Development and characterization of a mouse model for in utero type 2 diabetes exposure
Bibliographic record
Abstract
BACKGROUND: The prevalence of childhood type 2 diabetes (T2D) in Canada, and particularly in Manitoba, is amongst the highest worldwide, resulting in an increased incidence of pregnancies complicated by T2D as children approach their reproductive years. Exposure to T2D in utero has detrimental effects on the health and well-being of offspring, including various malformations, stillbirth, congenital defects, metabolic disorders, a significantly higher predisposition to diabetes, early kidney failure, chronic low-grade inflammation, cardiovascular issues, mental health issues, and cognitive deficits. However, the mechanisms responsible for poorer health outcomes in T2D-exposed offspring and greater intergenerational risk remain unclear. To investigate the effects of maternal T2D on offspring physiology and health, an appropriate T2D mouse model is required. Existing approaches to induce T2D in mice often result in hypoinsulinemia and severe hyperglycemia, which does not accurately resemble T2D in humans. These approaches to induce T2D typically lead to offspring microsomia, whereas human offspring of T2D mothers often have macrosomia. Genetic models of T2D models either produce infertile mice or induce diabetes in males only, making it impossible to study the effects of in utero T2D exposure on offspring. Therefore, the development and characterization of an appropriate rodent model of T2D that can be used during pregnancy and more accurately resembling T2D in humans, is needed to effectively investigate the mechanisms responsible for the intergenerational transmission of T2D and mechanistic contributors to adverse health outcomes in exposed offspring. METHODS: To develop a model of T2D pre-pregnancy, female C57BL/6J mice were exposed to a high-fat and sucrose (HFS) diet for varying durations (4, 6, 8, and 10 weeks) to induce obesity and insulin resistance. Subsequently, a one-time administration of different concentrations of streptozotocin (STZ; 75 mg/kg, 100 mg/kg, or 150 mg/kg), a chemical that specifically targets and kills pancreatic β-cell, was used to impair adaptive beta cell function without completely eliminating the β-cell pool. Weekly body weight and biweekly fasted blood glucose measurements were performed on all female mice. Two weeks after the STZ injection, the mice underwent glucose metabolism assessments, including a glucose tolerance test (GTT), insulin tolerance test (ITT), and weekly fasted blood glucose and body weight measurements. Control mice were fed a chow diet and injected with citrate buffer (the vehicle for STZ) and underwent metabolic assessments alongside the T2D groups. After pre-gestational metabolic assessments were completed, female mice were mated with healthy chow-fed C57BL/6J male mice. Maternal glycemia and body weight were measured during each trimester of gestation (weekly). Additionally, an HFS-only control group (no STZ) was established to determine the impact of the HFS diet alone. These mice were placed on the HFS diet for 10 weeks and then injected with vehicle (citrate buffer) and metabolically assessed. RESULTS: The study revealed that female mice fed an HFS diet for 10 weeks prior to a 150 mg/kg STZ injection developed mild-to-moderate fasted hyperglycemia, glucose intolerance, insulin resistance, and higher fasted glycemia, which was maintained throughout gestation compared to control mice, indicative of pre-existing T2D prior to pregnancy and T2D throughout pregnancy. In contrast, the HFS-only control group of mice, while showing increased body weight, developed less glucose intolerance and maintained euglycemia, suggesting that the reduction of β-cell mass via STZ was needed for T2D development in C57B6 female mice. CONCLUSIONS: These findings suggest that through a combination of an HFS diet (10 weeks) and STZ injection (150 mg/kg of STZ), T2D that includes key features of human T2D can be generated in female C57BL6 mice while maintaining fertility. This model can be used to study the effects of in utero exposure to T2D on offspring development and function, while also identifying pathophysiological mechanisms underlying structural and functional changes. This information gained from the use of this model has the potential to contribute to various therapeutic approaches, the development of new drugs, and the adjustment of current clinical protocols, among other potential outcomes.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".