Synaptic Mechanisms Regulating Mood State Transitions in Depression.

Depression is an episodic form of mental illness characterized by mood state transitions with poorly understood neurobiological mechanisms. Antidepressants reverse the effects of stress and depression on synapse function, enhancing neurotransmission, increasing plasticity, and generating new synapses in stress-sensitive brain regions. These properties are shared to varying degrees by all known antidepressants, suggesting that synaptic remodeling could play a key role in depression pathophysiology and antidepressant function. Still, it is unclear whether and precisely how synaptogenesis contributes to mood state transitions. Here, we review evidence supporting an emerging model in which depression is defined by a distinct brain state distributed across multiple stress-sensitive circuits, with neurons assuming altered functional properties, synapse configurations, and, importantly, a reduced capacity for plasticity and adaptation. Antidepressants act initially by facilitating plasticity and enabling a functional reconfiguration of this brain state. Subsequently, synaptogenesis plays a specific role in sustaining these changes over time.

Antidepressants can induce mutation and enhance persistence toward multiple antibiotics.

Antibiotic resistance is an urgent threat to global health. Antidepressants are consumed in large quantities, with a similar pharmaceutical market share (4.8%) to antibiotics (5%). While antibiotics are acknowledged as the major driver of increasing antibiotic resistance, little attention is paid to the contribution of antidepressants in this process. Here, we demonstrate that antidepressants at clinically relevant concentrations induce resistance to multiple antibiotics, even following short periods of exposure. Antibiotic persistence was also enhanced. Phenotypic and genotypic analyses revealed the enhanced production of reactive oxygen species following exposure to antidepressants was directly associated with increased resistance. An enhanced stress signature response and stimulation of efflux pump expression were also associated with increased resistance and persistence. Mathematical modeling also predicted that antidepressants would accelerate the emergence of antibiotic-resistant bacteria, and persister cells would help to maintain the resistance. Overall, our findings highlight the antibiotic resistance risk caused by antidepressants.

Transcriptional signatures of early-life stress and antidepressant treatment efficacy.

Individuals with a history of early-life stress (ELS) tend to have an altered course of depression and lower treatment response rates. Research suggests that ELS alters brain development, but the molecular changes in the brain following ELS that may mediate altered antidepressant response have not been systematically studied. Sex and gender also impact the risk of depression and treatment response. Here, we leveraged existing RNA sequencing datasets from 1) blood samples from depressed female- and male-identifying patients treated with escitalopram or desvenlafaxine and assessed for treatment response or failure; 2) the nucleus accumbens (NAc) of female and male mice exposed to ELS and/or adult stress; and 3) the NAc of mice after adult stress, antidepressant treatment with imipramine or ketamine, and assessed for treatment response or failure. We find that transcriptomic signatures of adult stress after a history of ELS correspond with transcriptomic signatures of treatment nonresponse, across species and multiple classes of antidepressants. Transcriptomic correspondence with treatment outcome was stronger among females and weaker among males. We next pharmacologically tested these predictions in our mouse model of early-life and adult social defeat stress and treatment with either chronic escitalopram or acute ketamine. Among female mice, the strongest predictor of behavior was an interaction between ELS and ketamine treatment. Among males, however, early experience and treatment were poor predictors of behavior, mirroring our bioinformatic predictions. These studies provide neurobiological evidence for molecular adaptations in the brain related to sex and ELS that contribute to antidepressant treatment response.

The role of serotonin in depression-A historical roundup and future directions.

Depression is one of the most common psychiatric disorders worldwide, affecting approximately 280 million people, with probably much higher unrecorded cases. Depression is associated with symptoms such as anhedonia, feelings of hopelessness, sleep disturbances, and even suicidal thoughts. Tragically, more than 700 000 people commit suicide each year. Although depression has been studied for many decades, the exact mechanisms that lead to depression are still unknown, and available treatments only help a fraction of patients. In the late 1960s, the serotonin hypothesis was published, suggesting that serotonin is the key player in depressive disorders. However, this hypothesis is being increasingly doubted as there is evidence for the influence of other neurotransmitters, such as noradrenaline, glutamate, and dopamine, as well as larger systemic causes such as altered activity in the limbic network or inflammatory processes. In this narrative review, we aim to contribute to the ongoing debate on the involvement of serotonin in depression. We will review the evolution of antidepressant treatments, systemic research on depression over the years, and future research applications that will help to bridge the gap between systemic research and neurotransmitter dynamics using biosensors. These new tools in combination with systemic applications, will in the future provide a deeper understanding of the serotonergic dynamics in depression.

