Intellectual disability (ID) is a neurodevelopmental disorder with a strong genetic component. For many patients the genetic cause is yet unknown as no protein-damaging mutations can be identified. To accurately predict the risk for ID from a person’s complete DNA sequence, it is essential to know how and when genetic perturbation of a gene regulatory element causes abnormal neurodevelopment. The knowledge and statistical methodology to do so are currently lacking.Recently, the ENCODE and Roadmap Epigenomics projects identified millions of gene regulatory elements across a wide range of tissues. These regulatory elements are small DNA regions where cooperative binding of specific transcription factors (TFs) strongly influences the level of expression of one or more genes, often in a highly tissue-specific manner. However, since only static characterizations are available, it is very difficult to predict how the transcriptional network defined by the regulatory elements responds to genetic perturbations.I will therefore perturb gene regulatory elements underlying ID by knocking-down the expression of established ID transcription factors in neurons. Previous efforts relied on partial or noisy measurements of TF binding. Instead, I will use TF-footprinting to obtain a complete view of how the knock-down perturbs TF-binding in gene regulatory elements. Combining this with gene expression and epigenetic profiling, I will model of how perturbation of cooperative binding in regulatory elements causes misregulation of ID and neurodevelopmental genes. To predict how perturbation of the transcriptional network disrupts biological pathways, I will integrate in my Bayesian network model existing data sets of neuronal morphology, structural brain imaging GWAS, and behavioural studies in model organisms.My research will provide much-needed understanding and methodology to predict the functional consequences of genetic perturbation of gene regulatory elements for ID.