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.

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.

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.

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.

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.

The Effects of CYP2C19 Genotype on Proxies of SSRI Antidepressant Response in the UK Biobank.

Selective serotonin reuptake inhibitors (SSRIs) are the most commonly used psychopharmaceutical treatment for major depressive disorder (MDD), but individual responses to SSRIs vary greatly. CYP2C19 is a key enzyme involved in the metabolism of several drugs, including SSRIs. Variations in the CYP2C19 gene are associated with differential metabolic activity, and thus differential SSRI exposure; accordingly, the CYP2C19 genotype may affect the therapeutic response and clinical outcomes, though existing evidence of this link is not entirely consistent. Therefore, we analysed data from the UK Biobank, a large, deeply phenotyped prospective study, to investigate the effects of CYP2C19 metaboliser phenotypes on several clinical outcomes derived from primary care records, including multiple measures of antidepressant switching, discontinuation, duration, and side effects. In this dataset, 24,729 individuals were prescribed citalopram, 3012 individuals were prescribed escitalopram, and 12,544 individuals were prescribed sertraline. Consistent with pharmacological expectations, CYP2C19 poor metabolisers on escitalopram were more likely to switch antidepressants, have side effects following first prescription, and be on escitalopram for a shorter duration compared to normal metabolisers. CYP2C19 poor and intermediate metabolisers on citalopram also exhibited increased odds of discontinuation and shorter durations relative to normal metabolisers. Generally, no associations were found between metabolic phenotypes and proxies of response to sertraline. Sensitivity analyses in a depression subgroup and metabolic activity scores corroborated results from the primary analysis. In summary, our findings suggest that CYP2C19 genotypes, and thus metabolic phenotypes, may have utility in determining clinical responses to SSRIs, particularly escitalopram and citalopram, though further investigation of such a relationship is warranted.

Correlation between emotion dysregulation and mood symptoms of bipolar disorder: A systematic review and meta-analysis.

BACKGROUND: Emotion dysregulation (ED) is a transdiagnostic construct characterized by difficulties regulating intense emotions. People with bipolar disorder (BD) are more likely to show ED and use maladaptive emotion regulation strategies than adaptive ones. However, little is known about whether ED in BD is a trait or it is rather an epiphenomenon of mood symptoms. METHODS: We conducted a systematic review and meta-analysis of the evidence across major literature databases reporting correlations between measures of emotion regulation (overall ED and different emotion regulation strategies) and measures of depressive and (hypo)manic symptoms in BD from inception until April 12th, 2022. RESULTS: Fourteen studies involving 1371 individuals with BD were included in the qualitative synthesis, of which 11 reported quantitative information and were included in the meta-analysis. ED and maladaptive strategies were significantly higher during periods with more severe mood symptoms, especially depressive ones, while adaptive strategies were lower. CONCLUSION: ED significantly correlates with BD symptomatology, and it mainly occurs during mood alterations. ED may be a target for specific psychotherapeutic and pharmacological treatments, according to precision psychiatry. However, further studies are needed, including patients with mood episodes and longitudinal design, to provide more robust evidence and explore the causal direction of the associations.

Meta-analysis of CYP2C19 and CYP2D6 metabolic activity on antidepressant response from 13 clinical studies using genotype imputation.

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. The association of CYP2C19 and CYP2D6 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 and CYP2D6, 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. CYP2D6 structural variants cannot be imputed from genotype data, limiting inference of pharmacogenetic effects. 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.

Obsessive-Compulsive, Psychotic, and Autism Dimensions Overlap in Real World: A Case Report.

BACKGROUND: Obsessions, compulsions, and stereotypes are common psychopathological manifestations of obsessive-compulsive, psychotic, and autism spectrum disorders (ASDs). These nosological entities may be present in comorbidity, with relevant clinical difficulties in the differential diagnosis process. Moreover, ASDs are a complex group of disorders, with a childhood onset, which also persist into adulthood and present heterogeneous symptom patterns that could be confused with psychotic disorders. METHODS AND RESULTS: We report a case of a 21-year-old man characterized by sexual and doubt obsessions; disorganized, bizarre, and stereotyped behaviors and compulsions; and social withdrawal, inadequate social skills, visual dispersions, and hypersensitivity to light stimuli. Obsessive and compulsive features were initially included within the differential diagnosis of psychotic and obsessive-compulsive spectrum disorders. However, aforementioned psychopathological elements did not improve when multiple antipsychotic drugs (olanzapine, haloperidol, and lurasidone) were administered in the hypothesis of schizophrenia and even worsened with clozapine therapy at a dose of 100 mg/d. Obsessions and compulsions progressively reduced during the fluvoxamine 14-week treatment paradigm at a dose of 200 mg/d. Considering the persistent deficits in social communication and interactions as well as the restricted interests pattern, a differential diagnostic hypothesis of ASD was formulated, and it was then confirmed at the final evaluation at a third-level health care center. CONCLUSIONS: We discuss similarities and differences in the psychopathology of obsessions, compulsions, and stereotypes in the previously mentioned disorders, to underline factors that can help in the differential diagnosis of similar cases, and consequently in the appropriateness of treatment choice.

