Variance Component Score Statistics for QTL Mapping

Variance Components based models are commonly used for linkage and association mapping of quantitative traits. Score Tests based on these models are generally more robust to various modeling assumptions than the corresponding likelihood ratio tests. They are also computationally much simpler than the likelihood ratio tests, making them the natural choice for whole genome scans, which have become increasingly common with the emergence of high-throughput genotyping technologies. However the popularity of score statistics havebeen limited, due to several practical issues, such as lack of availability of software and guidelines for choice of score statistic variants. In this dissertation, we develop novel score statistics for both linkage and association mapping, elucidate the theoretical properties of these and of the existing variants, and also compare some of the existing and proposed score variants using simulation. Analytical arguments and simulation results are used to develop guidelines for choice of appropriate score variants under different practical situations. In this dissertation, we are primarily concerned with identifying robust and powerful score statistics for detecting genetic susceptibility loci for complex diseases by mapping underlying quantitative phenotypes. Unlike Mendelian disorders, complex diseases in humans typically have a large number of modest genetic effects, which cumulatively have a significant impact on the disease. The work in this dissertation is aimed at maximizing the power of genome scans to detect more of these small genetic effects. This is of considerable public health significance, as the identified genetic variants can be followed up to gain important insights into the etiology of the disease, which can further lead to development of screening tests and preventive and therapeutic interventions for complex diseases

Linkage mapping of a complex trait in the New York population of the GAW14 simulated dataset: a multivariate phenotype approach

Multivariate phenotypes underlie complex traits. Thus, instead of using the end-point trait, it may be statistically more powerful to use a multivariate phenotype correlated to the end-point trait for detecting linkage. In this study, we develop a reverse regression method to analyze linkage of Kofendrerd Personality Disorder affection status in the New York population of the Genetic Analysis Workshop 14 (GAW14) simulated dataset. When we used the multivariate phenotype, we obtained significant evidence of linkage near four of the six putative loci in at least 25% of the replicates. On the other hand, the linkage analysis based on Kofendrerd Personality Disorder status as a phenotype produced significant findings only near two of the loci and in a smaller proportion of replicates

Analysis of Metabolic Syndrome Components in >15 000 African Americans Identifies Pleiotropic Variants: Results From the Population Architecture Using Genomics and Epidemiology Study

Metabolic syndrome (MetS) refers to the clustering of cardio-metabolic risk factors including dyslipidemia, central adiposity, hypertension and hyperglycemia in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS

A single nucleotide polymorphism associated with hepatitis C virus infections located in the distal region of the IL28B promoter influences NF-κB-mediated gene transcription.

Persistence of hepatitis C virus (HCV) infection is observed only in a subset of infected individuals and among them only some respond to treatment. Genome-wide association studies (GWAS) carried out around the world identified single nucleotide polymorphisms (SNPs) in the IL28B locus that are strongly associated with both HCV clearance and treatment response. The functional significance of these associations however, is not clear. In this report we show that an SNP rs28416813 in the distal promoter region of IL28B that is in close proximity to a non-consensus NF-κB-binding site affects downstream reporter gene expression. The effect is likely due to differential binding of NF-κB at the non-consensus site. The non-protective allele showed a reduction in luciferase reporter gene expression compared to the protective allele in HEK293T cells under different experimental conditions including treatment with tumor necrosis factor alpha (TNF-α) and 5' triphosphorylated dsRNA. Furthermore, the HCV RNA polymerase was able to induce transcription from the IL28B promoter in a RIG-I-dependent manner. This induction was influenced by the alleles present at rs28416813. We also demonstrate strong linkage disequilibrium between rs28416813 and another important SNP rs12979860 in two ethnic populations. These results suggest possible mechanisms by which SNPs at the IL28B locus influence spontaneous clearance and treatment response in chronic HCV infections