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.

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.

Aims: We aimed to identify the prevalence of anxiety, depression, and suicidality and identify relevant risk and protecting factors among university students during the COVID-19 pandemic in Georgia. Materials and methods: We conducted an anonymous online survey ( n = 984, convenience sample by approaching all universities in Georgia and some student organizations) using valid instruments (e.g., STAI to assess anxiety, CES-D for depression, and RASS to assess suicidality). We calculated frequencies and prevalence and applied regression analysis and Chi-square tests to identify risk and protecting factors. Findings: Respondents’ mental health had been significantly affected (with a high prevalence of depression (46.7%) and anxiety (79%)) during the pandemic (which coincided with political turmoil and caused an economic crisis) in Georgia. Some of the critical factors affecting mental health were: female sex ( p = .000), bad general health condition (anxiety p = .001, depression p = .004), finances (anxiety and depression p < .001), reduced physical activity (anxiety p < .001, depression p = .014), and a history of self-harming (suicidality p < .001). Less family conflicts (anxiety and depression p < .05), absence of nightmares (anxiety and depression p < .001), moderate or low fears of COVID-19 (anxiety p < .001), and lower substance use (anxiety p = .023) were among the potentially protective factors. International students coped better, despite vulnerability. Medical students had a lower risk of depression. Conclusions: In the complex socioeconomic context, mental health of students in Georgia suffered a lot during the COVID-19 pandemic, requiring thorough planning and delivery of student support services in higher educational institutions during and after the pandemic.

Background: Molecular mechanisms of depression remain unclear. The brain metabolome after antidepressant therapy is poorly understood and had not been performed for different routes of drug administration before the present study. Rats were exposed to chronic ultrasound stress and treated with intranasal and intraperitoneal clomipramine. We then analyzed 28 metabolites in the frontal cortex and hippocampus. Methods: Rats’ behavior was identified in such tests: social interaction, sucrose preference, forced swim, and Morris water maze. Metabolic analysis was performed with liquid chromatography. Results: After ultrasound stress pronounced depressive-like behavior, clomipramine had an equally antidepressant effect after intranasal and intraperitoneal administration on behavior. Ultrasound stress contributed to changes of the metabolomic pathways associated with pathophysiology of depression. Clomipramine affected global metabolome in frontal cortex and hippocampus in a different way that depended on the route of administration. Intranasal route was associated with more significant changes of metabolites composition in the frontal cortex compared to the control and ultrasound groups while the intraperitoneal route corresponded with more profound changes in hippocampal metabolome compared to other groups. Since far metabolic processes in the brain can change in many ways depending on different routes of administration, the antidepressant therapy should also be evaluated from this point of view.