Pharmacogenomic analysis of ATP-sensitive potassium channels coexpressing the common type 2 diabetes risk variants E23K and S1369A
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Bibliographic record
Abstract
OBJECTIVES: The common ATP-sensitive potassium (KATP) channel variants E23K and S1369A, found in the KCNJ11 and ABCC8 genes, respectively, form a haplotype that is associated with an increased risk for type 2 diabetes. Our previous studies showed that KATP channel inhibition by the A-site sulfonylurea gliclazide was increased in the K23/A1369 haplotype. Therefore, we studied the pharmacogenomics of seven clinically used sulfonylureas and glinides to determine their structure-activity relationships in KATP channels containing either the E23/S1369 nonrisk or K23/A1369 risk haplotypes. RESEARCH DESIGN AND METHODS: The patch-clamp technique was used to determine sulfonylurea and glinide inhibition of recombinant human KATP channels containing either the E23/S1369 or the K23/A1369 haplotype. RESULTS: KATP channels containing the K23/A1369 risk haplotype were significantly less sensitive to inhibition by tolbutamide, chlorpropamide, and glimepiride (IC50 values for K23/A1369 vs. E23/S1369=1.15 vs. 0.71 μmol/l; 4.19 vs. 3.04 μmol/l; 4.38 vs. 2.41 nmol/l, respectively). In contrast, KATP channels containing the K23/A1369 haplotype were significantly more sensitive to inhibition by mitiglinide (IC50=9.73 vs. 28.19 nmol/l for K23/A1369 vs. E23/S1369) and gliclazide. Nateglinide, glipizide, and glibenclamide showed similar inhibitory profiles in KATP channels containing either haplotype. CONCLUSION: Our results demonstrate that the ring-fused pyrrole moiety in several A-site drugs likely underlies the observed inhibitory potency of these drugs on KATP channels containing the K23/A1369 risk haplotype. It may therefore be possible to tailor existing therapy or design novel drugs that display an increased efficacy in type 2 diabetes patients homozygous for these common KATP channel haplotypes.
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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) | 0.001 | 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)
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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 it