Analysis of master transcription factors related to Parkinson's disease through the gene transcription regulatory network

Inference of gene regulatory networks based on directed graph convolutional networks

Inferring gene regulatory network (GRN) is one of the important challenges in systems biology, and many outstanding computational methods have been proposed; however there remains some challenges especially in real datasets. In this study, we propose Directed Graph Convolutional neural network-based method for GRN inference (DGCGRN). To better understand and process the directed graph structure data of GRN, a directed graph convolutional neural network is conducted which retains the structural information of the directed graph while also making full use of neighbor node features. The local augmentation strategy is adopted in graph neural network to solve the problem of poor prediction accuracy caused by a large number of low-degree nodes in GRN. In addition, for real data such as E.coli, sequence features are obtained by extracting hidden features using Bi-GRU and calculating the statistical physicochemical characteristics of gene sequence. At the training stage, a dynamic update strategy is used to convert the obtained edge prediction scores into edge weights to guide the subsequent training process of the model. The results on synthetic benchmark datasets and real datasets show that the prediction performance of DGCGRN is significantly better than existing models. Furthermore, the case studies on bladder uroepithelial carcinoma and lung cancer cells also illustrate the performance of the proposed model.

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here, we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and OVOL2, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy and discovered a role for IL2 STAT5 signaling in heart failure. Our findings underscore the importance of TF activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

Identification of Hub Genes and Potential Molecular Pathogenesis in Substantia Nigra in Parkinson's Disease via Bioinformatics Analysis

Parkinson's disease (PD) is the second most common neurodegenerative disease, with significant socioeconomic burdens. One of the crucial pathological features of PD is the loss of dopaminergic neurons in the substantia nigra (SN). However, the exact pathogenesis remains unknown. Moreover, therapies to prevent neurodegenerative progress are still being explored. We performed bioinformatics analysis to identify candidate genes and molecular pathogenesis in the SN of patients with PD. We analyzed the expression profiles, GSE49036 and GSE7621, which included 31 SN tissues in PD samples and 17 SN tissues in healthy control samples, and identified 86 common differentially expressed genes (DEGs). Then, GO and KEGG pathway analyses of the identified DEGs were performed to understand the biological processes and significant pathways of PD. Subsequently, a protein-protein interaction network was established, with 15 hub genes and four key modules which were screened in this network. The expression profiles, GSE8397 and GSE42966, were used to verify these hub genes. We demonstrated a decrease in the expression levels of 14 hub genes in the SN tissues of PD samples. Our results indicated that, among the 14 hub genes, DRD2, SLC18A2, and SLC6A3 may participate in the pathogenesis of PD by influencing the function of the dopaminergic synapse. CACNA1E, KCNJ6, and KCNB1 may affect the function of the dopaminergic synapse by regulating ion transmembrane transport. Moreover, we identified eight microRNAs (miRNAs) that can regulate the hub genes and 339 transcription factors (TFs) targeting these hub genes and miRNAs. Subsequently, we established an mTF-miRNA-gene-gTF regulatory network. Together, the identification of DEGs, hub genes, miRNAs, and TFs could provide better insights into the pathogenesis of PD and contribute to the diagnosis and therapies.

Protective effects of functional foods against Parkinson's disease: A narrative review on pharmacology, phytochemistry, and molecular mechanisms

In Persian Medicine (PM), PD (brain-based tremor) is a known CNS disorder with several therapeutic and preventive options. In their medical textbooks and pharmacopeias, Persian great scientists such as Rhazes (854-925 AD), Avicenna (980-1037 AD), and Jorjani (1042-1136 AD), have discussed pharmacological and nutritional strategies for the prevention, slowing progression, and treatment of PD. In the present study, we surveyed plant- and animal-based foods recommended by PM for the prevention and treatment of CNS-related tremors. In vivo and in-vitro pharmacological evidence supporting the beneficial effects of PM-recommended foods in prevention and alleviating PD, major active phytochemicals along with the relevant mechanisms of action were studied. Several PM plants possess potent antioxidant, antiinflammatory, and PD preventing properties. Garlic and allicin, cabbage and isothiocyanates, chickpea seed and its O-methylated isoflavones biochanin A and formononetin, cinnamon, and cinnamaldehyde, saffron and its crocin, crocetin, and safranal, black cumin and its thymoquinone, black pepper and piperine, pistachio and genistein and daidzein, and resveratrol are among the most effective dietary itemsagainst PD. They act through attenuating neurotoxin-induced memory loss and behavioral impairment, oxidative stress, and dopaminergic cell death. PM-recommended foods can help alleviate PD progression and also discovering and developing new neuroprotective anti-PD pharmaceuticals.

Inhibition of histone deacetylase promotes a neuroprotective mechanism in an experimental model of Parkinson's disease

Introduction

Therapies targeting histone deacetylase (HDAC) have gained wider attention in the treatment of various clinical conditions. However, the use of HDAC inhibitors in pre-clinical trials in the case of Parkinson's disease (PD) is very limited. In the present study, the HDAC inhibitor, entinostat, was tested in animals induced with Parkinson's disease experimentally.

Material and methods

Wistar male rats (150 ±10 g) were administered with rotenone (2 mg/kg/day, s.c.) for 21 days to induce PD, while entinostat (20 mg/kg) was given intraperitoneally. Then, the neurological functions, PD markers, and HDACs were analysed in the control and experimental animals.

Results

The results demonstrated that rats that received entinostat displayed progressive motor, behavioural, and neurological function with attenuated α-synuclein and improved tyrosine-hydroxylase compared to control cells. Moreover, the induction of PD in rats demonstrated reduced levels of H2S, dopamine, 3, and 4-dihydroxyphenylacetic acid (DOPAC), and increased monoamine oxidase activity in PD rats. However, the rats that received entinostat demonstrated progressive levels of dopa and DOPAC, with attenuated levels of HDAC-2, -4, and -6 mRNA in the PD rats compared to controls. On the other hand, elevated (p < 0.01) levels of PD marker genes such as GDF3 and NMDA2b were reduced, with a significant increase in neuroprotective genes such as VDAC3 and CBX5 in entinostat-supplemented rats.

Conclusions

The study results suggest that inhibition of HDAC systematically improves the neurological functions, and hence treatments, emphasizing that HDACI, as the speculated mechanism, will be a promising mode of treatment in PD.