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1. SAM-DNMT3A, a strategy for induction of genome-wide DNA methylation, identifies DNA methylation as a vulnerability in ER-positive breast cancers

Author

Mahnaz Hosseinpour, Xinqi Xi, Ling Liu, Luis Malaver-Ortega, Laura Perlaza-Jimenez, Jihoon E. Joo, Harrison M. York, Jonathan Beesley, C. Elizabeth Caldon, Pierre-Antoine Dugué, James G. Dowty, Senthil Arumugam, Melissa C. Southey, and Joseph Rosenbluh

Subjects
Science
Abstract

Abstract DNA methylation is an epigenetic mark that plays a critical role in regulating gene expression. DNA methyltransferase (DNMT) inhibitors, inhibit global DNA methylation and have been a key tool in studies of DNA methylation. A major bottleneck is the lack of tools to induce global DNA methylation. Here, we engineered a CRISPR based approach, that we initially designed, to enable site-specific DNA methylation. Using the synergistic activation mediator (SAM) system, we unexpectedly find that regardless of the targeted sequence any sgRNA induces global genome-wide DNA methylation. We term this method SAM-DNMT3A and show that induction of global DNA methylation is a unique vulnerability in ER-positive breast cancer suggesting a therapeutic approach. Our findings highlight the need of caution when using CRISPR based approaches for inducing DNA methylation and demonstrate a method for global induction of DNA methylation.

Published
2024
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2. Saliva-derived DNA is suitable for the detection of clonal haematopoiesis of indeterminate potential

Author

Robert L. O’Reilly, Jared Burke, Philip Harraka, Paul Yeh, Kerryn Howlett, Kiarash Behrouzfar, Amanda Rewse, Helen Tsimiklis, Graham G. Giles, Kristen J. Bubb, Stephen J. Nicholls, Roger L. Milne, and Melissa C. Southey

Subjects
Clonal haematopoiesis, CHIP, Somatic mutations, Next generation sequencing, Saliva, Blood, Medicine, Science
Abstract

Abstract Clonal haematopoiesis of indeterminate potential (CHIP) has been associated with many adverse health outcomes. However, further research is required to understand the critical genes and pathways relevant to CHIP subtypes, evaluate how CHIP clones evolve with time, and further advance functional characterisation and therapeutic studies. Large epidemiological studies are well placed to address these questions but often collect saliva rather than blood from participants. Paired saliva- and blood-derived DNA samples from 94 study participants were sequenced using a targeted CHIP-gene panel. The ten genes most frequently identified to carry CHIP-associated variants were analysed. Fourteen unique variants associated with CHIP, ten in DNMT3A, two in TP53 and two in TET2, were identified with a variant allele fraction (VAF) between 0.02 and 0.2 and variant depth ≥ 5 reads. Eleven of these CHIP-associated variants were detected in both the blood- and saliva-derived DNA sample. Three variants were detected in blood with a VAF > 0.02 but fell below this threshold in the paired saliva sample (VAF 0.008—0.013). Saliva-derived DNA is suitable for detecting CHIP-associated variants. Saliva can offer a cost-effective biospecimen that could both advance CHIP research and facilitate clinical translation into settings such as risk prediction, precision prevention, and treatment monitoring.

Published
2024
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3. Detection of differentially methylated CpGs between tumour and adjacent benign cells in diagnostic prostate cancer samples

Author

Liesel M. FitzGerald, Chol-hee Jung, Ee Ming Wong, JiHoon E. Joo, Julie K. Bassett, James G. Dowty, Xiaoyu Wang, James Y. Dai, Janet L. Stanford, Neil O’Callaghan, Tim Nottle, John Pedersen, Graham G. Giles, and Melissa C. Southey

Subjects
Medicine, Science
Abstract

Abstract Differentially methylated CpG sites (dmCpGs) that distinguish prostate tumour from adjacent benign tissue could aid in the diagnosis and prognosis of prostate cancer. Previously, the identification of such dmCpGs has only been undertaken in radical prostatectomy (RP) samples and not primary diagnostic tumour samples (needle biopsy or transurethral resection of the prostate). We interrogated an Australian dataset comprising 125 tumour and 43 adjacent histologically benign diagnostic tissue samples, including 41 paired samples, using the Infinium Human Methylation450 BeadChip. Regression analyses of paired tumour and adjacent benign samples identified 2,386 significant dmCpGs (Bonferroni p

Published
2024
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4. Epigenetic Ageing and Breast Cancer Risk: A Systematic Review

Author

Emily McLennan, Danmeng Lily Li, Melissa C. Southey, and Pierre‐Antoine Dugué

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

ABSTRACT Background Age is one of the strongest risk factors for breast cancer. Measures of biological age based on DNA methylation have gained popularity for their strong association with risk of many diseases, including cancer, which may help to identify high‐risk subgroups for targeted prevention. Methods We carried out a systematic review of prospective studies that examined the association of methylation‐based markers of ageing with risk of invasive breast cancer in healthy (breast cancer‐free) women, published up to May 2023. The search of three databases (MEDLINE, EMBASE and Web of Science) identified 2913 individual abstracts eligible for screening. Risk of bias assessment was conducted using ROBINS‐E. Results Ten prospective studies met the eligibility criteria, and these were heterogeneous in design and findings. The most frequently assessed epigenetic ageing measures were Horvath's first‐generation clock, PhenoAge and GrimAge. Four studies reported mainly positive associations, five null associations and one reported a negative association. These associations were generally weak and the results were not consistent across epigenetic ageing measures. Conclusion The summarised evidence is insufficient to support a role for current epigenetic ageing measures to stratify breast cancer risk. PROSPERO Registration: This systematic review was registered in the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023417559)

Published
2024
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5. Fine-mapping analysis including over 254,000 East Asian and European descendants identifies 136 putative colorectal cancer susceptibility genes

Author

Zhishan Chen, Xingyi Guo, Ran Tao, Jeroen R. Huyghe, Philip J. Law, Ceres Fernandez-Rozadilla, Jie Ping, Guochong Jia, Jirong Long, Chao Li, Quanhu Shen, Yuhan Xie, Maria N. Timofeeva, Minta Thomas, Stephanie L. Schmit, Virginia Díez-Obrero, Matthew Devall, Ferran Moratalla-Navarro, Juan Fernandez-Tajes, Claire Palles, Kitty Sherwood, Sarah E. W. Briggs, Victoria Svinti, Kevin Donnelly, Susan M. Farrington, James Blackmur, Peter G. Vaughan-Shaw, Xiao-Ou Shu, Yingchang Lu, Peter Broderick, James Studd, Tabitha A. Harrison, David V. Conti, Fredrick R. Schumacher, Marilena Melas, Gad Rennert, Mireia Obón-Santacana, Vicente Martín-Sánchez, Jae Hwan Oh, Jeongseon Kim, Sun Ha Jee, Keum Ji Jung, Sun-Seog Kweon, Min-Ho Shin, Aesun Shin, Yoon-Ok Ahn, Dong-Hyun Kim, Isao Oze, Wanqing Wen, Keitaro Matsuo, Koichi Matsuda, Chizu Tanikawa, Zefang Ren, Yu-Tang Gao, Wei-Hua Jia, John L. Hopper, Mark A. Jenkins, Aung Ko Win, Rish K. Pai, Jane C. Figueiredo, Robert W. Haile, Steven Gallinger, Michael O. Woods, Polly A. Newcomb, David Duggan, Jeremy P. Cheadle, Richard Kaplan, Rachel Kerr, David Kerr, Iva Kirac, Jan Böhm, Jukka-Pekka Mecklin, Pekka Jousilahti, Paul Knekt, Lauri A. Aaltonen, Harri Rissanen, Eero Pukkala, Johan G. Eriksson, Tatiana Cajuso, Ulrika Hänninen, Johanna Kondelin, Kimmo Palin, Tomas Tanskanen, Laura Renkonen-Sinisalo, Satu Männistö, Demetrius Albanes, Stephanie J. Weinstein, Edward Ruiz-Narvaez, Julie R. Palmer, Daniel D. Buchanan, Elizabeth A. Platz, Kala Visvanathan, Cornelia M. Ulrich, Erin Siegel, Stefanie Brezina, Andrea Gsur, Peter T. Campbell, Jenny Chang-Claude, Michael Hoffmeister, Hermann Brenner, Martha L. Slattery, John D. Potter, Kostas K. Tsilidis, Matthias B. Schulze, Marc J. Gunter, Neil Murphy, Antoni Castells, Sergi Castellví-Bel, Leticia Moreira, Volker Arndt, Anna Shcherbina, D. Timothy Bishop, Graham G. Giles, Melissa C. Southey, Gregory E. Idos, Kevin J. McDonnell, Zomoroda Abu-Ful, Joel K. Greenson, Katerina Shulman, Flavio Lejbkowicz, Kenneth Offit, Yu-Ru Su, Robert Steinfelder, Temitope O. Keku, Bethany van Guelpen, Thomas J. Hudson, Heather Hampel, Rachel Pearlman, Sonja I. Berndt, Richard B. Hayes, Marie Elena Martinez, Sushma S. Thomas, Paul D. P. Pharoah, Susanna C. Larsson, Yun Yen, Heinz-Josef Lenz, Emily White, Li Li, Kimberly F. Doheny, Elizabeth Pugh, Tameka Shelford, Andrew T. Chan, Marcia Cruz-Correa, Annika Lindblom, David J. Hunter, Amit D. Joshi, Clemens Schafmayer, Peter C. Scacheri, Anshul Kundaje, Robert E. Schoen, Jochen Hampe, Zsofia K. Stadler, Pavel Vodicka, Ludmila Vodickova, Veronika Vymetalkova, Christopher K. Edlund, W. James Gauderman, David Shibata, Amanda Toland, Sanford Markowitz, Andre Kim, Stephen J. Chanock, Franzel van Duijnhoven, Edith J. M. Feskens, Lori C. Sakoda, Manuela Gago-Dominguez, Alicja Wolk, Barbara Pardini, Liesel M. FitzGerald, Soo Chin Lee, Shuji Ogino, Stephanie A. Bien, Charles Kooperberg, Christopher I. Li, Yi Lin, Ross Prentice, Conghui Qu, Stéphane Bézieau, Taiki Yamaji, Norie Sawada, Motoki Iwasaki, Loic Le Marchand, Anna H. Wu, Chenxu Qu, Caroline E. McNeil, Gerhard Coetzee, Caroline Hayward, Ian J. Deary, Sarah E. Harris, Evropi Theodoratou, Stuart Reid, Marion Walker, Li Yin Ooi, Ken S. Lau, Hongyu Zhao, Li Hsu, Qiuyin Cai, Malcolm G. Dunlop, Stephen B. Gruber, Richard S. Houlston, Victor Moreno, Graham Casey, Ulrike Peters, Ian Tomlinson, and Wei Zheng

Subjects
Science
Abstract

Abstract Genome-wide association studies (GWAS) have identified more than 200 common genetic variants independently associated with colorectal cancer (CRC) risk, but the causal variants and target genes are mostly unknown. We sought to fine-map all known CRC risk loci using GWAS data from 100,204 cases and 154,587 controls of East Asian and European ancestry. Our stepwise conditional analyses revealed 238 independent association signals of CRC risk, each with a set of credible causal variants (CCVs), of which 28 signals had a single CCV. Our cis-eQTL/mQTL and colocalization analyses using colorectal tissue-specific transcriptome and methylome data separately from 1299 and 321 individuals, along with functional genomic investigation, uncovered 136 putative CRC susceptibility genes, including 56 genes not previously reported. Analyses of single-cell RNA-seq data from colorectal tissues revealed 17 putative CRC susceptibility genes with distinct expression patterns in specific cell types. Analyses of whole exome sequencing data provided additional support for several target genes identified in this study as CRC susceptibility genes. Enrichment analyses of the 136 genes uncover pathways not previously linked to CRC risk. Our study substantially expanded association signals for CRC and provided additional insight into the biological mechanisms underlying CRC development.

Published
2024
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6. Using polygenic risk modification to improve breast cancer prevention: study protocol for the PRiMo multicentre randomised controlled trial

Author

Melissa C Southey, Georgia Chenevix-Trench, Paul A James, Simone McInerny, Lyon Mascarenhas, Tatiane Yanes, Lara Petelin, and Mary-Anne Young

Subjects
Medicine
Abstract

Introduction Established personal and familial risk factors contribute collectively to a woman’s risk of breast or ovarian cancer. Existing clinical services offer genetic testing for pathogenic variants in high-risk genes to investigate these risks but recent information on the role of common genomic variants, in the form of a Polygenic Risk Score (PRS), has provided the potential to further personalise breast and ovarian cancer risk assessment. Data from cohort studies support the potential of an integrated risk assessment to improve targeted risk management but experience of this approach in clinical practice is limited.Methods and analysis The polygenic risk modification trial is an Australian multicentre prospective randomised controlled trial of integrated risk assessment including personal and family risk factors with inclusion of breast and ovarian PRS vs standard care. The study will enrol women, unaffected by cancer, undergoing predictive testing at a familial cancer clinic for a pathogenic variant in a known breast cancer (BC) or ovarian cancer (OC) predisposition gene (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D). Array-based genotyping will be used to generate breast cancer (313 SNP) and ovarian cancer (36 SNP) PRS. A suite of materials has been developed for the trial including an online portal for patient consent and questionnaires, and a clinician education programme to train healthcare providers in the use of integrated risk assessment. Long-term follow-up will evaluate differences in the assessed risk and management advice, patient risk management intentions and adherence, patient-reported experience and outcomes, and the health service implications of personalised risk assessment.Ethics and dissemination This study has been approved by the Human Research Ethics Committee of Peter MacCallum Cancer Centre and at all participating centres. Study findings will be disseminated via peer-reviewed publications and conference presentations, and directly to participants.Trial registration number ACTRN12621000009819.

Published
2024
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7. Blood-based DNA methylation markers for lung cancer prediction

Author

Marc Chadeau-Hyam, Paolo Vineis, Caroline Relton, Mattias Johansson, Gianluca Severi, Roger L Milne, Melissa C Southey, Pierre-Antoine Dugué, Florence Guida, Mikael Johansson, Torkjel Sandanger, Justina Ucheojor Onwuka, Ryan Langdon, Therese Haugdahl Nøst, Hilary A. Robbins, and Matthew Suderman

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Objective Screening high-risk individuals with low-dose CT reduces mortality from lung cancer, but many lung cancers occur in individuals who are not eligible for screening. Risk biomarkers may be useful to refine risk models and improve screening eligibility criteria. We evaluated if blood-based DNA methylation markers can improve a traditional lung cancer prediction model.Methods and analysis This study used four prospective cohorts with blood samples collected prior to lung cancer diagnosis. The study was restricted to participants with a history of smoking, and one control was individually matched to each lung cancer case using incidence density sampling by cohort, sex, date of blood collection, age and smoking status. To train a DNA methylation-based risk score, we used participants from Melbourne Collaborative Cohort Study-Australia (n=648) and Northern Sweden Health and Disease Study-Sweden (n=380) based on five selected CpG sites. The risk discriminative performance of the methylation score was subsequently validated in participants from European Investigation into Cancer and Nutrition-Italy (n=267) and Norwegian Women and Cancer-Norway (n=185) and compared with that of the questionnaire-based PLCOm2012 lung cancer risk model.Results The area under the receiver operating characteristic curve (AUC) for the PLCOm2012 model in the validation studies was 0.70 (95% CI: 0.65 to 0.75) compared with 0.73 (95% CI: 0.68 to 0.77) for the methylation score model (Pdifference=0.07). Incorporating the methylation score with the PLCOm2012 model did not improve the risk discrimination (AUC: 0.73, 95% CI: 0.68 to 0.77, Pdifference=0.73).Conclusions This study suggests that the methylation-based risk prediction score alone provides similar lung cancer risk-discriminatory performance as the questionnaire-based PLCOm2012 risk model.

