Yuki Bradford

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. Here we enumerate some of the challenges in QC of GWAS data and describe the approaches that the electronic MEdical Records and Genomics (eMERGE) network is using for quality assurance in GWAS data, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of GWAS data, including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We propose best practices and discuss areas of ongoing and future research. Curr. Protoc. Hum. Genet. 68:1.19.1‐1.19.18

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. The most significant loci were evaluated within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium QRS genome-wide association study meta-analysis. Twenty-three single-nucleotide polymorphisms in 5 loci, previously described by CHARGE, were replicated in the eMERGE samples; 18 single-nucleotide polymorphisms were in the chromosome 3 SCN5A and SCN10A loci, where the most significant single-nucleotide polymorphisms were rs1805126 in SCN5A with P=1.2×10−8 (eMERGE) and P=2.5×10−20 (CHARGE) and rs6795970 in SCN10A with P=6×10−6 (eMERGE) and P=5×10−27 (CHARGE). The other loci were in NFIA, near CDKN1A, and near C6orf204. We then performed phenome-wide association studies on variants in these 5 loci in 13859 European Americans to search for diagnoses associated with these markers. Phenome-wide association study identified atrial fibrillation and cardiac arrhythmias as the most common associated diagnoses with SCN10A and SCN5A variants. SCN10A variants were also associated with subsequent development of atrial fibrillation and arrhythmia in the original 5272 “heart-healthy” study population. Conclusions— We conclude that DNA biobanks coupled to electronic medical records not only provide a platform for genome-wide association study but also may allow broad interrogation of the longitudinal incidence of disease associated with genetic variants. The phenome-wide association study approach implicated sodium channel variants modulating QRS duration in subjects without cardiac disease as predictors of subsequent arrhythmias.

A Large Candidate Gene Survey Identifies the KCNE1 D85N Polymorphism as a Possible Modulator of Drug-Induced Torsades de Pointes

Background— Drug-induced long-QT syndrome (diLQTS) is an adverse drug effect that has an important impact on drug use, development, and regulation. We tested the hypothesis that common variants in key genes controlling cardiac electric properties modify the risk of diLQTS. Methods and Results— In a case-control setting, we included 176 patients of European descent from North America and Europe with diLQTS, defined as documented torsades de pointes during treatment with a QT-prolonging drug. Control samples were obtained from 207 patients of European ancestry who displayed <50 ms QT lengthening during initiation of therapy with a QT-prolonging drug and 837 control subjects from the population-based KORA study. Subjects were successfully genotyped at 1424 single-nucleotide polymorphisms (SNPs) in 18 candidate genes including 1386 SNPs tagging common haplotype blocks and 38 nonsynonymous ion channel gene SNPs. For validation, we used a set of cases (n=57) and population-based control subjects of European descent. The SNP KCNE1 D85N (rs1805128), known to modulate an important potassium current in the heart, predicted diLQTS with an odds ratio of 9.0 (95% confidence interval, 3.5–22.9). The variant allele was present in 8.6% of cases, 2.9% of drug-exposed control subjects, and 1.8% of population control subjects. In the validation cohort, the variant allele was present in 3.5% of cases and in 1.4% of control subjects. Conclusions— This high-density candidate SNP approach identified a key potassium channel susceptibility allele that may be associated with the rare adverse drug reaction torsades de pointes.

