基于表型相似性的方法用于未解决的罕见疾病的变异优先级:初步方法报告
David Lagorce1, Emeline Lebreton2, Leslie Matalonga3
1INSERM, US14 - Orphanet, Plateforme Maladies Rares, 75014, Paris, France. david.lagorce@inserm.fr.
European journal of human genetics : EJHG
|November 5, 2023
概括
这项研究引入了一种使用表型相似性的新方法,以优先考虑罕见疾病 (RD) 的变异. 这种方法有助于诊断未被诊断的遗传疾病的患者,改善诊断时间表.
科学领域:
- 遗传学 是一个遗传学.
- 罕见疾病 罕见疾病
- 生物信息学是一种生物信息学.
背景情况:
- 罕见疾病 (RD) 存在诊断挑战,许多疾病的遗传起源,但未确定的致病基因.
- 在疑似遗传RD的患者中,不确定的外体/基因组测序结果是常见的.
- 解决 RD 项目旨在通过确定分子原因来诊断未被诊断的 RD.
研究的目的:
- 为未被诊断的罕见疾病开发和评估基于表型相似性的变异优先级方法.
- 为了提高对罕见疾病患者的外体/基因组测序的诊断产量.
- 为实现国际罕见病研究联盟 (IRDiRC) 的目标,即在一年内诊断罕见病,做出贡献.
主要方法:
- 开发了使用人类表型本体学 (HPO),孤儿网罕见病本体学 (ORDO) 和HPO-ORDO本体学模块 (HOOM) 的三个互补的表型相似性计算方法.
- 使用RD-Connect基因组-基因组分析平台 (GPAP) 进行基因组数据再分析.
- 将提交的病例与其他病例进行比较,并在Orphanet.com上进行已知的RD.
主要成果:
- 在通过相似性聚类分析的725个病例中,8.8%的病例中发现了感兴趣的变异 (致病性/可能致病性).
- 在42.1%的病例中验证了诊断假设.
- 需要对另外10.9%的病例进行进一步的探索.
结论:
- 基于表型相似性的变异优先级方法在诊断未诊断的罕见疾病方面显示出有前途.
- 该方法成功地确定了潜在的致病变体,并产生了经过验证的诊断假设.
- 一个基于表型的自动化,标准化的再分析管道正在开发中,用于更广泛的应用.
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