Bipolar affective disorder is a severe mood disorder, which is characterised by episodes of mania and depression. The aetiology of bipolar disorder remains elusive, with little known about the underlying biological, anatomical, or biochemical effects. However, family, twin and adoption studies provide evidence for a strong genetic component to the disorder. Due to the high heritability, familial clustering, and common population prevalence of the illness, molecular genetic studies can be implemented to identify bipolar disorder susceptibility genes. This thesis investigated the candidate gene serotonin 2A receptor (HTR2A), which lay within a region on chromosome 13q14 previously identified by bipolar disorder genome-wide linkage scans. Significant association was found with bipolar disorder and a SNP within intron 2 of HTR2A in an Australian case-control cohort. Haplotype association analysis identified a 5-SNP protective haplotype within HTR2A. Conducting a new genome-wide linkage scan on 35 Australian bipolar disorder pedigrees found significant evidence for linkage on chromosome 15q25-26. Subsequent fine-mapping of the region verified the linkage peak with a significant maximum multipoint LOD score of 4.58. Haplotype analysis, based on pedigree-specific, identical-by-descent allele sharing, supported the location of a bipolar susceptibility gene within a 6.2Mb confidence interval. The candidate gene sialyltransferase 8B (ST8SIA2), which had previously shown association with SNPs within the gene’s promoter region and schizophrenia in two independent Asian cohorts, lies within the chromosome 15q25-26 locus. Failing to replicate the association found with these specific SNPs, and without finding association with two additional SNPs in an upstream conserved putative regulatory region, a fine-mapping association study was conducted across the entire 6.2Mb interval. The strongest association signals were observed at SNPs 16kb upstream from and within the fourth intron of ST8SIA2. A specific bipolar disorder risk haplotype was identified for ST8SIA2, and this was also observed to be over-represented in a cohort of Australian schizophrenia cases. This finding suggests that the ST8SIA2 gene, for which strong developmental regulation was observed, may be a shared susceptibility gene for both bipolar disorder and schizophrenia. In summary, this thesis has provided evidence identifying both HTR2A and ST8SIA2 as bipolar disorder susceptibility genes.

Balancing selection refers to the maintenance of multiple phenotypic variants within a population. There are a number of proposed mechanisms explaining the origin and persistence of the evolution and genetics of polymorphisms, but they largely remain unresolved in the specific instances in which they occur. This study aims to identify the genetic basis of a polymorphism in the butterfly, Heliconius doris, which displays four distinct color patterns on the dorsal hindwings of individuals. While Mullerian mimetic theory proposes that phenotypes will converge on a common, aposematic phenotype, this is not the case in Heliconius doris. We identify an interval perfectly associated with the presence/absence of the red ray phenotype, and propose potential mechanisms and genetic architecture through which this polymorphism has been allowed to persist.

No description available.

BACKGROUND:Airway hyperresponsiveness (AHR), a primary characteristic of asthma, involves increased airway smooth muscle contractility in response to certain exposures. We sought to determine whether common genetic variants were associated with AHR severity.METHODS:A genome-wide association study (GWAS) of AHR, quantified as the natural log of the dosage of methacholine causing a 20% drop in FEV1, was performed with 994 non-Hispanic white asthmatic subjects from three drug clinical trials: CAMP, CARE, and ACRN. Genotyping was performed on Affymetrix 6.0 arrays, and imputed data based on HapMap Phase 2, was used to measure the association of SNPs with AHR using a linear regression model. Replication of primary findings was attempted in 650 white subjects from DAG, and 3,354 white subjects from LHS. Evidence that the top SNPs were eQTL of their respective genes was sought using expression data available for 419 white CAMP subjects.RESULTS:The top primary GWAS associations were in rs848788 (P-value 7.2E-07) and rs6731443 (P-value 2.5E-06), located within the ITGB5 and AGFG1 genes, respectively. The AGFG1 result replicated at a nominally significant level in one independent population (LHS P-value 0.012), and the SNP had a nominally significant unadjusted P-value (0.0067) for being an eQTL of AGFG1.CONCLUSIONS:Based on current knowledge of ITGB5 and AGFG1, our results suggest that variants within these genes may be involved in modulating AHR. Future functional studies are required to confirm that our associations represent true biologically significant findings.

