Dissemination of methicillin-resistant Staphylococcus aureus USA300 sequence type 8 lineage in Latin America.

BACKGROUND: Methicillin-resistant Staphylococus aureus (MRSA) is an important nosocomial and community-associated (CA) pathogen. Recently, a variant of the MRSA USA300 clone emerged and disseminated in South America, causing important clinical problems. METHODS: S. aureus isolates were prospectively collected (2006-2008) from 32 tertiary hospitals in Colombia, Ecuador, Peru, and Venezuela. MRSA isolates were subjected to antimicrobial susceptibility testing and pulsed-field gel electrophoresis and were categorized as health care-associated (HA)-like or CA-like clones on the basis of genotypic characteristics and detection of genes encoding Panton-Valentine leukocidin and staphylococcal cassette chromosome (SCC) mec IV. In addition, multilocus sequence typing of representative isolates of each major CA-MRSA pulsotype was performed, and the presence of USA300-associated toxins and the arcA gene was investigated for all isolates categorized as CA-MRSA. RESULTS: A total of 1570 S. aureus were included; 651 were MRSA (41%)--with the highest rate of MRSA isolation in Peru (62%) and the lowest in Venezuela (26%)--and 71%, 27%, and 2% were classified as HA-like, CA-like, and non-CA/HA-like clones, respectively. Only 9 MRSA isolates were confirmed to have reduced susceptibility to glycopeptides (glycopeptide-intermediate S. aureus phenotype). The most common pulsotype (designated ComA) among the CA-like MRSA strains was found in 96% of isolates, with the majority (81%) having a < or =6-band difference with the USA300-0114 strain. Representative isolates of this clone were sequence type 8; however, unlike the USA300-0114 strain, they harbored a different SCCmec IV subtype and lacked arcA (an indicator of the arginine catabolic mobile element). CONCLUSION: A variant CA-MRSA USA300 clone has become established in South America and, in some countries, is endemic in hospital settings.

Outcomes and cost effectiveness of treating type 2 diabetes with a nurse case manager following treatment algorithms versus primary care physicians

Background. Diabetes places a significant burden on the health care system. Reduction in blood glucose levels (HbA1c) reduces the risk of complications; however, little is known about the impact of disease management programs on medical costs for patients with diabetes. In 2001, economic costs associated with diabetes totaled $100 billion, and indirect costs totaled $54 billion. ^ Objective. To compare outcomes of nurse case management by treatment algorithms with conventional primary care for glycemic control and cardiovascular risk factors in type 2 diabetic patients in a low-income Mexican American community-based setting, and to compare the cost effectiveness of the two programs. Patient compliance was also assessed. ^ Research design and methods. An observational group-comparison to evaluate a treatment intervention for type 2 diabetes management was implemented at three out-patient health facilities in San Antonio, Texas. All eligible type 2 diabetic patients attending the clinics during 1994–1996 became part of the study. Data were obtained from the study database, medical records, hospital accounting, and pharmacy cost lists, and entered into a computerized database. Three groups were compared: a Community Clinic Nurse Case Manager (CC-TA) following treatment algorithms, a University Clinic Nurse Case Manager (UC-TA) following treatment algorithms, and Primary Care Physicians (PCP) following conventional care practices at a Family Practice Clinic. The algorithms provided a disease management model specifically for hyperglycemia, dyslipidemia, hypertension, and microalbuminuria that progressively moved the patient toward ideal goals through adjustments in medication, self-monitoring of blood glucose, meal planning, and reinforcement of diet and exercise. Cost effectiveness of hemoglobin AI, final endpoints was compared. ^ Results. There were 358 patients analyzed: 106 patients in CC-TA, 170 patients in UC-TA, and 82 patients in PCP groups. Change in hemoglobin A1c (HbA1c) was the primary outcome measured. HbA1c results were presented at baseline, 6 and 12 months for CC-TA (10.4%, 7.1%, 7.3%), UC-TA (10.5%, 7.1%, 7.2%), and PCP (10.0%, 8.5%, 8.7%). Mean patient compliance was 81%. Levels of cost effectiveness were significantly different between clinics. ^ Conclusion. Nurse case management with treatment algorithms significantly improved glycemic control in patients with type 2 diabetes, and was more cost effective. ^

