Association of Roadway Proximity with Fasting Plasma Glucose and Metabolic Risk Factors for Cardiovascular Disease in a Cross-Sectional Study of Cardiac Catheterization Patients

BACKGROUND

The relationship between traffic-related air pollution (TRAP) and risk factors for cardiovascular disease needs to be better understood in order to address the adverse impact of air pollution on human health.

OBJECTIVE

We examined associations between roadway proximity and traffic exposure zones, as markers of TRAP exposure, and metabolic biomarkers for cardiovascular disease risk in a cohort of patients undergoing cardiac catheterization.

METHODS

We performed a cross-sectional study of 2,124 individuals residing in North Carolina (USA). Roadway proximity was assessed via distance to primary and secondary roadways, and we used residence in traffic exposure zones (TEZs) as a proxy for TRAP. Two categories of metabolic outcomes were studied: measures associated with glucose control, and measures associated with lipid metabolism. Statistical models were adjusted for race, sex, smoking, body mass index, and socioeconomic status (SES).

RESULTS

An interquartile-range (990 m) decrease in distance to roadways was associated with higher fasting plasma glucose (β = 2.17 mg/dL; 95% CI: -0.24, 4.59), and the association appeared to be limited to women (β = 5.16 mg/dL; 95% CI: 1.48, 8.84 compared with β = 0.14 mg/dL; 95% CI: -3.04, 3.33 in men). Residence in TEZ 5 (high-speed traffic) and TEZ 6 (stop-and-go traffic), the two traffic zones assumed to have the highest levels of TRAP, was positively associated with high-density lipoprotein cholesterol (HDL-C; β = 8.36; 95% CI: -0.15, 16.9 and β = 5.98; 95% CI: -3.96, 15.9, for TEZ 5 and 6, respectively).

CONCLUSION

Proxy measures of TRAP exposure were associated with intermediate metabolic traits associated with cardiovascular disease, including fasting plasma glucose and possibly HDL-C.

Epigenetic profiling identifies novel genes for ascending aortic aneurysm formation with bicuspid aortic valves

BACKGROUND

  Bicuspid aortic valves predispose to ascending aortic aneurysms, but the mechanisms underlying this aortopathy remain incompletely characterized.  We sought to identify epigenetic pathways predisposing to aneurysm formation in bicuspid patients.

METHODS

  Ascending aortic aneurysm tissue samples were collected at the time of aortic replacement in subjects with bicuspid and trileaflet aortic valves.  Genome-wide DNA methylation status was determined on DNA from tissue using the Illumina 450K methylation chip, and gene expression was profiled on the same samples using Illumina Whole-Genome DASL arrays.  Gene methylation and expression were compared between bicuspid and trileaflet individuals using an unadjusted Wilcoxon rank sum test.  

RESULTS

  Twenty-seven probes in 9 genes showed significant differential methylation and expression (P<5.5x10-4).  The top gene was protein tyrosine phosphatase, non-receptor type 22 (PTPN22), which was hypermethylated (delta beta range: +15.4 to +16.0%) and underexpressed (log 2 gene expression intensity: bicuspid 5.1 vs. trileaflet 7.9, P=2x10-5) in bicuspid patients, as compared to tricuspid patients.  Numerous genes involved in cardiovascular development were also differentially methylated, but not differentially expressed, including ACTA2 (4 probes, delta beta range:  -10.0 to -22.9%), which when mutated causes the syndrome of familial thoracic aortic aneurysms and dissections

CONCLUSIONS

  Using an integrated, unbiased genomic approach, we have identified novel genes associated with ascending aortic aneurysms in patients with bicuspid aortic valves, modulated through epigenetic mechanisms.  The top gene was PTPN22, which is involved in T-cell receptor signaling and associated with various immune disorders.  These differences highlight novel potential mechanisms of aneurysm development in the bicuspid population.

