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This study aimed to identify different symptom trajectories based on the severity of depression symptoms within a 2-month follow-up, and to explore predictive factors for different symptom trajectories. Three hundred and ninety-two adults diagnosed with major depressive disorder (MDD) were recruited from two longitudinal cohorts. Patients received antidepressant treatment as usual, and the depression symptoms were evaluated by the 17-item Hamilton depression rating scale (HAMD-17) at baseline, two weeks, and eight weeks. Based on the HAMD-17 scores, different trajectories of symptom change were distinguished by applying Growth Mixture Modeling (GMM). Furthermore, the baseline sociodemographic, clinical, and cognitive characteristics were compared to identify potential predictors for different trajectories. Through GMM, three unique depressive symptom trajectories of MDD patients were identified: (1) mild-severity class with significant improvement (Mild, n = 255); (2) high-severity class with significant improvement (High, n = 39); (3) moderate-severity class with limited improvement (Limited, n = 98). Among the three trajectories, the Mild class had a relatively low level of anxiety symptoms at baseline, whereas the High class had the lowest education level and the worst cognitive performance. Additionally, participants in the Limited class exhibited an early age of onset and experienced a higher level of emotional abuse. MDD patients could be categorised into three distinct latent subtypes through different symptom trajectories in this study, and the characteristics of these subtype patients may inform identifications for trajectory-specific intervention targets.
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BACKGROUND: Norepinephrine transporter (NET) is encoded by the SLC6A2 gene and is a potential target for studying the pathogenesis of PTSD. To the best of our knowledge, no prior investigations have examined SLC6A2 polymorphism-related neuroimaging abnormalities in PTSD patients. METHODS: In 218 Han Chinese adults who had lost their sole child, we investigated the association between the T-182 C SLC6A2 genotype and gray matter volume (GMV). Participants included 57 PTSD sufferers and 161 non-PTSD sufferers, and each group was further separated into three subgroups based on each participant's SLC6A2 genotype (TT, CT, and CC). All participants received magnetic resonance imaging (MRI) and clinical evaluation. To assess the effects of PTSD diagnosis, genotype, and genotype × diagnosis interaction on GMV, 2 × 3 full factorial designs were used. Pearson's correlations were used to examine the association between GMV and CAPS, HAMD, and HAMA. RESULTS: The SLC6A2 genotype showed significant main effects on GMV of the left superior parietal gyrus (SPG) and the bilateral middle cingulate gyrus (MCG). Additionally, impacts of the SLC6A2 genotype-diagnosis interaction were discovered in the left superior frontal gyrus (SFG). The CAPS, HAMA, and HAMD scores, as well as the genotype main effect and diagnostic SLC6A2 interaction, did not significantly correlate with each other. CONCLUSION: These findings indicate a modulatory effect that the SLC6A2 polymorphism exerts on the SPG and MCG, irrespective of PTSD diagnosis. We found evidence to suggest that the SLC6A2 genotype-diagnosis interaction on SFG may potentially contribute to PTSD pathogenesis in adults who lost their sole child.
Subject(s)
Gray Matter , Norepinephrine Plasma Membrane Transport Proteins , Stress Disorders, Post-Traumatic , Adult , Child , Humans , Brain/diagnostic imaging , Brain/pathology , China , Gray Matter/pathology , Magnetic Resonance Imaging/methods , Norepinephrine Plasma Membrane Transport Proteins/genetics , Polymorphism, Single Nucleotide , Prefrontal Cortex , Stress Disorders, Post-Traumatic/geneticsABSTRACT
OBJECTIVE: To investigate the impact of baseline painful physical symptoms (PPS) on subsequent first-episode major depressive disorder (MDD) in adults with subthreshold depressive symptoms, including subgroup analyses to assess whether the associations differ in individuals with and without physical diseases. METHODS: A total of 2343 adults with subthreshold depressive symptoms were recruited at 34 primary health care centers. PPS were measured at baseline. First-episode MDD during follow-up was diagnosed by professional psychiatrists using the Mini-International Neuropsychiatric Interview. RESULTS: Baseline PPS showed independent impacts on first-episode MDD in adults with subthreshold depressive symptoms without physical diseases, but not in those with physical diseases. A non-linear association (P < 0.001) was observed between PPS burden and the risk of first-episode MDD. The HRs for first-episode MDD exhibited a rapidly increasing trend between PPS burden scores of 10-16, and maintained consistently high when scores exceeded 16. The analyses for specific PPS revealed that headache, neck pain, and heart or chest pain were independently associated with first-episode MDD in participants without physical diseases, the HRs were 1.57 (1.15-2.36), 1.53 (1.02-2.30), and 1.69 (1.14-2.50), respectively. Further network analysis demonstrated that heart or chest pain serves as a bridge symptom among the seven specific PPS and first-episode MDD in those without physical diseases. CONCLUSION: PPS burden and heart or chest pain may be significant indicators for first-episode MDD in adults with subthreshold depressive symptoms without physical diseases. Future studies should investigate whether interventions targeting PPS can prevent episode MDD in this subthreshold population.
