SUPPLEMENTAR Y INFORMATION - Nature · Association analysis identifies 65 new breast cancer risk loci and predicts target genes. Kyriaki Michailidou, Sara Lindström, Joe Dennis,

Association analysis identifies 65 new breast cancer risk loci and predicts target genes.

Kyriaki Michailidou, Sara Lindström, Joe Dennis, Jonathan Beesley, Shirley Hui, Siddhartha Kar, Audrey Lemaçon, Penny Soucy, Dylan Glubb, Asha Rostamianfar, Manjeet K. Bolla, Qin Wang, Jonathan Tyrer, Ed Dicks, Andrew Lee, Zhaoming Wang, Jamie Allen, Renske Keeman, Ursula Eilber, Juliet D. French, Xiao Qing Chen, Laura Fachal, Karen McCue, Amy E. McCart Reed, Maya Ghoussaini, Jason Carroll, Xia Jiang, Hilary Finucane,, Marcia Adams, Muriel A. Adank, Habibul Ahsan, Kristiina Aittomäki, Hoda Anton-Culver, Natalia N. Antonenkova, Volker Arndt, Kristan J. Aronson, Banu Arun, Paul L. Auer, François Bacot, Myrto Barrdahl, Caroline Baynes, Matthias W. Beckmann, Sabine Behrens, Javier Benitez, Marina Bermisheva, Leslie Bernstein, Carl Blomqvist, Natalia V. Bogdanova, Stig E. Bojesen, Bernardo Bonanni, Anne-Lise Børresen-Dale, Judith S. Brand, Hiltrud Brauch, Paul Brennan, Hermann Brenner, Louise Brinton, Per Broberg, Ian W. Brock, Annegien Broeks, Angela Brooks-Wilson, Sara Y. Brucker, Thomas Brüning, Barbara Burwinkel, Katja Butterbach, Qiuyin Cai, Hui Cai, Trinidad Caldés, Federico Canzian, Angel Carracedo,, Brian D. Carter, Jose E. Castelao, Tsun L. Chan, Ting-Yuan David Cheng, Kee Seng Chia, Ji-Yeob Choi,, Hans Christiansen, Christine L. Clarke, NBCS Collaborators, Margriet Collée, Don M. Conroy, Emilie Cordina-Duverger, Sten Cornelissen, David G Cox, Angela Cox, Simon S. Cross, Julie M. Cunningham, Kamila Czene, Mary B. Daly, Peter Devilee, Kimberly F. Doheny, Thilo Dörk, Isabel dos-Santos-Silva, Martine Dumont, Lorraine Durcan, Miriam Dwek, Diana M. Eccles, Arif B. Ekici, A. Heather Eliassen, Carolina Ellberg, Mingajeva Elvira, Christoph Engel, Mikael Eriksson, Peter A. Fasching, Jonine Figueroa, Dieter Flesch-Janys, Olivia Fletcher, Henrik Flyger, Lin Fritschi, Valerie Gaborieau, Marike Gabrielson, Manuela Gago-Dominguez, Yu-Tang Gao, Susan M. Gapstur, José A. García-Sáenz, Mia M. Gaudet, Vassilios Georgoulias, Graham G. Giles, Gord Glendon, Mark S. Goldberg, David E. Goldgar, Anna González-Neira, Grethe I. Grenaker Alnæs, Mervi Grip, Jacek Gronwald, Anne Grundy, Pascal Guénel, Lothar Haeberle, Eric Hahnen, Christopher A. Haiman, Niclas Håkansson, Ute Hamann, Nathalie Hamel, Susan Hankinson, Patricia Harrington, Steven N. Hart, Jaana M. Hartikainen, Mikael Hartman, Alexander Hein, Jane Heyworth, Belynda Hicks, Peter Hillemanns, Dona N. Ho, Antoinette Hollestelle, Maartje J. Hooning, Robert N. Hoover, John L. Hopper, Ming-Feng Hou, Chia-Ni Hsiung, Guanmengqian Huang, Keith Humphreys, Junko Ishiguro, Hidemi Ito, Motoki Iwasaki, Hiroji Iwata, Anna Jakubowska, Wolfgang Janni, Esther M. John, Nichola Johnson, Kristine Jones, Michael Jones, Arja Jukkola-Vuorinen, Rudolf Kaaks, Maria Kabisch, Katarzyna Kaczmarek, Daehee Kang, Yoshio Kasuga, Michael J. Kerin, Sofia Khan, Elza Khusnutdinova, Johanna I. Kiiski, Sung-Won Kim, Julia A. Knight, Veli-Matti Kosma, Vessela N. Kristensen, Ute Krüger, Ava Kwong, Diether Lambrechts, Loic Le Marchand, Eunjung Lee, Min Hyuk Lee, Jong Won Lee, Chuen Neng Lee, Flavio Lejbkowicz, Jingmei Li, Jenna Lilyquist, Annika Lindblom, Jolanta Lissowska, Wing-Yee Lo, Sibylle Loibl, Jirong Long, Artitaya Lophatananon, Jan Lubinski, Craig Luccarini, Michael P. Lux, Edmond S.K. Ma, Robert J. MacInnis, Tom Maishman, Enes Makalic, Kathleen E Malone, Ivana Maleva Kostovska, Arto Mannermaa, Siranoush Manoukian, JoAnn E. Manson,, Sara Margolin, Shivaani Mariapun, Maria Elena Martinez,, Keitaro Matsuo,, Dimitrios Mavroudis, James McKay, Catriona McLean, Hanne Meijers-Heijboer, Alfons Meindl, Primitiva Menéndez, Usha Menon, Jeffery Meyer, Hui Miao, Nicola Miller, Nur Aishah Mohd Taib, Kenneth Muir, Anna Marie Mulligan, Claire Mulot, Susan L. Neuhausen, Heli Nevanlinna, Patrick Neven, Sune F. Nielsen, Dong-Young Noh, Børge G. Nordestgaard, Aaron Norman, Olufunmilayo I. Olopade, Janet E. Olson, Håkan Olsson, Curtis Olswold, Nick Orr, V. Shane Pankratz, Sue K. Park,, Tjoung-Won Park-Simon, Rachel Lloyd, Jose I.A. Perez, Paolo Peterlongo, Julian Peto, Kelly-Anne Phillips, Mila Pinchev, Dijana Plaseska-Karanfilska, Ross Prentice, Nadege Presneau, Darya Prokofieva, Elizabeth Pugh, Katri Pylkäs, Brigitte Rack, Paolo Radice, Nazneen Rahman, Gadi Rennert, Hedy S. Rennert, Valerie Rhenius, Atocha Romero, Jane Romm, Kathryn J Ruddy, Thomas Rüdiger, Anja Rudolph, Matthias Ruebner, Emiel J. Th. Rutgers, Emmanouil Saloustros, Dale P. Sandler, Suleeporn Sangrajrang, Elinor J. Sawyer, Daniel F.

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SUPPLEMENTARY INFORMATIONdoi:10.1038/nature24284

Schmidt, Rita K. Schmutzler, Andreas Schneeweiss, Minouk J. Schoemaker, Fredrick Schumacher, Peter Schürmann, Rodney J. Scott, Christopher Scott, Sheila Seal, Caroline Seynaeve, Mitul Shah, Priyanka Sharma, Chen-Yang Shen, Grace Sheng, Mark E. Sherman, Martha J. Shrubsole, Xiao-Ou Shu, Ann Smeets, Christof Sohn, Melissa C. Southey, John J. Spinelli, Christa Stegmaier, Sarah Stewart-Brown, Jennifer Stone, Daniel O. Stram, Harald Surowy, Anthony Swerdlow, Rulla Tamimi, Jack A. Taylor, Maria Tengström, Soo H. Teo, Mary Beth Terry, Daniel C. Tessier, Somchai Thanasitthichai, Kathrin Thöne, Rob A.E.M. Tollenaar, Ian Tomlinson, Ling Tong, Diana Torres, Thérèse Truong, Chiu-chen Tseng, Shoichiro Tsugane, Hans-Ulrich Ulmer, Giske Ursin,, Michael Untch, Celine Vachon, Christi J. van Asperen, David Van Den Berg, Ans M.W. van den Ouweland, Lizet van der Kolk, Rob B. van der Luijt, Daniel Vincent, Jason Vollenweider, Quinten Waisfisz, Shan Wang-Gohrke, Clarice R. Weinberg, Camilla Wendt, Alice S. Whittemore, Hans Wildiers, Walter Willett, Robert Winqvist, Alicja Wolk, Anna H. Wu, Lucy Xia, Taiki Yamaji, Xiaohong R. Yang, Cheng Har Yip, Keun-Young Yoo, Jyh-Cherng Yu, Wei Zheng, Ying Zheng, Bin Zhu, Argyrios Ziogas, Elad Ziv, ABCTB Investigators, kConFab/AOCS Investigators, Sunil R. Lakhani, Antonis C. Antoniou, Arnaud Droit, Irene L. Andrulis,, Christopher I. Amos, Fergus J. Couch, Paul D.P. Pharoah,, Jenny Chang-Claude,, Per Hall,, David J. Hunter,, Roger L. Milne, Montserrat García-Closas, Marjanka K. Schmidt, Stephen J. Chanock, Alison M. Dunning, Stacey L. Edwards, Gary D. Bader, Georgia Chenevix-Trench, Jacques Simard, Peter Kraft, Douglas F. Easton.


doi:10.1038/nature24284 SUPPLEMENTARY INFORMATIONRESEARCH

Supplementary Table 1: Participating studies contributing to the OncoArray, numbers of samples genotyped, and numbers passing QC and after removal of samples in the previous GWAS and iCOGS stages.

