Neuronetwork Approach in the Early Diagnosis of Depression.

BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the part of both patient and clinician. In the last few years, deep (machine) learning is emerging as a more objective approach for measuring depression severity. We now investigate how neural networks might serve for the early diagnosis of depression. SUBJECTS AND METHODS: We searched Medline (Pubmed) for articles published up to June 1, 2023. The search term included Depression AND Diagnostics AND Artificial Intelligence. We did not search for depression studies of machine learning other than neural networks, and selected only those papers attesting to diagnosis or screening for depression. RESULTS: Fifty-four papers met our criteria, among which 14 using facial expression recordings, 14 using EEG, 5 using fMRI, and 5 using audio speech recording analysis, whereas 6 used multimodality approach, two were the text analysis studies, and 8 used other methods. CONCLUSIONS: Research methodologies include both audio and video recordings of clinical interviews, task performance, including their subsequent conversion into text, and resting state studies (EEG, MRI, fMRI). Convolutional neural networks (CNN), including 3D-CNN and 2D-CNN, can obtain diagnostic data from the videos of the facial area. Deep learning in relation to EEG signals is the most commonly used CNN. fMRI approaches use graph convolutional networks and 3D-CNN with voxel connectivity, whereas the text analyses use CNNs, including LSTM (long/short-term memory). Audio recordings are analyzed by a hybrid CNN and support vector machine model. Neural networks are used to analyze biomaterials, gait, polysomnography, ECG, data from wrist wearable devices, and present illness history records. Multimodality studies analyze the fusion of audio features with visual and textual features using LSTM and CNN architectures, a temporal convolutional network, or a recurrent neural network. The accuracy of different hybrid and multimodality models is 78-99%, relative to the standard clinical diagnoses.

G.T. MSRS On-Line Calculator Targeting the Early Diagnosis of Mixed Affective States: the Multicenter Study Project Design on the Approbation and Validity of the Three Language Versions of the Rating Scale.

BACKGROUND: Mixed affective states (MS) are often misdiagnosed by the clinicians and lead to the inappropriate treatment strategies contributing to the severe forms, poor outcome with higher rates of comorbid conditions and worse remission quality in affective and bipolar disorders, as well as to a decreased psychosocial functioning of these patients. The development of reliable tools for the MS assessments or so called the phenomenon of mixity in affective disorders, is still an unmet need of psychiatric research and clinical practice. In this paper, we present PC program "Multilingual IBM-PC on-line calculator for early diagnosis of the mixed affective states" based on the Giuseppe Tavormina Mixed States Rating Scale (G.T. MSRS) (Russian, English, Italian language versions) created by the ICERN group using programming language JavaScript, working for such operation systems (OS) as Windows, Linux, MacOs, Android, iOS, and aims to contribute to the accurate assessment of the presence and severity of the mixed states among affective disorders. SUBJECTS AND METHODS: The G.T. Mixed States Rating Scale on-line calculator consists of 11 items which evaluate various aspects of MS in patients with major depression, bipolar or recurrent depressive disorder. A total score is automatically calculated, considering the type of affective temperament according to the Akiskal's and Tavormina's schemas, thus, the specific sub-groups of MS are differentiated based on the ranges: Medium-light (2-6), Medium (7-12), and High (13-19) Mixity level. The study will enroll 330 participants during two (three months follow-up) visits (110 native speakers in each of the three languages) of both genders aged from 18 till 55 y.o. with the diagnoses of depressive episodes, major depression, bipolar or recurrent depressive disorder according to the DSM-5 criteria. Assessments will be provided by the two investigators (second one will be blinded to the G.T. MSRS results obtained by the first researcher), based on the use of DSM-5 clinical interview, Young Mania Rating Scale, Montgomery-Åsberg Depression Rating Scale, Clinical Global Impression - Severity scale (CGI-S), Clinical Global Impression - Improvement scale (CGI-I), Patient Global Impression of Change (PGIC). RESULTS: The study will assess the agreement between the diagnostic category/clinical impression and the on-line G.T. MSRS calculator use results, its test-retest reliability, and diagnosis stability for further assessment of the on-line G.T. MSRS calculator validity and clinical utility. Secondary variables will evaluate internal reliability and such statistical analyses as Cronbach's alpha, Cohen's Kappa, biserial correction, and agreement between initial and follow-up diagnoses. CONCLUSIONS: Current multicenter validation study of the on-line G.T. MSRS calculator will enhance the understanding of the mixity phenomenon and its clinical implication, aiming to improve the treatment strategies to manage the course of mental disorder, quality of life and psychosocial functioning in patients with affective (bipolar) disorders, accompanied by MS, and a clinical recommendation for the routine administration of the user-friendly on-line G.T. MSRS version in clinical practice.

