10 results on '"Michael Feolo"'
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2. Identifying Datasets for Cross-Study Analysis in dbGaP using PhenX
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Huaqin Pan, Vesselina Bakalov, Lisa Cox, Michelle L. Engle, Stephen W. Erickson, Michael Feolo, Yuelong Guo, Wayne Huggins, Stephen Hwang, Masato Kimura, Michelle Krzyzanowski, Josh Levy, Michael Phillips, Ying Qin, David Williams, Erin M. Ramos, and Carol M. Hamilton
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Science - Abstract
Abstract Identifying relevant studies and harmonizing datasets are major hurdles for data reuse. Common Data Elements (CDEs) can help identify comparable study datasets and reduce the burden of retrospective data harmonization, but they have not been required, historically. The collaborative team at PhenX and dbGaP developed an approach to use PhenX variables as a set of CDEs to link phenotypic data and identify comparable studies in dbGaP. Variables were identified as either comparable or related, based on the data collection mode used to harmonize data across mapped datasets. We further added a CDE data field in the dbGaP data submission packet to indicate use of PhenX and annotate linkages in the future. Some 13,653 dbGaP variables from 521 studies were linked through PhenX variable mapping. These variable linkages have been made accessible for browsing and searching in the repository through dbGaP CDE-faceted search filter and the PhenX variable search tool. New features in dbGaP and PhenX enable investigators to identify variable linkages among dbGaP studies and reveal opportunities for cross-study analysis.
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- 2022
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3. GRAF-pop: A Fast Distance-Based Method To Infer Subject Ancestry from Multiple Genotype Datasets Without Principal Components Analysis
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Yumi Jin, Alejandro A. Schaffer, Michael Feolo, J. Bradley Holmes, and Brandi L. Kattman
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ancestry inference ,population structure ,admixture mapping ,GWAS ,barycentric coordinates ,Genetics ,QH426-470 - Abstract
Inferring subject ancestry using genetic data is an important step in genetic association studies, required for dealing with population stratification. It has become more challenging to infer subject ancestry quickly and accurately since large amounts of genotype data, collected from millions of subjects by thousands of studies using different methods, are accessible to researchers from repositories such as the database of Genotypes and Phenotypes (dbGaP) at the National Center for Biotechnology Information (NCBI). Study-reported populations submitted to dbGaP are often not harmonized across studies or may be missing. Widely-used methods for ancestry prediction assume that most markers are genotyped in all subjects, but this assumption is unrealistic if one wants to combine studies that used different genotyping platforms. To provide ancestry inference and visualization across studies, we developed a new method, GRAF-pop, of ancestry prediction that is robust to missing genotypes and allows researchers to visualize predicted population structure in color and in three dimensions. When genotypes are dense, GRAF-pop is comparable in quality and running time to existing ancestry inference methods EIGENSTRAT, FastPCA, and FlashPCA2, all of which rely on principal components analysis (PCA). When genotypes are not dense, GRAF-pop gives much better ancestry predictions than the PCA-based methods. GRAF-pop employs basic geometric and probabilistic methods; the visualized ancestry predictions have a natural geometric interpretation, which is lacking in PCA-based methods. Since February 2018, GRAF-pop has been successfully incorporated into the dbGaP quality control process to identify inconsistencies between study-reported and computationally predicted populations and to provide harmonized population values in all new dbGaP submissions amenable to population prediction, based on marker genotypes. Plots, produced by GRAF-pop, of summary population predictions are available on dbGaP study pages, and the software, is available at https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/Software.cgi.
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- 2019
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4. Quickly identifying identical and closely related subjects in large databases using genotype data.