Study Acronym

Study Name

Study design Country Samples received for OncoArray genotyping

Sample size post QC excluding samples previously genotyped European Ancestry

Asian Ancestry

Controls Cases Controls Cases Controls Cases 2SISTER The Two Sister Study77

Cases from sister-matched case-control study

USA 0 3047 0 1068 0 0

ABCFS Australian Breast Cancer Family Study78

Population-based case-control study Australia 383 1372 188 589 0 0

ABCS Amsterdam Breast Cancer Study79

Hospital-based consecutive cases; population-based controls

Netherlands

190 380 4 143 0 0

ABCTB Australian Breast Cancer Tissue Bank

Hospital based multi-site newly diagnosed breast cancer cases

Australia 380 1095 374 848 0 0

ACP Asia Cancer Program Hospital based case-control study Thailand 660 767 0 0 642 752 BBCC Bavarian Breast Cancer

Cases and Controls80,81 Hospital based cases; population based controls

Germany 278 821 248 676 0 0

BBCS British Breast Cancer Study82,83

Cancer registry and National Cancer Research network (NCRN) based cases; population based controls

UK 444 126 442 100 0 0

BCEES Breast Cancer Employment and Environment Study84

Population-based case-control study

Australia 859 833 834 782 0 0

BCFR-NY New York Breast Cancer Family Registry85-87

Clinic-based recruitment of families; family-based cohort

USA 63 759 27 454 0 0

BCFR-PA Philadelphia Breast Cancer Clinic-based recruitment of families; USA 0 200 0 137 0 0



Family Registry85,88 family-based cohort BCFR-UT Utah Breast Cancer Family

Registry85,88

Clinic-based recruitment of non-BRCA1/2 familial breast cancer cases; unaffected BRCA1/2 carriers as controls

USA 0 114 0 102 0 0

BCINIS Breast Cancer in Northern Israel Study89,90


Israel 759 1509 723 1437 0 0

BREOGAN Breast Oncology Galicia Network91,92


Spain 820 1453 725 1378 0 0

BSUCH Breast Cancer Study of the University of Heidelberg93

Hospital based cases; healthy blood donator controls

Germany 171 304 167 265 0 0

CBCS Canadian Breast Cancer Study94-97

Population-based case-control study Canada 1052 1090 817 678 170 336

CCGP Crete Cancer Genetics Program

Hospital-based case-control study Greece 366 728 332 681 0 0

CECILE CECILE Breast Cancer Study98 Population-based case-control study France 164 310 3 11 0 0 CGPS Copenhagen General

Population Study99


Denmark 736 1472 712 1406 0 0

CPSII Cancer Prevention Study-II Nutrition Cohort100

Nested case-control study USA 3257 3317 3025 3029 0 0

CTS California Teachers Study101

Prospective cohort study: nested case-control

USA 557 1270 577 1100 0 0

DIETCOMPLYF DietCompLyf Breast Cancer Survival Study102

Multi-centre prospective case study UK 0 732 0 646 0 0

EPIC European Prospective Nested case-control study within Multiple 3736 3951 3522 3535 0 0



Investigation Into Cancer and Nutrition103

prospective cohort

ESTHER ESTHER Breast Cancer Study104


Germany 187 302 3 3 0 0

GC-HBOC German Consortium for Hereditary Breast & Ovarian Cancer105,106

Clinic-based familial case-control study Germany 1615 3839 1593 3365 0 0

GENICA Gene Environment Interaction and Breast Cancer in Germany107,108


Germany 289 471 284 459 0 0

GeparSixto Randomized phase II trial investigating the addition of carboplatin to neoadjuvant therapy for triple-negative and HER2-positive early breast cancer109

Multicenter, prospective, randomized, open-label phase II study

Germany 0 419 0 385 0 0

GESBC Genetic Epidemiology Study of Breast Cancer by Age 50110

Population-based case-control study of women <50 years

Germany 190 380 180 357 0 0

HABCS Hannover Breast Cancer Study111

Hospital-based case-control study Germany 950 1000 865 916 0 0

HCSC Hospital Clinico San Carlos112,113

Population-based case study of priori sporadic breast cancer cases

Spain 0 475 0 426 0 0

HEBCS Helsinki Breast Cancer Study114-116

Hospital-based case-control study, plus additional familial cases

Finland 189 285 2 53 0 0

HERPACC Hospital-based Epidemiologic Research Program at Aichi Cancer

Hospital-based case-control study Japan 284 284 0 0 283 282



Center117 HKBCS Hong Kong Breast Cancer

Study118,119 Hospital-based case-control study China 570 570 0 0 454 564

HMBCS Hannover-Minsk Breast Cancer Study120

Hospital based cases; population based controls

Belarus 349 285 214 70 0 0

HUBCS Hannover-Ufa Breast Cancer Study120

Population and hospital-based cases; geographically matched controls

Russia 238 349 131 221 0 0

KARBAC Karolinska Breast Cancer Study121,122

Population and hospital-based cases; geographically matched controls

Sweden 0 554 0 77 0 0

KARMA Karolinska Mammography Project for Risk Prediction of Breast Cancer

Nested case-control study within population-based cohort, plus prevalent cases

Sweden 6327 3079 6042 2205 0 0

KBCP Kuopio Breast Cancer Project123,124

Clinic-based cases; population-based controls

Finland 255 584 182 136 0 0

KOHBRA Korean Hereditary Breast Cancer Study125

Population-based Case-Control study Korea 706 1498 0 0 665 1463

LMBC Leuven Multidisciplinary Breast Centre126,127

Hospital-based case-control study Belgium 1360 823 435 805 0 0

MABCS Macedonian Breast Cancer Study

Hospital-based case-control study Macedonia 93 93 93 90 0 0

MARIE Mammary Carcinoma Risk Factor Investigation128

Population-based case-control study Germany 302 553 288 57 0 0

MBCSG Milan Breast Cancer Study Group129,130

Clinic-based recruitment of familial/early onset breast cancer cases ; population-based controls

Italy 387 817 366 788 0 0

MCBCS Mayo Clinic Breast Cancer Study131

Hospital-based case-control study USA 230 958 179 651 0 0

MCCS Melbourne Collaborative Cohort Study132

Population-based prospective cohort study

Australia 1023 1102 712 615 0 0

MEC Multi-ethnic Cohort133 Nested case-control study within USA 800 746 127 70 0 0



prospective cohort MISS Melanoma Inquiry of

Southern Sweden134 Nested case-control study within population-based prospective cohort study

Sweden 1670 822 1523 692 0 0

MMHS Mayo Mammography Health Study135

Nested case-control study within prospective cohort

USA 1706 398 1605 375 0 0

MTLGEBCS Montreal Gene-Environment Breast Cancer Study

Population-based case-control study Canada 183 366 29 44 0 0

MYBRCA Malaysian Breast Cancer Genetic Study136

Hospital-based case-control study Malaysia 1450 866 0 0 1256 660

NBCS Norwegian Breast Cancer Study137

Hospital-based case-control study Norway 0 1478 0 1283 0 0

NBHS Nashville Breast Health Study138

Population-based case-control study USA 856 944 613 641 0 0

NGOBCS Nagano Breast Cancer Study139

Hospital-based case-control study Japan 380 380 0 0 366 369

NC-BCFR Northern California Breast Cancer Family Registry85

Population-based familial case-control study

USA 211 2085 149 776 50 453

NHS Nurses Health Study140

Nested case-control study within population-based cohort

USA 2028 1862 1804 1588 0 0

NHS2 Nurses Health Study 2141 Nested case-control study within population-based cohort

USA 2163 1883 1905 1606 0 0

OFBCR Ontario Familial Breast Cancer Registry85

Population-based familial case-control study

Canada 380 1789 217 993 0 0

ORIGO Leiden University Medical Centre Breast Cancer Study142,143

Hospital based case-control study Netherlands

688 1117 660 1015 0 0

PBCS NCI Polish Breast Cancer Study144

Population-based case-control study Poland 2138 1979 1658 1439 0 0

PLCO The Prostate, Lung, Colorectal and Ovarian

Nested case-control study within population-based cohort

USA 1098 1123 858 865 0 0



(PLCO) Cancer Screening Trial145

POSH Prospective Study of Outcomes in Sporadic Versus Hereditary Breast Cancer146

Case series UK 0 1140 0 1019 0 0

PreFace Evaluation of Predictive Factors regarding the Effectivity of Aromatase Inhibitor Therapy

Multicenter, prospective, randomized, open-label phase IV study

Germany 0 1018 0 968 0 0

RBCS Rotterdam Breast Cancer Study147

Hospital based case-control study Netherlands

254 506 231 451 0 0

SBCGS Shanghai Breast Cancer Genetic Study138

Population-based case-control study, cohort study

China 946 861 0 0 935 839

SEARCH Study of Epidemiology and Risk factors in Cancer Heredity148

Population-based case-control study UK 2902 4204 989 3999 0 0

SEBCS Seoul Breast Cancer Study149,150

Hospital-based case-control study Korea 1140 1140 0 0 1107 1098

SGBCC Singapore Breast Cancer Cohort

Hospital based breast cancer cohort and population based controls

Singapore 799 994 0 0 296 432

SISTER The Sister Study151 Case-cohort nested in prospective cohort of women with a sister-history of breast cancer

USA 1914 2362 1560 2014 0 0

SKKDKFZS Städtisches Klinikum Karlsruhe Deutsches Krebsforschungszentrum Study152

Hospital-based case series

Germany 0 1140 0 1017 0 0

SMC Swedish Mammography Cohort153

Nested case control study within population-based cohort

Sweden 734 1545 708 1478 0 0



SuccessB Simultaneous Study of Gemcitabine-Docetaxel Combination adjuvant treatment

Multicenter, prospective, randomized, open-label phase III study

Germany 0 454 0 439 0 0

SuccessC Simultaneous Study of Docetaxel Based Anthracycline Free Adjuvant Treatment Evaluation154

Multicenter, prospective, randomized, open-label phase III study

Germany 0 1418 0 1335 0 0

SZBCS IHCC-Szczecin Breast Cancer Study155,156

Hospital based case-control study Poland 182 388 157 387 0 0

TNBCC Triple-negative Breast Cancer Consortium

Multiple case series USA/Germany

0 1008 0 759 0 0

TWBCS Taiwanese Breast Cancer Study157,158

Hospital-based case-control study Taiwan 281 563 0 0 256 551

UCIBCS UCI Breast Cancer Study159,160 Population-based case-control study USA 321 629 258 501 0 0 UKBGS UK Breakthrough

Generations Study161 Prospective cohort study: nested case–control study of incident and prevalent cases from within the cohort

UK 734 1735 567 1159 0 0

UKOPS UK Ovarian Cancer Population Study (http://www.instituteforwomenshealth.ucl.ac.uk/womens-cancer/gcrc/ukops)

Apparently health women from Ovarian Cancer Screening Trial (UKCTOCS)

UK 1023 0 974 0 0 0

WHI Women's Health Initiative (https://www.nhlbi.nih.gov/whi/)

Nested case-control study with population-based cohort

USA 4904 5374 4613 4908 0 0



Supplementary Table 2: Associations between previously reported breast cancer associated SNPs and breast cancer risk in the combined analysis of GWAS + iCOGS + OncoArray data for overall breast cancer.

