Review of pharmacogenetics of antiseizure medications: focusing on genetic variants of mechanistic targets

Antiseizure medications (ASMs) play a central role in seizure management, however, unpredictability in the response to treatment persists, even among patients with similar seizure manifestations and clinical backgrounds. An objective biomarker capable of reliably predicting the response to ASMs woul...

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Bibliographic Details
Published in:Frontiers in pharmacology 2024-08, Vol.15, p.1411487
Main Authors: Lin, Chih-Hsiang, Ho, Chen-Jui, Chen, Shih-Ying, Lu, Yan-Ting, Tsai, Meng-Han
Format: Article
Language:English
Subjects:
antiseizure medication
drug-resistant epilepsy
genetic variants
mechanistic targets
pharmacogenetic studies
Pharmacology
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Summary:Antiseizure medications (ASMs) play a central role in seizure management, however, unpredictability in the response to treatment persists, even among patients with similar seizure manifestations and clinical backgrounds. An objective biomarker capable of reliably predicting the response to ASMs would profoundly impact epilepsy treatment. Presently, clinicians rely on a trial-and-error approach when selecting ASMs, a time-consuming process that can result in delays in receiving alternative non-pharmacological therapies such as a ketogenetic diet, epilepsy surgery, and neuromodulation therapies. Pharmacogenetic studies investigating the correlation between ASMs and genetic variants regarding their mechanistic targets offer promise in predicting the response to treatment. Sodium channel subunit genes have been extensively studied along with other ion channels and receptors as targets, however, the results have been conflicting, possibly due to methodological disparities including inconsistent definitions of drug response, variations in ASM combinations, and diversity of genetic variants/genes studied. Nonetheless, these studies underscore the potential effect of genetic variants on the mechanism of ASMs and consequently the prediction of treatment response. Recent advances in sequencing technology have led to the generation of large genetic datasets, which may be able to enhance the predictive accuracy of the response to ASMs.
ISSN:1663-9812
1663-9812
DOI:10.3389/fphar.2024.1411487