Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention.
Michael Inouye,Gad Abraham,Christopher P. Nelson,Angela M. Wood,Michael J. Sweeting,Frank Dudbridge,Florence Lai,Stephen Kaptoge,Marta Brozynska,Tingting Wang,Shu Ye,Tom R. Webb,Martin K. Rutter,Ioanna Tzoulaki,Riyaz S. Patel,Ruth J. F. Loos,Bernard Keavney,Harry Hemingway,John F. Thompson,Hugh Watkins,Panos Deloukas,Emanuele Di Angelantonio,Adam S. Butterworth,John Danesh,Nilesh J. Samani +24 more
TLDR
The genomic score developed and evaluated here substantially advances the concept of using genomic information to stratify individuals with different trajectories of CAD risk and highlights the potential for genomic screening in early life to complement conventional risk prediction.About:
This article is published in Journal of the American College of Cardiology.The article was published on 2018-10-16 and is currently open access. It has received 522 citations till now. The article focuses on the topics: Framingham Risk Score.read more
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A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage
TL;DR: In this paper , a meta-genomic risk score (metaGRS) consisting of 2.6 million variants was developed to predict lifetime risk of ICH beyond established clinical risk factors among individuals of European ancestry.
Posted ContentDOI
Leveraging functional genomic annotations and genome coverage to improve polygenic prediction of complex traits within and between ancestries
Zhili Zheng,Shouye Liu,Julia Sidorenko,Loic Yengo,Patrick Turley,Alireza Ani,Rujia Wang,Ilja M. Nolte,Harold Snieder,Jian Yang,Naomi R. Wray,Michael E. Goddard,Peter M. Visscher,Jian Zeng +13 more
TL;DR: A new method is developed that integrates GWAS summary statistics with functional genomic annotations to improve polygenic prediction of complex traits and refines signals from functional annotations by allowing them to affect both causal variant probability and causal effect distribution.
Journal ArticleDOI
Genomic risk prediction of coronary artery disease in women with breast cancer: a prospective cohort study.
Lathan Liou,Stephen Kaptoge,Joe Dennis,Mitul Shah,Jonathan Tyrer,Michael Inouye,Michael Inouye,Douglas F. Easton,Paul D.P. Pharoah +8 more
TL;DR: In this paper, the authors assess the association between a coronary artery disease-specific polygenic risk score and incident coronary artery events in female breast cancer survivors and find that a 1 standard deviation higher risk score was associated with an adjusted hazard ratio of 1.33 (95% CI 1.20, 1.47) for incident CAD.
Journal ArticleDOI
Genetic information improves the prediction of major adverse cardiovascular events in the GENEMACOR population.
Maria Isabel Mendonça,Eva Henriques,S. Borges,Ana Célia Sousa,Andreia Pereira,Marina Santos,Margarida Temtem,Sónia Freitas,J.P Monteiro,J. Sousa,Ricardo Ribeiro Rodrigues,G Guerra,Roberto Palma dos Reis +12 more
TL;DR: In this article, a weighted genetic risk score (wGRS) was used to predict the risk of major adverse cardiovascular events (MACE) in 1587 patients from the GENEMACOR study.
Journal ArticleDOI
Clinical Conditions and Their Impact on Utility of Genetic Scores for Prediction of Acute Coronary Syndrome
Jiwoo Lee,Tuomo Kiiskinen,Nina Mars,Sakari Jukarainen,Erik Ingelsson,Benjamin M. Neale,Benjamin M. Neale,Samuli Ripatti,Samuli Ripatti,Samuli Ripatti,Pradeep Natarajan,Andrea Ganna,Andrea Ganna,Andrea Ganna +13 more
TL;DR: In this article, the association between polygenic scores (PS) and acute coronary syndrome (ACS) was investigated in the UK Biobank and the Finnish Genome Data Set (FGN).
