Colin Estelle, Duffourd Yannis, Chevarin Martin, Tisserant Emilie, Verdez Simon, Paccaud Julien, Bruel Ange-Line, Tran Mau-Them Frédéric, Denommé-Pichon Anne-Sophie, Thevenon Julien, Safraou Hana, Besnard Thomas, Goldenberg Alice, Cogné Benjamin, Isidor Bertrand, Delanne Julian, Sorlin Arthur, Moutton Sébastien, Fradin Mélanie, Dubourg Christèle, Gorce Magali, Bonneau Dominique, El Chehadeh Salima, Debray François-Guillaume, Doco-Fenzy Martine, Uguen Kevin, Chatron Nicolas, Aral Bernard, Marle Nathalie, Kuentz Paul, Boland Anne, Olaso Robert, Deleuze Jean-François, Sanlaville Damien, Callier Patrick, Philippe Christophe, Thauvin-Robinet Christel, Faivre Laurence, Vitobello Antonio
UFR Des Sciences de Santé, INSERM-Université de Bourgogne UMR1231 GAD "Génétique des Anomalies du Développement", FHUTRANSLAD, Dijon, France.
Service de Génétique Médicale, CHU d'Angers, Angers, France.
Front Cell Dev Biol. 2023 Feb 28;11:1021920. doi: 10.3389/fcell.2023.1021920. eCollection 2023.
Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches. In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%-9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%-6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis. SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization. Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.
多组学为诊断实验室提供了有价值且日益普及的技术,这些实验室正在寻求潜在的二线策略来帮助患有未确诊罕见病的患者,尤其是临床诊断为罕见OMIM(《人类孟德尔遗传在线》)疾病的患者。然而,对于标准方法检测结果为阴性后应采用的最佳诊断护理途径,目前尚无共识。在15例临床诊断为可识别的OMIM疾病但一线基因检测结果为阴性或不确定的未确诊个体中,我们探索了使用几种新型组学技术的多步骤方法来建立分子诊断的效用。纳入标准包括临床常染色体隐性疾病诊断以及一线分析在感兴趣基因中鉴定出的单杂合致病变体(60%,即15例中的9例),或临床诊断为X连锁隐性或常染色体显性疾病但未鉴定出致病变体(40%,即15例中的6例)。我们进行了多步骤分析,包括短读长基因组测序(srGS)以及根据GS分析结果选择的互补方法,如mRNA测序(mRNA-seq)、长读长基因组测序(lrG)或光学基因组图谱分析(oGM)。单独的srGS或与其他基因组和/或转录组技术结合使用,使我们能够通过识别一线靶向检测遗漏的单核苷酸变体/插入缺失、识别影响转录的变体或有时需要lrGS或oGM来表征的结构变体,解决87%个体的问题。假设驱动的组合组学技术实施在识别分子病因方面特别有效。在本研究中,我们详细介绍了在一组先前经过调查、具有典型临床诊断但无分子病因的患者中实施基因组学和转录组学技术的经验。