Date of Award

2009

Degree Type

Thesis

Degree Name

Master of Science

Program

Biology

Supervisor

Dr. Shiva Singh

Abstract

Schizophrenia (MIM 181500) is a complex and devastating human disease that affects greater than 1% of the population (Huxley et al., 1964). The disease has a heritability of 80%, but a concordance rate in monozygotic (MZ) twins of only 48% (Gottesman, 1991). This suggests a role for both genetics and random/environmental factors in the etiology of this complex disorder (Singh et al., 2009). Copy Number Variation (CNV) is now a known candidate for disease associated variation in humans. CNVs have been identified as a common feature covering 12% of the genome in normal, healthy individuals (Feuk et al., 2006; Redon et al., 2006). Although little is known about the causes and consequences of this common genomic phenomenon, CNVs represent causal mutational events in any study of genetic causes of complex diseases. This study focuses on monozygotic twins who represent the best possible genetic match, but are discordant for the disease; this approach' allows for a significant reduction of disease heterogeneity. A genome wide analysis of copy number variation on three pairs of monozygotic twins was performed using the Affymetrix Human Array 6.0. The results show that they differ significantly in variation profile and that the affected member of each twin pair had a significantly higher number of CNV when compared to their unaffected co-twin (p=0.01). In addition, a set of five de novo CNV’s were found to be shared in all three unrelated patients. These regions contain genes, many of which play a role in neurodevelopment and have the potential to cause schizophrenia pathogenesis. The results support a role for de novo CNVs in the etiology of schizophrenia.

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.