Gene by BMI Interactions Influencing C-Reactive Protein Levels in European-Americans

C-Reactive Protein (CRP) is a biomarker indicating tissue damage, inflammation, and infection. High-sensitivity CRP (hsCRP) is an emerging biomarker often used to estimate an individual’s risk for future coronary heart disease (CHD). hsCRP levels falling below 1.00 mg/l indicate a low risk for developing CHD, levels ranging between 1.00 mg/l and 3.00 mg/l indicate an elevated risk, and levels exceeding 3.00 mg/l indicate high risk. Multiple Genome-Wide Association Studies (GWAS) have identified a number of genetic polymorphisms which influence CRP levels. SNPs implicated in such studies have been found in or near genes of interest including: CRP, APOE, APOC, IL-6, HNF1A, LEPR, and GCKR. A strong positive correlation has also been found to exist between CRP levels and BMI, a known risk factor for CHD and a state of chronic inflammation. We conducted a series of analyses designed to identify loci which interact with BMI to influence CRP levels in a subsample of European-Americans in the ARIC cohort. In a stratified GWA analysis, 15 genetic regions were identified as having significantly (p-value < 2.00*10-3) distinct effects on hsCRP levels between the two obesity strata: lean (18.50 kg/m2 < BMI < 24.99 kg/m2) and obese (BMI ≥ 30.00 kg/m2). A GWA analysis performed on all individuals combined (i.e. not a priori stratified for obesity status) with the inclusion of an additional parameter for BMI by gene interaction, identified 11 regions which interact with BMI to influence hsCRP levels. Two regions containing the genes GJA5 and GJA8 (on chromosome 1) and FBXO11 (on chromosome 2) were identified in both methods of analysis suggesting that these genes possibly interact with BMI to influence hsCRP levels. We speculate that atrial fibrillation (AF), age-related cataracts and the TGF-β pathway may be the biological processes influenced by the interaction of GJA5, GJA8 and FBXO11, respectively, with BMI to cause changes in hsCRP levels. Future studies should focus on the influence of gene x bmi interaction on AF, age-related cataracts and TGF-β.

Gene by smoking interaction in blood pressure

Hypertension (HT) is mediated by the interaction of many genetic and environmental factors. Previous genome-wide linkage analysis studies have found many loci that show linkage to HT or blood pressure (BP) regulation, but the results were generally inconsistent. Gene by environment interaction is among the reasons that potentially explain these inconsistencies between studies. Here we investigate influences of gene by smoking (GxS) interaction on HT and BP in European American (EA), African American (AA) and Mexican American (MA) families from the GENOA study. A variance component-based method was utilized to perform genome-wide linkage analysis of systolic blood pressure (SBP), diastolic blood pressure (DBP), and HT status, as well as bivariate analysis for SBP and DBP for smokers, non-smokers, and combined groups. The most significant results were found for SBP in MA. The strongest signal was for chromosome 17q24 (LOD = 4.2), increased to (LOD = 4.7) in bivariate analysis but there was no evidence of GxS interaction at this locus (p = 0.48). Two signals were identified only in one group: on chromosome 15q26.2 (LOD = 3.37) in non-smokers and chromosome 7q21.11 (LOD = 1.4) in smokers, both of which had strong evidence for GxS interaction (p = 0.00039 and 0.009 respectively). There were also two other signals, one on chromosome 20q12 (LOD = 2.45) in smokers, which became much higher in the combined sample (LOD = 3.53), and one on chromosome 6p22.2 (LOD = 2.06) in non-smokers. Neither peak had very strong evidence for GxS interaction (p = 0.08 and 0.06 respectively). A fine mapping association study was performed using 200 SNPs in 30 genes located under the linkage signals on chromosomes 15 and 17. Under the chromosome 15 peak, the association analysis identified 6 SNPs accounting for a 7 mmHg increase in SBP in MA non-smokers. For the chromosome 17 linkage peak, the association analysis identified 3 SNPs accounting for a 6 mmHg increase in SBP in MA. However, none of these SNPs was significant after correcting for multiple testing, and accounting for them in the linkage analysis produced very small reductions in the linkage signal. ^ The linkage analysis of BP traits considering the smoking status produced very interesting signals for SBP in the MA population. The fine mapping association analysis gave some insight into the contribution of some SNPs to two of the identified signals, but since these SNPs did not remain significant after multiple testing correction and did not explain the linkage peaks, more work is needed to confirm these exploratory results and identify the culprit variations under these linkage peaks. ^

Transcriptional and translational regulators of gene expression in germ cell development

Germ cell development is a highly coordinated process driven, in part, by regulatory mechanisms that control gene expression. Not only transcription, but also translation, is under regulatory control to direct proper germ cell development. In this dissertation, I have focused on two regulators of germ cell development. One is the homeobox protein RHOX10, which has the potential to be both a transcriptional and translational regulator in mouse male germ cell development. The other is the RNA-binding protein, Hermes, which functions as a translational regulator in Xenopus laevis female germ cell development. ^ Rhox10 is a member of reproductive homeobox gene X-(linked (Rhox) gene cluster, of which expression is developmentally regulated in developing mouse testes. To identify the cell types and developmental stages in which Rhox10 might function, I characterized its temporal and spatial expression pattern in mouse embryonic, neonatal, and adult tissues. Among other things, this analysis revealed that both the level and the subcellular localization of RHOX10 are regulated during germ cell development. To understand the role of Rhox10 in germ cell development, I generated transgenic mice expressing an artificial microRNA (miRNA) targeting Rhox10. While this artificial miRNA robustly downregulated RHOX10 protein expression in vitro, it did not significantly reduce RHOX10 expression in vivo. So I next elected to knockdown RHOX10 levels in spermatogonial stem cells (SSCs), which I found highly express both Rhox10 mRNA and RHOX10 protein. Using a recently developed in vitro culture system for SSCs combined with a short-hairpin RNA (shRNA) approach, I strongly depleted RHOX10 expression in SSCs. These RHOX10-depleted cells exhibited a defect in the ability to form stem cell clusters in vitro. Expression profiling analysis revealed many genes regulated by Rhox10, including many meiotic genes, which could be downstream of Rhox10 in a molecular pathway that controls SSC differentiation. ^ RNA recognition motif (RRM) containing protein, Hermes is localized in germ plasm, where dormant mRNAs are also located, of Xenopus oocytes, which implicates its role in translational regulator. To understand the function of Hermes in oocyte meiosis, I used a morpholino oligonucleotide (MO) based knockdown approach. Microinjection of Hermes MO into fully grown oocytes, which are arrested in meiotic prophase, caused acceleration of oocytes reentry into meiosis (i.e., maturation) upon progesterone induction. Using a candidate approach, I identified at least three targets of Hermes: Ringo/Spy, Xcat2, and Mos. Ringo/Spy and Mos are known to have functions in oocyte maturation, while Ringo/Spy, Xcat2 mRNA are localized in the germ plasm of oocytes, which drives germ cell specification after fertilization. This led me to propose that Hermes functions in both oocyte maturation and germ cell development through its ability to regulate 3 crucial target mRNAs. ^

Multiple independent genetic factors at NOS1AP modulate the QT interval in a multi-ethnic population.

Extremes of electrocardiographic QT interval are associated with increased risk for sudden cardiac death (SCD); thus, identification and characterization of genetic variants that modulate QT interval may elucidate the underlying etiology of SCD. Previous studies have revealed an association between a common genetic variant in NOS1AP and QT interval in populations of European ancestry, but this finding has not been extended to other ethnic populations. We sought to characterize the effects of NOS1AP genetic variants on QT interval in the multi-ethnic population-based Dallas Heart Study (DHS, n = 3,072). The SNP most strongly associated with QT interval in previous samples of European ancestry, rs16847548, was the most strongly associated in White (P = 0.005) and Black (P = 3.6 x 10(-5)) participants, with the same direction of effect in Hispanics (P = 0.17), and further showed a significant SNP x sex-interaction (P = 0.03). A second SNP, rs16856785, uncorrelated with rs16847548, was also associated with QT interval in Blacks (P = 0.01), with qualitatively similar results in Whites and Hispanics. In a previously genotyped cohort of 14,107 White individuals drawn from the combined Atherosclerotic Risk in Communities (ARIC) and Cardiovascular Health Study (CHS) cohorts, we validated both the second locus at rs16856785 (P = 7.63 x 10(-8)), as well as the sex-interaction with rs16847548 (P = 8.68 x 10(-6)). These data extend the association of genetic variants in NOS1AP with QT interval to a Black population, with similar trends, though not statistically significant at P<0.05, in Hispanics. In addition, we identify a strong sex-interaction and the presence of a second independent site within NOS1AP associated with the QT interval. These results highlight the consistent and complex role of NOS1AP genetic variants in modulating QT interval.

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models.

Multifactor effects and evidence of potential interaction between complement factor H Y402H and LOC387715 A69S in age-related macular degeneration.

