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274 results on '"Chanock, Stephen J"'

1. Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions

Author

Lindström, Sara, Wang, Lu, Feng, Helian, Majumdar, Arunabha, Huo, Sijia, Macdonald, James, Harrison, Tabitha, Turman, Constance, Chen, Hongjie, Mancuso, Nicholas, Bammler, Theo, Consortium, Breast Cancer Association, Gallinger, Steve, Gruber, Stephen B, Gunter, Marc J, Le Marchand, Loic, Moreno, Victor, Offit, Kenneth, Study, Genetics And Epidemiology Of Colorectal Cancer Consortium Colorectal Transdisciplinary Study Colon Cancer Family Registry, De Vivo, Immaculata, O’Mara, Tracy A, Spurdle, Amanda B, Tomlinson, Ian, Consortium, Endometrial Cancer Association, Fitzgerald, Rebecca, Gharahkhani, Puya, Gockel, Ines, Jankowski, Janusz, Macgregor, Stuart, Schumacher, Johannes, Barnholtz-Sloan, Jill, Bondy, Melissa L, Houlston, Richard S, Jenkins, Robert B, Melin, Beatrice, Wrensch, Margaret, Brennan, Paul, Christiani, David C, Johansson, Mattias, Mckay, James, Aldrich, Melinda C, Amos, Christopher I, Landi, Maria Teresa, Tardon, Adonina, Consortium, International Lung Cancer, Bishop, D Timothy, Demenais, Florence, Goldstein, Alisa M, Iles, Mark M, Kanetsky, Peter A, Law, Matthew H, Consortium, Ovarian Cancer Association, Amundadottir, Laufey T, Stolzenberg-Solomon, Rachael, Wolpin, Brian M, Consortium, Pancreatic Cancer Cohort, Klein, Alison, Petersen, Gloria, Risch, Harvey, Consortium, The PRACTICAL Consortium Pancreatic Cancer Case-Control, Chanock, Stephen J, Purdue, Mark P, Scelo, Ghislaine, Pharoah, Paul, Kar, Siddhartha, Hung, Rayjean J, Pasaniuc, Bogdan, and Kraft, Peter

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Human Genome, Genetics, Digestive Diseases, Prevention, Clinical Research, Urologic Diseases, Cancer, Rare Diseases, Aetiology, 2.1 Biological and endogenous factors, Male, Humans, Genome-Wide Association Study, Genetic Predisposition to Disease, Neoplasms, Risk Factors, Transcriptome, Polymorphism, Single Nucleotide, Breast Cancer Association Consortium, Colorectal Transdisciplinary Study (CORECT), Colon Cancer Family Registry Study (CCFR), Genetics And Epidemiology Of Colorectal Cancer Consortium, Endometrial Cancer Association Consortium, International Lung Cancer Consortium, Ovarian Cancer Association Consortium, Pancreatic Cancer Cohort Consortium, Pancreatic Cancer Case-Control Consortium (Panc4), The PRACTICAL Consortium, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundThe shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci.MethodsWe collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci.ResultsWe observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci.ConclusionsOverall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

Published
2023

2. Genetically adjusted PSA levels for prostate cancer screening.

Author

Kachuri, Linda, Hoffmann, Thomas J, Jiang, Yu, Berndt, Sonja I, Shelley, John P, Schaffer, Kerry R, Machiela, Mitchell J, Freedman, Neal D, Huang, Wen-Yi, Li, Shengchao A, Easterlin, Ryder, Goodman, Phyllis J, Till, Cathee, Thompson, Ian, Lilja, Hans, Van Den Eeden, Stephen K, Chanock, Stephen J, Haiman, Christopher A, Conti, David V, Klein, Robert J, Mosley, Jonathan D, Graff, Rebecca E, and Witte, John S

Subjects
Humans, Prostatic Neoplasms, Prostate-Specific Antigen, Biopsy, Male, Early Detection of Cancer, Neoplasm Grading, Aging, Prevention, Cancer, Urologic Diseases, Prostate Cancer, Genetics, Good Health and Well Being, Medical and Health Sciences, Immunology
Abstract

Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. In this study, we discovered 128 genome-wide significant associations (P

Published
2023

3. 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

4. Aggregation tests identify new gene associations with breast cancer in populations with diverse ancestry

Author

Mueller, Stefanie H, Lai, Alvina G, Valkovskaya, Maria, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Lush, Michael, Abu-Ful, Zomoruda, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baert, Thais, Freeman, Laura E Beane, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Brenner, Hermann, Brucker, Sara Y, Buys, Saundra S, Castelao, Jose E, Chan, Tsun L, Chang-Claude, Jenny, Chanock, Stephen J, Choi, Ji-Yeob, Chung, Wendy K, Colonna, Sarah V, Cornelissen, Sten, Couch, Fergus J, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Yu-Tang, García-Closas, Montserrat, García-Sáenz, José A, Genkinger, Jeanine, Gentry-Maharaj, Aleksandra, Grassmann, Felix, Guénel, Pascal, Gündert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Harkness, Elaine F, Harrington, Patricia A, Hartikainen, Jaana M, Hartman, Mikael, Hein, Alexander, Ho, Weang-Kee, Hooning, Maartje J, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Huo, Dezheng, Ito, Hidemi, Iwasaki, Motoki, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Khusnutdinova, Elza K, Kim, Sung-Won, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Kwong, Ava, Lacey, James V, Lambrechts, Diether, and Le Marchand, Loic

Subjects
Breast Cancer, Genetics, Clinical Research, Cancer, Aetiology, 2.1 Biological and endogenous factors, Humans, Female, Breast Neoplasms, Genetic Predisposition to Disease, Black People, Genetic Testing, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Formins, Breast cancer susceptibility, Diverse ancestry, Rare variants, Gene regulation, Genome-wide association study, NBCS Collaborators, CTS Consortium, ABCTB Investigators, Clinical Sciences
Abstract

BackgroundLow-frequency variants play an important role in breast cancer (BC) susceptibility. Gene-based methods can increase power by combining multiple variants in the same gene and help identify target genes.MethodsWe evaluated the potential of gene-based aggregation in the Breast Cancer Association Consortium cohorts including 83,471 cases and 59,199 controls. Low-frequency variants were aggregated for individual genes' coding and regulatory regions. Association results in European ancestry samples were compared to single-marker association results in the same cohort. Gene-based associations were also combined in meta-analysis across individuals with European, Asian, African, and Latin American and Hispanic ancestry.ResultsIn European ancestry samples, 14 genes were significantly associated (q

Published
2023

5. Inflated expectations: Rare-variant association analysis using public controls

Author

Kim, Jung, Karyadi, Danielle M, Hartley, Stephen W, Zhu, Bin, Wang, Mingyi, Wu, Dongjing, Song, Lei, Armstrong, Gregory T, Bhatia, Smita, Robison, Leslie L, Yasui, Yutaka, Carter, Brian, Sampson, Joshua N, Freedman, Neal D, Goldstein, Alisa M, Mirabello, Lisa, Chanock, Stephen J, Morton, Lindsay M, Savage, Sharon A, and Stewart, Douglas R

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Motivation, High-Throughput Nucleotide Sequencing, Polymorphism, Single Nucleotide, Software, General Science & Technology
Abstract

The use of publicly available sequencing datasets as controls (hereafter, "public controls") in studies of rare variant disease associations has great promise but can increase the risk of false-positive discovery. The specific factors that could contribute to inflated distribution of test statistics have not been systematically examined. Here, we leveraged both public controls, gnomAD v2.1 and several datasets sequenced in our laboratory to systematically investigate factors that could contribute to the false-positive discovery, as measured by λΔ95, a measure to quantify the degree of inflation in statistical significance. Analyses of datasets in this investigation found that 1) the significantly inflated distribution of test statistics decreased substantially when the same variant caller and filtering pipelines were employed, 2) differences in library prep kits and sequencers did not affect the false-positive discovery rate and, 3) joint vs. separate variant-calling of cases and controls did not contribute to the inflation of test statistics. Currently available methods do not adequately adjust for the high false-positive discovery. These results, especially if replicated, emphasize the risks of using public controls for rare-variant association tests in which individual-level data and the computational pipeline are not readily accessible, which prevents the use of the same variant-calling and filtering pipelines on both cases and controls. A plausible solution exists with the emergence of cloud-based computing, which can make it possible to bring containerized analytical pipelines to the data (rather than the data to the pipeline) and could avert or minimize these issues. It is suggested that future reports account for this issue and provide this as a limitation in reporting new findings based on studies that cannot practically analyze all data on a single pipeline.

Published
2023

6. Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study

Author

Dixon-Suen, Suzanne C, Lewis, Sarah J, Martin, Richard M, English, Dallas R, Boyle, Terry, Giles, Graham G, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Lush, Michael, Investigators, ABCTB, Ahearn, Thomas U, Ambrosone, Christine B, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Auvinen, Päivi, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Brenner, Hermann, Brüning, Thomas, Buys, Saundra S, Camp, Nicola J, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Cessna, Melissa H, Chang-Claude, Jenny, Chanock, Stephen J, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Goldberg, Mark S, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Häberle, Lothar, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hart, Steven N, Harvie, Michelle, Hillemanns, Peter, Hollestelle, Antoinette, Hooning, Maartje J, Hoppe, Reiner, Hopper, John, Howell, Anthony, Hunter, David J, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Loibl, Sibylle, Lubiński, Jan, Mannermaa, Arto, and Manoochehri, Mehdi

Subjects
Aging, Genetics, Breast Cancer, Clinical Research, Cancer, Prevention, Female, Humans, Breast Neoplasms, Exercise, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Risk Factors, Sedentary Behavior, Breast Cancer Association Consortium, Breast, Physical activity, Sedentary Behaviour, Engineering, Medical and Health Sciences, Education, Sport Sciences
Abstract

ObjectivesPhysical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics.MethodsWe performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity.ResultsGreater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger).ConclusionOur study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.

Published
2022

7. Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.

Author

Byun, Jinyoung, Han, Younghun, Li, Yafang, Xia, Jun, Long, Erping, Choi, Jiyeon, Xiao, Xiangjun, Zhu, Meng, Zhou, Wen, Sun, Ryan, Bossé, Yohan, Song, Zhuoyi, Schwartz, Ann, Lusk, Christine, Rafnar, Thorunn, Stefansson, Kari, Zhang, Tongwu, Zhao, Wei, Pettit, Rowland W, Liu, Yanhong, Li, Xihao, Zhou, Hufeng, Walsh, Kyle M, Gorlov, Ivan, Gorlova, Olga, Zhu, Dakai, Rosenberg, Susan M, Pinney, Susan, Bailey-Wilson, Joan E, Mandal, Diptasri, de Andrade, Mariza, Gaba, Colette, Willey, James C, You, Ming, Anderson, Marshall, Wiencke, John K, Albanes, Demetrius, Lam, Stephan, Tardon, Adonina, Chen, Chu, Goodman, Gary, Bojeson, Stig, Brenner, Hermann, Landi, Maria Teresa, Chanock, Stephen J, Johansson, Mattias, Muley, Thomas, Risch, Angela, Wichmann, H-Erich, Bickeböller, Heike, Christiani, David C, Rennert, Gad, Arnold, Susanne, Field, John K, Shete, Sanjay, Le Marchand, Loic, Melander, Olle, Brunnstrom, Hans, Liu, Geoffrey, Andrew, Angeline S, Kiemeney, Lambertus A, Shen, Hongbing, Zienolddiny, Shanbeh, Grankvist, Kjell, Johansson, Mikael, Caporaso, Neil, Cox, Angela, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B, Aldrich, Melinda C, Patel, Alpa, Lan, Qing, Rothman, Nathaniel, Taylor, Fiona, Kachuri, Linda, Witte, John S, Sakoda, Lori C, Spitz, Margaret, Brennan, Paul, Lin, Xihong, McKay, James, Hung, Rayjean J, and Amos, Christopher I

Subjects
Humans, Lung Neoplasms, Genetic Predisposition to Disease, RNA-Binding Proteins, DNA-Binding Proteins, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Human Genome, Cancer, Genetics, Lung, 2.1 Biological and endogenous factors, Aetiology, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

Published
2022

8. 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

9. 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

10. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author

Ahearn, Thomas U, Zhang, Haoyu, Michailidou, Kyriaki, Milne, Roger L, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Lush, Michael, Wang, Qin, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baten, Adinda, Becher, Heiko, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Collée, J Margriet, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Floris, Giuseppe, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Alnæs, Grethe I Grenaker, Grip, Mervi, Guénel, Pascal, Haiman, Christopher A, Hall, Per, Hamann, Ute, Harkness, Elaine F, Heemskerk-Gerritsen, Bernadette AM, Holleczek, Bernd, Hollestelle, Antoinette, Hooning, Maartje J, Hoover, Robert N, Hopper, John L, Howell, Anthony, Jakimovska, Milena, Jakubowska, Anna, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Kauppila, Saila, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kristensen, Vessela N, Krüger, Ute, Kubelka-Sabit, Katerina, Kurian, Allison W, Kyriacou, Kyriacos, Lambrechts, Diether, Lee, Derrick G, Lindblom, Annika, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, MacInnis, Robert J, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martinez, Maria Elena, and McLean, Catriona

Subjects
Human Genome, Cancer, Genetics, Clinical Research, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Biomarkers, Tumor, Breast Neoplasms, Female, Genome-Wide Association Study, Humans, Receptor, ErbB-2, Receptors, Estrogen, Receptors, Progesterone, Risk, Breast cancer, Etiologic heterogeneity, Genetic predisposition, Common breast cancer susceptibility variants, NBCS Collaborators, ABCTB Investigators, kConFab/AOCS Investigators, Receptor, erbB-2, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundGenome-wide association studies (GWAS) have identified multiple common breast cancer susceptibility variants. Many of these variants have differential associations by estrogen receptor (ER) status, but how these variants relate with other tumor features and intrinsic molecular subtypes is unclear.MethodsAmong 106,571 invasive breast cancer cases and 95,762 controls of European ancestry with data on 173 breast cancer variants identified in previous GWAS, we used novel two-stage polytomous logistic regression models to evaluate variants in relation to multiple tumor features (ER, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and grade) adjusting for each other, and to intrinsic-like subtypes.ResultsEighty-five of 173 variants were associated with at least one tumor feature (false discovery rate

Published
2022

11. 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

12. Association of germline genetic variants with breast cancer-specific survival in patient subgroups defined by clinic-pathological variables related to tumor biology and type of systemic treatment

Author

Morra, Anna, Escala-Garcia, Maria, Beesley, Jonathan, Keeman, Renske, Canisius, Sander, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Augustinsson, Annelie, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Brüning, Thomas, Buys, Saundra S, Caan, Bette, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Cheng, Ting-Yuan David, Clarke, Christine L, Colonna, Sarah V, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Dörk, Thilo, Dossus, Laure, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fritschi, Lin, Gago-Dominguez, Manuela, García-Sáenz, José A, Giles, Graham G, Grip, Mervi, Guénel, Pascal, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hart, Steven N, Hartikainen, Jaana M, Hartmann, Arndt, He, Wei, Hooning, Maartje J, Hoppe, Reiner, Hopper, John L, Howell, Anthony, Hunter, David J, Jager, Agnes, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey Y, Kaaks, Rudolf, Keupers, Machteld, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Linet, Martha, Luben, Robert N, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martens, John WM, Martinez, Maria Elena, Mavroudis, Dimitrios, Michailidou, Kyriaki, Milne, Roger L, Mulligan, Anna Marie, Muranen, Taru A, Nevanlinna, Heli, Newman, William G, and Nielsen, Sune F

