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.

Epithelial ovarian cancer is the leading cause of death by gynaecological malignancy. Elucidation of the driver genes of ovarian cancer will lead to treatment targets and tailored therapy for this disease. The Affymetrix Genome-Wide SNP Array 6.0 was used to study 100 serous ovarian samples and 10 normal ovarian samples to identify loci and driver genes. The ovarian cancer genome was found to have high overall genomic instability across all chromosomes and key known genes in this disease were identified in the dataset. Aberrant regions of copy number gain were located in “blocks” of constant copy number at 1p, 1q, 8q, 12p, 19q and 20q. The range in copy number for gains was 4.2 to 5.1. The “blocks” of genes were located at 8p and 5p for copy number losses. The range for copy number loss was 0.6 to 0.9.

Epithelial ovarian cancer is the leading cause of death by gynaecological malignancy. Elucidation of the driver genes of ovarian cancer will lead to treatment targets and tailored therapy for this disease. The Affymetrix Genome-Wide SNP Array 6.0 was used to study 100 serous ovarian samples and 10 normal ovarian samples to identify loci and driver genes. The ovarian cancer genome was found to have high overall genomic instability across all chromosomes and key known genes in this disease were identified in the dataset. Aberrant regions of copy number gain were located in “blocks” of constant copy number at 1p, 1q, 8q, 12p, 19q and 20q. The range in copy number for gains was 4.2 to 5.1. The “blocks” of genes were located at 8p and 5p for copy number losses. The range for copy number loss was 0.6 to 0.9.

Copy number variation (CNV) is a class of genetic variation where large segments of the genome vary in copy number among different individuals. It has become clear in the past decade that CNV affects a significant proportion of the human genome and can play an important role in human disease. With array-based copy number detection and the current generation of sequencing technologies, our ability to discover genetic variants is running far ahead of our ability to interpret their functional impact. One approach to close this gap is to explore statistical association between genetic variants and phenotypes. In contrast to the successes of genome-wide association studies for common disease using common single nucleotide polymorphism (SNP) as markers, the majority of disease CNVs discovered so far have low population frequencies and are mainly involved in rare developmental disorders. Another strategy to improve interpretation of genomic variants is to establish a predictive understanding of their functional impact. Large heterozygous deletions are of particular interest, since (i) loss-of-function (LOF) of coding sequences encompassed by large deletions can be relatively unambiguously ascribed and (ii) haploinsufficiency (HI), wherein only one functional copy of a gene is not sufficient to maintain normal phenotype, is a major cause of dominant diseases. This thesis explored both approaches. Initially, I developed an informatics pipeline for robust discovery of CNVs from large numbers of samples genotyped using the Affymetrix whole-genome SNP array 6.0, to support both the association-based and prediction-based study. For the disease association strategy, I studied the role of both common and rare CNVs in severe early-onset obesity using a case-control design, from which a rare 220kb heterozygous deletion at 16p11.2 that encompasses SH2B1 was found causal for the phenotype and an 8kb common deletion upstream of NEGR1 was found to be significantly associated with the disease, particularly in females. Using the prediction-based approach, I characterized the properties of HI genes by comparing with genes observed to be deleted in apparently healthy individuals and I developed a prediction model to distinguish HI and haplosufficient (HS) genes using the most informative properties identified from these comparisons. An HI-based pathogenicity score was devised to distinguish pathogenic genic CNVs from benign genic CNVs. Finally, I proposed a probabilistic diagnostic framework to incorporate population variation, and integrate other sources of evidence, to enable an improved, and quantitative, identification of causal variants.