BACKGROUND: Variants in the complement cascade genes and the LOC387715/HTRA1, have been widely reported to associate with age-related macular degeneration (AMD), the most common cause of visual impairment in industrialized countries. METHODS/PRINCIPAL FINDINGS: We investigated the association between the LOC387715 A69S and complement component C3 R102G risk alleles in the Finnish case-control material and found a significant association with both variants (OR 2.98, p = 3.75 x 10(-9); non-AMD controls and OR 2.79, p = 2.78 x 10(-19), blood donor controls and OR 1.83, p = 0.008; non-AMD controls and OR 1.39, p = 0.039; blood donor controls), respectively. Previously, we have shown a strong association between complement factor H (CFH) Y402H and AMD in the Finnish population. A carrier of at least one risk allele in each of the three susceptibility loci (LOC387715, C3, CFH) had an 18-fold risk of AMD when compared to a non-carrier homozygote in all three loci. A tentative gene-gene interaction between the two major AMD-associated loci, LOC387715 and CFH, was found in this study using a multiplicative (logistic regression) model, a synergy index (departure-from-additivity model) and the mutual information method (MI), suggesting that a common causative pathway may exist for these genes. Smoking (ever vs. never) exerted an extra risk for AMD, but somewhat surprisingly, only in connection with other factors such as sex and the C3 genotype. Population attributable risks (PAR) for the CFH, LOC387715 and C3 variants were 58.2%, 51.4% and 5.8%, respectively, the summary PAR for the three variants being 65.4%. CONCLUSIONS/SIGNIFICANCE: Evidence for gene-gene interaction between two major AMD associated loci CFH and LOC387715 was obtained using three methods, logistic regression, a synergy index and the mutual information (MI) index.

Phosphorylation of the proline-rich domain of Xp95 modulates Xp95 interaction with partner proteins.

The mammalian adaptor protein Alix [ALG-2 (apoptosis-linked-gene-2 product)-interacting protein X] belongs to a conserved family of proteins that have in common an N-terminal Bro1 domain and a C-terminal PRD (proline-rich domain), both of which mediate partner protein interactions. Following our previous finding that Xp95, the Xenopus orthologue of Alix, undergoes a phosphorylation-dependent gel mobility shift during progesteroneinduced oocyte meiotic maturation, we explored potential regulation of Xp95/Alix by protein phosphorylation in hormone-induced cell cycle re-entry or M-phase induction. By MALDI-TOF (matrix-assisted laser-desorption ionization-time-of-flight) MS analyses and gel mobility-shift assays, Xp95 is phosphorylated at multiple sites within the N-terminal half of the PRD during Xenopus oocyte maturation, and a similar region in Alix is phosphorylated in mitotically arrested but not serum-stimulated mammalian cells. By tandem MS, Thr745 within this region, which localizes in a conserved binding site to the adaptor protein SETA [SH3 (Src homology 3) domain-containing, expressed in tumorigenic astrocytes] CIN85 (a-cyano-4-hydroxycinnamate)/SH3KBP1 (SH3-domain kinase-binding protein 1), is one of the phosphorylation sites in Xp95. Results from GST (glutathione S-transferase)-pull down and peptide binding/competition assays further demonstrate that the Thr745 phosphorylation inhibits Xp95 interaction with the second SH3 domain of SETA. However, immunoprecipitates of Xp95 from extracts of M-phase-arrested mature oocytes contained additional partner proteins as compared with immunoprecipitates from extracts of G2-arrested immature oocytes. The deubiquitinase AMSH (associated molecule with the SH3 domain of signal transducing adaptor molecule) specifically interacts with phosphorylated Xp95 in M-phase cell lysates. These findings establish that Xp95/Alix is phosphorylated within the PRD during M-phase induction, and indicate that the phosphorylation may both positively and negatively modulate their interaction with partner proteins.

Phosphorylation of the proline-rich domain of Xp95 modulates Xp95 interaction with partner proteins.