Published
2024
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8. Causal relationships between breast cancer risk factors based on mammographic features

Author

Zhoufeng Ye, Tuong L. Nguyen, Gillian S. Dite, Robert J. MacInnis, Daniel F. Schmidt, Enes Makalic, Osamah M. Al-Qershi, Minh Bui, Vivienne F. C. Esser, James G. Dowty, Ho N. Trinh, Christopher F. Evans, Maxine Tan, Joohon Sung, Mark A. Jenkins, Graham G. Giles, Melissa C. Southey, John L. Hopper, and Shuai Li

Subjects
Breast cancer, Mammographic density, Textural feature, ICE FALCON, Causal inference, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. Methods We used digitised mammograms for 371 monozygotic twin pairs, aged 40–70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. Results The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22–0.81; all P

Published
2023
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9. Association of the CHEK2 c.1100delC variant, radiotherapy, and systemic treatment with contralateral breast cancer risk and breast cancer‐specific survival

Author

Anna Morra, Maartje A. C. Schreurs, Irene L. Andrulis, Hoda Anton‐Culver, Annelie Augustinsson, Matthias W. Beckmann, Sabine Behrens, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Annegien Broeks, Saundra S. Buys, Nicola J. Camp, Jose E. Castelao, Melissa H. Cessna, Jenny Chang‐Claude, Wendy K. Chung, NBCS Collaborators, Sarah V. Colonna, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Joe Dennis, Peter Devilee, Thilo Dörk, Alison M. Dunning, Miriam Dwek, Douglas F. Easton, Diana M. Eccles, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Tanja N. Fehm, Jonine D. Figueroa, Henrik Flyger, Marike Gabrielson, Manuela Gago‐Dominguez, Montserrat García‐Closas, José A. García‐Sáenz, Jeanine Genkinger, Felix Grassmann, Melanie Gündert, Eric Hahnen, Christopher A. Haiman, Ute Hamann, Patricia A. Harrington, Jaana M. Hartikainen, Reiner Hoppe, John L. Hopper, Richard S. Houlston, Anthony Howell, ABCTB Investigators, kConFab Investigators, Anna Jakubowska, Wolfgang Janni, Helena Jernström, Esther M. John, Nichola Johnson, Michael E. Jones, Vessela N. Kristensen, Allison W. Kurian, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Jan Lubiński, Michael P. Lux, Arto Mannermaa, Dimitrios Mavroudis, Anna Marie Mulligan, Taru A. Muranen, Heli Nevanlinna, Ines Nevelsteen, Patrick Neven, William G. Newman, Nadia Obi, Kenneth Offit, Andrew F. Olshan, Tjoung‐Won Park‐Simon, Alpa V. Patel, Paolo Peterlongo, Kelly‐Anne Phillips, Dijana Plaseska‐Karanfilska, Eric C. Polley, Nadege Presneau, Katri Pylkäs, Brigitte Rack, Paolo Radice, Muhammad U. Rashid, Valerie Rhenius, Mark Robson, Atocha Romero, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Sabine Schuetze, Christopher Scott, Mitul Shah, Snezhana Smichkoska, Melissa C. Southey, William J. Tapper, Lauren R. Teras, Rob A. E. M. Tollenaar, Katarzyna Tomczyk, Ian Tomlinson, Melissa A. Troester, Celine M. Vachon, Elke M. vanVeen, Qin Wang, Camilla Wendt, Hans Wildiers, Robert Winqvist, Argyrios Ziogas, Per Hall, Paul D. P. Pharoah, Muriel A. Adank, Antoinette Hollestelle, Marjanka K. Schmidt, and Maartje J. Hooning

Subjects
CHEK2 c.1100delC germline genetic variant, contralateral breast cancer risk, radiotherapy, survival, systemic treatment, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Breast cancer (BC) patients with a germline CHEK2 c.1100delC variant have an increased risk of contralateral BC (CBC) and worse BC‐specific survival (BCSS) compared to non‐carriers. Aim To assessed the associations of CHEK2 c.1100delC, radiotherapy, and systemic treatment with CBC risk and BCSS. Methods Analyses were based on 82,701 women diagnosed with a first primary invasive BC including 963 CHEK2 c.1100delC carriers; median follow‐up was 9.1 years. Differential associations with treatment by CHEK2 c.1100delC status were tested by including interaction terms in a multivariable Cox regression model. A multi‐state model was used for further insight into the relation between CHEK2 c.1100delC status, treatment, CBC risk and death. Results There was no evidence for differential associations of therapy with CBC risk by CHEK2 c.1100delC status. The strongest association with reduced CBC risk was observed for the combination of chemotherapy and endocrine therapy [HR (95% CI): 0.66 (0.55–0.78)]. No association was observed with radiotherapy. Results from the multi‐state model showed shorter BCSS for CHEK2 c.1100delC carriers versus non‐carriers also after accounting for CBC occurrence [HR (95% CI): 1.30 (1.09–1.56)]. Conclusion Systemic therapy was associated with reduced CBC risk irrespective of CHEK2 c.1100delC status. Moreover, CHEK2 c.1100delC carriers had shorter BCSS, which appears not to be fully explained by their CBC risk.

Published
2023
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10. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Pooja Middha, Xiaoliang Wang, Sabine Behrens, Manjeet K. Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J. Aronson, Paul L. Auer, Annelie Augustinsson, Thaïs Baert, Laura E. Beane Freeman, Heiko Becher, Matthias W. Beckmann, Javier Benitez, Stig E. Bojesen, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Daniele Campa, Federico Canzian, Angel Carracedo, Jose E. Castelao, Stephen J. Chanock, Georgia Chenevix-Trench, CTS Consortium, Emilie Cordina-Duverger, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Laure Dossus, Pierre-Antoine Dugué, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine D. Figueroa, Olivia Fletcher, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Graham G. Giles, Anna González-Neira, Felix Grassmann, Anne Grundy, Pascal Guénel, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Susan E. Hankinson, Elaine F. Harkness, Bernd Holleczek, Reiner Hoppe, John L. Hopper, Richard S. Houlston, Anthony Howell, David J. Hunter, Christian Ingvar, ABCTB Investigators, kConFab Investigators, Karolin Isaksson, Helena Jernström, Esther M. John, Michael E. Jones, Rudolf Kaaks, Renske Keeman, Cari M. Kitahara, Yon-Dschun Ko, Stella Koutros, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Nicole L. Larson, Susanna Larsson, Loic Le Marchand, Flavio Lejbkowicz, Shuai Li, Martha Linet, Jolanta Lissowska, Maria Elena Martinez, Tabea Maurer, Anna Marie Mulligan, Claire Mulot, Rachel A. Murphy, William G. Newman, Sune F. Nielsen, Børge G. Nordestgaard, Aaron Norman, Katie M. O’Brien, Janet E. Olson, Alpa V. Patel, Ross Prentice, Erika Rees-Punia, Gad Rennert, Valerie Rhenius, Kathryn J. Ruddy, Dale P. Sandler, Christopher G. Scott, Mitul Shah, Xiao-Ou Shu, Ann Smeets, Melissa C. Southey, Jennifer Stone, Rulla M. Tamimi, Jack A. Taylor, Lauren R. Teras, Katarzyna Tomczyk, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Sophia S. Wang, Clarice R. Weinberg, Hans Wildiers, Walter Willett, Stacey J. Winham, Alicja Wolk, Xiaohong R. Yang, M. Pilar Zamora, Wei Zheng, Argyrios Ziogas, Alison M. Dunning, Paul D. P. Pharoah, Montserrat García-Closas, Marjanka K. Schmidt, Peter Kraft, Roger L. Milne, Sara Lindström, Douglas F. Easton, and Jenny Chang-Claude

Subjects
Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Genome-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. Methods Analyses 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. Results Assuming a 1 × 10–5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Published
2023
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11. Associations of height, body mass index, and weight gain with breast cancer risk in carriers of a pathogenic variant in BRCA1 or BRCA2: the BRCA1 and BRCA2 Cohort Consortium

Author

Karin Kast, Esther M. John, John L. Hopper, Nadine Andrieu, Catherine Noguès, Emmanuelle Mouret-Fourme, Christine Lasset, Jean-Pierre Fricker, Pascaline Berthet, Véronique Mari, Lucie Salle, Marjanka K. Schmidt, Margreet G. E. M. Ausems, Encarnacion B. Gomez Garcia, Irma van de Beek, Marijke R. Wevers, D. Gareth Evans, Marc Tischkowitz, Fiona Lalloo, Jackie Cook, Louise Izatt, Vishakha Tripathi, Katie Snape, Hannah Musgrave, Saba Sharif, Jennie Murray, EMBRACE Collaborators, Sarah V. Colonna, Irene L. Andrulis, Mary B. Daly, Melissa C. Southey, Miguel de la Hoya, Ana Osorio, Lenka Foretova, Dita Berkova, Anne-Marie Gerdes, Edith Olah, Anna Jakubowska, Christian F. Singer, Yen Tan, Annelie Augustinsson, Johanna Rantala, Jacques Simard, Rita K. Schmutzler, Roger L. Milne, Kelly-Anne Phillips, Mary Beth Terry, David Goldgar, Flora E. van Leeuwen, Thea M. Mooij, Antonis C. Antoniou, Douglas F. Easton, Matti A. Rookus, and Christoph Engel

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Introduction Height, body mass index (BMI), and weight gain are associated with breast cancer risk in the general population. It is unclear whether these associations also exist for carriers of pathogenic variants in the BRCA1 or BRCA2 genes. Patients and methods An international pooled cohort of 8091 BRCA1/2 variant carriers was used for retrospective and prospective analyses separately for premenopausal and postmenopausal women. Cox regression was used to estimate breast cancer risk associations with height, BMI, and weight change. Results In the retrospective analysis, taller height was associated with risk of premenopausal breast cancer for BRCA2 variant carriers (HR 1.20 per 10 cm increase, 95% CI 1.04–1.38). Higher young-adult BMI was associated with lower premenopausal breast cancer risk for both BRCA1 (HR 0.75 per 5 kg/m2, 95% CI 0.66–0.84) and BRCA2 (HR 0.76, 95% CI 0.65–0.89) variant carriers in the retrospective analysis, with consistent, though not statistically significant, findings from the prospective analysis. In the prospective analysis, higher BMI and adult weight gain were associated with higher postmenopausal breast cancer risk for BRCA1 carriers (HR 1.20 per 5 kg/m2, 95% CI 1.02–1.42; and HR 1.10 per 5 kg weight gain, 95% CI 1.01–1.19, respectively). Conclusion Anthropometric measures are associated with breast cancer risk for BRCA1 and BRCA2 variant carriers, with relative risk estimates that are generally consistent with those for women from the general population.

Published
2023
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12. Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

Author

Chenglong Yu, Allison M Hodge, Ee Ming Wong, Jihoon E Joo, Enes Makalic, Daniel F Schmidt, Daniel D Buchanan, Gianluca Severi, John L Hopper, Dallas R English, Graham G Giles, Roger L Milne, Melissa C Southey, and Pierre-Antoine Dugué

Subjects
dna methylation, gene–environment interaction, lifestyle, polygenic score, cpg site, epigenetic ageing, Genetics, QH426-470
Abstract

Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene–environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10−14), ~0.6% (P = 2 × 10−7), and ~8.7% (P = 7 × 10−87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P

Published
2022
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13. PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Author

Daniele Giardiello, Maartje J. Hooning, Michael Hauptmann, Renske Keeman, B. A. M. Heemskerk-Gerritsen, Heiko Becher, Carl Blomqvist, Stig E. Bojesen, Manjeet K. Bolla, Nicola J. Camp, Kamila Czene, Peter Devilee, Diana M. Eccles, Peter A. Fasching, Jonine D. Figueroa, Henrik Flyger, Montserrat García-Closas, Christopher A. Haiman, Ute Hamann, John L. Hopper, Anna Jakubowska, Floor E. Leeuwen, Annika Lindblom, Jan Lubiński, Sara Margolin, Maria Elena Martinez, Heli Nevanlinna, Ines Nevelsteen, Saskia Pelders, Paul D. P. Pharoah, Sabine Siesling, Melissa C. Southey, Annemieke H. van der Hout, Liselotte P. van Hest, Jenny Chang-Claude, Per Hall, Douglas F. Easton, Ewout W. Steyerberg, and Marjanka K. Schmidt

Subjects
Contralateral breast cancer, Risk prediction, Contralateral preventive mastectomy, Clinical decision-making, Breast cancer genetic predisposition, Breast Cancer Association Consortium, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors. Methods We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models. Results The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56–0.74) versus 0.63 (95%PI 0.54–0.71). PredictCBC-2.0 was well calibrated with an observed/expected ratio at 10 years of 0.92 (95%PI 0.34–2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. Conclusions Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging.

