Trait - driven analysis of the 2p15p16.1 microdeletion syndrome suggests a complex pattern of interactions between candidate genes

Background Individuals with the 2p15p16.1 microdeletion syndrome share a complex phenotype including neurodevelopmental delay, brain malformations, microcephaly, and autistic behavior. The analysis of the shortest region of overlap (SRO) between deletions in similar to 40 patients has led to the identification of two critical regions and four strongly candidate genes (BCL11A, REL, USP34 and XPO1). However, the delineation of their role in the occurrence of specific traits is hampered by their incomplete penetrance. Objective To better delineate the role of hemizygosity of specific regions in selected traits by leveraging information both from penetrant and non - penetrant deletions. Methods Deletions in patients that do not present a specific trait cannot contribute to delineate the SROs. We recently developed a probabilistic model that, by considering also the non - penetrant deletions, allows a more reliable assignment of peculiar traits to specific genomic segments. We apply this method adding two new patients to the published cases. Results Our results delineate an intricate pattern of genotype - phenotype correlation where BCL11A emerges as the main gene for autistic behavior while USP34 and/or XPO1 haploinsufficiency are mainly associated with microcephaly, hearing loss and IUGR. BCL11A, USP34 and XPO1 genes are broadly related with brain malformations albeit with distinct patterns of brain damage. Conclusions The observed penetrance of deletions encompassing different SROs and that predicted when considering each single SRO as acting independently, may reflect a more complex model than the additive one. Our approach may improve the genotype/phenotype correlation and may help to identify specific pathogenic mechanisms in contiguous gene syndromes.

Automated summary

Individuals with 2p15p16.1 microdeletion syndrome exhibit a complex phenotype. The study identifies BCL11A, REL, USP34, and XPO1 as candidate genes. By considering non-penetrant deletions, the study provides a more accurate correlation between specific genomic segments and traits.