A second-generation genomic screen for multiple sclerosis

Multiple sclerosis (MS) is a debilitating neuroimmunological and neurodegenerative disorder. Despite substantial evidence for polygenic inheritance of the disease, the major histocompatibility complex is the only region that clearly and consistently demonstrates linkage and association in MS studies. The goal of this study was to identify additional chromosomal regions that harbor susceptibility genes for MS. With a panel of 390 microsatellite markers genotyped in 245 U.S. and French multiplex families (456 affected relative pairs), this is the largest genomic screen for MS conducted to date. Four regions met both of our primary criteria for further interest (heterogeneity LOD [HLOD] and Z scores >2.0): 1q (HLOD=2.17; Z=3.38), 6p (HLOD=4.21; Z=2.26), 9q (HLOD; Z=2.71), and 16p (HLOD=2.64; Z=2.05). Two additional regions met only the Z score criterion: 3q (Z=2.39) and 5q (Z=2.17). Further examination of the data by country (United States vs. France) identified one additional region demonstrating suggestive linkage in the U.S. subset (18p [HLOD=2.39]) and two additional regions generating suggestive linkage in the French subset (1p [HLOD=2.08] and 22q [HLOD=2.06]). Examination of the data by human leukocyte antigen (HLA)-DR2 stratification identified four additional regions demonstrating suggestive linkage: 2q (HLOD=3.09 in the U.S. DR2- families), 6q (HLOD=3.10 in the French DR2- families), 13q (HLOD=2.32 in all DR2+ families and HLOD=2.17 in the U.S. DR2+ families), and 16q (HLOD=2.32 in all DR2+ families and HLOD=2.13 in the U.S. DR2+ families). These data suggest several regions that warrant further investigation in the search for MS susceptibility genes.

Examination of NRCAM , LRRN3 , KIAA0716, and LAMB1 as autism candidate genes

BackgroundA substantial body of research supports a genetic involvement in autism. Furthermore, results from various genomic screens implicate a region on chromosome 7q31 as harboring an autism susceptibility variant. We previously narrowed this 34 cM region to a 3 cM critical region (located between D7S496 and D7S2418) using the Collaborative Linkage Study of Autism (CLSA) chromosome 7 linked families. This interval encompasses about 4.5 Mb of genomic DNA and encodes over fifty known and predicted genes. Four candidate genes (NRCAM, LRRN3, KIAA0716, and LAMB1) in this region were chosen for examination based on their proximity to the marker most consistently cosegregating with autism in these families (D7S1817), their tissue expression patterns, and likely biological relevance to autism.MethodsThirty-six intronic and exonic single nucleotide polymorphisms (SNPs) and one microsatellite marker within and around these four candidate genes were genotyped in 30 chromosome 7q31 linked families. Multiple SNPs were used to provide as complete coverage as possible since linkage disequilibrium can vary dramatically across even very short distances within a gene. Analyses of these data used the Pedigree Disequilibrium Test for single markers and a multilocus likelihood ratio test.ResultsAs expected, linkage disequilibrium occurred within each of these genes but we did not observe significant LD across genes. None of the polymorphisms in NRCAM, LRRN3, or KIAA0716 gave p < 0.05 suggesting that none of these genes is associated with autism susceptibility in this subset of chromosome 7-linked families. However, with LAMB1, the allelic association analysis revealed suggestive evidence for a positive association, including one individual SNP (p = 0.02) and three separate two-SNP haplotypes across the gene (p = 0.007, 0.012, and 0.012).ConclusionsNRCAM, LRRN3, KIAA0716 are unlikely to be involved in autism. There is some evidence that variation in or near the LAMB1 gene may be involved in autism.

Familial mesial temporal lobe epilepsy maps to chromosome 4q13.2-q21.3

Purpose: To report results of linkage analysis in a large family with autosomal dominant (AD) familial mesial temporal lobe epilepsy (FMTLE). Background: Although FMTLE is a heterogeneous syndrome, one important subgroup is characterized by a relatively benign course, absence of antecedent febrile seizures, and absence of hippocampal sclerosis. These patients have predominantly simple partial seizures (SPS) and infrequent complex partial seizures (CPS), and intense and frequent déjà vu phenomenon may be the only manifestation of this epilepsy syndrome. No linkage has been described in this form of FMTLE. Methods: We identified a four-generation kindred with several affected members meeting criteria for FMTLE and enrolled 21 individuals who gave informed consent. Every individual was personally interviewed and examined; EEG and MRI studies were performed on three affected subjects. DNA was extracted from every enrolled individual. We performed a genome-wide search using an 8 cM panel and fine mapping was performed in the regions with a multipoint lod score >1. We sequenced the highest priority candidate genes. Results: Inheritance was consistent with AD mode with reduced penetrance. Eleven individuals were classified as affected with FMTLE and we also identified two living asymptomatic individuals who had affected offspring. Seizure semiologies included predominantly SPS with déjà vu feeling, infrequent CPS, and rare secondarily generalized tonic-clonic seizures. No structural abnormalities, including hippocampal sclerosis, were detected on MRI performed on three individuals. Genetic analysis detected a group of markers with lod score >3 on chromosome 4q13.2–q21.3 spanning a 7 cM region. No ion channel genes are predicted to be localized within this locus. We sequenced all coding exons of sodium bicarbonate cotransporter (SLC4A) gene, which plays an important role in tissue excitability, and cyclin I (CCNI), because of its role in the cell migration and possibility of subtle cortical abnormalities. No disease-causing mutations were identified in these genes. Conclusion: We report identification of a genetic locus for familial mesial temporal lobe epilepsy. The identification of a disease-causing gene will contribute to our understanding of the pathogenesis of temporal lobe epilepsies.