Astrocyte-derived lactate in stress disorders.

Stress disorders are psychiatric disorders arising following stressful or traumatic events. They could deleteriously affect an individual's health because they often co-occur with mental illnesses. Considerable attention has been focused on neurons when considering the neurobiology of stress disorders. However, like other mental health conditions, recent studies have highlighted the importance of astrocytes in the pathophysiology of stress-related disorders. In addition to their structural and homeostatic support role, astrocytes actively serve several functions in regulating synaptic transmission and plasticity, protecting neurons from toxic compounds, and providing metabolic support for neurons. The astrocyte-neuron lactate shuttle model sets forth the importance of astrocytes in providing lactate for the metabolic supply of neurons under intense activity. Lactate also plays a role as a signaling molecule and has been recently studied regarding its antidepressant activity. This review discusses the involvement of astrocytes and brain energy metabolism in stress and further reflects on the importance of lactate as an energy supply in the brain and its emerging antidepressant role in stress-related disorders.

Antidepressant drugs and risk of developing glioma: a national registry-based case control study and a meta-analysis.

The aim of the present study was to investigate if use of antidepressants is related to the risk of developing lower (WHO grade 2-3) and higher grade (WHO grade 4) glioma. A registry-based case-control study was performed using 1283 glioma cases and 6400 age-, sex- and geographically matched controls, diagnosed in Sweden 2009-2013. Conditional logistic regression was used to analyze whether Selective Serotonin Reuptake Inhibitors (SSRIs) or non-SSRIs were associated with the risk of developing lower- or higher-grade glioma in the study population. Our results show that use of antidepressant medication was not associated with the risk of developing glioma. We also performed a meta-analysis in which the dataset from the present study was combined with results from two previous epidemiological studies to answer the same questions. The meta-analysis showed a modest risk reduction of developing glioma in relation to antidepressant treatment (OR 0.90 [95% CI 0.83-0.97]), when all glioma subgroups and all forms of antidepressant medications were combined. In conclusion, it remains possible that antidepressants may have common monoaminergic mechanism(s) that reduce the risk of developing glioma.

Deprescribing of antidepressants: development of indicators of high-risk and overprescribing using the RAND/UCLA Appropriateness Method.

BACKGROUND: Antidepressants are first-line medications for many psychiatric disorders. However, their widespread long-term use in some indications (e.g., mild depression and insomnia) is concerning. Particularly in older adults with comorbidities and polypharmacy, who are more susceptible to adverse drug reactions, the risks and benefits of treatment should be regularly reviewed. The aim of this consensus process was to identify explicit criteria of potentially inappropriate antidepressant use (indicators) in order to support primary care clinicians in identifying situations, where deprescribing of antidepressants should be considered. METHODS: We used the RAND/UCLA Appropriateness Method to identify the indicators of high-risk and overprescribing of antidepressants. We combined a structured literature review with a 3-round expert panel, with results discussed in moderated meetings in between rounds. Each of the 282 candidate indicators was scored on a 9-point Likert scale representing the necessity of a critical review of antidepressant continuation (1-3 = not necessary; 4-6 = uncertain; 7-9 = clearly necessary). Experts rated the indicators for the necessity of review, since decisions to deprescribe require considerations of patient risk/benefit balance and preferences. Indicators with a median necessity rating of ≥ 7 without disagreement after 3 rating rounds were accepted. RESULTS: The expert panel comprised 2 general practitioners, 2 clinical pharmacologists, 1 gerontopsychiatrist, 2 psychiatrists, and 3 internists/geriatricians (total N = 10). After 3 assessment rounds, there was consensus for 37 indicators of high-risk and 25 indicators of overprescribing, where critical reviews were felt to be necessary. High-risk prescribing indicators included settings posing risks of drug-drug, drug-disease, and drug-age interactions or the occurrence of adverse drug reactions. Indicators with the highest ratings included those suggesting the possibility of cardiovascular risks (QTc prolongation), delirium, gastrointestinal bleeding, and liver injury in specific patient subgroups with additional risk factors. Overprescribing indicators target patients with long treatment durations for depression, anxiety, and insomnia as well as high doses for pain and insomnia. CONCLUSIONS: Explicit indicators of antidepressant high-risk and overprescribing may be used directly by patients and health care providers, and integrated within clinical decision support tools, in order to improve the overall risk/benefit balance of this commonly prescribed class of prescription drugs.

