The Effect of Type 2 Diabetes Risk Loci on Insulin Requirements in Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To analyze the correlation between insulin requirements of type 1 diabetic (T1D) patients and genotype at type 2 diabetes (T2D) risk loci, obtained in our genome-wide association study. METHODS: From a database of detailed insulin dosing of 567 patients, we selected 177 for whom we also had genome-wide genotyping data. Using PLINK software, we examined the association between insulin requirement as a quantitative trait and nineteen T2D risk loci. RESULTS: Out of 19 single-nucleotide polymorphisms (SNPs), rs13266634 on chromosome 8 and rs7901695 on chromosome 10 showed nominal significance of association (p < 0.05). The first SNP is nonsynonymous (325 Arg>Trp) and maps to the SLC30A8 gene encoding the β-cell-specific ZnT8 zinc transporter, while the second is an intronic SNP in TCF7L2, the strongest known T2D association. Both loci exert their effect on β-cells and, in both, the T2D risk allele is associated with lower insulin requirements. CONCLUSION: We identified two T2D susceptibility loci that modulate insulin requirements in T1D patients. Our results are consistent with the association of lower insulin secretion with higher insulin sensitivity. To explain the continuation of this correlation after β-cell destruction, we hypothesize an epigenetic mechanism that alters insulin responsiveness in T1D patients based on β-cell function in early life. Such knowledge may allow a more precise approach to treatment.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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".