Imperial College London



TITLEAnalysis of heritability and shared heritability based on genome-wide association studies for thirteen cancer typesAUTHORSJoshua N Sampson1,?, William A Wheeler2,252, Meredith Yeager3,252, Orestis Panagiotou1,252, Zhaoming Wang3,252, Sonja I Berndt1,252, Qing Lan1,252, Christian C Abnet1,252, Laufey T Amundadottir1,252, Jonine D Figueroa1,252, Maria Teresa Landi1,252, Lisa Mirabello1,252, Sharon A Savage1,252, Philip R Taylor1,252, Immaculata De Vivo4,5,252, Katherine A McGlynn1,252, Mark P Purdue6,252, Preetha Rajaraman1,252, Hans-Olov Adami5,7, Anders Ahlbom8, Demetrius Albanes1, Maria Fernanda Amary9,10, She-Juan An11, Ulrika Andersson12, Gerald Andriole Jr13, Irene L Andrulis14,15, Emanuele Angelucci16, Stephen M Ansell17, Cecilia Arici18, Bruce K Armstrong19, Alan A Arslan20,21,22,23, Melissa A Austin24, Dalsu Baris1, Donald A Barkauskas25, Bryan A Bassig1,26, Nikolaus Becker27, Yolanda Benavente28,29, Simone Benhamou30,31, Christine Berg32, David Van Den Berg25,33, Leslie Bernstein34, Kimberly A Bertrand4,5, Brenda M Birmann4, Amanda Black1, Heiner Boeing35, Paolo Boffetta36, Marie-Christine Boutron-Ruault37,38,39, Paige M Bracci40, Louise Brinton1, Angela R Brooks-Wilson41,42, H Bas Bueno-de-Mesquita43,44, Laurie Burdett3, Julie Buring45,46, Mary Ann Butler47, Qiuyin Cai48,49, Geraldine Cancel-Tassin50,51, Federico Canzian52, Alfredo Carrato53, Tania Carreon47, Angela Carta18, John K C Chan54, Ellen T Chang55,56, Gee-Chen Chang57,58, I-Shou Chang59, Jiang Chang60, Jenny Chang-Claude27, Chien-Jen Chen61, Chih-Yi Chen62, Chu Chen63, Chung-Hsing Chen59, Constance Chen4,5,64, Hongyan Chen65, Kexin Chen66, Kuan-Yu Chen67, Kun-Chieh Chen58, Ying Chen68, Ying-Hsiang Chen69, Yi-Song Chen69, Yuh-Min Chen70,71, Li-Hsin Chien69, María-Dolores Chirlaque29,72, Jin Eun Choi73, Yi Young Choi73, Wong-Ho Chow1, Charles C Chung1, Jacqueline Clavel38,74, Fran?oise Clavel-Chapelon37,38,39, Pierluigi Cocco75, Joanne S Colt1, Eva Comperat50,51,76,77, Lucia Conde78,79, Joseph M Connors80,81, David Conti25,33, Victoria K Cortessis25,33,82, Michelle Cotterchio83,84, Wendy Cozen25,33, Simon Crouch85, Marta Crous-Bou4,5, Olivier Cussenot50,51,86, Faith G Davis87, Ti Ding88, W Ryan Diver89, Miren Dorronsoro29,90, Laure Dossus37,38,39, Eric J Duell91, Maria Grazia Ennas92, Ralph L Erickson93, Maria Feychting8, Adrienne M Flanagan9,10, Lenka Foretova94, Joseph F Fraumeni Jr1, Neal D Freedman1, Laura E Beane Freeman1, Charles Fuchs4,95, Manuela Gago-Dominguez96, Steven Gallinger15, Yu-Tang Gao97, Susan M Gapstur89, Montserrat Garcia-Closas1,98, Reina García-Closas99, Randy D Gascoyne80,100, Julie Gastier-Foster101,102, Mia M Gaudet89, J Michael Gaziano45,46,103, Carol Giffen2, Graham G Giles104,105, Edward Giovannucci4,5,64, Bengt Glimelius106,107, Michael Goggins108,109,110, Nalan Gokgoz14,15, Alisa M Goldstein1, Richard Gorlick111, Myron Gross112, Robert Grubb III13, Jian Gu113, Peng Guan114, Marc Gunter115, Huan Guo116, Thomas M Habermann17, Christopher A Haiman33, Dina Halai9,10, Goran Hallmans117, Manal Hassan118, Claudia Hattinger119, Qincheng He114, Xingzhou He120, Kathy Helzlsouer121, Brian Henderson25, Roger Henriksson12, Henrik Hjalgrim122, Judith Hoffman-Bolton121, Chancellor Hohensee63, Theodore R Holford123, Elizabeth A Holly40, Yun-Chul Hong124, Robert N Hoover1, Pamela L Horn-Ross125, GM Monawar Hosain126, H Dean Hosgood III127, Chin-Fu Hsiao69,128, Nan Hu1, Wei Hu1, Zhibin Hu129,130, Ming-Shyan Huang131, Jose-Maria Huerta72, Jen-Yu Hung131, Amy Hutchinson3, Peter D Inskip1, Rebecca D Jackson132, Eric J Jacobs89, Mazda Jenab133, Hyo-Sung Jeon134, Bu-Tian Ji1, Guangfu Jin129,130, Li Jin65, Christoffer Johansen135, Alison Johnson136, Yoo Jin Jung137, Rudolph Kaaks27, Aruna Kamineni138, Eleanor Kane85, Chang Hyun Kang137, Margaret R Karagas139, Rachel S Kelly5,140, Kay-Tee Khaw141, Christopher Kim1, Hee Nam Kim142, Jin Hee Kim143, Jun Suk Kim144, Yeul Hong Kim145, Young Tae Kim137, Young-Chul Kim146,147, Cari M Kitahara1, Alison P Klein121,148, Robert J Klein149, Manolis Kogevinas150,151,152, Takashi Kohno153, Laurence N Kolonel154, Charles Kooperberg63, Anne Kricker19, Vittorio Krogh155, Hideo Kunitoh156, Robert C Kurtz157, Sun-Seog Kweon158,159, Andrea LaCroix63, Charles Lawrence160, Fernando Lecanda161, Victor Ho Fun Lee162, Donghui Li118, Haixin Li66, Jihua Li163, Yao-Jen Li61, Yuqing Li164, Linda M Liao1, Mark Liebow17, Tracy Lightfoot85, Wei-Yen Lim68, Chien-Chung Lin165, Dongxin Lin60, Sara Lindstrom4,5, Martha S Linet1, Brian K Link166, Chenwei Liu3, Jianjun Liu167, Li Liu168, B?rje Ljungberg169, Josep Lloreta29, Simonetta Di Lollo170, Daru Lu65, Eiluv Lund171, Nuria Malats172, Satu Mannisto173, Loic Le Marchand174, Neyssa Marina175, Giovanna Masala176, Giuseppe Mastrangelo177, Keitaro Matsuo178, Marc Maynadie179, James McKay133, Roberta McKean-Cowdin25, Mads Melbye122,180, Beatrice S Melin12, Dominique S Michaud181,182, Tetsuya Mitsudomi183, Alain Monnereau38,74,184, Rebecca Montalvan160, Lee E Moore1, Lotte Maxild Mortensen185,186, Alexandra Nieters187, Kari E North188,189, Anne J Novak17, Ann L Oberg190, Kenneth Offit157, In-Jae Oh146,147, Sara H Olson191, Domenico Palli176, William Pao192, In Kyu Park137, Jae Yong Park193, Kyong Hwa Park145, Ana Pati?o-Garcia161, Sofia Pavanello177, Petra H M Peeters115,194,195, Reury-Perng Perng70, Ulrike Peters63, Gloria M Petersen196, Piero Picci119, Malcolm C Pike191, Stefano Porru18, Jennifer Prescott4,5, Ludmila Prokunina-Olsson1, Biyun Qian197, You-Lin Qiao198, Marco Rais75, Elio Riboli182, Jacques Riby78,79, Harvey A Risch199, Cosmeri Rizzato52, Rebecca Rodabough63, Eve Roman85, Morgan Roupret50,51,76, Avima M Ruder47, Silvia de Sanjose28,29, Ghislaine Scelo133, Alan Schned139, Fredrick Schumacher25, Kendra Schwartz200,201, Molly Schwenn202, Katia Scotlandi119, Adeline Seow68, Consol Serra203, Massimo Serra119, Howard D Sesso5,45,46, Veronica Wendy Setiawan25, Gianluca Severi104,105,204, Richard K Severson200, Tait D Shanafelt17, Hongbing Shen129,130, Wei Shen129,130, Min-Ho Shin159, Kouya Shiraishi153, Xiao-Ou Shu48,49, Afshan Siddiq182, Luis Sierrasesúmaga161, Alan Dart Loon Sihoe205, Christine F Skibola78,79, Alex Smith85, Martyn T Smith79, Melissa C Southey206, John J Spinelli207,208, Anthony Staines209, Meir Stampfer4,5,64, Marianna C Stern25,33, Victoria L Stevens89, Rachael S Stolzenberg-Solomon1, Jian Su11, Wu-Chou Su210, Malin Sund211, Jae Sook Sung212, Sook Whan Sung213, Wen Tan60, Wei Tang1, Adonina Tardón29,214, David Thomas215, Carrie A Thompson17, Lesley F Tinker63, Roberto Tirabosco10, Anne Tj?nneland216, Ruth C Travis217, Dimitrios Trichopoulos5,218,219, Fang-Yu Tsai59, Ying-Huang Tsai220, Margaret Tucker1, Jenny Turner221,222, Claire M Vajdic223, Roel C H Vermeulen194,224, Danylo J Villano157, Paolo Vineis140,204, Jarmo Virtamo173, Kala Visvanathan121, Jean Wactawski-Wende225, Chaoyu Wang1, Chih-Liang Wang226, Jiu-Cun Wang65,227, Junwen Wang228,229, Fusheng Wei230, Elisabete Weiderpass7,171,231,232, George J Weiner166, Stephanie Weinstein1, Nicolas Wentzensen1, Emily White24,63, Thomas E Witzig17, Brian M Wolpin95,233, Maria Pik Wong234, Chen Wu60,235, Guoping Wu230, Junjie Wu65, Tangchun Wu116, Wei Wu114, Xifeng Wu113, Yi-Long Wu11, Jay S Wunder14,15, Yong-Bing Xiang236, Jun Xu237, Ping Xu238, Pan-Chyr Yang239, Tsung-Ying Yang58, Yuanqing Ye113, Zhihua Yin114, Jun Yokota240, Ho-Il Yoon241, Chong-Jen Yu67, Herbert Yu174, Kai Yu1, Jian-Min Yuan242, Andrew Zelenetz157, Anne Zeleniuch-Jacquotte21,22,23, Xu-Chao Zhang11, Yawei Zhang26, Xueying Zhao65, Zhenhong Zhao65, Hong Zheng66, Tongzhang Zheng26, Wei Zheng48,49, Baosen Zhou114, Meng Zhu129,130, Mariagrazia Zucca92, Simina M Boca243,244,253, James R Cerhan245,253, Giovanni M Ferri246,253, Patricia Hartge1,253, Chao Agnes Hsiung69,253, Corrado Magnani247,253, Lucia Miligi248,253, Lindsay M Morton1,253, Karin E Smedby249,253, Lauren R Teras89,253, Joseph Vijai157,253, Sophia S Wang34,253, Paul Brennan133,253, Neil E Caporaso1,253, David J Hunter4,5,64,250,253, Peter Kraft5,251,253, Nathaniel Rothman1,253, Debra T Silverman1,253, Susan L Slager245,253, Stephen J Chanock1,254, Nilanjan Chatterjee1,254,?.AFFILIATIONS1Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA. 2Information Management Services, Silver Spring, Maryland, USA. 3Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Gaithersburg, Maryland, USA. 4Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. 5Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. 6Ontario Health Study, Toronto, Ontario, Canada. 7Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. 8Unit of Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. 9UCL Cancer Institute, London, United Kingdom. 10Royal National Orthopaedic Hospital NHS Trust, Stanmore, Middlesex, United Kingdom. 11Guangdong Lung Cancer Institute, Guangdong Provincial Key Laboratory of Translational Medicine in Lung Cancer, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China. 12Department of Radiation Sciences, Oncology, Umea University, Umea, Sweden. 13Division of Urologic Surgery, Washington University School of Medicine, Saint Louis, Missouri, USA. 14Litwin Centre for Cancer Genetics, University of Toronto, Ontario, Canada. 15Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. 16Hematology Unit, Ospedale Oncologico di Riferimento Regionale A. Businco, Cagliari, Italy. 17Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA. 18Department of Medical and Surgical Specialties, Radiological Sciences and Public Health, University of Brescia, Brescia, Italy. 19Sydney School of Public Health, The University of Sydney, Sydney, New South Wales, Australia. 20Department of Obstetrics and Gynecology, New York University School of Medicine, New York, New York, USA. 21Department of Environmental Medicine, New York University School of Medicine, New York, New York, USA. 22Department of Population Health, New York University School of Medicine, New York, New York, USA. 23Perlmutter Cancer Center, NYU Langone Medical Center, New York, New York, USA. 24Department of Epidemiology, University of Washington, Seattle, Washington, USA. 25Department of Preventive Medicine, USC Keck School of Medicine, University of Southern California, Los Angeles, California, USA. 26Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA. 27Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Baden-Württemberg, Germany. 28Unit of Infections and Cancer (UNIC), Cancer Epidemiology Research Programme, Institut Catala d’Oncologia, IDIBELL, Barcelona, Spain. 29Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain. 30Institut national de la sante et de la recherche medicale, U946, Foundation Jean Dausset Centre d'Etude du Polymorphisme Humain (CEPH), Paris, France. 31Centre National de la Receherche Scientifique, UMR8200, Institut Gustave-Roussy, Villejuif, France. 32Early Detection Research Group, Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, USA. 33Norris Comprehensive Cancer Center, USC Keck School of Medicine, University of Southern California, Los Angeles, California, USA. 34Department of Cancer Etiology, Beckman Research Institute of City of Hope, Duarte, California, USA. 35Department of Epidemiology, German Institute for Human Nutrition, Potsdam, Germany. 36The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA. 37Inserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Nutrition, Hormones and Women’s Health team, F-94805, Villejuif, France. 38Université Paris Sud, UMRS 1018, F-94805, Villejuif, France. 39Institut Gustave Roussy, F-94805, Villejuif, France. 40Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, California, USA. 41Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada. 42Department of Biomedical Physiology and Kinesiology, Simon Fraser University, Burnaby, British Columbia, Canada. 43National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands. 44Department of Gastroenterology and Hepatology, University Medical Centre Utrecht, Utrecht, The Netherlands. 45Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA. 46Division of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Maryland, USA. 47Centers for Disease Control and Prevention, National Institute for Occupational Safety and Health, Cincinnati, Ohio, USA. 48Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 49Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 50Centre de Recherche sur les Pathologies Prostatiques, Paris, France. 51UPMC Univ Paris 06, GRC n°5, ONCOTYPE-URO, Paris, France. 52Genomic Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany. 53Ramon y Cajal University Hospital, Madrid, Spain. 54Department of Pathology, Queen Elizabeth Hospital, Hong Kong, China. 55Division of Epidemiology, Department of Health Research and Policy, Stanford University School of Medicine, Stanford, California, USA. 56Center for Epidemiology and Computational Biology, Health Sciences , Exponent, Inc., Menlo Park , California, USA. 57Department of Medicine, School of Medicine, National Yang-Ming University, Taipei, Taiwan. 58Department of Internal Medicine, Division of Chest Medicine, Taichung Veterans General Hospital, Taichung, Taiwan. 59National Institute of Cancer Research, National Health Research Institutes, Zhunan, Taiwan. 60Department of Etiology and Carcinogenesis, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 61Genomic Research Center, Taipei, Taiwan. 62Institute of Medicine, Division of Thoracic Surgery, Department of Surgery, Chung Shan Medical University, Chung Shan Medical University Hospital, Taichung, Taiwan. 63Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA. 64Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA. 65Ministry of Education Key Laboratory of Contemporary Anthropology, School of Life Sciences, Fudan University, Shanghai, China. 66Department of Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Center of Cancer, Medical University Cancer Institute and Hospital, Tianjin, China. 67Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan. 68Saw Swee Hock School of Public Health, National University of Singapore, Republic of Singapore. 69Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan. 70Department of Chest Medicine, Taipei Veterans General Hospital, Taipei, Taiwan. 71Taipei Cancer Center, Taipei Medical University, Taipei, Taiwan. 72Department of Epidemiology , Murcia Regional Health Authority, IMIB-Arrixaca, Murcia, Spain. 73Cancer Research Center, Kyungpook National University Medical Center, Daegu, Republic of Korea. 74Environmental epidemiology of Cancer Group, Inserm, Centre for research in Epidemiology and Population Health (CESP), U1018, Villejuif Cedex, France. 75Department of Public Health, Clinical and Molecular Medicine, University of Cagliari, Monserrato, Cagliari, Italy. 76Department of Urology , Pitié-Salpétrière, Assistance-Publique H?pitaux de Paris (APHP), Paris, France. 77Department of Pathology, Pitié-Salpétrière, Assistance-Publique H?pitaux de Paris (APHP), Paris, France. 78Department of Epidemiology, School of Public Health and Comprehensive Cancer Center, Birmingham, Alabama, USA. 79Division of Environmental Health Sciences, University of California Berkeley School of Public Health, Berkeley, California, USA. 80Center for Lymphoid Cancer, BC Cancer Agency, Vancouver, British Columbia, Canada. 81Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada. 82Department of Obstetrics and Gynecology, University of Southern California, Los Angeles, California, USA. 83Cancer Care Ontario, Toronto, Ontario, Canada. 84Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada. 85Department of Health Sciences, University of York, York, United Kingdom. 86Department of Urology , Tenon, Assistance-Publique H?pitaux de Paris (APHP), Paris, France. 87School of Public Health, University of Alberta, Edmonton, Alberta, Canada. 88Shanxi Cancer Hospital, Taiyuan, Shanxi, China. 89Epidemiology Research Program, American Cancer Society, Atlanta, Georgia, USA. 90Health Department, BioDonostia Research Institute, Basque Region, Spain. 91Unit of Nutrition, Environment and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain. 92Department of Biomedical Science, University of Cagliari, Monserrato, Cagliari, Italy. 93Walter Reed Army Institute of Research, Silver Spring, Maryland, USA. 94Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute and MF MU, Brno, Czech Republic. 95Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA. 96Genomic Medicine Group, Galician Foundation of Genomic Medicine, Servicio Galego de Saude (SERGAS), Instituto de Investigación Sanitaria de Santiago (IDIS), Santiago de Compostela, Spain. 97Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China. 98Division of Genetics and Epidemiology, Institute of Cancer Research, London, United Kingdom. 99Unidad de Investigación, Hospital Universitario de Canarias, La Laguna, Spain. 100Department of Pathology, University of British Columbia, Vancouver, British Columbia, Canada. 101Nationwide Children's Hospital, Columbus, Ohio, USA. 102Department of Pathology and Pediatrics, The Ohio State University, Columbus, Ohio, USA. 103Massachusetts Veteran's Epidemiology, Research and Information Center, Geriatric Research Education and Clinical Center, Veterans Affairs Boston Healthcare System, Boston, Massachusetts, USA. 104Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia. 105Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Carlton, Victoria, Australia. 106Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden. 107Department of Radiology, Oncology and Radiation Science, Uppsala University, Uppsala, Sweden. 108Department of Oncology, Sidney Kimmel Cancer Center and Johns Hopkins University, Baltimore, Maryland, USA. 109Department of Pathology, Sidney Kimmel Cancer Center and Johns Hopkins University, Baltimore, Maryland, USA. 110Department of Medicine, Sidney Kimmel Cancer Center and Johns Hopkins University, Baltimore, Maryland, USA. 111Albert Einstein College of Medicine, The Children's Hospital at Montefiore, Bronx, New York, USA. 112Laboratory of Medicine and Pathology, University of Minnesota, Minneapolis, Minnesota, USA. 113Department of Epidemiology, M.D. Anderson Cancer Center, Houston, Texas, USA. 114Department of Epidemiology, School of Public Health, China Medical University, Shenyang, China. 115Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom. 116Institute of Occupational Medicine and Ministry of Education Key Lab for Environment and Health, School of Public Health, Huazhong University of Science and Technology, Wuhan, China. 117Department of Public Health and Clinical Medicine, Nutritional Research, Umea University, Umea, Sweden. 118Department of Gastrointestinal Medical Oncology, University of Texas M.D. Anderson Cancer Center, Houston, Texas, USA. 119Laboratory of Experimental Oncology, Orthopaedic Rizzoli Institute, Bologna, Italy. 120Chinese Center for Disease Control and Prevention, Beijing, China. 121Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA. 122Department of Epidemiology Research, Division of Health Surveillance and Research, Statens Serum Institut, Copenhagen, Denmark. 123Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA. 124Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea. 125Cancer Prevention Institute of California, Fremont, California, USA. 126New Hampshire State Cancer Registry, Concord, New Hampshire, USA. 127Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, USA. 128Taiwan Lung Cancer Tissue/Specimen Information Resource Center, National Health Research Institutes, Zhunan, Taiwan. 129Jiangsu Collaborative Innovation Center For Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China. 130Jiangsu Key Laboratory of Cancer Biomarkers, Prevention and Treatment, Cancer Center, School of Public Health, Nanjing Medical University, Nanjing, China. 131Department of Internal Medicine, Kaohsiung Medical University Hospital, School of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. 132Division of Endocrinology, Diabetes and Metabolism, The Ohio State University, Columbus, Ohio, USA. 133International Agency for Research on Cancer (IARC), Lyon, France. 134Molecular Diagnostics and Imaging Center, Kyungpook National University, Daegu, Republic of Korea. 135Unit of Survivorship, The Danish Cancer Society Research Center, Copenhagen, Denmark. 136Vermont Cancer Registry, Burlington, Vermont, USA. 137Department of Thoracic and Cardiovascular Surgery, Cancer Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea. 138Group Health Research Institute, Seattle, Washington, USA. 139Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire, USA. 140MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom. 141School of Clinical Medicine, University of Cambridge, United Kingdom. 142Center for Creative Biomedical Scientists, Chonnam National University, Gwangju, Republic of Korea. 143Department of Environmental Health, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea. 144Department of Internal Medicine, Division of Medical Oncology, College of Medicine, Korea University Guro Hospital, Seoul, Republic of Korea. 145Department of Internal Medicine, Division of Oncology/Hematology, College of Medicine, Korea University Anam Hospital, Seoul, Republic of Korea. 146Lung and Esophageal Cancer Clinic, Chonnam National University Hwasun Hospital, Hwasun-eup, Republic of Korea. 147Department of Internal Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea. 148Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA. 149Icahn Institute for Genomics and Multiscale Biology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA. 150Centre for Research in Environmental Epidemiology (CREAL), Barcelona, Spain. 151Municipal Institute of Medical Research, (IMIM - Hospital del Mar), Barcelona, Spain. 152National School of Public Health, Athens, Greece. 153Division of Genome Biology, National Cancer Center Research Institute, Tokyo, Japan. 154The Cancer Research Center of Hawaii, Honolulu, Hawaii, USA. 155Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, Italy. 156Department of Medical Oncology, Japanese Red Cross Medical Center, Tokyo, Japan. 157Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York, USA. 158Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun-eup, Republic of Korea. 159Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Republic of Korea. 160Westat, Rockville, Maryland, USA. 161Department Of Pediatrics, University Clinic of Navarra, Universidad de Navarra, Pamplona, Spain. 162Department of Clinical Oncology, The University of Hong Kong, Hong Kong, China. 163Qujing Center for Diseases Control and Prevention, Sanjiangdadao, Qujing, China. 164Cancer Prevention Institute of California, Fremont, California, USA. 165Department of Internal Medicine, National Cheng Kung University Medical College and Hospital, National Cheng Kung University, Tainan, Taiwan. 166Department of Internal Medicine, Carver College of Medicine, The University of Iowa, Iowa City, Iowa, USA. 167Human Genetics, Genome Institute of Singapore, Singapore, Republic of Singapore. 168Cancer Center, Union Hospital, Huazhong University of Science and Technology, Wuhan, China. 169Department of Surgical and Perioperative Sciences, Urology and Andrology, Umea University, Umea, Sweden. 170Department of Surgery and Translational Medicine, Section of Anatomo-Pathology, University of Florence, Florence, Italy. 171Department of Community Medicine, Faculty of Health Sciences, University of Troms?, The Arctic University of Norway, Troms?, Norway. 172Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain. 173Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland. 174Cancer Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, USA. 175Lucile Packard Children's Hospital, Stanford University, Palo Alto, California, USA. 176Molecular and Nutritional Epidemiology Unit, Cancer? Research and Prevention Institute (ISPO), Florence, Italy. 177Department of Cardiac, Thoracic and Vascular Sciences, University of Padova, Padova, Italy. 178Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan. 179EA 4184, Registre des Hémopathies Malignes de C?te d’Or, University of Burgundy and Dijon University Hospital, Dijon, France. 180Department of Medicine, Stanford University School of Medicine, Stanford, California, USA. 181Division of Biology and Medicine, Department of Epidemiology, Brown University, Providence, Rhode Island, USA. 182School of Public Health, Imperial College London, London, United Kingdom. 183Division of Thoracic Surgery, Kinki University School of Medicine, Sayama, Japan. 184Registre des hémopathies malignes de la Gironde, Institut Bergonié, Bordeaux Cedex, France. 185Section for Epidemiology, Aarhus University, Denmark. 186Department of Cardiology, Aalborg University Hospital, Denmark. 187Center for Chronic Immunodeficiency, University Medical Center Freiburg, Freiburg, Baden-Württemberg, Germany. 188Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 189Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. 190Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA. 191Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York, USA. 192Division of Hematology and Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA. 193Lung Cancer Center, Kyungpook National University Medical Center, Daegu, Republic of Korea. 194Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands. 195Department of Primary Care and Public Health, School of Public Health, Imperial College London, London, United Kingdom. 196Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA. 197Genomics Research Center, Academia Sinica, Taipei, Taiwan. 198Department of Epidemiology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences, Beijing, China. 199Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut, USA. 200Department of Family Medicine and Public Health Sciences, Wayne State University, Detroit, Michigan, USA. 201Population Studies and Disparities Research Program, Karmanos Cancer Institute, Detroit, Michigan, USA. 202Maine Cancer Registry, Augusta, Maine, USA. 203Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain. 204Human Genetics Foundation, Turin, Italy. 205Department of Surgery, Division of Cardiothoracic Surgery, Queen Mary Hospital, Hong Kong, China. 206Department of Pathology, University of Melbourne, Parkville, Victoria, Australia. 207Cancer Control Research, BC Cancer Agency, Vancouver, British Columbia, Canada. 208School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada. 209School of Nursing and Human Sciences, Dublin City University, Dublin, Ireland. 210National Cheng Kung University Medical College and Hospital, Tainan, Taiwan. 211Department of Surgical and Perioperative Sciences, Surgery, Umea University, Umea, Sweden. 212Cancer Research Institute, Korea University, Seoul, Republic of Korea. 213Department of Thoracic and Cardiovascular Surgery, Seoul St Mary's Hospital, Seoul, Republic of Korea. 214Instituto Universitario de Oncología, Universidad de Oviedo, Oviedo, Spain. 215The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia. 216Danish Cancer Society Research Center, Copenhagen, Denmark. 217Cancer Epidemiology Unit, University of Oxford, Oxford, United Kingdom. 218Bureau of Epidemiologic Research, Academy of Athens, Athens, Greece. 219Hellenic Health Foundation, Athens, Greece. 220Department of Respiratory Thearpy, Chang Gung Memorial Hospital, Chiayi, Taiwan. 221Australian School of Advanced Medicine, Macquarie University, Sydney, New South Wales, Australia. 222Department of Histopathology, Douglass Hanly Moir Pathology, Macquarie Park, New South Wales, Australia. 223Prince of Wales Clinical School, University of New South Wales, Sydney, New South Wales, Australia. 224Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands. 225Department of Social and Preventive Medicine, University at Buffalo, State University of New York, Buffalo, New York, USA. 226Department of Pulmonary and Critical Care, Chang Gung Memorial Hospital, Taoyuan, Taiwan. 227State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China. 228Centre for Genomic Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China. 229Department of Biochemistry, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China. 230China National Environmental Monitoring Center, Beijing, China. 231Cancer Registry of Norway, Oslo, Norway. 232Department of Genetic Epidemiology, Folkhalsan Research Center, Helsinki, Finland. 233Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA. 234Department of Pathology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China. 235State Key Laboratory of Molecular Oncology, Cancer Institute and Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. 236Shanghai Cancer Institute, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China. 237School of Public Health, The University of Hong Kong, Hong Kong. 238Department of Oncology, Wuhan Iron and Steel Corporation Staff Worker Hospital, Wuhan, China. 239Department of Internal Medicine, National Taiwan University College of Medicine, Taipei, Taiwan. 240Institute of Predictive and Personalized Medicine of Cancer (IMPPC), Barcelona, Spain. 241Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. 242University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania, USA. 243Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, District of Columbia, USA. 244Department of Oncology, Georgetown University Medical Center, Washington, District of Columbia, USA. 245Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA. 246Interdisciplinary?Department of Medicine, University of Bari, Bari, Italy. 247CPO-Piemonte and Unit of Medical Statistics and Epidemiology, Department Translational Medicine, University of Piemonte Orientale, Novara, Italy. 248Environmental and Occupational Epidemiology Unit, Cancer Prevention and Research Institute (ISPO), Florence, Italy. 249Department of Medicine, Solna, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden. 250Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. 251Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA. 252These authors contributed equally to this work. 253These authors contributed equally to this work. 254These authors contributed equally to this work. ?Corresponding authors.AbstractBackground: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common SNPs for cancer at 13 anatomical sites.Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49,492 cancer cases and 34,131 controls. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl2, on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% CI = 14% - 37%) and 7% (4% - 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ=0.73, SE=0.28), Diffuse Large B-Cell Lymphoma (DLBCL) and pediatric osteosarcoma (ρ=0.53, SE=0.21), DLBCL and Chronic Lymphocytic Leukemia (CLL) (ρ=0.51, SE=0.18), and bladder and lung (ρ=0.35, SE=0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a non-smoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.IntroductionStudies of related individuals have consistently demonstrated that there is notable familial aggregation of cancer. The three largest studies, based on the Swedish Family-Cancer DatabasePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5DemVuZTwvQXV0aG9yPjxZZWFyPjIwMDI8L1llYXI+PFJl

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ADDIN EN.CITE.DATA [6], have shown familial aggregation for cancer at nearly every anatomical site. For common cancers such as prostate, breast, and lung, the familial relative risk (FRR), defined as the increase in risk associated with each affected first degree relative of an individual, is generally estimated to be below or around 2.0. In contrast, for some rare cancers occurring early in life, such as those of testes and bone, estimates of FRR can exceed 5. Although shared environmental factors contribute to this aggregation, studies of twinsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BaGxib208L0F1dGhvcj48WWVhcj4xOTk3PC9ZZWFyPjxS

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ADDIN EN.CITE.DATA [6, 9, 10] have clearly identified a substantial genetic contribution, commonly known as heritability. Genome wide association studies (GWAS) have provided an opportunity to study the contribution of common single nucleotide polymorphisms (SNPs) to the heritability of complex traits, including cancers. In addition to identifying specific susceptibility SNPs , novel mixed-effect modeling methods PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZWU8L0F1dGhvcj48WWVhcj4yMDExPC9ZZWFyPjxSZWNO

