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Cruz LA, Cooke Bailey JN, Crawford DC. Importance of Diversity in Precision Medicine: Generalizability of Genetic Associations Across Ancestry Groups Toward Better Identification of Disease Susceptibility Variants. Annu Rev Biomed Data Sci 2023; 6:339-356. [PMID: 37196357 PMCID: PMC10720270 DOI: 10.1146/annurev-biodatasci-122220-113250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Genome-wide association studies (GWAS) revolutionized our understanding of common genetic variation and its impact on common human disease and traits. Developed and adopted in the mid-2000s, GWAS led to searchable genotype-phenotype catalogs and genome-wide datasets available for further data mining and analysis for the eventual development of translational applications. The GWAS revolution was swift and specific, including almost exclusively populations of European descent, to the neglect of the majority of the world's genetic diversity. In this narrative review, we recount the GWAS landscape of the early years that established a genotype-phenotype catalog that is now universally understood to be inadequate for a complete understanding of complex human genetics. We then describe approaches taken to augment the genotype-phenotype catalog, including the study populations, collaborative consortia, and study design approaches aimed to generalize and then ultimately discover genome-wide associations in non-European descent populations. The collaborations and data resources established in the efforts to diversify genomic findings undoubtedly provide the foundations of the next chapters of genetic association studies with the advent of budget-friendly whole-genome sequencing.
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Affiliation(s)
- Lauren A Cruz
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA;
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jessica N Cooke Bailey
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA;
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
| | - Dana C Crawford
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, Ohio, USA;
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, USA
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA
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2
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Radhakrishnan A, Friedman SF, Khurshid S, Ng K, Batra P, Lubitz SA, Philippakis AA, Uhler C. Cross-modal autoencoder framework learns holistic representations of cardiovascular state. Nat Commun 2023; 14:2436. [PMID: 37105979 PMCID: PMC10140057 DOI: 10.1038/s41467-023-38125-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Accepted: 04/18/2023] [Indexed: 04/29/2023] Open
Abstract
A fundamental challenge in diagnostics is integrating multiple modalities to develop a joint characterization of physiological state. Using the heart as a model system, we develop a cross-modal autoencoder framework for integrating distinct data modalities and constructing a holistic representation of cardiovascular state. In particular, we use our framework to construct such cross-modal representations from cardiac magnetic resonance images (MRIs), containing structural information, and electrocardiograms (ECGs), containing myoelectric information. We leverage the learned cross-modal representation to (1) improve phenotype prediction from a single, accessible phenotype such as ECGs; (2) enable imputation of hard-to-acquire cardiac MRIs from easy-to-acquire ECGs; and (3) develop a framework for performing genome-wide association studies in an unsupervised manner. Our results systematically integrate distinct diagnostic modalities into a common representation that better characterizes physiologic state.
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Affiliation(s)
| | | | - Shaan Khurshid
- Broad Institute of MIT and Harvard, Cambridge, USA
- Massachusetts General Hospital, Massachusetts, USA
| | - Kenney Ng
- IBM T.J. Watson Research Center, New York, USA
| | - Puneet Batra
- Broad Institute of MIT and Harvard, Cambridge, USA
| | - Steven A Lubitz
- Broad Institute of MIT and Harvard, Cambridge, USA.
- Massachusetts General Hospital, Massachusetts, USA.
| | | | - Caroline Uhler
- Massachusetts Institute of Technology, Cambridge, USA.
- Broad Institute of MIT and Harvard, Cambridge, USA.
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3
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Wang W, Yao J, Li W, Wu Y, Duan H, Xu C, Tian X, Li S, Tan Q, Zhang D. Epigenome-wide association study in Chinese monozygotic twins identifies DNA methylation loci associated with blood pressure. Clin Epigenetics 2023; 15:38. [PMID: 36869404 PMCID: PMC9985232 DOI: 10.1186/s13148-023-01457-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 02/24/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND Hypertension is a crucial risk factor for developing cardiovascular disease and reducing life expectancy. We aimed to detect DNA methylation (DNAm) variants potentially related to systolic blood pressure (SBP) and diastolic blood pressure (DBP) by conducting epigenome-wide association studies in 60 and 59 Chinese monozygotic twin pairs, respectively. METHODS Genome-wide DNA methylation profiling in whole blood of twins was performed using Reduced Representation Bisulfite Sequencing, yielding 551,447 raw CpGs. Association between DNAm of single CpG and blood pressure was tested by applying generalized estimation equation. Differentially methylated regions (DMRs) were identified by comb-P approach. Inference about Causation through Examination of Familial Confounding was utilized to perform the causal inference. Ontology enrichment analysis was performed using Genomic Regions Enrichment of Annotations Tool. Candidate CpGs were quantified using Sequenom MassARRAY platform in a community population. Weighted gene co-expression network analysis (WGCNA) was conducted using gene expression data. RESULTS The median age of twins was 52 years (95% range 40, 66). For SBP, 31 top CpGs (p < 1 × 10-4) and 8 DMRs were identified, with several DMRs within NFATC1, CADM2, IRX1, COL5A1, and LRAT. For DBP, 43 top CpGs (p < 1 × 10-4) and 12 DMRs were identified, with several DMRs within WNT3A, CNOT10, and DAB2IP. Important pathways, such as Notch signaling pathway, p53 pathway by glucose deprivation, and Wnt signaling pathway, were significantly enriched for SBP and DBP. Causal inference analysis suggested that DNAm at top CpGs within NDE1, MYH11, SRRM1P2, and SMPD4 influenced SBP, while SBP influenced DNAm at CpGs within TNK2. DNAm at top CpGs within WNT3A influenced DBP, while DBP influenced DNAm at CpGs within GNA14. Three CpGs mapped to WNT3A and one CpG mapped to COL5A1 were validated in a community population, with a hypermethylated and hypomethylated direction in hypertension cases, respectively. Gene expression analysis by WGCNA further identified some common genes and enrichment terms. CONCLUSION We detect many DNAm variants that may be associated with blood pressure in whole blood, particularly the loci within WNT3A and COL5A1. Our findings provide new clues to the epigenetic modification underlying hypertension pathogenesis.
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Affiliation(s)
- Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
| | - Jie Yao
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
- Jiangsu Health Development Research Center, Nanjing, Jiangsu, China
| | - Weilong Li
- Population Research Unit, Faculty of Social Sciences, University of Helsinki, Helsinki, Finland
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Shuxia Li
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Qihua Tan
- Unit of Human Genetics, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 308 Ningxia Road, Qingdao, 266021, Shandong, China.
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4
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Bhattacharyya S, Kollipara RK, Orquera-Tornakian G, Goetsch S, Zhang M, Perry C, Li B, Shelton JM, Bhakta M, Duan J, Xie Y, Xiao G, Evers BM, Hon GC, Kittler R, Munshi NV. Global chromatin landscapes identify candidate noncoding modifiers of cardiac rhythm. J Clin Invest 2023; 133:e153635. [PMID: 36454649 PMCID: PMC9888383 DOI: 10.1172/jci153635] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 11/30/2022] [Indexed: 12/03/2022] Open
Abstract
Comprehensive cis-regulatory landscapes are essential for accurate enhancer prediction and disease variant mapping. Although cis-regulatory element (CRE) resources exist for most tissues and organs, many rare - yet functionally important - cell types remain overlooked. Despite representing only a small fraction of the heart's cellular biomass, the cardiac conduction system (CCS) unfailingly coordinates every life-sustaining heartbeat. To globally profile the mouse CCS cis-regulatory landscape, we genetically tagged CCS component-specific nuclei for comprehensive assay for transposase-accessible chromatin-sequencing (ATAC-Seq) analysis. Thus, we established a global CCS-enriched CRE database, referred to as CCS-ATAC, as a key resource for studying CCS-wide and component-specific regulatory functions. Using transcription factor (TF) motifs to construct CCS component-specific gene regulatory networks (GRNs), we identified and independently confirmed several specific TF sub-networks. Highlighting the functional importance of CCS-ATAC, we also validated numerous CCS-enriched enhancer elements and suggested gene targets based on CCS single-cell RNA-Seq data. Furthermore, we leveraged CCS-ATAC to improve annotation of existing human variants related to cardiac rhythm and nominated a potential enhancer-target pair that was dysregulated by a specific SNP. Collectively, our results established a CCS-regulatory compendium, identified novel CCS enhancer elements, and illuminated potential functional associations between human genomic variants and CCS component-specific CREs.
