The role of LMX1B and PITX2 in anterior segment development and adult ocular function

Several congenital syndromes associated with anterior segment (AS) anomalies can lead to impaired vision and glaucoma, such as nail-patella syndrome (NPS), caused by mutations in the LIM homeodomain transcription factor LMX1B and Axenfeld-Rieger's syndrome (ARS), caused by mutations in the bicoid-related homeodomain transcription factor PITX2. Targeted mutations in lmx1b and pitx2 and RNA in situ analysis reveal that both genes are required for AS development and are co-expressed within the periocular mesenchyme, suggesting they participate in a shared genetic pathway. Lmx1b homozygous mutants display iris and corneal stroma hypoplasia, and defects in ciliary body formation. In contrast, pitx2 homozygous mutants exhibit a more severe phenotype: the AS chamber, corneal endothelium, and extraocular muscles (EOM) fail to develop. The absence of EOM in pitx2 mutants suggests pitx2 acts upstream of lmx1b, or that other lmx1b family members, such as lmx1a, can compensate for lmx1b function. Lmxla/lmx1b double homozygous mutants have a reduced capacity to generate EOM, implying that lmx1 gene products have a redundant function in EOM development and that lmx1 family members may act downstream of pitx2. However, analysis of pitx2 expression in the AS tissues of lmx1b mutants and reciprocal studies of lmx1b expression in pitx2 mutants indicate that these genes do not function in a simple linear pathway. Instead, lmx1b and pitx2 may regulate a shared set of downstream targets or both genes may work in parallel transcribing unique targets required for a common biological process. Ultrastructural analysis of lmx1b and pitx2 mutant corneas indicates that collagen fibrillogenesis is perturbed, revealing a common role for both genes in the deposition of extracellular matrix. Furthermore, lmx1b/pitx2 double heterozygotes develop corneal opacities not observed in single heterozygotes demonstrating that lmx1b and pitx2 genetically interact. Data suggests that defects in the basement membrane of the corneal endothelium underlie the opacities observed in double heterozygotes. Additionally, double heterozygotes develop anterior synechias that occlude the trabecular meshwork, potentially blocking aqueous humor drainage. These data suggest that lmx1b and pitx2 are responsible for ECM deposition in multiple cell types and imply that such defects may contribute to the glaucomas observed in NPS and ARS patients. ^

Comparison of multiple comparison methods for identifying differential gene expression in simulated and real papillary thyroid cancer microarray data

The difficulty of detecting differential gene expression in microarray data has existed for many years. Several correction procedures try to avoid the family-wise error rate in multiple comparison process, including the Bonferroni and Sidak single-step p-value adjustments, Holm's step-down correction method, and Benjamini and Hochberg's false discovery rate (FDR) correction procedure. Each multiple comparison technique has its advantages and weaknesses. We studied each multiple comparison method through numerical studies (simulations) and applied the methods to the real exploratory DNA microarray data, which detect of molecular signatures in papillary thyroid cancer (PTC) patients. According to our results of simulation studies, Benjamini and Hochberg step-up FDR controlling procedure is the best process among these multiple comparison methods and we discovered 1277 potential biomarkers among 54675 probe sets after applying the Benjamini and Hochberg's method to PTC microarray data.^

Rules to limit snacking in front of the TV and childhood BMI status: Findings from the "Fun Families Study"

Childhood obesity is increasing at epidemic rates, and thus there is a need to target appropriate childhood behaviors that contribute to obesity. Many factors contribute to childhood weight status. The aim of this study was to look at relationships between parental rules to limit snacking while watching television and childhood weight status. The study looked at the presence of the behavior of snacking while watching television yesterday, congruence between child- and parent-reported perception of the presence of rules to limit snacking while watching television, and parent-reported frequency of children following rules to limit snacking while watching television. The outcomes were examined in a multi-ethnic population of children ages 6 to 9 years in Southeast Texas.^ This study was a cross-sectional secondary data analysis of the pilot program, Fun Families. This study examined baseline data from 202 parent-child dyads, which included both the control ( N= 101) and intervention groups (N= 101). Data were gathered using validated questions that were administered to 6-9 year old children and their primary caregiver (referred to as parent in the rest of the discussion) in Southeast Texas, between 2006 and 2008. The main study outcome was childhood weight status based on CDC BMI-for-age categories. The independent variables are (1) the presence of parental rules to limit snacking while watching television, (2) the congruence between child and parent about the presence of rules to limit snacking while watching television, and (3) the parent-reported frequency of the child following the rules to limit snacking while watching television. Chi-Square analyses were used to determine if weight status was different for (1) children who reported rules to limit snacking yesterday, (2) children who reported snacking, (3) children whose parents reported rules were present, and (4) those who had rule congruence with the parents not. Chi-Square analyses also examined if there was a difference in the presence of snacking behavior for children who reported rules, for children whose parents reported rules, and for those children who had congruence about rules. Linear regressions were used to determine if any of the studied variables predicted increased weight status or reported snacking while watching television yesterday.^ This study found that child-reported snacking yesterday was significantly different for children who reported rules (4.12, p= 0.04). Child-reported rules was significantly associated with (p= -0.14, α= 0.04) and predicted child-reported snacking yesterday (R 2 0.021, p= 0.04, t= -2.04, 95% CI -0.31, -0.01). There was statistical significant incongruence between child and parent perception about the presence of rules to limit snacking yesterday (15.06, p= 0.00). For this population, parent education level was significantly associated with child-reported rules (r= -0.16, p= 0.02), child-reported snacking yesterday (r= -0.15, p= 0.04), and parent-reported frequency of child following rules to limit snacking (r= 0.29, p= -0.01). Parent-reported speaking another language besides English at home was significantly associated with parent-reported rules (r= 0.17, p= 0.02).^ Although the studied variables did not show any significant associations or predictors for childhood weight status, the significant discord between parent and child perception about the presence of rules provides valuable information to future interventions that aim to reduce childhood weight status. Including the creation and enforcement of parental rules in interventions to reduce childhood weight status will be beneficial for future studies.^

Low birthweight and the risk of developing subsequent high blood pressure and/or dyslipidemia in childhood

The association between birthweight and blood pressure (BP), and birthweight and serum lipid concentrations at age 7 through 11 years was examined in 1446 black and white children. The prevalence ratio (with 95% confidence interval) for being in the race-, sex- and age-specific upper decile of diastolic BP in children born with low birthweight (LBW, $<$2500 grams) versus children with birthweight $\geq$2500 grams was for black boys, 2.66 (1.24-5.70). In the other race-sex groups for diastolic BP, and in all race-sex groups for systolic BP this ratio did not differ from one. Among white boys with LBW, but not in the other race-sex groups, higher than expected percentages of subjects were in the highest decile group of triglyceride concentrations (0.01 $<$ p $<$ 0.05). The prevalence ratio was 2.42 (1.19-4.91). When prematures were excluded only more than expected white girls with LBW were in the highest decile group of triglyceride concentrations. The prevalence ratio was 3.23 (1.16-9.00). Prevalence ratios for triglyceride concentrations in black boys and girls, and for LDL/HDL-C ratio, cholesterol and VLDL-C concentrations in all race-sex groups were not different from one in analyses including and in those excluding prematures. Mean triglyceride concentrations stratified by tertiles of Quetelet Index, race and sex showed a strongly positive association between triglyceride concentrations and Quetelet Index, and in the upper tertile of the Quetelet Index an association between LBW and raised triglyceride concentrations. Multiple linear regression analyses showed that after adjusting for sex, race and age present Quetelet Index (p $<$ 0.001) is a much stronger predictor of systolic and diastolic BP, and also of LDL-C/HDL-C ratio and triglyceride concentrations in this age group than birthweight (p $>$ 0.05). Thus, an association between LBW and subsequent risk for elevated BP was confirmed for diastolic BP in black boys, but not for the other race-sex groups, and not for systolic BP in any group. This is the first study finding an association between LBW and elevated triglyceride concentrations in boys (white and black) and girls (white). A follow-up study to assess whether the findings can be confirmed at adult age is recommended. ^