Subjects
Clinical Research, Cancer, Breast Cancer, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, Female, Genome-Wide Association Study, Germ-Line Mutation, Humans, Polymorphism, Single Nucleotide, Prognosis, Survival Analysis, Common germline genetic variants, Breast cancer-specific survival, Patient subgroups, Tumor biology, Systemic treatment, NBCS Collaborators, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundGiven the high heterogeneity among breast tumors, associations between common germline genetic variants and survival that may exist within specific subgroups could go undetected in an unstratified set of breast cancer patients.MethodsWe performed genome-wide association analyses within 15 subgroups of breast cancer patients based on prognostic factors, including hormone receptors, tumor grade, age, and type of systemic treatment. Analyses were based on 91,686 female patients of European ancestry from the Breast Cancer Association Consortium, including 7531 breast cancer-specific deaths over a median follow-up of 8.1 years. Cox regression was used to assess associations of common germline variants with 15-year and 5-year breast cancer-specific survival. We assessed the probability of these associations being true positives via the Bayesian false discovery probability (BFDP

Published
2021

13. Mendelian randomisation study of smoking exposure in relation to breast cancer risk

Author

Park, Hanla A, Neumeyer, Sonja, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baten, Adinda, Beane Freeman, Laura E, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bogdanova, Natalia V, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brucker, Sara Y, Burwinkel, Barbara, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, dos-Santos-Silva, Isabel, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fritschi, Lin, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Glendon, Gord, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Grip, Mervi, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Han, Sileny, Harkness, Elaine F, Hart, Steven N, He, Wei, Heemskerk-Gerritsen, Bernadette AM, Hopper, John L, Hunter, David J, Jager, Agnes, Jakubowska, Anna, John, Esther M, Jung, Audrey, Kaaks, Rudolf, Kapoor, Pooja Middha, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Koppert, Linetta B, Koutros, Stella, Kristensen, Vessela N, Kurian, Allison W, Lacey, James, Lambrechts, Diether, Le Marchand, Loic, Lo, Wing-Yee, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martinez, Maria Elena, Mavroudis, Dimitrios, Meindl, Alfons, Menon, Usha, Milne, Roger L, Muranen, Taru A, and Nevanlinna, Heli

Subjects
Genetics, Cancer, Substance Misuse, Clinical Research, Human Genome, Prevention, Drug Abuse (NIDA only), Breast Cancer, Tobacco, Tobacco Smoke and Health, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Breast Neoplasms, Case-Control Studies, Cigarette Smoking, Female, Genetic Pleiotropy, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotyping Techniques, Humans, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, NBCS Collaborators, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundDespite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk.MethodsWe applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy.ResultsGenetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect.ConclusionOur MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Published
2021

14. Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis.

Author

Escala-Garcia, Maria, Canisius, Sander, Keeman, Renske, Beesley, Jonathan, Anton-Culver, Hoda, Arndt, Volker, Augustinsson, Annelie, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Couch, Fergus J, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Dörk, Thilo, Dunning, Alison M, Easton, Douglas F, Ekici, Arif B, Eliassen, A Heather, Fasching, Peter A, Flyger, Henrik, Gago-Dominguez, Manuela, García-Closas, Montserrat, García-Sáenz, José A, Geisler, Jürgen, Giles, Graham G, Grip, Mervi, Gündert, Melanie, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hartikainen, Jaana M, Heemskerk-Gerritsen, Bernadette AM, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Hunter, David J, Jacot, William, Jakubowska, Anna, John, Esther M, Jung, Audrey Y, Kaaks, Rudolf, Khusnutdinova, Elza, Koppert, Linetta B, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Lindblom, Annika, Luben, Robert N, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Mavroudis, Dimitrios, Muranen, Taru A, Nevanlinna, Heli, Olshan, Andrew F, Olsson, Håkan, Park-Simon, Tjoung-Won, Patel, Alpa V, Peterlongo, Paolo, Pharoah, Paul DP, Punie, Kevin, Radice, Paolo, Rennert, Gad, Rennert, Hedy S, Romero, Atocha, Roylance, Rebecca, Rüdiger, Thomas, Ruebner, Matthias, Saloustros, Emmanouil, Sawyer, Elinor J, Schmutzler, Rita K, Schoemaker, Minouk J, Scott, Christopher, Southey, Melissa C, Surowy, Harald, Swerdlow, Anthony J, Tamimi, Rulla M, Teras, Lauren R, Thomas, Emilie, Tomlinson, Ian, Troester, Melissa A, Vachon, Celine M, Wang, Qin, Winqvist, Robert, and Wolk, Alicja

Subjects
kConFab/AOCS Investigators, Cancer, Genetics, Breast Cancer, Prevention, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies
Abstract

Breast cancer metastasis accounts for most of the deaths from breast cancer. Identification of germline variants associated with survival in aggressive types of breast cancer may inform understanding of breast cancer progression and assist treatment. In this analysis, we studied the associations between germline variants and breast cancer survival for patients with distant metastases at primary breast cancer diagnosis. We used data from the Breast Cancer Association Consortium (BCAC) including 1062 women of European ancestry with metastatic breast cancer, 606 of whom died of breast cancer. We identified two germline variants on chromosome 1, rs138569520 and rs146023652, significantly associated with breast cancer-specific survival (P = 3.19 × 10-8 and 4.42 × 10-8). In silico analysis suggested a potential regulatory effect of the variants on the nearby target genes SDE2 and H3F3A. However, the variants showed no evidence of association in a smaller replication dataset. The validation dataset was obtained from the SNPs to Risk of Metastasis (StoRM) study and included 293 patients with metastatic primary breast cancer at diagnosis. Ultimately, larger replication studies are needed to confirm the identified associations.

Published
2021

15. Genetic insights into biological mechanisms governing human ovarian ageing

Author

Ruth, Katherine S, Day, Felix R, Hussain, Jazib, Martínez-Marchal, Ana, Aiken, Catherine E, Azad, Ajuna, Thompson, Deborah J, Knoblochova, Lucie, Abe, Hironori, Tarry-Adkins, Jane L, Gonzalez, Javier Martin, Fontanillas, Pierre, Claringbould, Annique, Bakker, Olivier B, Sulem, Patrick, Walters, Robin G, Terao, Chikashi, Turon, Sandra, Horikoshi, Momoko, Lin, Kuang, Onland-Moret, N Charlotte, Sankar, Aditya, Hertz, Emil Peter Thrane, Timshel, Pascal N, Shukla, Vallari, Borup, Rehannah, Olsen, Kristina W, Aguilera, Paula, Ferrer-Roda, Mònica, Huang, Yan, Stankovic, Stasa, Timmers, Paul RHJ, Ahearn, Thomas U, Alizadeh, Behrooz Z, Naderi, Elnaz, Andrulis, Irene L, Arnold, Alice M, Aronson, Kristan J, Augustinsson, Annelie, Bandinelli, Stefania, Barbieri, Caterina M, Beaumont, Robin N, Becher, Heiko, Beckmann, Matthias W, Benonisdottir, Stefania, Bergmann, Sven, Bochud, Murielle, Boerwinkle, Eric, Bojesen, Stig E, Bolla, Manjeet K, Boomsma, Dorret I, Bowker, Nicholas, Brody, Jennifer A, Broer, Linda, Buring, Julie E, Campbell, Archie, Campbell, Harry, Castelao, Jose E, Catamo, Eulalia, Chanock, Stephen J, Chenevix-Trench, Georgia, Ciullo, Marina, Corre, Tanguy, Couch, Fergus J, Cox, Angela, Crisponi, Laura, Cross, Simon S, Cucca, Francesco, Czene, Kamila, Smith, George Davey, de Geus, Eco JCN, de Mutsert, Renée, De Vivo, Immaculata, Demerath, Ellen W, Dennis, Joe, Dunning, Alison M, Dwek, Miriam, Eriksson, Mikael, Esko, Tõnu, Fasching, Peter A, Faul, Jessica D, Ferrucci, Luigi, Franceschini, Nora, Frayling, Timothy M, Gago-Dominguez, Manuela, Mezzavilla, Massimo, García-Closas, Montserrat, Gieger, Christian, Giles, Graham G, Grallert, Harald, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hayward, Caroline, He, Chunyan, He, Wei, and Heiss, Gerardo

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Estrogen, Prevention, Women's Health, Contraception/Reproduction, Aging, Infertility, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Good Health and Well Being, Adult, Alleles, Animals, Bone and Bones, Checkpoint Kinase 1, Checkpoint Kinase 2, Diabetes Mellitus, Type 2, Diet, Europe, Asia, Eastern, Female, Fertility, Fragile X Mental Retardation Protein, Genetic Predisposition to Disease, Genome-Wide Association Study, Healthy Aging, Humans, Longevity, Menopause, Menopause, Premature, Mice, Mice, Inbred C57BL, Middle Aged, Ovary, Primary Ovarian Insufficiency, Uterus, Biobank-based Integrative Omics Study (BIOS) Consortium, eQTLGen Consortium, Biobank Japan Project, China Kadoorie Biobank Collaborative Group, kConFab Investigators, LifeLines Cohort Study, InterAct consortium, 23andMe Research Team, General Science & Technology
Abstract

Reproductive longevity is essential for fertility and influences healthy ageing in women1,2, but insights into its underlying biological mechanisms and treatments to preserve it are limited. Here we identify 290 genetic determinants of ovarian ageing, assessed using normal variation in age at natural menopause (ANM) in about 200,000 women of European ancestry. These common alleles were associated with clinical extremes of ANM; women in the top 1% of genetic susceptibility have an equivalent risk of premature ovarian insufficiency to those carrying monogenic FMR1 premutations3. The identified loci implicate a broad range of DNA damage response (DDR) processes and include loss-of-function variants in key DDR-associated genes. Integration with experimental models demonstrates that these DDR processes act across the life-course to shape the ovarian reserve and its rate of depletion. Furthermore, we demonstrate that experimental manipulation of DDR pathways highlighted by human genetics increases fertility and extends reproductive life in mice. Causal inference analyses using the identified genetic variants indicate that extending reproductive life in women improves bone health and reduces risk of type 2 diabetes, but increases the risk of hormone-sensitive cancers. These findings provide insight into the mechanisms that govern ovarian ageing, when they act, and how they might be targeted by therapeutic approaches to extend fertility and prevent disease.

Published
2021

16. Functional annotation of the 2q35 breast cancer risk locus implicates a structural variant in influencing activity of a long-range enhancer element

Author

Baxter, Joseph S, Johnson, Nichola, Tomczyk, Katarzyna, Gillespie, Andrea, Maguire, Sarah, Brough, Rachel, Fachal, Laura, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bogdanova, Natalia V, Bojesen, Stig E, Brenner, Hermann, Brucker, Sara Y, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chan, Tsun L, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Choi, Ji-Yeob, Clarke, Christine L, Collaborators, NBCS, Colonna, Sarah, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dossus, Laure, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Engel, Christoph, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Gago-Dominguez, Manuela, Gao, Chi, García-Closas, Montserrat, García-Sáenz, José A, Ghoussaini, Maya, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Guénel, Pascal, Gündert, Melanie, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Hall, Per, Hamann, Ute, Hartman, Mikael, Hatse, Sigrid, Hauke, Jan, Hollestelle, Antoinette, Hoppe, Reiner, Hopper, John L, Hou, Ming-Feng, Investigators, kConFab, Investigators, ABCTB, Ito, Hidemi, Iwasaki, Motoki, Jager, Agnes, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Joseph, Vijai, Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Keeman, Renske, Khusnutdinova, Elza, Kim, Sung-Won, Kosma, Veli-Matti, Kraft, Peter, Kristensen, Vessela N, Kubelka-Sabit, Katerina, Kurian, Allison W, Kwong, Ava, and Lacey, James V

Subjects
Human Genome, Genetics, Cancer, Estrogen, Prevention, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, CRISPR-Cas Systems, Cell Line, Chromosome Mapping, Chromosomes, Human, Pair 2, Female, Genetic Association Studies, Genetic Variation, Humans, Insulin-Like Growth Factor Binding Protein 5, Molecular Sequence Annotation, Promoter Regions, Genetic, Risk Factors, Sequence Deletion, NBCS Collaborators, kConFab Investigators, ABCTB Investigators, breast cancer risk, functional annotation, risk locus, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

A combination of genetic and functional approaches has identified three independent breast cancer risk loci at 2q35. A recent fine-scale mapping analysis to refine these associations resulted in 1 (signal 1), 5 (signal 2), and 42 (signal 3) credible causal variants at these loci. We used publicly available in silico DNase I and ChIP-seq data with in vitro reporter gene and CRISPR assays to annotate signals 2 and 3. We identified putative regulatory elements that enhanced cell-type-specific transcription from the IGFBP5 promoter at both signals (30- to 40-fold increased expression by the putative regulatory element at signal 2, 2- to 3-fold by the putative regulatory element at signal 3). We further identified one of the five credible causal variants at signal 2, a 1.4 kb deletion (esv3594306), as the likely causal variant; the deletion allele of this variant was associated with an average additional increase in IGFBP5 expression of 1.3-fold (MCF-7) and 2.2-fold (T-47D). We propose a model in which the deletion allele of esv3594306 juxtaposes two transcription factor binding regions (annotated by estrogen receptor alpha ChIP-seq peaks) to generate a single extended regulatory element. This regulatory element increases cell-type-specific expression of the tumor suppressor gene IGFBP5 and, thereby, reduces risk of estrogen receptor-positive breast cancer (odds ratio = 0.77, 95% CI 0.74-0.81, p = 3.1 × 10-31).