Subject(s)
Depressive Disorder, Major , Adult , Humans , Depressive Disorder, Major/diagnosis , Depression , Prospective Studies , Chest Pain/complications , Pain MeasurementABSTRACT
Neuroimage studies have reported functional connectome abnormalities in posttraumatic stress disorder (PTSD), especially in adults. However, these studies often treated the brain as a static network, and time-variance of connectome topology in pediatric posttraumatic stress disorder remain unclear. To explore case-control differences in dynamic connectome topology, resting-state functional magnetic resonance imaging data were acquired from 24 treatment-naïve non-comorbid pediatric posttraumatic stress disorder patients and 24 demographically matched trauma-exposed non-posttraumatic stress disorder controls. A graph-theoretic analysis was applied to construct time-varying modular structure of whole-brain networks by maximizing the multilayer modularity. Network switching rate at the global, subnetwork, and nodal levels were calculated and compared between posttraumatic stress disorder and trauma-exposed non-posttraumatic stress disorder groups, and their associations with posttraumatic stress disorder symptom severity and sex interactions were explored. At the global level, individuals with posttraumatic stress disorder exhibited significantly lower network switching rates compared to trauma-exposed non-posttraumatic stress disorder controls. This difference was mainly involved in default-mode and dorsal attention subnetworks, as well as in inferior temporal and parietal brain nodes. Posttraumatic stress disorder symptom severity was negatively correlated with switching rate in the global network and default mode network. No significant differences were observed in the interaction between diagnosis and sex/age. Pediatric posttraumatic stress disorder is associated with dynamic reconfiguration of brain networks, which may provide insights into the biological basis of this disorder.
Subject(s)
Connectome , Stress Disorders, Post-Traumatic , Adult , Humans , Child , Stress Disorders, Post-Traumatic/diagnostic imaging , Magnetic Resonance Imaging/methods , Nerve Net , Brain , Connectome/methodsABSTRACT
BACKGROUND: Total white blood cell count (TWBCc), an index of chronic and low-grade inflammation, is associated with clinical symptoms and metabolic alterations in patients with schizophrenia. The effect of antipsychotics on TWBCc, predictive values of TWBCc for drug response, and role of metabolic alterations require further study. METHODS: Patients with schizophrenia were randomized to monotherapy with risperidone, olanzapine, quetiapine, aripiprazole, ziprasidone, perphenazine or haloperidol in a 6-week pharmacological trial. We repeatedly measured clinical symptoms, TWBCc, and metabolic measures (body mass index, blood pressure, waist circumference, fasting blood lipids and glucose). We used mixed-effect linear regression models to test whether TWBCc can predict drug response. Mediation analysis to investigate metabolic alteration effects on drug response. RESULTS: At baseline, TWBCc was higher among patients previously medicated. After treatment with risperidone, olanzapine, quetiapine, perphenazine, and haloperidol, TWBCc decreased significantly (p < 0.05). Lower baseline TWBCc predicted greater reductions in Positive and Negative Syndrome Scale (PANSS) total and negative scores over time (p < 0.05). We found significant mediation of TWBCc for effects of waist circumference, fasting low-density lipoprotein cholesterol, and glucose on reductions in PANSS total scores and PANSS negative subscale scores (p < 0.05). CONCLUSION: TWBCc is affected by certain antipsychotics among patients with schizophrenia, with decreases observed following short-term, but increases following long-term treatment. TWBCc is predictive of drug response, with lower TWBCc predicting better responses to antipsychotics. It also mediates the effects of certain metabolic measures on improvement of negative symptoms. This indicates that the metabolic state may affect clinical manifestations through inflammation.
