Analysis of life expectancy using linear and nonlinear models

Life expectancy has consistently increased over the last 150 years due to improvements in nutrition, medicine, and public health. Several studies found that in many developed countries, life expectancy continued to rise following a nearly linear trend, which was contrary to a common belief that the rate of improvement in life expectancy would decelerate and was fit with an S-shaped curve. Using samples of countries that exhibited a wide range of economic development levels, we explored the change in life expectancy over time by employing both nonlinear and linear models. We then observed if there were any significant differences in estimates between linear models, assuming an auto-correlated error structure. When data did not have a sigmoidal shape, nonlinear growth models sometimes failed to provide meaningful parameter estimates. The existence of an inflection point and asymptotes in the growth models made them inflexible with life expectancy data. In linear models, there was no significant difference in the life expectancy growth rate and future estimates between ordinary least squares (OLS) and generalized least squares (GLS). However, the generalized least squares model was more robust because the data involved time-series variables and residuals were positively correlated. ^

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.

Design, Synthesis and Development of Transporter Targeting Agents for Image-guided Therapy and Drug Delivery

The purpose of this study was to design, synthesize and develop novel transporter targeting agents for image-guided therapy and drug delivery. Two novel agents, N4-guanine (N4amG) and glycopeptide (GP) were synthesized for tumor cell proliferation assessment and cancer theranostic platform, respectively. N4amG and GP were synthesized and radiolabeled with 99mTc and 68Ga. The chemical and radiochemical purities as well as radiochemical stabilities of radiolabeled N4amG and GP were tested. In vitro stability assessment showed both 99mTc-N4amG and 99mTc-GP were stable up to 6 hours, whereas 68Ga-GP was stable up to 2 hours. Cell culture studies confirmed radiolabeled N4amG and GP could penetrate the cell membrane through nucleoside transporters and amino acid transporters, respectively. Up to 40% of intracellular 99mTc-N4amG and 99mTc-GP was found within cell nucleus following 2 hours of incubation. Flow cytometry analysis revealed 99mTc-N4amG was a cell cycle S phase-specific agent. There was a significant difference of the uptake of 99mTc-GP between pre- and post- paclitaxel-treated cells, which suggests that 99mTc-GP may be useful in chemotherapy treatment monitoring. Moreover, radiolabeled N4amG and GP were tested in vivo using tumor-bearing animal models. 99mTc-N4amG showed an increase in tumor-to-muscle count density ratios up to 5 at 4 hour imaging. Both 99mTc-labeled agents showed decreased tumor uptake after paclitaxel treatment. Immunohistochemistry analysis demonstrated that the uptake of 99mTc-N4amG was correlated with Ki-67 expression. Both 99mTc-N4amG and 99mTc-GP could differentiate between tumor and inflammation in animal studies. Furthermore, 68Ga-GP was compared to 18F-FDG in rabbit PET imaging studies. 68Ga-GP had lower tumor standardized uptake values (SUV), but similar uptake dynamics, and different biodistribution compared with 18F-FDG. Finally, to demonstrate that GP can be a potential drug carrier for cancer theranostics, several drugs, including doxorubicin, were selected to be conjugated to GP. Imaging studies demonstrated that tumor uptake of GP-drug conjugates was increased as a function of time. GP-doxorubicin (GP-DOX) showed a slow-release pattern in in vitro cytotoxicity assay and exhibited anti-cancer efficacy with reduced toxicity in in vivo tumor growth delay study. In conclusion, both N4amG and GP are transporter-based targeting agents. Radiolabeled N4amG can be used for tumor cell proliferation assessment. GP is a potential agent for image-guided therapy and drug delivery.

Development and Characterization of an in vitro Four-species Anaerobic Dental Biofilm Model

