One of the most important tasks in human genetics is to search for disease susceptibility genes. Linkage and association analyses are two major approaches for disease-gene mapping. Chapter 1 reviewed the development of disease-gene mapping methods in the past decades. Gene mapping of complex human diseases often results in the identification of multiple potential risk variants within a gene and/or in the identification of multiple genes within a linkage peak. Thus a question of interest is to test whether the linkage result can be explained in part or in full by the candidate SNP if it shows evidence of association, and then provide some guidance for the next time-consuming step of positional cloning of susceptibility genes. Two methods, GIST and LAMP, which access whether the SNP can partially or fully account for the linkage signal in the region identified by a linkage scan, are evaluated on Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis (RA) data and discussed in Chapter 2. The simulation results showed that GIST is simple and works slightly better than LAMP-LE test when there is little linkage evidence, LAMP linkage test has limited power when there is not much linkage evidence, and LAMP association test is the best not only when the linkage evidence is extremely high, but also when there is some LD between the candidate SNP and the trait locus. The fact that complex traits are often determined by multiple genetic and environmental factors with small-to-moderate effects makes it important to investigate the behavior of current association methods under multiple risk variants model. In Chapter 3, we compared APL, FBAT, LAMP, APL-Haplotype, FBAT-LC and APL-OSA conditional test in five multiple risk variants models. The simulation results showed that the power of single marker association tests is closely correlated with the amount of LD between marker and disease loci, and these tests maintain good power to detect multiple risk variants in a small region with moderate degree of LD for fully genotyped families. Global tests, such as FBAT-LC are sensitive to the presence of at least one susceptibility variant, but are not helpful for selecting the most promising SNPs for further study. We reported that if multiple haplotypes are associated with different disease loci, the haplotype tests results can be misleading while APL-OSA conditional test has the greatest power to properly dissect the clustered associated markers for all models with an acceptable type I error rate ranging from 0.033 to 0.056. We applied APL-OSA conditional test on GENECARD samples, and got reasonable results. One linkage region of particular interest on chromosome 3 was identified by two independent genome linkage scan with Coronary Artery Disease (CAD). Multiple disease susceptibility genes have been reported from this region, and there are also linkage evidence that this region may harbors a gene or genes determining HDL-C levels. Within this region, a search for HDL-C QTL and analyses of the relationship between genetic variants, HDL-C level to CAD risk are discussed in Chapter 4. We performed CAD association and HDL-C QTL analysis on two independent datasets. We identified SNP rs2979307 in the OSBPL11 gene which survives a Bonferroni correction. We observed different HDL-C trends with HDL-C associated SNPs. Even with the evident heterogeneity presented in our CAD population, we detected several association signals with SNPs in KALRN, MYLK, CDGAP and PAK2 genes in both CAD datasets for HDL-C, where all these genes belong to a Rho pathway.
| Identifer | oai:union.ndltd.org:NCSU/oai:NCSU:etd-06122008-114358 |
| Date | 04 August 2008 |
| Creators | Lou, Xuemei |
| Contributors | Greg Gibson, Eric Stone, Elizabeth R. Hauser, Zhao-Bang Zeng |
| Publisher | NCSU |
| Source Sets | North Carolina State University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://www.lib.ncsu.edu/theses/available/etd-06122008-114358/ |
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