Thesis advisor: Gabor T. Marth / Structural variations (SVs), like single nucleotide polymorphisms (SNPs) and short insertion-deletion polymorphisms (INDELs), are a ubiquitous feature of genomic sequences and are major contributors to human genetic diversity and disease. Due to technical difficulties, i.e. the high data-acquisition cost and/or low detection resolution of previous genome-scanning technologies, this source of genetic variation has not been well studied until the completion of the Human Genome Project and the emergence of next-generation sequencing (NGS) technologies. The assembly of the human genome and economical high-throughput sequencing technologies enable the development of numerous new SV detection algorithms with unprecedented accuracy, sensitivity and precision. Although a number of SV detection programs have been developed for various SV types, such as copy number variations, deletions, tandem duplications, inversions and translocations, some types of SVs, e.g. copy number variations (CNVs) in capture sequencing data and mobile element insertions (MEIs) have undergone limited study. This is a result of the lack of suitable statistical models and computational approaches, e.g. efficient mapping method to handle multiple aligned reads from mobile element (ME) sequences. The focus of my dissertation was to identify and characterize CNVs in capture sequencing data and MEI from large-scale whole-genome sequencing data. This was achieved by building sophisticated statistical models and developing efficient algorithms and analysis methods for NGS data. In Chapter 2, I present a novel algorithm that uses the read depth (RD) signal to detect CNVs in deep-coverage exon capture sequencing data that are originally designed for SNPs discovery. We were one of the early pioneers to tackle this problem. In Chapter 3, I present a fast, convenient and memory-efficient program, Tangram, that integrates read-pair (RP) and split-read (SR) signals to detect and genotype MEI events. Based on the results from both simulated and experimental data, Tangram has superior sensitivity, specificity, breakpoint resolution and genotyping accuracy, when compared to other recently published MEI detection methods. Lastly, Chapter 4 summarizes my work for SV detection in human genomes during my PhD study and describes the future direction of genetic variant researches. / Thesis (PhD) — Boston College, 2013. / Submitted to: Boston College. Graduate School of Arts and Sciences. / Discipline: Biology.

Schizophrenia is a genetically complex neuropsychiatric disease. Myths and uncertainty about aetiology, and concerns about familial recurrence, may contribute to the significant stigma and burden on families. There has recently been concrete progress in understanding individual genetic causes of schizophrenia, which are now known to extend beyond 22q11.2 microdeletions to include other large rare copy number variations. However, there are limited data on issues germane to the translation of these genetic discoveries into clinical practice. The aim of this thesis was to evaluate the contemporary clinical applicability of genetic testing and genetic counselling in schizophrenia. First, general genetic counselling was provided to both adults with schizophrenia without individually relevant genetic test results and their family members. Pre-counselling, there was evidence of widespread misconceptions about schizophrenia aetiology and familial recurrence risks, which were associated with considerable psychological distress. Post-counselling, the myriad significant lasting benefits of genetic counselling included reductions in stigma. The results provided initial evidence of need for, and efficacy of, genetic counselling for schizophrenia. A first ever study was then conducted of the impact of providing a specific aetiological explanation for schizophrenia. Affected individuals and family members were found to value a molecular genetic diagnosis of a 22q11.2 microdeletion for its ability to explain the presence of stigmatized neuropsychiatric conditions. An investigation of transmission patterns and reproductive fitness associated with 22q11.2 microdeletions provided novel insights into the evolutionary biology and clinical correlates of this structural rearrangement. The results demonstrated the scientific and clinical benefits of identifying a genetic subtype of schizophrenia. Last, high resolution genome-wide microarrays were used to investigate rare copy number variations in a prospectively recruited community-based schizophrenia cohort. Clinically significant variants were greatly enriched in schizophrenia, even with 22q11.2 microdeletions a priori excluded. The collective prevalence of these genetic variants in a single community catchment area was high, approaching that seen in autism, where clinical microarray testing is now a first-tier diagnostic test. Collectively, the findings of these pioneering studies suggest a role for genetic testing and genetic counselling in the contemporary management of schizophrenia.

