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对扩展携带者筛查面板上的 176 个基因进行严重程度评估和分类。

Evaluation and classification of severity for 176 genes on an expanded carrier screening panel.

机构信息

Division of Medical Affairs, Myriad Women's Health, South San Francisco, CA, USA.

Department of Pediatric Genetics, Boston University School of Medicine, Boston, MA, USA.

出版信息

Prenat Diagn. 2020 Sep;40(10):1246-1257. doi: 10.1002/pd.5762. Epub 2020 Jun 16.

Abstract

BACKGROUND

Disease severity is important when considering genes for inclusion on reproductive expanded carrier screening (ECS) panels. We applied a validated and previously published algorithm that classifies diseases into four severity categories (mild, moderate, severe, and profound) to 176 genes screened by ECS. Disease traits defining severity categories in the algorithm were then mapped to four severity-related ECS panel design criteria cited by the American College of Obstetricians and Gynecologists (ACOG).

METHODS

Eight genetic counselors (GCs) and four medical geneticists (MDs) applied the severity algorithm to subsets of 176 genes. MDs and GCs then determined by group consensus how each of these disease traits mapped to ACOG severity criteria, enabling determination of the number of ACOG severity criteria met by each gene.

RESULTS

Upon consensus GC and MD application of the severity algorithm, 68 (39%) genes were classified as profound, 71 (40%) as severe, 36 (20%) as moderate, and one (1%) as mild. After mapping of disease traits to ACOG severity criteria, 170 out of 176 genes (96.6%) were found to meet at least one of the four criteria, 129 genes (73.3%) met at least two, 73 genes (41.5%) met at least three, and 17 genes (9.7%) met all four.

CONCLUSION

This study classified the severity of a large set of Mendelian genes by collaborative clinical expert application of a trait-based algorithm. Further, it operationalized difficult to interpret ACOG severity criteria via mapping of disease traits, thereby promoting consistency of ACOG criteria interpretation.

摘要

背景

在考虑将基因纳入生殖扩展携带者筛查 (ECS) 面板时,疾病严重程度很重要。我们应用了一种经过验证和先前发表的算法,将疾病分为四个严重程度类别(轻度、中度、重度和重度),对 ECS 筛选的 176 个基因进行分类。然后将算法中定义严重程度类别的疾病特征映射到美国妇产科医师学会 (ACOG) 引用的四个与严重程度相关的 ECS 面板设计标准。

方法

八名遗传咨询师 (GC) 和四名医学遗传学家 (MD) 将严重程度算法应用于 176 个基因的子集。然后,MD 和 GC 通过小组共识确定这些疾病特征中的每一个如何映射到 ACOG 严重程度标准,从而确定每个基因符合 ACOG 严重程度标准的数量。

结果

在共识 GC 和 MD 应用严重程度算法后,68 个(39%)基因被归类为重度,71 个(40%)为重度,36 个(20%)为中度,1 个(1%)为轻度。在将疾病特征映射到 ACOG 严重程度标准后,发现 176 个基因中的 170 个(96.6%)至少符合四个标准之一,129 个基因(73.3%)至少符合两个,73 个基因(41.5%)至少符合三个,17 个基因(9.7%)符合所有四个标准。

结论

本研究通过协作临床专家应用基于特征的算法对一组大型孟德尔基因进行了严重程度分类。此外,它通过疾病特征映射使难以解释的 ACOG 严重程度标准具有操作性,从而促进了 ACOG 标准解释的一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b88f/7540025/ce7ae3493a81/PD-40-1246-g001.jpg

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