The bidirectional interaction between antidepressants and the gut microbiota: are there implications for treatment response?

This review synthesizes the evidence on associations between antidepressant use and gut microbiota composition and function, exploring the microbiota's possible role in modulating antidepressant treatment outcomes. Antidepressants exert an influence on measures of gut microbial diversity. The most consistently reported differences were in ß-diversity between those exposed to antidepressants and those not exposed, with longitudinal studies supporting a potential causal association. Compositional alterations in antidepressant users include an increase in the Bacteroidetes phylum, Christensenellaceae family, and Bacteroides and Clostridium genera, while a decrease was found in the Firmicutes phylum, Ruminococcaceae family, and Ruminococcus genus. In addition, antidepressants attenuate gut microbial differences between depressed and healthy individuals, modulate microbial serotonin transport, and influence microbiota's metabolic functions. These include lyxose degradation, peptidoglycan maturation, membrane transport, and methylerythritol phosphate pathways, alongside gamma-aminobutyric acid metabolism. Importantly, baseline increased α-diversity and abundance of the Roseburia and Faecalibacterium genera, in the Firmicutes phylum, are associated with antidepressant response, emerging as promising biomarkers. This review highlights the potential for gut microbiota as a predictor of treatment response and emphasizes the need for further research to elucidate the mechanisms underlying antidepressant-microbiota interactions. More homogeneous studies and standardized techniques are required to confirm these initial findings.

Metabolic activity of CYP2C19 and CYP2D6 on antidepressant response from 13 clinical studies using genotype imputation: a meta-analysis.

Cytochrome P450 enzymes including CYP2C19 and CYP2D6 are important for antidepressant metabolism and polymorphisms of these genes have been determined to predict metabolite levels. Nonetheless, more evidence is needed to understand the impact of genetic variations on antidepressant response. In this study, individual clinical and genetic data from 13 studies of European and East Asian ancestry populations were collected. The antidepressant response was clinically assessed as remission and percentage improvement. Imputed genotype was used to translate genetic polymorphisms to metabolic phenotypes (poor, intermediate, normal, and rapid+ultrarapid) of CYP2C19 and CYP2D6. CYP2D6 structural variants cannot be imputed from genotype data, limiting the determination of metabolic phenotypes, and precluding testing for association with response. The association of CYP2C19 metabolic phenotypes with treatment response was examined using normal metabolizers as the reference. Among 5843 depression patients, a higher remission rate was found in CYP2C19 poor metabolizers compared to normal metabolizers at nominal significance but did not survive after multiple testing correction (OR = 1.46, 95% CI [1.03, 2.06], p = 0.033, heterogeneity I2 = 0%, subgroup difference p = 0.72). No metabolic phenotype was associated with percentage improvement from baseline. After stratifying by antidepressants primarily metabolized by CYP2C19, no association was found between metabolic phenotypes and antidepressant response. Metabolic phenotypes showed differences in frequency, but not effect, between European- and East Asian-ancestry studies. In conclusion, metabolic phenotypes imputed from genetic variants using genotype were not associated with antidepressant response. CYP2C19 poor metabolizers could potentially contribute to antidepressant efficacy with more evidence needed. Sequencing and targeted pharmacogenetic testing, alongside information on side effects, antidepressant dosage, depression measures, and diverse ancestry studies, would more fully capture the influence of metabolic phenotypes.

Understanding and treating postpartum depression: a narrative review.

Postpartum depression (PPD) is an increasingly prevalent but still poorly characterized disorder. Causal and modulating factors include hormones fluctuations, such as estrogen, progesterone, and allopregnolone, pathways imbalances, such as oxytocin and kynurenine, chronobiological factors, and brain imaging alterations. Treatment may differ from the traditional major depression management, while selective serotonin reuptake inhibitors such as sertraline are commonly used and suggested by guidelines, neurosteroids such as brexanolone and the more convenient zuranolone have been recently approved. Newer neurosteroids such as ganaxolone, valaxanolone, and lysaxanolone are currently under development, but also esketamine and psychedelics are promising potential treatments. Other somatic treatments including brain stimulation techniques and light therapy also showed benefit. PPD is therefore increasingly understood as, at least partially, independent from major depressive disorder. Specific and individualized treatments including pharmacological and non-pharmacological therapies are progressively being introduced in the routine clinical practice.

