Erwin P Bottinger

Icahn School of Medicine at Mount Sinai, Borough of Manhattan, New York, United States

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Publications (115)1064.03 Total impact

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    ABSTRACT: We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals, and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2, ZNF259/APOA5, KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5, LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol, and GCKR, TRIB1, ZNF259/APOA5 and NCAN/MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol (FN1 and SAMM50), two for HDL cholesterol (LOC100996634 and COPB1) and one for LDL cholesterol (LINC00324/CTC1/PFAS). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.
    Full-text · Article · Feb 2016 · Scientific Reports
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    Cristian Pattaro · Alexander Teumer · Mathias Gorski · Audrey Y. Chu · Man Li · Vladan Mijatovic · Maija Garnaas · Adrienne Tin · Rossella Sorice · Yong Li · [...] · Katalin Susztak · Pavel Hamet · Johanne Tremblay · Ian H. de Boer · Carsten A. Böger · Wolfram Goessling · Daniel I. Chasman · Anna Köttgen · W. H. Linda Kao · Caroline S. Fox ·

    Full-text · Article · Jan 2016 · Nature Communications
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    ABSTRACT: Importance Large-scale DNA sequencing identifies incidental rare variants in established Mendelian disease genes, but the frequency of related clinical phenotypes in unselected patient populations is not well established. Phenotype data from electronic medical records (EMRs) may provide a resource to assess the clinical relevance of rare variants.Objective To determine the clinical phenotypes from EMRs for individuals with variants designated as pathogenic by expert review in arrhythmia susceptibility genes.Design, Setting, and Participants This prospective cohort study included 2022 individuals recruited for nonantiarrhythmic drug exposure phenotypes from October 5, 2012, to September 30, 2013, for the Electronic Medical Records and Genomics Network Pharmacogenomics project from 7 US academic medical centers. Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were assessed for potential pathogenicity by 3 laboratories with ion channel expertise and by comparison with the ClinVar database. Relevant phenotypes were determined from EMRs, with data available from 2002 (or earlier for some sites) through September 10, 2014.Exposures One or more variants designated as pathogenic in SCN5A or KCNH2.Main Outcomes and Measures Arrhythmia or electrocardiographic (ECG) phenotypes defined by International Classification of Diseases, Ninth Revision (ICD-9) codes, ECG data, and manual EMR review.Results Among 2022 study participants (median age, 61 years [interquartile range, 56-65 years]; 1118 [55%] female; 1491 [74%] white), a total of 122 rare (minor allele frequency <0.5%) nonsynonymous and splice-site variants in 2 arrhythmia susceptibility genes were identified in 223 individuals (11% of the study cohort). Forty-two variants in 63 participants were designated potentially pathogenic by at least 1 laboratory or ClinVar, with low concordance across laboratories (Cohen κ = 0.26). An ICD-9 code for arrhythmia was found in 11 of 63 (17%) variant carriers vs 264 of 1959 (13%) of those without variants (difference, +4%; 95% CI, −5% to +13%; P = .35). In the 1270 (63%) with ECGs, corrected QT intervals were not different in variant carriers vs those without (median, 429 vs 439 milliseconds; difference, −10 milliseconds; 95% CI, −16 to +3 milliseconds; P = .17). After manual review, 22 of 63 participants (35%) with designated variants had any ECG or arrhythmia phenotype, and only 2 had corrected QT interval longer than 500 milliseconds.Conclusions and Relevance Among laboratories experienced in genetic testing for cardiac arrhythmia disorders, there was low concordance in designating SCN5A and KCNH2 variants as pathogenic. In an unselected population, the putatively pathogenic genetic variants were not associated with an abnormal phenotype. These findings raise questions about the implications of notifying patients of incidental genetic findings.
