Abstract
Introduction
Although there is accumulating evidence that genetic factors play a vital role in the pathogenesis of epilepsy, few epilepsy-associated genes have been identified. Additionally, the role of KCNJ15 in epilepsy has not been evaluated so far.
Methods
Here, we performed differentially expressed gene analysis, expression quantitative trait loci analysis, gene co-expression analysis, and protein–protein interaction analysis to evaluate the role of KCNJ15 in epilepsy.
Results
Analysis of gene expression and expression quantitative trait loci data revealed that KCNJ15 was significantly downregulated in patients with epilepsy (adjusted P = 0.0146 and log2 Fold change = − 1.0025), and an epilepsy-associated polymorphism (rs2833098) was linked to altered KCNJ15 expression level in human temporal lobe brain tissue (P = 0.0036). Gene co-expression analysis revealed that KCNJ15 was co-expressed with genes that have been reported to be associated with epilepsy in human brain tissue. Furthermore, protein–protein interaction analysis revealed strong supportive evidence for the role of KCNJ15 in epilepsy.
Conclusion
Our results show that KCNJ15 may be a candidate target for epilepsy. Functional analysis of KCNJ15 may provide novel insights for epilepsy treatment.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Epilepsy is one of the nervous system diseases with complex inheritance. However, the role of KCNJ15 in epilepsy remains unknown. |
About 30% of patients do not respond well to current antiepileptic drugs. Furthermore, current antiepileptic drugs are often correlated with multiple adverse reactions. Considering the limitations of current therapeutic strategies, gene therapy may be a promising option. |
The protein encoded by KCNJ15, ATP-sensitive inward rectifier potassium channel 15, is an integral membrane protein. Its physiological function is to act as an inward potassium channel that allows potassium to flow into the cell through the cell membrane. |
By an integrative analysis with data on KCNJ15 expression, expression quantitative trait locus (eQTL), gene co-expression, and protein–protein interaction (PPI), we hypothesize that KCNJ15 has an active role in epilepsy. |
Introduction
Epilepsy is the most prevalent nervous system disease [1], and it is characterized by episodes of excessive synchronized neuronal activity. About 30% of patients do not respond well to current antiepileptic drugs [2, 3]. Furthermore, these drugs often have multiple adverse side effects [4, 5]. Although surgery is an effective option for drug-resistant epilepsy, it is suitable only for a few patients [6] and might also affect other brain tissues surrounding the epileptic focus [7]. Considering the limitations of current therapeutic strategies, gene therapy may be a promising option [8]
K+ channels play an important role in membrane repolarization of active neurons.Therefore, K+ channels may be potential targets for epilepsy treatment [9]. The protein encoded by KCNJ15, ATP-sensitive inward rectifier potassium channel 15, is an integral membrane protein. Its physiological function is to act as an inward potassium channel that allows potassium to flow into the cell through the cell membrane. The expression of KCNJ15 has been observed in glial cells [10]. Knockdown of KCNJ15 can result in compromised electrotaxis [11]. KCNJ15 is associated with Parkinson’s disease [12], and it also plays a vital role in Alzheimer’s disease pathogenesis [13], suggesting that it is involved in the pathogenesis of central nervous system diseases more broadly. However, the association between KCNJ15 and epilepsy has not been evaluated so far. Therefore, we conducted a study including differentially expressed gene (DEG) analysis, expression quantitative trait locus (eQTL) analysis, gene co-expression analysis, and protein–protein interaction (PPI) analysis, to systematically investigate the role of KCNJ15 in epilepsy.
Methods
Differentially Expressed Genes Identified in Human Brain Tissue
The GSE6834 data set was downloaded from NCBI (https://www.ncbi.nlm.nih.gov), and R software was used to screen the DEGs between epilepsy and controls. The GSE6834 data set is divided into temporal lobe brain tissue samples from patients with epilepsy and temporal lobe brain tissue samples from the control group. Specifically, ten epilepsy temporal lobe brain tissue samples were obtained from patients undergoing therapeutic surgery for drug-resistant mesial temporal lobe epilepsy according to routine clinical protocols and controls from ten nonepileptic temporal lobe samples. Patients in the case group were between 18 and 60 years old, and those in the control group were between 56 and 90 years old. An adjusted P ≤ 0.05 and |log2 Fold change| ≥ 1 were considered statistically significant.