The mammalian adaptor protein Alix [ALG-2 (apoptosis-linked-gene-2 product)-interacting protein X] belongs to a conserved family of proteins that have in common an N-terminal Bro1 domain and a C-terminal PRD (proline-rich domain), both of which mediate partner protein interactions. Following our previous finding that Xp95, the Xenopus orthologue of Alix, undergoes a phosphorylation-dependent gel mobility shift during progesteroneinduced oocyte meiotic maturation, we explored potential regulation of Xp95/Alix by protein phosphorylation in hormone-induced cell cycle re-entry or M-phase induction. By MALDI-TOF (matrix-assisted laser-desorption ionization-time-of-flight) MS analyses and gel mobility-shift assays, Xp95 is phosphorylated at multiple sites within the N-terminal half of the PRD during Xenopus oocyte maturation, and a similar region in Alix is phosphorylated in mitotically arrested but not serum-stimulated mammalian cells. By tandem MS, Thr745 within this region, which localizes in a conserved binding site to the adaptor protein SETA [SH3 (Src homology 3) domain-containing, expressed in tumorigenic astrocytes] CIN85 (a-cyano-4-hydroxycinnamate)/SH3KBP1 (SH3-domain kinase-binding protein 1), is one of the phosphorylation sites in Xp95. Results from GST (glutathione S-transferase)-pull down and peptide binding/competition assays further demonstrate that the Thr745 phosphorylation inhibits Xp95 interaction with the second SH3 domain of SETA. However, immunoprecipitates of Xp95 from extracts of M-phase-arrested mature oocytes contained additional partner proteins as compared with immunoprecipitates from extracts of G2-arrested immature oocytes. The deubiquitinase AMSH (associated molecule with the SH3 domain of signal transducing adaptor molecule) specifically interacts with phosphorylated Xp95 in M-phase cell lysates. These findings establish that Xp95/Alix is phosphorylated within the PRD during M-phase induction, and indicate that the phosphorylation may both positively and negatively modulate their interaction with partner proteins.

The interaction of P160 BCR with BCR-ABL gene products unique to Philadelphia chromosome leukemias

The BCR gene is involved in the pathogenesis of Philadelphia chromosome-positive (Ph$\sp1$) leukemias. Typically, the 5$\sp\prime$ portion of BCR on chromosome 22 becomes fused to a 5$\sp\prime$ truncated ABL gene from chromosome 9 resulting in a chimeric BCR-ABL gene. To investigate the role of the BCR gene product, a number of BCR peptide sequences were used to generate anti-BCR antibodies for detection of BCR and BCR-ABL proteins. Since both BCR and ABL proteins have kinase activity, the anti-BCR antibodies were tested for their ability to immunoprecipitate BCR and BCR-ABL proteins from cellular lysates by use of an immunokinase assay. Antisera directed towards the C-terminal portions of P160 BCR, sequences not present in BCR-ABL proteins, were capable of co-immunoprecipitating P210 BCR-ABL from the Ph$\sp1$- positive cell line K562. Re-immunoprecipitation studies following complete denaturation showed that C-terminal BCR antisera specifically recognized P160 BCR but not P210 BCR-ABL. These and other results indicated the presence of a P160 BCR/P210 BCR-ABL protein complex in K562 cells. Experiments performed with Ph$\sp1$-positive ALL cells and uncultured Ph$\sp1$-positive patient white blood cells established the general presence of BCR/BCR-ABL protein complexes in BCR-ABL expressing cells. However, two cell lines derived from Ph$\sp1$-positive patients lacked P160 BCR/P210 BCR-ABL complexes. Lysates from one of these cell lines mixed with lysates from a cell line that expresses only P160 BCR failed to generate BCR/BCR-ABL protein complexes in vitro indicating that P160 BCR and P210 BCR-ABL do not simply oligomerize.^ Two-dimensional tryptic maps were performed on both BCR and BCR-ABL proteins labeled in vitro with $\sp{32}$P. These maps indicate that the autophosphorylation sites in BCR-ABL proteins are primarily located within BCR exon 1 sequences in both P210 and P185 BCR-ABL, and that P160 BCR is phosphorylated in trans in similar sites by the activated ABL kinase of both BCR-ABL proteins. These results provide strong evidence that P160 BCR serves as a target for the BCR-ABL oncoprotein.^ K562 cells, induced to terminally differentiate with the tumor promoter TPA, show a loss of P210 BCR-ABL kinase activity 12-18 hours after addition of TPA. This loss coincides with the loss of activity in P160 BCR/P210 BCR-ABL complexes but not with the loss of the P210 BCR-ABL, suggesting the existence of an inactive form of P210 BCR-ABL. However, a degraded BCR-ABL protein served as the kinase active form preferentially sequestered within the remaining BCR/BCR-ABL protein complex.^ The results described in this thesis form the basis for a model for BCR-ABL induced leukemias which is presented and discussed. ^