Published
2021

17. 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

18. Discovery and fine-mapping of height loci via high-density imputation of GWASs in individuals of African ancestry

Author

Graff, Mariaelisa, Justice, Anne E, Young, Kristin L, Marouli, Eirini, Zhang, Xinruo, Fine, Rebecca S, Lim, Elise, Buchanan, Victoria, Rand, Kristin, Feitosa, Mary F, Wojczynski, Mary K, Yanek, Lisa R, Shao, Yaming, Rohde, Rebecca, Adeyemo, Adebowale A, Aldrich, Melinda C, Allison, Matthew A, Ambrosone, Christine B, Ambs, Stefan, Amos, Christopher, Arnett, Donna K, Atwood, Larry, Bandera, Elisa V, Bartz, Traci, Becker, Diane M, Berndt, Sonja I, Bernstein, Leslie, Bielak, Lawrence F, Blot, William J, Bottinger, Erwin P, Bowden, Donald W, Bradfield, Jonathan P, Brody, Jennifer A, Broeckel, Ulrich, Burke, Gregory, Cade, Brian E, Cai, Qiuyin, Caporaso, Neil, Carlson, Chris, Carpten, John, Casey, Graham, Chanock, Stephen J, Chen, Guanjie, Chen, Minhui, Chen, Yii-Der I, Chen, Wei-Min, Chesi, Alessandra, Chiang, Charleston WK, Chu, Lisa, Coetzee, Gerry A, Conti, David V, Cooper, Richard S, Cushman, Mary, Demerath, Ellen, Deming, Sandra L, Dimitrov, Latchezar, Ding, Jingzhong, Diver, W Ryan, Duan, Qing, Evans, Michele K, Falusi, Adeyinka G, Faul, Jessica D, Fornage, Myriam, Fox, Caroline, Freedman, Barry I, Garcia, Melissa, Gillanders, Elizabeth M, Goodman, Phyllis, Gottesman, Omri, Grant, Struan FA, Guo, Xiuqing, Hakonarson, Hakon, Haritunians, Talin, Harris, Tamara B, Harris, Curtis C, Henderson, Brian E, Hennis, Anselm, Hernandez, Dena G, Hirschhorn, Joel N, McNeill, Lorna Haughton, Howard, Timothy D, Howard, Barbara, Hsing, Ann W, Hsu, Yu-Han H, Hu, Jennifer J, Huff, Chad D, Huo, Dezheng, Ingles, Sue A, Irvin, Marguerite R, John, Esther M, Johnson, Karen C, Jordan, Joanne M, Kabagambe, Edmond K, Kang, Sun J, Kardia, Sharon L, Keating, Brendan J, Kittles, Rick A, Klein, Eric A, Kolb, Suzanne, and Kolonel, Laurence N

Subjects
Human Genome, Genetics, Africa, Black or African American, Black People, Body Height, Europe, Female, Genome-Wide Association Study, Humans, Male, Polymorphism, Single Nucleotide, African ancestry, fine-mapping, genome-wide, height, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

Published
2021

19. A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Author

Coignard, Juliette, Lush, Michael, Beesley, Jonathan, O'Mara, Tracy A, Dennis, Joe, Tyrer, Jonathan P, Barnes, Daniel R, McGuffog, Lesley, Leslie, Goska, Bolla, Manjeet K, Adank, Muriel A, Agata, Simona, Ahearn, Thomas, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Arnold, Norbert, Aronson, Kristan J, Arun, Banu K, Augustinsson, Annelie, Azzollini, Jacopo, Barrowdale, Daniel, Baynes, Caroline, Becher, Heiko, Bermisheva, Marina, Bernstein, Leslie, Białkowska, Katarzyna, Blomqvist, Carl, Bojesen, Stig E, Bonanni, Bernardo, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Buys, Saundra S, Caldés, Trinidad, Caligo, Maria A, Campa, Daniele, Carter, Brian D, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, GEMO Study Collaborators, EMBRACE Collaborators, Collée, J Margriet, Conroy, Don M, Czene, Kamila, Daly, Mary B, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Domchek, Susan M, Dörk, Thilo, Dos-Santos-Silva, Isabel, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Eliassen, A Heather, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Fostira, Florentia, Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gago-Dominguez, Manuela, Gapstur, Susan M, Garber, Judy, Garcia-Barberan, Vanesa, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Gayther, Simon A, Gehrig, Andrea, Georgoulias, Vassilios, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A, Hart, Steven N, He, Wei, Hogervorst, Frans BL, Hollestelle, Antoinette, and Hopper, John L

Subjects
GEMO Study Collaborators, EMBRACE Collaborators, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, BRCA1 Protein, BRCA2 Protein, Risk Factors, Genotype, Linkage Disequilibrium, Mutation, Polymorphism, Single Nucleotide, Alleles, Quantitative Trait Loci, Adult, Middle Aged, Female, Genome-Wide Association Study, Breast Cancer, Prevention, Cancer, Genetic Testing, Human Genome, Genetics, 2.1 Biological and endogenous factors
Abstract

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P

Published
2021

20. CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers

Author

Johnson, Nichola, Maguire, Sarah, Morra, Anna, Kapoor, Pooja Middha, Tomczyk, Katarzyna, Jones, Michael E, Schoemaker, Minouk J, Gilham, Clare, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baynes, Caroline, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dörk, Thilo, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Floris, Giuseppe, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Closas, Montserrat, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A, Hart, Steven N, Hooning, Maartje J, Hopper, John L, Howell, Anthony, Hunter, David J, Jager, Agnes, Jakubowska, Anna, John, Esther M, Kaaks, Rudolf, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Kosma, Veli-Matti, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Linet, Martha, Lubiński, Jan, Mannermaa, Arto, Manoukian, Siranoush, Margolin, Sara, Martens, John WM, Mavroudis, Dimitrios, Mayes, Rebecca, Meindl, Alfons, Milne, Roger L, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Obi, Nadia, Olshan, Andrew F, and Olson, Janet E

Subjects
Estrogen, Human Genome, Clinical Research, Cancer, Aging, Breast Cancer, Genetics, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Cytochrome P-450 CYP3A, Estrone, Female, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Pregnanediol, Premenopause, Progesterone, Receptors, Estrogen, Receptors, Progesterone, NBCS Collaborators, AOCS Group, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundEpidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk.MethodsWe carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry.ResultsFor pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8).ConclusionsThe CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Published
2021

21. Breast Cancer Risk Genes — Association Analysis in More than 113,000 Women

Author

Dorling, Leila, Carvalho, Sara, Allen, Jamie, González-Neira, Anna, Luccarini, Craig, Wahlström, Cecilia, Pooley, Karen A, Parsons, Michael T, Fortuno, Cristina, Wang, Qin, Bolla, Manjeet K, Dennis, Joe, Keeman, Renske, Alonso, M Rosario, Álvarez, Nuria, Herraez, Belen, Fernandez, Victoria, Núñez-Torres, Rocio, Osorio, Ana, Valcich, Jeanette, Li, Minerva, Törngren, Therese, Harrington, Patricia A, Baynes, Caroline, Conroy, Don M, Decker, Brennan, Fachal, Laura, Mavaddat, Nasim, Ahearn, Thomas, Aittomäki, Kristiina, Antonenkova, Natalia N, Arnold, Norbert, Arveux, Patrick, Ausems, Margreet GEM, Auvinen, Päivi, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Bermisheva, Marina, Białkowska, Katarzyna, Blomqvist, Carl, Bogdanova, Natalia V, Bogdanova-Markov, Nadja, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Bremer, Michael, Briceno, Ignacio, Brüning, Thomas, Burwinkel, Barbara, Cameron, David A, Camp, Nicola J, Campbell, Archie, Carracedo, Angel, Castelao, Jose E, Cessna, Melissa H, Chanock, Stephen J, Christiansen, Hans, Collée, J Margriet, Cordina-Duverger, Emilie, Cornelissen, Sten, Czene, Kamila, Dörk, Thilo, Ekici, Arif B, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Försti, Asta, Gabrielson, Marike, Gago-Dominguez, Manuela, Georgoulias, Vassilios, Gil, Fabian, Giles, Graham G, Glendon, Gord, Garcia, Encarna B Gómez, Alnæs, Grethe I Grenaker, Guénel, Pascal, Hadjisavvas, Andreas, Haeberle, Lothar, Hahnen, Eric, Hall, Per, Hamann, Ute, Harkness, Elaine F, Hartikainen, Jaana M, Hartman, Mikael, He, Wei, Heemskerk-Gerritsen, Bernadette AM, Hillemanns, Peter, Hogervorst, Frans BL, Hollestelle, Antoinette, Ho, Weang Kee, Hooning, Maartje J, Howell, Anthony, Humphreys, Keith, Idris, Faiza, Jakubowska, Anna, and Jung, Audrey

Subjects
Breast Cancer, Cancer, Genetics, Aetiology, 2.1 Biological and endogenous factors, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genetic Variation, Humans, Logistic Models, Middle Aged, Mutation, Missense, Odds Ratio, Risk, Sequence Analysis, DNA, Young Adult, Breast Cancer Association Consortium, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundGenetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.MethodsWe used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.ResultsProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.ConclusionsThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Published
2021

22. Cross-Cancer Genome-Wide Association Study of Endometrial Cancer and Epithelial Ovarian Cancer Identifies Genetic Risk Regions Associated with Risk of Both Cancers

Author

Glubb, Dylan M, Thompson, Deborah J, Aben, Katja KH, Alsulimani, Ahmad, Amant, Frederic, Annibali, Daniela, Attia, John, Barricarte, Aurelio, Beckmann, Matthias W, Berchuck, Andrew, Bermisheva, Marina, Bernardini, Marcus Q, Bischof, Katharina, Bjorge, Line, Bodelon, Clara, Brand, Alison H, Brenton, James D, Brinton, Louise A, Bruinsma, Fiona, Buchanan, Daniel D, Burghaus, Stefanie, Butzow, Ralf, Cai, Hui, Carney, Michael E, Chanock, Stephen J, Chen, Chu, Chen, Xiao Qing, Chen, Zhihua, Cook, Linda S, Cunningham, Julie M, De Vivo, Immaculata, deFazio, Anna, Doherty, Jennifer A, Dörk, Thilo, du Bois, Andreas, Dunning, Alison M, Dürst, Matthias, Edwards, Todd, Edwards, Robert P, Ekici, Arif B, Ewing, Ailith, Fasching, Peter A, Ferguson, Sarah, Flanagan, James M, Fostira, Florentia, Fountzilas, George, Friedenreich, Christine M, Gao, Bo, Gaudet, Mia M, Gawełko, Jan, Gentry-Maharaj, Aleksandra, Giles, Graham G, Glasspool, Rosalind, Goodman, Marc T, Gronwald, Jacek, Harris, Holly R, Harter, Philipp, Hein, Alexander, Heitz, Florian, Hildebrandt, Michelle AT, Hillemanns, Peter, Høgdall, Estrid, Høgdall, Claus K, Holliday, Elizabeth G, Huntsman, David G, Huzarski, Tomasz, Jakubowska, Anna, Jensen, Allan, Jones, Michael E, Karlan, Beth Y, Karnezis, Anthony, Kelley, Joseph L, Khusnutdinova, Elza, Killeen, Jeffrey L, Kjaer, Susanne K, Klapdor, Rüdiger, Köbel, Martin, Konopka, Bozena, Konstantopoulou, Irene, Kopperud, Reidun K, Koti, Madhuri, Kraft, Peter, Kupryjanczyk, Jolanta, Lambrechts, Diether, Larson, Melissa C, Le Marchand, Loic, Lele, Shashikant, Lester, Jenny, Li, Andrew J, Liang, Dong, Liebrich, Clemens, Lipworth, Loren, Lissowska, Jolanta, Lu, Lingeng, Lu, Karen H, Macciotta, Alessandra, Mattiello, Amalia, May, Taymaa, McAlpine, Jessica N, and McGuire, Valerie

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Human Genome, Uterine Cancer, Genetics, Biotechnology, Ovarian Cancer, Prevention, Cancer, Rare Diseases, 2.1 Biological and endogenous factors, Aetiology, Carcinoma, Ovarian Epithelial, Endometrial Neoplasms, Female, Genome-Wide Association Study, Humans, Ovarian Neoplasms, Quantitative Trait Loci, Risk Factors, OPAL Study Group, AOCS Group, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundAccumulating evidence suggests a relationship between endometrial cancer and ovarian cancer. Independent genome-wide association studies (GWAS) for endometrial cancer and ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. We aimed to identify joint endometrial and ovarian cancer risk loci by performing a meta-analysis of GWAS summary statistics from these two cancers.MethodsUsing LDScore regression, we explored the genetic correlation between endometrial cancer and ovarian cancer. To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e., inverse-variance meta-analysis, colocalization, and M-values) and performed analyses stratified by subtype. Candidate target genes were then prioritized using functional genomic data.ResultsGenetic correlation analysis revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10-5). We found seven loci associated with risk for both cancers (P Bonferroni < 2.4 × 10-9). In addition, four novel subgenome-wide regions at 7p22.2, 7q22.1, 9p12, and 11q13.3 were identified (P < 5 × 10-7). Promoter-associated HiChIP chromatin loops from immortalized endometrium and ovarian cell lines and expression quantitative trait loci data highlighted candidate target genes for further investigation.ConclusionsUsing cross-cancer GWAS meta-analysis, we have identified several joint endometrial and ovarian cancer risk loci and candidate target genes for future functional analysis.ImpactOur research highlights the shared genetic relationship between endometrial cancer and ovarian cancer. Further studies in larger sample sets are required to confirm our findings.

Published
2021

23. Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women

Author

Adedokun, Babatunde, Du, Zhaohui, Gao, Guimin, Ahearn, Thomas U, Lunetta, Kathryn L, Zirpoli, Gary, Figueroa, Jonine, John, Esther M, Bernstein, Leslie, Zheng, Wei, Hu, Jennifer J, Ziegler, Regina G, Nyante, Sarah, Bandera, Elisa V, Ingles, Sue A, Press, Michael F, Deming-Halverson, Sandra L, Rodriguez-Gil, Jorge L, Yao, Song, Ogundiran, Temidayo O, Ojengbede, Oladosu, Blot, William, Troester, Melissa A, Nathanson, Katherine L, Hennis, Anselm, Nemesure, Barbara, Ambs, Stefan, Fiorica, Peter N, Sucheston-Campbell, Lara E, Bensen, Jeannette T, Kushi, Lawrence H, Torres-Mejia, Gabriela, Hu, Donglei, Fejerman, Laura, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Easton, Douglas F, Michailidou, Kyriaki, Pharoah, Paul DP, Wang, Qin, Sandler, Dale P, Taylor, Jack A, O’Brien, Katie M, Kitahara, Cari M, Falusi, Adeyinka G, Babalola, Chinedum, Yarney, Joel, Awuah, Baffour, Addai-Wiafe, Beatrice, Chanock, Stephen J, Olshan, Andrew F, Ambrosone, Christine B, Conti, David V, Ziv, Elad, Olopade, Olufunmilayo I, Garcia-Closas, Montserrat, Palmer, Julie R, Haiman, Christopher A, and Huo, Dezheng

Subjects
Genetics, Breast Cancer, Human Genome, Cancer, Prevention, Aging, 2.1 Biological and endogenous factors, Aetiology, Black People, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Introns, Polymorphism, Single Nucleotide, Quantitative Trait Loci, White People, GBHS Study Team
Abstract

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P

Published
2021

24. Pathway Analysis of Renal Cell Carcinoma Genome-Wide Association Studies Identifies Novel Associations

Author

Purdue, Mark P, Song, Lei, Scélo, Ghislaine, Houlston, Richard S, Wu, Xifeng, Sakoda, Lori C, Thai, Khanh, Graff, Rebecca E, Rothman, Nathaniel, Brennan, Paul, Chanock, Stephen J, and Yu, Kai

Subjects
Epidemiology, Health Sciences, Human Genome, Genetics, Rare Diseases, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Carcinoma, Renal Cell, Genome-Wide Association Study, Humans, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundMuch of the heritable risk of renal cell carcinoma (RCC) associated with common genetic variation is unexplained. New analytic approaches have been developed to increase the discovery of risk variants in genome-wide association studies (GWAS), including multi-locus testing through pathway analysis.MethodsWe conducted a pathway analysis using GWAS summary data from six previous scans (10,784 cases and 20,406 controls) and evaluated 3,678 pathways and gene sets drawn from the Molecular Signatures Database. To replicate findings, we analyzed GWAS summary data from the UK Biobank (903 cases and 451,361 controls) and the Genetic Epidemiology Research on Adult Health and Aging cohort (317 cases and 50,511 controls).ResultsWe identified 14 pathways/gene sets associated with RCC in both the discovery (P < 1.36 × 10-5, the Bonferroni correction threshold) and replication (P < 0.05) sets, 10 of which include components of the PI3K/AKT pathway. In tests across 2,035 genes in these pathways, associations (Bonferroni corrected P < 2.46 × 10-5 in discovery and replication sets combined) were observed for CASP9, TIPIN, and CDKN2C. The strongest SNP signal was for rs12124078 (P Discovery = 2.6 × 10-5; P Replication = 1.5 × 10-4; P Combined = 6.9 × 10-8), a CASP9 expression quantitative trait locus.ConclusionsOur pathway analysis implicates genetic variation within the PI3K/AKT pathway as a source of RCC heritability and identifies several promising novel susceptibility genes, including CASP9, which warrant further investigation.ImpactOur findings illustrate the value of pathway analysis as a complementary approach to analyzing GWAS data.