A Guide for a Cardiovascular Genomics Biorepository: the CATHGEN Experience

The CATHeterization GENetics (CATHGEN) biorepository was assembled in four phases. First, project start-up began in 2000. Second, between 2001 and 2010, we collected clinical data and biological samples from 9334 individuals undergoing cardiac catheterization. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included the following: subject demographics (birth date, race, gender, etc.); cardiometabolic history including symptoms; coronary anatomy and cardiac function at catheterization; and fasting chemistry data. Third, as part of the DDCD regular follow-up protocol, yearly evaluations included interim information: vital status (verified via National Death Index search and supplemented by Social Security Death Index search), myocardial infarction (MI), stroke, rehospitalization, coronary revascularization procedures, medication use, and lifestyle habits including smoking. Fourth, samples were used to generate molecular data. CATHGEN offers the opportunity to discover biomarkers and explore mechanisms of cardiovascular disease.

Computing a Synthetic Chronic Psychosocial Stress Measurement in Multiple Datasets and its Application in the Replication of G × E Interactions of the EBF1 Gene

Chronic psychosocial stress adversely affects health and is associated with the development of disease [Williams, 2008]. Systematic epidemiological and genetic studies are needed to uncover genetic variants that interact with stress to modify metabolic responses across the life cycle that are the proximal contributors to the development of cardiovascular disease and precipitation of acute clinical events. Among the central challenges in the field are to perform and replicate gene-by-environment (G × E) studies. The challenge of measurement of individual experience of psychosocial stress is magnified in this context. Although many research datasets exist that contain genotyping and disease-related data, measures of psychosocial stress are often either absent or vary substantially across studies. In this paper, we provide an algorithm to create a synthetic measure of chronic psychosocial stress across multiple datasets, applying a consistent criterion that uses proxy indicators of stress components. We validated the computed scores of chronic psychosocial stress by observing moderately strong and significant correlations with the self-rated chronic psychosocial stress in the Multi-Ethnic Study of Atherosclerosis Cohort (Rho = 0.23, P < 0.0001) and with the measures of depressive symptoms in five datasets (Rho = 0.15-0.42, Ps = 0.005 to <0.0001) and by comparing the distributions of the self-rated and computed measures. Finally, we demonstrate the utility of this computed chronic psychosocial stress variable by providing three additional replications of our previous finding of gene-by-stress interaction with central obesity traits [Singh et al., 2015].

Feasibility of a bilateral 4000-6000 Hz notch as a phenotype for genetic association analysis

OBJECTIVE

Noise-induced hearing loss (NIHL) is a worldwide health problem and a growing concern among young people. Although some people appear to be more susceptible to NIHL, genetic association studies lack a specific phenotype. We tested the feasibility of a bilateral 4000-6000 Hz audiometric notch as a phenotype for identifying genetic contributions to hearing loss in young adults.

DESIGN

A case-control-control study was conducted to examine selected SNPs in 52 genes previously associated with hearing loss and/or expressed in the cochlea. A notch was defined as a minimum of a 15-dB drop at 4000-6000 Hz from the previous best threshold with a 5-dB 'recovery' at 8000 Hz.

STUDY SAMPLE

Participants were 252 individuals of European descent taken from a population of 640 young adults who are students of classical music. Participants were grouped as No-notch (NN), Unilateral Notch (UN), or Bilateral Notch (BN).

RESULTS

The strongest evidence of a genetic association with the 4000-6000 Hz notch was a nonsynonymous SNP variant in the ESRR- gene (rs61742642:C> T, P386S). Carriers of the minor allele accounted for 26% of all bilateral losses.

CONCLUSION

This study indicates that the 4000-6000 Hz bilateral notch is a feasible phenotype for identifying genetic susceptibility to hearing loss.

Simultaneous consideration of multiple candidate protein biomarkers for long-term risk for cardiovascular events

BACKGROUND

Although individual protein biomarkers are associated with cardiovascular risk, rarely have multiple proteins been considered simultaneously to identify which set of proteins best predicts risk.