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Affiliation(s)
| | | | | | - Sean Goetsch
- Department of Internal Medicine, Division of Cardiology
| | - Minzhe Zhang
- Quantitative Biomedical Research Center, Department of Population and Data Sciences
| | - Cameron Perry
- Department of Internal Medicine, Division of Cardiology
| | - Boxun Li
- Laboratory of Regulatory Genomics, Cecil H. and Ida Green Center for Reproductive Biology Sciences, Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology
| | | | - Minoti Bhakta
- Department of Internal Medicine, Division of Cardiology
| | - Jialei Duan
- Laboratory of Regulatory Genomics, Cecil H. and Ida Green Center for Reproductive Biology Sciences, Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology
| | - Yang Xie
- Quantitative Biomedical Research Center, Department of Population and Data Sciences
- Department of Bioinformatics
| | - Guanghua Xiao
- Quantitative Biomedical Research Center, Department of Population and Data Sciences
- Department of Bioinformatics
| | - Bret M. Evers
- Department of Internal Medicine, Division of Cardiology
| | - Gary C. Hon
- Laboratory of Regulatory Genomics, Cecil H. and Ida Green Center for Reproductive Biology Sciences, Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology
- Department of Bioinformatics
- Hamon Center for Regenerative Science and Medicine, and
| | - Ralf Kittler
- McDermott Center for Human Growth and Development
| | - Nikhil V. Munshi
- Department of Internal Medicine, Division of Cardiology
- McDermott Center for Human Growth and Development
- Hamon Center for Regenerative Science and Medicine, and
- Department of Molecular Biology, UT Southwestern Medical Center, Dallas, Texas, USA
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Hoffmann TJ, Lu M, Oni-Orisan A, Lee C, Risch N, Iribarren C. A large genome-wide association study of QT interval length utilizing electronic health records. Genetics 2022; 222:iyac157. [PMID: 36271874 PMCID: PMC9713425 DOI: 10.1093/genetics/iyac157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 09/22/2022] [Indexed: 12/13/2022] Open
Abstract
QT interval length is an important risk factor for adverse cardiovascular outcomes; however, the genetic architecture of QT interval remains incompletely understood. We conducted a genome-wide association study of 76,995 ancestrally diverse Kaiser Permanente Northern California members enrolled in the Genetic Epidemiology Research on Adult Health and Aging cohort using 448,517 longitudinal QT interval measurements, uncovering 9 novel variants, most replicating in 40,537 individuals in the UK Biobank and Population Architecture using Genomics and Epidemiology studies. A meta-analysis of all 3 cohorts (n = 117,532) uncovered an additional 19 novel variants. Conditional analysis identified 15 additional variants, 3 of which were novel. Little, if any, difference was seen when adjusting for putative QT interval lengthening medications genome-wide. Using multiple measurements in Genetic Epidemiology Research on Adult Health and Aging increased variance explained by 163%, and we show that the ≈6 measurements in Genetic Epidemiology Research on Adult Health and Aging was equivalent to a 2.4× increase in sample size of a design with a single measurement. The array heritability was estimated at ≈17%, approximately half of our estimate of 36% from family correlations. Heritability enrichment was estimated highest and most significant in cardiovascular tissue (enrichment 7.2, 95% CI = 5.7-8.7, P = 2.1e-10), and many of the novel variants included expression quantitative trait loci in heart and other relevant tissues. Comparing our results to other cardiac function traits, it appears that QT interval has a multifactorial genetic etiology.
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Affiliation(s)
- Thomas J Hoffmann
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Meng Lu
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Akinyemi Oni-Orisan
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Clinical Pharmacy, University of California San Francisco, San Francisco, CA 94143, USA
| | - Catherine Lee
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Neil Risch
- Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94143, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA 94143, USA
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
| | - Carlos Iribarren
- Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA
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Dueker ND, Beecham A, Wang L, Dong C, Sacco RL, Blanton SH, Rundek T. Rare variants in previously identified linkage regions associated with carotid plaque in Dominican Republic families. PLoS One 2022; 17:e0250799. [PMID: 35020748 PMCID: PMC8754284 DOI: 10.1371/journal.pone.0250799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 04/13/2021] [Indexed: 11/18/2022] Open
Abstract
Carotid plaque is a subclinical measure of atherosclerosis. We have previously shown measures of carotid plaque to be heritable in a sample of 100 Dominican families and found evidence for linkage and association of common variants (CVs) on 7q36, 11p15, 14q32 and 15q23 with plaque presence. Our current study aimed to refine these regions further and identify rare variants (RVs) influencing plaque presence. Therefore, we performed targeted sequencing of the one LOD unit down region on 7q36, 11p15, 14q32 and 15q23 in 12 Dominican families with evidence for linkage to plaque presence. Gene-based RV analyses were performed using the Sequence Association Test for familial data (F-SKAT) under two filtering algorithms; 1. all exonic RVs and 2. non-synonymous RVs. Replication analyses were performed using a sample of 22 Dominican families and 556 unrelated Dominicans with Exome Array data. To identify additional non-synonymous RVs influencing plaque, we looked for co-segregation of RVs with plaque in each of the sequenced families. Our most strongly associated gene with evidence for replication was AMPD3 which showed suggestive association with plaque presence in the sequenced families (exonic RV p = 0.003, nonsynonymous RV p = 0.005) and replication families (exonic RV p = 0.04, nonsynonymous RV p = 0.02). Examination of the sequenced family pedigrees revealed two missense variants on chromosome 11 which co-segregated with plaque presence in one of our families; rs61751342 (located in DENND2B), and rs61760882 (located in RNF141). The rs61751342 missense variant is an eQTL for SCUBE2 in the atrial appendage. Notably, SCUBE2 encodes a protein which interacts with vascular endothelial growth factor (VEGF) receptor 2 to regulate VEGF-induced angiogenesis, thus providing biologic plausibility for this gene in atherosclerosis. In conclusion, using targeted sequencing of previously-identified linkage regions, we have identified suggestive evidence for the role of RVs in carotid plaque pathogenesis.
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MESH Headings
- AMP Deaminase/genetics
- Adaptor Proteins, Signal Transducing/genetics
- Adult
- Aged
- Calcium-Binding Proteins/genetics
- Chromosomes, Human, Pair 11/genetics
- Chromosomes, Human, Pair 14/genetics
- Chromosomes, Human, Pair 15/genetics
- Chromosomes, Human, Pair 7/genetics
- DNA-Binding Proteins/genetics
- Dominican Republic
- Genetic Linkage
- Genotype
- Humans
- Middle Aged
- Pedigree
- Plaque, Atherosclerotic/genetics
- Plaque, Atherosclerotic/pathology
- Polymorphism, Genetic
- Quantitative Trait Loci
- Transcription Factors/genetics
- Tumor Suppressor Proteins/genetics
- Vascular Endothelial Growth Factor Receptor-2/genetics
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Affiliation(s)
- Nicole D. Dueker
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, United States of America
| | - Ashley Beecham
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, United States of America
| | - Liyong Wang
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, United States of America
| | - Chuanhui Dong
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
| | - Ralph L. Sacco
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, United States of America
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL, United States of America
- Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami, Miami, FL, United States of America
| | - Susan H. Blanton
- John P. Hussman Institute for Human Genomics, University of Miami, Miami, FL, United States of America
- Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, Miami, FL, United States of America
| | - Tatjana Rundek
- Department of Neurology, Miller School of Medicine, University of Miami, Miami, FL, United States of America
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL, United States of America
- Evelyn F. McKnight Brain Institute, Department of Neurology, University of Miami, Miami, FL, United States of America
- * E-mail:
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Benaglio P, D'Antonio-Chronowska A, Ma W, Yang F, Young Greenwald WW, Donovan MKR, DeBoever C, Li H, Drees F, Singhal S, Matsui H, van Setten J, Sotoodehnia N, Gaulton KJ, Smith EN, D'Antonio M, Rosenfeld MG, Frazer KA. Allele-specific NKX2-5 binding underlies multiple genetic associations with human electrocardiographic traits. Nat Genet 2019; 51:1506-1517. [PMID: 31570892 PMCID: PMC6858543 DOI: 10.1038/s41588-019-0499-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2018] [Accepted: 08/15/2019] [Indexed: 12/15/2022]
Abstract
The cardiac transcription factor (TF) gene NKX2-5 has been associated with electrocardiographic (EKG) traits through genome-wide association studies (GWASs), but the extent to which differential binding of NKX2-5 at common regulatory variants contributes to these traits has not yet been studied. We analyzed transcriptomic and epigenomic data from induced pluripotent stem cell-derived cardiomyocytes from seven related individuals, and identified ~2,000 single-nucleotide variants associated with allele-specific effects (ASE-SNVs) on NKX2-5 binding. NKX2-5 ASE-SNVs were enriched for altered TF motifs, for heart-specific expression quantitative trait loci and for EKG GWAS signals. Using fine-mapping combined with epigenomic data from induced pluripotent stem cell-derived cardiomyocytes, we prioritized candidate causal variants for EKG traits, many of which were NKX2-5 ASE-SNVs. Experimentally characterizing two NKX2-5 ASE-SNVs (rs3807989 and rs590041) showed that they modulate the expression of target genes via differential protein binding in cardiac cells, indicating that they are functional variants underlying EKG GWAS signals. Our results show that differential NKX2-5 binding at numerous regulatory variants across the genome contributes to EKG phenotypes.
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Affiliation(s)
- Paola Benaglio
- Department of Pediatrics, Rady Children's Hospital, Division of Genome Information Sciences, University of California, San Diego, La Jolla, CA, USA
| | | | - Wubin Ma
- Howard Hughes Medical Institute, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Feng Yang
- Howard Hughes Medical Institute, Department of Medicine, University of California, San Diego, La Jolla, CA, USA
| | | | - Margaret K R Donovan
- Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA.,Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA, USA
| | - Christopher DeBoever
- Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA
| | - He Li
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Frauke Drees
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Sanghamitra Singhal
- Department of Pediatrics, Rady Children's Hospital, Division of Genome Information Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Hiroko Matsui
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jessica van Setten
- Department of Cardiology, University Medical Center Utrecht, University of Utrecht, Utrecht, the Netherlands
| | - Nona Sotoodehnia
- Department of Medicine, Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA.,Department of Epidemiology, Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Kyle J Gaulton
- Department of Pediatrics, Rady Children's Hospital, Division of Genome Information Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Erin N Smith
- Department of Pediatrics, Rady Children's Hospital, Division of Genome Information Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Matteo D'Antonio
- Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Michael G Rosenfeld
- Howard Hughes Medical Institute, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.
| | - Kelly A Frazer
- Department of Pediatrics, Rady Children's Hospital, Division of Genome Information Sciences, University of California, San Diego, La Jolla, CA, USA. .,Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA, USA.
