Literature DB >> 30926966

Clinical use of current polygenic risk scores may exacerbate health disparities.

Alicia R Martin1,2,3, Masahiro Kanai4,5,6,7,8, Yoichiro Kamatani8,9, Yukinori Okada8,10,11, Benjamin M Neale4,5,6, Mark J Daly4,5,6,12.   

Abstract

Polygenic risk scores (PRS) are poised to improve biomedical outcomes via precision medicine. However, the major ethical and scientific challenge surrounding clinical implementation of PRS is that those available today are several times more accurate in individuals of European ancestry than other ancestries. This disparity is an inescapable consequence of Eurocentric biases in genome-wide association studies, thus highlighting that-unlike clinical biomarkers and prescription drugs, which may individually work better in some populations but do not ubiquitously perform far better in European populations-clinical uses of PRS today would systematically afford greater improvement for European-descent populations. Early diversifying efforts show promise in leveling this vast imbalance, even when non-European sample sizes are considerably smaller than the largest studies to date. To realize the full and equitable potential of PRS, greater diversity must be prioritized in genetic studies, and summary statistics must be publically disseminated to ensure that health disparities are not increased for those individuals already most underserved.

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Year:  2019        PMID: 30926966      PMCID: PMC6563838          DOI: 10.1038/s41588-019-0379-x

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  71 in total

1.  Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data.

Authors:  P C Sham; S S Cherny; S Purcell; J K Hewitt
Journal:  Am J Hum Genet       Date:  2000-04-12       Impact factor: 11.025

2.  The United States Leads Other Nations In Differences By Income In Perceptions Of Health And Health Care.

Authors:  Joachim O Hero; Alan M Zaslavsky; Robert J Blendon
Journal:  Health Aff (Millwood)       Date:  2017-06-01       Impact factor: 6.301

3.  Trends in lipids and lipoproteins in US adults, 1988-2010.

Authors:  Margaret D Carroll; Brian K Kit; David A Lacher; Susan T Shero; Michael E Mussolino
Journal:  JAMA       Date:  2012-10-17       Impact factor: 56.272

4.  In the Era of Precision Medicine and Big Data, Who Is Normal?

Authors:  Arjun K Manrai; Chirag J Patel; John P A Ioannidis
Journal:  JAMA       Date:  2018-05-15       Impact factor: 56.272

5.  Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations.

Authors:  Jimmy Z Liu; Suzanne van Sommeren; Hailiang Huang; Siew C Ng; Rudi Alberts; Atsushi Takahashi; Stephan Ripke; James C Lee; Luke Jostins; Tejas Shah; Shifteh Abedian; Jae Hee Cheon; Judy Cho; Naser E Dayani; Lude Franke; Yuta Fuyuno; Ailsa Hart; Ramesh C Juyal; Garima Juyal; Won Ho Kim; Andrew P Morris; Hossein Poustchi; William G Newman; Vandana Midha; Timothy R Orchard; Homayon Vahedi; Ajit Sood; Joseph Y Sung; Reza Malekzadeh; Harm-Jan Westra; Keiko Yamazaki; Suk-Kyun Yang; Jeffrey C Barrett; Behrooz Z Alizadeh; Miles Parkes; Thelma Bk; Mark J Daly; Michiaki Kubo; Carl A Anderson; Rinse K Weersma
Journal:  Nat Genet       Date:  2015-07-20       Impact factor: 41.307

6.  Using Genetic Distance to Infer the Accuracy of Genomic Prediction.

Authors:  Marco Scutari; Ian Mackay; David Balding
Journal:  PLoS Genet       Date:  2016-09-02       Impact factor: 5.917

7.  Fine-mapping inflammatory bowel disease loci to single-variant resolution.

Authors:  Hailiang Huang; Ming Fang; Luke Jostins; Maša Umićević Mirkov; Gabrielle Boucher; Carl A Anderson; Vibeke Andersen; Isabelle Cleynen; Adrian Cortes; François Crins; Mauro D'Amato; Valérie Deffontaine; Julia Dmitrieva; Elisa Docampo; Mahmoud Elansary; Kyle Kai-How Farh; Andre Franke; Ann-Stephan Gori; Philippe Goyette; Jonas Halfvarson; Talin Haritunians; Jo Knight; Ian C Lawrance; Charlie W Lees; Edouard Louis; Rob Mariman; Theo Meuwissen; Myriam Mni; Yukihide Momozawa; Miles Parkes; Sarah L Spain; Emilie Théâtre; Gosia Trynka; Jack Satsangi; Suzanne van Sommeren; Severine Vermeire; Ramnik J Xavier; Rinse K Weersma; Richard H Duerr; Christopher G Mathew; John D Rioux; Dermot P B McGovern; Judy H Cho; Michel Georges; Mark J Daly; Jeffrey C Barrett
Journal:  Nature       Date:  2017-06-28       Impact factor: 49.962

8.  Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.