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ADDIN EN.CITE.DATA [6]. GWAS have also directly identified shared regions, such as 8q24.1 and 5p15.33 (TERT-CLPTM1L), containing SNPs affecting cancer at multiple sites, while earlier studies have identified major genes, such as TP53 ADDIN EN.CITE <EndNote><Cite><Author>Petitjean</Author><Year>2007</Year><RecNum>258</RecNum><DisplayText>[16]</DisplayText><record><rec-number>258</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">258</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Petitjean, A.</author><author>Achatz, M. I.</author><author>Borresen-Dale, A. L.</author><author>Hainaut, P.</author><author>Olivier, M.</author></authors></contributors><auth-address>International Agency for Research on Cancer, Lyon, France.</auth-address><titles><title>TP53 mutations in human cancers: functional selection and impact on cancer prognosis and outcomes</title><secondary-title>Oncogene</secondary-title><alt-title>Oncogene</alt-title></titles><periodical><full-title>Oncogene</full-title><abbr-1>Oncogene</abbr-1></periodical><alt-periodical><full-title>Oncogene</full-title><abbr-1>Oncogene</abbr-1></alt-periodical><pages>2157-65</pages><volume>26</volume><number>15</number><keywords><keyword>Genetic Markers</keyword><keyword>Humans</keyword><keyword>Li-Fraumeni Syndrome/genetics</keyword><keyword>Mutagenesis</keyword><keyword>Mutation</keyword><keyword>Neoplasms/*genetics/*pathology</keyword><keyword>Polymorphism, Genetic</keyword><keyword>Prognosis</keyword><keyword>Tumor Markers, Biological/*genetics</keyword><keyword>Tumor Suppressor Protein p53/*genetics</keyword></keywords><dates><year>2007</year><pub-dates><date>Apr 2</date></pub-dates></dates><isbn>0950-9232 (Print)&#xD;0950-9232 (Linking)</isbn><accession-num>17401424</accession-num><urls><related-urls><url>;[16] and BRCA ADDIN EN.CITE <EndNote><Cite><Author>Friedenson</Author><Year>2005</Year><RecNum>281</RecNum><DisplayText>[17]</DisplayText><record><rec-number>281</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">281</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Friedenson, Bernard</author></authors></contributors><titles><title>BRCA1 and BRCA2 pathways and the risk of cancers other than breast or ovarian</title><secondary-title>Medscape General Medicine</secondary-title></titles><periodical><full-title>Medscape General Medicine</full-title></periodical><pages>60</pages><volume>7</volume><number>2</number><dates><year>2005</year></dates><urls></urls></record></Cite></EndNote>[17], containing highly-penetrant rare variants affecting multiple cancers. Sites with overlapping genetic architectures may be studied together to understand shared biology and to increase power to detect susceptibility loci. In this study, we performed an analysis of heritability and shared heritability for cancer at 13 different sites using data from case/control GWAS of more than 80,000 individuals carried out or reported to the US National Cancer Institute. We expand upon recent GWAS estimates of heritability ADDIN EN.CITE <EndNote><Cite><Author>Lu</Author><Year>2014</Year><RecNum>255</RecNum><DisplayText>[13]</DisplayText><record><rec-number>255</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">255</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Lu, Yi</author><author>Ek, Weronica E.</author><author>Whiteman, David</author><author>Vaughan, Thomas L.</author><author>Spurdle, Amanda B.</author><author>Easton, Douglas F.</author><author>Pharoah, Paul D.</author><author>Thompson, Deborah J.</author><author>Dunning, Alison M.</author><author>Hayward, Nicholas K.</author><author>Chenevix-Trench, Georgia</author><author>Q-MEGA</author><author>AMFS Investigators</author><author>ANECS-SEARCH?</author><author>UKOPS-SEARCH?</author><author>BEACON Consortium?</author><author>Macgregor, Stuart</author></authors></contributors><titles><title>Most common ‘sporadic’ cancers have a significant germline genetic component</title><secondary-title>Human Molecular Genetics</secondary-title></titles><periodical><full-title>Human Molecular Genetics</full-title></periodical><dates><year>2014</year><pub-dates><date>June 18, 2014</date></pub-dates></dates><urls><related-urls><url>;[13] by nearly doubling the number of cases evaluated, exploring 6 new cancer (sub)types, and considering populations of non-European ancestry. We use detailed information on multiple smoking characteristics to assess the proportion of heritability in smoking-related cancers that can be attributed to the genetic determinants of cigarette smoking. Furthermore, we use genetic correlation analysis to assess shared heritability across cancer sites, and for lung cancer, across two distinct ethnic populations to assess the evidence of gene-environment interactions for this complex malignancy. These analyses provide insights into the contribution of common SNPs to cancer heritability, co-heritability and their relationships to a major environmental risk-factor, smoking. MethodsStudy Populations. The study includes 49,492 cancer cases and 34,131 controls who participated in large case/control GWAS that were genotyped at or reported to the National Cancer Institute’s (NCI) Cancer Genomics Research Laboratory (CGR) between 2007 and 2014. GWAS were conducted in individuals of European ancestry unless otherwise stated. Details about the GWAS can be found in the Supplementary Methods. Studies were approved by the local institutional review boards.Estimation of Heritability and Genetic Correlation. We estimated heritability, hl2, and genetic correlation using the mixed model approaches in the GCTA softwarePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MZWU8L0F1dGhvcj48WWVhcj4yMDExPC9ZZWFyPjxSZWNO

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ADDIN EN.CITE.DATA [11, 12], adjusting for gender, substudy, and the top 20 eigenvectors, and after following the stringent quality control procedures described in the supplementary methods. To estimate heritability attributable to undiscovered loci, we identified SNPs (Supplementary Table 1) from the National Human Genome Research Institute (NHGRI) catalog or from recent publicationsaWdoYW0gYW5kIFdvbWVuJmFwb3M7cyBIb3NwaXRhbCBhbmQgSGFydmFyZCBNZWRpY2FsIFNjaG9v

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ADDIN EN.CITE.DATA [18-20] that were associated with a given cancer (p < 5 x 10-8) and removed all SNPs within 250 KB of those loci prior to calculation of the genetic relation matrix. A description of the GCTA methodology, determining FRR, and sensitivity analyses are provided in the Supplementary Methods.Shared SNP Analysis. Among the 375 SNPs associated with at least one of the studied cancers in the NHGRI catalog or a recent publication, we considered only the 318 SNPs that were outside regions surrounding TERT (1280000 +/- 500 kb on chromosome 5) and 8q24 (128000000 +/- 500 kb on chromosome 8), both already known?to have pleiotripic effects on multiple cancers, and that could be imputed accurately in at least one GWAS. Among those SNPs, we evaluated their associations with all other cancers and reported their associations if the corresponding p-value was below 0.001. Next, we created a polygenic risk score for each cancer. Let “T” denote a specific cancer site, RiT be an individual’s risk of cancer “T”, ΩT be the subset of the 318 SNPs associated with cancer “T”, and Gij be the number of minor alleles for individual i at SNP j in ΩT. Then the polygenic risk score, ZTi, for individual i was defined as where was estimated from fitting the model logitusing our GWAS. We then tested for an association between the polygenic risk score of the primary cancer and the risk of each of the other cancers.Estimation of the Heritability of Smoking and its Contribution to Cancer Heritability. To estimate the proportion of cancer heritability that can be explained by genetic determinants of smoking, we first defined a smoking-related-risk-score variable (ST) that weights three smoking-related risk factors, namely smoking status, intensity, and duration according to their strength of association with a particular cancer (Supplementary Methods). Variability of ST , a mathematical construct which we denote by Var(ST), explains the variation of cancer risk due to smoking in a population on the log-risk scale. The component of VarST attributable to genetics can be estimated as , where hTS2 is the heritability of ST and Var(ST) is the total variability of ST in the underlying population, which we approximate by the 10530 controls with relevant smoking variables. The proportion, P, of cancer heritability attributable to smoking is then estimated as P=VGS/VG , where VG=2log?