Nursing Informatics and Epigenetics: Methodological Considerations for Big Data Analysis.

Nursing informatics requires an understanding of patient-centered data and clinical workflow, and epigenetic research requires an understanding of data analysis. The purpose of this article is to document the methodology that nursing informatics specialists can use to conduct epigenetic research and subsequently strengthen patient-centered care. A pilot study of a secondary methylation data analysis using The Cancer Genome Atlas data from individuals with colon cancer is utilized to illustrate the methodology. The steps for conducting the study using public and free resources are discussed. These steps include finding a data source; downloading and analyzing differentially methylated regions; annotating differentially methylated region, gene ontology and function analysis; and reporting results. A model of epigenetic testing workflow is provided, as is a list of publicly available data and analysis sources that can be used to conduct epigenetic research.

Current status and future directions of U.S. genomic nursing health care policy.

BACKGROUND: As genomic science moves beyond government-academic collaborations into routine healthcare operations, nursing's holistic philosophy and evidence-based practice approach positions nurses as leaders to advance genomics and precision health care in routine patient care. PURPOSE: To examine the status of and identify gaps for U.S. genomic nursing health care policy and precision health clinical practice implementation. METHODS: We conducted a scoping review and policy priorities analysis to clarify key genomic policy concepts and definitions, and to examine trends and utilization of health care quality benchmarking used in precision health. FINDINGS: Genomic nursing health care policy is an emerging area. Educating and training the nursing workforce to achieve full dissemination and integration of precision health into clinical practice remains an ongoing challenge. Use of health care quality measurement principles and federal benchmarking performance evaluation criteria for precision health implementation are not developed. DISCUSSION: Nine recommendations were formed with calls to action across nursing practice workforce and education, nursing research, and health care policy arenas. CONCLUSIONS: To advance genomic nursing health care policy, it is imperative to develop genomic performance measurement tools for clinicians, purchasers, regulators and policymakers and to adequately prepare the nursing workforce.

APOA5 Gene Polymorphisms and Cardiovascular Diseases: Metaprediction in Global Populations.

BACKGROUND: Apolipoprotein A5 (APOA5) 1131 is one of the most investigated gene polymorphisms in association with cardiovascular diseases (CVD) for its roles in epigenetics pathways. OBJECTIVES: The major objective of this metaprediction study was to comprehensively examine the association of polymorphism risk subtypes of APOA5 1131 gene and potential contributing factors of CVD risks in global populations. METHODS: This study is a meta-analysis to determine APOA5 gene polymorphisms as risk factors for CVDs. Following the guidelines of meta-analyses, we applied big data analytics including the recursive partition tree, nonlinear association curve fit, and heat maps for data visualization-in addition to the conventional pooled analyses. RESULTS: A total of 17,692 CVD cases and 23,566 controls from 50 study groups were included. The frequency of APOA5 1131 CC and TC polymorphisms in Asian populations (22.2%-52.6%) were higher than that in other populations, including Caucasians and Eurasians (10.0%-25.0%). The homozygous CC and heterozygous TC genotypes (both p < .0001) were associated with increased risks for CVD and were higher in many Western nations, including Canada, Spain, the Czech Republic, Hungary, Turkey, Egypt, France, and Iran. The CC genotype was associated with greater risks (RR > 2.00, p < .0001) for dyslipidemia and myocardial infarction, whereas RR > 1.00 was associated with metabolic syndrome, coronary artery disease, and stroke. Air pollution was significantly associated with APOA5 1131 CC and TC polymorphisms. DISCUSSION: The findings of this study provided novel insight to further understand the associations among APOA5 1131 polymorphisms, air pollution, and the development of CVDs. Methylation studies are needed to examine epigenetic factors associated with APOA5 1131 polymorphisms and CVD and to suggest potential prevention strategies for CVD.

MTHFR Gene Polymorphism-Mutations and Air Pollution as Risk Factors for Breast Cancer: A Metaprediction Study.

