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Xi Q, Fennell N, Archer S, Tischkowitz M, Antoniou AC, Morris S. Economic evaluation of personalised versus conventional risk assessment for women who have undergone testing for hereditary breast and ovarian cancer genes: a modelling study. J Med Genet 2025:jmg-2024-109948. [PMID: 40210464 DOI: 10.1136/jmg-2024-109948] [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: 02/24/2024] [Accepted: 03/22/2025] [Indexed: 04/12/2025]
Abstract
BACKGROUND The management of women with germline pathogenic variants (GPVs) in breast (BC) and ovarian cancer (OC) susceptibility genes is focused on surveillance and risk-reducing surgery/medication. Most women are assigned an average range of risk and treated accordingly, but it is possible to personalise this. Here, we explore the economic impact of risk personalisation. METHOD We compared two strategies for risk stratification for female participants: conventional risk assessment (CRA), which only involves information from genetic testing and personalised risk assessment (PRA), using genetic and non-genetic risk modifiers. Three different versions of PRA were compared, which were combinations of polygenic risk score and questionnaire-based factors. A patient-level Markov model was designed to estimate the overall National Health Service cost and quality-adjusted life years (QALYs) after risk assessment. Results were given for 20 different groups of women based on their GPV status and family history. RESULTS Across the 20 scenarios, the results showed that PRA was cost-effective compared with CRA using a £20 000 per QALY threshold in women with a GPV in PALB2 who have OC or BC+OC family history, and women with a GPV in ATM, CHEK2, RAD51C or RAD51D. For women with a GPV in BRCA1 or BRCA2, women with no pathogenic variant and women with a GPV in PALB2 who have unknown family history or BC family history, CRA was more cost-effective. PRA was cost-effective compared with CRA in specific situations predominantly associated with moderate-risk BC GPVs (RAD51C/RAD51D/CHEK2/ATM), while CRA was cost-effective compared with PRA predominantly with high-risk BC GPVs (BRCA1/BRCA2/PALB2). CONCLUSION PRA was cost-effective in specific situations compared with CRA in the UK for assessment of women with or without GPVs in BC and OC susceptibility genes.
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Affiliation(s)
- Qin Xi
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Nichola Fennell
- Department of Medical Genetics, University of Cambridge, Cambridge, UK
| | - Stephanie Archer
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Marc Tischkowitz
- Department of Medical Genetics, University of Cambridge, Cambridge, UK
| | - Antonis C Antoniou
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen Morris
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Liu S, Guan Y, Lin S, Wu P, Zhang Q, Chu T, Dong R. Risk of Cervical Carcinoma After Unfavorable Behavior and High Genetic Risk in the UK Biobank: A Prospective Nested Case-Control Study. Biomedicines 2025; 13:464. [PMID: 40002877 PMCID: PMC11853234 DOI: 10.3390/biomedicines13020464] [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: 12/23/2024] [Revised: 01/14/2025] [Accepted: 01/24/2025] [Indexed: 02/27/2025] Open
Abstract
Background: Previous studies have established a general understanding of the association between risky sexual behavior, genetic risk, and cervical carcinoma. However, these studies were conducted several years ago and lack systematic analysis using high-quality and population-based data. Methods: We conducted a prospective nested case-control study to identify risky behaviors and developed a behavior score. Combining the behavior score and genetic risk, we evaluated the effect of sexual and reproductive behavior and PRS on cervical carcinoma through the developed conditional logistic regression models. Results: We verified increased carcinoma risk in individuals with early sexual intercourse (OR: 1.41 [95% CI 1.09 to 1.83], p = 0.0083), non-monogamous sexual partners (OR: 3.13 [95% CI 2.15 to 4.57], p < 0.0001), three or more live births (OR: 1.44 [95% CI 1.12 to 1.84], p = 0.0040), and high PRS (polygenic risk score) (top 25% of PRS, OR: 1.58 [95% CI 1.15 to 2.16], p = 0.0044). The unfavorable sexual and reproductive behavior score we developed was linked to a 151% increased risk (OR: 2.51 [95% CI 1.79 to 3.52], p < 0.0001) after adjusting for PRS. Women with both unfavorable behavior and high genetic risk had a 5.5-fold increased cervical carcinoma risk (OR: 5.45 [95% CI 2.72 to 10.95], p < 0.0001) compared to individuals with favorable behavior and low genetic risk. Conclusions: Unfavorable sexual and reproductive behavior increases the risk of cervical carcinoma, especially in those with a high genetic risk. These findings encourage us to adhere to a healthy sexual and reproductive pattern.
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Affiliation(s)
- Shiyi Liu
- Department of Gynecology and Obstetrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China; (S.L.); (S.L.); (P.W.)
- National Clinical Research Center for Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China
| | - Yunlong Guan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China;
| | - Shitong Lin
- Department of Gynecology and Obstetrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China; (S.L.); (S.L.); (P.W.)
| | - Peng Wu
- Department of Gynecology and Obstetrics, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China; (S.L.); (S.L.); (P.W.)
| | - Qing Zhang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250000, China;
- Gynecology Oncology Key Laboratory, Qilu Hospital of Shandong University, Jinan 250000, China
| | - Tian Chu
- National Clinical Research Center for Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education), Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China
- Department of Gynecologic Oncology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China
| | - Ruifen Dong
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan 250000, China;
- Gynecology Oncology Key Laboratory, Qilu Hospital of Shandong University, Jinan 250000, China
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3
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Huang X, Lott PC, Hu D, Zavala VA, Jamal ZN, Vidaurre T, Casavilca-Zambrano S, Navarro Vásquez J, Castañeda CA, Valencia G, Morante Z, Calderón M, Abugattas JE, Fuentes HA, Liendo-Picoaga R, Cotrina JM, Neciosup SP, Rioja Viera P, Salinas LA, Galvez-Nino M, Huntsman S, Sanchez SE, Williams MA, Gelaye B, Estrada-Florez AP, Polanco-Echeverry G, Echeverry M, Velez A, Carmona-Valencia JA, Bohorquez-Lozano ME, Torres J, Cruz M, Ho WK, Teo SH, Tai MC, John EM, Haiman CA, Conti DV, Chen F, Torres-Mejía G, Kushi LH, Neuhausen SL, Ziv E, Carvajal-Carmona LG, Fejerman L. Evaluation of Multiple Breast Cancer Polygenic Risk Score Panels in Women of Latin American Heritage. Cancer Epidemiol Biomarkers Prev 2025; 34:234-245. [PMID: 39625644 PMCID: PMC11799839 DOI: 10.1158/1055-9965.epi-24-1247] [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: 08/22/2024] [Revised: 10/24/2024] [Accepted: 11/25/2024] [Indexed: 02/07/2025] Open
Abstract
BACKGROUND A substantial portion of the genetic predisposition for breast cancer is explained by multiple common genetic variants of relatively small effect. A subset of these variants, which have been identified mostly in individuals of European (EUR) and Asian ancestries, have been combined to construct a polygenic risk score (PRS) to predict breast cancer risk, but the prediction accuracy of existing PRSs in Hispanic/Latinx individuals (H/L) remain relatively low. We assessed the performance of several existing PRS panels with and without addition of H/L-specific variants among self-reported H/L women. METHODS PRS performance was evaluated using multivariable logistic regression and the area under the ROC curve. RESULTS Both EUR and Asian PRSs performed worse in H/L samples compared with original reports. The best EUR PRS performed better than the best Asian PRS in pooled H/L samples. EUR PRSs had decreased performance with increasing Indigenous American (IA) ancestry, while Asian PRSs had increased performance with increasing IA ancestry. The addition of two H/L SNPs increased performance for all PRSs, most notably in the samples with high IA ancestry, and did not impact the performance of PRSs in individuals with lower IA ancestry. CONCLUSIONS A single PRS that incorporates risk variants relevant to the multiple ancestral components of individuals from Latin America, instead of a set of ancestry-specific panels, could be used in clinical practice. IMPACT The results highlight the importance of population-specific discovery and suggest a straightforward approach to integrate ancestry-specific variants into PRSs for clinical application.
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Affiliation(s)
- Xiaosong Huang
- Department of Public Health Sciences, University of California Davis, Davis, California
- Genome Center, University of California Davis, Davis, California
| | - Paul C. Lott
- Genome Center, University of California Davis, Davis, California
| | - Donglei Hu
- Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, California
| | - Valentina A. Zavala
- Department of Public Health Sciences, University of California Davis, Davis, California
- Genome Center, University of California Davis, Davis, California
| | - Zoeb N. Jamal
- Genome Center, University of California Davis, Davis, California
| | | | | | | | | | | | - Zaida Morante
- Instituto Nacional de Enfermedades Neoplasicas, Lima, Peru
| | | | | | | | | | | | | | | | | | | | - Scott Huntsman
- Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, California
| | - Sixto E. Sanchez
- Departamento Académico de Medicina Preventiva y Salud Pública, Universidad Nacional Mayor de San Marcos, Lima, Peru
| | - Michelle A. Williams
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Bizu Gelaye
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Ana P. Estrada-Florez
- Genome Center, University of California Davis, Davis, California
- Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia
| | | | - Magdalena Echeverry
- Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia
| | - Alejandro Velez
- Dinamica IPS, Medellín, Colombia
- Hospital Pablo Tobon Uribe, Medellín, Colombia
| | | | - Mabel E. Bohorquez-Lozano
- Grupo de Citogenética, Filogenia y Evolución de Poblaciones, Facultades de Ciencias y Facultad de Ciencias de la Salud, Universidad del Tolima, Ibagué, Colombia
| | - Javier Torres
- UIM en Enfermedades Infecciosas, UMAE Pediatria, CMN SXXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Miguel Cruz
- UIM en Bioquimica, UMAE especialidades, CMN SXXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Weang-Kee Ho
- School of Mathematical Sciences, Faculty of Science and Engineering, University of Nottingham Malaysia, Selangor, Malaysia
- Cancer Research Malaysia, Selangor, Malaysia
| | - Soo Hwang Teo
- Cancer Research Malaysia, Selangor, Malaysia
- Department of Surgery, Faculty of Medicine, University of Malaya Centre, UM Cancer Research Institute, Kuala Lumpur, Malaysia
| | | | - Esther M. John
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
- Department of Medicine (Oncology), Stanford University School of Medicine, Stanford, California
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California
| | - Christopher A. Haiman
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - David V. Conti
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Fei Chen
- Department of Population and Public Health Science, Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Gabriela Torres-Mejía
- Center for Population Health Research, National Institute of Public Health (INSP), Cuernavaca, Mexico
| | - Lawrence H. Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Susan L. Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, University of California San Francisco, San Francisco, California
| | - Luis G. Carvajal-Carmona
- Genome Center, University of California Davis, Davis, California
- UC Davis Comprehensive Cancer Center, University of California Davis, Davis, California
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California Davis, Davis, California
| | | | - Laura Fejerman
- Department of Public Health Sciences, University of California Davis, Davis, California
- Genome Center, University of California Davis, Davis, California
- UC Davis Comprehensive Cancer Center, University of California Davis, Davis, California
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4
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Manna EDF, Serrano D, Cazzaniga L, Mannucci S, Zanzottera C, Fava F, Aurilio G, Guerrieri-Gonzaga A, Risti M, Calvello M, Feroce I, Marabelli M, Altemura C, Bertario L, Bonanni B, Lazzeroni M. Hereditary Breast Cancer: Comprehensive Risk Assessment and Prevention Strategies. Genes (Basel) 2025; 16:82. [PMID: 39858629 PMCID: PMC11764557 DOI: 10.3390/genes16010082] [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: 11/27/2024] [Revised: 12/29/2024] [Accepted: 01/11/2025] [Indexed: 01/27/2025] Open
Abstract
Women carrying pathogenic/likely pathogenic (P/LP) variants in moderate- or high-penetrance genes have an increased risk of developing breast cancer. However, most P/LP variants associated with breast cancer risk show incomplete penetrance. Age, gender, family history, polygenic risk, lifestyle, reproductive, hormonal, and environmental factors can affect the expressivity and penetrance of the disease. However, there are gaps in translating how individual genomic variation affects phenotypic presentation. The expansion of criteria for genetic testing and the increasing utilization of comprehensive genetic panels may enhance the identification of individuals carrying P/LP variants linked to hereditary breast cancer. Individualized risk assessment could facilitate the implementation of personalized risk-reduction strategies for these individuals. Preventive interventions encompass lifestyle modifications, chemoprevention, enhanced surveillance through breast imaging, and risk-reducing surgeries. This review addresses the current literature's inconsistencies and limitations, particularly regarding risk factors and the intensity of preventive strategies for women with P/LP variants in moderate- and high-penetrance genes. In addition, it synthesizes the latest evidence on risk assessment and primary and secondary prevention in women at high risk of breast cancer.
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Affiliation(s)
| | - Davide Serrano
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Laura Cazzaniga
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
- Department of Health Sciences, Medical Genetics, University of Milan, 20122 Milan, Italy
| | - Sara Mannucci
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Cristina Zanzottera
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Francesca Fava
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Gaetano Aurilio
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Aliana Guerrieri-Gonzaga
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Matilde Risti
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Mariarosaria Calvello
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
- Department of Health Sciences, Medical Genetics, University of Milan, 20122 Milan, Italy
- Oncology Competence Center, Gruppo Ospedaliero Moncucco, 6900 Lugano, Switzerland
| | - Irene Feroce
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Monica Marabelli
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Cecilia Altemura
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Lucio Bertario
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Bernardo Bonanni
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
| | - Matteo Lazzeroni
- Division of Cancer Prevention and Genetics, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy; (D.S.); (L.C.); (S.M.); (C.Z.); (F.F.); (G.A.); (A.G.-G.); (M.R.); (M.C.); (I.F.); (M.M.); (C.A.); (L.B.); (B.B.)
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Kuligina ES, Romanko AA, Jankevic T, Martianov AS, Ivantsov AO, Sokolova TN, Trofimov D, Kashyap A, Cybulski C, Lubiński J, Imyanitov EN. HLA gene polymorphism is a modifier of age-related breast cancer penetrance in carriers of BRCA1 pathogenic alleles. Breast Cancer Res Treat 2025; 209:341-354. [PMID: 39306605 DOI: 10.1007/s10549-024-07497-2] [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: 01/25/2024] [Accepted: 09/11/2024] [Indexed: 02/02/2025]
Abstract
PURPOSE Female carriers of germline BRCA1 mutations almost invariably develop breast cancer (BC); however, the age at onset is a subject of variation. We hypothesized that the age-related penetrance of BRCA1 mutations may depend on inherited variability in the host immune system. METHODS Next-generation sequencing was utilized for genotyping of HLA class I/II genes (HLA-A, HLA-B, HLA-C, HLA-DPB1, HLA-DQB1, and HLA-DRB1/3/4/5) in patients with BRCA1-associated BC with early (< / = 38 years, n = 215) and late (> / = 58 years, n = 108) age at onset. RESULTS HLA-DQB1*06:03P prevalence was higher in the late-onset group due to the excess of allele carriers [25/108 (23.1%) vs. 22/215 (10.2%); OR 2.96, p < 0.001]. For all HLA-I loci, there was a trend toward an increase in the number of homozygotes in the early-onset group. This trend reached statistical significance for the HLA-A [14.4% vs. 6.5%, p = 0.037; OR 2.4, p = 0.042]. The frequencies of HLA-DPB1, HLA-DQB1, and HLA-DRB1/3/4/5 homozygous genotypes did not differ between young-onset and late-onset patients. The maximum degree of homozygosity detected in this study was 6 out of 7 HLA class I/II loci; all six carriers of these genotypes were diagnosed with BC at the age < / = 38 years [OR 6.97, p = 0.187]. CONCLUSION HLA polymorphism may play a role in modifying the penetrance of BRCA1 pathogenic variants. Certain HLA alleles or HLA homozygosity may modify the risk of BC in BRCA1 carriers.
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Affiliation(s)
- Ekaterina S Kuligina
- N.N. Petrov Institute of Oncology, St. Petersburg, Russia.
- Laboratory of Molecular Oncology, N.N. Petrov Institute of Oncology, Pesochny-2, St. Petersburg, Russia, 197758.
| | - Alexandr A Romanko
- N.N. Petrov Institute of Oncology, St. Petersburg, Russia
- St. Petersburg Pediatric Medical University, St. Petersburg, Russia
| | | | | | | | | | | | - Aniruddh Kashyap
- International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Cezary Cybulski
- International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Jan Lubiński
- International Hereditary Cancer Center, Pomeranian Medical University in Szczecin, Szczecin, Poland
| | - Evgeny N Imyanitov
- N.N. Petrov Institute of Oncology, St. Petersburg, Russia
- St. Petersburg Pediatric Medical University, St. Petersburg, Russia
- Mechnikov North-Western Medical University, St. Petersburg, Russia
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6
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Vorstman J, Sebat J, Bourque VR, Jacquemont S. Integrative genetic analysis: cornerstone of precision psychiatry. Mol Psychiatry 2025; 30:229-236. [PMID: 39215185 DOI: 10.1038/s41380-024-02706-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 08/13/2024] [Accepted: 08/19/2024] [Indexed: 09/04/2024]
Abstract
The role of genetic testing in the domain of neurodevelopmental and psychiatric disorders (NPDs) is gradually changing from providing etiological explanation for the presence of NPD phenotypes to also identifying young individuals at high risk of developing NPDs before their clinical manifestation. In clinical practice, the latter implies a shift towards the availability of individual genetic information predicting a certain liability to develop an NPD (e.g., autism, intellectual disability, psychosis etc.). The shift from mostly a posteriori explanation to increasingly a priori risk prediction is the by-product of the systematic implementation of whole exome or genome sequencing as part of routine diagnostic work-ups during the neonatal and prenatal periods. This rapid uptake of genetic testing early in development has far-reaching consequences for psychiatry: Whereas until recently individuals would come to medical attention because of signs of abnormal developmental and/or behavioral symptoms, increasingly, individuals are presented based on genetic liability for NPD outcomes before NPD symptoms emerge. This novel clinical scenario, while challenging, also creates opportunities for research on prevention interventions and precision medicine approaches. Here, we review why optimization of individual risk prediction is a key prerequisite for precision medicine in the sphere of NPDs, as well as the technological and statistical methods required to achieve this ambition.
