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.

Parental influence on adolescent smoking initiation among Mexican origin youth

Smoking is often initiated in adolescence through trying or experimenting with cigarettes. Smoking initiation is the beginning critical stage in the smoking trajectory often resulting in addiction. This dissertation examined the effect of parenting variables on smoking initiation behavior among 11–14 year old Mexican origin adolescents, a largely understudied group. The participants in this study were part of a population-based cohort of Mexican origin adolescents residing in Houston, Texas. ^ Aim 1 of this study assessed the appropriateness of the Family Life Questionnaire (FLQ) among Mexican origin adolescents. Second order confirmatory factor analysis (CFA) was performed to examine the factor structure of the FLQ and measurement invariance testing was conducted to evaluate the cross-cultural validity of this scale. Aim 2 analyzed cross-sectional associations between parenting variables and adolescent ever tried smoking behavior while aim 3 focused on prospective examination of changes in parenting variables from baseline to final follow-up on ever tried smoking behavior among never smokers. ^ Overall, the results of the CFA indicated that the original factor structure of the FLQ, with alterations, was a good fit for the Mexican origin adolescents. The measurement invariance analysis of the modified FLQ scale indicated adequate measurement invariance. The aim 2 cross-sectional analyses indicated that family cohesion was significantly associated with lower odds of ever tried smoking. Authoritarian parenting was significantly associated with smoking initiation only at the baseline while family conflict was significantly associated with smoking initiation only at the two-year final home visit. The findings from the aim 3 prospective analysis indicated that changes in levels of family cohesion and conflict are important predictors of smoking initiation among those who have never tried smoking. Specifically, perceiving low levels of family cohesion and a decrease in the family cohesion over two years, as well as perceiving high levels of family conflict and an increase in conflict over two years was associated with smoking initiation among never smokers. ^ In general, the findings of this study provide important insights on the links between parenting and adolescent smoking and assist in designing prevention and intervention programs that emphasize the role of family bonding to prevent adolescent smoking behavior. Family education programs for Mexican culture could also highlight the positive effects of authoritarian practices and good family communication to prevent family conflict and subsequent smoking behavior.^

INFANT MORTALITY IN THE MEXICAN AMERICAN COMMUNITY: AN ANALYSIS OF DIFFERENTIALS IN INFANT, NEONATAL, AND POSTNEONATAL MORTALITY BY ETHNICITY AND PARENTAL NATIVITY, 1974-75 SINGLE LIVE BIRTH COHORT, HARRIS COUNTY, TEXAS

The paradoxically low infant mortality rates for Mexican Americans in Texas have been attributed to inaccuracies in vital registration and idiosyncracies in Mexican migration in rural areas along the U.S.-Mexico border. This study examined infant (IMR), neonatal (NMR), and postneonatal (PNMR) mortality rates of Mexican Americans in an urban, non-border setting, using linked birth and death records of the 1974-75 single live birth cohort (N = 68,584) in Harris County, Texas, which includes the city of Houston and is reported to have nearly complete birth and death registration. The use of parental nativity with the traditional Spanish surname criterion made it possible to distinguish infants of Mexican-born immigrants from those of Blacks, Anglos, other Hispanics, and later-generation, more Anglicized Mexican Americans. Mortality rates were analyzed by ethnicity, parental nativity, and cause of death, with respect to birth weight, birth order, maternal age, legitimacy status, and time of first prenatal care.^ While overall IMRs showed Spanish surname rates slightly higher than Anglo rates, infants of Mexican-born immigrants had much lower NMRs than did Anglos, even for moderately low birth weight infants. However, among infants under 1500 grams, presumably unable to be discharged home in the neonatal period, Mexican Americans had the highest NMR. The inconsistency suggested unreported deaths for Mexican American low birth weight infants after hospital discharge. The PNMR of infants of Mexican immigrants was also lower than for Anglos, and the usual mortality differentials were reversed: high-risk categories of high birth order, high maternal age, and late/no prenatal care had the lowest PNMRs. Since these groups' characteristics are congruent with those of low-income migrants, the data suggested the possibility of migration losses. Cause of death analysis suggested that prematurity and birth injuries are greater problems than heretofore recognized among Mexican Americans, and that home births and "shoebox burials" may be unrecorded even in an urban setting.^ Caution is advised in the interpretation of infant mortality rates for a Spanish surname population of Mexican origin, even in an urban, non-border area with reportedly excellent birth and death registration. ^