Background: Parkinson’s disease is a complex disease with its monogenic forms accounting for less than 10% of all cases. Whole-exome sequencing technology has been used successfully to find mutations in large families. However, because of the late onset of the disease, only small families and unrelated patients are usually available. Whole-exome sequencing conducted in such cases yields in a large number of candidate variants. There are currently a number of imperfect software tools that allow the pathogenicity of variants to be evaluated. Objectives: We analyzed 48 unrelated patients with an alleged autosomal dominant familial form of Parkinson’s disease using whole-exome sequencing and developed a strategy for selecting potential pathogenetically significant variants using almost all available bioinformatics resources for the analysis of exonic areas. Methods: DNA sequencing of 48 patients with excluded frequent mutations was performed using an Illumina HiSeq 2500 platform. The possible pathogenetic significance of identified variants and their involvement in the pathogenesis of Parkinson’s disease was assessed using SVS, CADD, and REVEL software. Functional evaluation was performed using the Pathway Studio database. Results: A significant reduction in the search range from 7082 to 25 variants in 23 genes associated with Parkinson’s disease or neuronal function was achieved. Eight (FXN, MFN2, MYOC, NPC1, PSEN1, RET, SCN3A, and SPG7) were the most significant. Conclusions: The multistep approach developed made it possible to conduct an effective search for potential pathogenetically significant variants, presumably involved in the pathogenesis of Parkinson’s disease. The data obtained need to be further verified experimentally.

To assess the biology of the lethal endpoint in patients with SARS-CoV-2 infection, we compared the transcriptional response to the virus in patients who survived or died during severe COVID-19. We applied gene expression profiling to generate transcriptional signatures for peripheral blood mononuclear cells (PBMCs) from patients with SARS-CoV-2 infection at the time when they were placed in the Intensive Care Unit of the Pavlov First State Medical University of St. Petersburg (Russia). Three different bioinformatics approaches to RNA-seq analysis identified a downregulation of three common pathways in survivors compared with nonsurvivors among patients with severe COVID-19, namely, low-density lipoprotein (LDL) particle receptor activity (GO:0005041), important for maintaining cholesterol homeostasis, leukocyte differentiation (GO:0002521), and cargo receptor activity (GO:0038024). Specifically, PBMCs from surviving patients were characterized by reduced expression of PPARG, CD36, STAB1, ITGAV, and ANXA2. Taken together, our findings suggest that LDL particle receptor pathway activity in patients with COVID-19 infection is associated with poor disease prognosis.

Parkinson’s Disease (PD) is a widespread severe neurodegenerative disease that is characterized by pronounced deficiency of the dopaminergic system and disruption of the function of other neuromodulator systems. Although heritable genetic factors contribute significantly to PD pathogenesis, only a small percentage of sporadic cases of PD can be explained using known genetic risk factors. Due to that, it could be inferred that changes in gene expression could be important for explaining a significant percentage of PD cases. One of the ways to investigate such changes, while minimizing the effect of genetic factors on experiment, are the study of PD discordant monozygotic twins. In the course of the analysis of transcriptome data obtained from IPSC and NPCs, 20 and 1906 differentially expressed genes were identified respectively. We have observed an overexpression of TNF in NPC cultures, derived from twin with PD. Through investigation of gene interactions and gene involvement in biological processes, we have arrived to a hypothesis that TNF could play a crucial role in PD-related changes occurring in NPC derived from twins with PD, and identified INHBA, WNT7A and DKK1 as possible downstream effectors of TNF.

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases. Investigating individuals with the most identical genetic background is optimal for minimizing the genetic contribution to gene expression. These individuals include monozygotic twins discordant for PD. Monozygotic twins have the same genetic background, age, sex, and often similar environmental conditions. The aim of this study was to carry out a transcriptome analysis of the peripheral blood of three pairs of monozygotic twins discordant for PD. We identified the metabolic process “circadian behavior” as a priority process for further study. Different expression of genes included in the term “circadian behavior” confirms that this process is involved in PD pathogenesis. We found increased expression of three genes associated with circadian behavior, i.e., PTGDS, ADORA2A, and MTA1, in twins with PD. These genes can be considered as potential candidate genes for this disease.

The forced swim test (FST) is widely used to screen for potential antidepressant drugs and treatments. Despite this, the nature of stillness during FST and whether it resembles “depressive-like behavior” are widely debated issues. Furthermore, despite being widely used as a behavioral assay, the effects of the FST on the brain transcriptome are rarely investigated. Therefore, in this study we have investigated changes in the transcriptome of the rat hippocampus 20 min and 24 h after FST exposure. RNA-Seq is performed on the hippocampus tissues of rats 20 min and 24 h after an FST. Differentially expressed genes (DEGs) were identified using limma and used to construct gene interaction networks. Fourteen differentially expressed genes (DEGs) were identified only in the 20-m group. No DEGs were identified 24 h after the FST. These genes were used for Gene Ontology term enrichment and gene-network construction. Based on the constructed gene-interaction networks, we identified a group of DEGs (Dusp1, Fos, Klf2, Ccn1, and Zfp36) that appeared significant based on multiple methods of downstream analysis. Dusp1 appears especially important, as its role in the pathogenesis of depression has been demonstrated both in various animal models of depression and in patients with depressive disorders.