Peripheral Blood Mononuclear Cell-Related Biomarkers in Schizophrenia.

INTRODUCTION: Schizophrenia is a severe mental illness causing significant impairment in personal, family, social, educational, occupational, and other important areas of life. While there is no widely accepted endophenotype, peripheral blood cells may serve as an accessible model of intracellular changes in schizophrenia. METHODS: We reviewed the literature on the query "peripheral blood mononuclear cells AND schizophrenia" in Medline (Pubmed), selecting studies that searched for specific biomarkers of schizophrenia. We considered both diagnostic biomarkers and biomarkers of therapeutic response, specific schizophrenia disorders or differential diagnostic biomarkers. RESULTS: We retrieved 41 articles matching the search criteria, among which were studies that considered changes in the production of pro-inflammatory and anti-inflammatory markers, proteins, receptors, enzyme activity, and gene expression as potential biomarkers. CONCLUSION: Approaches analysing a biological axis or a group of related biomarkers may hold the greatest promise for identifying schizophrenia. In addition, pharmacological status, smoking status, inflammatory markers and glucose metabolites, the presence of comorbidities should be considered. Certain biomarkers, while not specific for the diagnosis of schizophrenia, may indicate the prognosis and effectiveness of treatment in the established diagnosis.

Post-COVID Neuropsychiatric Complications in Children and Adolescents: a Study Design for Early Diagnosis and Treatment Using Innovative Technologies.

BACKGROUND: The COVID-19 pandemic has had significant impacts on the child and adolescent population, with long-term consequences for physical health, socio-psychological well-being, and cognitive development, which require further investigation. We herein describe a study design protocol for recognizing neuropsychiatric complications associated with pediatric COVID-19, and for developing effective prevention and treatment strategies grounded on the evidence-based findings. METHODS: The study includes two cohorts, each with 163 participants, aged from 7 to 18 years old, and matched by gender. One cohort consisted of individuals with a history of COVID-19, while the other group presents those without such a history. We undertake comprehensive assessments, including neuropsychiatric evaluations, blood tests, and validated questionnaires completed by parents/guardians and by the children themselves. The data analysis is based on machine learning techniques to develop predictive models for COVID-19-associated neuropsychiatric complications in children and adolescents. RESULTS: The first model is focused on a binary classification to distinguish participants with and without a history of COVID-19. The second model clusters significant indicators of clinical dynamics during the follow-up observation period, including the persistence of COVID-19 related somatic and neuropsychiatric symptoms over time. The third model manages the predictors of discrete trajectories in the dynamics of post-COVID-19 states, tailored for personalized prediction modeling of affective, behavioral, cognitive, disturbances (academic/school performance), and somatic symptoms of the long COVID. CONCLUSIONS: The current protocol outlines a comprehensive study design aiming to bring a better understanding of COVID-19-associated neuropsychiatric complications in a population of children and adolescents, and to create a mobile phone-based applications for the diagnosis and treatment of affective, cognitive, and behavioral conditions. The study will inform about the improved management of preventive and personalized care strategies for pediatric COVID-19 patients. Study results support the development of engaging and age-appropriate mobile technologies addressing the needs of this vulnerable population group.

Comparison of Anxiety and Depression Rates in Russian Health Care Professionals in 2020 and 2023.

