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Shang H, Ding Y, Venkateswaran V, Boulier K, Kathuria-Prakash N, Malidarreh PB, Luber JM, Pasaniuc B. Generalizability of PGS 313 for breast cancer risk in a Los Angeles biobank. HGG ADVANCES 2024; 5:100302. [PMID: 38704641 DOI: 10.1016/j.xhgg.2024.100302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 04/30/2024] [Accepted: 04/30/2024] [Indexed: 05/06/2024] Open
Abstract
Polygenic scores (PGSs) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors. One of the most well-validated PGSs in breast cancer to date is PGS313, which was developed from a Northern European biobank but has shown attenuated performance in non-European ancestries. We further investigate the generalizability of the PGS313 for American women of European (EA), African (AFR), Asian (EAA), and Latinx (HL) ancestry within one institution with a singular electronic health record (EHR) system, genotyping platform, and quality control process. We found that the PGS313 achieved overlapping areas under the receiver operator characteristic (ROC) curve (AUCs) in females of HL (AUC = 0.68, 95% confidence interval [CI] = 0.65-0.71) and EA ancestry (AUC = 0.70, 95% CI = 0.69-0.71) but lower AUCs for the AFR and EAA populations (AFR: AUC = 0.61, 95% CI = 0.56-0.65; EAA: AUC = 0.64, 95% CI = 0.60-0.680). While PGS313 is associated with hormone-receptor-positive (HR+) disease in EA Americans (odds ratio [OR] = 1.42, 95% CI = 1.16-1.64), this association is lost in African, Latinx, and Asian Americans. In summary, we found that PGS313 was significantly associated with breast cancer but with attenuated accuracy in women of AFR and EAA descent within a singular health system in Los Angeles. Our work further highlights the need for additional validation in diverse cohorts prior to the clinical implementation of PGSs.
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Affiliation(s)
- Helen Shang
- Division of Internal Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA; Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA.
| | - Yi Ding
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Kristin Boulier
- Division of Cardiology, Department of Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA
| | - Nikhita Kathuria-Prakash
- Division of Hematology-Oncology, Department of Medicine, Ronald Reagan UCLA Medical Center, Los Angeles, CA, USA
| | - Parisa Boodaghi Malidarreh
- Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA; Multi-Interprofessional Center for Health Informatics, University of Texas at Arlington, Arlington, TX, USA
| | - Jacob M Luber
- Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX, USA; Multi-Interprofessional Center for Health Informatics, University of Texas at Arlington, Arlington, TX, USA; Department of Bioengineering, University of Texas at Arlington, Arlington, TX, USA
| | - Bogdan Pasaniuc
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
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Jia G, Ping J, Guo X, Yang Y, Tao R, Li B, Ambs S, Barnard ME, Chen Y, Garcia-Closas M, Gu J, Hu JJ, Huo D, John EM, Li CI, Li JL, Nathanson KL, Nemesure B, Olopade OI, Pal T, Press MF, Sanderson M, Sandler DP, Shu XO, Troester MA, Yao S, Adejumo PO, Ahearn T, Brewster AM, Hennis AJM, Makumbi T, Ndom P, O'Brien KM, Olshan AF, Oluwasanu MM, Reid S, Butler EN, Huang M, Ntekim A, Qian H, Zhang H, Ambrosone CB, Cai Q, Long J, Palmer JR, Haiman CA, Zheng W. Genome-wide association analyses of breast cancer in women of African ancestry identify new susceptibility loci and improve risk prediction. Nat Genet 2024; 56:819-826. [PMID: 38741014 DOI: 10.1038/s41588-024-01736-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 03/25/2024] [Indexed: 05/16/2024]
Abstract
We performed genome-wide association studies of breast cancer including 18,034 cases and 22,104 controls of African ancestry. Genetic variants at 12 loci were associated with breast cancer risk (P < 5 × 10-8), including associations of a low-frequency missense variant rs61751053 in ARHGEF38 with overall breast cancer (odds ratio (OR) = 1.48) and a common variant rs76664032 at chromosome 2q14.2 with triple-negative breast cancer (TNBC) (OR = 1.30). Approximately 15.4% of cases with TNBC carried six risk alleles in three genome-wide association study-identified TNBC risk variants, with an OR of 4.21 (95% confidence interval = 2.66-7.03) compared with those carrying fewer than two risk alleles. A polygenic risk score (PRS) showed an area under the receiver operating characteristic curve of 0.60 for the prediction of breast cancer risk, which outperformed PRS derived using data from females of European ancestry. Our study markedly increases the population diversity in genetic studies for breast cancer and demonstrates the utility of PRS for risk prediction in females of African ancestry.
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Affiliation(s)
- Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yaohua Yang
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center of Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | | | - Yu Chen
- Division of Epidemiology, Department of Population Health, NYU Grossman School of Medicine, New York, NY, USA
| | | | - Jian Gu
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer J Hu
- Department of Public Health Sciences, University of Miami School of Medicine, Miami, FL, USA
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Esther M John
- Departments of Epidemiology & Population Health and of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher I Li
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - James L Li
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Katherine L Nathanson
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Renaissance School of Medicine, Stony Brook University, New York, NY, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Tuya Pal
- Division of Genetic Medicine, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Michael F Press
- Department of Pathology, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Melissa A Troester
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Elm & Carlton Streets, Buffalo, NY, USA
| | - Prisca O Adejumo
- Department of Nursing, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Abenaa M Brewster
- Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Anselm J M Hennis
- George Alleyne Chronic Disease Research Centre, University of the West Indies, Bridgetown, Barbados
- Department of Family, Population and Preventive Medicine, Stony Brook University, New York, NY, USA
| | | | - Paul Ndom
- Yaounde General Hospital, Yaounde, Cameroon
| | - Katie M O'Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Andrew F Olshan
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Mojisola M Oluwasanu
- Department of Health Promotion and Education, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Sonya Reid
- Division of Hematology and Oncology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ebonee N Butler
- Department of Epidemiology and Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Maosheng Huang
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Atara Ntekim
- Department of Radiation Oncology, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Huijun Qian
- Department of Statistics and Operation Research, University of North Carolina, Chapel Hill, NC, USA
| | - Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Elm & Carlton Streets, Buffalo, NY, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
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3
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Ochs-Balcom HM, Preus L, Du Z, Elston RC, Teerlink CC, Jia G, Guo X, Cai Q, Long J, Ping J, Li B, Stram DO, Shu XO, Sanderson M, Gao G, Ahearn T, Lunetta KL, Zirpoli G, Troester MA, Ruiz-Narváez EA, Haddad SA, Figueroa J, John EM, Bernstein L, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Mancuso N, Press MF, Deming SL, Rodriguez-Gil JL, Yao S, Ogundiran TO, Ojengbede O, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Sandler DP, Taylor JA, Wang Q, O’Brien KM, Weinberg CR, Kitahara CM, Blot W, Nathanson KL, Hennis A, Nemesure B, Ambs S, Sucheston-Campbell LE, Bensen JT, Chanock SJ, Olshan AF, Ambrosone CB, Olopade OI, the Ghana Breast Health Study Team, Conti DV, Palmer J, García-Closas M, Huo D, Zheng W, Haiman C. Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia. Hum Mol Genet 2024; 33:687-697. [PMID: 38263910 PMCID: PMC11000665 DOI: 10.1093/hmg/ddae002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/02/2024] [Accepted: 01/03/2024] [Indexed: 01/25/2024] Open
Abstract
BACKGROUND Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.
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Affiliation(s)
- Heather M Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY 14214, United States
| | - Leah Preus
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY 14214, United States
| | - Zhaohui Du
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
- Public Health Sciences, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave, N. Seattle, WA 98109, United States
| | - Robert C Elston
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, 10900 Euclid Avenue, Cleveland, OH 44106, United States
| | - Craig C Teerlink
- Department of Internal Medicine, University of Utah School of Medicine, 30 North Mario Capecchi Dr, 3rd Floor North, Salt Lake City, UT 84112, United States
| | - Guochong Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Xingyi Guo
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jie Ping
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Bingshan Li
- Department of Molecular Physiology and Biophysics, Vanderbilt University, 707 Light Hall 2215 Garland Avenue, Nashville, TN 37232, United States
| | - Daniel O Stram
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, 1005 Dr. DB Todd Jr, Blvd. Nashville, TN 37208, United States
| | - Guimin Gao
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, United States
| | - Thomas Ahearn
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University, 715 Albany St, Boston, MA 02118, United States
| | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Melissa A Troester
- Department of Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC 27599, United States
| | - Edward A Ruiz-Narváez
- Department of Nutritional Sciences, University of Michigan School of Public Health, 1860 SPH I, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Stephen A Haddad
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
- Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, 9 Little France Road, Edinburgh, EH16 4UX, United Kingdom
- Cancer Research UK Edinburgh Centre, Crewe Rd S, Edinburgh, EH4 2XR, United Kingdom
| | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, 3145 Porter Dr, Suite E223, MC 5393, Palo Alto, CA 94304, United States
- Department of Medicine (Oncology), Stanford University School of Medicine, 291 Campus Drive Li Ka Shing Building, Stanford, CA 94305, United States
| | - Leslie Bernstein
- Division of Biomarkers of Early Detection and Prevention Department of Population Sciences, Beckman Research Institute of the City of Hope, City of Hope Comprehensive Cancer Center, 1500 East Duarte Road, Duarte, CA 91010, United States
| | - Jennifer J Hu
- Sylvester Comprehensive Cancer Center and Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14th St, CRB 1511, Miami, FL 33136, United States
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Sarah Nyante
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, 130 Mason Farm Rd., Chapel Hill, NC 27599, United States
| | - Elisa V Bandera
- Cancer Epidemiology and Health Outcomes, Rutgers Cancer Institute of New Jersey, 120 Albany Street, Tower 2, 8th Floor, New Brunswick, NJ 08903, United States
| | - Sue A Ingles
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Nicholas Mancuso
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Michael F Press
- Department of Pathology, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1441 Eastlake Ave., Los Angeles, CA 90033, United States
| | - Sandra L Deming
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Jorge L Rodriguez-Gil
- Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, National Institutes of Health, 31 Center Dr, Bethesda, MD 20894, United States
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison, 750 Highland Ave., Madison, WI 53705, United States
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, United States
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Queen Elizabeth II Road, Ibadan, 200285, Nigeria
| | - Oladosu Ojengbede
- Center for Population and Reproductive Health, College of Medicine, University of Ibadan, UCH, Queen Elizabeth II Road, Ibadan, 200285, Nigeria
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Iroon Avenue 6, 2371 Ayius Dometios, Nicosia, Cyprus
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Research Laboratory, Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, 2 Worts Causeway, Cambridge, CB1 8RN, United Kingdom
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Clarice R Weinberg
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, PO Box 12233, Research Triangle Park, NC 27709, United States
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
- International Epidemiology Institute, 1455 Research Boulevard, Rockville, MD 20850, United States
| | - Katherine L Nathanson
- Department of Medicine, Abramson Cancer Center, The Perelman School of Medicine at the University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19140, United States
| | - Anselm Hennis
- Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Jemmotts Lane, Avalon, Bridgetown, Barbados
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, 100 Nicolls Road, Stony Brook, NY 11794, United States
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, 37 Convent Drive, Bethesda, MD 20892, United States
| | - Lara E Sucheston-Campbell
- College of Pharmacy, The Ohio State University, 217 Lloyd M. Parks Hall, 500 West 12th Ave., Columbus, OH 43210, United States
- College of Veterinary Medicine, The Ohio State University, 1900 Coffey Road, Columbus, OH 43210, United States
| | - Jeannette T Bensen
- Department of Epidemiology, Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, 135 Dauer Drive, CB 7435, Chapel Hill, NC 27599, United States
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, 170 Rosenau Hall, CB #7400, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Elm and Carlton Streets, Buffalo, NY 14263, United States
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics and Global Health, Department of Medicine, University of Chicago, 5841 S Maryland Avenue, Chicago, IL 60637, United States
| | | | - David V Conti
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
| | - Julie Palmer
- Slone Epidemiology Center, Boston University, L-7, 72 East Concord Street, Boston, MA 02118, United States
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, Department of Health and Human Services, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Bethesda, MD 20892, United States
| | - Dezheng Huo
- Department of Public Health Sciences, University of Chicago, 5841 S. Maryland Ave., Chicago, IL 60637, United States
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, 2525 West End Avenue, Nashville, TN 37203, United States
| | - Christopher Haiman
- Department of Preventive Population and Public Health Sciences, Keck School of Medicine and Norris Comprehensive Cancer Center, University of Southern California, 1450 Biggy Street, Los Angeles, CA 90033, United States
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Yiangou K, Mavaddat N, Dennis J, Zanti M, Wang Q, Bolla MK, Abubakar M, Ahearn TU, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Aronson KJ, Augustinsson A, Baten A, Behrens S, Bermisheva M, de Gonzalez AB, Białkowska K, Boddicker N, Bodelon C, Bogdanova NV, Bojesen SE, Brantley KD, Brauch H, Brenner H, Camp NJ, Canzian F, Castelao JE, Cessna MH, Chang-Claude J, Chenevix-Trench G, Chung WK, Colonna SV, Couch FJ, Cox A, Cross SS, Czene K, Daly MB, Devilee P, Dörk T, Dunning AM, Eccles DM, Eliassen AH, Engel C, Eriksson M, Evans DG, Fasching PA, Fletcher O, Flyger H, Fritschi L, Gago-Dominguez M, Gentry-Maharaj A, González-Neira A, Guénel P, Hahnen E, Haiman CA, Hamann U, Hartikainen JM, Ho V, Hodge J, Hollestelle A, Honisch E, Hooning MJ, Hoppe R, Hopper JL, Howell S, Howell A, Jakovchevska S, Jakubowska A, Jernström H, Johnson N, Kaaks R, Khusnutdinova EK, Kitahara CM, Koutros S, Kristensen VN, Lacey JV, Lambrechts D, Lejbkowicz F, Lindblom A, Lush M, Mannermaa A, Mavroudis D, Menon U, Murphy RA, Nevanlinna H, Obi N, Offit K, Park-Simon TW, Patel AV, Peng C, Peterlongo P, Pita G, Plaseska-Karanfilska D, Pylkäs K, Radice P, Rashid MU, Rennert G, Roberts E, Rodriguez J, Romero A, Rosenberg EH, Saloustros E, Sandler DP, Sawyer EJ, Schmutzler RK, Scott CG, Shu XO, Southey MC, Stone J, Taylor JA, Teras LR, van de Beek I, Willett W, Winqvist R, Zheng W, Vachon CM, Schmidt MK, Hall P, MacInnis RJ, Milne RL, Pharoah PD, Simard J, Antoniou AC, Easton DF, Michailidou K. Differences in polygenic score distributions in European ancestry populations: implications for breast cancer risk prediction. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.12.24302043. [PMID: 38410445 PMCID: PMC10896416 DOI: 10.1101/2024.02.12.24302043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
The 313-variant polygenic risk score (PRS313) provides a promising tool for breast cancer risk prediction. However, evaluation of the PRS313 across different European populations which could influence risk estimation has not been performed. Here, we explored the distribution of PRS313 across European populations using genotype data from 94,072 females without breast cancer, of European-ancestry from 21 countries participating in the Breast Cancer Association Consortium (BCAC) and 225,105 female participants from the UK Biobank. The mean PRS313 differed markedly across European countries, being highest in south-eastern Europe and lowest in north-western Europe. Using the overall European PRS313 distribution to categorise individuals leads to overestimation and underestimation of risk in some individuals from south-eastern and north-western countries, respectively. Adjustment for principal components explained most of the observed heterogeneity in mean PRS. Country-specific PRS distributions may be used to calibrate risk categories in individuals from different countries.
