Daniel Kaschta

Daniel Kaschta

@danielkaschta.bsky.social

🔬 Scientist | PhD candidate in Biochemistry & Molecular Biology | 🧬 Genomics & Rare Diseases | Researcher @UKSH Kiel

9 followers11 following14 posts

View full thread
Daniel Kaschta
@danielkaschta.bsky.social

Concordance analysis showed that Talos captured most manually reported P/LP findings: 80.0% concordance in singleton cases and 75.2% in trio cases, rising to 82.8% when considering proband-only findings. VUS concordance was lower, as expected for a P/LP-focused workflow.

Daniel Kaschta
@danielkaschta.bsky.social

Take-home: reanalysis after ~1.8 years gives a modest but clinically relevant diagnostic gain. Scalable workflows could help unresolved rare disease cases benefit from evolving genomic knowledge.

Daniel Kaschta
@danielkaschta.bsky.social

Why this matters: genome interpretation evolves over time, but fully manual reanalysis is difficult to scale in routine diagnostics. Automated prioritisation may help make periodic reanalysis more feasible.

Daniel Kaschta
@danielkaschta.bsky.social

After a mean reanalysis interval of 660 days, manual review added 3 P/LP cases and 2 newly classified VUS. Talos recovered all 3 new P/LP findings and 1 of 2 VUS, while reducing review to ~3 candidate variants per case.

Daniel Kaschta
@danielkaschta.bsky.social

✨ Delighted to share our open-access paper in Genome Medicine is finally fully published: genomemedicine.biomedcentral.com/articles/10....

genomemedicine.biomedcentral.comEvaluating genome sequencing strategies: trio, singleton, and standard testing in rare disease diagnosis - Genome MedicineBackground 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.
Daniel Kaschta
@danielkaschta.bsky.social

Beyond diagnostic yield, the study provides practical insights for labs evaluating GS as a new first-tier standard, including the added value of inheritance information for less-experienced teams and the types of variants GS captures that SoC often misses.

Daniel Kaschta
@danielkaschta.bsky.social

How do genome sequencing strategies stack up for diagnosing rare diseases? In our preprint we compare GS and standard-of-care approaches in 448 cases. The results could transform your rare disease diagnostics! 🧬 #RareDiseases #Genomics 🧵👇

Daniel Kaschta
@danielkaschta.bsky.social

Key Results: •tGS achieved the highest diagnostic yield (42.2% P/LP). •sGS followed closely at 41.3%, missing only de novo scientific variants. •GS outperformed SoC (38.6%) by better identification of non-coding, intronic, and STR variants. #RareDiseaseDiagnosis

Daniel Kaschta
@danielkaschta.bsky.social

How do genome sequencing strategies stack up for diagnosing rare diseases? In our preprint we compare GS and standard-of-care approaches in 448 cases. The results could transform your rare disease diagnostics! 🧬 #RareDiseases #Genomics 🧵👇

Daniel Kaschta
@danielkaschta.bsky.social

How do genome sequencing strategies stack up for diagnosing rare diseases? In our preprint we compare GS and standard-of-care approaches in 448 cases. The results could transform your rare disease diagnostics! 🧬 #RareDiseases #Genomics 🧵👇

Daniel Kaschta
@danielkaschta.bsky.social

We compared: 1️⃣ Standard-of-care methods (SoC: exome sequencing, karyotyping, array-CGH) 2️⃣ Singleton genome sequencing (sGS) 3️⃣ Trio genome sequencing (tGS) Can genome sequencing outperform traditional methods? #GenomicsResearch

Daniel Kaschta
@danielkaschta.bsky.social

How do genome sequencing strategies stack up for diagnosing rare diseases? In our preprint we compare GS and standard-of-care approaches in 448 cases. The results could transform your rare disease diagnostics! 🧬 #RareDiseases #Genomics 🧵👇

Daniel Kaschta
@danielkaschta.bsky.social

Rare diseases affect millions. At UKSH, Germany's second-largest hospital, we hosted a direct face-off between standard-of-care methods, singleton genome sequencing, and trio genome sequencing in real-world clinical settings. #PrecisionMedicine #RareDiseases

Daniel Kaschta
@danielkaschta.bsky.social

How do genome sequencing strategies stack up for diagnosing rare diseases? In our preprint we compare GS and standard-of-care approaches in 448 cases. The results could transform your rare disease diagnostics! 🧬 #RareDiseases #Genomics 🧵👇

You are up to date.