METHODS AND RESULTS

In a nested case-control study of 273 death/myocardial infarction (MI) cases and 273 age- (within 10 years), sex-, and race-matched and event-free controls from among 2023 consecutive patients (median follow-up 2.5 years) with suspected coronary disease, plasma levels of 53 previously reported biomarkers of cardiovascular risk were determined in a core laboratory. Three penalized logistic regression models were fit using the elastic net to identify panels of proteins independently associated with death/MI: proteins alone (Model 1); proteins in a model constrained to retain clinical variables (Model 2); and proteins and clinical variables available for selection (Model 3). Model 1 identified 6 biomarkers strongly associated with death/MI: intercellular adhesion molecule-1, matrix metalloproteinase-3, N-terminal pro-B-type natriuretic peptide, interleukin-6, soluble CD40 ligand, and insulin-like growth factor binding protein-2. In Model 2, only soluble CD40 ligand remained strongly associated with death/MI when all clinical risk predictors were retained. Model 3 identified a set of 6 biomarkers (intercellular adhesion molecule-1, matrix metalloproteinase-3, N-terminal pro-B-type natriuretic peptide, interleukin-6, soluble CD40 ligand, and insulin-like growth factor binding protein-2) and 5 clinical variables (age, red-cell distribution width, diabetes mellitus, hemoglobin, and New York Heart Association class) strongly associated with death/MI.

CONCLUSIONS

Simultaneously assessing the association between multiple putative protein biomarkers of cardiovascular risk and clinical outcomes is useful in identifying relevant biomarker panels for further assessment.

Genetic simulation tools for post-genome wide association studies of complex diseases

Genetic simulation programs are used to model data under specified assumptions to facilitate the understanding and study of complex genetic systems. Standardized data sets generated using genetic simulation are essential for the development and application of novel analytical tools in genetic epidemiology studies. With continuing advances in high-throughput genomic technologies and generation and analysis of larger, more complex data sets, there is a need for updating current approaches in genetic simulation modeling. To provide a forum to address current and emerging challenges in this area, the National Cancer Institute (NCI) sponsored a workshop, entitled "Genetic Simulation Tools for Post-Genome Wide Association Studies of Complex Diseases" at the National Institutes of Health (NIH) in Bethesda, Maryland on March 11-12, 2014. The goals of the workshop were to (1) identify opportunities, challenges, and resource needs for the development and application of genetic simulation models; (2) improve the integration of tools for modeling and analysis of simulated data; and (3) foster collaborations to facilitate development and applications of genetic simulation. During the course of the meeting, the group identified challenges and opportunities for the science of simulation, software and methods development, and collaboration. This paper summarizes key discussions at the meeting, and highlights important challenges and opportunities to advance the field of genetic simulation.

Gene by stress genome-wide interaction analysis and path analysis identify EBF1 as a cardiovascular and metabolic risk gene

We performed gene-environment interaction genome-wide association analysis (G × E GWAS) to identify SNPs whose effects on metabolic traits are modified by chronic psychosocial stress in the Multi-Ethnic Study of Atherosclerosis (MESA). In Whites, the G × E GWAS for hip circumference identified five SNPs within the Early B-cell Factor 1 (EBF1) gene, all of which were in strong linkage disequilibrium. The gene-by-stress interaction (SNP × STRESS) term P-values were genome-wide significant (Ps = 7.14E-09 to 2.33E-08, uncorrected; Ps = 1.99E-07 to 5.18E-07, corrected for genomic control). The SNP-only (without interaction) model P-values (Ps = 0.011-0.022) were not significant at the conventional genome-wide significance level. Further analysis of related phenotypes identified gene-by-stress interaction effects for waist circumference, body mass index (BMI), fasting glucose, type II diabetes status, and common carotid intimal-medial thickness (CCIMT), supporting a proposed model of gene-by-stress interaction that connects cardiovascular disease (CVD) risk factor endophenotypes such as central obesity and increased blood glucose or diabetes to CVD itself. Structural equation path analysis suggested that the path from chronic psychosocial stress to CCIMT via hip circumference and fasting glucose was larger (estimate = 0.26, P = 0.033, 95% CI = 0.02-0.49) in the EBF1 rs4704963 CT/CC genotypes group than the same path in the TT group (estimate = 0.004, P = 0.34, 95% CI = -0.004-0.012). We replicated the association of the EBF1 SNPs and hip circumference in the Framingham Offspring Cohort (gene-by-stress term P-values = 0.007-0.012) as well as identified similar path relationships. This observed and replicated interaction between psychosocial stress and variation in the EBF1 gene may provide a biological hypothesis for the complex relationship between psychosocial stress, central obesity, diabetes, and cardiovascular disease.

