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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Challenges and opportunities for developing more generalizable polygenic risk scores
TL;DR: This review aims to comprehensively discuss current progress on the development of polygenic risk scores, the factors that affect their generalizability, and promising areas for improving their accuracy, portable, and implementation.
Posted Content
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness
Sebastian J. Vollmer,Bilal A. Mateen,Gergo Bohner,Franz J. Király,Rayid Ghani,Pall Jonsson,Sarah Cumbers,A Jonas,Kate McAllister,Puja R. Myles,David Granger,Mark Birse,Richard Branson,Karel G. M. Moons,Gary S. Collins,John P. A. Ioannidis,Christopher Holmes,Harry Hemingway +17 more
TL;DR: 20 questions that span the entire project life cycle, from inception, data analysis, and model evaluation, to implementation, are presented, as a means to facilitate project planning and post-hoc (structured) independent evaluation.
Journal ArticleDOI
Design and user experience testing of a polygenic score report: a qualitative study of prospective users.
Deanna Brockman,Lia Petronio,Jacqueline S. Dron,Bum Chul Kwon,Trish Vosburg,Lisa Nip,Andrew Tang,Mary O'Reilly,Niall J. Lennon,Bang Wong,Kenney Ng,Katherine H. Huang,Akl C. Fahed,Akl C. Fahed,Amit Khera,Amit Khera +15 more
TL;DR: In this paper, a group of clinicians, geneticists, data visualization specialists, and software developers assembled a working group to review the landscape of polygen score reporting and describe a generalizable approach for development of a polygenic score disclosure tool for coronary artery disease.
Journal ArticleDOI
The Genetic Basis of Obesity and Related Metabolic Diseases in Humans and Companion Animals.
Natalie Wallis,Eleanor Raffan +1 more
TL;DR: How large-scale human studies and niche investigations of rare mutations in severely affected patients have improved the authors' understanding of obesity biology can inform their ability to interpret results of animal studies and demonstrate translational benefits to human research is discussed.
Journal ArticleDOI
Understanding polygenic models, their development and the potential application of polygenic scores in healthcare
TL;DR: An overview of the methodological aspects of polygenic model construction is provided and the state of the field is considered and implications for potential applications ofpolygenic scores for risk estimation within healthcare are considered.
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.
Journal ArticleDOI
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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