Systems genetics of susceptibility to obesity-induced diabetes in mice
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Bibliographic record
Abstract
Inbred strains of mice are strikingly different in susceptibility to obesity-driven diabetes. For instance, deficiency in leptin receptor (db/db) leads to hyperphagia and obesity in both C57BL/6 and DBA/2 mice, but only on the DBA/2 background do the mice develop beta-cell loss leading to severe diabetes, while C57BL/6 mice are relatively resistant. To further investigate the genetic factors predisposing to diabetes, we have studied leptin receptor-deficient offspring of an F2 cross between C57BL/6J (db/+) males and DBA/2J females. The results show that the genetics of diabetes susceptibility are enormously complex and a number of quantitative trait loci (QTL) contributing to diabetes-related traits were identified, notably on chromosomes 4, 6, 7, 9, 10, 11, 12, and 19. The Chr. 4 locus is likely due to a disruption of the Zfp69 gene in C57BL/6J mice. To identify candidate genes and to model coexpression networks, we performed global expression array analysis in livers of the F2 mice. Expression QTL (eQTL) were identified and used to prioritize candidate genes at clinical trait QTL. In several cases, clusters of eQTLs colocalized with clinical trait QTLs, suggesting a common genetic basis. We constructed coexpression networks for both 5 and 12 wk old mice and identified several modules significantly associated with clinical traits. One module in 12 wk old mice was associated with several measures of hepatic fat content as well as with other lipid- and diabetes-related traits. These results add to the understanding of the complex genetic interactions contributing to obesity-induced diabetes.
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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) | 0.000 | 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 it