Principal Investigator: Dr Santhosh Girirajan
Pennsylvania State University, University Park, Pennsylvania, USATags: 45023, Autism, Complex Traits, copy-number variants, genetic interactions, Machine Learning, neurodevelopment
Rare copy-number variants (CNVs), which are large regions of DNA spanning multiple genes that are either duplicated or deleted in an individual, have been associated with several developmental disorders, including autism, schizophrenia, and intellectual disability. In many cases, individuals with the same CNV have very different clinical features. For example, only 40% of individuals with a deletion on chromosome 16p11.2 have autism, while intellectual disability, epilepsy and obesity are also observed in carriers of the deletion. Because of this, it is likely that multiple genes within each CNV region interact with each other and other genes with mutations outside of the CNV to produce the unique set of clinical features in eachindividual. In this study, we plan to use the UK BioBank data to explore complex interactions between genes that underlie the clinical features of CNVs. We will first identify individuals with developmental disorders in the UK BioBank cohort, and compare frequencies of CNVs between each group with a group of healthy individuals to identify any CNVs that have not been previously described. Next, we will develop new computational methods to uncover associations between genes within CNV regions and specific clinical features, such as an association between genes that function early in development and autism. We will finally map genes associated with clinical features to networks of gene interactions to see if they interact with each other and share a similar function. Our project, which will last for three years, will hopefully identify common functions of genes within CNV regions that are associated with the clinical features of CNV carriers. This will allow researchers to test whether drugs that affect the same functions can be used to treat the clinical features of CNV carriers. Further, if we identify any new CNVs in our study, individuals carryingthose CNVs will be able to receive a genetic diagnosis and potential treatment options for their clinical feature.
Rare pathogenic copy-number variants (CNVs) are often characterized by variable expressivity of neuropsychiatric features among carriers of the same variant. This suggests a role for complex genetic interactions among genes both within the CNV region and with variants in the genetic background towards these clinical features. We propose to use the UK BioBank genomic and clinical datasets to understand the genetic complexity of neurodevelopmental features. We will first identify pathogenic CNVs among individuals with specific neurodevelopmental disorders, such as autism, intellectual disability and schizophrenia, as well as healthy control individuals within the cohort. Next, we will use machine-learning methods to correlate CNVs with phenotypes, and look for associations between genes affected by CNVs with individual neuropsychiatric phenotypes. Finally, we will identify potential interactions between genes within CNV regions associated with neurodevelopmental phenotypes. We hope to identify novel variants, interactions and biological pathways that modulate the neurodevelopmental phenotypes of individual genes within CNV regions.
The availability of both microarray and exome sequencing data for individuals in the UK BioBank will allow us to extend our analysis of associations between genes and specific neurodevelopmental phenotypes to include genes disrupted by both CNVs and SNVs. We will also be able to identify interactions between genes within CNV regions and variants in the genetic background to better understand the pathogenicity of variably expressive CNVs.
Last updated Sep 16, 2019