Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies

Differential Expression of the β3 Subunit of Voltage-Gated Ca2+ Channel in Mesial Temporal Lobe Epilepsy

The purpose of this study was to identify and validate new putative lead drug targets in drug-resistant mesial temporal lobe epilepsy (mTLE) starting from differentially expressed genes (DEGs) previously identified in mTLE in humans by transcriptome analysis. We identified consensus DEGs among two independent mTLE transcriptome datasets and assigned them status as "lead target" if they (1) were involved in neuronal excitability, (2) were new in mTLE, and (3) were druggable. For this, we created a consensus DEG network in STRING and annotated it with information from the DISEASES database and the Target Central Resource Database (TCRD). Next, we attempted to validate lead targets using qPCR, immunohistochemistry, and Western blot on hippocampal and temporal lobe neocortical tissue from mTLE patients and non-epilepsy controls, respectively. Here we created a robust, unbiased list of 113 consensus DEGs starting from two lists of 3040 and 5523 mTLE significant DEGs, respectively, and identified five lead targets. Next, we showed that CACNB3, a voltage-gated Ca2+ channel subunit, was significantly regulated in mTLE at both mRNA and protein level. Considering the key role of Ca2+ currents in regulating neuronal excitability, this suggested a role for CACNB3 in seizure generation. This is the first time changes in CACNB3 expression have been associated with drug-resistant epilepsy in humans, and since efficient therapeutic strategies for the treatment of drug-resistant mTLE are lacking, our finding might represent a step toward designing such new treatment strategies.

Identifying novel candidate compounds for therapeutic strategies in retinopathy of prematurity via computational drug-gene association analysis

Purpose

Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. Although interventions such as anti-VEGF and laser have high success rates in treating severe ROP, current treatment and preventative strategies still have their limitations. Thus, we aim to identify drugs and chemicals for ROP with comprehensive safety profiles and tolerability using a computational bioinformatics approach.

Methods

We generated a list of genes associated with ROP to date by querying PubMed Gene which draws from animal models, human studies, and genomic studies in the NCBI database. Gene enrichment analysis was performed on the ROP gene list with the ToppGene program which draws from multiple drug-gene interaction databases to predict compounds with significant associations to the ROP gene list. Compounds with significant toxicities or without known clinical indications were filtered out from the final drug list.

Results

The NCBI query identified 47 ROP genes with pharmacologic annotations present in ToppGene. Enrichment analysis revealed multiple drugs and chemical compounds related to the ROP gene list. The top ten most significant compounds associated with ROP include ascorbic acid, simvastatin, acetylcysteine, niacin, castor oil, penicillamine, curcumin, losartan, capsaicin, and metformin. Antioxidants, NSAIDs, antihypertensives, and anti-diabetics are the most common top drug classes derived from this analysis, and many of these compounds have potential to be readily repurposed for ROP as new prevention and treatment strategies.

Conclusion

This bioinformatics analysis creates an unbiased approach for drug discovery by identifying compounds associated to the known genes and pathways of ROP. While predictions from bioinformatic studies require preclinical/clinical studies to validate their results, this technique could certainly guide future investigations for pathologies like ROP.

Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Proliferative Vitreoretinopathy

Purpose

Proliferative vitreoretinopathy (PVR) is the dreaded cause of failure following retinal detachment repair; however, no cures or preventative therapies exist to date. The purpose of this study was to use bioinformatics tools to identify drugs or compounds that interact with biomarkers and pathways involved in PVR pathogenesis that could be eligible for further testing for the prevention and treatment of PVR.

Methods

We queried PubMed to compile a comprehensive list of genes described in PVR to date from human studies, animal models, and genomic studies found in the National Center for Biotechnology Information database. Gene enrichment analysis was performed using ToppGene on PVR-related genes against drug-gene interaction databases to construct a pharmacome and estimate the statistical significance of overrepresented compounds. Compounds with no clinical indications were filtered out from the resulting drug lists.

Results

Our query identified 34 unique genes associated with PVR. Out of 77,146 candidate drugs or compounds in the drug databases, our analysis revealed multiple drugs and compounds that have significant interactions with genes involved in PVR, including antiproliferatives, corticosteroids, cardiovascular agents, antioxidants, statins, and micronutrients. Top compounds, including curcumin, statins, and cardiovascular agents such as carvedilol and enalapril, have well-established safety profiles and potentially could be readily repurposed for PVR. Other significant compounds such as prednisone and methotrexate have shown promising results in ongoing clinical trials for PVR.

Conclusions

This bioinformatics approach of studying drug-gene interactions can identify drugs that may affect genes and pathways implicated in PVR. Predicted bioinformatics studies require further validation by preclinical or clinical studies; however, this unbiased approach could identify potential candidates among existing drugs and compounds that could be repurposed for PVR and guide future investigations.

