Systematic interpretation of molecular beacon polymerase chain reaction for identifying rpoB mutations in Mycobacterium tuberculosis isolates with mixed resistant and susceptible bacteria

Detection of multidrug-resistant tuberculosis (MDR-TB), a frequent cause of treatment failure, takes 2 or more weeks to identify by culture. RIF-resistance is a hallmark of MDR-TB, and detection of mutations in the rpoB gene of Mycobacterium tuberculosis using molecular beacon probes with real-time quantitative polymerase chain reaction (qPCR) is a novel approach that takes ≤2 days. However, qPCR identification of resistant isolates, particularly for isolates with mixed RIF-susceptible and RIF-resistant bacteria, is reader dependent and limits its clinical use. The aim of this study was to develop an objective, reader-independent method to define rpoB mutants using beacon qPCR. This would facilitate the transition from a research protocol to the clinical setting, where high-throughput methods with objective interpretation are required. For this, DNAs from 107 M. tuberculosis clinical isolates with known susceptibility to RIF by culture-based methods were obtained from 2 regions where isolates have not previously been subjected to evaluation using molecular beacon qPCR: the Texas–Mexico border and Colombia. Using coded DNA specimens, mutations within an 81-bp hot spot region of rpoB were established by qPCR with 5 beacons spanning this region. Visual and mathematical approaches were used to establish whether the qPCR cycle threshold of the experimental isolate was significantly higher (mutant) compared to a reference wild-type isolate. Visual classification of the beacon qPCR required reader training for strains with a mixture of RIF-susceptible and RIF-resistant bacteria. Only then had the visual interpretation by an experienced reader had 100% sensitivity and 94.6% specificity versus RIF-resistance by culture phenotype and 98.1% sensitivity and 100% specificity versus mutations based on DNA sequence. The mathematical approach was 98% sensitive and 94.5% specific versus culture and 96.2% sensitive and 100% specific versus DNA sequence. Our findings indicate the mathematical approach has advantages over the visual reading, in that it uses a Microsoft Excel template to eliminate reader bias or inexperience, and allows objective interpretation from high-throughput analyses even in the presence of a mixture of RIF-resistant and RIF-susceptible isolates without the need for reader training.^

EXPRESSION OF THE HUMAN PLACENTAL LACTOGEN GENES

The placenta is the site of synthesis of various peptide and steroid hormones related to pregnancy. Human placental lactogen (hPL) is the predominant peptide hormone secreted by term placenta and its synthesis is tissue-specific and coupled to placenta development. The objective of this work was to study the structure and expression of the hPL.^ Poly(A('+))RNA from human term placenta was translated in a mouse-derived cell-free system. A major band corresponding to pre-hPL and a minor band comigrating with mature hPL, represent (TURN)15% of the total radioactively labeled proteins. Analysis of the poly(A('+))RNA showed a prominent band at approximately 860 nucleotides. A corresponding band was observed in Northern blots of total RNA, hybridized with {('32)P}-labeled recombinant plasmid containing a portion of hPL cDNA. Similar analyses of nuclear RNA showed at least four additional bands at 990, 1200, 1460 and 1760 nucleotides, respectively, which are likely precursors of hPL mRNA. Poly(A('+))RNA was used to construct a cDNA library, of which approximately 5% of the clones were found to hybridize to hPL DNA sequences. Heteroduplexes constructed between a clone containing a 815 bp hPL cDNA insert and a hPL genomic DNA clone revealed four small intervening sequences which can account for the lengths observed in hnRNA molecules.^ Recombinant plasmid HCS-pBR322 containing a 550 bp insert of a cDNA transcript of human placental lactogen (hPL) mRNA was ('3)H-labeled an hybridized in situ to human chromosome preparations. These experiments allowed assignment of the hPL and growth hormone (hGH) genes, which have over 90% nucleotide homology in their coding sequences, to band q22-24 of chromosome 17. A gene copy number experiment showed that both genes are present in (TURN)3 copies per haploid genome.^ Experiments were designed to determine if all members of the hPL gene cluster, consisting of four non-allelic genes, are transcribed in term placenta. Advantage was taken of differences in restriction endonuclease sites in the coding portions of the different hPL genes, to distinguish the putative cDNAs of the transcriptionally active genes. Two genes were found to be represented in the cDNA library and their cDNA transcripts were isolated and characterized. Three independent methods showed that their corresponding mRNAs are about equally represented in the hPL mRNA population. The two cDNAs code for prehPL proteins which differ at a single amino acid position. However the secreted hPLs have identical amino acid sequences. A tetramer insertion duplication was found in a palindrome area of the 3' untranslated region of one of the hPL mRNAs. ^

The relationship between surgical residents' perception of leadership and patient safety culture

Introduction. Patient safety culture is the integration of interrelated practices that once developed is supported by both the culture and leadership of the organization (Sagan, 1993). The purpose of this study is to describe and examine the relationship between surgical residents’ perception of their leadership and the resulting organizational safety culture within their clinical setting. This assessment is important to understanding the extent that leadership style affects the perception of the safety culture.^ Methods. A secondary dataset was used which included data from 68 surgical residents from two survey instruments, Organizational Description Questionnaire (ODQ) and Patient Safety Climate In Healthcare Organizations (PSCHO) Survey. Multiple regressions followed by hierarchical regressions with the introduction of the Post Graduate Year (PGY) variable examined the association between the leadership styles, Transactional and Transformational and the organizational safety culture variables, Overall Emphasis on Safety, Senior management engagement, Organizational resources for safety. Independent t-tests were conducted to assess whether males and females differ among the organizational safety culture variables and either leadership style.^ Results. The surgical residents perceived their organizational leadership to have greater emphasis placed on transformational leadership culture style relative to transactional leadership culture style. The only significant association found was between Transformational leadership and Organizational resources for safety. PGY had no significant effect on the leadership or the safety culture perceived. No significant difference was found between females and males in regards to the safety culture or the leadership style.^ Discussion. These results have implications as they support the premise for the study which is surgical residents perceive their existing leadership and organizational culture to be more transformational in nature than transactional. Significance was found between the leadership perceived and one of the safety culture variables, Organizational resources for safety. The foundation for this association lies in the fact that surgical residents are the personnel which are a part of the organizational resources. Although PGY differentiation did not seem to play a difference in the leadership perceived this could be attributed to the small sample size. No gender difference were found which supports the assumption that within such a highly specialized group such as surgical residents there is no gender differences since the highly specialized field draws a certain type of person with distinct characteristics. In future research these survey tools can be used to gauge the survey audiences’ perception and safety interventions can be developed based on the results. ^

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

THE MECHANISM OF TUMORIGENESIS IN THE IMMORTALIZED HUMAN PANCREATIC CELL LINES: CELL CULTURE MODELS OF HUMAN PANCREATIC CANCER

The mechanism of tumorigenesis in the immortalized human pancreatic cell lines: cell culture models of human pancreatic cancer Pancreatic ductal adenocarcinoma (PDAC) is the most lethal cancer in the world. The most common genetic lesions identified in PDAC include activation of K-ras (90%) and Her2 (70%), loss of p16 (95%) and p14 (40%), inactivation p53 (50-75%) and Smad4 (55%). However, the role of these signature gene alterations in PDAC is still not well understood, especially, how these genetic lesions individually or in combination contribute mechanistically to human pancreatic oncogenesis is still elusive. Moreover, a cell culture transformation model with sequential accumulation of signature genetic alterations in human pancreatic ductal cells that resembles the multiple-step human pancreatic carcinogenesis is still not established. In the present study, through the stepwise introduction of the signature genetic alterations in PDAC into the HPV16-E6E7 immortalized human pancreatic duct epithelial (HPDE) cell line and the hTERT immortalized human pancreatic ductal HPNE cell line, we developed the novel experimental cell culture transformation models with the most frequent gene alterations in PDAC and further dissected the molecular mechanism of transformation. We demonstrated that the combination of activation of K-ras and Her2, inactivation of p16/p14 and Smad4, or K-ras mutation plus p16 inactivation, was sufficient for the tumorigenic transformation of HPDE or HPNE cells respectively. We found that these transformed cells exhibited enhanced cell proliferation, anchorage-independent growth in soft agar, and grew tumors with PDAC histopathological features in orthotopic mouse model. Molecular analysis showed that the activation of K-ras and Her2 downstream effector pathways –MAPK, RalA, FAK, together with upregulation of cyclins and c-myc were involved in the malignant transformation. We discovered that MDM2, BMP7 and Bmi-1 were overexpressed in the tumorigenic HPDE cells, and that Smad4 played important roles in regulation of BMP7 and Bmi-1 gene expression and the tumorigenic transformation of HPDE cells. IPA signaling pathway analysis of microarray data revealed that abnormal signaling pathways are involved in transformation. This study is the first complete transformation model of human pancreatic ductal cells with the most common gene alterations in PDAC. Altogether, these novel transformation models more closely recapitulate the human pancreatic carcinogenesis from the cell origin, gene lesion, and activation of specific signaling pathway and histopathological features.