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Affiliation(s)
- Kristia Yiangou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus, 2371
| | - Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Maria Zanti
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus, 2371
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Mustapha Abubakar
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA, 20850
| | - Thomas U. Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA, 20850
| | - Irene L. Andrulis
- Fred A, Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada, M5G 1X5
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada, M5S 1A8
| | - Hoda Anton-Culver
- Department of Medicine, Genetic Epidemiology Research Institute, University of California Irvine, Irvine, CA, USA, 92617
| | - Natalia N. Antonenkova
- NN Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus, 223040
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Kristan J. Aronson
- Department of Public Health Sciences, and Cancer Research Institute, Queen’s University, Kingston, ON, Canada, K7L 3N6
| | | | - Adinda Baten
- Leuven Multidisciplinary Breast Center, Department of Oncology, Leuven Cancer Institute, University Hospitals Leuven, Leuven, Belgium, 3000
| | - Sabine Behrens
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Marina Bermisheva
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia, 450054
- St Petersburg State University, St, Petersburg, Russia, 199034
| | | | - Katarzyna Białkowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland, 71-252
| | - Nicholas Boddicker
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA, 55905
| | - Clara Bodelon
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Natalia V. Bogdanova
- NN Alexandrov Research Institute of Oncology and Medical Radiology, Minsk, Belarus, 223040
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany, 30625
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany, 30625
| | - Stig E. Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark, 2730
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark, 2730
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark, 2200
| | - Kristen D. Brantley
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
| | - Hiltrud Brauch
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany, 70376
- iFIT-Cluster of Excellence, University of Tübingen, Tübingen, Germany, 72074
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Partner Site Tübingen, Tübingen, Germany, 72074
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany, 69120
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Nicola J. Camp
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA, 84112
| | - Federico Canzian
- Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Jose E. Castelao
- Oncology and Genetics Unit, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS) Foundation, Complejo Hospitalario Universitario de Santiago, SERGAS, Vigo, Spain, 36312
| | - Melissa H. Cessna
- Department of Pathology, Intermountain Healthcare, Salt Lake City, UT, USA, 84143
- Intermountain Biorepository, Intermountain Healthcare, Salt Lake City, UT, USA, 84143
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
- Cancer Epidemiology Group, University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 20246
| | - Georgia Chenevix-Trench
- Cancer Research Program, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia, 4006
| | - Wendy K. Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA, 10032
| | - NBCS Collaborators
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital-Radiumhospitalet, Oslo, Norway, 0379
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway, 0450
- Department of Research, Vestre Viken Hospital, Drammen, Norway, 3019
- Section for Breast- and Endocrine Surgery, Department of Cancer, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital-Ullevål, Oslo, Norway, 0450
- Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway, 0379
- Department of Pathology, Akershus University Hospital, Lørenskog, Norway, 1478
- Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway, 0379
- Department of Oncology, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital-Radiumhospitalet, Oslo, Norway, 0379
- National Advisory Unit on Late Effects after Cancer Treatment, Oslo University Hospital, Oslo, Norway, 0379
- Department of Oncology, Akershus University Hospital, Lørenskog, Norway, 1478
- Oslo Breast Cancer Research Consortium, Oslo University Hospital, Oslo, Norway, 0379
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway, 0379
| | - Sarah V. Colonna
- Department of Internal Medicine and Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA, 84112
| | - Fergus J. Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA, 55905
| | - Angela Cox
- Division of Clinical Medicine, School of Medicine and Population Health, University of Sheffield, Sheffield, UK, S10 2TN
| | - Simon S. Cross
- Division of Neuroscience, School of Medicine and Population Health, University of Sheffield, Sheffield, UK, S10 2TN
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
| | - Mary B. Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA, USA, 19111
| | - Peter Devilee
- Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands, 2333 ZA
- Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands, 2333 ZA
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany, 30625
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Diana M. Eccles
- Faculty of Medicine, University of Southampton, Southampton, UK, SO17 1BJ
| | - A. Heather Eliassen
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA, 02115
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany, 04107
- LIFE - Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany, 04103
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
| | - D. Gareth Evans
- Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK, M13 9WL
- North West Genomics Laboratory Hub, Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK, M13 9WL
| | - Peter A. Fasching
- Department of Gynecology and Obstetrics, Comprehensive Cancer Center Erlangen-EMN, Friedrich-Alexander University Erlangen-Nuremberg, University Hospital Erlangen, Erlangen, Germany, 91054
| | - Olivia Fletcher
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK, SW7 3RP
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark, 2730
| | - Lin Fritschi
- School of Population Health, Curtin University, Perth, Western Australia, Australia, 6102
| | - Manuela Gago-Dominguez
- Cancer Genetics and Epidemiology Group, Genomic Medicine Group, Fundación Instituto de Investigación Sanitaria de Santiago de Compostela (FIDIS), Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain, 15706
| | - Aleksandra Gentry-Maharaj
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK, WC1V 6LJ
- Department of Women’s Cancer, Elizabeth Garrett Anderson Institute for Women’s Health, University College London, London, UK
| | - Anna González-Neira
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain, 28029
- Spanish Network on Rare Diseases (CIBERER)
| | - Pascal Guénel
- Team ‘Exposome and Heredity’, CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France, 94805
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
| | - Christopher A. Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA, 90033
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Jaana M. Hartikainen
- Cancer RC, University of Eastern Finland, Kuopio, Finland, 70210
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland, 70210
| | - Vikki Ho
- Health Innovation and Evaluation Hub, Université de Montréal Hospital Research Centre (CRCHUM), Montréal, Québec, Canada
| | - James Hodge
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Antoinette Hollestelle
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands, 3015 GD
| | - Ellen Honisch
- Department of Gynecology and Obstetrics, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany, 40225
| | - Maartje J. Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands, 3015 GD
| | - Reiner Hoppe
- Dr Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany, 70376
- University of Tübingen, Tübingen, Germany, 72074
| | - John L. Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
| | - Sacha Howell
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, UK
| | - Anthony Howell
- Division of Cancer Sciences, University of Manchester, Manchester, UK, M13 9PL
| | - ABCTB Investigators
- Australian Breast Cancer Tissue Bank, Westmead Institute for Medical Research, University of Sydney, Sydney, New South Wales, Australia, 2145
| | - kConFab Investigators
- Research Department, Peter MacCallum Cancer Center, Melbourne, Victoria, Australia, 3000
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Parkville, Victoria, Australia, 3000
| | - Simona Jakovchevska
- Research Centre for Genetic Engineering and Biotechnology ‘Georgi D, Efremov’, MASA, Skopje, Republic of North Macedonia, 1000
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland, 71-252
- Independent Laboratory of Molecular Biology and Genetic Diagnostics, Pomeranian Medical University, Szczecin, Poland, 171-252
| | - Helena Jernström
- Oncology, Clinical Sciences in Lund, Lund University, Lund, Sweden, 221 85
| | - Nichola Johnson
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK, SW7 3RP
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
| | - Elza K. Khusnutdinova
- Institute of Biochemistry and Genetics of the Ufa Federal Research Centre of the Russian Academy of Sciences, Ufa, Russia, 450054
- Department of Genetics and Fundamental Medicine, Ufa University of Science and Technology, Ufa, Russia, 450076
| | - Cari M. Kitahara
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA, 20892
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, MD, USA, 20850
| | - Vessela N. Kristensen
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway, 0450
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway, 0379
| | - James V. Lacey
- Department of Computational and Quantitative Medicine, City of Hope, Duarte, CA, USA, 91010
- City of Hope Comprehensive Cancer Center, City of Hope, Duarte, CA, USA, 91010
| | - Diether Lambrechts
- Laboratory for Translational Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium, 3000
- VIB Center for Cancer Biology, VIB, Leuven, Belgium, 3001
| | | | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden, 171 76
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden, 171 76
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Arto Mannermaa
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland, 70210
- Translational Cancer Research Area, University of Eastern Finland, Kuopio, Finland, 70210
- Biobank of Eastern Finland, Kuopio University Hospital, Kuopio, Finland
| | - Dimitrios Mavroudis
- Department of Medical Oncology, University Hospital of Heraklion, Heraklion, Greece, 711 10
| | - Usha Menon
- MRC Clinical Trials Unit, Institute of Clinical Trials and Methodology, University College London, London, UK, WC1V 6LJ
| | - Rachel A. Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada, V6T 1Z4
- Cancer Control Research, BC Cancer Agency, Vancouver, BC, Canada, V5Z 1L3
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland, 00290
| | - Nadia Obi
- Institute for Occupational and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 20246
- Institute for Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 20246
| | - Kenneth Offit
- Clinical Genetics Research Lab, Department of Cancer Biology and Genetics, Memorial Sloan Kettering Cancer Center, New York, NY, USA, 10065
- Clinical Genetics Service, Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA, 10065
| | | | - Alpa V. Patel
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Cheng Peng
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA, 02115
| | - Paolo Peterlongo
- Genome Diagnostics Program, IFOM ETS - the AIRC Institute of Molecular Oncology, Milan, Italy, 20139
| | - Guillermo Pita
- Human Genotyping Unit-CeGen, Spanish National Cancer Research Centre (CNIO), Madrid, Spain, 28029
| | - Dijana Plaseska-Karanfilska
- Research Centre for Genetic Engineering and Biotechnology ‘Georgi D, Efremov’, MASA, Skopje, Republic of North Macedonia, 1000
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland, 90220
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland, 90220
| | - Paolo Radice
- Unit of Predictice Medicine, Molecular Bases of Genetic Risk, Department of Research, Fondazione IRCCS Istituto Nazionale dei Tumori (INT), Milan, Italy, 20133
| | - Muhammad U. Rashid
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany, 69120
- Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and Research Centre (SKMCH & RC), Lahore, Pakistan, 54000
| | - Gad Rennert
- Technion, Faculty of Medicine and Association for Promotion of Research in Precision Medicine, Haifa, Israel
| | - Eleanor Roberts
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Juan Rodriguez
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
| | - Atocha Romero
- Medical Oncology Department, Hospital Universitario Puerta de Hierro, Madrid, Spain, 28222
| | - Efraim H. Rosenberg
- Department of Pathology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands, 1066 CX
| | | | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA, 27709
| | - Elinor J. Sawyer
- School of Cancer & Pharmaceutical Sciences, Comprehensive Cancer Centre, Guy’s Campus, King’s College London, London, UK
| | - Rita K. Schmutzler
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50937
- Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany, 50931
| | - Christopher G. Scott
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA, 55905
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA, 37232
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia, 3168
- Department of Clinical Pathology, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia, 3004
| | - Jennifer Stone
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Genetic Epidemiology Group, School of Population and Global Health, University of Western Australia, Perth, Western Australia, Australia, 6000
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA, 27709
- Epigenetic and Stem Cell Biology Laboratory, National Institute of Environmental Health Sciences, NIH, Research Triangle Park, NC, USA, 27709
| | - Lauren R. Teras
- Department of Population Science, American Cancer Society, Atlanta, GA, USA, 30303
| | - Irma van de Beek
- Department of Clinical Genetics, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands, 1066 CX
| | - Walter Willett
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA, 02115
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA, 02115
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Translational Medicine Research Unit, Biocenter Oulu, University of Oulu, Oulu, Finland, 90220
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre Oulu, Oulu, Finland, 90220
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA, 37232
| | - Celine M. Vachon
- Department of Quantitative Health Sciences, Division of Epidemiology, Mayo Clinic, Rochester, MN, USA, 55905
| | - Marjanka K. Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands, 1066 CX
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute - Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands, 1066 CX
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands, 2333 ZA
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, 171 65
- Department of Oncology, Södersjukhuset, Stockholm, Sweden, 118 83
| | - Robert J. MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia, 3004
| | - Roger L. Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia, 3010
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia, 3168
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia, 3004
| | - Paul D.P. Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, West Hollywood, CA, USA, 90069
| | - Jacques Simard
- Genomics Center, Centre Hospitalier Universitaire de Québec – Université Laval Research Center, Québec City, Québec, Canada, G1V 4G2
| | - Antonis C. Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK, CB1 8RN
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus, 2371
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK, CB1 8RN
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5
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Wilkerson AD, Gentle CK, Ortega C, Al-Hilli Z. Disparities in Breast Cancer Care-How Factors Related to Prevention, Diagnosis, and Treatment Drive Inequity. Healthcare (Basel) 2024; 12:462. [PMID: 38391837 PMCID: PMC10887556 DOI: 10.3390/healthcare12040462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
Breast cancer survival has increased significantly over the last few decades due to more effective strategies for prevention and risk modification, advancements in imaging detection, screening, and multimodal treatment algorithms. However, many have observed disparities in benefits derived from such improvements across populations and demographic groups. This review summarizes published works that contextualize modern disparities in breast cancer prevention, diagnosis, and treatment and presents potential strategies for reducing disparities. We conducted searches for studies that directly investigated and/or reported disparities in breast cancer prevention, detection, or treatment. Demographic factors, social determinants of health, and inequitable healthcare delivery may impede the ability of individuals and communities to employ risk-mitigating behaviors and prevention strategies. The disparate access to quality screening and timely diagnosis experienced by various groups poses significant hurdles to optimal care and survival. Finally, barriers to access and inequitable healthcare delivery patterns reinforce inequitable application of standards of care. Cumulatively, these disparities underlie notable differences in the incidence, severity, and survival of breast cancers. Efforts toward mitigation will require collaborative approaches and partnerships between communities, governments, and healthcare organizations, which must be considered equal stakeholders in the fight for equity in breast cancer care and outcomes.