Schizophrenia is a genetically complex neuropsychiatric disease. Myths and uncertainty about aetiology, and concerns about familial recurrence, may contribute to the significant stigma and burden on families. There has recently been concrete progress in understanding individual genetic causes of schizophrenia, which are now known to extend beyond 22q11.2 microdeletions to include other large rare copy number variations. However, there are limited data on issues germane to the translation of these genetic discoveries into clinical practice. The aim of this thesis was to evaluate the contemporary clinical applicability of genetic testing and genetic counselling in schizophrenia. First, general genetic counselling was provided to both adults with schizophrenia without individually relevant genetic test results and their family members. Pre-counselling, there was evidence of widespread misconceptions about schizophrenia aetiology and familial recurrence risks, which were associated with considerable psychological distress. Post-counselling, the myriad significant lasting benefits of genetic counselling included reductions in stigma. The results provided initial evidence of need for, and efficacy of, genetic counselling for schizophrenia. A first ever study was then conducted of the impact of providing a specific aetiological explanation for schizophrenia. Affected individuals and family members were found to value a molecular genetic diagnosis of a 22q11.2 microdeletion for its ability to explain the presence of stigmatized neuropsychiatric conditions. An investigation of transmission patterns and reproductive fitness associated with 22q11.2 microdeletions provided novel insights into the evolutionary biology and clinical correlates of this structural rearrangement. The results demonstrated the scientific and clinical benefits of identifying a genetic subtype of schizophrenia. Last, high resolution genome-wide microarrays were used to investigate rare copy number variations in a prospectively recruited community-based schizophrenia cohort. Clinically significant variants were greatly enriched in schizophrenia, even with 22q11.2 microdeletions a priori excluded. The collective prevalence of these genetic variants in a single community catchment area was high, approaching that seen in autism, where clinical microarray testing is now a first-tier diagnostic test. Collectively, the findings of these pioneering studies suggest a role for genetic testing and genetic counselling in the contemporary management of schizophrenia.

No description available.

In recent years, microarray technology has revealed the widespread presence of submicroscopic deletions and duplications throughout the human genome termed copy number variants (CNVs). CNVs have a profound effect on gene expression and are an important source of normal genetic variation. In addition, a small proportion of CNVs contribute to genetically simple and complex disease. This thesis focuses on the identification of pathogenic CNVs contributing to the etiology of diseases with "missing heritability" using a well-planned study design individually tailored to each disease cohort to optimize CNV detection and interpretation. We performed a genome-wide analysis for CNVs in five disease cohorts with genetic etiology: autism, age-related macular degeneration (AMD), glaucoma, clubfoot, and Bardet-Biedl syndrome (BBS). Our results indicate that CNVs likely account for a proportion of cases for each disease cohort reported in this thesis. Approximately 20% of our cohort of individuals with autism from trio pedigrees harbors a CNV known to confer risk to develop autism and we identified other novel and rare variants that may play a role in autism pathogenesis. We also characterized a duplication of 2p25.3 identified in two male half-siblings with autism and determined that their mother was somatic mosaic for the duplication. Our work provides evidence that this novel CNV disrupting the genes PXDN and MYT1L are the autism-causing mutation in this pedigree. A comparative cases experimental design was used in the study of AMD and glaucoma. While no common "risk CNVs" were identified for either eye disorder, we did identify several rare overlapping CNVs disrupting genes known to play a role in the eye that may confer risk to disease in a small proportion of individuals. In a fourth genetically complex disease, clubfoot, we identified a duplication of 17q23.2 disrupting the genes TBX4, NACA2, and BRIP1 that segregates with the autosomal dominant clubfoot phenotype in a large pedigree with 16 affected individuals. In addition, the duplication is within the linkage interval identified for this family. We also applied microarray technology to analyze the genomes of individuals with BBS, an autosomal recessive disorder, for the presence of CNVs in known BBS genes as well as CNVs that elucidate novel candidate genes for BBS. From 34 BBS patients with an unidentified mutation, we observed one CNV, a heterozygous deletion of BBS10, unmasking a BBS10 frameshift mutation. A promising BBS candidate gene also emerged from our studies, implicated by an intragenic deletion of the gene MARK3 predicted to result in a frameshift and premature truncation of the protein. Functional studies utilizing antisense morpholino gene knockdown in the zebrafish provide additional evidence that MARK3 is a BBS gene as knockdown of zebrafish mark3 results in a Kupffer's Vesicle defect and a melanosome transport delay, two cardinal BBS phenotypes in the zebrafish. In addition to identifying CNVs involved in disease, the work outlined in this thesis provides valuable insight into the study design and interpretation of a genome-wide analysis of CNV. This includes the appropriate use of controls and publicly available control databases, methods for enriching for CNVs in a patient cohort to maximize efficiency and discovery, and the importance of analyzing all patient cohorts with heritable disease for the presence of CNVs disrupting known disease genes and CNVs that implicate novel genetic candidates. As the reliability and resolution of CNV detection continue to improve, allowing detection of > 1,000 CNVs in each individual genome, it becomes more important than ever to have a well-defined study design for both the detection and interpretation of CNVs.

