Abstract
Temporal lobe epilepsy (TLE) is the most prevalent type of focal epilepsy. Recent developments in sequencing, proteomics and network analysis tools provide new avenues for investigating potential molecular therapeutic targets. Both the TGF-β/SMAD signaling pathways and subsets of microRNAs (including miR-21a-5p, miR-142a-5p, and miR-10a-5p) have been shown to be altered in several preclinical models of epilepsy and were mathematically modeled in this study. Using prior systems-based findings, a changeover between ‘seizure’ and ‘anti-seizure’ cellular states has been identified upon inhibition of microRNA activity achieved by the injection of antagomirs. Methods for seizure suppression were explored under various antagomir dosages as well as the regulatory effect of each microRNA in order to ascertain intracellular responses. Promising antagomir administration strategies were then identified, which may offer new avenues for seizure suppression.
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Data availability
The datasets analyzed in the current study are available as Supporting Information Datasets S01–S04 in https://doi.org/10.1073/pnas.1919313117.
References
Henshall, D. C. MicroRNA and epilepsy: profiling, functions and potential clinical applications. Curr. Opin. Neurol. 27, 199–205 (2014).
Tóth, K. et al. Hyperexcitability of the network contributes to synchronization processes in the human epileptic neocortex. J. Physiol. 596, 317–342 (2018).
Fisher, R. S. et al. Operational classification of seizure types by the international league against epilepsy: position paper of the ILAE Commission for Classification and Terminology. Epilepsia 58, 522–530 (2017).
Scheffer, I. E. et al. Ilae classification of the epilepsies: position paper of the ILAE Commission for Classification and Terminology. Epilepsia 58, 512–521 (2017).
Chang, B. S. & Lowenstein, D. H. Epilepsy. N. Engl. J. Med. 349, 1257–1266 (2003).
Wang, M. & Chen, Y. Inflammation: a network in the pathogenesis of status epilepticus. Front. Mol. Neurosci. 11, 341 (2018).
Schuele, S. U. & Lüders, H. O. Intractable epilepsy: management and therapeutic alternatives. Lancet. Neurol. 7, 514–524 (2008).
Blumcke, I. et al. Histopathological findings in brain tissue obtained during epilepsy surgery. N. Engl. J. Med. 377, 1648–1656 (2017).
Pitkänen, A. & Lukasiuk, K. Mechanisms of epileptogenesis and potential treatment targets. Lancet. Neurol. 10, 173–186 (2011).
Devinsky, O. et al. Epilepsy. Nat. Rev. Dis. Primers. 4, 18024 (2018).
Kwan, P., Schachter, S. C. & Brodie, M. J. Drug-resistant epilepsy. N. Engl. J. Med. 365, 919–926 (2011).
McKnight, K. et al. Serum antibodies in epilepsy and seizure-associated disorders. Neurology 65, 1730–1736 (2005).
Stockwell, J., Abdi, N., Lu, X., Maheshwari, O. & Taghibiglou, C. Novel central nervous system drug delivery systems. Chem. Biol. Drug Des. 83, 507–520 (2014).
Tajes, M. et al. The blood-brain barrier: structure, function, and therapeutic approaches to cross it. Mol. Membr. Biol. 31, 152–167 (2014).
Alam, M. I. et al. Strategy for effective brain drug delivery. Eur. J. Pharm. Sci. 40, 385–403 (2010).
Gorter, J. A. et al. Potential new antiepileptogenic targets indicated by microarray analysis in a rat model for temporal lobe epilepsy. J. Neurosci. 26, 11083–11110 (2006).
McClelland, S. et al. The transcription factor NRSF contributes to epileptogenesis by selective repression of a subset of target genes. eLife 3, e01267 (2014).
Johnson, M. R. et al. Systems genetics identifies sestrin 3 as a regulator of a proconvulsant gene network in human epileptic hippocampus. Nat. Commun. 6, 6031 (2015).
Srivastava, P. K. et al. A systems-level framework for drug discovery identifies CSF1R as an anti-epileptic drug target. Nat. Commun. 9, 3561 (2018).
Song, Y. J. et al. Temporal lobe epilepsy induces differential expression of hippocampal miRNAs including let-7e and mir-23a/b. Brain Res. 1387, 134–140 (2011).
Hu, K. et al. MicroRNA expression profile of the hippocampus in a rat model of temporal lobe epilepsy and mir-34a-targeted neuroprotection against hippocampal neurone cell apoptosis post-status epilepticus. BMC Neurosci. 13, 115 (2012).
Bot, A. M., Dȩbski, K. J. & Lukasiuk, K. Alterations in miRNA levels in the dentate gyrus in epileptic rats. PLoS ONE 8, e76051 (2013).