Locus Best published SNP

Chr1 Position2 Alleles3 MAF4 GWAS iCOGS OncoArray Combined P-value

Genes Ref.7

OR(95%CI)5 P-value6 OR(95%CI)5 P-value6 OR(95%CI)5 P-value6

1p36.22 rs616488 1 10566215 A/G 0.33 0.93 (0.9-0.96)

9.5X10-5 0.94 (0.92-0.96)

8.8X10-09 0.94 (0.93-0.96)

1.8X10-09 5.0X10-20 PEX14 2

1p13.2 rs11552449 1 114448389 C/T 0.17 1.09 (1.04-1.14)

2.0X10-4 1.07 (1.04-1.09)

6.0X10-07 1.04 (1.01-1.06)

2.3X10-03 4.6Χ10-11 DCLRE1B 2

1p11.2 rs11249433 1 121280613 A/G 0.41 1.1 (1.05-1.16)

2.0X10-4 1.09 (1.07-1.12)

4.4X10-20 1.11 (1.09-1.13)

2.2X10-31 1.8X10-52 EMBP1 162

1q21.1 rs12405132 1 145644984 C/T 0.37 0.95 (0.91-1)

3.7X10-2 0.95 (0.93-0.97)

5.0X10-07 0.97 (0.95-0.99)

1.0X10-03 6.3X10-10 RNF115 20

1q21.2 rs12048493 1 149927034 A/C 0.38 1.04 (1-1.09)

7.5X10-2 1.06 (1.04-1.09)

3.2X10-09 1.04 (1.02-1.06)

9.4X10-06 8.6X10-14 OTUD7B 20

1q32.1 rs6678914 1 202187176 G/A 0.41 0.94 (0.91-0.98)

1.4X10-3 1.00 (0.98-1.02)

7.1X10-01 1.00 (0.99-1.02)

7.3X10-01 3.0X10-01 LGR6 163

1q32.1 rs4245739 1 204518842 A/C 0.26 1.03 (0.99-1.08)

1.4X10-1 1.03 (1.01-1.05)

5.0X10-03 1.02 (1-1.04)

2.5X10-02 1.3X10-04 MDM4 163

1q43 rs72755295 1 242034263 A/G 0.03 1.14 (0.99-1.31)

7.6X10-2 1.15 (1.09-1.21)

2.0X10-07 1.15 (1.09-1.2)

8.0X10-08 1.7X10-14 EXO1 20

2p24.1 rs12710696 2 19320803 C/T 0.37 1.09 (1.05-1.13)

5.1X10-6 1.04 (1.02-1.06)

4.8X10-04 1.03 (1.01-1.04)

6.6X10-03 1.3X10-08 - 163

2p23.2 rs4577244 2 29120733 C/T 0.23 0.98 (0.94-1.02)

3.0X10-1 0.98 (0.96-1)

5.5X10-02 1.01 (0.99-1.03)

2.4X10-01 4.3X10-01 WDR43 164

2q14.1 rs4849887 2 121245122 C/T 0.1 0.92 (0.87-0.98)

5.1X10-3 0.91 (0.88-0.94)

4.9X10-09 0.91 (0.88-0.94)

1.2X10-10 6.9X10-20 2

2q31.1 rs2016394 2 172972971 G/A 0.47 0.98 (0.95-1.02)

3.4X10-1 0.95 (0.94-0.97)

1.9X10-06 0.95 (0.94-0.97)

3.1X10-07 6.2X10-12 DLX2-AS1 2

2q31.1 rs1550623 2 174212894 A/G 0.15 0.94 (0.9-0.99)

1.6X10-2 0.95 (0.92-0.97)

2.9X10-05 0.95 (0.93-0.98)

8.8X10-05 5.4X10-10 CDCA7 2

2q33.1 rs1830298 2 202181247 T/C 0.28 1.11 1.2X10-7 1.04 8.8X10-05 1.06 1.7X10-08 1.9X10-16 CASP8/ 165



(1.07-1.15) (1.02-1.06) (1.04-1.08) ALS2CR12

2q35 rs34005590 2 217963060 C/A 0.05 0.74 (0.67-0.82)

3.7X10-9 0.82 (0.78-0.86)

1.3X10-16 0.82 (0.79-0.86)

1.6X10-19 3.2X10-41 IGFBP5 166

2q35 rs4442975 2 217920769 G/T 0.5 0.87 (0.84-0.9)

3.9X10-15 0.87 (0.86-0.89)

2.9X10-44 0.89 (0.87-0.9)

3.6X10-40 1.1X10-95 IGFBP5 60

2q35 rs16857609 2 218296508 C/T 0.26 1.09 (1.05-1.13)

1.5X10-5 1.08 (1.06-1.11)

9.5X10-14 1.06 (1.04-1.09)

1.4X10-09 1.8X10-25 DIRC3 2

3p26.1 rs6762644 3 4742276 A/G 0.38 1.03 (1-1.07)

6.9X10-2 1.07 (1.05-1.09)

6.3X10-11 1.05 (1.03-1.07)

1.6X10-08 4.0X10-18 EGOT/ITPR1 2

3p24.1 rs4973768 3 27416013 C/T 0.47 1.11 (1.08-1.15)

7.0X10-10 1.1 (1.08-1.12)

4.7X10-22 1.11 (1.09-1.13)

1.7X10-28 4.8X10-57 SLC4A7 167

3p.24.1 rs12493607 3 30682939 G/C 0.34 1.03 (1-1.07)

8.6X10-2 1.06 (1.04-1.08)

7.0X10-08 1.05 (1.03-1.07)

4.9X10-07 6.9X10-14 TGFBR2 2

3p21.31 rs6796502 3 46866866 G/A 0.1 0.92 (0.87-0.98)

9.3X10-3 0.92 (0.89-0.95)

1.4X10-06 0.92 (0.89-0.95)

2.5X10-08 5.5X10-15 20

3p14.1 rs1053338 3 63967900 A/G 0.14 1.06 (1.01-1.12)

1.6X10-2 1.08 (1.05-1.11)

1.7X10-07 1.05 (1.02-1.07)

5.0X10-04 5.3X10-11 ATNX7 168

4q24 rs9790517 4 106084778 C/T 0.23 1.09 (1.05-1.14)

3.0X10-5 1.05 (1.03-1.08)

6.9X10-06 1.04 (1.01-1.06)

1.1X10-03 5.0X10-11 TET2 2

4q34.1 rs6828523 4 175846426 C/A 0.12 0.9 (0.85-0.95)

1.6X10-4 0.9 (0.87-0.93)

2.9X10-12 0.91 (0.88-0.93)

1.2X10-11 1.8X10-25 ADAM29 2

5p15.33 rs10069690 5 1279790 C/T 0.26 1.07 (1.02-1.13)

8.9X10-3 1.06 (1.04-1.09)

1.7X10-08 1.06 (1.04-1.08)

2.5X10-08 7.8X10-17 TERT 169

5p15.33 rs3215401 5 1296255 A/AG 0.31 0.95 (0.9-1)

4.6X10-2 0.94 (0.92-0.96)

1.4X10-08 0.93 (0.91-0.95)

7.1X10-13 1.1X10-20 TERT 170

5p15.1 rs13162653 5 16187528 G/T 0.45 0.93 (0.9-0.97)

9.0X10-5 0.96 (0.94-0.97)

1.2X10-05 0.99 (0.97-1.01)

1.8X10-01 5.4X10-07 20

5p13.3 rs2012709 5 32567732 C/T 0.48 1.06 (1.02-1.09)

1.7X10-3 1.05 (1.03-1.07)

1.6X10-06 1.02 (1-1.04)

2.1X10-02 1.2X10-08 20

5p12 rs10941679 5 44706498 A/G 0.25 1.12 (1.07-1.16)

5.9X10-8 1.12 (1.1-1.15)

3.2X10-26 1.15 (1.13-1.18)

6.2X10-43 5.6X10-73 FGF10, MRPS30

171

5q11.2 rs62355902 5 56053723 A/T 0.16 1.18 (1.13-1.24)

2.0X10-12 1.21 (1.18-1.24)

1.4X10-47 1.18 (1.15-1.21)

8.5X10-42 6.8X10-98 MAP3K1 172

5q11.2 rs10472076 5 58184061 T/C 0.38 1.04 (1.01-1.08)

1.8X10-2 1.05 (1.03-1.07)

1.8X10-06 1.03 (1.01-1.04)

6.6X10-03 9.6X10-09 RAB3C 2



5q11.2 rs1353747 5 58337481 T/G 0.09 0.92 (0.87-0.98)

5.5X10-3 0.92 (0.89-0.95)

1.4X10-06 0.96 (0.93-0.99)

7.6X10-03 4.1X10-09 PDE4D 2

5q14.2 rs7707921 5 81538046 A/T 0.25 0.95 (0.92-0.99)

1.7X10-2 0.94 (0.91-0.96)

1.5X10-08 0.96 (0.94-0.98)

1.2X10-04 1.7X10-12 ATG10 20

5q33.3 rs1432679 5 158244083 T/C 0.43 1.07 (1.03-1.11)

1.5X10-4 1.07 (1.05-1.09)

3.6X10-12 1.08 (1.06-1.1)

2.9X10-17 6.6X10-31 EBF1 2

6p25.3 rs11242675 6 1318878 T/C 0.37 0.95 (0.91-0.98)

2.0X10-3 0.96 (0.94-0.98)

1.0X10-05 1 (0.98-1.02)

9.7X10-01 1.0X10-04 FOXQ1 2

6p24.3 rs9348512 6 10456706 C/A 0.33 1 (0.96-1.04)

1 1 (0.98-1.02)

9.2X10-01 1 (0.99-1.02)

6.4X10-01 8.0X10-01 TFAP2A 173

6p23 rs204247 6 13722523 A/G 0.44 1.06 (1.02-1.1)

1.2X10-3 1.05 (1.03-1.07)

2.7X10-07 1.04 (1.02-1.06)

6.4X10-05 7.9X10-13 RANBP9 2

6p22.1 rs9257408 6 28926220 G/C 0.41 1.05 (1.02-1.09)

4.0X10-3 1.05 (1.03-1.07)

1.5X10-06 1.02 (1-1.04)

5.5X10-02 6.9X10-08 20

6q14.1 rs17529111 6 82128386 T/C 0.22 1.09 (1.05-1.14)

2.7X10-5 1.06 (1.04-1.08)

4.9X10-07 1.02 (1-1.04)

4.2X10-02 1.3X10-09 174

6q25 rs3757322 6 151942194 T/G 0.32 1.14 (1.1-1.18)

1.4X10-12 1.09 (1.07-1.11)

1.5X10-16 1.08 (1.06-1.1)

1.1X10-16 3.3X10-41 ESR1 175

6q25 rs9397437 6 151952332 G/A 0.07 1.32 (1.23-1.41)

5.4X10-16 1.2 (1.16-1.25)

2.0X10-22 1.17 (1.14-1.21)

6.3X10-21 4.8X10-54 ESR1 175

6q25 rs2747652 6 152437016 C/T 0.48 0.92 (0.89-0.96)

7.1X10-6 0.93 (0.92-0.95)

3.0X10-12 0.94 (0.92-0.96)

1.2X10-11 1.3X10-26 ESR1 175

7q21.2 rs6964587 7 91630620 G/T 0.39 1.04 (1.01-1.08)

1.7X10-2 1.05 (1.03-1.07)

1.1X10-06 1.03 (1.02-1.05)

2.2X10-04 9.0X10-11 AKAP9 168

7q32.3 rs4593472 7 130667121 C/T 0.35 0.92 (0.89-0.96)

1.9X10-5 0.95 (0.94-0.97)

4.0X10-06 0.97 (0.95-0.99)

7.9X10-04 1.8X10-11 FLJ43663 20

7q34 rs11977670 7 139942304 G/A 0.43 1.04 (1.00-1.08)

3.9X10-02 1.05 (1.03-1.07)

3.7X10-06 1.06 (1.04-1.08)

1.9X10-11 1.0X10-16 176

7q35 rs720475 7 144074929 G/A 0.25 0.96 (0.92-1)

6.0X10-2 0.94 (0.92-0.96)

1.2X10-08 0.96 (0.94-0.98)

3.0X10-04 1.2X10-11 NOBOX, ARHGEF6

2

8p12 rs9693444 8 29509616 C/A 0.32 1.06 (1.02-1.1)

