Penetrance of Hemochromatosis in HFE Genotypes Resulting in p.Cys282Tyr and p.[Cys282Tyr];[His63Asp] in the eMERGE Network.

Hereditary hemochromatosis (HH) is a common autosomal-recessive disorder associated with pathogenic HFE variants, most commonly those resulting in p.Cys282Tyr and p.His63Asp. Recommendations on returning incidental findings of HFE variants in individuals undergoing genome-scale sequencing should be informed by penetrance estimates of HH in unselected samples.

Evaluation of the F2R IVS-14A/T PAR1 polymorphism with subsequent cardiovascular events and bleeding in patients who have undergone percutaneous coronary intervention.

Abnormal platelet reactivity is associated with recurrent ischemia and bleeding following percutaneous coronary intervention (PCI). Protease-activated receptor-1 (PAR1), encoded by F2R, is a high affinity thrombin receptor on platelets and the target of the antiplatelet drug vorapaxar. The intronic single nucleotide polymorphism F2R IVS-14 A/T affects PAR1 receptor density and function. We hypothesized that carriers of the T allele, who have been shown to have decreased platelet reactivity, would be at lower risk for thrombotic events, but higher risk for bleeding following PCI.

Genetics of glucocorticoid-associated osteonecrosis in children with acute lymphoblastic leukemia.

Glucocorticoids are important therapy for acute lymphoblastic leukemia (ALL) and their major adverse effect is osteonecrosis. Our goal was to identify genetic and nongenetic risk factors for osteonecrosis. We performed a genome-wide association study of single nucleotide polymorphisms (SNPs) in a discovery cohort comprising 2285 children with ALL, treated on the Children's Oncology Group AALL0232 protocol (NCT00075725), adjusting for covariates.

A prognostic model based on readily available clinical data enriched a preemptive pharmacogenetic testing program.

We describe the development, implementation, and evaluation of a model to preemptively select patients for genotyping based on medication exposure risk.

Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record.

Large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations. However, the extent to which such resources are capable of delivering on this promise is unknown. We studied whether an EMR-linked DNA biorepository can be used to detect known genotype-phenotype associations for five diseases.

Assessing the accuracy of observer-reported ancestry in a biorepository linked to electronic medical records.

The Vanderbilt DNA Databank (BioVU) is a biorepository that currently contains >80,000 DNA samples linked to electronic medical records. Although BioVU is a valuable source of samples and phenotypes for genetic association studies, it is unclear whether the administratively assigned race/ethnicity in BioVU can accurately describe and be used as a proxy for genetic ancestry.

Identification of genomic predictors of atrioventricular conduction: using electronic medical records as a tool for genome science.

Recent genome-wide association studies in which selected community populations are used have identified genomic signals in SCN10A influencing PR duration. The extent to which this can be demonstrated in cohorts derived from electronic medical records is unknown.

The eMERGE Network: a consortium of biorepositories linked to electronic medical records data for conducting genomic studies.

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.

Electronic medical records for genetic research: results of the eMERGE consortium.

Clinical data in electronic medical records (EMRs) are a potential source of longitudinal clinical data for research. The Electronic Medical Records and Genomics Network (eMERGE) investigates whether data captured through routine clinical care using EMRs can identify disease phenotypes with sufficient positive and negative predictive values for use in genome-wide association studies (GWAS). Using data from five different sets of EMRs, we have identified five disease phenotypes with positive predictive values of 73 to 98% and negative predictive values of 98 to 100%.

Knowledge-driven multi-locus analysis reveals gene-gene interactions influencing HDL cholesterol level in two independent EMR-linked biobanks.

Genome-wide association studies (GWAS) are routinely being used to examine the genetic contribution to complex human traits, such as high-density lipoprotein cholesterol (HDL-C). Although HDL-C levels are highly heritable (h(2)∼0.7), the genetic determinants identified through GWAS contribute to a small fraction of the variance in this trait. Reasons for this discrepancy may include rare variants, structural variants, gene-environment (GxE) interactions, and gene-gene (GxG) interactions.

RSS: