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Molecules (Basel, Switzerland) Nov 2023Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry... (Review)
Review
Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.
Topics: Humans; Depressive Disorder, Major; Mass Spectrometry; Gas Chromatography-Mass Spectrometry; Metabolomics; Chromatography, Liquid
PubMed: 37959849
DOI: 10.3390/molecules28217430 -
Life Sciences Aug 2024Major depressive disorder (MDD) is characterized by a high rate of recurrence and disability, which seriously affects the quality of life of patients. That's why a... (Review)
Review
Major depressive disorder (MDD) is characterized by a high rate of recurrence and disability, which seriously affects the quality of life of patients. That's why a deeper understanding of the mechanisms of MDD pathology is an urgent task, and some studies have found that intestinal symptoms accompany people with MDD. The microbiota-gut-brain axis is the bidirectional communication between the gut microbiota and the central nervous system, which was found to have a strong association with the pathogenesis of MDD. Previous studies have focused more on the communication between the gut and the brain through neuroendocrine, neuroimmune and autonomic pathways, and the role of gut microbes and their metabolites in depression is unclear. Metabolites of intestinal microorganisms (e.g., tryptophan, kynurenic acid, indole, and lipopolysaccharide) can participate in the pathogenesis of MDD through immune and inflammatory pathways or by altering the permeability of the gut and blood-brain barrier. In addition, intestinal microbes can communicate with intestinal neurons and glial cells to affect the integrity and function of intestinal nerves. However, the specific role of gut microbes and their metabolites in the pathogenesis of MDD is not well understood. Hence, the present review summarizes how gut microbes and their metabolites are directly or indirectly involved in the pathogenesis of MDD.
Topics: Humans; Depressive Disorder, Major; Gastrointestinal Microbiome; Brain-Gut Axis; Animals; Brain; Tryptophan
PubMed: 38866215
DOI: 10.1016/j.lfs.2024.122815 -
Genes Dec 2023Major depressive disorder (MDD) is a complex disorder and a leading cause of disability in 280 million people worldwide. Many environmental factors, such as microbes,... (Review)
Review
Major depressive disorder (MDD) is a complex disorder and a leading cause of disability in 280 million people worldwide. Many environmental factors, such as microbes, drugs, and diet, are involved in the pathogenesis of depressive disorders. However, the underlying mechanisms of depression are complex and include the interaction of genetics with epigenetics and the host immune system. Modifications of the gut microbiome and its metabolites influence stress-related responses and social behavior in patients with depressive disorders by modulating the maturation of immune cells and neurogenesis in the brain mediated by epigenetic modifications. Here, we discuss the potential roles of a leaky gut in the development of depressive disorders via changes in gut microbiota-derived metabolites with epigenetic effects. Next, we will deliberate how altering the gut microbiome composition contributes to the development of depressive disorders via epigenetic alterations. In particular, we focus on how microbiota-derived metabolites such as butyrate as an epigenetic modifier, probiotics, maternal diet, polyphenols, drugs (e.g., antipsychotics, antidepressants, and antibiotics), and fecal microbiota transplantation could positively alleviate depressive-like behaviors by modulating the epigenetic landscape. Finally, we will discuss challenges associated with recent therapeutic approaches for depressive disorders via microbiome-related epigenetic shifts, as well as opportunities to tackle such problems.
Topics: Humans; Depressive Disorder, Major; Microbiota; Gastrointestinal Microbiome; Probiotics; Epigenesis, Genetic
PubMed: 38137038
DOI: 10.3390/genes14122217 -
The International Journal of... Oct 2023The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery...
BACKGROUND
The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation.
METHODS
We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values.
RESULTS
A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response.
CONCLUSIONS
The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.
Topics: Humans; Depressive Disorder, Major; Genome-Wide Association Study; Antidepressive Agents
PubMed: 36655406
DOI: 10.1093/ijnp/pyad001 -
The Journal of Clinical Psychiatry Nov 2023Quality of life (QoL) is an important patient-centric outcome to evaluate in treatment of major depressive disorder (MDD). This work sought to investigate the...
