Literature DB >> 32273609

Polygenic and clinical risk scores and their impact on age at onset and prediction of cardiometabolic diseases and common cancers.

Nina Mars1, Jukka T Koskela1, Pietari Ripatti1, Tuomo T J Kiiskinen1, Aki S Havulinna1,2, Joni V Lindbohm3, Ari Ahola-Olli1, Mitja Kurki1,4,5, Juha Karjalainen1,6,7, Priit Palta1,8, Benjamin M Neale4,7, Mark Daly1,6, Veikko Salomaa2, Aarno Palotie1,5,6, Elisabeth Widén1, Samuli Ripatti9,10,11.   

Abstract

Polygenic risk scores (PRSs) have shown promise in predicting susceptibility to common diseases1-3. We estimated their added value in clinical risk prediction of five common diseases, using large-scale biobank data (FinnGen; n = 135,300) and the FINRISK study with clinical risk factors to test genome-wide PRSs for coronary heart disease, type 2 diabetes, atrial fibrillation, breast cancer and prostate cancer. We evaluated the lifetime risk at different PRS levels, and the impact on disease onset and on prediction together with clinical risk scores. Compared to having an average PRS, having a high PRS contributed 21% to 38% higher lifetime risk, and 4 to 9 years earlier disease onset. PRSs improved model discrimination over age and sex in type 2 diabetes, atrial fibrillation, breast cancer and prostate cancer, and over clinical risk in type 2 diabetes, breast cancer and prostate cancer. In all diseases, PRSs improved reclassification over clinical thresholds, with the largest net reclassification improvements for early-onset coronary heart disease, atrial fibrillation and prostate cancer. This study provides evidence for the additional value of PRSs in clinical disease prediction. The practical applications of polygenic risk information for stratified screening or for guiding lifestyle and medical interventions in the clinical setting remain to be defined in further studies.

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Year:  2020        PMID: 32273609     DOI: 10.1038/s41591-020-0800-0

Source DB:  PubMed          Journal:  Nat Med        ISSN: 1078-8956            Impact factor:   53.440


  1 in total

1.  Genetic Risk, Lifestyle, and Coronary Artery Disease.

Authors:  Amit V Khera; Connor A Emdin; Sekar Kathiresan
Journal:  N Engl J Med       Date:  2017-03-23       Impact factor: 91.245

  1 in total
  73 in total

1.  Ranking the risk of heart disease.

Authors:  Michael Eisenstein
Journal:  Nature       Date:  2021-06       Impact factor: 49.962

2.  A Platelet Function Modulator of Thrombin Activation Is Causally Linked to Cardiovascular Disease and Affects PAR4 Receptor Signaling.

Authors:  Benjamin A T Rodriguez; Arunoday Bhan; Andrew Beswick; Peter C Elwood; Teemu J Niiranen; Veikko Salomaa; David-Alexandre Trégouët; Pierre-Emmanuel Morange; Mete Civelek; Yoav Ben-Shlomo; Thorsten Schlaeger; Ming-Huei Chen; Andrew D Johnson
Journal:  Am J Hum Genet       Date:  2020-07-09       Impact factor: 11.025

Review 3.  Risk Prediction Using Polygenic Risk Scores for Prevention of Stroke and Other Cardiovascular Diseases.

Authors:  Gad Abraham; Loes Rutten-Jacobs; Michael Inouye
Journal:  Stroke       Date:  2021-08-17       Impact factor: 7.914

4.  Genome-Wide Polygenic Score, Clinical Risk Factors, and Long-Term Trajectories of Coronary Artery Disease.

Authors:  George Hindy; Krishna G Aragam; Kenney Ng; Mark Chaffin; Luca A Lotta; Aris Baras; Isabel Drake; Marju Orho-Melander; Olle Melander; Sekar Kathiresan; Amit V Khera
Journal:  Arterioscler Thromb Vasc Biol       Date:  2020-09-22       Impact factor: 8.311

5.  Real-time, personalized medicine through wearable sensors and dynamic predictive modeling: a new paradigm for clinical medicine.

Authors:  Jonathan Tyler; Sung Won Choi; Muneesh Tewari
Journal:  Curr Opin Syst Biol       Date:  2020-07-07

6.  Improved prediction of fracture risk leveraging a genome-wide polygenic risk score.

Authors:  Tianyuan Lu; Vincenzo Forgetta; Julyan Keller-Baruch; Maria Nethander; Derrick Bennett; Marie Forest; Sahir Bhatnagar; Robin G Walters; Kuang Lin; Zhengming Chen; Liming Li; Magnus Karlsson; Dan Mellström; Eric Orwoll; Eugene V McCloskey; John A Kanis; William D Leslie; Robert J Clarke; Claes Ohlsson; Celia M T Greenwood; J Brent Richards
Journal:  Genome Med       Date:  2021-02-03       Impact factor: 11.117

7.  Prediction of complex phenotypes using the Drosophila melanogaster metabolome.

Authors:  Palle Duun Rohde; Torsten Nygaard Kristensen; Pernille Sarup; Joaquin Muñoz; Anders Malmendal
Journal:  Heredity (Edinb)       Date:  2021-01-28       Impact factor: 3.821

Review 8.  Systems biology in cardiovascular disease: a multiomics approach.

Authors:  Abhishek Joshi; Marieke Rienks; Konstantinos Theofilatos; Manuel Mayr
Journal:  Nat Rev Cardiol       Date:  2020-12-18       Impact factor: 32.419

9.  Integrated Polygenic Tool Substantially Enhances Coronary Artery Disease Prediction.

Authors:  Vincent Plagnol; Peter Donnelly; Fernando Riveros-Mckay; Michael E Weale; Rachel Moore; Saskia Selzam; Eva Krapohl; R Michael Sivley; William A Tarran; Peter Sørensen; Alexander S Lachapelle; Jonathan A Griffiths; Ayden Saffari; John Deanfield; Chris C A Spencer; Julia Hippisley-Cox; David J Hunter; Jack W O'Sullivan; Euan A Ashley
Journal:  Circ Genom Precis Med       Date:  2021-03-02

10.  Polygenic Risk Scores Predict Hypertension Onset and Cardiovascular Risk.

Authors:  Felix Vaura; Anni Kauko; Karri Suvila; Aki S Havulinna; Nina Mars; Veikko Salomaa; Susan Cheng; Teemu Niiranen
Journal:  Hypertension       Date:  2021-02-22       Impact factor: 10.190

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