Published
2022
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14. Methylation-based markers of aging and lifestyle-related factors and risk of breast cancer: a pooled analysis of four prospective studies

Author

Pierre-Antoine Dugué, Clara Bodelon, Felicia F. Chung, Hannah R. Brewer, Srikant Ambatipudi, Joshua N. Sampson, Cyrille Cuenin, Veronique Chajès, Isabelle Romieu, Giovanni Fiorito, Carlotta Sacerdote, Vittorio Krogh, Salvatore Panico, Rosario Tumino, Paolo Vineis, Silvia Polidoro, Laura Baglietto, Dallas English, Gianluca Severi, Graham G. Giles, Roger L. Milne, Zdenko Herceg, Montserrat Garcia-Closas, James M. Flanagan, and Melissa C. Southey

Subjects
Prospective study, DNA methylation, Epigenetic aging, Lifestyle, Breast cancer risk, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background DNA methylation in blood may reflect adverse exposures accumulated over the lifetime and could therefore provide potential improvements in the prediction of cancer risk. A substantial body of research has shown associations between epigenetic aging and risk of disease, including cancer. Here we aimed to study epigenetic measures of aging and lifestyle-related factors in association with risk of breast cancer. Methods Using data from four prospective case–control studies nested in three cohorts of European ancestry participants, including a total of 1,655 breast cancer cases, we calculated three methylation-based measures of lifestyle factors (body mass index [BMI], tobacco smoking and alcohol consumption) and seven measures of epigenetic aging (Horvath-based, Hannum-based, PhenoAge and GrimAge). All measures were regression-adjusted for their respective risk factors and expressed per standard deviation (SD). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional or unconditional logistic regression and pooled using fixed-effects meta-analysis. Subgroup analyses were conducted by age at blood draw, time from blood sample to diagnosis, oestrogen receptor-positivity status and tumour stage. Results None of the measures of epigenetic aging were associated with risk of breast cancer in the pooled analysis: Horvath ‘age acceleration’ (AA): OR per SD = 1.02, 95%CI: 0.95–1.10; AA-Hannum: OR = 1.03, 95%CI:0.95–1.12; PhenoAge: OR = 1.01, 95%CI: 0.94–1.09 and GrimAge: OR = 1.03, 95%CI: 0.94–1.12, in models adjusting for white blood cell proportions, body mass index, smoking and alcohol consumption. The BMI-adjusted predictor of BMI was associated with breast cancer risk, OR per SD = 1.09, 95%CI: 1.01–1.17. The results for the alcohol and smoking methylation-based predictors were consistent with a null association. Risk did not appear to substantially vary by age at blood draw, time to diagnosis or tumour characteristics. Conclusion We found no evidence that methylation-based measures of aging, smoking or alcohol consumption were associated with risk of breast cancer. A methylation-based marker of BMI was associated with risk and may provide insights into the underlying associations between BMI and breast cancer.

Published
2022
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15. Breast cancer risks associated with missense variants in breast cancer susceptibility genes

Author

Leila Dorling, Sara Carvalho, Jamie Allen, Michael T. Parsons, Cristina Fortuno, Anna González-Neira, Stephan M. Heijl, Muriel A. Adank, Thomas U. Ahearn, Irene L. Andrulis, Päivi Auvinen, Heiko Becher, Matthias W. Beckmann, Sabine Behrens, Marina Bermisheva, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Michael Bremer, Ignacio Briceno, Nicola J. Camp, Archie Campbell, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Georgia Chenevix-Trench, NBCS Collaborators, J. Margriet Collée, Kamila Czene, Joe Dennis, Thilo Dörk, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Henrik Flyger, Marike Gabrielson, Manuela Gago-Dominguez, Montserrat García-Closas, Graham G. Giles, Gord Glendon, Pascal Guénel, Melanie Gündert, Andreas Hadjisavvas, Eric Hahnen, Per Hall, Ute Hamann, Elaine F. Harkness, Mikael Hartman, Frans B. L. Hogervorst, Antoinette Hollestelle, Reiner Hoppe, Anthony Howell, kConFab Investigators, SGBCC Investigators, Anna Jakubowska, Audrey Jung, Elza Khusnutdinova, Sung-Won Kim, Yon-Dschun Ko, Vessela N. Kristensen, Inge M. M. Lakeman, Jingmei Li, Annika Lindblom, Maria A. Loizidou, Artitaya Lophatananon, Jan Lubiński, Craig Luccarini, Michael J. Madsen, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Dimitrios Mavroudis, Roger L. Milne, Nur Aishah Mohd Taib, Kenneth Muir, Heli Nevanlinna, William G. Newman, Jan C. Oosterwijk, Sue K. Park, Paolo Peterlongo, Paolo Radice, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Mitul Shah, Xueling Sim, Melissa C. Southey, Harald Surowy, Maija Suvanto, Ian Tomlinson, Diana Torres, Thérèse Truong, Christi J. van Asperen, Regina Waltes, Qin Wang, Xiaohong R. Yang, Paul D. P. Pharoah, Marjanka K. Schmidt, Javier Benitez, Bas Vroling, Alison M. Dunning, Soo Hwang Teo, Anders Kvist, Miguel de la Hoya, Peter Devilee, Amanda B. Spurdle, Maaike P. G. Vreeswijk, and Douglas F. Easton

Subjects
Breast cancer, Genetic epidemiology, Risk prediction, Missense variants, Medicine, Genetics, QH426-470
Abstract

Abstract Background Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain. Methods We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated. Results The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47–2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set. Conclusions These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

Published
2022
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16. Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci

Author

Hongjie Chen, Shaoqi Fan, Jennifer Stone, Deborah J. Thompson, Julie Douglas, Shuai Li, Christopher Scott, Manjeet K. Bolla, Qin Wang, Joe Dennis, Kyriaki Michailidou, Christopher Li, Ulrike Peters, John L. Hopper, Melissa C. Southey, Tu Nguyen-Dumont, Tuong L. Nguyen, Peter A. Fasching, Annika Behrens, Gemma Cadby, Rachel A. Murphy, Kristan Aronson, Anthony Howell, Susan Astley, Fergus Couch, Janet Olson, Roger L. Milne, Graham G. Giles, Christopher A. Haiman, Gertraud Maskarinec, Stacey Winham, Esther M. John, Allison Kurian, Heather Eliassen, Irene Andrulis, D. Gareth Evans, William G. Newman, Per Hall, Kamila Czene, Anthony Swerdlow, Michael Jones, Marina Pollan, Pablo Fernandez-Navarro, Daniel S. McConnell, Vessela N. Kristensen, NBCS Investigators, Joseph H. Rothstein, Pei Wang, Laurel A. Habel, Weiva Sieh, Alison M. Dunning, Paul D. P. Pharoah, Douglas F. Easton, Gretchen L. Gierach, Rulla M. Tamimi, Celine M. Vachon, and Sara Lindström

Subjects
Mammographic density, Breast cancer, Genome-wide association study (GWAS), Transcriptome-wide association study (TWAS), Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. Methods We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. Results We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p

Published
2022
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17. Genome-wide interaction analysis of menopausal hormone therapy use and breast cancer risk among 62,370 women

Author

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

Subjects
Medicine, Science
Abstract

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
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18. Population-based estimates of age-specific cumulative risk of breast cancer for pathogenic variants in ATM

Author

Anne-Laure Renault, James G. Dowty, Jason A. Steen, Shuai Li, Ingrid M. Winship, Graham G. Giles, John L. Hopper, Melissa C. Southey, and Tú Nguyen-Dumont

Subjects
ATM, Breast cancer predisposition, Genetic risk factors, Age-specific cumulative risk, Penetrance, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Multigene panel tests for breast cancer predisposition routinely include ATM as it is now a well-established breast cancer predisposition gene. Methods We included ATM in a multigene panel test applied to the Australian Breast Cancer Family Registry (ABCFR), a population-based case–control–family study of breast cancer, with the purpose of estimating the prevalence and penetrance of heterozygous ATM pathogenic variants from the family data, using segregation analysis. Results The estimated breast cancer hazard ratio for carriers of pathogenic ATM variants in the ABCFR was 1.32 (95% confidence interval 0.45–3.87; P = 0.6). The estimated cumulative risk of breast cancer to age 80 years for heterozygous ATM pathogenic variant carriers was estimated to be 13% (95% CI 4.6–30). Conclusions Although ATM has been definitively identified as a breast cancer predisposition gene, further evidence, such as variant-specific penetrance estimates, are needed to inform risk management strategies for carriers of pathogenic variants to increase the clinical utility of population testing of this gene.

Published
2022
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19. Common variants in breast cancer risk loci predispose to distinct tumor subtypes

Author

Thomas U. Ahearn, Haoyu Zhang, Kyriaki Michailidou, Roger L. Milne, Manjeet K. Bolla, Joe Dennis, Alison M. Dunning, Michael Lush, Qin Wang, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Kristan J. Aronson, Paul L. Auer, Annelie Augustinsson, Adinda Baten, Heiko Becher, Sabine Behrens, Javier Benitez, Marina Bermisheva, Carl Blomqvist, Stig E. Bojesen, Bernardo Bonanni, Anne-Lise Børresen-Dale, Hiltrud Brauch, Hermann Brenner, Angela Brooks-Wilson, Thomas Brüning, Barbara Burwinkel, Saundra S. Buys, Federico Canzian, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Georgia Chenevix-Trench, Christine L. Clarke, NBCS Collaborators, J. Margriet Collée, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Peter Devilee, Thilo Dörk, Miriam Dwek, Diana M. Eccles, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Giuseppe Floris, Manuela Gago-Dominguez, Susan M. Gapstur, José A. García-Sáenz, Mia M. Gaudet, Graham G. Giles, Mark S. Goldberg, Anna González-Neira, Grethe I. Grenaker Alnæs, Mervi Grip, Pascal Guénel, Christopher A. Haiman, Per Hall, Ute Hamann, Elaine F. Harkness, Bernadette A. M. Heemskerk-Gerritsen, Bernd Holleczek, Antoinette Hollestelle, Maartje J. Hooning, Robert N. Hoover, John L. Hopper, Anthony Howell, ABCTB Investigators, kConFab/AOCS Investigators, Milena Jakimovska, Anna Jakubowska, Esther M. John, Michael E. Jones, Audrey Jung, Rudolf Kaaks, Saila Kauppila, Renske Keeman, Elza Khusnutdinova, Cari M. Kitahara, Yon-Dschun Ko, Stella Koutros, Vessela N. Kristensen, Ute Krüger, Katerina Kubelka-Sabit, Allison W. Kurian, Kyriacos Kyriacou, Diether Lambrechts, Derrick G. Lee, Annika Lindblom, Martha Linet, Jolanta Lissowska, Ana Llaneza, Wing-Yee Lo, Robert J. MacInnis, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Maria Elena Martinez, Catriona McLean, Alfons Meindl, Usha Menon, Heli Nevanlinna, William G. Newman, Jesse Nodora, Kenneth Offit, Håkan Olsson, Nick Orr, Tjoung-Won Park-Simon, Alpa V. Patel, Julian Peto, Guillermo Pita, Dijana Plaseska-Karanfilska, Ross Prentice, Kevin Punie, Katri Pylkäs, Paolo Radice, Gad Rennert, Atocha Romero, Thomas Rüdiger, Emmanouil Saloustros, Sarah Sampson, Dale P. Sandler, Elinor J. Sawyer, Rita K. Schmutzler, Minouk J. Schoemaker, Ben Schöttker, Mark E. Sherman, Xiao-Ou Shu, Snezhana Smichkoska, Melissa C. Southey, John J. Spinelli, Anthony J. Swerdlow, Rulla M. Tamimi, William J. Tapper, Jack A. Taylor, Lauren R. Teras, Mary Beth Terry, Diana Torres, Melissa A. Troester, Celine M. Vachon, Carolien H. M. van Deurzen, Elke M. van Veen, Philippe Wagner, Clarice R. Weinberg, Camilla Wendt, Jelle Wesseling, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Wei Zheng, Fergus J. Couch, Jacques Simard, Peter Kraft, Douglas F. Easton, Paul D. P. Pharoah, Marjanka K. Schmidt, Montserrat García-Closas, and Nilanjan Chatterjee

Subjects
Breast cancer, Etiologic heterogeneity, Genetic predisposition, Common breast cancer susceptibility variants, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Genome-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. Methods Among 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. Results Eighty-five of 173 variants were associated with at least one tumor feature (false discovery rate

Published
2022
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20. Rare germline copy number variants (CNVs) and breast cancer risk

Author

Joe Dennis, Jonathan P. Tyrer, Logan C. Walker, Kyriaki Michailidou, Leila Dorling, Manjeet K. Bolla, Qin Wang, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Natalia N. Antonenkova, Volker Arndt, Kristan J. Aronson, Laura E. Beane Freeman, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Natalia V. Bogdanova, Stig E. Bojesen, Hermann Brenner, Jose E. Castelao, Jenny Chang-Claude, Georgia Chenevix-Trench, Christine L. Clarke, NBCS Collaborators, J. Margriet Collée, CTS Consortium, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Peter Devilee, Thilo Dörk, Laure Dossus, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Marike Gabrielson, Manuela Gago-Dominguez, Montserrat García-Closas, Graham G. Giles, Anna González-Neira, Pascal Guénel, Eric Hahnen, Christopher A. Haiman, Per Hall, Antoinette Hollestelle, Reiner Hoppe, John L. Hopper, Anthony Howell, ABCTB Investigators, kConFab/AOCS Investigators, Agnes Jager, Anna Jakubowska, Esther M. John, Nichola Johnson, Michael E. Jones, Audrey Jung, Rudolf Kaaks, Renske Keeman, Elza Khusnutdinova, Cari M. Kitahara, Yon-Dschun Ko, Veli-Matti Kosma, Stella Koutros, Peter Kraft, Vessela N. Kristensen, Katerina Kubelka-Sabit, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Nicole L. Larson, Martha Linet, Alicja Ogrodniczak, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, Dimitrios Mavroudis, Roger L. Milne, Taru A. Muranen, Rachel A. Murphy, Heli Nevanlinna, Janet E. Olson, Håkan Olsson, Tjoung-Won Park-Simon, Charles M. Perou, Paolo Peterlongo, Dijana Plaseska-Karanfilska, Katri Pylkäs, Gad Rennert, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Marjanka K. Schmidt, Rita K. Schmutzler, Rana Shibli, Ann Smeets, Penny Soucy, Melissa C. Southey, Anthony J. Swerdlow, Rulla M. Tamimi, Jack A. Taylor, Lauren R. Teras, Mary Beth Terry, Ian Tomlinson, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Camilla Wendt, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Wei Zheng, Argyrios Ziogas, Jacques Simard, Alison M. Dunning, Paul D. P. Pharoah, and Douglas F. Easton

Subjects
Biology (General), QH301-705.5
Abstract

Dennis et al. investigate potential breast cancer associations with rare germline copy number variants (CNVs) by conducting a genome-wide analysis in a large breast cancer case-control dataset. The authors detected associations with exonic deletions in established breast cancer susceptibility genes and suggestive associations for a number of non-coding CNVs.

Published
2022
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21. Wildfire-related PM2.5 and DNA methylation: An Australian twin and family study

Author

Rongbin Xu, Shanshan Li, Yao Wu, Xu Yue, Ee Ming Wong, Melissa C. Southey, John L. Hopper, Michael J. Abramson, Shuai Li, and Yuming Guo

Subjects
PM2.5, Wildfire smoke, DNA methylation, Epigenome-wide association study, Twin and family study, Environmental sciences, GE1-350
Abstract

Background: Wildfire-related fine particulate matter (PM2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM2.5. Methods: We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant’s home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. Results: The 3-year average wildfire-related PM2.5 (range: 0.3 to 7.6 µg/m3, mean: 1.6 µg/m3) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM2.5 (Bonferroni adjusted p-value

Published
2023
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22. Epigenome-wide association study of short-term temperature fluctuations based on within-sibship analyses in Australian females

Author

Yao Wu, Rongbin Xu, Shanshan Li, Ee Ming Wong, Melissa C. Southey, John L. Hopper, Michael J. Abramson, Shuai Li, and Yuming Guo

Subjects
DNA methylation, Temperature variability, Diurnal temperature range, Temperature change between neighbouring days, Twin and family study, Environmental sciences, GE1-350
Abstract

Background: Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation. Methods: Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant’s home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0–1 to TV 0–7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied. Results: Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0–3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0–3). Conclusions: Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.