(FRR) transforms our estimate of cancer heritability to the variability in risk on the log-risk scale ADDIN EN.CITE <EndNote><Cite><Author>Pharoah</Author><Year>2002</Year><RecNum>279</RecNum><DisplayText>[21]</DisplayText><record><rec-number>279</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">279</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Pharoah, P. D. P.</author><author>Antoniou, A.</author><author>Bobrow, M.</author><author>Zimmern, R. L.</author><author>Easton, D. F.</author><author>Ponder, B. A. J.</author></authors></contributors><auth-address>Pharoah, PDP&#xD;Strangeways Res Labs, Dept Oncol, Canc Res UK Human Canc Genet Grp, Cambridge CB1 8RN, England&#xD;Strangeways Res Labs, Dept Oncol, Canc Res UK Human Canc Genet Grp, Cambridge CB1 8RN, England&#xD;Strangeways Res Labs, Dept Oncol, Canc Res UK Human Canc Genet Grp, Cambridge CB1 8RN, England&#xD;Strangeways Res Labs, Publ Hlth Genet Unit, Cambridge CB1 8RN, England&#xD;Strangeways Res Labs, Canc Res UK Genet Epidemiol Unit, Cambridge CB1 8RN, England&#xD;Addenbrookes Hosp, Dept Clin Genet, Cambridge CB1 2QQ, England</auth-address><titles><title>Polygenic susceptibility to breast cancer and implications for prevention</title><secondary-title>Nature Genetics</secondary-title><alt-title>Nat Genet</alt-title></titles><alt-periodical><full-title>Nat Genet</full-title></alt-periodical><pages>33-36</pages><volume>31</volume><number>1</number><keywords><keyword>clinical-practice</keyword><keyword>risk</keyword><keyword>metaanalysis</keyword><keyword>populations</keyword><keyword>medicine</keyword><keyword>genetics</keyword><keyword>family</keyword><keyword>twins</keyword><keyword>women</keyword></keywords><dates><year>2002</year><pub-dates><date>May</date></pub-dates></dates><isbn>1061-4036</isbn><accession-num>WOS:000175362500011</accession-num><urls><related-urls><url>&lt;Go to ISI&gt;://WOS:000175362500011</url></related-urls></urls><electronic-resource-num>Doi 10.1038/Ng853</electronic-resource-num><language>English</language></record></Cite></EndNote>[21].ResultsThe estimates of array-based heritability, hl2, on the liability threshold (LT) scale ranged from 0.05 to 0.38 across the 13 cancer sites (Table 1), with esophageal cancer (hl2=0.38, 95th CI = 0.17-0.59, Asian population), prostate cancer (hl2=0.38, 95th CI = 0.24 – 0.51), and testicular cancer (hl2=0.30, 95th CI = 0.08-0.51) displaying the strongest heritable components. After removing known susceptibility loci (Supplementary Table 1), the adjusted estimates of heritability remained similar (Table 1) for most of the cancer sites, indicating that the majority of the common underlying susceptibility loci remain to be discovered. Known loci constituted the largest proportion of heritability for cancers of the testes (33%) and prostate (25%). We transformed our measures of the genetic contribution to cancer from heritability on the liability threshold scale to familial relative risk (FRR) for direct comparison with registry-based family studies (Table 2). For most cancers, the FRR explained by GWAS SNPs was between 1.28 and 1.63. The estimates of FRR were highest for testicular cancer (FRR = 3.09, 95th CI = 1.41-6.05), osteosarcoma (2.90, 1.73-4.70) and CLL (2.28, 1.86-2.77). The GWAS estimates of excess risk (FRR-1) in the studies of European ancestry were in the range of 15-53% of the average estimates based on the Icelandic, Swedish and Utah registry data, with the exception of DLBCL (4.5%). For lung cancer in an Asian population, our observed FRR of 1.31 (95?% CI?=?1.16-1.46, Table 2) can be compared with an estimate of 2.44, (95?% CI?=?1.79-3.32) from a Taiwanese family studyPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MbzwvQXV0aG9yPjxZZWFyPjIwMTM8L1llYXI+PFJlY051

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ADDIN EN.CITE.DATA [22].Smoking is heritable and is a strong risk factor for both lung and bladder cancers. We estimated the heritability of the lung cancer smoking-related risk score to be 0.15 (95% CI=0.10-0.20) and the heritability of the bladder cancer smoking-related risk score to be 0.16 (0.09-0.22) (Table 3, Supplementary Tables 3-4, Supplementary Figures 1-2). Based on a comparison with our estimates for the total heritability of cancer (Table 3), we estimated that 23.6% (95% CI = 14.2% - 37.4%) and 7.1% (4.3% - 11.3%) of the heritability for lung and bladder cancer, respectively, can be attributed to the genetic determinants of the three smoking characteristics. When restricting the analysis to ever-smokers, the heritability of the smoking-related risk scores remained similar (Table 3), and we estimated that 22.0% (7.8% - 43.0%) and 3.0% (1.2% - 5.9%) of the total heritability, respectively, was attributable to that of smoking behavior for lung and bladder cancers. Although limited by the number of never-smokers, we also noted lower estimates of heritability in this subgroup (Supplementary Table 5).The estimated genetic correlations between most pairs of cancer sites were modest and statistically non-significant (Fig. 1, Supplementary Table 6). Among the 91 compared pairs, all combinations of the 12 solid tumors, CLL, and DLBCL, the median (mean) correlation was 0.031 (0.055) and in tests for statistical significance, only 12% and 22% of these 91 p-values were below 0.1 and 0.2, providing little evidence of the enrichment that would be expected to occur with many strongly correlated pairs. The four pairs with the strongest correlations (p-value < 0.01) were kidney and testes (ρ=0.73, SE = 0.28), DLBCL and osteosarcoma (ρ = 0.53, SE=0.21), DLBCL and CLL (ρ = 0.51, SE = 0.18), and bladder and lung (ρ=0.35, SE =0.14). The two types, CLL and osteosarcoma, that were individually correlated with DLBCL showed minimal correlation (ρ =0.19, SE=0.15) with each other. For prostate cancer, the best-fitting estimate of the genetic correlation between aggressive and non-aggressive disease was at the upper boundary (ρ =1, SE = 0.25) indicating a shared genetic architecture between the two clinical subtypes of this malignancy. For lung cancer, on the other hand, we estimated the genetic correlation across two distinct racial/ethnic groups and found the correlation between non-smoking Asian women and individuals of European ancestry to be only modest and statistically non-significant (ρ =0.10, SE = 0.15), suggesting distinct genetic etiologies for the same malignancy in two distinct populations with different ethnic background and exposure history.As a second means to assess genetic overlap, we tested whether the 318 SNPs previously associated with one of the 13 cancers at GWAS levels if statistical significance(p < 5 x 10-8), but outside the known pleiotropic regions of 5p15.33 and 8q24, were associated with other cancers (Supplementary Tables 7-8). Among the 318 SNPs, 25 were associated with a second cancer at p < 0.001 (Supplementary Tables 7-8). We further calculated a polygenic risk score for each cancer (Methods) with at least ten associated SNPs among the 318 previously discovered. We found individuals with a high risk score for lung cancer were at an increased risk of bladder cancer (RR of bladder cancer comparing 90th vs 10th percentile = 1.07 , 95% CI = 1.05 – 1.10 ) and individuals with a high risk score for CLL were at an increased risk of DLBCL (RR = 1.12, 95% CI = 1.07 – 1.16 ) (Supplementary Table 9-12). After adjusting for status, intensity, and duration of smoking, the strength of association between the lung cancer score and bladder cancer was reduced, but remained statistically significant (RR = 1.05, 95% CI = 1.02 – 1.08).We estimated heritability separately for men and women (Supplementary Tables 13 - 14). Although we observed differences by gender, none reached statistical significance. When studies were divided by gender, the genetic correlation between cancer in men and women exceeded 0.9 in nearly all scenarios, with the 95% CI always including 1. Moreover, we also estimated heritability under multiple additional analytical settings (Supplementary Table 15), and found the results from these sensitivity analyses to be qualitatively similar. Sensitivity analyses further suggested that population stratification was adequately handled by adjusting for principal components (Supplementary Table 16). DiscussionOur analysis confirms that common SNPs contribute statistically significantly to risk across the spectrum of cancers and account for different fractions of estimated heritability. The estimates of array-based heritability on the liability threshold scale spanned a wide range, from 5% (glioma) to 38% (prostate, esophageal cancer), and the majority of the observed heritability for most cancers is likely attributable to genetic variants that are not located in previously identified susceptibility regions. The corresponding estimates of familial relative risk were between 1.19 (glioma) and 2.90 (osteosarcoma). 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Pn==

