Literature DB >> 32620971

The emerging field of polygenic risk scores and perspective for use in clinical care.

Tatiane Yanes1, Aideen M McInerney-Leo1, Matthew H Law2,3, Shelly Cummings4.   

Abstract

Genetic testing is used widely for diagnostic, carrier and predictive testing in monogenic diseases. Until recently, there were no genetic testing options available for multifactorial complex diseases like heart disease, diabetes and cancer. Genome-wide association studies (GWAS) have been invaluable in identifying single-nucleotide polymorphisms (SNPs) associated with increased or decreased risk for hundreds of complex disorders. For a given disease, SNPs can be combined to generate a cumulative estimation of risk known as a polygenic risk score (PRS). After years of research, PRSs are increasingly used in clinical settings. In this article, we will review the literature on how both genome-wide and restricted PRSs are developed and the relative merit of each. The validation and evaluation of PRSs will also be discussed, including the recognition that PRS validity is intrinsically linked to the methodological and analytical approach of the foundation GWAS together with the ethnic characteristics of that cohort. Specifically, population differences may affect imputation accuracy, risk magnitude and direction. Even as PRSs are being introduced into clinical practice, there is a push to combine them with clinical and demographic risk factors to develop a holistic disease risk. The existing evidence regarding the clinical utility of PRSs is considered across four different domains: informing population screening programs, guiding therapeutic interventions, refining risk for families at high risk, and facilitating diagnosis and predicting prognostic outcomes. The evidence for clinical utility in relation to five well-studied disorders is summarized. The potential ethical, legal and social implications are also highlighted.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2020        PMID: 32620971     DOI: 10.1093/hmg/ddaa136

Source DB:  PubMed          Journal:  Hum Mol Genet        ISSN: 0964-6906            Impact factor:   6.150


  6 in total

1.  Personalised Risk Prediction in Hereditary Breast and Ovarian Cancer: A Protocol for a Multi-Centre Randomised Controlled Trial.

Authors:  Stephanie Archer; Nichola Fennell; Ellen Colvin; Rozelle Laquindanum; Meredith Mills; Romy Dennis; Francisca Stutzin Donoso; Rochelle Gold; Alice Fan; Kate Downes; James Ford; Antonis C Antoniou; Allison W Kurian; D Gareth Evans; Marc Tischkowitz
Journal:  Cancers (Basel)       Date:  2022-05-31       Impact factor: 6.575

2.  Genome-wide variants and polygenic risk scores for cognitive impairment following blood or marrow transplantation.

Authors:  Noha Sharafeldin; Jianqing Zhang; Purnima Singh; Alysia Bosworth; Yanjun Chen; Sunita K Patel; Xuexia Wang; Liton Francisco; Stephen J Forman; F Lennie Wong; Akinyemi I Ojesina; Smita Bhatia
Journal:  Bone Marrow Transplant       Date:  2022-04-04       Impact factor: 5.174

3.  False positive findings during genome-wide association studies with imputation: influence of allele frequency and imputation accuracy.

Authors:  Zhihui Zhang; Xiangjun Xiao; Wen Zhou; Dakai Zhu; Christopher I Amos
Journal:  Hum Mol Genet       Date:  2021-12-17       Impact factor: 5.121

4.  Genomic and Metabolomic Landscape of Right-Sided and Left-Sided Colorectal Cancer: Potential Preventive Biomarkers.

Authors:  Ming-Wei Su; Chung-Ke Chang; Chien-Wei Lin; Hou-Wei Chu; Tsen-Ni Tsai; Wei-Chih Su; Yen-Cheng Chen; Tsung-Kun Chang; Ching-Wen Huang; Hsiang-Lin Tsai; Chang-Chieh Wu; Huang-Chi Chou; Bei-Hao Shiu; Jaw-Yuan Wang
Journal:  Cells       Date:  2022-02-03       Impact factor: 6.600

5.  Assessing agreement between different polygenic risk scores in the UK Biobank.

Authors:  Lei Clifton; Jennifer A Collister; Xiaonan Liu; Thomas J Littlejohns; David J Hunter
Journal:  Sci Rep       Date:  2022-07-27       Impact factor: 4.996

6.  The Future of Precision Prevention for Advanced Melanoma.

Authors:  Katie J Lee; Brigid Betz-Stablein; Mitchell S Stark; Monika Janda; Aideen M McInerney-Leo; Liam J Caffery; Nicole Gillespie; Tatiane Yanes; H Peter Soyer
Journal:  Front Med (Lausanne)       Date:  2022-01-17
  6 in total

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