Potential deprescribing indications for antidepressants between 2012 and 2019: repeated cross-sectional analysis in two Scottish health boards.

BACKGROUND: Antidepressants have a pivotal role in the treatment of many psychiatric disorders, but there are concerns about long-term use and adverse effects. The objectives of this study were (1) to examine time trends in antidepressant use, (2) to estimate the prevalence of long-term and potential high-risk antidepressant use, and (3) to examine patient characteristics associated with potential deprescribing indications (PDIs) (i.e., simultaneous long-term and potential high-risk antidepressant use). METHODS: Repeated population-based cross-sectional study for all 609,299 people aged ≥ 18 years resident in the Tayside or Fife regions of Scotland. The prevalence of antidepressant use was examined on June 30th (index date) of each year from 2012 to 2019, while the prevalence of long-term and potential high-risk use as well as PDIs was assessed and compared on the same dates in 2012 and 2019. Binary logistic regression modeling was used to examine patient characteristics associated with PDIs. RESULTS: Antidepressant use increased by 27% from 12.0 to 15.3% among adult residents between 2012 and 2019. While the proportion of antidepressants users dispensed ≥ 1 antidepressant for > 2 years increased from 54.3 to 61.9% between 2012 and 2019, the proportion of antidepressant users triggering ≥ 1 indicator of potential high-risk use decreased slightly from 37.9 to 34.7%. In 2019, potential high-risk use most commonly related to indicators targeting fall risk (16.0%), cardiovascular risks (14.1%), insomnia (10.6%), and risk of orthostatic hypotension (8.6%). More than 1 in 4 (25.8%) antidepressant users had PDIs. The main risk factors associated with PDIs included increasing age (65-79, adjusted OR 14.12; 95% CI, 13.15-15.17), increasing number of drugs taken concomitantly (≥ 15 drugs, adjusted OR 7.37; 95% CI, 6.71-8.10), use of tricyclic antidepressants (≥ 50 mg) (adjusted OR 5.49; 95% CI, 5.02-6.01), and concomitant use of ≥ 2 antidepressants (adjusted OR 5.52; 95% CI, 5.20-5.85). CONCLUSIONS: Long-term and potential high-risk use of antidepressants is widespread, and potential deprescribing indications (PDIs) are increasing, suggesting the need for a critical review of their ongoing use by clinicians. If deemed necessary, future deprescribing interventions may use the criteria applied here for identification of patients with PDIs and for evaluating intervention effectiveness.

The relationship between antidepressants and breast cancer: evidence from Mendelian randomization.

BACKGROUND: The use of antidepressants has increased over the years, but the relationship between antidepressant use and the risk of breast cancer is not uniform because of confounding factors. We aimed to assess the effect of antidepressants on breast cancer risk using a two-sample Mendelian randomization (MR) approach.stet METHODS: Secondary data analysis was performed on pooled data from genome-wide association studies based on single-nucleotide polymorphisms that were highly correlated with antidepressants, SSRI drugs, and serotonin and prolactin levels were selected as instrumental variables to evaluate the association between antidepressants and SSRI drugs and prolactin levels with breast cancer and ER+/ER- breast cancer. We then performed a test of the hypothesis that SSRI drugs elevate prolactin concentrations. We performed two-sample Mendelian randomization analyses using inverse variance weighting, MR-Egger regression, and weighted median methods, respectively. RESULTS: There was no significant risk association between antidepressant and SSRI use and the development of breast cancer, ER-positive or ER-negative breast cancer (P > 0.05), and serotonin concentration was not associated with breast cancer risk (P > 0.05). There was a positive causal relationship between prolactin levels and breast cancer (IVW, P = 0.02, OR = 1.058) and ER-positive breast cancer (Weighted median, P = 0.043, OR = 1.141; IVW, P = 0.009, OR = 1.125). Results in SSRI medication and prolactin levels showed no association between SSRI analogs and prolactin levels (P > 0.05). CONCLUSION: Large MR analysis showed that antidepressants as well as SSRI drugs were not associated with breast cancer risk and the SSRI-prolactin-breast cancer hypothesis did not hold in our analysis.