BACKGROUND: The COVID-19 pandemic had a significant impact on the mental health of medical personnel worldwide, leading to increased levels of anxiety and depression. This study aimed to compare anxiety and depression levels among healthcare workers during the initial wave of the pandemic in April-May 2020 and the post-pandemic period in January-May 2023 in Russia. METHODS: Data from two similar surveys conducted during the respective periods were combined, and a case-control matching approach was used to ensure compatibility between the two samples. The Hospital Anxiety and Depression Scale (HADS) was used to assess anxiety and depression levels. RESULTS: The mean total score for Anxiety subscale in 2020 was 4.126 (SD = 3.042), and in 2023 it increased to 6.632 (SD = 4.132) (F=20.751, df (1, 172), p<0.001, η2p=0.108). Similarly, the mean total score for Depression subscale increased from 3.253 (SD = 2.616) in 2020 to 4.115 (SD = 2.939) in 2023 (F=4.177, df (1, 172), p=0.043, η2p=0.024). The proportion of healthcare workers with higher-than-normal levels of anxiety increased from 16.09% in 2020 to 39.08% in 2023, whereas the effect size for depression remained negligible. The increase in anxiety severity was contrary to previous longitudinal studies showing a decrease in anxiety and depression levels after an initial increase during the pandemic. CONCLUSION: The increase in anxiety and depression levels in healthcare workers in 2023 may be attributed to other factors like "special military operation" in Ukraine, sanctions, and announcement of partial mobilization in September 2022. These factors could be perceived as more serious adverse factors, leading to increased anxiety levels.

Neurological and Psychiatric Aspects of Biological Markers for the Provision of Medical Care to Patients with Spinal Muscular Atrophy 5q.

BACKGROUND: Spinal muscular atrophy (SMA) is a rare genetic disorder, in which, for the common childhood onset forms, loss of function of the SMA 5q gene leads to disability and death before adulthood. Symptomatic treatment focusses on respiratory and nutritional support, and physical therapy, but there is little consideration of psychiatric manifestations of SMA. The aim of this study was to explore blood biomarker levels, electromyography (EMG) data, and clinical manifestations, including psychiatric impairments, in patients with SMA 5q. Our objectives were twofold: First, to assess the clinical relevance of standard biomarkers, i.e., creatinine, creatine kinase (CK), and lactate dehydrogenase (LDH) levels, and second, to obtain data supporting the development of an effective prognostic algorithm for the course of this disease. RESULTS: We analyzed retrospective data from 112 medical records of 58 registered patients (2008-2022) with SMA. At the time of last registration, the 58 patients had a mean age 38.4 years [13.68; 55.0], of whom 32 (52%) were female. The subgroup of 21 pediatric patients had a mean age 12.32 years [6.57; 13.93], of whom 14 (24%) were girls. The ICD-10 diagnoses were as follows: G12.0 (n=7, 12%, children), G12.1 (n=14, 24% children; n=29, 50% adults), G12.8 (n=6, 10% adults), G12.9 (n=2, 1% adults). The archival data on psychiatric status indicated emotional lability (n=6, 10.3%), fatigue (n=10, 17.2%), and tearfulness (n=3, 5.2%) in some patients. There were no significant subgroup differences in serum creatinine and CK levels, but there were significant differences in LDH levels between the G12.0, G12.1, G12.8, and G12.9 subgroups. Among the serum biomarkers, only LDH levels showed significant differences among the subgroups of SMA 5q patients; higher levels in the G12.1, G12.8, and G12.9 groups compared to the G12.0 (infantile) group related to age, weight, gender, and level of physical activity. Data on psychiatric status were insufficient to identify group differences and associations with biomarker levels. Likewise, longitudinal data on repeat hospitalizations did not indicate associations with biomarker levels. CONCLUSIONS: Creatinine, CK, and LDH levels were insufficient for monitoring and predicting the course of SMA. Further prospective research is needed to elaborate the weak relationships between CK levels, the dynamics of the clinical presentation, and therapeutic interventions, and to investigate psychiatric co-morbidities in SMA 5q patients.

Dietary Patterns as Modifiable Risk Factors for Depression: a Narrative Review.