Shared genetics linking sociability with the brain's default mode network.

The brain's default mode network (DMN) plays a role in social cognition, with altered DMN function being associated with social impairments across various neuropsychiatric disorders. In the present study, we examined the genetic relationship between sociability and DMN-related resting-state functional magnetic resonance imaging (rs-fMRI) traits. To this end, we used genome-wide association summary statistics for sociability and 31 activity and 64 connectivity DMN-related rs-fMRI traits (N=34,691-342,461). First, we examined global and local genetic correlations between sociability and the rs-fMRI traits. Second, to assess putatively causal relationships between the traits, we conducted bi-directional Mendelian randomisation (MR) analyses. Finally, we prioritised genes influencing both sociability and rs-fMRI traits by combining three methods: gene-expression eQTL MR analyses, the CELLECT framework using single-nucleus RNA-seq data, and network propagation in the context of a protein-protein interaction network. Significant local genetic correlations were found between sociability and two rs-fMRI traits, one representing spontaneous activity within the temporal cortex, the other representing connectivity between the frontal/cingulate and angular/temporal cortices. Sociability affected 12 rs-fMRI traits when allowing for weakly correlated genetic instruments. Combing all three methods for gene prioritisation, we defined 17 highly prioritised genes, with DRD2 and LINGO1 showing the most robust evidence across all analyses. By integrating genetic and transcriptomics data, our gene prioritisation strategy may serve as a blueprint for future studies. The prioritised genes could be explored as potential biomarkers for social dysfunction in the context of neuropsychiatric disorders and as drug target genes.

Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance.

An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of treatment-resistant depression (TRD) represents a major goal of precision psychiatry, which is hampered by the clinical and biological heterogeneity. To uncover biologically-driven subtypes of MDD, we applied an unsupervised data-driven framework to stratify 102 MDD patients on their neuroimaging signature, including extracted measures of cortical thickness, grey matter volumes, and white matter fractional anisotropy. Our novel analytical pipeline integrated different machine learning algorithms to harmonize data, perform data dimensionality reduction, and provide a stability-based relative clustering validation. The obtained clusters were characterized for immune-inflammatory peripheral biomarkers, TRD, history of childhood trauma and depressive symptoms. Our results indicated two different clusters of patients, differentiable with 67 % of accuracy: one cluster (n = 59) was associated with a higher proportion of TRD, and higher scores of energy-related depressive symptoms, history of childhood abuse and emotional neglect; this cluster showed a widespread reduction in cortical thickness (d = 0.43-1.80) and volumes (d = 0.45-1.05), along with fractional anisotropy in the fronto-occipital fasciculus, stria terminalis, and corpus callosum (d = 0.46-0.52); the second cluster (n = 43) was associated with cognitive and affective depressive symptoms, thicker cortices and wider volumes. Multivariate analyses revealed distinct brain-inflammation relationships between the two clusters, with increase in pro-inflammatory markers being associated with decreased cortical thickness and volumes. Our stratification of MDD patients based on structural neuroimaging identified clinically-relevant subgroups of MDD with specific symptomatic and immune-inflammatory profiles, which can contribute to the development of tailored personalized interventions for MDD.

The clinical perspective on late-onset depression in European real-world treatment settings.

