随着时间的推移,ClinVar和HGMD基因组变异分类的准确性得到了改进,这是通过隐含的疾病负担来衡量的
Andrew G Sharo1,2,3, Yangyun Zou4,5,6, Aashish N Adhikari4,5,7
1Biophysics Graduate Group, University of California, Berkeley, CA, 94720, USA. sharo@compbio.berkeley.edu.
Genome medicine
|July 13, 2023
概括
遗传数据库中的变异错误分类正在减少,但偏见仍然存在,特别是对于非洲祖先. 改进的指导方针和多样化的数据是准确基因变异解释的关键.
科学领域:
- 遗传学 是一个遗传学.
- 生物信息学是一种生物信息学.
- 临床基因组学 临床基因组学
背景情况:
- 遗传变异数据库对于临床和研究解释至关重要.
- 在这些数据库中存在错误分类的变体,随着时间的推移错误分类的趋势尚不清楚.
- 不断变化的指导方针对变体准确性的影响需要进行调查.
研究的目的:
- 评估6年来ClinVar和HGMD变异错误分类率的变化.
- 为了评估不同祖先群体的错误分类模式.
- 了解更新指南对变体准确性的影响.
主要方法:
- 使用了ClinVar和HGMD档案,跨越了6年的时间.
- 用代谢的先天性错误 (IEMs) 作为模型系统,因为它们的透和新生儿呈现.
- 使用1000个基因组项目 (1KGP) 的样本来识别可能错误分类的致病性基因型.
主要成果:
- 随着时间的推移,ClinVar和HGMD都显示了虚假阳性率的降低.
- 与ClinVar相比,1KGP中HGMD变种涉及的受影响个体明显更多.
- 在HGMD中有利于非洲基因组的祖先偏见通过根据新准则删除常见变异来减轻.
结论:
- 重归类趋势反映了对罕见遗传变异的更好理解.
- 变异分类准则和多样化的基因基因频率数据库对于准确的重新分类至关重要.
- 在欧洲和南亚人群中常见的ClinVar变异更容易被重新分类到较低的置信度水平.
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