BackgroundThe long-term effects of psychotropic drugs are associated with the reversal of disease-related alterations through the reorganization and normalization of neuronal connections. Molecular factors that trigger drug-induced brain plasticity remain only partly understood. Doublecortin-like kinase 1 (Dclk1) possesses microtubule-polymerizing activity during synaptic plasticity and neurogenesis. However, the Dclk1 gene shows a complex profile of transcriptional regulation, with two alternative promoters and exon splicing patterns that suggest the expression of multiple isoforms with different kinase activities.ResultsHere, we applied next-generation sequencing to analyze changes in the expression of Dclk1 gene isoforms in the brain in response to several psychoactive drugs with diverse pharmacological mechanisms of action. We used bioinformatics tools to define the range and levels of Dclk1 transcriptional regulation in the mouse nucleus accumbens and prefrontal cortex. We also sought to investigate the presence of DCLK1-derived peptides using mass spectrometry. We detected 15 transcripts expressed from the Dclk1 locus (FPKM > 1), including 2 drug-regulated variants (fold change > 2). Drugs that act on serotonin receptors (5-HT2A/C) regulate a subset of Dclk1 isoforms in a brain-region-specific manner. The strongest influence was observed for the mianserin-induced expression of an isoform with intron retention. The drug-activated expression of novel alternative Dclk1 isoforms was validated using qPCR. The drug-regulated isoform contains genetic variants of DCLK1 that have been previously associated with schizophrenia and hyperactivity disorder in humans. We identified a short peptide that might originate from the novel DCLK1 protein product. Moreover, protein domains encoded by the regulated variant indicate their potential involvement in the negative regulation of the canonical DCLK1 protein.ConclusionsIn summary, we identified novel isoforms of the neuroplasticity-related gene Dclk1 that are expressed in the brain in response to psychotropic drug treatments.Electronic supplementary materialThe online version of this article (10.1186/s12868-018-0458-4) contains supplementary material, which is available to authorized users.
Three strains of mice with various susceptibilities to restraint stress (RS), i.e., mice with a knocked out norepinephrine transporter gene (NET-KO), SWR/J and C57BL/6J (WT) mice were shown to serve as a good model to study the molecular mechanisms underlying different stress-coping strategies. We identified 14 miRNAs that were altered by RS in the PFC of these mice in a genotype-dependent manner, where the most interesting was let-7e. Further in silico analysis of its potential targets allowed us to identify five mRNAs (Bcl2l11, Foxo1, Pik3r1, Gab1 and Map2k4), and their level alterations were experimentally confirmed. A next-generation sequencing (NGS) approach, which was employed to find transcripts differentially expressed in the PFC of NET-KO and WT mice, showed that, among others, two additional mRNAs were regulated by mmu-let-7e, i.e., mRNAs that encode Kmt2d and Inf2. Since an increase in Bcl2l11 and Pik3r1 mRNAs upon RS in the PFC of WT mice resulted from the decrease in mmu-let-7e and mmu-miR-484 regulations, we postulated that MAPK, FoxO and PI3K-Akt signaling pathways were associated with stress resilience, although via different, genotype-dependent regulation of various mRNAs by let-7e and miR-484. However, a higher level of Kmt2d mRNA (regulated by let-7e) that was found with NGS analysis in the PFC of NET-KO mice indicated that histone methylation was also important for stress resilience.
Dopamine receptor D2 gene (DRD2) polymorphisms have been associated with cognitive abilities, obesity, addictions, and physical-activity-related behaviors, which may underlie differences in the effectiveness of training programs. What is not yet clear is the impact of DRD2 polymorphisms on the effectiveness of exercise programs. Thus, the aim of this study was to investigate the association between the DRD2 polymorphic sites (rs1076560, rs12364283, rs1799732, rs1800497, and rs1800498) and the body’s response to regular physical activity. We studied genotypes and haplotypes distribution in a group of 165 females measured for body mass and body composition measurements, lipid profile, and glucose levels before and after realization of a 12-week training program. When tested individually, statistical analyses revealed one significant genotype by training interaction under the general model (for the basal metabolic rate, BMR, p = 0.033). Carriers of the rs1076560 CC genotype exhibited a decrease in BMR in response to training (p = 0.006). Haplotype analyses also showed that (i) the CACCC and CACTT haplotypes were associated with a post-training decrease in glucose level (β = −4.11, p = 0.032; β = −6.86, p = 0.020, respectively); (ii) the CGCCT with an increase in BMR (β = 0.65, p = 0.003) and fat free mass (FFM, β = 1.20, p = 0.009); (iii) the CA-CT with a decrease in low-density lipoprotein cholesterol (LDL, β = −17.26, p = 0.046). These results provide some evidence that the DRD2 polymorphisms may play a role in post-training changes in lipid and carbohydrate metabolism, and, as a consequence, in the effectiveness of training programs.
