Major depressive disorder (MDD) is among the most prevalent mental disorders worldwide. Factors causing the pathogenesis of MDD include gut microbiota (GM), which interacts with the host through the gut–brain axis. In previous studies of GM in MDD patients, 16S rRNA sequencing was used, which provided information about composition but not about function. In our study, we analyzed whole metagenome sequencing data to assess changes in both the composition and functional profile of GM. We looked at the GM of 36 MDD patients, compared with that of 38 healthy volunteers. Comparative taxonomic analysis showed decreased abundances of Faecalibacterium prausnitzii, Roseburia hominis, and Roseburia intestinalis, and elevated abundances of Escherichia coli and Ruthenibacterium lactatiformans in the GM of MDD patients. We observed decreased levels of bacterial genes encoding key enzymes involved in the production of arginine, asparagine, glutamate, glutamine, melatonin, acetic, butyric and conjugated linoleic acids, and spermidine in MDD patients. These genes produced signature pairs with Faecalibacterium prausntizii and correlated with decreased levels of this species in the GM of MDD patients. These results show the potential impact of the identified biomarker bacteria and their metabolites on the pathogenesis of MDD, and should be confirmed in future metabolomic studies.

Recently published large-scale randomised controlled trials (RCTs) have questioned the efficacy of preventive interventions in individuals at clinical high risk for psychosis (CHR-P). We conducted a systematic review and meta-analysis to include this new evidence and provide future directions for the field. We followed the PRISMA guidelines and a pre-registered protocol, with a literature search conducted from inception to November 2023. We included RCTs that collected data on psychosis transition (the primary outcome) in CHR-P. Secondary outcomes were symptoms severity and functioning. Investigated time points were 6,12,24,36, and +36 months. We used odd ratios (ORs) and standardised mean differences (SMD) as summary outcomes. Heterogeneity was estimated with the Higgins I². Twenty-four RCTs, involving 3236 CHR-P individuals, were included. Active interventions were Cognitive Behavioural Therapy (CBT), family-focused therapy, Integrated Psychological Therapy, antipsychotics, omega-3 fatty acids, CBT plus risperidone, minocycline, and other non-pharmacological approaches (cognitive remediation, sleep-targeted therapy, brain stimulation). Results showed no evidence that any of the investigated active interventions had a sustained and robust effect on any of the investigated outcomes in CHR-P, when compared to control interventions, including CBT on transition to psychosis at 12 months (9 RCTs; OR: 0.64; 95% CI: 0.39–1.06; I²: 21%; P = 0.08). These results highlight the need for novel treatment approaches in CHR-P. Future studies should consider the heterogeneity of this clinical population and prioritise stratification strategies and bespoke treatments.

Background. In 2020, the COVID-19 pandemic evoked a variety of research into the virus and its effects on mentalhealth. A variety of mental health and psychological problems have been reported: stress, anxiety, depressivesymptoms, insomnia, denial, stigma, anger and fear. Objectives. To assess the level of anxiety, depression and distress in the general population during the lockdownin Russia and to reveal factors associated with distress. Methods. An online survey was carried out from 22–27 April 2020 (the fourth week of lockdown) among the generalpopulation (mostly Moscow residents). The survey questions covered general information about people’s social anddemographic characteristics, experience of COVID-19, health condition (physical and mental), attitudes and views onthe pandemic, and the need for psychological support. The survey included the Hospital Anxiety and Depression Scale(HADS) and evaluation of the preceding week’s subjective distress level using a visual numeric scale (from 0 to 10). Wealso asked respondents to specify the causes of distress, adopted from the WHO information sheet relating to themajor psychological challenges of the COVID-19 pandemic. Results. In total, 352 responses were collected (men = 74, women = 278; age (M ± SD) = 36.81 ± 11.36 y.o.).Most respondents (n = 225, 63.92%) did not have any personal experience of the coronavirus infection. Normallevels of anxiety and depression scores were prevalent in the sample. Higher than normal levels of HADS anxiety/depression ( 7 scores) were observed in 105 (29.83%) and 59 (16.76%) respondents, respectively; mean (95% CI)scores for HADS anxiety/depression were 6.23 [5.77, 6.68] /4.65 [4.22, 5.08] (women) and 4.20 [3.32, 5.09] /3.46[2.63, 4.29] (men), respectively.The leading causes of distress were: 1) the risk of financial problems in the future (n = 267, 76.3%); 2) violationof plans and the disruption to normal life (n = 235, 67.1%; and n = 240, 68.6%, respectively); 3) the health of elderlyor chronically diseased relatives (n = 205, 58.6%) and 4) being in self-isolation (n = 186, 53.1%). Conclusion. The level of anxiety and depression during the COVID-19 pandemic in the study sample did not exceed thenorm for the population in non-pandemic conditions. Our assessment of distress levels captured existing emotionalproblems, and distress levels were found to be connected with the reported need for psychological support.

We investigated the associations of rs4680 COMT, rs6280 DRD3, and rs7322347 5HT2A with youth-onset schizophrenia in the Russian population in a case–control study, and the role of the genotype in the severity of clinical features. The association between rs7322347 and schizophrenia (p = 0.0001) is described for the first time. Furthermore, we found a link with rs6280 and rs4680 in females (p = 0.001 and p = 0.02 respectively) and with rs7322347 in males (p = 0.002). Clinical symptoms were assessed on three scales: the Clinician-Rated Dimensions of Psychosis Symptom Severity scale, Positive and Negative Syndrome Scale, and Frontal Assessment Battery. Gender differences in clinical features are of particular interest. In our study we found gender differences in the severity of clinical features—higher scores for delusions (Positive and Negative Syndrome Scale and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition) in males and higher scores for depression, delusions, somatic concern, motor retardation, poor attention were found in females.

The detection of specific markers of dementia and mild cognitive decline (MCI) could be the key to disease prevention and forehanded treatment. Female gender is one of the major risk factor for dementia. The aim of our study was to compare serum concentration of some factors related to lipid metabolism and the immune system in patients with MCI and dementia. The study was performed on women >65 years old: controls (n = 75), diagnosed with dementia (n = 73) and MCI (n = 142). Patients were evaluated using Mini-Mental State Examination, Clock Drawing Test and Montreal Cognitive Assessment scales in the period 2020–2021. The level of Apo A1 and HDL was significantly decreased in patients with dementia; the level of Apo A1 was also decreased in MCI. EGF, eotaxin-1, GRO-α, and IP-10 were elevated in patients with dementia compared to the controls. IL-8, MIP-1β, sCD40L, and TNF-α levels were decreased in MCI patients and increased in patients with dementia compared to the control. Serum VEGF levels were decreased in MCI and dementia patients in comparison with the control. We hypothesize that no single marker can indicate a neurodegenerative process. Future research should focus on identifying markers to determine possible diagnostic combinations that can reliably predict neurodegeneration.