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Your search keyword '"Nordestgaard, Børge G"' showing total 5 results
Start Over Author "Nordestgaard, Børge G" Journal breast cancer research
5 results on '"Nordestgaard, Børge G"'

1. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Middha, Pooja, Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baert, Thaïs, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Benitez, Javier, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dossus, Laure, Dugué, Pierre-Antoine, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G, González-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Holleczek, Bernd, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ingvar, Christian, Isaksson, Karolin, Jernström, Helena, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Larson, Nicole L, Larsson, Susanna, Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Norman, Aaron, O’Brien, Katie M, Olson, Janet E, Patel, Alpa V, Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J, and Sandler, Dale P

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer Genomics, Human Genome, Estrogen, Cancer, Women's Health, Genetics, Prevention, Aging, Breast Cancer, 2.1 Biological and endogenous factors, Adult, Female, Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Breast Neoplasms, Bayes Theorem, Genome-Wide Association Study, Risk Factors, Polymorphism, Single Nucleotide, Case-Control Studies, Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, CTS Consortium, ABCTB Investigators, kConFab Investigators, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundGenome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.MethodsAnalyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.ResultsAssuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Published
2023

2. Refined histopathological predictors of BRCA1 and BRCA2mutation status: a large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Author

Spurdle, Amanda B, Couch, Fergus J, Parsons, Michael T, McGuffog, Lesley, Barrowdale, Daniel, Bolla, Manjeet K, Wang, Qin, Healey, Sue, Schmutzler, Rita Katharina, Wappenschmidt, Barbara, Rhiem, Kerstin, Hahnen, Eric, Engel, Christoph, Meindl, Alfons, Ditsch, Nina, Arnold, Norbert, Plendl, Hansjoerg, Niederacher, Dieter, Sutter, Christian, Wang-Gohrke, Shan, Steinemann, Doris, Preisler-Adams, Sabine, Kast, Karin, Varon-Mateeva, Raymonda, Ellis, Steve, Frost, Debra, Platte, Radka, Perkins, Jo, Evans, D Gareth, Izatt, Louise, Eeles, Ros, Adlard, Julian, Davidson, Rosemarie, Cole, Trevor, Scuvera, Giulietta, Manoukian, Siranoush, Bonanni, Bernardo, Mariette, Frederique, Fortuzzi, Stefano, Viel, Alessandra, Pasini, Barbara, Papi, Laura, Varesco, Liliana, Balleine, Rosemary, Nathanson, Katherine L, Domchek, Susan M, Offitt, Kenneth, Jakubowska, Anna, Lindor, Noralane, Thomassen, Mads, Jensen, Uffe Birk, Rantala, Johanna, Borg, Åke, Andrulis, Irene L, Miron, Alexander, Hansen, Thomas VO, Caldes, Trinidad, Neuhausen, Susan L, Toland, Amanda E, Nevanlinna, Heli, Montagna, Marco, Garber, Judy, Godwin, Andrew K, Osorio, Ana, Factor, Rachel E, Terry, Mary B, Rebbeck, Timothy R, Karlan, Beth Y, Southey, Melissa, Rashid, Muhammad Usman, Tung, Nadine, Pharoah, Paul DP, Blows, Fiona M, Dunning, Alison M, Provenzano, Elena, Hall, Per, Czene, Kamila, Schmidt, Marjanka K, Broeks, Annegien, Cornelissen, Sten, Verhoef, Senno, Fasching, Peter A, Beckmann, Matthias W, Ekici, Arif B, Slamon, Dennis J, Bojesen, Stig E, Nordestgaard, Børge G, Nielsen, Sune F, Flyger, Henrik, Chang-Claude, Jenny, Flesch-Janys, Dieter, Rudolph, Anja, Seibold, Petra, Aittomäki, Kristiina, Muranen, Taru A, Heikkilä, Päivi, Blomqvist, Carl, Figueroa, Jonine, Chanock, Stephen J, and Brinton, Louise

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Breast Cancer, Cancer, Prevention, Genetics, Detection, screening and diagnosis, 4.2 Evaluation of markers and technologies, Adult, Age Factors, Aged, Breast Neoplasms, Carcinoma, Female, Genes, BRCA1, Genes, BRCA2, Humans, Likelihood Functions, Middle Aged, Mutation, Neoplasm Grading, Neoplasm Staging, Receptor, ErbB-2, Receptors, Estrogen, Receptors, Progesterone, Triple Negative Breast Neoplasms, ABCTB Investigators, EMBRACE Group, GENICA Network, HEBON Group, kConFab Investigators, Receptor, erbB-2, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the likelihood of mutation status by histopathological markers were derived using a Mantel-Haenszel approach. ER-positive phenotype negatively predicted BRCA1 mutation status, irrespective of grade (LRs from 0.08 to 0.90). ER-negative grade 3 histopathology was more predictive of positive BRCA1 mutation status in women 50 years or older (LR = 4.13 (3.70 to 4.62)) versus younger than 50 years (LR = 3.16 (2.96 to 3.37)). For BRCA2, ER-positive grade 3 phenotype modestly predicted positive mutation status irrespective of age (LR = 1.7-fold), whereas ER-negative grade 3 features modestly predicted positive mutation status at 50 years or older (LR = 1.54 (1.27 to 1.88)). Triple-negative tumor status was highly predictive of BRCA1 mutation status for women younger than 50 years (LR = 3.73 (3.43 to 4.05)) and 50 years or older (LR = 4.41 (3.86 to 5.04)), and modestly predictive of positive BRCA2 mutation status in women 50 years or older (LR = 1.79 (1.42 to 2.24)). These results refine likelihood-ratio estimates for predicting BRCA1 and BRCA2 mutation status by using commonly measured histopathological features. Age at diagnosis is an important variable for most analyses, and grade is more informative than ER status for BRCA2 mutation carrier prediction. The estimates will improve BRCA1 and BRCA2 variant classification and inform patient mutation testing and clinical management.

Published
2014

3. Assessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the Breast Cancer Association Consortium: a combined case-control study

Author

Milne, Roger L, Gaudet, Mia M, Spurdle, Amanda B, Fasching, Peter A, Couch, Fergus J, Benítez, Javier, Arias Pérez, José Ignacio, Zamora, M Pilar, Malats, Núria, dos Santos Silva, Isabel, Gibson, Lorna J, Fletcher, Olivia, Johnson, Nichola, Anton-Culver, Hoda, Ziogas, Argyrios, Figueroa, Jonine, Brinton, Louise, Sherman, Mark E, Lissowska, Jolanta, Hopper, John L, Dite, Gillian S, Apicella, Carmel, Southey, Melissa C, Sigurdson, Alice J, Linet, Martha S, Schonfeld, Sara J, Freedman, D Michal, Mannermaa, Arto, Kosma, Veli-Matti, Kataja, Vesa, Auvinen, Päivi, Andrulis, Irene L, Glendon, Gord, Knight, Julia A, Weerasooriya, Nayana, Cox, Angela, Reed, Malcolm WR, Cross, Simon S, Dunning, Alison M, Ahmed, Shahana, Shah, Mitul, Brauch, Hiltrud, Ko, Yon-Dschun, Brüning, Thomas, hiltrud.brauch@ikp-stuttgart.de, Lambrechts, Diether, Reumers, Joke, Smeets, Ann, Wang-Gohrke, Shan, Hall, Per, Czene, Kamila, Liu, Jianjun, Irwanto, Astrid K, Chenevix-Trench, Georgia, Holland, Helene, Georgia.Trench@qimr.edu.au, Giles, Graham G, Baglietto, Laura, Severi, Gianluca, Bojensen, Stig E, Nordestgaard, Børge G, Flyger, Henrik, John, Esther M, West, Dee W, Whittemore, Alice S, Vachon, Celine, Olson, Janet E, Fredericksen, Zachary, Kosel, Matthew, Hein, Rebecca, Vrieling, Alina, Flesch-Janys, Dieter, Heinz, Judith, Beckmann, Matthias W, Heusinger, Katharina, Ekici, Arif B, Haeberle, Lothar, Humphreys, Manjeet K, Morrison, Jonathan, Easton, Doug F, Pharoah, Paul D, García-Closas, Montserrat, Goode, Ellen L, and Chang-Claude, Jenny

Abstract

Abstract Introduction Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. Methods We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. Results These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. Conclusions The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.

Published
2010

5. Patient survival and tumor characteristics associated with CHEK2:p.I157T – findings from the Breast Cancer Association Consortium

Author

Muranen, Taru A., primary, Blomqvist, Carl, additional, Dörk, Thilo, additional, Jakubowska, Anna, additional, Heikkilä, Päivi, additional, Fagerholm, Rainer, additional, Greco, Dario, additional, Aittomäki, Kristiina, additional, Bojesen, Stig E., additional, Shah, Mitul, additional, Dunning, Alison M., additional, Rhenius, Valerie, additional, Hall, Per, additional, Czene, Kamila, additional, Brand, Judith S., additional, Darabi, Hatef, additional, Chang-Claude, Jenny, additional, Rudolph, Anja, additional, Nordestgaard, Børge G., additional, Couch, Fergus J., additional, Hart, Steven N., additional, Figueroa, Jonine, additional, García-Closas, Montserrat, additional, Fasching, Peter A., additional, Beckmann, Matthias W., additional, Li, Jingmei, additional, Liu, Jianjun, additional, Andrulis, Irene L., additional, Winqvist, Robert, additional, Pylkäs, Katri, additional, Mannermaa, Arto, additional, Kataja, Vesa, additional, Lindblom, Annika, additional, Margolin, Sara, additional, Lubinski, Jan, additional, Dubrowinskaja, Natalia, additional, Bolla, Manjeet K., additional, Dennis, Joe, additional, Michailidou, Kyriaki, additional, Wang, Qin, additional, Easton, Douglas F., additional, Pharoah, Paul D. P., additional, Schmidt, Marjanka K., additional, and Nevanlinna, Heli, additional

Published
2016
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