Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10−6 (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort (n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.

Clonal mosaicism for large chromosomal anomalies (duplications, deletions and uniparental disomy) was detected using SNP microarray data from over 50,000 subjects recruited for genome-wide association studies. This detection method requires a relatively high frequency of cells (>5–10%) with the same abnormal karyotype (presumably of clonal origin) in the presence of normal cells. The frequency of detectable clonal mosaicism in peripheral blood is low (<0.5%) from birth until 50 years of age, after which it rises rapidly to 2–3% in the elderly. Many of the mosaic anomalies are characteristic of those found in hematological cancers and identify common deleted regions that pinpoint the locations of genes previously associated with hematological cancers. Although only 3% of subjects with detectable clonal mosaicism had any record of hematological cancer prior to DNA sampling, those without a prior diagnosis have an estimated 10-fold higher risk of a subsequent hematological cancer (95% confidence interval = 6–18).

The Electronic Medical Records and Genomics (eMERGE) Network is a National Human Genome Research Institute (NHGRI)-funded consortium engaged in the development of methods and best-practices for utilizing the Electronic Medical Record (EMR) as a tool for genomic research. Now in its sixth year, its second funding cycle and comprising nine research groups and a coordinating center, the network has played a major role in validating the concept that clinical data derived from EMRs can be used successfully for genomic research. Current work is advancing knowledge in multiple disciplines at the intersection of genomics and healthcare informatics, particularly electronic phenotyping, genome-wide association studies, genomic medicine implementation and the ethical and regulatory issues associated with genomics research and returning results to study participants. Here we describe the evolution, accomplishments, opportunities and challenges of the network since its inception as a five-group consortium focused on genotype-phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting towards implementation of genomic medicine.

Background-Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. Methods and Results-We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("eventreplication" group; nϭ63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial Pϭ0.002, replication Pϭ0.01), and 1 comprising urea cycle metabolites (factor 9, initial Pϭ0.0004, replication Pϭ0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; Pϭ0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; Pϭ0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; Pϭ0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; Pϭ0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; Pϭ0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; Pϭ0.01). Conclusions-Metabolite profiles are associated with CAD and subsequent cardiovascular events.(Circ Cardiovasc Genet. 2010;3:207-214.)Key Words: metabolism Ⅲ risk factors Ⅲ coronary artery disease C oronary artery disease (CAD) is the leading cause of death in industrialized countries. Many accepted risk factors for CAD are metabolic. However, there remains an incomplete mechanistic understanding of CAD risk and equally important, a need to refine our ability to identify individuals at highest risk of cardiovascular events. Given the complex nature of CAD, evaluation with more comprehensive tools may improve risk stratification and enhance our understanding of the disease process. Metabolomics, the study of small-molecule metabolites, may be particularly useful for the diagnosis of human disease. Studies have demonstrated heritability of metabolites in mice, 1 and we have shown that metabolite profiles are heritable in human families with early-onset CAD, 2 suggesting that the known heritability of CAD may be mediated at least in part through metabolic components measurable in peripheral blood. Clinical Perspective on p 214In this study, we performed quantitative profiling of 69 metabolites, including acylcarnitine species (byproducts of mitochondrial fatty aci...