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. ^

Physiologic and psychosocial stage-based differences for dietary fat consumption in women with type 2 diabetes

Purpose. This cross-sectional, observational study explored differences among groups staged for intent to decrease dietary fat intake in women with type 2 diabetes in relation to demographic, weight concern, physiological, and psychosocial variables. ^ Methods. A sample of 100 community-dwelling, English-speaking women, who were over age 30 and had type 2 diabetes for at least a year, was accessed through a culturally diverse endocrinology clinic. Subjects completed 7 self-report instruments: demographic sheet, with 11-point weight satisfaction scale; staging algorithm; fat intake (MEDFICTS); depression (CES-D); diabetes-specific dietary knowledge (ADKnowl), social support and self-efficacy scales (SE-Type 2). Physiological variables were abstracted from the medical record (HbA 1c, blood pressure, serum cholesterol and triglycerides). ^ Results. The women's average age was 57.69 years ( SD = 3.07); 50% were married. Subjects were well-educated ( M = 14 years; SD = 3.33), with average diabetes duration of 10.57 years (SD = 9.11), high body mass index (M = 35.72; SD = 8.36), low diabetes-specific dietary knowledge, low weight satisfaction, but in good diabetes control. Racial/ethnic composition was 44% non-Hispanic-White-American, 18% Hispanic-White-American, 15% non-Hispanic-African-American, 16% Hispanic-African-American and 5% other. Fat intake was low and differed by racial/ethnic demographics. The highest fat intake scores were for non-Hispanic-African-Americans (M = 53), followed by Hispanic-White-Americans (M = 51), non-Hispanic-White-Americans (M = 45), and Hispanic-African-Americans (M = 32), who had the lowest fat intake scores. ^ MANOVA analyses revealed no significant differences between stages of behavior change in relation to psychosocial or weight concern variables, age, education, HbA1c, or cholesterol levels. Single women were more likely to be in the three preaction stages (precontemplation, contemplation, and preparation); married women were equally distributed across stages (the preaction stages plus action and maintenance). African-American women (Hispanic and non-Hispanic) were more likely in contemplation and preparation. Triglycerides were higher in women in the action stage than contemplation or preparation. Systolic blood pressure was higher in action than preparation; diastolic blood pressure was higher in action than preaction. ^ Conclusions. Healthcare professionals should consider race, ethnicity, and marital status in client interactions. Dietary intake can vary according to both race and ethnicity; collapsing racial/ethnic groups can alter means and distributions, generating faulty conclusions. Further research is warranted to explore relationships between dietary self-care and marital status, race, ethnicity, and physiological variables. ^

The effectiveness of a promotora-led intervention for Mexican Americans with type 2 diabetes

Purpose. The purpose of this randomized control repeated measures trial was to determine the effectiveness of a self-management intervention led by community lay workers called promotoras on the health outcomes of Mexican Americans with type 2 diabetes living in a major city on the Texas - Mexico border. The specific aims of this study, in relation to the intervention group participants, were to: (1) decrease the glycosylated hemoglobin (A1c) blood levels at the six-month assessment, (2) increase diabetes knowledge at the three and six-month assessments, and (3) strengthen the participants' beliefs in their ability to manage diabetes at the three and six-month assessments.^ Methods. One hundred and fifty Mexican American participants were recruited at a Catholic faith-based clinic and randomized into an intervention group and a usual-care control group. Personal characteristics, acculturation and baseline A1c, diabetes knowledge and diabetes health beliefs were measured. The six-month, two-phase intervention was culturally specific and it was delivered entirely by promotoras. Phase One of the intervention consisted of sixteen hours of participative group education and bi-weekly telephone contact follow-up. Phase Two consisted of bi-weekly follow-up using inspirational faith-based health behavior change postcards. The A1c levels, diabetes knowledge and diabetes health beliefs were measured at baseline, and three and six months post-baseline. The mean changes between the groups were analyzed using analysis of covariance. ^ Results. The 80% female sample, with a mean age of 58 years, demonstrated very low: acculturation, income, education, health insurance coverage, and strong Catholicism. No significant changes were noted at the three-month assessment, but the mean change of the A1c levels (F (1, 148 = 10.28, p < .001) and the diabetes knowledge scores (F (1, 148 = 9.0, p < .002) of the intervention group improved significantly at six months, adjusting for health insurance coverage. The diabetes health belief scores decreased in both groups.^ Conclusions. This study demonstrated that an intervention led by promotoras could result in decreased A1c levels and increased diabetes knowledge in spite of the very low acculturation, educational level and insurance coverage of the intervention group participants. Clinical implications and recommendations for future research are suggested. ^