Gorter, J. A. et al. Hippocampal subregion-specific microRNA expression during epileptogenesis in experimental temporal lobe epilepsy. Neurobiol. Dis. 62, 508–520 (2013).
Henshall, D. C. et al. Micrornas in epilepsy: pathophysiology and clinical utility. Lancet Neurol. 15, 1368–1376 (2016).
Brennan, G. P. & Henshall, D. C. MicroRNAs in the pathophysiology of epilepsy. Neurosci. Lett. 667, 47–52 (2018).
Schirle, N. T. & MacRae, I. J. The crystal structure of human argonaute2. Science 336, 1037–1040 (2012).
Landgraf, P. et al. A mammalian microRNA expression atlas based on small RNA library sequencing. Cell 129, 1401–1414 (2007).
Raoof, R. M. Could Extracellular microRNAs Act as Novel Biomarkers of Temporal Lobe Epilepsy? Ph.D. thesis (Royal College of Surgeons in Ireland, 2017).
Uğurel, E. et al. Increased complexin-1 and decreased mir-185 expression levels in Behçet’s disease with and without neurological involvement. Neurol. Sci. 37, 411–416 (2016).
Fabian, M. R., Sonenberg, N. & Filipowicz, W. Regulation of mRNA translation and stability by microRNAs. Annu. Rev. Biochem. 79, 351–379 (2010).
Christensen, M. & Schratt, G. M. microRNA involvement in developmental and functional aspects of the nervous system and in neurological diseases. Neurosci. Lett. 466, 55–62 (2009).
Gupta, P. et al. miRNAs in alzheimer disease—a therapeutic perspective. Curr. Alzheimer. Res. 14, 1198–1206 (2017).
Emamzadeh, F. N. & Surguchov, A. Parkinson’s disease: biomarkers, treatment, and risk factors. Front. Neurosci. 12, 612 (2018).
Goh, S. Y., Chao, Y. X., Dheen, S. T., Tan, E. K. & Tay, S. S. W. Role of microRNAs in parkinson’s disease. Int. J. Mol. Sci. 20, 5649 (2019).
Takousis, P. et al. Differential expression of microRNAs in alzheimer’s disease brain, blood, and cerebrospinal fluid. Alzheimers Dement. 15, 1468–1477 (2019).
Si, W. et al. Methyltransferase 3 mediated miRNA m6a methylation promotes stress granule formation in the early stage of acute ischemic stroke. Front. Mol. Neurosci. 13, 103 (2020).
Venø, M. T. et al. A systems approach delivers a functional microRNA catalog and expanded targets for seizure suppression in temporal lobe epilepsy. Proc. Natl Acad. Sci. USA 117, 15977–15988 (2020).
Rupaimoole, R. & Slack, F. J. Microrna therapeutics: towards a new era for the management of cancer and other diseases. Nat. Rev. Drug Discov. 16, 203–222 (2017).
Betel, D., Koppal, A., Agius, P., Sander, C. & Leslie, C. Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites. Genome Biol. 11, R90 (2010).
Garzon, R., Marcucci, G. & Croce, C. M. Targeting microRNAs in cancer: rationale, strategies and challenges. Nat. Rev. Drug Discov. 9, 775–789 (2010).
Bhalala, O. G., Srikanth, M. & Kessler, J. A. The emerging roles of microRNAs in CNS injuries. Nat. Rev. Neurol. 9, 328–339 (2013).
Brown, B. D. & Naldini, L. Exploiting and antagonizing microRNA regulation for therapeutic and experimental applications. Nat. Rev. Genet. 10, 578–585 (2009).
van Rooij, E. & Kauppinen, S. Development of microRNA therapeutics is coming of age. EMBO Mol. Med. 6, 851–864 (2014).
Henshall, D. C. Manipulating microRNAs in murine models: targeting the multi-targeting in epilepsy. Epilepsy Curr. 17, 43–47 (2017).
Jimenez-Mateos, E. M. et al. Silencing microRNA-134 produces neuroprotective and prolonged seizure-suppressive effects. Nat. Med. 18, 1087–1094 (2012).
Sano, T. et al. Microrna-34a upregulation during seizure-induced neuronal death. Cell Death Dis. 3, e287 (2012).
Jimenez-Mateos, E. M. et al. miRNA expression profile after status epilepticus and hippocampal neuroprotection by targeting miR-132. Am. J. Pathol. 179, 2519–2532 (2011).