BACKGROUND: The methylenetetrahydrofolate reductase gene (MTHFR) is one of the most investigated genes associated with breast cancer for its role in epigenetic pathways. OBJECTIVES: The objectives of this metaprediction study were to examine the polymorphism-mutation risk subtypes of MTHFR and air pollution as contributing factors for breast cancer. METHODS: For triangulation purposes in metapredictive analyses, we used a recursive partition tree, nonlinear association curve fit, and heat maps for data visualization, in addition to the conventional comparison procedure and pooled analyses. RESULTS: We included 36,683 breast cancer cases and 40,689 controls across 82 studies for MTHFR 677 and 23,252 cases and 27,094 controls across 50 studies for MTHFR 1298. MTHFR 677 TT was a risk genotype for breast cancer (p = .0004) and in the East Asian subgroup (p = .005). On global maps, the most polymorphism-mutations on MTHFR 677 TT were found in the Middle East, Europe, Asia, and the Americas, whereas the most mutations on MTHFR 1298 CC were located in Europe and the Middle East for the control group. The geographic information system maps further revealed that MTHFR 677 TT mutations yielded a higher risk of breast cancer for Australia, East Asia, the Middle East, South Europe, Morocco, and the Americas and that MTHFR 1298 CC mutations yielded a higher risk in Asia, the Middle East, South Europe, and South America. Metapredictive analysis revealed that air pollution level was significantly associated with MTHFR 677 TT polymorphism-mutation genotype. DISCUSSION: We present the most comprehensive analyses to date of MTHFR polymorphism-mutations and breast cancer risk. Future nursing studies are needed to investigate the health impact on breast cancer of epigenetics and air pollution across populations.

Gene-Metabolite Interaction in the One Carbon Metabolism Pathway: Predictors of Colorectal Cancer in Multi-Ethnic Families.

For personalized healthcare, the purpose of this study was to examine the key genes and metabolites in the one-carbon metabolism (OCM) pathway and their interactions as predictors of colorectal cancer (CRC) in multi-ethnic families. In this proof-of-concept study, we included a total of 30 participants, 15 CRC cases and 15 matched family/friends representing major ethnic groups in southern California. Analytics based on supervised machine learning were applied, with the target variable being specified as cancer, including the ensemble method and generalized regression (GR) prediction. Elastic Net with Akaike's Information Criterion with correction (AICc) and Leave-One-Out cross validation GR methods were used to validate the results for enhanced optimality, prediction, and reproducibility. The results revealed that despite some family members sharing genetic heritage, the CRC group had greater combined gene polymorphism-mutations than the family controls (p < 0.1) for five genes including MTHFR C677T, MTHFR A1298C, MTR A2756G, MTRR A66G, and DHFR 19bp. Blood metabolites including homocysteine (7 µmol/L), methyl-folate (40 nmol/L) with total gene mutations (≥4); age (51 years) and vegetable intake (2 cups), and interactions of gene mutations and methylmalonic acid (MMA) (400 nmol/L) were significant predictors (all p < 0.0001) using the AICc. The results were validated by a 3% misclassification rate, AICc of 26, and >99% area under the receiver operating characteristic curve. These results point to the important roles of blood metabolites as potential markers in the prevention of CRC. Future intervention studies can be designed to target the ways to mitigate the enzyme-metabolite deficiencies in the OCM pathway to prevent cancer.

Meta-analysis of homocysteine-related factors on the risk of colorectal cancer.

The major objective of this meta-analysis was to examine the association between homocysteine and related measurements with the risk of colorectal cancer (CRC) and adenomatous polyps (AP). Many studies presented an association between methyltetrahydrofolate reductase (MTHFR) gene polymorphisms and risk of CRC. Yet, there have been variances on what homocysteine-related and dietary factors play on the risk of CRC or AP, in association with folate-related one carbon metabolism pathways. We pooled analyses to examine comprehensively all homocysteine related factors including blood tests measurements, dietary, and lifestyle factors for their associations with the risk of CRC and AP. We located 86 articles published from 1995 to 2017. The results revealed that elevated homocysteine levels and decreased vitamin B12 levels in the blood were associated with increased risks of CRC and AP, with case-control studies having greater significant effect sizes compared to that of cohort-control studies. Decreased methionine and vitamin B6 levels in the blood increased the risk of CRC. MTHFR 677 TT and CT polymorphisms were interacting with elevated homocysteine levels to increase the risk of CRC. Decreased dietary fiber, methionine, vitamin B9 or folate, and vitamin B6 intakes were associated with increased risks of CRC; whereas, increased dietary B12 intake, alcohol intake, and smoking were associated with increased risk of CRC. Further studies can be conducted to examine the mechanistic differences of blood levels of homocysteine-related and dietary factors, including different types of dietary fiber, for their effects on decreasing the homocysteine toxicity to prevent CRC.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls (p < 0.05), on MTHFR C677T, MTR A2756G, MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05) except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike's information criterion and leave-one-out cross validation methods. Body mass index (BMI) and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene-environment interactions in the prevention of CRC.