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Yumi Jin, Alejandro A Schäffer, Stephen T Sherry, and Michael Feolo
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Medicine ,Science - Abstract
Genome-wide association studies (GWAS) usually rely on the assumption that different samples are not from closely related individuals. Detection of duplicates and close relatives becomes more difficult both statistically and computationally when one wants to combine datasets that may have been genotyped on different platforms. The dbGaP repository at the National Center of Biotechnology Information (NCBI) contains datasets from hundreds of studies with over one million samples. There are many duplicates and closely related individuals both within and across studies from different submitters. Relationships between studies cannot always be identified by the submitters of individual datasets. To aid in curation of dbGaP, we developed a rapid statistical method called Genetic Relationship and Fingerprinting (GRAF) to detect duplicates and closely related samples, even when the sets of genotyped markers differ and the DNA strand orientations are unknown. GRAF extracts genotypes of 10,000 informative and independent SNPs from genotype datasets obtained using different methods, and implements quick algorithms that enable it to find all of the duplicate pairs from more than 880,000 samples within and across dbGaP studies in less than two hours. In addition, GRAF uses two statistical metrics called All Genotype Mismatch Rate (AGMR) and Homozygous Genotype Mismatch Rate (HGMR) to determine subject relationships directly from the observed genotypes, without estimating probabilities of identity by descent (IBD), or kinship coefficients, and compares the predicted relationships with those reported in the pedigree files. We implemented GRAF in a freely available C++ program of the same name. In this paper, we describe the methods in GRAF and validate the usage of GRAF on samples from the dbGaP repository. Other scientists can use GRAF on their own samples and in combination with samples downloaded from dbGaP.
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- 2017
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5. HLA diversity in the 1000 genomes dataset.
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Pierre-Antoine Gourraud, Pouya Khankhanian, Nezih Cereb, Soo Young Yang, Michael Feolo, Martin Maiers, John D Rioux, Stephen Hauser, and Jorge Oksenberg
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Medicine ,Science - Abstract
The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation by sequencing at a level that should allow the genome-wide detection of most variants with frequencies as low as 1%. However, in the major histocompatibility complex (MHC), only the top 10 most frequent haplotypes are in the 1% frequency range whereas thousands of haplotypes are present at lower frequencies. Given the limitation of both the coverage and the read length of the sequences generated by the 1000 Genomes Project, the highly variable positions that define HLA alleles may be difficult to identify. We used classical Sanger sequencing techniques to type the HLA-A, HLA-B, HLA-C, HLA-DRB1 and HLA-DQB1 genes in the available 1000 Genomes samples and combined the results with the 103,310 variants in the MHC region genotyped by the 1000 Genomes Project. Using pairwise identity-by-descent distances between individuals and principal component analysis, we established the relationship between ancestry and genetic diversity in the MHC region. As expected, both the MHC variants and the HLA phenotype can identify the major ancestry lineage, informed mainly by the most frequent HLA haplotypes. To some extent, regions of the genome with similar genetic or similar recombination rate have similar properties. An MHC-centric analysis underlines departures between the ancestral background of the MHC and the genome-wide picture. Our analysis of linkage disequilibrium (LD) decay in these samples suggests that overestimation of pairwise LD occurs due to a limited sampling of the MHC diversity. This collection of HLA-specific MHC variants, available on the dbMHC portal, is a valuable resource for future analyses of the role of MHC in population and disease studies.
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- 2014
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6. Supplementing high-density SNP microarrays for additional coverage of disease-related genes: addiction as a paradigm.
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Scott F Saccone, Laura J Bierut, Elissa J Chesler, Peter W Kalivas, Caryn Lerman, Nancy L Saccone, George R Uhl, Chuan-Yun Li, Vivek M Philip, Howard J Edenberg, Stephen T Sherry, Michael Feolo, Robert K Moyzis, and Joni L Rutter
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Medicine ,Science - Abstract
Commercial SNP microarrays now provide comprehensive and affordable coverage of the human genome. However, some diseases have biologically relevant genomic regions that may require additional coverage. Addiction, for example, is thought to be influenced by complex interactions among many relevant genes and pathways. We have assembled a list of 486 biologically relevant genes nominated by a panel of experts on addiction. We then added 424 genes that showed evidence of association with addiction phenotypes through mouse QTL mappings and gene co-expression analysis. We demonstrate that there are a substantial number of SNPs in these genes that are not well represented by commercial SNP platforms. We address this problem by introducing a publicly available SNP database for addiction. The database is annotated using numeric prioritization scores indicating the extent of biological relevance. The scores incorporate a number of factors such as SNP/gene functional properties (including synonymy and promoter regions), data from mouse systems genetics and measures of human/mouse evolutionary conservation. We then used HapMap genotyping data to determine if a SNP is tagged by a commercial microarray through linkage disequilibrium. This combination of biological prioritization scores and LD tagging annotation will enable addiction researchers to supplement commercial SNP microarrays to ensure comprehensive coverage of biologically relevant regions.
