Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

From gene to protein: Investigating the disease etiology of retinitis pigmentosa

Retinitis pigmentosa (RP) is a name given to a group of inherited retinal dystrophies that lead to progressive photoreceptor degeneration, and thus, visual impairment. It is evident at both the clinical and the molecular level that these are heterogeneous disorders, with wide variation in severity, mode of inheritance, and phenotype. The genetics of RP are not simple; the disease can be inherited in dominant, recessive, X-linked, and digenic modes. Autosomal dominant RP (adRP) results from mutations in at least ten mapped loci, but there may be dozens of genetic loci where mutations can cause RP. To date, there are over a hundred genes known to cause retinal degenerative diseases, and less than half of these have been cloned (RetNet). Among the dozens of retinitis pigmentosa loci known to exist, only a few have been identified and the remainders are inferred from linkage studies. Today, the genes for seven of the twelve-adRP loci have been identified, and these are rhodopsin, peripherin/RDS, NRL, ROM1, CRX, RP13 and RP1. My research projects involved a combination of the continued search for genes involved in retinal dystrophies, as well the investigation into the role of peripherin/RDS and RP1 in the disease etiology of autosomal dominant RP. ^ Most of the mutations leading to inherited retinal disorders have been identified in predominately retina expressed genes like rhodopsin, peripherin/RDS, and RP1. Expressed sequence tags (ESTs) that were retina-specific were culled from sequence databases and, together with laboratory analysis, were analyzed as potential candidate genes for retinal dystrophies. Thirteen of the fifty-five identified retina-specific ESTs mapped to within candidate regions for inherited retinopathies. One of these is RP1L1, a homologue of RP1 and a potential cause of adRP. ^ Once a disease-associated gene has been identified, elucidating the role of that gene in the visual process is essential for understanding what happens when the process is defective as it is in adRP. My next projects involved investigating the role of a novel 5′ donor +3 splice site mutation on the mRNA of peripherin/RDS in adRP affected individuals, and comparative sequencing in RP1 to define conserved regions of the protein. Comparative sequencing is a powerful way to delineate critical regions of a sequence because different regions of a gene have different functions, and each region is subject to different levels of functional or structural constraints. Establishing a framework of conserved domains is beneficial not only for structural or functional studies, but can also aid in determining the potential effects of mutations. With the completion of sequencing of human genome, and other organisms such as Saccharomyces cerevisiae, Caenorhabditis elegans , and Drosophila, the facility of comparative sequencing will only increase in the future. Comparative sequencing has already become an established procedure for pinpointing conserved regions of a protein, and is an efficient way to target regions of a protein for experimental and/or evolutionary analysis. ^

A multivariate frailty model for disease recurrences and survival

A multivariate frailty hazard model is developed for joint-modeling of three correlated time-to-event outcomes: (1) local recurrence, (2) distant recurrence, and (3) overall survival. The term frailty is introduced to model population heterogeneity. The dependence is modeled by conditioning on a shared frailty that is included in the three hazard functions. Independent variables can be included in the model as covariates. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The algorithm used in present application is the hybrid Metropolis-Hastings algorithm, which simultaneously updates all parameters with evaluations of gradient of log posterior density. The performance of this approach is examined based on simulation studies using Exponential and Weibull distributions. We apply the proposed methods to a study of patients with soft tissue sarcoma, which motivated this research. Our results indicate that patients with chemotherapy had better overall survival with hazard ratio of 0.242 (95% CI: 0.094 - 0.564) and lower risk of distant recurrence with hazard ratio of 0.636 (95% CI: 0.487 - 0.860), but not significantly better in local recurrence with hazard ratio of 0.799 (95% CI: 0.575 - 1.054). The advantages and limitations of the proposed models, and future research directions are discussed. ^

Joint effects of pulmonary function and aerobic power on survival in a cohort of healthy adults

