This application is being submitted to PA-18-591 in accordance with NOT-OD-18-194. Developmental brain disorders (DBD) include a wide range of developmental and psychiatric disorders that are etiologically heterogeneous with variable impacts on neurodevelopmental functioning. Down syndrome (DS) is the most common genetic cause of DBD that historically has been described as having a relatively homogeneous phenotype. However, with increasing life expectancies in individuals with DS, distinct cognitive, behavioral and genetic differences are becoming apparent. To investigate this inter-individual variability, we will use the Research Domain Criteria (RDoC) framework to elucidate risk and resilience to comorbid diagnoses and examine genomic contributors that influence neurodevelopmental functioning. We will add a Down syndrome cohort to our existing grant, ?Dimensional Analysis of Developmental Brain Disorders using an Online, Genome- first Approach? (R01-MH107431), to build validated, quantitative measures of psychopathology for DS through the following specific aims:
Aim 1 : Onsite and online phenotyping across RDoC domains and constructs of patients with Down syndrome and their unaffected family members. Using a combination of onsite and online phenotyping batteries, we will take a dimensional approach to assess the inter-individual variability in 50 individuals with DS and their unaffected family members focusing on four RDoC domains: Cognitive Processes, Social Processes, and Negative and Positive Valence Systems. Use of the RDoC-framework will allow quantification and comparison between individuals of the impact of having three copies of chromosome 21 on neurodevelopmental functioning. Rather than using traditional diagnostic thresholds to assess impact, we will compare performance in the proband to bi-parental performance on the corresponding domains. We hypothesize that the bi-parental data will predict the degree of impact in the proband, helping to explain inter-individual variability based on familial background.
Aim 2 : Examination of sleep wake dysfunction as a contributor to variable expressivity. Sleep wake dysfunction (SWD) is deleterious to behavior and neurocognitive performance. Individuals with DS experience SWD at a higher rate than neurotypical individuals. In addition, some individuals with DS are predisposed to a neurodegenerative progression to Alzheimer's disease, which is exacerbated by SWD. Comprehensive sleep wake characterization will provide a novel dimension of the DS phenotype and will also allow us to evaluate the influence of co-morbid untreated SWD on RDoC Domains.
Aim 3 : Identification of quantitative genomic contributors to variable expressivity. The presence of additional genomic variants in DS may also contribute to the observed phenotypic heterogeneity, including performance on RDoC Domains and sleep wake characteristics. Whole exome sequencing (WES) will be performed to discover modifying copy number or sequence-level variants that affect comorbid diagnoses and mental health outcomes. Overall, this study will enhance our understanding of the molecular snapshot of DS through novel phenotyping of a DS cohort, which includes assessment of the influence of sleep wake dysfunction and second hit genomic factors. The complementary analyses proposed in this study will not only improve our understanding of the factors that contribute to phenotypic variability in DS, but may also reveal novel therapeutic targets to improve neurocognitive and behavioral outcomes. This focus is highly aligned with the new trans-NIH INCLUDE Project, which is investigating co-occurring conditions across the lifespan of individuals with DS to better understand the factors that contribute to variable expressivity, particularly those that confer protective or susceptibility effects. By adding a cohort of individuals with DS to our existing project, we will be able to create a molecular snapshot of DS via detailed quantitative phenotyping and whole exome sequencing - one of the INCLUDE Project's research objectives encompassing Component 2. Furthermore, this supplementary project will lay the foundation for future clinical trials of individuals with DS. The standardized phenotypic and genome- wide sequencing data that we will collect and analyze as part of this study will establish an infrastructure that primes our cohort for participation in clinical trials with baseline, standardized data already well-characterized.
The clinical features observed in Down syndrome can be quite variable. Our project will examine the impact that genetic variants and sleep wake characteristics have on clinical features in individuals with Down syndrome compared to their unaffected family members to determine why there are differences. The results from these analyses will help researchers, families, and clinicians understand the various presentations of Down syndrome, and pave the way towards targeted behavioral and medical interventions.
| Evans, David W; Lusk, Laina G; Slane, Mylissa M et al. (2018) Dimensional assessment of schizotypal, psychotic, and other psychiatric traits in children and their parents: development and validation of the Childhood Oxford-Liverpool Inventory of Feelings and Experiences on a representative US sample. J Child Psychol Psychiatry 59:574-585 |
| Wain, Karen E; Palen, Emily; Savatt, Juliann M et al. (2018) The value of genomic variant ClinVar submissions from clinical providers: Beyond the addition of novel variants. Hum Mutat 39:1660-1667 |
| Clements, Caitlin C; Wenger, Tara L; Zoltowski, Alisa R et al. (2017) Critical region within 22q11.2 linked to higher rate of autism spectrum disorder. Mol Autism 8:58 |
| Girirajan, Santhosh (2017) Missing heritability and where to find it. Genome Biol 18:89 |
| Wang, Qingyu; Shashikant, Cooduvalli S; Jensen, Matthew et al. (2017) Novel metrics to measure coverage in whole exome sequencing datasets reveal local and global non-uniformity. Sci Rep 7:885 |
