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追踪临床数据库中的更新可提高变异重新分析的效率。

Tracking updates in clinical databases increases efficiency for variant reanalysis.

作者信息

Li Lele, Tian Xia, Woodzell Vaughan, Gibbs Richard A, Yuan Bo, Venner Eric

机构信息

The Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX.

Codified Genomics, Houston, TX.

出版信息

Genet Med Open. 2024 Mar 19;2:101841. doi: 10.1016/j.gimo.2024.101841. eCollection 2024.

Abstract

PURPOSE

Variant interpretation, guided by American College of Medical Genetics and Genomics guidelines, can inform clinical decision-making. However, interpretations may change over time for a variety of reasons. Periodic reanalysis of previous variant interpretations is important to ensure that reported genetic findings remain accurate according to current knowledge.

METHODS

We performed automated filtering by comparing ClinVar variants available in August 2020 with those from August 2021 to screen for potential reanalysis candidates from 3 projects. These variants were subsequently interpreted based on the American College of Medical Genetics and Genomics/Association for Molecular Pathology variant interpretation guideline or ClinGen revised gene-specific guidelines if applicable.

RESULTS

Our method annotated 241 unique variants requiring reanalysis, from 3 projects containing 3,832,210 previously interpreted variants, including those filtered automatically. Among these 241 variants, 43 variants changed interpretation, including 55.81% ( = 24) with upgraded and 44.19% ( = 19) with downgraded classifications. An efficiency study showed that our strategy increased the reanalysis efficiency and saved reviewing time.

CONCLUSION

We demonstrated an effective high-throughput method, initiating from external data updates, to achieve variant reanalysis in a clinical laboratory. This filtering method reduced the number of variants that need to be reanalyzed, screened potential variants, and saved time and cost for clinical laboratories.

摘要

目的

在美国医学遗传学与基因组学学会指南的指导下进行变异解读,可为临床决策提供依据。然而,由于各种原因,解读可能会随时间而变化。定期重新分析先前的变异解读对于确保报告的基因发现根据当前知识保持准确至关重要。

方法

我们通过比较2020年8月和2021年8月可用的ClinVar变异,对来自3个项目的潜在重新分析候选者进行自动筛选。随后根据美国医学遗传学与基因组学学会/分子病理学协会变异解读指南或适用时的ClinGen修订的基因特异性指南对这些变异进行解读。

结果

我们的方法注释了241个需要重新分析的独特变异,这些变异来自3个项目,包含3,832,210个先前解读的变异,包括自动筛选的变异。在这241个变异中,43个变异的解读发生了变化,其中分类升级的占55.81%(n = 24),分类降级的占44.19%(n = 19)。一项效率研究表明,我们的策略提高了重新分析效率并节省了审查时间。

结论

我们展示了一种有效的高通量方法,从外部数据更新开始,在临床实验室中实现变异重新分析。这种筛选方法减少了需要重新分析的变异数量,筛选出潜在变异,并为临床实验室节省了时间和成本。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d098/11613846/4238db2cb5cc/gr1.jpg

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