The clinical phenotype of the so-called late-onset depression (LOD) affecting up to 30% of older adults and yielding heterogeneous manifestations concerning symptoms, severity and course has not been fully elucidated yet. This European, cross-sectional, non-interventional, naturalistic multicenter study systematically investigated socio-demographic and clinical correlates of early-onset depression (EOD) and LOD (age of onset ≥ 50 years) in 1410 adult in- and outpatients of both sexes receiving adequate psychopharmacotherapy. In a total of 1329 patients (94.3%) with known age of disease onset, LOD was identified in 23.2% and was associated with unemployment, an ongoing relationship, single major depressive episodes, lower current suicidal risk and higher occurrence of comorbid hypertension. In contrast, EOD was related to higher rates of comorbid migraine and additional psychotherapy. Although the applied study design does not allow to draw any causal conclusions, the present results reflect broad clinical settings and emphasize easily obtainable features which might be characteristic for EOD and LOD. A thoughtful consideration of age of onset might, hence, contribute to optimized diagnostic and therapeutic processes in terms of the globally intended precision medicine, ideally enabling early and adequate treatment allocations and implementation of respective prevention programs.

Suicide ideation and male-female differences in major depressive disorder.

OBJECTIVE: This study aimed to explore male-female differences in suicide ideation (SI) and suicide risk factors in major depressive disorder (MDD). METHODS: We analysed 482 adults (sample 1) and 438 elderly outpatients (sample 2) with MDD. Sample 1 was treated with different antidepressant combinations (escitalopram; bupropion plus escitalopram; venlafaxine plus mirtazapine) and assessed by means of the Concise Health Risk Tracking (SI), Quick Inventory of Depressive Symptomatology, Altman Mania Rating Scale and Psychiatric Diagnostic Screening Questionnaire. Sample 2 was treated with venlafaxine and assessed using the Hamilton scale for depression, Anxiety Sensitivity Index and Penn State Worry Questionnaire for anxiety, Beck Scale for Suicide Ideation and Repeatable Battery for the Assessment of Neuropsychological Status. RESULTS: In sample 1, females had greater depression severity (O.R 0.961 99%CI: 0.929 - 0.995), males reported more alcohol abuse (O.R 1.299 99%CI: 1.118 - 1.509) and active SI (O.R 1.109 99%CI: 1.005 - 1.255). In sample 2 men showed more severe SI (O.R 1.067; 99%CI: 1.014 - 1.122) and weight loss (OR = 5.89 99%CI: 1.01 - 34.19), women more gastrointestinal symptoms. CONCLUSIONS: In these selected samples, although women had more severe depression, men had more suicide risk factors. Such differences might contribute to men's increased suicide risk.

In major depressive disorder sex differences affect the clinical expression of depressive episodes. In comparison to men, women endorse higher levels of overall depression in adult MDD and more somatic anxiety and gastrointestinal symptoms in late-life MDD.After controlling for confounding variables, males have more severe SI and a larger number of suicide risk factors (eg. alcohol abuse; weight loss). The association between male sex and SI is detectable in both adults and elderly patients with MDD.Further studies are necessary to elucidate how sex differences in suicide ideation and suicide risk factors are related to men's increased suicide risk.

A Critical View on New and Future Antidepressants.

For the first time after many decades, many new antidepressants have been approved and many more are under various stages of development and will soon be available in the market. The new drugs present a range of new mechanisms of action with benefits in terms of speed of action, tolerability and range of treatable disorders. Neurosteroids have been recently approved and their rapid benefit may extend from postpartum depression to anxious depression and bipolar depression, dextromethorphan and bupropion combination may prove useful in major depression but also in treatment resistant depression, dextromethadone is a possible augmentation in partial antidepressant response, psychedelic drugs have the potential of long lasting benefits after a single administration, though are still experimental treatments. Botulinum has the same advantage of psychedelics of a single administration and its antidepressant effects may last for weeks or more. Further potentially interesting new antidepressant mechanisms include new drug targets, drug repurposing and genetic or epigenetic manipulations. It is therefore important that clinicians are kept up to date with new evidence so that new evidence can be rapidly translated into clinical practice.

Neurological, Metabolic, and Psychopathological Correlates of Lifetime Suicidal Behaviour in Major Depressive Disorder without Current Suicide Ideation.