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8
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Swenson BR, Louie T, Lin HJ, Méndez-Giráldez R, Below JE, Laurie CC, Kerr KF, Highland H, Thornton TA, Ryckman KK, Kooperberg C, Soliman EZ, Seyerle AA, Guo X, Taylor KD, Yao J, Heckbert SR, Darbar D, Petty LE, McKnight B, Cheng S, Bello NA, Whitsel EA, Hanis CL, Nalls MA, Evans DS, Rotter JI, Sofer T, Avery CL, Sotoodehnia N. GWAS of QRS duration identifies new loci specific to Hispanic/Latino populations. PLoS One 2019; 14:e0217796. [PMID: 31251759 PMCID: PMC6599128 DOI: 10.1371/journal.pone.0217796] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 05/17/2019] [Indexed: 01/02/2023] Open
Abstract
BACKGROUND The electrocardiographically quantified QRS duration measures ventricular depolarization and conduction. QRS prolongation has been associated with poor heart failure prognosis and cardiovascular mortality, including sudden death. While previous genome-wide association studies (GWAS) have identified 32 QRS SNPs across 26 loci among European, African, and Asian-descent populations, the genetics of QRS among Hispanics/Latinos has not been previously explored. METHODS We performed a GWAS of QRS duration among Hispanic/Latino ancestry populations (n = 15,124) from four studies using 1000 Genomes imputed genotype data (adjusted for age, sex, global ancestry, clinical and study-specific covariates). Study-specific results were combined using fixed-effects, inverse variance-weighted meta-analysis. RESULTS We identified six loci associated with QRS (P<5x10-8), including two novel loci: MYOCD, a nuclear protein expressed in the heart, and SYT1, an integral membrane protein. The top SNP in the MYOCD locus, intronic SNP rs16946539, was found in Hispanics/Latinos with a minor allele frequency (MAF) of 0.04, but is monomorphic in European and African descent populations. The most significant QRS duration association was with intronic SNP rs3922344 (P = 1.19x10-24) in SCN5A/SCN10A. Three other previously identified loci, CDKN1A, VTI1A, and HAND1, also exceeded the GWAS significance threshold among Hispanics/Latinos. A total of 27 of 32 previously identified QRS duration SNPs were shown to generalize in Hispanics/Latinos. CONCLUSIONS Our QRS duration GWAS, the first in Hispanic/Latino populations, identified two new loci, underscoring the utility of extending large scale genomic studies to currently under-examined populations.
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Affiliation(s)
- Brenton R. Swenson
- Institute for Public Health Genetics, University of Washington, Seattle, WA, United States of America
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Henry J. Lin
- The Institute for Translational Genomics and Population Sciences, and Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA, United States of America
- Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Raúl Méndez-Giráldez
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC, United States of America
| | - Jennifer E. Below
- Department of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Cathy C. Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Kathleen F. Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Heather Highland
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
| | - Timothy A. Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Kelli K. Ryckman
- Departments of Epidemiology and Pediatrics, University of Iowa, Iowa City, IA, United States of America
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Elsayed Z. Soliman
- Department of Internal Medicine, Section on Cardiology, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
- Epidemiological Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - Amanda A. Seyerle
- Division of Pharmaceutical Outcomes and Policy, Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, United States of America
- Carolina Health Informatics Program, University of North Carolina, Chapel Hill, NC, United States of America
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, and Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, and Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, and Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Susan R. Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
- Department of Epidemiology, University of Washington, Seattle, WA, United States of America
| | - Dawood Darbar
- Division of Cardiology, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Lauren E. Petty
- Department of Medical Genetics, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Barbara McKnight
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
- Department of Biostatistics, University of Washington, Seattle, WA, United States of America
| | - Susan Cheng
- Smidt Heart Institute, Cedars-Sinai Medical Center, Los Angeles, CA, United States of America
| | - Natalie A. Bello
- Brigham and Women's Hospital, Division of Cardiovascular Medicine, Boston, MA, United States of America
- Division of Cardiology, Columbia University Medical Center, New York, NY, United States of America
| | - Eric A. Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
- Department of Medicine, University of North Carolina, Chapel Hill, NC, United States of America
| | - Craig L. Hanis
- Human Genetics Center, University of Texas, Health Science Center at Houston, Houston, TX, United States of America
| | - Mike A. Nalls
- Data Technical International, Glen Echo, MD, United States of America
- Laboratory of Neurogenetics, National Institute of Aging, Bethesda, MD, United States of America
| | - Daniel S. Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, United States of America
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, and Department of Pediatrics, Los Angeles Biomedical Research Institute, Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, MA, United States of America
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, United States of America
| | - Christy L. Avery
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, United States of America
- Carolina Population Center, University of North Carolina, Chapel Hill, NC, United States of America
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, United States of America
- Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, United States of America
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9
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Jeong C, Witonsky DB, Basnyat B, Neupane M, Beall CM, Childs G, Craig SR, Novembre J, Di Rienzo A. Detecting past and ongoing natural selection among ethnically Tibetan women at high altitude in Nepal. PLoS Genet 2018; 14:e1007650. [PMID: 30188897 PMCID: PMC6143271 DOI: 10.1371/journal.pgen.1007650] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Revised: 09/18/2018] [Accepted: 08/21/2018] [Indexed: 12/21/2022] Open
Abstract
Adaptive evolution in humans has rarely been characterized for its whole set of components, i.e. selective pressure, adaptive phenotype, beneficial alleles and realized fitness differential. We combined approaches for detecting polygenic adaptations and for mapping the genetic bases of physiological and fertility phenotypes in approximately 1000 indigenous ethnically Tibetan women from Nepal, adapted to high altitude. The results of genome-wide association analyses and tests for polygenic adaptations showed evidence of positive selection for alleles associated with more pregnancies and live births and evidence of negative selection for those associated with higher offspring mortality. Lower hemoglobin level did not show clear evidence for polygenic adaptation, despite its strong association with an EPAS1 haplotype carrying selective sweep signals.
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Affiliation(s)
- Choongwon Jeong
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - David B. Witonsky
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Buddha Basnyat
- Oxford University Clinical Research Unit, Patan Hospital, Kathmandu, Nepal
| | | | - Cynthia M. Beall
- Department of Anthropology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Geoff Childs
- Department of Anthropology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Sienna R. Craig
- Department of Anthropology, Dartmouth College, Hanover, New Hampshire, United States of America
| | - John Novembre
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
| | - Anna Di Rienzo
- Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America
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10
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Méndez-Giráldez R, Gogarten SM, Below JE, Yao J, Seyerle AA, Highland HM, Kooperberg C, Soliman EZ, Rotter JI, Kerr KF, Ryckman KK, Taylor KD, Petty LE, Shah SJ, Conomos MP, Sotoodehnia N, Cheng S, Heckbert SR, Sofer T, Guo X, Whitsel EA, Lin HJ, Hanis CL, Laurie CC, Avery CL. GWAS of the electrocardiographic QT interval in Hispanics/Latinos generalizes previously identified loci and identifies population-specific signals. Sci Rep 2017; 7:17075. [PMID: 29213071 PMCID: PMC5719082 DOI: 10.1038/s41598-017-17136-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2017] [Accepted: 11/21/2017] [Indexed: 01/08/2023] Open
Abstract
QT interval prolongation is a heritable risk factor for ventricular arrhythmias and can predispose to sudden death. Most genome-wide association studies (GWAS) of QT were performed in European ancestral populations, leaving other groups uncharacterized. Herein we present the first QT GWAS of Hispanic/Latinos using data on 15,997 participants from four studies. Study-specific summary results of the association between 1000 Genomes Project (1000G) imputed SNPs and electrocardiographically measured QT were combined using fixed-effects meta-analysis. We identified 41 genome-wide significant SNPs that mapped to 13 previously identified QT loci. Conditional analyses distinguished six secondary signals at NOS1AP (n = 2), ATP1B1 (n = 2), SCN5A (n = 1), and KCNQ1 (n = 1). Comparison of linkage disequilibrium patterns between the 13 lead SNPs and six secondary signals with previously reported index SNPs in 1000G super populations suggested that the SCN5A and KCNE1 lead SNPs were potentially novel and population-specific. Finally, of the 42 suggestively associated loci, AJAP1 was suggestively associated with QT in a prior East Asian GWAS; in contrast BVES and CAP2 murine knockouts caused cardiac conduction defects. Our results indicate that whereas the same loci influence QT across populations, population-specific variation exists, motivating future trans-ethnic and ancestrally diverse QT GWAS.
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Affiliation(s)
| | | | - Jennifer E Below
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Amanda A Seyerle
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,Division of Epidemiology and Community, University of Minnesota, Minneapolis, MN, USA
| | - Heather M Highland
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Elsayed Z Soliman
- Department of Internal Medicine, Section on Cardiology, Wake Forest School of Medicine, Winston-Salem, NC, USA.,Epidemiological Cardio Research Center (EPICARE), Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Kathleen F Kerr
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Kelli K Ryckman
- Departments of Epidemiology and Pediatrics, University of Iowa, Iowa City, IA, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Lauren E Petty
- Human Genetics Center, University of Texas, Health Science Center at Houston, Houston, TX, USA.,Center for Precision Medicine, University of Texas, Health Science Center at Houston, Houston, TX, USA
| | - Sanjiv J Shah
- Division of Cardiology, Bluhm Cardiovascular Institute, Northwestern Memorial Hospital, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Matthew P Conomos
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Division of Cardiology, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Susan Cheng
- Brigham and Women's Hospital, Division of Cardiovascular Medicine, Boston, MA, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA.,Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA, USA.,Department of Medicine, Harvard Medical School, Boston, MA, USA.,Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA.,Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences and Department of Pediatrics, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA.,Division of Medical Genetics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Craig L Hanis
- Human Genetics Center, University of Texas, Health Science Center at Houston, Houston, TX, USA
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Christy L Avery
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA. .,Carolina Population Center, University of North Carolina, Chapel Hill, NC, USA.