Published
2023
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23. Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing

Author

Melissa C. Southey, James G. Dowty, Moeen Riaz, Jason A. Steen, Anne-Laure Renault, Katherine Tucker, Judy Kirk, Paul James, Ingrid Winship, Nicholas Pachter, Nicola Poplawski, Scott Grist, Daniel J. Park, Bernard J. Pope, Khalid Mahmood, Fleur Hammet, Maryam Mahmoodi, Helen Tsimiklis, Derrick Theys, Amanda Rewse, Amanda Willis, April Morrow, Catherine Speechly, Rebecca Harris, Robert Sebra, Eric Schadt, Paul Lacaze, John J. McNeil, Graham G. Giles, Roger L. Milne, John L. Hopper, and Tú Nguyen-Dumont

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing are urgently required. Most prior research has been based on women selected for high-risk features and more data is needed to make inference about breast cancer risk for women unselected for family history, an important consideration of population screening. We tested 1464 women diagnosed with breast cancer and 862 age-matched controls participating in the Australian Breast Cancer Family Study (ABCFS), and 6549 healthy, older Australian women enroled in the ASPirin in Reducing Events in the Elderly (ASPREE) study for rare germline variants using a 24-gene-panel. Odds ratios (ORs) were estimated using unconditional logistic regression adjusted for age and other potential confounders. We identified pathogenic variants in 11.1% of the ABCFS cases, 3.7% of the ABCFS controls and 2.2% of the ASPREE (control) participants. The estimated breast cancer OR [95% confidence interval] was 5.3 [2.1–16.2] for BRCA1, 4.0 [1.9–9.1] for BRCA2, 3.4 [1.4–8.4] for ATM and 4.3 [1.0–17.0] for PALB2. Our findings provide a population-based perspective to gene-panel testing for breast cancer predisposition and opportunities to improve predictors for identifying women who carry pathogenic variants in breast cancer predisposition genes.

Published
2021
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24. Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay

Author

Chenglong Yu, Pierre-Antoine Dugué, James G. Dowty, Fleur Hammet, JiHoon E. Joo, Ee Ming Wong, Mahnaz Hosseinpour, Graham G. Giles, John L. Hopper, Tu Nguyen-Dumont, Robert J. MacInnis, and Melissa C. Southey

Subjects
DNA methylation, Whole blood, Formalin-fixed paraffin-embedded, Illumina Infinium methylation arrays, Targeted bisulphite sequencing, Intraclass correlation coefficient, Medicine, Biology (General), QH301-705.5, Science (General), Q1-390
Abstract

Abstract Objective In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE). Results The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62–0.81), 0.59 (0.47–0.71) and 0.80 (0.73–0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39–0.68), 0.43 (0.31–0.56) and 0.70 (0.59–0.80), respectively. Bland–Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined.

Published
2021
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25. Germline variants and breast cancer survival in patients with distant metastases at primary breast cancer diagnosis

Author

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

Subjects
Medicine, Science
Abstract

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
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26. 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

Anna Morra, Maria Escala-Garcia, Jonathan Beesley, Renske Keeman, Sander Canisius, Thomas U. Ahearn, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Paul L. Auer, Annelie Augustinsson, Laura E. Beane Freeman, Heiko Becher, Matthias W. Beckmann, Sabine Behrens, Stig E. Bojesen, Manjeet K. Bolla, Hermann Brenner, Thomas Brüning, Saundra S. Buys, Bette Caan, Daniele Campa, Federico Canzian, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Ting-Yuan David Cheng, Christine L. Clarke, NBCS Collaborators, Sarah V. Colonna, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Joe Dennis, Thilo Dörk, Laure Dossus, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Arif B. Ekici, A. Heather Eliassen, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Henrik Flyger, Lin Fritschi, Manuela Gago-Dominguez, José A. García-Sáenz, Graham G. Giles, Mervi Grip, Pascal Guénel, Melanie Gündert, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Steven N. Hart, Jaana M. Hartikainen, Arndt Hartmann, Wei He, Maartje J. Hooning, Reiner Hoppe, John L. Hopper, Anthony Howell, David J. Hunter, ABCTB Investigators, kConFab Investigators, Agnes Jager, Anna Jakubowska, Wolfgang Janni, Esther M. John, Audrey Y. Jung, Rudolf Kaaks, Machteld Keupers, Cari M. Kitahara, Stella Koutros, Peter Kraft, Vessela N. Kristensen, Allison W. Kurian, James V. Lacey, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Martha Linet, Robert N. Luben, Jan Lubiński, Michael Lush, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, John W. M. Martens, Maria Elena Martinez, Dimitrios Mavroudis, Kyriaki Michailidou, Roger L. Milne, Anna Marie Mulligan, Taru A. Muranen, Heli Nevanlinna, William G. Newman, Sune F. Nielsen, Børge G. Nordestgaard, Andrew F. Olshan, Håkan Olsson, Nick Orr, Tjoung-Won Park-Simon, Alpa V. Patel, Bernard Peissel, Paolo Peterlongo, Dijana Plaseska-Karanfilska, Karolina Prajzendanc, Ross Prentice, Nadege Presneau, Brigitte Rack, Gad Rennert, Hedy S. Rennert, Valerie Rhenius, Atocha Romero, Rebecca Roylance, Matthias Ruebner, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Andreas Schneeweiss, Christopher Scott, Mitul Shah, Snezhana Smichkoska, Melissa C. Southey, Jennifer Stone, Harald Surowy, Anthony J. Swerdlow, Rulla M. Tamimi, William J. Tapper, Lauren R. Teras, Mary Beth Terry, Rob A. E. M. Tollenaar, Ian Tomlinson, Melissa A. Troester, Thérèse Truong, Celine M. Vachon, Qin Wang, Amber N. Hurson, Robert Winqvist, Alicja Wolk, Argyrios Ziogas, Hiltrud Brauch, Montserrat García-Closas, Paul D. P. Pharoah, Douglas F. Easton, Georgia Chenevix-Trench, and Marjanka K. Schmidt

Subjects
Common germline genetic variants, Breast cancer-specific survival, Patient subgroups, Tumor biology, Systemic treatment, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Given 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. Methods We 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
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27. Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging

Author

Daniel L. McCartney, Josine L. Min, Rebecca C. Richmond, Ake T. Lu, Maria K. Sobczyk, Gail Davies, Linda Broer, Xiuqing Guo, Ayoung Jeong, Jeesun Jung, Silva Kasela, Seyma Katrinli, Pei-Lun Kuo, Pamela R. Matias-Garcia, Pashupati P. Mishra, Marianne Nygaard, Teemu Palviainen, Amit Patki, Laura M. Raffield, Scott M. Ratliff, Tom G. Richardson, Oliver Robinson, Mette Soerensen, Dianjianyi Sun, Pei-Chien Tsai, Matthijs D. van der Zee, Rosie M. Walker, Xiaochuan Wang, Yunzhang Wang, Rui Xia, Zongli Xu, Jie Yao, Wei Zhao, Adolfo Correa, Eric Boerwinkle, Pierre-Antoine Dugué, Peter Durda, Hannah R. Elliott, Christian Gieger, The Genetics of DNA Methylation Consortium, Eco J. C. de Geus, Sarah E. Harris, Gibran Hemani, Medea Imboden, Mika Kähönen, Sharon L. R. Kardia, Jacob K. Kresovich, Shengxu Li, Kathryn L. Lunetta, Massimo Mangino, Dan Mason, Andrew M. McIntosh, Jonas Mengel-From, Ann Zenobia Moore, Joanne M. Murabito, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Miina Ollikainen, James S. Pankow, Nancy L. Pedersen, Annette Peters, Silvia Polidoro, David J. Porteous, Olli Raitakari, Stephen S. Rich, Dale P. Sandler, Elina Sillanpää, Alicia K. Smith, Melissa C. Southey, Konstantin Strauch, Hemant Tiwari, Toshiko Tanaka, Therese Tillin, Andre G. Uitterlinden, David J. Van Den Berg, Jenny van Dongen, James G. Wilson, John Wright, Idil Yet, Donna Arnett, Stefania Bandinelli, Jordana T. Bell, Alexandra M. Binder, Dorret I. Boomsma, Wei Chen, Kaare Christensen, Karen N. Conneely, Paul Elliott, Luigi Ferrucci, Myriam Fornage, Sara Hägg, Caroline Hayward, Marguerite Irvin, Jaakko Kaprio, Deborah A. Lawlor, Terho Lehtimäki, Falk W. Lohoff, Lili Milani, Roger L. Milne, Nicole Probst-Hensch, Alex P. Reiner, Beate Ritz, Jerome I. Rotter, Jennifer A. Smith, Jack A. Taylor, Joyce B. J. van Meurs, Paolo Vineis, Melanie Waldenberger, Ian J. Deary, Caroline L. Relton, Steve Horvath, and Riccardo E. Marioni

Subjects
DNA methylation, GWAS, Epigenetic clock, Biology (General), QH301-705.5, Genetics, QH426-470
Abstract

Abstract Background Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. Results Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. Conclusion This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.

Published
2021
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28. Evaluation of the association of heterozygous germline variants in NTHL1 with breast cancer predisposition: an international multi-center study of 47,180 subjects

Author

Na Li, Magnus Zethoven, Simone McInerny, Lisa Devereux, Yu-Kuan Huang, Niko Thio, Dane Cheasley, Sara Gutiérrez-Enríquez, Alejandro Moles-Fernández, Orland Diez, Tu Nguyen-Dumont, Melissa C. Southey, John L. Hopper, Jacques Simard, Martine Dumont, Penny Soucy, Alfons Meindl, Rita Schmutzler, Marjanka K. Schmidt, Muriel A. Adank, Irene L. Andrulis, Eric Hahnen, Christoph Engel, Fabienne Lesueur, Elodie Girard, Susan L. Neuhausen, Elad Ziv, Jamie Allen, Douglas F. Easton, Rodney J. Scott, Kylie L. Gorringe, Paul A. James, and Ian G. Campbell

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Bi-allelic loss-of-function (LoF) variants in the base excision repair (BER) gene NTHL1 cause a high-risk hereditary multi-tumor syndrome that includes breast cancer, but the contribution of heterozygous variants to hereditary breast cancer is unknown. An analysis of 4985 women with breast cancer, enriched for familial features, and 4786 cancer-free women revealed significant enrichment for NTHL1 LoF variants. Immunohistochemistry confirmed reduced NTHL1 expression in tumors from heterozygous carriers but the NTHL1 bi-allelic loss characteristic mutational signature (SBS 30) was not present. The analysis was extended to 27,421 breast cancer cases and 19,759 controls from 10 international studies revealing 138 cases and 93 controls with a heterozygous LoF variant (OR 1.06, 95% CI: 0.82–1.39) and 316 cases and 179 controls with a missense variant (OR 1.31, 95% CI: 1.09–1.57). Missense variants selected for deleterious features by a number of in silico bioinformatic prediction tools or located within the endonuclease III functional domain showed a stronger association with breast cancer. Somatic sequencing of breast cancers from carriers indicated that the risk associated with NTHL1 appears to operate through haploinsufficiency, consistent with other described low-penetrance breast cancer genes. Data from this very large international multicenter study suggests that heterozygous pathogenic germline coding variants in NTHL1 may be associated with low- to moderate- increased risk of breast cancer.

Published
2021
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29. A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers

Author

Juliette Coignard, Michael Lush, Jonathan Beesley, Tracy A. O’Mara, Joe Dennis, Jonathan P. Tyrer, Daniel R. Barnes, Lesley McGuffog, Goska Leslie, Manjeet K. Bolla, Muriel A. Adank, Simona Agata, Thomas Ahearn, Kristiina Aittomäki, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Norbert Arnold, Kristan J. Aronson, Banu K. Arun, Annelie Augustinsson, Jacopo Azzollini, Daniel Barrowdale, Caroline Baynes, Heko Becher, Marina Bermisheva, Leslie Bernstein, Katarzyna Białkowska, Carl Blomqvist, Stig E. Bojesen, Bernardo Bonanni, Ake Borg, Hiltrud Brauch, Hermann Brenner, Barbara Burwinkel, Saundra S. Buys, Trinidad Caldés, Maria A. Caligo, Daniele Campa, Brian D. Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Wendy K. Chung, Kathleen B. M. Claes, Christine L. Clarke, GEMO Study Collaborators, EMBRACE Collaborators, J. Margriet Collée, Don M. Conroy, Kamila Czene, Mary B. Daly, Peter Devilee, Orland Diez, Yuan Chun Ding, Susan M. Domchek, Thilo Dörk, Isabel dos-Santos-Silva, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, A. Heather Eliassen, Christoph Engel, Mikael Eriksson, D. Gareth Evans, Peter A. Fasching, Henrik Flyger, Florentia Fostira, Eitan Friedman, Lin Fritschi, Debra Frost, Manuela Gago-Dominguez, Susan M. Gapstur, Judy Garber, Vanesa Garcia-Barberan, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Simon A. Gayther, Andrea Gehrig, Vassilios Georgoulias, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Mark H. Greene, Pascal Guénel, Lothar Haeberle, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Per Hall, Ute Hamann, Patricia A. Harrington, Steven N. Hart, Wei He, Frans B. L. Hogervorst, Antoinette Hollestelle, John L. Hopper, Darling J. Horcasitas, Peter J. Hulick, David J. Hunter, Evgeny N. Imyanitov, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Agnes Jager, Anna Jakubowska, Paul A. James, Uffe Birk Jensen, Esther M. John, Michael E. Jones, Rudolf Kaaks, Pooja Middha Kapoor, Beth Y. Karlan, Renske Keeman, Elza Khusnutdinova, Johanna I. Kiiski, Yon-Dschun Ko, Veli-Matti Kosma, Peter Kraft, Allison W. Kurian, Yael Laitman, Diether Lambrechts, Loic Le Marchand, Jenny Lester, Fabienne Lesueur, Tricia Lindstrom, Adria Lopez-Fernández, Jennifer T. Loud, Craig Luccarini, Arto Mannermaa, Siranoush Manoukian, Sara Margolin, John W. M. Martens, Noura Mebirouk, Alfons Meindl, Austin Miller, Roger L. Milne, Marco Montagna, Katherine L. Nathanson, Susan L. Neuhausen, Heli Nevanlinna, Finn C. Nielsen, Katie M. O’Brien, Olufunmilayo I. Olopade, Janet E. Olson, Håkan Olsson, Ana Osorio, Laura Ottini, Tjoung-Won Park-Simon, Michael T. Parsons, Inge Sokilde Pedersen, Beth Peshkin, Paolo Peterlongo, Julian Peto, Paul D. P. Pharoah, Kelly-Anne Phillips, Eric C. Polley, Bruce Poppe, Nadege Presneau, Miquel Angel Pujana, Kevin Punie, Paolo Radice, Johanna Rantala, Muhammad U. Rashid, Gad Rennert, Hedy S. Rennert, Mark Robson, Atocha Romero, Maria Rossing, Emmanouil Saloustros, Dale P. Sandler, Regina Santella, Maren T. Scheuner, Marjanka K. Schmidt, Gunnar Schmidt, Christopher Scott, Priyanka Sharma, Penny Soucy, Melissa C. Southey, John J. Spinelli, Zoe Steinsnyder, Jennifer Stone, Dominique Stoppa-Lyonnet, Anthony Swerdlow, Rulla M. Tamimi, William J. Tapper, Jack A. Taylor, Mary Beth Terry, Alex Teulé, Darcy L. Thull, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Alison H. Trainer, Thérèse Truong, Nadine Tung, Celine M. Vachon, Ana Vega, Joseph Vijai, Qin Wang, Barbara Wappenschmidt, Clarice R. Weinberg, Jeffrey N. Weitzel, Camilla Wendt, Alicja Wolk, Siddhartha Yadav, Xiaohong R. Yang, Drakoulis Yannoukakos, Wei Zheng, Argyrios Ziogas, Kristin K. Zorn, Sue K. Park, Mads Thomassen, Kenneth Offit, Rita K. Schmutzler, Fergus J. Couch, Jacques Simard, Georgia Chenevix-Trench, Douglas F. Easton, Nadine Andrieu, and Antonis C. Antoniou

Subjects
Science
Abstract

Breast cancer risk for BRCA1/BRCA2 mutation carriers varies depending on other genetic factors. Here, the authors perform a case-only genome-wide association study and highlight novel loci associated with breast cancer risk for BRCA1/BRCA2 mutation carriers.