3.3X10-3 1.07 (1.05-1.09)

1.1X10-10 1.06 (1.04-1.08)

1.7X10-10 1.6X10-21 2

8p11.23 rs13365225 8 36858483 A/G 0.18 0.91 (0.87-0.95)

6.6X10-5 0.95 (0.93-0.98)

2.0X10-04 0.91 (0.89-0.93)

1.2X10-15 1.4X10-20 20

8q21.11 rs6472903 8 76230301 T/G 0.17 0.92 3.8X10-4 0.91 2.7X10-13 0.94 3.1X10-07 4.4X10-21 2



(0.88-0.96) (0.89-0.93) (0.92-0.96)

8q21.11 rs2943559 8 76417937 A/G 0.08 1.2 (1.12-1.28)

2.7X10-8 1.13 (1.09-1.17)

6.8X10-11 1.1 (1.07-1.14)

4.2X10-09 4.0X10-24 HNF4G 2

8q23.3 rs13267382 8 117209548 G/A 0.36 1.08 (1.04-1.12)

8.1X10-5 1.05 (1.03-1.07)

1.3X10-06 1.03 (1.01-1.05)

8.7X10-04 1.6X10-11 LINC00536 20

8q24.21 rs13281615 8 128355618 A/G 0.41 1.12 (1.08-1.16)

1.1X10-10 1.1 (1.08-1.12)

3.3X10-22 1.11 (1.09-1.13)

5.0X10-28 1.9X10-57 147

8q24.21 rs11780156 8 129194641 C/T 0.17 1.09 (1.05-1.14)

8.0X10-5 1.07 (1.04-1.09)

7.7X10-07 1.05 (1.03-1.08)

2.5X10-05 1.1X10-13 MYC 2

9p21.3 rs1011970 9 22062134 G/T 0.16 1.12 (1.07-1.17)

8.2X10-7 1.06 (1.03-1.08)

2.7X10-05 1.07 (1.04-1.09)

1.4X10-07 1.0X10-15 CDKN2A, CDKN2B

177

9q31.2 rs10759243 9 110306115 C/A 0.29 1.08 (1.04-1.12)

1.9X10-4 1.05 (1.03-1.08)

6.9X10-07 1.06 (1.04-1.08)

4.2X10-10 2.2X10-18 2

9q31.2 rs676256 9 110895353 T/C 0.38 0.91 (0.88-0.94)

9.9X10-08 0.9 (0.88-0.91)

1.0X10-27 0.91 (0.9-0.93)

1.9X10-21 3.5X10-53 178

9q31.2 rs10816625 9 110837073 A/G 0.06 1.15 (1.06-1.24)

5.1X10-04 1.12 (1.08-1.16)

1.3X10-08 1.11 (1.07-1.15)

2.3X10-08 5.0X10-18 178

9q31.2 rs13294895 9 110837176 C/T 0.18 1.05 (1.01-1.11)

2.8X10-02 1.09 (1.06-1.12)

1.5X10-11 1.06 (1.03-1.08)

1.9X10-06 6.5X10-17 178

10p15.1 rs2380205 10 5886734 C/T 0.44 0.94 (0.91-0.98)

6.9X10-04 0.99 (0.97-1.01)

2.0X10-01 0.98 (0.96-0.99)

1.1X10-02 1.7X10-04 ANKRD16 177

10p12.31 rs7072776 10 22032942 G/A 0.29 1.1 (1.06-1.15)

3.5X10-06 1.07 (1.05-1.09)

7.7X10-10 1.05 (1.03-1.07)

2.7X10-07 1.8X10-19 DNAJC1 2

10p12.31 rs11814448 10 22315843 A/C 0.02 1.35 (1.17-1.56)

3.2X10-05 1.27 (1.19-1.36)

2.7X10-13 1.12 (1.06-1.19)

1.4X10-04 6.1X10-18 DNAJC1 2

10q21.2 rs10995201 10 64299890 A/G 0.16 0.86(0.82-0.91)

1.0X10-08 0.85 (0.83-0.88)

9.3X10-31 0.9 (0.88-0.92)

4.7X10-17 1.6X10-51 ZNF365 179

10q22.3 rs704010 10 80841148 C/T 0.38 1.11 (1.07-1.15)

2.5X10-09 1.08 (1.06-1.1)

2.9X10-15 1.07 (1.05-1.09)

1.1X10-14 1.7X10-35 ZMZ1 177

10q25.2 rs7904519 10 114773927 A/G 0.46 1.08 (1.05-1.12)

4.3X10-06 1.05 (1.03-1.07)

4.7X10-08 1.03 (1.01-1.05)

8.6X10-04 1.5X10-13 TCFL2 2

10q26.12 rs11199914 10 123093901 C/T 0.32 0.95 (0.92-0.99)

7.7X10-03 0.95 (0.93-0.97)

2.3X10-06 0.96 (0.94-0.98)

2.1X10-05 6.5X10-12 2

10q26.13 rs35054928 10 123340431 G/GC 0.4 1.3 (1.26-1.36)

1.6X10-43 1.27 (1.24-1.29)

4.7X10-129 1.27 (1.25-1.3)

3.5X10-154 2.3X10-322 FGFR2 180



10q26.13 rs45631563 10 123349324 A/T 0.05 0.83 (0.75-0.91)

7.4X10-05 0.83 (0.79-0.87)

2.4X10-14 0.81 (0.78-0.85)

9.1X10-21 7.3X10-37 FGFR2 180

10q26.13 rs2981578 10 123340311 T/C 0.47 1.23 (1.19-1.27)

9.6X10-31 1.24 (1.21-1.26)

4.5X10-104 1.23 (1.21-1.25)

1.0X10-114 1.3X10-245 FGFR2 180

11p15.5 rs3817198 11 1909006 T/C 0.32 1.07 (1.03-1.11)

1.8X10-04 1.07 (1.05-1.09)

1.1X10-10 1.05 (1.03-1.07)

6.2X10-07 9.9X10-19 LSP1 147

11q13.1 rs3903072 11 65583066 G/T 0.47 0.93 (0.9-0.96)

2.7X10-05 0.95 (0.93-0.97)

3.0X10-07 0.97 (0.95-0.99)

9.1X10-04 2.3X10-12 2

11q13.3 rs554219 11 69331642 C/G 0.13 - - - - 1.21 (1.18-1.24)

5.8X10-47 5.8X10-47 CCND1 181

11q13.3 rs75915166 11 69379161 C/A 0.06 1.32 (1.23-1.43)

2.5X10-13 1.31 (1.26-1.36)

2.4X10-43 1.28 (1.24-1.33)

4.1X10-42 4.1X10-95 CCND1 181

11q24.3 rs11820646 11 129461171 C/T 0.4 0.93 (0.9-0.96)

5.6X10-05 0.95 (0.93-0.97)

1.7X10-07 0.96 (0.94-0.98)

2.5X10-05 2.1X10-14 2

12p13.1 rs12422552 12 14413931 G/C 0.26 1.1 (1.05-1.14)

5.8X10-06 1.04 (1.02-1.07)

9.4X10-05 1.06 (1.04-1.08)

3.2X10-08 3.6X10-15 2

12p11.22 rs7297051 12 28174817 C/T 0.24 0.87 (0.84-0.91)

4.0X10-10 0.89 (0.87-0.91)

2.6X10-26 0.89 (0.87-0.91)

2.9X10-27 3.0X10-60 182

12q22 rs17356907 12 96027759 A/G 0.3 0.92 (0.88-0.95)

6.3X10-06 0.91 (0.9-0.93)

5.6X10-17 0.91 (0.9-0.93)

6.6X10-20 1.0X10-39 NTN4 2

12q24.21 rs1292011 12 115836522 A/G 0.42 0.92 (0.89-0.95)

3.4X10-06 0.92 (0.9-0.94)

1.2X10-16 0.92 (0.9-0.94)

2.4X10-19 4.4X10-39 TBX3 183

13q13.1 rs11571833 13 32972626 A/T 0.01 1.6 (0.77-3.3)

2.1X10-01 1.27 (1.15-1.4)

2.2X10-06 1.35 (1.23-1.48)

4.0X10-10 3.1X10-15 BRCA2 2

13q22.1 rs6562760 13 73957681 G/A 0.24 0.92 (0.88-0.96)

4.2X10-05 0.97 (0.95-0.99)

1.5X10-02 0.95 (0.93-0.97)

8.6X10-06 1.5X10-09 164

14q13.3 rs2236007 14 37132769 G/A 0.21 0.93 (0.89-0.97)

5.6X10-04 0.93 (0.91-0.95)

4.7X10-10 0.93 (0.91-0.95)

5.8X10-10 4.2X10-21 PAX9 2

14q24.1 rs2588809 14 68660428 C/T 0.17 1.04 (0.99-1.09)

1.6X10-01 1.08 (1.05-1.11)

3.7X10-09 1.06 (1.03-1.08)

2.6X10-06 6.3X10-14 RAD51B 2

14q24.1 rs999737 14 69034682 C/T 0.23 0.87 (0.83-0.91)

1.7X10-11 0.92 (0.9-0.94)

4.1X10-13 0.91 (0.89-0.93)

1.1X10-18 6.5X10-39 RAD51B 162

14q32.11 rs941764 14 91841069 A/G 0.35 1.04 (1-1.07)

5.3X10-02 1.07 (1.05-1.09)

2.4X10-10 1.03 (1.02-1.05)

3.6X10-04 8.2X10-13 CCDC88C 2

14q32.12 rs11627032 14 93104072 T/C 0.25 0.95 6.7X10-03 0.94 1.3X10-06 0.96 1.6X10-04 4.1X10-11 RIN3 20



(0.91-0.98) (0.92-0.97) (0.94-0.98)

16q12.1 rs4784227 16 52599188 C/T 0.24 1.27 (1.22-1.32)

1.9X10-30 1.25 (1.22-1.28)

6.1X10-87 1.23 (1.2-1.25)

7.0X10-88 6.8X10-201 TOX3 184

16q12.2 rs17817449 16 53813367 T/G 0.41 0.95 (0.92-0.99)

1.1X10-02 0.93 (0.91-0.95)

6.9X10-13 0.95 (0.93-0.96)

4.9X10-09 2.5X10-21 FTO 2

16q12.2 rs11075995 16 53855291 T/A 0.24 1.1 (1.05-1.15)

5.3X10-05 1.04 (1.02-1.06)

5.0X10-04 1.03 (1.01-1.06)

1.3X10-03 8.7X10-09 FTO 163

16q23.2 rs13329835 16 80650805 A/G 0.23 1.12 (1.08-1.17)

7.6X10-08 1.08 (1.06-1.11)

6.1X10-12 1.07 (1.05-1.09)

8.3X10-11 8.8X10-27 CDYL2 2

17q11.2 rs146699004 17 29230520 GGT/G 0.27 0.95 (0.91-0.99)

8.6X10-03 0.95 (0.93-0.97)

6.0X10-06 0.97 (0.95-0.99)

