agents of antidepressants for treatment-resistant depression. Thus, this study aimed to estimate the network structure of depression symptom criteria among unipolar depression patients with mood stabilizers, using data from the Research on Asian Psychotropic Prescription Patterns for mood stabilizers (REAP-MS). We estimated a network of the 9 depression symptom criteria among 411 unipolar depression patients in Asia. Each of the depression symptom criteria was considered to be a dichotomous categorical variable. Suicidality (suicidal ideation or attempt) was the most centrally situated within the network of depression symptoms, followed by depressed mood, loss of energy, anhedonia and weight loss or gain. Contrastingly, concentration problem was the least interconnected. The depression symptom criteria were organized into 4 clusters by the community detection method. The findings suggest that suicidality may be one of the significant therapeutic target symptoms in unipolar depression patients with mood stabilizers.

Seasonality in mood disorders: Probing association of accelerometer-derived physical activity with daylength and solar insolation

Mood disorders are the leading cause of disability worldwide. Up to 30 percent of individuals with major depressive disorder (MDD) and bipolar disorder (BD) display a seasonal pattern of onset, a phenomenon now recognized in the official diagnostic manuals (DSM-5 and ICD-11). Very little is known about the influence of day length (photoperiod) and sunlight intensity (solar insolation) on seasonal patterns in MDD and BD. Here we report a quantitative approach to examine the relationship between sunlight measures and objectively measured motor activity patterns to understand environmental factors driving seasonality in MDD and BD. Our generalized linear model (GLM) assessment of the Depresjon dataset, which includes short-term (up to two weeks) motor activity recordings of 23 unipolar and bipolar depressed patients and 32 healthy controls recruited to the study at the University of Bergen Norway (60.4° N latitude, 5.3° E longitude), revealed significant association of accelerometer-derived daytime physical activity with participant’s depressed state (p<0.001), photoperiod (p<0.001), and solar insolation (p<0.001). Our study presents a generalizable strategy to decipher the complex interplay between sunlight, physical activity, and depressed state using open-source digital tools. The ability to identify mood disturbances, particularly in seasonally susceptible individuals, using passive digital biomarker data offers great promise in informing next-generation predictive, personalized diagnostics in mental health.

Convergence and divergence in neurostructural signatures of unipolar and bipolar depressions: Insights from surface-based morphometry and prospective follow-up

BackgroundBipolar disorder (BD) is often misidentified as unipolar depression (UD) during its early stages, typically until the onset of the first manic episode. This study aimed to explore both shared and unique neurostructural changes in patients who transitioned from UD to BD during follow-up, as compared to those with UD. MethodsThis study utilized high-resolution structural magnetic resonance imaging (MRI) to collect brain data from individuals initially diagnosed with UD. During the average 3-year follow-up, 24 of the UD patients converted to BD (cBD). For comparison, the study included 48 demographically matched UD patients who did not convert and 48 healthy controls. The MRI data underwent preprocessing using FreeSurfer, followed by surface-based morphometry (SBM) analysis to identify cortical thickness (CT), surface area (SA), and cortical volume (CV) among groups. ResultsThe SBM analysis identified shared neurostructural characteristics between the cBD and UD groups, specifically thinner CT in the right precentral cortex compared to controls. Unique to the cBD group, there was a greater SA in the right inferior parietal cortex compared to the UD group. Furthermore, no significant correlations were observed between cortical morphological measures and cognitive performance and clinical features in the cBD and UD groups. LimitationsThe sample size is relatively small. ConclusionsOur findings suggest that while cBD and UD exhibit some common alterations in cortical macrostructure, numerous distinct differences are also present. These differences offer valuable insights into the neuropathological underpinnings that distinguish these two conditions.