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Affiliation(s)
- Avia D Wilkerson
- Department of General Surgery, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Corey K Gentle
- Department of General Surgery, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Camila Ortega
- Department of General Surgery, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Zahraa Al-Hilli
- Department of General Surgery, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, OH 44195, USA
- Breast Center, Integrated Surgical Institute, Cleveland Clinic, Cleveland, OH 44195, USA
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6
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Baliakas P, Munters AR, Kämpe A, Tesi B, Bondeson ML, Ladenvall C, Eriksson D. Integrating a Polygenic Risk Score into a clinical setting would impact risk predictions in familial breast cancer. J Med Genet 2024; 61:150-154. [PMID: 37580114 PMCID: PMC10850617 DOI: 10.1136/jmg-2023-109311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Accepted: 07/28/2023] [Indexed: 08/16/2023]
Abstract
BACKGROUND Low-impact genetic variants identified in population-based genetic studies are not routinely measured as part of clinical genetic testing in familial breast cancer (BC). We studied the consequences of integrating an established Polygenic Risk Score (PRS) (BCAC 313, PRS313) into clinical sequencing of women with familial BC in Sweden. METHODS We developed an add-on sequencing panel to capture 313 risk variants in addition to the clinical screening of hereditary BC genes. Index patients with no pathogenic variant from 87 families, and 1000 population controls, were included in comparative PRS calculations. Including detailed family history, sequencing results and tumour pathology information, we used BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.6 to estimate contralateral and lifetime risks without and with PRS313. RESULTS Women with BC but no pathogenic variants in hereditary BC genes have a higher PRS313 compared with population controls (mean+0.78 SD, p<3e-9). Implementing PRS313 in the clinical risk estimation before their BC diagnosis would have changed the recommended follow-up in 24%-45% of women. CONCLUSIONS Our results show the potential impact of incorporating PRS313 directly in the clinical genomic investigation of women with familial BC.
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Affiliation(s)
- Panagiotis Baliakas
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Arielle R Munters
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Anders Kämpe
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
| | - Bianca Tesi
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Genetics, Karolinska Institutet, Stockholm, Sweden
| | - Marie-Louise Bondeson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Claes Ladenvall
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Daniel Eriksson
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
- Department of Clinical Genetics, Akademiska Sjukhuset, Uppsala, Sweden
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7
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Zirpoli GR, Pfeiffer RM, Bertrand KA, Huo D, Lunetta KL, Palmer JR. Addition of polygenic risk score to a risk calculator for prediction of breast cancer in US Black women. Breast Cancer Res 2024; 26:2. [PMID: 38167144 PMCID: PMC10763003 DOI: 10.1186/s13058-023-01748-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Previous work in European ancestry populations has shown that adding a polygenic risk score (PRS) to breast cancer risk prediction models based on epidemiologic factors results in better discriminatory performance as measured by the AUC (area under the curve). Following publication of the first PRS to perform well in women of African ancestry (AA-PRS), we conducted an external validation of the AA-PRS and then evaluated the addition of the AA-PRS to a risk calculator for incident breast cancer in Black women based on epidemiologic factors (BWHS model). METHODS Data from the Black Women's Health Study, an ongoing prospective cohort study of 59,000 US Black women followed by biennial questionnaire since 1995, were used to calculate AUCs and 95% confidence intervals (CIs) for discriminatory accuracy of the BWHS model, the AA-PRS alone, and a new model that combined them. Analyses were based on data from 922 women with invasive breast cancer and 1844 age-matched controls. RESULTS AUCs were 0.577 (95% CI 0.556-0.598) for the BWHS model and 0.584 (95% CI 0.563-0.605) for the AA-PRS. For a model that combined estimates from the questionnaire-based BWHS model with the PRS, the AUC increased to 0.623 (95% CI 0.603-0.644). CONCLUSIONS This combined model represents a step forward for personalized breast cancer preventive care for US Black women, as its performance metrics are similar to those from models in other populations. Use of this new model may mitigate exacerbation of breast cancer disparities if and when it becomes feasible to include a PRS in routine health care decision-making.
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Affiliation(s)
- Gary R Zirpoli
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - Ruth M Pfeiffer
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
- Division of Cancer Epidemiology and Biostatistics, National Cancer Institute, Bethesda, USA.
| | - Kimberly A Bertrand
- Slone Epidemiology Center at Boston University, Boston, MA, USA
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Dezheng Huo
- Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA.
- Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
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8
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Kachuri L, Chatterjee N, Hirbo J, Schaid DJ, Martin I, Kullo IJ, Kenny EE, Pasaniuc B, Witte JS, Ge T. Principles and methods for transferring polygenic risk scores across global populations. Nat Rev Genet 2024; 25:8-25. [PMID: 37620596 PMCID: PMC10961971 DOI: 10.1038/s41576-023-00637-2] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2023] [Indexed: 08/26/2023]
Abstract
Polygenic risk scores (PRSs) summarize the genetic predisposition of a complex human trait or disease and may become a valuable tool for advancing precision medicine. However, PRSs that are developed in populations of predominantly European genetic ancestries can increase health disparities due to poor predictive performance in individuals of diverse and complex genetic ancestries. We describe genetic and modifiable risk factors that limit the transferability of PRSs across populations and review the strengths and weaknesses of existing PRS construction methods for diverse ancestries. Developing PRSs that benefit global populations in research and clinical settings provides an opportunity for innovation and is essential for health equity.
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Affiliation(s)
- Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jibril Hirbo
- Department of Medicine Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Iman Martin
- Division of Genomic Medicine, National Human Genome Research Institute, Bethesda, MD, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Biomedical Data Science, Stanford University, Stanford, CA, USA.
- Department of Genetics, Stanford University, Stanford, CA, USA.
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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9
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Gallagher JH, Vassy JL, Clayman ML. Navigating the uncertainty of precision cancer screening: The role of shared decision-making. PEC INNOVATION 2023; 2:100127. [PMID: 37214512 PMCID: PMC10194244 DOI: 10.1016/j.pecinn.2023.100127] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 01/20/2023] [Accepted: 01/23/2023] [Indexed: 05/24/2023]
Abstract
Objective Describe how applying a shared decision making (SDM) lens to the implementation of new technologies can improve patient-centeredness. Methods This paper argues that the emergence of polygenic risk scores (PRS) for cancer screening presents an illustrative opportunity to include SDM when novel technologies enter clinical care. Results PRS are novel tools that indicate an individual's genetic risk of a given disease relative to the population. PRS are anticipated to help identify individuals most and least likely to benefit from screening. However, PRS have several types of uncertainty, including validity across populations, disparate computational methods, and inclusion of different genomic data across laboratories. Conclusion Implementing SDM alongside new technologies could prove useful for their ethical and patient-centered utilization. SDM's importance as an approach to decision-making will not diminish, as evidence, uncertainty, and patient values will remain intrinsic to the art and science of clinical care. Innovation SDM can help providers and patients navigate the considerable uncertainty inherent in implementing new technologies, enabling decision-making based on existing evidence and patient values.
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Affiliation(s)
- Joseph H. Gallagher
- Virginia Commonwealth University School of Medicine, Richmond, VA, United States of America
| | - Jason L. Vassy
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Health Administration, Bedford MA and Boston MA, United States
- Harvard Medical School, Boston, MA United States
- Brigham and Women’s Hospital, Boston, MA, United States
- Population Precision Health, Ariadne Labs, Boston, MA, United States
| | - Marla L. Clayman
- Center for Healthcare Organization and Implementation Research (CHOIR), Veterans Health Administration, Bedford MA and Boston MA, United States
- UMass Chan School of Medicine, Department of Population and Quantitative Health Sciences, Worcester, MA, United States
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10
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Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel) 2023; 15:5380. [PMID: 38001640 PMCID: PMC10670420 DOI: 10.3390/cancers15225380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 10/26/2023] [Accepted: 11/03/2023] [Indexed: 11/26/2023] Open
Abstract
Single nucleotide polymorphisms (SNPs) in the form of a polygenic risk score (PRS) have emerged as a promising factor that could improve the predictive performance of breast cancer (BC) risk prediction tools. This study aims to appraise and critically assess the current evidence on these tools. Studies were identified using Medline, EMBASE and the Cochrane Library up to November 2022 and were included if they described the development and/ or validation of a BC risk prediction model using a PRS for women of the general population and if they reported a measure of predictive performance. We identified 37 articles, of which 29 combined genetic and non-genetic risk factors using seven different risk prediction tools. Most models (55.0%) were developed on populations from European ancestry and performed better than those developed on populations from other ancestry groups. Regardless of the number of SNPs in each PRS, models combining a PRS with genetic and non-genetic risk factors generally had better discriminatory accuracy (AUC from 0.52 to 0.77) than those using a PRS alone (AUC from 0.48 to 0.68). The overall risk of bias was considered low in most studies. BC risk prediction tools combining a PRS with genetic and non-genetic risk factors provided better discriminative accuracy than either used alone. Further studies are needed to cross-compare their clinical utility and readiness for implementation in public health practices.
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Affiliation(s)
- Cynthia Mbuya-Bienge
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Nora Pashayan
- Department of Applied Health Research, University College London, London WC1E 6BT, UK;
| | - Cornelia D. Kazemali
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
| | - Jacques Simard
- Endocrinology and Nephology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1V 4G2, Canada;
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada
| | - Hermann Nabi
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Quebec City, QC G1V 0A6, Canada; (C.M.-B.); (C.D.K.)
- Oncology Division, CHU de Québec-Université Laval Research Center, Quebec City, QC G1S 4L8, Canada;
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11
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Tao LR, Ye Y, Zhao H. Early breast cancer risk detection: a novel framework leveraging polygenic risk scores and machine learning. J Med Genet 2023; 60:960-964. [PMID: 37055164 DOI: 10.1136/jmg-2022-108582] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Accepted: 03/27/2023] [Indexed: 04/15/2023]
Abstract
BACKGROUND Breast cancer (BC) is the most common cancer and the second leading cause of cancer death in women; an estimated one in eight women in the USA will develop BC during her lifetime. However, current methods of BC screening, including clinical breast exams, mammograms, biopsies and others, are often underused due to limited access, expense and a lack of risk awareness, causing 30% (up to 80% in low-income and middle-income countries) of patients with BC to miss the precious early detection phase. METHODS This study creates a key step to supplement the current BC diagnostic pipeline: a prescreening platform, prior to traditional detection and diagnostic steps. We have developed BREast CAncer Risk Detection Application (BRECARDA), a novel framework that personalises BC risk assessment using artificial intelligence neural networks to incorporate relevant genetic and non-genetic risk factors. A polygenic risk score (PRS) was enhanced by employing AnnoPred and validated by fivefolds cross-validation, outperforming three existing state-of-the-art PRS methods. RESULTS We used data from 97 597 female participants of the UK BioBank to train our algorithm. Using the enhanced PRS thus trained together with non-genetic information, BRECARDA was evaluated in a testing dataset with 48 074 UK Biobank female participants and achieved a high accuracy of 94.28% and area under the curve of 0.7861. Our optimised AnnoPred outperformed other state-of-the-art methods on quantifying genetic risk, indicating its potential for supplementing the current BC detection tests, population screening and risk evaluation. CONCLUSION BRECARDA can enhance disease risk prediction, identify high-risk individuals for BC screening, facilitate disease diagnosis and improve population-level screening efficiency. It can serve as a valuable and supplemental platform to assist doctors in BC diagnosis and evaluation.
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Affiliation(s)
- Lynn Rose Tao
- Thomas Jefferson High School for Science and Technology, Alexandria, Virginia, USA
| | - Yixuan Ye
- Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, CT, USA
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12
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Zhang H, Zhan J, Jin J, Zhang J, Lu W, Zhao R, Ahearn TU, Yu Z, O'Connell J, Jiang Y, Chen T, Okuhara D, Garcia-Closas M, Lin X, Koelsch BL, Chatterjee N. A new method for multiancestry polygenic prediction improves performance across diverse populations. Nat Genet 2023; 55:1757-1768. [PMID: 37749244 PMCID: PMC10923245 DOI: 10.1038/s41588-023-01501-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 08/16/2023] [Indexed: 09/27/2023]
Abstract
Polygenic risk scores (PRSs) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning. We evaluated CT-SLEB and nine alternative methods with large-scale simulated genome-wide association studies (~19 million common variants) and datasets from 23andMe, Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank, involving 5.1 million individuals of diverse ancestry, with 1.18 million individuals from four non-European populations across 13 complex traits. Results demonstrated that CT-SLEB significantly improves PRS performance in non-European populations compared with simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offered insights into sample size requirements and SNP density effects on multiancestry risk prediction.