Border intervention by Promotores for type 2 diabetes

Purpose of the study. This study had two components. The first component of the study was the development and implementation of an infrastructure that integrated Promotores who teach diabetes self-management into a community clinic. The second component was a six-month randomized clinical trial (RCT) designed to test the effectiveness of the Promotores in changing knowledge, beliefs, and HbA1c levels among Mexican American patients with type 2 diabetes. ^ Methods. Starfield's adaptation of the Donbedian structure, process, and outcome methodology was used to develop a clinic infrastructure that allowed the integration of Promotores as diabetes educators. The RCT of the culturally sensitive Promotores-led 10-week diabetes self-management program compared the outcomes of 63 patients in the intervention group with 68 patients in a wait-list, usual care control group. Participants were Mexican Americans, at least 18 years of age, with type 2 diabetes, who were patients at a Federally Qualified Health Center on the Texas-Mexico border. At baseline, three months, and six months, data were collected using the Diabetes Knowledge Questionnaire (DKQ, the Health Beliefs Questionnaire (HBQ, and HbA1c levels were drawn by the clinic laboratory. A mixed model methodology was used to analyze the data. ^ Results. The infrastructure to support a Promotores-led diabetes self-management course designed in concert with administration, the physicians, and the CDE, resulted in (1) employment of Promotores to teach diabetes self-management courses; (2) integration of provider and nurse oversight of course design and implementation; (3) management of Promotora training, and the development of teaching competencies and skills; (4) coordination of care through communication and documentation policies and procedures; (5) utilization of quality control mechanisms to maintain patient safety; and (6) promotion of a culturally competent approach to the educational process. The RCT resulted in a significant improvement in the intervention group's DKQ scores over time (F [1, 129] = 4.77, p = 0.0308), and in treatment by time (F [2, 168] = 5.85, p = 0.0035). Neither the HBQ scores nor the HbA1c changed over time. However, the baseline HbA1c was 7.49, almost at the therapeutic level. The DKQ, HBQ, and HbA1c results were significantly affected by age; the DKQ and HbA1c by years with diabetes. ^ Conclusions. The clinic model provides a systematic approach to safely address the educational needs of large numbers of patients with type 2 diabetes who live in communities that suffer from a lack of health care professionals. The Promotores-led diabetes self-management course improved the knowledge of patients with diabetes and may be a culturally sensitive strategy for meeting patient educational needs. The low baseline HbA1c levels in this border community suggested that patients in this Federally Qualified Health Center on the Texas-Mexico border were experiencing good medical management of their diabetes. ^

The impact of nutrition intervention on glycemic control in a pediatric type 1 diabetes mellitus population

Aim: The goal of this study was to evaluate the change in hemoglobin A1C and glycemic control after nutrition intervention among a population of type 1 diabetic pediatric patients. Methods: Data was collected from all type 1 diabetic patients who were scheduled for a consultation with the diabetes/endocrine RD from January 2006 through December 2006. Two groups were compared, those who kept their RD appointment and those who did not keep their appointment. The main outcome measure was HgbA1C. An independent samples t-test compared the two groups with respect to change in HbgA1C before and after the most recent scheduled appointment with the RD. Baseline characteristics were used as covariates and analyzed and controlled for using analysis of covariance (ANCOVA). Results: There was no difference in HgbA1c after either attending an RD appointment or not having attended an RD appointment. Those who arrived for and attended their RD appointment and those who did not arrive for and attend their RD appointment, had statistically different HgbA1C's before their scheduled appointment as well as after the RD appointment. However, the two groups were not equal at the beginning of the study period. Discussion: A study design with inclusion criteria of a specified range of HgbA1C values within which the study subjects needed to fall, would have potentially eliminated the difference between the two groups at the beginning of the study period. Conducting either another retrospective study that controlled for the initial HgbA1C value or conducting a prospective study that designated a range of HgbA1C values would be worth investigating to evaluate the impact of medical nutrition therapy intervention and the role of the RD in diabetes management. It is an interesting finding that there was a significant difference in the initial HgbA1c for those who came to the RD appointment compared to those who did not come. The fact that in this study those who did not arrive for their RD appointment had worse control of their diabetes suggests that this is a high-risk group. Targeting diabetes education toward this group of patients may prove to be beneficial. ^