Identification of two vitamin D response elements in the rat osteopontin gene

Studies to elucidate the function of vitamin D have demonstrated an important role in regulating bone-related cells, including osteoblasts and osteoclasts. A seemingly paradoxical observation is that 1,25(OH)$\sb2$D$\sb3$, the active metabolite of vitamin D, stimulates bone resorption, yet regulates transcription of genes expressed by osteoblasts. One mechanism that could explain these actions is the upregulation of transcription of osteoblast-specific genes. These gene products could then act as effectors to influence osteoclastic activity. We hypothesized that molecular signals could be deposited directly into the mineralized matrix in the form of noncollagenous proteins, such as osteopontin (OPN). The structure, biosynthesis and localization of OPN suggest that it could function to mediate the molecular "cross talk" between osteoblasts and osteoclasts in response to 1,25(OH)$\sb2$D$\sb3$. To begin to address this hypothesis, elucidation of the molecular mechanisms of action involved in the transactivation of OPN by 1,25(OH)$\sb2$D$\sb3$ is essential.^ In the present study, the rat opn gene was isolated and characterized. Functional analysis by transient transfection of the 5$\sp\prime$ flanking sequences of the rat opn gene fused to the luciferase gene demonstrated that OPN is transcriptionally upregulated by 1,25(OH)$\sb2$D$\sb3$, mediated through two vitamin D response elements (VDRE). Both proximal and distal VDREs are structurally similar (two imperfect direct repeats separated by a 3 nucleotide spacer) and bind protein complexes that include the VDR and retinoid-X receptor (RXR). Isolated VDRE expression constructs produce functional activity of equivalent magnitude of responsiveness to 1,25(OH)$\sb2$D$\sb3$. However, expression constructs containing either VDRE and at least 200 bp of 5$\sp\prime$ and 3$\sp\prime$ flanking sequence demonstrated that the distal VDRE produces an amplitude of response significantly higher than the proximal VDRE. We conclude that the transcriptional upregulation of the opn gene by 1,25(OH)$\sb2$D$\sb3$ involves the transactivation of two VDREs, while maximal responsiveness requires interaction of the VDREs with additional cis-elements contained in the 5$\sp\prime$ sequence. ^

Genome-wide gene-gene interaction analysis for cardiovascular disease

Numerous studies have been carried out to try to better understand the genetic predisposition for cardiovascular disease. Although it is widely believed that multifactorial diseases such as cardiovascular disease is the result from effects of many genes which working alone or interact with other genes, most genetic studies have been focused on identifying of cardiovascular disease susceptibility genes and usually ignore the effects of gene-gene interactions in the analysis. The current study applies a novel linkage disequilibrium based statistic for testing interactions between two linked loci using data from a genome-wide study of cardiovascular disease. A total of 53,394 single nucleotide polymorphisms (SNPs) are tested for pair-wise interactions, and 8,644 interactions are found to be significant with p-values less than 3.5×10-11. Results indicate that known cardiovascular disease susceptibility genes tend not to have many significantly interactions. One SNP in the CACNG1 (calcium channel, voltage-dependent, gamma subunit 1) gene and one SNP in the IL3RA (interleukin 3 receptor, alpha) gene are found to have the most significant pair-wise interactions. Findings from the current study should be replicated in other independent cohort to eliminate potential false positive results.^

Gene-gene interaction and gene-pathway analysis of genome-wide association for schizophrenia

Schizophrenia (SZ) is a complex disorder with high heritability and variable phenotypes that has limited success in finding causal genes associated with the disease development. Pathway-based analysis is an effective approach in investigating the molecular mechanism of susceptible genes associated with complex diseases. The etiology of complex diseases could be a network of genetic factors and within the genes, interaction may occur. In this work we argue that some genes might be of small effect that by itself are neither sufficient nor necessary to cause the disease however, their effect may induce slight changes to the gene expression or affect the protein function, therefore, analyzing the gene-gene interaction mechanism within the disease pathway would play crucial role in dissecting the genetic architecture of complex diseases, making the pathway-based analysis a complementary approach to GWAS technique. ^ In this study, we implemented three novel linkage disequilibrium based statistics, the linear combination, the quadratic, and the decorrelation test statistics, to investigate the interaction between linked and unlinked genes in two independent case-control GWAS datasets for SZ including participants of European (EA) and African (AA) ancestries. The EA population included 1,173 cases and 1,378 controls with 729,454 genotyped SNPs, while the AA population included 219 cases and 288 controls with 845,814 genotyped SNPs. We identified 17,186 interacting gene-sets at significant level in EA dataset, and 12,691 gene-sets in AA dataset using the gene-gene interaction method. We also identified 18,846 genes in EA dataset and 19,431 genes in AA dataset that were in the disease pathways. However, few genes were reported of significant association to SZ. ^ Our research determined the pathways characteristics for schizophrenia through the gene-gene interaction and gene-pathway based approaches. Our findings suggest insightful inferences of our methods in studying the molecular mechanisms of common complex diseases.^

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.