Rare copy number variants (CNVs) are strongly associated with neuropsychiatric disorders, suggesting that they might serve as a magnifying glass to study general mechanisms of psychopathology as otherwise subtle perturbations to neuropsychiatric functions may be more clearly discerned through the major `hit' of the CNV. However, our understanding of the impact of CNVs on psychiatric symptomatology, RDoC domains and neurocognitive ability (termed `dimensional neuropsychiatric phenotypes') is limited in at least three ways. First, the effects sizes of the vast majority of CNVs on neuropsychiatric phenotypes remain poorly understood and their rarity will likely to prevent individual association studies. Prior studies concentrated on the most recurrent CNVs, leaving more than 90% of these variants undocumented. Second, for CNVs frequent enough to be studied individually, the full spectrum of phenotypic variation is unknown because ascertainment has been performed through neurodevelopmental and specialty clinics, which presumably represent the severe end of the phenotypic spectrum. Only a few studies have been conducted in unselected populations. Finally, many CNVs seem to impact the same neuropsychiatric domains, suggesting a poly/omnigenic model for psychiatric symptomatology, RDoC domains and neurocognitive ability. Based on this hypothesis, our previous work has shown that genetic scores and functional annotations can accurately predict the effect of any CNV on IQ but these approaches have not yet been extended beyond IQ to other dimensional neuropsychiatric phenotypes. We will fill these knowledge gaps with a novel, multidisciplinary, collaborative project that leverages existing archival data (n=255,303) to estimate and predict the effect sizes of CNVs (duplications and deletions) on dimensional neuropsychiatric phenotypes.
Our aims i nclude 1) phenotypic harmonization; 2) characterizing previously identified risk CNVs for mental illness in a large in general population cohorts and in samples ascertained for mental illnesses; 3) examine the contribution of common variants to variable expressivity of rare CNVs via polygenic risk scores (PRS) in the domains of mood, psychosis, developmental disability, and general cognitive ability; and 4) develop novel models to explain the effect size of any rare CNVs on dimensional neuropsychiatric phenotypes. Finally, we will develop tools for data sharing. Dr. David Glahn, Boston Children's Hospital, Dr. Laura Almasy, Children's Hospital of Philadelphia, and Dr. Sbastien Jacquemont, Centre Hospitalier Universitaire Sainte-Justine, are co-principal investigators on this application and bring complementary domains of expertise to the project. As this project involves analysis of existing archival data, it is an exceptionally cost-effective approach to better characterizing the rare genetic variants and elucidating general principles regarding the genetic architecture of dimensional neuropsychiatric phenotypes. Our application is responsive to RFA-MH-19-200.
Rare genetic variants, particularly copy number variants (CNV), are strongly associated with risk for neuropsychiatric disorders. By studying the effects of CNVs on a wide array of neuropsychiatric traits in over 250,000 individuals, our study will provide insights into how CNVs confer risk for mental illness.
