Literature DB >> 31186341

Addition of a 161-SNP polygenic risk score to family history-based risk prediction: impact on clinical management in non-BRCA1/2 breast cancer families.

Inge M M Lakeman1, Florentine S Hilbers1,2, Mar Rodríguez-Girondo3, Andrew Lee4, Maaike P G Vreeswijk1, Antoinette Hollestelle5, Caroline Seynaeve5, Hanne Meijers-Heijboer6, Jan C Oosterwijk7, Nicoline Hoogerbrugge8, Edith Olah9, Hans F A Vasen10, Christi J van Asperen11, Peter Devilee12,13.   

Abstract

BACKGROUND: The currently known breast cancer-associated single nucleotide polymorphisms (SNPs) are presently not used to guide clinical management. We explored whether a genetic test that incorporates a SNP-based polygenic risk score (PRS) is clinically meaningful in non-BRCA1/2 high-risk breast cancer families.
METHODS: 101 non-BRCA1/2 high-risk breast cancer families were included; 323 cases and 262 unaffected female relatives were genotyped. The 161-SNP PRS was calculated and standardised to 327 population controls (sPRS). Association analysis was performed using a Cox-type random effect regression model adjusted by family history. Updated individualised breast cancer lifetime risk scores were derived by combining the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm breast cancer lifetime risk with the effect of the sPRS.
RESULTS: The mean sPRS for cases and their unaffected relatives was 0.70 (SD=0.9) and 0.53 (SD=0.9), respectively. A significant association was found between sPRS and breast cancer, HR=1.16, 95% CI 1.03 to 1.28, p=0.026. Addition of the sPRS to risk prediction based on family history alone changed screening recommendations in 11.5%, 14.7% and 19.8 % of the women according to breast screening guidelines from the USA (National Comprehensive Cancer Network), UK (National Institute for Health and Care Excellence and the Netherlands (Netherlands Comprehensive Cancer Organisation), respectively.
CONCLUSION: Our results support the application of the PRS in risk prediction and clinical management of women from genetically unexplained breast cancer families. © Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.

Entities:  

Keywords:  cancer: breast; clinical genetics; genetic epidemiology; genetic screening/counselling; polygenic risk score

Mesh:

Substances:

Year:  2019        PMID: 31186341     DOI: 10.1136/jmedgenet-2019-106072

Source DB:  PubMed          Journal:  J Med Genet        ISSN: 0022-2593            Impact factor:   6.318


  10 in total

1.  Polygenic risk scores indicate extreme ages at onset of breast cancer in female BRCA1/2 pathogenic variant carriers.

Authors:  Rita K Schmutzler; Eitan Friedman; Eric Hahnen; Corinna Ernst; Julika Borde; Yael Laitman; Britta Blümcke; Dieter Niederacher; Konstantin Weber-Lassalle; Christian Sutter; Andreas Rump; Norbert Arnold; Shan Wang-Gohrke; Judit Horváth; Andrea Gehrig; Gunnar Schmidt; Véronique Dutrannoy; Juliane Ramser; Julia Hentschel; Alfons Meindl; Christopher Schroeder; Barbara Wappenschmidt; Christoph Engel; Karoline Kuchenbaecker
Journal:  BMC Cancer       Date:  2022-06-27       Impact factor: 4.638

Review 2.  Improving reporting standards for polygenic scores in risk prediction studies.

Authors:  Hannah Wand; Samuel A Lambert; Cecelia Tamburro; Michael A Iacocca; Jack W O'Sullivan; Catherine Sillari; Iftikhar J Kullo; Robb Rowley; Jacqueline S Dron; Deanna Brockman; Eric Venner; Mark I McCarthy; Antonis C Antoniou; Douglas F Easton; Robert A Hegele; Amit V Khera; Nilanjan Chatterjee; Charles Kooperberg; Karen Edwards; Katherine Vlessis; Kim Kinnear; John N Danesh; Helen Parkinson; Erin M Ramos; Megan C Roberts; Kelly E Ormond; Muin J Khoury; A Cecile J W Janssens; Katrina A B Goddard; Peter Kraft; Jaqueline A L MacArthur; Michael Inouye; Genevieve L Wojcik
Journal:  Nature       Date:  2021-03-10       Impact factor: 69.504

