A Genome-Wide Association Study Reveals a BDNF-Centered Molecular Network Associated with Alcohol Dependence and Related Clinical Measures.

At least 50% of factors predisposing to alcohol dependence (AD) are genetic and women affected with this disorder present with more psychiatric comorbidities, probably indicating different genetic factors involved. We aimed to run a genome-wide association study (GWAS) followed by a bioinformatic functional annotation of associated genomic regions in patients with AD and eight related clinical measures. A genome-wide significant association of rs220677 with AD (p-value = 1.33 × 10-8 calculated with the Yates-corrected χ2 test under the assumption of dominant inheritance) was discovered in female patients. Associations of AD and related clinical measures with seven other single nucleotide polymorphisms listed in previous GWASs of psychiatric and addiction traits were differently replicated in male and female patients. The bioinformatic analysis showed that regulatory elements in the eight associated linkage disequilibrium blocks define the expression of 80 protein-coding genes. Nearly 68% of these and of 120 previously published coding genes associated with alcohol phenotypes directly interact in a single network, where BDNF is the most significant hub gene. This study indicates that several genes behind the pathogenesis of AD are different in male and female patients, but implicated molecular mechanisms are functionally connected. The study also reveals a central role of BDNF in the pathogenesis of AD.

16S rRNA gene sequencing data of the upper respiratory tract microbiome in the SARS-CoV-2 infected patients.

The SARS-CoV-2 pandemic is a big challenge for humanity. The COVID-19 severity differs significantly from patient to patient, and it is important to study the factors protecting from severe forms of the disease. Respiratory microbiota may influence the patient's susceptibility to infection and disease severity due to its ability to modulate the immune system response of the host organism. This data article describes the microbiome dataset from the upper respiratory tract of SARS-CoV-2 positive patients from Russia. This dataset reports the microbial community profile of 335 human nasopharyngeal swabs collected between 2020-05 and 2021-03 during the first and the second epidemic waves. Samples were collected from both inpatients and outpatients in 4 cities of the Russian Federation (Moscow, Kazan, Irkutsk, Nizhny Novgorod) and sequenced using the 16S rRNA gene amplicon sequencing of V3-V4 region. Data contains information about the patient such as age, sex, hospitalization status, percent of damaged lung tissue, oxygen saturation (SpO2), respiratory rate, need for supplemental oxygen, chest computer tomography severity score, SARS-CoV-2 lineage, and also information about smoking and comorbidities. The amplicon sequencing data were deposited at NCBI SRA as BioProject PRJNA751478.

Association of antioxidant deficiency and the level of products of protein and lipid peroxidation in patients with the first episode of schizophrenia.

Schizophrenia is considered a multifactorial disease, where one of the pathogenetic links is oxidative stress; however, the results of studies are often contradictory, largely due to significant heterogeneity among study methods. The present study was undertaken to compare the levels of oxidative stress markers in the peripheral blood of patients with a first episode of schizophrenia (FES) and in healthy volunteers (HV). The study included 50 patients with FES and 37 HV. Blood samples were collected for spectrophotometric assessment of reduced glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA), aldehyde-2,4-dinitrophenylhydrazone (ADNPH), and ketone-2,4-dinitrophenylhydrazone (KDNPH) in blood plasma. Results showed that in patients with FES compared with HV, a significant decrease in CAT activity and an increase in oxidative modification of proteins (OMP) were found. In both groups, a significant increase in the level of MDA with age was revealed. In patients, the GSH plasma level was inversely proportional to the ADNPH level, and SOD activity was directly proportional to the KDNPH level. In volunteers there was no such correlation; however, there was a direct correlation between CAT activity and the levels of OMP and MDA. In both groups, a moderate direct correlation between peroxidation products was observed. The results confirm that a redox imbalance (a deficiency of antioxidants, in particular CAT, and excess OMP) may be a pathogenetic link in schizophrenia, which is manifested already at an early stage of the disease.

Artificial Intelligence Predicts Severity of COVID-19 Based on Correlation of Exaggerated Monocyte Activation, Excessive Organ Damage and Hyperinflammatory Syndrome: A Prospective Clinical Study.

Background: Prediction of the severity of COVID-19 at its onset is important for providing adequate and timely management to reduce mortality. Objective: To study the prognostic value of damage parameters and cytokines as predictors of severity of COVID-19 using an extensive immunologic profiling and unbiased artificial intelligence methods. Methods: Sixty hospitalized COVID-19 patients (30 moderate and 30 severe) and 17 healthy controls were included in the study. The damage indicators high mobility group box 1 (HMGB1), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), alanine aminotransferase (ALT), extensive biochemical analyses, a panel of 47 cytokines and chemokines were analyzed at weeks 1, 2 and 7 along with clinical complaints and CT scans of the lungs. Unbiased artificial intelligence (AI) methods (logistic regression and Support Vector Machine and Random Forest algorithms) were applied to investigate the contribution of each parameter to prediction of the severity of the disease. Results: On admission, the severely ill patients had significantly higher levels of LDH, IL-6, monokine induced by gamma interferon (MIG), D-dimer, fibrinogen, glucose than the patients with moderate disease. The levels of macrophage derived cytokine (MDC) were lower in severely ill patients. Based on artificial intelligence analysis, eight parameters (creatinine, glucose, monocyte number, fibrinogen, MDC, MIG, C-reactive protein (CRP) and IL-6 have been identified that could predict with an accuracy of 83-87% whether the patient will develop severe disease. Conclusion: This study identifies the prognostic factors and provides a methodology for making prediction for COVID-19 patients based on widely accepted biomarkers that can be measured in most conventional clinical laboratories worldwide.

Opening up new horizons for psychiatric genetics in the Russian Federation: moving toward a national consortium.

We provide an overview of the recent achievements in psychiatric genetics research in the Russian Federation and present genotype-phenotype, population, epigenetic, cytogenetic, functional, ENIGMA, and pharmacogenetic studies, with an emphasis on genome-wide association studies. The genetic backgrounds of mental illnesses in the polyethnic and multicultural population of the Russian Federation are still understudied. Furthermore, genetic, genomic, and pharmacogenetic data from the Russian Federation are not adequately represented in the international scientific literature, are currently not available for meta-analyses and have never been compared with data from other populations. Most of these problems cannot be solved by individual centers working in isolation but warrant a truly collaborative effort that brings together all the major psychiatric genetic research centers in the Russian Federation in a national consortium. For this reason, we have established the Russian National Consortium for Psychiatric Genetics (RNCPG) with the aim to strengthen the power and rigor of psychiatric genetics research in the Russian Federation and enhance the international compatibility of this research.The consortium is set up as an open organization that will facilitate collaborations on complex biomedical research projects in human mental health in the Russian Federation and abroad. These projects will include genotyping, sequencing, transcriptome and epigenome analysis, metabolomics, and a wide array of other state-of-the-art analyses. Here, we discuss the challenges we face and the approaches we will take to unlock the huge potential that the Russian Federation holds for the worldwide psychiatric genetics community.