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Are CNV Risk Scores Linked to Neurodevelopmental and Mental Health Characteristics Within CNV-Associated Intellectual
Medrxiv : the Preprint Server for Health Sciences
|July 30, 2026
Summary
Copy number variant (CNV) risk scores in children with intellectual disability (ID) do not universally predict neurodevelopmental and mental health issues. Complex interactions between CNV scores, inheritance, and individual context are key for understanding needs.
Area of Science:
- Genetics
- Neurodevelopmental Disorders
- Mental Health
Background:
- Children and young people (CYP) with intellectual disability (ID) often exhibit co-occurring neurodevelopmental (ND) and mental health (MH) difficulties.
- Copy number variants (CNVs) are a known cause of ID, but their role in predicting ND and MH characteristics in affected individuals is not fully understood.
Purpose of the Study:
- To investigate whether CNV risk scores predict neurodevelopmental and mental health characteristics in children and young people with ID.
- To explore the complex relationships between CNV risk scores, inheritance patterns, and phenotypic outcomes in this population.
Main Methods:
- Analysis of the UK-based IMAGINE-ID cohort (N=1,640) of CYP (aged 4-19 years) with ID and reported CNVs.
- Calculation of CNV risk scores using summed probability of loss-of-function intolerance (pLI) and dosage sensitivity.
- Multivariate regression models to assess the predictive value of CNV variables and inheritance on ND and MH characteristics, using DAWBA assessments.
Main Results:
- Higher summed pLI scores unexpectedly predicted fewer MH difficulties and lower likelihood of ND diagnoses.
- A threshold effect was observed: in the lower pLI range, higher scores correlated with more MH issues, while in the higher pLI range, they correlated with fewer MH issues, particularly in severe ID cases.
Conclusions:
- CNV genomic risk scores do not universally predict ND and MH difficulties in individuals with CNV-associated ID.
- Complex interactions exist between CNV risk scores, inheritance, and phenotypes, necessitating integration of genomic data with familial and developmental context for personalized support.
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