Burden re-analysis of neurodevelopmental disorder cohorts for prioritization of candidate genes.

Abstract

This study aimed to uncover novel genes associated with neurodevelopmental disorders (NDD) by leveraging recent large-scale de novo burden analysis studies to enhance a virtual gene panel used in a diagnostic setting. We re-analyzed historical trio-exome sequencing data from 745 individuals with NDD according to the most recent diagnostic standards, resulting in a cohort of 567 unsolved individuals. Next, we designed a virtual gene panel containing candidate genes from three large de novo burden analysis studies in NDD and prioritized candidate genes by stringent filtering for ultra-rare de novo variants with high pathogenicity scores. Our analysis revealed an increased burden of de novo variants in our selected candidate genes within the unsolved NDD cohort and identified qualifying de novo variants in seven candidate genes: RIF1, CAMK2D, RAB11FIP4, AGO3, PCBP2, LEO1, and VCP. Clinical data were collected from six new individuals with de novo or inherited LEO1 variants and three new individuals with de novo PCBP2 variants. Our findings add additional evidence for LEO1 as a risk gene for autism and intellectual disability. Furthermore, we prioritize PCBP2 as a candidate gene for NDD associated with motor and language delay. In summary, by leveraging de novo burden analysis studies, employing a stringent variant filtering pipeline, and engaging in targeted patient recruitment, our study contributes to the identification of novel genes implicated in NDDs.