Subject(s)
Antipsychotic Agents , Schizophrenia , Humans , Antipsychotic Agents/therapeutic use , Schizophrenia/drug therapy , Schizophrenia/metabolism , Olanzapine/therapeutic use , Risperidone/therapeutic use , Quetiapine Fumarate/therapeutic use , Haloperidol/therapeutic use , Perphenazine/therapeutic use , Benzodiazepines/adverse effects , Glucose/therapeutic use , Inflammation/drug therapyABSTRACT
OBJECTIVE: Bipolar disorder is easily misdiagnosed with major depressive disorder (MDD). The Rapid Mood Screener (RMS) was developed to address this unmet clinical need. This study aims to translate and evaluated the reliability and validity of the RMS in Chinese adults with bipolar I/II disorder (BD-I/II). METHODS: Brislin's translation and Delphi method were conducted to formulate the RMS-Chinses version (RMS-C). Patients with MDD (N = 99), BD-I (N = 77) and BD-II (N = 78) were included to assess the validity and reliability of RMS-C. The area under the curve (AUC) was computed to ascertain the ability of the Mood Disorder Questionnaire (MDQ) and RMS-C to distinguish BD-I and BD-II from MDD. The optimal cut-off scores for classification were also calculated by the maximum sensitivity and specificity. RESULTS: The intraclass correlation coefficient of the RMS-C was 0.82 (95%CI, 0.71-0.89). The content validity index by six items were 0.71, 0.86, 1.00, 0.86, 1.00, and 1.00 in turn, and by scales was 0.90. The AUCs of the RMS-C in both BD-I/II, BD-I alone and BD-II alone were 0.83 (95 % CI, 0.78-0.89), 0.82 (95 % CI, 0.75-0.89) and 0.85 (95 % CI, 0.79-0.91), respectively, and were comparably to the MDQ. The optimal RMS-C values of the presence of BD-I and BD-II were >4 and 3, respectively. CONCLUSION: The RMS-C is a valid, simple self-administer screening tool to help identify BD-I or BD-II in persons experiencing a depressive episode. Validating the impact of screening with the RMS-C on health outcomes and health economics is warranted.
Subject(s)
Bipolar Disorder , Depressive Disorder, Major , Adult , Humans , Bipolar Disorder/diagnosis , Depressive Disorder, Major/diagnosis , Reproducibility of Results , Surveys and Questionnaires , China , Mood Disorders/diagnosisABSTRACT
BACKGROUND: Dysfunctional attitudes, which are characterized by distorted self-cognitions, were considered to be linked to personality traits. It was found that certain personality traits may predict dysfunctional attitudes in patients with major depressive disorder (MDD). Nonetheless, the relationship between personality traits and dysfunctional attitudes remains under-researched. AIMS: The aim of this study is to examine the relationship between specific domains of Sixteen Personality Factor (16PF) and dysfunctional attitudes in Chinese participants with or without MDD. In addition, the present study explores the associations between 16PF and eight subtypes of dysfunctional attitudes, based on the proposed eight-factor structure of the Chinese version of the Dysfunctional Attitude Scale-Form A (C-DAS-A). METHODS: One hundred and sixty-eight participants with MDD and 130 healthy participants were included in the study (Trial Registration Number: ChiCTR1800014591). Personality was assessed using the 16PF Questionnaire. Dysfunctional attitudes were measured through the C-DAS-A. RESULTS: The 16PF dimensions associated with dysfunctional attitudes and the eight subtypes were mainly concentrated in the four anxiety facets including factors C, L, O, and Q4, in both MDD and HC groups. There were significant differences in the 16 PF dimensions that would explain dysfunctional attitudes between the two groups, which were as follows: factors C, G, and O in the MDD group, and factors L and Q4 in the HC group. CONCLUSIONS: Personality traits, especially the anxiety-related personality traits, were distinctly associated with the development of dysfunctional attitudes in people with or without MDD.