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- 2009
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7. Database resources of the National Center for Biotechnology Information
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Eric W. Sayers, Tanya Barrett, Dennis A. Benson, Evan Bolton, Stephen H. Bryant, Kathi Canese, Vyacheslav Chetvernin, Deanna M. Church, Michael DiCuccio, Scott Federhen, Michael Feolo, Lewis Y. Geer, Wolfgang Helmberg, Yuri Kapustin, David Landsman, David J. Lipman, Zhiyong Lu, Thomas L. Madden, Tom Madej, Donna R. Maglott, Aron Marchler-Bauer, Vadim Miller, Ilene Mizrachi, James Ostell, Anna Panchenko, Kim D. Pruitt, Gregory D. Schuler, Edwin Sequeira, Stephen T. Sherry, Martin Shumway, Karl Sirotkin, Douglas Slotta, Alexandre Souvorov, Grigory Starchenko, Tatiana A. Tatusova, Lukas Wagner, Yanli Wang, W. John Wilbur, Eugene Yaschenko, and Jian Ye
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Internet ,0303 health sciences ,National Library of Medicine (U.S.) ,Computational Biology ,Information Storage and Retrieval ,Genome, Viral ,Articles ,United States ,3. Good health ,03 medical and health sciences ,0302 clinical medicine ,National Institutes of Health (U.S.) ,030220 oncology & carcinogenesis ,Databases, Genetic ,Genetics ,Animals ,Humans ,natural sciences ,Databases, Nucleic Acid ,Databases, Protein ,Algorithms ,Genome, Bacterial ,Software ,030304 developmental biology - Abstract
In addition to maintaining the GenBank® nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides analysis and retrieval resources for the data in GenBank and other biological data made available through the NCBI web site. NCBI resources include Entrez, the Entrez Programming Utilities, MyNCBI, PubMed, PubMed Central, Entrez Gene, the NCBI Taxonomy Browser, BLAST, BLAST Link (BLink), Electronic PCR, OrfFinder, Spidey, Splign, Reference Sequence, UniGene, HomoloGene, ProtEST, dbMHC, dbSNP, Cancer Chromosomes, Entrez Genomes and related tools, the Map Viewer, Model Maker, Evidence Viewer, Trace Archive, Sequence Read Archive, Retroviral Genotyping Tools, HIV-1/Human Protein Interaction Database, Gene Expression Omnibus, Entrez Probe, GENSAT, Online Mendelian Inheritance in Man, Online Mendelian Inheritance in Animals, the Molecular Modeling Database, the Conserved Domain Database, the Conserved Domain Architecture Retrieval Tool, Biosystems, Peptidome, Protein Clusters and the PubChem suite of small molecule databases. Augmenting many of the web applications are custom implementations of the BLAST program optimized to search specialized data sets. All these resources can be accessed through the NCBI home page at www.ncbi.nlm.nih.gov.
