The molecular mechanisms and pharmacotherapy of ATP-sensitive potassium channel gene mutations underlying neonatal diabetes
Bibliographic record
Abstract
Veronica Lang, Peter E LightDepartment of Pharmacology and Alberta Diabetes Institute, Faculty of Medicine and Dentistry, School of Molecular and Systems Medicine, University of Alberta, Edmonton, Alberta, CanadaAbstract: Neonatal diabetes mellitus (NDM) is a monogenic disorder caused by mutations in genes involved in regulation of insulin secretion from pancreatic β-cells. Mutations in the KCNJ11 and ABCC8 genes, encoding the adenosine triphosphate (ATP)-sensitive potassium (KATP) channel Kir6.2 and SUR1 subunits, respectively, are found in ~50% of NDM patients. In the pancreatic β-cell, KATP channel activity couples glucose metabolism to insulin secretion via cellular excitability and mutations in either KCNJ11 or ABCC8 genes alter KATP channel activity, leading to faulty insulin secretion. Inactivation mutations decrease KATP channel activity and stimulate excessive insulin secretion, leading to hyperinsulinism of infancy. In direct contrast, activation mutations increase KATP channel activity, resulting in impaired insulin secretion, NDM, and in severe cases, developmental delay and epilepsy. Many NDM patients with KCNJ11 and ABCC8 mutations can be successfully treated with sulfonylureas (SUs) that inhibit the KATP channel, thus replacing the need for daily insulin injections. There is also strong evidence indicating that SU therapy ameliorates some of the neurological defects observed in patients with more severe forms of NDM. This review focuses on the molecular and cellular mechanisms of mutations in the KATP channel that underlie NDM. SU pharmacogenomics is also discussed with respect to evaluating whether patients with certain KATP channel activation mutations can be successfully switched to SU therapy.Keywords: neonatal diabetes, KCNJ11, ABCC8, ATP-sensitive potassium channels
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".