    No preview · Article · Jan 2016 · JAMA The Journal of the American Medical Association
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    ABSTRACT: The incidence of chronic kidney disease (CKD) varies by ancestry, with African Americans (AA) having a threefold to fourfold higher rate than whites. Notably, two APOL1 alleles, termed G1 [c.(1072A>G; 1200T>G)] and G2 (c.1212_1217del6), are strongly associated with higher rates of nondiabetic CKD and an increased risk for hypertensive end-stage renal disease. This has prompted the opportunity to implement APOL1 testing to identify at-risk patients and modify other risk factors to reduce the progression of CKD to end-stage renal disease. We developed an APOL1 genotyping assay using multiplex allele-specific primer extension, and validated using 58 positive and negative controls. Genotyping results were completely concordant with Sanger sequencing; both triplicate interrun and intrarun genotyping results were completely concordant. Multiethnic APOL1 allele frequencies were also determined by genotyping 7059 AA, Hispanic, and Asian individuals from the New York City metropolitan area. The AA, Hispanic, and Asian APOL1 G1 and G2 allele frequencies were 0.22 and 0.13, 0.037 and 0.025, and 0.013 and 0.004, respectively. Notably, approximately 14% of the AA population carried two risk alleles and are at increased risk for CKD, compared with <1% of the Hispanic and Asian populations. This novel APOL1 genotyping assay is robust and highly accurate, and represents one of the first personalized medicine clinical genetic tests for disease risk prediction.
    No preview · Article · Jan 2016 · The Journal of molecular diagnostics: JMD
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    ABSTRACT: Objective: More than 80% of autoimmune disease is female dominant, but the mechanism for this female bias is poorly understood. We suspected an X chromosome dose effect and hypothesized that trisomy X (47,XXX, 1 in ∼1,000 live female births) would be increased in female predominant diseases (e.g. systemic lupus erythematosus [SLE], primary Sjögren's syndrome [SS], primary biliary cirrhosis [PBC] and rheumatoid arthritis [RA]) compared to diseases without female predominance (sarcoidosis) and controls. Methods: We identified 47,XXX subjects using aggregate data from single nucleotide polymorphism (SNP) arrays and confirmed, when possible, by fluorescent in situ hybridization (FISH) or quantitative polymerase chain reaction (q-PCR). Results: We found 47,XXX in seven of 2,826 SLE and three of 1,033 SS female patients, but only in two of the 7,074 female controls (p=0.003, OR=8.78, 95% CI: 1.67-86.79 and p=0.02, OR=10.29, 95% CI: 1.18-123.47; respectively). One 47,XXX subject was present for ∼404 SLE women and ∼344 SS women. 47,XXX was present in excess among SLE and SS subjects. Conclusion: The estimated prevalence of SLE and SS in women with 47,XXX was respectively ∼2.5 and ∼2.9 times higher than in 46,XX women and ∼25 and ∼41 times higher than in 46,XY men. No statistically significant increase of 47,XXX was observed in other female-biased diseases (PBC or RA), supporting the idea of multiple pathways to sex bias in autoimmunity. This article is protected by copyright. All rights reserved.
    Full-text · Article · Dec 2015 · Arthritis and Rheumatology
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    ABSTRACT: People of African ancestry (Blacks) have increased risk of kidney failure due to numerous socioeconomic, environmental, and clinical factors. Two variants in the APOL1 gene are now thought to account for much of the racial disparity associated with hypertensive kidney failure in Blacks. However, this knowledge has not been translated into clinical care to help improve patient outcomes and address disparities. GUARDD is a randomized trial to evaluate the effects and challenges of incorporating genetic risk information into primary care. Hypertensive, non-diabetic, adults with self-reported African ancestry, without kidney dysfunction, are recruited from diverse clinical settings and randomized to undergo APOL1 genetic testing at baseline (intervention) or at one year (waitlist control). Providers are educated about genomics and APOL1. Guided by a genetic counselor, trained staff return APOL1 results to patients and provide low-literacy educational materials. Real-time clinical decision support tools alert clinicians of their patients' APOL1 results and associated risk status at the point of care. Our academic-community-clinical partnership designed a study to generate information about the impact of genetic risk information on patient care (blood pressure and renal surveillance) and on patient and provider knowledge, attitudes, beliefs, and behaviors. GUARDD will help establish the effective implementation of APOL1 risk-informed management of hypertensive patients at high risk of CKD, and will provide a robust framework for future endeavors to implement genomic medicine in diverse clinical practices. It will also add to the important dialog about factors that contribute to and may help eliminate racial disparities in kidney disease.