References
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UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age
Cathie Sudlow,John Gallacher,Naomi E. Allen,Valerie Beral,Paul Burton,John Danesh,Paul Downey,Paul Elliott,Jane Green,Martin J Landray,Bette Liu,Paul M. Matthews,Giok Ong,Jill P. Pell,Alan J. Silman,Alan Young,Tim Sprosen,Tim Peakman,Rory Collins +18 more
TL;DR: The UK Biobank is described, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
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ROCR: visualizing classifier performance in R
TL;DR: UNLABELLED ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R that features over 25 performance measures that can be freely combined to create two-dimensional performance curves.
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A reference panel of 64,976 haplotypes for genotype imputation
Shane A. McCarthy,Sayantan Das,Warren W. Kretzschmar,Olivier Delaneau,Andrew R. Wood,Alexander Teumer,Hyun Min Kang,Christian Fuchsberger,Petr Danecek,Kevin Sharp,Yang Luo,C Sidore,Alan Kwong,Nicholas J. Timpson,Seppo Koskinen,Scott I. Vrieze,Laura J. Scott,He Zhang,Anubha Mahajan,Jan H. Veldink,Ulrike Peters,Ulrike Peters,Carlos N. Pato,Cornelia M. van Duijn,Christopher E. Gillies,Ilaria Gandin,Massimo Mezzavilla,Arthur Gilly,Massimiliano Cocca,Michela Traglia,Andrea Angius,Jeffrey C. Barrett,D.I. Boomsma,Kari Branham,Gerome Breen,Gerome Breen,Chad M. Brummett,Fabio Busonero,Harry Campbell,Andrew T. Chan,Sai Chen,Emily Y. Chew,Francis S. Collins,Laura J Corbin,George Davey Smith,George Dedoussis,Marcus Dörr,Aliki-Eleni Farmaki,Luigi Ferrucci,Lukas Forer,Ross M. Fraser,Stacey Gabriel,Shawn Levy,Leif Groop,Leif Groop,Tabitha A. Harrison,Andrew T. Hattersley,Oddgeir L. Holmen,Kristian Hveem,Matthias Kretzler,James Lee,Matt McGue,Thomas Meitinger,David Melzer,Josine L. Min,Karen L. Mohlke,John B. Vincent,Matthias Nauck,Deborah A. Nickerson,Aarno Palotie,Aarno Palotie,Michele T. Pato,Nicola Pirastu,Melvin G. McInnis,J. Brent Richards,J. Brent Richards,Cinzia Sala,Veikko Salomaa,David Schlessinger,Sebastian Schoenherr,P. Eline Slagboom,Kerrin S. Small,Tim D. Spector,Dwight Stambolian,Marcus A. Tuke,Jaakko Tuomilehto,Leonard H. van den Berg,Wouter van Rheenen,Uwe Völker,Cisca Wijmenga,Daniela Toniolo,Eleftheria Zeggini,Paolo Gasparini,Matthew G. Sampson,James F. Wilson,Timothy M. Frayling,Paul I.W. de Bakker,Morris A. Swertz,Steven A. McCarroll,Charles Kooperberg,Annelot M. Dekker,David Altshuler,Cristen J. Willer,William G. Iacono,Samuli Ripatti,Nicole Soranzo,Nicole Soranzo,Klaudia Walter,Anand Swaroop,Francesco Cucca,Carl A. Anderson,Richard M. Myers,Michael Boehnke,Mark I. McCarthy,Mark I. McCarthy,Richard Durbin,Gonçalo R. Abecasis,Jonathan Marchini +117 more
TL;DR: A reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies.
Journal ArticleDOI
Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population.
Anna Fry,Thomas J. Littlejohns,Catherine Sudlow,Nicola Doherty,Ligia Adamska,Tim Sprosen,Rory Collins,Naomi E. Allen +7 more
TL;DR: UK Biobank is not representative of the sampling population; there is evidence of a “healthy volunteer” selection bias; valid assessment of exposure-disease relationships may be widely generalizable and does not require participants to be Representative of the population at large.
