Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization.

The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal mendelian long-QT syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals, we identified 35 common variant loci associated with QT interval that collectively explain ∼8-10% of QT-interval variation and highlight the importance of calcium regulation in myocardial repolarization.

Genetic variants associated with angiotensin-converting enzyme inhibitor-associated angioedema.

Objective: The objective of this study was to identify genetic variants associated with angiotensin-converting enzyme (ACE) inhibitor-associated angioedema.

Participants And Methods: We carried out a genome-wide association study in 175 individuals with ACE inhibitor-associated angioedema and 489 ACE inhibitor-exposed controls from Nashville (Tennessee) and Marshfield (Wisconsin). We tested for replication in 19 cases and 57 controls who participated in Ongoing Telmisartan Alone and in Combination with Ramipril Global Endpoint Trial (ONTARGET).

Enhancing the power of genetic association studies through the use of silver standard cases derived from electronic medical records.

The feasibility of using imperfectly phenotyped "silver standard" samples identified from electronic medical record diagnoses is considered in genetic association studies when these samples might be combined with an existing set of samples phenotyped with a gold standard technique. An analytic expression is derived for the power of a chi-square test of independence using either research-quality case/control samples alone, or augmented with silver standard data. The subset of the parameter space where inclusion of silver standard samples increases statistical power is identified.

Genome- and phenome-wide analyses of cardiac conduction identifies markers of arrhythmia risk.

Background: ECG QRS duration, a measure of cardiac intraventricular conduction, varies ≈2-fold in individuals without cardiac disease. Slow conduction may promote re-entrant arrhythmias.

Methods And Results: We performed a genome-wide association study to identify genomic markers of QRS duration in 5272 individuals without cardiac disease selected from electronic medical record algorithms at 5 sites in the Electronic Medical Records and Genomics (eMERGE) network.

Mapping the incidentalome: estimating incidental findings generated through clinical pharmacogenomics testing.

Purpose: Greater clinical validity and economic feasibility are driving the more widespread use of multiplex genetic technologies in routine clinical care, especially for applications in pharmacogenomics. Empirical data on the numbers and types of incidental findings generated through such testing are needed to develop policies and practices related to their clinical use. Of particular importance are disparities in findings relevant to different ancestry groups.

High density GWAS for LDL cholesterol in African Americans using electronic medical records reveals a strong protective variant in APOE.

Only one low-density lipoprotein cholesterol (LDL-C) genome-wide association study (GWAS) has been previously reported in -African Americans. We performed a GWAS of LDL-C in African Americans using data extracted from electronic medical records (EMR) in the eMERGE network. African Americans were genotyped on the Illumina 1M chip.

Predicting warfarin dosage in European-Americans and African-Americans using DNA samples linked to an electronic health record.

Aim: Warfarin pharmacogenomic algorithms reduce dosing error, but perform poorly in non-European-Americans. Electronic health record (EHR) systems linked to biobanks may allow for pharmacogenomic analysis, but they have not yet been used for this purpose.

Patients & Methods: We used BioVU, the Vanderbilt EHR-linked DNA repository, to identify European-Americans (n = 1022) and African-Americans (n = 145) on stable warfarin therapy and evaluated the effect of 15 pharmacogenetic variants on stable warfarin dose.

Pitfalls of merging GWAS data: lessons learned in the eMERGE network and quality control procedures to maintain high data quality.

Genome-wide association studies (GWAS) are a useful approach in the study of the genetic components of complex phenotypes. Aside from large cohorts, GWAS have generally been limited to the study of one or a few diseases or traits. The emergence of biobanks linked to electronic medical records (EMRs) allows the efficient reuse of genetic data to yield meaningful genotype-phenotype associations for multiple phenotypes or traits.

Interrogating the complex role of chromosome 16p13.13 in multiple sclerosis susceptibility: independent genetic signals in the CIITA-CLEC16A-SOCS1 gene complex.

Multiple sclerosis (MS) is a neurodegenerative, autoimmune disease of the central nervous system, and numerous studies have shown that MS has a strong genetic component. Independent studies to identify MS-associated genes have often indicated multiple signals in physically close genomic regions, although by their proximity it is not always clear if these data indicate redundant or truly independent genetic signals. Recently, three MS study samples were genotyped in parallel using an Illumina Custom BeadChip.

Quality control procedures for genome-wide association studies.

Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of complex disease. Regardless of context, the practical utility of this information will ultimately depend upon the quality of the original data. Quality control (QC) procedures for GWAS are computationally intensive, operationally challenging, and constantly evolving.

Evidence for CRHR1 in multiple sclerosis using supervised machine learning and meta-analysis in 12,566 individuals.

The primary genetic risk factor in multiple sclerosis (MS) is the HLA-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has yet to be elucidated. Several lines of evidence support a role for neuroendocrine system involvement in autoimmunity which may, in part, be genetically determined. Here, we comprehensively investigated variation within eight candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS.

Variation within DNA repair pathway genes and risk of multiple sclerosis.

Multiple sclerosis (MS) is a complex autoimmune disease of the central nervous system with a prominent genetic component. The primary genetic risk factor is the human leukocyte antigen (HLA)-DRB1*1501 allele; however, much of the remaining genetic contribution to MS has not been elucidated. The authors investigated the relation between variation in DNA repair pathway genes and risk of MS.

CIITA variation in the presence of HLA-DRB1*1501 increases risk for multiple sclerosis.

The MHC class II transactivator gene (CIITA) is an important transcription factor regulating gene required for HLA class II MHC-restricted antigen presentation. Association with HLA class II variation, particularly HLA-DRB1*1501, has been well-established for multiple sclerosis (MS). In addition, the -168A/G CIITA promoter variant (rs3087456) has been reported to be associated with MS.

Genetic variation in the IL7RA/IL7 pathway increases multiple sclerosis susceptibility.

Multiple sclerosis (MS) is characterized as an autoimmune demyelinating disease. Numerous family studies have confirmed a strong genetic component underlying its etiology. After several decades of frustrating research, the advent and application of affordable genotyping of dense SNP maps in large data sets has ushered in a new era in which rapid progress is being made in our understanding of the genetics underlying many complex traits.