Interleukin-6 inhibition of hERG underlies risk for acquired long QT in cardiac and systemic inflammation
Bibliographic record
Abstract
Increased proinflammatory interleukin-6 (IL-6) levels are associated with acquired long QT-syndrome (LQTS) in patients with systemic inflammation, leading to higher risks for life-threatening polymorphic ventricular tachycardia such as Torsades de Pointes. However, the functional and molecular mechanisms of this association are not known. In most cases of acquired LQTS, the target ion channel is the human ether-á-go-go-related gene (hERG) encoding the rapid component of the delayed rectifier K current, IKr, which plays a critical role in cardiac repolarization. Here, we tested the hypothesis that IL-6 may cause QT prolongation by suppressing IKr. Electrophysiological and biochemical assays were used to assess the impact of IL-6 on the functional expression of IKr in HEK293 cells and adult guinea-pig ventricular myocytes (AGPVM). In HEK293 cells, IL-6 alone or in combination with the soluble IL-6 receptor (IL-6R), produced a significant depression of IKr peak and tail current densities. Block of IL-6R or Janus kinase (JAK) reversed the inhibitory effects of IL-6 on IKr. In AGPVM, IL-6 prolonged action potential duration (APD) which was further prolonged in the presence of IL-6R. Similar to heterologous cells, IL-6 reduced endogenous guinea pig ERG channel mRNA and protein expression. The data are first to demonstrate that IL-6 inhibition of IKr and the resulting prolongation of APD is mediated via IL-6R and JAK pathway activation and forms the basis for the observed clinical QT interval prolongation. These novel findings may guide the development of targeted anti-arrhythmic therapeutic interventions in patients with LQTS and inflammatory disorders.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".