Meta-Prediction of MTHFR Gene Polymorphisms and Air Pollution on the Risk of Hypertensive Disorders in Pregnancy Worldwide.

Hypertensive disorders in pregnancy (HDP) are devastating health hazards for both women and children. Both methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms and air pollution can affect health status and result in increased risk of HDP for women. The major objective of this study was to investigate the effect of MTHFR polymorphisms, air pollution, and their interaction on the risk of HDP by using meta-predictive analytics. We searched various databases comprehensively to access all available studies conducted for various ethnic populations from countries worldwide, from 1997 to 2017. Seventy-one studies with 8064 cases and 13,232 controls for MTHFR C677T and 11 studies with 1425 cases and 1859 controls for MTHFR A1298C were included. MTHFR C677T homozygous TT (risk ratio (RR) = 1.28, p < 0.0001) and CT plus TT (RR = 1.07, p = 0.0002) were the risk genotypes, while wild-type CC played a protective role (RR = 0.94, p = 0.0017) for HDP. The meta-predictive analysis found that the percentage of MTHFR C677T TT plus CT (p = 0.044) and CT (p = 0.043) genotypes in the HDP case group were significantly increased with elevated levels of air pollution worldwide. Additionally, in countries with higher air pollution levels, the pregnant women with wild-type CC MTHFR 677 had a protection effect against HDP (p = 0.014), whereas, the homozygous TT of MTHFR C677T polymorphism was a risk genotype for developing HDP. Air pollution level is an environmental factor interacting with increased MTHFR C677T polymorphisms, impacting the susceptibility of HDP for women.

Meta-Prediction of MTHFR Gene Polymorphism and Air Pollution on the Risks of Congenital Heart Defects Worldwide: A Transgenerational Analysis.

Congenital heart disease (CHD) is the leading cause of death in children, and is affected by genetic and environmental factors. To investigate the association of air pollution with methylene-tetrahydrofolate reductase (MTHFR) polymorphisms and the risk of CHD, we included 58 study groups of children and parents, with 12,347 cases and 18,106 controls worldwide. Both MTHFR C677T (rs 1801133) and A1298C (rs 1801131) gene polymorphisms were risks for CHD in children with transgenerational effects from their parents. Countries with greater risks of CHD with a pooled risk ratio (RR) > 2 from MTHFR 677 polymorphisms included Germany, Portugal, China, and Egypt for children; and Brazil, Puerto Rico, Mexico, China, and Egypt for mothers. Whereas, countries with greater risk of CHD with RR > 2 from MTHFR 1298 polymorphisms included Taiwan, Turkey, and Egypt for children; and Brazil, China, and Egypt for mothers. Additionally, meta-prediction analysis revealed that the percentages of MTHFR 677TT and TT plus CT polymorphisms together were increased in countries with higher levels of air pollution, with a trend of increased CHD risks with higher levels of air pollution for children (p = 0.07). Our findings may have significant implications for inflammatory pathways in association with MTHFR polymorphisms and future intervention studies to correct for folate-related enzyme deficits resultied from MTHFR polymorphisms to prevent CHDs for future generations.

Personalized Nutrition-Genes, Diet, and Related Interactive Parameters as Predictors of Cancer in Multiethnic Colorectal Cancer Families.

