Targeted sequence capture and GS-FLX Titanium sequencing of 23 hypertrophic and dilated cardiomyopathy genes: implementation into diagnostics
Bibliographic record
Abstract
BACKGROUND: Genetic evaluation of cardiomyopathies poses a challenge. Multiple genes are involved but no clear genotype-phenotype correlations have been found so far. In the past, genetic evaluation for hypertrophic (HCM) and dilated (DCM) cardiomyopathies was performed by sequential screening of a very limited number of genes. Recent developments in sequencing have increased the throughput, enabling simultaneous screening of multiple genes for multiple patients in a single sequencing run. OBJECTIVE: Development and implementation of a next generation sequencing (NGS) based genetic test as replacement for Sanger sequencing. METHODS AND RESULTS: In order to increase the number of genes that can be screened in a shorter time period, we enriched all exons of 23 of the most relevant HCM and DCM related genes using on-array multiplexed sequence capture followed by massively parallel pyrosequencing on the GS-FLX Titanium. After optimisation of array based sequence capture it was feasible to reliably detect a large panel of known and unknown variants in HCM and DCM patients, whereby the unknown variants could be confirmed by Sanger sequencing. CONCLUSIONS: The rate of detection of (pathogenic) variants in both HCM and DCM patients was increased due to a larger number of genes studied. Array based target enrichment followed by NGS showed the same accuracy as Sanger sequencing. Therefore, NGS is ready for implementation in a diagnostic setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".