Published
2021
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30. Correction: PredictCBC-2.0: a contralateral breast cancer risk prediction model developed and validated in ~ 200,000 patients

Author

Daniele Giardiello, Maartje J. Hooning, Michael Hauptmann, Renske Keeman, B. A. M. Heemskerk-Gerritsen, Heiko Becher, Carl Blomqvist, Stig E. Bojesen, Manjeet K. Bolla, Nicola J. Camp, Kamila Czene, Peter Devilee, Diana M. Eccles, Peter A. Fasching, Jonine D. Figueroa, Henrik Flyger, Montserrat García-Closas, Christopher A. Haiman, Ute Hamann, John L. Hopper, Anna Jakubowska, Floor E. Leeuwen, Annika Lindblom, Jan Lubiński, Sara Margolin, Maria Elena Martinez, Heli Nevanlinna, Ines Nevelsteen, Saskia Pelders, Paul D. P. Pharoah, Sabine Siesling, Melissa C. Southey, Annemieke H. van der Hout, Liselotte P. van Hest, Jenny Chang-Claude, Per Hall, Douglas F. Easton, Ewout W. Steyerberg, and Marjanka K. Schmidt

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Published
2022
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31. Analytical validation of an error-corrected ultra-sensitive ctDNA next-generation sequencing assay

Author

Heidi Fettke, Jason A Steen, Edmond M Kwan, Patricia Bukczynska, Shivakumar Keerthikumar, David Goode, Maria Docanto, Nicole Ng, Luciano Martelotto, Christine Hauser, Melissa C Southey, Arun A Azad, and Tu Nguyen-Dumont

Subjects
cell-free DNA, cfDNA, circulating tumor DNA, ctDNA, liquid biopsy, molecular barcoding, Biology (General), QH301-705.5
Abstract

Plasma circulating tumor DNA (ctDNA) analysis has emerged as a minimally invasive means to perform molecular tumor typing. Here we developed a custom ultra-sensitive ctDNA next-generation sequencing assay using molecular barcoding technology and off-the-shelf reagents combined with bioinformatics tools for enhanced ctDNA analysis. Assay performance was assessed via a spike-in experiment and the technique was applied to analyze 41 plasma samples from men with advanced prostate cancer. Orthogonal validation was performed using a commercial assay. Sensitivity and specificity of 93 and 99.5% were recorded for ultra-rare somatic variants (

Published
2020
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32. Smoking and blood DNA methylation: an epigenome-wide association study and assessment of reversibility

Author

Pierre-Antoine Dugué, Chol-Hee Jung, Jihoon E Joo, Xiaochuan Wang, Ee Ming Wong, Enes Makalic, Daniel F Schmidt, Laura Baglietto, Gianluca Severi, Melissa C Southey, Dallas R English, Graham G Giles, and Roger L Milne

Subjects
epigenome-wide association study, dna methylation, smoking, blood, reversibility, replication, Genetics, QH426-470
Abstract

We conducted a genome-wide association study of blood DNA methylation and smoking, attempted replication of previously discovered associations, and assessed the reversibility of smoking-associated methylation changes. DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study. For 1,032 participants, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. A cross-sectional analysis of the association between smoking and DNA methylation and a longitudinal analysis of changes in smoking status and changes in DNA methylation were conducted. We used our cross-sectional analysis to replicate previously reported associations for current (N = 3,327) and former (N = 172) smoking. A comprehensive smoking index accounting for the biological half-life of smoking compounds and several aspects of smoking history was constructed to assess the reversibility of smoking-induced methylation changes. This measure of lifetime exposure to smoking allowed us to detect more associations than comparing current with never smokers. We identified 4,496 cross-sectional associations at P

Published
2020
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33. A network analysis to identify mediators of germline-driven differences in breast cancer prognosis

Author

Maria Escala-Garcia, Jean Abraham, Irene L. Andrulis, Hoda Anton-Culver, Volker Arndt, Alan Ashworth, Paul L. Auer, Päivi Auvinen, Matthias W. Beckmann, Jonathan Beesley, Sabine Behrens, Javier Benitez, Marina Bermisheva, Carl Blomqvist, William Blot, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Anne-Lise Børresen-Dale, Hiltrud Brauch, Hermann Brenner, Sara Y. Brucker, Barbara Burwinkel, Carlos Caldas, Federico Canzian, Jenny Chang-Claude, Stephen J. Chanock, Suet-Feung Chin, Christine L. Clarke, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Joe Dennis, Peter Devilee, Janet A. Dunn, Alison M. Dunning, Miriam Dwek, Helena M. Earl, Diana M. Eccles, A. Heather Eliassen, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Jonine Figueroa, Henrik Flyger, Manuela Gago-Dominguez, Susan M. Gapstur, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Angela George, Graham G. Giles, David E. Goldgar, Anna González-Neira, Mervi Grip, Pascal Guénel, Qi Guo, Christopher A. Haiman, Niclas Håkansson, Ute Hamann, Patricia A. Harrington, Louise Hiller, Maartje J. Hooning, John L. Hopper, Anthony Howell, Chiun-Sheng Huang, Guanmengqian Huang, David J. Hunter, Anna Jakubowska, Esther M. John, Rudolf Kaaks, Pooja Middha Kapoor, Renske Keeman, Cari M. Kitahara, Linetta B. Koppert, Peter Kraft, Vessela N. Kristensen, Diether Lambrechts, Loic Le Marchand, Flavio Lejbkowicz, Annika Lindblom, Jan Lubiński, Arto Mannermaa, Mehdi Manoochehri, Siranoush Manoukian, Sara Margolin, Maria Elena Martinez, Tabea Maurer, Dimitrios Mavroudis, Alfons Meindl, Roger L. Milne, Anna Marie Mulligan, Susan L. Neuhausen, Heli Nevanlinna, William G. Newman, Andrew F. Olshan, Janet E. Olson, Håkan Olsson, Nick Orr, Paolo Peterlongo, Christos Petridis, Ross L. Prentice, Nadege Presneau, Kevin Punie, Dhanya Ramachandran, Gad Rennert, Atocha Romero, Mythily Sachchithananthan, Emmanouil Saloustros, Elinor J. Sawyer, Rita K. Schmutzler, Lukas Schwentner, Christopher Scott, Jacques Simard, Christof Sohn, Melissa C. Southey, Anthony J. Swerdlow, Rulla M. Tamimi, William J. Tapper, Manuel R. Teixeira, Mary Beth Terry, Heather Thorne, Rob A. E. M. Tollenaar, Ian Tomlinson, Melissa A. Troester, Thérèse Truong, Clare Turnbull, Celine M. Vachon, Lizet E. van der Kolk, Qin Wang, Robert Winqvist, Alicja Wolk, Xiaohong R. Yang, Argyrios Ziogas, Paul D. P. Pharoah, Per Hall, Lodewyk F. A. Wessels, Georgia Chenevix-Trench, Gary D. Bader, Thilo Dörk, Douglas F. Easton, Sander Canisius, and Marjanka K. Schmidt

Subjects
Science
Abstract

In breast cancer the contribution of different genetic variants to disease heritability is complex and not fully understood. Here, the authors present a network-based analysis in 84,567 patients studying ~7.3 million variants, identifying gene modules associated with breast cancer survival.

Published
2020
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34. Early life affects late-life health through determining DNA methylation across the lifespan: A twin study

Author

Shuai Li, Zhoufeng Ye, Karen A. Mather, Tuong L. Nguyen, Gillian S. Dite, Nicola J. Armstrong, Ee Ming Wong, Anbupalam Thalamuthu, Graham G. Giles, Jeffrey M. Craig, Richard Saffery, Melissa C. Southey, Qihua Tan, Perminder S. Sachdev, and John L. Hopper

Subjects
DNA methylation, Twin study, DOHaD hypothesis, Heritability, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: Previous findings for the genetic and environmental contributions to DNA methylation variation were for limited age ranges only. We investigated the lifespan contributions and their implications for human health for the first time. Methods: 1,720 monozygotic twin (MZ) pairs and 1,107 dizygotic twin (DZ) pairs aged 0-92 years were included. Familial correlations (i.e., correlations between twins) for 353,681 methylation sites were estimated and modelled as a function of twin pair cohabitation history. Findings: The methylome average familial correlation was around zero at birth (MZ pair: -0.01; DZ pair: -0.04), increased with the time of twins living together during childhood at rates of 0.16 (95%CI: 0.12-0.20) for MZ pairs and 0.13 (95%CI: 0.07-0.20) for DZ pairs per decade, and decreased with the time of living apart during adulthood at rates of 0.026 (95%CI: 0.019-0.033) for MZ pairs and 0.027 (95%CI: 0.011-0.043) for DZ pairs per decade. Neither the increasing nor decreasing rate differed by zygosity (both P>0.1), consistent with cohabitation environment shared by twins, rather than genetic factors, influencing the methylation familial correlation changes. Familial correlations for 6.6% (23,386/353,681) sites changed with twin pair cohabitation history. These sites were enriched for high heritability, proximal promoters, and epigenetic/genetic associations with various early-life factors and late-life health conditions. Interpretation: Early life strongly influences DNA methylation variation across the lifespan, and the effects are stronger for heritable sites and sites biologically relevant to the regulation of gene expression. Early life could affect late-life health through influencing DNA methylation. Funding: Victorian Cancer Agency, Cancer Australia, Cure Cancer Foundation.

Published
2022
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35. Residential surrounding greenness and DNA methylation: An epigenome-wide association study

Author

Rongbin Xu, Shuai Li, Shanshan Li, Ee Ming Wong, Melissa C. Southey, John L. Hopper, Michael J. Abramson, and Yuming Guo

Subjects
Greenness, Epigenetics, DNA methylation, Gene-environment interaction, Epigenome-wide association study, Environmental sciences, GE1-350
Abstract

Background: DNA methylation is a potential biological mechanism through which residential greenness affects health, but little is known about its association with greenness and whether the association could be modified by genetic background. We aimed to evaluate the association between surrounding greenness and genome-wide DNA methylation and potential gene-greenness interaction effects on DNA methylation. Methods: We measured blood-derived DNA methylation using the HumanMethylation450 BeadChip array (Illumina) for 479 Australian women, including 66 monozygotic, 66 dizygotic twin pairs, and 215 sisters of these twins. Surrounding greenness was represented by Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) within 300, 500, 1000 or 2000 m surrounding participants’ home addresses. For each cytosine-guanine dinucleotide (CpG), the associations between its methylation level and NDVI or EVI were evaluated by generalized estimating equations, after adjusting for age, education, marital status, area-level socioeconomic status, smoking behavior, cell-type proportions, and familial clustering. We used comb-p and DMRcate to identify significant differentially methylated regions (DMRs). For each significant CpG, we evaluated the interaction effects of greenness and single-nucleotide polymorphisms (SNPs) within ±1 Mb window on its methylation level. Results: We found associations between surrounding greenness and blood DNA methylation for one CpG (cg04720477, mapped to the promoter region of CNP gene) with false discovery rate [FDR]

Published
2021
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36. Androgens alter the heterogeneity of small extracellular vesicles and the small RNA cargo in prostate cancer

Author

Elena S. Martens‐Uzunova, Gina D. Kusuma, Stefania Crucitta, Hong Kiat Lim, Crystal Cooper, James E. Riches, Arun Azad, Takahiro Ochiya, Glen M. Boyle, Melissa C. Southey, Marzia Del Re, Rebecca Lim, Grant A. Ramm, Guido W. Jenster, and Carolina Soekmadji

Subjects
androgen, androgen receptor, enzalutamide, exosomes, extracellular RNA, extracellular vesicles, Cytology, QH573-671
Abstract

Abstract Proliferation and survival of prostate cancer cells are driven by the androgen receptor (AR) upon binding to androgen steroid hormones. Manipulating the AR signalling axis is the focus for prostate cancer therapy; thus, it is crucial to understand the role of androgens and AR on extracellular vesicle (EV) secretion and cargo. In this study, we report that plasma‐derived circulating vesicles consisting of CD9 and double‐positive for CD9 and Prostate Specific Membrane Antigen (PSMA) are increased in patients with advanced metastatic prostate cancer, whereas double positives for CD9 and CD63 small extracellular vesicles (S‐EVs) are significantly higher in patients with localised prostate cancer. Androgen manipulation by dihydrotestosterone (DHT) and the clinical antagonist enzalutamide (ENZ) altered the heterogeneity and size of CD9 positive S‐EVs in AR expressing prostate cancer cells, while assessment of the total number and protein cargo of total S‐EVs was unaltered across different treatment groups. Furthermore, hormone stimulation caused strong and specific effects on the small RNA cargo of S‐EVs. A total of 543 small RNAs were found to be regulated by androgens including miR‐19‐3p and miR‐361‐5p. Analysis of S‐EVs heterogeneity and small RNA cargo may provide clinical utility for prostate cancer and be informative to understand further the mechanism of resistance to androgen targeted therapy in castration‐resistant prostate cancer.

