Large-scale genetic studies are producing valuable new leads to understand disease mechanisms and identify new treatment targets. However, the underlying genetic architecture is complex, with many rare and common genetic variants contributing to disease risk. For instance, recent large-scale exome sequencing has identified over 100 risk genes for autism spectrum disorder (ASD) whose mutations are highly predictive of ASD onset, and the SFARI Gene database contains 1,231 genes implicated in autism spectrum disorder (ASD), among which are 418 high-confidence and strong candidate autism risk genes (categories 1–2) and 17 recurrent copy number variant (CNV) loci reported in individuals with ASD.

To translate these important findings into testable hypotheses on disease mechanisms and prioritize new treatment targets requires a better understanding of how and where in the brain these genes work together in specific gene networks and pathways involved in disease risk. Although some ASD-associated genes have hardly been studied, for many others a wealth of basic research data is already available.

In the current project, August Smit and Matthijs Verhage aim to better disclose this available information, especially for synaptic genes, to support the translation of genetic findings into specific disease concepts. They aim to integrate this information in a systematic and computer-readable format based on assessments made by key opinion leaders in the field on a validated method for evidence tracking and on a previously optimized annotation and quality control interface.

In particular, this project will establish (1) a database of validated synaptic protein-protein interactions relevant for ASD, curated by experts in the field and based on strong published evidence and (2) gather the evidence on the function of these proteins from perturbation experiments. Making the available information on synaptic protein interactions and functions relevant for ASD more accessible to the research community will help support the translation of genetic findings into specific disease concepts.