Sexually dimorphic neuroanatomical differences relate to ASD-relevant behavioral outcomes in a maternal autoantibody mouse model
Bibliographic record
Abstract
Abstract Immunoglobulin G (IgG) autoantibodies reactive to fetal brain proteins in mothers of children with ASD have been described by several groups. To understand their pathologic significance, we developed a mouse model of maternal autoantibody related ASD (MAR-ASD) utilizing the peptide epitopes from human autoantibody reactivity patterns. Male and female offspring prenatally exposed to the salient maternal autoantibodies displayed robust deficits in social interactions and increased repetitive self-grooming behaviors as juveniles and adults. In the present study, neuroanatomical differences in adult MAR-ASD and control offspring were assessed via high-resolution ex vivo magnetic resonance imaging (MRI) at 6 months of age. Of interest, MAR-ASD mice displayed significantly larger total brain volume and of the 159 regions examined, 31 were found to differ significantly in absolute volume (mm 3 ) at an FDR of <5%. Specifically, the absolute volumes of several white matter tracts, cortical regions, and basal nuclei structures were significantly increased in MAR-ASD animals. These phenomena were largely driven by female MAR-ASD offspring, as no significant differences were seen with either absolute or relative regional volume in male MAR-ASD mice. However, structural covariance analysis suggests network-level desynchronization in brain volume in both male and female MAR-ASD mice. Additionally, preliminary correlational analysis with behavioral data relates that volumetric increases in numerous brain regions of MAR-ASD mice were correlated with social interaction and repetitive self-grooming behaviors in a sex-specific manner. These results demonstrate significant sex-specific effects in brain size, regional relationships, and behavior for offspring prenatally exposed to MAR-ASD autoantibodies relative to controls.
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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 | 0.000 | 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 | 0.001 |
| 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".