    Full-text · Article · Dec 2015 · Contemporary clinical trials
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    ABSTRACT: Background: Patients, clinicians, researchers and payers are seeking to understand the value of using genomic information (as reflected by genotyping, sequencing, family history or other data) to inform clinical decision-making. However, challenges exist to widespread clinical implementation of genomic medicine, a prerequisite for developing evidence of its real-world utility. Methods: To address these challenges, the National Institutes of Health-funded IGNITE (Implementing GeNomics In pracTicE; www.ignite-genomics.org) Network, comprised of six projects and a coordinating center, was established in 2013 to support the development, investigation and dissemination of genomic medicine practice models that seamlessly integrate genomic data into the electronic health record and that deploy tools for point of care decision making. IGNITE site projects are aligned in their purpose of testing these models, but individual projects vary in scope and design, including exploring genetic markers for disease risk prediction and prevention, developing tools for using family history data, incorporating pharmacogenomic data into clinical care, refining disease diagnosis using sequence-based mutation discovery, and creating novel educational approaches. Results: This paper describes the IGNITE Network and member projects, including network structure, collaborative initiatives, clinical decision support strategies, methods for return of genomic test results, and educational initiatives for patients and providers. Clinical and outcomes data from individual sites and network-wide projects are anticipated to begin being published over the next few years. Conclusions: The IGNITE Network is an innovative series of projects and pilot demonstrations aiming to enhance translation of validated actionable genomic information into clinical settings and develop and use measures of outcome in response to genome-based clinical interventions using a pragmatic framework to provide early data and proofs of concept on the utility of these interventions. Through these efforts and collaboration with other stakeholders, IGNITE is poised to have a significant impact on the acceleration of genomic information into medical practice.
    Full-text · Article · Dec 2015 · BMC Medical Genomics
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    Gabriella Casalena · Erwin Bottinger · Ilse Daehn
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    ABSTRACT: Background/aims: In podocytes, the overexpression of TGFβ ligands and receptors during glomerulosclerosis could be a causal factor for injury induction and perpetuation in glomerular tufts. Mitochondrial dysfunction and oxidative stress are emerging as potential therapeutic targets in glomerular injury, and TGFβ has been shown to modulate mitochondrial metabolism in different cell types. This study aims at investigating the role of TGFβ in podocyte energy metabolism and cytoskeleton dynamics. Methods: Mitochondrial function and cytoskeleton dynamics were analyzed in TGFβ-treated WT and Smad2/3 double KO podocytes. Results: TGFβ treatment in podocytes induced a significant Smad-dependent increase of mitochondrial oxygen consumption rate (OCR). ATP content was unchanged and increased respiration was not associated with increased mitochondrial mass. Increased cellular reactive oxygen species induced by Smad-mediated TGFβ signaling were reverted by NADPH oxidase inhibitor apocynin. TGFβ treatment did not induce mitochondrial oxidative stress, and Smad2/3-dependent TGFβ signaling and increased mitochondrial OCR were found to be associated with actin cytoskeleton dynamics. The role of motor proteins myosin II and dynamin in TGFβ-induced actin polymerization was demonstrated by specific inhibition, resulting in actin stabilization and normalization of mitochondrial OCR. Conclusion: TGFβ-induced rearrangements of actin cytoskeleton are controlled by Smad2/3 signaling pathways and coupled with the activation of mitochondrial ATP synthesis as bioenergetic adaptation to ATP consumption by ATP- and GTP-dependent motor proteins, myosin II and dynamin.
    Full-text · Article · Nov 2015 · Nephron - Physiology
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    ABSTRACT: Background: Genomic medicine has the potential to improve care by tailoring treatments to the individual. There is consensus in the literature that pharmacogenomics (PGx) may be an ideal starting point for real-world implementation, due to the presence of well-characterized drug-gene interactions. Clinical Decision Support (CDS) is an ideal avenue by which to implement PGx at the bedside. Previous literature has established theoretical models for PGx CDS implementation and discussed a number of anticipated real-world challenges. However, work detailing actual PGx CDS implementation experiences has been limited. Anticipated challenges include data storage and management, system integration, physician acceptance, and more. Methods: In this study, we analyzed the experiences of ten members of the Electronic Medical Records and Genomics (eMERGE) Network, and one affiliate, in their attempts to implement PGx CDS. We examined the resulting PGx CDS system characteristics and conducted a survey to understand the unanticipated implementation challenges sites encountered. Results: Ten sites have successfully implemented at least one PGx CDS rule in the clinical setting. The majority of sites elected to create an Omic Ancillary System (OAS) to manage genetic and genomic data. All sites were able to adapt their existing CDS tools for PGx knowledge. The most common and impactful delays were not PGx-specific issues. Instead, they were general IT implementation problems, with top challenges including team coordination/communication and staffing. The challenges encountered caused a median total delay in system go-live of approximately two months. Conclusions: These results suggest that barriers to PGx CDS implementations are generally surmountable. Moreover, PGx CDS implementation may not be any more difficult than other healthcare IT projects of similar scope, as the most significant delays encountered were not unique to genomic medicine. These are encouraging results for any institution considering implementing a PGx CDS tool, and for the advancement of genomic medicine.