1.3X10-03 2.0X10-09 ATAD5 20

17q22 rs2787486 17 53209774 A/C 0.3 0.93 (0.9-0.97)

4.33X10-04 0.93 (0.91-0.94)

3.1X10-13 0.93 (0.91-0.94)

1.2X10-14 5.6X10-29 185

17q25.3 rs745570 17 77781725 G/A 0.5 1.05 (1.01-1.08)

1.1X10-02 1.05 (1.03-1.07)

2.9X10-07 1.03 (1.01-1.05)

2.1X10-03 3.9X10-10 20

18q11.2 rs527616 18 24337424 G/C 0.38 0.9 (0.87-0.93)

1.6X10-08 0.95 (0.93-0.97)

1.5X10-07 0.97 (0.95-0.98)

2.8X10-04 6.7X10-15 2

18q11.2 rs1436904 18 24570667 T/G 0.4 0.94 (0.91-0.98)

7.7X10-04 0.96 (0.94-0.97)

4.7X10-06 0.95 (0.94-0.97)

1.1X10-07 9.9X10-15 CHST9 2

18q12.3 rs6507583 18 42399590 A/G 0.07 0.93 (0.87-0.99)

2.9X10-02 0.91 (0.87-0.94)

4.5X10-07 0.92 (0.89-0.96)

9.5X10-06 2.2x10-12 SETBP1 20

19p13.11 rs67397200 19 17401404 C/G 0.3 1.1 (1.06-1.14)

9.3X10-07 1.03 (1.01-1.05)

2.2X10-03 1.03 (1.01-1.05)

4.2X10-03 1.6X10-08 186

19p13.11 rs4808801 19 18571141 A/G 0.34 0.94 (0.91-0.98)

9.7X10-04 0.93 (0.91-0.94)

5.9X10-14 0.93 (0.91-0.95)

2.0X10-13 4.7x10-28 ELL 2

19q13.31 rs3760982 19 44286513 G/A 0.46 1.05 (1.02-1.09)

3.8X10-03 1.05 (1.03-1.07)

9.6X10-08 1.05 (1.03-1.07)

2.1X10-08 1.4X10-16 KCCN4, LYPD5

2

20q11.22 rs2284378 20 32588095 C/T 0.32 1.08 (1.04-1.12)

3.9X10-05 1.01 (0.99-1.04)

1.8X10-01 1 (0.98-1.02)

7.9X10-01 3.2X10-02 RALY 174

21q21.1 rs2823093 21 16520832 G/A 0.27 0.96 (0.93-1)

6.7X10-02 0.93 (0.91-0.95)

2.4X10-12 0.94 (0.92-0.96)

1.1X10-09 1.5X10-20 NRIP1 183

22q12.1 rs17879961 22 29121087 A/G 0.005 0.96 (0.72-1.28)

7.7X10-01 1.37 (1.21-1.55)

7.9X10-07 1.26 (1.11-1.42)

2.4X10-04 9.7X10-09 CHEK2 2

22q12.2 rs132390 22 29621477 T/C 0.04 1.27 (1.13-1.43)

3.6X10-05 1.14 (1.08-1.2)

3.8X10-07 1.04 (0.99-1.09)

8.1X10-02 1.2X10-08 EM1D1 2



22q13.1 rs6001930 22 40876234 T/C 0.1 1.15 (1.09-1.22)

3.5X10-07 1.12 (1.09-1.16)

3.5X10-14 1.12 (1.09-1.16)

5.7X10-16 4.4X10-34 MKL1 2

1q32.19 rs4951011 1 203766331 A/G 0.16 1.03 (0.99-1.08)

1.8X10-01 1.03 (1.01-1.06)

1.9X10-02 1.04 (1.02-1.07)

5.4X10-04 1.3X10-05 ZC3H11A 4

5q14.39 rs10474352 5 90732225 C/T 0.16 0.95 (0.91-1)

4.6X10-02 0.94 (0.91-0.97)

2.7X10-05 0.94 (0.92-0.97)

2.7X10-06 4.5X10-11 ARRDC3 4

6q25.19 rs9485372 6 149608874 G/A 0.19 1.01 (0.97-1.06)

5.4X10-01 0.96 (0.93-0.98)

7.9X10-04 0.96 (0.93-0.98)

7.7X10-05 3.5X10-06 TAB2 3

15q26.19 rs2290203 15 91512067 G/A 0.21 0.96 (0.92-1.01)

9.2X10-02 0.96 (0.94-0.99)

2.1X10-03 0.94 (0.92-0.96)

1.8X10-07 8.07X10-10 PRC1 4

22q13.19 chr22:39359355 22 39359355 I/D10 0.1 1.12 (1.04-1.22)

4.9X10-03 1.06 (1.02-1.11)

3.4X10-03 1.1 (1.07-1.14)

6.1X10-09 4.9X10-12 APOBEC3A, APOBEC3B

5



Supplementary Table 24: Comparison of themes found in the enrichment map (Extended Data Figure 2) and those found in previous analysis of breast cancer GWAS, together with references.

Theme BC GWAS References Theme FDR Novel Genes

Androgen Receptor Activity 187

Antigen Processing and Presentation 75

AP-1 Pathway 188

ATF-2 Pathway 189

Autophosphorylation 3.10E-05 FES,MAP3K11,CLK2,GRK7

Beta Catenin Signaling 190

c-Myb Pathway 191

c-Myc Pathway 192

cAMP Metabolism 73,75

Catabolic Process 0.04126 USP25,DFFA,PKP1,ZKSCAN3

Cell Cycle/DNA Damage Checkpoint 74

Ceramide Signaling 193

Circadian Clock 71

Double Strand Break Repair 194

ERK1/2 Cascade 72

Estrogen Receptor Alpha Pathway 195

Exocytosis 0.00248 SYT8,RAB3A,TC2N,FES

FGF Signaling 14

FOXM1 Signaling 196

Gene Silencing 197

Growth Factor Pathways 74

Hedgehog Signaling 198

IL2 Signaling 74

Interferon Gamma Signaling 199

Ion Homeostasis 72


SUPPLEMENTARY INFORMATIONRESEARCHdoi:10.1038/nature24284

KRAS Signaling 0.02961 PLEK2,KCNN4,ATG10,CBX8, TSPAN1

LKB1 Signaling 200

Map Kinase Signaling 72

Mitochondrial Protein Import 0.03529 HSCB,SLC25A13,SLC25A12,MTX1,TOMM70A,COQ2

Mitochondrial Translation 201

NF-kB Pathway 202

Nitric Oxide Biosynthesis 203

Notch Signaling 71

Organ Morphogenesis 72

p38 MAPK Signaling 204

Protein Kinase Activity 72

RAS Signaling 205

T Cell Activation 72

Telomerase Activity 206

Wnt Signaling 16



Supplementary Note

In Silico Annotation of Candidate Causal Variants

Guide to results in Supplementary Tables 13 and linked UCSC Genome Browser sessions.

Each candidate causal SNP has been annotated with publicly available genomic data in order to highlight potentially functional variants, prioritise experimental validation, and predict target genes. Annotations fall into categories relating to putative effects on transcription factors, regulatory element activities, expression quantitative trait loci (eQTL) and target gene prediction. For each variant, a link to the UCSC Genome Browser is provided that shows a 1 Mb region with relevant genomic data.

Transcription factors

Information regarding potential effects on transcription factor recognition sequences was obtained from the ENCODE-Motifs resource (http://compbio.mit.edu/encode-motifs)207 using VCFtools v0.1.11 to access the downloaded HaploReg v4.0 database208. The impact each variant has on the position weight matrix for specific transcription factors is expressed as ‘+’ or ‘-’ for strengthened or weakened motifs relative to elements carrying the reference allele, respectively. Processed transcription factor ChIP-seq peak data for breast cell types were downloaded from ENCODE and other publications via NCBI GEO, in BED or NarrowPeak format, converted to the hg19 assembly using LiftOver if required, and given a standardised naming system (format = “celltype;target” in Supplementary Table 13). More details about the overlapping binding sites may be found within browser session track "TF-chip peaks overlapping candidate SNP" where TF-ChIP-seq peaks are named in the format “Biosample_term_name, Experiment_target, Biosample_treatments, Biological_replicate(s), File_accession”. All ChIP-seq datasets are listed in Supplementary Table 6. Variants were assessed for overlap with ChIP-seq peaks using BedTools v2.25.0.209

Regulatory features

Histone signatures derived from histone modification ChIP-seq experiments on breast cell types carried out by ENCODE, NIH Roadmap Epigenomics, and other published studies were obtained and formatted as for ChIP-seq data. Histone modification peaks overlapping candidate causal variants are represented as “celltype;histone_mark” in Supplementary Table 13 and “Biosample_term_name, Experiment_target, Biosample_treatments, Biological_replicate(s), File_accession” in the browser track “Histone modification ChIP-seq peaks overlapping candidate SNP”. BedTools was used to intersect variants with histone signatures including commonly used marks associated with enhancers (H3K4me1, H3K4me2 and H3K27ac) and promoters (H3K4me3 and H3K9ac). Chromatin Hidden Markov Modelling (ChromHMM) states were obtained for breast cells from Roadmap (HMEC and myoepithelial cells) and published MCF7 data210 and filtered for states corresponding to ‘enhancers’ (Roadmap 25-state E13, E14, E15, E16, E17, E18) or ‘promoters’ (Roadmap 25-state E1, E2, E3, E4, E22, E23). Chromatin state features containing candidate variants are represented as “celltype;chromatin_state”. Chromatin accessibility data obtained from ENCODE, Roadmap and other published sources via NCBI GEO measured using DNase-seq and FAIRE-seq for relevant breast cell types were also tested for overlap with candidate causal variants. Intersected



http://h/

regions are reported in the format “celltype;method”. Scores based on RegulomeDB211 are presented for available SNPs (based on dbSNP141), where lower scores are increasingly likely to be functional (http://regulomedb.org/help#score).

Other genomic features

Chromosomal position, the lead variant for the associated locus, and potentially conflicting rsIDs (assessed as overlapping at the query position) are given for each variant. GWAS tagSNPs were downloaded from the UCSC Table Browser (December 2015) and associated traits are listed if the tagSNP is within a 10 kb window of the candidate causal variant. NCBI RefSeq gene annotations were downloaded from the UCSC Table Browser and BedTools was used to determine overlapping genes (“Overlapping_RefGene”). The nearest RefGene transcription start site is also presented, given in the format “RefGeneTSS|distance”. Basic genomic annotations such as intergenic, intronic, exonic, and untranslated regions based on RefSeq gene annotations were determined for each variant.