Published
2020

25. Transcriptome‐wide association study of breast cancer risk by estrogen‐receptor status

Author

Feng, Helian, Gusev, Alexander, Pasaniuc, Bogdan, Wu, Lang, Long, Jirong, Abu‐full, Zomoroda, Aittomäki, Kristiina, Andrulis, Irene L, Anton‐Culver, Hoda, Antoniou, Antonis C, Arason, Adalgeir, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Asseryanis, Ella, Auer, Paul L, Azzollini, Jacopo, Balmaña, Judith, Barkardottir, Rosa B, Barnes, Daniel R, Barrowdale, Daniel, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Białkowska, Katarzyna, Blanco, Ana, Blomqvist, Carl, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Bonanni, Bernardo, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Broeks, Annegien, Brüning, Thomas, Burwinkel, Barbara, Cai, Qiuyin, Caldés, Trinidad, Caligo, Maria A, Campbell, Ian, Canisius, Sander, Campa, Daniele, Carter, Brian D, Carter, Jonathan, Castelao, Jose E, Chang‐Claude, Jenny, Chanock, Stephen J, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, Collaborators, GEMO Study, Collaborators, EMBRACE, Collaborators, GC‐HBOC study, Couch, Fergus J, Cox, Angela, Cross, Simon S, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, de la Hoya, Miguel, De Leeneer, Kim, Dennis, Joe, Devilee, Peter, Diez, Orland, Domchek, Susan M, Dörk, Thilo, dos‐Santos‐Silva, Isabel, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Ejlertsen, Bent, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Fostira, Florentia, Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gabrielson, Marike, Ganz, Patricia A, Gapstur, Susan M, Garber, Judy, García‐Closas, Montserrat, García‐Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González‐Neira, Anna, and Greene, Mark H

Subjects
Biological Sciences, Health Sciences, Genetics, Cancer, Biotechnology, Prevention, Clinical Research, Human Genome, Estrogen, Breast Cancer, Aetiology, 2.1 Biological and endogenous factors, Breast Neoplasms, Estrogens, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genomics, Humans, Receptors, Estrogen, Risk Assessment, Transcriptome, Vesicular Transport Proteins, breast cancer subtype, causal gene, GWAS, TWAS, GEMO Study Collaborators, EMBRACE Collaborators, GC-HBOC study Collaborators, ABCTB Investigators, HEBON Investigators, BCFR Investigators, OCGN Investigators, Public Health and Health Services, Epidemiology
Abstract

Previous transcriptome-wide association studies (TWAS) have identified breast cancer risk genes by integrating data from expression quantitative loci and genome-wide association studies (GWAS), but analyses of breast cancer subtype-specific associations have been limited. In this study, we conducted a TWAS using gene expression data from GTEx and summary statistics from the hitherto largest GWAS meta-analysis conducted for breast cancer overall, and by estrogen receptor subtypes (ER+ and ER-). We further compared associations with ER+ and ER- subtypes, using a case-only TWAS approach. We also conducted multigene conditional analyses in regions with multiple TWAS associations. Two genes, STXBP4 and HIST2H2BA, were specifically associated with ER+ but not with ER- breast cancer. We further identified 30 TWAS-significant genes associated with overall breast cancer risk, including four that were not identified in previous studies. Conditional analyses identified single independent breast-cancer gene in three of six regions harboring multiple TWAS-significant genes. Our study provides new information on breast cancer genetics and biology, particularly about genomic differences between ER+ and ER- breast cancer.

Published
2020

26. Genome-wide association study identifies 32 novel breast cancer susceptibility loci from overall and subtype-specific analyses.

Author

Zhang, Haoyu, Ahearn, Thomas U, Lecarpentier, Julie, Barnes, Daniel, Beesley, Jonathan, Qi, Guanghao, Jiang, Xia, O'Mara, Tracy A, Zhao, Ni, Bolla, Manjeet K, Dunning, Alison M, Dennis, Joe, Wang, Qin, Ful, Zumuruda Abu, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Auer, Paul L, Azzollini, Jacopo, Barrowdale, Daniel, Becher, Heiko, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bialkowska, Katarzyna, Blanco, Ana, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Bondavalli, Davide, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Broeks, Annegien, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Byers, Helen, Caldés, Trinidad, Caligo, Maria A, Calvello, Mariarosaria, Campa, Daniele, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Christiaens, Melissa, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, Cornelissen, Sten, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Diez, Orland, Domchek, Susan M, Dörk, Thilo, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Foretova, Lenka, Fostira, Florentia, Friedman, Eitan, Frost, Debra, Gago-Dominguez, Manuela, Gapstur, Susan M, Garber, Judy, García-Sáenz, José A, Gaudet, Mia M, Gayther, Simon A, Giles, Graham G, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Gronwald, Jacek, Guénel, Pascal, Häberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Hake, Christopher R, Hall, Per, Hamann, Ute, Harkness, Elaine F, Heemskerk-Gerritsen, Bernadette AM, and Hillemanns, Peter

Subjects
kConFab Investigators, ABCTB Investigators, EMBRACE Study, GEMO Study Collaborators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, BRCA1 Protein, Case-Control Studies, Linkage Disequilibrium, Mutation, Female, Genome-Wide Association Study, Triple Negative Breast Neoplasms, Human Genome, Cancer, Prevention, Genetics, Breast Cancer, 2.1 Biological and endogenous factors, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

Breast cancer susceptibility variants frequently show heterogeneity in associations by tumor subtype1-3. To identify novel loci, we performed a genome-wide association study including 133,384 breast cancer cases and 113,789 controls, plus 18,908 BRCA1 mutation carriers (9,414 with breast cancer) of European ancestry, using both standard and novel methodologies that account for underlying tumor heterogeneity by estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2 status and tumor grade. We identified 32 novel susceptibility loci (P

Published
2020

27. Cross-cancer genome-wide association study of endometrial cancer and epithelial ovarian cancer identifies genetic risk regions associated with risk of both cancers

Author

Glubb, Dylan M, Thompson, Deborah J, Aben, Katja KH, Alsulimani, Ahmad, Amant, Frederic, Annibali, Daniela, Attia, John, Barricarte, Aurelio, Beckmann, Matthias W, Berchuck, Andrew, Bermisheva, Marina, Bernardini, Marcus Q, Bischof, Katharina, Bjorge, Line, Bodelon, Clara, Brand, Alison H, Brenton, James D, Brinton, Louise, Bruinsma, Fiona, Buchanan, Daniel D, Burghaus, Stefanie, Butzow, Ralf, Cai, Hui, Carney, Michael E, Chanock, Stephen J, Chen, Chu, Chen, Xiao Qing, Chen, Zhihua, Cook, Linda S, Cunningham, Julie M, De Vivo, Immaculata, deFazio, Anna, Doherty, Jennifer A, Dörk, Thilo, du Bois, Andreas, Dunning, Alison M, Dürst, Matthias, Edwards, Todd, Edwards, Robert P, Ekici, Arif B, Ewing, Ailith, Fasching, Peter A, Ferguson, Sarah, Flanagan, James M, Fostira, Florentia, Fountzilas, George, Friedenreich, Christine M, Gao, Bo, Gaudet, Mia M, Gawełko, Jan, Gentry-Maharaj, Aleksandra, Giles, Graham G, Glasspool, Rosalind, Goodman, Marc T, Gronwald, Jacek, Group, OPAL Study, Group, AOCS, Harris, Holly R, Harter, Philipp, Hein, Alexander, Heitz, Florian, Hildebrandt, Michelle AT, Hillemanns, Peter, Høgdall, Estrid, Høgdall, Claus K, Holliday, Elizabeth G, Huntsman, David G, Huzarski, Tomasz, Jakubowska, Anna, Jensen, Allan, Jones, Michael E, Karlan, Beth Y, Karnezis, Anthony, Kelley, Joseph L, Khusnutdinova, Elza, Killeen, Jeffrey L, Kjaer, Susanne K, Klapdor, Rüdiger, Köbel, Martin, Konopka, Bozena, Konstantopoulou, Irene, Kopperud, Reidun K, Koti, Madhuri, Kraft, Peter, Kupryjanczyk, Jolanta, Lambrechts, Diether, Larson, Melissa C, Le Marchand, Loic, Lele, Shashikant B, Lester, Jenny, Li, Andrew J, Liang, Dong, Liebrich, Clemens, Lipworth, Loren, Lissowska, Jolanta, Lu, Lingeng, Lu, Karen H, Macciotta, Alessandra, Mattiello, Amalia, and May, Taymaa

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Statistics, Mathematical Sciences, Oncology and Carcinogenesis, Aging, Rare Diseases, Human Genome, Cancer, Uterine Cancer, Ovarian Cancer, Prevention, Biotechnology, Aetiology, 2.1 Biological and endogenous factors
Abstract

Abstract: Accumulating evidence suggests a relationship between endometrial cancer and epithelial ovarian cancer. For example, endometrial cancer and epithelial ovarian cancer share epidemiological risk factors and molecular features observed across histotypes are held in common (e.g. serous, endometrioid and clear cell). Independent genome-wide association studies (GWAS) for endometrial cancer and epithelial ovarian cancer have identified 16 and 27 risk regions, respectively, four of which overlap between the two cancers. Using GWAS summary statistics, we explored the shared genetic etiology between endometrial cancer and epithelial ovarian cancer. Genetic correlation analysis using LD Score regression revealed significant genetic correlation between the two cancers (rG = 0.43, P = 2.66 × 10−5). To identify loci associated with the risk of both cancers, we implemented a pipeline of statistical genetic analyses (i.e. inverse-variance meta-analysis, co-localization, and M-values), and performed analyses by stratified by subtype. We found seven loci associated with risk for both cancers (PBonferroni < 2.4 × 10−9). In addition, four novel regions at 7p22.2, 7q22.1, 9p12 and 11q13.3 were identified at a sub-genome wide threshold (P < 5 × 10−7). Integration with promoter-associated HiChIP chromatin loops from immortalized endometrium and epithelial ovarian cell lines, and expression quantitative trait loci (eQTL) data highlighted candidate target genes for further investigation.

Published
2020

28. Assessment of interactions between 205 breast cancer susceptibility loci and 13 established risk factors in relation to breast cancer risk, in the Breast Cancer Association Consortium

Author

Kapoor, Pooja Middha, Lindström, Sara, Behrens, Sabine, Wang, Xiaoliang, Michailidou, Kyriaki, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Dunning, Alison M, Pharoah, Paul DP, Schmidt, Marjanka K, Kraft, Peter, García-Closas, Montserrat, Easton, Douglas F, Milne, Roger L, Chang-Claude, Jenny, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bernstein, Leslie, Berrandou, Takiy, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brock, Ian W, Broeks, Annegien, Brooks-Wilson, Angela, Butterbach, Katja, Cai, Qiuyin, Campa, Daniele, Canzian, Federico, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Clarke, Christine L, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dai, James Y, Dite, Gillian S, Earp, H Shelton, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, Gaudet, Mia M, Giles, Graham G, González-Neira, Anna, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Harstad, Tricia, He, Wei, Heyworth, Jane, Hoover, Robert N, Hopper, John L, Humphreys, Keith, Hunter, David J, Marrón, Pablo Isidro, John, Esther M, Jones, Michael E, Jung, Audrey, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Krüger, Ute, Lambrechts, Diether, Le Marchand, Loic, Lee, Eunjung, Lejbkowicz, Flavio, Linet, Martha, Lissowska, Jolanta, Llaneza, Ana, Lo, Wing-Yee, and Makalic, Enes

Subjects
Genetics, Estrogen, Clinical Research, Cancer, Breast Cancer, Prevention, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Europe, Factor XIII, Female, Gene-Environment Interaction, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Receptors, Estrogen, Risk Factors, White People, Breast Cancer Association Consortium, Europeans, Gene-environment interaction, breast cancer, epidemiology, risk factors, single nucleotide polymorphism, Statistics, Public Health and Health Services, Epidemiology
Abstract

BackgroundPrevious gene-environment interaction studies of breast cancer risk have provided sparse evidence of interactions. Using the largest available dataset to date, we performed a comprehensive assessment of potential effect modification of 205 common susceptibility variants by 13 established breast cancer risk factors, including replication of previously reported interactions.MethodsAnalyses were performed using 28 176 cases and 32 209 controls genotyped with iCOGS array and 44 109 cases and 48 145 controls genotyped using OncoArray from the Breast Cancer Association Consortium (BCAC). Gene-environment interactions were assessed using unconditional logistic regression and likelihood ratio tests for breast cancer risk overall and by estrogen-receptor (ER) status. Bayesian false discovery probability was used to assess the noteworthiness of the meta-analysed array-specific interactions.ResultsNoteworthy evidence of interaction at ≤1% prior probability was observed for three single nucleotide polymorphism (SNP)-risk factor pairs. SNP rs4442975 was associated with a greater reduction of risk of ER-positive breast cancer [odds ratio (OR)int = 0.85 (0.78-0.93), Pint = 2.8 x 10-4] and overall breast cancer [ORint = 0.85 (0.78-0.92), Pint = 7.4 x 10-5) in current users of estrogen-progesterone therapy compared with non-users. This finding was supported by replication using OncoArray data of the previously reported interaction between rs13387042 (r2 = 0.93 with rs4442975) and current estrogen-progesterone therapy for overall disease (Pint = 0.004). The two other interactions suggested stronger associations between SNP rs6596100 and ER-negative breast cancer with increasing parity and younger age at first birth.ConclusionsOverall, our study does not suggest strong effect modification of common breast cancer susceptibility variants by established risk factors.

