<scp>CIM6P</scp>/<scp>IGF</scp>‐2 Receptor Ligands Reverse Deficits in Angelman Syndrome Model Mice
Bibliographic record
Abstract
Angelman syndrome (AS), a genetic disorder that primarily affects the nervous system, is characterized by delayed development, intellectual disability, severe speech impairment, and problems with movement and balance (ataxia). Most affected children also have recurrent seizures (epilepsy). No existing therapies are capable of comprehensively treating the deficits in AS; hence, there is an urgent need to identify new treatments. Here we show that insulin‐like growth factor 2 (IGF‐2) and mannose‐6‐phosphate (M6P), ligands of two independent binding sites of the cation‐independent M6P/IGF‐2 receptor (CIM6P/IGF‐2R), reverse most major deficits of AS modeled in mice. Subcutaneous injection of IGF‐2 or M6P in mice modeling AS restored cognitive impairments as assessed by measurements of contextual and recognition memories, motor deficits assessed by rotarod and hindlimb clasping, and working memory/flexibility measured by Y‐maze. IGF‐2 also corrected deficits in marble burying and significantly attenuated acoustically induced seizures. An observational battery of tests confirmed that neither ligand changed basic functions including physical characteristics, general behavioral responses, and sensory reflexes, indicating that they are relatively safe. Our data provide strong preclinical evidence that targeting CIM6P/IGF‐2R is a promising approach for developing novel therapeutics for AS. Lay Summary There is no effective treatment for the neurodevelopmental disorder Angelman syndrome (AS). Using a validated AS mouse model, the Ube3am−/p+, in this study we show that systemic administration of ligands of the cation independent mannose‐6‐phosphate receptor, also known as insulin‐like growth factor 2 receptor (CIM6P/IGF‐2R) reverses cognitive impairment, motor deficits, as well as seizures associated with AS. Thus, ligands that activate the CIM6P/IGF‐2R may represent novel, potential therapeutic targets for AS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".