在预测功能丧失的病原性方面,REVEL比功能获取变体更好
Jasmin J Hopkins1, Matthew N Wakeling1, Matthew B Johnson1
1Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
Human mutation
|April 14, 2025
概括
用于变异性致病性的REVEL分数,在功能丧失与功能获取变异中表现不同. 功能增益变体不太可能达到高REVEL分数,影响其根据ACMG指南的分类.
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.
- 计算生物学 计算生物学
背景情况:
- 在形工具帮助变种的病原性评估.
- REVEL是错误的变种致病性的一种流行的元预测器.
- 之前的研究没有根据变异机制 (功能丧失与功能增加) 评估REVEL的性能.
研究的目的:
- 评估REVEL的性能是否在功能丧失 (LoF) 和功能增益 (GoF) 的误解变体中不同.
- 评估变异机制对REVEL分数解释在美国医学遗传学与基因组学学院 (ACMG) 准则中的影响.
主要方法:
- 使用了66个已确认的LoF和65个已确认的GoF变体的精选数据集.
- 分析了REVEL得分与已确定的致病率值 (0.5和0.75) 相比.
- 对比了符合ACMG值 (0.932) 的LoF和GoF变异的比例,以获得强有力的致病性证据.
主要成果:
- 几乎所有的LoF (98%) 和GoF (100%) 变种都达到0.5 REVEL病原性值.
- 两种LoF (89%) 和GoF (88%) 变种的高比例都超过了0.75的值.
- 与LoF变体相比 (55%) (P = 0.0352),相对较少的GoF变体 (35%) 达到0.932的强有力的证据值.
结论:
- 在LoF和GoF两种变体中,REVEL分数通常都很高.
- 功能获取变体不太可能达到根据ACMG指南要求的强有力的证据所需的最高REVEL分数.
- 这一发现对变种分类有影响,可能低估了GoF变种的致病性.
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