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系统的基因-疾病关系(GDR)整理揭示了61种基因-疾病关联,并突出了其对基因检测的影响。

Systematic gene-disease relationship (GDR) curation unveils 61 gene-disease associations and highlights the impact on genetic testing.

作者信息

Zonic Emir, Ferreira Mariana, Pardo Luba M, Martini Javier, Rocha Maria Eugenia, Aanicai Ruxandra, Ordonez-Herrera Natalia, Saravanakumar Deepa, Almeida Ligia S, Fernandes Inês C, Gulati Nishtha, Mannepalli Sumanth, Hercegovac Amela, Al-Ali Ruslan, Pereira Catarina, Paknia Omid, Hladnik Uros, Bauer Peter, Pinto Basto Jorge, Bertoli-Avella Aida M

机构信息

CENTOGENE GmbH, Rostock, Germany.

University of Tuzla, Faculty of Natural Sciences and Mathematics, Bosnia and Herzegovina.

出版信息

Genet Med Open. 2023 Sep 9;1(1):100833. doi: 10.1016/j.gimo.2023.100833. eCollection 2023.

Abstract

PURPOSE

With this study, we aimed to explore the gene-disease relationship (GDR) evidence for 109 gene-disease pairs and the significance of a large Biodatabank for this classification.

METHODS

The Clinical Genome Resource (ClinGen) Clinical Validity Framework for evaluation of GDR was applied. Most of the assessed genes were without a phenotype entry in the Online Mendelian Inheritance in Man (OMIM) database. Our Biodatabank with genetic data from over 670,000 previously tested individuals, in addition to data available in literature and public databases, were used for gene curation.

RESULTS

We confirmed 61 GDR (Definitive: 4 genes, Strong: 22 genes, Moderate: 35 genes). For 84 of 109 gene-disease pairs, a higher score was reached when using data from our Biodatabank in addition to externally obtainable data. This increased the final level of classification in 21 of the genes. Over 400 patients received a genetic report with clinically relevant variants in these 61 genes.

CONCLUSION

Our results demonstrate the importance of careful assessment of gene clinical validity data, along with the use of genetic data repositories. Implementation of the ClinGen Clinical Validity Framework for assessment of GDR is relatively straightforward. We encourage diagnostic laboratories to implement such a system and contribute to closing the knowledge gap in genetic research and diagnostics.

摘要

目的

通过本研究,我们旨在探索109个基因-疾病对的基因-疾病关系(GDR)证据以及大型生物数据库在此分类中的意义。

方法

应用临床基因组资源(ClinGen)评估GDR的临床有效性框架。大多数评估的基因在《人类孟德尔遗传在线》(OMIM)数据库中没有表型条目。我们的生物数据库包含来自超过670,000名先前检测个体的遗传数据,此外还利用了文献和公共数据库中的数据进行基因整理。

结果

我们确认了61种GDR(确定:4个基因,强:22个基因,中等:35个基因)。对于109个基因-疾病对中的84个,除了外部可获得的数据外,使用我们生物数据库的数据时得分更高。这提高了21个基因的最终分类水平。超过400名患者收到了包含这61个基因中临床相关变异的遗传报告。

结论

我们的结果证明了仔细评估基因临床有效性数据以及使用遗传数据存储库的重要性。实施ClinGen临床有效性框架来评估GDR相对简单。我们鼓励诊断实验室实施这样的系统,并为缩小遗传研究和诊断中的知识差距做出贡献。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8e8d/11613557/74fdf67ee955/gr1.jpg

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