Translational Relevance

Novel repurposable drug therapies for PVR can be found using advanced bioinformatics models.

Reprogramming the Circadian Dynamics of Epileptic Genes in Mouse Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) is a common and severe epilepsy displaying rhythmicity in humans and animals. However, how the circadian clock contributes to TLE remains elusive. A recent circadian analysis of the ventral hippocampal transcriptome of pilocarpine-induced TLE mice revealed as many as 1650 rhythmically expressed transcripts. Here, a comparison of the mouse ventral hippocampal transcriptome with the human epilepsy-related gene set identified 315 possible mouse epilepsy-related genes. Rhythmicity analysis classified them into arrhythmicity, loss-of-rhythmicity, gain-of-rhythmicity, and rhythmicity-maintaining groups. KEGG and GO analyses of these mouse epilepsy genes suggest their involvement in circadian entrainment. In TLE mice, Htr1d, Drd2, and Chrna3 lose rhythmicity, but P2rx7 gains rhythmicity; the up-regulation of Htr1d and Drd2 and down-regulation of Chrna3 inhibit adenylate cyclase (AC), and up-regulation of Htr1d, Drd2, and P2rx7 activates protein kinase C (PKC). Together, these results suggest that epilepsy can disrupt the circadian dynamics of the epileptic genes, shed light on possible TLE pathogenesis, and provide potential targets for TLE diagnosis and chronotherapy.

Using Computational Drug-Gene Analysis to Identify Novel Therapeutic Candidates for Retinal Neuroprotection

Retinal cell death is responsible for irreversible vision loss in many retinal disorders. No commercially approved treatments are currently available to attenuate retinal cell loss and preserve vision. We seek to identify chemicals/drugs with thoroughly-studied biological functions that possess neuroprotective effects in the retina using a computational bioinformatics approach. We queried the National Center for Biotechnology Information (NCBI) to identify genes associated with retinal neuroprotection. Enrichment analysis was performed using ToppGene to identify compounds related to the identified genes. This analysis constructs a Pharmacome from multiple drug-gene interaction databases to predict compounds with statistically significant associations to genes involved in retinal neuroprotection. Compounds with known deleterious effects (e.g., asbestos, ethanol) or with no clinical indications (e.g., paraquat, ozone) were manually filtered. We identified numerous drug/chemical classes associated to multiple genes implicated in retinal neuroprotection using a systematic computational approach. Anti-diabetics, lipid-lowering medicines, and antioxidants are among the treatments anticipated by this analysis, and many of these drugs could be readily repurposed for retinal neuroprotection. Our technique serves as an unbiased tool that can be utilized in the future to lead focused preclinical and clinical investigations for complex processes such as neuroprotection, as well as a wide range of other ocular pathologies.

Potassium channels and epilepsy

With the development and application of next-generation sequencing technology, the aetiological diagnosis of genetic epilepsy is rapidly becoming easier and less expensive. Additionally, there is a growing body of research into precision therapy based on genetic diagnosis. The numerous genes in the potassium ion channel family constitute the largest family of ion channels: this family is divided into different subtypes. Potassium ion channels play a crucial role in the electrical activity of neurons and are directly involved in the mechanism of epileptic seizures. In China, scientific research on genetic diagnosis and studies of precision therapy for genetic epilepsy are progressing rapidly. Many cases of epilepsy caused by mutation of potassium channel genes have been identified, and several potassium channel gene targets and drug candidates have been discovered. The purpose of this review is to briefly summarize the progress of research on the precise diagnosis and treatment of potassium ion channel-related genetic epilepsy, especially the research conducted in China. Here in, we review several large cohort studies on the genetic diagnosis of epilepsy in China in recent years, summarized the proportion of potassium channel genes. We focus on the progress of precison therapy on some hot epilepsy related potassium channel genes: KCNA1, KCNA2, KCNB1, KCNC1, KCND2, KCNQ2, KCNQ3, KCNMA1, and KCNT1.

Using Advanced Bioinformatics Tools to Identify Novel Therapeutic Candidates for Age-Related Macular Degeneration

Purpose

Age-related macular degeneration (AMD) is the most common cause of aging-related blindness in the developing world. Although medications can slow progressive wet AMD, currently, no drugs to treat dry-AMD are available. We use a systems or in silico biology analysis to identify chemicals and drugs approved by the Food and Drug Administration for other indications that can be used to treat and prevent AMD.

Methods

We queried National Center for Biotechnology Information to identify genes associated with AMD, wet AMD, dry AMD, intermediate AMD, and geographic atrophy to date. We combined genes from various AMD subtypes to reflect distinct stages of disease. Enrichment analysis using the ToppGene platform predicted molecules that can influence AMD genes. Compounds without clinical indications or with deleterious effects were manually filtered.

