Using common genetic variants to find drugs for common epilepsies
Authors: Mirza Nasir , Stevelink Remi , Taweel Basel , Koeleman Bobby P C , Marson Anthony G ,   International League Against Epilepsy Consortium on Complex Epilepsies, Abou-Khalil Bassel , Auce Pauls , Avbersek Andreja , Bahlo Melanie , Balding David J , Bast Thomas , Baum Larry , Becker Albert J , Berghuis Felicitas Becker Bianca , Berkovic Samuel F , Boysen Katja E , Bradfield Jonathan P , Brody Lawrence C , Buono Russell J , Campbell Ellen , Cascino Gregory D , Catarino Claudia B , Cavalleri Gianpiero L , Cherny Stacey S , Chinthapalli Krishna , Coffey Alison J , Compston Alastair , Coppola Antonietta , Cossette Patrick , Craig John J , de Haan Gerrit-Jan , De Jonghe Peter , de Kovel Carolien G. F , Delanty Norman , Depondt Chantal , Devinsky Orrin , Dlugos Dennis J , Doherty Colin P , Elger Christian E , Eriksson Johan G , Ferraro Thomas N , Feucht Martha , Francis Ben , Franke Andre , French Jacqueline A , Freytag Saskia , Gaus Verena , Geller Eric B , Gieger Christian , Glauser Tracy , Glynn Simon , Goldstein David B , Gui Hongsheng , Guo Youling , Haas Kevin F , Hakonarson Hakon , Hallmann Kerstin , Haut Sheryl , Heinzen Erin L , Helbig Ingo , Hengsbach Christian , Hjalgrim Helle , Iacomino Michele , Ingason Andrés , Jamnadas-Khoda Jennifer , Johnson Michael R , Kälviäinen Reetta , Kantanen Anne-Mari , Kasperavičiūte Dalia , Trenite Dorothee Kasteleijn-Nolst , Kirsch Heidi E , Knowlton Robert C , Koeleman Bobby P. C , Krause Roland , Krenn Martin , Kunz Wolfram S , Kuzniecky Ruben , Kwan Patrick , Lal Dennis , Lau Yu-Lung , Lerche Holger , Leu Costin , Lieb Wolfgang , Lindhout Dick , Lo Warren D , Lopes-Cendes Iscia , Lowenstein Daniel H , Malovini Alberto , Marson Anthony G , Mayer Thomas , McCormack Mark , Mills James L , Mirza Nasir , Moerzinger Martina , Møller Rikke S , Molloy Anne M , Muhle Hiltrud , Newton Mark , Ng Ping-Wing , Nöthen Markus M , Nürnberg Peter , O’Brien Terence J , Oliver Karen L , Palotie Aarno , Pangilinan Faith , Peter Sarah , Petrovski Slavé , Poduri Annapurna , Privitera Michael , Radtke Rodney , Rau Sarah , Reif Philipp S , Reinthaler Eva M , Rosenow Felix , Sander Josemir W , Sander Thomas , Scattergood Theresa , Schachter Steven C , Schankin Christoph J , Scheffer Ingrid E , Schmitz Bettina , Schoch Susanne , Sham Pak C , Shih Jerry J , Sills Graeme J , Sisodiya Sanjay M , Slattery Lisa , Smith Alexander , Smith David F , Smith Michael C , Smith Philip E , Sonsma Anja C. M , Speed Doug , Sperling Michael R , Steinhoff Bernhard J , Stephani Ulrich , Stevelink Remi , Strauch Konstantin , Striano Pasquale , Stroink Hans , Surges Rainer , Tan K. Meng , Thio Liu Lin , Thomas G. Neil , Todaro Marian , Tozzi Rossana , Vari Maria S , Vining Eileen P. G , Visscher Frank , Spiczak Sarah von , Walley Nicole M , Weber Yvonne G , Wei Zhi , Weisenberg Judith , Whelan Christopher D , Widdess-Walsh Peter , Wolff Markus , Wolking Stefan , Yang Wanling , Zara Federico , Zimprich Fritz 
Published: December 2021

Better drugs are needed for common epilepsies. Drug repurposing offers the potential of significant savings in the time and cost of developing new treatments. In order to select the best candidate drug(s) to repurpose for a disease, it is desirable to predict the relative clinical efficacy that drugs will have against the disease. Common epilepsy can be divided into different types and syndromes. Different antiseizure medications are most effective for different types and syndromes of common epilepsy. For predictions of antiepileptic efficacy to be clinically translatable, it is essential that the predictions are specific to each form of common epilepsy, and reflect the patterns of drug efficacy observed in clinical studies and practice. These requirements are not fulfilled by previously published drug predictions for epilepsy. We developed a novel method for predicting the relative efficacy of drugs against any common epilepsy, by using its Genome-Wide Association Study summary statistics and drugs’ activity data. The methodological advancement in our technique is that the drug predictions for a disease are based upon drugs’ effects on the function and abundance of proteins, and the magnitude and direction of those effects, relative to the importance, degree and direction of the proteins’ dysregulation in the disease. We used this method to predict the relative efficacy of all drugs, licensed for any condition, against each of the major types and syndromes of common epilepsy. Our predictions are concordant with findings from real-world experience and randomized clinical trials. Our method predicts the efficacy of existing antiseizure medications against common epilepsies; in this prediction, our method outperforms the best alternative existing method: area under receiver operating characteristic curve (mean ± standard deviation) 0.83 ± 0.03 and 0.63 ± 0.04, respectively. Importantly, our method predicts which antiseizure medications are amongst the more efficacious in clinical practice, and which antiseizure medications are amongst the less efficacious in clinical practice, for each of the main syndromes of common epilepsy, and it predicts the distinct order of efficacy of individual antiseizure medications in clinical trials of different common epilepsies. We identify promising candidate drugs for each of the major syndromes of common epilepsy. We screen five promising predicted drugs in an animal model: each exerts a significant dose-dependent effect upon seizures. Our predictions are a novel resource for selecting suitable candidate drugs that could potentially be repurposed for each of the major syndromes of common epilepsy. Our method is potentially generalizable to other complex diseases.