Endophenotype Research in Epilepsy Across Time

Background/Objectives: Endophenotypes-quantifiable biological markers bridging genetic variations and clinical manifestations-have significantly evolved since their introduction to psychiatric genetics. This study presents the first comprehensive analysis of endophenotype research in epilepsy, examining validation frameworks, methodological approaches, and the potential for clinical translation. Methods: We employed a dual-methodological approach combining the bibliometric analysis with a systematic review and a meta-analysis. Literature searches in the Web of Science and Scopus databases (17 July 2025) employed comprehensive strategies that incorporated endophenotype and epilepsy terminology. In the bibliometric analysis, the 'Bibliometrix' R package (version 4.4.3 (R Core Team, 2024) was used for publication trends, collaboration networks, and thematic evolution. The meta-analysis quantitatively synthesized validation outcomes across studies. For the systematic review, we compared traditional validation criteria with the Endophenotype 2.0 framework and applied machine learning-based validation techniques across 53 studies meeting rigorous inclusion criteria. Results: An analysis of 169 publications (2001-2025) revealed moderate annual growth (6.94%) with acceleration after 2015. Neuroimaging features achieved exceptional validation rates (77.8% perfect scores under Endophenotype 2.0), with functional MRI studies reaching 87.5% success. The Endophenotype 2.0 framework significantly outperformed traditional criteria (58.5% vs. 43.4%), particularly for genetic/molecular endophenotypes (83.3% vs. 0%). Family-based designs emerged as the strongest validation predictors (96% vs. 25% for population-based studies). International collaboration remained limited (4.1%). Conclusions: The endophenotype research in epilepsy has evolved toward validated biomarkers. The more comprehensive performance of the novel validation framework positions multiple endophenotypes-particularly neuroimaging and genetic markers-for the implementation of precision medicine. Our findings reveal opportunities for transdiagnostic biomarkers that could revolutionize risk assessment, early intervention, and personalized treatment across neurodevelopmental conditions.