SeqSIMLA2: simulating correlated quantitative traits accounting for shared environmental effects in user-specified pedigree structure

Simulation tools that simulate sequence data in unrelated cases and controls or in families with quantitative traits or disease status are important for genetic studies. The simulation tools can be used to evaluate the statistical power for detecting the causal variants when planning a genetic epidemiology study, or to evaluate the statistical properties for new methods. We previously developed SeqSIMLA version 1 (SeqSIMLA1), which simulates family or case-control data with a disease or quantitative trait model. SeqSIMLA1, and several other tools that simulate quantitative traits, do not specifically model the shared environmental effects among relatives on a trait. However, shared environmental effects are commonly observed for some traits in families, such as body mass index. SeqSIMLA1 simulates a fixed three-generation family structure. However, it would be ideal to simulate prespecified pedigree structures for studies involving large pedigrees. Thus, we extended SeqSIMLA1 to create SeqSIMLA2, which can simulate correlated traits and considers the shared environmental effects. SeqSIMLA2 can also simulate prespecified large pedigree structures. There are no restrictions on the number of individuals that can be simulated in a pedigree. We used a blood pressure example to demonstrate that SeqSIMLA2 can simulate realistic correlation structures between the systolic and diastolic blood pressure among relatives. We also showed that SeqSIMLA2 can simulate large pedigrees with large chromosomal regions in a reasonable time frame.

Quality of family history collection with use of a patient facing family history assessment tool

Background

Studies have shown that the quality of family health history (FHH) collection in primary care is inadequate to assess disease risk. To use FHH for risk assessment, collected data must have adequate detail. To address this issue, we developed a patient facing FHH assessment tool, MeTree. In this paper we report the content and quality of the FHH collected using MeTree.

Methods

Design: A hybrid implementation-effectiveness study. Patients were recruited from 2009 to 2012. Setting: Two community primary care clinics in Greensboro, NC. Participants: All non-adopted adult English speaking patients with upcoming appointments were invited to participate. Intervention: Education about and collection of FHH with entry into MeTree. Measures: We report the proportion of pedigrees that were high-quality. High-quality pedigrees are defined as having all the following criteria: (1) three generations of relatives, (2) relatives’ lineage, (3) relatives’ gender, (4) an up-to-date FHH, (5) pertinent negatives noted, (6) age of disease onset in affected relatives, and for deceased relatives, (7) the age and (8) cause of death (Prim Care31:479–495, 2004.).

Results

Enrollment: 1,184. Participant demographics: age range 18-92 (mean 58.8, SD 11.79), 56% male, and 75% white. The median pedigree size was 21 (range 8-71) and the FHH entered into MeTree resulted in a database of 27,406 individuals. FHHs collected by MeTree were found to be high quality in 99.8% (N = 1,182/1,184) as compared to <4% at baseline. An average of 1.9 relatives per pedigree (range 0-50, SD 4.14) had no data reported. For pedigrees where at least one relative has no data (N = 497/1,184), 4.97 relatives per pedigree (range 1-50, SD 5.44) had no data. Talking with family members before using MeTree significantly decreased the proportion of relatives with no data reported (4.98% if you talked to your relative vs. 10.85% if you did not, p-value < 0.001.).

Conclusion

Using MeTree improves the quantity and quality of the FHH data that is collected and talking with relatives prior to the collection of FHH significantly improves the quantity and quality of the data provided. This allows more patients to be accurately risk stratified and offered appropriate preventive care guided by their risk level.

Trial number

NCT01372553

A functional polymorphism in the 5HTR2C gene associated with stress responses also predicts incident cardiovascular events