Isolated central hypothyroidism: Underlying pathophysiology and relation to antidepressant and antipsychotic medications-A multi-centre South Wales study.

OBJECTIVE: Isolated biochemical central hypothyroidism is a presentation we are experiencing more frequently as endocrinologists, with variation in levels of investigation between physicians. We therefore conducted research to investigate the final diagnosis and clinical outcome of patients across multiple hospitals in South Wales with biochemical isolated central hypothyroidism; namely to establish whether this isolated biochemical picture was clinically significant. We also analysed whether there is an association between this biochemical picture and treatment with antidepressant and antipsychotic medications, and how common this is. DESIGN: We performed a retrospective observational study of patients across nine different hospitals in South Wales. We analysed patients referred to endocrinology at each site over a 6-year period with unexplained isolated biochemical central hypothyroidism. MATERIALS AND METHODOLOGY: 1022 individual patients' thyroid function test results were identified from our biochemical database using our inclusion criteria. After exclusion criteria were applied, 71 patients' results were analysed as to the final pathophysiology of their central hypothyroidism. RESULT: Of the 71 patients included in the study, none were found to have any clinically significant pathology on pituitary imaging. On reviewing their medications, 46/71 (65%) were found to be taking psychotropic medications. CONCLUSIONS: Our study strongly suggests isolated central hypothyroidism, in the absence of other pituitary hormone dysfunction or visual field defect, does not require further investigation, saving resources as well as sparing patients unnecessary anxiety. It also strongly supports a relationship between patients taking psychotropic medications and biochemical isolated central hypothyroidism, an association only described in a very limited amount of literature before this, and further supporting our previous single-centre study findings. The mechanism behind this is likely to be the suppression of thyrotropin secretion via antagonism of the dopamine-serotoninergic pathway. In our opinion, patients found to have isolated biochemical central hypothyroidism who are taking psychotropic medications can therefore be regarded to have a recognised cause for this biochemical finding and do not require further radiological investigation.

GluN2A: a promising target for developing novel antidepressants.

BACKGROUND: Depression is a heterogeneous disorder with high morbidity and disability rates that poses serious problems in regard to mental health care. It is now well established that N-methyl D-aspartate receptors (NMDARs) modulators are being increasingly explored as potential therapeutic options for treating depression, although relatively little is known about their mechanisms of action. NMDARs are glutamate-gated ion channels that are ubiquitously expressed in the central nervous system (CNS) and they have been shown to play key roles in excitatory synaptic transmission. GluN2A, the predominant Glu2N subunit of functional NMDARs in neurons, is involved in various physiological processes in the CNS and is associated with diseases such as anxiety, depression, and schizophrenia. However, the role of GluN2A in the pathophysiology of depression has not yet been elucidated. METHODS: We reviewed several past studies in order to better understand the function of GluN2A in depression. Additionally, we also summarized the pathogenesis of depression based on the regulation of GluN2A expression, particularly its interaction with neuroinflammation and neurogenesis, which has received considerable critical attention and is highly implicated in the onset of depression. RESULTS: These evidences suggest that GluN2A overexpression impairs structural and functional synaptic plasticity, which contributes to the development of depression. Consequently, this knowledge is vital for the development of selective antagonists targeting GluN2A subunits using pharmacological and molecular methods. CONCLUSIONS: Specific inhibition of GluN2A NMDAR subunit is resistant to chronic stress-induced depressive-like behaviors, making them promising targets for the development of novel antidepressants.

