Farmakogenetyka w leczeniu epilepsji w Azji
Pharmacogenomics in epilepsy care across Asia
W skrócie
Wybór leków przeciwpadaczkowych opiera się głównie na doświadczeniu lekarza, co prowadzi do zmiennej skuteczności i wielu niepożądanych działań. Badanie pokazuje, że analiza genetyczna pacjenta może pomóc w wyborze najlepszego leku dla konkretnej osoby, szczególnie w Azji gdzie istnieją specjalne warianty genetyczne związane z niebezpieczną reakcją na karbamazepinę i zaburzeniami metabolizmu leków. Chociaż takie testy genetyczne są ważne i mogą ratować zdrowie, wciąż nie są rutynowo stosowane wszędzie ze względu na różne dostępności testów, koszty i różnice między krajami.
Oryginalny abstract (angielski)
The selection of anti-seizure medications (ASMs) in epilepsy remains largely empirical, leading to varied efficacy and a significant burden of adverse drug reactions (ADRs). A pharmacogenomic-based strategy can be used to personalize ASM selection, as it incorporates genetic information into clinical decision-making. While more than 50 gene-drug associations have been reported in epilepsy, few pairs have strong, replicated evidence with clinical applicability. In Asia, key variants include HLA-B15:02 and HLA-A31:01, which are associated with severe cutaneous adverse reactions (SCARs), and CYP2C9 and CYP2C19 variants, which affect drug metabolism. These pairs have influenced regional regulatory policies, with HLA-B15:02 screening widely implemented prior to carbamazepine use. However, routine practice is still heterogenous due to variability in allele frequencies, healthcare infrastructure, and policy frameworks across countries. We propose evidence-based criteria for clinical implementation of pharmacogenomic markers, emphasizing replicated associations, clinical significance, actionable alternatives, and cost-effectiveness. Currently, HLA-B15:02 possesses the strongest evidence for mandatory screening, while others remain advisory due to limited outcome data. Real-world challenges include incomplete risk prediction from single-allele testing, overlapping drug hypersensitivity profiles, and workflow limitations, particularly in urgent care settings. In lower resource regions, test availability and access are additional hurdles to implementation. Future research should include multiethnic datasets, improved health-economic evaluations, and integration of genomic data into clinical decision-support systems. Advancing polygenic and multi-omics approaches could improve prediction of treatment response and toxicity.