Previously we have shown that a functional nonsynonymous single nucleotide polymorphism (rs6318) of the 5HTR2C gene located on the X-chromosome is associated with hypothalamic-pituitary-adrenal axis response to a stress recall task, and with endophenotypes associated with cardiovascular disease (CVD). These findings suggest that individuals carrying the rs6318 Ser23 C allele will be at higher risk for CVD compared to Cys23 G allele carriers. The present study examined allelic variation in rs6318 as a predictor of coronary artery disease (CAD) severity and a composite endpoint of all-cause mortality or myocardial infarction (MI) among Caucasian participants consecutively recruited through the cardiac catheterization laboratory at Duke University Hospital (Durham, NC) as part of the CATHGEN biorepository. Study population consisted of 6,126 Caucasian participants (4,036 [65.9%] males and 2,090 [34.1%] females). A total of 1,769 events occurred (1,544 deaths and 225 MIs; median follow-up time =  5.3 years, interquartile range  = 3.3–8.2). Unadjusted Cox time-to-event regression models showed, compared to Cys23 G carriers, males hemizygous for Ser23 C and females homozygous for Ser23C were at increased risk for the composite endpoint of all-cause death or MI: Hazard Ratio (HR)  = 1.47, 95% confidence interval (CI)  = 1.17, 1.84, p  = .0008. Adjusting for age, rs6318 genotype was not related to body mass index, diabetes, hypertension, dyslipidemia, smoking history, number of diseased coronary arteries, or left ventricular ejection fraction in either males or females. After adjustment for these covariates the estimate for the two Ser23 C groups was modestly attenuated, but remained statistically significant: HR  = 1.38, 95% CI = 1.10, 1.73, p = .005. These findings suggest that this functional polymorphism of the 5HTR2C gene is associated with increased risk for CVD mortality and morbidity, but this association is apparently not explained by the association of rs6318 with traditional risk factors or conventional markers of atherosclerotic disease.

Validation of the association between a branched chain amino acid metabolite profile and extremes of coronary artery disease in patients referred for cardiac catheterization

OBJECTIVE

To validate independent associations between branched-chain amino acids (BCAA) and other metabolites with coronary artery disease (CAD).

METHODS

We conducted mass-spectrometry-based profiling of 63 metabolites in fasting plasma from 1983 sequential patients undergoing cardiac catheterization. Significant CAD was defined as CADindex ≥ 32 (at least one vessel with ≥ 95% stenosis; N = 995) and no CAD as CADindex ≤ 23 and no previous cardiac events (N = 610). Individuals (N = 378) with CAD severity between these extremes were excluded. Principal components analysis (PCA) reduced large numbers of correlated metabolites into uncorrelated factors. Association between metabolite factors and significant CAD vs. no CAD was tested using logistic regression; and between metabolite factors and severity of CAD was tested using linear regression.

RESULTS

Of twelve PCA-derived metabolite factors, two were associated with CAD in multivariable models: factor 10, composed of BCAA (adjusted odds ratio, OR, 1.20; 95% CI 1.05-1.35, p = 0.005) and factor 7, composed of short-chain acylcarnitines, which include byproducts of BCAA metabolism (adjusted OR 1.30; 95% CI 1.14-1.48, p = 0.001). After adjustment for glycated albumin (marker of insulin resistance [IR]) both factors 7 (p = 0.0001) and 10 (p = 0.004) remained associated with CAD. Severity of CAD as a continuous variable (including patients with non-obstructive disease) was associated with metabolite factors 2, 3, 6, 7, 8 and 9; only factors 7 and 10 were associated in multivariable models.

CONCLUSIONS

We validated the independent association of metabolites involved in BCAA metabolism with CAD extremes. These metabolites may be reporting on novel mechanisms of CAD pathogenesis that are independent of IR and diabetes.

The genetic basis for survivorship in coronary artery disease

Survivorship is a trait characterized by endurance and virility in the face of hardship. It is largely considered a psychosocial attribute developed during fatal conditions, rather than a biological trait for robustness in the context of complex, age-dependent diseases like coronary artery disease (CAD). The purpose of this paper is to present the novel phenotype, survivorship in CAD as an observed survival advantage concurrent with clinically significant CAD. We present a model for characterizing survivorship in CAD and its relationships with overlapping time- and clinically-related phenotypes. We offer an optimal measurement interval for investigating survivorship in CAD. We hypothesize genetic contributions to this construct and review the literature for evidence of genetic contribution to overlapping phenotypes in support of our hypothesis. We also present preliminary evidence of genetic effects on survival in people with clinically significant CAD from a primary case-control study of symptomatic coronary disease. Identifying gene variants that confer improved survival in the context of clinically appreciable CAD may improve our understanding of cardioprotective mechanisms acting at the gene level and potentially impact patients clinically in the future. Further, characterizing other survival-variant genetic effects may improve signal-to-noise ratio in detecting gene associations for CAD.