Quality of life (QoL) is an important patient-centric outcome to evaluate in treatment of major depressive disorder (MDD). This work sought to investigate the performance of several machine learning methods to predict a return to normative QoL in patients with MDD after antidepressant treatment. Several binary classification algorithms were trained on data from the first 2 weeks of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study (n = 651, conducted from 2001 to 2006) to predict week 9 normative QoL (score ≥ 67, based on a community normative sample, on the Quality of Life Enjoyment and Satisfaction Questionnaire-Short Form [Q-LES-Q-SF]) after treatment with citalopram. Internal validation was performed using a STAR*D holdout dataset, and external validation was performed using the Canadian Biomarker Integration Network in Depression-1 (CAN-BIND-1) dataset (n = 175, study conducted from 2012 to 2017) after treatment with escitalopram. Feature importance was calculated using SHapley Additive exPlanations (SHAP). Random Forest performed most consistently on internal and external validation, with balanced accuracy (area under the receiver operator curve) of 71% (0.81) on the STAR*D dataset and 69% (0.75) on the CAN-BIND-1 dataset. Random Forest Classifiers trained on Q-LES-Q-SF and Quick Inventory of Depressive Symptomatology-Self-Rated variables had similar performance on both internal and external validation. Important predictive variables came from psychological, physical, and socioeconomic domains. Machine learning can predict normative QoL after antidepressant treatment with similar performance to that of prior work predicting depressive symptom response and remission. These results suggest that QoL outcomes in MDD patients can be predicted with simple patient-rated measures and provide a foundation to further improve performance and demonstrate clinical utility. ClinicalTrials.gov identifiers NCT00021528 and NCT01655706.
Topics: Humans; Antidepressive Agents; Biomarkers; Canada; Citalopram; Depressive Disorder, Major; Quality of Life; Treatment Outcome; Clinical Studies as Topic
PubMed: 37967350
DOI: 10.4088/JCP.23m14864 -
Journal of Affective Disorders Sep 2024Rumination is a maladaptive response to distress characteristic of Major Depressive Disorder (MDD). It is unclear to what degree rumination is associated with depression...
BACKGROUND
Rumination is a maladaptive response to distress characteristic of Major Depressive Disorder (MDD). It is unclear to what degree rumination is associated with depression severity prior to treatment and how it responds to antidepressant treatment. Therefore, we evaluated the association between rumination and depression severity in 92 untreated patients with MDD and explored the changes in rumination after initiation of antidepressant medication.
METHOD
We measured rumination using the Rumination Response Scale (RRS) and depression severity with the Hamilton Depression Rating Scale (HDRS or HDRS) before and after initiation of 12 weeks of antidepressant treatment. The association between RRS and pre-treatment HDRS was evaluated using a linear regression model. RRS at week 4, 8, and 12 across treatment response categories (remission vs. non-response) were evaluated using a mixed effect model.
RESULTS
RRS was positively associated with depression severity prior to treatment at a trend level (p = 0.06). After initiation of treatment RRS decreased significantly (p < 0.0001) and remitters exhibited lower rumination compared to non-responders at week 4 (p = 0.03), 8 (p = 0.01), and 12 (p = 0.007).
LIMITATIONS
The study had no placebo group.
CONCLUSIONS
Although pre-treatment rumination did not significantly associate with depressive symptoms, rumination was closely connected to change in depressive symptoms. Tormented patients could be reassured that rumination symptoms may be alleviated over the course of antidepressant treatment.
Topics: Humans; Depressive Disorder, Major; Female; Male; Adult; Antidepressive Agents; Rumination, Cognitive; Middle Aged; Severity of Illness Index; Psychiatric Status Rating Scales; Treatment Outcome
PubMed: 38810785
DOI: 10.1016/j.jad.2024.05.135 -
BMC Public Health Nov 2023Depression is increasingly recognized as a worldwide serious, public health concern. A better understanding of depression is important for advancing its management and...
BACKGROUND
Depression is increasingly recognized as a worldwide serious, public health concern. A better understanding of depression is important for advancing its management and learning the difference between major depressive disorder (MDD) and dysthymia. Our aim is to conduct a concurrent analysis of the trends of both MDD and dysthymia in China.