Identifying misdiagnosed bipolar disorder using support vector machine: feature selection based on fMRI of follow-up confirmed affective disorders

Nearly a quarter of bipolar disorder (BD) patients were misdiagnosed as major depressive disorder (MDD) patients, which cannot be corrected until mania/hypomania develops. It is important to recognize these obstacles so that the appropriate treatment can be initiated. Thus, we sought to distinguish patients with BD from MDD, especially to identify misdiagnosed BD before mania/hypomania, and further explore potential trait features that allow accurate differential diagnosis independent of state matters. Functional magnetic resonance imaging scans were performed at baseline on 92 MDD patients and 48 BD patients. The MDD patients were then followed up for more than two years. After follow-up, 23 patients transformed into BD (tBD), and 69 patients whose diagnoses remained unchanged were eligible for unipolar depression (UD). A support vector machine classifier was trained on the amygdala-based functional connectivity (FC) of 48 BD and 50 UD patients using a novel region-based feature selection. Then, the classifier was tested on the dataset, encompassing tBD and the remaining UD. It performed well for known BD and UD and can also distinguish tBD from UD with an accuracy of 81%, sensitivity of 82.6%, specificity of 79%, and AUC of 74.6%, respectively. Feature selection results revealed that ten regions within the cortico-limbic neural circuit contributed most to classification. Furthermore, in the FC comparisons among diseases, BD and tBD shared almost overlapped FC patterns in the cortico-limbic neural circuit, and both of them presented pronounced differences in most regions within the circuit compared with UD. The FC values of the most discriminating brain regions had no prominent correlations with the severity of depression, anxiety, and mania/hypomania (FDR correction). It suggests that BD possesses some trait features in the cortico-limbic neural circuit, rendering it dichotomized by the classifier based on known-diagnosis data.

Razlike u indikatorima inflamacije obolelih od bipolarne i unipolarne depresije

Introduction/Aim: Patients with bipolar disorder, unrecognized and with a delayed onset of manic or hypomanic episodes are often mistakenly diagnosed with unipolar depression (UD) due to shared symptomatology. The two disorders, however, have related but not identical etiopathogenesis. Immune system alterations might play a crucial role in both the onset and manifestation of these conditions. This study aimed to compare immune markers between patients with bipolar depression (BD) and unipolar depression (UD) and explore their associations with acute episode characteristics and disease progression. Material and Methods: This retrospective study included patients with BD (n=60) and UD (n=242) who were hospitalized within a two year period and whose sociodemographic information, acute episode and course of illness characteristics, and indicators of inflammation were available. Results: Patients with BD exhibited elevated mean platelet volume (MPV) compared to those with UD. MPV levels correlated with clinical characteristics in both groups; higher MPV was observed in UD patients with an earlier age of onset and a longer duration of illness. In BD patients, elevated MPV was associated with the severity of psychopathology, particularly in individuals with a history of suicide attempts and a prolonged duration of untreated disorder. Conclusion: This study indicates the presence of chronic low-grade inflammation in specific subpopulations of patients with affective disorders. Immune changes are distinct in regard to the polarity of the disorder and could be a potential indicator of the severity of psychopathology and illness chronicity.

Electroconvulsive therapy is associated with increased immunoreactivity of neuroplasticity markers in the hippocampus of depressed patients

Electroconvulsive therapy (ECT) is an effective therapy for depression, but its cellular effects on the human brain remain elusive. In rodents, electroconvulsive shocks increase proliferation and the expression of plasticity markers in the hippocampal dentate gyrus (DG), suggesting increased neurogenesis. Furthermore, MRI studies in depressed patients have demonstrated increases in DG volume after ECT, that were notably paralleled by a decrease in depressive mood scores. Whether ECT also triggers cellular plasticity, inflammation or possibly injury in the human hippocampus, was unknown. We here performed a first explorative, anatomical study on the human post-mortem hippocampus of a unique, well-documented cohort of bipolar or unipolar depressed patients, who had received ECT in the 5 years prior to their death. They were compared to age-matched patients with a depressive disorder who had not received ECT and to matched healthy controls. Upon histopathological examination, no indications were observed for major hippocampal cell loss, overt cytoarchitectural changes or classic neuropathology in these 3 groups, nor were obvious differences present in inflammatory markers for astrocytes or microglia. Whereas the numbers of proliferating cells expressing Ki-67 was not different, we found a significantly higher percentage of cells positive for Doublecortin, a marker commonly used for young neurons and cellular plasticity, in the subgranular zone and CA4 / hilus of the hippocampus of ECT patients. Also, the percentage of positive Stathmin 1 cells was significantly higher in the subgranular zone of ECT patients, indicating neuroplasticity. These first post-mortem observations suggest that ECT has no damaging effects but may rather have induced neuroplasticity in the DG of depressed patients.

