Somatic Mosaicism in Neuropsychiatric Disorders

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Project Abstract In the United States, neuropsychiatric disorders are the leading cause of disability. These disorders can have deep consequences on different dimensions of the individual such as social and emotional. The standard of diagnosis is based on relatively subjective criteria that tends to dichotomize disease categories, even when individuals have a spectrum of presentations. This discordance emphasizes the need to further understand the underlying patient biology. In the proposed study, I will focus on Schizophrenia (SCZ), Bipolar disorder (BP), and ADHD, because even though they have many clinical differences they contribute to a great proportion of years lived with disability in the United states, with a combined 4.38%. In addition, SCZ is one of the top 10 global causes of disability. Even though the great health burden of these disorders is known, their biological mechanism remains greatly unknown. Genetic studies have implicated a strong genetic component for these disorders, including inherited variants, as well as rare de novo mutations. However, it has recently been proposed that somatic mosaicism might contribute partly to the missing risk. Somatic mutations have shown to play an important pathogenic role in several neurodevelopmental disorders such epileptic focal cortical dysplasia, Sturge-Weber disorder. Our lab and others have implicated mosaic single nucleotide variants (SNVs) as well as copy number variants (CNVs) to autism spectrum disorder (ASD). Strong overlap in the genetic architecture of ASD in multiple neuropsychiatric disorders has been reported. This observation poses the question of whether somatic mutations could contribute to the genetic architecture of SCZ and related disorders. With this grant, I propose to systematically test and characterize the contribution of somatic mutations to the genetic architecture of neuropsychiatric disorders such as SCZ, BP, and ADHD. Aim 1 proposes to test the hypothesis that mosaic copy number variants (CNVs) contribute to these disorders. This will be accomplished by leveraging a recently developed method by our collaborator Prof. Po Ru Loh. I will enhance the robustness of the algorithm to varying array platforms to exploit large case-control SNP array databases. This method will allow for the systematic identification and burden quantification of mosaic CNVs across large datasets of SCZ, BP, ADHD from the Psychiatric Genomic Consortium. Aim 2 proposes to test the hypothesis that mosaic SNVs contribute to these disorders. This will be accomplished by developing methodology to identify mosaic SNVs from brain derived RNA-seq data, since there have been growing brain derived RNA-seq databases for neuropsychiatric disorders with enough coverage to identify somatic SNVs compared to whole exome and whole genome sequencing efforts. With this novel method it will be possible to systematically characterize mutational burden and patterns across SCZ and BP from readily available datasets from PsychEncode, CommonMind, and BrainSpan.