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11
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Meyers JL, Zhang J, Wang JC, Su J, Kuo SI, Kapoor M, Wetherill L, Bertelsen S, Lai D, Salvatore JE, Kamarajan C, Chorlian D, Agrawal A, Almasy L, Bauer L, Bucholz KK, Chan G, Hesselbrock V, Koganti L, Kramer J, Kuperman S, Manz N, Pandey A, Seay M, Scott D, Taylor RE, Dick DM, Edenberg HJ, Goate A, Foroud T, Porjesz B. An endophenotype approach to the genetics of alcohol dependence: a genome wide association study of fast beta EEG in families of African ancestry. Mol Psychiatry 2017; 22:1767-1775. [PMID: 28070124 PMCID: PMC5503794 DOI: 10.1038/mp.2016.239] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/17/2016] [Revised: 09/24/2016] [Accepted: 10/27/2016] [Indexed: 01/16/2023]
Abstract
Fast beta (20-28 Hz) electroencephalogram (EEG) oscillatory activity may be a useful endophenotype for studying the genetics of disorders characterized by neural hyperexcitability, including substance use disorders (SUDs). However, the genetic underpinnings of fast beta EEG have not previously been studied in a population of African-American ancestry (AA). In a sample of 2382 AA individuals from 482 families drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a genome-wide association study (GWAS) on resting-state fast beta EEG power. To further characterize our genetic findings, we examined the functional and clinical/behavioral significance of GWAS variants. Ten correlated single-nucleotide polymorphisms (SNPs) (r2>0.9) located in an intergenic region on chromosome 3q26 were associated with fast beta EEG power at P<5 × 10-8. The most significantly associated SNP, rs11720469 (β: -0.124; P<4.5 × 10-9), is also an expression quantitative trait locus for BCHE (butyrylcholinesterase), expressed in thalamus tissue. Four of the genome-wide SNPs were also associated with Diagnostic and Statistical Manual of Mental Disorders Alcohol Dependence in COGA AA families, and two (rs13093097, rs7428372) were replicated in an independent AA sample (Gelernter et al.). Analyses in the AA adolescent/young adult (offspring from COGA families) subsample indicated association of rs11720469 with heavy episodic drinking (frequency of consuming 5+ drinks within 24 h). Converging findings presented in this study provide support for the role of genetic variants within 3q26 in neural and behavioral disinhibition. These novel genetic findings highlight the importance of including AA populations in genetics research on SUDs and the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.
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Affiliation(s)
- J L Meyers
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - J Zhang
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - J C Wang
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - J Su
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - S I Kuo
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
| | - M Kapoor
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - L Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - S Bertelsen
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - D Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - J E Salvatore
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - C Kamarajan
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - D Chorlian
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - A Agrawal
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - L Almasy
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - L Bauer
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - K K Bucholz
- Department of Psychiatry, Washington University School of Medicine in St Louis, St Louis, MO, USA
| | - G Chan
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - V Hesselbrock
- Department of Psychiatry, University of Connecticut School of Medicine, Farmington, CT, USA
| | - L Koganti
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - J Kramer
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - S Kuperman
- Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa City, IA, USA
| | - N Manz
- Department of Physics, The College of Wooster, Wooster, OH, USA
| | - A Pandey
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - M Seay
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
| | - D Scott
- Collaborative Alcohol Research Center, Howard University College of Medicine, Washington, DC, USA
| | - R E Taylor
- Collaborative Alcohol Research Center, Howard University College of Medicine, Washington, DC, USA
| | - D M Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, VA, USA
- Virginia Institute of Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - H J Edenberg
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - A Goate
- Department of Neuroscience, Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - T Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - B Porjesz
- Department of Psychiatry, State University of New York Downstate Medical Center, Brooklyn, NY, USA
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12
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Ghouse J, Skov MW, Bigseth RS, Ahlberg G, Kanters JK, Olesen MS. Distinguishing pathogenic mutations from background genetic noise in cardiology: The use of large genome databases for genetic interpretation. Clin Genet 2017; 93:459-466. [PMID: 28589536 DOI: 10.1111/cge.13066] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2017] [Revised: 05/31/2017] [Accepted: 06/01/2017] [Indexed: 12/15/2022]
Abstract
Advances in clinical genetic testing have led to increased insight into the human genome, including how challenging it is to interpret rare genetic variation. In some cases, the ability to detect genetic mutations exceeds the ability to understand their clinical impact, limiting the advantage of these technologies. Obstacles in genomic medicine are many and include: understanding the level of certainty/uncertainty behind pathogenicity determination, the numerous different variant interpretation-guidelines used by clinical laboratories, delivering the certain or uncertain result to the patient, helping patients evaluate medical decisions in light of uncertainty regarding the consequence of the findings. Through publication of large publicly available exome/genome databases, researchers and physicians are now able to highlight dubious variants previously associated with different cardiac traits. Also, continuous efforts through data sharing, international collaborative efforts to develop disease-gene-specific guidelines, and computational analyses using large data, will indubitably assist in better variant interpretation and classification. This article discusses the current, and quickly changing, state of variant interpretation resources within cardiovascular genetic research, e.g., publicly available databases and ways of how cardiovascular genetic counselors and geneticists can aid in improving variant interpretation in cardiology.
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Affiliation(s)
- J Ghouse
- Laboratory of Molecular Cardiology, Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - M W Skov
- Laboratory of Molecular Cardiology, Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - R S Bigseth
- Laboratory of Molecular Cardiology, Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - G Ahlberg
- Laboratory of Molecular Cardiology, Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - J K Kanters
- Laboratory of Experimental Cardiology, Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - M S Olesen
- Laboratory of Molecular Cardiology, Department of Cardiology, The Heart Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
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13
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Randolph TC, Broderick S, Shaw LK, Chiswell K, Mentz RJ, Kutyifa V, Velazquez EJ, Gilliam FR, Thomas KL. Race and Sex Differences in QRS Interval and Associated Outcome Among Patients with Left Ventricular Systolic Dysfunction. J Am Heart Assoc 2017; 6:JAHA.116.004381. [PMID: 28320746 PMCID: PMC5523998 DOI: 10.1161/jaha.116.004381] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background Prolonged QRS duration is associated with increased mortality among heart failure patients, but race or sex differences in QRS duration and associated effect on outcomes are unknown. Methods and Results We investigated QRS duration and morphology among 2463 black and white patients with heart failure and left ventricular ejection fraction ≤35% who underwent coronary angiography and 12‐lead electrocardiography at Duke University Hospital from 1995 through 2011. We used multivariable Cox regression models to assess the relationship between QRS duration and all‐cause mortality and investigate race‐QRS and sex‐QRS duration interaction. Median QRS duration was 105 ms (interquartile range [IQR], 92–132) with variation by race and sex (P<0.001). QRS duration was longest in white men (111 ms; IQR, 98–139) followed by white women (108 ms; IQR, 92–140), black men (100 ms; IQR, 91–120), and black women (94 ms; IQR, 86–118). Left bundle branch block was more common in women than men (24% vs 14%) and in white (21%) versus black individuals (12%). In black patients, there was a 16% increase in risk of mortality for every 10 ms increase in QRS duration up to 112 ms (hazard ratio, 1.16; 95% CI, 1.07, 1.25) that was not present among white patients (interaction, P=0.06). Conclusions Black individuals with heart failure had a shorter QRS duration and more often had non‐left bundle branch block morphology than white patients. Women had left bundle branch block more commonly than men. Among black patients, modest QRS prolongation was associated with increased mortality.
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Affiliation(s)
- Tiffany C Randolph
- Duke Clinical Research Institute, Durham, NC .,Department of Medicine, Duke University School of Medicine, Durham, NC
| | | | | | | | - Robert J Mentz
- Duke Clinical Research Institute, Durham, NC.,Department of Medicine, Duke University School of Medicine, Durham, NC
| | | | - Eric J Velazquez
- Department of Medicine, Duke University School of Medicine, Durham, NC
| | | | - Kevin L Thomas
- Duke Clinical Research Institute, Durham, NC.,Department of Medicine, Duke University School of Medicine, Durham, NC
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14
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Smith R, Thayer JF, Khalsa SS, Lane RD. The hierarchical basis of neurovisceral integration. Neurosci Biobehav Rev 2017; 75:274-296. [PMID: 28188890 DOI: 10.1016/j.neubiorev.2017.02.003] [Citation(s) in RCA: 262] [Impact Index Per Article: 37.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2016] [Revised: 01/31/2017] [Accepted: 02/03/2017] [Indexed: 02/07/2023]
Abstract
The neurovisceral integration (NVI) model was originally proposed to account for observed relationships between peripheral physiology, cognitive performance, and emotional/physical health. This model has also garnered a considerable amount of empirical support, largely from studies examining cardiac vagal control. However, recent advances in functional neuroanatomy, and in computational neuroscience, have yet to be incorporated into the NVI model. Here we present an updated/expanded version of the NVI model that incorporates these advances. Based on a review of studies of structural/functional anatomy, we first describe an eight-level hierarchy of nervous system structures, and the contribution that each level plausibly makes to vagal control. Second, we review recent work on a class of computational models of brain function known as "predictive coding" models. We illustrate how the computational dynamics of these models, when implemented within our proposed vagal control hierarchy, can increase understanding of the relationship between vagal control and both cognitive performance and emotional/physical health. We conclude by discussing novel implications of this updated NVI model for future research.
