THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.

Physical and functional interaction between the dopamine transporter and the synaptic vesicle protein synaptogyrin-3.

Uptake through the dopamine transporter (DAT) represents the primary mechanism used to terminate dopaminergic transmission in brain. Although it is well known that dopamine (DA) taken up by the transporter is used to replenish synaptic vesicle stores for subsequent release, the molecular details of this mechanism are not completely understood. Here, we identified the synaptic vesicle protein synaptogyrin-3 as a DAT interacting protein using the split ubiquitin system. This interaction was confirmed through coimmunoprecipitation experiments using heterologous cell lines and mouse brain. DAT and synaptogyrin-3 colocalized at presynaptic terminals from mouse striatum. Using fluorescence resonance energy transfer microscopy, we show that both proteins interact in live neurons. Pull-down assays with GST (glutathione S-transferase) proteins revealed that the cytoplasmic N termini of both DAT and synaptogyrin-3 are sufficient for this interaction. Furthermore, the N terminus of DAT is capable of binding purified synaptic vesicles from brain tissue. Functional assays revealed that synaptogyrin-3 expression correlated with DAT activity in PC12 and MN9D cells, but not in the non-neuronal HEK-293 cells. These changes were not attributed to changes in transporter cell surface levels or to direct effect of the protein-protein interaction. Instead, the synaptogyrin-3 effect on DAT activity was abolished in the presence of the vesicular monoamine transporter-2 (VMAT2) inhibitor reserpine, suggesting a dependence on the vesicular DA storage system. Finally, we provide evidence for a biochemical complex involving DAT, synaptogyrin-3, and VMAT2. Collectively, our data identify a novel interaction between DAT and synaptogyrin-3 and suggest a physical and functional link between DAT and the vesicular DA system.

A case-control study of hepatitis C virus and its interaction with hepatitis B virus on the development of hepatocellular carcinoma in the USA

Objective. The aim of this study was to assess the independent risk of hepatitis C virus (HCV) infection in the development of hepatocellular carcinoma (HCC). The independent risk of hepatitis B virus (HBV), its interaction with hepatitis C virus and the association with other risk factors were examined.^ Methods. A hospital-based case-control study was conducted between January 1994 and December 1995. We enrolled 115 pathologically confirmed HCC patients and 230 nonliver cancer controls, who were matched by age ($\pm$5 years), gender, and year of diagnosis. Both cases and controls were recruited from The University of Texas M. D. Anderson Cancer Center at Houston. The risk factors were collected through personal interviews and blood samples were tested for HCV and HBV markers. Univariate and multivariate analyses were performed through conditional logistic regression.^ The prevalence of anti-HCV positive is 25.2% in HCC cases compared to 3.0% in controls. The univariate analysis showed that anti-HCV, HBsAg, alcohol drinking and cigarette smoking were significantly associated with HCC, however, family history of cancer, occupational chemical exposure, and use of oral contraceptive were not. Multivariate analysis revealed a matched odds ratio (OR) of 10.1 (95% CI 3.7-27.4) for anti-HCV, and an OR of 11.9 (95% CI 2.5-57.5) for HBsAg. However, dual infection of HCV and HBV had only a thirteen times increase in the risk of HCC, OR = 13.9 (95% CI 1.3-150.6). The estimated population attributable risk percent was 23.4% for HCV, 12.6% for HBV, and 5.3% for both viruses. Ever alcohol drinkers was positively associated with HCC, especially among daily drinkers, matched OR was 5.7 (95% CI 2.1-15.6). However, there was no significant increase in the risk of HCC among smokers as compared to nonsmokers. The mean age of HCC patients was significantly younger among the HBV(+) group and among the HCV(+)/HBV(+) group, when compared to the group of HCC patients with no viral markers. The association between past histories of blood transfusion, acupuncture, tattoo and IVDU was highly significant among the HCV(+) group and the HBV(+)/HCV(+) group, as compared to HCC patients with no viral markers. Forty percent of the HCC patients were pathologically or clinically diagnosed with liver cirrhosis. Anti-HCV(+) (OR = 3.6 95% CI 1.5-8.9) and alcohol drinking (OR = 2.7 95% CI 1.1-6.7), but not HBsAg, are the major risk factors for liver cirrhosis in HCC patients.^ Conclusion. Both hepatitis B virus and hepatitis C virus were independent risk factors for HCC. There was not enough evidence to determine the interaction between both viruses. Only daily alcoholic drinkers showed increasing risk for HCC development, as compared to nondrinkers. ^