Subject(s)
Depressive Disorder, Major , Humans , Case-Control Studies , Attitude , Personality , CognitionABSTRACT
BACKGROUND: Associations between adverse childhood experiences (ACEs) and common psychiatric disorders among older Chinese individuals have not been well reported. The objectives of this study are to examine the prevalence of ACEs and the associations of ACEs with common psychiatric disorders among older adults in China. METHODS: The study used data from the China Mental Health Survey (CMHS), a nationally representative epidemiological survey, which used computer-assisted personal interviewing (CAPI), logistic regression models were used to examine community-based adult psychiatric disorders and associated risk factors. Finally, 2,317 individuals aged 60 years or over were included in the CMHS. The national prevalence of ACEs in older adults were estimated and logistic regression were used to analyse the association between ACEs and past-year psychiatric disorders. RESULTS: Prevalence of ACEs among older adults in China was 18.1%. The three most common types of ACEs were neglect (11.6%), domestic violence (9.2%), and parental loss (9.1%). This study proved the association between ACEs and common past-year psychiatric disorders in older adults. ACEs increased the risk of past-year psychiatric disorders in older adults. After adjustment for age, sex, marital status, employment status, education, rural or urban residence, region, and physical diseases, the association between ACEs and past-year psychiatric disorders were still significant. CONCLUSIONS: ACEs are linked to an increased risk for past-year psychiatric disorders in older adults. ACEs may have long-term effects on older adults' mental well-being. Preventing ACEs may help reduce possible adverse health outcomes in later life.
Subject(s)
Adverse Childhood Experiences , Mental Disorders , Humans , Aged , Mental Disorders/epidemiology , Mental Health , China/epidemiology , Health SurveysABSTRACT
The functional connectome of the human brain represents the fundamental network architecture of functional interdependence in brain activity, but its normative growth trajectory across the life course remains unknown. Here, we aggregate the largest, quality-controlled multimodal neuroimaging dataset from 119 global sites, including 33,809 task-free fMRI and structural MRI scans from 32,328 individuals ranging in age from 32 postmenstrual weeks to 80 years. Lifespan growth charts of the connectome are quantified at the whole cortex, system, and regional levels using generalized additive models for location, scale, and shape. We report critical inflection points in the non-linear growth trajectories of the whole-brain functional connectome, particularly peaking in the fourth decade of life. Having established the first fine-grained, lifespan-spanning suite of system-level brain atlases, we generate person-specific parcellation maps and further show distinct maturation timelines for functional segregation within different subsystems. We identify a spatiotemporal gradient axis that governs the life-course growth of regional connectivity, transitioning from primary sensory cortices to higher-order association regions. Using the connectome-based normative model, we demonstrate substantial individual heterogeneities at the network level in patients with autism spectrum disorder and patients with major depressive disorder. Our findings shed light on the life-course evolution of the functional connectome and serve as a normative reference for quantifying individual variation in patients with neurological and psychiatric disorders.
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BACKGROUND: Depression is the second most important cause of disability worldwide. Reducing this major burden on global health requires a better understanding of the etiology, risk factors, and course of the disorder. With the goal of improving the prevention, recognition, and appropriate management of depressive disorders in China, the China Depression Cohort Study will establish a nationally representative sample of at least 85,000 adults (the China Depression Cohort Study-I) and 15,000 middle school students (the China Depression Cohort Study-II) and follow them over time to identify factors that influence the onset, characteristics, and course of depressive disorders. This protocol describes the China Depression Cohort Study-I. METHODS: A multistage stratified random sampling method will be used to identify a nationally representative community-based cohort of at least 85,000 adults (i.e., ≥ 18 years of age) from 34 communities in 17 of mainland China's 31 provincial-level administrative regions. Baseline data collection includes 1) demographic, social and clinical data, 2) diagnostic information, 3) biological samples (i.e., blood, urine, hair), 4) brain MRI scans, and 5) environmental data (e.g., community-level metrics of climate change, air pollution, and socio-economic characteristics). Baseline findings will identify participants with or without depressive disorders. Annual reassessments will monitor potential risk factors for depression and identify incident cases of depression. Cox Proportional-Hazards Regression, Network analysis, Disease trajectory modelling, and Machine learning prediction models will be used to analyze the collected data. The study's main outcomes are the occurrence of depressive disorders; secondary outcomes include adverse behaviors (e.g., self-harm, suicide), the recurrence of depression and the incidence other mental disorders. DISCUSSION: The China Depression Cohort Study-I will collect a comprehensive, nationally representative set of individual-level and community-level variables over time. The findings will reframe the understanding of depression from a 'biology-psychology-society' perspective. This perspective will improve psychiatrists' understanding of depression and, thus, promote the development of more effective subgroup-specific antidepressant drugs and other interventions based on the new biomarkers and relationships identified in the study. TRAIL REGISTRATION: The protocol has been registered on the Chinese Clinical Trial Registry (No. ChiCTR2200059016).
