Using common genetic variants to find drugs for common epilepsies.
Using common genetic variants to find drugs for common epilepsies.
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DOI：
10.1093/braincomms/fcab287
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发表时间：
2021
影响因子：
4.8
通讯作者：
International League Against Epilepsy Consortium on Complex Epilepsies
中科院分区：
文献类型：
--
作者：
Mirza N;Stevelink R;Taweel B;Koeleman BPC;Marson AG;International League Against Epilepsy Consortium on Complex Epilepsies
对于常见的癫痫病，需要更好的药物。药物再利用可以大大节省开发新疗法的时间和成本。为了选择最佳候选药物以重新用于疾病，期望预测药物将具有的对抗疾病的相对临床功效。常见的癫痫可分为不同的类型和综合征。不同的抗癫痫药物对不同类型和症状的常见癫痫最有效。为了使抗癫痫疗效预测具有临床可翻译性，预测必须针对每种常见癫痫，并反映临床研究和实践中观察到的药物疗效模式。先前发表的癫痫药物预测不符合这些要求。我们开发了一种新的方法来预测药物对任何常见癫痫的相对疗效，通过使用其全基因组关联研究汇总统计和药物的活性数据。我们的技术在方法上的进步是，疾病的药物预测是基于药物对蛋白质功能和丰度的影响，以及这些影响的大小和方向，相对于疾病中蛋白质失调的重要性，程度和方向。我们使用这种方法来预测所有药物的相对疗效，许可用于任何条件，对每一个主要类型和常见癫痫综合征。我们的预测与现实经验和随机临床试验的结果一致。我们的方法预测了现有抗癫痫药物对常见癫痫的疗效;在此预测中，我们的方法优于现有的最佳替代方法：受试者工作特征曲线下面积（平均值±标准差）分别为0.83 ± 0.03和0.63 ± 0.04。重要的是，我们的方法预测哪些抗癫痫药物在临床实践中更有效，哪些抗癫痫药物在临床实践中效果较差，对于常见癫痫的每种主要症状，它预测了不同常见癫痫临床试验中个别抗癫痫药物疗效的不同顺序。我们确定有前途的候选药物的每一个主要综合征的常见癫痫。我们在动物模型中筛选了五种有前景的预测药物：每种药物对癫痫发作都有显著的剂量依赖性作用。我们的预测是一种新的资源，用于选择合适的候选药物，这些药物可能被重新用于常见癫痫的每一种主要综合征。我们的方法有可能推广到其他复杂的疾病。Mirza等人开发并使用一种新的基因组方法来预测药物对常见癫痫的每种主要类型和综合征的相对疗效。这个数据集是一个新的和有价值的资源，用于选择最好的候选药物，以重新用于这些癫痫。
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. Mirza et al. develop and use a novel genomic method to predict the relative efficacy of drugs for each of the major types and syndromes of common epilepsy. This dataset is a novel and valuable resource for selecting the best candidate drug(s) to repurpose for these epilepsies.
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影响因子：
16.6
作者：
Cheng F;Desai RJ;Handy DE;Wang R;Schneeweiss S;Barabási AL;Loscalzo J
通讯作者：
Loscalzo J
DOI：
10.1056/nejmoa0902014
发表时间：
2010-03-04
期刊：
The New England journal of medicine
影响因子：
--
作者：
Glauser TA;Cnaan A;Shinnar S;Hirtz DG;Dlugos D;Masur D;Clark PO;Capparelli EV;Adamson PC;Childhood Absence Epilepsy Study Group
通讯作者：
Childhood Absence Epilepsy Study Group
影响因子：
46.9
作者：
Kamb, Alexander;Harper, Sean;Stefansson, Kari
通讯作者：
Stefansson, Kari
影响因子：
5.6
作者：
Baker, GA;Jacoby, A;Monnet, D
通讯作者：
Monnet, D
SCN1A周围常见的遗传变异相关的癫痫，海马硬化和发热性癫痫发作。
DOI：
10.1093/brain/awt233
发表时间：
2013-10
期刊：
Brain : a journal of neurology
影响因子：
--
作者：
Kasperaviciute D;Catarino CB;Matarin M;Leu C;Novy J;Tostevin A;Leal B;Hessel EV;Hallmann K;Hildebrand MS;Dahl HH;Ryten M;Trabzuni D;Ramasamy A;Alhusaini S;Doherty CP;Dorn T;Hansen J;Krämer G;Steinhoff BJ;Zumsteg D;Duncan S;Kälviäinen RK;Eriksson KJ;Kantanen AM;Pandolfo M;Gruber-Sedlmayr U;Schlachter K;Reinthaler EM;Stogmann E;Zimprich F;Théâtre E;Smith C;O'Brien TJ;Meng Tan K;Petrovski S;Robbiano A;Paravidino R;Zara F;Striano P;Sperling MR;Buono RJ;Hakonarson H;Chaves J;Costa PP;Silva BM;da Silva AM;de Graan PN;Koeleman BP;Becker A;Schoch S;von Lehe M;Reif PS;Rosenow F;Becker F;Weber Y;Lerche H;Rössler K;Buchfelder M;Hamer HM;Kobow K;Coras R;Blumcke I;Scheffer IE;Berkovic SF;Weale ME;UK Brain Expression Consortium;Delanty N;Depondt C;Cavalleri GL;Kunz WS;Sisodiya SM
通讯作者：
Sisodiya SM