Familial aggregation of atrial fibrillation in Iceland

To access publisher full text version of this article. Please click on the hyperlink in Additional Links fieldAIMS: To examine the heritability of atrial fibrillation (AF) in Icelanders, utilizing a nationwide genealogy database and population-based data on AF. AF is a disorder with a high prevalence, which has been known to cluster in families, but the heritability of the common form has not been well defined. METHODS AND RESULTS: The study population included 5269 patients diagnosed since 1987 and age-sex-matched controls randomly selected from the genealogy database. Kinship coefficients (KC), expressed as genealogical index of familiality (GIF = average KC x 100,000), were calculated before and after exclusion of relatives separated by one to five meiotic events. Risk ratios (RR) were calculated for first- to fifth-degree relatives. The average pairwise GIF among patients with AF was 15.9 (mean GIF for controls 13.9, 95%CI = 13.3, 14.4); this declined to 15.4 (mean GIF for controls 13.6, 95%CI = 13.1, 14.2) after exclusion of relatives separated by one meiosis and to 13.7 (mean GIF for controls 12.6, 95%CI = 12.1, 13.2), 12.7 (mean GIF for controls 11.9, 95%CI = 11.4, 12.4), and 11.3 (mean GIF for controls 10.6, 95%CI = 10.1, 11.1) after exclusion of relatives within two, three, and four meioses, respectively (all P<0.00001). RRs among relative pairs also declined incrementally, from 1.77 in first-degree relatives to 1.36, 1.18, 1.10, and 1.05 in second- through fifth-degree relatives (all P<0.001), consistent with the declining proportion of alleles shared identically by descent. When the analysis was limited to subjects diagnosed with AF before the age of 60, first-degree relatives of the AF cases were nearly five times more likely to have AF than the general population. CONCLUSION: AF shows strong evidence of heritability among unselected patients in Iceland, suggesting that there may be undiscovered genetic variants underlying the risk of the common form of AF

Increased left ventricular mass is a risk factor for the development of a depressed left ventricular ejection fraction within five years The Cardiovascular Health Study

AbstractObjectivesOur aim in this study was to determine whether increased left ventricular mass (LVM) is a risk factor for the development of a reduced left ventricular ejection fraction (LVEF).BackgroundPrior studies have shown that increased LVM is a risk factor for heart failure but not whether it is a risk factor for a low LVEF.MethodsAs part of the Cardiovascular Health Study, a prospective population-based longitudinal study, we performed echocardiograms upon participant enrollment and again at follow-up of 4.9 ± 0.14 years. In the present analysis, we identified 3,042 participants who had at baseline a normal LVEF and an assessment of LVM (either by electrocardiogram or echocardiogram), and at follow-up a measurable LVEF. The frequency of the development of a qualitatively depressed LVEF on two-dimensional echocardiography, corresponding approximately to an LVEF <55%, was analyzed by quartiles of baseline LVM. Multivariable regression determined whether LVM was independently associated with the development of depressed LVEF.ResultsBaseline quartile of echocardiographic LVM indexed to body surface area was associated with development of a depressed LVEF (4.8% in quartile 1, 4.4% in quartile 2, 7.5% in quartile 3, and 14.1% in quartile 4 [p < 0.001]). A similar relationship was seen in the subgroup of participants without myocardial infarction (p < 0.001). In multivariable regression that adjusted for confounders, both baseline echocardiographic (p < 0.001) and electrocardiographic (p < 0.001) LVM remained associated with development of depressed LVEF.ConclusionsIncreased LVM as assessed by electrocardiography or echocardiography is an independent risk factor for the development of depressed LVEF

Associations Between Metabolomic Compounds and Incident Heart Failure Among African Americans: The ARIC Study

Heart failure is more prevalent among African Americans than in the general population. Metabolomic studies among African Americans may efficiently identify novel biomarkers of heart failure. We used untargeted methods to measure 204 stable serum metabolites and evaluated their associations with incident heart failure hospitalization (n = 276) after a median follow-up of 20 years (1987–2008) by using Cox regression in data from 1,744 African Americans aged 45–64 years without heart failure at baseline from the Jackson, Mississippi, field center of the Atherosclerosis Risk in Communities (ARIC) Study. After adjustment for established risk factors, we found that 16 metabolites (6 named with known structural identities and 10 unnamed with unknown structural identities, the latter denoted by using the format X-12345) were associated with incident heart failure (P < 0.0004 based on a modified Bonferroni procedure). Of the 6 named metabolites, 4 are involved in amino acid metabolism, 1 (prolylhydroxyproline) is a dipeptide, and 1 (erythritol) is a sugar alcohol. After additional adjustment for kidney function, 2 metabolites remained associated with incident heart failure (for metabolite X-11308, hazard ratio = 0.75, 95% confidence interval: 0.65, 0.86; for metabolite X-11787, hazard ratio = 1.23, 95% confidence interval: 1.10, 1.37). Further structural analysis revealed X-11308 to be a dihydroxy docosatrienoic acid and X-11787 to be an isoform of either hydroxyleucine or hydroxyisoleucine. Our metabolomic analysis revealed novel biomarkers associated with incident heart failure independent of traditional risk factors

New Models for Large Prospective Studies: Is There a Better Way?