BACKGROUND: The role of nutrition in treating clinical depression has been widely discussed. Unhealthy lifestyle patterns, like lack of physical activity, junk food consumption, and irregular sleep patterns are common in depressed patients. Considering the mental and physical side-effects, the daily nutrition of these patients seems to be a plausible option for reducing depressive symptoms and enhancing treatment results. METHODS: A PubMed search was done for meta-analyses published from January 2018 to June 2023 with the query: (diet) AND (psychiatric disorder) AND (depression). We selected meta-analyses that met specific criteria like including the entire diet or specific diet patterns and having depression or depressive symptoms as a primary or secondary outcome. RESULTS: Out of 28 papers found, the 9 meta-analyses, selected for review, revealed different types of correlation between dietary patterns and the symptoms of depression and anxiety. Healthy diets were associated with higher intake of fruits, vegetables, nuts, and lower intake of pro-inflammatory food items like processed meats and trans fats. Adherence to such diets showed a negative association with incident depression in cross-sectional and longitudinal studies. A diet mostly including ultra-processed foods was associated with higher odds of depressive and anxiety symptoms. Women were found to be more susceptible than men both in developing the depressive symptoms with unhealthy diet and in reducing the symptoms of depression and anxiety with improvement of diet quality. Statistically significant improvement in symptoms of depression and anxiety in both sexes was observed in study groups assigned for individual consultations of a dietician and a psychotherapist when compared with group sessions or general recommendations. CONCLUSIONS: Research on the correlation of healthy dietary patterns and symptoms of depression and anxiety has mainly focused on non-clinical populations. The evidence supports an inverse association between healthy eating habits and symptoms of depression. Further research should be encouraged on the eating habits of clinically depressed individuals and the underlying physiological mechanisms of uncontrolled food intake.

Evaluation of the Polygenic Risk Score for Alzheimer's Disease in Russian Patients with Dementia Using a Low-Density Hydrogel Oligonucleotide Microarray.

The polygenic risk score (PRS), together with the ɛ4 allele of the APOE gene (APOE-ɛ4), has shown high potential for Alzheimer's disease (AD) risk prediction. The aim of this study was to validate the model of polygenic risk in Russian patients with dementia. A microarray-based assay was developed to identify 21 markers of polygenic risk and ɛ alleles of the APOE gene. This case-control study included 348 dementia patients and 519 cognitively normal volunteers. Cerebrospinal fluid (CSF) amyloid-ß (Aß) and tau protein levels were assessed in 57 dementia patients. PRS and APOE-ɛ4 were significant genetic risk factors for dementia. Adjusted for APOE-ɛ4, individuals with PRS corresponding to the fourth quartile had an increased risk of dementia compared to the first quartile (OR 1.85; p-value 0.002). The area under the curve (AUC) was 0.559 for the PRS model only, and the inclusion of APOE-ɛ4 improved the AUC to 0.604. PRS was positively correlated with tTau and pTau181 and inversely correlated with Aß42/Aß40 ratio. Carriers of APOE-ɛ4 had higher levels of tTau and pTau181 and lower levels of Aß42 and Aß42/Aß40. The developed assay can be part of a strategy for assessing individuals for AD risk, with the purpose of assisting primary preventive interventions.

Are subjective language complaints in memory clinic patients informative?

To diagnose mild cognitive impairment, it is crucial to understand whether subjective cognitive complaints reflect objective cognitive deficits. This question has mostly been investigated in the memory domain, with mixed results. Our study was one of the first to address it for language. Participants were 55-to-93-year-old memory clinic patients (n = 163). They filled in a questionnaire about subjective language and memory complaints and performed two language tasks (naming-by-definition and sentence comprehension). Greater language complaints were associated with two language measures, thus showing a moderate value in predicting language performance. Greater relative severity of language versus memory complaints was a better predictor, associated with three language performance measures. Surprisingly, greater memory complaints were associated with better naming, probably due to anosognosia in further disease progression or personality-related factors. Our findings highlight the importance of relative complaint severity across domains and, clinically, call for developing self-assessment questionnaires asking specific questions about multiple cognitive functions.