    Full-text · Article · Nov 2015
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    Full-text · Dataset · Nov 2015
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    ABSTRACT: We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
    Full-text · Article · Nov 2015 · Nature Genetics
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    ABSTRACT: Type 2 diabetes (T2D) is a heterogeneous complex disease affecting more than 29 million Americans alone with a rising prevalence trending toward steady increases in the coming decades. Thus, there is a pressing clinical need to improve early prevention and clinical management of T2D and its complications. Clinicians have understood that patients who carry the T2D diagnosis have a variety of phenotypes and susceptibilities to diabetes-related complications. We used a precision medicine approach to characterize the complexity of T2D patient populations based on high-dimensional electronic medical records (EMRs) and genotype data from 11,210 individuals. We successfully identified three distinct subgroups of T2D from topology-based patient-patient networks. Subtype 1 was characterized by T2D complications diabetic nephropathy and diabetic retinopathy; subtype 2 was enriched for cancer malignancy and cardiovascular diseases; and subtype 3 was associated most strongly with cardiovascular diseases, neurological diseases, allergies, and HIV infections. We performed a genetic association analysis of the emergent T2D subtypes to identify subtype-specific genetic markers and identified 1279, 1227, and 1338 single-nucleotide polymorphisms (SNPs) that mapped to 425, 322, and 437 unique genes specific to subtypes 1, 2, and 3, respectively. By assessing the human disease-SNP association for each subtype, the enriched phenotypes and biological functions at the gene level for each subtype matched with the disease comorbidities and clinical differences that we identified through EMRs. Our approach demonstrates the utility of applying the precision medicine paradigm in T2D and the promise of extending the approach to the study of other complex, multifactorial diseases.
    No preview · Article · Oct 2015 · Science translational medicine
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    ABSTRACT: Genomic, proteomic, epigenomic, and other "omic" data have the potential to enable precision medicine, also commonly referred to as personalized medicine. The volume and complexity of omic data are rapidly overwhelming human cognitive capacity, requiring innovative approaches to translate such data into patient care. Here, we outline a conceptual model for the application of omic data in the clinical context, called "the omic funnel." This model parallels the classic "Data, Information, Knowledge, Wisdom pyramid" and adds context for how to move between each successive layer. Its goal is to allow informaticians, researchers, and clinicians to approach the problem of translating omic data from bench to bedside, by using discrete steps with clearly defined needs. Such an approach can facilitate the development of modular and interoperable software that can bring precision medicine into widespread practice.
    No preview · Article · Oct 2015
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    ABSTRACT: Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.
    Full-text · Article · Oct 2015 · PLoS Genetics
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    ABSTRACT: Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men 50y, men >50y, women 50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed signifi- cant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (!50y). No sex-dependent effects were identified for BMI. For WHRadjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHRadjBMI. This is the first genome-wide interaction meta-analy- sis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHRadjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimor- phism of body shape.