Interactions between social/ behavioral factors and ADRB2 genotypes may be associated with health at advanced ages in China

BACKGROUND

Existing literature indicates that ADRB2 gene is associated with health and longevity, but none of previous studies investigated associations of carrying the ADRB2 minor alleles and interactions between ADRB2 genotypes and social/behavioral factors(GxE) with health outcomes at advanced ages. This study intends to fill in this research gap.

METHOD

We conducted an exploratory analysis, using longitudinal survey phenotype/genotype data from 877 oldest-old aged 90+. To estimate association of GxE interactions with health outcome, adjusted for the potential correlation between genotypes and social/behavioral factors and various other potentially confounding factors, we develop and test an innovative three-step procedure which combines logistic regression and structural equation methods.

RESULTS

Interaction between regular exercise and carrying rs1042718 minor allele is significantly and positively associated with good cognitive function; interaction between regular exercise and carrying rs1042718 or rs1042719 minor allele is significantly and positively associated with self-reported good health; and interaction between social-leisure activities and carrying rs1042719 minor allele is significantly and positively associated with self-reported good health. Carrying rs1042718 or rs1042719 minor alleles is significantly and negatively associated with negative emotion, but the ADRB2 SNPs are not significantly associated with cognitive function and self-reported health. Our structural equation analysis found that, adjusted for the confounding effects of correlation of the ADRB2 SNPs with negative emotion, interaction between negative emotion and carrying rs1042718 or rs1042719 minor allele is significantly and negatively associated with cognitive function. The positive association of regular exercise and social-leisure activities with cognitive function and self-reported health, and negative association of negative emotion with cognitive function, were much stronger among carriers of rs1042718 or rs1042719 alleles, compared to the non-carriers.

CONCLUSIONS

The results indicate significant positive associations of interactions between social/behavioral factors and the ADRB2 genotypes with health outcomes of cognitive function and self-reported health, and negative associations of carrying rs1042718 or rs1042719 minor alleles with negative emotion, at advanced ages in China. Our findings are exploratory rather than causal conclusions. This study implies that near-future health promotion programs considering individuals' genetic profiles, with appropriate protection of privacy/confidentiality, would yield increased benefits and reduced costs to the programs and their participants.

Patient and primary care provider experience using a family health history collection, risk stratification, and clinical decision support tool: a type 2 hybrid controlled implementation-effectiveness trial

BACKGROUND

Family health history (FHH) is the single strongest predictor of disease risk and yet is significantly underutilized in primary care. We developed a patient facing FHH collection tool, MeTree, that uses risk stratification to generate clinical decision support for breast cancer, colorectal cancer, ovarian cancer, hereditary cancer syndromes, and thrombosis. Here we present data on the experience of patients and providers after integration of MeTree into 2 primary care practices.

METHODS

This was a Type 2 hybrid controlled implementation-effectiveness study in 3 community-based primary care clinics in Greensboro, NC. All non-adopted adult English speaking patients with upcoming routine appointments were invited. Patients were recruited from December 2009 to the present and followed for one year. Ease of integration of MeTree into clinical practice at the two intervention clinics was evaluated through patient surveys after their appointment and at 3 months post-visit, and physician surveys 3 months after tool integration.

RESULTS

Total enrollment =1,184. Average time to complete MeTree = 27 minutes. Patients found MeTree: easy to use (93%), easy to understand (97%), useful (98%), raised awareness of disease risk (85%), and changed how they think about their health (86%). Of the 26% (N = 311) asking for assistance to complete the tool, age (65 sd 9.4 vs. 57 sd 11.8, p-value < 0.00) and large pedigree size (24.4 sd 9.81 vs. 22.2 sd 8.30, p-value < 0.00) were the only significant factors; 77% of those requiring assistance were over the age of 60. Providers (N = 14) found MeTree: improved their practice (86%), improved their understanding of FHH (64%), made practice easier (79%), and worthy of recommending to their peers (93%).

CONCLUSIONS

Our study shows that MeTree has broad acceptance and support from both patients and providers and can be implemented without disruption to workflow.

Epigenetic regulation of COL15A1 in smooth muscle cell replicative aging and atherosclerosis

Smooth muscle cell (SMC) proliferation is a hallmark of vascular injury and disease. Global hypomethylation occurs during SMC proliferation in culture and in vivo during neointimal formation. Regardless of the programmed or stochastic nature of hypomethylation, identifying these changes is important in understanding vascular disease, as maintenance of a cells' epigenetic profile is essential for maintaining cellular phenotype. Global hypomethylation of proliferating aortic SMCs and concomitant decrease of DNMT1 expression were identified in culture during passage. An epigenome screen identified regions of the genome that were hypomethylated during proliferation and a region containing Collagen, type XV, alpha 1 (COL15A1) was selected by 'genomic convergence' for characterization. COL15A1 transcript and protein levels increased with passage-dependent decreases in DNA methylation and the transcript was sensitive to treatment with 5-Aza-2'-deoxycytidine, suggesting DNA methylation-mediated gene expression. Phenotypically, knockdown of COL15A1 increased SMC migration and decreased proliferation and Col15a1 expression was induced in an atherosclerotic lesion and localized to the atherosclerotic cap. A sequence variant in COL15A1 that is significantly associated with atherosclerosis (rs4142986, P = 0.017, OR = 1.434) was methylated and methylation of the risk allele correlated with decreased gene expression and increased atherosclerosis in human aorta. In summary, hypomethylation of COL15A1 occurs during SMC proliferation and the consequent increased gene expression may impact SMC phenotype and atherosclerosis formation. Hypomethylated genes, such as COL15A1, provide evidence for concomitant epigenetic regulation and genetic susceptibility, and define a class of causal targets that sit at the intersection of genetic and epigenetic predisposition in the etiology of complex disease.

The genomic medicine model: an integrated approach to implementation of family health history in primary care

As an essential tool for risk stratification, family health history (FHH) is a central component of personalized medicine; yet, despite its widespread acceptance among professional societies and its established place in the medical interview, its widespread adoption is hindered by three major barriers: quality of FHH collection, risk stratification capabilities and interpretation of risk stratification for clinical care. To overcome these barriers and bring FHH to the forefront of the personalized medicine effort, we developed the genomic medicine model (GMM) for primary care. The GMM, founded upon the principles of the Health Belief Model, Adult Learning Theory and the implementation sciences, shifts responsibility for FHH onto the patient, uses information technology (MeTree©) for risk stratification and interpretation, and provides education across multiple levels for each stakeholder, freeing up the clinical encounter for discussion around personalized preventive healthcare plans. The GMM has been implemented and optimized as part of an implementation-effectiveness hybrid pilot study for breast/ovarian cancer, colon cancer and thrombosis, and risk for hereditary cancer syndromes in two primary care clinics in NC, USA. This paper describes the conceptual development of the model and key findings relevant for broader uptake and sustainability in the primary care community.

Phenotyping clinical disorders: lessons learned from pelvic organ prolapse

Genetic epidemiology, the study of genetic contributions to risk for disease, is an innovative area in medicine. Although research in this arena has advanced in other disciplines, few genetic epidemiological studies have been conducted in obstetrics and gynecology. It is crucial that we study the genetic susceptibility for issues in women's health because this information will shape the new frontier of personalized medicine. To date, preterm birth may be one of the best examples of genetic susceptibility in obstetrics and gynecology, but many areas are being evaluated including endometriosis, fibroids, polycystic ovarian syndrome, and pelvic floor disorders. An essential component to genetic epidemiological studies is to characterize, or phenotype, the disorder to identify genetic effects. Given the growing importance of genomics and genetic epidemiology, we discuss the importance of accurate phenotyping of clinical disorders and highlight critical considerations and opportunities in phenotyping, using pelvic organ prolapse as a clinical example.

Association between the chromosome 9p21 locus and angiographic coronary artery disease burden: a collaborative meta-analysis

OBJECTIVES

This study sought to ascertain the relationship of 9p21 locus with: 1) angiographic coronary artery disease (CAD) burden; and 2) myocardial infarction (MI) in individuals with underlying CAD.

BACKGROUND

Chromosome 9p21 variants have been robustly associated with coronary heart disease, but questions remain on the mechanism of risk, specifically whether the locus contributes to coronary atheroma burden or plaque instability.

METHODS

We established a collaboration of 21 studies consisting of 33,673 subjects with information on both CAD (clinical or angiographic) and MI status along with 9p21 genotype. Tabular data are provided for each cohort on the presence and burden of angiographic CAD, MI cases with underlying CAD, and the diabetic status of all subjects.