Dental caries is the most common chronic disease worldwide. It is characterized by the demineralization of tooth enamel caused by acid produced by cariogenic dental bacteria growing on tooth surfaces, termed bacterial biofilms. Cariogenesis is a complex biological process that is influence by multiple factors and is not attributed to a sole causative agent. Instead, caries is associated with multispecies microbial biofilm communities composed of some bacterial species that directly influence the development of a caries lesion and other species that are seemingly benign but must contribute to the community in an uncharacterized way. Clinical analysis of dental caries and its microbial populations is challenging due to many factors including low sensitivity of clinical measurement tools, variability in saliva chemistry, and variation in the microbiota. Our laboratory has developed an in vitro anaerobic biofilm model for dental carries to facilitate both clinical and basic research-based analyses of the multispecies dynamics and individual factors that contribute to cariogenicity. The rational for development of this system was to improve upon the current models that lack key elements. This model places an emphasis on physiological relevance and ease of maintenance and reproducibility. The uniqueness of the model is based on integrating four critical elements: 1) a biofilm community composed of four distinct and representative species typically associated with dental caries, 2) a semi-defined synthetic growth medium designed to mimic saliva, 3) physiologically relevant biofilm growth substrates, and 4) a novel biofilm reactor device designed to facilitate the maintenance and analysis. Specifically, human tooth sections or hydroxyapatite discs embedded into poly(methyl methacrylate) (PMMA) discs are incubated for an initial 24 hr in a static inverted removable substrate (SIRS) biofilm reactor at 37°C under anaerobic conditions in artificial saliva (CAMM) without sucrose in the presence of 1 X 106 cells/ml of each Actinomyces odontolyticus, Fusobacterium nucleatum, Streptococcus mutans, and Veillonella dispar. During days 2 and 3 the samples are maintained continually in CAMM with various exposures to 0.2% sucrose; all of the discs are transferred into fresh medium every 24 hr. To validate that this model is an appropriate in vitro representation of a caries-associated multispecies biofilm, research aims were designed to test the following overarching hypothesis: an in vitro anaerobic biofilm composed of four species (S. mutans, V. dispar, A. odontolyticus, and F. nucleatum) will form a stable biofilm with a community profile that changes in response to environmental conditions and exhibits a cariogenic potential. For these experiments the biofilms as described above were exposed on days 2 and 3 to either CAMM lacking sucrose (no sucrose), CAMM with 0.2% sucrose (constant sucrose), or were transferred twice a day for 1 hr each time into 0.2% sucrose (intermittent sucrose). Four types of analysis were performed: 1) fluorescence microscopy of biofilms stained with Syto 9 and hexidium idodine to determine the biofilm architecture, 2) quantitative PCR (qPCR) to determine the cell number of each species per cm2, 3) vertical scanning interferometry (VSI) to determine the cariogenic potential of the biofilms, and 4) tomographic pH imaging using radiometric fluorescence microscopy after exposure to pH sensitive nanoparticles to measure the micro-environmental pH. The qualitative and quantitative results reveal the expected dynamics of the community profile when exposed to different sucrose conditions and the cariogenic potential of this in vitro four-species anaerobic biofilm model, thus confirming its usefulness for future analysis of primary and secondary dental caries.

Experimental models for p53, hepatitis B and aflatoxin hepatocarcinogenesis

The major risk factors for liver cancer in Southeast Asia: HBV infection, aflatoxin exposure and p53 expression/mutation, were examined in experimental models. Four groups were examined for development of hepatocellular carcinoma (HCC) with and without neonatal exposure to aflatoxin (AFB$\sb1)$: (Group I.) Transgenic HBsAg mice with one p53 allele. (Group II) Transgenic HBsAg mice with two p53 alleles. (Group III) Non-transgenic litter mates with one p53 allele. (Group IV) Non-transgenic litter mates with two p53 alleles. HCC developed in Group I animals exposed to aflatoxin at an earlier time and were of a higher grade than those seen later in other groups. These results provide an explanation for as to why p53 is a target for deletion and/or mutation in human HCC especially when found in high risk areas where HBV infection and Aflatoxin B1 food contamination is high, and nicely illustrates a synergistic interaction among these three factors. None of the tumors analyzed had loss or mutation in the p53 gene.^ To determine the significance of the specific p53ser249 mutation found in HBV/aflatoxin associated human hepatomas in an in-vivo experimental model using transgenic mice, a two-nucleotide change in the mouse p53 gene at amino acid position 246, which is equivalent to that of 249 in human p53, was introduced. Transgenic mice with mutant p53 controlled by the albumin promoter were generated and shown to express the p53ser246 mutant RNA and protein specifically in liver. Three groups were examined for development of HCC with and without neonatal exposure to aflatoxin: (Group V) Transgenic p53ser246 mice with two p53 alleles. (Group VI) Transgenic p53ser246 mice with one p53 allele. (Group VII) Double transgenic for p53ser246 and HBsAg with two p53 alleles. One hundred percent of male mice with the three risk factors injected with aflatoxin developed high grade liver tumors, compared to 66.6% from group VI and only 14.2% of group V suggesting synergistic interaction between HBsAg and this particular ser246 p53 mutation.^ In order to examine the growth properties of hepatocytes and correlation with p53 loss and/or mutation, cell proliferation and ploidy analysis of liver from normal heterozyous, homozygous null mice and from transgenic mutant p53ser246, mice were studied. Loss of wild-type p53 increased G1/G0 ratios of cells as well as proliferation and decreased cell ploidy. The mutant p53ser246 did not show a significant effect on cell ploidy or proliferation. However a striking 5-10X increase in G1/G0 ratio suggests that this specific mutation specifically induces G0 to G1 transition, which in turn further predisposes hepatocytes to the damaging effect of Aflatoxin. (Abstract shortened by UMI.) ^