Effects of medication on dopamine transporter imaging using [123I]I-FP-CIT SPECT in routine practice.

PURPOSE: Dopamine transporter (DAT) imaging is used to support the diagnosis of neurodegenerative parkinsonian disorders. Specific medications have been reported to confound the interpretation of [123I]I-FP-CIT SPECT scans, but there is limited data. The aim of the current study is to identify potential medication effects on the interpretation of [123I]I-FP-CIT SPECT scans in routine practice. MATERIALS AND METHODS: Consecutive patients undergoing a [123I]I-FP-CIT SPECT/CT scan on a 360° CZT camera between September 2019 and December 2022 were included. An exhaustive review of patient medications (antidepressants, antipsychotics, anti-epileptics, anti-parkinsonians, benzodiazepines, lithium, opioids, and stimulants) was performed. Two experienced nuclear physicians, blinded to the medication reports, interpreted the [123I]I-FP-CIT SPECT scans visually and a semi-quantitative analysis was performed using a local normal database. RESULTS: The study included 305 patients (71.0 ± 10.4, 135 women) and 145 (47.5%) visually interpreted normal scans. In normal scans, the striatum/occiput radioligand uptake ratio was decreased by noradrenergic and specific serotonergic antidepressants (NASSAs) (n = 15, z-score of - 0.93) and opioid medication (tramadol, n = 6, z-score of - 0.85) and was associated with a younger age in the multivariate analysis. In the overall population, the striatum/occiput ratio was influenced by NASSAs and associated with consensual visual analysis, age, sex, and anti-parkinsonian medications related to the status of the disease. CONCLUSION: Our study confirms the potential impact of antidepressant (NASSA) and opioid (tramadol) medications on the semi-quantitative analysis of [123I]I-FP-CIT SPECT scans. However, when performing a visual analysis, only NASSAs significantly impacted the interpretation of [123I]I-FP-CIT SPECT scans.

Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials.

BACKGROUND: Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment. AIMS: To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants. METHOD: Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses. RESULTS: Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, ßpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, ßpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (ßpooled = 0.16) and the IMD index (ßpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission. CONCLUSIONS: Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Measuring the impact of therapy on medication use: data-linkage study.

BACKGROUND: The psychological therapies service (PTS) in the Northern Health and Social Care Trust, in Northern Ireland, provides therapies to adults with moderate or severe mental health difficulties. Psychometric outcomes data are routinely collected to assess if a patient demonstrates significant improvement in their main presenting problem area following therapy. The wider impact of therapy is not fully measured in the outcomes database as this would be disproportionately burdensome for both patient and therapist. The present study, to our knowledge, is the first to use data linkage to link patient therapy outcomes data with prescriptions data. AIMS: To widen our understanding of patient medication use before and after therapy. METHOD: Using Health and Care Number as a unique identifier, the Psychological Therapies Service - Routine Outcome Measurement Database (n = 3625) and data from 72 500 controls were linked with data from the Enhanced Prescribing Database (EPD). The EPD data were sourced from the Honest Broker Service. RESULTS: Key findings from the study were: (a) the odds of PTS clients using antipsychotics in the year before therapy were 25 times greater compared with controls (odds ratio (OR) = 24.53, 95% CI 20.16-29.84); (b) in the 1st year post discharge, PTS clients who clinically improved post therapy discharge were more likely than 'non-engagers' and 'non-improvers' to come off antianxiety medication (OR = 0.61, 95%, CI 0.38-0.98); and (c) therapy did not have an impact on antidepressant use. CONCLUSIONS: The results highlight the need for discussion between therapy services, GPs and psychiatry about whether more engagement and collaboration is needed to plan phased reduction in medication.

Association between a selective 5-HT4 receptor agonist and incidence of major depressive disorder: emulated target trial.