This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors.
Expression Quantitative Trait Locus Analysis in Human Brain Tissue
Rs2833098 has been reported to be associated with the risk of epilepsy [14]. To explore if rs2833098 regulates the expression level of KCNJ15 in human temporal lobe brain tissue, we conducted eQTL analysis in the BRAINEAC database (http://www.braineac.org/), which provides gene expression values across ten brain tissues. KCNJ15 expression was measured using RNA sequencing, and a linear regression analysis under an additive model was used to explore the association of rs2833098 with KCNJ15 expression levels.
Gene Co-expression Analysis in Human Brain Tissue
We queried the Coexpedia database (https://www.coexpedia.org/), a database for studying gene co-expression in mice and humans, to evaluate the co-expression network of KCNJ15 for genes with co-expression scores greater than 1 with KCNJ15 in the brain. This database was supported by the National Research Foundation of Korea.
Protein–Protein Interaction Analysis
PPI networks can be used to develop new drugs and discover novel drug targets. To explore the association between KCNJ15 and epilepsy drug therapy, we identified 115 genes (Table 1) targeted by approved antiepileptic drugs from two databases, Therapeutic Target Database 2020 and DrugBank 5.0 [15, 16]. These drug databases include molecular information about drugs, as well as their mechanisms, interactions, and targets. The PPI analysis was conducted using the STRING database (https://string-db.org/cgi/input.pl) [17]. Finally, the PPI network was built using Cytoscape software [18].
Results
Differentially Expressed Genes Identified in Human Brain Tissue
On the basis of the DEG analysis, KCNJ15 was identified as differentially expressed in one microarray data set (GSE6834). As shown in the volcano plot (Fig. 1), the results showed that the expression level of KCNJ15 in epileptic temporal lobe brain tissue was significantly downregulated compared with that in controls (adjusted P = 0.0146 and log2 Fold change = − 1.0025) (Table 2).
Expression Quantitative Trait Locus Analysis in Human Brain Tissue
eQTL analysis in the BRAINEAC database indicated that rs2833098 is associated with KCNJ15 expression level in human temporal lobe brain tissue (P = 0.0036), providing evidence that this polymorphism is involved in modifying KCNJ15 expression in human temporal lobe brain tissue. Specifically, the AA genotype is associated with downregulated KCNJ15 expression compared with that of the GG and GA genotypes in the human temporal lobe (Fig. 2).
Gene Co-expression Analysis in Human Brain Tissue
As shown in the co-expression network map (Fig. 3), the genes with co-expression scores greater than 1 with KCNJ15 in brain tissue are A1CF, RABAC1, CYP2A6, SIGLEC6, and CRHR2. Thus, these genes are likely to be functionally associated with KCNJ15.
Protein–Protein Interaction Analysis
PPI analysis was performed for 115 genes targeted by epilepsy drugs and KCNJ15. The PPI network indicated that the protein encoded by KCNJ15 directly interacts with two epilepsy drug targets encoded by GABBR1 and GABBR2 (Fig. 4). GABBR1 is the target of vigabatrin and gabapentin, and GABBR2 is the target of gabapentin.
Discussion
Although genetic factors play a vital role in the pathogenesis of epilepsy [19], the genetic association between polymorphisms of KCNJ15 and epilepsy has not yet been evaluated. Here, we conducted an association study to explore the role of KCNJ15 in contributing genetic risk to epilepsy. By an integrative analysis with data on KCNJ15 expression, eQTLs, gene co-expression, and PPI, we hypothesize that KCNJ15 has an active role in epilepsy. To our knowledge, this is the first report evaluating the genetic association of KCNJ15 with epilepsy.