Cognitive distortions and perfectionism during bipolar and unipolar depressive episode

BackgroundThe aim of the current study was to compare bipolar depression (BD) and unipolar depression (UD) patients and healthy controls in terms of their cognitive distortions and perfectionist traits during acute depressive episodes.ResultsThe current dissertation study is a cross-sectional study consisting of 80 patients with unipolar depression, 80 patients with bipolar depression, and 80 healthy controls. Sociodemographic and Clinical Data Form, Cognitive Distortion Scale (CDS), Frost’s Multidimensional Perfectionism Scale (FMPS), Hamilton Anxiety Rating Scale (HARS), Hamilton Depression Rating Scale (HDRS), and Young Mania Rating Scale (YMRS) were used as measurement tools. Healthy controls were selected on the basis that they had the same gender and age distribution as the other participants. It was found that patients with unipolar and bipolar depression had statistically equal but higher total CDS interpersonal and personal achievement scores than healthy controls, and all subtypes of the CDS labeling score were higher in the unipolar depression group than in the other groups. It was found that both depression groups had higher FMPS self-oriented and social-oriented perfectionism scores than healthy controls, lower others-oriented perfectionism scores than healthy controls, and there were no statistically significant differences between them in terms of perfectionism subtypes.ConclusionsIn the light of the research data, it was found that the patients with bipolar/unipolar depression had more cognitive distortion than healthy controls and cognitive distortion was not significantly different in the two groups. According to the research data, it is observed that perfectionism is higher in unipolar depression than in bipolar depression. The data obtained have the potential to provide a theoretical basis for a psychotherapeutic approach.

Systemic inflammation and oxidative stress markers in patients with unipolar and bipolar depression: A large-scale study

ObjectiveNumerous studies have demonstrated that neutrophil/HDL ratio (NHR), lymphocyte/HDL ratio (LHR), monocyte/HDL (MHR) ratio, platelet/HDL ratio (PHR), neutrophil/ALB ratio (NAR) and platelet/ALB ratio (PAR) can serve as systemic inflammation and oxidative stress markers in a variety of diseases. However, few studies have estimated the associations of these markers with unipolar depression (UD) and bipolar depression (BD), as well as psychotic symptoms in UD and BD. Methods6297 UD patients, 1828 BD patients and 7630 healthy subjects were recruited. The differences in these indicators among different groups were compared, and the influencing factors for the occurrence of UD or BD and psychotic symptoms were analyzed. ResultsThese ratios displayed unique variation patterns across different diagnostic groups. BD group exhibited higher NHR, LHR, MHR, NAR and lower PAR than UD and HC groups, UD group showed higher MHR than HC group. The psychotic UD group had higher NHR, LHR, MHR and NAR than non-psychotic UD group. Higher LHR, MHR, NAR and lower PAR were risk factors in BD when compared to UD group. ConclusionsOur study demonstrated differences in inflammation and oxidative stress profile between UD and BD patients, as well as between subjects with or without psychotic symptom exist, highlighting the role of inflammation and oxidative stress in the pathophysiology of UD and BD.

A smartphone- and wearable-based biomarker for the estimation of unipolar depression severity.

Drug development for mood disorders can greatly benefit from the development of robust, reliable, and objective biomarkers. The incorporation of smartphones and wearable devices in clinical trials provide a unique opportunity to monitor behavior in a non-invasive manner. The objective of this study is to identify the correlations between remotely monitored self-reported assessments and objectively measured activities with depression severity assessments often applied in clinical trials. 30 unipolar depressed patients and 29 age- and gender-matched healthy controls were enrolled in this study. Each participant's daily physiological, physical, and social activity were monitored using a smartphone-based application (CHDR MORE™) for 3 weeks continuously. Self-reported depression anxiety stress scale-21 (DASS-21) and positive and negative affect schedule (PANAS) were administered via smartphone weekly and daily respectively. The structured interview guide for the Hamilton depression scale and inventory of depressive symptomatology-clinical rated (SIGHD-IDSC) was administered in-clinic weekly. Nested cross-validated linear mixed-effects models were used to identify the correlation between the CHDR MORE™ features with the weekly in-clinic SIGHD-IDSC scores. The SIGHD-IDSC regression model demonstrated an explained variance (R2) of 0.80, and a Root Mean Square Error (RMSE) of ± 15 points. The SIGHD-IDSC total scores were positively correlated with the DASS and mean steps-per-minute, and negatively correlated with the travel duration. Unobtrusive, remotely monitored behavior and self-reported outcomes are correlated with depression severity. While these features cannot replace the SIGHD-IDSC for estimating depression severity, it can serve as a complementary approach for assessing depression and drug effects outside the clinic.

