The eMERGE (electronic MEdical Records and GEnomics) Network is an NHGRI-supported consortium of five institutions to explore the utility of DNA repositories coupled to Electronic Medical Record ...(EMR) systems for advancing discovery in genome science. eMERGE also includes a special emphasis on the ethical, legal and social issues related to these endeavors.
The five sites are supported by an Administrative Coordinating Center. Setting of network goals is initiated by working groups: (1) Genomics, (2) Informatics, and (3) Consent & Community Consultation, which also includes active participation by investigators outside the eMERGE funded sites, and (4) Return of Results Oversight Committee. The Steering Committee, comprised of site PIs and representatives and NHGRI staff, meet three times per year, once per year with the External Scientific Panel.
The primary site-specific phenotypes for which samples have undergone genome-wide association study (GWAS) genotyping are cataract and HDL, dementia, electrocardiographic QRS duration, peripheral arterial disease, and type 2 diabetes. A GWAS is also being undertaken for resistant hypertension in ≈ 2,000 additional samples identified across the network sites, to be added to data available for samples already genotyped. Funded by ARRA supplements, secondary phenotypes have been added at all sites to leverage the genotyping data, and hypothyroidism is being analyzed as a cross-network phenotype. Results are being posted in dbGaP. Other key eMERGE activities include evaluation of the issues associated with cross-site deployment of common algorithms to identify cases and controls in EMRs, data privacy of genomic and clinically-derived data, developing approaches for large-scale meta-analysis of GWAS data across five sites, and a community consultation and consent initiative at each site.
Plans are underway to expand the network in diversity of populations and incorporation of GWAS findings into clinical care.
By combining advanced clinical informatics, genome science, and community consultation, eMERGE represents a first step in the development of data-driven approaches to incorporate genomic information into routine healthcare delivery.
To inform the study and regulation of emerging tobacco products, we sought to identify sensitive biomarkers of tobacco-induced subclinical cardiovascular damage by testing the cross-sectional ...associations of smoking with 17 biomarkers of inflammation in 2,702 GENOA study participants belonging to sibships ascertained on the basis of hypertension. Cigarette smoking was assessed by status, intensity (number of cigarettes per day), burden (pack-years of smoking), and time since quitting. We modeled biomarkers as geometric mean (GM) ratios using generalized estimating equations (GEE). The mean age of participants was 61 ±10 years; 64.5% were women and 54.4% African American. The prevalence of smoking was 12.2%. After adjusting for potential confounders, 6 of 17 biomarkers were significantly higher among current smokers at a Bonferroni adjusted p-value threshold (p<0.003). High sensitivity C-reactive protein was the most elevated biomarker among current smokers when compared to never smokers GM ratio = 1.39 (95% CI: 1.23, 1.57); p <0.001. Among former smokers, each pack-year of cigarettes smoked was associated with a 0.4% higher serum level of hsCRP GM ratio = 1.004 (95% CI: 1.001, 1.006); p = 0.002 and each 5-year lapsed since quitting was associated with a 4% lower serum level of hsCRP GM ratio = 0.96 (95% CI: 0.93, 0.99); p = 0.006. However, we found no significant association of smoking intensity or burden with biomarkers of inflammation among current smokers. HsCRP appears to be the most sensitive biomarker of inflammation associated with cigarette smoking of those investigated, and could be a useful biomarker of smoking-related injury for the study and regulation of emerging tobacco products.
Objectives This study sought to assess sex differences in ventricular-arterial interactions. Background Heart failure with preserved ejection fraction is more prevalent in women than in men, but the ...basis for this difference remains unclear. Methods Echocardiography and arterial tonometry were performed to quantify arterial and ventricular stiffening and interaction in 461 participants without heart failure (189 men, age 67 ± 9 years; 272 women, age 65 ± 10 years). Aortic characteristic impedance (Zc ), total arterial compliance (pulsatile load), and systemic vascular resistance index (steady load) were compared between men and women, and sex-specific multivariable regression analyses were performed to assess associations of these arterial parameters with diastolic dysfunction and ventricular-arterial coupling (effective arterial elastance/left ventricular end-systolic elastance Ea/Ees) after adjustment for potential confounders. Results Zc was higher and total arterial compliance was lower in women, whereas systemic vascular resistance index was similar between sexes. In women but not men, higher log Zc was associated with mitral inflow E/A ratio (β ± SE: −0.17 ± 0.07), diastolic dysfunction (odds ratio: 7.8; 95% confidence interval: 2.0 to 30.2) and Ea/Ees (β ± SE: 0.13 ± 0.04) (p ≤ 0.01 for all). Similarly, total arterial compliance was associated with E/A ratio (β ± SE: 0.12 ± 0.04), diastolic dysfunction (odds ratio: 0.33; 95% confidence interval: 0.12 to 0.89), and Ea/Ees (β ± SE: −0.09 ± 0.03) in women only (p ≤ 0.03 for all). Systemic vascular resistance index was not associated with diastolic dysfunction or Ea/Ees. Conclusions Proximal aortic stiffness (Zc ) is greater in women than men, and women may be more susceptible to the deleterious effects of greater pulsatile and early arterial load on diastolic function and ventricular-arterial interaction. This may contribute to the greater risk of heart failure with preserved ejection fraction in women.