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- 2009
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8. The dbMHC microsatellite portal: a public resource for the storage and display of MHC microsatellite information
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Anne Cambon-Thomsen, Wolfgang Helmberg, Michael Feolo, Pierre-Antoine Gourraud, and Douglas W. Hoffman
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Genetic Markers ,Genetics ,Internet ,biology ,Sequence analysis ,Immunology ,Single-nucleotide polymorphism ,Locus (genetics) ,General Medicine ,Human leukocyte antigen ,Computational biology ,Major histocompatibility complex ,Biochemistry ,Histocompatibility ,Major Histocompatibility Complex ,Databases, Genetic ,biology.protein ,Animals ,Humans ,Immunology and Allergy ,Microsatellite ,Primer (molecular biology) ,Microsatellite Repeats - Abstract
Major histocompatibility complex (MHC) region Microsatellites (Msat) have been extensively used in various applications, such as disease mapping, forensics, and population genetics. A comprehensive review of HLA Msat primers has been previously published based on literature and sequence analysis, but electronic tools are lacking to make it easily accessible and actually used by the community. We have integrated data from this review, with an overlapping set of 31 Msat markers used in the 13th International Histocompatibility and Immunogenetics Workshop (IHIWS) to create a public archive that will synchronize published descriptions to a common framework. http://www.ncbi.nlm.nih.gov/projects/mhc. Currently, the dbMHC contains 389 primer pairs across the extended MHC targeting 281 distinct repeat regions (approximately 1/45 kb). Literature review and analysis of the primers reveal that over 200 synonymous names have been published for these markers. Users may view or download specific Msat data sets using the portal. Query options include name or partial name, primer sequence, neighboring genes, and/or position. Query results include locus name(s), a graphic showing of the relative location of the marker in relation to the classical HLA genes, a listing of the constituent primer pairs and name, a link to UniSTS, aliases, allele range (bp), overlapping single nucleotide polymorphisms, a link to e-polymerase chain reaction, and physical mapping information. To increase the utility of this resource, researchers using Msat markers in the HLA region are encouraged by the authors to submit new primers to the dbMHC. The minimal Msat submission consists of primers sequences, a submitter's name and contact information. Additional information recommended but not required is the laboratory protocol(s), known allele size range (bp), known aliases, and an exemplar sequence. Assigned UniSTS numbers can be used for primer pair standard identification.
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- 2006
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9. A haplotype map of the human genome
