Genomic copy number variation in schizophrenia

Danielle Song Rudd

doi:10.17077/etd.ezs0wnfu

Schizophrenia (OMIM 181500) is an incurable and severe psychiatric disorder comprised of three symptom domains (positive symptoms, negative symptoms and cognitive impairments) with a worldwide prevalence of approximately 1%. There is a substantial amount of evidence demonstrating that schizophrenia has a strong a genetic component. Broad-sense heritability estimates range from 64-80% and first-degree relatives of schizophrenia patients have 10-fold increased risk of developing the disorder compared to the general population. It is thought that both single nucleotide polymorphisms and copy number variants (CNVs) contribute to the heritability of schizophrenia. This thesis focuses on the role of CNVs in the etiology of schizophrenia. We performed a genome-wide CNV analysis of 166 schizophrenia patients and 52 psychiatrically healthy controls. In our overall CNV analysis we did not find any significant differences between cases and controls across a variety of CNV categories, nor did we find significant differences when CNVs were partitioned by size (small, medium or large). However, we were the first group to consider small CNVs (< 100-500 kb) in a multiple-hit model where we observed that a slightly higher proportion of case subjects had two-or-more conservative CNVs. We defined a CNV as conservative if it met any of the following three criteria: 1) a known deleterious CNV, 2) a CNV > 1 Mb that was novel to the Database of Genomic Variants (DGV) or 3) a CNV < 1 Mb that was novel to the DGV and that overlapped the coding region of a gene of interest. Genes of interest included genes with a previous association with a neuropsychiatric disorder, or genes with high or specific brain expression, or an association with any other neurocognitive or neuropsychiatric disorders. Two of our case subjects who harbored the highest amount of conservative CNVs also shared a 15q11.2 breakpoint 1-2 (BP1-2) deletion which is a compelling candidate risk locus for schizophrenia. We also found that a slightly higher proportion of case subjects harbored clinically significant CNVs (conservative CNVs > 1 Mb or clinically recognized as deleterious) when compared to controls. Additionally, we hypothesized that individuals with more severe CNVs would show more neurocognitive deficits and more pronounced abnormalities in brain structure volume, however, we had largely negative results. We also reported a case of childhood-onset schizophrenia who had three large chromosomal abnormalities including a paternally inherited 2.2 Mb deletion of chromosome 3p12.2-p12.1, a de novo 17.6 Mb duplication of chromosome 16q22.3-q24.3 and a de novo 43 Mb deletion of chromosome Xq23-q28. We were able to confirm previous reports of CNV findings in schizophrenia such as the involvement of large, rare and de novo CNVs. In addition, the work in this thesis leads us to propose a multiple-hit CNV model which requires a shift in the way we currently approach schizophrenia genetics. First, we must identify all CNVs, especially those of smaller size (< 100 kb). Next, we require a more precise understanding of the impact that CNVs have on gene expression, especially in the brain. With all of the right tools in place, we can move towards a disease model for schizophrenia that considers the totality of CNVs in any given individual. We propose that the use of recurrent CNVs such as the 15q11.2 BP1-2 CNV is a good starting point for studying a multiple-hit CNV model.

Genomic copy number variation in schizophrenia

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