Published
2020

29. A network analysis to identify mediators of germline-driven differences in breast cancer prognosis.

Author

Escala-Garcia, Maria, Abraham, Jean, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Ashworth, Alan, Auer, Paul L, Auvinen, Päivi, Beckmann, Matthias W, Beesley, Jonathan, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Blot, William, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brucker, Sara Y, Burwinkel, Barbara, Caldas, Carlos, Canzian, Federico, Chang-Claude, Jenny, Chanock, Stephen J, Chin, Suet-Feung, Clarke, Christine L, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Dennis, Joe, Devilee, Peter, Dunn, Janet A, Dunning, Alison M, Dwek, Miriam, Earl, Helena M, Eccles, Diana M, Eliassen, A Heather, Ellberg, Carolina, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, George, Angela, Giles, Graham G, Goldgar, David E, González-Neira, Anna, Grip, Mervi, Guénel, Pascal, Guo, Qi, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, Harrington, Patricia A, Hiller, Louise, Hooning, Maartje J, Hopper, John L, Howell, Anthony, Huang, Chiun-Sheng, Huang, Guanmengqian, Hunter, David J, Jakubowska, Anna, John, Esther M, Kaaks, Rudolf, Kapoor, Pooja Middha, Keeman, Renske, Kitahara, Cari M, Koppert, Linetta B, Kraft, Peter, Kristensen, Vessela N, Lambrechts, Diether, Le Marchand, Loic, Lejbkowicz, Flavio, Lindblom, Annika, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Maurer, Tabea, Mavroudis, Dimitrios, Meindl, Alfons, Milne, Roger L, Mulligan, Anna Marie, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Olshan, Andrew F, Olson, Janet E, and Olsson, Håkan

Subjects
Germ Cells, Humans, Breast Neoplasms, GTP-Binding Protein alpha Subunits, GTP-Binding Protein alpha Subunits, Gq-G11, Receptors, Estrogen, Prognosis, Computational Biology, Signal Transduction, Apoptosis, Genotype, Female, Gene Regulatory Networks, Genetic Variation, Genome-Wide Association Study, Circadian Clocks, Gq-G11, Receptors, Estrogen, Cancer, Breast Cancer, Genetics, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies
Abstract

Identifying the underlying genetic drivers of the heritability of breast cancer prognosis remains elusive. We adapt a network-based approach to handle underpowered complex datasets to provide new insights into the potential function of germline variants in breast cancer prognosis. This network-based analysis studies ~7.3 million variants in 84,457 breast cancer patients in relation to breast cancer survival and confirms the results on 12,381 independent patients. Aggregating the prognostic effects of genetic variants across multiple genes, we identify four gene modules associated with survival in estrogen receptor (ER)-negative and one in ER-positive disease. The modules show biological enrichment for cancer-related processes such as G-alpha signaling, circadian clock, angiogenesis, and Rho-GTPases in apoptosis.

Published
2020

30. A meta-analysis of genome-wide association studies of multiple myeloma among men and women of African ancestry

Author

Du, Zhaohui, Weinhold, Niels, Song, Gregory Chi, Rand, Kristin A, Van Den Berg, David J, Hwang, Amie E, Sheng, Xin, Hom, Victor, Ailawadhi, Sikander, Nooka, Ajay K, Singhal, Seema, Pawlish, Karen, Peters, Edward S, Bock, Cathryn, Mohrbacher, Ann, Stram, Alexander, Berndt, Sonja I, Blot, William J, Casey, Graham, Stevens, Victoria L, Kittles, Rick, Goodman, Phyllis J, Diver, W Ryan, Hennis, Anselm, Nemesure, Barbara, Klein, Eric A, Rybicki, Benjamin A, Stanford, Janet L, Witte, John S, Signorello, Lisa, John, Esther M, Bernstein, Leslie, Stroup, Antoinette M, Stephens, Owen W, Zangari, Maurizio, Van Rhee, Frits, Olshan, Andrew, Zheng, Wei, Hu, Jennifer J, Ziegler, Regina, Nyante, Sarah J, Ingles, Sue Ann, Press, Michael F, Carpten, John David, Chanock, Stephen J, Mehta, Jayesh, Colditz, Graham A, Wolf, Jeffrey, Martin, Thomas G, Tomasson, Michael, Fiala, Mark A, Terebelo, Howard, Janakiraman, Nalini, Kolonel, Laurence, Anderson, Kenneth C, Le Marchand, Loic, Auclair, Daniel, Chiu, Brian C-H, Ziv, Elad, Stram, Daniel, Vij, Ravi, Bernal-Mizrachi, Leon, Morgan, Gareth J, Zonder, Jeffrey A, Huff, Carol Ann, Lonial, Sagar, Orlowski, Robert Z, Conti, David V, Haiman, Christopher A, and Cozen, Wendy

Subjects
Hematology, Rare Diseases, Genetics, Cancer, Clinical Research, Prevention, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Multiple Myeloma, Polymorphism, Single Nucleotide, Transcriptional Elongation Factors
Abstract

Persons of African ancestry (AA) have a twofold higher risk for multiple myeloma (MM) compared with persons of European ancestry (EA). Genome-wide association studies (GWASs) support a genetic contribution to MM etiology in individuals of EA. Little is known about genetic risk factors for MM in individuals of AA. We performed a meta-analysis of 2 GWASs of MM in 1813 cases and 8871 controls and conducted an admixture mapping scan to identify risk alleles. We fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. In GWAS meta-analysis, we identified 2 suggestive novel loci located at 9p24.3 and 9p13.1 at P < 1 × 10-6; however, no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. Of the 23 known EA risk variants, 20 showed directional consistency, and 9 replicated at P < .05 in AA individuals. In 8 regions, we identified markers that better capture MM risk in persons with AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95% confidence interval, 1.56-2.11) increased MM risk compared with those with average risk (25%-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P = 5.1 × 10-12). Our study shows that common genetic variation contributes to MM risk in individuals with AA.

Published
2020

31. Assessment of polygenic architecture and risk prediction based on common variants across fourteen cancers

Author

Zhang, Yan Dora, Hurson, Amber N, Zhang, Haoyu, Choudhury, Parichoy Pal, Easton, Douglas F, Milne, Roger L, Simard, Jacques, Hall, Per, Michailidou, Kyriaki, Dennis, Joe, Schmidt, Marjanka K, Chang-Claude, Jenny, Gharahkhani, Puya, Whiteman, David, Campbell, Peter T, Hoffmeister, Michael, Jenkins, Mark, Peters, Ulrike, Hsu, Li, Gruber, Stephen B, Casey, Graham, Schmit, Stephanie L, O’Mara, Tracy A, Spurdle, Amanda B, Thompson, Deborah J, Tomlinson, Ian, De Vivo, Immaculata, Landi, Maria Teresa, Law, Matthew H, Iles, Mark M, Demenais, Florence, Kumar, Rajiv, MacGregor, Stuart, Bishop, D Timothy, Ward, Sarah V, Bondy, Melissa L, Houlston, Richard, Wiencke, John K, Melin, Beatrice, Barnholtz-Sloan, Jill, Kinnersley, Ben, Wrensch, Margaret R, Amos, Christopher I, Hung, Rayjean J, Brennan, Paul, McKay, James, Caporaso, Neil E, Berndt, Sonja I, Birmann, Brenda M, Camp, Nicola J, Kraft, Peter, Rothman, Nathaniel, Slager, Susan L, Berchuck, Andrew, Pharoah, Paul DP, Sellers, Thomas A, Gayther, Simon A, Pearce, Celeste L, Goode, Ellen L, Schildkraut, Joellen M, Moysich, Kirsten B, Amundadottir, Laufey T, Jacobs, Eric J, Klein, Alison P, Petersen, Gloria M, Risch, Harvey A, Stolzenberg-Solomon, Rachel Z, Wolpin, Brian M, Li, Donghui, Eeles, Rosalind A, Haiman, Christopher A, Kote-Jarai, Zsofia, Schumacher, Fredrick R, Al Olama, Ali Amin, Purdue, Mark P, Scelo, Ghislaine, Dalgaard, Marlene D, Greene, Mark H, Grotmol, Tom, Kanetsky, Peter A, McGlynn, Katherine A, Nathanson, Katherine L, Turnbull, Clare, Wiklund, Fredrik, Chanock, Stephen J, Chatterjee, Nilanjan, and Garcia-Closas, Montserrat

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Oncology and Carcinogenesis, Prevention, Prostate Cancer, Urologic Diseases, Human Genome, Cancer, Aetiology, 2.1 Biological and endogenous factors, Animals, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Incidence, Male, Models, Genetic, Multifactorial Inheritance, Neoplasms, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Breast Cancer Association Consortium, Barrett’s and Esophageal Adenocarcinoma Consortium, Colon Cancer Family Registry, Transdisciplinary Studies of Genetic Variation in Colorectal Cancer, Endometrial Cancer Association Consortium, Genetics and Epidemiology of Colorectal Cancer Consortium, Melanoma Genetics Consortium, Glioma International Case-Control Study, International Lung Cancer Consortium, Integrative Analysis of Lung Cancer Etiology and Risk (INTEGRAL) Consortium, International Consortium of Investigators Working on Non-Hodgkin’s Lymphoma Epidemiologic Studies, Ovarian Cancer Association Consortium, Oral Cancer GWAS, Pancreatic Cancer Case-Control Consortium, Pancreatic Cancer Cohort Consortium, Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome, Renal Cancer GWAS, Testicular Cancer Consortium
Abstract

Genome-wide association studies (GWAS) have led to the identification of hundreds of susceptibility loci across cancers, but the impact of further studies remains uncertain. Here we analyse summary-level data from GWAS of European ancestry across fourteen cancer sites to estimate the number of common susceptibility variants (polygenicity) and underlying effect-size distribution. All cancers show a high degree of polygenicity, involving at a minimum of thousands of loci. We project that sample sizes required to explain 80% of GWAS heritability vary from 60,000 cases for testicular to over 1,000,000 cases for lung cancer. The maximum relative risk achievable for subjects at the 99th risk percentile of underlying polygenic risk scores (PRS), compared to average risk, ranges from 12 for testicular to 2.5 for ovarian cancer. We show that PRS have potential for risk stratification for cancers of breast, colon and prostate, but less so for others because of modest heritability and lower incidence.

Published
2020

32. Genetic overlap between autoimmune diseases and non‐Hodgkin lymphoma subtypes

Author

Din, Lennox, Sheikh, Mohammad, Kosaraju, Nikitha, Smedby, Karin Ekstrom, Bernatsky, Sasha, Berndt, Sonja I, Skibola, Christine F, Nieters, Alexandra, Wang, Sophia, McKay, James D, Cocco, Pierluigi, Maynadié, Marc, Foretová, Lenka, Staines, Anthony, Mack, Thomas M, de Sanjosé, Silvia, Vyse, Timothy J, Padyukov, Leonid, Monnereau, Alain, Arslan, Alan A, Moore, Amy, Brooks‐Wilson, Angela R, Novak, Anne J, Glimelius, Bengt, Birmann, Brenda M, Link, Brian K, Stewart, Carolyn, Vajdic, Claire M, Haioun, Corinne, Magnani, Corrado, Conti, David V, Cox, David G, Casabonne, Delphine, Albanes, Demetrius, Kane, Eleanor, Roman, Eve, Muzi, Giacomo, Salles, Gilles, Giles, Graham G, Adami, Hans‐Olov, Ghesquières, Hervé, De Vivo, Immaculata, Clavel, Jacqueline, Cerhan, James R, Spinelli, John J, Hofmann, Jonathan, Vijai, Joseph, Curtin, Karen, Costenbader, Karen H, Onel, Kenan, Offit, Kenneth, Teras, Lauren R, Morton, Lindsay, Conde, Lucia, Miligi, Lucia, Melbye, Mads, Ennas, Maria Grazia, Liebow, Mark, Purdue, Mark P, Glenn, Martha, Southey, Melissa C, Din, Morris, Rothman, Nathaniel, Camp, Nicola J, Doo, Nicole Wong, Becker, Nikolaus, Pradhan, Nisha, Bracci, Paige M, Boffetta, Paolo, Vineis, Paolo, Brennan, Paul, Kraft, Peter, Lan, Qing, Severson, Richard K, Vermeulen, Roel CH, Milne, Roger L, Kaaks, Rudolph, Travis, Ruth C, Weinstein, Stephanie J, Chanock, Stephen J, Ansell, Stephen M, Slager, Susan L, Zheng, Tongzhang, Zhang, Yawei, Benavente, Yolanda, Taub, Zachary, Madireddy, Lohith, Gourraud, Pierre‐Antoine, Oksenberg, Jorge R, Cozen, Wendy, Hjalgrim, Henrik, and Khankhanian, Pouya

Subjects
Biological Sciences, Genetics, Lymphoma, Arthritis, Neurodegenerative, Brain Disorders, Autoimmune Disease, Cancer, Human Genome, Rare Diseases, Hematology, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Alleles, Autoimmune Diseases, Female, Genetic Predisposition to Disease, HLA Antigens, Humans, Lymphoma, Non-Hodgkin, Male, Middle Aged, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Risk Factors, autoimmune disease, genome-wide association study, meta-analysis, non-Hodgkin lymphoma, Public Health and Health Services, Epidemiology
Abstract

Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.

Published
2019

33. Two truncating variants in FANCC and breast cancer risk.

Author

Dörk, Thilo, Peterlongo, Paolo, Mannermaa, Arto, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Freeman, Laura E Beane, Beckmann, Matthias W, Beeghly-Fadiel, Alicia, Behrens, Sabine, Bermisheva, Marina, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Canzian, Federico, Chan, Tsun L, Chang-Claude, Jenny, Chanock, Stephen J, Choi, Ji-Yeob, Christiansen, Hans, Clarke, Christine L, Couch, Fergus J, Czene, Kamila, Daly, Mary B, Dos-Santos-Silva, Isabel, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gao, Chi, Gapstur, Susan M, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, Goldgar, David E, Guénel, Pascal, Haeberle, Lothar, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hartman, Mikael, Hauke, Jan, Hein, Alexander, Hillemanns, Peter, Hogervorst, Frans BL, Hooning, Maartje J, Hopper, John L, Howell, Tony, Huo, Dezheng, Ito, Hidemi, Iwasaki, Motoki, Jakubowska, Anna, Janni, Wolfgang, John, Esther M, Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Kapoor, Pooja Middha, Khusnutdinova, Elza, Kim, Sung-Won, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kwong, Ava, Lambrechts, Diether, Marchand, Loic Le, Li, Jingmei, Lindström, Sara, Linet, Martha, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Lubiński, Jan, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Elena, Matsuo, Keitaro, Mavroudis, Dimitris, and Meindl, Alfons

Subjects
ABCTB Investigators, NBCS Collaborators, Humans, Breast Neoplasms, Fanconi Anemia, Genetic Predisposition to Disease, BRCA1 Protein, BRCA2 Protein, Case-Control Studies, Sequence Deletion, Female, Fanconi Anemia Complementation Group C Protein, Genetic Variation, Clinical Research, Breast Cancer, Genetics, Cancer, 2.1 Biological and endogenous factors, Biochemistry and Cell Biology, Other Physical Sciences
Abstract

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.

Published
2019

34. Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer.

