Imaging-Genetics in Autism Spectrum Disorder: Advances, Translational Impact, and Future Directions
Bibliographic record
Abstract
Autism Spectrum Disorder (ASD) refers to a group of heterogeneous neurodevelopmental disorders that are unified by impairments in reciprocal social communication and a pattern of inflexible behaviors. Recent genetic advances have resolved some of the complexity of the genetic architecture underlying ASD by identifying several genetic variants that contribute to the disorder. Different etiological pathways associated with ASD may converge through effects on common molecular mechanisms, such as synaptogenesis, neuronal motility, and axonal guidance. Recently, with more sophisticated techniques, neuroimaging, and neuropathological studies have provided some consistency of evidence that altered structure, activity, and connectivity within complex neural networks is present in ASD, compared to typically developing children. The imaging-genetics approach promises to help bridge the gap between genetic variation, resultant biological effects on the brain, and production of complex neuropsychiatric symptoms. Here, we review recent findings from the developing field of imaging-genetics applied to ASD. Studies to date have indicated that relevant risk genes are associated with alterations in circuits that mediate socio-emotional, visuo-spatial, and language processing. Longitudinal studies ideally focused on early development, in conjunction with investigation for gene-gene, and gene-environment interactions may move the promise of imaging-genetics in ASD closer to the clinical domain.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".