ADDIN EN.CITE.DATA [1, 5, 6]. A number of additional factors are likely to contribute to familial aggregation, including rare genetic variantsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5Kb25lczwvQXV0aG9yPjxZZWFyPjIwMDk8L1llYXI+PFJl

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ADDIN EN.CITE.DATA [23-25], non-additive effects, and shared environment.Expanding GWAS, either through new genotyping or meta-analyses, should continue to yield new susceptibility loci. The pace of expected discovery, measured by the number of additional associations for given study sizes, will likely continue to be faster for those cancers with the highest FRR’s. For stomach cancer (Asian population), osteosarcoma, testes, and CLL, all with FRR > 2, we predict that more loci may be identified for studies of comparable sizePEVuZE5vdGU+PENpdGU+PEF1dGhvcj5QYXJrPC9BdXRob3I+PFllYXI+MjAxMDwvWWVhcj48UmVj

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ADDIN EN.CITE.DATA [15]. Consistent with this prediction, comparatively smaller GWAS of these highly heritable cancers have historically yielded more associations. Genetic variants can influence cancer risk, either indirectly through associations with nicotine dependence and smoking behavior, or directly through other mechanisms ADDIN EN.CITE <EndNote><Cite><Author>Subramanian</Author><Year>2008</Year><RecNum>305</RecNum><DisplayText>[26]</DisplayText><record><rec-number>305</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">305</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Subramanian, J.</author><author>Govindan, R.</author></authors></contributors><auth-address>Department of Medicine, Washington University School of Medicine, St Louis, MO, USA.</auth-address><titles><title>Molecular genetics of lung cancer in people who have never smoked</title><secondary-title>Lancet Oncol</secondary-title><alt-title>The Lancet. Oncology</alt-title></titles><periodical><full-title>Lancet Oncol</full-title><abbr-1>The lancet oncology</abbr-1></periodical><pages>676-82</pages><volume>9</volume><number>7</number><keywords><keyword>Carcinoma/*genetics/pathology/therapy</keyword><keyword>Chromosome Aberrations</keyword><keyword>Female</keyword><keyword>Humans</keyword><keyword>Lung Neoplasms/*genetics/pathology/therapy</keyword><keyword>Male</keyword><keyword>Mutation/genetics</keyword><keyword>Smoking</keyword></keywords><dates><year>2008</year><pub-dates><date>Jul</date></pub-dates></dates><isbn>1474-5488 (Electronic)&#xD;1470-2045 (Linking)</isbn><accession-num>18598932</accession-num><urls><related-urls><url>(08)70174-8</electronic-resource-num></record></Cite></EndNote>[26]. We estimate that the genetic determinants of smoking behavior accounted for at least 24% and 7% of the total heritability of lung and bladder cancers, respectively, in our study populations. These percentages likely underestimate the true influence of smoking genetics by not accounting for other, unmeasured, smoking characteristics, and may be slightly biased by systematic differences in the distribution of smoking characteristics between the general population and our GWAS control sample selected according to experimental design (Supplementary Table 17). Our result is consistent with the largest meta-analysis ADDIN EN.CITE <EndNote><Cite><Author>Matakidou</Author><Year>2005</Year><RecNum>54</RecNum><DisplayText>[27]</DisplayText><record><rec-number>54</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">54</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Matakidou, A.</author><author>Eisen, T.</author><author>Houlston, R. S.</author></authors></contributors><auth-address>Section of Cancer Genetics, Institute of Cancer Research, Sutton, Surrey, UK. athenam@icr.ac.uk</auth-address><titles><title>Systematic review of the relationship between family history and lung cancer risk</title><secondary-title>Br J Cancer</secondary-title><alt-title>British journal of cancer</alt-title></titles><periodical><full-title>Br J Cancer</full-title><abbr-1>British journal of cancer</abbr-1></periodical><alt-periodical><full-title>Br J Cancer</full-title><abbr-1>British journal of cancer</abbr-1></alt-periodical><pages>825-33</pages><volume>93</volume><number>7</number><edition>2005/09/15</edition><keywords><keyword>Case-Control Studies</keyword><keyword>Cohort Studies</keyword><keyword>Environmental Exposure</keyword><keyword>*Family</keyword><keyword>*Genetic Predisposition to Disease</keyword><keyword>Humans</keyword><keyword>Lung Neoplasms/epidemiology/*genetics</keyword><keyword>Risk Factors</keyword><keyword>Twin Studies as Topic</keyword></keywords><dates><year>2005</year><pub-dates><date>Oct 3</date></pub-dates></dates><isbn>0007-0920 (Print)&#xD;0007-0920 (Linking)</isbn><accession-num>16160696</accession-num><work-type>Research Support, Non-U.S. Gov&apos;t&#xD;Review</work-type><urls><related-urls><url>;[27] of case-control studies in which the excess relative risk (FRR=1.82, 95th CI = 1.64-2.05) for lung cancer was reduced by 36% when focused on non-smokers (FRR=1.52, 95th CI = 1.11 – 2.06). Our analysis of co-heritability indicated that, in general, most pairs of cancers studied here are unlikely to have strong genetic correlations. Although our study had low power to detect modest but possibly important correlations between specific pair of cancers PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5WaXNzY2hlcjwvQXV0aG9yPjxZZWFyPjIwMTQ8L1llYXI+

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ADDIN EN.CITE.DATA [6] found that the relative risks for testicular cancer were elevated in relatives of kidney cancer cases, as indicated by our results.Analysis of the genetic correlation for the same cancer site, but across distinct subtypes and populations can provide important insights. For instance, the strong genetic correlation between aggressive and non-aggressive prostate cancer indicates that common SNPs are unlikely to offer a diagnostic means to distinguish these two subtypes of cancer with different prognoses. On the other hand, there was an absence of correlation for lung cancer between studies in non-smoking Asian females and a Caucasian population where cases were primarily smokers. This result is consistent with the observation that distinct sets of susceptibility SNPs have emerged in these two populationsPEVuZE5vdGU+PENpdGU+PEF1dGhvcj5MYW48L0F1dGhvcj48WWVhcj4yMDEyPC9ZZWFyPjxSZWNO