Unipolar ve Bipolar Depresif Bozuklukta Bazı Hematolojik Parametrelerin

Background: Major depressive disorder and bipolar disorder, which are the most severe types of mood disorders, are among the diseases that cause the most disability worldwide. One of the biggest challenges in providing early and effective treatment in mood disorders is the inability to make an early differential diagnosis between UD and BD. Many studies have suggested that neuroinflammation may play a role in the pathophysiology of mood disorders. Neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), and monocyte/lymphocyte ratio (MLR) are relatively cheap hematological parameters recommended to measure the level of inflammation. This study aimed to examine the potential role of inflammatory processes in the pathogenesis of unipolar depression(UD) and bipolar depression(BD) by analyzing various hematologic markers, including NLR, PLR, and MLR Materials and Methods: The patient group comprised 54 individuals(UD: 31, BD: 23), while the healthy control(HC) group comprised 40 individuals. The study compared the values of hematologic markers between the groups. Results:The study found significant differences only in the levels of NLR among the analyzed hematologic markers(p=0.004). When the UD and BD groups were compared with HC separately, NLR was significantly higher in both the UD and BD groups compared to the HC group(p=0.002, p=0.015). When UD and BD were compared with each other, there was no significant difference in terms of NLR(P=0,416). Conclusions: In our study, although there was no significant difference between BD and UD in terms of NLR, PLR and MLR, the higher NLR in both patient groups compared to HC suggests the presence of inflammation in both BD and UD patients. More evidence is needed to evaluate it as a disease-specific marker.

Unipolar and Bipolar Depression Detection and Classification Based on Actigraphic Registration of Motor Activity Using Machine Learning and Uniform Manifold Approximation and Projection Methods.

Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting the number of daily steps or calories expended. Due to the patient's inability to obtain the necessary information to understand their conditions and detect illness, such as depression, objectively, methods for evaluating various mental disorders, such as the Montgomery-Asberg depression rating scale (MADRS) and observations, currently require a significant amount of effort on the part of specialists. In this study, a novel dataset was provided, comprising sensor data gathered from depressed patients. The dataset included 32 healthy controls and 23 unipolar and bipolar depressive patients with motor activity recordings. Along with the sensor data collected over several days of continuous measurement for each patient, some demographic information was also offered. The result of the experiment showed that less than 70 of the 100 epochs of the model's training were completed. The Cohen Kappa score did not even pass 0.1 in the validation set, due to an imbalance in the class distribution, whereas in the second experiment, the majority of scores peaked in about 20 epochs, but because training continued during each epoch, it took much longer for the loss to decline before it fell below 0.1. In the second experiment, the model soon reached an accuracy of 0.991, which is as expected given the outcome of the UMAP dimensionality reduction. In the last experiment, UMAP and neural networks worked together to produce the best outcomes. They used a variety of machine learning classification algorithms, including the nearest neighbors, linear kernel SVM, Gaussian process, and random forest. This paper used the UMAP unsupervised machine learning dimensionality reduction without the neural network and showed a slightly lower score (QDA). By considering the ratings of the patient's depressive symptoms that were completed by medical specialists, it is possible to better understand the relationship between depression and motor activity.