Glaucoma is the second leading cause of irreversible blindness in the United States and is the leading cause of blindness in African Americans. Cupping or excavation of the optic nerve, which sends the visual signal from the photoreceptors in the eye to the brain, is a chief feature of glaucoma. A similar excavated appearance of the optic nerve is also the primary clinical sign of other congenital malformations of the eye including optic nerve head coloboma, optic pit, and morning glory disc anomaly collectively termed cavitary optic disc anomaly (CODA). Clinical similarities between CODA and glaucoma have suggested that these conditions may have overlapping pathophysiology. Although risk factors are known, such as the elevated intraocular pressure (IOP) observed in some glaucoma subjects, the biological pathways and molecular events that lead to excavation of the optic disc in glaucoma and in CODA are incompletely understood, which has hindered efforts to improve diagnosis and treatment of these diseases. Consequently, there is a critical need to clarify the biological mechanisms that lead to excavation of the optic nerve, which will lead to improvements in our understanding of these important disease processes. Because of their similar clinical phenotypes and the limited therapy geared at lowering IOP in glaucoma patients, our central hypothesis is that genes involved in Mendelian forms of CODA would also be involved in a subset of glaucoma cases and may provide insight into glaucomatous optic neuropathy. The purpose of my research project has been to identify and functionally characterize the gene that causes congenital autosomal dominant CODA in a multiplex family with 17 affected members. The gene that causes CODA was previously mapped to chromosome 12q14 and following screening of candidate genes within the region that did not yield any plausible coding sequence mutations, a triplication of a 6KB segment of DNA upstream of the matrix metalloproteinase 19 (MMP19) gene was subsequently identified using comparative genomic hybridization arrays and qPCR. This copy number variation (CNV) was present in all affected family members but absent in unaffected family members, a panel of 78 normal control subjects, and the Database of Genomic Variants. In a case-control study of singleton CODA subjects, CNVs were also detected; we detected the same 6KB triplication in 1 of 24 subjects screened. This subject was part of another 3-generation autosomal dominant CODA pedigree where affected members each have the same CNV identified in the larger CODA pedigree. A separate case-control study with 172 glaucoma cases (primary open angle glaucoma = 84, normal tension glaucoma = 88) was evaluated for MMP19 CNVs, however none were detected. Although our cohort of CODA patients is small limiting our ability to accurately determine the proportion of CODA caused by MMP19 mutations, our data indicates that the MMP19 CNV is not an isolated case and additional CODA subjects may have MMP19 defects. Because of the location of the CNV, we evaluated its effect on downstream gene expression with luciferase reporter gene assays. These assays revealed that the 6KB sequence spanned by the CNV in CODA subjects functioned as a transcriptional enhancer; in particular, a 773bp segment had a strong positive influence (8-fold higher) on downstream gene expression. MMP19, a largely understudied gene, was further characterized by expression studies in the optic nerve and retina. Using frozen sections from normal donor eyes, we demonstrated that MMP19 is predominantly localized to the optic nerve head in the lamina cribrosa region with moderate labeling in the postlaminar region, and weak labeling in the prelaminar region and retina. We also evaluated MMP19 expression in relation to the cell types that populate the optic nerve such as astrocytes and retinal ganglion cells. The pattern of expression is consistent with MMP19 being a secreted protein accumulating in the extracellular spaces and basement membranes of the optic nerve. Our studies have identified the first gene associated with CODA and future research is focused on recapitulating CODA phenotypes in animal models and assessing the mechanism of MMP19 involvement during development.