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Mark Leppert, Aravinda Chakravarti, Charmaine D.M. Royal, Sarah S. Murray, Renzong Qiu, Panos Deloukas, Renwu Wang, David A. Hinds, Barbara E. Stranger, Xiaoli Tang, Huanming Yang, John W. Belmont, Nigel P. Carter, Huy Nguyen, William Mak, Kazuto Kato, Shiran Pasternak, Chaohua Li, Jeffrey C. Barrett, Lon R. Cardon, Vincent Ferretti, Atsushi Nagashima, Peter E. Chen, Stephen F. Schaffner, Hongbo Fu, Zhu Chen, Siqi Liu, John Burton, Paul Hardenbol, Gudmundur A. Thorisson, Yusuke Nakamura, Mark Griffiths, Imtiaz Yakub, Eiko Suda, Gonçalo R. Abecasis, Carl S. Kashuk, Qingrun Zhang, Yoshimitsu Fukushima, Karen Kennedy, Sarah E. Hunt, Yi Wang, Norio Niikawa, Ichiro Matsuda, Lynn F. Zacharia, Lalitha Krishnan, Zhen Wang, Stéphanie Roumy, C M Clee, David J. Cutler, Albert V. Smith, Lincoln Stein, Simon Myers, Jane Peterson, Jun Zhou, Yozo Ohnishi, Weihua Guan, Matthew Stephens, Xiaoyan Xiong, Julian Maller, Houcan Zhang, Pui-Yan Kwok, Mark S. Guyer, Liuda Ziaugra, Jonathan Witonsky, Matthew C. Jones, Stacey Gabriel, You-Qiang Song, Daochang An, Haifeng Wang, Gilean McVean, Lawrence M. Sung, Zhijian Yao, Yan Shen, Yangfan Liu, George M. Weinstock, Ludmila Pawlikowska, Erica Sodergren, Mark T. Ross, Andrew Boudreau, Toshihiro Tanaka, Thomas D. Willis, Weitao Hu, Kelly A. Frazer, Li Jin, Robert W. Plumb, Paul I.W. de Bakker, Hongbin Zhao, Wei Lin, Sarah Sims, Richard A. Gibbs, Maura Faggart, Michael Feolo, Dennis G. Ballinger, Xun Chu, Lucinda Fulton, Marcos Delgado, Ellen Winchester, Wei Huang, Fuli Yu, Christianne R. Bird, Shaun Purcell, Jessica Roy, Dongmei Cai, Launa M. Galver, Bartha Maria Knoppers, Emmanouil T. Dermitzakis, Gao Yang, Takashi Morizono, Rachel Barry, Kirsten McLay, Daryl J. Thomas, Steve McCarroll, Jonathan Marchini, Daniel J. Richter, Andy Peiffer, Patricia Taillon-Miller, Richard K. Wilson, Stephen Kwok-Wing Tsui, Jian-Bing Fan, Lisa D. Brooks, Laura L. Stuve, Paul L'Archevêque, David M. Evans, Clémentine Sallée, Peter Donnelly, Hong Xue, Hui Zhao, Charles N. Rotimi, Jean E. McEwen, J. Tze Fei Wong, Hao Pan, Alastair Kent, Brendan Blumenstiel, Qing Li, Weiwei Sun, L. Kang, Colin Freeman, John Stewart, Chibuzor Nkwodimmah, Morris W. Foster, Don Powell, Leonardo Bottolo, Raymond D. Miller, Stephen T. Sherry, Francis S. Collins, Donna M. Muzny, Jun Yu, Ike Ajayi, Hua Han, Pardis C. Sabeti, Hongguang Wang, Takahisa Kawaguchi, Tatsuhiko Tsunoda, Guy Bellemare, Zhaohui S. Qin, H. B. Hu, Jane Rogers, Thomas J. Hudson, Mark J. Daly, Andrew P. Morris, Supriya Gupta, Ming Xiao, Patrick Varilly, Nick Patterson, Akihiro Sekine, Chris C. A. Spencer, Jonathan Morrison, Missy Dixon, Paul K.H. Tam, Jian Wang, Matthew Defelice, Susana Eyheramendy, Michael Shi, Yungang He, Ellen Wright Clayton, Richa Saxena, Heather M. Munro, Arthur L. Holden, Yayun Shen, Christine P. Bird, Bruce W. Birren, Itsik Pe'er, David R. Bentley, Lynne V. Nazareth, Pamela Whittaker, Pak C. Sham, Amy L. Camargo, David A. Wheeler, Koji Saeki, Martin Godbout, David Altshuler, Liang Xu, Ying Wang, David Willey, Alexandre Montpetit, Shin Lin, Michael S. Phillips, Changqing Zeng, Clement Adebamowo, John C. Wallenburg, Mark S. Chee, Ben Fry, Erich Stahl, Melissa Parkin, Rhian Gwilliam, Andrei Verner, Patrick J. Nailer, Lap-Chee Tsui, Bo Zhang, Fanny Chagnon, David R. Cox, Jack Spiegel, Jamie Moore, Vivian Ota Wang, Patricia A. Marshall, Takuya Kitamoto, Bruce S. Weir, Darryl Macer, Geraldine M. Clarke, Robert C. Onofrio, Mary M.Y. Waye, Wei Wang, Suzanne M. Leal, James C. Mullikin, Toyin Aniagwu, Daniel C. Koboldt, Mary Goyette, Martin Leboeuf, Isaac F. Adewole, Ruth Jamieson, Arnold Oliphant, Jessica Watkin, and Jean François Olivier