Clinical specificity profile for novel rapid acting antidepressant drugs.

Mood disorders are recurrent/chronic diseases with variable clinical remission rates. Available antidepressants are not effective in all patients and often show a relevant response latency, with a range of adverse events, including weight gain and sexual dysfunction. Novel rapid agents were developed with the aim of overcoming at least in part these issues. Novel drugs target glutamate, gamma-aminobutyric acid, orexin, and other receptors, providing a broader range of pharmacodynamic mechanisms, that is, expected to increase the possibility of personalizing treatments on the individual clinical profile. These new drugs were developed with the aim of combining a rapid action, a tolerable profile, and higher effectiveness on specific symptoms, which were relatively poorly targeted by standard antidepressants, such as anhedonia and response to reward, suicidal ideation/behaviours, insomnia, cognitive deficits, and irritability. This review discusses the clinical specificity profile of new antidepressants, namely 4-chlorokynurenine (AV-101), dextromethorphan-bupropion, pregn-4-en-20-yn-3-one (PH-10), pimavanserin, PRAX-114, psilocybin, esmethadone (REL-1017/dextromethadone), seltorexant (JNJ-42847922/MIN-202), and zuranolone (SAGE-217). The main aim is to provide an overview of the efficacy/tolerability of these compounds in patients with mood disorders having different symptom/comorbidity patterns, to help clinicians in the optimization of the risk/benefit ratio when prescribing these drugs.

Clinical insights into the cross-link between mood disorders and type 2 diabetes: A review of longitudinal studies and Mendelian randomisation analyses.

Mood disorders and type 2 diabetes mellitus (T2DM) are prevalent conditions that often co-occur. We reviewed the available evidence from longitudinal and Mendelian randomisation (MR) studies on the relationship between major depressive disorder (MDD), bipolar disorder and T2DM. The clinical implications of this comorbidity on the course of either condition and the impact of antidepressants, mood stabilisers, and antidiabetic drugs were examined. Consistent evidence indicates a bidirectional association between mood disorders and T2DM. T2DM leads to more severe depression, whereas depression is associated with more complications and higher mortality in T2DM. MR studies demonstrated a causal effect of MDD on T2DM in Europeans, while a suggestive causal association in the opposite direction was found in East Asians. Antidepressants, but not lithium, were associated with a higher T2DM risk in the long-term, but confounders cannot be excluded. Some oral antidiabetics, such as pioglitazone and liraglutide, may be effective on depressive and cognitive symptoms. Studies in multi-ethnic populations, with a more careful assessment of confounders and appropriate power, would be important.

Age as a moderating factor of treatment resistance in depression.

BACKGROUND: Treatment-resistant depression (TRD) is an important clinical challenge and may present differently between age groups. METHODS: A total of 893 depressed patients recruited within the framework of the European research consortium "Group for the Studies of Resistant Depression" were assessed by generalized linear models regarding age effects (both as numerical and factorial predictors) on treatment outcome, number of lifetime depressive episodes, hospitalization time, and duration of the current episode. Effects of age as numerical predictor on the severity of common depressive symptoms, measured with Montgomery-Åsberg Depression Rating Scale (MADRS) for two-time points, were assessed by linear mixed models, respectively, for patients showing TRD and treatment response. A corrected p threshold of 0.001 was applied. RESULTS: Overall symptom load reflected by MADRS (p < 0.0001) and lifetime hospitalization time (p < 0.0001) increased with age in TRD patients but not treatment responders. In TRD, higher age was predicting symptom severity of inner tension, reduced appetite, concentrations difficulties, and lassitude (all p ≤ 0.001). Regarding clinical significance, older TRD patients were more likely to report severe symptoms (item score > 4) for these items both before and after treatment (all p ≤ 0.001). CONCLUSIONS: In this naturalistic sample of severely ill depressed patients, antidepressant treatment protocols were equally effective in addressing TRD in old age. However, specific symptoms such as sadness, appetite, and concentration showed an age-dependent presentation, impacting residual symptoms in severely affected TRD patients and calling for a precision approach by a better integration of age profiles in treatment recommendations.

Real-world characteristics of European patients receiving SNRIs as first-line treatment for major depressive disorder.