Characterizing Unipolar and Bipolar Depression by Alterations in Inflammatory Mediators and the Prefrontal-Limbic Structural Network

Objective. The prefrontal-limbic system is closely associated with emotion processing in both unipolar depression (UD) and bipolar depression (BD). Evidence for this link is derived mostly from task-fMRI studies, with limited support from structural findings. Therefore, this study explores the differences in the emotional circuit in these two disorders on a structural, large-scale network basis, coupled with the highly noted inflammatory and growth factors. Methods. In this study, 31 BD patients, 37 UD patients, and 61 age-, sex-, and education-matched healthy controls (HCs) underwent diffusion-weighted imaging (DWI) scanning and serum cytokine sampling. The study compared cytokine levels and prefrontal-limbic network alterations among the three groups and explored potential biological and neurobiological markers to distinguish the two disorders using graph theory, network-based statistics (NBS), and logistic regression. Results. Compared to BD patients, UD patients showed greater s-100β protein levels, higher efficiency of the right amygdala, and significantly elevated prefrontal-cingulate-amygdala subnetwork intensity. Importantly, the altered prefrontal-cingulate-amygdala subnetwork, nodal efficiency of the right amygdala, IL-8, IL-17, and s-100β levels were risk factors for the diagnosis of UD, whereas anxiety symptoms tended to closely correlate with BD. Moreover, binary logistic regression manifested these factors achieved an area under the curve (AUC) of the receiver operating characteristics (ROC) of 0.949, with 0.875 sensitivity and 0.938 specificity in UD vs. BD classification. Conclusions. These findings narrow the gap in the structural network of emotional circuits in bipolar and unipolar depression, pointing to distinct emotion-processing mechanisms in both disorders.

Pain perception and modulation profiles in patients suffering from unipolar and bipolar depression

There is a need to find meaningful markers that can distinguish between unipolar and bipolar depression (UPD and BD respectively). In patients with unipolar depression (UPD), unique and inconsistent patterns of pain perception and modulation have been widely described. At the same time, patterns of pain processing in BD have been poorly studied. A recent study showed that initial evaluation of pain intensity is elevated in UPD compared with healthy controls (HC). The aim of the present study was to compare the pain processing profile between UPD and BD. Participants were 40 UPD patients, 36 age- and sex-matched BD patients, and 35 healthy controls (HC). Thermal stimuli were used to determine sensory threshold and pain threshold. Pain 60 temperature (i.e., a temperature that elicits a pain rating of 60 out of 100) was the first noxious stimulus administered during the experimental session. Central pain inhibition was assessed using conditioned pain modulation (CPM). All participants completed questionnaires on sociodemographic and clinical information. The only discriminatory experimental pain finding between UPD and BD was related to pain-60. Patients diagnosed with UPD had significantly lower pain-60. indices than patients with BD (p = .004). This finding was confounded by the level of anxiety symptoms. Patients diagnosed with UPD initially rated their pain intensity higher than patients with BPD and HC. Nonetheless, this difference becomes insignificant when controlling for the higher anxiety scores in the UPD group. Possibly, the higher levels of anxiety were manifested in a pronounced negative cognitive bias. This finding is important for the management of pain symptoms in patients with UPD and BD. Further studies should focus on anxiety as a mediator in pain processing. We used the pain 60-temperature test, a method not yet established as an instrument for this purpose, to assess an evaluation bias. Antidepressants treatment of participants might have an antinociceptive effect. Physical and mental comorbidities of the participants may confound the results of our study.

Resting-state Fronto-limbic Connectivity in Unipolar Depressive Patients as a Predictor for Sporadic Conversion to (Hypo)mania

IntroductionPatients with a bipolar disorder (BD) may experience one or several episodes of major depression before transitioning into a manic phase. Given that treatment with common antidepressants may exacerbate symptoms of mania in patients with BD, initial diagnosis of major depressive disorder (MDD) is a significant issue affecting BD patients. Currently, a family history of BD is used as an early identifier for BD, but as genetic factors associated with BD confer susceptibility to a wide range of psychiatric illnesses, this approach lacks specificity. Thus, there is a pressing need for a biomarker which specifically predicts development of bipolar symptoms in patients with MDD, rather than a trait vulnerability to psychiatric disorderObjectives The aim of this study is to assess alterations in fronto-limbic function that exist prior to the manifestation of the first manic episode in BD patients without familial predisposition for BD.MethodsTo identify a biomarker for conversion to BD we performed a study in a naturalistic sample of MDD patients without a familial risk for BD, which were followed for 9 years. We used a seed-based functional connectivity analysis to assess differences in resting-state fronto-limbic connectivity between MDD patients who converted to BD during the follow-up period (n = 11), and non-converting MDD patients (n = 56).ResultsClusters of significantly reduced functional connectivity were found in the fronto-limbic network of prospective converters relative to non-converters.ConclusionsFindings suggest that alterations of fronto-limbic functional connectivity during episodes of depression predate and associate with conversion to BD later in life, in the absence of familial risk. These fronto-limbic functional connectivity disturbances may be of interest for diagnosing early-stage BD, and may offer insight in the mechanisms that drive conversion in the absence of familial predisposition. Findings from this study need to be verified through large-scale longitudinal imaging studies in naturalistic cohorts of MDD patients.Disclosure of InterestNone Declared