Subject(s)
Air Pollution , Depression , Adult , Humans , China/epidemiology , Cohort Studies , Depression/epidemiology , Prospective StudiesABSTRACT
BACKGROUND: Previous studies suggested that childhood maltreatment is associated with poor health outcomes. While not everyone who experiences abuse as a child goes on to experience poor mental health, some traumatized people are grown to be more resilient than others. Few studies have examined the association between childhood maltreatment and adult resilience. This study aimed to determine different relationships between specific types and features of childhood maltreatment with adult resilience among Chinese with Major Depressive Disorder (MDD) and healthy controls (HCs). METHODS: A total of 101 patients with MDD and 116 participants in the healthy control (HC) group from Zhumadian Psychiatric Hospital and its nearby communities were included in this analysis. Childhood maltreatment was assessed retrospectively using Childhood Trauma Questionnaire (CTQ). Adults' resilience was assessed by the Connor-Davidson Resilience Scale (CD-RISC). Generalized linear models were applied between childhood maltreatment (specific types and features) and resilience adjusting for covariates. RESULTS: The total score of CD-RISC and factor scores of strength, optimism, and tenacity in the HC group were higher than those in the MDD group. CTQ total score had a negative association with optimism score among participants in MDD (ß=-0.087, P < 0.001) and HC (ß=-0.074, P = 0.023) groups. Higher emotional neglect (EN) score (ß=-0.169, P = 0.001) and physical neglect (PN) score (ß=-0.153, P = 0.043) were related to a worse optimism score in MDD group. Emotional abuse (EA) score was associated with a worse tenacity score (ß=-0.674, P = 0.031) in MDD group. For participants in HC group, higher EN and PN scores were related to worse resilience scores (tenacity, strength, and optimism). CONCLUSIONS: Patients with MDD showed lower optimism than HCs. Childhood maltreatment, especially childhood negect, independently contributed to optimism, with more severe childhood maltreatment predictive of worse performance of optimism. EA in childhood was also linked to worse tenacity in adult patients with MDD.
Subject(s)
Adverse Childhood Experiences , Depressive Disorder, Major , Adult , Child , Humans , Emotional Abuse , Retrospective Studies , East Asian PeopleABSTRACT
This study aimed to investigate whether there are different cognitive subtypes in patients with major depressive disorder (MDD) and the change pattern of cognitive clusters across the course of MDD. A battery of comprehensive cognitive tests was used to assess the executive function, processing speed, attention, and memory of 153 medication-free patients and 142 healthy controls (HCs). After 6 months of treatment with antidepressants, 87 patients completed cognitive tests again. K-means cluster analysis was performed to determine the cognitive subtypes. A preserved cognition cluster and an impaired cognition cluster were identified in the acute episode phase and the 6-month follow-up phase. 80.5% of the patients remained in their original subgroup after 6 months of treatment. The impaired cognition cluster during the 6-month follow-up period could be predicted by impaired cognition during the episode phase, disease state (remission or non-remission), current illness duration, and education level. This study supporting the heterogeneity of cognitive performance across the course of disease in patients with MDD using cluster analysis. It was found that cognitive impairment during depressive episodes was predictive of poorer cognitive performance even after treatment with antidepressants. Therefore, interventions targeting cognitive function from the early stages of MDD is essential.
Subject(s)
Cognition Disorders , Cognitive Dysfunction , Depressive Disorder, Major , Humans , Depressive Disorder, Major/complications , Depressive Disorder, Major/drug therapy , Depressive Disorder, Major/psychology , Cognition Disorders/etiology , Cognition Disorders/psychology , Cognitive Dysfunction/etiology , Cognition , Neuropsychological Tests , Cluster Analysis , Antidepressive Agents/therapeutic useABSTRACT
BACKGROUND: A disruption of the kynurenine (KYN) pathway may exist in major depressive disorder (MDD). However, the changing pattern of the KYN pathway across the different disease states in MDD is unclear. Herein, we performed a meta-analysis to examine the differences in KYN metabolites between patients in the current episode of MDD (cMDD) and patients in remission (rMDD), as well as the changes after treatments. METHODS: Literature was systematically searched from electronic databases, from inception up to September 2022. Random-effect models were used to quantify the differences in KYN metabolites between patients with MDD across acute depressive episode and remission phases, as well as the changes after treatments. RESULTS: Fifty-one studies involving 7056 participants were included. Tryptophan (TRP), KYN, kynurenic acid (KYNA), KYNA/quinolinic acid (QA), KYNA/3-hydroxykynurenine (3-HK), and KYNA/KYN were significantly lower, while KYN/TRP was significantly higher in patients with cMDD. Moreover, these effect sizes were generally larger in medication-free patients. No significant differences were found between patients with rMDD and HCs. Additionally, KYNA was found negatively correlated with depression severity and significantly increased after treatments, while the alteration was not found in QA. LIMITATIONS: The number of included studies of patients with rMDD and longitudinal studies investigating the change of the KYN metabolites after treatment with antidepressants was limited. In addition, the heterogeneity across included studies was relatively high. CONCLUSIONS: These findings showed a comprehensive image of the unique dysfunction pattern of the KYN pathway across different MDD states and highlighted KYNA as a potentially sensitive biomarker of MDD.