BACKGROUND: Serotonin-norepinephrine reuptake inhibitors (SNRIs) are among the most frequently prescribed antidepressants (ADs) for major depressive disorder (MDD), with an increasing trend in the last decade. Given the relative dearth of information regarding rationales for their preferred use as first-line ADs in the broad clinical routine, the present study systematically investigated real-world characteristics of MDD patients prescribed either SNRIs or other AD substances across different countries and treatment settings. METHODS: In the present secondary analyses based on a large European, multi-site, naturalistic and cross-sectional investigation with a retrospective assessment of treatment outcome, we firstly defined the proportion of MDD patients receiving SNRIs as first-line AD psychopharmacotherapy and secondly compared their sociodemographic and clinical characteristics to those patients prescribed alternative first-line ADs during their current major depressive episode (MDE). RESULTS: Within the total sample of 1410 MDD patients, 336 (23.8 %) received first-line SNRIs. Compared to other ADs, SNRIs were significantly associated with inpatient care, suicidality and treatment resistance during the current MDE, and a longer lifetime duration of psychiatric hospitalizations. Moreover, greater severity of depressive symptoms at study entry, higher daily doses of the administered ADs, as well as more frequent prescriptions of psychopharmacotherapeutic add-on strategies in general and antipsychotic augmentation in particular, were significantly related to first-line SNRIs. CONCLUSIONS: Considering the limitations of a cross-sectional and retrospective study design, our data point towards a preferred use of first-line SNRIs in a generally more severely ill MDD patients, although they did not lead to superior treatment outcomes compared to alternative ADs.

Hyperthyroidism and depression: a clinical case of atypical thyrotoxicosis manifestation.

The relationship between psychiatric symptoms and thyroid function has been well known and studied since antiquity. The common view is that clinical hypothyroidism is associated with depressive symptoms, whereas the psychiatric manifestations of hyperthyroidism are agitation, emotional lability, hyperexcitability, occasionally accompanied by angry outbursts, and euphoria. The case here reported overturns this conventional medical knowledge. A 73-year-old Italian woman experienced a severe major depressive episode with psychotic and melancholic features during laboratory thyrotoxicosis. No classical clinical signs and symptoms of thyrotoxicosis were present. Psychiatric symptoms improved together with the resolution of the hyperthyroid state. Historically, different cases of so-called 'apathetic hyperthyroidism' have been described. Recent neuroimaging and animal studies provided possible neurobiological explanations, showing how the excess thyroid hormones could affect brain structures involved in the regulation of mood, leading to depression. A direct link between hyperthyroidism and depression seems to be likely. This insight may be relevant in facilitating early diagnosis of thyroid disease and the planning of therapeutic strategies.

Multi-omics data integration methods and their applications in psychiatric disorders.

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.

Genetics of nonpharmacological treatments of depression.

Nonpharmacological antidepressant treatments are effective and well tolerated in selected patients. However, response is heterogeneous and validated biomarkers would be precious to aid treatment choice. We searched Pubmed, Scopus, and Google Scholar until May 2022 for original articles evaluating the association of genetic variables with the efficacy of nonpharmacological treatments for major depressive episodes. Most studies analyzed small sample sizes using the candidate gene approach, leading to poorly replicated findings that need to be interpreted cautiously. The few available methylome-wide and genome-wide association studies (GWASs) considered only electroconvulsive therapy (ECT) and cognitive-behavioral therapy in small samples, providing interesting findings by using polygenic risk scores. A deeper knowledge of the genetic factors implicated in treatment response may lead to a better understanding of the neurobiological mechanisms of nonpharmacological therapies for depression, and depression itself. Future GWAS are going to expand their sample size, thanks to consortia such as the gen-ECT-ic consortium.

Efficacy of the additional use of subgingival air-polishing with erythritol powder in the treatment of periodontitis patients: a randomized controlled clinical trial. Part II: effect on sub-gingival microbiome.

OBJECTIVES: To date, scarce evidence exists around the application of subgingival air-polishing during treatment of severe periodontitis. The aim of this study was to evaluate the effect on the health-related and periodontitis-related subgingival microbiome of air-polishing during non-surgical treatment of deep bleeding pockets in stage III-IV periodontitis patients. MATERIALS AND METHODS: Forty patients with stage III-IV periodontitis were selected, and pockets with probing depth (PD) 5-9 mm and bleeding on probing were selected as experimental sites. All patients underwent a full-mouth session of erythritol powder supragingival air-polishing and ultrasonic instrumentation. Test group received additional subgingival air-polishing at experimental sites. Subgingival microbial samples were taken from the maxillary experimental site showing the deepest PD at baseline. Primary outcome of the first part of the present study was the 3-month change in the number of experimental sites. Additional analysis of periodontal pathogens and other sub-gingival plaque bacteria sampled at one experimental site at baseline and 3 months following treatment was performed through a real-time quantitative PCR microarray. RESULTS: In the test group, a statistical increase of some health-related species was observed (Abiotropha defectiva, Capnocytophaga sputigena, and Lautropia mirabilis), together with the decrease of pathogens such as of Actinomyces israelii, Catonella morbi, Filifactor alocis, Porphyromonas endodontalis, Sele-nomonas sputigena, Tannerella forsythia, Treponema denticola, and Treponema socranskii. In the control group, statistical significance was found only in the decrease of Filifactor alocis, Tannerella forsythia, and Treponema socranskii. CONCLUSIONS: The addition of erythritol-chlorhexidine powder seems to cause a shift of the periodontal micro-biome toward a more eubiotic condition compared to a conventional treatment. The study was registered on Clinical Trials.gov (NCT04264624). CLINICAL RELEVANCE: Subgingival air-polishing could help re-establishing a eubiotic microbioma in deep bleeding periodontal pockets after initial non-surgical treatment.