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Affiliation(s)
- Ryan Smith
- Department of Psychiatry, University of Arizona, 1501 N. Campbell Ave, Tucson, AZ 85724-5002, United States.
| | - Julian F Thayer
- Department of Psychology, Ohio State University, Columbus, OH, United States
| | - Sahib S Khalsa
- Laureate Institute for Brain Research, Tulsa, OK, United States; University of Tulsa, Oxley College of Health Sciences, Tulsa, OK, United States
| | - Richard D Lane
- Department of Psychiatry, University of Arizona, 1501 N. Campbell Ave, Tucson, AZ 85724-5002, United States
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15
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Evans DS, Avery CL, Nalls MA, Li G, Barnard J, Smith EN, Tanaka T, Butler AM, Buxbaum SG, Alonso A, Arking DE, Berenson GS, Bis JC, Buyske S, Carty CL, Chen W, Chung MK, Cummings SR, Deo R, Eaton CB, Fox ER, Heckbert SR, Heiss G, Hindorff LA, Hsueh WC, Isaacs A, Jamshidi Y, Kerr KF, Liu F, Liu Y, Lohman KK, Magnani JW, Maher JF, Mehra R, Meng YA, Musani SK, Newton-Cheh C, North KE, Psaty BM, Redline S, Rotter JI, Schnabel RB, Schork NJ, Shohet RV, Singleton AB, Smith JD, Soliman EZ, Srinivasan SR, Taylor HA, Van Wagoner DR, Wilson JG, Young T, Zhang ZM, Zonderman AB, Evans MK, Ferrucci L, Murray SS, Tranah GJ, Whitsel EA, Reiner AP, Sotoodehnia N. Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans. Hum Mol Genet 2016; 25:4350-4368. [PMID: 27577874 PMCID: PMC5291202 DOI: 10.1093/hmg/ddw284] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2016] [Revised: 08/03/2016] [Accepted: 08/19/2016] [Indexed: 12/14/2022] Open
Abstract
The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 × 10-14) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 × 10-4). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 × 10-8) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 × 10-9). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 × 10-7), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS-SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved.
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Affiliation(s)
- Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA .
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Guo Li
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - John Barnard
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Erin N Smith
- Department of Pediatrics and Rady Children's Hospital, University of California at San Diego, School of Medicine, La Jolla, CA, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Anne M Butler
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Sarah G Buxbaum
- Center of Excellence in Minority Health and Health Disparities, Jackson State University, Jackson, MS, USA
- Department of Epidemiology and Biostatistics, Jackson State University School of Public Health (Initiative), Jackson, MS, USA
| | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Gerald S Berenson
- Department of Medicine and Cardiology, Tulane University, New Orleans, LA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Steven Buyske
- Department of Statistics and Biostatistics and Department of Genetics, Rutgers University, Piscataway, NJ, USA
| | - Cara L Carty
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Mina K Chung
- Department of Cardiovascular Medicine, Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Cleveland Clinic Lerner College of Medicine of Case Western Reserve University, Cleveland, OH, USA
| | - Steven R Cummings
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Rajat Deo
- Division of Cardiovascular Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Charles B Eaton
- Departments of Family Medicine and Epidemiology, Alpert Medical School, Brown University, Providence, RI, USA
| | - Ervin R Fox
- Department of Medicine, Division of Cardiovascular Disease, University of Mississippi Medical Center, Jackson, MS, USA
| | - Susan R Heckbert
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
| | - Gerardo Heiss
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Lucia A Hindorff
- National Institutes of Health, National Human Genome Research Institute, Office of Population Genomics, Bethesda, MD, USA
| | - Wen-Chi Hsueh
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Phoenix, AZ, USA
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- CARIM School for Cardiovascular Diseases, Maastricht Centre for Systems Biology (MaCSBio), Dept. of Biochemistry, Maastricht University, Maastricht, the Netherlands
| | - Yalda Jamshidi
- Cardiogenetics Lab, Institute of Cardiovascular and Cell Sciences, St George's University of London, UK
| | - Kathleen F Kerr
- Department of Biostatistics, School of Public Health, University of Washington, Seattle, WA, USA
| | - Felix Liu
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC, USA
| | - Kurt K Lohman
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University, Winston-Salem, NC, USA
| | - Jared W Magnani
- Department of Medicine, Division of Cardiology, University of Pittsburgh Medical Center Heart and Vascular Institute, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joseph F Maher
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Reena Mehra
- Program for Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yan A Meng
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Solomon K Musani
- Cardiovascular Research Center and Center for Human Genetic Research, Massachusetts General Hospital and Harvard Medical School, Boston,MA, USA
| | - Christopher Newton-Cheh
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA
- Department of Medicine, Division of Sleep Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Susan Redline
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Departments of Medicine and Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jerome I Rotter
- University Heart Center Hamburg and German Center for Cardiovascular Research, Hamburg, Germany
| | | | - Nicholas J Schork
- Center for Cardiovascular Research, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI, USA
| | - Ralph V Shohet
- Department of Cellular and Molecular Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jonathan D Smith
- Epidemiological Cardiology Research Center (EPICARE), Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Elsayed Z Soliman
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Herman A Taylor
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - David R Van Wagoner
- Department of Molecular Cardiology, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | - James G Wilson
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Taylor Young
- Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Zhu-Ming Zhang
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Alan B Zonderman
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Michele K Evans
- Department of Pathology, University of California San Diego, La Jolla, CA, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Sarah S Murray
- Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Gregory J Tranah
- California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
- Membership of the CHARGE QRS Consortium is provided in the acknowledgements and
| | - Alex P Reiner
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Nona Sotoodehnia
- Department of Epidemiology, University of Washington, Seattle, WA, USA .
- Division of Cardiology, University of Washington, Seattle, WA, USA
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16
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Duan G, Han C, Wang Q, Guo S, Zhang Y, Ying Y, Huang P, Zhang L, Macala L, Shah P, Zhang M, Li N, Dib-Hajj SD, Waxman SG, Zhang X. A SCN10A SNP biases human pain sensitivity. Mol Pain 2016; 12:12/0/1744806916666083. [PMID: 27590072 PMCID: PMC5011395 DOI: 10.1177/1744806916666083] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2016] [Accepted: 07/19/2016] [Indexed: 12/19/2022] Open
Abstract
Background: Nav1.8 sodium channels, encoded by SCN10A, are preferentially expressed in nociceptive neurons and play an important role in human pain. Although rare gain-of-function variants in SCN10A have been identified in individuals with painful peripheral neuropathies, whether more common variants in SCN10A can have an effect at the channel level and at the dorsal root ganglion, neuronal level leading to a pain disorder or an altered normal pain threshold has not been determined. Results: Candidate single nucleotide polymorphism association approach together with experimental pain testing in human subjects was used to explore possible common SCN10A missense variants that might affect human pain sensitivity. We demonstrated an association between rs6795970 (G > A; p.Ala1073Val) and higher thresholds for mechanical pain in a discovery cohort (496 subjects) and confirmed it in a larger replication cohort (1005 female subjects). Functional assessments showed that although the minor allele shifts channel activation by −4.3 mV, a proexcitatory attribute, it accelerates inactivation, an antiexcitatory attribute, with the net effect being reduced repetitive firing of dorsal root ganglion neurons, consistent with lower mechanical pain sensitivity. Conclusions: At the association and mechanistic levels, the SCN10A single nucleotide polymorphism rs6795970 biases human pain sensitivity.
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Affiliation(s)
- Guangyou Duan
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China Department of Anesthesiology, Xinqiao Hospital, Third Military Medical University, Chongqing, P.R. China
| | - Chongyang Han
- Department of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA Rehabilitation Research Center, Veterans' Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Qingli Wang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China Department of Anesthesiology, Wuhan General Hospital of Guangzhou Military, Wuhan, P.R. China
| | - Shanna Guo
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Yuhao Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Ying Ying
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Penghao Huang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Li Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Lawrence Macala
- Department of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA Rehabilitation Research Center, Veterans' Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Palak Shah
- Department of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA Rehabilitation Research Center, Veterans' Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Mi Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Ningbo Li
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
| | - Sulayman D Dib-Hajj
- Department of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA Rehabilitation Research Center, Veterans' Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Stephen G Waxman
- Department of Neurology and Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, CT, USA Rehabilitation Research Center, Veterans' Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Xianwei Zhang
- Department of Anesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, P.R. China
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17
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Abstract
Genome-wide association studies (GWASs) have revolutionized the search for genetic variants regulating resting heart rate. In the last 10years, GWASs have led to the identification of at least 21 novel heart rate loci. These discoveries have provided valuable insights into the mechanisms and pathways that regulate heart rate and link heart rate to cardiovascular morbidity and mortality. GWASs capture majority of genetic variation in a population sample by utilizing high-throughput genotyping chips measuring genotypes for up to several millions of SNPs across the genome in thousands of individuals. This allows the identification of the strongest heart rate associated signals at genome-wide level. While GWASs provide robust statistical evidence of the association of a given genetic locus with heart rate, they are only the starting point for detailed follow-up studies to locate the causal variants and genes and gain further insights into the biological mechanisms underlying the observed associations.