In this study, KCNJ15 was highly downregulated in the temporal brain tissue of drug-resistant mesial temporal lobe patients with epilepsy (Fig. 1), suggesting an important role of KCNJ15 in epilepsy. KCNJ15 encodes the ATP-sensitive inward rectifier potassium channel 15, which is involved in the activation of microglia [20, 21]. Previous studies indicated that epilepsy is linked to microglial activation [22, 23]. There may be various mechanisms by which glia are involved in the pathogenesis of epilepsy. However, the major mechanisms include increased excitability and inflammation [24]. Furthermore, the transcript level of KCNJ15 has been positively associated with Alzheimer’s disease [13], and epilepsy and Alzheimer’s disease may share similar pathogenic mechanisms [25], further suggesting a role of KCNJ15 in epilepsy.
We also explored the association between single nucleotide polymorphisms (SNPs) that have been reported to be associated with epilepsy and KCNJ15 expression in human temporal lobe brain tissue. Rs2833098, which is located in a noncoding region, was previously associated with the risk of epilepsy in a genome-wide meta-analysis [14]. Additionally, eQTL analysis showed that the AA genotype of rs2833098 is associated with decreased KCNJ15 mRNA level in human temporal lobe brain tissue (Fig. 2). SNPs in non-coding regions often confer risk of disease by regulating the expression of their target genes [26]. Furthermore, we also found that KCNJ15 was significantly downregulated in the temporal lobe brain tissue of patients with epilepsy. Therefore, we speculate that rs2833098 may be a marker of epilepsy risk by regulating the expression level of KCNJ15 in human temporal lobe brain tissue.
Gene co-expression networks can be used to identify regulatory genes [27]. Gene expression and regulation are highly tissue-specific, and most disease-related genes have different expression levels in different tissues [28, 29]. Gene co-expression analysis revealed that KCNJ15 is co-expressed with multiple genes, including A1CF, RABAC1, CYP2A6, SIGLEC6, and CRHR2, in human brain tissue (Fig. 3), suggesting that these genes are functionally associated. Previous studies have identified that CYP2A6 is associated with the efficacy of antiepileptic drug treatment in patients with epilepsy [30, 31], so we speculate that CYP2A6 may play an important role in epilepsy, and KCNJ15 may be a candidate target for epilepsy treatment. However, CYP2A6 has many substrates and interactors, not only antiepileptic drugs, so the role of KCNJ15 in epilepsy still needs further verification.
Considering the limitations of current therapeutic strategies, it is necessary to discover new targets for epilepsy treatment. Understanding the association between genes and drug targets will facilitate the translation of clinical utility in the future. The PPI network is an effective tool to discover drug targets and drugs [32]. Our study demonstrated that KCNJ15 is more likely to interact with targets of approved epilepsy drugs, including GABBR1 and GABBR2 (Fig. 4), indicating that these proteins may be functionally associated. By querying the DrugBank database and the Therapeutic Target Database, we found that GABBR1 is the target of vigabatrin and gabapentin, and GABBR2 is the target of gabapentin, further supporting a role of KCNJ15 in epilepsy.
Although no patients with epileptic syndrome with de novo mutations in this gene have yet been found, we found that a SNP associated with the risk of epilepsy is associated with the expression level of KCNJ15 in brain tissue. Therefore, we speculate that KCNJ15 may not affect the risk of epilepsy through mutations in the amino acid sequence, but through altered expression level in human brain tissue, thereby affecting the risk of epilepsy. Therefore, this study may contribute to the discovery of new targets for epilepsy treatment. However, this is a future prospect that requires further in-depth studies. Knockdown or overexpression of the gene in epilepsy animal models can help to further validate the role of the gene in epilepsy, and epilepsy pharmacogenomics can help translate genetic findings into clinical treatment.
Although we identified KCNJ15 as a potential biological target by integrative analysis, some limitations of our study should be acknowledged. First, the sample size of the temporal lobe brain tissue samples in our study is relatively small. Second, we did not validate our conclusions with animal models, so more investigations are necessary to confirm our findings. Third, the association of KCNJ15 with epilepsy has not been evaluated by other studies, so it is important to validate our results in different populations.
