Defense Date

2013

Document Type

Thesis

Degree Name

Master of Science

Department

Human Genetics

First Advisor

Rita Shiang

Abstract

Schizophrenia is a complex disorder affecting 1% of the population and is highly heritable, but the majority of contributing genetic factors has remained elusive. Current risk estimates for clinical practice are primarily determined by family history and associated empirical risk. Copy number variants (CNVs) may hold the key to explaining the missing heritability in schizophrenia research; schizophrenia risk estimates as high as 30% have been found for the most-studied CNV associated with schizophrenia, 22q11. Currently, there are methods to identify CNVs though previously collected data from SNP microarrays that would facilitate these types of studies. To determine if algorithms that call CNVs from microarray data are robust four genomic regions with putative CNVs called by the Wellcome Trust Consortium using Birdseye in Birdsuite with Affymetrix 6.0 array raw SNP intensities, primarily affecting genes CHD1L, COX5B, PAK7, ZFYVE20, were validated using Taqman real-time qPCR assays in 29 samples by research groups at VCU and Dublin. CNVs called from the algorithm were 100% validated at VCU though there were false negatives from the algorithm that were validated. Two samples at loci with putative duplications were not called by the Dublin group, which may be because of differing sensitivities of the Taqman assays to be able to detect a 50% difference in copy number between duplications and diploid controls, or because of another technical or analytical difference between the two sites. Deletion frequency of one common CNV found in the gene ERBB4, was assessed by qPCR in both Irish singleton (ICCSS) and Irish family (IHDSF) samples and compared with Irish control (Trinity Biobank) and North American control populations. The ERBB4 deletion frequency was not significantly different when comparing the Irish controls to the Irish singleton or the Irish family samples though the family samples were different when compared against the North American control population, which suggests population stratification, rather than a true association between ERBB4 and increased schizophrenia risk. Current clinical practice has been improved by knowledge and evaluation of CNV-related disorders that include risk for psychosis and additional phenotypes. Genotyping of individuals with known psychosis has led to improved patient care for non-psychosis-related phenotypes associated with CNVs. Individuals with suspected genomic disorders that are found to have CNVs can be counseled on potential psychosis risk and potential risk to their offspring. Recurrent CNVs may hold promise in future clinical practice in order to individualize risk estimates in the general patient population, and increase the number of individuals able to receive anticipatory treatment to minimize disease severity.

Rights

© The Author

Is Part Of

VCU University Archives

Is Part Of

VCU Theses and Dissertations

Date of Submission

August 2013

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