Large prospective cohort studies are critical for identifying etiologic factors for disease, but they require substantial long-term research investment. Such studies can be conducted as multisite consortia of academic medical centers, combinations of smaller ongoing studies, or a single large site such as a dominant regional health-care provider. Still another strategy relies upon centralized conduct of most or all aspects, recruiting through multiple temporary assessment centers. This is the approach used by a large-scale national resource in the United Kingdom known as the “UK Biobank,” which completed recruitment/examination of 503,000 participants between 2007 and 2010 within budget and ahead of schedule. A key lesson from UK Biobank and similar studies is that large studies are not simply small studies made large but, rather, require fundamentally different approaches in which “process” expertise is as important as scientific rigor. Embedding recruitment in a structure that facilitates outcome determination, utilizing comprehensive and flexible information technology, automating biospecimen processing, ensuring broad consent, and establishing essentially autonomous leadership with appropriate oversight are all critical to success. Whether and how these approaches may be transportable to the United States remain to be explored, but their success in studies such as UK Biobank makes a compelling case for such explorations to begin

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them

Genotype Imputation of MetabochipSNPs Using a Study-Specific Reference Panel of ∼4,000 Haplotypes in African Americans From the Women's Health Initiative: Imputation of Metabochip SNPs in African Americans

Genetic imputation has become standard practice in modern genetic studies. However, several important issues have not been adequately addressed including the utility of study-specific reference, performance in admixed populations, and quality for less common (minor allele frequency [MAF] 0.005–0.05) and rare (MAF 0.05 (0.03–0.05, 0.01–0.03, 0.005–0.01, and 0.001–0.005) passed the post-imputation filter. The average dosage r2 for these SNPs is 94.7%, 92.1%, 89.0%, 83.1%, and 79.7%, respectively. These results suggest that for African Americans imputation of Metabochip SNPs from GWAS data, including low frequency SNPs with MAF 0.005–0.05, is feasible and worthwhile for power increase in downstream association analysis provided a sizable reference panel is available

Genome-Wide Association Analysis of Ischemic Stroke in Young Adults

Ischemic stroke (IS) is among the leading causes of death in Western countries. There is a significant genetic component to IS susceptibility, especially among young adults. To date, research to identify genetic loci predisposing to stroke has met only with limited success. We performed a genome-wide association (GWA) analysis of early-onset IS to identify potential stroke susceptibility loci. The GWA analysis was conducted by genotyping 1 million SNPs in a biracial population of 889 IS cases and 927 controls, ages 15–49 years. Genotypes were imputed using the HapMap3 reference panel to provide 1.4 million SNPs for analysis. Logistic regression models adjusting for age, recruitment stages, and population structure were used to determine the association of IS with individual SNPs. Although no single SNP reached genome-wide significance (P < 5 × 10−8), we identified two SNPs in chromosome 2q23.3, rs2304556 (in FMNL2; P = 1.2 × 10−7) and rs1986743 (in ARL6IP6; P = 2.7 × 10−7), strongly associated with early-onset stroke. These data suggest that a novel locus on human chromosome 2q23.3 may be associated with IS susceptibility among young adults

A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources.

OBJECTIVE: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled Developing a Clinical Genomic Informatics Research Agenda . The meeting\u27s goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. MATERIALS AND METHODS: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting\u27s goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. RESULTS: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. DISCUSSION: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them

The Next PAGE in Understanding Complex Traits: Design for the Analysis of Population Architecture Using Genetics and Epidemiology (PAGE) Study

Genetic studies have identified thousands of variants associated with complex traits. However, most association studies are limited to populations of European descent and a single phenotype. The Population Architecture using Genomics and Epidemiology (PAGE) Study was initiated in 2008 by the National Human Genome Research Institute to investigate the epidemiologic architecture of well-replicated genetic variants associated with complex diseases in several large, ethnically diverse population-based studies. Combining DNA samples and hundreds of phenotypes from multiple cohorts, PAGE is well-suited to address generalization of associations and variability of effects in diverse populations; identify genetic and environmental modifiers; evaluate disease subtypes, intermediate phenotypes, and biomarkers; and investigate associations with novel phenotypes. PAGE investigators harmonize phenotypes across studies where possible and perform coordinated cohort-specific analyses and meta-analyses. PAGE researchers are genotyping thousands of genetic variants in up to 121,000 DNA samples from African-American, white, Hispanic/Latino, Asian/Pacific Islander, and American Indian participants. Initial analyses will focus on single nucleotide polymorphisms (SNPs) associated with obesity, lipids, cardiovascular disease, type 2 diabetes, inflammation, various cancers, and related biomarkers. PAGE SNPs are also assessed for pleiotropy using the “phenome-wide association study” approach, testing each SNP for associations with hundreds of phenotypes. PAGE data will be deposited into the National Center for Biotechnology Information's Database of Genotypes and Phenotypes and made available via a custom browser

Population genomics of cardiometabolic traits: design of the University College London-London School of Hygiene and Tropical Medicine-Edinburgh-Bristol (UCLEB) Consortium.

Substantial advances have been made in identifying common genetic variants influencing cardiometabolic traits and disease outcomes through genome wide association studies. Nevertheless, gaps in knowledge remain and new questions have arisen regarding the population relevance, mechanisms, and applications for healthcare. Using a new high-resolution custom single nucleotide polymorphism (SNP) array (Metabochip) incorporating dense coverage of genomic regions linked to cardiometabolic disease, the University College-London School-Edinburgh-Bristol (UCLEB) consortium of highly-phenotyped population-based prospective studies, aims to: (1) fine map functionally relevant SNPs; (2) precisely estimate individual absolute and population attributable risks based on individual SNPs and their combination; (3) investigate mechanisms leading to altered risk factor profiles and CVD events; and (4) use Mendelian randomisation to undertake studies of the causal role in CVD of a range of cardiovascular biomarkers to inform public health policy and help develop new preventative therapies