METHODS
The data on depression from 1990 to 2019 were collected from the Global Burden of Disease Study 2019 (GBD 2019). To determine the average annual percent changes (AAPC) and relative risks (RRs), joinpoint regression and the age-period-cohort models were employed, respectively.
RESULTS
The incidence number of MDD and dysthymia continuously increased in China from 1990 to 2019, however, the age-standardized rates (ASR) had a decreasing trend in both men and women. The results from joinpoint regression showed that a declining trend was presented in young people (< 50 years) but an increased trend in the elderly (≥ 50 years) both in men and women, during 1990-2019. Age is the most influential factor for MDD and dysthymia. Age RRs for MDD incidence had an overall increasing trend with age. Period RR in MDD presented a U-shaped pattern, while Cohort RRs presented an inverted U-shaped pattern. On the other hand, RRs in dysthymia for period and cohort effects had no statistical significance, only the age effect presented an inverted U-shaped pattern.
CONCLUSIONS
The disparities in trends observed between MDD and dysthymia during the period of 1990-2019 indicated the significance of distinguishing between these two disorders. The age, period and cohort effects all had a greater impact on MDD than on dysthymia, and age effects presented different influential patterns in these two. To alleviate the burden of depressive disorders in China, proactive measures need to be implemented, with particular attention to the elderly population.
Topics: Male; Humans; Female; Aged; Adolescent; Depressive Disorder, Major; Dysthymic Disorder; Incidence; China; Cohort Effect
PubMed: 37926849
DOI: 10.1186/s12889-023-17025-4 -
Psychiatry Research Jan 2024Electroconvulsive therapy (ECT) is endorsed as a principal treatment approach for major depressive disorder (MDD) worldwide. Despite prior studies highlighting potential... (Meta-Analysis)
Meta-Analysis
OBJECTIVE
Electroconvulsive therapy (ECT) is endorsed as a principal treatment approach for major depressive disorder (MDD) worldwide. Despite prior studies highlighting potential short-term cognitive deficits post-ECT, the debate regarding its long-term implications persists. This study endeavors to elucidate the reasons for this contention using an evidence-based approach.
METHODS
This investigation, meticulously aligned with PRISMA guidelines, was prospectively enlisted on PROSPERO (CRD42023439259). A comprehensive search was performed across various databases, including PubMed, Cochrane Library, Web of Science, Embase, SCOPUS, PsycINFO, CINAHL Plus, and OpenGrey. This review, traversing the literature from inception until June 2023, encapsulated 10 studies (five RCTs and five quasi-experimental studies) involving a cohort of 868 individuals diagnosed with major depressive disorder.
RESULTS
The meta-analysis revealed that the persistent discourse on ECT-induced long-term cognitive impairment chiefly emanates from the inadequacies in the specificity and sensitivity of conventional assessment instruments. Conversely, subgroup analyses showed that cognitive impairment in ECT, as gauged by the nascent assessment tool, Electroconvulsive Therapy Cognitive Assessment (ECCA) (SMD = -0.94, 95 % CI [-1.33, -0.54], p < 0.00001), exerted a detrimental influence on the long-term trajectory of individuals with MDD. Notably, there was an adverse effect of ECT on the subdomain of long-term learning cognitive abilities in patients with MDD (SMD = -0.37, 95 % CI [-0.55, -0.18], p < 0.0001). Contrarily, memory (SMD = 0.16, 95 % CI [-0.02, 0.34], p = 0.08), attention (SMD = 0.23, 95 % CI [-0.07, 0.54], p = 0.14), language (SMD = -0.10, 95 % CI [-0.25, 0.05], p = 0.19), spatial perception, and orientation (SMD = -0.04, 95 % CI [-0.28, 0.20], p = 0.75) exhibited no significant detriments. Intriguingly, ECT showed favorable effects on executive function and processing speed among patients with MDD (SMD = 0.52, 95 % CI [0.29, 0.74], p < 0.00001).