Published
2021
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37. Prediction and clinical utility of a contralateral breast cancer risk model

Author

Daniele Giardiello, Ewout W. Steyerberg, Michael Hauptmann, Muriel A. Adank, Delal Akdeniz, Carl Blomqvist, Stig E. Bojesen, Manjeet K. Bolla, Mariël Brinkhuis, Jenny Chang-Claude, Kamila Czene, Peter Devilee, Alison M. Dunning, Douglas F. Easton, Diana M. Eccles, Peter A. Fasching, Jonine Figueroa, Henrik Flyger, Montserrat García-Closas, Lothar Haeberle, Christopher A. Haiman, Per Hall, Ute Hamann, John L. Hopper, Agnes Jager, Anna Jakubowska, Audrey Jung, Renske Keeman, Iris Kramer, Diether Lambrechts, Loic Le Marchand, Annika Lindblom, Jan Lubiński, Mehdi Manoochehri, Luigi Mariani, Heli Nevanlinna, Hester S. A. Oldenburg, Saskia Pelders, Paul D. P. Pharoah, Mitul Shah, Sabine Siesling, Vincent T. H. B. M. Smit, Melissa C. Southey, William J. Tapper, Rob A. E. M. Tollenaar, Alexandra J. van den Broek, Carolien H. M. van Deurzen, Flora E. van Leeuwen, Chantal van Ongeval, Laura J. Van’t Veer, Qin Wang, Camilla Wendt, Pieter J. Westenend, Maartje J. Hooning, and Marjanka K. Schmidt

Subjects
Contralateral breast cancer, Risk prediction model, Clinical decision-making, BRCA mutation carriers, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Breast cancer survivors are at risk for contralateral breast cancer (CBC), with the consequent burden of further treatment and potentially less favorable prognosis. We aimed to develop and validate a CBC risk prediction model and evaluate its applicability for clinical decision-making. Methods We included data of 132,756 invasive non-metastatic breast cancer patients from 20 studies with 4682 CBC events and a median follow-up of 8.8 years. We developed a multivariable Fine and Gray prediction model (PredictCBC-1A) including patient, primary tumor, and treatment characteristics and BRCA1/2 germline mutation status, accounting for the competing risks of death and distant metastasis. We also developed a model without BRCA1/2 mutation status (PredictCBC-1B) since this information was available for only 6% of patients and is routinely unavailable in the general breast cancer population. Prediction performance was evaluated using calibration and discrimination, calculated by a time-dependent area under the curve (AUC) at 5 and 10 years after diagnosis of primary breast cancer, and an internal-external cross-validation procedure. Decision curve analysis was performed to evaluate the net benefit of the model to quantify clinical utility. Results In the multivariable model, BRCA1/2 germline mutation status, family history, and systemic adjuvant treatment showed the strongest associations with CBC risk. The AUC of PredictCBC-1A was 0.63 (95% prediction interval (PI) at 5 years, 0.52–0.74; at 10 years, 0.53–0.72). Calibration-in-the-large was -0.13 (95% PI: -1.62–1.37), and the calibration slope was 0.90 (95% PI: 0.73–1.08). The AUC of Predict-1B at 10 years was 0.59 (95% PI: 0.52–0.66); calibration was slightly lower. Decision curve analysis for preventive contralateral mastectomy showed potential clinical utility of PredictCBC-1A between thresholds of 4–10% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers. Conclusions We developed a reasonably calibrated model to predict the risk of CBC in women of European-descent; however, prediction accuracy was moderate. Our model shows potential for improved risk counseling, but decision-making regarding contralateral preventive mastectomy, especially in the general breast cancer population where limited information of the mutation status in BRCA1/2 is available, remains challenging.

Published
2019
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38. Alcohol consumption, cigarette smoking, and familial breast cancer risk: findings from the Prospective Family Study Cohort (ProF-SC)

Author

Nur Zeinomar, Julia A. Knight, Jeanine M. Genkinger, Kelly-Anne Phillips, Mary B. Daly, Roger L. Milne, Gillian S. Dite, Rebecca D. Kehm, Yuyan Liao, Melissa C. Southey, Wendy K. Chung, Graham G. Giles, Sue-Anne McLachlan, Michael L. Friedlander, Prue C. Weideman, Gord Glendon, Stephanie Nesci, kConFab Investigators, Irene L. Andrulis, Saundra S. Buys, Esther M. John, Robert J. MacInnis, John L. Hopper, and Mary Beth Terry

Subjects
Breast cancer, Alcohol consumption, Cigarette smoking, Familial risk, BOADICEA, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Alcohol consumption and cigarette smoking are associated with an increased risk of breast cancer (BC), but it is unclear whether these associations vary by a woman’s familial BC risk. Methods Using the Prospective Family Study Cohort, we evaluated associations between alcohol consumption, cigarette smoking, and BC risk. We used multivariable Cox proportional hazard models to estimate hazard ratios (HR) and 95% confidence intervals (CI). We examined whether associations were modified by familial risk profile (FRP), defined as the 1-year incidence of BC predicted by Breast Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), a pedigree-based algorithm. Results We observed 1009 incident BC cases in 17,435 women during a median follow-up of 10.4 years. We found no overall association of smoking or alcohol consumption with BC risk (current smokers compared with never smokers HR 1.02, 95% CI 0.85–1.23; consuming ≥ 7 drinks/week compared with non-regular drinkers HR 1.10, 95% CI 0.92–1.32), but we did observe differences in associations based on FRP and by estrogen receptor (ER) status. Women with lower FRP had an increased risk of ER-positive BC associated with consuming ≥ 7 drinks/week (compared to non-regular drinkers), whereas there was no association for women with higher FRP. For example, women at the 10th percentile of FRP (5-year BOADICEA = 0.15%) had an estimated HR of 1.46 (95% CI 1.07–1.99), whereas there was no association for women at the 90th percentile (5-year BOADICEA = 4.2%) (HR 1.07, 95% CI 0.80–1.44). While the associations with smoking were not modified by FRP, we observed a positive multiplicative interaction by FRP (p interaction = 0.01) for smoking status in women who also consumed alcohol, but not in women who were non-regular drinkers. Conclusions Moderate alcohol intake was associated with increased BC risk, particularly for women with ER-positive BC, but only for those at lower predicted familial BC risk (5-year BOADICEA

Published
2019
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39. Publisher Correction: Shared heritability and functional enrichment across six solid cancers

Author

Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R. Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H. M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström

Subjects
Science
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019
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40. Hi-Plex2: a simple and robust approach to targeted sequencing-based genetic screening

Author

Fleur Hammet, Khalid Mahmood, Thomas R Green, Tu Nguyen-Dumont, Melissa C Southey, Daniel D Buchanan, Andrew Lonie, Katherine L Nathanson, Fergus J Couch, Bernard J Pope, and Daniel J Park

Subjects
genetic screening, Hi-Plex, multiplex PCR, targeted DNA sequencing, variant detection, Biology (General), QH301-705.5
Abstract

We have previously reported Hi-Plex, a multiplex PCR methodology for building targeted DNA sequencing libraries that offers a low-cost protocol compatible with high-throughput processing. Here, we detail an improved protocol, Hi-Plex2, that more effectively enables the robust construction of small-to-medium panel-size libraries while maintaining low cost, simplicity and accuracy benefits of the Hi-Plex platform. Hi-Plex2 was applied to three panels, comprising 291, 740 and 1193 amplicons, targeting genes associated with risk for breast and/or colon cancer. We show substantial reduction of off-target amplification to enable library construction for small-to-medium-sized design panels not possible using the previous Hi-Plex chemistry.

Published
2019
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41. Blood DNA methylation and breast cancer risk: a meta-analysis of four prospective cohort studies

Author

Clara Bodelon, Srikant Ambatipudi, Pierre-Antoine Dugué, Annelie Johansson, Joshua N. Sampson, Belynda Hicks, Eric Karlins, Amy Hutchinson, Cyrille Cuenin, Veronique Chajès, Melissa C. Southey, Isabelle Romieu, Graham G. Giles, Dallas English, Silvia Polidoro, Manuela Assumma, Laura Baglietto, Paolo Vineis, Gianluca Severi, Zdenko Herceg, James M. Flanagan, Roger L. Milne, and Montserrat Garcia-Closas

Subjects
Breast cancer risk, Blood DNA methylation, Prospective study, Meta-analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Environmental and genetic factors play an important role in the etiology of breast cancer. Several small blood-based DNA methylation studies have reported risk associations with methylation at individual CpGs and average methylation levels; however, these findings require validation in larger prospective cohort studies. To investigate the role of blood DNA methylation on breast cancer risk, we conducted a meta-analysis of four prospective cohort studies, including a total of 1663 incident cases and 1885 controls, the largest study of blood DNA methylation and breast cancer risk to date. Methods We assessed associations with methylation at 365,145 CpGs present in the HumanMethylation450 (HM450K) Beadchip, after excluding CpGs that did not pass quality controls in all studies. Each of the four cohorts estimated odds ratios (ORs) and 95% confidence intervals (CI) for the association between each individual CpG and breast cancer risk. In addition, each study assessed the association between average methylation measures and breast cancer risk, adjusted and unadjusted for cell-type composition. Study-specific ORs were combined using fixed-effect meta-analysis with inverse variance weights. Stratified analyses were conducted by age at diagnosis ( 10 years). The false discovery rate (q value) was used to account for multiple testing. Results The average age at blood draw ranged from 52.2 to 62.2 years across the four cohorts. Median follow-up time ranged from 6.6 to 8.4 years. The methylation measured at individual CpGs was not associated with breast cancer risk (q value > 0.59). In addition, higher average methylation level was not associated with risk of breast cancer (OR = 0.94, 95% CI = 0.85, 1.05; P = 0.26; P for study heterogeneity = 0.86). We found no evidence of modification of this association by age at diagnosis (P = 0.17), ER status (P = 0.88), time since blood collection (P = 0.98), or CpG location (P = 0.98). Conclusions Our data indicate that DNA methylation measured in the blood prior to breast cancer diagnosis in predominantly postmenopausal women is unlikely to be associated with substantial breast cancer risk on the HM450K array. Larger studies or with greater methylation coverage are needed to determine if associations exist between blood DNA methylation and breast cancer risk.

Published
2019
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42. Joint association of mammographic density adjusted for age and body mass index and polygenic risk score with breast cancer risk

Author

Celine M. Vachon, Christopher G. Scott, Rulla M. Tamimi, Deborah J. Thompson, Peter A. Fasching, Jennifer Stone, Melissa C. Southey, Stacey Winham, Sara Lindström, Jenna Lilyquist, Graham G. Giles, Roger L. Milne, Robert J. MacInnis, Laura Baglietto, Jingmei Li, Kamila Czene, Manjeet K. Bolla, Qin Wang, Joe Dennis, Lothar Haeberle, Mikael Eriksson, Peter Kraft, Robert Luben, Nick Wareham, Janet E. Olson, Aaron Norman, Eric C. Polley, Gertraud Maskarinec, Loic Le Marchand, Christopher A. Haiman, John L. Hopper, Fergus J. Couch, Douglas F. Easton, Per Hall, Nilanjan Chatterjee, and Montse Garcia-Closas

Subjects
Breast density, Breast cancer risk, Polygenic risk score, Genetic variation, Risk models, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Mammographic breast density, adjusted for age and body mass index, and a polygenic risk score (PRS), comprised of common genetic variation, are both strong risk factors for breast cancer and increase discrimination of risk models. Understanding their joint contribution will be important to more accurately predict risk. Methods Using 3628 breast cancer cases and 5126 controls of European ancestry from eight case-control studies, we evaluated joint associations of a 77-single nucleotide polymorphism (SNP) PRS and quantitative mammographic density measures with breast cancer. Mammographic percent density and absolute dense area were evaluated using thresholding software and examined as residuals after adjusting for age, 1/BMI, and study. PRS and adjusted density phenotypes were modeled both continuously (per 1 standard deviation, SD) and categorically. We fit logistic regression models and tested the null hypothesis of multiplicative joint associations for PRS and adjusted density measures using likelihood ratio and global and tail-based goodness of fit tests within the subset of six cohort or population-based studies. Results Adjusted percent density (odds ratio (OR) = 1.45 per SD, 95% CI 1.38–1.52), adjusted absolute dense area (OR = 1.34 per SD, 95% CI 1.28–1.41), and the 77-SNP PRS (OR = 1.52 per SD, 95% CI 1.45–1.59) were associated with breast cancer risk. There was no evidence of interaction of the PRS with adjusted percent density or dense area on risk of breast cancer by either the likelihood ratio (P > 0.21) or goodness of fit tests (P > 0.09), whether assessed continuously or categorically. The joint association (OR) was 2.60 in the highest categories of adjusted PD and PRS and 0.34 in the lowest categories, relative to women in the second density quartile and middle PRS quintile. Conclusions The combined associations of the 77-SNP PRS and adjusted density measures are generally well described by multiplicative models, and both risk factors provide independent information on breast cancer risk.

Published
2019
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43. Regular use of aspirin and other non-steroidal anti-inflammatory drugs and breast cancer risk for women at familial or genetic risk: a cohort study

Author

Rebecca D. Kehm, John L. Hopper, Esther M. John, Kelly-Anne Phillips, Robert J. MacInnis, Gillian S. Dite, Roger L. Milne, Yuyan Liao, Nur Zeinomar, Julia A. Knight, Melissa C. Southey, Linda Vahdat, Naomi Kornhauser, Tessa Cigler, Wendy K. Chung, Graham G. Giles, Sue-Anne McLachlan, Michael L. Friedlander, Prue C. Weideman, Gord Glendon, Stephanie Nesci, kConFab Investigators, Irene L. Andrulis, Saundra S. Buys, Mary B. Daly, and Mary Beth Terry

Subjects
Breast cancer, Non-steroidal anti-inflammatory drugs, Family history, High-risk population, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background The use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) has been associated with reduced breast cancer risk, but it is not known if this association extends to women at familial or genetic risk. We examined the association between regular NSAID use and breast cancer risk using a large cohort of women selected for breast cancer family history, including 1054 BRCA1 or BRCA2 mutation carriers. Methods We analyzed a prospective cohort (N = 5606) and a larger combined, retrospective and prospective, cohort (N = 8233) of women who were aged 18 to 79 years, enrolled before June 30, 2011, with follow-up questionnaire data on medication history. The prospective cohort was further restricted to women without breast cancer when medication history was asked by questionnaire. Women were recruited from seven study centers in the United States, Canada, and Australia. Associations were estimated using multivariable Cox proportional hazards regression models adjusted for demographics, lifestyle factors, family history, and other medication use. Women were classified as regular or non-regular users of aspirin, COX-2 inhibitors, ibuprofen and other NSAIDs, and acetaminophen (control) based on self-report at follow-up of ever using the medication for at least twice a week for ≥1 month prior to breast cancer diagnosis. The main outcome was incident invasive breast cancer, based on self- or relative-report (81% confirmed pathologically). Results From fully adjusted analyses, regular aspirin use was associated with a 39% and 37% reduced risk of breast cancer in the prospective (HR = 0.61; 95% CI = 0.33–1.14) and combined cohorts (HR = 0.63; 95% CI = 0.57–0.71), respectively. Regular use of COX-2 inhibitors was associated with a 61% and 71% reduced risk of breast cancer (prospective HR = 0.39; 95% CI = 0.15–0.97; combined HR = 0.29; 95% CI = 0.23–0.38). Other NSAIDs and acetaminophen were not associated with breast cancer risk in either cohort. Associations were not modified by familial risk, and consistent patterns were found by BRCA1 and BRCA2 carrier status, estrogen receptor status, and attained age. Conclusion Regular use of aspirin and COX-2 inhibitors might reduce breast cancer risk for women at familial or genetic risk.