THE EFFECT OF RELAXIN ON BIOCHEMICAL AND MORPHOLOGICAL PARAMETERS OF RAT MYOMETRIAL CELLS IN CULTURE (CYCLIC-AMP, CELL SHAPE CHANGE)

Relaxin is able to inhibit spontaneous, oxytocin-and prostaglandin-driven uterine contractions. The intracellular mechanism of action of relaxin on uterine relaxation had previously been studied using isometrically suspended uterine strips. Since uterine strips contain stroma as well as myometrium, the changes in biochemical parameters induced by relaxin treatment may not occur in the same cell types responsible for the physical changes. In these studies, cultures of enriched populations of rat myometrial cells were used to investigate the effect of relaxin on biochemical and morphological parameters which are related to relaxation.^ Under optimal culture conditions (initial plating density 1 - 1.5 x 10('6)cells/ml, 3 ml/35 mm dish, 2 days culture), enzymatically isolated rat myometrial cells were able to respond to relaxin with cAMP elevation. Relaxin elevated cAMP levels in the presence but not the absence of 0.1 mM methylisobutylxanthine or 0.4 um forskolin in a time- and concentration-dependent manner. In contrast, isoproterenol was able to elevate cAMP levels in the presence and absence of 0.1 mM methylisobutylxanthine.^ Oxytocin treatment caused a decrease in mean cell length and area of myometrial cells in culture which could be considered analogous to contraction. Under optimal culture conditions, relaxin increased myometrial cell length and area (i.e. analogous to relaxation) of oxytocin-treated cells in a time- and concentration-dependent manner. Other relaxants such as isoproterenol and dibutyryl cAMP also increased cell length and area of oxytocin - treated myometrial cells in culture.^ Under optimal culture conditions, relaxin decreased myosin light chain kinase activity in a time-and concentration-dependent manner by increasing the K(,50) of the enzyme for calmodulin (CaM), i.e. decreasing the affinity of the enzyme for CaM. The decrease in the affinity of myosin light chain kinase for CaM may be due to the phosphorylation of the enzyme by cAMP-dependent protein kinase. Relaxin also decreased the Ca('2+)(.)CaM-independent myosin light chain kinase activity to a lesser extent than that of the Ca('2+)(.)CaM-dependent enzyme activity. This was not attributable to a decrease in the affinity of the enzyme for myosin in myometrial cells in culture, in contrast to the finding of such a change following relaxin treatment of uterine strips. Further studies are required to clarify this point.^ There was a temporal association between the effects of relaxin on elevation of cAMP levels in the presence of 0.4 uM forskolin, increase in cell length and decrease in myosin light chain kinase activity. . . . (Author's abstract exceeds stipulated maximum length. Discontinued here with permission of author.) UMI ^

An analysis of two methods for the classification of stage of readiness to obtain repeat mammography screening

Background and purpose: Breast cancer continues to be a health problem for women, representing 28 percent of all female cancers and remaining one of the leading causes of death for women. Breast cancer incidence rates become substantial before the age of 50. After menopause, breast cancer incidence rates continue to increase with age creating a long-lasting source of concern (Harris et al., 1992). Mammography, a technique for the detection of breast tumors in their nonpalpable stage when they are most curable, has taken on considerable importance as a public health measure. The lifetime risk of breast cancer is approximately 1 in 9 and occurs over many decades. Recommendations are that screening be periodic in order to detect cancer at early stages. These recommendations, largely, are not followed. Not only are most women not getting regular mammograms, but this circumstance is particularly the case among older women where regular mammography has been proven to reduce mortality by approximately 30 percent. The purpose of this project was to increase our understanding of factors that are associated with stage of readiness to obtain subsequent mammograms. A secondary purpose of this research was to suggest further conceptual considerations toward the extension of the Transtheoretical Model (TTM) of behavior change to repeat screening mammography. ^ Methods. A sample (n = 1,222) of women 50 years and older in a large multi-specialty clinic in Houston, Texas was surveyed by mail questionnaire regarding their previous screening experience and stage of readiness to obtain repeat screening. A computerized database, maintained on all women who undergo mammography at the clinic, was used to identify women who are eligible for the project. The major statistical technique employed to select the significant variables and to examine the man and interaction effects of independent variables on dependent variables was polychotomous stepwise, logistic regression. A prediction model for each stage of readiness definition was estimated. The expected probabilities for stage of readiness were calculated to assess the magnitude and direction of significant predictors. ^ Results. Analysis showed that both ways of defining stage of readiness for obtaining a screening mammogram were associated with specific constructs, including decisional balance and processes of the change. ^ Conclusions. The results of the present study demonstrate that the TTM appears to translate to repeat mammography screening. Findings in the current study also support finding of previous studies that suggest that stage of readiness is associated with respondent decisional balance and the processes of change. ^

