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Time to move beyond genetics towards biomedical data-driven translational genomic research in severe paediatric epilepsies
European Journal of Paediatric Neurology ( IF 2.3 ) Pub Date : 2020-01-01 , DOI: 10.1016/j.ejpn.2019.12.001
Andreas Brunklaus 1 , Costin Leu 2 , Marie Gramm 3 , Eduardo Pérez-Palma 2 , Sumaiya Iqbal 4 , Dennis Lal 5
Affiliation  

By accumulating ever greater amounts of genomic data, scientists have identified >100 genes associated with Mendelian forms of epilepsy and neurodevelopmental disorders with seizures. For most of the identified genes a wide range of genetic variants have been identified and affected patients are clinically heterogeneous. It is not clear to which degree the clinical heterogeneity can be attributed to the disease causing variant alone. We need to improve our current understanding of biophysical effects of variants on protein function and the role of polygenic background in modifying the clinical representation. In addition, longitudinal clinical data need to be recorded using standardized methods and shared across research centers to build large virtual cohorts for each single gene disorder. Without large, comprehensive, longitudinal datasets, studying the interplay of environmental factors and genetic factors will be challenging. As a community, we must work together to set the foundation for biorepositories and the collection and sharing of 'big data' in order to allow genetic-phenotypic characterization of the epilepsies and to fully utilize the potential for drug discovery, and patient-specific tailored management.

中文翻译:

是时候从遗传学转向严重儿科癫痫的生物医学数据驱动的转化基因组研究了

通过积累越来越多的基因组数据,科学家们已经确定了 100 多个与孟德尔形式的癫痫和癫痫发作的神经发育障碍相关的基因。对于大多数确定的基因,已经确定了广泛的遗传变异,并且受影响的患者在临床上具有异质性。目前尚不清楚临床异质性在多大程度上可归因于单独的致病变异。我们需要提高我们目前对变异对蛋白质功能的生物物理影响的理解,以及多基因背景在改变临床表现中的作用。此外,需要使用标准化方法记录纵向临床数据并在研究中心之间共享,以便为每个单基因疾病建立大型虚拟队列。如果没有大型、全面、纵向的数据集,研究环境因素和遗传因素的相互作用将具有挑战性。作为一个社区,我们必须共同努力为生物储存库和“大数据”的收集和共享奠定基础,以便对癫痫进行基因表型表征,并充分利用药物发现的潜力,并针对特定患者量身定制管理。
更新日期:2020-01-01
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