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Daniel Kaschta

@danielkaschta.bsky.social
9 followers 11 following 14 posts

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

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Daniel Kaschta @danielkaschta.bsky.social · 22/05/2026
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.
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Daniel Kaschta @danielkaschta.bsky.social · 22/05/2026
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.
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Daniel Kaschta @danielkaschta.bsky.social · 22/05/2026
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.
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Daniel Kaschta @danielkaschta.bsky.social · 22/05/2026
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.
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Daniel Kaschta @danielkaschta.bsky.social · 22/05/2026
Our medRxiv preprint is out: Automated versus manual reanalysis in rare disease genomics. We reanalysed 377 rare disease cases from a routine diagnostic genome sequencing cohort, comparing the established manual workflow with Talos-based automation. www.medrxiv.org/content/10.6...
medrxiv.org
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Reposted by Daniel Kaschta
Alex Hoischen @ahoischen.bsky.social · 24/09/2025
Wow! Amazing - and first glimpses of hope for patients and families with this devastating rare disease. www.bbc.com/news/article...
bbc.com
Huntington's disease successfully treated for first time
One of the most devastating diseases finally has a treatment that can slow its progression and transform lives, tearful doctors tell BBC.
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Daniel Kaschta @danielkaschta.bsky.social · 25/09/2025
Grateful to the UKSH Genome Consortium and all collaborators. #RareDisease #Genomics #WholeGenomeSequencing #TrioSequencing #ClinicalGenomics #GenomeMedicine #Diagnostics #GeneticTesting www.uksh.de/Das+UKSH/Neu...
uksh.de
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Daniel Kaschta @danielkaschta.bsky.social · 25/09/2025
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.
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Daniel Kaschta @danielkaschta.bsky.social · 25/09/2025
✨ Delighted to share our open-access paper in Genome Medicine is finally fully published: genomemedicine.biomedcentral.com/articles/10....
genomemedicine.biomedcentral.com
Evaluating genome sequencing strategies: trio, singleton, and standard testing in rare disease diagnosis - Genome Medicine
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.
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Reposted by Daniel Kaschta
mspielmann.bsky.social @mspielmann.bsky.social · 25/03/2025
Hope to meet many of you there!
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Daniel Kaschta @danielkaschta.bsky.social · 17/02/2025
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
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Daniel Kaschta @danielkaschta.bsky.social · 17/02/2025
Over 1,000 individuals from 448 rare disease cases participated. In this blind study we examined the diagnostic yield analyzing both prospective and retrospective data. #GenomeSequencing
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Daniel Kaschta @danielkaschta.bsky.social · 17/02/2025
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
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Daniel Kaschta @danielkaschta.bsky.social · 17/02/2025
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
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Daniel Kaschta @danielkaschta.bsky.social · 17/02/2025
Preprint to our full study here: medrxiv.org/content/10.1... Let’s transform rare disease diagnosis with genome sequencing. Join the conversation below or reach out for collaboration! 🧵👇 #RareDiseases #Genomics With @mspielmann.bsky.social
medrxiv.org
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Daniel Kaschta @danielkaschta.bsky.social · 17/02/2025
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 🧵👇
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