Despite the general awareness of the need to reduce air pollution, the efforts were undertaken in Poland to eliminate the pollutants and their harmful effect on human health seem to be insufficient. Moreover, the latest data indicate that the city of Krakow is at the forefront of the most polluted cities worldwide. Hence, in this report, we investigated the impact of particulate matter isolated from the air of Krakow (PM KRK) on the gene expression profile of peripheral blood mononuclear cells (PBMCs) in healthy donors (HD) and patients with atherosclerosis (AS), rheumatoid arthritis (RA) and multiple sclerosis (MS), after in vitro exposure. Blood samples were collected in two seasons, differing in the concentration of PM in the air (below or above a daily limit of 50 µg/m3 for PM 10). Data show that PBMCs exposed in vitro to PM KRK upregulated the expression of genes involved, among others, in pro-inflammatory response, cell motility, and regulation of cell metabolism. The transcriptional effects were observed predominantly in the group of patients with AS and MS. The observed changes seem to be dependent on the seasonal concentration of PM in the air of Krakow and may suggest their important role in the progression of AS, MS, and RA in the residents of Krakow.
Despite the variable chemical and physical characteristics of particulate air pollutants, inflammation and oxidative stress have been identified as common mechanisms for cell damage and negative health influences. These effects are produced by organic components, especially by endotoxins. This study analyzed the gene expression profile after exposure of RAW 264.7 cells to the standard particulate matter (PM) material, NIST1648a, and PM with a reduced organic matter content, LAp120, in comparison to the effects of lipopolysaccharide (LPS). The selected parameters of cell viability, cell cycle progression, and metabolic and inflammatory activity were also investigated. Both forms of PM negatively influenced the parameters of cell activity. These results were generally reflected in the gene expression profile. Only NIST1648a, excluding LAp120, contained endotoxins and showed small but statistically significant pro-inflammatory activity. However, the gene expression profiling revealed strong pro-inflammatory cell activation induced by NIST1648a that was close to the effects of LPS. Changes in gene expression triggered by LAp120 were relatively small. The observed differences in the effects of NIST1648a and LAp120 were related to the content of organic matter in which bacterial endotoxins play an important role. However, other organic compounds and their interactions with other PM components also appear to be of significant importance.
The acceptability of antidepressant drugs partly depends on genetic factors. The list of genes involved in antidepressant response, including Adverse Drug Reactions (ADRs) is broad and contains both drug-metabolizing enzymes (pharmacogenes) and genes involved in pharmacodynamics. Variants in pharmacogenes are traditionally reported in the form of star alleles and are partially annotated with known phenotypic consequences. As it is unfeasible to analyze all genotype-phenotype pairs, computational approaches remain the practical solution. A pharmacogenetic framework to predict responses to antidepressant drug treatment would provide great benefit to patients. In this study, we present a scoring system (PharmGScore) to assess both rare and common genetic variant burden across multiple genes. The PharmGScore is constructed by normalizing and aggregating existing, well-established computational variant predictors (CADD, Fathmm-xf, PROVEAN, Mutation Assessor). We show that this score effectively distinguishes no and decreased function from normal and increased function pharmacogenetic variants reported in PharmVar (PharmGScore AUC = 0.86). PharmGScore has improved performance when compared to its component scores (AUCs: CADD = 0.79; FATHMM-XF = 0.81; PROVEAN = 0.81; Mutation Assessor = 0.75). We then apply the PharmGScore to the 200k exome sequences of the UK Biobank (UKB). We report the overrepresentation of UKB participants with high (>50) gene PharmGScore for CYP2C19 and CYP2C9 and with high (>100) compound PharmGScore from nine pharmacogenes within a group with an antidepressant toxicity diagnostic code (T43.2). We then analyze all UKB participants that received any antidepressant toxicity or ADR diagnosis (n = 602). We indicate genes for which a higher burden may be associated with antidepressant toxicity or ADRs and confirm the known roles of CYP2C19 and CYP2D6 in this process. Finally, we show that patients who experienced ADRs to antidepressants in the therapeutic process or accidental poisoning with antidepressants have a higher PharmGScore composed of nine cytochrome P450 genes. Our study proposes a novel paradigm to assess the compound genetic variant burden associated with antidepressant response from exome sequencing data. This approach can be further applied to a user-defined set of genes to investigate other pharmacological traits.
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