Subject(s)
Depressive Disorder, Major , Kynurenine , Humans , Kynurenine/metabolism , Tryptophan/metabolism , Depression/metabolism , Biomarkers , Kynurenic Acid/metabolism , Quinolinic Acid/metabolismABSTRACT
BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking. METHODS: Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11-93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity. RESULTS: Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes. CONCLUSIONS: These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder.
Subject(s)
Connectome , Depressive Disorder, Major , Adolescent , Humans , Adult , Depressive Disorder, Major/diagnostic imaging , Depressive Disorder, Major/drug therapy , Reproducibility of Results , Magnetic Resonance Imaging/methods , Brain/diagnostic imaging , Brain MappingABSTRACT
Post-traumatic stress disorder (PTSD) is one of the most severe sequelae of trauma. But a nationally representative epidemiological data for PTSD and trauma events (TEs) was unavailable in China. This article firstly demonstrated detailed epidemiological information on PTSD, TEs, and related comorbidities in the national-wide community-based mental health survey in China. A total of 9,378 participants completed the PTSD-related interview of the CIDI 3.0. Lifetime prevalence and 12-month prevalence of PTSD in total respondents were 0.3% and 0.2%. while the conditional lifetime and 12-month prevalence of PTSD after trauma exposure were 1.8% and 1.1%. The prevalence of exposure to any type of TE was 17.2%. Among individuals with the exposed to TEs, younger, without regular work (being a homemaker or retried), and intimate relationship breakdown (separated/Widowed/Divorced), living rurally were associated with either the lifetime PTSD or the 12-month PTSD, while the count of a specific TE, the unexpected death of loved one, was related to both. Alcohol dependence was the most common comorbidity among male participants with PTSD but major depressive disorder (MDD) for female counterparts. Our study can provide a reliable reference for future identification and intervention for people with PTSD.
Subject(s)
Depressive Disorder, Major , Stress Disorders, Post-Traumatic , Humans , Male , Female , Stress Disorders, Post-Traumatic/epidemiology , Stress Disorders, Post-Traumatic/psychology , Life Change Events , Depressive Disorder, Major/epidemiology , Cross-Sectional Studies , China/epidemiology , Prevalence , ComorbidityABSTRACT
Nitrous oxide (N2O) has demonstrated an antidepressant effect for treatment-resistant depression (TRD), but no studies investigated the effects of N2O on different cognition domains. This study aimed to test whether N2O would display pro-cognitive effects. We conducted a double-blinded, placebo-controlled, randomized controlled trial, 44 patients with TRD were randomized to N2O group (one-hour inhalation of 50% N2O/50% oxygen) or placebo group (50% air/50% oxygen). Thirty-four patients completed cognitive tests at the pre-treatment phase, 1-week, and 2 weeks post-treatment including subjective cognitive function, processing speed, attention, and executive function. Although the antidepressant effect of N2O was not significant at 1 week, patients still showed better performance of executive function at 1 week after receiving N2O compared with the placebo. Moreover, this significant improvement still existed at 1 week after controlling for the change in depressive symptoms over-time. Additionally, no significant difference was observed in subjective cognitive function, processing speed, and attention between these two groups across the 2-week follow-up period. As the first study investigating the treatment effects of N2O on improving cognitive function in TRD patients, the current study indicated that N2O has a potential pro-cognitive effect on executive function and this effect might be independent from improvements in depressive symptoms.