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A comprehensive 1000 Genomes–based genome-wide association meta-analysis of coronary artery disease
Majid Nikpay,Anuj Goel,Won H-H.,Leanne M. Hall,Christina Willenborg,Stavroula Kanoni,Danish Saleheen,Theodosios Kyriakou,Christopher P. Nelson,Christopher P. Nelson,Jemma C. Hopewell,Tom R. Webb,Tom R. Webb,Lingyao Zeng,Abbas Dehghan,Maris Alver,Sebastian M. Armasu,Kirsi Auro,Kirsi Auro,Andrew Bjonnes,Daniel I. Chasman,Shufeng Chen,Ian Ford,Nora Franceschini,Christian Gieger,Christopher Grace,Stefan Gustafsson,Jie Huang,Hwang S-J.,Yun Kyoung Kim,Marcus E. Kleber,King Wai Lau,Xiangfeng Lu,Yingchang Lu,Lyytikäinen L-P.,Evelin Mihailov,Alanna C. Morrison,Natalia Pervjakova,Natalia Pervjakova,Natalia Pervjakova,Liming Qu,Lynda M. Rose,Elias Salfati,Richa Saxena,Markus Scholz,Albert V. Smith,Emmi Tikkanen,André G. Uitterlinden,Xueli Yang,Weihua Zhang,Wei Zhao,M. De Andrade,P. De Vries,N. R. van Zuydam,N. R. van Zuydam,Sonia S. Anand,Lars Bertram,Frank Beutner,George Dedoussis,Philippe M. Frossard,Dominique Gauguier,Alison H. Goodall,Omri Gottesman,Marc Haber,Han B-G.,Shapour Jalilzadeh,Thorsten Kessler,Inke R. König,Lars Lannfelt,Wolfgang Lieb,Lars Lind,Cecilia M. Lindgren,Lokki M-L.,Lokki M-L.,Patrik K. E. Magnusson,Nadeem Hayyat Mallick,Narinder K. Mehra,Thomas Meitinger,Memon F-U-R.,Andrew P. Morris,Andrew P. Morris,Markku S. Nieminen,Nancy L. Pedersen,Annette Peters,Loukianos S. Rallidis,Adil Rasheed,M Samuel,Svati H. Shah,Juha Sinisalo,Kathleen Stirrups,Stella Trompet,Ligui Wang,Ligui Wang,Khan Shah Zaman,Diego Ardissino,Eric Boerwinkle,Ingrid B. Borecki,Erwin P. Bottinger,Julie E. Buring,John C. Chambers,Rory Collins,L. A. Cupples,L. A. Cupples,John Danesh,Ilja Demuth,Roberto Elosua,Stephen E. Epstein,Tõnu Esko,Mary F. Feitosa,Oscar H. Franco,MariaGrazia Franzosi,Christopher B. Granger,Dongfeng Gu,Vilmundur Gudnason,Alistair S. Hall,Anders Hamsten,Tamara B. Harris,Stanley L. Hazen,Christian Hengstenberg,Albert Hofman,Erik Ingelsson,Carlos Iribarren,J W Jukema,Pekka J. Karhunen,Kim B-J.,Jaspal S. Kooner,Iftikhar J. Kullo,Terho Lehtimäki,Loos Rjf.,Olle Melander,Andres Metspalu,Winfried März,Winfried März,Winfried März,Colin N. A. Palmer,Markus Perola,Markus Perola,Markus Perola,Thomas Quertermous,Daniel J. Rader,Paul M. Ridker,Samuli Ripatti,Samuli Ripatti,Robert Roberts,Veikko Salomaa,Dharambir K. Sanghera,Stephen M. Schwartz,Udo Seedorf,Alexandre F.R. Stewart,David J. Stott,Joachim Thiery,Pierre Zalloua,Christopher J. O'Donnell,Christopher J. O'Donnell,Muredach P. Reilly,Themistocles L. Assimes,John R. Thompson,Jeanette Erdmann,Robert Clarke,Hugh Watkins,Sekar Kathiresan,Ruth McPherson,Panos Deloukas,Panos Deloukas,Heribert Schunkert,Nilesh J. Samani,Nilesh J. Samani,Martin Farrall +167 more
TL;DR: This article conducted a meta-analysis of coronary artery disease (CAD) cases and controls, interrogating 6.7 million common (minor allele frequency (MAF) > 0.05) and 2.7 millions low-frequency (0.005 < MAF < 0.5) variants.
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