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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Prediction of incident atherosclerotic cardiovascular disease with polygenic risk of metabolic disease: Analysis of 3 prospective cohort studies in Korea.
TL;DR: In this article , a grid search of combinations of metabolic risk scores was conducted to identify the most optimal weighted score for incident ASCVD (PRSMetS-ASCVD), which was validated in an independent prospective cohort (n = 4333).
Posted ContentDOI
Assessing agreement between different polygenic risk scores in the UK Biobank
TL;DR: In this article , the authors compared two recently published polygenic risk scores for each of three conditions, breast cancer, hypertension and dementia, to assess the stability of running these algorithms for risk prediction in a single large population, using imputed genotyping data from the UK Biobank (UKB) prospective cohort, limited to the White British subset.
Journal ArticleDOI
Polygenic risk score improves the accuracy of a clinical risk score for coronary artery disease
TL;DR: In this paper , an observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted to examine whether an integrated polygenic risk score improves the prediction of coronary artery disease beyond pooled cohort equations.
Journal ArticleDOI
Ethical layering in AI-driven polygenic risk scores—New complexities, new challenges
Marie-Christine Fritzsche,Kaya Akyüz,Mónica Cano Abadía,Stuart McLennan,Pekka Marttinen,Michaela Th. Mayrhofer,Alena Buyx +6 more
TL;DR: In this paper , a comprehensive review of the existing literature on polygenic risk score applications in the clinical setting is presented, and the authors strongly advocate taking a proactive approach to embedding ethics in research and implementation processes for polygen risk scores driven by artificial intelligence.
Journal ArticleDOI
New Cardiovascular Risk Assessment Techniques for Primary Prevention: JACC Review Topic of the Week.
Kunal Verma,Michael Inouye,Peter J. Meikle,Stephen J. Nicholls,Melinda Carrington,Thomas H. Marwick +5 more
TL;DR: In this article , a multidimensional approach to risk prediction holds the promise of precise risk prediction, which could allow for targeted prevention minimizing unnecessary costs and risks while maximizing benefits, and high-risk individuals could also be identified early in life.
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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.
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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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