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Affiliation(s)
- Haoyu Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | | | - Jin Jin
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Jingning Zhang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wenxuan Lu
- Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA
| | - Ruzhang Zhao
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Zhi Yu
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | | | - Tony Chen
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Montserrat Garcia-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
- Division of Genetics and Epidemiology, Institute of Cancer Research, London, UK
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Statistics, Harvard University, Cambridge, MA, USA
| | | | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.
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13
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Herzog C, Jones A, Evans I, Zikan M, Cibula D, Harbeck N, Colombo N, Rådestad AF, Gemzell-Danielsson K, Pashayan N, Widschwendter M. DNA methylation at quantitative trait loci (mQTLs) varies with cell type and nonheritable factors and may improve breast cancer risk assessment. NPJ Precis Oncol 2023; 7:99. [PMID: 37758816 PMCID: PMC10533818 DOI: 10.1038/s41698-023-00452-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023] Open
Abstract
To individualise breast cancer (BC) prevention, markers to follow a person's changing environment and health extending beyond static genetic risk scores are required. Here, we analysed cervical and breast DNA methylation (n = 1848) and single nucleotide polymorphisms (n = 1442) and demonstrate that a linear combination of methylation levels at 104 BC-associated methylation quantitative trait loci (mQTL) CpGs, termed the WID™-qtBC index, can identify women with breast cancer in hormone-sensitive tissues (AUC = 0.71 [95% CI: 0.65-0.77] in cervical samples). Women in the highest combined risk group (high polygenic risk score and WID™-qtBC) had a 9.6-fold increased risk for BC [95% CI: 4.7-21] compared to the low-risk group and tended to present at more advanced stages. Importantly, the WID™-qtBC is influenced by non-genetic BC risk factors, including age and body mass index, and can be modified by a preventive pharmacological intervention, indicating an interaction between genome and environment recorded at the level of the epigenome. Our findings indicate that methylation levels at mQTLs in relevant surrogate tissues could enable integration of heritable and non-heritable factors for improved disease risk stratification.
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Affiliation(s)
- Chiara Herzog
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria
- Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria
| | - Allison Jones
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK
| | - Iona Evans
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK
| | - Michal Zikan
- Department of Gynecology and Obstetrics, Charles University in Prague, First Faculty of Medicine and Hospital Na Bulovce, Prague, Czech Republic
| | - David Cibula
- Gynaecologic Oncology Center, Department of Obstetrics and Gynecology, First Faculty of Medicine, Charles University in Prague, General University Hospital in Prague, Prague, Czech Republic
| | - Nadia Harbeck
- Breast Center, Department of Obstetrics and Gynecology and CCC Munich, LMU University Hospital, Munich, Germany
| | - Nicoletta Colombo
- Istituto Europeo di Oncologia, Milan, Italy
- University of Milano-Bicocca, Milan, Italy
| | | | | | - Nora Pashayan
- Department of Applied Health Research, University College London, London, UK
| | - Martin Widschwendter
- European Translational Oncology Prevention and Screening (EUTOPS) Institute, Milser Str. 10, 6060, Hall in Tirol, Austria.
- Research Institute for Biomedical Aging Research, Universität Innsbruck, 6020, Innsbruck, Austria.
- Department of Women's Cancer, UCL EGA Institute for Women's Health, University College London, Medical School Building, Room 340, 74 Huntley Street, WC1E 6AU, London, UK.
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden.
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14
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Roberts E, van Veen EM, Byers H, Barnett-Griness O, Gronich N, Lejbkowicz F, Pinchev M, Smith MJ, Howell A, Newman WG, Woodward ER, Harkness EF, Brentnall AR, Cuzick J, Rennert G, Howell SJ, Evans DG. Breast cancer polygenic risk scores derived in White European populations are not calibrated for women of Ashkenazi Jewish descent. Genet Med 2023; 25:100846. [PMID: 37061873 DOI: 10.1016/j.gim.2023.100846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 04/05/2023] [Accepted: 04/06/2023] [Indexed: 04/17/2023] Open
Abstract
PURPOSE Polygenic risk scores (PRSs) are a major component of accurate breast cancer (BC) risk prediction but require ethnicity-specific calibration. Ashkenazi Jewish (AJ) population is assumed to be of White European (WE) origin in some commercially available PRSs despite differing effect allele frequencies (EAFs). We conducted a case-control study of WE and AJ women from the Predicting Risk of Cancer at Screening Study. The Breast Cancer in Northern Israel Study provided a separate AJ population-based case-control validation series. METHODS All women underwent Illumina OncoArray single-nucleotide variation (SNV; formerly single-nucleotide polymorphism [SNP]) analysis. Two PRSs were assessed, SNV142 and SNV78. A total of 221 of 2243 WE women (discovery: cases = 111; controls = 110; validation: cases = 651; controls = 1772) and 221 AJ women (cases = 121; controls = 110) were included from the UK study; the Israeli series consisted of 2045 AJ women (cases = 1331; controls = 714). EAFs were obtained from the Genome Aggregation Database. RESULTS In the UK study, the mean SNV142 PRS demonstrated good calibration and discrimination in WE population, with mean PRS of 1.33 (95% CI 1.18-1.48) in cases and 1.01 (95% CI 0.89-1.13) in controls. In AJ women from Manchester, the mean PRS of 1.54 (1.38-1.70) in cases and 1.20 (1.08-1.32) in controls demonstrated good discrimination but overestimation of BC relative risk. After adjusting for EAFs for the AJ population, mean risk was corrected (mean SNV142 PRS cases = 1.30 [95% CI 1.16-1.44] and controls = 1.02 [95% CI 0.92-1.12]). This was recapitulated in the larger Israeli data set with good discrimination (area under the curve = 0.632 [95% CI 0.607-0.657] for SNV142). CONCLUSION AJ women should not be given BC relative risk predictions based on PRSs calibrated to EAFs from the WE population. PRSs need to be recalibrated using AJ-derived EAFs. A simple recalibration using the mean PRS adjustment ratio likely performs well.
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Affiliation(s)
- Eleanor Roberts
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Elke M van Veen
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Helen Byers
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Ofra Barnett-Griness
- Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel
| | - Naomi Gronich
- Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel; The Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Flavio Lejbkowicz
- Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel
| | - Mila Pinchev
- Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel
| | - Miriam J Smith
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Anthony Howell
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, United Kingdom
| | - William G Newman
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Emma R Woodward
- Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Elaine F Harkness
- Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom; Division of Informatics, Imaging & Data Sciences, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Adam R Brentnall
- Queen Mary University of London, Centre for Cancer Prevention, Wolfson Institute of Population Health, Charterhouse Square, London, United Kingdom
| | - Jack Cuzick
- Queen Mary University of London, Centre for Cancer Prevention, Wolfson Institute of Population Health, Charterhouse Square, London, United Kingdom
| | - Gad Rennert
- Department of Community Medicine and Epidemiology, Carmel Medical Center, Haifa, Israel; The Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Sacha J Howell
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, United Kingdom
| | - D Gareth Evans
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom; Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom; Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom; Nightingale/Prevent Breast Cancer Centre, Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester, United Kingdom; Manchester Breast Centre, Manchester Cancer Research Centre, The Christie Hospital, Manchester, United Kingdom.
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15
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King CB, Bychkovsky BL, Warner ET, King TA, Freedman RA, Mittendorf EA, Katlin F, Revette A, Crookes DM, Maniar N, Pace LE. Inequities in referrals to a breast cancer risk assessment and prevention clinic: a mixed methods study. BMC PRIMARY CARE 2023; 24:165. [PMID: 37626335 PMCID: PMC10464083 DOI: 10.1186/s12875-023-02126-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Accepted: 08/16/2023] [Indexed: 08/27/2023]
Abstract
BACKGROUND Inequitable access to personalized breast cancer screening and prevention may compound racial and ethnic disparities in outcomes. The Breast Cancer Personalized Risk Assessment, Education and Prevention (B-PREP) program, located within the Brigham and Women's Hospital (BWH) Comprehensive Breast Health Center (BHC), provides care to patients at high risk for developing breast cancer. We sought to characterize the differences between BWH primary care patients referred specifically to B-PREP for risk evaluation and those referred to the BHC for benign breast conditions. Through interviews with primary care clinicians, we sought to explore contributors to potentially inequitable B-PREP referral patterns. METHODS We used electronic health record data and the B-PREP clinical database to identify patients referred by primary care clinicians to the BHC or B-PREP between 2017 and 2020. We examined associations with likelihood of referral to B-PREP for risk assessment. Semi-structured interviews were conducted with nine primary care clinicians from six clinics to explore referral patterns. RESULTS Of 1789 patients, 78.0% were referred for benign breast conditions, and 21.5% for risk assessment. In multivariable analyses, Black individuals were less likely to be referred for risk than for benign conditions (OR 0.38, 95% CI:0.23-0.63) as were those with Medicaid/Medicare (OR 0.72, 95% CI:0.53-0.98; OR 0.52, 95% CI:0.27-0.99) and those whose preferred language was not English (OR 0.26, 95% CI:0.12-0.57). Interviewed clinicians described inconsistent approaches to risk assessment and variable B-PREP awareness. CONCLUSIONS In this single-site evaluation, among individuals referred by primary care clinicians for specialized breast care, Black, publicly-insured patients, and those whose preferred language was not English were less likely to be referred for risk assessment. Larger studies are needed to confirm these findings. Interventions to standardize breast cancer risk assessment in primary care may improve equity.
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Affiliation(s)
- Claire B King
- Comprehensive Breast Health Center, Brigham and Women's Hospital, Boston, MA, USA
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Brittany L Bychkovsky
- Comprehensive Breast Health Center, Brigham and Women's Hospital, Boston, MA, USA
- Division of Cancer Genetics and Prevention, Dana-Farber Cancer Institute, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Erica T Warner
- Harvard Medical School, Boston, MA, USA
- Massachusetts General Hospital, Boston, MA, USA
| | - Tari A King
- Comprehensive Breast Health Center, Brigham and Women's Hospital, Boston, MA, USA
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
- Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Rachel A Freedman
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA
- Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Elizabeth A Mittendorf
- Comprehensive Breast Health Center, Brigham and Women's Hospital, Boston, MA, USA
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
- Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Fisher Katlin
- Comprehensive Breast Health Center, Brigham and Women's Hospital, Boston, MA, USA
- Division of Breast Surgery, Department of Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Anna Revette
- Division of Population Science, Dana-Farber Cancer Institute, Boston, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Danielle M Crookes
- Department of Health Sciences, Northeastern University, Boston, MA, USA
- Department of Sociology and Anthropology, Northeastern University, Boston, MA, USA
| | - Neil Maniar
- Department of Health Sciences, Northeastern University, Boston, MA, USA
| | - Lydia E Pace
- Comprehensive Breast Health Center, Brigham and Women's Hospital, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- Division of Women's Health, Brigham and Women's Hospital, Boston, MA, USA.
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16
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Kurniansyah N, Goodman MO, Khan AT, Wang J, Feofanova E, Bis JC, Wiggins KL, Huffman JE, Kelly T, Elfassy T, Guo X, Palmas W, Lin HJ, Hwang SJ, Gao Y, Young K, Kinney GL, Smith JA, Yu B, Liu S, Wassertheil-Smoller S, Manson JE, Zhu X, Chen YDI, Lee IT, Gu CC, Lloyd-Jones DM, Zöllner S, Fornage M, Kooperberg C, Correa A, Psaty BM, Arnett DK, Isasi CR, Rich SS, Kaplan RC, Redline S, Mitchell BD, Franceschini N, Levy D, Rotter JI, Morrison AC, Sofer T. Evaluating the use of blood pressure polygenic risk scores across race/ethnic background groups. Nat Commun 2023; 14:3202. [PMID: 37268629 PMCID: PMC10238525 DOI: 10.1038/s41467-023-38990-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Accepted: 05/24/2023] [Indexed: 06/04/2023] Open
Abstract
We assess performance and limitations of polygenic risk scores (PRSs) for multiple blood pressure (BP) phenotypes in diverse population groups. We compare "clumping-and-thresholding" (PRSice2) and LD-based (LDPred2) methods to construct PRSs from each of multiple GWAS, as well as multi-PRS approaches that sum PRSs with and without weights, including PRS-CSx. We use datasets from the MGB Biobank, TOPMed study, UK biobank, and from All of Us to train, assess, and validate PRSs in groups defined by self-reported race/ethnic background (Asian, Black, Hispanic/Latino, and White). For both SBP and DBP, the PRS-CSx based PRS, constructed as a weighted sum of PRSs developed from multiple independent GWAS, perform best across all race/ethnic backgrounds. Stratified analysis in All of Us shows that PRSs are better predictive of BP in females compared to males, individuals without obesity, and middle-aged (40-60 years) compared to older and younger individuals.
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Affiliation(s)
- Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Matthew O Goodman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
| | - Alyna T Khan
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jiongming Wang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Elena Feofanova
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, MA, USA
| | - Tanika Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Tali Elfassy
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Xiuqing Guo
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Henry J Lin
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Shih-Jen Hwang
- The Population Sciences Branch of the National Heart, Lung and Blood Institute, Bethesda, MD, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Kendra Young
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Gregory L Kinney
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Simin Liu
- Center for Global Cardiometabolic Health, Department of Epidemiology, Brown University, Providence, RI, USA
- Department of Medicine, Brown University, Providence, RI, USA
| | - Sylvia Wassertheil-Smoller
- Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - JoAnn E Manson
- Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA
| | - Yii-Der Ida Chen
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - I-Te Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung City, 40705, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei, 11221, Taiwan
| | - C Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Adolfo Correa
- Departments of Medicine and Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Bruce M Psaty
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Donna K Arnett
- Office of the Provost, University of South Carolina, Columbia, SC, USA
| | - Carmen R Isasi
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Robert C Kaplan
- Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA
| | - Braxton D Mitchell
- Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Daniel Levy
- The Population Sciences Branch of the National Heart, Lung and Blood Institute, Bethesda, MD, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Jerome I Rotter
- Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
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17
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Luoh SW, Minnier J, Zhao H, Gao L. Predicting Breast Cancer Risk for Women Veterans of African Ancestry in the Million Veteran Program. Health Equity 2023; 7:303-306. [PMID: 37284538 PMCID: PMC10240329 DOI: 10.1089/heq.2023.0011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2023] [Indexed: 06/08/2023] Open
Abstract
Breast cancer is a leading cause of cancer and, therefore, a major health threat for women in the United States and worldwide. We have seen over the years major advances in breast cancer prevention and care. Breast cancer screening with mammography leads to reduction in breast cancer mortality, and breast cancer prevention treatment with antiestrogens results in reduction in breast cancer incidence. More progress, however, is urgently needed for this common cancer that affects 1 in 11 American women in their lifetime. Not all women have the same breast cancer risk. A personalized approach is highly desirable as women with higher breast cancer risk may benefit from more intense breast cancer screening and/or prevention intervention while lower risk women may be spared with the cost, inconvenience, and emotional burden of these procedures. In addition to age, demographics, family history, lifestyle, and personal health, genetics is an important determinant of an individual's risk for breast cancer. Over the past 10 years, advances in cancer genomics identified multiple common genetic variants from population studies that collectively can contribute significantly to an individual's breast cancer risk. The effects of these genetic variants can be summarized as a "polygenic risk score" (PRS). We are among the first groups to prospectively evaluate the performance of these risk prediction instruments among women veterans of the Million Veteran Program (MVP). A 313-variant PRS (PRS313) predicted incident breast cancer for a prospective cohort of European (EUR) ancestry women veterans with an area under the receiver operating characteristic curve (AUC) of 0.622. The PRS313 performed less well for AFR ancestry however, with an AUC of 0.579. This is not surprising as most genome-wide association studies were conducted in people of European ancestry. This is an important area of health disparity and unmet need. The large population size and diversity of the MVP provide a unique and important opportunity to explore novel approaches to produce accurate and clinically useful genetic risk prediction instruments for minority populations.
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Affiliation(s)
- Shiuh-Wen Luoh
- VA Portland Health Care System, Portland, Oregon, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
| | - Jessica Minnier
- VA Portland Health Care System, Portland, Oregon, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
- OHSU-PSU School of Public Health, Portland, Oregon, USA
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, VA Connecticut Health Care System, New Haven, Connecticut, USA
| | - Lina Gao
- VA Portland Health Care System, Portland, Oregon, USA
- Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA
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18
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Lakeman IMM, Rodríguez-Girondo MDM, Lee A, Celosse N, Braspenning ME, van Engelen K, van de Beek I, van der Hout AH, Gómez García EB, Mensenkamp AR, Ausems MGEM, Hooning MJ, Adank MA, Hollestelle A, Schmidt MK, van Asperen CJ, Devilee P. Clinical applicability of the Polygenic Risk Score for breast cancer risk prediction in familial cases. J Med Genet 2023; 60:327-336. [PMID: 36137616 DOI: 10.1136/jmg-2022-108502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 07/19/2022] [Indexed: 11/04/2022]
Abstract
BACKGROUND Common low-risk variants are presently not used to guide clinical management of familial breast cancer (BC). We explored the additive impact of a 313-variant-based Polygenic Risk Score (PRS313) relative to standard gene testing in non-BRCA1/2 Dutch BC families. METHODS We included 3918 BC cases from 3492 Dutch non-BRCA1/2 BC families and 3474 Dutch population controls. The association of the standardised PRS313 with BC was estimated using a logistic regression model, adjusted for pedigree-based family history. Family history of the controls was imputed for this analysis. SEs were corrected to account for relatedness of individuals. Using the BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) V.5 model, lifetime risks were retrospectively calculated with and without individual PRS313. For 2586 cases and 2584 controls, the carrier status of pathogenic variants (PVs) in ATM, CHEK2 and PALB2 was known. RESULTS The family history-adjusted PRS313 was significantly associated with BC (per SD OR=1.97, 95% CI 1.84 to 2.11). Including the PRS313 in BOADICEA family-based risk prediction would have changed screening recommendations in up to 27%, 36% and 34% of cases according to BC screening guidelines from the USA, UK and the Netherlands (National Comprehensive Cancer Network, National Institute for Health and Care Excellence, and Netherlands Comprehensive Cancer Organisation), respectively. For the population controls, without information on family history, this was up to 39%, 44% and 58%, respectively. Among carriers of PVs in known moderate BC susceptibility genes, the PRS313 had the largest impact for CHEK2 and ATM. CONCLUSIONS Our results support the application of the PRS313 in risk prediction for genetically uninformative BC families and families with a PV in moderate BC risk genes.
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Affiliation(s)
- Inge M M Lakeman
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Mar D M Rodríguez-Girondo
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Andrew Lee
- Public Health and Primary Care, University of Cambridge Centre for Cancer Genetic Epidemiology, Cambridge, UK
| | - Nandi Celosse
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Merel E Braspenning
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Klaartje van Engelen
- Department of Human Genetics, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | - Irma van de Beek
- Department of Human Genetics, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | - Annemiek H van der Hout
- Department of Clinical Genetics, University Medical Centre Groningen, Groningen, The Netherlands
| | - Encarna B Gómez García
- Department of Clinical Genetics, Maastricht University Medical Centre+, Maastricht, The Netherlands
| | - Arjen R Mensenkamp
- Department of Human Genetics, University Medical Center Nijmegen, Nijmegen, The Netherlands
| | - Margreet G E M Ausems
- Department of Medical Genetics, University Medical Centre Utrecht, Utrecht, The Netherlands
| | - Maartje J Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Muriel A Adank
- Family Cancer Clinic, Antoni van Leeuwenhoek Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Antoinette Hollestelle
- Department of Medical Oncology, Erasmus MC Cancer Institute, Erasmus Medical Center, Rotterdam, The Netherlands
| | - Marjanka K Schmidt
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Division of Psychosocial Research and Epidemiology, Antoni van Leeuwenhoek Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - Christi J van Asperen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Peter Devilee
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
- Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
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19
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Ayoub A, Lapointe J, Nabi H, Pashayan N. Risk-Stratified Breast Cancer Screening Incorporating a Polygenic Risk Score: A Survey of UK General Practitioners’ Knowledge and Attitudes. Genes (Basel) 2023; 14:genes14030732. [PMID: 36981003 PMCID: PMC10048009 DOI: 10.3390/genes14030732] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/10/2023] [Accepted: 03/13/2023] [Indexed: 03/19/2023] Open
Abstract
A polygenic risk score (PRS) quantifies the aggregated effects of common genetic variants in an individual. A ‘personalised breast cancer risk assessment’ combines PRS with other genetic and nongenetic risk factors to offer risk-stratified screening and interventions. Large-scale studies are evaluating the clinical utility and feasibility of implementing risk-stratified screening; however, General Practitioners’ (GPs) views remain largely unknown. This study aimed to explore GPs’: (i) knowledge of risk-stratified screening; (ii) attitudes towards risk-stratified screening; and (iii) preferences for continuing professional development. A cross-sectional online survey of UK GPs was conducted between July–August 2022. The survey was distributed by the Royal College of General Practitioners and via other mailing lists and social media. In total, 109 GPs completed the survey; 49% were not familiar with the concept of PRS. Regarding risk-stratified screening pathways, 75% agreed with earlier and more frequent screening for women at high risk, 43% neither agreed nor disagreed with later and less screening for women at lower-than-average risk, and 55% disagreed with completely removing screening for women at much lower risk. In total, 81% felt positive about the potential impact of risk-stratified screening towards patients and 62% felt positive about the potential impact on their practice. GPs selected training of healthcare professionals as the priority for future risk-stratified screening implementation, preferring online formats for learning. The results suggest limited knowledge of PRS and risk-stratified screening amongst GPs. Training—preferably using online learning formats—was identified as the top priority for future implementation. GPs felt positive about the potential impact of risk-stratified screening; however, there was hesitance and disagreement towards a low-risk screening pathway.
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Affiliation(s)
- Aya Ayoub
- National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK
- Correspondence:
| | - Julie Lapointe
- Oncology Division, CHU de Québec-Université Laval Research Center, Québec City, QC G1R 3S3, Canada
| | - Hermann Nabi
- Oncology Division, CHU de Québec-Université Laval Research Center, Québec City, QC G1R 3S3, Canada
- Department of Social and Preventive Medicine, Faculty of Medicine, Université Laval, Québec City, QC G1V 0A6, Canada
| | - Nora Pashayan
- Department of Applied Health Research, University College London (UCL), London WC1E 7HB, UK
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20
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Mavaddat N, Ficorella L, Carver T, Lee A, Cunningham AP, Lush M, Dennis J, Tischkowitz M, Downes K, Hu D, Hahnen E, Schmutzler RK, Stockley TL, Downs GS, Zhang T, Chiarelli AM, Bojesen SE, Liu C, Chung WK, Pardo M, Feliubadaló L, Balmaña J, Simard J, Antoniou AC, Easton DF. Incorporating Alternative Polygenic Risk Scores into the BOADICEA Breast Cancer Risk Prediction Model. Cancer Epidemiol Biomarkers Prev 2023; 32:422-427. [PMID: 36649146 PMCID: PMC9986688 DOI: 10.1158/1055-9965.epi-22-0756] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 11/09/2022] [Accepted: 01/10/2023] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND The multifactorial risk prediction model BOADICEA enables identification of women at higher or lower risk of developing breast cancer. BOADICEA models genetic susceptibility in terms of the effects of rare variants in breast cancer susceptibility genes and a polygenic component, decomposed into an unmeasured and a measured component - the polygenic risk score (PRS). The current version was developed using a 313 SNP PRS. Here, we evaluated approaches to incorporating this PRS and alternative PRS in BOADICEA. METHODS The mean, SD, and proportion of the overall polygenic component explained by the PRS (α2) need to be estimated. $\alpha $ was estimated using logistic regression, where the age-specific log-OR is constrained to be a function of the age-dependent polygenic relative risk in BOADICEA; and using a retrospective likelihood (RL) approach that models, in addition, the unmeasured polygenic component. RESULTS Parameters were computed for 11 PRS, including 6 variations of the 313 SNP PRS used in clinical trials and implementation studies. The logistic regression approach underestimates $\alpha $, as compared with the RL estimates. The RL $\alpha $ estimates were very close to those obtained by assuming proportionality to the OR per 1 SD, with the constant of proportionality estimated using the 313 SNP PRS. Small variations in the SNPs included in the PRS can lead to large differences in the mean. CONCLUSIONS BOADICEA can be readily adapted to different PRS in a manner that maintains consistency of the model. IMPACT : The methods described facilitate comprehensive breast cancer risk assessment.
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Affiliation(s)
- Nasim Mavaddat
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Lorenzo Ficorella
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Tim Carver
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Andrew Lee
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Alex P. Cunningham
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Michael Lush
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Marc Tischkowitz
- Department of Medical Genetics and National Institute for Health Research, Cambridge Biomedical Research Centre, The University of Cambridge, Cambridge, United Kingdom
| | - Kate Downes
- Cambridge Genomics Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Donglei Hu
- Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, California
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Rita K. Schmutzler
- Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Center for Molecular Medicine Cologne (CMMC), Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Tracy L. Stockley
- Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, The University of Toronto, Ontario, Canada
- Division of Clinical Laboratory Genetics, Laboratory Medicine Program, University Health Network, Toronto, Canada
| | - Gregory S. Downs
- Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
- Division of Clinical Laboratory Genetics, Laboratory Medicine Program, University Health Network, Toronto, Canada
| | - Tong Zhang
- Advanced Molecular Diagnostics Laboratory, Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | - Anna M. Chiarelli
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Ontario Health, Cancer Care Ontario, Toronto, Ontario, Canada
| | - Stig E. Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Wendy K. Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, New York
| | - Monica Pardo
- Hereditary Cancer Genetics Group, Vall d'Hebron Institut d'Oncologia, Barcelona, Spain
| | - Lidia Feliubadaló
- Hereditary Cancer Program, Catalan Institute of Oncology (ICO), L'Hospitalet de Llobregat, Spain
- Program in Molecular Mechanisms and Experimental Therapy in Oncology (Oncobell), IDIBELL, L'Hospitalet de Llobregat, Spain
- Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Madrid, Spain
| | - Judith Balmaña
- Hereditary Cancer Genetics Group, Vall d'Hebron Institut d'Oncologia, Barcelona, Spain
- Medical Oncology Department, University Hospital of Vall d'Hebron, Barcelona, Spain
| | - Jacques Simard
- Department of Molecular Medicine, Université Laval and CHU de Québec-Université Laval Research Center, Québec, Canada
| | - Antonis C. Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
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21
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Jiao Y, Truong T, Eon-Marchais S, Mebirouk N, Caputo SM, Dondon MG, Karimi M, Le Gal D, Beauvallet J, Le Floch É, Dandine-Roulland C, Bacq-Daian D, Olaso R, Albuisson J, Audebert-Bellanger S, Berthet P, Bonadona V, Buecher B, Caron O, Cavaillé M, Chiesa J, Colas C, Collonge-Rame MA, Coupier I, Delnatte C, De Pauw A, Dreyfus H, Fert-Ferrer S, Gauthier-Villars M, Gesta P, Giraud S, Gladieff L, Golmard L, Lasset C, Lejeune-Dumoulin S, Léoné M, Limacher JM, Lortholary A, Luporsi É, Mari V, Maugard CM, Mortemousque I, Mouret-Fourme E, Nambot S, Noguès C, Popovici C, Prieur F, Pujol P, Sevenet N, Sobol H, Toulas C, Uhrhammer N, Vaur D, Venat L, Boland-Augé A, Guénel P, Deleuze JF, Stoppa-Lyonnet D, Andrieu N, Lesueur F. Association and performance of polygenic risk scores for breast cancer among French women presenting or not a familial predisposition to the disease. Eur J Cancer 2023; 179:76-86. [PMID: 36509001 DOI: 10.1016/j.ejca.2022.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 10/26/2022] [Accepted: 11/06/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND Three partially overlapping breast cancer polygenic risk scores (PRS) comprising 77, 179 and 313 SNPs have been proposed for European-ancestry women by the Breast Cancer Association Consortium (BCAC) for improving risk prediction in the general population. However, the effect of these SNPs may vary from one country to another and within a country because of other factors. OBJECTIVE To assess their associated risk and predictive performance in French women from (1) the CECILE population-based case-control study, (2) BRCA1 or BRCA2 (BRCA1/2) pathogenic variant (PV) carriers from the GEMO study, and (3) familial breast cancer cases with no BRCA1/2 PV and unrelated controls from the GENESIS study. RESULTS All three PRS were associated with breast cancer in all studies, with odds ratios per standard deviation varying from 1.7 to 2.0 in CECILE and GENESIS, and hazard ratios varying from 1.1 to 1.4 in GEMO. The predictive performance of PRS313 in CECILE was similar to that reported in BCAC but lower than that in GENESIS (area under the receiver operating characteristic curve (AUC) = 0.67 and 0.75, respectively). PRS were less performant in BRCA2 and BRCA1 PV carriers (AUC = 0.58 and 0.54 respectively). CONCLUSION Our results are in line with previous validation studies in the general population and in BRCA1/2 PV carriers. Additionally, we showed that PRS may be of clinical utility for women with a strong family history of breast cancer and no BRCA1/2 PV, and for those carrying a predicted PV in a moderate-risk gene like ATM, CHEK2 or PALB2.
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Affiliation(s)
- Yue Jiao
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Thérèse Truong
- Université Paris-Saclay, UVSQ, INSERM, U1018, Gustave Roussy, CESP, Team Exposome and Heredity, Villejuif, France
| | - Séverine Eon-Marchais
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Noura Mebirouk
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Sandrine M Caputo
- PSL Research University, Paris, France; Department of Genetics, Institut Curie, Paris, France
| | - Marie-Gabrielle Dondon
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Mojgan Karimi
- Université Paris-Saclay, UVSQ, INSERM, U1018, Gustave Roussy, CESP, Team Exposome and Heredity, Villejuif, France
| | - Dorothée Le Gal
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Juana Beauvallet
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Édith Le Floch
- Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Claire Dandine-Roulland
- Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Delphine Bacq-Daian
- Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Robert Olaso
- Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Juliette Albuisson
- Centre de Lutte contre le Cancer Georges François Leclerc, Dijon, France
| | | | - Pascaline Berthet
- Département de Biopathologie, Centre François Baclesse, Caen, France; INSERM, U1245, Rouen, France
| | - Valérie Bonadona
- Université Claude Bernard Lyon 1, Villeurbanne, France; CNRS UMR 5558, Centre Léon Bérard, Unité de Prévention et épidémiologie Génétique, Lyon, France
| | - Bruno Buecher
- PSL Research University, Paris, France; Department of Genetics, Institut Curie, Paris, France
| | - Olivier Caron
- Gustave Roussy, Département de Médecine Oncologique, Villejuif, France
| | - Mathias Cavaillé
- Université Clermont Auvergne, UMR INSERM, U1240, Clermont Ferrand, France; Département d'Oncogénétique, Centre Jean Perrin, Clermont Ferrand, France
| | - Jean Chiesa
- UF de Génétique Médicale et Cytogénétique, CHRU Caremeau, Nîmes, France
| | - Chrystelle Colas
- PSL Research University, Paris, France; Department of Genetics, Institut Curie, Paris, France; INSERM, U830, Paris, France
| | - Marie-Agnès Collonge-Rame
- Service Génétique et Biologie du Développement - Histologie, CHU Hôpital Saint-Jacques, Besançon, France
| | - Isabelle Coupier
- Hôpital Arnaud de Villeneuve, CHU Montpellier, Service de Génétique Médicale et Oncogénétique, Montpellier, France; INSERM, U896, CRCM Val d'Aurelle, Montpellier, France
| | - Capucine Delnatte
- Institut de Cancérologie de l'Ouest, Unité d'Oncogénétique, Saint Herblain, France
| | - Antoine De Pauw
- PSL Research University, Paris, France; Department of Genetics, Institut Curie, Paris, France
| | - Hélène Dreyfus
- Clinique Sainte Catherine, Avignon, CHU de Grenoble, Grenoble, France; Hôpital Couple-Enfant, Département de Génétique, Grenoble, France
| | | | - Marion Gauthier-Villars
- PSL Research University, Paris, France; Department of Genetics, Institut Curie, Paris, France
| | - Paul Gesta
- CH Georges Renon, Service d'Oncogénétique Régional Poitou-Charentes, Niort, France
| | - Sophie Giraud
- Hospices Civils de Lyon, Service de Génétique, Groupement Hospitalier Est, Bron, France
| | - Laurence Gladieff
- Institut Claudius Regaud - IUCT-Oncopole, Service d'Oncologie Médicale, Toulouse, France
| | - Lisa Golmard
- PSL Research University, Paris, France; Department of Genetics, Institut Curie, Paris, France
| | - Christine Lasset
- Université Claude Bernard Lyon 1, Villeurbanne, France; CNRS UMR 5558, Centre Léon Bérard, Unité de Prévention et épidémiologie Génétique, Lyon, France
| | | | - Mélanie Léoné
- Hospices Civils de Lyon, Service de Génétique, Groupement Hospitalier Est, Bron, France
| | | | - Alain Lortholary
- Service d'Oncologie Médicale, Centre Catherine de Sienne, Nantes, France; Hôpital Privé du Confluent, Nantes, France
| | - Élisabeth Luporsi
- Service de Génétique UF4128 CHR Metz-Thionville, Hôpital de Mercy, Metz, France
| | - Véronique Mari
- Unité d'Oncogénétique, Centre Antoine Lacassagne, Nice, France
| | - Christine M Maugard
- Génétique Oncologique Moléculaire, UF1422, Département d'Oncobiologie, LBBM, Hôpitaux Universitaires de Strasbourg, Strasbourg, France; UF6948 Génétique Oncologique Clinique, évaluation Familiale et Suivi, Strasbourg, France
| | | | | | - Sophie Nambot
- Centre de Lutte contre le Cancer Georges François Leclerc, Dijon, France; Institut GIMI, CHU de Dijon, Hôpital d'Enfants, France; Oncogénétique, Dijon, France
| | - Catherine Noguès
- Département d'Anticipation et de Suivi des Cancers, Oncogénétique Clinique, Institut Paoli-Calmettes, Marseille, France; Aix Marseille Université, INSERM, IRD, SESSTIM, Marseille, France
| | - Cornel Popovici
- Département d'Anticipation et de Suivi des Cancers, Oncogénétique Clinique, Institut Paoli-Calmettes, Marseille, France
| | - Fabienne Prieur
- CHU de Saint-Etienne; Hôpital Nord, Service de Génétique, Saint-Etienne, France
| | - Pascal Pujol
- Hôpital Arnaud de Villeneuve, CHU Montpellier, Service de Génétique Médicale et Oncogénétique, Montpellier, France; INSERM, U896, CRCM Val d'Aurelle, Montpellier, France
| | | | - Hagay Sobol
- Département d'Anticipation et de Suivi des Cancers, Oncogénétique Clinique, Institut Paoli-Calmettes, Marseille, France
| | - Christine Toulas
- Institut Claudius Regaud - IUCT-Oncopole, Service d'Oncologie Médicale, Toulouse, France
| | - Nancy Uhrhammer
- Centre Jean Perrin, LBM OncoGenAuvergne, Clermont Ferrand, France
| | - Dominique Vaur
- Département de Biopathologie, Centre François Baclesse, Caen, France; INSERM, U1245, Rouen, France
| | - Laurence Venat
- Hôpital Universitaire Dupuytren, Service d'Oncologie Médicale, Limoges, France
| | - Anne Boland-Augé
- Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Pascal Guénel
- Université Paris-Saclay, UVSQ, INSERM, U1018, Gustave Roussy, CESP, Team Exposome and Heredity, Villejuif, France
| | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine, Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Dominique Stoppa-Lyonnet
- Department of Genetics, Institut Curie, Paris, France; Département d'Oncogénétique, Centre Jean Perrin, Clermont Ferrand, France; Université Paris-Cité, Paris, France
| | - Nadine Andrieu
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France
| | - Fabienne Lesueur
- INSERM, U900, Paris, France; Institut Curie, Paris, France; Mines ParisTech, Fontainebleau, France; PSL Research University, Paris, France.
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22
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Hughes E, Wagner S, Pruss D, Bernhisel R, Probst B, Abkevich V, Simmons T, Hullinger B, Judkins T, Rosenthal E, Roa B, Domchek SM, Eng C, Garber J, Gary M, Klemp J, Mukherjee S, Offit K, Olopade OI, Vijai J, Weitzel JN, Whitworth P, Yehia L, Gordon O, Pederson H, Kurian A, Slavin TP, Gutin A, Lanchbury JS. Development and Validation of a Breast Cancer Polygenic Risk Score on the Basis of Genetic Ancestry Composition. JCO Precis Oncol 2022; 6:e2200084. [PMID: 36331239 PMCID: PMC9666117 DOI: 10.1200/po.22.00084] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 07/11/2022] [Accepted: 09/08/2022] [Indexed: 08/12/2023] Open
Abstract
PURPOSE Polygenic risk scores (PRSs) for breast cancer (BC) risk stratification have been developed primarily in women of European ancestry. Their application to women of non-European ancestry has lagged because of the lack of a formal approach to incorporate genetic ancestry and ancestry-dependent variant frequencies and effect sizes. Here, we propose a multiple-ancestry PRS (MA-PRS) that addresses these issues and may be useful in the development of equitable PRSs across other cancers and common diseases. MATERIALS AND METHODS Women referred for hereditary cancer testing were divided into consecutive cohorts for development (n = 189,230) and for independent validation (n = 89,126). Individual genetic composition as fractions of three reference ancestries (African, East Asian, and European) was determined from ancestry-informative single-nucleotide polymorphisms. The MA-PRS is a combination of three ancestry-specific PRSs on the basis of genetic ancestral composition. Stratification of risk was evaluated by multivariable logistic regression models controlling for family cancer history. Goodness-of-fit analysis compared expected with observed relative risks by quantiles of the MA-PRS distribution. RESULTS In independent validation, the MA-PRS was significantly associated with BC risk in the full cohort (odds ratio, 1.43; 95% CI, 1.40 to 1.46; P = 8.6 × 10-308) and within each major ancestry. The top decile of the MA-PRS consistently identified patients with two-fold increased risk of developing BC. Goodness-of-fit tests showed that the MA-PRS was well calibrated and predicted BC risk accurately in the tails of the distribution for both European and non-European women. CONCLUSION The MA-PRS uses genetic ancestral composition to expand the utility of polygenic risk prediction to non-European women. Inclusion of genetic ancestry in polygenic risk prediction presents an opportunity for more personalized treatment decisions for women of varying and mixed ancestries.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | - Susan M. Domchek
- Basser Center for BRCA, University of Pennsylvania, Philadelphia, PA
| | - Charis Eng
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH
| | | | | | - Jennifer Klemp
- The University of Kansas Cancer Center, The University of Kansas Medical Center, Kansas City, KS
| | | | - Kenneth Offit
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | - Joseph Vijai
- Memorial Sloan Kettering Cancer Center, New York, NY
| | | | | | - Lamis Yehia
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH
| | - Ora Gordon
- Providence Health and Services, Renton, WA
| | - Holly Pederson
- Medical Breast Services, Cleveland Clinic, Cleveland, OH
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23
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Gao G, Zhao F, Ahearn TU, Lunetta KL, Troester MA, Du Z, Ogundiran TO, Ojengbede O, Blot W, Nathanson KL, Domchek SM, Nemesure B, Hennis A, Ambs S, McClellan J, Nie M, Bertrand K, Zirpoli G, Yao S, Olshan AF, Bensen JT, Bandera EV, Nyante S, Conti DV, Press MF, Ingles SA, John EM, Bernstein L, Hu JJ, Deming-Halverson SL, Chanock SJ, Ziegler RG, Rodriguez-Gil JL, Sucheston-Campbell LE, Sandler DP, Taylor JA, Kitahara CM, O’Brien KM, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Wang Q, Figueroa J, Biritwum R, Adjei E, Wiafe S, Ambrosone CB, Zheng W, Olopade OI, García-Closas M, Palmer JR, Haiman CA, Huo D. Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach. Hum Mol Genet 2022; 31:3133-3143. [PMID: 35554533 PMCID: PMC9476624 DOI: 10.1093/hmg/ddac102] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 03/29/2022] [Accepted: 04/26/2022] [Indexed: 11/13/2022] Open
Abstract
Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.
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Affiliation(s)
- Guimin Gao
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Fangyuan Zhao
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Thomas U Ahearn
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Melissa A Troester
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Zhaohui Du
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Temidayo O Ogundiran
- Department of Surgery, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oladosu Ojengbede
- Centre for Population & Reproductive Health, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - William Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Katherine L Nathanson
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Susan M Domchek
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
| | - Anselm Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY 11794, USA
- University of the West Indies, Bridgetown, Bardados
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Julian McClellan
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Mark Nie
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | | | - Gary Zirpoli
- Slone Epidemiology Center, Boston University, Boston, MA 02215, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Andrew F Olshan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jeannette T Bensen
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Elisa V Bandera
- Cancer Prevention and Control Program, Rutgers Cancer Institute of New Jersey, New Brunswick, NJ 08903, USA
| | - Sarah Nyante
- Department of Radiology, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA
| | - David V Conti
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Michael F Press
- Department of Pathology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Esther M John
- Departments of Epidemiology & Population Health and of Medicine (Oncology) and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Leslie Bernstein
- Biomarkers of Early Detection and Prevention, Department of Population Sciences, Beckman Research Institute, City of Hope Comprehensive Cancer Center, Duarte, CA 91010, USA
| | - Jennifer J Hu
- Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Sandra L Deming-Halverson
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Regina G Ziegler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Jorge L Rodriguez-Gil
- Genomics, Development and Disease Section, Genetic Disease Research Branch, National Human Genome Research Institute, Bethesda, MD 20894, USA
| | - Lara E Sucheston-Campbell
- Department of Veterinary Biosciences, College of Veterinary Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Dale P Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Jack A Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Cari M Kitahara
- Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Katie M O’Brien
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709, USA
| | - Manjeet K Bolla
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Joe Dennis
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Kyriaki Michailidou
- Biostatistics Unit, The Cyprus Institute of Neurology & Genetics, Nicosia 2371, Cyprus
| | - Paul D P Pharoah
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Qin Wang
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge CB1 8RN, UK
| | - Jonine Figueroa
- Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh EH16 5TJ, UK
- Cancer Research UK Edinburgh Centre, Edinburgh EH4 2XR, UK
| | | | | | - Seth Wiafe
- School of Public Health, Loma Linda University, Loma Linda, CA 92350, USA
| | | | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY 14203, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN 37232, USA
| | - Olufunmilayo I Olopade
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD 20850, USA
| | - Julie R Palmer
- Slone Epidemiology Center, Boston University, Boston, MA 02215, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Dezheng Huo
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
- Center for Clinical Cancer Genetics & Global Health, The University of Chicago, Chicago, IL 60637, USA
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24
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Singhal SK, Byun JS, Yan T, Yancey R, Caban A, Gil Hernandez S, Bufford S, Hewitt SM, Winfield J, Pradhan JS, Mustkov V, McDonald JA, Pérez-Stable EJ, Napoles AM, Vohra N, De Siervi A, Yates C, Davis MB, Yang M, Tsai YC, Weissman AM, Gardner K. Protein expression of the gp78 E3-ligase predicts poor breast cancer outcome based on race. JCI Insight 2022; 7:157465. [PMID: 35639484 PMCID: PMC9310521 DOI: 10.1172/jci.insight.157465] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 05/20/2022] [Indexed: 11/17/2022] Open
Abstract
Women of African ancestry suffer higher rates of breast cancer mortality compared to all other groups in the United States. Though the precise reasons for these disparities remain unclear, many recent studies have implicated a role for differences in tumor biology. Using an epitope-validated antibody against the endoplasmic reticulum-associated degradation (ERAD) E3 ubiquitin ligase, gp78, we show that elevated levels of gp78 in patient breast cancer cells predict poor survival. Moreover, high levels of gp78 are associated with poor outcomes in both ER-positive and ER-negative tumors, and breast cancers expressing elevated amounts of gp78 protein are enriched in gene expression pathways that influence cell cycle, metabolism, receptor-mediated signaling, and cell stress response pathways. In multivariate analysis adjusted for subtype and grade, gp78 protein is an independent predictor of poor outcomes in women of African ancestry. Furthermore, gene expression signatures, derived from patients stratified by gp78 protein expression, are strong predictors of recurrence and pathological complete response in retrospective clinical trial data and share many common features with gene sets previously identified to be overrepresented in breast cancers based on race. These findings implicate a prominent role for gp78 in tumor progression and offer new insights into our understanding of racial differences in breast cancer outcomes.
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Affiliation(s)
- Sandeep K Singhal
- Department of Pathology, University of North Dakota, Grand Forks, United States of America
| | - Jung S Byun
- Intramural Research Program, National Institutes of Minority Health and Health Disparities, Bethesda, United States of America
| | - Tingfen Yan
- Intramural Research Program, National Institutes of Minority Health and Health Disparities, Bethesda, United States of America
| | - Ryan Yancey
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, United States of America
| | - Ambar Caban
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, United States of America
| | - Sara Gil Hernandez
- Intramural Research Program, National Institutes of Minority Health and Health Disparities, Bethesda, United States of America
| | - Sediqua Bufford
- Masters of Science Biotechnology, Morehouse School of Medicine, Atlanta, United States of America
| | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, United States of America
| | - Joy Winfield
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, United States of America
| | - Jaya Sarin Pradhan
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, United States of America
| | - Vesco Mustkov
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, United States of America
| | - Jasmine A McDonald
- Department of Epidemiology, Columbia University Medical Center, New York, United States of America
| | - Eliseo J Pérez-Stable
- Intramural Research Program, National Institutes of Minority Health and Health Disparities, Bethesda, United States of America
| | - Anna Maria Napoles
- Intramural Research Program, National Institutes of Minority Health and Health Disparities, Bethesda, United States of America
| | - Nasreen Vohra
- Brody School of Medicine, East Carolina University, Greenville, United States of America
| | - Adriana De Siervi
- Directora del Laboratorio de Oncología Molecular y Nuevos Blancos Terapéut, CONICET, Buenos Aiers, Argentina
| | - Clayton Yates
- Department of Biology and Center for Cancer Research, Tuskegee University, Tuskegee, United States of America
| | - Melissa B Davis
- Department of Surgery (Breast Surgery & Oncology), Weill Cornell Medicine, New York, United States of America
| | - Mei Yang
- Laboratory of Protein Dynamics and Signaling, National Cancer Institute, Frederick, United States of America
| | - Yien Che Tsai
- Laboratory of Protein Dynamics and Signaling, National Cancer Institute, Frederick, United States of America
| | - Allan M Weissman
- Laboratory of Protein Dynamics and Signaling, National Cancer Institute, Frederick, United States of America
| | - Kevin Gardner
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, United States of America
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25
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Mars N, Kerminen S, Feng YCA, Kanai M, Läll K, Thomas LF, Skogholt AH, della Briotta Parolo P, Neale BM, Smoller JW, Gabrielsen ME, Hveem K, Mägi R, Matsuda K, Okada Y, Pirinen M, Palotie A, Ganna A, Martin AR, Ripatti S. Genome-wide risk prediction of common diseases across ancestries in one million people. CELL GENOMICS 2022; 2:None. [PMID: 35591975 PMCID: PMC9010308 DOI: 10.1016/j.xgen.2022.100118] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 08/24/2021] [Accepted: 03/18/2022] [Indexed: 12/14/2022]
Abstract
Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate. All four PRSs had similar accuracy across European and Asian populations, with poorer transferability in the smaller group of individuals of African ancestry. The PRSs had highly similar effect sizes in different populations of European ancestry, and in early- and late-settlement regions with different recent population bottlenecks in Finland. Comparing genome-wide PRSs to PRSs containing a smaller number of variants, the highly polygenic, genome-wide PRSs generally displayed higher effect sizes and better transferability across global ancestries. Our findings indicate that in the populations investigated, the current genome-wide polygenic scores for common diseases have potential for clinical utility within different health-care settings for individuals of European ancestry, but that the utility in individuals of African ancestry is currently much lower.
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Affiliation(s)
- Nina Mars
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland
| | - Sini Kerminen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland
| | - Yen-Chen A. Feng
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Laurent F. Thomas
- Department of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway,K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway,BioCore - Bioinformatics Core Facility, Norwegian University of Science and Technology, Trondheim, Norway
| | - Anne Heidi Skogholt
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Pietro della Briotta Parolo
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland
| | | | | | - Benjamin M. Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Harvard Medical School, Boston, MA, USA
| | - Maiken E. Gabrielsen
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway,HUNT Research Center, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Kristian Hveem
- K. G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health, Norwegian University of Science and Technology, Trondheim, Norway
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan,Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Matti Pirinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Department of Public Health, University of Helsinki, Helsinki, Finland,Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Andrea Ganna
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alicia R. Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA,Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA,Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Biomedicum 2U, Tukholmankatu 8, 00290 Helsinki, Finland,Department of Public Health, University of Helsinki, Helsinki, Finland,Broad Institute of MIT and Harvard, Cambridge, MA, USA,Corresponding author
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26
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Wang L, Desai H, Verma SS, Le A, Hausler R, Verma A, Judy R, Doucette A, Gabriel PE, Nathanson KL, Damrauer SM, Mowery DL, Ritchie MD, Kember RL, Maxwell KN. Performance of polygenic risk scores for cancer prediction in a racially diverse academic biobank. Genet Med 2022; 24:601-609. [PMID: 34906489 PMCID: PMC9680700 DOI: 10.1016/j.gim.2021.10.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 08/09/2021] [Accepted: 10/22/2021] [Indexed: 01/08/2023] Open
Abstract
PURPOSE Genome-wide association studies have identified hundreds of single nucleotide variations (formerly single nucleotide polymorphisms) associated with several cancers, but the predictive ability of polygenic risk scores (PRSs) is unclear, especially among non-Whites. METHODS PRSs were derived from genome-wide significant single-nucleotide variations for 15 cancers in 20,079 individuals in an academic biobank. We evaluated the improvement in discriminatory accuracy by including cancer-specific PRS in patients of genetically-determined African and European ancestry. RESULTS Among the individuals of European genetic ancestry, PRSs for breast, colon, melanoma, and prostate were significantly associated with their respective cancers. Among the individuals of African genetic ancestry, PRSs for breast, colon, prostate, and thyroid were significantly associated with their respective cancers. The area under the curve of the model consisting of age, sex, and principal components was 0.621 to 0.710, and it increased by 1% to 4% with the inclusion of PRS in individuals of European genetic ancestry. In individuals of African genetic ancestry, area under the curve was overall higher in the model without the PRS (0.723-0.810) but increased by <1% with the inclusion of PRS for most cancers. CONCLUSION PRS moderately increased the ability to discriminate the cancer status in individuals of European but not African ancestry. Further large-scale studies are needed to identify ancestry-specific genetic factors in non-White populations to incorporate PRS into cancer risk assessment.
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Affiliation(s)
- Louise Wang
- Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Heena Desai
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Shefali S Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Anh Le
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Ryan Hausler
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Anurag Verma
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Renae Judy
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Abigail Doucette
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA
| | - Peter E Gabriel
- Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA; Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Katherine L Nathanson
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA; Division of Translational Medicine and Human Genetics, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Scott M Damrauer
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Corporal Michael J. Crescenz VA Medical Center, U.S. Department of Veterans Affairs, Philadelphia, PA
| | - Danielle L Mowery
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Rachel L Kember
- Corporal Michael J. Crescenz VA Medical Center, U.S. Department of Veterans Affairs, Philadelphia, PA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Kara N Maxwell
- Division of Hematology/Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA; Corporal Michael J. Crescenz VA Medical Center, U.S. Department of Veterans Affairs, Philadelphia, PA.
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27
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Laza-Vásquez C, Codern-Bové N, Cardona-Cardona À, Hernández-Leal MJ, Pérez-Lacasta MJ, Carles-Lavila M, Rué M. Views of health professionals on risk-based breast cancer screening and its implementation in the Spanish National Health System: A qualitative discussion group study. PLoS One 2022; 17:e0263788. [PMID: 35120169 PMCID: PMC8815913 DOI: 10.1371/journal.pone.0263788] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 01/26/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND With the aim of increasing benefits and decreasing harms, risk-based breast cancer screening has been proposed as an alternative to age-based screening. This study explores barriers and facilitators to implementing a risk-based breast cancer screening program from the perspective of health professionals, in the context of a National Health Service. METHODS Socio-constructivist qualitative research carried out in Catalonia (Spain), in the year 2019. Four discussion groups were conducted, with a total of 29 health professionals from primary care, breast cancer screening programs, hospital breast units, epidemiology units, and clinical specialties. A descriptive-interpretive thematic analysis was performed. RESULTS Identified barriers included resistance to reducing the number of screening exams for low-risk women; resistance to change for health professionals; difficulties in risk communication; lack of conclusive evidence of the benefits of risk-based screening; limited economic resources; and organizational transformation. Facilitators include benefits of risk-based strategies for high and low-risk women; women's active role in their health care; proximity of women and primary care professionals; experience of health professionals in other screening programs; and greater efficiency of a risk-based screening program. Organizational and administrative changes in the health system, commitment by policy makers, training of health professionals, and educational interventions addressed to the general population will be required. CONCLUSIONS Despite the expressed difficulties, participants supported the implementation of risk-based screening. They highlighted its benefits, especially for women at high risk of breast cancer and those under 50 years of age, and assumed a greater efficiency of the risk-based program compared to the aged-based one. Future studies should assess the efficiency and feasibility of risk-based breast cancer screening for its transfer to clinical practice.
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Affiliation(s)
- Celmira Laza-Vásquez
- Department of Nursing and Physiotherapy, University of Lleida-IRBLleida, Lleida, Spain
- Health Care Research Group (GRECS), Lleida, Spain
| | - Núria Codern-Bové
- Escola Universitària d’Infermeria i Teràpia Ocupacional de Terrassa, Universitat Autònoma de Barcelona, Terrassa, Spain
- Health, Participation, Occupation and Care Research Group (GrEUIT), Terrassa, Spain
- ÀreaQ, Evaluation and Qualitative Research, Barcelona, Spain
| | | | - Maria José Hernández-Leal
- Department of Economics and Research Centre on Economics and Sustainability (ECO-SOS), Rovira i Virgili University (URV), Tarragona, Spain
- Research Group in Statistical and Economic Analysis in Health (GRAEES), Reus, Spain
| | - Maria José Pérez-Lacasta
- Department of Economics and Research Centre on Economics and Sustainability (ECO-SOS), Rovira i Virgili University (URV), Tarragona, Spain
- Research Group in Statistical and Economic Analysis in Health (GRAEES), Reus, Spain
| | - Misericòrdia Carles-Lavila
- Department of Economics and Research Centre on Economics and Sustainability (ECO-SOS), Rovira i Virgili University (URV), Tarragona, Spain
- Research Group in Statistical and Economic Analysis in Health (GRAEES), Reus, Spain
| | - Montserrat Rué
- Department of Basic Medical Sciences, University of Lleida-IRBLleida, Lleida, Spain
- Research Group in Statistical and Economic Analysis in Health (GRAEES), Lleida, Spain
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28
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Reid S, Spalluto LB, Lang K, Weidner A, Pal T. An overview of genetic services delivery for hereditary breast cancer. Breast Cancer Res Treat 2022; 191:491-500. [PMID: 35079980 PMCID: PMC8789372 DOI: 10.1007/s10549-021-06478-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 12/02/2021] [Indexed: 02/06/2023]
Abstract
Breast cancer is the most common cancer diagnosed in women worldwide, with approximately 5-10% of cases attributed to high penetrance hereditary breast cancer (HBC) genes. The tremendous advances in precision oncology have broadened indications for germline genetic testing to guide both systemic and surgical treatment, with increasing demand for cancer genetic services. The HBC continuum of care includes (1) identification, access, and uptake of genetic counseling and testing; (2) the delivery of genetic counseling and testing services; and (3) initiation of guideline-adherent follow-up care and family communication of results. Challenges to delivering care on the HBC care continuum include factors such as access to services, cost, discrimination and bias, and lack of education and awareness, which can be mitigated through implementing a multi-level approach. This includes strategies such as increasing awareness and utilization of genetic counseling and testing, developing new methods to meet the growing demand for genetic services, and improving the uptake of follow-up care by increasing patient and provider awareness of the management recommendations.
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Affiliation(s)
- Sonya Reid
- Vanderbilt University Medical Center (VUMC)/Vanderbilt-Ingram Cancer Center (VICC), 2220 Pierce Ave. 777 PRB, Nashville, TN, 37232, USA.
| | - Lucy B Spalluto
- Vanderbilt University Medical Center (VUMC)/Vanderbilt-Ingram Cancer Center (VICC), 2220 Pierce Ave. 777 PRB, Nashville, TN, 37232, USA
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine/Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Veterans Health Administration-Tennessee Valley Healthcare System Geriatric Research, Education and Clinical Center, Nashville, USA
| | - Katie Lang
- Department of Medicine/Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Anne Weidner
- Department of Medicine/Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Tuya Pal
- Vanderbilt University Medical Center (VUMC)/Vanderbilt-Ingram Cancer Center (VICC), 2220 Pierce Ave. 777 PRB, Nashville, TN, 37232, USA.
- Department of Medicine/Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt University Medical Center (VUMC)/Vanderbilt-Ingram Cancer Center (VICC), 1500 21st Avenue South. Suite 2810, Nashville, TN, 37212, USA.
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29
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Saghatchian M, Abehsera M, Yamgnane A, Geyl C, Gauthier E, Hélin V, Bazire M, Villoing-Gaudé L, Reyes C, Gentien D, Golmard L, Stoppa-Lyonnet D. Feasibility of personalized screening and prevention recommendations in the general population through breast cancer risk assessment: results from a dedicated risk clinic. Breast Cancer Res Treat 2022; 192:375-383. [PMID: 34994879 PMCID: PMC8739506 DOI: 10.1007/s10549-021-06445-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 11/08/2021] [Indexed: 11/02/2022]
Abstract
PURPOSE A personalized approach to prevention and early detection based on known risk factors should contribute to early diagnosis and treatment of breast cancer. We initiated a risk assessment clinic for all women wishing to undergo an individual breast cancer risk assessment. METHODS Women underwent a complete breast cancer assessment including a questionnaire, mammogram with evaluation of breast density, collection of saliva sample, consultation with a radiologist, and a breast cancer specialist. Women aged 40 or older, with 0 or 1 first-degree relative with breast cancer diagnosed after the age of 40 were eligible for risk assessment using MammoRisk, a machine learning-based tool that provides an individual 5-year estimated risk of developing breast cancer based on the patient's clinical data and breast density, with or without polygenic risk scores (PRSs). DNA was extracted from saliva samples for genotyping of 76 single-nucleotide polymorphisms. The individual risk was communicated to the patient, with individualized screening and prevention recommendations. RESULTS A total of 290 women underwent breast cancer assessment, among which 196 women (68%) were eligible for risk assessment using MammoRisk (median age 52, range 40-72). When PRS was added to MammoRisk, 40% (n = 78) of patients were assigned a different risk category, with 28% (n = 55) of patients changing from intermediate to moderate or high risk. CONCLUSION Individual risk assessment is feasible in the general population. Screening recommendations could be given based on individual risk. The use of PRS changed the risk score and screening recommendations in 40% of women.
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Affiliation(s)
- Mahasti Saghatchian
- American Hospital of Paris, Neuilly-sur-Seine, France. .,Paris-Descartes University, Paris, France.
| | - Marc Abehsera
- American Hospital of Paris, Neuilly-sur-Seine, France
| | | | - Caroline Geyl
- American Hospital of Paris, Neuilly-sur-Seine, France
| | | | | | | | | | | | | | - Lisa Golmard
- INSERM U830 D.R.U.M. Team, Institut Curie Hospital, Paris-University, Paris, France
| | - Dominique Stoppa-Lyonnet
- Institut Curie, Paris, France.,INSERM U830 D.R.U.M. Team, Institut Curie Hospital, Paris-University, Paris, France
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30
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Palmer JR, Zirpoli G, Bertrand KA, Battaglia T, Bernstein L, Ambrosone CB, Bandera EV, Troester MA, Rosenberg L, Pfeiffer RM, Trinquart L. A Validated Risk Prediction Model for Breast Cancer in US Black Women. J Clin Oncol 2021; 39:3866-3877. [PMID: 34623926 DOI: 10.1200/jco.21.01236] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
PURPOSE Breast cancer risk prediction models are used to identify high-risk women for early detection, targeted interventions, and enrollment into prevention trials. We sought to develop and evaluate a risk prediction model for breast cancer in US Black women, suitable for use in primary care settings. METHODS Breast cancer relative risks and attributable risks were estimated using data from Black women in three US population-based case-control studies (3,468 breast cancer cases; 3,578 controls age 30-69 years) and combined with SEER age- and race-specific incidence rates, with incorporation of competing mortality, to develop an absolute risk model. The model was validated in prospective data among 51,798 participants of the Black Women's Health Study, including 1,515 who developed invasive breast cancer. A second risk prediction model was developed on the basis of estrogen receptor (ER)-specific relative risks and attributable risks. Model performance was assessed by calibration (expected/observed cases) and discriminatory accuracy (C-statistic). RESULTS The expected/observed ratio was 1.01 (95% CI, 0.95 to 1.07). Age-adjusted C-statistics were 0.58 (95% CI, 0.56 to 0.59) overall and 0.63 (95% CI, 0.58 to 0.68) among women younger than 40 years. These measures were almost identical in the model based on estrogen receptor-specific relative risks and attributable risks. CONCLUSION Discriminatory accuracy of the new model was similar to that of the most frequently used questionnaire-based breast cancer risk prediction models in White women, suggesting that effective risk stratification for Black women is now possible. This model may be especially valuable for risk stratification of young Black women, who are below the ages at which breast cancer screening is typically begun.
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Affiliation(s)
- Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA.,Boston University School of Medicine, Boston, MA
| | - Gary Zirpoli
- Slone Epidemiology Center at Boston University, Boston, MA
| | - Kimberly A Bertrand
- Slone Epidemiology Center at Boston University, Boston, MA.,Boston University School of Medicine, Boston, MA
| | | | | | | | | | - Melissa A Troester
- University of North Carolina Lineberger Comprehensive Cancer Center, Chapel Hill, NC
| | - Lynn Rosenberg
- Slone Epidemiology Center at Boston University, Boston, MA
| | - Ruth M Pfeiffer
- National Cancer Institute, Division of Cancer Epidemiology and Genetics, Bethesda, MD
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Wang Y, Zhu M, Ma H, Shen H. Polygenic risk scores: the future of cancer risk prediction, screening, and precision prevention. MEDICAL REVIEW (BERLIN, GERMANY) 2021; 1:129-149. [PMID: 37724297 PMCID: PMC10471106 DOI: 10.1515/mr-2021-0025] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 12/13/2021] [Indexed: 09/20/2023]
Abstract
Genome-wide association studies (GWASs) have shown that the genetic architecture of cancers are highly polygenic and enabled researchers to identify genetic risk loci for cancers. The genetic variants associated with a cancer can be combined into a polygenic risk score (PRS), which captures part of an individual's genetic susceptibility to cancer. Recently, PRSs have been widely used in cancer risk prediction and are shown to be capable of identifying groups of individuals who could benefit from the knowledge of their probabilistic susceptibility to cancer, which leads to an increased interest in understanding the potential utility of PRSs that might further refine the assessment and management of cancer risk. In this context, we provide an overview of the major discoveries from cancer GWASs. We then review the methodologies used for PRS construction, and describe steps for the development and evaluation of risk prediction models that include PRS and/or conventional risk factors. Potential utility of PRSs in cancer risk prediction, screening, and precision prevention are illustrated. Challenges and practical considerations relevant to the implementation of PRSs in health care settings are discussed.
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Affiliation(s)
- Yuzhuo Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hongxia Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Hongbing Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, Jiangsu, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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Diversity in cancer genomics research is a matter of equity and scientific discovery. Genet Med 2021; 24:549-551. [PMID: 34906472 DOI: 10.1016/j.gim.2021.11.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 11/17/2021] [Accepted: 11/17/2021] [Indexed: 11/24/2022] Open
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Holmes MD, Peng C. Vitamin A: A Potential Intervention for Breast Cancer Racial Disparities. J Nutr 2021; 151:3602-3603. [PMID: 34753173 PMCID: PMC8643599 DOI: 10.1093/jn/nxab359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
| | - Cheng Peng
- Channing Division of Network Medicine, Harvard Medical School, Boston, MA, USA
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Liu C, Zeinomar N, Chung WK, Kiryluk K, Gharavi AG, Hripcsak G, Crew KD, Shang N, Khan A, Fasel D, Manolio TA, Jarvik GP, Rowley R, Justice AE, Rahm AK, Fullerton SM, Smoller JW, Larson EB, Crane PK, Dikilitas O, Wiesner GL, Bick AG, Terry MB, Weng C. Generalizability of Polygenic Risk Scores for Breast Cancer Among Women With European, African, and Latinx Ancestry. JAMA Netw Open 2021; 4:e2119084. [PMID: 34347061 PMCID: PMC8339934 DOI: 10.1001/jamanetworkopen.2021.19084] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
IMPORTANCE Multiple polygenic risk scores (PRSs) for breast cancer have been developed from large research consortia; however, their generalizability to diverse clinical settings is unknown. OBJECTIVE To examine the performance of previously developed breast cancer PRSs in a clinical setting for women of European, African, and Latinx ancestry. DESIGN, SETTING, AND PARTICIPANTS This cohort study using the Electronic Medical Records and Genomics (eMERGE) network data set included 39 591 women from 9 contributing medical centers in the US that had electronic medical records (EMR) linked to genotype data. Breast cancer cases and controls were identified through a validated EMR phenotyping algorithm. MAIN OUTCOMES AND MEASURES Multivariable logistic regression was used to assess the association between breast cancer risk and 7 previously developed PRSs, adjusting for age, study site, breast cancer family history, and first 3 ancestry informative principal components. RESULTS This study included 39 591 women: 33 594 with European, 3801 with African, and 2196 with Latinx ancestry. The mean (SD) age at breast cancer diagnosis was 60.7 (13.0), 58.8 (12.5), and 60.1 (13.0) years for women with European, African, and Latinx ancestry, respectively. PRSs derived from women with European ancestry were associated with breast cancer risk in women with European ancestry (highest odds ratio [OR] per 1-SD increase, 1.46; 95% CI, 1.41-1.51), women with Latinx ancestry (highest OR, 1.31; 95% CI, 1.09-1.58), and women with African ancestry (OR, 1.19; 95% CI, 1.05-1.35). For women with European ancestry, this association with breast cancer risk was largest in the extremes of the PRS distribution, with ORs ranging from 2.19 (95% CI, 1.84-2.53) to 2.48 (95% CI, 1.89-3.25) for the 3 different PRSs examined for those in the highest 1% of the PRS compared with those in the middle quantile. Among women with Latinx and African ancestries at the extremes of the PRS distribution, there were no statistically significant associations. CONCLUSIONS AND RELEVANCE This cohort study found that PRS models derived from women with European ancestry for breast cancer risk generalized well for women with European, Latinx, and African ancestries across different clinical settings, although the effect sizes for women with African ancestry were smaller, likely because of differences in risk allele frequencies and linkage disequilibrium patterns. These results highlight the need to improve representation of diverse population groups, particularly women with African ancestry, in genomic research cohorts.
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Affiliation(s)
- Cong Liu
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Nur Zeinomar
- Department of Epidemiology, Columbia University Irving Medical Center, New York, New York
- Division of Medical Oncology, Rutgers Cancer Institute of New Jersey, Robert Wood Johnson Medical School, New Brunswick, New Jersey
| | - Wendy K. Chung
- Department of Pediatrics, Columbia University Irving Medical Center, New York, New York
| | - Krzysztof Kiryluk
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Ali G. Gharavi
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - George Hripcsak
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Katherine D. Crew
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Ning Shang
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Atlas Khan
- Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - David Fasel
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
| | - Teri A. Manolio
- National Human Genome Research Institute, Bethesda, Maryland
| | - Gail P. Jarvik
- Department of Medicine, University of Washington, Seattle
| | - Robb Rowley
- National Human Genome Research Institute, Bethesda, Maryland
| | - Ann E. Justice
- Department of Population Health Sciences, Geisinger, Danville, Pennsylvania
| | - Alanna K. Rahm
- Genomic Medicine Institute, Geisinger, Danville, Pennsylvania
| | | | - Jordan W. Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
| | - Georgia L. Wiesner
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Alexander G. Bick
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mary Beth Terry
- Department of Epidemiology, Columbia University Irving Medical Center, New York, New York
| | - Chunhua Weng
- Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York
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