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Linkage disequilibrium ,Biology ,DNA, Mitochondrial ,Polymorphism, Single Nucleotide ,Article ,Linkage Disequilibrium ,Structural variation ,Gene Frequency ,Humans ,Selection, Genetic ,International HapMap Project ,Genetic association ,Haplotypes - genetics ,Recombination, Genetic ,Genetics ,Chromosomes, Human, Y ,Multidisciplinary ,Genome, Human ,DNA, Mitochondrial - genetics ,Haplotype ,Tag SNP ,Polymorphism, Single Nucleotide - genetics ,Haplotypes ,Human genome ,Haplotype estimation ,Chromosomes, Human, Y - genetics - Abstract
Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution. © 2005 Nature Publishing Group., link_to_OA_fulltext
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- 2005
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10. Whole-exome sequencing identifies rare and low-frequency coding variants associated with LDL cholesterol
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Leslie A. Lange, Youna Hu, He Zhang, Chenyi Xue, Ellen M. Schmidt, Zheng-Zheng Tang, Chris Bizon, Ethan M. Lange, Joshua D. Smith, Emily H. Turner, Goo Jun, Hyun Min Kang, Gina Peloso, Paul Auer, Kuo-ping Li, Jason Flannick, Ji Zhang, Christian Fuchsberger, Kyle Gaulton, Cecilia Lindgren, Adam Locke, Alisa Manning, Xueling Sim, Manuel A. Rivas, Oddgeir L. Holmen, Omri Gottesman, Yingchang Lu, Douglas Ruderfer, Eli A. Stahl, Qing Duan, Yun Li, Peter Durda, Shuo Jiao, Aaron Isaacs, Albert Hofman, Joshua C. Bis, Adolfo Correa, Michael E. Griswold, Johanna Jakobsdottir, Albert V. Smith, Pamela J. Schreiner, Mary F. Feitosa, Qunyuan Zhang, Jennifer E. Huffman, Jacy Crosby, Christina L. Wassel, Ron Do, Nora Franceschini, Lisa W. Martin, Jennifer G. Robinson, Themistocles L. Assimes, David R. Crosslin, Elisabeth A. Rosenthal, Michael Tsai, Mark J. Rieder, Deborah N. Farlow, Aaron R. Folsom, Thomas Lumley, Ervin R. Fox, Christopher S. Carlson, Ulrike Peters, Rebecca D. Jackson, Cornelia M. van Duijn, André G. Uitterlinden, Daniel Levy, Jerome I. Rotter, Herman A. Taylor, Vilmundur Gudnason, David S. Siscovick, Myriam Fornage, Ingrid B. Borecki, Caroline Hayward, Igor Rudan, Y. Eugene Chen, Erwin P. Bottinger, Ruth J.F. Loos, Pål Sætrom, Kristian Hveem, Michael Boehnke, Leif Groop, Mark McCarthy, Thomas Meitinger, Christie M. Ballantyne, Stacey B. Gabriel, Christopher J. O’Donnell, Wendy S. Post, Kari E. North, Alexander P. Reiner, Eric Boerwinkle, Bruce M. Psaty, David Altshuler, Sekar Kathiresan, Dan-Yu Lin, Gail P. Jarvik, L. Adrienne Cupples, Charles Kooperberg, James G. Wilson, Deborah A. Nickerson, Goncalo R. Abecasis, Stephen S. Rich, Russell P. Tracy, Cristen J. Willer, David M. Altshuler, Gonçalo R. Abecasis, Hooman Allayee, Sharon Cresci, Mark J. Daly, Paul I.W. de Bakker, Mark A. DePristo, Peter Donnelly, Tim Fennell, Kiran Garimella, Stanley L. Hazen, Daniel M. Jordan, Adam Kiezun, Guillaume Lettre, Bingshan Li, Mingyao Li, Christopher H. Newton-Cheh, Sandosh Padmanabhan, Sara