3.  Evaluating Polygenic Risk Scores for Breast Cancer in Women of African Ancestry.

Authors:  Zhaohui Du; Guimin Gao; Babatunde Adedokun; Thomas Ahearn; Kathryn L Lunetta; Gary Zirpoli; Melissa A Troester; Edward A Ruiz-Narváez; Stephen A Haddad; Parichoy PalChoudhury; Jonine Figueroa; Esther M John; Leslie Bernstein; Wei Zheng; Jennifer J Hu; Regina G Ziegler; Sarah Nyante; Elisa V Bandera; Sue A Ingles; Nicholas Mancuso; Michael F Press; Sandra L Deming; Jorge L Rodriguez-Gil; Song Yao; Temidayo O Ogundiran; Oladosu Ojengbe; Manjeet K Bolla; Joe Dennis; Alison M Dunning; Douglas F Easton; Kyriaki Michailidou; Paul D P Pharoah; Dale P Sandler; Jack A Taylor; Qin Wang; Clarice R Weinberg; Cari M Kitahara; William Blot; Katherine L Nathanson; Anselm Hennis; Barbara Nemesure; Stefan Ambs; Lara E Sucheston-Campbell; Jeannette T Bensen; Stephen J Chanock; Andrew F Olshan; Christine B Ambrosone; Olufunmilayo I Olopade; Joel Yarney; Baffour Awuah; Beatrice Wiafe-Addai; David V Conti; Julie R Palmer; Montserrat Garcia-Closas; Dezheng Huo; Christopher A Haiman
Journal:  J Natl Cancer Inst       Date:  2021-09-04       Impact factor: 11.816

4.  Simplified Breast Risk Tool Integrating Questionnaire Risk Factors, Mammographic Density, and Polygenic Risk Score: Development and Validation.

Authors:  Bernard Rosner; Rulla M Tamimi; Peter Kraft; Chi Gao; Yi Mu; Christopher Scott; Stacey J Winham; Celine M Vachon; Graham A Colditz
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2020-12-04       Impact factor: 4.090

5.  Clustering of known low and moderate risk alleles rather than a novel recessive high-risk gene in non-BRCA1/2 sib trios affected with breast cancer.

Authors:  Florentine S Hilbers; Peter J van 't Hof; Caro M Meijers; Hailiang Mei; Kyriaki Michailidou; Joe Dennis; Frans B L Hogervorst; Petra M Nederlof; Christi J van Asperen; Peter Devilee
Journal:  Int J Cancer       Date:  2020-05-30       Impact factor: 7.396

6.  Integrating Clinical and Polygenic Factors to Predict Breast Cancer Risk in Women Undergoing Genetic Testing.

Authors:  Elisha Hughes; Placede Tshiaba; Susanne Wagner; Thaddeus Judkins; Eric Rosenthal; Benjamin Roa; Shannon Gallagher; Stephanie Meek; Kathryn Dalton; Wade Hedegard; Carol A Adami; Danna F Grear; Susan M Domchek; Judy Garber; Johnathan M Lancaster; Jeffrey N Weitzel; Allison W Kurian; Jerry S Lanchbury; Alexander Gutin; Mark E Robson
Journal:  JCO Precis Oncol       Date:  2021-01-28

7.  Polygenic Risk Scores for Prediction of Gastric Cancer Based on Bioinformatics Screening and Validation of Functional lncRNA SNPs.

Authors:  Fujiao Duan; Chunhua Song; Peng Wang; Hua Ye; Liping Dai; Jianying Zhang; Kaijuan Wang
Journal:  Clin Transl Gastroenterol       Date:  2021-11-18       Impact factor: 4.488

8.  Association between a 46-SNP Polygenic Risk Score and melanoma risk in Dutch patients with familial melanoma.

Authors:  Thomas P Potjer; Tara W J van der Grinten; Inge M M Lakeman; Sander H Bollen; Mar Rodríguez-Girondo; Mark M Iles; Jennifer H Barrett; Lambertus A Kiemeney; Nelleke A Gruis; Christi J van Asperen; Nienke van der Stoep
Journal:  J Med Genet       Date:  2020-09-29       Impact factor: 6.318

Review 9.  Clinical applications of polygenic breast cancer risk: a critical review and perspectives of an emerging field.

Authors:  Tatiane Yanes; Mary-Anne Young; Bettina Meiser; Paul A James
Journal:  Breast Cancer Res       Date:  2020-02-17       Impact factor: 6.466

Review 10.  Understanding polygenic models, their development and the potential application of polygenic scores in healthcare.

Authors:  Chantal Babb de Villiers; Mark Kroese; Sowmiya Moorthie
Journal:  J Med Genet       Date:  2020-05-06       Impact factor: 6.318

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.