Alteration of Blood Immune Biomarkers in MCI Patients with Different APOE Genotypes after Cognitive Training: A 1 Year Follow-Up Cohort Study.

Many studies aim to detect the early phase of dementia. One of the major ways to achieve this is to identify corresponding biomarkers, particularly immune blood biomarkers. The objective of this study was to identify such biomarkers in patients with mild cognitive impairment (MCI) in an experiment that included cognitive training. A group of patients with MCI diagnoses over the age of 65 participated in the study (n = 136). Measurements of cognitive functions (using the Mini-Mental State Examination scale and Montreal Cognitive Assessment) and determination of 27 serum biomarkers were performed twice: on the first visit and on the second visit, one year after the cognitive training. APOE genotypes were also determined. Concentrations of EGF (F = 17; p = 0.00007), Eotaxin (F = 7.17; p = 0.008), GRO (F = 13.42; p = 0.0004), IL-8 (F = 8.16; p = 0.005), MCP-1 (F = 13.46; p = 0.0001) and MDC (F = 5.93; p = 0.016) increased after the cognitive training in MCI patients. All these parameters except IL-8 demonstrated a weak correlation with other immune parameters and were poorly represented in the principal component analysis. Differences in concentrations of IP-10, FGF-2, TGFa and VEGF in patients with MCI were associated with APOE genotype. Therefore, the study identified several immune blood biomarkers that could potentially be associated with changes in cognitive function.

Inflammatory biomarkers and lipid metabolism parameters in women with mild cognitive impairment and dementia.

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-1ß, 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.

Treatment of Depression with Vortioxetine and Second Generation Antipsychotics During the Period of Remission Formation in Schizophrenia (Interim Data Analysis).

BACKGROUND: Depression in patients with schizophrenia worsens the course of the disease by increasing the risk of suicide, by complicating the clinical picture of the disorder, and by reducing the quality of the social functioning; its treatment is difficult, since monotherapy, even when involving modern antipsychotics, does not always prove successful. While the prescription of additional antidepressants (ADs) can improve the likelihood of a better outcome, the effectiveness of such augmentation in many cases is yet to be proven. Therefore, it is still important that one weighs the effectiveness of various combinations between most of the known ADs and some second-generation antipsychotic (SGA) in the treatment of depression that occurs at different stages of schizophrenia. In previous studies, the use of vortioxetine as an adjunct to an antipsychotic yielded a reduction in negative symptoms, a clinically significant improvement in cognitive functions that differed from its antidepressant effect, and good tolerability, which affects how committed to treatment a patient remains. AIM: To study the changes that occur over time in the clinical manifestations of depression, negative and cognitive impairment, as well as the social adequacy of patients receiving a combination therapy with second-generation antipsychotics and vortioxetine, which were prescribed in real clinical practice at doses approved in the Russian Federation. METHODS: We performed a comparative analysis of the changes in depression symptoms and negative symptoms, cognitive impairment, as well as function of 78 patients with severe manifestations of depression at the stage of exacerbation reduction and subsequent remission of paranoid schizophrenia. Combination treatment with SGA and vortioxetine was used in 39 patients, and 39 patients who had similar clinical manifestations received just SGA. During the observation period, the mental disorder severity and depression symptom severity were assessed 3 times (before the start of treatment, after three months, and after six months) using the Clinical Global Impression (CGI) scale and Calgary Depression Scale for Schizophrenia (CDSS), respectively; patients were also assessed using the Negative Symptoms Assessment-5 (NSA-5) scale, Perceived Deficits Questionnaire-20 items (PDQ-20) scale, and Personal and Social Performance (PSP) scale. RESULTS: According to the ANOVA results, by the end of the observation period, patients, regardless of their therapeutic group, showed a statistically significant decrease in the level of depression on the CDSS scale, the severity of negative symptoms on the NSA-5 scale, cognitive symptoms on the PDQ-20 scale, as well as an improvement in personality and society, judging by the increase in the total PSP scores. There were also significant differences between the compared main (SGA + vortioxetine) and control (SGA) groups in terms of the changes in the total score on the CDSS and PSP scales. An interesting aspect of the changes in the clinical scores was a noticeable improvement in the SGA + vortioxetine group after 3 months of treatment, in the absence of a similar improvement in the control group, and the achievement of approximately the same scores in both groups after 6 months. In particular, there were significant differences between the SGA + vortioxetine and SGA groups in terms of the mean CDSS (p 0.001), NSA-5 (p=0.003), PDQ-20 (p 0.001), and PSP (p=0.004) scores after 3 months. Analysis of the time before early withdrawal from the study showed that significantly more patients in the SGA + vortioxetine group completed the study program (n=27, 69.23%) compared with the SGA group (n=13, 33.33%) (2 =14.618, df=1, p 0.001, log-rank test. The mean survival time in the SGA group was significantly (p 0.001) less and amounted to 101.436 days (95% CI: 81.518121.354), and in the SGA + vortioxetine group it amounted to 161.744 days (147.981175.506). The relative risk of full study completion in the vortioxetine + SGA group compared with that in SGA was 3.618 (1.8716.994). CONCLUSION: The addition of vortioxetine to the SGA therapy accelerates the reduction of the depression symptoms that occur at the stage of psychosis regression and early remission, contributes to the accelerated reduction in negative symptoms, positively affects the subjective assessment of cognitive impairment severity, and has a significant positive effect on the level of psychosocial functioning.