Published
2019
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44. Genome-wide association and transcriptome studies identify target genes and risk loci for breast cancer

Author

Manuel A. Ferreira, Eric R. Gamazon, Fares Al-Ejeh, Kristiina Aittomäki, Irene L. Andrulis, Hoda Anton-Culver, Adalgeir Arason, Volker Arndt, Kristan J. Aronson, Banu K. Arun, Ella Asseryanis, Jacopo Azzollini, Judith Balmaña, Daniel R. Barnes, Daniel Barrowdale, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Katarzyna Białkowska, Carl Blomqvist, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Ake Borg, Hiltrud Brauch, Hermann Brenner, Annegien Broeks, Barbara Burwinkel, Trinidad Caldés, Maria A. Caligo, Daniele Campa, Ian Campbell, Federico Canzian, Jonathan Carter, Brian D. Carter, Jose E. Castelao, Jenny Chang-Claude, Stephen J. Chanock, Hans Christiansen, Wendy K. Chung, Kathleen B. M. Claes, Christine L. Clarke, EMBRACE Collaborators, GC-HBOC Study Collaborators, GEMO Study Collaborators, Fergus J. Couch, Angela Cox, Simon S. Cross, Kamila Czene, Mary B. Daly, Miguel de la Hoya, Joe Dennis, Peter Devilee, Orland Diez, Thilo Dörk, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Bent Ejlertsen, Carolina Ellberg, Christoph Engel, Mikael Eriksson, Peter A. Fasching, Olivia Fletcher, Henrik Flyger, Eitan Friedman, Debra Frost, Marike Gabrielson, Manuela Gago-Dominguez, Patricia A. Ganz, Susan M. Gapstur, Judy Garber, Montserrat García-Closas, José A. García-Sáenz, Mia M. Gaudet, Graham G. Giles, Gord Glendon, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Mark H. Greene, Jacek Gronwald, Pascal Guénel, Christopher A. Haiman, Per Hall, Ute Hamann, Wei He, Jane Heyworth, Frans B. L. Hogervorst, Antoinette Hollestelle, Robert N. Hoover, John L. Hopper, Peter J. Hulick, Keith Humphreys, Evgeny N. Imyanitov, ABCTB Investigators, HEBON Investigators, BCFR Investigators, Claudine Isaacs, Milena Jakimovska, Anna Jakubowska, Paul A. James, Ramunas Janavicius, Rachel C. Jankowitz, Esther M. John, Nichola Johnson, Vijai Joseph, Beth Y. Karlan, Elza Khusnutdinova, Johanna I. Kiiski, Yon-Dschun Ko, Michael E. Jones, Irene Konstantopoulou, Vessela N. Kristensen, Yael Laitman, Diether Lambrechts, Conxi Lazaro, Goska Leslie, Jenny Lester, Fabienne Lesueur, Sara Lindström, Jirong Long, Jennifer T. Loud, Jan Lubiński, Enes Makalic, Arto Mannermaa, Mehdi Manoochehri, Sara Margolin, Tabea Maurer, Dimitrios Mavroudis, Lesley McGuffog, Alfons Meindl, Usha Menon, Kyriaki Michailidou, Austin Miller, Marco Montagna, Fernando Moreno, Lidia Moserle, Anna Marie Mulligan, Katherine L. Nathanson, Susan L. Neuhausen, Heli Nevanlinna, Ines Nevelsteen, Finn C. Nielsen, Liene Nikitina-Zake, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Olufunmilayo I. Olopade, Håkan Olsson, Ana Osorio, Janos Papp, Tjoung-Won Park-Simon, Michael T. Parsons, Inge Sokilde Pedersen, Ana Peixoto, Paolo Peterlongo, Paul D. P. Pharoah, Dijana Plaseska-Karanfilska, Bruce Poppe, Nadege Presneau, Paolo Radice, Johanna Rantala, Gad Rennert, Harvey A. Risch, Emmanouil Saloustros, Kristin Sanden, Elinor J. Sawyer, Marjanka K. Schmidt, Rita K. Schmutzler, Priyanka Sharma, Xiao-Ou Shu, Jacques Simard, Christian F. Singer, Penny Soucy, Melissa C. Southey, John J. Spinelli, Amanda B. Spurdle, Jennifer Stone, Anthony J. Swerdlow, William J. Tapper, Jack A. Taylor, Manuel R. Teixeira, Mary Beth Terry, Alex Teulé, Mads Thomassen, Kathrin Thöne, Darcy L. Thull, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Thérèse Truong, Nadine Tung, Celine M. Vachon, Christi J. van Asperen, Ans M. W. van den Ouweland, Elizabeth J. van Rensburg, Ana Vega, Alessandra Viel, Qin Wang, Barbara Wappenschmidt, Jeffrey N. Weitzel, Camilla Wendt, Robert Winqvist, Xiaohong R. Yang, Drakoulis Yannoukakos, Argyrios Ziogas, Peter Kraft, Antonis C. Antoniou, Wei Zheng, Douglas F. Easton, Roger L. Milne, Jonathan Beesley, and Georgia Chenevix-Trench

Subjects
Science
Abstract

Over 170 susceptibility loci have been identified by genome-wide association studies in breast cancer. Here, the authors interrogated the role of risk-associated variants from non-breast tissue, and using expression quantitative trait loci, identify potential target genes of known breast cancer susceptibility variants, as well as 11 regions not previously known to be associated with breast cancer risk.

Published
2019
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45. Shared heritability and functional enrichment across six solid cancers

Author

Xia Jiang, Hilary K. Finucane, Fredrick R. Schumacher, Stephanie L. Schmit, Jonathan P. Tyrer, Younghun Han, Kyriaki Michailidou, Corina Lesseur, Karoline B. Kuchenbaecker, Joe Dennis, David V. Conti, Graham Casey, Mia M. Gaudet, Jeroen R. Huyghe, Demetrius Albanes, Melinda C. Aldrich, Angeline S. Andrew, Irene L. Andrulis, Hoda Anton-Culver, Antonis C. Antoniou, Natalia N. Antonenkova, Susanne M. Arnold, Kristan J. Aronson, Banu K. Arun, Elisa V. Bandera, Rosa B. Barkardottir, Daniel R. Barnes, Jyotsna Batra, Matthias W. Beckmann, Javier Benitez, Sara Benlloch, Andrew Berchuck, Sonja I. Berndt, Heike Bickeböller, Stephanie A. Bien, Carl Blomqvist, Stefania Boccia, Natalia V. Bogdanova, Stig E. Bojesen, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, James D. Brenton, Mark N. Brook, Joan Brunet, Hans Brunnström, Daniel D. Buchanan, Barbara Burwinkel, Ralf Butzow, Gabriella Cadoni, Trinidad Caldés, Maria A. Caligo, Ian Campbell, Peter T. Campbell, Géraldine Cancel-Tassin, Lisa Cannon-Albright, Daniele Campa, Neil Caporaso, André L. Carvalho, Andrew T. Chan, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, David C. Christiani, Kathleen B. M. Claes, Frank Claessens, Judith Clements, J. Margriet Collée, Marcia Cruz Correa, Fergus J. Couch, Angela Cox, Julie M. Cunningham, Cezary Cybulski, Kamila Czene, Mary B. Daly, Anna deFazio, Peter Devilee, Orland Diez, Manuela Gago-Dominguez, Jenny L. Donovan, Thilo Dörk, Eric J. Duell, Alison M. Dunning, Miriam Dwek, Diana M. Eccles, Christopher K. Edlund, Digna R Velez Edwards, Carolina Ellberg, D. Gareth Evans, Peter A. Fasching, Robert L. Ferris, Triantafillos Liloglou, Jane C. Figueiredo, Olivia Fletcher, Renée T. Fortner, Florentia Fostira, Silvia Franceschi, Eitan Friedman, Steven J. Gallinger, Patricia A. Ganz, Judy Garber, José A. García-Sáenz, Simon A. Gayther, Graham G. Giles, Andrew K. Godwin, Mark S. Goldberg, David E. Goldgar, Ellen L. Goode, Marc T. Goodman, Gary Goodman, Kjell Grankvist, Mark H. Greene, Henrik Gronberg, Jacek Gronwald, Pascal Guénel, Niclas Håkansson, Per Hall, Ute Hamann, Freddie C. Hamdy, Robert J. Hamilton, Jochen Hampe, Aage Haugen, Florian Heitz, Rolando Herrero, Peter Hillemanns, Michael Hoffmeister, Estrid Høgdall, Yun-Chul Hong, John L. Hopper, Richard Houlston, Peter J. Hulick, David J. Hunter, David G. Huntsman, Gregory Idos, Evgeny N. Imyanitov, Sue Ann Ingles, Claudine Isaacs, Anna Jakubowska, Paul James, Mark A. Jenkins, Mattias Johansson, Mikael Johansson, Esther M. John, Amit D. Joshi, Radka Kaneva, Beth Y. Karlan, Linda E. Kelemen, Tabea Kühl, Kay-Tee Khaw, Elza Khusnutdinova, Adam S. Kibel, Lambertus A. Kiemeney, Jeri Kim, Susanne K. Kjaer, Julia A. Knight, Manolis Kogevinas, Zsofia Kote-Jarai, Stella Koutros, Vessela N. Kristensen, Jolanta Kupryjanczyk, Martin Lacko, Stephan Lam, Diether Lambrechts, Maria Teresa Landi, Philip Lazarus, Nhu D. Le, Eunjung Lee, Flavio Lejbkowicz, Heinz-Josef Lenz, Goska Leslie, Davor Lessel, Jenny Lester, Douglas A. Levine, Li Li, Christopher I. Li, Annika Lindblom, Noralane M. Lindor, Geoffrey Liu, Fotios Loupakis, Jan Lubiński, Lovise Maehle, Christiane Maier, Arto Mannermaa, Loic Le Marchand, Sara Margolin, Taymaa May, Lesley McGuffog, Alfons Meindl, Pooja Middha, Austin Miller, Roger L. Milne, Robert J. MacInnis, Francesmary Modugno, Marco Montagna, Victor Moreno, Kirsten B. Moysich, Lorelei Mucci, Kenneth Muir, Anna Marie Mulligan, Katherine L. Nathanson, David E. Neal, Andrew R. Ness, Susan L. Neuhausen, Heli Nevanlinna, Polly A. Newcomb, Lisa F. Newcomb, Finn Cilius Nielsen, Liene Nikitina-Zake, Børge G. Nordestgaard, Robert L. Nussbaum, Kenneth Offit, Edith Olah, Ali Amin Al Olama, Olufunmilayo I. Olopade, Andrew F. Olshan, Håkan Olsson, Ana Osorio, Hardev Pandha, Jong Y. Park, Nora Pashayan, Michael T. Parsons, Tanja Pejovic, Kathryn L. Penney, Wilbert H M. Peters, Catherine M. Phelan, Amanda I. Phipps, Dijana Plaseska-Karanfilska, Miranda Pring, Darya Prokofyeva, Paolo Radice, Kari Stefansson, Susan J. Ramus, Leon Raskin, Gad Rennert, Hedy S. Rennert, Elizabeth J. van Rensburg, Marjorie J. Riggan, Harvey A. Risch, Angela Risch, Monique J. Roobol, Barry S. Rosenstein, Mary Anne Rossing, Kim De Ruyck, Emmanouil Saloustros, Dale P. Sandler, Elinor J. Sawyer, Matthew B. Schabath, Johanna Schleutker, Marjanka K. Schmidt, V. Wendy Setiawan, Hongbing Shen, Erin M. Siegel, Weiva Sieh, Christian F. Singer, Martha L. Slattery, Karina Dalsgaard Sorensen, Melissa C. Southey, Amanda B. Spurdle, Janet L. Stanford, Victoria L. Stevens, Sebastian Stintzing, Jennifer Stone, Karin Sundfeldt, Rebecca Sutphen, Anthony J. Swerdlow, Eloiza H. Tajara, Catherine M. Tangen, Adonina Tardon, Jack A. Taylor, M. Dawn Teare, Manuel R. Teixeira, Mary Beth Terry, Kathryn L. Terry, Stephen N. Thibodeau, Mads Thomassen, Line Bjørge, Marc Tischkowitz, Amanda E. Toland, Diana Torres, Paul A. Townsend, Ruth C. Travis, Nadine Tung, Shelley S. Tworoger, Cornelia M. Ulrich, Nawaid Usmani, Celine M. Vachon, Els Van Nieuwenhuysen, Ana Vega, Miguel Elías Aguado-Barrera, Qin Wang, Penelope M. Webb, Clarice R. Weinberg, Stephanie Weinstein, Mark C. Weissler, Jeffrey N. Weitzel, Catharine M. L. West, Emily White, Alice S. Whittemore, H-Erich Wichmann, Fredrik Wiklund, Robert Winqvist, Alicja Wolk, Penella Woll, Michael Woods, Anna H. Wu, Xifeng Wu, Drakoulis Yannoukakos, Wei Zheng, Shanbeh Zienolddiny, Argyrios Ziogas, Kristin K. Zorn, Jacqueline M. Lane, Richa Saxena, Duncan Thomas, Rayjean J. Hung, Brenda Diergaarde, James McKay, Ulrike Peters, Li Hsu, Montserrat García-Closas, Rosalind A. Eeles, Georgia Chenevix-Trench, Paul J. Brennan, Christopher A. Haiman, Jacques Simard, Douglas F. Easton, Stephen B. Gruber, Paul D. P. Pharoah, Alkes L. Price, Bogdan Pasaniuc, Christopher I. Amos, Peter Kraft, and Sara Lindström

Subjects
Science
Abstract

Similarities in cancers can be studied to interrogate their etiology. Here, the authors use genome-wide association study summary statistics from six cancer types based on 296,215 cases and 301,319 controls of European ancestry, showing that solid tumours arising from different tissues share a degree of common germline genetic basis.