Conclusions
Our study suggests that KCNJ15 may be a potential therapeutic target for epilepsy. Additional functional analysis of KCNJ15 may provide novel insights for epilepsy treatment.
References
Shorvon SD. Epidemiology, classification, natural history, and genetics of epilepsy. Lancet. 1990;336:93–6.
Brodie MJ, Barry SJE, Bamagous GA, Norrie JD, Kwan P. Patterns of treatment response in newly diagnosed epilepsy. Neurology. 2012;78:1548–54.
Picot MC, Baldy-Moulinier M, Daurès JP, Dujols P, Crespel A. The prevalence of epilepsy and pharmacoresistant epilepsy in adults: a population-based study in a Western European country. Epilepsia. 2008;49:1230–8.
Fisher RS, Vickrey BG, Gibson P, et al. The impact of epilepsy from the patient’s perspective II: views about therapy and health care. Epilepsy Res. 2000;41:53–61.
Eddy CM, Rickards HE, Cavanna AE. The cognitive impact of antiepileptic drugs. Ther Adv Neurol Disorder. 2011;4:385–407.
Duncan JS, Sander JW, Sisodiya SM, Walker MC. Adult epilepsy. Lancet. 2006;367:1087–100.
Perry MS, Duchowny M. Surgical versus medical treatment for refractory epilepsy: outcomes beyond seizure control. Epilepsia. 2013;54:2060–70.
Kullmann DM, Schorge S, Walker MC, Wykes RC. Gene therapy in epilepsy–is it time for clinical trials? Nat Rev Neurol. 2014;10:300–4.
Nikitin ES, Vinogradova LV. Potassium channels as prominent targets and tools for the treatment of epilepsy. Expert Opin Ther Targets. 2021;25:223–35.
Uhlén M, Fagerberg L, Hallström BM, et al. Proteomics: tissue-based map of the human proteome. Science. 2015;347:1260419.
Nakajima KI, Zhu K, Sun YH, et al. KCNJ15/Kir4.2 couples with polyamines to sense weak extracellular electric fields in galvanotaxis. Nat Commun. 2015;6:8532.
Bentley SR, Guella I, Sherman HE, et al. Hunting for familial Parkinson’s disease mutations in the post genome era. Genes (Basel). 2021;12:430.
Zhou X, Chen Y, Mok KY, et al. Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis. Proc Natl Acad Sci USA. 2018;115:1697–706.
International League Against Epilepsy Consortium on Complex Epilepsies. Genome-wide mega-analysis identifies 16 loci and highlights diverse biological mechanisms in the common epilepsies. Nat Commun. 2018;9:5269.
Wishart DS, Feunang YD, Guo AC, et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 2018;46:D1074–82.
Wang Y, Zhang S, Li F, et al. Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics. Nucleic Acids Res. 2020;48:D1031–41.
von Mering C, Huynen M, Jaeggi D, Schmidt S, Bork P, Snel B. STRING: a database of predicted functional associations between proteins. Nucleic Acids Res. 2003;31:258–61.
Su G, Morris JH, Demchak B, Bader GD. Biological network exploration with Cytoscape 3. Curr Protoc Bioinform. 2014;47:1–24.
Wang S, Zhou L, He C, et al. The association between STX1B polymorphisms and treatment response in patients with epilepsy. Front Pharmacol. 2021;12: 701575.
Wu SY, Chen YW, Tsai SF, et al. Estrogen ameliorates microglial activation by inhibiting the Kir2.1 inward-rectififier K(+) channel. Sci Rep. 2016;6:22864.
Di Lucente J, Nguyen HM, Wulff H, Jin LW, Maezawa I. The voltage-gated potassium channel Kv1.3 is required for microglial pro-inflammatory activation in vivo. Glia. 2018;66:1881–95.
