Psychological impact of neovagina creation and uterus transplantation in the patients affected from Mayer-Rokitanski-Kuster-Hauser syndrome: A narrative review.

Mayer-Rokitanski-Kuster-Hauser (MRKH) syndrome consists of a congenital aplasia of the uterus and the upper part of the vagina. It is the most frequent congenital cause of absolute uterine factor infertility, determining psychological disorders due to infertility and reduced quality of sexual activity. Being the necessity of baseline and prolonged assessments, clinicians need evaluation parameters for the monitoring of patients to plan a suitable management strategy and for efficient support before and after interventions, such as neovagina and uterus transplantation. Research of the literature was performed in PubMed and SCOPUS by searching for the terms "Mayer-Rokitanski-Kuster-Hauser" AND "psychological disorders"; from the 60 articles obtained, only 35 articles regarding neovagina creation and uterus transplantation were considered for the present manuscript. Based on the literature, management of MRKH syndrome by neovagina creation, either surgically or not, can restore a satisfactory sexual life and to reduce stress, signs of mental disorder and depression and improve sexual activity and quality of life. A psychological assessment of candidates to UT and of their partners is necessary. Recipients had low levels of anxiety compared to the normal population at baseline but a transiently lowered physical quality of life 1 year after surgery; elevated anxiety scores are associated with childlessness in the long-term evaluation. Further research is necessary to develop suitable evaluation protocols and adequate supportive services, to improve the outcomes of patients who undergo neovagina creation and uterus transplantation.

Mirtazapine blood levels and antidepressant response.

OBJECTIVE: Therapeutic drug monitoring (TDM) is an important tool for treatment optimisation. Its usefulness has recently been demonstrated for some first-line antidepressants; however, few studies have been reported on the relationship between blood levels of mirtazapine and its antidepressant effects. The aim of this study was to investigate the association between blood concentration of mirtazapine and antidepressant response. METHODS: 59 outpatients treated with mirtazapine for depression were recruited and followed up for three months in a naturalistic setting. Hamilton Depression Rating Scale-21 (HAMD-21) was administered at baseline, month 1, and month 3 to assess antidepressant response. Mirtazapine serum concentration was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between serum concentration of mirtazapine and antidepressant response. RESULTS: Our results showed no overall association between serum concentration of mirtazapine and symptom improvement at month 1 and month 3. A marginally significantly higher serum concentration of mirtazapine was found in responders vs non-responders at month 3. CONCLUSIONS: The study suggests that serum concentration of mirtazapine is not strongly associated with the antidepressant efficacy of mirtazapine. This is probably attributed to its pharmacodynamic profile, even though higher blood levels seem to be marginally more effective.

Mirtazapine plasma levels association with response is mild and do not follow the same curve of other antidepressantsMirtazapine higher plasma levels may show some benefit in a subgroup of patientsTherapeutic drug monitoring may help during antidepressant treatment.

Exploring the use of immunomethylomics in the characterization of depressed patients: A proof-of-concept study.

Alterations in DNA methylation and inflammation could represent valid biomarkers for the stratification of patients with major depressive disorder (MDD). This study explored the use of DNA-methylation based immunological cell-type profiles in the context of MDD and symptom severity over time. In 119 individuals with MDD, DNA-methylation was assessed on whole blood using the Illumina Infinium MethylationEPIC 850 k BeadChip. Quality control and data processing, as well as cell type estimation was conducted using the RnBeads package. The cell type composition was estimated using epigenome-wide DNA methylation signatures, applying the Houseman method, considering six cell types (neutrophils, natural killer cells (NK), B cells, CD4+ T cells, CD8+ T cells and monocytes). Two cytokines (IL-6 and IL-1ß) and hsCRP were quantified in serum. We performed a hierarchical cluster analysis on the six estimated cell-types and tested the differences between these clusters in relation to the two cytokines and hsCRP, depression severity at baseline, and after 6 weeks of treatment (celecoxib/placebo + vortioxetine). We performed a second cluster analysis with cell-types and cytokines combined. ANCOVA was used to test for differences across clusters. We applied the Bonferroni correction. After quality control, we included 113 participants. Two clusters were identified, cluster 1 was high in CD4+ cells and NK, cluster 2 was high in CD8+ T-cells and B-cells, with similar fractions of neutrophils and monocytes. The clusters were not associated with either of the two cytokines and hsCRP, or depression severity at baseline, but cluster 1 showed higher depression severity after 6 weeks, corrected for baseline (p = 0.0060). The second cluster analysis found similar results: cluster 1 was low in CD8+ T-cells, B-cells, and IL-1ß. Cluster 2 was low in CD4+ cells and natural killer cells. Neutrophils, monocytes, IL-6 and hsCRP were not different between the clusters. Participants in cluster 1 showed higher depression severity at baseline than cluster 2 (p = 0.034), but no difference in depression severity after 6 weeks. DNA-methylation based cell-type profiles may be valuable in the immunological characterization and stratification of patients with MDD. Future models should consider the inclusion of more cell-types and cytokines for better a prediction of treatment outcomes.