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Affiliation(s)
- Jacob Vorstman
- Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada.
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
- Program in Genetics and Genome Biology, Research Institute, The Hospital for Sick Children, Toronto, ON, Canada.
| | - Jonathan Sebat
- Department of Psychiatry, Department of Cellular & Molecular Medicine, Beyster Center of Psychiatric Genomics, University of California San Diego, San Diego, CA, USA
| | - Vincent-Raphaël Bourque
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Department of Psychiatry, McGill University, Montréal, QC, Canada
| | - Sébastien Jacquemont
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, QC, Canada
- Département de Pédiatrie, Université de Montréal, Montréal, QC, Canada
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Kalia SS, Boddicker NJ, Yadav S, Huang H, Na J, Hu C, Ambrosone CB, Yao S, Haiman CA, Chen F, John EM, Kurian AW, Guo B, Lindstrӧm S, Auer P, Lacey JV, Neuhausen SL, Martinez ME, Sandler DP, O’Brien KM, Taylor JA, Teras LR, Hodge JM, Lori A, Bodelon C, Trentham-Dietz A, Burnside ES, Vachon CM, Winham SJ, Goldgar DE, Domchek SM, Nathanson KL, Weitzel JN, Couch FJ, Kraft P. Development of a Breast Cancer Risk Prediction Model Integrating Monogenic, Polygenic, and Epidemiologic Risk. Cancer Epidemiol Biomarkers Prev 2024; 33:1490-1499. [PMID: 39259185 PMCID: PMC11530304 DOI: 10.1158/1055-9965.epi-24-0594] [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: 05/23/2024] [Revised: 07/25/2024] [Accepted: 09/06/2024] [Indexed: 09/12/2024] Open
Abstract
BACKGROUND Breast cancer has been associated with monogenic, polygenic, and epidemiologic (clinical, reproductive, and lifestyle) risk factors, but studies evaluating the combined effects of these factors have been limited. METHODS We extended previous work in breast cancer risk modeling, incorporating pathogenic variants (PV) in six breast cancer predisposition genes and a 105-SNP polygenic risk score (PRS), to include an epidemiologic risk score (ERS) in a sample of non-Hispanic White women drawn from prospective cohorts and population-based case-control studies, with 23,518 cases and 22,832 controls, from the Cancer Risk Estimates Related to Susceptibility (CARRIERS) Consortium. RESULTS The model predicts 4.4-fold higher risk of breast cancer for postmenopausal women with no predisposition PV and median PRS, but with the highest versus lowest ERS. Overall, women with CHEK2 PVs had >20% lifetime risk of breast cancer. However, 15.6% of women with CHEK2 PVs and a family history of breast cancer, and 45.1% of women with CHEK2 PVs but without a family history of breast cancer, had low (<20%) predicted lifetime risk and thus were below the threshold for MRI screening. CHEK2 PV carriers at the 10th percentile of the joint distribution of ERS and PRS, without a family history of breast cancer, had a predicted lifetime risk similar to the general population. CONCLUSIONS These results illustrate that an ERS, alone and combined with the PRS, can contribute to clinically relevant risk stratification. IMPACT Integrating monogenic, polygenic, and epidemiologic risk factors in breast cancer risk prediction models may inform personalized screening and prevention efforts.
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Affiliation(s)
- Sarah S. Kalia
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | | | - Hongyan Huang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jie Na
- Mayo Clinic, Rochester, MN, USA
| | | | | | - Song Yao
- Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | | | - Fei Chen
- Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Esther M. John
- Stanford University School of Medicine, Stanford, CA, USA
| | | | - Boya Guo
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Fred Hutchinson Cancer Research Center. Seattle, WA, USA
| | - Sara Lindstrӧm
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Fred Hutchinson Cancer Research Center. Seattle, WA, USA
| | - Paul Auer
- Medical College of Wisconsin, Milwaukee, WI, USA
| | - James V. Lacey
- Beckman Research Institute of City of Hope, Duarte, CA, USA
| | | | | | - Dale P. Sandler
- National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Katie M. O’Brien
- National Institute of Environmental Health Sciences, Durham, NC, USA
| | - Jack A. Taylor
- National Institute of Environmental Health Sciences, Durham, NC, USA
| | | | | | | | | | | | | | | | | | | | - Susan M. Domchek
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | | | | | | | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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8
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Thompson DJ, Wells D, Selzam S, Peneva I, Moore R, Sharp K, Tarran WA, Beard EJ, Riveros-Mckay F, Giner-Delgado C, Palmer D, Seth P, Harrison J, Futema M, McVean G, Plagnol V, Donnelly P, Weale ME. A systematic evaluation of the performance and properties of the UK Biobank Polygenic Risk Score (PRS) Release. PLoS One 2024; 19:e0307270. [PMID: 39292644 PMCID: PMC11410272 DOI: 10.1371/journal.pone.0307270] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Accepted: 07/01/2024] [Indexed: 09/20/2024] Open
Abstract
We assess the UK Biobank (UKB) Polygenic Risk Score (PRS) Release, a set of PRSs for 28 diseases and 25 quantitative traits that has been made available on the individuals in UKB, using a unified pipeline for PRS evaluation. We also release a benchmarking software tool to enable like-for-like performance evaluation for different PRSs for the same disease or trait. Extensive benchmarking shows the PRSs in the UKB Release to outperform a broad set of 76 published PRSs. For many of the diseases and traits we also validate the PRS algorithms in a separate cohort (100,000 Genomes Project). The availability of PRSs for 53 traits on the same set of individuals also allows a systematic assessment of their properties, and the increased power of these PRSs increases the evidence for their potential clinical benefit.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | - Marta Futema
- Cardiology Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, United Kingdom
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
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9
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Hovhannisyan M, Zemankova P, Nehasil P, Matejkova K, Borecka M, Cerna M, Dolezalova T, Dvorakova L, Foretova L, Horackova K, Jelinkova S, Just P, Kalousova M, Kral J, Machackova E, Nemcova B, Safarikova M, Springer D, Stastna B, Tavandzis S, Vocka M, Zima T, Soukupova J, Kleiblova P, Ernst C, Kleibl Z, Janatova M. Population-specific validation and comparison of the performance of 77- and 313-variant polygenic risk scores for breast cancer risk prediction. Cancer 2024; 130:2978-2987. [PMID: 38718029 DOI: 10.1002/cncr.35337] [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: 01/25/2024] [Revised: 03/22/2024] [Accepted: 04/03/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND The polygenic risk score (PRS) allows the quantification of the polygenic effect of many low-penetrance alleles on the risk of breast cancer (BC). This study aimed to evaluate the performance of two sets comprising 77 or 313 low-penetrance loci (PRS77 and PRS313) in patients with BC in the Czech population. METHODS In a retrospective case-control study, variants were genotyped from both the PRS77 and PRS313 sets in 1329 patients with BC and 1324 noncancer controls, all women without germline pathogenic variants in BC predisposition genes. Odds ratios (ORs) were calculated according to the categorical PRS in individual deciles. Weighted Cox regression analysis was used to estimate the hazard ratio (HR) per standard deviation (SD) increase in PRS. RESULTS The distributions of standardized PRSs in patients and controls were significantly different (p < 2.2 × 10-16) with both sets. PRS313 outperformed PRS77 in categorical and continuous PRS analyses. For patients in the highest 2.5% of PRS313, the risk reached an OR of 3.05 (95% CI, 1.66-5.89; p = 1.76 × 10-4). The continuous risk was estimated as an HRper SD of 1.64 (95% CI, 1.49-1.81; p < 2.0 × 10-16), which resulted in an absolute risk of 21.03% at age 80 years for individuals in the 95th percentile of PRS313. Discordant categorization into PRS deciles was observed in 248 individuals (9.3%). CONCLUSIONS Both PRS77 and PRS313 are able to stratify individuals according to their BC risk in the Czech population. PRS313 shows better discriminatory ability. The results support the potential clinical utility of using PRS313 in individualized BC risk prediction.
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Affiliation(s)
- Milena Hovhannisyan
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Petra Zemankova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Petr Nehasil
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Paediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Katerina Matejkova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Department of Genetics and Microbiology, Faculty of Science, Charles University in Prague, Prague, Czech Republic
| | - Marianna Borecka
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Marta Cerna
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Tatana Dolezalova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Lenka Dvorakova
- Department of Paediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Lenka Foretova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Klara Horackova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Sandra Jelinkova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Pavel Just
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Marta Kalousova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Jan Kral
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Centre for Medical Genetics and Reproductive Medicine, GENNET, Prague, Czech Republic
| | - Eva Machackova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Barbora Nemcova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Marketa Safarikova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Drahomira Springer
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Barbora Stastna
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Department of Biochemistry, Faculty of Science, Charles University, Prague, Czech Republic
| | - Spiros Tavandzis
- Department of Medical Genetics, AGEL Research and Training Institute, AGEL Laboratories, Novy Jicin, Czech Republic
| | - Michal Vocka
- Department of Oncology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Tomas Zima
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Jana Soukupova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Petra Kleiblova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Corinna Ernst
- Centre for Familial Breast and Ovarian Cancer, Center for Integrated Oncology, Medical Faculty, University of Cologne and University Hospital Cologne, Cologne, Germany
| | - Zdenek Kleibl
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Marketa Janatova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
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McInerny S, Mascarenhas L, Yanes T, Petelin L, Chenevix-Trench G, Southey MC, Young MA, James PA. Using polygenic risk modification to improve breast cancer prevention: study protocol for the PRiMo multicentre randomised controlled trial. BMJ Open 2024; 14:e087874. [PMID: 39107016 PMCID: PMC11308879 DOI: 10.1136/bmjopen-2024-087874] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/21/2024] [Accepted: 07/16/2024] [Indexed: 08/09/2024] Open
Abstract
INTRODUCTION Established personal and familial risk factors contribute collectively to a woman's risk of breast or ovarian cancer. Existing clinical services offer genetic testing for pathogenic variants in high-risk genes to investigate these risks but recent information on the role of common genomic variants, in the form of a Polygenic Risk Score (PRS), has provided the potential to further personalise breast and ovarian cancer risk assessment. Data from cohort studies support the potential of an integrated risk assessment to improve targeted risk management but experience of this approach in clinical practice is limited. METHODS AND ANALYSIS The polygenic risk modification trial is an Australian multicentre prospective randomised controlled trial of integrated risk assessment including personal and family risk factors with inclusion of breast and ovarian PRS vs standard care. The study will enrol women, unaffected by cancer, undergoing predictive testing at a familial cancer clinic for a pathogenic variant in a known breast cancer (BC) or ovarian cancer (OC) predisposition gene (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D). Array-based genotyping will be used to generate breast cancer (313 SNP) and ovarian cancer (36 SNP) PRS. A suite of materials has been developed for the trial including an online portal for patient consent and questionnaires, and a clinician education programme to train healthcare providers in the use of integrated risk assessment. Long-term follow-up will evaluate differences in the assessed risk and management advice, patient risk management intentions and adherence, patient-reported experience and outcomes, and the health service implications of personalised risk assessment. ETHICS AND DISSEMINATION This study has been approved by the Human Research Ethics Committee of Peter MacCallum Cancer Centre and at all participating centres. Study findings will be disseminated via peer-reviewed publications and conference presentations, and directly to participants. TRIAL REGISTRATION NUMBER ACTRN12621000009819.
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Affiliation(s)
- Simone McInerny
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Parkville Familial Cancer Centre, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Lyon Mascarenhas
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Parkville Familial Cancer Centre, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Tatiane Yanes
- Frazer Institute, Dermatology Research Centre, The University of Queensland, Brisbane, Queensland, Australia
| | - Lara Petelin
- The Daffodil Centre, joint venture with Cancer Council NSW, The University of Sydney, Sydney, New South Wales, Australia
- The University of Melbourne School of Population and Global Health, Melbourne, Victoria, Australia
| | - Georgia Chenevix-Trench
- Cancer Genetics Laboratory, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Melissa C Southey
- Precision Medicine, Monash University School of Clinical Sciences at Monash Health, Clayton, Victoria, Australia
- Cancer Council Victoria Cancer Epidemiology Division, Melbourne, Victoria, Australia
| | - Mary-Anne Young
- Clinical Translation and Engagement Platform, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Clinical Medicine, St Vincent's Healthcare Clinical Campus, Faculty of Medicine and Health, UNSW Sydney, Sydney, New South Wales, Australia
| | - Paul A James
- Parkville Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Parkville Familial Cancer Centre, The Royal Melbourne Hospital, Parkville, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
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11
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Baumann A, Ruckert C, Meier C, Hutschenreiter T, Remy R, Schnur B, Döbel M, Fankep RCN, Skowronek D, Kutz O, Arnold N, Katzke AL, Forster M, Kobiela AL, Thiedig K, Zimmer A, Ritter J, Weber BHF, Honisch E, Hackmann K, Schmidt G, Sturm M, Ernst C. Limitations in next-generation sequencing-based genotyping of breast cancer polygenic risk score loci. Eur J Hum Genet 2024; 32:987-997. [PMID: 38907004 PMCID: PMC11291653 DOI: 10.1038/s41431-024-01647-2] [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: 12/21/2023] [Revised: 05/17/2024] [Accepted: 06/10/2024] [Indexed: 06/23/2024] Open
Abstract
Considering polygenic risk scores (PRSs) in individual risk prediction is increasingly implemented in genetic testing for hereditary breast cancer (BC) based on next-generation sequencing (NGS). To calculate individual BC risks, the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) with the inclusion of the BCAC 313 or the BRIDGES 306 BC PRS is commonly used. The PRS calculation depends on accurately reproducing the variant allele frequencies (AFs) and, consequently, the distribution of PRS values anticipated by the algorithm. Here, the 324 loci of the BCAC 313 and the BRIDGES 306 BC PRS were examined in population-specific database gnomAD and in real-world data sets of five centers of the German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), to determine whether these expected AFs can be reproduced by NGS-based genotyping. Four PRS loci were non-existent in gnomAD v3.1.2 non-Finnish Europeans, further 24 loci showed noticeably deviating AFs. In real-world data, between 11 and 23 loci were reported with noticeably deviating AFs, and were shown to have effects on final risk prediction. Deviations depended on the sequencing approach, variant caller and calling mode (forced versus unforced) employed. Therefore, this study demonstrates the necessity to apply quality assurance not only in terms of sequencing coverage but also observed AFs in a sufficiently large cohort, when implementing PRSs in a routine diagnostic setting. Furthermore, future PRS design should be guided by the technical reproducibility of expected AFs across commonly used genotyping methods, especially NGS, in addition to the observed effect sizes.
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Affiliation(s)
- Alexandra Baumann
- Institute for Clinical Genetics, University Hospital Carl Gustav Carus at TUD Dresden University of Technology and Faculty of Medicine of TUD Dresden University of Technology, Dresden, Germany
- ERN GENTURIS, Hereditary Cancer Syndrome Center Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between German Cancer Research Center (DKFZ), Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Dresden, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Christian Ruckert
- Department of Medical Genetics, University Hospital Münster, Münster, Germany
| | - Christoph Meier
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
| | - Tim Hutschenreiter
- Institute for Clinical Genetics, University Hospital Carl Gustav Carus at TUD Dresden University of Technology and Faculty of Medicine of TUD Dresden University of Technology, Dresden, Germany
- ERN GENTURIS, Hereditary Cancer Syndrome Center Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between German Cancer Research Center (DKFZ), Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Dresden, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Robert Remy
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Medical Faculty, University of Cologne and University Hospital Cologne, Cologne, Germany
| | - Benedikt Schnur
- Department of Human Genetics, Hannover Medical School (MHH), Hannover, Germany
| | - Marvin Döbel
- Institute of Medical Genetics and Applied Genomics, University Hospital Tübingen, Tübingen, Germany
| | - Rudel Christian Nkouamedjo Fankep
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Medical Faculty, University of Cologne and University Hospital Cologne, Cologne, Germany
| | - Dariush Skowronek
- Department of Human Genetics, University Medicine Greifswald and Interfaculty Institute of Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
| | - Oliver Kutz
- Institute for Clinical Genetics, University Hospital Carl Gustav Carus at TUD Dresden University of Technology and Faculty of Medicine of TUD Dresden University of Technology, Dresden, Germany
- ERN GENTURIS, Hereditary Cancer Syndrome Center Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between German Cancer Research Center (DKFZ), Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Dresden, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- Department of Gynecology and Obstetrics, University Hospital Carl Gustav Carus at TUD Dresden University of Technology and Faculty of Medicine of TUD Dresden University of Technology, Dresden, Germany
| | - Norbert Arnold
- Department of Gynecology and Obstetrics, Institute of Clinical Chemistry Institute of Clinical Molecular Biology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Anna-Lena Katzke
- Department of Human Genetics, Hannover Medical School (MHH), Hannover, Germany
| | - Michael Forster
- Department of Gynecology and Obstetrics, Institute of Clinical Chemistry Institute of Clinical Molecular Biology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Anna-Lena Kobiela
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Medical Faculty, University of Cologne and University Hospital Cologne, Cologne, Germany
| | - Katharina Thiedig
- Division of Gynaecology and Obstetrics, Klinikum rechts der Isar der Technischen Universität München, München, Germany
| | - Andreas Zimmer
- Institute for Human Genetics, Medical Center University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Julia Ritter
- Department of Human Genetics, Labor Berlin - Charité Vivantes GmbH, Berlin, Germany
| | - Bernhard H F Weber
- Institute of Human Genetics, University of Regensburg, Regensburg, Germany
- Institute of Clinical Human Genetics, University Hospital Regensburg, Regensburg, Germany
| | - Ellen Honisch
- Department of Gynaecology and Obstetrics, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Karl Hackmann
- Institute for Clinical Genetics, University Hospital Carl Gustav Carus at TUD Dresden University of Technology and Faculty of Medicine of TUD Dresden University of Technology, Dresden, Germany
- ERN GENTURIS, Hereditary Cancer Syndrome Center Dresden, Dresden, Germany
- National Center for Tumor Diseases (NCT), NCT/UCC Dresden, a partnership between German Cancer Research Center (DKFZ), Faculty of Medicine and University Hospital Carl Gustav Carus, TUD Dresden University of Technology and Helmholtz-Zentrum Dresden-Rossendorf (HZDR), Dresden, Germany
- German Cancer Consortium (DKTK), Dresden, Germany
- German Cancer Research Center (DKFZ), Heidelberg, Germany
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Gunnar Schmidt
- Department of Human Genetics, Hannover Medical School (MHH), Hannover, Germany
| | - Marc Sturm
- Institute of Medical Genetics and Applied Genomics, University Hospital Tübingen, Tübingen, Germany
| | - Corinna Ernst
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Medical Faculty, University of Cologne and University Hospital Cologne, Cologne, Germany.
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12
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Bourque VR, Schmilovich Z, Huguet G, England J, Okewole A, Poulain C, Renne T, Jean-Louis M, Saci Z, Zhang X, Rolland T, Labbé A, Vorstman J, Rouleau GA, Baron-Cohen S, Mottron L, Bethlehem RAI, Warrier V, Jacquemont S. Integrating genomic variants and developmental milestones to predict cognitive and adaptive outcomes in autistic children. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.31.24311250. [PMID: 39211846 PMCID: PMC11361213 DOI: 10.1101/2024.07.31.24311250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Abstract
Although the first signs of autism are often observed as early as 18-36 months of age, there is a broad uncertainty regarding future development, and clinicians lack predictive tools to identify those who will later be diagnosed with co-occurring intellectual disability (ID). Here, we developed predictive models of ID in autistic children (n=5,633 from three cohorts), integrating different classes of genetic variants alongside developmental milestones. The integrated model yielded an AUC ROC=0.65, with this predictive performance cross-validated and generalised across cohorts. Positive predictive values reached up to 55%, accurately identifying 10% of ID cases. The ability to stratify the probabilities of ID using genetic variants was up to twofold greater in individuals with delayed milestones compared to those with typical development. These findings underscore the potential of models in neurodevelopmental medicine that integrate genomics and clinical observations to predict outcomes and target interventions.
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13
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Yadav S, Couch FJ, Domchek SM. Germline Genetic Testing for Hereditary Breast and Ovarian Cancer: Current Concepts in Risk Evaluation. Cold Spring Harb Perspect Med 2024; 14:a041318. [PMID: 38151326 PMCID: PMC11293548 DOI: 10.1101/cshperspect.a041318] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2023]
Abstract
Our understanding of hereditary breast and ovarian cancer has significantly improved over the past two decades. In addition to BRCA1/2, pathogenic variants in several other DNA-repair genes have been shown to increase the risks of breast and ovarian cancer. The magnitude of cancer risk is impacted not only by the gene involved, but also by family history of cancer, polygenic risk scores, and, in certain genes, pathogenic variant type or location. While estimates of breast and ovarian cancer risk associated with pathogenic variants are available, these are predominantly based on studies of high-risk populations with young age at diagnosis of cancer, multiple primary cancers, or family history of cancer. More recently, breast cancer risk for germline pathogenic variant carriers has been estimated from population-based studies. Here, we provide a review of the field of germline genetic testing and risk evaluation for hereditary breast and ovarian cancers in high-risk and population-based settings.
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Affiliation(s)
- Siddhartha Yadav
- Department of Oncology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55901, USA
| | - Susan M Domchek
- Basser Center for BRCA, Abramson Cancer Center, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
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14
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Horackova K, Zemankova P, Nehasil P, Vocka M, Hovhannisyan M, Matejkova K, Janatova M, Cerna M, Kleiblova P, Jelinkova S, Stastna B, Just P, Dolezalova T, Nemcova B, Urbanova M, Koudova M, Hazova J, Machackova E, Foretova L, Stranecky V, Zikan M, Kleibl Z, Soukupova J. A comprehensive analysis of germline predisposition to early-onset ovarian cancer. Sci Rep 2024; 14:16183. [PMID: 39003285 PMCID: PMC11246516 DOI: 10.1038/s41598-024-66324-2] [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: 02/26/2024] [Accepted: 07/01/2024] [Indexed: 07/15/2024] Open
Abstract
The subset of ovarian cancer (OC) diagnosed ≤ 30yo represents a distinct subgroup exhibiting disparities from late-onset OC in many aspects, including indefinite germline cancer predisposition. We performed DNA/RNA-WES with HLA-typing, PRS assessment and survival analysis in 123 early-onset OC-patients compared to histology/stage-matched late-onset and unselected OC-patients, and population-matched controls. Only 6/123(4.9%) early-onset OC-patients carried a germline pathogenic variant (GPV) in high-penetrance OC-predisposition genes. Nevertheless, our comprehensive germline analysis of early-onset OC-patients revealed two divergent trajectories of potential germline susceptibility. Firstly, overrepresentation analysis highlighted a connection to breast cancer (BC) that was supported by the CHEK2 GPV enrichment in early-onset OC(p = 1.2 × 10-4), and the presumably BC-specific PRS313, which successfully stratified early-onset OC-patients from controls(p = 0.03). The second avenue pointed towards the impaired immune response, indicated by LY75-CD302 GPV(p = 8.3 × 10-4) and diminished HLA diversity compared with controls(p = 3 × 10-7). Furthermore, we found a significantly higher overall GPV burden in early-onset OC-patients compared to controls(p = 3.8 × 10-4). The genetic predisposition to early-onset OC appears to be a heterogeneous and complex process that goes beyond the traditional Mendelian monogenic understanding of hereditary cancer predisposition, with a significant role of the immune system. We speculate that rather a cumulative overall GPV burden than specific GPV may potentially increase OC risk, concomitantly with reduced HLA diversity.
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Grants
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-09-00355 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-09-00355 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- RVO-VFN 00064165 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- NU20-03-00016 Ministerstvo Zdravotnictví Ceské Republiky
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- SVV260631 Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- COOPERATIO Univerzita Karlova v Praze
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- The National Center for Medical Genomics (LM2023067) Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
- LX22NPO05102 Ministerstvo Školství, Mládeže a Tělovýchovy
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Affiliation(s)
- Klara Horackova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Petra Zemankova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Petr Nehasil
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
- Department of Paediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Michal Vocka
- Department of Oncology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Milena Hovhannisyan
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Katerina Matejkova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Department of Genetics and Microbiology, Faculty of Science, Charles University in Prague, Prague, Czech Republic
| | - Marketa Janatova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Marta Cerna
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Petra Kleiblova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Sandra Jelinkova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Barbora Stastna
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Department of Biochemistry, Faculty of Science, Charles University, Prague, Czech Republic
| | - Pavel Just
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Tatana Dolezalova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Barbora Nemcova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Marketa Urbanova
- Centre for Medical Genetics and Reproductive Medicine, GENNET, Prague, Czech Republic
| | - Monika Koudova
- Centre for Medical Genetics and Reproductive Medicine, GENNET, Prague, Czech Republic
| | - Jana Hazova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Eva Machackova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Lenka Foretova
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Viktor Stranecky
- Department of Paediatrics and Inherited Metabolic Disorders, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Michal Zikan
- Department of Gynecology and Obstetrics, Bulovka University Hospital and First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Zdenek Kleibl
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
- Institute of Pathological Physiology, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Jana Soukupova
- Institute of Medical Biochemistry and Laboratory Diagnostics, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic.
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15
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Elia A, Pataccini G, Saldain L, Ambrosio L, Lanari C, Rojas P. Antiprogestins for breast cancer treatment: We are almost ready. J Steroid Biochem Mol Biol 2024; 241:106515. [PMID: 38554981 DOI: 10.1016/j.jsbmb.2024.106515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/05/2024] [Accepted: 03/20/2024] [Indexed: 04/02/2024]
Abstract
The development of antiprogestins was initially a gynecological purpose. However, since mifepristone was developed, its application for breast cancer treatment was immediately proposed. Later, new compounds with lower antiglucocorticoid and antiandrogenic effects were developed to be applied to different pathologies, including breast cancer. We describe herein the studies performed in the breast cancer field with special focus on those reported in recent years, ranging from preclinical biological models to those carried out in patients. We highlight the potential use of antiprogestins in breast cancer prevention in women with BRCA1 mutations, and their use for breast cancer treatment, emphasizing the need to elucidate which patients will respond. In this sense, the PR isoform ratio has emerged as a possible tool to predict antiprogestin responsiveness. The effects of combined treatments of antiprogestins together with other drugs currently used in the clinic, such as tamoxifen, CDK4/CDK6 inhibitors or pembrolizumab in preclinical models is discussed since it is in this scenario that antiprogestins will be probably introduced. Finally, we explain how transcriptomic or proteomic studies, that were carried out in different luminal breast cancer models and in breast cancer samples that responded or were predicted to respond to the antiprogestin therapy, show a decrease in proliferative pathways. Deregulated pathways intrinsic of each model are discussed, as well as how these analyses may contribute to a better understanding of the mechanisms involved.
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Affiliation(s)
- Andrés Elia
- Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME CONICET), Buenos Aires, Argentina
| | - Gabriela Pataccini
- Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME CONICET), Buenos Aires, Argentina
| | - Leo Saldain
- Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME CONICET), Buenos Aires, Argentina
| | - Luisa Ambrosio
- Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME CONICET), Buenos Aires, Argentina
| | - Claudia Lanari
- Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME CONICET), Buenos Aires, Argentina
| | - Paola Rojas
- Laboratory of Hormonal Carcinogenesis, Instituto de Biología y Medicina Experimental (IBYME CONICET), Buenos Aires, Argentina.
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16
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Siermann M, Vermeesch JR, Raivio T, Tšuiko O, Borry P. Polygenic embryo screening: quo vadis? J Assist Reprod Genet 2024; 41:1719-1726. [PMID: 38879662 PMCID: PMC11263429 DOI: 10.1007/s10815-024-03169-8] [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: 04/05/2024] [Accepted: 06/06/2024] [Indexed: 07/23/2024] Open
Abstract
Recently, the use of polygenic risk scores in embryo screening (PGT-P) has been introduced on the premise of reducing polygenic disease risk through embryo selection. However, it has been met with extensive critique: considered "technology-driven" rather than "evidence-based", concerns exist about its validity, utility, ethics, and societal effects. Its scientific foundations and criticisms thus need to be carefully considered. However, seeing as PGT-P is already offered in some settings, further questions need to be addressed, in order to give due diligence to various aspects of PGT-P. By examining the complexities of clinical introduction of PGT-P, we discuss whether PGT-P could be responsibly implemented in the first place, what elements need to be addressed if PGT-P is clinically implemented, and subsequently how counselling and decision-making of its users could be envisaged. By dissecting these elements, we provide an overview of important practical questions of PGT-P and emphasize elements of PGT-P that we think have yet to be given sufficient attention. These questions and elements are for example related to the potential target group, scope, and decision-making possibilities of PGT-P. The aspects we raise are crucial to consider by the scientific community and policy makers for the development of guidelines and/or an ethical framework for PGT-P.
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Affiliation(s)
- Maria Siermann
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 7, Box 7001, 3000, Leuven, Belgium.
- Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, P.O. Box 63, 00014, Helsinki, Finland.
| | | | - Taneli Raivio
- Faculty of Medicine, University of Helsinki, Haartmaninkatu 8, P.O. Box 63, 00014, Helsinki, Finland
| | - Olga Tšuiko
- Center for Human Genetics, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Pascal Borry
- Centre for Biomedical Ethics and Law, Department of Public Health and Primary Care, KU Leuven, Kapucijnenvoer 7, Box 7001, 3000, Leuven, Belgium
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17
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Marrison ST, Allen CG, Hughes K, Raines H, Banks M, Lee T, Meeder K, Diaz V. Implementation of risk assessment process for breast cancer risk in primary care. JOURNAL OF CANCER PREVENTION & CURRENT RESEARCH 2024; 15:65-69. [PMID: 39346015 PMCID: PMC11434167 DOI: 10.15406/jcpcr.2024.15.00552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Background Current cancer prevention guidelines recommend assessing breast cancer risk using validated risk calculators such as Tyrer-Cuzick and assessing genetic testing eligibility with NCCN. Women at high-risk of breast cancer may be recommended to undergo additional or earlier screening. Risk assessment is not consistently implemented in the primary care setting resulting in increased morbidity and mortality in unidentified high-risk individuals. Methods A single-arm interventional study was conducted in an academic primary care clinic for women 25-50 years old presenting for primary care appointments. Pre-visit workflows evaluated breast cancer risk using the Cancer Risk Assessment (CRA) Tool and information was provided to the clinician with guideline-based recommendations. Post-visit questionnaires and chart review were conducted. Results The survey response rate was 24.5% (144/587) with 80.3% of responses completed online (94/117). The average age of respondents was 35.8 years with 50.4% White and 35.9% Black. There were no differences in response rate based on race. Risk discussion was documented in the medical record in 15.4% of cases with a higher rate of documentation in high-risk patient based on risk assessment as compared with average risk respondents (34.6% vs. 9.7%, p<0.01). In the high-risk women identified 11.4% (4/35) were seen by the high-risk breast clinic, and 5.7% (2/35) were referred for genetic evaluation. None had previously obtained MRI screening or genetic testing. Conclusions There is limited identification and evaluation of women at high risk for breast cancer. Pre-visit surveys can be used as a tool to assess breast cancer risk in the primary care setting; however additional strategies are needed to implement systematic risk assessment and facilitate appropriate treatment based on risk level.
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Affiliation(s)
| | - Caitlin G Allen
- Department of Public Heath, Medical University of South Carolina, USA
| | - Kevin Hughes
- Department of Surgical Oncology Medical University of South Carolina, USA
| | - Holly Raines
- Department of Family Medicine, Medical University of South Carolina, USA
| | - Mattie Banks
- Department of Family Medicine, Medical University of South Carolina, USA
| | - Travita Lee
- Department of Family Medicine, Medical University of South Carolina, USA
| | - Kiersten Meeder
- Department of Surgical Oncology Medical University of South Carolina, USA
| | - Vanessa Diaz
- Department of Family Medicine, Medical University of South Carolina, USA
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18
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Kingdom R, Beaumont RN, Wood AR, Weedon MN, Wright CF. Genetic modifiers of rare variants in monogenic developmental disorder loci. Nat Genet 2024; 56:861-868. [PMID: 38637616 PMCID: PMC11096126 DOI: 10.1038/s41588-024-01710-0] [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: 12/07/2022] [Accepted: 03/06/2024] [Indexed: 04/20/2024]
Abstract
Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.
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Affiliation(s)
- Rebecca Kingdom
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Robin N Beaumont
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Andrew R Wood
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Michael N Weedon
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK
| | - Caroline F Wright
- Department of Clinical and Biomedical Sciences, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter, UK.
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19
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McDevitt T, Durkie M, Arnold N, Burghel GJ, Butler S, Claes KBM, Logan P, Robinson R, Sheils K, Wolstenholme N, Hanson H, Turnbull C, Hume S. EMQN best practice guidelines for genetic testing in hereditary breast and ovarian cancer. Eur J Hum Genet 2024; 32:479-488. [PMID: 38443545 PMCID: PMC11061103 DOI: 10.1038/s41431-023-01507-5] [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: 06/08/2023] [Revised: 11/07/2023] [Accepted: 11/21/2023] [Indexed: 03/07/2024] Open
Abstract
Hereditary Breast and Ovarian Cancer (HBOC) is a genetic condition associated with increased risk of cancers. The past decade has brought about significant changes to hereditary breast and ovarian cancer (HBOC) diagnostic testing with new treatments, testing methods and strategies, and evolving information on genetic associations. These best practice guidelines have been produced to assist clinical laboratories in effectively addressing the complexities of HBOC testing, while taking into account advancements since the last guidelines were published in 2007. These guidelines summarise cancer risk data from recent studies for the most commonly tested high and moderate risk HBOC genes for laboratories to refer to as a guide. Furthermore, recommendations are provided for somatic and germline testing services with regards to clinical referral, laboratory analyses, variant interpretation, and reporting. The guidelines present recommendations where 'must' is assigned to advocate that the recommendation is essential; and 'should' is assigned to advocate that the recommendation is highly advised but may not be universally applicable. Recommendations are presented in the form of shaded italicised statements throughout the document, and in the form of a table in supplementary materials (Table S4). Finally, for the purposes of encouraging standardisation and aiding implementation of recommendations, example report wording covering the essential points to be included is provided for the most common HBOC referral and reporting scenarios. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories.
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Affiliation(s)
- Trudi McDevitt
- Department of Clinical Genetics, Children's Health Ireland at Crumlin, Dublin, Ireland.
| | - Miranda Durkie
- Sheffield Diagnostic Genetics Service, North East and Yorkshire Genomic Laboratory Hub, Sheffield Children's NHS Foundation Trust Western Bank, Sheffield, UK
| | - Norbert Arnold
- UKSH Campus Kiel, Gynecology and Obstetrics, Institut of Clinical Chemistry, Institut of Clinical Molecular Biology, Kiel, Germany
| | - George J Burghel
- Manchester University NHS Foundation Trust, North West Genomic Laboratory Hub, Manchester, UK
| | - Samantha Butler
- Central and South Genomic Laboratory Hub, West Midlands Regional Genetics Laboratory, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | | | - Peter Logan
- HSCNI / Belfast Trust Laboratories, Regional Molecular Diagnostics Service, Belfast, Northern Ireland
| | - Rachel Robinson
- Leeds Teaching Hospitals NHS Trust, Genetics Department, Leeds, UK
| | | | | | - Helen Hanson
- St George's University Hospitals NHS Foundation Trust, Clinical Genetics, London, UK
| | | | - Stacey Hume
- University of British Columbia, Pathology and Laboratory Medicine, Vancouver, British Columbia, Canada
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20
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Hung CC, Moi SH, Huang HI, Hsiao TH, Huang CC. Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study. Sci Rep 2024; 14:6324. [PMID: 38491043 PMCID: PMC10943108 DOI: 10.1038/s41598-024-55976-9] [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: 12/06/2023] [Accepted: 02/29/2024] [Indexed: 03/18/2024] Open
Abstract
Mammographic screening has contributed to a significant reduction in breast cancer mortality. Several studies have highlighted the correlation between breast density, as detected through mammography, and a higher likelihood of developing breast cancer. A polygenic risk score (PRS) is a numerical score that is calculated based on an individual's genetic information. This study aims to explore the potential roles of PRS as candidate markers for breast cancer development and investigate the genetic profiles associated with clinical characteristics in Asian females with dense breasts. This is a retrospective cohort study integrated breast cancer screening, population genotyping, and cancer registry database. The PRSs of the study cohort were estimated using genotyping data of 77 single nucleotide polymorphisms based on the PGS000001 Catalog. A subgroup analysis was conducted for females without breast symptoms. Breast cancer patients constituted a higher proportion of individuals in PRS Q4 (37.8% vs. 24.8% in controls). Among dense breast patients with no symptoms, the high PRS group (Q4) consistently showed a significantly elevated breast cancer risk compared to the low PRS group (Q1-Q3) in both univariate (OR = 2.25, 95% CI 1.43-3.50, P < 0.001) and multivariate analyses (OR: 2.23; 95% CI 1.41-3.48, P < 0.001). The study was extended to predict breast cancer risk using common low-penetrance risk variants in a PRS model, which could be integrated into personalized screening strategies for Taiwanese females with dense breasts without prominent symptoms.
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Affiliation(s)
- Chih-Chiang Hung
- Division of Breast Surgery, Department of Surgery, Taichung Veterans General Hospital, Taichung, 407, Taiwan
- Department of Applied Cosmetology, College of Human Science and Social Innovation, Hung Kuang University, Taichung, 433, Taiwan
- College of Life Sciences, National Chung Hsing University, Taichung, 402, Taiwan
| | - Sin-Hua Moi
- Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
- Research Center for Precision Environmental Medicine, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, 807, Taiwan
| | - Hsin-I Huang
- Department of Information Management, National Sun Yat-Sen University, Kaohsiung, 804, Taiwan
- International Integrated Systems, INC, Kaohsiung, 806, Taiwan
| | - Tzu-Hung Hsiao
- Department of Medical Research, Taichung Veterans General Hospital, 1650 Taiwan Boulevard Sect. 4, Taichung, 407219, Taiwan.
- Department of Public Health, Fu Jen Catholic University, New Taipei City, 242, Taiwan.
- Institute of Genomics and Bioinformatics, National Chung Hsing University, Taichung, 402, Taiwan.
| | - Chi-Cheng Huang
- Division of Breast Surgery, Department of Surgery, Taipei Veterans General Hospital, Taipei, 112, Taiwan.
- Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, No.17, Xuzhou Rd., Taipei City, 100, Taiwan.
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21
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Nolan J, Buchanan J, Taylor J, Almeida J, Bedenham T, Blair E, Broadgate S, Butler S, Cazeaux A, Craft J, Cranston T, Crawford G, Forrest J, Gabriel J, George E, Gillen D, Haeger A, Hastings Ward J, Hawkes L, Hodgkiss C, Hoffman J, Jones A, Karpe F, Kasperaviciute D, Kovacs E, Leigh S, Limb E, Lloyd-Jani A, Lopez J, Lucassen A, McFarlane C, O'Rourke AW, Pond E, Sherman C, Stewart H, Thomas E, Thomas S, Thomas T, Thomson K, Wakelin H, Walker S, Watson M, Williams E, Ormondroyd E. Secondary (additional) findings from the 100,000 Genomes Project: Disease manifestation, health care outcomes, and costs of disclosure. Genet Med 2024; 26:101051. [PMID: 38131308 DOI: 10.1016/j.gim.2023.101051] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 12/15/2023] [Accepted: 12/15/2023] [Indexed: 12/23/2023] Open
Abstract
PURPOSE The UK 100,000 Genomes Project offered participants screening for additional findings (AFs) in genes associated with familial hypercholesterolemia (FH) or hereditary cancer syndromes including breast/ovarian cancer (HBOC), Lynch, familial adenomatous polyposis, MYH-associated polyposis, multiple endocrine neoplasia (MEN), and von Hippel-Lindau. Here, we report disclosure processes, manifestation of AF-related disease, outcomes, and costs. METHODS An observational study in an area representing one-fifth of England. RESULTS Data were collected from 89 adult AF recipients. At disclosure, among 57 recipients of a cancer-predisposition-associated AF and 32 recipients of an FH-associated AF, 35% and 88%, respectively, had personal and/or family history evidence of AF-related disease. During post-disclosure investigations, 4 cancer-AF recipients had evidence of disease, including 1 medullary thyroid cancer. Six women with an HBOC AF, 3 women with a Lynch syndrome AF, and 2 individuals with a MEN AF elected for risk-reducing surgery. New hyperlipidemia diagnoses were made in 6 FH-AF recipients and treatment (re-)initiated for 7 with prior hyperlipidemia. Generating and disclosing AFs in this region cost £1.4m; £8680 per clinically significant AF. CONCLUSION Generation and disclosure of AFs identifies individuals with and without personal or familial evidence of disease and prompts appropriate clinical interventions. Results can inform policy toward secondary findings.
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Affiliation(s)
- Joshua Nolan
- Radcliffe Department of Medicine, University of Oxford, United Kingdom
| | - James Buchanan
- Health Economics Research Centre, University of Oxford, United Kingdom
| | - John Taylor
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Joao Almeida
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Tina Bedenham
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Edward Blair
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Suzanne Broadgate
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Samantha Butler
- Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Angela Cazeaux
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Judith Craft
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Treena Cranston
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Gillian Crawford
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Jamie Forrest
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; University of Manchester, Manchester, United Kingdom
| | - Jessica Gabriel
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Elaine George
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Donna Gillen
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Ash Haeger
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | | | - Lara Hawkes
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Claire Hodgkiss
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Jonathan Hoffman
- Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Alan Jones
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
| | - Fredrik Karpe
- Radcliffe Department of Medicine, University of Oxford, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom
| | - Dalia Kasperaviciute
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Erika Kovacs
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Sarah Leigh
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Elizabeth Limb
- Population Health Research Institute, St George's University of London, London, United Kingdom
| | - Anjali Lloyd-Jani
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Javier Lopez
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Anneke Lucassen
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Centre for Personalised Medicine, Nuffield Department of Medicine, University of Oxford, United Kingdom
| | - Carlos McFarlane
- Birmingham Women's and Children's Hospitals NHS Foundation Trust, Birmingham, United Kingdom
| | - Anthony W O'Rourke
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Emily Pond
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Catherine Sherman
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Helen Stewart
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Ellen Thomas
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Simon Thomas
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Tessy Thomas
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Kate Thomson
- Oxford Genetic Laboratories, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Hannah Wakelin
- Oxford Centre for Genomic Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom
| | - Susan Walker
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Melanie Watson
- University Hospitals Southampton NHS Foundation Trust, Southampton, United Kingdom
| | - Eleanor Williams
- Genomics England, United Kingdom Department of Health and Social Care, United Kingdom
| | - Elizabeth Ormondroyd
- Radcliffe Department of Medicine, University of Oxford, United Kingdom; NIHR Oxford Biomedical Research Centre, Oxford, United Kingdom.
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22
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Stan DL, Kim JO, Schaid DJ, Carlson EE, Kim CA, Sinnwell JP, Couch FJ, Vachon CM, Cooke AL, Goldenberg BA, Pruthi S. Breast Cancer Polygenic-Risk Score Influence on Risk-Reducing Endocrine Therapy Use: Genetic Risk Estimate (GENRE) Trial 1-Year and 2-Year Follow-Up. Cancer Prev Res (Phila) 2024; 17:77-84. [PMID: 38154464 DOI: 10.1158/1940-6207.capr-23-0256] [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: 07/13/2023] [Revised: 10/26/2023] [Accepted: 12/21/2023] [Indexed: 12/30/2023]
Abstract
Refinement of breast cancer risk estimates with a polygenic-risk score (PRS) may improve uptake of risk-reducing endocrine therapy (ET). A previous clinical trial assessed the influence of adding a PRS to traditional risk estimates on ET use. We stratified participants according to PRS-refined breast cancer risk and evaluated ET use and ET-related quality of life (QOL) at 1-year (previously reported) and 2-year follow-ups. Of 151 participants, 58 (38.4%) initiated ET, and 22 (14.6%) discontinued ET by 2 years; 42 (27.8%) and 36 (23.8%) participants were using ET at 1- and 2-year follow-ups, respectively. At the 2-year follow-up, 39% of participants with a lifetime breast cancer risk of 40.1% to 100.0%, 18% with a 20.1% to 40.0% risk, and 16% with a 0.0% to 20.0% risk were taking ET (overall P = 0.01). Moreover, 40% of participants whose breast cancer risk increased by 10% or greater with addition of the PRS to a traditional breast cancer-risk model were taking ET versus 0% whose risk decreased by 10% or greater (P = 0.004). QOL was similar for participants taking or not taking ET at 1- and 2-year follow-ups, although most who discontinued ET did so because of adverse effects. However, these QOL results may have been skewed by the long interval between QOL surveys and lack of baseline QOL data. PRS-informed breast cancer prevention counseling has a lasting, but waning, effect over time. Additional follow-up studies are needed to address the effect of PRS on ET adherence, ET-related QOL, supplemental breast cancer screening, and other risk-reducing behaviors. PREVENTION RELEVANCE Risk-reducing medications for breast cancer are considerably underused. Informing women at risk with precise and individualized risk assessment tools may substantially affect the incidence of breast cancer. In our study, a risk assessment tool (IBIS-polygenic-risk score) yielded promising results, with 39% of women at highest risk starting preventive medication.
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Affiliation(s)
- Daniela L Stan
- Breast Diagnostic Clinic, Mayo Clinic, Rochester, Minnesota
- Mayo Clinic Cancer Center, Mayo Clinic, Rochester, Minnesota
| | - Julian O Kim
- Department of Radiation Oncology, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Erin E Carlson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Christina A Kim
- Department of Medical Oncology and Hematology, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Jason P Sinnwell
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Fergus J Couch
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota
- Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, Minnesota
| | - Celine M Vachon
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - Andrew L Cooke
- Department of Radiation Oncology, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Benjamin A Goldenberg
- Department of Medical Oncology and Hematology, Max Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Sandhya Pruthi
- Breast Diagnostic Clinic, Mayo Clinic, Rochester, Minnesota
- Mayo Clinic Cancer Center, Mayo Clinic, Rochester, Minnesota
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23
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Wang A, Shen J, Rodriguez AA, Saunders EJ, Chen F, Janivara R, Darst BF, Sheng X, Xu Y, Chou AJ, Benlloch S, Dadaev T, Brook MN, Plym A, Sahimi A, Hoffman TJ, Takahashi A, Matsuda K, Momozawa Y, Fujita M, Laisk T, Figuerêdo J, Muir K, Ito S, Liu X, Uchio Y, Kubo M, Kamatani Y, Lophatananon A, Wan P, Andrews C, Lori A, Choudhury PP, Schleutker J, Tammela TL, Sipeky C, Auvinen A, Giles GG, Southey MC, MacInnis RJ, Cybulski C, Wokolorczyk D, Lubinski J, Rentsch CT, Cho K, Mcmahon BH, Neal DE, Donovan JL, Hamdy FC, Martin RM, Nordestgaard BG, Nielsen SF, Weischer M, Bojesen SE, Røder A, Stroomberg HV, Batra J, Chambers S, Horvath L, Clements JA, Tilly W, Risbridger GP, Gronberg H, Aly M, Szulkin R, Eklund M, Nordstrom T, Pashayan N, Dunning AM, Ghoussaini M, Travis RC, Key TJ, Riboli E, Park JY, Sellers TA, Lin HY, Albanes D, Weinstein S, Cook MB, Mucci LA, Giovannucci E, Lindstrom S, Kraft P, Hunter DJ, Penney KL, Turman C, Tangen CM, Goodman PJ, Thompson IM, Hamilton RJ, Fleshner NE, Finelli A, Parent MÉ, Stanford JL, Ostrander EA, Koutros S, Beane Freeman LE, Stampfer M, Wolk A, Håkansson N, Andriole GL, Hoover RN, Machiela MJ, Sørensen KD, Borre M, Blot WJ, Zheng W, Yeboah ED, Mensah JE, Lu YJ, Zhang HW, Feng N, Mao X, Wu Y, Zhao SC, Sun Z, Thibodeau SN, McDonnell SK, Schaid DJ, West CM, Barnett G, Maier C, Schnoeller T, Luedeke M, Kibel AS, Drake BF, Cussenot O, Cancel-Tassin G, Menegaux F, Truong T, Koudou YA, John EM, Grindedal EM, Maehle L, Khaw KT, Ingles SA, Stern MC, Vega A, Gómez-Caamaño A, Fachal L, Rosenstein BS, Kerns SL, Ostrer H, Teixeira MR, Paulo P, Brandão A, Watya S, Lubwama A, Bensen JT, Butler EN, Mohler JL, Taylor JA, Kogevinas M, Dierssen-Sotos T, Castaño-Vinyals G, Cannon-Albright L, Teerlink CC, Huff CD, Pilie P, Yu Y, Bohlender RJ, Gu J, Strom SS, Multigner L, Blanchet P, Brureau L, Kaneva R, Slavov C, Mitev V, Leach RJ, Brenner H, Chen X, Holleczek B, Schöttker B, Klein EA, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Kim J, Neuhausen SL, Steele L, Ding YC, Isaacs WB, Nemesure B, Hennis AJ, Carpten J, Pandha H, Michael A, Ruyck KD, Meerleer GD, Ost P, Xu J, Razack A, Lim J, Teo SH, Newcomb LF, Lin DW, Fowke JH, Neslund-Dudas CM, Rybicki BA, Gamulin M, Lessel D, Kulis T, Usmani N, Abraham A, Singhal S, Parliament M, Claessens F, Joniau S, den Broeck TV, Gago-Dominguez M, Castelao JE, Martinez ME, Larkin S, Townsend PA, Aukim-Hastie C, Bush WS, Aldrich MC, Crawford DC, Srivastava S, Cullen J, Petrovics G, Casey G, Wang Y, Tettey Y, Lachance J, Tang W, Biritwum RB, Adjei AA, Tay E, Truelove A, Niwa S, Yamoah K, Govindasami K, Chokkalingam AP, Keaton JM, Hellwege JN, Clark PE, Jalloh M, Gueye SM, Niang L, Ogunbiyi O, Shittu O, Amodu O, Adebiyi AO, Aisuodionoe-Shadrach OI, Ajibola HO, Jamda MA, Oluwole OP, Nwegbu M, Adusei B, Mante S, Darkwa-Abrahams A, Diop H, Gundell SM, Roobol MJ, Jenster G, van Schaik RH, Hu JJ, Sanderson M, Kachuri L, Varma R, McKean-Cowdin R, Torres M, Preuss MH, Loos RJ, Zawistowski M, Zöllner S, Lu Z, Van Den Eeden SK, Easton DF, Ambs S, Edwards TL, Mägi R, Rebbeck TR, Fritsche L, Chanock SJ, Berndt SI, Wiklund F, Nakagawa H, Witte JS, Gaziano JM, Justice AC, Mancuso N, Terao C, Eeles RA, Kote-Jarai Z, Madduri RK, Conti DV, Haiman CA. Characterizing prostate cancer risk through multi-ancestry genome-wide discovery of 187 novel risk variants. Nat Genet 2023; 55:2065-2074. [PMID: 37945903 PMCID: PMC10841479 DOI: 10.1038/s41588-023-01534-4] [Citation(s) in RCA: 50] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 09/15/2023] [Indexed: 11/12/2023]
Abstract
The transferability and clinical value of genetic risk scores (GRSs) across populations remain limited due to an imbalance in genetic studies across ancestrally diverse populations. Here we conducted a multi-ancestry genome-wide association study of 156,319 prostate cancer cases and 788,443 controls of European, African, Asian and Hispanic men, reflecting a 57% increase in the number of non-European cases over previous prostate cancer genome-wide association studies. We identified 187 novel risk variants for prostate cancer, increasing the total number of risk variants to 451. An externally replicated multi-ancestry GRS was associated with risk that ranged from 1.8 (per standard deviation) in African ancestry men to 2.2 in European ancestry men. The GRS was associated with a greater risk of aggressive versus non-aggressive disease in men of African ancestry (P = 0.03). Our study presents novel prostate cancer susceptibility loci and a GRS with effective risk stratification across ancestry groups.
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Affiliation(s)
- Anqi Wang
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jiayi Shen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Fei Chen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Rohini Janivara
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Burcu F. Darst
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Yili Xu
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Alisha J. Chou
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Sara Benlloch
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology,University of Cambridge, Cambridge, UK
| | | | | | - Anna Plym
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Urology Division, Department of Surgery, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ali Sahimi
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | - Thomas J. Hoffman
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Atushi Takahashi
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Department of Genomic Medicine, National Cerebral and Cardiovascular Center Research Institute, Suita, Japan
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Laboratory of Clinical Genome Sequencing,Graduate school of Frontier Sciences,The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - Masashi Fujita
- Laboratory for Cancer Genomics, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jéssica Figuerêdo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Warwick Medical School, University of Warwick, Coventry, UK
| | - Shuji Ito
- Department of Orthopaedics, Shimane University, Izumo, Shimane, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
| | - The Biobank Japan Project
- Corresponding Author: Christopher A. Haiman, Harlyne J. Norris Cancer Research Tower, USC Norris Comprehensive Cancer Center, 1450 Biggy Street, Rm 1504, Los Angeles, CA 90033 or
| | - Yuji Uchio
- Department of Orthopaedics, Shimane University, Izumo, Shimane, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Artitaya Lophatananon
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester, UK
| | - Peggy Wan
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | - Caroline Andrews
- Harvard TH Chan School of Public Health and Division of Population Sciences,Dana Farber Cancer Institute, Boston, MA, USA
| | - Adriana Lori
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | | | - Johanna Schleutker
- Institute of Biomedicine, University of Turku, Turku, Finland
- Department of Medical Genetics, Genomics, Laboratory Division, Turku University Hospital, Turku, Finland
| | | | - Csilla Sipeky
- Institute of Biomedicine, University of Turku, Turku, Finland
| | - Anssi Auvinen
- Unit of Health Sciences, Faculty of Social Sciences, Tampere University, Tampere, Finland
| | - Graham G. Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health,The University of Melbourne, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Melissa C. Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Robert J. MacInnis
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health,The University of Melbourne, Victoria, Australia
| | - Cezary Cybulski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Dominika Wokolorczyk
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Jan Lubinski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Christopher T. Rentsch
- Yale School of Medicine, New Haven, CT, USA
- Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK
- VA Connecticut Healthcare System, West Haven, CT, USA
| | - Kelly Cho
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | - David E. Neal
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- University of Cambridge, Department of Oncology, Addenbrooke’s Hospital, Cambridge, UK
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
| | - Jenny L. Donovan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Freddie C. Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK
- Faculty of Medical Science, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Richard M. Martin
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Borge G. Nordestgaard
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Sune F. Nielsen
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Maren Weischer
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Stig E. Bojesen
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Andreas Røder
- Copenhagen Prostate Cancer Center, Department of Urology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Hein V. Stroomberg
- Copenhagen Prostate Cancer Center, Department of Urology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Jyotsna Batra
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | | | - Lisa Horvath
- Chris O’Brien Lifehouse (COBLH), Camperdown, Sydney, NSW, Australia, Sydney, Australia
- Garvan Institute of Medical Research, Sydney, Australia
| | - Judith A. Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | - Wayne Tilly
- Dame Roma Mitchell Cancer Research Laboratories, University of Adelaide, Adelaide, Australia
| | - Gail P. Risbridger
- Department of Anatomy and Developmental Biology, Biomedicine Discovery Institute, Monash University, Melbourne, Victoria, Australia
- Prostate Cancer Translational Research Program, Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Henrik Gronberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Markus Aly
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, and Department of Urology, Karolinska University Hospital, Solna, Stockholm, Sweden
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | - Robert Szulkin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- SDS Life Sciences, Stockholm, Sweden
| | - Martin Eklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Tobias Nordstrom
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Clinical Sciences at Danderyd Hospital, Karolinska Institutet, Stockholm, Sweden
| | - Nora Pashayan
- University College London, Department of Applied Health Research, London, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Laboratory, Cambridge, UK
- Department of Applied Health Research, University College London, London, UK
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Laboratory, Cambridge, UK
| | - Maya Ghoussaini
- Open Targets, Wellcome Sanger Institute, Hinxton, Saffron Walden, Hinxton, UK
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Tim J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jong Y. Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Thomas A. Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Hui-Yi Lin
- School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephanie Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael B. Cook
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH,, Bethesda, MD, USA
| | - Lorelei A. Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Edward Giovannucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Sara Lindstrom
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Peter Kraft
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David J. Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kathryn L. Penney
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | - Constance Turman
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Catherine M. Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Phyllis J. Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ian M. Thompson
- CHRISTUS Santa Rosa Hospital – Medical Center, San Antonio, TX, USA
| | - Robert J. Hamilton
- Dept. of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Canada
- Dept. of Surgery (Urology), University of Toronto, Toronto, Canada
| | - Neil E. Fleshner
- Dept. of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Canada
| | - Antonio Finelli
- Division of Urology, Princess Margaret Cancer Centre, Toronto, Canada
| | - Marie-Élise Parent
- Epidemiology and Biostatistics Unit, Centre Armand-Frappier Santé Biotechnologie, Laval, QC, Canada
| | - Janet L. Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Elaine A. Ostrander
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Laura E. Beane Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Meir Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | - Alicja Wolk
- Division of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Niclas Håkansson
- Division of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Gerald L. Andriole
- Brady Urological Institute in National Capital Region, Johns Hopkins University, Baltimore, MD, USA
| | - Robert N. Hoover
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Mitchell J. Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Karina Dalsgaard Sørensen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Michael Borre
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Urology, Aarhus University Hospital, Aarhus, Denmark
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- International Epidemiology Institute, Rockville, MD, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - James E. Mensah
- University of Ghana Medical School, Accra, Ghana
- Korle Bu Teaching Hospital, Accra, Ghana
| | - Yong-Jie Lu
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK
| | | | - Ninghan Feng
- Wuxi Second Hospital, Nanjing Medical University, Wuxi, Jiangzhu Province, China
| | - Xueying Mao
- Centre for Molecular Oncology, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK
| | - Yudong Wu
- Department of Urology, First Affiliated Hospital, The Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China
| | - Shan-Chao Zhao
- Department of Urology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Zan Sun
- The People’s Hospital of Liaoning Proviouce, The People’s Hospital of China Medical University, Shenyang, China, Shenyang, China
| | - Stephen N. Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | - Daniel J. Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Catharine M.L. West
- Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | - Gill Barnett
- University of Cambridge Department of Oncology, Oncology Centre, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | | | | | - Adam S. Kibel
- Division of Urologic Surgery, Brigham and Womens Hospital, Boston, MA, USA
| | | | - Olivier Cussenot
- GRC 5 Predictive Onco-Urology, Sorbonne Université, Paris, France
- CeRePP, Paris, France
| | | | - Florence Menegaux
- Exposome and Heredity, CESP (UMR 1018), Paris-Saclay Medical School, Paris-Saclay University, Inserm, Gustave Roussy, Villejuif, France
| | - Thérèse Truong
- Exposome and Heredity, CESP (UMR 1018), Paris-Saclay Medical School, Paris-Saclay University, Inserm, Gustave Roussy, Villejuif, France
| | - Yves Akoli Koudou
- Cancer & Environment Group, Center for Research in Epidemiology and Population Health (CESP), INSERM, University Paris-Sud, University Paris-Saclay, Villejuif Cédex, France
| | - Esther M. John
- Department of Medicine, Stanford Cancer Institute,Stanford University School of Medicine, Stanford, CA, USA
| | | | - Lovise Maehle
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, UK
| | - Sue A. Ingles
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Mariana C Stern
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Ana Vega
- Fundación Pública Galega Medicina Xenómica, Santiago De Compostela, Spain
- Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Spain
| | - Antonio Gómez-Caamaño
- Department of Radiation Oncology, Complexo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
| | - Laura Fachal
- Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Spain
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
- Fundación Pública Galega Medicina Xenómica, Santiago de Compostela, Spain
| | - Barry S. Rosenstein
- Department of Radiation Oncology and Department of Genetics and Genomic Sciences, 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
| | - Sarah L. Kerns
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Harry Ostrer
- Professor of Pathology and Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Manuel R. Teixeira
- Department of Laboratory Genetics, Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
- School of Medicine and Biomedical Sciences (ICBAS), University of Porto, Porto, Portugal
| | - Paula Paulo
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
| | - Andreia Brandão
- Cancer Genetics Group, IPO Porto Research Center (CI-IPOP) / RISE@CI-IPOP (Health Research Network), Portuguese Oncology Institute of Porto (IPO Porto) / Porto Comprehensive Cancer Center, Porto, Portugal
| | | | | | - Jeannette T. Bensen
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ebonee N. Butler
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - James L. Mohler
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Urology, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Jack A. Taylor
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
- Laboratory of Molecular Carcinogenesis, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Manolis Kogevinas
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Trinidad Dierssen-Sotos
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- University of Cantabria-IDIVAL, Santander, Spain
| | - Gemma Castaño-Vinyals
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Lisa Cannon-Albright
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Craig C. Teerlink
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Chad D. Huff
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Patrick Pilie
- Department of Genitourinary Medical Oncology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Yao Yu
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Ryan J. Bohlender
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Jian Gu
- Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA
| | - Sara S. Strom
- The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Luc Multigner
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France
| | - Pascal Blanchet
- CHU de Pointe-à-Pitre, Univ Antilles, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Pointe-à-Pitre, France
| | - Laurent Brureau
- CHU de Pointe-à-Pitre, Univ Antilles, Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Pointe-à-Pitre, France
| | - Radka Kaneva
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, Bulgaria
| | - Chavdar Slavov
- Department of Urology and Alexandrovska University Hospital, Medical University of Sofia, Sofia, Bulgaria
| | - Vanio Mitev
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, Bulgaria
| | - Robin J. Leach
- Department of Cell Systems and Anatomy and Mays Cancer Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Eric A. Klein
- Cleveland Clinic Lerner Research Institute, Cleveland, OH, USA
- Glickman Urological & Kidney Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Ann W. Hsing
- Department of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Adam B. Murphy
- Department of Urology, Northwestern University, Chicago, IL, USA
| | - Christopher J. Logothetis
- The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, Houston, TX, USA
| | - Jeri Kim
- The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, Houston, TX, USA
| | - Susan L. Neuhausen
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Linda Steele
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - Yuan Chun Ding
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - William B. Isaacs
- James Buchanan Brady Urological Institute, Johns Hopkins Hospital and Medical Institution, Baltimore, MD, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anselm J.M. Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
- Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados
| | - John Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Kim De Ruyck
- Ghent University, Faculty of Medicine and Health Sciences, Basic Medical Sciences, Ghent, Belgium
| | - Gert De Meerleer
- Ghent University Hospital, Department of Radiotherapy, Ghent, Belgium
| | - Piet Ost
- Ghent University Hospital, Department of Radiotherapy, Ghent, Belgium
| | - Jianfeng Xu
- Program for Personalized Cancer Care and Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Azad Razack
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Jasmine Lim
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Soo-Hwang Teo
- Cancer Research Malaysia (CRM), Outpatient Centre, Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Lisa F. Newcomb
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Daniel W. Lin
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Jay H. Fowke
- Department of Preventive Medicine, Division of Epidemiology,The University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - Benjamin A. Rybicki
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, Detroit, MI, USA
| | - Marija Gamulin
- Division of Medical Oncology, Urogenital Unit, Department of Oncology, University Hospital Centre Zagreb, Zagreb, Croatia
| | - Davor Lessel
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tomislav Kulis
- Department of Urology, University Hospital Center Zagreb, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Nawaid Usmani
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Aswin Abraham
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Sandeep Singhal
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
| | - Matthew Parliament
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Frank Claessens
- Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, Leuven, Belgium
| | - Steven Joniau
- Department of Urology, University Hospitals Leuven, Leuven, Belgium
| | - Thomas Van den Broeck
- Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, Leuven, Belgium
- Department of Urology, University Hospitals Leuven, Leuven, Belgium
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, Servicio Galego de Saúde, SERGAS, Santiago de Compostela, Spain
- University of California San Diego, Moores Cancer Center, La Jolla, CA, USA
| | - Jose Esteban Castelao
- Genetic Oncology Unit, CHUVI Hospital, Complexo Hospitalario Universitario de Vigo, Instituto de Investigación Biomédica Galicia Sur (IISGS), Vigo (Pontevedra), Spain
| | - Maria Elena Martinez
- University of California San Diego, Moores Cancer Center, Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Samantha Larkin
- Scientific Education Support, Thames Ditton, Surrey, Formerly Cancer Sciences, University of Southampton, Southampton, UK
| | - Paul A. Townsend
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Surrey, UK
| | | | - William S. Bush
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Melinda C. Aldrich
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dana C. Crawford
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
| | - Shiv Srivastava
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC, USA
| | - Jennifer Cullen
- Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH, USA
- Department of Surgery, Center for Prostate Disease Research,Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Gyorgy Petrovics
- Department of Surgery, Center for Prostate Disease Research,Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Graham Casey
- Department of Public Health Science, Center for Public Health Genomics,University of Virginia, Charlottesville, VA, USA
| | - Ying Wang
- Department of Population Science, American Cancer Society, Kennesaw, GA, USA
| | - Yao Tettey
- Korle Bu Teaching Hospital, Accra, Ghana
- Department of Pathology, University of Ghana, Accra, Ghana
| | - Joseph Lachance
- School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA
| | - Wei Tang
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | | | - Andrew A. Adjei
- Department of Pathology, University of Ghana Medical School, Accra, Ghana
| | - Evelyn Tay
- Korle Bu Teaching Hospital, Accra, Ghana
| | | | | | - Kosj Yamoah
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, FL, USA
| | | | | | - Jacob M. Keaton
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Center for Precision Health Research, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Jacklyn N. Hellwege
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Nashville, TN, USA
| | - Peter E. Clark
- Atrium Health/Levine Cancer Institute, Charlotte, NC, USA
| | | | | | | | - Olufemi Ogunbiyi
- Department of Pathology, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Olayiwola Shittu
- Department of Surgery, College of Medicine, University of Ibadan and Univerity College Hospital, Ibadan, Nigeria
| | - Olukemi Amodu
- Institute of Child Health, College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria
| | - Akindele O. Adebiyi
- Clinical Epidemiology Unit, Department of Community Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Oseremen I. Aisuodionoe-Shadrach
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Hafees O. Ajibola
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Mustapha A. Jamda
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Olabode P. Oluwole
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | - Maxwell Nwegbu
- College of Health Sciences, University of Abuja, University of Abuja Teaching Hospital and Cancer Science Center, Abuja, Nigeria
| | | | | | | | - Halimatou Diop
- Laboratoires Bacteriologie et Virologie, Hôpital Aristide Le Dantec, Dakar, Senegal
| | - Susan M. Gundell
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Monique J. Roobol
- Department of Urology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Guido Jenster
- Department of Urology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Ron H.N. van Schaik
- Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Jennifer J. Hu
- The University of Miami School of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Maureen Sanderson
- Department of Family and Community Medicine, Meharry Medical College, Nashville, TN, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford Cancer Institute, Stanford, CA, USA
| | - Rohit Varma
- Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA
| | - Roberta McKean-Cowdin
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | - Mina Torres
- Southern California Eye Institute, CHA Hollywood Presbyterian Medical Center, Los Angeles, CA, USA
| | - Michael H. Preuss
- The Charles Bronfman Institute for Personalized Medicine,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth J.F. Loos
- The Charles Bronfman Institute for Personalized Medicine,Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Matthew Zawistowski
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Sebastian Zöllner
- Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Department of Psychiatry, University of Michigan, Ann Arbor, MI, USA
| | - Zeyun Lu
- Department of Population and Public Health Sciences, Keck School of Medicine,University of Southern California, Los Angeles, CA, USA
| | | | - Douglas F. Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology,, Cambridge, UK
| | - Stefan Ambs
- Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA
| | - Todd L. Edwards
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Timothy R. Rebbeck
- Harvard TH Chan School of Public Health and Division of Population Sciences, Dana Farber Cancer Institute, Boston, MA, USA
| | - Lars Fritsche
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Hidewaki Nakagawa
- Laboratory for Cancer Genomics, RIKEN Center of Integrative Medical Sciences, Yokohama, Japan
| | - John S. Witte
- Department of Epidemiology and Population Health, Stanford Cancer Institute, Stanford, CA, USA
- Departments of Biomedical Data Science, Stanford University, Stanford, CA, USA
| | - J. Michael Gaziano
- Division of Aging, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- VA Boston Healthcare System, Boston, MA, USA
| | | | - Nick Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, Center for Integrative Medical Sciences, RIKEN, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, School of Pharmaceutical Sciences, Shizuoka, Japan
| | - Rosalind A. Eeles
- The Institute of Cancer Research, London, UK
- Royal Marsden NHS Foundation Trust, London, UK
| | | | | | - David V. Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Abou Tayoun AN. Unequal global implementation of genomic newborn screening. Nat Rev Genet 2023; 24:801-802. [PMID: 37723349 DOI: 10.1038/s41576-023-00654-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Affiliation(s)
- Ahmad N Abou Tayoun
- Genomics Center of Excellence, Al Jalila Children's Specialty Hospital, Dubai, United Arab Emirates.
- Center for Genomic Discovery, Mohammed bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates.
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Speiser D, Bick U. Primary Prevention and Early Detection of Hereditary Breast Cancer. Breast Care (Basel) 2023; 18:448-454. [PMID: 38125920 PMCID: PMC10730103 DOI: 10.1159/000533391] [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: 04/16/2023] [Accepted: 08/01/2023] [Indexed: 12/23/2023] Open
Abstract
Background Primary prevention and early detection of hereditary breast cancer has been one of the main topics of breast cancer research in recent decades. The knowledge of risk factors for breast cancer has been increasing continuously just like the recommendations for risk management. Pathogenic germline variants (mutations, class 4/5) of risk genes are significant susceptibility factors in healthy individuals. At the same time, germline mutations serve as biomarkers for targeted therapy in breast cancer treatment. Therefore, management of healthy mutation carriers to enable primary prevention is in the focus as much as the consideration of pathogenic germline variants for therapeutic decisions. Since 1996, the German Consortium has provided quality-assured care for counselees and patients with familial burden of breast and ovarian cancer. Summary Currently, there are 23 university centers with over 100 cooperating DKG-certified breast and gynecological cancer centers. These centers provide standardized, evidence-based, and knowledge-generating care, which includes aspects of primary as well as secondary and tertiary prevention. An important aspect of quality assurance and development was the inclusion of the HBOC centers in the certification system of the German Cancer Society (GCS). Since 2020, the centers have been regularly audited and their quality standards continuously reviewed according to quality indicators adapted to the current state of research. The standard of care at GC-HBOC' centers involves the evaluation as well as evolution of various aspects of care like inclusion criteria, identification of new risk genes, management of variants of unknown significance (class 3), evaluation of risk-reducing options, intensified surveillance, and communication of risks. Among these, the possibility of intensified surveillance in the GC-HBOC for early detection of breast cancer is an important component of individual risk management for many counselees. As has been shown in recent years, in carriers of pathogenic variants in high-risk genes, this approach enables the detection of breast cancer at very early, more favorable stages although no reduction of mortality has been demonstrated yet. The key component of the intensified surveillance is annual contrast-enhanced breast MRI, supplemented by up to biannual breast ultrasound and mammography usually starting at age 40. Key Messages Apart from early detection, the central goal of care is the prevention of cancer. By utilizing individualized risk calculation, the optimal timeframe for risk-reducing surgery can be estimated, and counselees can be supported in reaching preference-sensitive decisions.
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Affiliation(s)
- Dorothee Speiser
- HBOC-Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Gynecology with Breast Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ulrich Bick
- HBOC-Center, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Radiology, Charité-Universitätsmedizin Berlin, Berlin, Germany
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26
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Ying S, Heung T, Thiruvahindrapuram B, Engchuan W, Yin Y, Blagojevic C, Zhang Z, Hegele RA, Yuen RKC, Bassett AS. Polygenic risk for triglyceride levels in the presence of a high impact rare variant. BMC Med Genomics 2023; 16:281. [PMID: 37940981 PMCID: PMC10634078 DOI: 10.1186/s12920-023-01717-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 10/25/2023] [Indexed: 11/10/2023] Open
Abstract
BACKGROUND Elevated triglyceride (TG) levels are a heritable and modifiable risk factor for cardiovascular disease and have well-established associations with common genetic variation captured in a polygenic risk score (PRS). In young adulthood, the 22q11.2 microdeletion conveys a 2-fold increased risk for mild-moderate hypertriglyceridemia. This study aimed to assess the role of the TG-PRS in individuals with this elevated baseline risk for mild-moderate hypertriglyceridemia. METHODS We studied a deeply phenotyped cohort of adults (n = 157, median age 34 years) with a 22q11.2 microdeletion and available genome sequencing, lipid level, and other clinical data. The association between a previously developed TG-PRS and TG levels was assessed using a multivariable regression model adjusting for effects of sex, BMI, and other covariates. We also constructed receiver operating characteristic (ROC) curves using logistic regression models to assess the ability of TG-PRS and significant clinical variables to predict mild-moderate hypertriglyceridemia status. RESULTS The TG-PRS was a significant predictor of TG-levels (p = 1.52E-04), along with male sex and BMI, in a multivariable model (pmodel = 7.26E-05). The effect of TG-PRS appeared to be slightly stronger in individuals with obesity (BMI ≥ 30) (beta = 0.4617) than without (beta = 0.1778), in a model unadjusted for other covariates (p-interaction = 0.045). Among ROC curves constructed, the inclusion of TG-PRS, sex, and BMI as predictor variables produced the greatest area under the curve (0.749) for classifying those with mild-moderate hypertriglyceridemia, achieving an optimal sensitivity and specificity of 0.746 and 0.707, respectively. CONCLUSIONS These results demonstrate that in addition to significant effects of sex and BMI, genome-wide common variation captured in a PRS also contributes to the variable expression of the 22q11.2 microdeletion with respect to elevated TG levels.
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Affiliation(s)
- Shengjie Ying
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tracy Heung
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
- The Dalglish Family 22Q Clinic, University Health Network, Toronto, ON, Canada
| | | | - Worrawat Engchuan
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Yue Yin
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
| | - Christina Blagojevic
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Zhaolei Zhang
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
- Department of Computer Science, University of Toronto, Toronto, ON, Canada
| | - Robert A Hegele
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Ryan K C Yuen
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Anne S Bassett
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, ON, Canada.
- The Dalglish Family 22Q Clinic, University Health Network, Toronto, ON, Canada.
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.
- Toronto General Hospital Research Institute and Campbell Family Mental Health Research Institute, Toronto, ON, Canada.
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27
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Chatterjee N, Dun Y. From Hazard Rate to Age-at-Onset Distribution: Mind the Gap. Cancer Epidemiol Biomarkers Prev 2023; 32:1477-1478. [PMID: 37698541 DOI: 10.1158/1055-9965.epi-23-0897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 09/13/2023] Open
Abstract
A recent study published in the journal claimed that genetic susceptibility to breast cancer occurs mainly due to rare inherited variants. The claim relies on a set of deductive arguments following observations on patterns of age-at-onset distribution of the disease among twin pairs. In this brief commentary, we point out a major gap in the given argument due to the interchangeable use of hazard rates and age-at-onset distribution, and thus conclude that the published study does not provide any evidence against polygenic risk of breast cancer due to common variants. See related article by Yasui et al., p. 1518.
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Affiliation(s)
- Nilanjan Chatterjee
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
- Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Yuzheng Dun
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
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28
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Koch S, Schmidtke J, Krawczak M, Caliebe A. Clinical utility of polygenic risk scores: a critical 2023 appraisal. J Community Genet 2023; 14:471-487. [PMID: 37133683 PMCID: PMC10576695 DOI: 10.1007/s12687-023-00645-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 03/31/2023] [Indexed: 05/04/2023] Open
Abstract
Since their first appearance in the context of schizophrenia and bipolar disorder in 2009, polygenic risk scores (PRSs) have been described for a large number of common complex diseases. However, the clinical utility of PRSs in disease risk assessment or therapeutic decision making is likely limited because PRSs usually only account for the heritable component of a trait and ignore the etiological role of environment and lifestyle. We surveyed the current state of PRSs for various diseases, including breast cancer, diabetes, prostate cancer, coronary artery disease, and Parkinson disease, with an extra focus upon the potential improvement of clinical scores by their combination with PRSs. We observed that the diagnostic and prognostic performance of PRSs alone is consistently low, as expected. Moreover, combining a PRS with a clinical score at best led to moderate improvement of the power of either risk marker. Despite the large number of PRSs reported in the scientific literature, prospective studies of their clinical utility, particularly of the PRS-associated improvement of standard screening or therapeutic procedures, are still rare. In conclusion, the benefit to individual patients or the health care system in general of PRS-based extensions of existing diagnostic or treatment regimens is still difficult to judge.
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Affiliation(s)
- Sebastian Koch
- Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität zu Kiel, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel, Germany
| | - Jörg Schmidtke
- Amedes MVZ Wagnerstibbe, Hannover, Germany
- Institut für Humangenetik, Medizinische Hochschule Hannover, Hannover, Germany
| | - Michael Krawczak
- Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität zu Kiel, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel, Germany
| | - Amke Caliebe
- Institut für Medizinische Informatik und Statistik, Christian-Albrechts-Universität zu Kiel, Universitätsklinikum Schleswig-Holstein Campus Kiel, Kiel, Germany.
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29
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Evans DG, Burghel GJ, Schlecht H, Harkness EF, Gandhi A, Howell SJ, Howell A, Forde C, Lalloo F, Newman WG, Smith MJ, Woodward ER. Detection of pathogenic variants in breast cancer susceptibility genes in bilateral breast cancer. J Med Genet 2023; 60:974-979. [PMID: 37055167 DOI: 10.1136/jmg-2023-109196] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2023] [Accepted: 03/22/2023] [Indexed: 04/15/2023]
Abstract
PURPOSE To investigate the frequency of germline pathogenic variants (PVs) in women with bilateral breast cancer. METHODS We undertook BRCA1/2 and CHEK2 c.1100delC molecular analysis in 764 samples and a multigene panel in 156. Detection rates were assessed by age at first primary, Manchester Score, and breast pathology. Oestrogen receptor (ER) status of the contralateral versus first breast cancer was compared on 1081 patients with breast cancer with BRCA1/BRCA2 PVs. RESULTS 764 women with bilateral breast cancer have undergone testing of BRCA1/2 and CHEK2; 407 were also tested for PALB2 and 177 for ATM. Detection rates were BRCA1 11.6%, BRCA2 14.0%, CHEK2 2.4%, PALB2 1.0%, ATM 1.1% and, for a subset of mainly very early onset tumours, TP53 4.6% (9 of 195). The highest PV detection rates were for triple negative cancers for BRCA1 (26.4%), grade 3 ER+HER2 for BRCA2 (27.9%) and HER2+ for CHEK2 (8.9%). ER status of the first primary in BRCA1 and BRCA2 PV heterozygotes was strongly predictive of the ER status of the second contralateral tumour since ~90% of second tumours were ER- in BRCA1 heterozygotes, and 50% were ER- in BRCA2 heterozygotes if the first was ER-. CONCLUSION We have shown a high rate of detection of BRCA1 and BRCA2 PVs in triple negative and grade 3 ER+HER2- first primary diagnoses, respectively. High rates of HER2+ were associated with CHEK2 PVs, and women ≤30 years were associated with TP53 PVs. First primary ER status in BRCA1/2 strongly predicts the second tumour will be the same ER status even if unusual for PVs in that gene.
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Affiliation(s)
- D Gareth Evans
- Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK
- Genomic Medicine, Manchester Academic Health Science Centre, Manchester, UK
| | - George J Burghel
- Genomic Diagnostic Laboratory, Manchester University NHS Foundation Trust, Manchester, UK
| | - Helene Schlecht
- North West Genomic Laboratory Hub, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | | | - Ashu Gandhi
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Manchester, UK
| | - Sacha J Howell
- Genomic Medicine, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, UK
- Genomic Medicine, The Christie NHS Foundation Trust, Manchester, UK
| | - Anthony Howell
- Genomic Medicine, Prevent Breast Cancer Centre, Manchester, UK
| | - Claire Forde
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - Fiona Lalloo
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Central Manchester University Hospitals NHS Foundation Trust, Manchester, UK
| | - William G Newman
- Genetics, Central Manchester University foundation Trust, Manchester, UK
| | | | - Emma Roisin Woodward
- Manchester Centre for Genomic Medicine, Central Manchester NHS Foundation Trust, Manchester, UK
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30
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Pei L, Yan D, He Q, Kong J, Yang M, Ruan H, Lin Q, Huang L, Huang J, Lin T, Qin H. LncRNA MIR4435-2HG drives cancer progression by modulating cell cycle regulators and mTOR signaling in stroma-enriched subtypes of urothelial carcinoma of the bladder. Cell Oncol (Dordr) 2023; 46:1509-1527. [PMID: 37355516 PMCID: PMC10618329 DOI: 10.1007/s13402-023-00826-5] [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] [Accepted: 05/02/2023] [Indexed: 06/26/2023] Open
Abstract
BACKGROUND The risk for recurrence and metastasis after treatment for urothelial carcinoma of the bladder (UCB) is high. Therefore, identifying efficient prognostic markers and novel therapeutic targets is urgently needed. Several long noncoding RNAs (lncRNAs) have been reported to be correlated with UCB progression. In this study, we found that the subtype-specific lncRNA MIR4435-2 host gene (MIR4435-2HG) plays a novel oncogenic role in UCB. METHODS RNA-Seq data of TCGA/BLCA were analyzed. The expression of MIR4435-2HG was measured by qRT-PCR in 16 pairs of bladder cancer tissues and adjacent normal tissues. The clinical relecance of MIR4435-2HG was validated via in situ hybridization performed on an in-house cohort of 116 UCB patient samples. RNA pull-down followed by mass spectrometry was performed to identify MIR4435-2HG-binding proteins. To identify signaling pathways involved in MIR4435-2HG activity, comprehensive in vitro and in vivo studies and RNA-Seq assays were performed using UCB cells in which MIR4435-2HG expression was knocked down or exogenously overexpressed. In addition, we performed RNA immunoprecipitation and Western blot analyses to validate the identified MIR4435-2HG-binding proteins and to determine the molecular mechanisms by which MIR4435-2HG promotes UCB progression. RESULTS We found that MIR4435-2HG was significantly upregulated in the stromal-enriched subtype of UCB. Increased MIR4435-2HG expression was positively correlated with a high histological grade, advanced T stages, larger tumors, lymph node metastasis and a poor prognosis. In vitro experiments revealed that MIR4435-2HG expression silencing suppressed cell proliferation and induced apoptosis. Inhibition of MIR4434-2HG delayed xenograft tumor growth, while MIR4435-2HG overexpression reversed the MIR4435-2HG silencing-induced inhibition of UCB tumor phenotype acquisition. Mechanistically, we found that MIR4435-2HG positively regulated the expression of a variety of cell cycle regulators, including BRCA2 and CCND1. Knocking down MIR4435-2HG increased the sensitivity of tumor cells to the VEGFR inhibitor cediranib. Furthermore, we found that MIR4435-2HG regulated mTOR signaling and epithelial-mesenchymal transition (EMT) signaling pathways by modulating the phosphorylation of mTOR, 70S6K and 4EBP1. Finally, we confirmed that MIR4435-2HG enhances tumor metastasis through regulation of the EMT pathway. CONCLUSIONS Our data indicate that upregulated MIR4435-2HG expression levels are significantly correlated with a poor prognosis of UCB patients. MIR4435-2HG promotes bladder cancer progression, mediates cell cycle (de)regulation and modulates mTOR signaling. MIR4435-2HG is an oncogenic lncRNA in UCB that may serve as a diagnostic and therapeutic target.
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Affiliation(s)
- Lu Pei
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Dong Yan
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Qingqing He
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jianqiu Kong
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Meihua Yang
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
- Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Honglian Ruan
- School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Qiongqiong Lin
- Department of Pathology, The Second Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Lifang Huang
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jian Huang
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Tianxin Lin
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
| | - Haide Qin
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
- Department of Urology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China.
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31
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Abstract
Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.
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Affiliation(s)
- Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D P Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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32
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Martins Custodio H, Clayton LM, Bellampalli R, Pagni S, Silvennoinen K, Caswell R, Brunklaus A, Guerrini R, Koeleman BPC, Lemke JR, Møller RS, Scheffer IE, Weckhuysen S, Zara F, Zuberi S, Kuchenbaecker K, Balestrini S, Mills JD, Sisodiya SM. Widespread genomic influences on phenotype in Dravet syndrome, a 'monogenic' condition. Brain 2023; 146:3885-3897. [PMID: 37006128 PMCID: PMC10473570 DOI: 10.1093/brain/awad111] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 02/01/2023] [Accepted: 03/12/2023] [Indexed: 04/04/2023] Open
Abstract
Dravet syndrome is an archetypal rare severe epilepsy, considered 'monogenic', typically caused by loss-of-function SCN1A variants. Despite a recognizable core phenotype, its marked phenotypic heterogeneity is incompletely explained by differences in the causal SCN1A variant or clinical factors. In 34 adults with SCN1A-related Dravet syndrome, we show additional genomic variation beyond SCN1A contributes to phenotype and its diversity, with an excess of rare variants in epilepsy-related genes as a set and examples of blended phenotypes, including one individual with an ultra-rare DEPDC5 variant and focal cortical dysplasia. The polygenic risk score for intelligence was lower, and for longevity, higher, in Dravet syndrome than in epilepsy controls. The causal, major-effect, SCN1A variant may need to act against a broadly compromised genomic background to generate the full Dravet syndrome phenotype, whilst genomic resilience may help to ameliorate the risk of premature mortality in adult Dravet syndrome survivors.
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Affiliation(s)
- Helena Martins Custodio
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
| | - Lisa M Clayton
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
| | - Ravishankara Bellampalli
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
| | - Susanna Pagni
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
| | - Katri Silvennoinen
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
- Kuopio Epilepsy Center, Neurocenter, Kuopio University Hospital, Kuopio 70210, Finland
| | - Richard Caswell
- Exeter Genomics Laboratory, Royal Devon University Healthcare NHS Foundation Trust, Exeter EX2 5DW, UK
| | - Andreas Brunklaus
- Paediatric Neuroscience Research Group, Royal Hospital for Children, Glasgow G51 4TF, UK
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8TB, UK
| | - Renzo Guerrini
- Neuroscience Department, Meyer Children’s Hospital IRCSS, University of Florence, 50139 Florence, Italy
| | - Bobby P C Koeleman
- Department of Genetics, University Medical Centre Utrecht, 3584CX Utrecht, The Netherlands
| | - Johannes R Lemke
- Institute of Human Genetics, University of Leipzig Medical Center, Leipzig 04103, Germany
- Center for Rare Diseases, University of Leipzig Medical Center, Leipzig 04103, Germany
| | - Rikke S Møller
- Department of Epilepsy Genetics and Personalized Medicine, Danish Epilepsy Centre, DK-4293 Dianalund, Denmark
- Department of Regional Health Research, University of Southern Denmark, DK-5230 Odense, Denmark
| | - Ingrid E Scheffer
- Epilepsy Research Centre, Florey Institute, University of Melbourne, Austin Health and Royal Children's Hospital, Melbourne, VIC 3084, Australia
- Murdoch Children's Research Institute, Parkville, VIC 3052, Australia
| | - Sarah Weckhuysen
- Applied and Translational Neurogenomics Group, VIB Centre for Molecular Neurology, VIB, Antwerp 2610, Belgium
- Translational Neurosciences, Faculty of Medicine and Health Science, University of Antwerp, Antwerp 2650, Belgium
- Department of Neurology, University Hospital Antwerp, Antwerp 2650, Belgium
- µNEURO Research Centre of Excellence, University of Antwerp, Antwerp 2610, Belgium
| | - Federico Zara
- Unit of Medical Genetics, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
- Department of Neurosciences Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy
| | - Sameer Zuberi
- Paediatric Neuroscience Research Group, Royal Hospital for Children, Glasgow G51 4TF, UK
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8TB, UK
| | | | - Simona Balestrini
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
- Neuroscience Department, Meyer Children’s Hospital IRCSS, University of Florence, 50139 Florence, Italy
| | - James D Mills
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
- Amsterdam UMC, University of Amsterdam, Department of (Neuro)Pathology, Amsterdam Neuroscience, 1105 AZ Amsterdam, The Netherlands
| | - Sanjay M Sisodiya
- University College London Queen Square Institute of Neurology, Department of Clinical and Experimental Epilepsy, London, WC1N 3BG, UK
- Chalfont Centre for Epilepsy, Chalfont St Peter SL9 0RJ, UK
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Stiller S, Drukewitz S, Lehmann K, Hentschel J, Strehlow V. Clinical Impact of Polygenic Risk Score for Breast Cancer Risk Prediction in 382 Individuals with Hereditary Breast and Ovarian Cancer Syndrome. Cancers (Basel) 2023; 15:3938. [PMID: 37568754 PMCID: PMC10417109 DOI: 10.3390/cancers15153938] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 07/21/2023] [Accepted: 07/28/2023] [Indexed: 08/13/2023] Open
Abstract
Single nucleotide polymorphisms are currently not considered in breast cancer (BC) risk predictions used in daily practice of genetic counselling and clinical management of familial BC in Germany. This study aimed to assess the clinical value of incorporating a 313-variant-based polygenic risk score (PRS) into BC risk calculations in a cohort of German women with suspected hereditary breast and ovarian cancer syndrome (HBOC). Data from 382 individuals seeking counselling for HBOC were analysed. Risk calculations were performed using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm with and without the inclusion of the PRS. Changes in risk predictions and their impact on clinical management were evaluated. The PRS led to changes in risk stratification based on 10-year risk calculations in 13.6% of individuals. Furthermore, the inclusion of the PRS in BC risk predictions resulted in clinically significant changes in 12.0% of cases, impacting the prevention recommendations established by the German Consortium for Hereditary Breast and Ovarian Cancer. These findings support the implementation of the PRS in genetic counselling for personalized BC risk assessment.
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Affiliation(s)
- Sarah Stiller
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Stephan Drukewitz
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
- Core Unit for Molecular Tumor Diagnostics (CMTD), National Center for Tumor Diseases (NCT), Partner Site Dresden, 01307 Dresden, Germany
| | - Kathleen Lehmann
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Julia Hentschel
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
| | - Vincent Strehlow
- Institute of Human Genetics, University of Leipzig Medical Center, 04103 Leipzig, Germany
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34
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Xi Q, Jin S, Morris S. Economic evaluations of predictive genetic testing: A scoping review. PLoS One 2023; 18:e0276572. [PMID: 37531363 PMCID: PMC10395838 DOI: 10.1371/journal.pone.0276572] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 04/03/2023] [Indexed: 08/04/2023] Open
Abstract
Predictive genetic testing can provide information about whether or not someone will develop or is likely to develop a specific condition at a later stage in life. Economic evaluation can assess the value of money for such testing. Studies on the economic evaluation of predictive genetic testing have been carried out in a variety of settings, and this research aims to conduct a scoping review of findings from these studies. We searched the PubMed, Web of Science, Embase, and Cochrane databases with combined search terms, from 2019 to 2022. Relevant studies from 2013 to 2019 in a previous systematic review were also included. The study followed the recommended stages for undertaking a scoping review. A total of 53 studies were included, including 33 studies from the previous review and 20 studies from the search of databases. A significant number of studies focused on the US, UK, and Australia (34%, 23%, and 11%). The most frequently included health conditions were cancer and cardiovascular diseases (68% and 19%). Over half of the studies compared predictive genetic testing with no genetic testing, and the majority of them concluded that at least some type of genetic testing was cost-effective compared to no testing (94%). Some studies stated that predictive genetic testing is becoming more cost-effective with the trend of lowering genetic testing costs. Studies on predictive genetic testing covered various health conditions, particularly cancer and cardiovascular diseases. Most studies indicated that predictive genetic testing is cost-effective compared to no testing.
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Affiliation(s)
- Qin Xi
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Shihan Jin
- Department of Pharmaceutical and Health Economics, Leonard D. Schaeffer Center for Health Policy and Economics, School of Pharmacy, University of Southern California, Los Angeles, California, United States of America
| | - Stephen Morris
- Primary Care Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
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35
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Liu Q, Davis J, Han X, Mackey DA, MacGregor S, Craig JE, Si L, Hewitt AW. Cost-effectiveness of polygenic risk profiling for primary open-angle glaucoma in the United Kingdom and Australia. Eye (Lond) 2023; 37:2335-2343. [PMID: 36513856 PMCID: PMC10366078 DOI: 10.1038/s41433-022-02346-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 10/11/2022] [Accepted: 12/01/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Primary open-angle glaucoma (POAG) is the most common subtype of glaucoma. We evaluate the cost-effectiveness of polygenic risk score (PRS) profiling as a screening tool for POAG. METHODS We used a Markov cohort model to evaluate the cost-effectiveness of implementing PRS screening in the UK and Australia, conducted from the healthcare payer's perspective. We used published data to calculate prevalence, transition probabilities, utility, cost and other parameters in the model. Our main outcome measure was the incremental cost-effectiveness ratio (ICER) and secondary outcomes were years of blindness avoided and a 'Blindness ICER'. We did one-way as well as two-way deterministic and probabilistic sensitivity analyses. RESULTS The proposed screening programme for POAG in the UK is predicted to result in ICER of £24,783 (95% CI: £13,373-66,960) and would avoid 1 year of blindness at ICER of £10,095 (95% CI: £5513-27,656). In Australia, it is predicted to result in ICER of AU$34,252 (95% CI: AU$21,324-95,497) and would avoid 1 year of blindness at ICER of AU$13,359 (95% CI: AU$8143-37,448). Using the willingness to pay thresholds of $54,808 and £30,000, the proposed screening model is 79.2% likely to be cost-effective in Australia and is 60.2% likely to be cost-effective in the UK, respectively. CONCLUSION We describe and model the cost-efficacy of incorporating a polygenic risk score for POAG screening in Australia and the UK for the first time and results indicated this is a promising cost-effectiveness strategy.
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Affiliation(s)
- Qinqin Liu
- Menzies Institute for Medical Research, School of Medicine, University of Tasmania, Hobart, TAS, Australia
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, Australia
| | - John Davis
- Menzies Institute for Medical Research, School of Medicine, University of Tasmania, Hobart, TAS, Australia
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, Australia
| | - Xikun Han
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - David A Mackey
- Menzies Institute for Medical Research, School of Medicine, University of Tasmania, Hobart, TAS, Australia
- Centre for Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Perth, WA, Australia
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Jamie E Craig
- Department of Ophthalmology, Flinders University, Flinders Medical Centre, Adelaide, SA, Australia
| | - Lei Si
- School of Health Sciences, Western Sydney University, Campbelltown, NSW, Australia.
- The George Institute for Global Health, University of New South Wales, Kensington, NSW, Australia.
| | - Alex W Hewitt
- Menzies Institute for Medical Research, School of Medicine, University of Tasmania, Hobart, TAS, Australia.
- Centre for Eye Research Australia, University of Melbourne, Melbourne, VIC, Australia.
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Raben TG, Lello L, Widen E, Hsu SDH. Biobank-scale methods and projections for sparse polygenic prediction from machine learning. Sci Rep 2023; 13:11662. [PMID: 37468507 PMCID: PMC10356957 DOI: 10.1038/s41598-023-37580-5] [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: 03/24/2023] [Accepted: 06/23/2023] [Indexed: 07/21/2023] Open
Abstract
In this paper we characterize the performance of linear models trained via widely-used sparse machine learning algorithms. We build polygenic scores and examine performance as a function of training set size, genetic ancestral background, and training method. We show that predictor performance is most strongly dependent on size of training data, with smaller gains from algorithmic improvements. We find that LASSO generally performs as well as the best methods, judged by a variety of metrics. We also investigate performance characteristics of predictors trained on one genetic ancestry group when applied to another. Using LASSO, we develop a novel method for projecting AUC and correlation as a function of data size (i.e., for new biobanks) and characterize the asymptotic limit of performance. Additionally, for LASSO (compressed sensing) we show that performance metrics and predictor sparsity are in agreement with theoretical predictions from the Donoho-Tanner phase transition. Specifically, a future predictor trained in the Taiwan Precision Medicine Initiative for asthma can achieve an AUC of [Formula: see text] and for height a correlation of [Formula: see text] for a Taiwanese population. This is above the measured values of [Formula: see text] and [Formula: see text], respectively, for UK Biobank trained predictors applied to a European population.
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Affiliation(s)
- Timothy G Raben
- Department of Physics and Astronomy, Michigan State University, Michigan, USA.
| | - Louis Lello
- Department of Physics and Astronomy, Michigan State University, Michigan, USA
- Genomic Prediction, Inc., North Brunswick, NJ, USA
| | - Erik Widen
- Department of Physics and Astronomy, Michigan State University, Michigan, USA
- Genomic Prediction, Inc., North Brunswick, NJ, USA
| | - Stephen D H Hsu
- Department of Physics and Astronomy, Michigan State University, Michigan, USA
- Genomic Prediction, Inc., North Brunswick, NJ, USA
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Wu Y, Goleva SB, Breidenbach LB, Kim M, MacGregor S, Gandal MJ, Davis LK, Wray NR. 150 risk variants for diverticular disease of intestine prioritize cell types and enable polygenic prediction of disease susceptibility. CELL GENOMICS 2023; 3:100326. [PMID: 37492107 PMCID: PMC10363821 DOI: 10.1016/j.xgen.2023.100326] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 03/11/2023] [Accepted: 04/20/2023] [Indexed: 07/27/2023]
Abstract
We conducted a genome-wide association study (GWAS) analysis of diverticular disease (DivD) of intestine within 724,372 individuals and identified 150 independent genome-wide significant DNA variants. Integration of the GWAS results with human gut single-cell RNA sequencing data implicated gut myocyte, mesothelial and stromal cells, and enteric neurons and glia in DivD development. Ninety-five genes were prioritized based on multiple lines of evidence, including SLC9A3, a drug target gene of tenapanor used for the treatment of the constipation subtype of irritable bowel syndrome. A DivD polygenic score (PGS) enables effective risk prediction (area under the curve [AUC], 0.688; 95% confidence interval [CI], 0.645-0.732) and the top 20% PGS was associated with ∼3.6-fold increased DivD risk relative to the remaining population. Our statistical and bioinformatic analyses suggest that the mechanism of DivD is through colon structure, gut motility, gastrointestinal mucus, and ionic homeostasis. Our analyses reinforce the link between gastrointestinal disorders and the enteric nervous system through genetics.
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Affiliation(s)
- Yeda Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
- QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | - Slavina B. Goleva
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Lindsay B. Breidenbach
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Minsoo Kim
- Department of Psychiatry, 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
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD 4029, Australia
| | - Michael J. Gandal
- Department of Psychiatry, 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
- Program in Neurobehavioral Genetics, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Lea K. Davis
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Department of Psychiatry and Behavioural Sciences, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Departments of Medicine and Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University, 511-A Light Hall, 2215 Garland Avenue, Nashville, TN 37232, USA
| | - Naomi R. Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4072, Australia
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Ko C, Brody JP. Evaluation of a genetic risk score computed using human chromosomal-scale length variation to predict breast cancer. Hum Genomics 2023; 17:53. [PMID: 37328908 PMCID: PMC10273758 DOI: 10.1186/s40246-023-00482-8] [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: 08/25/2022] [Accepted: 03/30/2023] [Indexed: 06/18/2023] Open
Abstract
INTRODUCTION The ability to accurately predict whether a woman will develop breast cancer later in her life, should reduce the number of breast cancer deaths. Different predictive models exist for breast cancer based on family history, BRCA status, and SNP analysis. The best of these models has an accuracy (area under the receiver operating characteristic curve, AUC) of about 0.65. We have developed computational methods to characterize a genome by a small set of numbers that represent the length of segments of the chromosomes, called chromosomal-scale length variation (CSLV). METHODS We built machine learning models to differentiate between women who had breast cancer and women who did not based on their CSLV characterization. We applied this procedure to two different datasets: the UK Biobank (1534 women with breast cancer and 4391 women who did not) and the Cancer Genome Atlas (TCGA) 874 with breast cancer and 3381 without. RESULTS We found a machine learning model that could predict breast cancer with an AUC of 0.836 95% CI (0.830.0.843) in the UK Biobank data. Using a similar approach with the TCGA data, we obtained a model with an AUC of 0.704 95% CI (0.702, 0.706). Variable importance analysis indicated that no single chromosomal region was responsible for significant fraction of the model results. CONCLUSION In this retrospective study, chromosomal-scale length variation could effectively predict whether or not a woman enrolled in the UK Biobank study developed breast cancer.
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Affiliation(s)
- Charmeine Ko
- Department of Biomedical Engineering, University of California, Irvine, USA
| | - James P Brody
- Department of Biomedical Engineering, University of California, Irvine, USA.
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Berga-Švītiņa E, Maksimenko J, Miklaševičs E, Fischer K, Vilne B, Mägi R. Polygenic Risk Score Predicts Modified Risk in BRCA1 Pathogenic Variant c.4035del and c.5266dup Carriers in Breast Cancer Patients. Cancers (Basel) 2023; 15:cancers15112957. [PMID: 37296919 DOI: 10.3390/cancers15112957] [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: 04/28/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023] Open
Abstract
The aim of this study was to assess the power of the polygenic risk score (PRS) in estimating the overall genetic risk of women carrying germline BRCA1 pathogenic variants (PVs) c.4035del or c.5266dup to develop breast (BC) or ovarian cancer (OC) due to additional genetic variations. In this study, PRSs previously developed from two joint models using summary statistics of age-at-onset (BayesW model) and case-control data (BayesRR-RC model) from a genome-wide association analysis (GWAS) were applied to 406 germline BRCA1 PV (c.4035del or c.5266dup) carriers affected by BC or OC, compared with unaffected individuals. A binomial logistic regression model was used to assess the association of PRS with BC or OC development risk. We observed that the best-fitting BayesW PRS model effectively predicted the individual's BC risk (OR = 1.37; 95% CI = 1.03-1.81, p = 0.02905 with AUC = 0.759). However, none of the applied PRS models was a good predictor of OC risk. The best-fitted PRS model (BayesW) contributed to assessing the risk of developing BC for germline BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timely patient stratification and decision-making to improve the current BC treatment or even prevention strategies.
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Affiliation(s)
- Egija Berga-Švītiņa
- Bioinformatics Lab, Rīga Stradiņš University, Dzirciema Street 16, LV-1007 Riga, Latvia
- Institute of Oncology, Rīga Stradiņš University, Pilsoņu Street 13, Block 13, LV-1002 Riga, Latvia
| | - Jeļena Maksimenko
- Institute of Oncology, Rīga Stradiņš University, Pilsoņu Street 13, Block 13, LV-1002 Riga, Latvia
- Pauls Stradiņš Clinical University Hospital, Pilsoņu Street 13, LV-1002 Riga, Latvia
| | - Edvīns Miklaševičs
- Institute of Oncology, Rīga Stradiņš University, Pilsoņu Street 13, Block 13, LV-1002 Riga, Latvia
- Department of Biology and Microbiology, Rīga Stradiņš University, LV-1007 Riga, Latvia
| | - Krista Fischer
- Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Narva mnt 18, 51009 Tartu, Estonia
| | - Baiba Vilne
- Bioinformatics Lab, Rīga Stradiņš University, Dzirciema Street 16, LV-1007 Riga, Latvia
| | - Reedik Mägi
- Institute of Genomics, University of Tartu, Riia 23b, 51010 Tartu, Estonia
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Chen CY, Tian R, Ge T, Lam M, Sanchez-Andrade G, Singh T, Urpa L, Liu JZ, Sanderson M, Rowley C, Ironfield H, Fang T, Daly M, Palotie A, Tsai EA, Huang H, Hurles ME, Gerety SS, Lencz T, Runz H. The impact of rare protein coding genetic variation on adult cognitive function. Nat Genet 2023:10.1038/s41588-023-01398-8. [PMID: 37231097 DOI: 10.1038/s41588-023-01398-8] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 04/13/2023] [Indexed: 05/27/2023]
Abstract
Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.
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Affiliation(s)
- Chia-Yen Chen
- Research and Development, Biogen Inc, Cambridge, MA, USA.
| | - Ruoyu Tian
- Research and Development, Biogen Inc, Cambridge, MA, USA
- Dewpoint Therapeutics, Boston, MA, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- 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
| | - Max Lam
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | | | - Tarjinder Singh
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Lea Urpa
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Jimmy Z Liu
- Research and Development, Biogen Inc, Cambridge, MA, USA
- GlaxoSmithKline, Philadelphia, PA, USA
| | | | | | | | - Terry Fang
- Research and Development, Biogen Inc, Cambridge, MA, USA
| | - Mark Daly
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Aarno Palotie
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Institute for Molecular Medicine Finland, HiLIFE, University of Helsinki, Helsinki, Finland
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ellen A Tsai
- Research and Development, Biogen Inc, Cambridge, MA, USA
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | | | | | - Todd Lencz
- Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health, Glen Oaks, NY, USA
- Institute of Behavioral Science, Feinstein Institutes for Medical Research, Manhasset, NY, USA
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Molecular Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Heiko Runz
- Research and Development, Biogen Inc, Cambridge, MA, USA.
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Bassi N, Hovland HN, Rasheed K, Jarhelle E, Pedersen N, Mchaina EK, Bakkan SME, Iversen N, Høberg-Vetti H, Haukanes BI, Knappskog PM, Aukrust I, Ognedal E, Van Ghelue M. Functional analyses of rare germline BRCA1 variants by transcriptional activation and homologous recombination repair assays. BMC Cancer 2023; 23:368. [PMID: 37085799 PMCID: PMC10122298 DOI: 10.1186/s12885-023-10790-w] [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: 01/25/2023] [Accepted: 03/30/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Damaging alterations in the BRCA1 gene have been extensively described as one of the main causes of hereditary breast and ovarian cancer (HBOC). BRCA1 alterations can lead to impaired homologous recombination repair (HRR) of double-stranded DNA breaks, a process which involves the RING, BRCT and coiled-coil domains of the BRCA1 protein. In addition, the BRCA1 protein is involved in transcriptional activation (TA) of several genes through its C-terminal BRCT domain. METHODS In this study, we have investigated the effect on HRR and TA of 11 rare BRCA1 missense variants classified as variants of uncertain clinical significance (VUS), located within or in close proximity to the BRCT domain, with the aim of generating additional knowledge to guide the correct classification of these variants. The variants were selected from our previous study "BRCA1 Norway", which is a collection of all BRCA1 variants detected at the four medical genetic departments in Norway. RESULTS All variants, except one, showed a significantly reduced HRR activity compared to the wild type (WT) protein. Two of the variants (p.Ala1708Val and p.Trp1718Ser) also exhibited low TA activity similar to the pathogenic controls. The variant p.Trp1718Ser could be reclassified to likely pathogenic. However, for ten of the variants, the total strength of pathogenic evidence was not sufficient for reclassification according to the CanVIG-UK BRCA1/BRCA2 gene-specific guidelines for variant interpretation. CONCLUSIONS When including the newly achieved functional evidence with other available information, one VUS was reclassified to likely pathogenic. Eight of the investigated variants affected only one of the assessed activities of BRCA1, highlighting the importance of comparing results obtained from several functional assays to better understand the consequences of BRCA1 variants on protein function. This is especially important for multifunctional proteins such as BRCA1.
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Affiliation(s)
- Nicola Bassi
- Department of Medical Genetics, Division of Child and Adolescent Health, University Hospital of North Norway, Tromsø, Norway
| | - Henrikke Nilsen Hovland
- Familial Cancer Center, Haukeland University Hospital, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Kashif Rasheed
- Department of Medical Biology, University of Tromsø, Tromsø, Norway
- Present address: Institute for Clinical and Molecular Medicine, Norwegian University of Science and Technology, NTNU, Trondheim, Norway
| | - Elisabeth Jarhelle
- Department of Medical Genetics, Division of Child and Adolescent Health, University Hospital of North Norway, Tromsø, Norway
- Northern Norway Family Cancer Center, University Hospital of North Norway, Tromsø, Norway
| | - Nikara Pedersen
- Department of Biological Sciences, University of Bergen, Bergen, Norway
| | - Eunice Kabanyana Mchaina
- Familial Cancer Center, Haukeland University Hospital, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | | | - Nina Iversen
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
| | - Hildegunn Høberg-Vetti
- Familial Cancer Center, Haukeland University Hospital, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Bjørn Ivar Haukanes
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Per Morten Knappskog
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Ingvild Aukrust
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway.
- Department of Clinical Science, University of Bergen, Bergen, Norway.
| | - Elisabet Ognedal
- Familial Cancer Center, Haukeland University Hospital, Bergen, Norway
- Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
| | - Marijke Van Ghelue
- Department of Medical Genetics, Division of Child and Adolescent Health, University Hospital of North Norway, Tromsø, Norway
- Northern Norway Family Cancer Center, University Hospital of North Norway, Tromsø, Norway
- Department of Clinical Medicine, University of Tromsø, Tromsø, Norway
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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: 11] [Impact Index Per Article: 5.5] [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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Tomaszowski KH, Roy S, Guerrero C, Shukla P, Keshvani C, Chen Y, Ott M, Wu X, Zhang J, DiNardo CD, Schindler D, Schlacher K. Hypomorphic Brca2 and Rad51c double mutant mice display Fanconi anemia, cancer and polygenic replication stress. Nat Commun 2023; 14:1333. [PMID: 36906610 PMCID: PMC10008622 DOI: 10.1038/s41467-023-36933-y] [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: 02/26/2021] [Accepted: 02/10/2023] [Indexed: 03/13/2023] Open
Abstract
The prototypic cancer-predisposition disease Fanconi Anemia (FA) is identified by biallelic mutations in any one of twenty-three FANC genes. Puzzlingly, inactivation of one Fanc gene alone in mice fails to faithfully model the pleiotropic human disease without additional external stress. Here we find that FA patients frequently display FANC co-mutations. Combining exemplary homozygous hypomorphic Brca2/Fancd1 and Rad51c/Fanco mutations in mice phenocopies human FA with bone marrow failure, rapid death by cancer, cellular cancer-drug hypersensitivity and severe replication instability. These grave phenotypes contrast the unremarkable phenotypes seen in mice with single gene-function inactivation, revealing an unexpected synergism between Fanc mutations. Beyond FA, breast cancer-genome analysis confirms that polygenic FANC tumor-mutations correlate with lower survival, expanding our understanding of FANC genes beyond an epistatic FA-pathway. Collectively, the data establish a polygenic replication stress concept as a testable principle, whereby co-occurrence of a distinct second gene mutation amplifies and drives endogenous replication stress, genome instability and disease.
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Affiliation(s)
- Karl-Heinz Tomaszowski
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Sunetra Roy
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Carolina Guerrero
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Poojan Shukla
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Caezaan Keshvani
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Yue Chen
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Martina Ott
- Department of Neurosurgery, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Xiaogang Wu
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Jianhua Zhang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Courtney D DiNardo
- Department of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA
| | - Detlev Schindler
- Institut fuer Humangenetik, University of Wuerzburg, Wuerzburg, Germany
| | - Katharina Schlacher
- Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA.
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44
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Guan Z, Begg CB, Shen R. Predicting Cancer Risk from Germline Whole-exome Sequencing Data Using a Novel Context-based Variant Aggregation Approach. CANCER RESEARCH COMMUNICATIONS 2023; 3:483-488. [PMID: 36969913 PMCID: PMC10032232 DOI: 10.1158/2767-9764.crc-22-0355] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 01/24/2023] [Accepted: 02/21/2023] [Indexed: 06/18/2023]
Abstract
Many studies have shown that the distributions of the genomic, nucleotide, and epigenetic contexts of somatic variants in tumors are informative of cancer etiology. Recently, a new direction of research has focused on extracting signals from the contexts of germline variants and evidence has emerged that patterns defined by these factors are associated with oncogenic pathways, histologic subtypes, and prognosis. It remains an open question whether aggregating germline variants using meta-features capturing their genomic, nucleotide, and epigenetic contexts can improve cancer risk prediction. This aggregation approach can potentially increase statistical power for detecting signals from rare variants, which have been hypothesized to be a major source of the missing heritability of cancer. Using germline whole-exome sequencing data from the UK Biobank, we developed risk models for 10 cancer types using known risk variants (cancer-associated SNPs and pathogenic variants in known cancer predisposition genes) as well as models that additionally include the meta-features. The meta-features did not improve the prediction accuracy of models based on known risk variants. It is possible that expanding the approach to whole-genome sequencing can lead to gains in prediction accuracy. Significance There is evidence that cancer is partly caused by rare genetic variants that have not yet been identified. We investigate this issue using novel statistical methods and data from the UK Biobank.
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Affiliation(s)
- Zoe Guan
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Colin B. Begg
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Ronglai Shen
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
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45
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Robson M. Testing for Inherited Susceptibility to Breast Cancer. Hematol Oncol Clin North Am 2023; 37:17-31. [PMID: 36435609 DOI: 10.1016/j.hoc.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
When BRCA1 and BRCA2 were first identified, the initial models for delivering testing were shaped by concepts of genetic exceptionalism and a lack of data regarding therapeutic implications and the effectiveness of risk reduction. Since then, interventions have been effective, and treatment implications have become clear. The sensitivity of guideline-based testing is incomplete, leading to calls for universal testing. Completely universal testing, however, is not necessary to identify the great majority of BRCA1 or BRCA2 variants. Broader testing (both in terms of eligibility and genes tested) will identify more variants, particularly in moderate penetrance genes, but the clinical implications remain less clear for these variants.
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Affiliation(s)
- Mark Robson
- Breast Medicine Service, Department of Medicine, Memorial Hospital for Treatment of Cancer and Allied Disease, Memorial Sloan Kettering Cancer Center, Weill Cornell Medical College, 300 East 66th Street, Room 813, New York, NY 10065, USA.
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46
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Ding YC, Adamson AW, Bakhtiari M, Patrick C, Park J, Laitman Y, Weitzel JN, Bafna V, Friedman E, Neuhausen SL. Variable number tandem repeats (VNTRs) as modifiers of breast cancer risk in carriers of BRCA1 185delAG. Eur J Hum Genet 2023; 31:216-222. [PMID: 36434258 PMCID: PMC9905572 DOI: 10.1038/s41431-022-01238-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 10/10/2022] [Accepted: 11/08/2022] [Indexed: 11/27/2022] Open
Abstract
Despite substantial efforts in identifying both rare and common variants affecting disease risk, in the majority of diseases, a large proportion of unexplained genetic risk remains. We propose that variable number tandem repeats (VNTRs) may explain a proportion of the missing genetic risk. Herein, in a pilot study with a retrospective cohort design, we tested whether VNTRs are causal modifiers of breast cancer risk in 347 female carriers of the BRCA1 185delAG pathogenic variant, an important group given their high risk of developing breast cancer. We performed targeted-capture to sequence VNTRs, called genotypes with adVNTR, tested the association of VNTRs and breast cancer risk using Cox regression models, and estimated the effect size using a retrospective likelihood approach. Of 303 VNTRs that passed quality control checks, 4 VNTRs were significantly associated with risk to develop breast cancer at false discovery rate [FDR] < 0.05 and an additional 4 VNTRs had FDR < 0.25. After determining the specific risk alleles, there was a significantly earlier age at diagnosis of breast cancer in carriers of the risk alleles compared to those without the risk alleles for seven of eight VNTRs. One example is a VNTR in exon 2 of LINC01973 with a per-allele hazard ratio of 1.58 (1.07-2.33) and 5.28 (2.79-9.99) for the homozygous risk-allele genotype. Results from this first systematic study of VNTRs demonstrate that VNTRs may explain a proportion of the unexplained genetic risk for breast cancer.
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Affiliation(s)
- Yuan Chun Ding
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Aaron W Adamson
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Mehrdad Bakhtiari
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Carmina Patrick
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Jonghun Park
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Yael Laitman
- Oncogenetics Unit, Institute of Human Genetics, Sheba Medical Center, Ramat Gan, Israel
| | - Jeffrey N Weitzel
- Latin American School of Oncology, Tuxla Gutierrez, Chiapas, MX and Natera, San Carlos, CA, USA
| | - Vineet Bafna
- Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA
| | - Eitan Friedman
- Oncogenetics Unit, Institute of Human Genetics, Sheba Medical Center, Ramat Gan, Israel
- The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Center for Preventive Personalized Medicine, Assuta Medical Center, Tel Aviv, Israel
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA.
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47
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Jung S, Kim Y, Park D, Lee Y, Park S, Baek J, Hwang SW, Park SH, Yang SK, Ye BD, Han B, Song K, Lee HS. Case-case genome-wide association analysis identifying genetic loci with divergent effects on Crohn's disease and ulcerative colitis. Hum Mol Genet 2023; 32:677-684. [PMID: 36164742 DOI: 10.1093/hmg/ddac241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/07/2022] [Accepted: 09/21/2022] [Indexed: 02/07/2023] Open
Abstract
Crohn's disease (CD) and ulcerative colitis (UC), two major subtypes of inflammatory bowel disease, show substantial differences in their clinical course and treatment response. To identify the genetic factors underlying the distinct characteristics of these two diseases, we performed a genome-wide association study (GWAS) between CD (n = 2359) and UC (n = 2175) in a Korean population, followed by replication in an independent sample of 772 CD and 619 UC cases. Two novel loci were identified with divergent effects on CD and UC: rs9842650 in CD200 and rs885026 in NCOR2. In addition, the seven established susceptibility loci [major histocompatibility complex (MHC), TNFSF15, OTUD3, USP12, IL23R, FCHSD2 and RIPK2] reached genome-wide significance. Of the nine loci, six (MHC, TNFSF15, OTUD3, USP12, IL23R and CD200) were replicated in the case-case GWAS of European populations. The proportion of variance explained in CD-UC status by polygenic risk score analysis was up to 22.6%. The area under the receiver-operating characteristic curve value was 0.74, suggesting acceptable discrimination between CD and UC. This CD-UC GWAS provides new insights into genetic differences between the two diseases with similar symptoms and might be useful in improving their diagnosis and treatment.
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Affiliation(s)
- Seulgi Jung
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Yongjae Kim
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Dohoon Park
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Yoonho Lee
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Sojung Park
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Jiwon Baek
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Sung Wook Hwang
- Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Sang Hyoung Park
- Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Suk-Kyun Yang
- Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Byong Duk Ye
- Department of Gastroenterology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Buhm Han
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Korea
| | - Kyuyoung Song
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
| | - Ho-Su Lee
- Department of Biochemistry and Molecular Biology, University of Ulsan College of Medicine, Seoul 05505, Korea
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48
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Lello L, Hsu M, Widen E, Raben TG. Sibling variation in polygenic traits and DNA recombination mapping with UK Biobank and IVF family data. Sci Rep 2023; 13:376. [PMID: 36611071 PMCID: PMC9825593 DOI: 10.1038/s41598-023-27561-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023] Open
Abstract
We use UK Biobank and a unique IVF family dataset (including genotyped embryos) to investigate sibling variation in both phenotype and genotype. We compare phenotype (disease status, height, blood biomarkers) and genotype (polygenic scores, polygenic health index) distributions among siblings to those in the general population. As expected, the between-siblings standard deviation in polygenic scores is [Formula: see text] times smaller than in the general population, but variation is still significant. As previously demonstrated, this allows for substantial benefit from polygenic screening in IVF. Differences in sibling genotypes result from distinct recombination patterns in sexual reproduction. We develop a novel sibling-pair method for detection of recombination breaks via statistical discontinuities. The new method is used to construct a dataset of 1.44 million recombination events which may be useful in further study of meiosis.
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Affiliation(s)
- Louis Lello
- Genomic Prediction, Inc., North Brunswick, NJ, USA.
- Department of Physics and Astronomy, Michigan State University, East Lansing, USA.
| | - Maximus Hsu
- Genomic Prediction, Inc., North Brunswick, NJ, USA
| | - Erik Widen
- Genomic Prediction, Inc., North Brunswick, NJ, USA
- Department of Physics and Astronomy, Michigan State University, East Lansing, USA
| | - Timothy G Raben
- Department of Physics and Astronomy, Michigan State University, East Lansing, USA
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49
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Namba S, Saito Y, Kogure Y, Masuda T, Bondy ML, Gharahkhani P, Gockel I, Heider D, Hillmer A, Jankowski J, MacGregor S, Maj C, Melin B, Ostrom QT, Palles C, Schumacher J, Tomlinson I, Whiteman DC, Okada Y, Kataoka K. Common Germline Risk Variants Impact Somatic Alterations and Clinical Features across Cancers. Cancer Res 2023; 83:20-27. [PMID: 36286845 PMCID: PMC9811159 DOI: 10.1158/0008-5472.can-22-1492] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 08/20/2022] [Accepted: 10/21/2022] [Indexed: 02/03/2023]
Abstract
Aggregation of genome-wide common risk variants, such as polygenic risk score (PRS), can measure genetic susceptibility to cancer. A better understanding of how common germline variants associate with somatic alterations and clinical features could facilitate personalized cancer prevention and early detection. We constructed PRSs from 14 genome-wide association studies (median n = 64,905) for 12 cancer types by multiple methods and calibrated them using the UK Biobank resources (n = 335,048). Meta-analyses across cancer types in The Cancer Genome Atlas (n = 7,965) revealed that higher PRS values were associated with earlier cancer onset and lower burden of somatic alterations, including total mutations, chromosome/arm somatic copy-number alterations (SCNA), and focal SCNAs. This contrasts with rare germline pathogenic variants (e.g., BRCA1/2 variants), showing heterogeneous associations with somatic alterations. Our results suggest that common germline cancer risk variants allow early tumor development before the accumulation of many somatic alterations characteristic of later stages of carcinogenesis. SIGNIFICANCE Meta-analyses across cancers show that common germline risk variants affect not only cancer predisposition but the age of cancer onset and burden of somatic alterations, including total mutations and copy-number alterations.
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Affiliation(s)
- Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Yuki Saito
- Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo, Japan
- Department of Gastroenterology, Keio University School of Medicine, Tokyo, Japan
| | - Yasunori Kogure
- Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo, Japan
| | - Tatsuo Masuda
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Obstetrics and Gynecology, Osaka University Graduate School of Medicine, Osaka, Japan
- StemRIM Institute of Regeneration-Inducing Medicine, Osaka University, Osaka, Japan
| | - Melissa L. Bondy
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
| | - Puya Gharahkhani
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany
| | - Dominik Heider
- Department of Mathematics and Computer Science, University of Marburg, Marburg, Germany
| | - Axel Hillmer
- Institute of Pathology, University of Cologne, Faculty of Medicine and University Hospital Cologne, Cologne, Germany
| | - Janusz Jankowski
- Office of Vice President Research and Innovation, Laucala Bay Campus, University of South Pacific, Suva, Fiji
- Institute for Clinical Trials, University College London, Holborn, London
| | - Stuart MacGregor
- Statistical Genetics Laboratory, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
| | - Beatrice Melin
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Quinn T. Ostrom
- Department of Neurosurgery, Duke University School of Medicine, Durham, North Carolina
- The Preston Robert Tisch Brain Tumor Center, Duke University School of Medicine, Durham, North Carolina
- Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina
| | - Claire Palles
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | | | - Ian Tomlinson
- Edinburgh Cancer Research Centre, IGMM, University of Edinburgh, Crewe Road, Edinburgh, United Kingdom
| | - David C. Whiteman
- Cancer Control, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 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
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita, Japan
| | - Keisuke Kataoka
- Division of Molecular Oncology, National Cancer Center Research Institute, Tokyo, Japan
- Division of Hematology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
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50
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Dite GS, Spaeth E, Murphy NM, Allman R. A combined clinical and genetic model for predicting risk of ovarian cancer. Eur J Cancer Prev 2023; 32:57-64. [PMID: 36503897 PMCID: PMC9746333 DOI: 10.1097/cej.0000000000000771] [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: 08/18/2022] [Accepted: 09/06/2022] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Women with a family history of ovarian cancer or a pathogenic or likely pathogenic gene variant are at high risk of the disease, but very few women have these risk factors. We assessed whether a combined polygenic and clinical risk score could predict risk of ovarian cancer in population-based women who would otherwise be considered as being at average risk. METHODS We used the UK Biobank to conduct a prospective cohort study assessing the performance of 10-year ovarian cancer risks based on a polygenic risk score, a clinical risk score and a combined risk score. We used Cox regression to assess association, Harrell's C-index to assess discrimination and Poisson regression to assess calibration. RESULTS The combined risk model performed best and problems with calibration were overcome by recalibrating the model, which then had a hazard ratio per quintile of risk of 1.338 [95% confidence interval (CI), 1.152-1.553], a Harrell's C-index of 0.663 (95% CI, 0.629-0.698) and overall calibration of 1.000 (95% CI, 0.874-1.145). In the refined model with estimates based on the entire dataset, women in the top quintile of 10-year risk were at 1.387 (95% CI, 1.086-1.688) times increased risk, while women in the top quintile of full-lifetime risk were at 1.527 (95% CI, 1.187-1.866) times increased risk compared with the population. CONCLUSION Identification of women who are at high risk of ovarian cancer can allow healthcare providers and patients to engage in joint decision-making discussions around the risks and benefits of screening options or risk-reducing surgery.
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Affiliation(s)
| | - Erika Spaeth
- Phenogen Sciences Inc, Charlotte, North Carolina, USA
| | | | - Richard Allman
- Genetic Technologies Limited, Fitzroy, Victoria, Australia
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