Wyatt-Johnson SK, Brewster AL. Emerging roles for phagocytic microglial signaling in epilepsy. Epilepsy Curr. 2020;20:33–8.
Zhao XF, Liao Y, Alam MM, et al. Microglial mTOR is neuronal protective and antiepileptogenic in the pilocarpine model of temporal lobe epilepsy. J Neurosci. 2020;40:7593–608.
Devinsky O, Vezzani A, Najjar S, De Lanerolle NC, Rogawski MA. Glia and epilepsy: excitability and inflammation. Trends Neurosci. 2013;36:174–84.
Heinzen EL, Yoon W, Weale ME, et al. Alternative ion channel splicing in mesial temporal lobe epilepsy and Alzheimer’s disease. Genome Biol. 2007;8:R32.
Wang S, Zhang X, Zhou L, Wu Q, Han Y. Analysis of GABRG2 C588T polymorphism in genetic epilepsy and evaluation of GABRG2 in drug treatment. Clin Transl Sci. 2021;00:1–9.
van Dam S, Võsa U, van der Graaf A, Franke L, de Magalhães JP. Gene co-expression analysis for functional classification and gene–disease predictions. Brief Bioinform. 2018;19:575–92.
Goh KI, Cusick ME, Valle D, Childs B, Vidal M, Barabási AL. The human disease network. Proc Natl Acad Sci USA. 2007;104:8685–90.
Lage K, Hansen NT, Karlberg EO, et al. A large-scale analysis of tissue-specific pathology and gene expression of human disease genes and complexes. Proc Natl Acad Sci USA. 2008;105:20870–5.
Zhao M, Zhang T, Li G, Qiu F, Sun Y, Zhao L. Associations of CYP2C9 and CYP2A6 polymorphisms with the concentrations of valproate and its hepatotoxin metabolites and valproate-induced hepatotoxicity. Basic Clin Pharmacol Toxicol. 2017;121:138–43.
Yoon HY, Ahn MH, Yee J, Lee N, Han JM, Gwak HS. Influence of CYP2C9 and CYP2A6 on plasma concentrations of valproic acid: a meta-analysis. Eur J Clin Pharmacol. 2020;76:1053–8.
Chakraborty C, Doss CGP, Chen L, Zhu H. Evaluating protein-protein interaction (PPI) networks for diseases pathway, target discovery, and drug-design using ‘in silico pharmacology.’ Curr Protein Pept Sci. 2014;15:561–71.
Acknowledgements
Funding
No funding or sponsorship was received for this study or for the publication of this article. Lili Dai funded the journal's Rapid Service Fee.
Editorial Assistance
We thank International Science Editing for editing this manuscript. Shitao Wang funded this assistance
Authorship
All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published
Author Contributions
Xiangqian Ding, Lili Dai, Shitao Wang, and Mengen Zhang wrote the manuscript. Shitao Wang and Lili Dai designed the research. Shitao Wang, Lili Dai, and Zongyou Zhao performed the research. Hui Xu, Zongyou Zhao, and Lili Dai analyzed the data. Shitao Wang, Jinghong Lu, and Zongyou Li contributed analytical tools. All authors revised the manuscript and approved the final version to be published.
Disclosures
Shitao Wang, Zongyou Li, Xiangqian Ding, Zongyou Zhao, Mengen Zhang, Hui Xu, Jinghong Lu, and Lili Dai declare that they do not have any personal, financial, commercial, or academic conflicts of interest.
Compliance with Ethics Guidelines
This article is based on previously conducted studies and does not contain any new studies with human participants or animals performed by any of the authors.
Data Availability
The data sets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request .
Author information
Authors and Affiliations
Corresponding authors
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc/4.0/.
About this article
Cite this article
Wang, S., Li, Z., Ding, X. et al. Integrative Analyses Identify KCNJ15 as a Candidate Gene in Patients with Epilepsy. Neurol Ther 11, 1767–1776 (2022). https://doi.org/10.1007/s40120-022-00407-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40120-022-00407-y