BACKGROUND: The serotonin 4 receptor (5-HT4R) is a promising target for the treatment of depression. Highly selective 5-HT4R agonists, such as prucalopride, have antidepressant-like and procognitive effects in preclinical models, but their clinical effects are not yet established. AIMS: To determine whether prucalopride (a 5-HT4R agonist and licensed treatment for constipation) is associated with reduced incidence of depression in individuals with no past history of mental illness, compared with anti-constipation agents with no effect on the central nervous system. METHOD: Using anonymised routinely collected data from a large-scale USA electronic health records network, we conducted an emulated target trial comparing depression incidence over 1 year in individuals without prior diagnoses of major mental illness, who initiated treatment with prucalopride versus two alternative anti-constipation agents that act by different mechanisms (linaclotide and lubiprostone). Cohorts were matched for 121 covariates capturing sociodemographic factors, and historical and/or concurrent comorbidities and medications. The primary outcome was a first diagnosis of major depressive disorder (ICD-10 code F32) within 1 year of the index date. Robustness of the results to changes in model and population specification was tested. Secondary outcomes included a first diagnosis of six other neuropsychiatric disorders. RESULTS: Treatment with prucalopride was associated with significantly lower incidence of depression in the following year compared with linaclotide (hazard ratio 0.87, 95% CI 0.76-0.99; P = 0.038; n = 8572 in each matched cohort) and lubiprostone (hazard ratio 0.79, 95% CI 0.69-0.91; P < 0.001; n = 8281). Significantly lower risks of all mood disorders and psychosis were also observed. Results were similar across robustness analyses. CONCLUSIONS: These findings support preclinical data and suggest a role for 5-HT4R agonists as novel agents in the prevention of major depression. These findings should stimulate randomised controlled trials to confirm if these agents can serve as a novel class of antidepressant within a clinical setting.

Patterns, predictors, and patient-reported reasons for antidepressant discontinuation in the WHO World Mental Health Surveys.

BACKGROUND: Despite their documented efficacy, substantial proportions of patients discontinue antidepressant medication (ADM) without a doctor's recommendation. The current report integrates data on patient-reported reasons into an investigation of patterns and predictors of ADM discontinuation. METHODS: Face-to-face interviews with community samples from 13 countries (n = 30 697) in the World Mental Health (WMH) Surveys included n = 1890 respondents who used ADMs within the past 12 months. RESULTS: 10.9% of 12-month ADM users reported discontinuation-based on recommendation of the prescriber while 15.7% discontinued in the absence of prescriber recommendation. The main patient-reported reason for discontinuation was feeling better (46.6%), which was reported by a higher proportion of patients who discontinued within the first 2 weeks of treatment than later. Perceived ineffectiveness (18.5%), predisposing factors (e.g. fear of dependence) (20.0%), and enabling factors (e.g. inability to afford treatment cost) (5.0%) were much less commonly reported reasons. Discontinuation in the absence of prescriber recommendation was associated with low country income level, being employed, and having above average personal income. Age, prior history of psychotropic medication use, and being prescribed treatment from a psychiatrist rather than from a general medical practitioner, in comparison, were associated with a lower probability of this type of discontinuation. However, these predictors varied substantially depending on patient-reported reasons for discontinuation. CONCLUSION: Dropping out early is not necessarily negative with almost half of individuals noting they felt better. The study underscores the diverse reasons given for dropping out and the need to evaluate how and whether dropping out influences short- or long-term functioning.

Clinical factors associated with relapse in depression in a sample of UK primary care patients who have been on long-term antidepressant treatment.

BACKGROUND: This paper investigates whether age of onset of depression, duration of the last episode, number of episodes, and residual symptoms of depression and anxiety are associated with depression relapse in primary care patients who have been on long-term maintenance antidepressant treatment and no longer meet ICD10 criteria for depression. METHODS: An observational cohort using data from ANTLER (N = 478), a double-blind placebo-controlled trial. The primary outcome was time to relapse using the retrospective CIS-R. Participants were followed for 12 months. RESULTS: Primary outcome was available for 468 participants. Time to relapse in those with more than five previous episodes of depression was shorter, hazard ratio (HR) 1.84 (95% confidence interval [CI] 1.23-2.75) compared to people with two episodes; HR 1.57 (95% CI 1.01-2.43) after adjustment. The residual symptoms of depression at baseline were also associated with increased relapse: HR 1.05 (95% CI 1.01-1.09) and HR 1.06 (95% CI 1.01-1.12) in the adjusted model. There was evidence of reduced rate of relapse in older age of onset group: HR 0.86 (95% CI 0.78-0.95); HR attenuated after adjustment HR 0.91 (95% CI 0.81-1.02). There was no evidence of an association between duration of the current episode and residual anxiety symptoms with relapse. CONCLUSIONS: The number of previous episodes and residual symptoms of depression were associated with increased likelihood of relapse. These factors could inform joint decision making when patients are considering tapering off maintenance antidepressant treatment or considering other treatments to prevent relapse.

