Induced pluripotent stem cells used to reveal drug actions in a long QT syndrome family with complex genetics
Bibliographic record
Abstract
Understanding the basis for differential responses to drug therapies remains a challenge despite advances in genetics and genomics. Induced pluripotent stem cells (iPSCs) offer an unprecedented opportunity to investigate the pharmacology of disease processes in therapeutically and genetically relevant primary cell types in vitro and to interweave clinical and basic molecular data. We report here the derivation of iPSCs from a long QT syndrome patient with complex genetics. The proband was found to have a de novo SCN5A LQT-3 mutation (F1473C) and a polymorphism (K897T) in KCNH2, the gene for LQT-2. Analysis of the biophysics and molecular pharmacology of ion channels expressed in cardiomyocytes (CMs) differentiated from these iPSCs (iPSC-CMs) demonstrates a primary LQT-3 (Na(+) channel) defect responsible for the arrhythmias not influenced by the KCNH2 polymorphism. The F1473C mutation occurs in the channel inactivation gate and enhances late Na(+) channel current (I(NaL)) that is carried by channels that fail to inactivate completely and conduct increased inward current during prolonged depolarization, resulting in delayed repolarization, a prolonged QT interval, and increased risk of fatal arrhythmia. We find a very pronounced rate dependence of I(NaL) such that increasing the pacing rate markedly reduces I(NaL) and, in addition, increases its inhibition by the Na(+) channel blocker mexiletine. These rate-dependent properties and drug interactions, unique to the proband's iPSC-CMs, correlate with improved management of arrhythmias in the patient and provide support for this approach in developing patient-specific clinical regimens.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".