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Affiliation(s)
- Tuomas O Kilpeläinen
- The Novo Nordisk Foundation center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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18
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Antzelevitch C, Patocskai B. Brugada Syndrome: Clinical, Genetic, Molecular, Cellular, and Ionic Aspects. Curr Probl Cardiol 2016; 41:7-57. [PMID: 26671757 PMCID: PMC4737702 DOI: 10.1016/j.cpcardiol.2015.06.002] [Citation(s) in RCA: 75] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Brugada syndrome (BrS) is an inherited cardiac arrhythmia syndrome first described as a new clinical entity in 1992. Electrocardiographically characterized by distinct coved type ST segment elevation in the right-precordial leads, the syndrome is associated with a high risk for sudden cardiac death in young adults, and less frequently in infants and children. The electrocardiographic manifestations of BrS are often concealed and may be unmasked or aggravated by sodium channel blockers, a febrile state, vagotonic agents, as well as by tricyclic and tetracyclic antidepressants. An implantable cardioverter defibrillator is the most widely accepted approach to therapy. Pharmacologic therapy is designed to produce an inward shift in the balance of currents active during the early phases of the right ventricular action potential (AP) and can be used to abort electrical storms or as an adjunct or alternative to device therapy when use of an implantable cardioverter defibrillator is not possible. Isoproterenol, cilostazol, and milrinone boost calcium channel current and drugs like quinidine, bepridil, and the Chinese herb extract Wenxin Keli inhibit the transient outward current, acting to diminish the AP notch and thus to suppress the substrate and trigger for ventricular tachycardia or fibrillation. Radiofrequency ablation of the right ventricular outflow tract epicardium of patients with BrS has recently been shown to reduce arrhythmia vulnerability and the electrocardiographic manifestation of the disease, presumably by destroying the cells with more prominent AP notch. This review provides an overview of the clinical, genetic, molecular, and cellular aspects of BrS as well as the approach to therapy.
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Affiliation(s)
| | - Bence Patocskai
- Masonic Medical Research Laboratory, Utica, NY 13501
- Department of Pharmacology & Pharmacotherapy, University of Szeged, Szeged, Hungary
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19
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Wells A, Kopp N, Xu X, O'Brien DR, Yang W, Nehorai A, Adair-Kirk TL, Kopan R, Dougherty JD. The anatomical distribution of genetic associations. Nucleic Acids Res 2015; 43:10804-20. [PMID: 26586807 PMCID: PMC4678833 DOI: 10.1093/nar/gkv1262] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2015] [Accepted: 11/04/2015] [Indexed: 01/13/2023] Open
Abstract
Deeper understanding of the anatomical intermediaries for disease and other complex genetic traits is essential to understanding mechanisms and developing new interventions. Existing ontology tools provide functional, curated annotations for many genes and can be used to develop mechanistic hypotheses; yet information about the spatial expression of genes may be equally useful in interpreting results and forming novel hypotheses for a trait. Therefore, we developed an approach for statistically testing the relationship between gene expression across the body and sets of candidate genes from across the genome. We validated this tool and tested its utility on three applications. First, we show that the expression of genes in associated loci from GWA studies implicates specific tissues for 57 out of 98 traits. Second, we tested the ability of the tool to identify novel relationships between gene expression and phenotypes. Specifically, we experimentally confirmed an underappreciated prediction highlighted by our tool: that white blood cell count--a quantitative trait of the immune system--is genetically modulated by genes expressed in the skin. Finally, using gene lists derived from exome sequencing data, we show that human genes under selective constraint are disproportionately expressed in nervous system tissues.
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Affiliation(s)
- Alan Wells
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nathan Kopp
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Xiaoxiao Xu
- The Preston M. Green Department of Electrical and Systems Engineering, Washington University, St. Louis, MO 63130, USA
| | - David R O'Brien
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Wei Yang
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Arye Nehorai
- The Preston M. Green Department of Electrical and Systems Engineering, Washington University, St. Louis, MO 63130, USA
| | - Tracy L Adair-Kirk
- Department of Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Raphael Kopan
- Division of Developmental Biology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - J D Dougherty
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
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20
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Dumitrescu L, Restrepo NA, Goodloe R, Boston J, Farber-Eger E, Pendergrass SA, Bush WS, Crawford DC. Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry. BioData Min 2015; 8:35. [PMID: 26566401 PMCID: PMC4642611 DOI: 10.1186/s13040-015-0068-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2014] [Accepted: 11/02/2015] [Indexed: 01/13/2023] Open
Abstract
Background Racial/ethnic differences for commonly measured clinical variables are well documented, and it has been postulated that population-specific genetic factors may play a role. The genetic heterogeneity of admixed populations, such as African Americans, provides a unique opportunity to identify genomic regions and variants associated with the clinical variability observed for diseases and traits across populations. Method To begin a systematic search for these population-specific genomic regions at the phenome-wide scale, we determined the relationship between global genetic ancestry, specifically European and African ancestry, and clinical variables measured in a population of African Americans from BioVU, Vanderbilt University’s biorepository linked to de-identified electronic medical records (EMRs) as part of the Epidemiologic Architecture using Genomics and Epidemiology (EAGLE) study. Through billing (ICD-9) codes, procedure codes, labs, and clinical notes, 36 common clinical and laboratory variables were mined from the EMR, including body mass index (BMI), kidney traits, lipid levels, blood pressure, and electrocardiographic measurements. A total of 15,863 DNA samples from non-European Americans were genotyped on the Illumina Metabochip containing ~200,000 variants, of which 11,166 were from African Americans. Tests of association were performed to examine associations between global ancestry and the phenotype of interest. Results Increased European ancestry, and conversely decreased African ancestry, was most strongly correlated with an increase in QRS duration, consistent with previous observations that African Americans tend to have shorter a QRS duration compared with European Americans. Despite known racial/ethnic disparities in blood pressure, European and African ancestry was neither associated with diastolic nor systolic blood pressure measurements. Conclusion Collectively, these results suggest that this clinical population can be used to identify traits in which population differences may be due, in part, to population-specific genetics. Electronic supplementary material The online version of this article (doi:10.1186/s13040-015-0068-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Logan Dumitrescu
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232 USA
| | - Nicole A Restrepo
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232 USA
| | - Robert Goodloe
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232 USA
| | - Jonathan Boston
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232 USA
| | - Eric Farber-Eger
- Center for Human Genetics Research, Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN 37232 USA
| | - Sarah A Pendergrass
- Center for Systems Genomics, Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802 USA
| | - William S Bush
- Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Suite 2527, Cleveland, OH 44106 USA
| | - Dana C Crawford
- Institute for Computational Biology, Department of Epidemiology and Biostatistics, Case Western Reserve University, Wolstein Research Building, 2103 Cornell Road, Suite 2527, Cleveland, OH 44106 USA
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21
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Veerman CC, Wilde AAM, Lodder EM. The cardiac sodium channel gene SCN5A and its gene product NaV1.5: Role in physiology and pathophysiology. Gene 2015; 573:177-87. [PMID: 26361848 DOI: 10.1016/j.gene.2015.08.062] [Citation(s) in RCA: 111] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2015] [Revised: 07/31/2015] [Accepted: 08/27/2015] [Indexed: 12/18/2022]
Abstract
The gene SCN5A encodes the main cardiac sodium channel NaV1.5. This channel predominates the cardiac sodium current, INa, which underlies the fast upstroke of the cardiac action potential. As such, it plays a crucial role in cardiac electrophysiology. Over the last 60years a tremendous amount of knowledge regarding its function at the electrophysiological and molecular level has been acquired. Furthermore, genetic studies have shown that mutations in SCN5A are associated with multiple cardiac diseases (e.g. Brugada syndrome, Long QT syndrome, conduction disease and cardiomyopathy), while genetic variation in the general population has been associated with differences in cardiac conduction and risk of arrhythmia through genome wide association studies. In this review we aim to give an overview of the current knowledge (and the gaps therein) on SCN5A and NaV1.5.
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Affiliation(s)
- Christiaan C Veerman
- Department of Clinical and Experimental Cardiology, Academic Medical Center, Amsterdam, The Netherlands
| | - Arthur A M Wilde
- Department of Clinical and Experimental Cardiology, Academic Medical Center, Amsterdam, The Netherlands.
| | - Elisabeth M Lodder
- Department of Clinical and Experimental Cardiology, Academic Medical Center, Amsterdam, The Netherlands.
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22
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Restrepo NA, Farber-Eger E, Goodloe R, Haines JL, Crawford DC. Extracting Primary Open-Angle Glaucoma from Electronic Medical Records for Genetic Association Studies. PLoS One 2015; 10:e0127817. [PMID: 26061293 PMCID: PMC4465698 DOI: 10.1371/journal.pone.0127817] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2014] [Accepted: 04/20/2015] [Indexed: 11/08/2022] Open
Abstract
Electronic medical records (EMRs) are being widely implemented for use in genetic and genomic studies. As a phenotypic rich resource, EMRs provide researchers with the opportunity to identify disease cohorts and perform genotype-phenotype association studies. The Epidemiologic Architecture for Genes Linked to Environment (EAGLE) study, as part of the Population Architecture using Genomics and Epidemiology (PAGE) I study, has genotyped more than 15,000 individuals of diverse genetic ancestry in BioVU, the Vanderbilt University Medical Center’s biorepository linked to a de-identified version of the EMR (EAGLE BioVU). Here we develop and deploy an algorithm utilizing data mining techniques to identify primary open-angle glaucoma (POAG) in African Americans from EAGLE BioVU for genetic association studies. The algorithm described here was designed using a combination of diagnostic codes, current procedural terminology billing codes, and free text searches to identify POAG status in situations where gold-standard digital photography cannot be accessed. The case algorithm identified 267 potential POAG subjects but underperformed after manual review with a positive predictive value of 51.6% and an accuracy of 76.3%. The control algorithm identified controls with a negative predictive value of 98.3%. Although the case algorithm requires more downstream manual review for use in large-scale studies, it provides a basis by which to extract a specific clinical subtype of glaucoma from EMRs in the absence of digital photographs.