Data from a Croatian isolate population are analysed in a genome-wide association study (GWAS) for a variety of disease-related quantitative traits. A novel genomewide approach to analysing pedigree-based association data called GRAMMAR is utilised. One of the significant findings, for uric acid, is followed up in greater detail, and is replicated in another isolate population, from Orkney. The associated SNPs are located in the SLC2A9 gene, coding for a known glucose transporter, which leads to identification of SLC2A9 as a urate transporter too (Vitart et al., 2008). These SNPs are later implicated in affecting gout, a disease known to be linked with high serum uric acid levels, in an independent study (Dehghan et al., 2008). Subsequently, investigation into different ways in which to use SNP data to identify quantitative trait loci (QTL) for genome-wide association (GWA) studies is performed. Several multi-marker approaches are compared to single SNP analysis using simulated phenotypes and real genotype data, and results show that for rare variants haplotype analysis is the most effective method of detection. Finally, the multi-marker methods are compared with single SNP analysis on the real uric acid data. Interpretation of real data results was complicated due to low sample size, since only founder and unrelated individuals may be used for population-based haplotype analysis, nonetheless, results of the prior analyses of simulated data indicate that multi-marker methods, in particular haplotypes, may greatly facilitate detection of QTL with low minor allele frequency in GWA studies.

As a large number of single nucleotide polymorphisms (SNPs) and microsatellite markers are available, high resolution mapping employing multiple markers or multiple allele markers is an important step to identify quantitative trait locus (QTL) of complex human disease. For many complex diseases, quantitative phenotype values contain more information than dichotomous traits do. Much research has been done on conducting high resolution mapping using information of linkage and linkage disequilibrium. The most commonly employed approaches for mapping QTL are pedigree-based linkage analysis and population-based association analysis. As one of the methods dealing with multiple alleles markers, mixed models are developed to work out family-based association study with the information of transmitted allele and nontransmitted allele from one parent to offspring. For multiple markers, variance component models are proposed to perform association study and linkage analysis simultaneously. Linkage analysis provides suggestive linkage based on a broad chromosome region and is robust to population admixtures. One the other hand, allelic association due to linkage disequilibrium (LD) usually operates over very short genetic distance, but is affected by population stratification. Combining both approaches plays a synergistic role in overcoming their limitations and in increasing the efficiency and effectiveness of gene mapping.

Purpose¡G Many single nucleotide polymorphisms (SNPs) have been found to be associated with breast cancer but their SNP interactions are seldom addressed. In this study, we focused on the joint effect for SNP combinations of seven CXCL12-related genes involved in major cancer related pathways. Patients and Methods¡G SNP genotyping was determined by PCR-restriction fragment length polymorphism (RFLP) in this study (case = 220, control = 334). Different numbers of combinational SNPs with genotypes called the pseudo-haplotypes from different chromosomes were used to evaluate their joint effect on breast cancer risk. Results¡G Except for VEGF rs3025039-CT, none of these SNPs was found to individually contribute to breast cancer risk. However, for two combined SNPs, the proportion of subjects with breast cancer was significantly low in the pseudo-haplotype with CC-GG genotypes in rs2228014-1801157 (CXCR4-CXCL12) compared to those with non-CC-GG genotypes. Similarly, the pseudo-haplotype of rs12812942-rs2228014-rs3025039 (CD4-CXCR4-CXCL12) And rs12812942-rs3136685-rs2228014 -rs1801157(CD4-CCR7-CXCR4-CXCL12)with specific genotype pattern (AT-CC-CC and AT-AG-CC-GG) among three and four combinational SNPs were significantly low in breast cancer occurrence. More SNP combinations larger than five SNPs were also addressed and shown the similar effect. After controlling for age, comparing to their corresponding non-pseudo-haplotypes, the estimated odds ratios for breast cancer ranged between 0.20 and 0.71 for specific pseudo-haplotypes with two to seven SNPs. Conclusion¡G We have identified the potential combined CXCL12-related SNPs with genotypes that were protective against breast cancer and may have an impact on identification of a low risk population for the development of breast cancer.