Relationship between Clostridium difficile toxin type and clinical features, severity and outcome in patients with C. difficile diarrhea (CDAD)

Background. Clostridium difficile infection is one of the major causes of antibiotic associated diarrhea and colitis in the United States. Currently, there is a dearth of literature on the risk factors and outcomes differences between the patients with infection due to the hypervirulent strain vs. the non-hypervirulent strains. The objective of this study was to determine the relationship between C. difficile toxin type and clinical features, severity and outcome in patients with C. difficile diarrhea. ^ Methods. The case group included 37 patients who had infections due to hypervirulent strain (tcdC deletion) and the control group included 55 patients with other toxin types (toxin A, B, binary toxin). A univariate analysis was performed followed by a multivariable logistic regression analysis to assess the differences between cases and controls. ^ Results. In the multivariate analyses, we found out that being a male was a protective factor for developing the infection due to the hypervirulent strain [OR 0.33; 95% CI 0.12-0.90]. Also, the hypervirulent group has worse clinical and economic outcomes, although the differences were small and nonsignificant. ^ Conclusions. There may likely be no predictive risk factor for acquiring infection due to the hypervirulent strain and the acquisition may be more linked to the infection control practices of the individual hospitals or location of patients. Hence, better infection control practices may prove helpful in decreasing the overall disease burden and thus improve patient outcomes. ^

Charity care and community benefits by hospital type in Texas

Hospital care is the largest component of the health care sector. This industry is made up of for profit hospital (FPH) organizations, not for profit (NFP) hospitals, and government (GOV) run hospital facilities. Objectives of this analysis were: (a) to conduct a literature review on NFP hospital legislation at the state level in Texas and at the federal level in the broader U.S.; and (b) to describe the types of charity care and community benefits currently being provided: by NFP hospitals compared to FPH hospitals and GOV hospitals; by hospitals geographic proximity to the Texas-Mexico border; and by hospital community type (rural, suburban, and urban); and (c) propose specific policy changes that may be needed to improve the current Texas State statute. Methods. In describing the historical and current policy context of NFP hospital legislation in the United States, federal legislation was reviewed from 1913 to the present and Texas State legislation was reviewed from 1980 to the present. In describing the provision of charity care, data from the 2008 Annual Cooperative Hospital Survey were examined by hospital organizational type, size, proximity to the border, and community type using linear regression and chi-squared tests to assess differences in charity care and community benefits. Results. The data included 123 NFP hospitals, 114 GOV hospitals, and 123 FPH. Results. Small sized (p<0.001) and medium sized (p<0.001) NFP hospitals provide a greater percent of total charity care when compared to FPH hospitals and to both GOV and FPH hospitals respectively; however, no significant difference in total charity care was found among large sized NFP hospitals when compared to FPH hospitals alone (p=.345) and both GOV and FPH facilities (p=.214). The amount of charity care provided was not found to be different based on proximity to the border or community type. Community benefit planning and budgeting was found to be similar regardless of community type and proximity to the border. Conclusion. No differences in charity care in Texas were found for large sized NFP hospitals compared to FPH and GOV hospitals. Contrary to widely held beliefs, this study did not find the border region to provide a greater amount of charity care or bad debt. Charity care also did not vary by community type. These findings underscore the need for continued collection of transparent data from all hospitals in order to provide policy makers and consumers with information on utilization trends to ensure benefits are being provided to the community. Policy changes or revoking tax-benefits may occur as charity care utilization declines with the implementation of health reform in the next few years.^

Assessing the relationship between obesity and type II diabetes among South Asian Indians in Houston A population based study