RESULTS

We first confirmed an association between 9p21 and CAD with angiographically defined cases and control subjects (pooled odds ratio [OR]: 1.31, 95% confidence interval [CI]: 1.20 to 1.43). Among subjects with angiographic CAD (n = 20,987), random-effects model identified an association with multivessel CAD, compared with those with single-vessel disease (OR: 1.10, 95% CI: 1.04 to 1.17)/copy of risk allele). Genotypic models showed an OR of 1.15, 95% CI: 1.04 to 1.26 for heterozygous carrier and OR: 1.23, 95% CI: 1.08 to 1.39 for homozygous carrier. Finally, there was no significant association between 9p21 and prevalent MI when both cases (n = 17,791) and control subjects (n = 15,882) had underlying CAD (OR: 0.99, 95% CI: 0.95 to 1.03)/risk allele.

CONCLUSIONS

The 9p21 locus shows convincing association with greater burden of CAD but not with MI in the presence of underlying CAD. This adds further weight to the hypothesis that 9p21 locus primarily mediates an atherosclerotic phenotype.

Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets

Single variant or single gene analyses generally account for only a small proportion of the phenotypic variation in complex traits. Alternatively, gene set or pathway association analyses are playing an increasingly important role in uncovering genetic architectures of complex traits through the identification of systematic genetic interactions. Two dominant paradigms for gene set analyses are association analyses based on SNP genotypes and those based on gene expression profiles. However, gene-disease association can manifest in many ways, such as alterations of gene expression, genotype, and copy number; thus, an integrative approach combining multiple forms of evidence can more accurately and comprehensively capture pathway associations. We have developed a single statistical framework, Gene Set Association Analysis (GSAA), that simultaneously measures genome-wide patterns of genetic variation and gene expression variation to identify sets of genes enriched for differential expression and/or trait-associated genetic markers. Simulation studies illustrate that joint analyses of genomic data increase the power to detect real associations when compared with gene set methods that use only one genomic data type. The analysis of two human diseases, glioblastoma and Crohn's disease, detected abnormalities in previously identified disease-associated pathways, such as pathways related to PI3K signaling, DNA damage response, and the activation of NFKB. In addition, GSAA predicted novel pathway associations, for example, differential genetic and expression characteristics in genes from the ABC transporter family in glioblastoma and from the HLA system in Crohn's disease. These demonstrate that GSAA can help uncover biological pathways underlying human diseases and complex traits.

Protocol for implementation of family health history collection and decision support into primary care using a computerized family health history system

Background

The CDC's Family History Public Health Initiative encourages adoption and increase awareness of family health history. To meet these goals and develop a personalized medicine implementation science research agenda, the Genomedical Connection is using an implementation research (T3 research) framework to develop and integrate a self-administered computerized family history system with built-in decision support into 2 primary care clinics in North Carolina.

Methods/Design

The family health history system collects a three generation family history on 48 conditions and provides decision support (pedigree and tabular family history, provider recommendation report and patient summary report) for 4 pilot conditions: breast cancer, ovarian cancer, colon cancer, and thrombosis. All adult English-speaking, non-adopted, patients scheduled for well-visits are invited to complete the family health system prior to their appointment. Decision support documents are entered into the medical record and available to provider's prior to the appointment. In order to optimize integration, components were piloted by stakeholders prior to and during implementation. Primary outcomes are change in appropriate testing for hereditary thrombophilia and screening for breast cancer, colon cancer, and ovarian cancer one year after study enrollment. Secondary outcomes include implementation measures related to the benefits and burdens of the family health system and its impact on clinic workflow, patients' risk perception, and intention to change health related behaviors. Outcomes are assessed through chart review, patient surveys at baseline and follow-up, and provider surveys. Clinical validity of the decision support is calculated by comparing its recommendations to those made by a genetic counselor reviewing the same pedigree; and clinical utility is demonstrated through reclassification rates and changes in appropriate screening (the primary outcome).

Discussion

This study integrates a computerized family health history system within the context of a routine well-visit appointment to overcome many of the existing barriers to collection and use of family history information by primary care providers. Results of the implementation process, its acceptability to patients and providers, modifications necessary to optimize the system, and impact on clinical care can serve to guide future implementation projects for both family history and other tools of personalized medicine, such as health risk assessments.