Evaluating genome sequencing strategies: trio, singleton, and standard testing in rare disease diagnosis

评估基因组测序策略:罕见病诊断中的三联体、单例和标准检测

阅读:1

Abstract

BACKGROUND: Short-read genome sequencing (GS) is among the most comprehensive genetic testing methods available, capable of detecting single-nucleotide variants, copy-number variants, mitochondrial variants, repeat expansions, and structural variants in a single assay. Despite its technical advantages, the full clinical utility of GS in real-world diagnostic settings remains to be fully established. METHODS: This study systematically compared singleton GS (sGS), trio GS (tGS), and exome sequencing-based standard-of-care (SoC) genetic testing in 416 patients with rare diseases in a blinded, prospective study. Three independent teams with divergent baseline expertise evaluated the diagnostic yield of GS as a unifying first-tier test and directly compared its variant detection capabilities, learning curve, and clinical feasibility. The SoC team had extensive prior experience in exome-based diagnostics, while the sGS and tGS teams were newly trained in GS interpretation. Diagnostic yield was assessed through both prospective and retrospective analyses. RESULTS: In our prospective analysis, tGS achieved the highest diagnostic yield for likely pathogenic/pathogenic variants at 36.1% in the newly trained team, surpassing the experienced SoC team at 35.1% and the newly trained sGS team at 28.8%. To evaluate which variants could technically be identified and account for differences in team experience, we conducted a retrospective analysis, achieving diagnostic yields of 36.7% for SoC, 39.1% for sGS, and 40.0% for tGS. The superior yield of GS was attributed to its ability to detect deep intronic, non-coding, and small copy-number variants missed by SoC. Notably, tGS identified three de novo variants classified as likely pathogenic based on recent GeneMatcher collaborations and newly published gene-disease association studies. CONCLUSIONS: Our findings demonstrate that GS, particularly tGS, outperforms SoC in diagnosing rare diseases, with sGS providing a more cost-effective alternative. These results suggest that GS should be considered a first-tier genetic test, offering an efficient, single-step approach to reduce the diagnostic odyssey for patients with rare diseases. The trio approach proved especially valuable for less experienced teams, as inheritance data facilitated variant interpretation and maintained high diagnostic yield, while experienced teams achieved comparable results with singleton analysis alone.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。