Individuals with autism spectrum disorders (ASDs) are impaired in cognitive processes and emotional regulation, and exhibit stereotyped behaviours. Dopamine (DA) modulates executive functions, learning, memory, emotional processing and social cognition; all of which are impaired in individuals with ASDs. Because DA modulates a number of processes that are impaired in individuals with ASDs, genes in the dopaminergic pathway are good candidates for genes influencing autistic behaviours. As our previous findings suggested a role for a dopamine-related gene in families with only affected males, this thesis describes a comprehensive study of five genes affecting DA synthesis, levels and function in mothers and affected males with ASDs in an initial TEST cohort of 112 male-only affected sib-pair families as well as a replication study in three additional male-only family cohorts. I genotyped three to five polymorphisms in the TH, SLC6A3, DRD1, DRD2 and PPP1R1B genes and performed population-based single marker case-control comparisons, family-based association tests, quantitative transmission disequilibrium tests as well as haplotype-based analyses and tests for gene-gene interactions. I found evidence for association of the DRD1 (P=0.0027-0.040), DRD2 (P=0.0002-0.007) and PPP1R1B (P=0.00042-0.001) genes with autism in affected males from the TEST cohort. Evidence for DA-related gene interactions were found between polymorphisms in DRD1, DRD2 and PPP1R1B (P=0.0094-0.012) in affected males relative to a comparison group. Furthermore, I found that polymorphisms in the TH and DRD1 genes were associated with the risk for mothers having sons with ASD in the TEST families (P=0.007-0.025) and putative risk alleles in DRD1 and DRD2 were preferentially transmitted from mothers (P=0.016) and fathers (P=0.023) respectively, to affected children. All findings remained significant following corrections for multiple testing. The TEST cohort findings were not replicated in other family cohorts. However, an examination of dysmorphology data for the different family sets revealed phenotypic differences and thus, genetic differences are to be expected. In summary, I found evidence for a contribution of DA-related genes in a specific family cohort with ASDs. Additional functional and phenotypic studies will enable a better understanding of the contributions and implications of these findings to our understanding of autism. / Thesis (Ph.D, Physiology) -- Queen's University, 2009-03-18 13:58:12.223

Obesity is a complex and a highly individualized disease and the molecular mechanisms behind this disorder need to be better elucidated. Identification of genes and genetic variants that are involved provide opportunities to establish a genetic understanding of the disease. These findings may also provide more rational approaches to therapy, either by identifying underlying causes or point out the need for different treatments. In addition, the timing and severity of obesity may provide insights into the aetiology of obesity and also identify age-specific determinants of weight gain. Recently, genome-wide association studies have led to a rapid progress in our understanding of the genetic basis of various diseases and candidate genes for obesity have been identified. The overall aim of this thesis was to investigate the genetic impact on severity of childhood obesity and the associations between obesity and genetic variants in the fat mass and obesity associated gene, FTO, and MGAT1, the gene encoding mannosyl (α-1,3-)-glycoprotein β-1,2-N-acetyl-glucosaminyltransferase. We show that the impact of parental body mass index (BMI) on the severity of obesity in children is strengthened as the child grows older, whereas the age at obesity onset is of limited importance. By association studies, we show that single nucleotide polymorphisms downstream MGAT1 influence susceptibility to obesity. Moreover, these variants affect the levels of unsaturated fatty acids and desaturase indices, variables previously shown to correlate with obesity. Furthermore, one variant in the first intronic region of FTO is associated with obesity among children but not with BMI or other measures of adiposity at older ages. However, this variant shows a weight-dependent association with cognitive function among elderly men. By direct sequencing, we identified novel variants in FTO, affecting glucose homeostasis in a BMI-independent manner. Furthermore, we found gender specific effects for FTO, both regarding obesity susceptibility and related phenotypes.

Source: Dissertation Abstracts International, Volume: 69-10, Section: B, page: 5857. Adviser: Momiao Xiong. Includes bibliographical references (leaves xx-xx).