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. Phase I of the electronic MEdical Records and GEnomics (eMERGE‐I) Network is a National Human Genome Research Institute‐supported consortium composed of five sites to perform various genetic association studies using DNA repositories and EMR systems. Each eMERGE site has developed EMR‐based algorithms to comprise a core set of 14 phenotypes for extraction of study samples from each sites DNA repository. Each eMERGE site selected samples for a specific phenotype, and these samples were genotyped at either the Broad Institute or at the Center for Inherited Disease Research using the Illumina Infinium BeadChip technology. In all, approximately 17,000 samples from across the five sites were genotyped. A unified quality control (QC) pipeline was developed by the eMERGE Genomics Working Group and used to ensure thorough cleaning of the data. This process includes examination of sample and marker quality and various batch effects. Upon completion of the genotyping and QC analyses for each sites primary study, eMERGE Coordinating Center merged the datasets from all five sites. This larger merged dataset reentered the established eMERGE QC pipeline. Based on lessons learned during the process, additional analyses and QC checkpoints were added to the pipeline to ensure proper merging. Here, we explore the challenges associated with combining datasets from different genotyping centers and describe the expansion to eMERGE QC pipeline for merged datasets. These additional steps will be useful as the eMERGE project expands to include additional sites in eMERGE‐II, and also serve as a starting point for investigators merging multiple genotype datasets accessible through the National Center for Biotechnology Information in the database of Genotypes and Phenotypes. Our experience demonstrates that merging multiple datasets after additional QC can be an efficient use of genotype data despite new challenges that appear in the process. Genet. Epidemiol. 35:887–898, 2011.

Imputation and quality control steps for combining multiple genome-wide datasets

The electronic MEdical Records and GEnomics (eMERGE) network brings together DNA biobanks linked to electronic health records (EHRs) from multiple institutions. Approximately 51,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R2 (estimated correlation between the imputed and true genotypes), and the relationship between allelic R2 and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2) were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.

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). Results There were no genome-wide significant associations of any single-nucleotide polymorphism (SNP) with angioedema. Sixteen SNPs in African Americans and 41 SNPs in European Americans were associated moderately with angioedema (P<10–4) and evaluated for association in ONTARGET. The T allele of rs500766 in PRKCQ was associated with a reduced risk, whereas the G allele of rs2724635 in ETV6 was associated with an increased risk of ACE inhibitor-associated angioedema in the Nashville/Marshfield sample and ONTARGET. In a candidate gene analysis, rs989692 in the gene encoding neprilysin (MME), an enzyme that degrades bradykinin and substance P, was significantly associated with angioedema in ONTARGET and Nashville/Marshfield African Americans. Conclusion Unlike other serious adverse drug effects, ACE inhibitor-associated angioedema is not associated with a variant with a large effect size. Variants in MME and genes involved in immune regulation may be associated with ACE inhibitor-associated angioedema.

Identification of a novel locus for febrile seizures and epilepsy on chromosome 21q22.

Summary:  Purpose: To report results of linkage analysis in a large family with autosomal dominant (AD) febrile seizures (FS) and epilepsy.