The dynamics of calmodulin signaling revealed using optical methods

The Ca2+-binding protein calmodulin (CaM) is a key transducer of Ca2+ oscillations by virtue of its ability to bind Ca 2+ selectively and then interact specifically with a large number of downstream enzymes and proteins. It remains unclear whether Ca2+ -dependent signaling alone can activate the full range of Ca 2+/CaM regulated processes or whether other regulatory schemes in the cell exist that allow specific targeting of CaM to subsets of Ca 2+/CaM binding sites or regions of the cell. Here we investigate the possibility that alterations of the availability of CaM may serve as a potential cellular mechanism for regulating the activation of CaM-dependent targets. By utilizing sensitive optical techniques with high spatial and temporal resolution, we examine the intracellular dynamics of CaM signaling at a resolution previously unattainable. After optimizing and characterizing both the optical methods and fluorescently labeled probes for intracellular measurements, the diffusion of CaM in the cytoplasm of HEK293 cells was analyzed. It was discovered that the diffusion characteristics of CaM are similar to that of a comparably sized inert molecule. Independent manipulation of experimental parameters, including increases in total concentrations of CaM and intracellular Ca2+ levels, did not change the diffusion of CaM in the cytoplasm. However, changes in diffusion were seen when the concentration of Ca2+/CaM-binding targets was increased in conjunction with elevated Ca2+. This indicates that CaM is not normally limiting for the activation of Ca 2+/CaM-dependent enzymes in HEK293 cells but reveals that the ratio of CaM to CaM-dependent targets is a potential mechanism for changing CaM availability. Next we considered whether cellular compartmentalization may act to regulate concentrations of available Ca2+/CaM in hippocampal neurons. We discovered changes in diffusion parameters of CaM under elevated Ca2+ conditions in the soma, neurite and nucleus which suggest that either the composition of cytoplasm is different in these compartments and/or they are composed of unique families of CaM-binding proteins. Finally, we return to the HEK293 cell and for the first time directly show the intracellular binding of CaM and CaMKII, an important target for CaM critical for neuronal function and plasticity. Furthermore, we analyzed the complex binding stoichiometry of this molecular interaction in the basal, activated and autophosphorylated states of CaMKII and determined the impact of this binding on CaM availability in the cell. Overall these results demonstrate that regulation of CaM availability is a viable cellular mechanism for regulating the output of CaM-dependent processes and that this process is tuned to the specific functional needs of a particular cell type and subcellular compartment. ^

The characterization of PKC-isozyme specific EGFR-dependent Erk1/2 activation in androgen-independent prostate cancer cell lines