Pulit, Daniel J. Rader, David Reich, Muredach P. Reilly, Steve Schwartz, Laura Scott, John A. Spertus, Nathaniel O. Stitziel, Nina Stoletzki, Shamil R. Sunyaev, Benjamin F. Voight, Ermeg Akylbekova, Larry D. Atwood, Maja Barbalic, R. Graham Barr, Emelia J. Benjamin, Joshua Bis, Donald W. Bowden, Jennifer Brody, Matthew Budoff, Greg Burke, Sarah Buxbaum, Jeff Carr, Donna T. Chen, Ida Y. Chen, Wei-Min Chen, Pat Concannon, Ralph D’Agostino, Anita L. DeStefano, Albert Dreisbach, Josée Dupuis, J. Peter Durda, Jaclyn Ellis, Caroline S. Fox, Ervin Fox, Vincent Funari, Santhi K. Ganesh, Julius Gardin, David Goff, Ora Gordon, Wayne Grody, Myron Gross, Xiuqing Guo, Ira M. Hall, Nancy L. Heard-Costa, Susan R. Heckbert, Nicholas Heintz, David M. Herrington, DeMarc Hickson, Jie Huang, Shih-Jen Hwang, David R. Jacobs, Nancy S. Jenny, Andrew D. Johnson, Craig W. Johnson, Steven Kawut, Richard Kronmal, Raluca Kurz, Martin G. Larson, Mark Lawson, Cora E. Lewis, Dalin Li, Honghuang Lin, Chunyu Liu, Jiankang Liu, Kiang Liu, Xiaoming Liu, Yongmei Liu, William T. Longstreth, Cay Loria, Kathryn Lunetta, Aaron J. Mackey, Rachel Mackey, Ani Manichaikul, Taylor Maxwell, Barbara McKnight, James B. Meigs, Alanna C. Morrison, Solomon K. Musani, Josyf C. Mychaleckyj, Jennifer A. Nettleton, Kari North, Daniel O’Leary, Frank Ong, Walter Palmas, James S. Pankow, Nathan D. Pankratz, Shom Paul, Marco Perez, Sharina D. Person, Joseph Polak, Aaron R. Quinlan, Leslie J. Raffel, Vasan S. Ramachandran, Kenneth Rice, Jill P. Sanders, Pamela Schreiner, Sudha Seshadri, Steve Shea, Stephen Sidney, Kevin Silverstein, Nicholas L. Smith, Nona Sotoodehnia, Asoke Srinivasan, Kent Taylor, Fridtjof Thomas, Michael Y. Tsai, Kelly A. Volcik, Chrstina L. Wassel, Karol Watson, Gina Wei, Wendy White, Kerri L. Wiggins, Jemma B. Wilk, O. Dale Williams, Gregory Wilson, Phillip Wolf, Neil A. Zakai, John Hardy, James F. Meschia, Michael Nalls, Andrew Singleton, Brad Worrall, Michael J. Bamshad, Kathleen C. Barnes, Ibrahim Abdulhamid, Frank Accurso, Ran Anbar, Terri Beaty, Abigail Bigham, Phillip Black, Eugene Bleecker, Kati Buckingham, Anne Marie Cairns, Daniel Caplan, Barbara Chatfield, Aaron Chidekel, Michael Cho, David C. Christiani, James D. Crapo, Julia Crouch, Denise Daley, Anthony Dang, Hong Dang, Alicia De Paula, Joan DeCelie-Germana, Allen DozorMitch Drumm, Maynard Dyson, Julia Emerson, Mary J. Emond, Thomas Ferkol, Robert Fink, Cassandra Foster, Deborah Froh, Li Gao, William Gershan, Ronald L. Gibson, Elizabeth Godwin, Magdalen Gondor, Hector Gutierrez, Nadia N. Hansel, Paul M. Hassoun, Peter Hiatt, John E. Hokanson, Michelle Howenstine, Laura K. Hummer, Jamshed Kanga, Yoonhee Kim, Michael R. Knowles, Michael Konstan, Thomas Lahiri, Nan Laird, Christoph Lange, Lin Lin, Xihong Lin, Tin L. Louie, David Lynch, Barry Make, Thomas R. Martin, Steve C. Mathai, Rasika A. Mathias, John McNamara, Sharon McNamara, Deborah Meyers, Susan Millard, Peter Mogayzel, Richard Moss, Tanda Murray, Dennis Nielson, Blakeslee Noyes, Wanda O’Neal, David Orenstein, Brian O’Sullivan, Rhonda Pace, Peter Pare, H. Worth Parker, Mary Ann Passero, Elizabeth Perkett, Adrienne Prestridge, Nicholas M. Rafaels, Bonnie Ramsey, Elizabeth Regan, Clement Ren, George