Parental high-fat/high-sugar diets and their lasting impact on brain development in offspring: a longitudinal mouse MRI study
Bibliographic record
Abstract
Maternal diet and metabolic conditions, such as obesity and diabetes, are associated with consequences for offspring brain health, including effects on behaviour and an increased risk for neurodevelopmental disorders (NDDs). The extent and sequence of neuroanatomical changes to offspring brain development produced by dietary conditions have not yet been reported. In this study, we used a mouse model of parental high-fat or high-fat/high-sugar diet consumption to examine its effects on offspring brain development using longitudinal magnetic resonance imaging. We demonstrated that exposure to these parental diets through gestation and lactation resulted in offspring brain structure changes. Different temporal patterns of change were observed: some structures exhibited volume differences already at postnatal day 3; some of these early appearing changes diminished early in development while others were still present in adulthood; other structure changes were found to emerge later in the pubertal period. Brain changes in adulthood were present despite switching to a healthy diet at weaning. Brain regions impacted included the cingulate cortex, subregions of the hippocampus, and the orbitofrontal cortex, regions previously reported as affected in human NDD populations, with functional roles in reward processing and social cognition, memory, and decision making, respectively. Affected cortical regions, including the cingulate and orbitofrontal cortex, were found to be increased in volume relative to the whole brain, while affected subcortical regions were largely decreased in volume. Our data provide new insights into the long-term neuroanatomical impact of parental diets and how those diets may impact NDD risk. Future studies could use this model to evaluate preventative or ameliorative measures.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".