Mapping Developmental Trajectories in 22q11.2 Deletion Syndrome

Background:  22q11.2 deletion syndrome is a common, recurrent CNV that is associated with autism spectrum disorder, with 20% of children with this genetic syndrome also having an autism diagnosis. However, the variability in developmental outcomes of children with 22q11.2 deletion syndrome is very broad, with varying amounts of ASD symptomology and varying degrees of intellectual disability. This variability makes it difficult to accurately predict outcomes (e.g., ASD v. non-ASD; level of cognitive impairment) that can be helpful for future planning. We have a pressing need for a comprehensive approach accounting for behavioral presentation while recognizing key factors that affect long-term phenotypic variability (e.g., genetic etiology, familial background and medical comorbidities).

Objectives: Our study aims to better understand longitudinal outcomes of children with 22q11.2 deletion syndrome (22qDS) by combining developmental assessments, medical comorbidities, genetic etiology, and family background in an ordinal logistic regression model.

Methods: We have identified 15 probands with 22qDS who have been consented for research and have been entered into our research database. All of these probands have at least one developmental assessment; in addition, 7 have at least two assessments ranging through as many as five developmental assessments already completed (at least annually). We used mathematical approaches, including generalized linear mixed models (GLMMs) and generalized estimating equations (GEEs), to identify clinical factors that are the most predictive of developmental outcomes. In particular, clinical factors we investigated include genetic diagnosis, and medical comorbidities. Longitudinal developmental profiles were developed for children with 22qDS were informed by the child’s and parents’ performance on various assessments of cognition.

Results:  Two separate models of language and visual motor age equivalents were created. We identified that both age and sex had a significant effect on the developmental trajectory of the child. In terms of sex, we found that gender was significantly associated with path of developmental trajectory in the language domains.

Conclusions: Overall, this project indicates initial evidence that mapping of developmental trajectories can lead to improved prediction of future outcomes including severity of cognitive impairment and presence of clinical ASD. Future results of our study has the potential to lead to an improved understanding of the quantitative effects of genetics, as well as behavioral and medical factors, on phenotypic outcome.