CONCLUSION
This meta-analysis underscores ECCA's superior sensitivity of the ECCA compared to the MMSE or MoCA in detecting cognitive changes in patients with post-ECT MDD. Following Electroconvulsive Therapy (ECT), deterioration was observed in overall cognitive function and learning capabilities, while memory, attention, language, and spatial perception remained stable. Notably, enhancements were discerned in executive function and processing speed, which not only augmented academic perspectives but also steered the formulation of international clinical guidelines, accentuating the progressive role of ECT in the therapeutic approach to MDD.
Topics: Humans; Cognition; Cognitive Dysfunction; Depressive Disorder, Major; Electroconvulsive Therapy; Executive Function
PubMed: 38101070
DOI: 10.1016/j.psychres.2023.115611 -
BMC Psychiatry Dec 2023Insomnia symptoms in patients with major depressive disorder (MDD) are common and deleterious. Childhood trauma, personality traits, interpersonal distress, and social...
BACKGROUND
Insomnia symptoms in patients with major depressive disorder (MDD) are common and deleterious. Childhood trauma, personality traits, interpersonal distress, and social support contribute to insomnia, but how they interact to affect insomnia remains uncertain.
METHODS
A total of 791 patients with MDD completed the Insomnia Severity Index, Eysenck Personality Questionnaire, Interpersonal Relationship Comprehensive Diagnostic Scale, Childhood Trauma Questionnaire, Social Support Rating Scale and Hamilton Depression Scale-17. This study utilized network analyses to identify the central symptoms of insomnia and their associations with psychosocial factors.
RESULTS
Worrying about sleep was identified as the central symptom in the insomnia network, insomnia and associated personality network, insomnia and associated interpersonal disturbance network, insomnia and associated childhood trauma network, insomnia and associated social support network, and the integrated network of insomnia symptoms and associated psychosocial factors. In the networks of insomnia symptoms and individual psychosocial factors, most psychosocial factors (other than childhood trauma) were directly or indirectly related to insomnia symptoms; however, neuroticism was the only factor directly associated with insomnia symptoms before and after controlling for covariates. In the final integrated network of insomnia symptoms and psychosocial factors, neuroticism was a bridge node and mediated the relationships of social support and interpersonal disturbances with insomnia symptoms, which is clearly presented in the shortest pathways.
CONCLUSIONS
Worrying about sleep and neuroticism were prominent in the integrated network of insomnia symptoms and associated psychosocial factors, and the edge between them connected psychosocial factors and insomnia symptoms in MDD patients.
Topics: Humans; Depression; Sleep Initiation and Maintenance Disorders; Depressive Disorder, Major; Personality
PubMed: 38104061
DOI: 10.1186/s12888-023-05454-9 -
Psychiatry Research Aug 2023Subthreshold depression (StD) is a condition that significantly reduces the quality of life and increases the risk of developing major depressive disorder (MDD). In... (Meta-Analysis)
Meta-Analysis
Effects of non-pharmacological interventions on depressive symptoms and risk of major depressive disorder in adults with subthreshold depression: A systematic review and meta-analysis.
Subthreshold depression (StD) is a condition that significantly reduces the quality of life and increases the risk of developing major depressive disorder (MDD). In order to investigate the effectiveness of non-pharmacological interventions (NPIs) in preventing the onset of MDD and improving depressive symptoms in adults with StD (AStDs), we conducted a systematic search of nine databases and included a total of 15 studies. Standardized mean differences (SMDs) were calculated using random effects models. RoB2 tool and GRADEpro software were used to assess the methodological quality and evidence. Funnel plots, Egger's, and Begg's tests were used to analyze publication bias. Sensitivity, subgroup and meta-regression analyses were performed to explore potential sources of heterogeneity. The results showed that NPIs had a significant effect in preventing the onset of MDD and improving depressive symptoms. Subgroup analysis revealed that NPIs were particularly effective in general adult populations, during short-term follow-up (FU) periods, among pregnant women, and in universal prevention programs. The results were found to be robust and credible, as they were less sensitive to changes in the analysis method. Timely detection and treatment of StD is feasible and important, as it can effectively delay or prevent the onset of MDD.
Topics: Adult; Female; Humans; Pregnancy; Depression; Depressive Disorder, Major; Quality of Life
PubMed: 37482046
DOI: 10.1016/j.psychres.2023.115333