Published
2019
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46. Genetically Determined Height and Risk of Non-hodgkin Lymphoma

Author

Amy Moore, Eleanor Kane, Zhaoming Wang, Orestis A. Panagiotou, Lauren R. Teras, Alain Monnereau, Nicole Wong Doo, Mitchell J. Machiela, Christine F. Skibola, Susan L. Slager, Gilles Salles, Nicola J. Camp, Paige M. Bracci, Alexandra Nieters, Roel C. H. Vermeulen, Joseph Vijai, Karin E. Smedby, Yawei Zhang, Claire M. Vajdic, Wendy Cozen, John J. Spinelli, Henrik Hjalgrim, Graham G. Giles, Brian K. Link, Jacqueline Clavel, Alan A. Arslan, Mark P. Purdue, Lesley F. Tinker, Demetrius Albanes, Giovanni M. Ferri, Thomas M. Habermann, Hans-Olov Adami, Nikolaus Becker, Yolanda Benavente, Simonetta Bisanzi, Paolo Boffetta, Paul Brennan, Angela R. Brooks-Wilson, Federico Canzian, Lucia Conde, David G. Cox, Karen Curtin, Lenka Foretova, Susan M. Gapstur, Hervé Ghesquières, Martha Glenn, Bengt Glimelius, Rebecca D. Jackson, Qing Lan, Mark Liebow, Marc Maynadie, James McKay, Mads Melbye, Lucia Miligi, Roger L. Milne, Thierry J. Molina, Lindsay M. Morton, Kari E. North, Kenneth Offit, Marina Padoan, Alpa V. Patel, Sara Piro, Vignesh Ravichandran, Elio Riboli, Silvia de Sanjose, Richard K. Severson, Melissa C. Southey, Anthony Staines, Carolyn Stewart, Ruth C. Travis, Elisabete Weiderpass, Stephanie Weinstein, Tongzhang Zheng, Stephen J. Chanock, Nilanjan Chatterjee, Nathaniel Rothman, Brenda M. Birmann, James R. Cerhan, and Sonja I. Berndt

Subjects
non-Hodgkin lymphoma, height, genetics, chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Although the evidence is not consistent, epidemiologic studies have suggested that taller adult height may be associated with an increased risk of some non-Hodgkin lymphoma (NHL) subtypes. Height is largely determined by genetic factors, but how these genetic factors may contribute to NHL risk is unknown. We investigated the relationship between genetic determinants of height and NHL risk using data from eight genome-wide association studies (GWAS) comprising 10,629 NHL cases, including 3,857 diffuse large B-cell lymphoma (DLBCL), 2,847 follicular lymphoma (FL), 3,100 chronic lymphocytic leukemia (CLL), and 825 marginal zone lymphoma (MZL) cases, and 9,505 controls of European ancestry. We evaluated genetically predicted height by constructing polygenic risk scores using 833 height-associated SNPs. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) for association between genetically determined height and the risk of four NHL subtypes in each GWAS and then used fixed-effect meta-analysis to combine subtype results across studies. We found suggestive evidence between taller genetically determined height and increased CLL risk (OR = 1.08, 95% CI = 1.00–1.17, p = 0.049), which was slightly stronger among women (OR = 1.15, 95% CI: 1.01–1.31, p = 0.036). No significant associations were observed with DLBCL, FL, or MZL. Our findings suggest that there may be some shared genetic factors between CLL and height, but other endogenous or environmental factors may underlie reported epidemiologic height associations with other subtypes.

Published
2020
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47. Predicting interval and screen-detected breast cancers from mammographic density defined by different brightness thresholds

Author

Tuong L. Nguyen, Ye K. Aung, Shuai Li, Nhut Ho Trinh, Christopher F. Evans, Laura Baglietto, Kavitha Krishnan, Gillian S. Dite, Jennifer Stone, Dallas R. English, Yun-Mi Song, Joohon Sung, Mark A. Jenkins, Melissa C. Southey, Graham G. Giles, and John L. Hopper

Subjects
Breast cancer, Masking effect, Interval cancer, Screen-detected, Nested case–control cohort study, Australian women, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background Case–control studies show that mammographic density is a better risk factor when defined at higher than conventional pixel-brightness thresholds. We asked if this applied to interval and/or screen-detected cancers. Method We conducted a nested case–control study within the prospective Melbourne Collaborative Cohort Study including 168 women with interval and 422 with screen-detected breast cancers, and 498 and 1197 matched controls, respectively. We measured absolute and percent mammographic density using the Cumulus software at the conventional threshold (Cumulus) and two increasingly higher thresholds (Altocumulus and Cirrocumulus, respectively). Measures were transformed and adjusted for age and body mass index (BMI). Using conditional logistic regression and adjusting for BMI by age at mammogram, we estimated risk discrimination by the odds ratio per adjusted standard deviation (OPERA), calculated the area under the receiver operating characteristic curve (AUC) and compared nested models using the likelihood ratio criterion and models with the same number of parameters using the difference in Bayesian information criterion (ΔBIC). Results For interval cancer, there was very strong evidence that the association was best predicted by Cumulus as a percentage (OPERA = 2.33 (95% confidence interval (CI) 1.85–2.92); all ΔBIC > 14), and the association with BMI was independent of age at mammogram. After adjusting for percent Cumulus, no other measure was associated with risk (all P > 0.1). For screen-detected cancer, however, the associations were strongest for the absolute and percent Cirrocumulus measures (all ΔBIC > 6), and after adjusting for Cirrocumulus, no other measure was associated with risk (all P > 0.07). Conclusion The amount of brighter areas is the best mammogram-based measure of screen-detected breast cancer risk, while the percentage of the breast covered by white or bright areas is the best mammogram-based measure of interval breast cancer risk, irrespective of BMI. Therefore, there are different features of mammographic images that give clinically important information about different outcomes.

Published
2018
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48. Age-specific breast cancer risk by body mass index and familial risk: prospective family study cohort (ProF-SC)

Author

John L. Hopper, Gillian S. Dite, Robert J. MacInnis, Yuyan Liao, Nur Zeinomar, Julia A. Knight, Melissa C. Southey, Roger L. Milne, Wendy K. Chung, Graham G. Giles, Jeanine M. Genkinger, Sue-Anne McLachlan, Michael L. Friedlander, Antonis C. Antoniou, Prue C. Weideman, Gord Glendon, Stephanie Nesci, kConFab Investigators, Irene L. Andrulis, Saundra S. Buys, Mary B. Daly, Esther M. John, Kelly Anne Phillips, and Mary Beth Terry

Subjects
Breast cancer, Body mass index, Familial risk, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm, Gene–environment interaction, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract Background The association between body mass index (BMI) and risk of breast cancer depends on time of life, but it is unknown whether this association depends on a woman’s familial risk. Methods We conducted a prospective study of a cohort enriched for familial risk consisting of 16,035 women from 6701 families in the Breast Cancer Family Registry and the Kathleen Cunningham Foundation Consortium for Research into Familial Breast Cancer followed for up to 20 years (mean 10.5 years). There were 896 incident breast cancers (mean age at diagnosis 55.7 years). We used Cox regression to model BMI risk associations as a function of menopausal status, age, and underlying familial risk based on pedigree data using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), all measured at baseline. Results The strength and direction of the BMI risk association depended on baseline menopausal status (P

Published
2018
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49. Identification of nine new susceptibility loci for endometrial cancer

Author

Tracy A. O’Mara, Dylan M. Glubb, Frederic Amant, Daniela Annibali, Katie Ashton, John Attia, Paul L. Auer, Matthias W. Beckmann, Amanda Black, Manjeet K. Bolla, Hiltrud Brauch, Hermann Brenner, Louise Brinton, Daniel D. Buchanan, Barbara Burwinkel, Jenny Chang-Claude, Stephen J. Chanock, Chu Chen, Maxine M. Chen, Timothy H. T. Cheng, Christine L. Clarke, Mark Clendenning, Linda S. Cook, Fergus J. Couch, Angela Cox, Marta Crous-Bous, Kamila Czene, Felix Day, Joe Dennis, Jeroen Depreeuw, Jennifer Anne Doherty, Thilo Dörk, Sean C. Dowdy, Matthias Dürst, Arif B. Ekici, Peter A. Fasching, Brooke L. Fridley, Christine M. Friedenreich, Lin Fritschi, Jenny Fung, Montserrat García-Closas, Mia M. Gaudet, Graham G. Giles, Ellen L. Goode, Maggie Gorman, Christopher A. Haiman, Per Hall, Susan E. Hankison, Catherine S. Healey, Alexander Hein, Peter Hillemanns, Shirley Hodgson, Erling A. Hoivik, Elizabeth G. Holliday, John L. Hopper, David J. Hunter, Angela Jones, Camilla Krakstad, Vessela N. Kristensen, Diether Lambrechts, Loic Le Marchand, Xiaolin Liang, Annika Lindblom, Jolanta Lissowska, Jirong Long, Lingeng Lu, Anthony M. Magliocco, Lynn Martin, Mark McEvoy, Alfons Meindl, Kyriaki Michailidou, Roger L. Milne, Miriam Mints, Grant W. Montgomery, Rami Nassir, Håkan Olsson, Irene Orlow, Geoffrey Otton, Claire Palles, John R. B. Perry, Julian Peto, Loreall Pooler, Jennifer Prescott, Tony Proietto, Timothy R. Rebbeck, Harvey A. Risch, Peter A. W. Rogers, Matthias Rübner, Ingo Runnebaum, Carlotta Sacerdote, Gloria E. Sarto, Fredrick Schumacher, Rodney J. Scott, V. Wendy Setiawan, Mitul Shah, Xin Sheng, Xiao-Ou Shu, Melissa C. Southey, Anthony J. Swerdlow, Emma Tham, Jone Trovik, Constance Turman, Jonathan P. Tyrer, Celine Vachon, David VanDen Berg, Adriaan Vanderstichele, Zhaoming Wang, Penelope M. Webb, Nicolas Wentzensen, Henrica M. J. Werner, Stacey J. Winham, Alicja Wolk, Lucy Xia, Yong-Bing Xiang, Hannah P. Yang, Herbert Yu, Wei Zheng, Paul D. P. Pharoah, Alison M. Dunning, Peter Kraft, Immaculata De Vivo, Ian Tomlinson, Douglas F. Easton, Amanda B. Spurdle, and Deborah J. Thompson

Subjects
Science
Abstract

Endometrial cancer is the most common invasive gynaecological cancer in developed countries. Here a meta-analysis identifies an additional nine novel endometrial cancer risk loci and eQTL analysis reveals risk variants associate with reduced expression of negative regulators of oncogenic signal transduction proteins.

Published
2018
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50. Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Author

Tokhir Dadaev, Edward J. Saunders, Paul J. Newcombe, Ezequiel Anokian, Daniel A. Leongamornlert, Mark N. Brook, Clara Cieza-Borrella, Martina Mijuskovic, Sarah Wakerell, Ali Amin Al Olama, Fredrick R. Schumacher, Sonja I. Berndt, Sara Benlloch, Mahbubl Ahmed, Chee Goh, Xin Sheng, Zhuo Zhang, Kenneth Muir, Koveela Govindasami, Artitaya Lophatananon, Victoria L. Stevens, Susan M. Gapstur, Brian D. Carter, Catherine M. Tangen, Phyllis Goodman, Ian M. Thompson, Jyotsna Batra, Suzanne Chambers, Leire Moya, Judith Clements, Lisa Horvath, Wayne Tilley, Gail Risbridger, Henrik Gronberg, Markus Aly, Tobias Nordström, Paul Pharoah, Nora Pashayan, Johanna Schleutker, Teuvo L. J. Tammela, Csilla Sipeky, Anssi Auvinen, Demetrius Albanes, Stephanie Weinstein, Alicja Wolk, Niclas Hakansson, Catharine West, Alison M. Dunning, Neil Burnet, Lorelei Mucci, Edward Giovannucci, Gerald Andriole, Olivier Cussenot, Géraldine Cancel-Tassin, Stella Koutros, Laura E. Beane Freeman, Karina Dalsgaard Sorensen, Torben Falck Orntoft, Michael Borre, Lovise Maehle, Eli Marie Grindedal, David E. Neal, Jenny L. Donovan, Freddie C. Hamdy, Richard M. Martin, Ruth C. Travis, Tim J. Key, Robert J. Hamilton, Neil E. Fleshner, Antonio Finelli, Sue Ann Ingles, Mariana C. Stern, Barry Rosenstein, Sarah Kerns, Harry Ostrer, Yong-Jie Lu, Hong-Wei Zhang, Ninghan Feng, Xueying Mao, Xin Guo, Guomin Wang, Zan Sun, Graham G. Giles, Melissa C. Southey, Robert J. MacInnis, Liesel M. FitzGerald, Adam S. Kibel, Bettina F. Drake, Ana Vega, Antonio Gómez-Caamaño, Laura Fachal, Robert Szulkin, Martin Eklund, Manolis Kogevinas, Javier Llorca, Gemma Castaño-Vinyals, Kathryn L. Penney, Meir Stampfer, Jong Y. Park, Thomas A. Sellers, Hui-Yi Lin, Janet L. Stanford, Cezary Cybulski, Dominika Wokolorczyk, Jan Lubinski, Elaine A. Ostrander, Milan S. Geybels, Børge G. Nordestgaard, Sune F. Nielsen, Maren Weisher, Rasmus Bisbjerg, Martin Andreas Røder, Peter Iversen, Hermann Brenner, Katarina Cuk, Bernd Holleczek, Christiane Maier, Manuel Luedeke, Thomas Schnoeller, Jeri Kim, Christopher J. Logothetis, Esther M. John, Manuel R. Teixeira, Paula Paulo, Marta Cardoso, Susan L. Neuhausen, Linda Steele, Yuan Chun Ding, Kim De Ruyck, Gert De Meerleer, Piet Ost, Azad Razack, Jasmine Lim, Soo-Hwang Teo, Daniel W. Lin, Lisa F. Newcomb, Davor Lessel, Marija Gamulin, Tomislav Kulis, Radka Kaneva, Nawaid Usmani, Chavdar Slavov, Vanio Mitev, Matthew Parliament, Sandeep Singhal, Frank Claessens, Steven Joniau, Thomas Van den Broeck, Samantha Larkin, Paul A. Townsend, Claire Aukim-Hastie, Manuela Gago-Dominguez, Jose Esteban Castelao, Maria Elena Martinez, Monique J. Roobol, Guido Jenster, Ron H. N. van Schaik, Florence Menegaux, Thérèse Truong, Yves Akoli Koudou, Jianfeng Xu, Kay-Tee Khaw, Lisa Cannon-Albright, Hardev Pandha, Agnieszka Michael, Andrzej Kierzek, Stephen N. Thibodeau, Shannon K. McDonnell, Daniel J. Schaid, Sara Lindstrom, Constance Turman, Jing Ma, David J. Hunter, Elio Riboli, Afshan Siddiq, Federico Canzian, Laurence N. Kolonel, Loic Le Marchand, Robert N. Hoover, Mitchell J. Machiela, Peter Kraft, The PRACTICAL (Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome) Consortium, Matthew Freedman, Fredrik Wiklund, Stephen Chanock, Brian E. Henderson, Douglas F. Easton, Christopher A. Haiman, Rosalind A. Eeles, David V. Conti, and Zsofia Kote-Jarai

Subjects
Science
Abstract

Prostate cancer (PrCa) involves a large heritable genetic component. Here, the authors perform multivariate fine-mapping of known PrCa GWAS loci, identifying variants enriched for biological function, explaining more familial relative risk, and with potential application in clinical risk profiling.

Published
2018
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