School of Medicine, Institute of Human Genetics, Technical University of Munich, Munich, Germany.
Institute of Neurogenomics, Computational Health Center, Helmholtz Munich, Neuherberg, Germany.
J Inherit Metab Dis. 2023 Sep;46(5):824-838. doi: 10.1002/jimd.12663.
Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.
在过去的十年中，高通量 DNA 测序方法，即全外显子组和全基因组测序，已成为孟德尔疾病诊断的标准程序。这些技术的应用极大地促进了诊断，并将分析范式从变异识别转移到优先级和评估。诊断率因队列规模、异质性和疾病的不同而有很大差异，范围从 30%到 50%不等，导致大多数患者无法得到诊断。组学技术和计算分析的进步为增加这些不利的诊断率提供了机会，为疾病引起的变异验证和优先级提供了证据。本文旨在概述几种组学技术的当前应用，包括 RNA 测序、蛋白质组学、代谢组学和 DNA 甲基化分析，用于一般罕见遗传性疾病和特定的先天性代谢错误的诊断。