Results

We identified several drug/chemical classes that can affect multiple genes involved in AMD. The drugs predicted from this analysis include antidiabetics, lipid-lowering agents, and antioxidants, which could theoretically be repurposed for AMD. Metformin was identified as the drug with the strongest association with wet AMD genes and is among the top candidates in all dry AMD subtypes. Curcumin, statins, and antioxidants are also among the top drugs correlating with AMD-risk genes.

Conclusions

We use a systematic computational process to discover potential therapeutic targets for AMD. Our systematic and unbiased approach can be used to guide targeted preclinical/clinical studies for AMD and other ocular diseases.

Translational Relevance

Advanced bioinformatics models identify novel chemicals and approved drug candidates that can be efficacious for different subtypes of AMD.

Ischemic heart injury leads to HIF1-dependent differential splicing of CaMK2γ

Ischemic heart disease is a leading cause of heart failure and hypoxia inducible factor 1 (HIF1) is a key transcription factor in the response to hypoxic injury. Our lab has developed a mouse model in which a mutated, oxygen-stable form of HIF1α (HIF-PPN) can be inducibly expressed in cardiomyocytes. We observed rapid cardiac dilation and loss of contractility in these mice due to lower expression of excitation-contraction coupling genes and reduced calcium flux. As alternative splicing plays an underappreciated role in transcriptional regulation, we used RNA sequencing to search for splicing changes in calcium-handling genes of HIF-PPN hearts and compared them to previous sequencing data from a model of myocardial infarction (MI) to select for transcripts that are modified in a pathological setting. We found overlap between genes differentially expressed in HIF-PPN and post-MI mice (54/131 genes upregulated in HIF-PPN hearts at 1 day and/or 3 days post-MI, and 45/78 downregulated), as well as changes in alternative splicing. Interestingly, calcium/calmodulin dependent protein kinase II, gamma (CAMK2G) was alternatively spliced in both settings, with variant 1 (v1) substantially decreased compared to variants 2 (v2) and 3 (v3). These findings were also replicated in vitro when cells were transfected with HIF-PPN or exposed to hypoxia. Further analysis of CAMK2γ protein abundance revealed only v1 was detectable and substantially decreased up to 7 days post-MI. Rbfox1, a splicing factor of CAMK2G, was also decreased in HIF-PPN and post-MI hearts. Subcellular fractionation showed CAMK2γ v1 was found in the nuclear and cytoplasmic fractions, and abundance decreased in both fractions post-MI. Chromatin immunoprecipitation analysis of HIF1 in post-MI hearts also demonstrated direct HIF1 binding to CAMK2G. CaMK2 is a key transducer of calcium signals in both physiological and pathological settings. The predominantly expressed isoform in the heart, CaMK2δ, has been extensively studied in cardiac injury, but the specific role of CaMK2γ is not well defined. Our data suggest that loss of CaMK2γ after MI is HIF1-dependent and may play an important role in the heart's calcium signaling and transcriptional response to hypoxia.

Exome hits demystified: The next frontier

Severe mental illnesses such as schizophrenia and bipolar disorder have complex inheritance patterns, involving both common and rare variants. Whole exome sequencing is a promising approach to find out the rare genetic variants. We had previously reported several rare variants in multiplex families with severe mental illnesses. The current article tries to summarise the biological processes and pattern of expression of genes harbouring the aforementioned variants, linking them to known clinical manifestations through a methodical narrative review. Of the 28 genes considered for this review from 7 families with multiple affected individuals, 6 genes are implicated in various neuropsychiatric manifestations including some variations in the brain morphology assessed by magnetic resonance imaging. Another 15 genes, though associated with neuropsychiatric manifestations, did not have established brain morphological changes whereas the remaining 7 genes did not have any previously recorded neuropsychiatric manifestations at all. Wnt/b-catenin signaling pathway was associated with 6 of these genes and PI3K/AKT, calcium signaling, ERK, RhoA and notch signaling pathways had at least 2 gene associations. We present a comprehensive review of biological and clinical knowledge about the genes previously reported in multiplex families with severe mental illness. A 'disease in dish approach' can be helpful to further explore the fundamental mechanisms.