INTRODUCTION: Suicidal behaviour (SB) has a complex aetiology. Although suicidal ideation (SI) is considered the most important risk factor for future attempts, many people who engage in SB do not report it. METHODS: We investigated neurological, metabolic, and psychopathological correlates of lifetime SB in two independent groups of patients with major depression (sample 1: n = 230; age: 18-65 years; sample 2: n = 258; age >60 years) who did not report SI during an index episode. RESULTS: Among adults (sample 1), SB was reported by 141 subjects (58.7%) and severe SB by 33 (15%). After controlling for interactions, four risk factors for SB emerged: male gender (OR 2.55; 95% CI: 1.06-6.12), negative self-perception (OR 1.76; 95% CI: 1.08-2.87), subthreshold hypomania (OR 4.50; 95% CI: 1.57-12.85), and sexual abuse (OR 3.09; 95% CI: 1.28-7.48). The presence of at least two of these factors had the best accuracy in predicting SB: sensitivity = 57.6% (39.2-74.5); specificity = 75.1% (68.5-82.0); PPV = 27.9% (20.9-37.2); NPV = 91.4% (87.6-94.1). In older patients (sample 2), 23 subjects (9%) reported previous suicide attempts, which were characterized by earlier onset (25 years: OR 0.95: 0.92-0.98), impaired verbal performance (verbal fluency: OR 0.95: 0.89-0.99), higher HDL cholesterol levels (OR 1.04: 1.00-1.07) and more dyskinesias (OR 2.86: 1.22-6.70). CONCLUSION: Our findings suggest that SB is common in major depressive disorder, even when SI is not reported. In these individuals it is feasible and recommended to investigate both psychiatric and organic risk factors. The predictive power of models excluding SI is comparable to that of models including SI.

Local patterns of genetic sharing challenge the boundaries between neuropsychiatric and insulin resistance-related conditions.

The co-occurrence of insulin resistance (IR)-related metabolic conditions with neuropsychiatric disorders is a complex public health challenge. Evidence of the genetic links between these phenotypes is emerging, but little is currently known about the genomic regions and biological functions that are involved. To address this, we performed Local Analysis of [co]Variant Association (LAVA) using large-scale (N=9,725-933,970) genome-wide association studies (GWASs) results for three IR-related conditions (type 2 diabetes mellitus, obesity, and metabolic syndrome) and nine neuropsychiatric disorders. Subsequently, positional and expression quantitative trait locus (eQTL)-based gene mapping and downstream functional genomic analyses were performed on the significant loci. Patterns of negative and positive local genetic correlations (|rg|=0.21-1, pFDR<0.05) were identified at 109 unique genomic regions across all phenotype pairs. Local correlations emerged even in the absence of global genetic correlations between IR-related conditions and Alzheimer's disease, bipolar disorder, and Tourette's syndrome. Genes mapped to the correlated regions showed enrichment in biological pathways integral to immune-inflammatory function, vesicle trafficking, insulin signalling, oxygen transport, and lipid metabolism. Colocalisation analyses further prioritised 10 genetically correlated regions for likely harbouring shared causal variants, displaying high deleterious or regulatory potential. These variants were found within or in close proximity to genes, such as SLC39A8 and HLA-DRB1, that can be targeted by supplements and already known drugs, including omega-3/6 fatty acids, immunomodulatory, antihypertensive, and cholesterol-lowering drugs. Overall, our findings underscore the complex genetic landscape of IR-neuropsychiatric multimorbidity, advocating for an integrated disease model and offering novel insights for research and treatment strategies in this domain.

Pharmacological treatments for psychotic depression: a systematic review and network meta-analysis.