Objective: My study aimed at determining the association between obesity and diabetes prevalence in South Asian Indian immigrants in Houston, Texas. To also compare the prevalence odds of diabetes given obesity, using WHO-BMI criteria and recommended Asian ethnic-specific BMI criteria for obesity, as well as using WHO-standard waist circumference criteria and ethnic-specific criteria for abdominal obesity, across gender and age, in this population. ^ Methods: My study was a secondary data analysis based on a cross-sectional study carried out on adult South Asian Indians who attended a local community health fair in Houston, in 2007. They recruited 213 voluntary, eligible, South Asian Indian participants aged between 18 to 79 years. Self reported history of Diabetes was obtained and height, weight, waist and hip circumference were measured. I classified BMI based on WHO-standard and ethnic-specific criteria, according to gender and age groups of 18–35 years, 36–64 years and 65 years and over. Waist circumference was also classified based on WHO-standard NCEP criteria and currently recommended ethnic-specific IDF criteria and analysis was done stratifying by gender and age groups. ^ Results: The prevalence of diabetes in this population was 14.6%, significantly higher in older age groups (25.8%) and males (19.2%). The prevalence of DM was statistically similar in individuals who were overweight/obese compared to those not overweight/obese, however in overweight/obese individuals, there was a statistically significant difference in the prevalence of DM between WHO and ethnic-specific criteria for both BMI and waist circumference. In older adults and in males, ethnic-specific criteria identified significantly more as overweight/obese compared to WHO-standard criteria. ^ Conclusions: Ethnic-specific criteria for both BMI and waist circumference give a better estimate for obesity in this South Asian Indian population. Diabetes is highly prevalent in migrant South Asian Indians even at low BMI or waist circumference levels and significantly more in males and older age groups, hence adequate awareness should be created for early prevention and intervention.^

Comparison of two statistical methods for rare variant association analysis

Studies have shown that rare genetic variants have stronger effects in predisposing common diseases, and several statistical methods have been developed for association studies involving rare variants. In order to better understand how these statistical methods perform, we seek to compare two recently developed rare variant statistical methods (VT and C-alpha) on 10,000 simulated re-sequencing data sets with disease status and the corresponding 10,000 simulated null data sets. The SLC1A1 gene has been suggested to be associated with diastolic blood pressure (DBP) in previous studies. In the current study, we applied VT and C-alpha methods to the empirical re-sequencing data for the SLC1A1 gene from 300 whites and 200 blacks. We found that VT method obtains higher power and performs better than C-alpha method with the simulated data we used. The type I errors were well-controlled for both methods. In addition, both VT and C-alpha methods suggested no statistical evidence for the association between the SLC1A1 gene and DBP. Overall, our findings provided an important comparison of the two statistical methods for future reference and provided preliminary and pioneer findings on the association between the SLC1A1 gene and blood pressure.^

Correlation of blood type with thrombosis in pancreatic cancer patients

Objective: The study aimed to identify the risk factors involved in initiating thromboembolism (TE) in pancreatic cancer (PC) patients, with focus on ABO blood type. ^ Methods and Patients: There were 35.7% confirmed cases of TE and 64.3% cases remained free of TE (n=687). There were 12.7% only Pulmonary embolism (PE), 9% only Deep vein thrombosis (DVT), 53.5% only other sites, 3.3% combined PE and DVT, 8.6% combined PE and other sites, 9.8% combined DVT and other sites, and 3.3% all three combined cases. ^ Results: The risk factors for thrombosis identified by multivariate logistic regression were: history of previous anti-thrombotic treatment, tumor site in pancreatic body or tail, large tumor size, maximum glucose category more than 126 and 200 mg/dL. ^ The factors with worse overall survival by multivariate Cox regression and Kaplan Meier analyses were: locally advanced or metastatic stage, worsening performance status, high CA 19-9 levels, and HbA1C levels more than 6 %, at diagnosis. ^ There were 29.1% and 39.1% of the patients with thrombosis in the O and non-O blood type groups respectively. Both Non-O blood type (P=0.02) and the A, B and AB blood types (P= 0.007) were associated with thrombosis as compared to O type. The odds of thrombosis were nearly half in O blood type patients as compared to non-O blood type [OR-0.54 (95% C.I.- 0.37-0.79), P<0.001]. ^ Conclusion: A better understanding of the TE and PC relationship and involved risk factors may provide insights on tumor biology and patient response to prophylactic anticoagulation therapy.^

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.