Target Gene Prediction

The column headed “Predicted_target_gene” lists genes predicted by various methods to be targets of, or the expression of which is associated with, regulatory elements in which the candidate causal variant lies. The reported gene is listed with cell type and method in the format “target:cell:method”. A database was created comprising publicly available data based on various methods aiming to link enhancers with target genes (Supplementary Table 33). Laboratory based experimental approaches include genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET)212, Hi-C41, and other Chromosome conformation capture (3C)-based techniques. Computational resources designed to predict target promoters by correlation of gene expression with ChIP-seq signals at specific regulatory elements including IM-PET45, PreSTIGE44 and data from Hnisz et al.47 are also included. These methods associate enhancers defined by histone modification ChIP-seq for H3K4me1 (PreSTIGE), H3K27ac (Hnisz), H3K4me1, H3K4me3 and H3K27ac (IM-PET) with gene expression signals measured by RNA-seq. FANTOM546 data representing enhancer-promoter cap analysis of gene expression (CAGE) expression correlation from all cell types were downloaded from http://enhancer.binf.ku.dk/. Target genes have been predicted for multiple cell types and all data were included in the database, and filtered for breast derived cell types for this analysis (see Supplementary Notes Table 32).

The following strategy was used to assign potential target genes to regulatory elements. The published computational methods (Hnisz, PreSTIGE and IM-PET) included target gene annotation in the reported data. For ChIA-PET and Hi-C data, interaction peaks were mapped to promoters defined as -1.0 kb to +0.1 kb around GENCODE (v19) transcription start sites. Enhancer definitions were used as reported for computational methods while for ChIA-PET and Hi-C were interpreted as any region interacting with a promoter (regardless of other enhancer annotation information such as histone modification or open chromatin). FANTOM5 target promoters were predefined and tissue specificity was determined by intersecting “TSS associated enhancers” with tissue-specific sets of enhancers.



http://regulomedb.org/help#/h

http://h/

All data were formatted to enable intersection of test variants with “enhancers” as defined by each method using the Galaxy “intersect” tool213. Each enhancer-promoter assignment or interaction was represented as a single record along with details about potential target promoter, cell type, method, scoring and confidence statistics from the original publication. A set of query SNPs (or any loci with genomic positional information in BED format) could be queried into a custom Galaxy workflow leading to generation of a table of predicted gene targets and a link to the UCSC Genome Browser for visualisation.

UCSC Genome Browser session

A custom session has been uploaded to UCSC Genome Browser214 to facilitate exploration of breast cancer risk associated variation and implicated regulatory features. This can be accessed via the hyperlink (ie. “browser”) in the functional annotation xlsx file. All standard Genome Browser data and functions are then available, including track display options (eg. right click on a particular track to activate visualisation options), highlighting regions (shift and mouse over region of interest), and the table browser (eg. to intersect or export data).

Within the session, OncoArray candidate causal variants are shown in red, and names can be shown by activating “pack” mode (as for all tracks). Target gene prediction data from Hnisz, PreSTIGE and IM-PET shows enhancers depicted as black bars. The segment name revealed in ‘pack’ mode lists predicted target gene and cell-type (eg “WNT7B.MCF7”). ChIA-PET interactions, represented in BED12 format, have been filtered to remove duplicates and trans-chromosomal interactions. The interactions are shaded to reflect statistical confidence based on enrichment in the original experiment. ChIA-PET interaction names show the genomic co-ordinates of either end of the interaction, the cell type (restricted to MCF7 for this analysis), the immunoprecipitation target, and the experimental replicate. Depicted interactions are restricted to those for which a candidate variant lies within an interaction “end” with the opposite end overlapping a TSS. All other interactions may be visualised by activating the standard ENCODE ChIA-PET track (\Regulation\ENCODE Chromatin Interactions Tracks\ChIA-PET from ENCODE/GIS-Ruan).

Chromatin interactions based on in situ Hi-C data from HMEC cells were downloaded from NCBI GEO (accession GSE63525)41. Annotated loops (representing potential enhancer-promoter interactions) processed by HiCCUPS were reformatted as BED files and tested for overlap with RefSeq promoters to assign potential target genes. Opposing ends of TSS-overlap loops were then annotated as ‘potential enhancers’. Specific loop regions which overlap BC risk candidate causal variants are depicted as black segments and named “TSS_target.Celltype”.

Various classes of genomic data representing regulatory features which harbour candidate variants are shown as separate tracks:

● Histone modification ChIP-seq peaks overlapping candidate SNP

● DNase HS and FAIRE-seq peaks overlapping candidate SNP



http://h/

● TF-chip peaks overlapping candidate SNP

As mentioned above, changing the track display to ‘pack’ mode will show details of the overlapping peak in the format:

“Biosample_term_name, Experiment_target, Biosample_treatments, Biological_replicate(s), File_accession”.

A representation of all TF and histone ChIP-seq, DNase-seq, and FAIRE-seq data tested for overlap with candidate variants is shown in three histogram tracks (computed with BedTools genomeCoverageBed). These show the summed peak density at each genomic position and allow simple visualisation of loci with relative abundance of regulatory features.

Tracks for Roadmap Epigenomics Chromatin state models (based on imputed data - 25 state, 12 marks, 127 epigenomes) were generated for breast Myoepithelial and HMEC cells. Chromatin states were separated and colour coded for states related to enhancers, promoters, and transcribed regions.

The bottom track (“Oncoarray SNPs”) shows all directly genotyped and imputed SNPs passing quality control (imputation r2>0.3) as black ticks. SNPs from dbSNP build 138 with a MAF > 0.01 in European samples which were not informative are shown in red.



Funding

Genotyping of the OncoArray was principally funded from three sources: the PERSPECTIVE project, funded from the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie, de la Science et de l'Innovation du Québec through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery,Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH Grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and. C1287/A16563). BCAC is funded by Cancer Research UK [C1287/A16563] and by the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS) and by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreements 633784 (B-CAST) and 634935 (BRIDGES). Genotyping of the iCOGS array was funded by the European Union (HEALTH-F2-2009-223175), Cancer Research UK (C1287/A10710), the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program, and the Ministry of Economic Development, Innovation and Export Trade of Quebec – grant # PSR-SIIRI-701. Combining the GWAS data was supported in part by The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA 148065 (DRIVE, part of the GAME-ON initiative).

This work was also funded by:

European Research Council [ERC-2011-294576], European Commission (DG-SANCO, MSCA-IF-2014-EF-656144)), International Agency for Research on Cancer (IARC), World Cancer Research Fund (WCRF), National Health and Medical Research Council of Australia (NHMRC) [400413, 400281, 199600, 209057, 251553, 504711], Victorian Health Promotion Foundation (Australia), Victorian Breast Cancer Research Consortium, National Breast Cancer Foundation (Australia), Queensland Cancer Fund, Cancer Councils of New South Wales, Victoria, Tasmania, South Australia, and Western Australia, Cancer Foundation of Western Australia, Cancer Institute NSW, VicHealth, Australian Institute of Health and Welfare (AIHW), Stichting tegen Kanker (Belgium), FWO (Belgium), Chief Physician Johan Boserup and Lise Boserup Fund (Denmark), Danish Medical Research Council, Herlev and Gentofte Hospital (Copenhagen), Helsinki University Central Hospital Research Fund, Academy of Finland (266528), Finnish Cancer Society, Nordic Cancer Union, Sigrid Juselius Foundation (Finland), special Government Funding (EVO) [Kuopio University Hospital, Oulu University Hospital], Cancer Fund of North Savo (Finland), Finnish Cancer Organizations, University of Eastern Finland, Finnish Cancer Foundation, Academy of Finland [250083, 122715, 251314],Sigrid Juselius Foundation,University of Oulu, University of Oulu Support Foundation, Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l'Alimentation, de l'Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR), Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale (France), Institut National de la Santé et de la Recherche Médicale (INSERM) (France), ELAN-Fond (University Hospital of Erlangen, Germany), Dietmar-Hopp Foundation, Helmholtz Society (Germany), German Cancer Research Center (DKFZ), Alexander von Humboldt Foundation (Germany), German Cancer Aid (70492, 110837 70-2892-BR I, 106332, 108253, 108419, 110826, 110828), Baden Württemberg Ministry of Science, Research and Arts, Federal Ministry of Education and Research (BMBF) (Germany) [01KW9975/5, 01KW9976/8, 01KW9977/0, 01KW0114, 01KH0402, RUS08/017], Robert Bosch Foundation (Germany), Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Evangelische Kliniken Bonn gGmbH (Germany), Johanniter Krankenhaus (Germany), Claudia von Schilling Foundation for Breast Cancer Research, Lower Saxonian Cancer Society (Germany), Rudolf Bartling Foundation (Germany), Friends of Hannover Medical School (Germany), Rudolf Bartling Foundation (Germany), German Academic Exchange Program, DAAD, Hamburg Cancer Society, European Regional Development



Fund and Free State of Saxony, Germany [LIFE - Leipzig Research Centre for Civilization Diseases, 713-241202, 713-241202, 14505/2470, 14575/2470], University of Crete, Hellenic Health Foundation (Greece), Stavros Niarchos Foundation (Greece), Associazione Italiana per la Ricerca sul Cancro-AIRC (Italy), National Research Council (Italy), Italian citizens “5x1000” to Fondazione IRCCS Istituto Nazionale Tumori, Ministry of Education, Science, Sports, Culture and Technology of Japan [170150181, 26253041, 17015049, 221S0001], Ministry Health, Labour and Welfare of Japan, National Cancer Center Research and Development Fund (Japan), Medical Research and development (AMED) (Japan) [15ck0106177h0001], Cancer Bio Bank Aichi (Japan), Program for Cancer Control, Ministry of Health and Welfare, Republic of Korea [#1020350, #1420190), Ministry of Education, Science and Technology [2012-0000347] (Republic of Korea), Research Centre for Genetic Engineering and Biotechnology "Georgi D. Efremov" (Macedonia), Malaysian Ministry of Higher Education [UM.C/HlR/MOHE/06, RP046B-15HTM], Cancer Research Malaysia, Yayasan Sime Darby LPGA Tournament, Dutch Cancer Society [NKI 2007-3839; 2009 4363, RUL 1997-1505, DDHK 2004-3124, DDHK 2009-4318], Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds (Netherlands), Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), Statistics Netherlands (The Netherlands), Biomolecular Resources Research Infrastructure [BBMRI-NL CP16], Research Council of Norway [193387/V50, 193387/H10], South Eastern Norway Health Authority [39346, 27208], Norwegian Cancer Society [419616-71248-PR-2006-0282],K.G. Jebsen Centre for Breast Cancer Research, PBZ_KBN_122/P05/2004 (Poland), Russian Foundation for Basic Research [14-04-97088], Agency for Science, Technology and Research of Singapore (A*STAR), National University Cancer Institute Singapore (NCIS), NMRC (Singapore), Biomedical Research Council (Singapore) [05/1/21/19/425], Instituto de Salud Carlos III (ISCIII) [JR14/00017, ], Programa Grupos Emergentes, Cancer Genetics Unit, Instituto de Investigacion Biomedica (IBI), Orense-Pontevedra-Vigo, Xerencia de Xestion Integrada de Vigo-SERGAS, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia (EC11-192), Fomento de la Investigación Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad (Spain), FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia (Spain), Consejo Nacional de Ciencia y Tecnología (CONACyT) (SALUD-2002-C01-7462), Red Temática de Investigación Cooperativa en Cáncer (Spain) [RD06/0020], Asociación Española Contra el Cáncer, Fondo de Investigación Sanitario (FIS) (Spain) [PI11/00923, PI12/00070, PI13/00061, PI13/01162, PI12/02125, PI13/01136, 10CSA012E], Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra (Spain), Stockholm County Council, Karolinska Institutet, Swedish Cancer Society, Gustav V Jubilee foundation, Bert von Kantzows foundation, Märit and Hans Rausings Initiative Against Breast Cancer (Sweden), Swedish Research Council, Berta Kamprad Foundation, Gunnar Nilsson, Swedish Cancer Foundation, Institute of Biomedical Sciences, Academia Sinica (Taiwan), National Cancer Institute Thailand, Cancer Research UK [14136, C490/A10124, C570/A16491, C1275/A11699, C1275/C22524, C1275/A19187, C1275/A15956, C8221/A19170, C8620/A8372, C12292/A11174, C12292/A20861], Breast Cancer Research Trust (UK), Breast Cancer Campaign [2010PR62, 2013PR044], Breast Cancer Now (UK), NHS funding to Institute of Cancer Research NIHR Biomedical Research Centre and NIHR Comprehensive Biomedical Research Centre, Guy's & St. Thomas' NHS Foundation Trust in partnership with King's College London, UK, the Oxford Biomedical Research Centre, Institute of Cancer Research (UK), National Cancer Research Network (NCRN), Against Breast Cancer (UK), Medical Research Council (UK) [1000143 , MR/M012190/1], Sheffield Experimental Cancer Medicine Centre, Health Research Biomedical Research Centre (Cambridge), Eve Appeal (The Oak Foundation), National Institute for Health Research University College London Hospitals Biomedical Research Centre, US National Cancer Institute (NCI) [CA54281, CA58860, CA63464, CA92044, CA97396, CA098758, CA116167, CA116201, CA128931, CA132839, CA140286, CA164973, CA176785, CA177150, CA192393, CA194393, D43 TW009112, K24 CA169004, N01CN25403, P01 CA87969, P30 CA68485, P41-GM1035, P50 CA125183, R01 CA59736, R01 CA 063697, R01 CA64277, R01 CA77398, R01 CA89085, R01 CA092447, R01 CA100374, R01 CA120120, R01-CA121941, R01 CA122171, R01 CA148667, R01