To personalize nutrition, the purpose of this study was to examine five key genes in the folate metabolism pathway, and dietary parameters and related interactive parameters as predictors of colorectal cancer (CRC) by measuring the healthy eating index (HEI) in multiethnic families. The five genes included methylenetetrahydrofolate reductase (MTHFR) 677 and 1298, methionine synthase (MTR) 2756, methionine synthase reductase (MTRR 66), and dihydrofolate reductase (DHFR) 19bp, and they were used to compute a total gene mutation score. We included 53 families, 53 CRC patients and 53 paired family friend members of diverse population groups in Southern California. We measured multidimensional data using the ensemble bootstrap forest method to identify variables of importance within domains of genetic, demographic, and dietary parameters to achieve dimension reduction. We then constructed predictive generalized regression (GR) modeling with a supervised machine learning validation procedure with the target variable (cancer status) being specified to validate the results to allow enhanced prediction and reproducibility. The results showed that the CRC group had increased total gene mutation scores compared to the family members (p < 0.05). Using the Akaike's information criterion and Leave-One-Out cross validation GR methods, the HEI was interactive with thiamine (vitamin B1), which is a new finding for the literature. The natural food sources for thiamine include whole grains, legumes, and some meats and fish which HEI scoring included as part of healthy portions (versus limiting portions on salt, saturated fat and empty calories). Additional predictors included age, as well as gender and the interaction of MTHFR 677 with overweight status (measured by body mass index) in predicting CRC, with the cancer group having more men and overweight cases. The HEI score was significant when split at the median score of 77 into greater or less scores, confirmed through the machine-learning recursive tree method and predictive modeling, although an HEI score of greater than 80 is the US national standard set value for a good diet. The HEI and healthy eating are modifiable factors for healthy living in relation to dietary parameters and cancer prevention, and they can be used for personalized nutrition in the precision-based healthcare era.

Predictors of the Healthy Eating Index and Glycemic Index in Multi-Ethnic Colorectal Cancer Families.

For personalized nutrition in preparation for precision healthcare, we examined the predictors of healthy eating, using the healthy eating index (HEI) and glycemic index (GI), in family-based multi-ethnic colorectal cancer (CRC) families. A total of 106 participants, 53 CRC cases and 53 family members from multi-ethnic families participated in the study. Machine learning validation procedures, including the ensemble method and generalized regression prediction, Elastic Net with Akaike's Information Criterion with correction and Leave-One-Out cross validation methods, were applied to validate the results for enhanced prediction and reproducibility. Models were compared based on HEI scales for the scores of 77 versus 80 as the status of healthy eating, predicted from individual dietary parameters and health outcomes. Gender and CRC status were interactive as additional predictors of HEI based on the HEI score of 77. Predictors of HEI 80 as the criterion score of a good diet included five significant dietary parameters (with intake amount): whole fruit (1 cup), milk or milk alternative such as soy drinks (6 oz), whole grain (1 oz), saturated fat (15 g), and oil and nuts (1 oz). Compared to the GI models, HEI models presented more accurate and fitted models. Milk or a milk alternative such as soy drink (6 oz) is the common significant parameter across HEI and GI predictive models. These results point to the importance of healthy eating, with the appropriate amount of healthy foods, as modifiable factors for cancer prevention.

A Meta-Prediction of Methylenetetrahydrofolate-Reductase Polymorphisms and Air Pollution Increased the Risk of Ischemic Heart Diseases Worldwide.

Ischemic heart disease (IHD) is among the leading causes of death worldwide. Methylenetetrahydrofolate reductase (MTHFR) polymorphisms have been associated with IHD risk, but the findings presented with heterogeneity. The purpose of the present meta-analysis was to provide an updated evaluation by integrating machine-learning based analytics to examine the potential source of heterogeneity on the associations between MTHFR polymorphisms and the risk of various subtypes of IHD, as well as the possible impact of air pollution on MTHFR polymorphisms and IHD risks. A comprehensive search of various databases was conducted to locate 123 studies (29,697 cases and 31,028 controls) for MTHFR C677T, and 18 studies (7158 cases and 5482 controls) for MTHFR A1298C. Overall, MTHFR 677 polymorphisms were risks for IHD (TT: Risk ratio (RR) = 1.23, p < 0.0001; CT: RR = 1.04, p = 0.0028, and TT plus CT: RR = 1.09, p < 0.0001). In contrast, MTHFR 677 CC wildtype was protective against IHD (RR = 0.91, p < 0.00001) for overall populations. Three countries with elevated IHD risks from MTHFR C677T polymorphism with RR >2 included India, Turkey, and Tunisia. Meta-predictive analysis revealed that increased air pollution was associated with increased MTHFR 677 TT and CT polymorphisms in both the case and control group (p < 0.05), with the trend of increased IHD risk resulting from increased air pollution. These results associate the potential inflammatory pathway with air pollution and the folate pathway with MTHFR polymorphism. Future intervention studies can be designed to mitigate MTHFR enzyme deficiencies resulting from gene polymorphisms to prevent IHDs for at-risk populations.

Meta-Analysis of NOS3 G894T Polymorphisms with Air Pollution on the Risk of Ischemic Heart Disease Worldwide.