    Full-text · Article · Oct 2015 · PLoS Genetics
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    ABSTRACT: 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. We used the eMERGE Network, a multicenter cohort with genotype data linked to electronic medical records, to estimate the diagnostic rate and clinical penetrance of HH in 98 individuals homozygous for the variant coding for HFE p.Cys282Tyr and 397 compound heterozygotes with variants resulting in p.[His63Asp];[Cys282Tyr]. The diagnostic rate of HH in males was 24.4% for p.Cys282Tyr homozygotes and 3.5% for compound heterozygotes (p < 0.001); in females, it was 14.0% for p.Cys282Tyr homozygotes and 2.3% for compound heterozygotes (p < 0.001). Only males showed differences across genotypes in transferrin saturation levels (100% of homozygotes versus 37.5% of compound heterozygotes with transferrin saturation > 50%; p = 0.003), serum ferritin levels (77.8% versus 33.3% with serum ferritin > 300 ng/ml; p = 0.006), and diabetes (44.7% versus 28.0%; p = 0.03). No differences were found in the prevalence of heart disease, arthritis, or liver disease, except for the rate of liver biopsy (10.9% versus 1.8% [p = 0.013] in males; 9.1% versus 2% [p = 0.035] in females). Given the higher rate of HH diagnosis than in prior studies, the high penetrance of iron overload, and the frequency of at-risk genotypes, in addition to other suggested actionable adult-onset genetic conditions, opportunistic screening should be considered for p.[Cys282Tyr];[Cys282Tyr] individuals with existing genomic data.
    No preview · Article · Sep 2015 · The American Journal of Human Genetics
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    ABSTRACT: Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of ∼185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate causal genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
    No preview · Article · Sep 2015 · Nature Genetics
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    ABSTRACT: Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of [sim]185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate casual genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
    No preview · Article · Sep 2015 · Nature Genetics
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    ABSTRACT: Existing knowledge of genetic variants affecting risk of coronary artery disease (CAD) is largely based on genome-wide association study (GWAS) analysis of common SNPs. Leveraging phased haplotypes from the 1000 Genomes Project, we report a GWAS meta-analysis of [sim]185,000 CAD cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 million low-frequency (0.005 < MAF < 0.05) variants. In addition to confirming most known CAD-associated loci, we identified ten new loci (eight additive and two recessive) that contain candidate casual genes newly implicating biological processes in vessel walls. We observed intralocus allelic heterogeneity but little evidence of low-frequency variants with larger effects and no evidence of synthetic association. Our analysis provides a comprehensive survey of the fine genetic architecture of CAD, showing that genetic susceptibility to this common disease is largely determined by common SNPs of small effect size.
    Full-text · Article · Sep 2015 · Nature Genetics
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    ABSTRACT: As whole-genome sequencing (WGS) increases in availability, WGS educational aids are needed for research participants, patients, and the general public. Our aim was therefore to develop an accessible and scalable WGS educational aid. We engaged multiple stakeholders in an iterative process over a 1-year period culminating in the production of a novel 10-minute WGS educational animated video, "Whole Genome Sequencing and You" (https://goo.gl/HV8ezJ). We then presented the animated video to 281 online-survey respondents (the video-information group). There were also two comparison groups: a written-information group (n = 281) and a no-information group (n = 300). In the video-information group, 79% reported the video was easy to understand, satisfaction scores were high (mean 4.00 on 1-5 scale, where 5 = high satisfaction), and knowledge increased significantly. There were significant differences in knowledge compared with the no-information group but few differences compared with the written-information group. Intention to receive personal results from WGS and decisional conflict in response to a hypothetical scenario did not differ between the three groups. The educational animated video, "Whole Genome Sequencing and You," was well received by this sample of online-survey respondents. Further work is needed to evaluate its utility as an aid to informed decision making about WGS in other populations.Genet Med advance online publication 03 September 2015Genetics in Medicine (2015); doi:10.1038/gim.2015.118.
    No preview · Article · Sep 2015 · Genetics in medicine: official journal of the American College of Medical Genetics

Publication Stats

5k Citations
1,064.03 Total Impact Points

Institutions

  • 2006-2016
    • Icahn School of Medicine at Mount Sinai
      • • Department of Genetics and Genomic Sciences
      • • Department of Medicine
      Borough of Manhattan, New York, United States
  • 2015
    • University of Oxford
      Oxford, England, United Kingdom
  • 2013
    • Columbia University
      • Division of Nephrology
      New York City, New York, United States
  • 2007-2011
    • Mount Sinai Medical Center
      New York City, New York, United States
  • 1999-2008
    • Albert Einstein College of Medicine
      • • Nephrology
      • • Department of Medicine
      New York, New York, United States
  • 2004
    • Vanderbilt University
      • Department of Medicine
      Нашвилл, Michigan, United States