The role of serotonin in depression and clotting in the coronary artery disease population

Background: The mechanisms underlying the relationship between depression and acute coronary syndrome (ACS) remain unclear. Platelet serotonin has been associated with both depression and coronary artery disease in stable outpatients. Understanding the association between depression and platelet serotonin, during ACS, may explain some of the acute cardiovascular events seen in some individuals with depression. ^ Objectives: This study was designed to evaluate whether levels of platelet serotonin, during ACS, differ between individuals who screen positive for depression and individuals who screen negative for depression and to determine if a dose-response relationship exists between depressive symptoms and platelet serotonin levels. ^ Methods: In this cross-sectional study, data was collected on 51 patients hospitalized for ACS. Multiple linear regression models were used to determine if a relationship exists between depression and platelet serotonin levels. ^ Results: Of the 51 ACS patients, 24 screened positive for depression and 27 screened negative for depression. Platelet serotonin levels were not significantly different between the depressed group (942.10 ± 461.3) and the non-depressed group (1192.41 ± 764.3) (p= .293 and β= -4.093) and a dose-response relationship between depressive symptoms and platelet serotonin levels was not found (p= .250 and β= -.254). ^ Discussion: In this study, a relationship between depression and platelet serotonin levels was not found. Future research should focus on gaining a better understanding of the variables that may influence platelet serotonin levels in the ACS population. ^

Identification of genetic variants that influence atherosclerosis in young persons

Atherosclerosis is widely accepted as a complex genetic phenotype and is the usual cause of cardiovascular disease, the world’s leading killer. Genetic factors have been proven to be important risk contributors for atherosclerosis and much work has been done to identify promising candidates that might play a role in the development of atherosclerosis. It is well known that many independent replications are needed to unequivocally establish a valid genotype-phenotype association across different populations before the findings are extended to clinical settings and to the expensive follow-up studies designed to identify causal genetic variants. Aiming to replicate the association with atherosclerosis in the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study, we assessed the relationship of 32 atherosclerosis candidate SNPs to atherosclerosis in the PDAY cohort, consisting of AA and EA young people aged 15-34 years who died of non-medical causes. Two association studies, a whole sample study and a 1:1 matched case control study were performed by use of multiple linear regression and logistic regression analyses, respectively. For the whole sample association study, 32 SNPs among 2,650 individuals (1,369 AA and 1,281 EA) were tested for the association with six early atherosclerosis phenotypes: abdominal aorta fatty streaks, abdominal aorta raised lesions, right coronary artery fatty streaks, right coronary artery raised lesions, thoracic aorta fatty streaks, and thoracic aorta raised lesions. For the matched case-control association study, 337 case-control paired samples were included; cases were chosen with the highest total raised lesion scores from the studied population, while controls were randomly selected from individuals that had no raised lesions and matched to cases by age, gender and race. Sixteen SNPs in 13 genes were found to be significantly associated with atherosclerosis in at least one of the PDAY association studies. Among these 16 findings: eight SNPs (rs9579646, rs6053733, rs3849150, rs10499903, rs2148079, rs5073691, rs10116277, and rs17228212) successfully replicated previous results, six SNPs (rs17222814, rs10811661, rs7028570, rs7291467, rs16996148 and rs10401969) were reported as new findings exclusive to our study, the last two of the 16 SNPs, rs501120 and rs6922269, showed either intriguing or conflicting result. SNP rs17222814 in ALOX5AP and SNP rs3849150 in LRRC18 were consistently associated with atherosclerosis in both prior and the two PDAY association studies. SNP rs3849150 was also identified to be highly correlated with a non-synonymous coding SNP, rs17772611, which may damage the protein (polyphen score = 0.996), suggesting that SNP rs17772611 may be the causal functional variant.^ In conclusion, our study added more support for the association of these candidate genes with atherosclerosis. SNPs rs3849150 and rs17772611 of LRRC18, as well as SNP rs17222814 of ALOX5AP, were the most significant findings from our study, and may be ranked among the best for further study.^

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.