Literature DB >> 35796859

Use of Polygenic Risk Scores for Coronary Heart Disease in Ancestrally Diverse Populations.

Ozan Dikilitas1,2,3, Daniel J Schaid4, Catherine Tcheandjieu5,6, Shoa L Clarke5,6, Themistocles L Assimes5,6, Iftikhar J Kullo7,8.   

Abstract

PURPOSE OF REVIEW: A polygenic risk score (PRS) is a measure of genetic liability to a disease and is typically normally distributed in a population. Individuals in the upper tail of this distribution often have relative risk equivalent to that of monogenic form of the disease. The majority of currently available PRSs for coronary heart disease (CHD) have been generated from cohorts of European ancestry (EUR) and vary in their applicability to other ancestry groups. In this report, we review the performance of PRSs for CHD across different ancestries and efforts to reduce variability in performance including novel population and statistical genetics approaches. RECENT
FINDINGS: PRSs for CHD perform robustly in EUR populations but lag in performance in non-EUR groups, particularly individuals of African ancestry. Several large consortia have been established to enable genomic studies in diverse ancestry groups and develop methods to improve PRS performance in multi-ancestry contexts as well as admixed individuals. These include fine-mapping to ascertain causal variants, trans ancestry meta-analyses, and ancestry deconvolution in admixed individuals. PRSs are being used in the clinical setting but enthusiasm has been tempered by the variable performance in non-EUR ancestry groups. Increasing diversity in genomic association studies and continued innovation in methodological approaches are needed to improve PRS performance in non-EUR individuals for equitable implementation of genomic medicine.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Coronary heart disease; Diverse; Multi-ancestry; Polygenic risk score; Risk prediction; Transethnic

Mesh:

Year:  2022        PMID: 35796859     DOI: 10.1007/s11886-022-01734-0

Source DB:  PubMed          Journal:  Curr Cardiol Rep        ISSN: 1523-3782            Impact factor:   3.955


  56 in total

Review 1.  Polygenic Scores to Assess Atherosclerotic Cardiovascular Disease Risk: Clinical Perspectives and Basic Implications.

Authors:  Krishna G Aragam; Pradeep Natarajan
Journal:  Circ Res       Date:  2020-04-23       Impact factor: 17.367

2.  Polymorphisms associated with cholesterol and risk of cardiovascular events.

Authors:  Sekar Kathiresan; Olle Melander; Dragi Anevski; Candace Guiducci; Noël P Burtt; Charlotta Roos; Joel N Hirschhorn; Göran Berglund; Bo Hedblad; Leif Groop; David M Altshuler; Christopher Newton-Cheh; Marju Orho-Melander
Journal:  N Engl J Med       Date:  2008-03-20       Impact factor: 91.245

3.  Incorporating a Genetic Risk Score Into Coronary Heart Disease Risk Estimates: Effect on Low-Density Lipoprotein Cholesterol Levels (the MI-GENES Clinical Trial).

Authors:  Iftikhar J Kullo; Hayan Jouni; Erin E Austin; Sherry-Ann Brown; Teresa M Kruisselbrink; Iyad N Isseh; Raad A Haddad; Tariq S Marroush; Khader Shameer; Janet E Olson; Ulrich Broeckel; Robert C Green; Daniel J Schaid; Victor M Montori; Kent R Bailey
Journal:  Circulation       Date:  2016-02-25       Impact factor: 29.690

4.  Polygenic background modifies penetrance of monogenic variants for tier 1 genomic conditions.

Authors:  Akl C Fahed; Minxian Wang; Julian R Homburger; Aniruddh P Patel; Alexander G Bick; Cynthia L Neben; Carmen Lai; Deanna Brockman; Anthony Philippakis; Patrick T Ellinor; Christopher A Cassa; Matthew Lebo; Kenney Ng; Eric S Lander; Alicia Y Zhou; Sekar Kathiresan; Amit V Khera
Journal:  Nat Commun       Date:  2020-08-20       Impact factor: 14.919

Review 5.  Reducing the Global Burden of Cardiovascular Disease, Part 1: The Epidemiology and Risk Factors.

Authors:  Philip Joseph; Darryl Leong; Martin McKee; Sonia S Anand; Jon-David Schwalm; Koon Teo; Andrew Mente; Salim Yusuf
Journal:  Circ Res       Date:  2017-09-01       Impact factor: 17.367

6.  A multilocus genetic risk score for coronary heart disease: case-control and prospective cohort analyses.

Authors:  Samuli Ripatti; Emmi Tikkanen; Marju Orho-Melander; Aki S Havulinna; Kaisa Silander; Amitabh Sharma; Candace Guiducci; Markus Perola; Antti Jula; Juha Sinisalo; Marja-Liisa Lokki; Markku S Nieminen; Olle Melander; Veikko Salomaa; Leena Peltonen; Sekar Kathiresan
Journal:  Lancet       Date:  2010-10-23       Impact factor: 79.321

7.  Genotype-informed estimation of risk of coronary heart disease based on genome-wide association data linked to the electronic medical record.

Authors:  Keyue Ding; Kent R Bailey; Iftikhar J Kullo
Journal:  BMC Cardiovasc Disord       Date:  2011-11-03       Impact factor: 2.298

8.  Risk prediction by genetic risk scores for coronary heart disease is independent of self-reported family history.

Authors:  Hayato Tada; Olle Melander; Judy Z Louie; Joseph J Catanese; Charles M Rowland; James J Devlin; Sekar Kathiresan; Dov Shiffman
Journal:  Eur Heart J       Date:  2015-09-20       Impact factor: 29.983

9.  Genomic prediction of coronary heart disease.

Authors:  Gad Abraham; Aki S Havulinna; Oneil G Bhalala; Sean G Byars; Alysha M De Livera; Laxman Yetukuri; Emmi Tikkanen; Markus Perola; Heribert Schunkert; Eric J Sijbrands; Aarno Palotie; Nilesh J Samani; Veikko Salomaa; Samuli Ripatti; Michael Inouye
Journal:  Eur Heart J       Date:  2016-09-21       Impact factor: 29.983

10.  Genomic Risk Prediction of Coronary Artery Disease in 480,000 Adults: Implications for Primary Prevention.

Authors:  Michael Inouye; Gad Abraham; Christopher P Nelson; Angela M Wood; Michael J Sweeting; Frank Dudbridge; Florence Y Lai; Stephen Kaptoge; Marta Brozynska; Tingting Wang; Shu Ye; Thomas R Webb; Martin K Rutter; Ioanna Tzoulaki; Riyaz S Patel; Ruth J F Loos; Bernard Keavney; Harry Hemingway; John Thompson; Hugh Watkins; Panos Deloukas; Emanuele Di Angelantonio; Adam S Butterworth; John Danesh; Nilesh J Samani
Journal:  J Am Coll Cardiol       Date:  2018-10-16       Impact factor: 24.094

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