The inflammatory underpinning of depression: An historical perspective.

Over the last thirty years, substantial evidence has accumulated in support of the hypothesis that dysregulation of inflammatory processes plays a critical role in the pathophysiology of depression. This review traces the evolution of research supporting this link, discussing key findings from several major investigative fronts: Alterations in inflammatory markers associated with depression; Mood changes following the exogenous administration of inflammatory challenges; The anti-inflammatory properties of traditional antidepressants and the promising antidepressant effects of anti-inflammatory drugs. Additionally, it explores how inflammatory processes interact with specific brain regions and neurochemical systems to drive depressive pathology. A thorough analysis of the 100 most-cited experimental studies on the topic ensures a comprehensive, transparent and unbiased collection of references. This methodological approach offers a panoramic view of the inflammation-depression nexus, shedding light on the complexity of its mechanisms and their connections to psychiatric categorizations, symptoms, demographics, and life events. Synthesizing insights from this extensive research, the review presents an integrative model of the biological foundations of inflammation-associated depression. It posits that we have reached a critical juncture where the translation of this knowledge into personalized immunomodulatory treatments for depression is not just possible, but imperative.

Patterns of pharmacotherapy for bipolar disorder: A GBC survey.

OBJECTIVES: To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well-characterized individuals with BD in North America, Europe, and Australia. METHODS: Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta-analyses with generalized linear mixed methods were conducted to identify prescription patterns. RESULTS: This study included 10,351 individuals from North America (n = 3985), Europe (n = 3822), and Australia (n = 2544). Overall, participants were predominantly female (60%) with BD-I (60%; vs. BD-II = 33%). Cross-sectionally, mood-stabilizing anticonvulsants (44%), second-generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First-generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD-II (47%) compared to BD-I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort. CONCLUSIONS: Mood-stabilizing anticonvulsants, second-generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first-generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence-based guidelines to help improve treatment practices in BD.

Prior psychiatric morbidity and differential psychopharmacological treatment patterns: Exploring the heterogeneity of bipolar disorder in a nationwide study of 9594 patients.

OBJECTIVES: Individuals with bipolar disorders (BD) have heterogenic pre-onset illness courses and responses to treatment. The pattern of illness preceding the diagnosis of BD may be a marker of future treatment response. Here, we examined associations between psychiatric morbidity preceding the diagnosis of BD and pharmacological treatment patterns in the 2 years following diagnosis. METHODS: In this register-based study, we included all patients with a diagnosis of BD attending Danish Psychiatric Services between January 1, 2012 and December 31, 2016. We examined the association between a diagnosis of substance use disorder, psychosis (other than schizophrenia or schizoaffective disorder), unipolar depression, anxiety/OCD, PTSD, personality disorder, or ADHD preceding BD and pharmacological treatment patterns following the diagnosis of BD (lithium, valproate, lamotrigine, antidepressants, olanzapine, risperidone, and quetiapine) via multivariable Cox proportional hazards regression adjusted for age, sex, and year of BD diagnosis. RESULTS: We included 9594 patients with a median age of 39 years, 58% of whom were female. Antidepressants, quetiapine, and lamotrigine were the most commonly used medications in BD and were all linked to prior depressive illness and female sex. Lithium was used among patients with less diagnostic heterogeneity preceding BD, while valproate was more likely to be used for patients with prior substance use disorder or ADHD. CONCLUSION: The pharmacological treatment of BD is linked to psychiatric morbidity preceding its diagnosis. Assuming that these associations reflect well-informed clinical decisions, this knowledge may inform future clinical trials by taking participants' prior morbidity into account in treatment allocation.