Evaluating Genome Sequencing Strategies: Trio, Singleton, and Standard Testing in Rare Disease Diagnosis
Authors
Daniel Kaschta, Christina Post, Franziska Gaass, Bianca Greiten, Anna-Sophie Liegmann, Rebecca Gembicki, Jelena Pozojevic, Michelle Meyenborg, Janne Wehnert, Katharina Schau-Römer, Franka Rust, Maj-Britt Salewski, Kristin Schulz, Varun Sreenivasan, Saranya Balachandran, Kristian Händler, Veronica Yumiceba, Laelia Rösler, Andreas Dalski, Kirstin Hoff, Nadine Hornig, Juliane Köhler, Vincent Arriens, Caroline Utermann-Thüsing, Kimberly Roberts, Eva Maria Murga Penas, Christine Zühlke, Monika Kautza-Lucht, Maike Dittmar, Irina Hüning, Yorck Hellenbroich, Britta Hanker, Valerie Berge, Friederike Birgel, Philip Rosenstiel, Andre Franke, Janina Fuß, Britt-Sabina Löscher, Sören Franzenburg, Dzhoy Papingi, Amelie van der Ven, Sandra Wilson, Rixa Woitschach, Jasmin Lisfeld, Alexander Volk, Theresia Herget, Christian Schlein, Anna Möllring, Birga Hoffmann, Imke Poggenburg, Henning Nommels, Milad Al-Tawil, Gloria Herrmann, Andreas Recke, Louiza Toutouna, Olaf Hiort, Nils Margraf, Bettina Gehring, Hiltrud Muhle, Tobias Bäumer, Lana Harder, Alexander Münchau, Norbert Brüggemann, Inga Vater, Almuth Caliebe, Inga Nagel, Malte Spielmann
Year of publication
2024Journal
UKNVolume
-Issue
-Abstract
Purpose
Short-read genome sequencing (GS) is a comprehensive genetic testing method capable of detecting multiple variant types. Despite its technical advantages, systemic comparisons of singleton GS (sGS), trio GS (tGS), and exome sequencing-based standard-of-care (SoC) in real-world diagnostics remain limited.
Methods
We systematically compared sGS, tGS, and SoC genetic testing in 448 patients with rare diseases in a blinded, prospective study. Three independent teams evaluated the diagnostic yield, variant detection capabilities, and clinical feasibility of GS as a first-tier test. Diagnostic yield was assessed through both prospective and retrospective analyses.
Results
In prospective analyses, tGS achieved the highest diagnostic yield for likely pathogenic/pathogenic variants (36.8%) in a newly trained team, outperforming the experienced SoC team (36.0%) and the sGS team (30.4%). Retrospective analyses, accounting for technical variant detection and team experience differences, reported diagnostic yields of 38.6% for SoC, 41.3% for sGS, and 42.2% for tGS. GS excelled in identifying deep intronic, non-coding, and small copy-number variants missed by SoC. Notably, tGS additionally identified three de novo variants classified as likely pathogenic based on recent GeneMatcher collaborations and newly published gene-disease association studies.
Conclusion
GS, particularly tGS, demonstrated superior diagnostic performance, supporting its use as a first-tier genetic test. sGS offers a cost-effective alternative, enabling faster, more efficient diagnoses for rare disease patients.