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Affiliation(s)
- Nicole A. Restrepo
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Eric Farber-Eger
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University, Nashville, Tennessee, United States of America
| | - Jonathan L. Haines
- Department of Epidemiology & Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Dana C. Crawford
- Department of Epidemiology & Biostatistics, Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, United States of America
- * E-mail:
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23
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Patocskai B, Antzelevitch C. Novel Therapeutic Strategies for the Management of Ventricular Arrhythmias Associated with the Brugada Syndrome. Expert Opin Orphan Drugs 2015; 3:633-651. [PMID: 27559494 PMCID: PMC4993532 DOI: 10.1517/21678707.2015.1037280] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
INTRODUCTION Brugada syndrome (BrS) is an inherited cardiac arrhythmia syndrome characterized by prominent J waves appearing as distinct coved type ST segment elevation in the right precordial leads of the ECG. It is associated with a high risk for sudden cardiac death. AREAS COVERED We discuss 1) ECG manifestations of BrS which can be unmasked or aggravated by sodium channel blockers, febrile states, vagotonic agents, as well as tricyclic and tetracyclic antidepressants; 2) Genetic basis of BrS; 3) Ionic and cellular mechanisms underlying BrS; 4) Therapy involving devices including an implantable cardioverter defibrillator (ICD); 5) Therapy involving radiofrequency ablation; and 6) Therapy involving pharmacological therapy which is aimed at producing an inward shift in the balance of the currents active during phase 1 of the right ventricular action potential either by boosting calcium channel current (isoproterenol, cilostazol and milrinone) or by inhibition of transient outward current Ito (quinidine, bepridil and the Chinese herb extract Wenxin Keli). EXPERT OPINION This review provides an overview of the clinical and molecular aspects of BrS with a focus on approaches to therapy. Available data suggest that agents capable of inhibiting the transient outward current Ito can exert an ameliorative effect regardless of the underlying cause.
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Affiliation(s)
- Bence Patocskai
- Department of Pharmacology & Pharmacotherapy, University of Szeged, Szeged, Hungary
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24
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Jeff JM, Brown-Gentry K, Goodloe R, Ritchie MD, Denny JC, Kho AN, Armstrong LL, McClellan B, Mayo P, Allen M, Jin H, Gillani NB, Schnetz-Boutaud N, Dilks HH, Basford MA, Pacheco JA, Jarvik GP, Chisholm RL, Roden DM, Hayes MG, Crawford DC. Replication of SCN5A Associations with Electrocardio-graphic Traits in African Americans from Clinical and Epidemiologic Studies. EVOLUTIONARY COMPUTATION, MACHINE LEARNING AND DATA MINING IN BIOINFORMATICS. EVOBIO (CONFERENCE) 2015; 2014:939-951. [PMID: 25590050 PMCID: PMC4290789 DOI: 10.1007/978-3-662-45523-4_76] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
The NAv1.5 sodium channel α subunit is the predominant α-subunit expressed in the heart and is associated with cardiac arrhythmias. We tested five previously identified SCN5A variants (rs7374138, rs7637849, rs7637849, rs7629265, and rs11129796) for an association with PR interval and QRS duration in two unique study populations: the Third National Health and Nutrition Examination Survey (NHANES III, n= 552) accessed by the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) and a combined dataset (n= 455) from two biobanks linked to electronic medical records from Vanderbilt University (BioVU) and Northwestern University (NUgene) as part of the electronic Medical Records & Genomics (eMERGE) network. A meta-analysis including all three study populations (n~4,000) suggests that eight SCN5A associations were significant for both QRS duration and PR interval (p<5.0E-3) with little evidence for heterogeneity across the study populations. These results suggest that published SCN5A associations replicate across different study designs in a meta-analysis and represent an important first step in utility of multiple study designs for genetic studies and the identification/characterization of genetic variants associated with ECG traits in African-descent populations.
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Affiliation(s)
- Janina M. Jeff
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kristin Brown-Gentry
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Robert Goodloe
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Marylyn D. Ritchie
- Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA 16802, USA
| | - Joshua C. Denny
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
- Department of Biomedical Informatics, Vanderbilt University, Nashville, TN 37232, USA
| | - Abel N. Kho
- Division of General Internal Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Loren L. Armstrong
- Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Bob McClellan
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Ping Mayo
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Melissa Allen
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Hailing Jin
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Niloufar B. Gillani
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | | | - Holli H. Dilks
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
| | - Melissa A. Basford
- Office of Personalized Medicine, Vanderbilt University, Nashville, TN 37232, USA
| | - Jennifer A. Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Gail P. Jarvik
- University of Washington Medical Center, Seattle, WA 98195, USA
| | - Rex L. Chisholm
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Dan M. Roden
- Department of Medicine, Division of Clinical Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
- Office of Personalized Medicine, Vanderbilt University, Nashville, TN 37232, USA
- Department of Pharmacology, Vanderbilt University, Nashville, TN 37232, USA
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Dana C. Crawford
- Center for Human Genetics Research, Vanderbilt University, Nashville, TN 37232, USA
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Peprah E, Xu H, Tekola-Ayele F, Royal CD. Genome-wide association studies in Africans and African Americans: expanding the framework of the genomics of human traits and disease. Public Health Genomics 2014; 18:40-51. [PMID: 25427668 DOI: 10.1159/000367962] [Citation(s) in RCA: 59] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2014] [Accepted: 08/29/2014] [Indexed: 01/11/2023] Open
Abstract
Genomic research is one of the tools for elucidating the pathogenesis of diseases of global health relevance and paving the research dimension to clinical and public health translation. Recent advances in genomic research and technologies have increased our understanding of human diseases, genes associated with these disorders, and the relevant mechanisms. Genome-wide association studies (GWAS) have proliferated since the first studies were published several years ago and have become an important tool in helping researchers comprehend human variation and the role genetic variants play in disease. However, the need to expand the diversity of populations in GWAS has become increasingly apparent as new knowledge is gained about genetic variation. Inclusion of diverse populations in genomic studies is critical to a more complete understanding of human variation and elucidation of the underpinnings of complex diseases. In this review, we summarize the available data on GWAS in recent African ancestry populations within the western hemisphere (i.e. African Americans and peoples of the Caribbean) and continental African populations. Furthermore, we highlight ways in which genomic studies in populations of recent African ancestry have led to advances in the areas of malaria, HIV, prostate cancer, and other diseases. Finally, we discuss the advantages of conducting GWAS in recent African ancestry populations in the context of addressing existing and emerging global health conditions.
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Mutations in SCN10A are responsible for a large fraction of cases of Brugada syndrome. J Am Coll Cardiol 2014; 64:66-79. [PMID: 24998131 DOI: 10.1016/j.jacc.2014.04.032] [Citation(s) in RCA: 165] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2014] [Revised: 03/23/2014] [Accepted: 04/23/2014] [Indexed: 12/19/2022]
Abstract
BACKGROUND BrS is an inherited sudden cardiac death syndrome. Less than 35% of BrS probands have genetically identified pathogenic variants. Recent evidence has implicated SCN10A, a neuronal sodium channel gene encoding Nav1.8, in the electrical function of the heart. OBJECTIVES The purpose of this study was to test the hypothesis that SCN10A variants contribute to the development of Brugada syndrome (BrS). METHODS Clinical analysis and direct sequencing of BrS susceptibility genes were performed for 150 probands and family members as well as >200 healthy controls. Expression and coimmunoprecipitation studies were performed to functionally characterize the putative pathogenic mutations. RESULTS We identified 17 SCN10A mutations in 25 probands (20 male and 5 female); 23 of the 25 probands (92.0%) displayed overlapping phenotypes. SCN10A mutations were found in 16.7% of BrS probands, approaching our yield for SCN5A mutations (20.1%). Patients with BrS who had SCN10A mutations were more symptomatic and displayed significantly longer PR and QRS intervals compared with SCN10A-negative BrS probands. The majority of mutations localized to the transmembrane-spanning regions. Heterologous coexpression of wild-type (WT) SCN10A with WT-SCN5A in HEK cells caused a near doubling of sodium channel current compared with WT-SCN5A alone. In contrast, coexpression of SCN10A mutants (R14L and R1268Q) with WT-SCN5A caused a 79.4% and 84.4% reduction in sodium channel current, respectively. The coimmunoprecipitation studies provided evidence for the coassociation of Nav1.8 and Nav1.5 in the plasma membrane. CONCLUSIONS Our study identified SCN10A as a major susceptibility gene for BrS, thus greatly enhancing our ability to genotype and risk stratify probands and family members.