Suicide-Related Single Nucleotide Polymorphisms, rs4918918 and rs10903034: Association with Dementia in Older Adults.

Dementia has enormous implications for patients and the health care system. Genetic markers are promising for detecting the risk of cognitive impairment. We hypothesized that genetic variants associated with suicide risk might significantly increase the risk of cognitive decline because suicide in older adults is often a consequence of cognitive impairment. We investigated several single-nucleotide polymorphisms that were initially associated with suicide risk in dementia older adults and identified the APOE gene alleles. The study was performed with subjects over the age of 65: 112 patients with dementia and 146 healthy volunteers. The MMSE score was used to assess cognitive functions. Study participants were genotyped using real-time PCR (APOE: rs429358, rs7412; genes associated with suicide: rs9475195, rs7982251, rs2834789, rs358592, rs4918918, rs3781878, rs10903034, rs165774, rs16841143, rs11833579 rs10898553, rs7296262, rs3806263, and rs2462021). Genotype analysis revealed the significance of APOEε4, APOEε2, and rs4918918 (SORBS1) when comparing dementia and healthy control groups. The association of APOEε4, APOEε2, and rs10903034 (IFNLR1) with the overall MMSE score was indicated. The study found an association with dementia of rs4918918 (SORBS1) and rs10903034 (IFNLR1) previously associated with suicide and confirmed the association of APOEε4 and APOEε2 with dementia.

Positive Effect of Cognitive Training in Older Adults with Different APOE Genotypes and COVID-19 History: A 1-Year Follow-Up Cohort Study.

(1) Background: Older people suffer from cognitive decline; several risk factors contribute to greater cognitive decline. We used acquired (COVID-19 infection) and non-modifiable (presence of APOE rs429358 and rs7412 polymorphisms) factors to study the progression of subjective cognitive impairment while observing patients for one year. Cognitive training was used as a protective factor. (2) Methods: Two groups of subjects over the age of 65 participated in the study: group with subjective cognitive decline receiving cognitive training and individuals who did not complain of cognitive decline without receiving cognitive training (comparison group). On the first visit, the concentration of antibodies to COVID-19 and APOE genotype was measured. At the first and last point (1 year later) the Mini-Mental State Examination scale and the Hospital Anxiety and Depression Scale were performed. (3) Results: COVID-19 infection did not affect cognitive function. A significant role of cognitive training in improving cognitive functions was revealed. Older adults with APOE-ε4 genotype showed no positive effect of cognitive training. (4) Conclusions: Future research should focus on cognitive dysfunction after COVID-19 in long-term follow-up. Attention to the factors discussed in our article, but not limited to them, are useful for a personalized approach to maintaining the cognitive health of older adults.

The Efficacy of Mobile Phone-Based Interventions for the Treatment of Depression: A Systematic Meta-Review of Meta-Analyses of Randomized Controlled Trials.