Many modern human genomes retain DNA inherited from interbreeding with archaic hominins, such as Neandertals, yet the influence of this admixture on human traits is largely unknown. We analyzed the ...contribution of common Neandertal variants to over 1000 electronic health record (EHR)–derived phenotypes in ~28,000 adults of European ancestry. We discovered and replicated associations of Neandertal alleles with neurological, psychiatric, immunological, and dermatological phenotypes. Neandertal alleles together explained a significant fraction of the variation in risk for depression and skin lesions resulting from sun exposure (actinic keratosis), and individual Neandertal alleles were significantly associated with specific human phenotypes, including hypercoagulation and tobacco use. Our results establish that archaic admixture influences disease risk in modern humans, provide hypotheses about the effects of hundreds of Neandertal haplotypes, and demonstrate the utility of EHR data in evolutionary analyses.
The measurement of multiple protein biomarkers may refine risk stratification in clinical settings. This concept has stimulated development of multiplexed immunoassay platforms that provide multiple, ...parallel protein measurements on the same specimen.
We provide an overview of antibody-based multiplexed immunoassay platforms and discuss technical and operational challenges. Multiplexed immunoassays use traditional immunoassay principles in which high-affinity capture ligands are immobilized in parallel arrays in either planar format or on microspheres in suspension. Development of multiplexed immunoassays requires rigorous validation of assay configuration and analytical performance to minimize assay imprecision and inaccuracy. Challenges associated with multiplex configuration include selection and immobilization of capture ligands, calibration, interference between antibodies and proteins and assay diluents, and compatibility of assay limits of quantification. We discuss potential solutions to these challenges. Criteria for assessing analytical multiplex assay performance include the range of linearity, analytical specificity, recovery, and comparison to a quality reference method. Quality control materials are not well developed for multiplexed protein immunoassays, and algorithms for interpreting multiplex quality control data are needed.
Technical and operational challenges have hindered implementation of multiplexed assays in clinical settings. Formal procedures that guide multiplex assay configuration, analytical validation, and quality control are needed before broad application of multiplexed arrays can occur in the in vitro diagnostic market.
The Electronic Medical Record (EMR) is a potential source for high throughput phenotyping to conduct genome-wide association studies (GWAS), including those of medically relevant quantitative traits. ...We describe use of the Mayo Clinic EMR to conduct a GWAS of red blood cell (RBC) traits in a cohort of patients with peripheral arterial disease (PAD) and controls without PAD.
Results for hemoglobin level, hematocrit, RBC count, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration were extracted from the EMR from January 1994 to September 2009. Out of 35,159 RBC trait values in 3,411 patients, we excluded 12,864 values in 1,165 patients that had been measured during hospitalization or in the setting of hematological disease, malignancy, or use of drugs that affect RBC traits, leaving a final genotyped sample of 3,012, 80% of whom had ≥2 measurements. The median of each RBC trait was used in the genetic analyses, which were conducted using an additive model that adjusted for age, sex, and PAD status. We identified four genomic loci that were associated (P<5 × 10(-8)) with one or more of the RBC traits (HBLS1/MYB on 6q23.3, TMPRSS6 on 22q12.3, HFE on 6p22.1, and SLC17A1 on 6p22.2). Three of these loci (HBLS1/MYB, TMPRSS6, and HFE) had been identified in recent GWAS and the allele frequencies, effect sizes, and the directions of effects of the replicated SNPs were similar to the prior studies.
Our results demonstrate feasibility of using the EMR to conduct high throughput genomic studies of medically relevant quantitative traits.
Polygenic scores (PGS) for coronary heart disease (CHD) are constructed using GWAS summary statistics for CHD. However, pleiotropy is pervasive in biology and disease-associated variants often share ...etiologic pathways with multiple traits. Therefore, incorporating GWAS summary statistics of additional traits could improve the performance of PGS for CHD. Using lasso regression models, we developed two multi-PGS for CHD: 1) multiPGS
, utilizing GWAS summary statistics for CHD, its risk factors, and other ASCVD as training data and the UK Biobank for tuning, and 2) extendedPGS
, using existing PGS for a broader range of traits in the PGS Catalog as training data and the Atherosclerosis Risk in Communities Study (ARIC) cohort for tuning. We evaluated the performance of multiPGS
and extendedPGS
in the Mayo Clinic Biobank, an independent cohort of 43,578 adults of European ancestry which included 4,479 CHD cases and 39,099 controls. In the Mayo Clinic Biobank, a 1 SD increase in multiPGS
and extendedPGS
was associated with a 1.66-fold (95% CI: 1.60-1.71) and 1.70-fold (95% CI: 1.64-1.76) increased odds of CHD, respectively, in models that included age, sex, and 10 PCs, whereas an already published PGS for CHD (CHD_PRSCS) increased the odds by 1.50 (95% CI: 1.45-1.56). In the highest deciles of extendedPGS
, multiPGS
, and CHD_PRSCS, 18.4%, 17.5%, and 16.3% of patients had CHD, respectively.
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