Author

Ferreira, Manuel A, Gamazon, Eric R, Al-Ejeh, Fares, Aittomäki, Kristiina, Andrulis, Irene L, Anton-Culver, Hoda, Arason, Adalgeir, Arndt, Volker, Aronson, Kristan J, Arun, Banu K, Asseryanis, Ella, Azzollini, Jacopo, Balmaña, Judith, Barnes, Daniel R, Barrowdale, Daniel, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Białkowska, Katarzyna, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Borg, Ake, Brauch, Hiltrud, Brenner, Hermann, Broeks, Annegien, Burwinkel, Barbara, Caldés, Trinidad, Caligo, Maria A, Campa, Daniele, Campbell, Ian, Canzian, Federico, Carter, Jonathan, Carter, Brian D, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Christiansen, Hans, Chung, Wendy K, Claes, Kathleen BM, Clarke, Christine L, EMBRACE Collaborators, GC-HBOC Study Collaborators, GEMO Study Collaborators, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, de la Hoya, Miguel, Dennis, Joe, Devilee, Peter, Diez, Orland, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Ejlertsen, Bent, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Fasching, Peter A, Fletcher, Olivia, Flyger, Henrik, Friedman, Eitan, Frost, Debra, Gabrielson, Marike, Gago-Dominguez, Manuela, Ganz, Patricia A, Gapstur, Susan M, Garber, Judy, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Glendon, Gord, Godwin, Andrew K, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Greene, Mark H, Gronwald, Jacek, Guénel, Pascal, Haiman, Christopher A, Hall, Per, Hamann, Ute, He, Wei, Heyworth, Jane, Hogervorst, Frans BL, Hollestelle, Antoinette, Hoover, Robert N, Hopper, John L, Hulick, Peter J, Humphreys, Keith, Imyanitov, Evgeny N, ABCTB Investigators, HEBON Investigators, and BCFR Investigators

Subjects
EMBRACE Collaborators, GC-HBOC Study Collaborators, GEMO Study Collaborators, ABCTB Investigators, HEBON Investigators, BCFR Investigators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, Gene Expression Profiling, Quantitative Trait Loci, Female, Genome-Wide Association Study, Prevention, Cancer, Human Genome, Aging, Breast Cancer, Genetics, Biotechnology, 2.1 Biological and endogenous factors
Abstract

Genome-wide association studies (GWAS) have identified more than 170 breast cancer susceptibility loci. Here we hypothesize that some risk-associated variants might act in non-breast tissues, specifically adipose tissue and immune cells from blood and spleen. Using expression quantitative trait loci (eQTL) reported in these tissues, we identify 26 previously unreported, likely target genes of overall breast cancer risk variants, and 17 for estrogen receptor (ER)-negative breast cancer, several with a known immune function. We determine the directional effect of gene expression on disease risk measured based on single and multiple eQTL. In addition, using a gene-based test of association that considers eQTL from multiple tissues, we identify seven (and four) regions with variants associated with overall (and ER-negative) breast cancer risk, which were not reported in previous GWAS. Further investigation of the function of the implicated genes in breast and immune cells may provide insights into the etiology of breast cancer.

Published
2019

35. Cross-cancer pleiotropic associations with lung cancer risk in African Americans

Author

Jones, Carissa C, Bradford, Yuki, Amos, Christopher I, Blot, William J, Chanock, Stephen J, Harris, Curtis C, Schwartz, Ann G, Spitz, Margaret R, Wiencke, John K, Wrensch, Margaret R, Wu, Xifeng, and Aldrich, Melinda C

Subjects
Biomedical and Clinical Sciences, Epidemiology, Health Services and Systems, Health Sciences, Oncology and Carcinogenesis, Human Genome, Cancer, Prevention, Genetics, Lung Cancer, Clinical Research, Lung, 2.1 Biological and endogenous factors, Aetiology, Black or African American, Case-Control Studies, Female, Humans, Lung Neoplasms, Male, Middle Aged, Risk Factors, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundIdentifying genetic variants with pleiotropic associations across multiple cancers can reveal shared biologic pathways. Prior pleiotropic studies have primarily focused on European-descent individuals. Yet population-specific genetic variation can occur, and potential pleiotropic associations among diverse racial/ethnic populations could be missed. We examined cross-cancer pleiotropic associations with lung cancer risk in African Americans.MethodsWe conducted a pleiotropic analysis among 1,410 African American lung cancer cases and 2,843 controls. We examined 36,958 variants previously associated (or in linkage disequilibrium) with cancer in prior genome-wide association studies. Logistic regression analyses were conducted, adjusting for age, sex, global ancestry, study site, and smoking status.ResultsWe identified three novel genomic regions significantly associated (FDR-corrected P

Published
2019

36. Genome-wide association study of germline variants and breast cancer-specific mortality.

Author

Escala-Garcia, Maria, Guo, Qi, Dörk, Thilo, Canisius, Sander, Keeman, Renske, Dennis, Joe, Beesley, Jonathan, Lecarpentier, Julie, Bolla, Manjeet K, Wang, Qin, Abraham, Jean, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Auer, Paul L, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bernstein, Leslie, Blomqvist, Carl, Boeckx, Bram, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Brenner, Hermann, Brentnall, Adam, Brinton, Louise, Broberg, Per, Brock, Ian W, Brucker, Sara Y, Burwinkel, Barbara, Caldas, Carlos, Caldés, Trinidad, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Carter, Brian D, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Chenevix-Trench, Georgia, Cheng, Ting-Yuan David, Chin, Suet-Feung, Clarke, Christine L, NBCS Collaborators, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, David G, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dunn, Janet A, Dunning, Alison M, Durcan, Lorraine, Dwek, Miriam, Earl, Helena M, Ekici, Arif B, Eliassen, A Heather, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Figueroa, Jonine, Flesch-Janys, Dieter, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Galle, Eva, Gapstur, Susan M, García-Closas, Montserrat, García-Sáenz, José A, Gaudet, Mia M, George, Angela, Georgoulias, Vassilios, Giles, Graham G, Glendon, Gord, Goldgar, David E, González-Neira, Anna, Alnæs, Grethe I Grenaker, Grip, Mervi, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan, Harkness, Elaine F, Harrington, Patricia A, Hart, Steven N, Hartikainen, Jaana M, Hein, Alexander, Hillemanns, Peter, Hiller, Louise, and Holleczek, Bernd

Subjects
NBCS Collaborators, Chromosomes, Human, Pair 7, Humans, Breast Neoplasms, Receptors, Estrogen, Prognosis, Proportional Hazards Models, Bayes Theorem, Female, Genetic Variation, Genome-Wide Association Study, White People, Genetics, Breast Cancer, Human Genome, Cancer, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundWe examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry.MethodsMeta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP).ResultsWe did not find any variant associated with breast cancer-specific mortality at P

Published
2019

37. Novel Common Genetic Susceptibility Loci for Colorectal Cancer

Author

Schmit, Stephanie L, Edlund, Christopher K, Schumacher, Fredrick R, Gong, Jian, Harrison, Tabitha A, Huyghe, Jeroen R, Qu, Chenxu, Melas, Marilena, Van Den Berg, David J, Wang, Hansong, Tring, Stephanie, Plummer, Sarah J, Albanes, Demetrius, Alonso, M Henar, Amos, Christopher I, Anton, Kristen, Aragaki, Aaron K, Arndt, Volker, Barry, Elizabeth L, Berndt, Sonja I, Bezieau, Stéphane, Bien, Stephanie, Bloomer, Amanda, Boehm, Juergen, Boutron-Ruault, Marie-Christine, Brenner, Hermann, Brezina, Stefanie, Buchanan, Daniel D, Butterbach, Katja, Caan, Bette J, Campbell, Peter T, Carlson, Christopher S, Castelao, Jose E, Chan, Andrew T, Chang-Claude, Jenny, Chanock, Stephen J, Cheng, Iona, Cheng, Ya-Wen, Chin, Lee Soo, Church, James M, Church, Timothy, Coetzee, Gerhard A, Cotterchio, Michelle, Correa, Marcia Cruz, Curtis, Keith R, Duggan, David, Easton, Douglas F, English, Dallas, Feskens, Edith JM, Fischer, Rocky, FitzGerald, Liesel M, Fortini, Barbara K, Fritsche, Lars G, Fuchs, Charles S, Gago-Dominguez, Manuela, Gala, Manish, Gallinger, Steven J, Gauderman, W James, Giles, Graham G, Giovannucci, Edward L, Gogarten, Stephanie M, Gonzalez-Villalpando, Clicerio, Gonzalez-Villalpando, Elena M, Grady, William M, Greenson, Joel K, Gsur, Andrea, Gunter, Marc, Haiman, Christopher A, Hampe, Jochen, Harlid, Sophia, Harju, John F, Hayes, Richard B, Hofer, Philipp, Hoffmeister, Michael, Hopper, John L, Huang, Shu-Chen, Huerta, Jose Maria, Hudson, Thomas J, Hunter, David J, Idos, Gregory E, Iwasaki, Motoki, Jackson, Rebecca D, Jacobs, Eric J, Jee, Sun Ha, Jenkins, Mark A, Jia, Wei-Hua, Jiao, Shuo, Joshi, Amit D, Kolonel, Laurence N, Kono, Suminori, Kooperberg, Charles, Krogh, Vittorio, Kuehn, Tilman, Küry, Sébastien, LaCroix, Andrea, Laurie, Cecelia A, Lejbkowicz, Flavio, Lemire, Mathieu, Lenz, Heinz-Josef, and Levine, David

Subjects
Prevention, Cancer, Digestive Diseases, Human Genome, Genetics, Clinical Research, Colo-Rectal Cancer, Aetiology, 2.1 Biological and endogenous factors, Case-Control Studies, Colorectal Neoplasms, Ethnicity, Follow-Up Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Polymorphism, Single Nucleotide, Prognosis, United States, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

BackgroundPrevious genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10-8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk.MethodsWe conducted a GWAS in European descent CRC cases and control subjects using a discovery-replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10-8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided.ResultsThe discovery GWAS identified 11 variants associated with CRC at P < 5 × 10-8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0.ConclusionsThis study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Published
2019

38. Shared heritability and functional enrichment across six solid cancers.

Author

Jiang, Xia, Finucane, Hilary K, Schumacher, Fredrick R, Schmit, Stephanie L, Tyrer, Jonathan P, Han, Younghun, Michailidou, Kyriaki, Lesseur, Corina, Kuchenbaecker, Karoline B, Dennis, Joe, Conti, David V, Casey, Graham, Gaudet, Mia M, Huyghe, Jeroen R, Albanes, Demetrius, Aldrich, Melinda C, Andrew, Angeline S, Andrulis, Irene L, Anton-Culver, Hoda, Antoniou, Antonis C, Antonenkova, Natalia N, Arnold, Susanne M, Aronson, Kristan J, Arun, Banu K, Bandera, Elisa V, Barkardottir, Rosa B, Barnes, Daniel R, Batra, Jyotsna, Beckmann, Matthias W, Benitez, Javier, Benlloch, Sara, Berchuck, Andrew, Berndt, Sonja I, Bickeböller, Heike, Bien, Stephanie A, Blomqvist, Carl, Boccia, Stefania, Bogdanova, Natalia V, Bojesen, Stig E, Bolla, Manjeet K, Brauch, Hiltrud, Brenner, Hermann, Brenton, James D, Brook, Mark N, Brunet, Joan, Brunnström, Hans, Buchanan, Daniel D, Burwinkel, Barbara, Butzow, Ralf, Cadoni, Gabriella, Caldés, Trinidad, Caligo, Maria A, Campbell, Ian, Campbell, Peter T, Cancel-Tassin, Géraldine, Cannon-Albright, Lisa, Campa, Daniele, Caporaso, Neil, Carvalho, André L, Chan, Andrew T, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Chu, Christiani, David C, Claes, Kathleen BM, Claessens, Frank, Clements, Judith, Collée, J Margriet, Correa, Marcia Cruz, Couch, Fergus J, Cox, Angela, Cunningham, Julie M, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, deFazio, Anna, Devilee, Peter, Diez, Orland, Gago-Dominguez, Manuela, Donovan, Jenny L, Dörk, Thilo, Duell, Eric J, Dunning, Alison M, Dwek, Miriam, Eccles, Diana M, Edlund, Christopher K, Edwards, Digna R Velez, Ellberg, Carolina, Evans, D Gareth, Fasching, Peter A, Ferris, Robert L, Liloglou, Triantafillos, Figueiredo, Jane C, Fletcher, Olivia, Fortner, Renée T, Fostira, Florentia, Franceschi, Silvia, Friedman, Eitan, Gallinger, Steven J, and Ganz, Patricia A

Subjects
Humans, Breast Neoplasms, Colorectal Neoplasms, Ovarian Neoplasms, Head and Neck Neoplasms, Lung Neoplasms, Prostatic Neoplasms, Genetic Predisposition to Disease, Neoplasm Proteins, Case-Control Studies, Smoking, Mental Disorders, Inheritance Patterns, Phenotype, Polymorphism, Single Nucleotide, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Prevention, Cancer, Breast Cancer, Genetics, Rare Diseases, Lung Cancer, Human Genome, Colo-Rectal Cancer, Digestive Diseases, Lung, MD Multidisciplinary
Abstract

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

Published
2019

39. Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Author

Mavaddat, Nasim, Michailidou, Kyriaki, Dennis, Joe, Lush, Michael, Fachal, Laura, Lee, Andrew, Tyrer, Jonathan P, Chen, Ting-Huei, Wang, Qin, Bolla, Manjeet K, Yang, Xin, Adank, Muriel A, Ahearn, Thomas, Aittomäki, Kristiina, Allen, Jamie, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Auvinen, Päivi, Barrdahl, Myrto, Beane Freeman, Laura E, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bernstein, Leslie, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Brauch, Hiltrud, Bremer, Michael, Brenner, Hermann, Brentnall, Adam, Brock, Ian W, Brooks-Wilson, Angela, Brucker, Sara Y, Brüning, Thomas, Burwinkel, Barbara, Campa, Daniele, Carter, Brian D, Castelao, Jose E, Chanock, Stephen J, Chlebowski, Rowan, Christiansen, Hans, Clarke, Christine L, Collée, J Margriet, Cordina-Duverger, Emilie, Cornelissen, Sten, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Daly, Mary B, Devilee, Peter, Dörk, Thilo, Dos-Santos-Silva, Isabel, Dumont, Martine, Durcan, Lorraine, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Ellberg, Carolina, Engel, Christoph, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Fletcher, Olivia, Flyger, Henrik, Försti, Asta, Fritschi, Lin, Gabrielson, Marike, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Georgoulias, Vassilios, Giles, Graham G, Gilyazova, Irina R, Glendon, Gord, Goldberg, Mark S, Goldgar, David E, González-Neira, Anna, Grenaker Alnæs, Grethe I, Grip, Mervi, Gronwald, Jacek, Grundy, Anne, Guénel, Pascal, Haeberle, Lothar, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hamann, Ute, and Hankinson, Susan E

Subjects
ABCTB Investigators, kConFab/AOCS Investigators, NBCS Collaborators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, Receptors, Estrogen, Medical History Taking, Risk Assessment, Reproducibility of Results, Age Factors, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Adult, Aged, Aged, 80 and over, Middle Aged, Female, breast, cancer, epidemiology, genetic, polygenic, prediction, risk, score, screening, stratification, Human Genome, Cancer, Genetics, Clinical Research, Prevention, Breast Cancer, Good Health and Well Being, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.

Published
2019

40. The FANCM:p.Arg658* truncating variant is associated with risk of triple-negative breast cancer

Author

Figlioli, Gisella, Bogliolo, Massimo, Catucci, Irene, Caleca, Laura, Lasheras, Sandra Viz, Pujol, Roser, Kiiski, Johanna I, Muranen, Taru A, Barnes, Daniel R, Dennis, Joe, Michailidou, Kyriaki, Bolla, Manjeet K, Leslie, Goska, Aalfs, Cora M, Adank, Muriel A, Adlard, Julian, Agata, Simona, Cadoo, Karen, Agnarsson, Bjarni A, Ahearn, Thomas, Aittomäki, Kristiina, Ambrosone, Christine B, Andrews, Lesley, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Arnold, Norbert, Aronson, Kristan J, Arun, Banu K, Asseryanis, Ella, Auber, Bernd, Auvinen, Päivi, Azzollini, Jacopo, Balmaña, Judith, Barkardottir, Rosa B, Barrowdale, Daniel, Barwell, Julian, Beane Freeman, Laura E, Beauparlant, Charles Joly, Beckmann, Matthias W, Behrens, Sabine, Benitez, Javier, Berger, Raanan, Bermisheva, Marina, Blanco, Amie M, Blomqvist, Carl, Bogdanova, Natalia V, Bojesen, Anders, Bojesen, Stig E, Bonanni, Bernardo, Borg, Ake, Brady, Angela F, Brauch, Hiltrud, Brenner, Hermann, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Caldés, Trinidad, Caliebe, Almuth, Caligo, Maria A, Campa, Daniele, Campbell, Ian G, Canzian, Federico, Castelao, Jose E, Chang-Claude, Jenny, Chanock, Stephen J, Claes, Kathleen BM, Clarke, Christine L, Collavoli, Anita, Conner, Thomas A, Cox, David G, Cybulski, Cezary, Czene, Kamila, Daly, Mary B, de la Hoya, Miguel, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Dite, Gillian S, Ditsch, Nina, Domchek, Susan M, Dorfling, Cecilia M, dos-Santos-Silva, Isabel, Durda, Katarzyna, Dwek, Miriam, Eccles, Diana M, Ekici, Arif B, Eliassen, A Heather, Ellberg, Carolina, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Flyger, Henrik, Foulkes, William D, Friebel, Tara M, Friedman, Eitan, Gabrielson, Marike, Gaddam, Pragna, and Gago-Dominguez, Manuela

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Clinical Research, Genetics, Breast Cancer, Cancer, Genetic Testing, 2.1 Biological and endogenous factors, Aetiology, ABCTB Investigators, GEMO Study Collaborators, KConFab, Cancer genetics, Clinical sciences, Oncology and carcinogenesis, Epidemiology
Abstract

Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM -/- patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors.