BACKGROUND: Depression is ranked by the World Health Organization as the single largest contributor to global disability. The shortage of health care resources, conditions of social distancing during the present pandemic, and the continuing need of patients with subclinical depression and in remission for supportive therapies, all together motivate a search for new approaches to deliver appropriate and timeous treatment for depression. SUBJECTS AND METHODS: We conducted a systematic literature search of meta-analyses and systematic reviews on the topic of mobile apps for the treatment of depression using the Medline (Pubmed) database during the period ending March 30th, 2022. This review was managed following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and entailed a search strategy using key-words related to depressive states and mobile phone apps for depression treatment and management. RESULTS: A total of 15 full-text articles met the inclusion criteria for the current systematic review. 13 of the 15 studies reported on the effectiveness of mobile apps for treating depression, finding a significant reduction in depressive symptoms with small-to-medium positive effect size. Patients with severe depression experienced greater benefits from a behavioral activation app, whereas those with mild depression responded better to a mindfulness app. The impact of clinicians' support is difficult to isolated completely from the particular interventions' effects. CONCLUSIONS: Mobile-based intervention apps present a convenient tool for prevention and supportive therapy of depression. The use of mobile apps may act as an efficient intervention to reduce depression in adult patients regardless the potential contributing factors of gender or co-morbidities, but the role of mobile apps should be contrasted with other digital interventions.

Anxiety, Depression and Suicidality in Healthcare Workers during the COVID-19 Pandemic: The Russian Study Sample of the COMET-G Project.

BACKGROUND: During the COVID-19 pandemic healthcare workers have been under pressure of high workload and an increased risk of contracting the SARS-Cov-2 virus, while confronting the most tragic and devastating aspects of the pandemic-related medical realities. These factors could lead to severe distress with potential consequences for productivity in performing professional duties, and substantially increased risk for affective reactions, including clinical states of anxiety, depression and suicidality as compared to the general population. Thus, we aimed to investigate the changes in rates of anxiety, depression and suicidality in response to the pandemic among medical staff as compared to a sample of the general population and to the period of prepandemic time. SUBJECTS AND METHODS: This study is part of the large-scale, international multicentre COMET-G project. We assessed the extents of anxiety, depression and suicidality risks using the Stait-Trait Anxiety Inventory (STAI) with a cut-off score 39/40, Center for Epidemiologic Studies Depression Scale (CES-D) with a cut-off score 23/24, and the Risk Assessment Suicidality Scale (RASS) with a cut-off score 499/500, respectively, in samples of Russian healthcare workers and the general population. RESULTS: Among 7777 respondents participating in the study, responses to a query about occupation indicated 1216 healthcare workers. 45.8% of medical staff vs 40.4% of non-medical staff (χ2=12.42, p<0.001) reported the increased anxiety, in excess of the clinical anxiety state threshold score of 39 according to the STAI. High suicidality risks, according to a RASS score > 500, were reported by 8.2% of medical professionals vs 10.6% of non-medical personnel (χ2=6.35, p=0.012). The increase in depression rates, including cases of clinical depression according to the threshold of CES-D ≥ 24, did not differ between the groups. CONCLUSIONS: A larger proportion of healthcare system staff, as compared to the general population, reported a significant increase in anxiety in response to the pandemic. Compared to medical doctors, other healthcare system workers had a significantly higher prevalence of depression and suicidality rates. Exploratory analysis suggested that it was not the occupation per se, but rather the burden of meaningful working duties that could be associated with psychological defense mechanisms against depression and suicidality among medical staff.

Virtual Reality-Based Interventions for Treating Depression in the Context of COVID-19 Pandemic: Inducing the Proficit in Positive Emotions as a Key Concept of Recovery and a Path Back to Normality.

