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Systematic validation of variants of unknown significance in APP, PSEN1 and PSEN2.
Neurobiology of Disease ( IF 5.1 ) Pub Date : 2020-02-19 , DOI: 10.1016/j.nbd.2020.104817
Simon Hsu 1 , Anna A Pimenova 2 , Kimberly Hayes 1 , Juan A Villa 1 , Matthew J Rosene 1 , Madhavi Jere 1 , Alison M Goate 2 , Celeste M Karch 1
Affiliation  

Alzheimer's disease (AD) is a neurodegenerative disease that is clinically characterized by progressive cognitive decline. More than 200 pathogenic mutations have been identified in amyloid-β precursor protein (APP), presenilin 1 (PSEN1) and presenilin 2 (PSEN2). Additionally, common and rare variants occur within APP, PSEN1, and PSEN2 that may be risk factors, protective factors, or benign, non-pathogenic polymorphisms. Yet, to date, no single study has carefully examined the effect of all of the variants of unknown significance reported in APP, PSEN1 and PSEN2 on Aβ isoform levels in vitro. In this study, we analyzed Aβ isoform levels by ELISA in a cell-based system in which each reported pathogenic and risk variant in APP, PSEN1, and PSEN2 was expressed individually. In order to classify variants for which limited family history data is available, we have implemented an algorithm for determining pathogenicity using available information from multiple domains, including genetic, bioinformatic, and in vitro analyses. We identified 90 variants of unknown significance and classified 19 as likely pathogenic mutations. We also propose that five variants are possibly protective. In defining a subset of these variants as pathogenic, individuals from these families may eligible to enroll in observational studies and clinical trials.

中文翻译:

APP、PSEN1 和 PSEN2 中意义不明的变异的系统验证。

阿尔茨海默病 (AD) 是一种神经退行性疾病,其临床特征是进行性认知能力下降。已在淀粉样蛋白 β 前体蛋白 (APP)、早老素 1 (PSEN1) 和早老素 2 (PSEN2) 中鉴定出 200 多种致病突变。此外,APP、PSEN1 和 PSEN2 中常见和罕见的变异可能是危险因素、保护因素或良性、非致病性多态性。然而,迄今为止,还没有一项研究仔细检查了 APP、PSEN1 和 PSEN2 中报告的所有未知意义的变异对体外 Aβ 同种型水平的影响。在这项研究中,我们通过 ELISA 在基于细胞的系统中分析了 Aβ 同种型水平,其中每个报告的 APP、PSEN1 和 PSEN2 中的致病性和风险变异都单独表达。为了对可用的家族史数据有限的变异进行分类,我们实施了一种算法,使用来自多个领域的可用信息来确定致病性,包括遗传、生物信息学和体外分析。我们确定了 90 个意义未知的变异,并将 19 个归类为可能的致病突变。我们还建议五个变体可能具有保护作用。在将这些变异的一个子集定义为致病性时,来自这些家族的个体可能有资格参加观察性研究和临床试验。我们还建议五个变体可能具有保护作用。在将这些变异的一个子集定义为致病性时,来自这些家族的个体可能有资格参加观察性研究和临床试验。我们还提出五个变体可能具有保护作用。在将这些变异的一个子集定义为致病性时,来自这些家族的个体可能有资格参加观察性研究和临床试验。
更新日期:2020-02-20
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