CA159868, R37CA70867, U01 CA199277, U19 CA148065, U41-HG006623, UM1 CA164917, UM1 CA164920, UM1 CA176726, UM1 CA186107, UMCA182910, Intramural Research Funds], US National Institute of Environmental Health Sciences (NIEHS) [Intramural Program, Z01-ES044005, Z01-ES049033 Z01-ES044005, Z01-ES102245], National Heart, Lung, and Blood Institute, US Department of Health and Human Services [HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C and HHSN271201100004C], United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], American Cancer Society, California Breast Cancer Act of 1993, California Breast Cancer Research Fund [97-10500], California Department of Public Health, Lon V Smith Foundation [LVS39420], California Breast Cancer Research Program [1RB-0287, 3PB-0102, 5PB-0018, 10PB-0098], Breast Cancer Research Foundation, David F. and Margaret T. Grohne Family Foundation, Robert and Kate Niehaus Clinical Cancer Genetics Initiative, Susan G. Komen Breast Cancer Foundation [FAS0703856, SAC110026], Dr. Ralph and Marian Falk Medical Research Trust, Avon Foundation for Women, Lon V Smith Foundation [LVS39420].

Acknowledgments

We thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. This study would not have been possible without the contributions of the following: Andrew Berchuck, Ali Amin Al Olama, Rosalind A. Eeles, Stephen Gruber, Zsofia Kote-Jarai, Sara Benlloch, Sylvie LaBoissière, Frederic Robidoux, Maggie Angelakos, Judi Maskiell, Gillian Dite, Blood bank Sanquin (The Netherlands), ABCTB Investigators (Christine Clarke,Rosemary Balleine, Robert Baxter,Stephen Braye, Jane Carpenter, Jane Dahlstrom, John Forbes, Soon Lee, Debbie Marsh, Adrienne Morey, Nirmala Pathmanathan, Rodney Scott, Allan Spigelman, Nicholas Wilcken, Desmond Yip), Thai Ministry of Public Health (MOPH) doctors and nurses, Prat Boonyawongviroj, Pornthep Siriwanarungsan, Eileen Williams, Elaine Ryder-Mills, Kara Sargus, Allyson Thomson, Christobel Saunders, Terry Slevin, BreastScreen Western Australia, Elizabeth Wylie, Rachel Peake, K. Landsman, N. Gronich, A. Flugelman, W. Saliba, E. Liani, I. Cohen, S. Kalet, V. Friedman, O. Barnet, NiallMcInerney, Gabrielle Colleran, Andrew Rowan, Angela Jones, Victor Muñoz Garzón, Alejandro NovoDomínguez, Sara Miranda Ponte, Carmen Redondo Marey, Maite Peña Fernández, Manuel EnguixCastelo, Maria Torres, Manuel Calaza, José Antúnez, Máximo Fraga and the staff of the Departmentof Pathology and Biobank of the University Hospital Complex of Santiago-CHUS, Instituto deInvestigación Sanitaria de Santiago, IDIS, Xerencia de Xestion Integrada de Santiago-SERGAS, JoaquínGonzález-Carreró and the staff of the Department of Pathology and Biobank of University HospitalComplex of Vigo, Instituto de Investigacion Biomedica (IBI) Orense-Pontevedra-Vigo, Vigo-SERGAS,Spain, Peter Bugert, Germán Castelazo, Sinhué Barroso Bravo, Fernando Mainero Ratchelous,Joaquín Zarco Méndez, Edelmiro Pérez Rodríguez, Jesús Pablo Esparza Cano, Heriberto Fabela,Fausto Hernández Morales, Pedro Coronel Brizio, Vicente A. Saldaña Quiroz, Agnes Lai, CelineMorissette, Styliani Apostolaki, Anna Margiolaki, Georgios Nintos, Maria Perraki, Georgia Saloustrou,Georgia Sevastaki, Konstantinos Pompodakis, Dorthe Uldall Andersen, Maria Birna Arnadottir, AnneBank, Dorthe Kjeldgård Hansen, Danish Cancer Biobank, Guillermo Pita, Charo Alonso, Nuria Álvarez,Pilar Zamora, Primitiva Menendez, the Human Genotyping-CEGEN Unit (CNIO), Justo G. Olaya,Mauricio Tawil, Lilian Torregrosa, Elias Quintero, Sebastian Quintero, Claudia Ramírez, José J.Caicedo, Jose F. Robledo, DT, Ignacio Briceno, Fabian Gil, Angela Umana, Angela Beltran, VivianaAriza, Michael Gilbert, CPS-II investigators, CPS-II Study Management Group, cancer registriessupported by the Centers for Disease Control and Prevention National Program of Cancer Registriesand National Cancer Institute Surveillance Epidemiology and End Results program, CTS SteeringCommittee (Leslie Bernstein, Susan Neuhausen, James Lacey, Sophia Wang, Huiyan Ma, JessicaClague DeHart, Dennis Deapen, Rich Pinder, and Eunjung Lee, Pam Horn-Ross, Peggy Reynolds,Christina Clarke Dur and David Nelson, Hoda Anton-Culver, Argyrios Ziogas, Hannah Park, FredSchumacher), EPIC investigators, Hartwig Ziegler, Sonja Wolf, Volker Hermann, Christa Stegmaier,



Katja Butterbach, Stefanie Engert, Heide Hellebrand, Sandra Kröber, The GENICA Network (Christina Justenhoven, Yon-Dschun Ko, Christian Baisch, Hans-Peter Fischer, Beate Pesch, Sylvia Rabstein, Anne Lotz, Volker Harth), Kelly Kohut, Patricia Gorman, Maria Troy, Michael Bremer, Rainer Fagerholm, Kirsimari Aaltonen, Karl von Smitten, Irja Erkkilä, Peter Hillemanns, Hans Christiansen, Johann H. Karstens, Shamil Gantsev, Kelly Kohut, Michele Caneppele, Maria Troy, Eija Myöhänen, Helena Kemiläinen, Heather Thorne, Eveline Niedermayr,Annie Fung, June Yashiki, Gilian Peuteman, Thomas Van Brussel, EvyVanderheyden, Kathleen Corthouts, Milena Jakimovska, Katerina Kubelka, Mitko Karadjozov, Andrej Arsovski, Liljana Stojanovska, Petra Seibold, Judith Heinz, Nadia Obi, Alina Vrieling, Sabine Behrens, UE, Muhabbet Celik, Til Olchers and Stefan Nickels, Bernard Peissel, Jacopo Azzollini, Daniela Zaffaroni, Lidia Pezzani, Monica Barile, Irene Feroce, staff of Cogentech Cancer Genetic Test Laboratory, Marina Corines, Lauren Jacobs, Martine Tranchant, Marie-France Valois, Annie Turgeon, Lea Heguy, Patsy Ng, Nurhidayu Hassan, Yoon Sook-Yee, Daphne Lee, Lee Sheau Yee, Phuah Sze Yee, Norhashimah Hassan, Kristine K.Sahlberg, Lars Ottestad, Em. Rolf Kåresen, Anita Langerød, Ellen Schlichting, Marit Muri Holmen, Toril Sauer, Vilde Haakensen, Olav Engebråten, Bjørn Naume, Cecile E. Kiserud, Kristin V. Reinertsen, Åslaug Helland, Margit Riis, Ida Bukholm, Per Eystein Lønning, the following US State Cancer Registries: (AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY), Arja Jukkola-Vuorinen, Mervi Grip, Saila Kauppila, Meeri Otsukka, Leena Keskitalo, Kari Mononen , Teresa Selander, Nayana Weerasooriya, E. Krol-Warmerdam, J. Blom, J. Molenaar, Louise Brinton, Mark Sherman, Neonila Szeszenia-Dabrowska, BeataPeplonska, WitoldZatonski, Pei Chao, Michael Stagner, Staff in the Experimental Cancer Medicine Centre, Southampton (ECMC), Sonja Oeser, Silke Landrith, Petra Bos, Jannet Blom, Ellen Crepin, Elisabeth Huijskens, Anja Kromwijk-Nieuwlaat, Annette Heemskerk, Erasmus MC Family Cancer Clinic, Sue Higham, Helen Cramp, Dan Connley, Sabapathy Balasubramanian, Malcolm W.R. Reed, the SEARCH and EPIC teams, Tan Siew Li, SUCCESS Study teams in Munich, Duessldorf, Erlangen and Ulm, Ewa Putresza, Irene Masunaka, LIFE - Leipzig Research Centre for Civilization Diseases (Markus Loeffler, Joachim Thiery, Matthias Nüchter, Ronny Baber), NBCS collaborators (Kristine K. Sahlberg, Lars Ottestad, Rolf Kåresen, Anita Langerød, Ellen Schlichting, Marit Muri Holmen, Toril Sauer, Vilde Haakensen, Olav Engebråten, Bjørn Naume, Cecile E. Kiserud, Kristin V. Reinertsen, Åslaug Helland, Margit Riis, Dr. Ida Bukholm, Per Eystein Lønning, OSBREAC (Oslo Breast Cancer Research Consortium)), and staff at Illumina, including Carsten Rosenow, Jennifer Stone, Claire Attwooll, Mark Hansen, Jane Hadlington. The expression quantitative locus (eQTL) analyses used data generated by the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), funded by Cancer Research UK and the British Columbia Cancer Agency Branch, and by The Cancer Genome Atlas (TCGA) Research Network. MCCS cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database.The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute, CDC, Mississippi Cancer Registry nor any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The authors wish to pay tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his vision and leadership, and sadly passed away before seeing its fruition.

