The ATP-Sensitive K+ Channel <i>ABCC8</i> S1369A Type 2 Diabetes Risk Variant Increases MgATPase Activity
Bibliographic record
Abstract
Pancreatic β-cell ATP-sensitive K(+) (K(ATP)) channels are composed of Kir6.2 and SUR1 subunits encoded by the KCNJ11 and ABCC8 genes, respectively. Although rare monogenic activating mutations in these genes cause overt neonatal diabetes, the common variants E23K (KCNJ11) and S1369A (ABCC8) form a tightly heritable haplotype that is associated with an increased susceptibility to type 2 diabetes (T2D) risk. However, the molecular mechanism(s) underlying this risk remain to be elucidated. A homology model of the SUR1 nucleotide-binding domains (NBDs) indicates that residue 1369 is in close proximity to the major MgATPase site. Therefore, we investigated the intrinsic MgATPase activity of K(ATP) channels containing these variants. Electrophysiological and biochemical techniques were used to study the MgATPase activity of recombinant human K(ATP) channels or glutathione S-transferase and NBD2 fusion proteins containing the E23/S1369 (nonrisk) or K23/A1369 (risk) variant haplotypes. K(ATP) channels containing the K23/A1369 haplotype displayed a significantly increased stimulation by guanosine triphosphate compared with the E23/S1369 haplotype (3.2- vs. 1.8-fold). This effect was dependent on the presence of the A1369 variant and was lost in the absence of Mg(2+) ions or in the presence of the MgATPase inhibitor beryllium fluoride. Direct biochemical assays also confirmed an increase in MgATPase activity in NBD2 fusion proteins containing the A1369 variant. Our findings demonstrate that the A1369 variant increases K(ATP) channel MgATPase activity, providing a plausible molecular mechanism by which the K23/A1369 haplotype increases susceptibility to T2D in humans homozygous for these variants.
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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 | 0.001 |
| 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) | 0.004 | 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".