Multi-scale top-down approach for modelling epileptic protein-protein interaction network analysis to identify driver nodes and pathways

Protein - Protein Interaction Network (PPIN) analysis unveils molecular level mechanisms involved in disease condition. To explore the complex regulatory mechanisms behind epilepsy and to address the clinical and biological issues of epilepsy, in silico techniques are feasible in a cost- effective manner. In this work, a hierarchical procedure to identify influential genes and regulatory pathways in epilepsy prognosis is proposed. To obtain key genes and pathways causing epilepsy, integration of two benchmarked datasets which are exclusively devoted for complex disorders is done as an initial step. Using STRING database, PPIN is constructed for modelling protein-protein interactions. Further, key interactions are obtained from the established PPIN using network centrality measures followed by network propagation algorithm -Random Walk with Restart (RWR). The outcome of the method reveals some influential genes behind epilepsy prognosis, along with their associated pathways like PI3 kinase, VEGF signaling, Ras, Wnt signaling etc. In comparison with similar works, our results have shown improvement in identifying unique molecular functions, biological processes, gene co-occurrences etc. Also, CORUM provides an annotation for approximately 60% of similarity in human protein complexes with the obtained result. We believe that the formulated strategy can put-up the vast consideration of indigenous drugs towards meticulous identification of genes encoded by protein against several combinatorial disorders.

Whole-genome analysis for effective clinical diagnosis and gene discovery in early infantile epileptic encephalopathy

Early infantile epileptic encephalopathy (EIEE) is a devastating epilepsy syndrome with onset in the first months of life. Although mutations in more than 50 different genes are known to cause EIEE, current diagnostic yields with gene panel tests or whole-exome sequencing are below 60%. We applied whole-genome analysis (WGA) consisting of whole-genome sequencing and comprehensive variant discovery approaches to a cohort of 14 EIEE subjects for whom prior genetic tests had not yielded a diagnosis. We identified both de novo point and INDEL mutations and de novo structural rearrangements in known EIEE genes, as well as mutations in genes not previously associated with EIEE. The detection of a pathogenic or likely pathogenic mutation in all 14 subjects demonstrates the utility of WGA to reduce the time and costs of clinical diagnosis of EIEE. While exome sequencing may have detected 12 of the 14 causal mutations, 3 of the 12 patients received non-diagnostic exome panel tests prior to genome sequencing. Thus, given the continued decline of sequencing costs, our results support the use of WGA with comprehensive variant discovery as an efficient strategy for the clinical diagnosis of EIEE and other genetic conditions.

Feifukang ameliorates pulmonary fibrosis by inhibiting JAK-STAT signaling pathway

Background

Feifukang (FFK) is a traditional Chinese medicine composed of herbs that protect lung function. However, difficulty arises regarding the clinical application of FFK due to the complex mechanism of Chinese medicines. This study aimed to investigate the efficacy of FFK and explore its targeted genes and pathways.

Methods

Histopathological changes and collagen deposition were measured to evaluate the effect of FFK on bleomycin-induced pulmonary fibrosis in mice. The differentially expressed targeted genes and pathways were first screened using RNA sequencing. Then network pharmacology and other experiments were conducted to confirm RNA sequencing data.

Results

FFK treatment reduced the pathological score and collagen deposition, with a decrease in α-SMA and collagen. RNA sequencing and network pharmacology results all showed that FFK can ameliorate pulmonary fibrosis through multi-genes and multi-pathways. The targeted genes in JAK-STAT signaling pathway are some of the most notable components of these multi-genes and multi-pathways. Further experiments illustrated that FFK regulated phosphorylation of SMAD3, STAT3 and JAK1, and their co-expressed lncRNAs, which all are the important genes in JAK-STAT signaling pathway.

Conclusion

FFK can ameliorate pulmonary fibrosis by inhibiting JAK-STAT signaling pathway and has potential therapeutic value for lung fibrosis treatment. Our study provides a new idea for the study of traditional Chinese medicine.

Identification of potential drug targets for treatment of refractory epilepsy using network pharmacology

Epilepsy is the fourth most common neurological disease after migraine, stroke, and Alzheimer's disease. Approximately one-third of all epilepsy cases are refractory to the existing anticonvulsants. Thus, there is an unmet need for newer antiepileptic drugs (AEDs) to manage refractory epilepsy (RE). Discovery of novel AEDs for the treatment of RE further retards for want of potential pharmacological targets, unavailable due to unclear etiology of this disease. In this regard, network pharmacology as an area of bioinformatics is gaining popularity. It combines the methods of network biology and polypharmacology, which makes it a promising approach for finding new molecular targets. This work is aimed at discovering new pharmacological targets for the treatment of RE using network pharmacology methods. In the framework of our study, the genes associated with the development of RE were selected based on analysis of available data. The methods of network pharmacology were used to select 83 potential pharmacological targets linked to the selected genes. Then, 10 most promising targets were chosen based on analysis of published data. All selected target proteins participate in biological processes, which are considered to play a key role in the development of RE. For 9 of 10 selected targets, the potential associations with different kinds of epilepsy have been recently mentioned in the literature published, which gives additional evidence that the approach applied is rather promising.