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A catalogue of new incidence estimates of monogenic neurodevelopmental disorders caused by de novo variants.
Brain ( IF 14.5 ) Pub Date : 2020-04-01 , DOI: 10.1093/brain/awaa051
Javier A López-Rivera 1, 2, 3 , Eduardo Pérez-Palma 2, 4 , Joseph Symonds 5, 6 , Amanda S Lindy 7 , Dianalee A McKnight 7 , Costin Leu 2, 3 , Sameer Zuberi 5, 6 , Andreas Brunklaus 5, 6 , Rikke S Møller 8, 9 , Dennis Lal 1, 2, 3, 4, 10, 11
Affiliation  

A large fraction of rare and severe neurodevelopmental disorders are caused by sporadic de novo variants. Epidemiological disease estimates are not available for the vast majority of these de novo monogenic neurodevelopmental disorders because of phenotypic heterogeneity and the absence of large-scale genomic screens. Yet, knowledge of disease incidence is important for clinicians and researchers to guide health policy planning. Here, we adjusted a statistical method based on genetic data to predict, for the first time, the incidences of 101 known de novo variant-associated neurodevelopmental disorders as well as 3106 putative monogenic disorders. Two corroboration analyses supported the validity of the calculated estimates. First, greater predicted gene-disorder incidences positively correlated with larger numbers of pathogenic variants collected from patient variant databases (Kendall's τ = 0.093, P-value = 6.9 × 10-6). Second, for six of seven (86%) de novo variant associated monogenic disorders for which epidemiological estimates were available (SCN1A, SLC2A1, SALL1, TBX5, KCNQ2, and CDKL5), the predicted incidence estimates matched the reported estimates. We conclude that in the absence of epidemiological data, our catalogue of 3207 incidence estimates for disorders caused by de novo variants can guide patient advocacy groups, clinicians, researchers, and policymakers in strategic decision-making.

中文翻译:

新发变异引起的单基因神经发育障碍的新发病率估计目录。

很大一部分罕见和严重的神经发育障碍是由散发的新生变异引起的。由于表型异质性和缺乏大规模基因组筛选,无法对绝大多数这些新发单基因神经发育障碍进行流行病学估计。然而,疾病发病率的知识对于临床医生和研究人员指导卫生政策规划很重要。在这里,我们调整了一种基于遗传数据的统计方法,首次预测了 101 种已知的新发变异相关神经发育障碍以及 3106 种假定的单基因疾病的发病率。两个确证分析支持计算估计的有效性。第一的,更大的预测基因疾病发生率与从患者变异数据库中收集到的更多致病变异呈正相关(Kendall's τ = 0.093,P 值 = 6.9 × 10-6)。其次,对于可获得流行病学估计值的 7 种新发变异相关单基因疾病中的 6 种(SCN1A、SLC2A1、SALL1、TBX5、KCNQ2 和 CDKL5),预测的发病率估计值与报告的估计值相符。我们的结论是,在缺乏流行病学数据的情况下,我们对新发变异引起的疾病的 3207 种发病率估计目录可以指导患者权益团体、临床医生、研究人员和政策制定者进行战略决策。对于可获得流行病学估计值的七种 (86%) 新发变异相关单基因疾病中的六种(SCN1A、SLC2A1、SALL1、TBX5、KCNQ2 和 CDKL5),预测的发病率估计值与报告的估计值相符。我们的结论是,在缺乏流行病学数据的情况下,我们对新发变异引起的疾病的 3207 种发病率估计目录可以指导患者权益团体、临床医生、研究人员和政策制定者进行战略决策。对于可获得流行病学估计值的七种 (86%) 新发变异相关单基因疾病中的六种(SCN1A、SLC2A1、SALL1、TBX5、KCNQ2 和 CDKL5),预测的发病率估计值与报告的估计值相符。我们的结论是,在缺乏流行病学数据的情况下,我们对新发变异引起的疾病的 3207 种发病率估计目录可以指导患者权益团体、临床医生、研究人员和政策制定者进行战略决策。
更新日期:2020-04-21
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