Objective measurements of physical fitness and pulmonary function are related individually to long-term survival, both in healthy people and in those who are ill. These factors are furthermore known to be related to one another physiologically in people with pulmonary disease, because advanced pulmonary disease causes ventilatory limitation to exercise. Healthy people do not have ventilatory limitation to exercise, but rather have ventilatory reserve. The relationship between pulmonary function and exercise performance in healthy people is minimal. Exercise performance has been shown to modify the effect of pulmonary function on mortality in people with chronic obstructive pulmonary disease, but the relationship between these factors in healthy people has not been studied and is not known. The purpose of this study is to quantify the joint effects of pulmonary function and exercise performance as these bear on mortality in a cohort of healthy adults. This investigation is an historical cohort study over 20 years of follow-up of 29,624 adults who had complete preventive medicine, spirometry and treadmill stress examinations at the Cooper Clinic in Dallas, Texas.^ In 20 years of follow-up, there were 738 evaluable deaths. Forced expiratory volume in one second (FEV$\sb1$) percent of predicted, treadmill time in minutes percent of predicted, age, gender, body mass index, baseline smoking status, serum glucose and serum total cholesterol were all significant, independent predictors of mortality risk. There were no frank interactions, although age had an important increasing effect on the risk associated with smoking when other covariates were controlled for in a proportional-hazards model. There was no confounding effect of exercise performance on pulmonary function. In agreement with the pertinent literature on independent effects, each unit increase in FEV$\sb1$ percent predicted was associated with about eight tenths of a percent reduction in adjusted mortality rate. The concept of physiologic reserve is useful in interpretation of the findings. Since pulmonary function does not limit exercise tolerance in healthy adults, it is reasonable to expect that exercise tolerance would not modify the effect of pulmonary function on mortality. Epidemiologic techniques are useful for elucidating physiological correlates of mortality risk. ^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Identification and evaluation of candidate genes for inherited retinal -degenerative diseases

Although more than 100 genes associated with inherited retinal disease have been mapped to chromosomal locations, less than half of these genes have been cloned. This text includes identification and evaluation of candidate genes for three autosomal dominant forms of inherited retinal degeneration: atypical vitelliform macular dystrophy (VMD1), cone-rod dystrophy (CORD), and retinitis pigmentosa (RP). ^ VMD1 is a disorder characterized by complete penetrance but extremely variable expressivity, and includes macular or peripheral retinal lesions and peripappilary abnormalitites. In 1984, linkage was reported between VMD1 and soluble glutamate-pyruvate transaminase GPT); however, placement of GPT to 8q24 on linkage maps had been debated, and VMD1 did not show linkage to microsatellite markers in that region. This study excluded linkage between the loci by cloning GPT, identifying the nucleotide substitution associated with the GPT sozymes, and by assaying VMD1 family samples with an RFLP designed to detect the substitution. In addition, linkage of VMD1 to the known dominant macular degeneration loci was excluded. ^ CORD is characterized by early onset of color-vision deficiency, and decreased visual acuity, However, this retinal degeneration progresses to no light perception, severe macular lesion, and “bone-spicule” accumulations in the peripheral retina. In this study, the disorder in a large Texan family was mapped to the CORD2 locus of 19q13, and a mutation in the retina/pineal-specific cone-rod homeobox gene (CRX) was identified as the disease cause. In addition, mutations in CRX were associated with significantly different retinal disease phenotypes, including retinitis pigmentosa and Leber congenital amaurosis. ^ Many of the mutations leading to inherited retinal disorders have been identified in genes like CRX, which are expressed predominantly in the retina and pineal gland. Therefore, a combination of database analysis and laboratory investigation was used to identify 26 novel retina/pineal-specific expressed sequence tag (EST) clusters as candidate genes for inherited retinal disorders. Eight of these genes were mapped into the candidate regions of inherited retinal degeneration loci. ^ Two of the eight clusters mapped into the retinitis pigmentosa RP13 candidate region of 17p13, and were both determined to represent a single gene that is highly expressed in photoreceptors. This gene, the Ah receptor-interacting like protein-1 (AIPL1), was cloned, characterized, and screened for mutations in RP13 patient DNA samples. ^