Subject(s)
Depressive Disorder, Treatment-Resistant , Nitrous Oxide , Humans , Nitrous Oxide/therapeutic use , Depressive Disorder, Treatment-Resistant/drug therapy , Double-Blind Method , Antidepressive Agents/therapeutic use , Oxygen/therapeutic use , Treatment OutcomeABSTRACT
Introduction: Major depressive disorder (MDD) is associated with low-grade inflammation, and anti-inflammatory treatment can help improve depressive symptoms. A recent study found that fluvoxamine (FLV) can reduce Interleukin-6 (IL-6) production via sigma-1 receptor in inflammation models. However, the anti- IL-6 effect of FLV in treating patients with MDD and whether it can contribute to antidepressant effects remain unclear. Methods: A total of 65 patients with MDD and 34 healthy controls were recruited at baseline, and 50 patients completed the FLV treatment for 2 months. We assessed depression and anhedonia and collected plasma IL-6 levels at baseline, 1 month, and 2 months after baseline. This study evaluated the changes in clinical measures and IL-6 during treatment and analyzed their association. Further subgroup analyses were conducted in patients with MDD with high, medium, or low IL-6. Results: Depression and anhedonia were significantly improved in patients with MDD, while the IL-6 did not significantly change after the FLV treatment. However, IL-6 significantly declined after the FLV treatment among patients with MDD with higher baseline IL-6. No significant associations were found between the changes in depressive symptoms and IL-6. Conclusion: Our study provided preliminary evidence suggesting that the anti-IL-6 effect of FLV might not play a vital role in its antidepressant treatment, at least in patients with MDD with low inflammation. However, for patients with MDD with higher IL-6, FLV can help reduce IL-6 significantly in the antidepressant treatment, which may help guide the individual treatment of MDD with higher IL-6 levels. Clinical trial registration: https://clinicaltrials.gov/ct2/show/NCT04160377, identifier NCT04160377.
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BACKGROUND: The mechanism by which antidepressants normalizing aberrant resting-state functional connectivity (rsFC) in patients with major depressive disorder (MDD) is still a matter of debate. The current study aimed to investigate aberrant rsFC and whether antidepressants would restore the aberrant rsFC in patients with MDD. METHODS: A total of 196 patients with MDD and 143 healthy controls (HCs) received the resting-state functional magnetic resonance imaging and clinical assessments at baseline. Patients with MDD received antidepressant treatment after baseline assessment and were re-scanned at the 6-month follow-up. Network-based statistics were employed to identify aberrant rsFC and rsFC changes in patients with MDD and to compare the rsFC differences between remitters and non-remitters. RESULTS: We identified a significantly decreased sub-network and a significantly increased sub-network in MDD at baseline. Approximately half of the aberrant rsFC remained significantly different from HCs after 6-month treatment. Significant overlaps were found between baseline reduced sub-network and follow-up increased sub-network, and between baseline increased sub-network and follow-up decreased sub-network. Besides, rsFC at baseline and rsFC changes between baseline and follow-up in remitters were not different from non-remitters. CONCLUSIONS: Most aberrant rsFC in patients with MDD showed state-independence. Although antidepressants may modulate aberrant rsFC, they may not specifically target these aberrations to achieve therapeutic effects, with only a few having been directly linked to treatment efficacy.
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Suicide-relevant attentional biases are found in suicide attempters (SAs) with depression. Wenzel and Beck provide a theoretical framework that suggests suicide-related attention biases confer vulnerability to suicide. In this study, we integrated eye-tracking dynamics of suicide-related attentional biases with self-report measures to test their model. A free-viewing eye-tracking paradigm, which simultaneously presented four images with different valences (suicide-related, negative, positive, neutral), was examined in 76 SAs with unipolar or bipolar depression, 66 nonsuicidal depressive participants (ND), and 105 healthy never-depressed healthy control participants (HC). Structural equation modeling (SEM) was used for the theory testing. SA gazed more at suicide-relevant stimuli throughout the 25-s trial compared with ND. SA and ND initially detected suicide-related stimuli faster than HC. Groups did not differ on how often they initially gazed at suicide images or how fast they disengaged away from them. Eye-tracking indices of attentional biases, together with self-reported hopelessness, adequately fit an SEM consistent with Wenzel and Beck's cognitive theory of suicide-related information processing. Potentially, suicide-related attention biases could increase vulnerability to suicidal ideation and eventual suicidal behaviors. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Subject(s)
Bipolar Disorder , Suicide , Humans , Bipolar Disorder/psychology , Eye-Tracking Technology , Suicidal Ideation , CognitionABSTRACT
Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS.