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5 results on '"Evans, Gareth D."'

1. Correction: Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Author

Dareng, Eileen O, Tyrer, Jonathan P, Barnes, Daniel R, Jones, Michelle R, Yang, Xin, Aben, Katja KH, Adank, Muriel A, Agata, Simona, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Aravantinos, Gerasimos, Arun, Banu K, Augustinsson, Annelie, Balmaña, Judith, Bandera, Elisa V, Barkardottir, Rosa B, Barrowdale, Daniel, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bermisheva, Marina, Bernardini, Marcus Q, Bjorge, Line, Black, Amanda, Bogdanova, Natalia V, Bonanni, Bernardo, Borg, Ake, Brenton, James D, Budzilowska, Agnieszka, Butzow, Ralf, Buys, Saundra S, Cai, Hui, Caligo, Maria A, Campbell, Ian, Cannioto, Rikki, Cassingham, Hayley, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Kexin, Chiew, Yoke-Eng, Chung, Wendy K, Claes, Kathleen BM, Colonna, Sarah, Cook, Linda S, Couch, Fergus J, Daly, Mary B, Dao, Fanny, Davies, Eleanor, de la Hoya, Miguel, de Putter, Robin, Dennis, Joe, DePersia, Allison, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Doherty, Jennifer A, Domchek, Susan M, Dörk, Thilo, du Bois, Andreas, Dürst, Matthias, Eccles, Diana M, Eliassen, Heather A, Engel, Christoph, Evans, Gareth D, Fasching, Peter A, Flanagan, James M, Fortner, Renée T, Machackova, Eva, Friedman, Eitan, Ganz, Patricia A, Garber, Judy, Gensini, Francesca, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goodman, Marc T, Greene, Mark H, Gronwald, Jacek, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Hansen, Thomas VO, Harris, Holly R, Hartman, Mikael, Heitz, Florian, Hildebrandt, Michelle AT, Høgdall, Estrid, Høgdall, Claus K, Hopper, John L, Huang, Ruea-Yea, Huff, Chad, Hulick, Peter J, Huntsman, David G, Imyanitov, Evgeny N, Isaacs, Claudine, Jakubowska, Anna, James, Paul A, and Janavicius, Ramunas

Subjects
GEMO Study Collaborators, GC-HBOC Study Collaborators, EMBRACE Collaborators, OPAL Study Group, AOCS Group, KConFab Investigators, HEBON Investigators, OCAC Consortium, CIMBA Consortium, Genetics, Clinical Sciences, Genetics & Heredity
Published
2022

2. Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Author

Dareng, Eileen O, Tyrer, Jonathan P, Barnes, Daniel R, Jones, Michelle R, Yang, Xin, Aben, Katja KH, Adank, Muriel A, Agata, Simona, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Aravantinos, Gerasimos, Arun, Banu K, Augustinsson, Annelie, Balmaña, Judith, Bandera, Elisa V, Barkardottir, Rosa B, Barrowdale, Daniel, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Benitez, Javier, Bermisheva, Marina, Bernardini, Marcus Q, Bjorge, Line, Black, Amanda, Bogdanova, Natalia V, Bonanni, Bernardo, Borg, Ake, Brenton, James D, Budzilowska, Agnieszka, Butzow, Ralf, Buys, Saundra S, Cai, Hui, Caligo, Maria A, Campbell, Ian, Cannioto, Rikki, Cassingham, Hayley, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Kexin, Chiew, Yoke-Eng, Chung, Wendy K, Claes, Kathleen BM, Colonna, Sarah, Cook, Linda S, Couch, Fergus J, Daly, Mary B, Dao, Fanny, Davies, Eleanor, de la Hoya, Miguel, de Putter, Robin, Dennis, Joe, DePersia, Allison, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Doherty, Jennifer A, Domchek, Susan M, Dörk, Thilo, du Bois, Andreas, Dürst, Matthias, Eccles, Diana M, Eliassen, Heather A, Engel, Christoph, Evans, Gareth D, Fasching, Peter A, Flanagan, James M, Fortner, Renée T, Machackova, Eva, Friedman, Eitan, Ganz, Patricia A, Garber, Judy, Gensini, Francesca, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goodman, Marc T, Greene, Mark H, Gronwald, Jacek, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Hansen, Thomas VO, Harris, Holly R, Hartman, Mikael, Heitz, Florian, Hildebrandt, Michelle AT, Høgdall, Estrid, Høgdall, Claus K, Hopper, John L, Huang, Ruea-Yea, Huff, Chad, Hulick, Peter J, Huntsman, David G, Imyanitov, Evgeny N, Isaacs, Claudine, Jakubowska, Anna, James, Paul A, and Janavicius, Ramunas

Subjects
Prevention, Cancer, Ovarian Cancer, Rare Diseases, Good Health and Well Being, Bayes Theorem, Breast Neoplasms, Carcinoma, Ovarian Epithelial, Female, Genetic Predisposition to Disease, Humans, Male, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Prospective Studies, Risk Factors, GEMO Study Collaborators, GC-HBOC Study Collaborators, EMBRACE Collaborators, OPAL Study Group, AOCS Group, KConFab Investigators, HEBON Investigators, OCAC Consortium, CIMBA Consortium, Genetics, Clinical Sciences, Genetics & Heredity
Abstract

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.

Published
2022

3. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Author

Wang, Xiaoliang, Kapoor, Pooja Middha, Auer, Paul L, Dennis, Joe, Dunning, Alison M, Wang, Qin, Lush, Michael, Michailidou, Kyriaki, Bolla, Manjeet K, Aronson, Kristan J, Murphy, Rachel A, Brooks-Wilson, Angela, Lee, Derrick G, Cordina-Duverger, Emilie, Guénel, Pascal, Truong, Thérèse, Mulot, Claire, Teras, Lauren R, Patel, Alpa V, Dossus, Laure, Kaaks, Rudolf, Hoppe, Reiner, Lo, Wing-Yee, Brüning, Thomas, Hamann, Ute, Czene, Kamila, Gabrielson, Marike, Hall, Per, Eriksson, Mikael, Jung, Audrey, Becher, Heiko, Couch, Fergus J, Larson, Nicole L, Olson, Janet E, Ruddy, Kathryn J, Giles, Graham G, MacInnis, Robert J, Southey, Melissa C, Le Marchand, Loic, Wilkens, Lynne R, Haiman, Christopher A, Olsson, Håkan, Augustinsson, Annelie, Krüger, Ute, Wagner, Philippe, Scott, Christopher, Winham, Stacey J, Vachon, Celine M, Perou, Charles M, Olshan, Andrew F, Troester, Melissa A, Hunter, David J, Eliassen, Heather A, Tamimi, Rulla M, Brantley, Kristen, Andrulis, Irene L, Figueroa, Jonine, Chanock, Stephen J, Ahearn, Thomas U, García-Closas, Montserrat, Evans, Gareth D, Newman, William G, van Veen, Elke M, Howell, Anthony, Wolk, Alicja, Håkansson, Niclas, Anton-Culver, Hoda, Ziogas, Argyrios, Jones, Michael E, Orr, Nick, Schoemaker, Minouk J, Swerdlow, Anthony J, Kitahara, Cari M, Linet, Martha, Prentice, Ross L, Easton, Douglas F, Milne, Roger L, Kraft, Peter, Chang-Claude, Jenny, and Lindström, Sara

Subjects
Genetics, Cancer, Aging, Human Genome, Breast Cancer, Prevention, Estrogen, 2.1 Biological and endogenous factors, Aetiology, Breast, Breast Neoplasms, Estrogen Replacement Therapy, Female, Hormone Replacement Therapy, Humans, Male, Menopause, Risk Factors
Abstract

Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values

Published
2022

4. Genome-Wide Interaction Analysis of Menopausal Hormone Therapy Use and Breast Cancer Risk Among 62,370 Women

Author

Wang, Xiaoliang, Kapoor, Pooja Middha, Auer, Paul L, Dennis, Joe, Dunning, Alison M, Wang, Qin, Lush, Michael, Michailidou, Kyriaki, Bolla, Manjeet K, Aronson, Kristan J, Murphy, Rachel A, Brooks-Wilson, Angela, Lee, Derrick G, Cordina-Duverger, Emilie, Guénel, Pascal, Truong, Thérèse, Mulot, Claire, Teras, Lauren R, Patel, Alpa V, Dossus, Laure, Kaaks, Rudolf, Hoppe, Reiner, Lo, Wing-Yee, Brüning, Thomas, Hamann, Ute, Czene, Kamila, Gabrielson, Marike, Hall, Per, Eriksson, Mikael, Jung, Audrey, Becher, Heiko, Couch, Fergus J, Larson, Nicole L, Olson, Janet E, Ruddy, Kathryn J, Giles, Graham G, MacInnis, Robert J, Southey, Melissa C, Marchand, Loic Le, Wilkens, Lynne R, Haiman, Christopher A, Olsson, Håkan, Augustinsson, Annelie, Krüger, Ute, Wagner, Philippe, Scott, Christopher, Winham, Stacey J, Vachon, Celine M, Perou, Charles M, Olshan, Andrew F, Troester, Melissa A, Hunter, David J, Eliassen, A Heather, Tamimi, Rulla M, Brantley, Kristen, Andrulis, Irene L, Figueroa, Jonine, Chanock, Stephen J, Ahearn, Thomas U, García-Closas, Montserrat, Evans, Gareth D, Newman, William G, Veen, Elke M van, Howell, Anthony, Wolk, Alicja, Håkansson, Niclas, Anton-Culver, Hoda, Ziogas, Argyrios, Jones, Michael E, Orr, Nick, Schoemaker, Minouk J, Swerdlow, Anthony J, Kitahara, Cari M, Linet, Martha, Prentice, Ross L, Easton, Douglas F, Milne, Roger L, Kraft, Peter, Chang-Claude, Jenny, and Lindström, Sara

Subjects
Cancer, Prevention, Breast Cancer, Genetics, Human Genome, Aging, Estrogen, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being
Abstract

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values

Published
2021

5. CTF meeting 2012: Translation of the basic understanding of the biology and genetics of NF1, NF2, and schwannomatosis toward the development of effective therapies

Author

Widemann, Brigitte C, Acosta, Maria T, Ammoun, Sylvia, Belzberg, Allan J, Bernards, Andre, Blakeley, Jaishri, Bretscher, Antony, Cichowski, Karen, Clapp, D Wade, Dombi, Eva, Evans, Gareth D, Ferner, Rosalie, Fernandez‐Valle, Cristina, Fisher, Michael J, Giovannini, Marco, Gutmann, David H, Hanemann, C Oliver, Hennigan, Robert, Huson, Susan, Ingram, David, Kissil, Joe, Korf, Bruce R, Legius, Eric, Packer, Roger J, McClatchey, Andrea I, McCormick, Frank, North, Kathryn, Pehrsson, Minja, Plotkin, Scott R, Ramesh, Vijaya, Ratner, Nancy, Schirmer, Susann, Sherman, Larry, Schorry, Elizabeth, Stevenson, David, Stewart, Douglas R, Ullrich, Nicole, Bakker, Annette C, and Morrison, Helen

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Cancer, Genetics, Neurosciences, Neurofibromatosis, Pediatric Research Initiative, Rare Diseases, Pediatric, Intellectual and Developmental Disabilities (IDD), Humans, Neurilemmoma, Neurofibromatoses, Neurofibromatosis 1, Neurofibromatosis 2, Skin Neoplasms, neurofibromatosis type 1, neurofibromatosis type 2, NF1, NF2, schwannomatosis, tumor suppressor, SMARCB1, merlin neurofibromin, preclinical models, Clinical sciences
Abstract

The neurofibromatoses (NF) are autosomal dominant genetic disorders that encompass the rare diseases NF1, NF2, and schwannomatosis. The NFs affect more people worldwide than Duchenne muscular dystrophy and Huntington's disease combined. NF1 and NF2 are caused by mutations of known tumor suppressor genes (NF1 and NF2, respectively). For schwannomatosis, although mutations in SMARCB1 were identified in a subpopulation of schwannomatosis patients, additional causative gene mutations are still to be discovered. Individuals with NF1 may demonstrate manifestations in multiple organ systems, including tumors of the nervous system, learning disabilities, and physical disfigurement. NF2 ultimately can cause deafness, cranial nerve deficits, and additional severe morbidities caused by tumors of the nervous system. Unmanageable pain is a key finding in patients with schwannomatosis. Although today there is no marketed treatment for NF-related tumors, a significant number of clinical trials have become available. In addition, significant preclinical efforts have led to a more rational selection of potential drug candidates for NF trials. An important element in fueling this progress is the sharing of knowledge. For over 20 years the Children's Tumor Foundation has convened an annual NF Conference, bringing together NF professionals to share novel findings, ideas, and build collaborations. The 2012 NF Conference held in New Orleans hosted over 350 NF researchers and clinicians. This article provides a synthesis of the highlights presented at the conference and as such, is a "state-of-the-field" for NF research in 2012.

Published
2014

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