Retsch-Bogart, Michael Rock, Antony Rosen, Margaret Rosenfeld, Ingo Ruczinski, Andrew Sanford, David Schaeffer, Cindy Sell, Daniel Sheehan, Edwin K. Silverman, Don Sin, Terry Spencer, Jackie Stonebraker, Holly K. Tabor, Laurie Varlotta, Candelaria I. Vergara, Robert Weiss, Fred Wigley, Robert A. Wise, Fred A. Wright, Mark M. Wurfel, Robert Zanni, Fei Zou, Phil Green, Jay Shendure, Joshua M. Akey, Carlos D. Bustamante, Evan E. Eichler, P. Keolu Fox, Wenqing Fu, Adam Gordon, Simon Gravel, Jill M. Johnsen, Mengyuan Kan, Eimear E. Kenny, Jeffrey M. Kidd, Fremiet Lara-Garduno, Suzanne M. Leal, Dajiang J. Liu, Sean McGee, Timothy D. O’Connor, Bryan Paeper, Peggy D. Robertson, Jeffrey C. Staples, Jacob A. Tennessen, Gao Wang, Qian Yi, Rebecca Jackson, Garnet Anderson, Hoda Anton-Culver, Paul L. Auer, Shirley Beresford, Henry Black, Robert Brunner, Robert Brzyski, Dale Burwen, Bette Caan, Cara L. Carty, Rowan Chlebowski, Steven Cummings, J. David Curb, Charles B. Eaton, Leslie Ford, Stephanie M. Fullerton, Margery Gass, Nancy Geller, Gerardo Heiss, Barbara V. Howard, Li Hsu, Carolyn M. Hutter, John Ioannidis, Karen C. Johnson, Lewis Kuller, Andrea LaCroix, Kamakshi Lakshminarayan, Dorothy Lane, Norman Lasser, Erin LeBlanc, Kuo-Ping Li, Marian Limacher, Benjamin A. Logsdon, Shari Ludlam, JoAnn E. Manson, Karen Margolis, Lisa Martin, Joan McGowan, Keri L. Monda, Jane Morley Kotchen, Lauren Nathan, Judith Ockene, Mary Jo O’Sullivan, Lawrence S. Phillips, Ross L. Prentice, John Robbins, Jacques E. Rossouw, Haleh Sangi-Haghpeykar, Gloria E. Sarto, Sally Shumaker, Michael S. Simon, Marcia L. Stefanick, Evan Stein, Hua Tang, Kira C. Taylor, Cynthia A. Thomson, Timothy A. Thornton, Linda Van Horn, Mara Vitolins, Jean Wactawski-Wende, Robert Wallace, Sylvia Wassertheil-Smoller, Donglin Zeng, Deborah Applebaum-Bowden, Michael Feolo, Weiniu Gan, Dina N. Paltoo, Phyliss Sholinsky, Anne Sturcke, Epidemiology, and Internal Medicine
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Male ,Genome-wide association study ,030204 cardiovascular system & hematology ,Cohort Studies ,0302 clinical medicine ,Gene Frequency ,Receptors ,Genotype ,Dyslipidemias/blood ,Receptors, LDL/genetics ,Genetics(clinical) ,Exome ,Genetics (clinical) ,Exome sequencing ,Genetics ,0303 health sciences ,Serine Endopeptidases ,Single Nucleotide ,Middle Aged ,3. Good health ,Cholesterol ,Phenotype ,Genetic Code ,Cholesterol, LDL/genetics ,Female ,lipids (amino acids, peptides, and proteins) ,Proprotein Convertases ,Proprotein Convertase 9 ,Sequence Analysis ,Adult ,Apolipoproteins E/blood ,LDL/genetics ,Serine Endopeptidases/genetics ,Single-nucleotide polymorphism ,Biology ,Polymorphism, Single Nucleotide ,Article ,03 medical and health sciences ,Apolipoproteins E ,SDG 3 - Good Health and Well-being ,Humans ,Polymorphism ,Allele frequency ,030304 developmental biology ,Genetic association ,Aged ,Dyslipidemias ,PCSK9 ,DNA ,Cholesterol, LDL ,Lipase ,Sequence Analysis, DNA ,Receptors, LDL ,Lipase/genetics ,Proprotein Convertases/genetics ,Follow-Up Studies ,Genome-Wide Association Study - Abstract
Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or
- Published
- 2014
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