Published
2019

41. Age‐specific genome‐wide association study in glioblastoma identifies increased proportion of ‘lower grade glioma’‐like features associated with younger age

Author

Ostrom, Quinn T, Kinnersley, Ben, Armstrong, Georgina, Rice, Terri, Chen, Yanwen, Wiencke, John K, McCoy, Lucie S, Hansen, Helen M, Amos, Christopher I, Bernstein, Jonine L, Claus, Elizabeth B, Eckel‐Passow, Jeanette E, Il'yasova, Dora, Johansen, Christoffer, Lachance, Daniel H, Lai, Rose K, Merrell, Ryan T, Olson, Sara H, Sadetzki, Siegal, Schildkraut, Joellen M, Shete, Sanjay, Rubin, Joshua B, Andersson, Ulrika, Rajaraman, Preetha, Chanock, Stephen J, Linet, Martha S, Wang, Zhaoming, Yeager, Meredith, consortium, on behalf of the GliomaScan, Houlston, Richard S, Jenkins, Robert B, Wrensch, Margaret R, Melin, Beatrice, Bondy, Melissa L, and Barnholtz‐Sloan, Jill S

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Brain Cancer, Rare Diseases, Neurosciences, Brain Disorders, Genetics, Cancer, Human Genome, Adolescent, Adult, Age Factors, Aged, Brain Neoplasms, Case-Control Studies, Female, Genome-Wide Association Study, Glioblastoma, Humans, Male, Middle Aged, Neoplasm Grading, Polymorphism, Single Nucleotide, Young Adult, glioma, brain tumors, age, GliomaScan consortium, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

Glioblastoma (GBM) is the most common malignant brain tumor in the United States. Incidence of GBM increases with age, and younger age-at-diagnosis is significantly associated with improved prognosis. While the relationship between candidate GBM risk SNPs and age-at-diagnosis has been explored, genome-wide association studies (GWAS) have not previously been stratified by age. Potential age-specific genetic effects were assessed in autosomal SNPs for GBM patients using data from four previous GWAS. Using age distribution tertiles (18-53, 54-64, 65+) datasets were analyzed using age-stratified logistic regression to generate p values, odds ratios (OR), and 95% confidence intervals (95%CI), and then combined using meta-analysis. There were 4,512 total GBM cases, and 10,582 controls used for analysis. Significant associations were detected at two previously identified SNPs in 7p11.2 (rs723527 [p54-63 = 1.50x10-9 , OR54-63 = 1.28, 95%CI54-63 = 1.18-1.39; p64+ = 2.14x10-11 , OR64+ = 1.32, 95%CI64+ = 1.21-1.43] and rs11979158 [p54-63 = 6.13x10-8 , OR54-63 = 1.35, 95%CI54-63 = 1.21-1.50; p64+ = 2.18x10-10 , OR64+ = 1.42, 95%CI64+ = 1.27-1.58]) but only in persons >54. There was also a significant association at the previously identified lower grade glioma (LGG) risk locus at 8q24.21 (rs55705857) in persons ages 18-53 (p18-53 = 9.30 × 10-11 , OR18-53 = 1.76, 95%CI18-53 = 1.49-2.10). Within The Cancer Genome Atlas (TCGA) there was higher prevalence of 'LGG'-like tumor characteristics in GBM samples in those 18-53, with IDH1/2 mutation frequency of 15%, as compared to 2.1% [54-63] and 0.8% [64+] (p = 0.0005). Age-specific differences in cancer susceptibility can provide important clues to etiology. The association of a SNP known to confer risk for IDH1/2 mutant glioma and higher prevalence of IDH1/2 mutation within younger individuals 18-53 suggests that more younger individuals may present initially with 'secondary glioblastoma.'

Published
2018

42. Mendelian randomisation study of age at menarche and age at menopause and the risk of colorectal cancer

Author

Neumeyer, Sonja, Banbury, Barbara L, Arndt, Volker, Berndt, Sonja I, Bezieau, Stephane, Bien, Stephanie A, Buchanan, Dan D, Butterbach, Katja, Caan, Bette J, Campbell, Peter T, Casey, Graham, Chan, Andrew T, Chanock, Stephen J, Dai, James Y, Gallinger, Steven, Giovannucci, Edward L, Giles, Graham G, Grady, William M, Hampe, Jochen, Hoffmeister, Michael, Hopper, John L, Hsu, Li, Jenkins, Mark A, Joshi, Amit, Larsson, Susanna C, Le Marchand, Loic, Lindblom, Annika, Moreno, Victor, Lemire, Mathieu, Li, Li, Lin, Yi, Offit, Kenneth, Newcomb, Polly A, Pharaoh, Paul D, Potter, John D, Qi, Lihong, Rennert, Gad, Schafmayer, Clemens, Schoen, Robert E, Slattery, Martha L, Song, Mingyang, Ulrich, Cornelia M, Win, Aung K, White, Emily, Wolk, Alicja, Woods, Michael O, Wu, Anna H, Gruber, Stephen B, Brenner, Hermann, Peters, Ulrike, and Chang-Claude, Jenny

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Estrogen, Genetics, Contraception/Reproduction, Prevention, Clinical Research, Colo-Rectal Cancer, Digestive Diseases, Cancer, Aging, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Age Factors, Case-Control Studies, Colorectal Neoplasms, Female, Genetic Predisposition to Disease, Humans, Logistic Models, Menarche, Mendelian Randomization Analysis, Menopause, Polymorphism, Single Nucleotide, Registries, Public Health and Health Services, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundSubstantial evidence supports an association between use of menopausal hormone therapy and decreased colorectal cancer (CRC) risk, indicating a role of exogenous sex hormones in CRC development. However, findings on endogenous oestrogen exposure and CRC are inconsistent.MethodsWe used a Mendelian randomisation approach to test for a causal effect of age at menarche and age at menopause as surrogates for endogenous oestrogen exposure on CRC risk. Weighted genetic risk scores based on 358 single-nucleotide polymorphisms associated with age at menarche and 51 single-nucleotide polymorphisms associated with age at menopause were used to estimate the association with CRC risk using logistic regression in 12,944 women diagnosed with CRC and 10,741 women without CRC from three consortia. Sensitivity analyses were conducted to address pleiotropy and possible confounding by body mass index.ResultsGenetic risk scores for age at menarche (odds ratio per year 0.98, 95% confidence interval: 0.95-1.02) and age at menopause (odds ratio 0.98, 95% confidence interval: 0.94-1.01) were not significantly associated with CRC risk. The sensitivity analyses yielded similar results.ConclusionsOur study does not support a causal relationship between genetic risk scores for age at menarche and age at menopause and CRC risk.

Published
2018

43. Sex-specific glioma genome-wide association study identifies new risk locus at 3p21.31 in females, and finds sex-differences in risk at 8q24.21.

Author

Ostrom, Quinn T, Kinnersley, Ben, Wrensch, Margaret R, Eckel-Passow, Jeanette E, Armstrong, Georgina, Rice, Terri, Chen, Yanwen, Wiencke, John K, McCoy, Lucie S, Hansen, Helen M, Amos, Christopher I, Bernstein, Jonine L, Claus, Elizabeth B, Il'yasova, Dora, Johansen, Christoffer, Lachance, Daniel H, Lai, Rose K, Merrell, Ryan T, Olson, Sara H, Sadetzki, Siegal, Schildkraut, Joellen M, Shete, Sanjay, Rubin, Joshua B, Lathia, Justin D, Berens, Michael E, Andersson, Ulrika, Rajaraman, Preetha, Chanock, Stephen J, Linet, Martha S, Wang, Zhaoming, Yeager, Meredith, GliomaScan consortium, Houlston, Richard S, Jenkins, Robert B, Melin, Beatrice, Bondy, Melissa L, and Barnholtz-Sloan, Jill S

Subjects
GliomaScan consortium, Chromosomes, Human, Pair 3, Chromosomes, Human, Pair 7, Chromosomes, Human, Pair 8, Humans, Glioma, Brain Neoplasms, Genetic Predisposition to Disease, Logistic Models, Odds Ratio, Risk Factors, Case-Control Studies, Sex Factors, Genotype, Polymorphism, Single Nucleotide, Alleles, Adult, Middle Aged, Female, Male, Genome-Wide Association Study, Neurosciences, Human Genome, Genetics, Prevention, Rare Diseases, Brain Cancer, Cancer, Brain Disorders
Abstract

Incidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.

Published
2018

44. Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer

Author

Milne, Roger L, Kuchenbaecker, Karoline B, Michailidou, Kyriaki, Beesley, Jonathan, Kar, Siddhartha, Lindström, Sara, Hui, Shirley, Lemaçon, Audrey, Soucy, Penny, Dennis, Joe, Jiang, Xia, Rostamianfar, Asha, Finucane, Hilary, Bolla, Manjeet K, McGuffog, Lesley, Wang, Qin, Aalfs, Cora M, Adams, Marcia, Adlard, Julian, Agata, Simona, Ahmed, Shahana, Ahsan, Habibul, Aittomäki, Kristiina, Al-Ejeh, Fares, Allen, Jamie, Ambrosone, Christine B, Amos, Christopher I, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Arnold, Norbert, Aronson, Kristan J, Auber, Bernd, Auer, Paul L, Ausems, Margreet GEM, Azzollini, Jacopo, Bacot, François, Balmaña, Judith, Barile, Monica, Barjhoux, Laure, Barkardottir, Rosa B, Barrdahl, Myrto, Barnes, Daniel, Barrowdale, Daniel, Baynes, Caroline, Beckmann, Matthias W, Benitez, Javier, Bermisheva, Marina, Bernstein, Leslie, Bignon, Yves-Jean, Blazer, Kathleen R, Blok, Marinus J, Blomqvist, Carl, Blot, William, Bobolis, Kristie, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Anders, Bojesen, Stig E, Bonanni, Bernardo, Børresen-Dale, Anne-Lise, Bozsik, Aniko, Bradbury, Angela R, Brand, Judith S, Brauch, Hiltrud, Brenner, Hermann, Bressac-de Paillerets, Brigitte, Brewer, Carole, Brinton, Louise, Broberg, Per, Brooks-Wilson, Angela, Brunet, Joan, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S, Byun, Jinyoung, Cai, Qiuyin, Caldés, Trinidad, Caligo, Maria A, Campbell, Ian, Canzian, Federico, Caron, Olivier, Carracedo, Angel, Carter, Brian D, Castelao, J Esteban, Castera, Laurent, Caux-Moncoutier, Virginie, Chan, Salina B, Chang-Claude, Jenny, Chanock, Stephen J, Chen, Xiaoqing, Cheng, Ting-Yuan David, Chiquette, Jocelyne, Christiansen, Hans, Claes, Kathleen BM, Clarke, Christine L, Conner, Thomas, Conroy, Don M, and Cook, Jackie

Subjects
Biological Sciences, Genetics, Cancer, Human Genome, Prevention, Breast Cancer, Aging, Estrogen, 2.1 Biological and endogenous factors, Aetiology, BRCA1 Protein, Breast Neoplasms, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Heterozygote, Humans, Mutation, Polymorphism, Single Nucleotide, Receptors, Estrogen, Risk Factors, White People, ABCTB Investigators, EMBRACE, GEMO Study Collaborators, HEBON, kConFab/AOCS Investigators, NBSC Collaborators, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.

Published
2017

45. Germline Genetic Variants and Lung Cancer Survival in African Americans

Author

Jones, Carissa C, Bush, William S, Crawford, Dana C, Wenzlaff, Angela S, Schwartz, Ann G, Wiencke, John K, Wrensch, Margaret R, Blot, William J, Chanock, Stephen J, Grogan, Eric L, and Aldrich, Melinda C

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Prevention, Cancer, Lung, Lung Cancer, Human Genome, Genetics, 2.1 Biological and endogenous factors, Aetiology, Good Health and Well Being, Adult, Black or African American, Aged, Cohort Studies, Female, Genetic Variation, Humans, Lung Neoplasms, Middle Aged, Risk Factors, Survival Analysis, Medical and Health Sciences, Biomedical and clinical sciences, Health sciences
Abstract

Background: African Americans have the highest lung cancer mortality in the United States. Genome-wide association studies (GWASs) of germline variants influencing lung cancer survival have not yet been conducted with African Americans. We examined five previously reported GWAS catalog variants and explored additional genome-wide associations among African American lung cancer cases.Methods: Incident non-small cell lung cancer cases (N = 286) in the Southern Community Cohort Study were genotyped on the Illumina HumanExome BeadChip. We used Cox proportional hazards models to estimate HRs and 95% confidence intervals (CIs) for overall mortality. Two independent African American studies (N = 316 and 298) were used for replication.Results: One previously reported variant, rs1878022 on 12q23.3, was significantly associated with mortality (HR = 0.70; 95% CI: 0.54-0.92). Replication findings were in the same direction, although attenuated (HR = 0.87 and 0.94). Meta-analysis had a HR of 0.83 (95% CI, 0.71-0.97). Analysis of common variants identified an association between chromosome 6q21.33 and mortality (HR = 0.46; 95% CI, 0.33-0.66).Conclusions: We identified an association between rs1878022 in CMKLR1 and lung cancer survival. However, our results in African Americans have a different direction of effect compared with a prior study in European Americans, suggesting a different genetic architecture or presence of gene-environment interactions. We also identified variants on chromosome 6 within the gene-rich HLA region, which has been previously implicated in lung cancer risk and survival.Impact: We found evidence that inherited genetic risk factors influence lung cancer survival in African Americans. Replication in additional populations is necessary to confirm potential genetic differences in lung cancer survival across populations. Cancer Epidemiol Biomarkers Prev; 26(8); 1288-95. ©2017 AACR.