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Rasmussen-Torvik LJ, Stallings SC, Gordon AS, Almoguera B, Basford MA, Bielinski SJ, Brautbar A, Brilliant MH, Carrell DS, Connolly JJ, Crosslin DR, Doheny KF, Gallego CJ, Gottesman O, Kim DS, Leppig KA, Li R, Lin S, Manzi S, Mejia AR, Pacheco JA, Pan V, Pathak J, Perry CL, Peterson JF, Prows CA, Ralston J, Rasmussen LV, Ritchie MD, Sadhasivam S, Scott SA, Smith M, Vega A, Vinks AA, Volpi S, Wolf WA, Bottinger E, Chisholm RL, Chute CG, Haines JL, Harley JB, Keating B, Holm IA, Kullo IJ, Jarvik GP, Larson EB, Manolio T, McCarty CA, Nickerson DA, Scherer SE, Williams MS, Roden DM, Denny JC. Design and anticipated outcomes of the eMERGE-PGx project: a multicenter pilot for preemptive pharmacogenomics in electronic health record systems. Clin Pharmacol Ther 2014; 96:482-9. [PMID: 24960519 PMCID: PMC4169732 DOI: 10.1038/clpt.2014.137] [Citation(s) in RCA: 181] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 06/13/2014] [Indexed: 11/09/2022]
Abstract
We describe here the design and initial implementation of the eMERGE-PGx project. eMERGE-PGx, a partnership of the eMERGE and PGRN consortia, has three objectives : 1) Deploy PGRNseq, a next-generation sequencing platform assessing sequence variation in 84 proposed pharmacogenes, in nearly 9,000 patients likely to be prescribed drugs of interest in a 1–3 year timeframe across several clinical sites; 2) Integrate well-established clinically-validated pharmacogenetic genotypes into the electronic health record with associated clinical decision support and assess process and clinical outcomes of implementation; and 3) Develop a repository of pharmacogenetic variants of unknown significance linked to a repository of EHR-based clinical phenotype data for ongoing pharmacogenomics discovery. We describe site-specific project implementation and anticipated products, including genetic variant and phenotype data repositories, novel variant association studies, clinical decision support modules, clinical and process outcomes, approaches to manage incidental findings, and patient and clinician education methods.
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Affiliation(s)
- L J Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - S C Stallings
- Vanderbilt Institute for Clinical and Translational Research, Nashville, Tennessee, USA
| | - A S Gordon
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - B Almoguera
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - M A Basford
- Vanderbilt Institute for Clinical and Translational Research, Nashville, Tennessee, USA
| | - S J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - A Brautbar
- Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - M H Brilliant
- Center for Human Genetics, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - D S Carrell
- Group Health Research Institute, Seattle, Washington, USA
| | - J J Connolly
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - D R Crosslin
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - K F Doheny
- Center for Inherited Disease Research, Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - C J Gallego
- Division of Medical Genetics, University of Washington, Seattle, Washington, USA
| | - O Gottesman
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - D S Kim
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - K A Leppig
- Group Health Research Institute, Seattle, Washington, USA
| | - R Li
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - S Lin
- Biomedical Informatics Research Center, Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
| | - S Manzi
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - A R Mejia
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - J A Pacheco
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - V Pan
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - J Pathak
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - C L Perry
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA
| | - J F Peterson
- Department of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - C A Prows
- 1] Division Human Genetics, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA [2] Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - J Ralston
- Group Health Research Institute, Seattle, Washington, USA
| | - L V Rasmussen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - M D Ritchie
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, State College, Pennsylvania, USA
| | - S Sadhasivam
- 1] Department of Anesthesia, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA [2] Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA
| | - S A Scott
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - M Smith
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - A Vega
- Mount Sinai Faculty Practice Associates Primary Care Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - A A Vinks
- 1] Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA [2] Division of Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, USA
| | - S Volpi
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - W A Wolf
- 1] Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA [2] Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - E Bottinger
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - R L Chisholm
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - C G Chute
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - J L Haines
- Center for Human Genetics Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - J B Harley
- 1] Department of Pediatrics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA [2] Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, Ohio, USA [3] US Department of Veterans Affairs Medical Center, Cincinnati, Ohio, USA
| | - B Keating
- Center for Applied Genomics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - I A Holm
- 1] Division of Genetics and Genomics, Boston Children's Hospital, Boston, Massachusetts, USA [2] Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA [3] The Manton Center for Orphan Disease Research, Boston Children's Hospital, Boston, Massachusetts, USA
| | - I J Kullo
- Division of Cardiovascular Diseases, Mayo Clinic, Rochester, Minnesota, USA
| | - G P Jarvik
- Division of Medical Genetics, University of Washington, Seattle, Washington, USA
| | - E B Larson
- Group Health Research Institute, Seattle, Washington, USA
| | - T Manolio
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - C A McCarty
- Essentia Institute of Rural Health, Duluth, Minnesota, USA
| | - D A Nickerson
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA
| | - S E Scherer
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - M S Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, Pennsylvania, USA
| | - D M Roden
- 1] Department of Pharmacology, Vanderbilt University School of Medicine, Nashville, Tennessee, USA [2] Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - J C Denny
- 1] Department of Biomedical Informatics and Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA [2] Department of Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
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Crawford DC, Crosslin DR, Tromp G, Kullo IJ, Kuivaniemi H, Hayes MG, Denny JC, Bush WS, Haines JL, Roden DM, McCarty CA, Jarvik GP, Ritchie MD. eMERGEing progress in genomics-the first seven years. Front Genet 2014; 5:184. [PMID: 24987407 PMCID: PMC4060012 DOI: 10.3389/fgene.2014.00184] [Citation(s) in RCA: 67] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2014] [Accepted: 05/30/2014] [Indexed: 12/15/2022] Open
Abstract
The electronic MEdical Records & GEnomics (eMERGE) network was established in 2007 by the National Human Genome Research Institute (NHGRI) of the National Institutes of Health (NIH) in part to explore the utility of electronic medical records (EMRs) in genome science. The initial focus was on discovery primarily using the genome-wide association paradigm, but more recently, the network has begun evaluating mechanisms to implement new genomic information coupled to clinical decision support into EMRs. Herein, we describe this evolution including the development of the individual and merged eMERGE genomic datasets, the contribution the network has made toward genomic discovery and human health, and the steps taken toward the next generation genotype-phenotype association studies and clinical implementation.
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Affiliation(s)
- Dana C Crawford
- Center for Human Genetics Research, Vanderbilt University Nashville, TN, USA ; Department of Molecular Physiology and Biophysics, Vanderbilt University Nashville, TN, USA
| | - David R Crosslin
- Medical Genetics, Department of Medicine, School of Medicine, University of Washington Seattle, WA, USA ; Department of Genome Sciences, University of Washington Seattle, WA, USA
| | - Gerard Tromp
- The Sigfried and Janet Weis Center for Research, Geisinger Health System Danville, PA, USA
| | - Iftikhar J Kullo
- Division of Cardiovascular Diseases and the Gonda Vascular Center, Mayo Clinic Rochester, MN, USA
| | - Helena Kuivaniemi
- The Sigfried and Janet Weis Center for Research, Geisinger Health System Danville, PA, USA
| | - M Geoffrey Hayes
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Feinberg School of Medicine, Northwestern University Chicago, IL, USA
| | - Joshua C Denny
- Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA ; Department of Medicine, Vanderbilt University Nashville, TN, USA
| | - William S Bush
- Center for Human Genetics Research, Vanderbilt University Nashville, TN, USA ; Department of Biomedical Informatics, Vanderbilt University Nashville, TN, USA
| | - Jonathan L Haines
- Department of Epidemiology and Biostatistics, Case Western Reserve University Cleveland, OH, USA ; Institute for Computational Biology, Case Western Reserve University Cleveland, OH, USA
| | - Dan M Roden
- Department of Medicine, Vanderbilt University Nashville, TN, USA ; Department of Pharmacology, Vanderbilt University Nashville, TN, USA
| | | | - Gail P Jarvik
- Medical Genetics, Department of Medicine, School of Medicine, University of Washington Seattle, WA, USA ; Department of Genome Sciences, University of Washington Seattle, WA, USA
| | - Marylyn D Ritchie
- Department of Biochemistry and Molecular Biology, Pennsylvania State University University Park, PA, USA ; Center for Systems Genomics, Pennsylvania State University University Park, PA, USA
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Secondary use of clinical data: the Vanderbilt approach. J Biomed Inform 2014; 52:28-35. [PMID: 24534443 DOI: 10.1016/j.jbi.2014.02.003] [Citation(s) in RCA: 168] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2013] [Revised: 12/21/2013] [Accepted: 02/04/2014] [Indexed: 01/04/2023]
Abstract
The last decade has seen an exponential growth in the quantity of clinical data collected nationwide, triggering an increase in opportunities to reuse the data for biomedical research. The Vanderbilt research data warehouse framework consists of identified and de-identified clinical data repositories, fee-for-service custom services, and tools built atop the data layer to assist researchers across the enterprise. Providing resources dedicated to research initiatives benefits not only the research community, but also clinicians, patients and institutional leadership. This work provides a summary of our approach in the secondary use of clinical data for research domain, including a description of key components and a list of lessons learned, designed to assist others assembling similar services and infrastructure.
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Abstract
Proper generation and conduction of the cardiac electrical impulse is essential for the continuous coordinated contraction of the heart. Dysregulation of cardiac electrical function may lead to cardiac arrhythmias, which constitute a huge medical and social burden. Identifying the genetic factors underlying cardiac electrical activity serves the double purpose of allowing the early identification of individuals at risk for arrhythmia and discovering new potential therapeutic targets for prevention. The aim of this review is to provide an overview of the genes and genetic loci linked thus far to cardiac electrical function and arrhythmia. These genes and loci have been primarily uncovered through studies on the familial rhythm disorders and through genome-wide association studies on electrocardiographic parameters in large sets of the general population. An overview of all genes and loci with their respective effect is given.
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Affiliation(s)
- Elisabeth M Lodder
- Department of Clinical and Experimental Cardiology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands. Tel.: +31 20 5665962; Fax: +31 20 6976177;
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