The purpose of this updated meta-analysis was to investigate the effect of nitric oxide synthase-3 (NOS3) G894T polymorphisms, air pollution and their interaction on ischemic heart disease (IHD) risk across populations worldwide. Recursive partition trees, nonlinear association curve fit and geographic information system maps were incorporated to verify results of conventional pooled analyses for sources of heterogeneity. Results from 61 studies (16,219 cases, 12,222 controls) revealed a significant increased relative risk (RR) of IHD associated with NOS3 894 polymorphisms TT (RR = 1.44) and GT (RR = 1.37). Subgroup analysis revealed that the TT polymorphism genotype had significantly increased risk of IHD in Caucasian, East Asian, South Asian, and Middle Eastern populations (all p < 0.05). It is important to point out that many countries demonstrated an average risk of greater than two, which identifies the NOS3 894 TT polymorphism as a potential causal factor and biological marker of IHD, based on criteria for strong evidence used in international consensus panels. These 10 countries include Ukraine, the United Kingdom, Brazil, Chile, Japan, South Korea, India, Iran, Egypt and Morocco. For these countries with elevated risk (RR > 2) from the NOS3 894 TT polymorphism, meta-predictive analysis demonstrated an increasing trend in air pollution association with increased NOS3 894 polymorphisms. Further studies are needed to explore the complexity of the associations among NOS3 gene polymorphisms per population stratifications within countries, detailed air pollution data for added specificity for geographic location across time, and disease risk.

Genome wide DNA differential methylation regions in colorectal cancer patients in relation to blood related family members, obese and non-obese controls - a preliminary report.

Despite evidences linking methylation changes in the cancer tissues, little is known about the methylation modification in the peripheral blood. With the current study, we identified differential methylation regions (DMRs) across human genome by collecting the blood samples of colorectal cancer (CRC) patients compared to that of their blood-related family who shared genetic inheritance and environmental influences, and unrelated obese and non-obese controls by accessing publicly available Gene Expression Omnibus data. We performed genome-wide analyses using the reduced representation bisulfite sequencing (RRBS) method covering about 25% of CpGs for whole human genome of the four groups (n = 5 each). In comparison to the non-obese controls, we observed significant DMRs in CRC for genes involved in tumorigenesis including MLH3, MSH2, MSH6, SEPT9, GNAS; and glucose transporter genes associated with obesity and diabetes including SLC2A1/GLUT1, and SLC2A3/GLUT3 that were reported on methylation being modified in cancer tissues. In addition, we observed significant DMRs in CRC for genes involved in the methylation pathways including PEMT, ALDH1L1, and DNMT3A. CRC and family members shared significant DMRs for genes of tumorigenesis including MSH2, SEPT9, GNAS, SLC2A1/GLUT1 and SLC2A3/GLUT3); and CAMK1, GLUT1/SLC2A1 and GLUT3/SLC2A3 genes involved in glucose and insulin metabolism that played vital role in development of obesity and diabetes. Our study provided evidences that these differentially methylated genes in the blood could potentially serve as candidate biomarkers for CRC diagnostic and may provide further understanding on CRC progression. Further studies are warranted to validate these methylation changes for diagnostic and prevention of CRC.

Meta-Prediction of the Effect of Methylenetetrahydrofolate Reductase Polymorphisms and Air Pollution on Alzheimer's Disease Risk.

Background: Alzheimer's disease (AD) is a significant public health issue. AD has been linked with methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism, but the findings have been inconsistent. The purpose of this meta-predictive analysis is to examine the associations between MTHFR polymorphisms and epigenetic factors, including air pollution, with AD risk using big data analytics approaches. Methods and Results: Forty-three studies (44 groups) were identified by searching various databases. MTHFR C677T TT and CT genotypes had significant associations with AD risk in all racial populations (RR = 1.13, p = 0.0047; and RR = 1.12, p < 0.0001 respectively). Meta-predictive analysis showed significant increases of percentages of MTHFR C677T polymorphism with increased air pollution levels in both AD case group and control group (p = 0.0021-0.0457); with higher percentages of TT and CT genotypes in the AD case group than that in the control group with increased air pollution levels. Conclusions: The impact of MTHFR C677T polymorphism on susceptibility to AD was modified by level of air pollution. Future studies are needed to further examine the effects of gene-environment interactions including air pollution on AD risk for world populations.