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通过评估基因型和表型数据来发现线粒体DNA疾病:Solve-RD体验

Thiloka Ratnaike¹, Ida Paramonov², Catarina Olimpio³

¹Department of Paediatrics, University of Cambridge, Cambridge, UK; Department of Paediatrics, Colchester Hospital, East Suffolk and North Essex NHS Foundation Trust, Colchester, UK.

American journal of human genetics

|April 30, 2025

概括

我们开发了一种新的生物信息管道,以改善线粒体DNA (mtDNA) 疾病的诊断. 这种工作流成功地在以前未被诊断的罕见病患者中识别了致病性mtDNA变异,增加了诊断产量.

科学领域:

遗传学遗传学是一个
生物信息学是一种生物信息学.
罕见疾病罕见疾病

背景情况:

线粒体DNA (mtDNA) 疾病的诊断是具有挑战性的,因为生物信息学专注于核基因组.
下一代测序 (NGS) 数据分析往往忽略了mtDNA变异.

研究的目的:

开发和验证使用NGS数据评估mtDNA疾病的工作流程.
为了提高罕见疾病队伍中mtDNA疾病的诊断产量.

主要方法:

使用MToolBox开发和验证了一种半自动化生物信息管道.
过标准包括血中异质体水平 (≥1%) 和疾病相关性.
基于MitoPhen的表型相似性得分被用于变体优先级.

主要成果:

该管道分析了来自Solve-RD队列中的9,923个人的10,157个外基因组/基因组数据集.
在135个未被诊断的个体中,有136个罕见的mtDNA变异被优先考虑.
评分门>0.3确定了测试队列中92%的mtDNA疾病病例,导致34个诊断和额外的0.4%的诊断收益率.

结论:

开发的mtDNA分析管道有效地识别了各种NGS数据集中的致病性mtDNA变异.
这种工作流提高了线粒体DNA疾病的诊断产量,特别是在未解决的罕见疾病病例中.
该管道为发现以前归因于核变异的罕见疾病的遗传原因提供了显著的价值.

关键词:

解决问题-RDD 生物信息学是一种生物信息学.线粒体DNA是线粒体DNA的组成部分.现型相似性现型相似性重新分析重新分析

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