Members of consortia listed as authors

ABCTB Investigators

Christine Clarke (Westmead Institute for Medical Research, University of Sydney, NSW, Australia); Rosemary Balleine (Pathology West ICPMR, Westmead, NSW, Australia); Robert Baxter (Kolling Institute of Medical Research, University of Sydney, Royal North Shore Hospital, NSW, Australia);



Stephen Braye (Pathology North, John Hunter Hospital, Newcastle, NSW, 2305, Australia); Jane Carpenter (Westmead Institute for Medical Research, University of Sydney); Jane Dahlstrom (Department of Anatomical Pathology, ACT Pathology, Canberra Hospital, ACT, Australia; ANU Medical School, Australian National University, ACT, Australia); John Forbes (Department of Surgical Oncology, Calvary Mater Newcastle Hospital, Australian New Zealand Breast Cancer Trials Group, and School of Medicine and Public Health, University of Newcastle, NSW, Australia); C Soon Lee (School of Science and Health, The University of Western Sydney, Sydney, Australia); Deborah Marsh (Hormones and Cancer Group, Kolling Institute of Medical Research, Royal North Shore Hospital, University of Sydney, NSW, Australia); Adrienne Morey (SydPath St Vincent's Hospital, Sydney, NSW, Australia); Nirmala Pathmanathan (Department of Tissue Pathology and Diagnostic Oncology, Pathology West; Westmead Breast Cancer Institute, Westmead Hospital, NSW, Australia); Rodney Scott (Centre for Information Based Medicine, Hunter Medical Research Institute, NSW, 2305, Australia; Priority Research Centre for Cancer, School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, NSW, Australia); Peter Simpson (The University of Queensland: UQ Centre for Clinical Research and School of Medicine, QLD, Australia); Allan Spigelman (Hereditary Cancer Clinic, St Vincent's Hospital, The Kinghorn Cancer Centre, Sydney, New South Wales, 2010, Australia); Nicholas Wilcken (Crown Princess Mary Cancer Centre, Westmead Hospital, Westmead, Australia; Sydney Medical School - Westmead, University of Sydney, NSW, Australia); Desmond Yip (Department of Medical Oncology, The Canberra Hospital, ACT, Australia; ANU Medical School, Australian National University, ACT, Australia); Nikolajs Zeps (St John of God Perth Northern Hospitals, Perth, WA, Australia).

kConFab/AOCS Investigators

Stephen Fox, Ian Campbell (Peter MacCallum Cancer Centre, Melbourne, Australia); Georgia Chenevix-Trench, Amanda Spurdle, Penny Webb (QIMR Berghofer Medical Research Institute, Brisbane, Australia); Anna de Fazio (Westmead Millenium Institute, Sydney, Australia); Margaret Tassell (BCNA delegate, Community Representative); Judy Kirk (Westmead Hospital, Sydney, Australia); Geoff Lindeman (Walter and Eliza Hall Institute, Melbourne, Australia); Melanie Price (University of Sydney, Sydney, Australia); Melissa Southey (University of Melbourne, Melbourne, Australia); Roger Milne (Cancer Council Victoria, Melbourne, Australia); Sid Deb (Melbourne Health, Melbourne, Australia); David Bowtell (Garvan Institute of Medical Research, Sydney, Australia).

NBSC Collaborators

Kristine K. Sahlberg (Department of Research, Vestre Viken Hospital, Drammen, Norway; Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Lars Ottestad (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Rolf Kåresen (Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Breast- and Endocrine Surgery, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital Ullevål, Oslo, Norway); Anita Langerød (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Ellen Schlichting (Department of Breast- and Endocrine Surgery, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital Ullevål, Oslo, Norway); Marit Muri Holmen (Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway); Toril Sauer (Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Pathology at Akershus University hospital, Lørenskog, Norway); Vilde Haakensen (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Olav Engebråten (Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Oncology, Division of Surgery and Cancer and Transplantation Medicine, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Bjørn Naume (Department of Oncology,



Division of Surgery and Cancer and Transplantation Medicine, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Cecile E. Kiserud (National Advisory Unit on Late Effects after Cancer Treatment, Department of Oncology, Oslo University Hospital, Oslo, Norway; Department of Oncology, Oslo University Hospital Ullevål, Oslo, Norway); Kristin V. Reinertsen (National Advisory Unit on Late Effects after Cancer Treatment, Department of Oncology, Oslo University Hospital, Oslo, Norway; Department of Oncology, Oslo University Hospital Ullevål, Oslo, Norway); Åslaug Helland (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Oncology, Division of Surgery and Cancer and Transplantation Medicine, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Margit Riis (Department of Breast- and Endocrine Surgery, Division of Surgery, Cancer and Transplantation Medicine, Oslo University Hospital Ullevål, Oslo, Norway); Jürgen Geisler (Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Breast-Endocrine Surgery, Akershus University Hospital, Oslo, Norway); Per Eystein Lønning (Section of Oncology, Institute of Medicine, University of Bergen and Department of Oncology, Haukeland University Hospital, Bergen, Norway); Solveig Hofvind (Cancer Registry of Norway, Oslo, Norway, Oslo; Akershus University College of Applied Sciences, Faculty of Health Science, Oslo, Norway); Tone F. Bathen (Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway); Elin Borgen (Department of Pathology, Division of Diagnostics and Intervention, Oslo University Hospital, Oslo, Norway); Øystein Fodstad (Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway; Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Øystein Garred (Department of Pathology, Oslo University Hospital, Oslo, Norway); Gry Aarum Geitvik (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Gunhild Mari Mælandsmo (Department of Tumor Biology, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Pharmacy, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway); Hege G. Russnes (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway; Department of Pathology, Oslo University Hospital, Oslo, Norway); Therese Sørlie (Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway); Ole Christian Lingjærde (Department of Computer Science, University of Oslo, Oslo, Norway); Helle Kristine Skjerven (Breast and Endocrine Surgery, Department of Breast and Endocrine Surgery, Vestre Viken Hospital, Drammen, Norway); Britt Fritzman (Østfold Hospital, Østfold, Norway).



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Supplementary Excel Table guide Supplied in a combined file:

Supplementary Table 3 Associations between previously reported breast cancer associated SNPs and ER-positive breast cancer risk in the combined analysis of the GWAS + iCOGS + OncoArray data, together with test of difference in per-allele ORs for ER-positive and ER-negative disease.

Supplementary Table 4 Associations between previously reported breast cancer associated SNPs and ER-negative breast cancer risk in the combined analysis of the GWAS + iCOGS + OncoArray data.

Supplementary Table 5 Associations by ER status, from the meta-analysis of GWAS, iCOGS and OncoArray data, for the 65 SNPs associated in women of Asian ancestry.

Supplementary Table 7 List of 65 breast cancer loci, with the number of credible risk variants and browser links.

Supplementary Table 9

Association analysis for two regions showing evidence of association after adjustment for the lead SNP.

Supplementary Table 10 Associations between SNP genotype and ER-negative disease for the 65 SNPs associated with overall breast cancer, together with test of difference in per-allele OR between ER-positive and ER-negative disease.

Supplementary Table 11 Associations between SNP genotype and ER-positive disease for the 65 SNPs associated with overall breast cancer.

Supplementary Table 12 Associations for novel breast cancer associated SNPs and breast cancer risk in women of Asian ancestry, in the combined iCOGS + OncoArray dataset.

Supplementary Table 14 List of 2,232 credible risk variants from 77 existing loci, defined by a p-value >1/100 fold that of the most significant SNP in the interval (see Online Methods). top_snp: most significant SNP in the region (see spreadsheet).

Supplementary Table 15 Genomic predictors of credible risk variants, for previously identified and novel loci.

Supplementary Table 16 List of 67 genomic predictors considered for association with credible risk variants.

Supplementary Table 17 In silico predictions and weighting scheme used in INQUISIT.



Supplementary Table 21 Analysis of association between driver genes and INQUISIT scores.

Supplementary Table 22 Enrichment map details. This table contains details about the themes, pathways, genes and SNPs appearing in the enrichment map (Extended Data Figure 2).

Supplementary Table 23 This table lists all unique genes and SNPs in the themes appearing in the enrichment map (Extended Data Figure 2). The tables list all enriched pathways containing between 10 and 200 genes with at least one gene reaching P<5×10-8 (See Online Methods). Only significant genes are listed in the tables (P<5×10-8). Novel genes (i.e. not found among genes in pathways known to be involved in breast cancer) are indicated under the theme name.

Supplementary Table 25 Global Genomic Feature Enrichments including significantly enriched baseline annotations for overall breast cancer (after Bonferroni correction for 53 annotations),

Supplementary Table 26 Global Genomic Feature Enrichments including significantly enriched cell type-specific annotations for overall breast cancer (after Bonferroni correction for 220 cell-type specific annotations).

Supplementary Table 27 Global Genomic Feature Enrichments including significantly enriched cell type-specific annotations for ER-positive breast cancer (after Bonferroni correction for 220 cell-type specific annotations).

Supplementary Table 28 Imputation quality score and heterogeneity among studies for the 65 newly identified risk variants for overall breast cancer.

Supplementary Table 29 Genotype specific ORs for the 65 novel SNPs for overall breast cancer. Estimated ORs based on a combined analysis of the estimated from the iCOGS and OncoArray stages.

Supplementary Table 30 ENCODE RNA-seq data accession numbers.

Supplementary Table 31 Breast cancer driver genes.

Supplementary Table 32 Oligonucleotides used in 3C assays.

Supplementary Table 33 Summary of chromatin interaction and enhancer-promoter annotation methods.

Supplied as individual files:

Supplementary Table 6 Sixty-five newly identified susceptibility loci for overall breast cancer.



Supplementary Table 8 This table contains summary statistics for all variants for which the association with overall breast cancer in the combined dataset was significant at P<0.00001.

Supplementary Table 13 This table contains a list of 2,221 credible variants at 65 novel loci, with annotations, UCSC Genome Browser links, and sources for genomic annotation data.

Supplementary Table 18 This table displays eQTL associations significant at P<0.05 in the TCGA and METABRIC datasets, for credible risk variants from the analyses for overall breast cancer (see Online Methods), together with the corresponding results for the most significant eQTL association in the region for the same gene.

Supplementary Table 19 This table contains summary INQUISIT gene prediction scores.

Supplementary Table 20 This table contains detailed INQUISIT gene prediction scores.



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SUPPLEMENTAR Y INFORMATION - Nature · Association analysis identifies 65 new breast cancer risk loci and predicts target genes. Kyriaki Michailidou, Sara Lindström, Joe Dennis,