BACKGROUND: There are no recommendations based on the efficacy of specific drugs for the treatment of psychotic depression. To address this evidence gap, we did a network meta-analysis to assess and compare the efficacy and safety of pharmacological treatments for psychotic depression. METHODS: In this systematic review and network meta-analysis, we searched ClinicalTrials.gov, CENTRAL, Embase, PsycINFO, PubMed, Scopus, and Web of Science from inception to Nov 23, 2023 for randomised controlled trials published in any language that assessed pharmacological treatments for individuals of any age with a diagnosis of a major depressive episode with psychotic features, in the context of major depressive disorder or bipolar disorder in any setting. We excluded continuation or maintenance trials. We screened the study titles and abstracts identified, and we extracted data from relevant studies after full-text review. If full data were not available, we requested data from study authors twice. We analysed treatments for individual drugs (or drug combinations) and by grouping them on the basis of mechanisms of action. The primary outcomes were response rate (ie, the proportion of participants who responded to treatment) and acceptability (ie, the proportion who discontinued treatment for any reason). We calculated risk ratios and did separate frequentist network meta-analyses by using random-effects models. The risk of bias of individual studies was assessed with the Cochrane risk-of-bias tool and the confidence in the evidence with the Confidence-In-Network-Meta-Analysis (CINeMA). This study was registered with PROSPERO, CRD42023392926. FINDINGS: Of 6313 reports identified, 16 randomised controlled trials were included in the systematic review, and 14 were included in the network meta-analyses. The 16 trials included 1161 people with psychotic depression (mean age 50·5 years [SD 11·4]). 516 (44·4%) participants were female and 422 (36·3%) were male; sex data were not available for the other 223 (19·2%). 489 (42·1%) participants were White, 47 (4·0%) were African American, and 12 (1·0%) were Asian; race or ethnicity data were not available for the other 613 (52·8%). Only the combination of fluoxetine plus olanzapine was associated with a higher proportion of participants with a treatment response compared with placebo (risk ratio 1·91 [95% CI 1·27-2·85]), with no differences in terms of safety outcomes compared with placebo. When treatments were grouped by mechanism of action, the combination of a selective serotonin reuptake inhibitor with a second-generation antipsychotic was associated with a higher proportion of treatment responses than was placebo (1·89 [1·17-3·04]), with no differences in terms of safety outcomes. In head-to-head comparisons of active treatments, a significantly higher proportion of participants had a response to amitriptyline plus perphenazine (3·61 [1·23-10·56]) and amoxapine (3·14 [1·01-9·80]) than to perphenazine, and to fluoxetine plus olanzapine compared with olanzapine alone (1·60 [1·09-2·34]). Venlafaxine, venlafaxine plus quetiapine (2·25 [1·09-4·63]), and imipramine (1·95 [1·01-3·79]) were also associated with a higher proportion of treatment responses overall. In head-to-head comparisons grouped by mechanism of action, antipsychotic plus antidepressant combinations consistently outperformed monotherapies from either drug class in terms of the proportion of participants with treatment responses. Heterogeneity was low. No high-risk instances were identified in the bias assessment for our primary outcomes. INTERPRETATION: According to the available evidence, the combination of a selective serotonin reuptake inhibitor and a second-generation antipsychotic-and particularly of fluoxetine and olanzapine-could be the optimal treatment choice for psychotic depression. These findings should be taken into account in the development of clinical practice guidelines. However, these conclusions should be interpreted cautiously in view of the low number of included studies and the limitations of these studies. FUNDING: None.

Polygenic risk scores for mood and related disorders and environmental factors: Interaction effects on wellbeing in the UK biobank.

Mood disorders have a genetic and environmental component and interactions (GxE) on the risk of psychiatric diseases have been investigated. The same GxE interactions may affect wellbeing measures, which go beyond categorical diagnoses and reflect the health-disease continuum. We evaluated GxE effects in the UK Biobank, considering as outcomes subjective wellbeing (feeling good and functioning well) and objective measures (education and income). We estimated the polygenic risk scores (PRSs) of major depressive disorder, bipolar disorder, schizophrenia, and attention deficit hyperactivity disorder. Stressful/traumatic events during adulthood or childhood were considered as E variables, as well as social support. The addition of the PRSxE interaction to PRS and E variables was tested in linear or multinomial regression models, adjusting for confounders. We included 33 k-380 k participants, depending on the variables considered. Most PRSs and E factors showed additive effects on outcomes, with effect sizes generally 3-5 times larger for E variables than PRSs. We found some interaction effects, particularly when considering recent stress, history of a long illness/disability/infirmity, and social support. Higher PRSs increased the negative effects of stress on wellbeing, but they also increased the positive effects of social support, with interaction effects particularly for the outcomes health satisfaction, loneliness, and income (p < Bonferroni corrected threshold of 1.92e-4). PRSxE terms usually added ∼0.01-0.02% variance explained to the corresponding additive model. PRSxE effects on wellbeing involve both positive and negative E factors. Despite small variance explained at the population level, preventive/therapeutic interventions that modify E factors could be beneficial at the individual level.