The P300 component of the auditory event-related potential in adult psychiatric and neurologic disorders: a narrative review of clinical and experimental evidence.

The auditory P300 wave, also known as P3b, is an event-related potential component thought to reflect central information processes involved in stimulus evaluation or categorization. It is typically elicited using the oddball paradigm, which involves mixing low-probability target items with high-probability standard stimuli. Its latency is associated with the timing of cognitive processes such as stimulus evaluation and response preparation, while its amplitude is related to the amount of attentional resources engaged during the task. Despite decades of use in research settings, its application in clinical practice has been limited. Prolongation of latencies and reduction of amplitudes in the auditory P3b have been observed in both psychiatric and neurological conditions. This includes cases where traditional neuropsychological tests are challenging due to severe motor or speech dysfunctions, or in conditions characterized by subtle cognitive deficits. Additionally, specific laterality patterns in psychoses and a loss of P300 habituation in migraines have been described. The wealth of experimental evidence supports the use of this evoked potential, which can be elicited through a relatively simple paradigm, for objectively evaluating cognition in psychiatric and neurological patients, particularly in follow-up assessments. Therefore, the auditory P300 appears to be a valuable tool for monitoring the clinical course of patients with mental and neurological disorders in certain circumstances.

Genetic factors and symptom dimensions associated with antidepressant treatment outcomes: clues for new potential therapeutic targets?

Treatment response and resistance in major depressive disorder (MDD) show a significant genetic component, but previous studies had limited power also due to MDD heterogeneity. This literature review focuses on the genetic factors associated with treatment outcomes in MDD, exploring their overlap with those associated with clinically relevant symptom dimensions. We searched PubMed for: (1) genome-wide association studies (GWASs) or whole exome sequencing studies (WESs) that investigated efficacy outcomes in MDD; (2) studies examining the association between MDD treatment outcomes and specific depressive symptom dimensions; and (3) GWASs of the identified symptom dimensions. We identified 13 GWASs and one WES of treatment outcomes in MDD, reporting several significant loci, genes, and gene sets involved in gene expression, immune system regulation, synaptic transmission and plasticity, neurogenesis and differentiation. Nine symptom dimensions were associated with poor treatment outcomes and studied by previous GWASs (anxiety, neuroticism, anhedonia, cognitive functioning, melancholia, suicide attempt, psychosis, sleep, sociability). Four genes were associated with both treatment outcomes and these symptom dimensions: CGREF1 (anxiety); MCHR1 (neuroticism); FTO and NRXN3 (sleep). Other overlapping signals were found when considering genes suggestively associated with treatment outcomes. Genetic studies of treatment outcomes showed convergence at the level of biological processes, despite no replication at gene or variant level. The genetic signals overlapping with symptom dimensions of interest may point to shared biological mechanisms and potential targets for new treatments tailored to the individual patient's clinical profile.

Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies.

Background: Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation. Methods: A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394). Results: Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported. Conclusions: Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.

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.

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.

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.

Optimisation of pharmacotherapy in psychiatry through therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests: Focus on antipsychotics.

BACKGROUND: For psychotic disorders (i.e. schizophrenia), pharmacotherapy plays a key role in controlling acute and long-term symptoms. To find the optimal individual dose and dosage strategy, specialised tools are used. Three tools have been proven useful to personalise drug treatments: therapeutic drug monitoring (TDM) of drug levels, pharmacogenetic testing (PG), and molecular neuroimaging. METHODS: In these Guidelines, we provide an in-depth review of pharmacokinetics, pharmacodynamics, and pharmacogenetics for 45 antipsychotics. Over 30 international experts in psychiatry selected studies that have measured drug concentrations in the blood (TDM), gene polymorphisms of enzymes involved in drug metabolism, or receptor/transporter occupancies in the brain (positron emission tomography (PET)). RESULTS: Study results strongly support the use of TDM and the cytochrome P450 (CYP) genotyping and/or phenotyping to guide drug therapies. Evidence-based target ranges are available for titrating drug doses that are often supported by PET findings. CONCLUSION: All three tools discussed in these Guidelines are essential for drug treatment. TDM goes well beyond typical indications such as unclear compliance and polypharmacy. Despite its enormous potential to optimise treatment effects, minimise side effects and ultimately reduce the global burden of diseases, personalised drug treatment has not yet become the standard of care in psychiatry.

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.

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.

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.