BACKGROUND: During the COVID-19 pandemic as much as 40% of the global population reported deterioration in depressive mood, whereas 26% experienced increased need for emotional support. At the same time, the availability of on-site psychiatric care declined drastically because of the COVID-19 preventive social restriction measures. To address this shortfall, telepsychiatry assumes a greater role in mental health care services. Among various on-line treatment modalities, immersive virtual reality (VR) environments provide an important resource for adjusting the emotional state in people living with depression. Therefore, we reviewed the literature on VR-based interventions for depression treatment during the COVID-19 pandemic. SUBJECTS AND METHODS: We searched the PubMed and Scopus databases, as well as the Internet, for full-length articles published during the period of 2020-2022 citing a set of following key words: "virtual reality", "depression", "COVID-19", as well as their terminological synonyms and word combinations. The inclusion criteria were: 1) the primary or secondary study objectives included the treatment of depressive states or symptoms; 2) the immersive VR intervention used a head-mounted display (HMD); 3) the article presented clinical study results and/or case reports 4) the study was urged by or took place during the COVID-19-associated lockdown period. RESULTS: Overall, 904 records were retrieved using the search strategy. Remarkably, only three studies and one case report satisfied all the inclusion criteria elaborated for the review. These studies included 155 participants: representatives of healthy population (n=40), a case report of a patient with major depressive disorder (n=1), patients with cognitive impairments (n=25), and COVID-19 patients who had survived from ICU treatment (n=89). The described interventions used immersive VR scenarios, in combination with other treatment techniques, and targeted depression. The most robust effect, which the VR-based approach had demonstrated, was an immediate post-intervention improvement in mood and the reduction of depressive symptoms in healthy population. However, studies showed no significant findings in relation to both short-term effectiveness in treatment of depression and primary prevention of depressive symptoms. Also, safety issues were identified, such as: three participants developed mild adverse events (e.g., headache, "giddiness", and VR misuse behavior), and three cases of discomfort related to wearing a VR device were registered. CONCLUSIONS: There has been a lack of appropriately designed clinical trials of the VR-based interventions for depression since the onset of the COVID-19 pandemic. Moreover, all these studies had substantial limitations due to the imprecise study design, small sample size, and minor safety issues, that did not allow us making meaningful judgments and conclude regarding the efficacy of VR in the treatment of depression, taking into account those investigations we have retrieved upon the inclusion criteria of our particularistic review design. This may call for randomized, prospective studies of the short-term and long-lasting effect of VR modalities in managing negative affectivity (sadness, anxiety, anhedonia, self-guilt, ignorance) and inducing positive affectivity (feeling of happiness, joy, motivation, self-confidence, viability) in patients suffering from clinical depression.

Psychoactive substance use, internet use and mental health changes during the COVID-19 lockdown in a French population: A study of gender effect.

Introduction: COVID-19 has enormous impacts on each individual. The goals of our study were (1) to assess the rate of internet and psychoactive substance use, clinical depression and anxiety in a French population during the lockdown (2) to study the role of clinical and socio-demographic variables (especially, gender). Materials and methods: During lockdown, an online anonymous questionnaire was used to assess socio-demographic and health data, previous psychiatric history, anterior and current internet and psychoactive substance use, current anxiety, depression and suicidal ideation. The associations of socio-demographic, clinical variables with anxiety, depression, internet or psychoactive substance use were examined. Results: The study included 263 participants (aged 38.1 ± 15.3-197 males and 64 females). During the lockdown, internet use increased in 14.4% of cases, alcohol use in 20.2%, and tobacco use in 6.8%. In contrast, more participants reported a decrease in alcohol, tobacco or illicit drug use (25.9, 24, and 27.8% respectively). Anxiety was reported in 62.4% and depression in 20.2% of cases; 29.7% of participants reported an increase in anxiety and 25.5% an increase in depression. Depression was associated with an increase in internet and tobacco use. Tobacco and alcohol use were positively associated and an increase in use was more frequent in previous users of both substances. Maintaining a daily routine and relationships with family, being self-employed were associated to lower risks of depression and anxiety. Conclusion: Higher rates of internet use, as well as depression and anxiety, were observed during the lockdown. Gender was not a significant associated factor.

Alterations of the Composition and Neurometabolic Profile of Human Gut Microbiota in Major Depressive Disorder.

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.

University students' mental health amidst the COVID-19 pandemic in Georgia.

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.