Neurochemical and microstructural alterations in bipolar and depressive disorders: A multimodal magnetic resonance imaging study.

Depression in bipolar disorder (BD) is often misdiagnosed as unipolar depression (UD), leading to mistreatments and poor clinical outcomes in many bipolar patients. Herein, we report direct comparisons between medication-free patients with BD and those with UD in terms of the microstructure and neurometabolites in eight brain regions. A total of 20 patients with BD, 30 with UD patients, and 20 matched healthy controls (HCs) underwent 3.0T magnetic resonance imaging with chemical exchange saturation transfer (CEST) for glutamate (Glu; GluCEST) imaging, multivoxel magnetic resonance spectroscopy, and diffusion kurtosis imaging. Compared with HCs, patients with UD showed significantly lower levels of multiple metabolites, GluCEST% values, and diffusional kurtosis [mean kurtosis (MK)] values in most brain regions. In contrast, patients with BD presented significantly higher levels of Glu in their bilateral ventral prefrontal white matter (VPFWM), higher choline (Cho)-containing compounds in their left VPFWM and anterior cingulate cortex (ACC), and higher GluCEST% values in their bilateral VPFWM and ACC; moreover, reduced MK in these patients was more prominent in the left VPFWM and left thalamus. The findings demonstrated that both patients with UD and BD have abnormal microstructure and metabolic alterations, and the changes are not completely consistent in the prefrontal lobe region. Elevated Glu, Cho, and GluCEST% in the ACC and VPFWM of patients with UD and BD may help in differentiating between these two disorders. Our findings support the significance for the microstructural integrity and brain metabolic changes of the prefrontal lobe region in BD and UD.

Distinguishing between bipolar depression and unipolar depression based on the reward circuit activities and clinical characteristics: A machine learning analysis

BackgroundDifferentiating bipolar depression (BD) from unipolar depression (UD) is a major clinical challenge. Identifying the potential classifying biomarkers between these two diseases is vital to optimize personalized management of depressed individuals. MethodsHere, we aimed to integrate neuroimaging and clinical data with machine learning method to classify BD and UD at the individual level. Data were collected from 31 healthy controls (HC group) and 80 depressive patients with an average follow-up period of 7.51 years. Of these patients, 32 got diagnosis conversion from major depressive disorder (MDD) to BD (BD group) and 48 remain persistent diagnosis of MDD (MDD group). Using graph theory and functional connectivity (FC) analysis, we investigated the differences in reward circuit properties among three groups. Then we applied a support vector machine and leave-one-out cross-validation methods to classify BD and UD patients based on neuroimaging and clinical data. ResultsCompared with MDD and HC, BD showed decreased degree centrality of right mediodorsal thalamus (MD) and nodal efficiency (NE) of left ventral pallidum. Compared with BD and HC, MDD showed decreased NE of right MD and increased FC between right MD and bilateral dorsolateral prefrontal cortex and left ventromedial prefrontal cortex. Notably, the classifier obtained high classification accuracies (87.50 %) distinguishing BD and UD patients based on reward circuit properties and clinical features. LimitationsThe classifying model requires out-of-sample replication analysis. ConclusionThe reward circuit dysfunction can not only provide additional information to assist clinical differential diagnosis, but also in turn informed treatment decision of depressive patients.