Authors:  Christopher S Carlson; Tara C Matise; Kari E North; Christopher A Haiman; Megan D Fesinmeyer; Steven Buyske; Fredrick R Schumacher; Ulrike Peters; Nora Franceschini; Marylyn D Ritchie; David J Duggan; Kylee L Spencer; Logan Dumitrescu; Charles B Eaton; Fridtjof Thomas; Alicia Young; Cara Carty; Gerardo Heiss; Loic Le Marchand; Dana C Crawford; Lucia A Hindorff; Charles L Kooperberg
Journal:  PLoS Biol       Date:  2013-09-17       Impact factor: 8.029

9.  Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations.

Authors:  Amit V Khera; Mark Chaffin; Krishna G Aragam; Mary E Haas; Carolina Roselli; Seung Hoan Choi; Pradeep Natarajan; Eric S Lander; Steven A Lubitz; Patrick T Ellinor; Sekar Kathiresan
Journal:  Nat Genet       Date:  2018-08-13       Impact factor: 38.330

10.  A machine-learning heuristic to improve gene score prediction of polygenic traits.

Authors:  Guillaume Paré; Shihong Mao; Wei Q Deng
Journal:  Sci Rep       Date:  2017-10-04       Impact factor: 4.379

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  503 in total

Review 1.  Genetic Risk Scores.

Authors:  Robert P Igo; Tyler G Kinzy; Jessica N Cooke Bailey
Journal:  Curr Protoc Hum Genet       Date:  2019-12

Review 2.  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

3.  Runs of homozygosity in sub-Saharan African populations provide insights into complex demographic histories.

Authors:  Francisco C Ceballos; Scott Hazelhurst; Michèle Ramsay
Journal:  Hum Genet       Date:  2019-07-16       Impact factor: 4.132

4.  Ancestry-specific polygenic scores and SNP heritability of 25(OH)D in African- and European-ancestry populations.

Authors:  Kathryn E Hatchell; Qiongshi Lu; Scott J Hebbring; Erin D Michos; Alexis C Wood; Corinne D Engelman
Journal:  Hum Genet       Date:  2019-07-24       Impact factor: 4.132

5.  Perspective: The Clinical Use of Polygenic Risk Scores: Race, Ethnicity, and Health Disparities.

Authors:  Megan C Roberts; Muin J Khoury; George A Mensah
Journal:  Ethn Dis       Date:  2019-07-18       Impact factor: 1.847

6.  Geographic Variation and Bias in the Polygenic Scores of Complex Diseases and Traits in Finland.

Authors:  Sini Kerminen; Alicia R Martin; Jukka Koskela; Sanni E Ruotsalainen; Aki S Havulinna; Ida Surakka; Aarno Palotie; Markus Perola; Veikko Salomaa; Mark J Daly; Samuli Ripatti; Matti Pirinen
Journal:  Am J Hum Genet       Date:  2019-05-30       Impact factor: 11.025

Review 7.  African genetic diversity and adaptation inform a precision medicine agenda.

Authors:  Luisa Pereira; Leon Mutesa; Paulina Tindana; Michèle Ramsay
Journal:  Nat Rev Genet       Date:  2021-01-11       Impact factor: 53.242

8.  From one human genome to a complex tapestry of ancestry.

Authors:  Charles N Rotimi; Adebowale A Adeyemo
Journal:  Nature       Date:  2021-02       Impact factor: 49.962

9.  Negative selection on complex traits limits phenotype prediction accuracy between populations.

Authors:  Arun Durvasula; Kirk E Lohmueller
Journal:  Am J Hum Genet       Date:  2021-03-09       Impact factor: 11.025

10.  Leveraging correlations between variants in polygenic risk scores to detect heterogeneity in GWAS cohorts.

Authors:  Jie Yuan; Henry Xing; Alexandre Louis Lamy; Todd Lencz; Itsik Pe'er
Journal:  PLoS Genet       Date:  2020-09-21       Impact factor: 5.917

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