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ADDIN EN.CITE.DATA [6]. However, the discrepancy also can be attributed to different cancers pathologies, environmental differences across populations, and, most importantly, other sources of shared heritability. Another limitation is that principal components may not perfectly adjust for ancestry and therefore shared environments or behaviors among individuals with similar ancestry may inflate our estimates of heritability. However, tests for such inflation found little evidence to support this concern. For some cancer sites, the individuals used in the previous study ADDIN EN.CITE <EndNote><Cite><Author>Lu</Author><Year>2014</Year><RecNum>255</RecNum><DisplayText>[13]</DisplayText><record><rec-number>255</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">255</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Lu, Yi</author><author>Ek, Weronica E.</author><author>Whiteman, David</author><author>Vaughan, Thomas L.</author><author>Spurdle, Amanda B.</author><author>Easton, Douglas F.</author><author>Pharoah, Paul D.</author><author>Thompson, Deborah J.</author><author>Dunning, Alison M.</author><author>Hayward, Nicholas K.</author><author>Chenevix-Trench, Georgia</author><author>Q-MEGA</author><author>AMFS Investigators</author><author>ANECS-SEARCH?</author><author>UKOPS-SEARCH?</author><author>BEACON Consortium?</author><author>Macgregor, Stuart</author></authors></contributors><titles><title>Most common ‘sporadic’ cancers have a significant germline genetic component</title><secondary-title>Human Molecular Genetics</secondary-title></titles><periodical><full-title>Human Molecular Genetics</full-title></periodical><dates><year>2014</year><pub-dates><date>June 18, 2014</date></pub-dates></dates><urls><related-urls><url>;[13] of GWAS heritability overlap with a subset the individuals used here, and therefore the two studies do not offer independent assessments of heritability. For kidney cancer, our population overlaps considerably with that studied by Lu and colleagues ADDIN EN.CITE <EndNote><Cite><Author>Lu</Author><Year>2014</Year><RecNum>255</RecNum><DisplayText>[13]</DisplayText><record><rec-number>255</rec-number><foreign-keys><key app="EN" db-id="t2azv9eenrvw0mew95h52wsgaa0vp5dtw02f">255</key></foreign-keys><ref-type name="Journal Article">17</ref-type><contributors><authors><author>Lu, Yi</author><author>Ek, Weronica E.</author><author>Whiteman, David</author><author>Vaughan, Thomas L.</author><author>Spurdle, Amanda B.</author><author>Easton, Douglas F.</author><author>Pharoah, Paul D.</author><author>Thompson, Deborah J.</author><author>Dunning, Alison M.</author><author>Hayward, Nicholas K.</author><author>Chenevix-Trench, Georgia</author><author>Q-MEGA</author><author>AMFS Investigators</author><author>ANECS-SEARCH?</author><author>UKOPS-SEARCH?</author><author>BEACON Consortium?</author><author>Macgregor, Stuart</author></authors></contributors><titles><title>Most common ‘sporadic’ cancers have a significant germline genetic component</title><secondary-title>Human Molecular Genetics</secondary-title></titles><periodical><full-title>Human Molecular Genetics</full-title></periodical><dates><year>2014</year><pub-dates><date>June 18, 2014</date></pub-dates></dates><urls><related-urls><url>;[13] who estimated its heritability to be 0.18. For other cancers, including bladder, lung, pancreas, and prostate, the prior study populations are primarily subsets of our own populations, including the 25%-50% of individuals from the earliest GWAS. Prior estimates for these four cancers were respectively 0.01, 0.10, 0.18, and 0.81, and show substantive differences from our updated estimates (Table 1).This analysis of more than 80,000 individuals provides important perspectives on the heritability of cancer across anatomical sites. We affirm that there is a large heritable component to most cancers, but the majority of cancer heritability cannot be attributed to known susceptibility loci. We further demonstrate that marker SNPs are not omnipresent across cancers, in that there does not appear to be strong genetic correlations between most pairs of cancer sites. Among smoking related cancers, we showed that the genetic determinants of smoking make a statistically significant contribution to the heritability of lung and bladder cancer. Overall, as GWAS expand in size and design, a comprehensive analysis should continue to focus on cancers individually, look across groups of cancers identified as being genetically similar, and account for important environmental risk factors.FundingThis study was supported by the Intramural Research Program of the NIH.NotesThe funders had no direct role in the design of the study, the collection, analysis and interpretation of the data, the writing of the manuscript, or the decision to submit the manuscript for publication.AcknowledgementsPlease see supplementary materialAuthor ContributionsPlease see supplementary materialREFERENCES ADDIN EN.REFLIST 1.Czene K, Lichtenstein P, Hemminki K. Environmental and heritable causes of cancer among 9.6 million individuals in the Swedish family-cancer database. 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Table 1 GWAS estimates of cancer heritability on the liability scale*Cancer hl2 (95% CI) hr2 (95% CI)Bladder0.123 (0.086, 0.160)0.112 (0.075, 0.148)Breast (ER-)0.096 (0, 0.199)0.079 (0, 0.181)Endometrium0.178 (0.085, 0.270)0.177 (0.085, 0.270)Esophagus?0.381 (0.174, 0.588)0.370 (0.164, 0.577)Glioma0.046 (0, 0.116)0.036 (0, 0.106)Kidney0.147 (0.023, 0.270)0.136 (0.012, 0.259)Lung Asian??0.121 (0.064, 0.177)0.102 (0.046, 0.159) European0.206 (0.142, 0.271)0.189 (0.125, 0.253)Lymphoma CLL0.220 (0.162, 0.278)0.164 (0.105, 0.222) DLBCL0.092 (0.038, 0.145)0.088 (0.035, 0.142)Osteosarcoma0.159 (0.079, 0.239)0.158 (0.078, 0.238)Pancreas0.098 (0.037, 0.160)0.084 (0.023, 0.145)Prostate Overall 0.378 (0.244, 0.513)0.285 (0.151, 0.419) Non-advanced Stage 0.351 (0.211, 0.491)0.259 (0.120, 0.399) Advanced Stage 0.232 (0.157, 0.307)0.193 (0.119, 0.268)Stomach? (non-cardia)0.253 (0, 0.522)0.243 (0, 0.512)Testes0.299 (0.084, 0.513)0.199 (0, 0.415)* hl2 (95% CI) is the estimated heritability on the liability scale (95% CI) using all qualifying SNPs, while hr2 is the heritability after removing SNPs within 250 kb of a previous GWAS hit. CI = confidence interval. ? Asian population? Non-smoking womenTable 2Estimates of first-degree familial relative risk from familial registries and GWAS*Cancer Sweden All 1st Degree Parent/Child Sibling Relationships FRR (95% CI) FRR (95% CI) FRR (95% CI) Iceland? FRR (90% CI) Utah?FRR (95% CI) GWAS FRR (95% CI)Bladder1.69 (1.33-2.14)1.53 (1.16–1.99)3.30 (1.70–5.78)1.68 (1.39-2.05)1.8 (1.4–2.3)1.37 (1.25-1.50)Breast (ER-)–––––1.28 (0.98-1.63)Endometrium3.02 (2.33-3.92)2.85 (2.08–3.82)3.97 (1.97–7.13)1.86 (1.31-2.62) 1.4 (1.1–1.8)1.56 (1.25-1.92)Esophagus–2.14 (0.77-4.70)–2.09 (1.30-3.31) 1.3 (0.2–10.0)1.63? (1.27-2.05)Glioma1.67 (1.43-1.94)–3.31 (2.08-5.02)1.41 (0.74-2.40) 2.3 (0.99-4.5)1.19 (0.91-1.54)Kidney1.78 (1.33-2.39)1.52 (1.06–2.11)4.52 (2.15–8.35)2.30 (1.89-2.80) 2.1 (1.3–3.5)1.54 (1.07-2.13)Lung European1.70 (1.42-2.05)1.64 (1.34–2.00)2.61 (1.29–4.68)2.00 (1.83-2.16) 2.4 (1.9–3.0)1.42 (1.28-1.57) Asian–––––1.31?§ (1.16-1.46)Lymphoma CLL8.5 (6.1-11.7)–––6.1 (4.75-7.65)2.28 (1.86-2.77) DLBCL9.8 (3.1-31.0)––––1.40 (1.15-1.68)Osteosarcoma–––––2.90 (1.73-4.70) Pancreas–1.68 (1.16–2.35)–2.33 (1.83-2.96) 2.1 (1.3–3.2)1.35 (1.12-1.62)Prostate2.75 (2.32-3.25)2.71 (2.26–3.22)4.91 (1.28–12.7)1.89 (1.75-2.01) 2.1 (1.9–2.2)1.51 (1.32-1.72)Stomach1.99 (1.47-2.71)1.72 (1.19–2.40)8.82 (3.50–18.3)1.90 (1.74-2.05) 2.0 (1.1–3.7)1.94? (0.95-3.49)Testes7.07 (5.34-9.37)4.31 (2.05–7.95)8.50 (6.01–11.7)3.52 (1.18-7.37) 1.8 (0.4–8.6)3.09 (1.41-6.05)* Comparison of first-degree familial relative risk (95% CI) measured by our GWAS (last column) with estimates of familial relative risk from the three largest family studies. Prior estimates are from PEVuZE5vdGU+PENpdGU+PEF1dGhvcj5BbXVuZGFkb3R0aXI8L0F1dGhvcj48WWVhcj4yMDA0PC9Z

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ADDIN EN.CITE.DATA [3]. FRR = Family Relative Risk. CI = confidence interval.? All first-degree relationships? Asian population§: Non-smoking womenTable 3Estimates of the contribution of smoking to cancer heritability* All SubjectsFormer/Current SmokersVGS: Smoking(95% CI)VG: cancer(95% CI)Ratio(95% CI)VGS: Smoking(95% CI)VG: cancer(95% CI)Ratio(95% CI)Bladder0.045 (0.029-0.061)0.62 (0.44-0.81)7.1% (4.3-11.3%)0.020 (0.0073-0.032)0.66 (0.41-0.88)3.0% (1.2% – 5.9%)Lung0.166 (0.098-0.23)0.70 (0.50-0.90)23.6% (14.2-37.4%)0.11 (0.043-0.167)0.47 (0.27-0.67)22.0% (7.8% - 43.0%)* The ratio, VGS:smoking/ VG:cancer , estimates the proportion of the genetic variability of cancer that can be attributed to the genetic determinants of smoking, where VGS:smoking and VG:cancer are the genetic variances of the smoking related-risk score and cancer, respectively. CI = confidence interval.Figure 1 Genetic correlation of cancer pairs (a) The genetic correlation between cancer sites. Dots indicate p < 0.01. (b) Distribution of the corresponding Z-statistics from testing the null hypotheses of no genetic correlations. Black curve illustrates the expected distribution under the null hypothesis of no genetic correlation. ADDIN ................
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