Published
2017

46. Two Novel Susceptibility Loci for Prostate Cancer in Men of African Ancestry

Author

Conti, David V, Wang, Kan, Sheng, Xin, Bensen, Jeannette T, Hazelett, Dennis J, Cook, Michael B, Ingles, Sue A, Kittles, Rick A, Strom, Sara S, Rybicki, Benjamin A, Nemesure, Barbara, Isaacs, William B, Stanford, Janet L, Zheng, Wei, Sanderson, Maureen, John, Esther M, Park, Jong Y, Xu, Jianfeng, Stevens, Victoria L, Berndt, Sonja I, Huff, Chad D, Wang, Zhaoming, Yeboah, Edward D, Tettey, Yao, Biritwum, Richard B, Adjei, Andrew A, Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Sellers, Thomas A, Yamoah, Kosj, Murphy, Adam B, Crawford, Dana C, Gapstur, Susan M, Bush, William S, Aldrich, Melinda C, Cussenot, Olivier, Petrovics, Gyorgy, Cullen, Jennifer, Neslund-Dudas, Christine, Stern, Mariana C, Jarai, Zsofia-Kote, Govindasami, Koveela, Chokkalingam, Anand P, Hsing, Ann W, Goodman, Phyllis J, Hoffmann, Thomas, Drake, Bettina F, Hu, Jennifer J, Clark, Peter E, Van Den Eeden, Stephen K, Blanchet, Pascal, Fowke, Jay H, Casey, Graham, Hennis, Anselm JM, Han, Ying, Lubwama, Alexander, Thompson, Ian M, Leach, Robin, Easton, Douglas F, Schumacher, Fredrick, Van den Berg, David J, Gundell, Susan M, Stram, Alex, Wan, Peggy, Xia, Lucy, Pooler, Loreall C, Mohler, James L, Fontham, Elizabeth TH, Smith, Gary J, Taylor, Jack A, Srivastava, Shiv, Eeles, Rosalind A, Carpten, John, Kibel, Adam S, Multigner, Luc, Parent, Marie-Elise, Menegaux, Florence, Cancel-Tassin, Geraldine, Klein, Eric A, Brureau, Laurent, Stram, Daniel O, Watya, Stephen, Chanock, Stephen J, Witte, John S, Blot, William J, Henderson, Brian E, and Haiman, Christopher A

Subjects
Aging, Human Genome, Cancer, Prevention, Prostate Cancer, Biotechnology, Clinical Research, Genetics, Urologic Diseases, 2.1 Biological and endogenous factors, Aetiology, Blacks, Case-Control Studies, Checkpoint Kinase 2, Chromosomes, Human, Pair 13, Chromosomes, Human, Pair 22, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Insulin Receptor Substrate Proteins, Male, Polymorphism, Single Nucleotide, Prostatic Neoplasms, PRACTICAL/ELLIPSE Consortium, Black People, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Prostate cancer incidence is 1.6-fold higher in African Americans than in other populations. The risk factors that drive this disparity are unknown and potentially consist of social, environmental, and genetic influences. To investigate the genetic basis of prostate cancer in men of African ancestry, we performed a genome-wide association meta-analysis using two-sided statistical tests in 10 202 case subjects and 10 810 control subjects. We identified novel signals on chromosomes 13q34 and 22q12, with the risk-associated alleles found only in men of African ancestry (13q34: rs75823044, risk allele frequency = 2.2%, odds ratio [OR] = 1.55, 95% confidence interval [CI] = 1.37 to 1.76, P = 6.10 × 10-12; 22q12.1: rs78554043, risk allele frequency = 1.5%, OR = 1.62, 95% CI = 1.39 to 1.89, P = 7.50 × 10-10). At 13q34, the signal is located 5' of the gene IRS2 and 3' of a long noncoding RNA, while at 22q12 the candidate functional allele is a missense variant in the CHEK2 gene. These findings provide further support for the role of ancestry-specific germline variation in contributing to population differences in prostate cancer risk.

Published
2017

47. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium.

Author

Ng, Maggie CY, Graff, Mariaelisa, Lu, Yingchang, Justice, Anne E, Mudgal, Poorva, Liu, Ching-Ti, Young, Kristin, Yanek, Lisa R, Feitosa, Mary F, Wojczynski, Mary K, Rand, Kristin, Brody, Jennifer A, Cade, Brian E, Dimitrov, Latchezar, Duan, Qing, Guo, Xiuqing, Lange, Leslie A, Nalls, Michael A, Okut, Hayrettin, Tajuddin, Salman M, Tayo, Bamidele O, Vedantam, Sailaja, Bradfield, Jonathan P, Chen, Guanjie, Chen, Wei-Min, Chesi, Alessandra, Irvin, Marguerite R, Padhukasahasram, Badri, Smith, Jennifer A, Zheng, Wei, Allison, Matthew A, Ambrosone, Christine B, Bandera, Elisa V, Bartz, Traci M, Berndt, Sonja I, Bernstein, Leslie, Blot, William J, Bottinger, Erwin P, Carpten, John, Chanock, Stephen J, Chen, Yii-Der Ida, Conti, David V, Cooper, Richard S, Fornage, Myriam, Freedman, Barry I, Garcia, Melissa, Goodman, Phyllis J, Hsu, Yu-Han H, Hu, Jennifer, Huff, Chad D, Ingles, Sue A, John, Esther M, Kittles, Rick, Klein, Eric, Li, Jin, McKnight, Barbara, Nayak, Uma, Nemesure, Barbara, Ogunniyi, Adesola, Olshan, Andrew, Press, Michael F, Rohde, Rebecca, Rybicki, Benjamin A, Salako, Babatunde, Sanderson, Maureen, Shao, Yaming, Siscovick, David S, Stanford, Janet L, Stevens, Victoria L, Stram, Alex, Strom, Sara S, Vaidya, Dhananjay, Witte, John S, Yao, Jie, Zhu, Xiaofeng, Ziegler, Regina G, Zonderman, Alan B, Adeyemo, Adebowale, Ambs, Stefan, Cushman, Mary, Faul, Jessica D, Hakonarson, Hakon, Levin, Albert M, Nathanson, Katherine L, Ware, Erin B, Weir, David R, Zhao, Wei, Zhi, Degui, Bone Mineral Density in Childhood Study (BMDCS) Group, Arnett, Donna K, Grant, Struan FA, Kardia, Sharon LR, Oloapde, Olufunmilayo I, Rao, DC, Rotimi, Charles N, Sale, Michele M, Williams, L Keoki, Zemel, Babette S, Becker, Diane M, and Borecki, Ingrid B

Subjects
Bone Mineral Density in Childhood Study (BMDCS) Group, Humans, Obesity, Genetic Predisposition to Disease, Serine Endopeptidases, Anthropometry, Body Mass Index, Waist-Hip Ratio, Chromosome Mapping, Gene Frequency, Linkage Disequilibrium, Polymorphism, Single Nucleotide, African Continental Ancestry Group, European Continental Ancestry Group, Female, Male, Adiposity, Genome-Wide Association Study, Transcription Factor 7-Like 2 Protein, Genetics, Human Genome, 2.1 Biological and endogenous factors, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (

Published
2017

48. Genome-wide association study of prostate-specific antigen levels identifies novel loci independent of prostate cancer

Author

Hoffmann, Thomas J, Passarelli, Michael N, Graff, Rebecca E, Emami, Nima C, Sakoda, Lori C, Jorgenson, Eric, Habel, Laurel A, Shan, Jun, Ranatunga, Dilrini K, Quesenberry, Charles P, Chao, Chun R, Ghai, Nirupa R, Aaronson, David, Presti, Joseph, Nordström, Tobias, Wang, Zhaoming, Berndt, Sonja I, Chanock, Stephen J, Mosley, Jonathan D, Klein, Robert J, Middha, Mridu, Lilja, Hans, Melander, Olle, Kvale, Mark N, Kwok, Pui-Yan, Schaefer, Catherine, Risch, Neil, Van Den Eeden, Stephen K, and Witte, John S

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Clinical Sciences, Oncology and Carcinogenesis, Urologic Diseases, Cancer, Human Genome, Aging, Prostate Cancer, Prevention, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Aged, 80 and over, Alleles, Asian People, Biomarkers, Tumor, Black People, Gene Expression, Gene Frequency, Genetic Loci, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Prostate, Prostate-Specific Antigen, Prostatic Neoplasms, White People
Abstract

Prostate-specific antigen (PSA) levels have been used for detection and surveillance of prostate cancer (PCa). However, factors other than PCa-such as genetics-can impact PSA. Here we present findings from a genome-wide association study (GWAS) of PSA in 28,503 Kaiser Permanente whites and 17,428 men from replication cohorts. We detect 40 genome-wide significant (P

Published
2017

49. A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci

Author

Rand, Kristin A, Song, Chi, Dean, Eric, Serie, Daniel J, Curtin, Karen, Sheng, Xin, Hu, Donglei, Huff, Carol Ann, Bernal-Mizrachi, Leon, Tomasson, Michael H, Ailawadhi, Sikander, Singhal, Seema, Pawlish, Karen, Peters, Edward S, Bock, Cathryn H, Stram, Alex, Van Den Berg, David J, Edlund, Christopher K, Conti, David V, Zimmerman, Todd, Hwang, Amie E, Huntsman, Scott, Graff, John, Nooka, Ajay, Kong, Yinfei, Pregja, Silvana L, Berndt, Sonja I, Blot, William J, Carpten, John, Casey, Graham, Chu, Lisa, Diver, W Ryan, Stevens, Victoria L, Lieber, Michael R, Goodman, Phyllis J, Hennis, Anselm JM, Hsing, Ann W, Mehta, Jayesh, Kittles, Rick A, Kolb, Suzanne, Klein, Eric A, Leske, Cristina, Murphy, Adam B, Nemesure, Barbara, Neslund-Dudas, Christine, Strom, Sara S, Vij, Ravi, Rybicki, Benjamin A, Stanford, Janet L, Signorello, Lisa B, Witte, John S, Ambrosone, Christine B, Bhatti, Parveen, John, Esther M, Bernstein, Leslie, Zheng, Wei, Olshan, Andrew F, Hu, Jennifer J, Ziegler, Regina G, Nyante, Sarah J, Bandera, Elisa V, Birmann, Brenda M, Ingles, Sue A, Press, Michael F, Atanackovic, Djordje, Glenn, Martha J, Cannon-Albright, Lisa A, Jones, Brandt, Tricot, Guido, Martin, Thomas G, Kumar, Shaji K, Wolf, Jeffrey L, Deming Halverson, Sandra L, Rothman, Nathaniel, Brooks-Wilson, Angela R, Rajkumar, S Vincent, Kolonel, Laurence N, Chanock, Stephen J, Slager, Susan L, Severson, Richard K, Janakiraman, Nalini, Terebelo, Howard R, Brown, Elizabeth E, De Roos, Anneclaire J, Mohrbacher, Ann F, Colditz, Graham A, Giles, Graham G, Spinelli, John J, Chiu, Brian C, Munshi, Nikhil C, Anderson, Kenneth C, Levy, Joan, Zonder, Jeffrey A, Orlowski, Robert Z, Lonial, Sagar, Camp, Nicola J, Vachon, Celine M, Ziv, Elad, Stram, Daniel O, and Hazelett, Dennis J

Subjects
Biomedical and Clinical Sciences, Cancer, Clinical Research, Genetics, Rare Diseases, Hematology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Black People, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Multiple Myeloma, Polycomb Repressive Complex 1, Polymorphism, Single Nucleotide, Protein Serine-Threonine Kinases, Repressor Proteins, Transmembrane Activator and CAML Interactor Protein, White People, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundGenome-wide association studies (GWAS) in European populations have identified genetic risk variants associated with multiple myeloma.MethodsWe performed association testing of common variation in eight regions in 1,318 patients with multiple myeloma and 1,480 controls of European ancestry and 1,305 patients with multiple myeloma and 7,078 controls of African ancestry and conducted a meta-analysis to localize the signals, with epigenetic annotation used to predict functionality.ResultsWe found that variants in 7p15.3, 17p11.2, 22q13.1 were statistically significantly (P < 0.05) associated with multiple myeloma risk in persons of African ancestry and persons of European ancestry, and the variant in 3p22.1 was associated in European ancestry only. In a combined African ancestry-European ancestry meta-analysis, variation in five regions (2p23.3, 3p22.1, 7p15.3, 17p11.2, 22q13.1) was statistically significantly associated with multiple myeloma risk. In 3p22.1, the correlated variants clustered within the gene body of ULK4 Correlated variants in 7p15.3 clustered around an enhancer at the 3' end of the CDCA7L transcription termination site. A missense variant at 17p11.2 (rs34562254, Pro251Leu, OR, 1.32; P = 2.93 × 10-7) in TNFRSF13B encodes a lymphocyte-specific protein in the TNF receptor family that interacts with the NF-κB pathway. SNPs correlated with the index signal in 22q13.1 cluster around the promoter and enhancer regions of CBX7 CONCLUSIONS: We found that reported multiple myeloma susceptibility regions contain risk variants important across populations, supporting the use of multiple racial/ethnic groups with different underlying genetic architecture to enhance the localization and identification of putatively functional alleles.ImpactA subset of reported risk loci for multiple myeloma has consistent effects across populations and is likely to be functional. Cancer Epidemiol Biomarkers Prev; 25(12); 1609-18. ©2016 AACR.

Published
2016

50. Genome-wide association study confirms lung cancer susceptibility loci on chromosomes 5p15 and 15q25 in an African-American population

Author

Zanetti, Krista A, Wang, Zhaoming, Aldrich, Melinda, Amos, Christopher I, Blot, William J, Bowman, Elise D, Burdette, Laurie, Cai, Qiuyin, Caporaso, Neil, Chung, Charles C, Gillanders, Elizabeth M, Haiman, Christopher A, Hansen, Helen M, Henderson, Brian E, Kolonel, Laurence N, Le Marchand, Loic, Li, Shengchao, McNeill, Lorna Haughton, Ryan, Bríd M, Schwartz, Ann G, Sison, Jennette D, Spitz, Margaret R, Tucker, Margaret, Wenzlaff, Angela S, Wiencke, John K, Wilkens, Lynne, Wrensch, Margaret R, Wu, Xifeng, Zheng, Wei, Zhou, Weiyin, Christiani, David, Palmer, Julie R, Penning, Trevor M, Rieber, Alyssa G, Rosenberg, Lynn, Ruiz-Narvaez, Edward A, Su, Li, Vachani, Anil, Wei, Yongyue, Whitehead, Alexander S, Chanock, Stephen J, and Harris, Curtis C

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prevention, Lung Cancer, Genetics, Clinical Research, Lung, Human Genome, Women's Health, Cancer, 2.1 Biological and endogenous factors, Respiratory, Black or African American, Case-Control Studies, Chromosomes, Human, Pair 15, Chromosomes, Human, Pair 5, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Lung Neoplasms, Polymorphism, Single Nucleotide, Population Surveillance, Quantitative Trait Loci, Genome-wide association study, Lung neoplasms, Smoking, African Americans, Telomerase, Receptors, Cholinergic, Clinical Sciences, Oncology & Carcinogenesis, Clinical sciences, Oncology and carcinogenesis
Abstract

ObjectivesGenome-wide association studies (GWAS) of lung cancer have identified regions of common genetic variation with lung cancer risk in Europeans who smoke and never-smoking Asian women. This study aimed to conduct a GWAS in African Americans, who have higher rates of lung cancer despite smoking fewer cigarettes per day when compared with Caucasians. This population provides a different genetic architecture based on underlying African ancestry allowing the identification of new regions and exploration of known regions for finer mapping.Materials and methodsWe genotyped 1,024,001 SNPs in 1737 cases and 3602 controls in stage 1, followed by a replication phase of 20 SNPs (p

Published
2016

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