A comprehensive overview of post-stroke depression treatment options.

Nearly one-third of all stroke patients develop depression at any time after a stroke, and its presence is associated with unfavorable outcomes. This narrative review aims to provide a synopsis of possible pharmacological and non-pharmacological treatment modalities for post-stroke depression (PSD). Several studies have demonstrated the efficacy and safety of selective serotonin reuptake inhibitors in treating the symptoms of this clinical condition. The treatment of PSD has been recently enhanced by innovative approaches, such as cognitive-behavioral therapy, virtual reality, telehealth, repetitive transcranial magnetic stimulation, and non-conventional therapies, which might improve depression treatment in stroke survivors. Future high-quality randomized controlled trials are necessary to confirm this hypothesis.

Temperament and character dimensions explain self-reported resilience deficits in patients with affective disorders.

This is the first study exploring how temperament and character personality dimensions impact self-reported resilience in major depressive disorder (MDD) and bipolar disorder (BD). We included 130 euthymic patients with affective disorders (AFD; 66 MDD and 64 BD) and 134 healthy controls (HC). Connor and Davidson resilience scale and Temperament and Character Inventory (TCI-140) were administered. Multiple linear regressions and interaction analyses were performed. Mediation analyses examined if personality dimensions explained group differences in resilience. Resilience was lower in MDD and BD vs. HC and in MDD vs. BD, adjusting for sex, age and education. Higher resilience was predicted by lower harm avoidance (HA) and higher persistence (P) in AFD and MDD, lower HA in BD and higher P and self-directedness (SD) in HC. However, only HA and P had a group-specific effect on resilience in AFD vs. HC. In mediation analyses, specific TCI dimensions at least partially explained differences in resilience: HA, P and SD in AFD or MDD vs. HC; SD in BD vs. HC; P in BD vs. MDD. Concludingly, two temperament traits (HA, P) and a character trait (SD) predict resilience in AFD. Focusing on personality could identify sources of compromised resilience as potential treatment targets.

Emotion dysregulation in bipolar disorder compared to other mental illnesses: a systematic review and meta-analysis.

People with bipolar disorder (BD) often present emotion dysregulation (ED), a pattern of emotional expression interfering with goal-directed behavior. ED is a transdiagnostic construct, and it is unclear whether it manifests itself similarly in other conditions, such as major depressive disorder (MDD) or borderline personality disorder (BPD), or has specific features in BD. The present systematic review and meta-analysis explored ED and adopted emotion regulation (ER) strategies in BD compared with other psychiatric conditions. PubMed/MEDLINE, EMBASE, Scopus, and PsycINFO databases were systematically searched from inception to April 28th, 2022. Studies implementing validated instruments assessing ED or ER strategies in BD and other psychiatric disorders were reviewed, and meta-analyses were conducted. Twenty-nine studies yielding multiple comparisons were included. BD was compared to MDD in 20 studies (n = 2451), to BPD in six studies (n = 1001), to attention deficit hyperactivity disorder in three studies (n = 232), to anxiety disorders in two studies (n = 320), to schizophrenia in one study (n = 223), and to post-traumatic stress disorder in one study (n = 31). BD patients did not differ from MDD patients in adopting most adaptive and maladaptive ER strategies. However, small-to-moderate differences in positive rumination and risk-taking behaviors were observed. In contrast, patients with BPD presented an overall higher degree of ED and more maladaptive ER strategies. There were insufficient data for a meta-analytic comparison with other psychiatric disorders. The present report further supports the idea that ED is a transdiagnostic construct spanning a continuum across different psychiatric disorders, outlining specific clinical features that could represent potential therapeutic targets.