McKiernan, R. C. et al. Expression profiling the microRNA response to epileptic preconditioning identifies mir-184 as a modulator of seizure-induced neuronal death. Exp. Neurol. 237, 346–354 (2012).
Tang, C. et al. Targeting of microRNA-21-5p protects against seizure damage in a kainic acid-induced status epilepticus model via PTEN-mTOR. Epilepsy Res. 144, 34–42 (2018).
De Benedittis, S. et al. Circulating microRNA: the potential novel diagnostic biomarkers to predict drug resistance in temporal lobe epilepsy, a pilot study. Int. J. Mol. Sci. 22, 702 (2021).
Zhang, S., Yu, N. & Arce, R. M. Periodontal inflammation: integrating genes and dysbiosis. Periodontology 2000 82, 129–142 (2020).
Xiao, D. et al. Mechanisms of microRNA-142 in mitochondrial autophagy and hippocampal damage in a rat model of epilepsy. Int. J. Mol. Sci. 47, 98 (2021).
Papagiannakopoulos, T., Shapiro, A. & Kosik, K. S. Microrna-21 targets a network of key tumor-suppressive pathways in glioblastoma cells. Cancer Res. 68, 8164–8172 (2008).
Srivastava, A., Dixit, A. B., Banerjee, J., Tripathi, M. & Sarat Chandra, P. Role of inflammation and its miRNA based regulation in epilepsy: implications for therapy. Clin. Chim. Acta. 452, 1–9 (2016).
Plata-Salamán, C. R. et al. Kindling modulates the il-β system, TNF-alpha, TGF-β1, and neuropeptide mRNAs in specific brain regions. Brain Res. Mol. Brain Res. 75, 248–258 (2000).
Aronica, E. et al. Upregulation of metabotropic glutamate receptor subtype mGlur3 and mGlur5 in reactive astrocytes in a rat model of mesial temporal lobe epilepsy. Eur. J. Neurosci. 12, 2333–2344 (2000).
Szelényi, J. Cytokines and the central nervous system. Brain Res. Bull. 54, 329–338 (2001).
Shi, Y. & Massagué, J. Mechanisms of tgf-β signaling from cell membrane to the nucleus. Cell 113, 685–700 (2003).
Weinand, M. E. A mathematical model of internal time processing in temporal lobe epilepsy. Med. Hypotheses 56, 134–136 (2001).
Batulin, D., Lagzi, F., Vezzani, A., Jedlicka, P. & Triesch, J. A mathematical model of neuroimmune interactions in epileptogenesis for discovering treatment strategies. iScience 25, 104343 (2022).
Morshed, A., Dutta, P. & Dillon, R. H. Mathematical modeling and numerical simulation of the tgf-β/smad signaling pathway in tumor microenvironments. Appl. Numer. Math. 133, 41–51 (2018).
Liu, J., Dai, W. & Hahn, J. Mathematical modeling and analysis of crosstalk between MAPK pathway and SMAD-dependent tgf-β signal transduction. Processes 2, 570–595 (2014).
Marino, S., Hogue, I. B., Ray, C. J. & Kirschner, D. E. A methodology for performing global uncertainty and sensitivity analysis in systems biology. J. Theor. Biol. 254, 178–196 (2008).
Kim, Y. & Roh, S. A hybrid model for cell proliferation and migration in glioblastoma. Discrete Continuous Dyn. Syst. Ser. B 18, 969–1015 (2013).
Kim, Y., Kang, H. & Lawler, S. The role of the miR-451-AMPK signaling pathway in regulation of cell migration and proliferation in glioblastoma. In Mathematical Models of Tumor-Immune System Dynamics, Vol. 107, 125–155 (2014).
Acknowledgements
This work was supported by the European Union’s EU-FET Open H202 PRIME Project under Grant Agreement No. 964712. This publication has emanated from research conducted with the financial support of Taighde Éireann – Research Ireland, under Grant Number 21/RC/10294_P2 at FutureNeuro Research Ireland Centre for Translational Brain Science.
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K.J.A.P. conceptualized the study, formulated the model, performed model simulations, generated the figures, and drafted the paper. A.K. assisted in conceptualizing the model and interpreting the results. D.P.M., J.H.M.P., and D.K. provided management, supervision, and recommendations to improve the content of the paper. All authors have contributed to the writing of the paper, and all have reviewed the submitted final version.
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Pumares, K.J.A., Martins, D.P., Khalil, A. et al. Modeling the microRNA regulation of TGF-β/SMAD signaling pathways for seizure control in temporal lobe epilepsy. npj Syst Biol Appl (2026). https://doi.org/10.1038/s41540-025-00643-6
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DOI: https://doi.org/10.1038/s41540-025-00643-6