One growth factor receptor commonly altered during prostate tumor progression is the epidermal growth factor receptor (EGFR). EGFR signaling regulates Erk1/2 phosphorylation through multiple mechanisms. We hypothesized that PKC isozymes play a role in EGFR-dependent signaling, and that through PKC isozyme selective inhibition, EGFR-dependent Erk1/2 activation can be attenuated in AICaP cells. ^ To test the hypothesis, PKC activation was induced by 12-O-tetradecanoyi-phorbol-13-acetate (TPA) in PC-3 cells. As a result, Erk1/2 was activated similarly to what was observed upon EGF stimulation. EGF-induced Erk1/2 activation in PC-3 cells was PKC-dependent, as demonstrated through use of a selective PKC inhibitor, GF109203X. This provides evidence for PKC regulatory control over Erk1/2 signaling downstream of EGFR. Next, we demonstrated that when PKC was inhibited by GF109203X, EGF-stimulated Erk1/2 activation was inhibited in PC-3, but not DU145 cells. TPA-stimulated Erk1/2 activation was EGFR-dependent in both DU145 and PC-3 cells, demonstrated through abrogation of Erk1/2 activation by a selective EGFR inhibitor AG1478. These data support PKC control at or upstream of EGFR in AICaP cells. We observed that interfering with ligand/EGFR binding abrogated Erk1/2 signaling in TPA-stimulated cells, revealing a role for PKC upstream of EGFR. ^ Next, we determined which PKC isozymes might be responsible for Erk1/2 regulation. We first determined that human AICaP cell lines express the same PKC isozymes as those observed in clinical prostate cancer specimens (α, ϵ, &zgr;, ι and PKD). Isozyme-selective methods were employed to characterize discrete PKC isozyme function in EGFR-dependent Erk1/2 activation. Pharmacologic inhibitors implicated PKCα in TPA-induced EGFR-dependent Erk1/2 activation in both PC-3 and DU145 cells. Further, the cPKC-specific inhibitor, Gö6976 decreased viablilty of DU145 cells, providing evidence that PKCα is necessary for growth and survival. Finally, resveratrol, a phytochemical with strong cancer therapeutic potential inhibited Erk1/2 activation, and this correlated with selective inhibition of PKCα. These results demonstrate that PKC regulates pathways critical to progression of CaP cells, including those mediated by EGFR. Thus, PKC isozyme-selective targeting is an attractive therapeutic strategy, and understanding the role of specific PKC isozymes in CaP cell growth and survival may aid in development of effective, non-toxic PKC-targeted therapies. ^

Culture and the social context of health inequalities

There has been a great deal of interest and debate recently concerning the linkages between inequality and health cross-nationally. Exposures to social and health inequalities likely vary as a consequence of different cultural contexts. It is important to guide research by a theoretical perspective that includes cultural and social contexts cross-nationally. If inequality affects health only under specific cultural conditions, this could explain why some of the literature that compares different societies finds no evidence of a relationship between inequality and health in certain countries. A theoretical framework is presented that combines sociological theory with constructs from cultural psychology in order to identify pathways that might lead from cultural dimensions to health inequalities. Three analyses are carried out. The first analysis explores whether there is a relationship between cultural dimensions at the societal level and self-rated health at the individual level. The findings suggest that different cultural norms at the societal level can produce both social and health inequalities, but the effects on health may differ depending on the socio-cultural context. The second analysis tests the hypothesis that health is affected by the density of social networks in a society, levels of societal trust, and inequality. The results suggest that commonly used measures of social cohesion and inequality may have both contextual and compositional effects on health in a large number of countries, and that societal measures of social cohesion and inequality interact with individual measures of social participation, trust, and income, moderating their effects on health. The third analysis explores whether value systems associated with vertical individualist societies may lead to health disparities because of their stigmatizing effects. I test the hypothesis that, within vertical individualist societies, subjective well-being will be affected by a social context where competition and the Protestant work ethic are valued, mediated by inequality. The hypothesis was not supported by the available cross-national data, most likely because of inadequate measures, missing data, and the small sample of vertical individualist countries. The overall findings demonstrate that cultural differences are important contextual factors that should not be overlooked when examining the causes of health inequalities. ^

Multivariate methods for correlated effects sizes

Current statistical methods for estimation of parametric effect sizes from a series of experiments are generally restricted to univariate comparisons of standardized mean differences between two treatments. Multivariate methods are presented for the case in which effect size is a vector of standardized multivariate mean differences and the number of treatment groups is two or more. The proposed methods employ a vector of independent sample means for each response variable that leads to a covariance structure which depends only on correlations among the $p$ responses on each subject. Using weighted least squares theory and the assumption that the observations are from normally distributed populations, multivariate hypotheses analogous to common hypotheses used for testing effect sizes were formulated and tested for treatment effects which are correlated through a common control group, through multiple response variables observed on each subject, or both conditions.^ The asymptotic multivariate distribution for correlated effect sizes is obtained by extending univariate methods for estimating effect sizes which are correlated through common control groups. The joint distribution of vectors of effect sizes (from $p$ responses on each subject) from one treatment and one control group and from several treatment groups sharing a common control group are derived. Methods are given for estimation of linear combinations of effect sizes when certain homogeneity conditions are met, and for estimation of vectors of effect sizes and confidence intervals from $p$ responses on each subject. Computational illustrations are provided using data from studies of effects of electric field exposure on small laboratory animals. ^

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.