The treatment efficacy of rTMS on bipolar depression – in comparison with unipolar depressed patients

The treatment efficacy of rTMS on bipolar depression – in comparison with unipolar depressed patients

Randomized controlled clinical trial of the efficacy of the digital self- help program edupression.com® in mild-to-moderate unipolar depressive patients (eFICASY-study)

Randomized controlled clinical trial of the efficacy of the digital self- help program edupression.com® in mild-to-moderate unipolar depressive patients (eFICASY-study)

The sociodemographic characteristics and clinical features of the late-life depression patients: results from the Beijing Anding Hospital mental health big data platform

BackgroundThe sociodemographic characteristics and clinical features of the Late-life depression (LLD) patients in psychiatric hospitals have not been thoroughly studied in China. This study aimed to explore the psychiatric outpatient attendance of LLD patients at a psychiatric hospital in China, with a subgroup analysis, such as with or without anxiety, gender differences.MethodsThis retrospective study examined outpatients with LLD from January 2013 to August 2019 using data in the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) in Beijing Anding Hospital. Age, sex, number of visits, use of drugs and comorbid conditions were extracted from medical records.ResultsIn a sample of 47,334 unipolar depression patients, 31,854 (67.30%) were women, and 15,480 (32.70%) were men. The main comorbidities of LDD are generalized anxiety disorder (GAD) (83.62%) and insomnia (74.52%).Among patients with unipolar depression, of which benzodiazepines accounted for the largest proportion (77.77%), Selective serotonin reuptake inhibitors (SSRIs) accounted for 59.00%, a noradrenergic and specific serotonergic antidepressant (NaSSAs) accounted for 36.20%. The average cost of each visit was approximately 646.27 yuan, and the cost of each visit was primarily attributed to Western medicine (22.97%) and Chinese herbal medicine (19.38%). For the cost of outpatient visits, depression comorbid anxiety group had a higher average cost than the non-anxiety group (p < 0.05). There are gender differences in outpatient costs, men spend more than women, for western medicine, men spend more than women, for Chinese herbal medicine, women spend more than men (all p < 0.05). The utilization rate of SSRIs and benzodiazepines in female patients is significantly higher than that in male patients (p < 0.05).ConclusionLLD patients are more commonly women than men and more commonly used SSRIs and NaSSAs. Elderly patients with depression often have comorbid generalized anxiety. LLD patients spend most of their visits on medicines, and while the examination costs are lower.

The Tryptophan Catabolite or Kynurenine Pathway in a Major Depressive Episode with Melancholia, Psychotic Features and Suicidal Behaviors: A Systematic Review and Meta-Analysis.

Major depressive disorder (MDD) and bipolar disorder (BD) with melancholia and psychotic features and suicidal behaviors are accompanied by activated immune-inflammatory and oxidative pathways, which may stimulate indoleamine 2,3-dioxygenase (IDO), the first and rate-limiting enzyme of the tryptophan catabolite (TRYCAT) pathway resulting in increased tryptophan degradation and elevated tryptophan catabolites (TRYCTAs). The purpose of the current study is to systematically review and meta-analyze levels of TRP, its competing amino acids (CAAs) and TRYCATs in patients with severe affective disorders. Methods: PubMed, Google Scholar and SciFinder were searched in the present study and we recruited 35 studies to examine 4647 participants including 2332 unipolar (MDD) and bipolar (BD) depressed patients and 2315 healthy controls. Severe patients showed significant lower (p < 0.0001) TRP (standardized mean difference, SMD = −0.517, 95% confidence interval, CI: −0.735; −0.299) and TRP/CAAs (SMD = −0.617, CI: −0.957; −0.277) levels with moderate effect sizes, while no significant difference in CAAs were found. Kynurenine (KYN) levels were unaltered in severe MDD/BD phenotypes, while the KYN/TRP ratio showed a significant increase only in patients with psychotic features (SMD = 0.224, CI: 0.012; 0.436). Quinolinic acid (QA) was significantly increased (SMD = 0.358, CI: 0.015; 0.701) and kynurenic acid (KA) significantly decreased (SMD = −0.260, CI: −0.487; −0.034) in severe MDD/BD. Patients with affective disorders with melancholic and psychotic features and suicidal behaviors showed normal IDO enzyme activity but a lowered availability of plasma/serum TRP to the brain, which is probably due to other processes such as low albumin levels.