Systematic Collaborative Reanalysis of Genomic Data Improves Diagnostic Yield in Neurologic Rare Diseases

现象 外显子组 外显子组测序 遗传学 基因组 生物 罕见病 基因组学 计算生物学 疾病 拷贝数变化 1000基因组计划 生物信息学 表型 医学 基因 基因型 单核苷酸多态性 病理
作者
Gemma Bullich,Leslie Matalonga,Montserrat Pujadas,Anastasios Papakonstantinou,Davide Piscia,Raúl Tonda,Rafael Artuch,P. Gallano,Glòria Garrabou,Juan R. González,Daniel Grinberg,Míriam Guitart,Steven S. Laurie,Conxi Lázaro,Cristina Luengo,Ramón Martí,Montserrat Milà,David Ovelleiro,Genı́s Parra,Aurora Pujol,Eduardo F. Tizzano,Alfons Macaya,Francesc Palau,Antònia Ribes,Luis A. Pérez‐Jurado,Sergi Beltrán
出处
期刊:The Journal of Molecular Diagnostics [Elsevier BV]
卷期号:24 (5): 529-542 被引量:4
标识
DOI:10.1016/j.jmoldx.2022.02.003
摘要

Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%).
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