Links to Exploration step
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">The effects of height and BMI on prostate cancer incidence and mortality: a Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium</title><author><name sortKey="Davies, Neil M" sort="Davies, Neil M" uniqKey="Davies N" first="Neil M." last="Davies">Neil M. Davies</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Gaunt, Tom R" sort="Gaunt, Tom R" uniqKey="Gaunt T" first="Tom R." last="Gaunt">Tom R. Gaunt</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Lewis, Sarah J" sort="Lewis, Sarah J" uniqKey="Lewis S" first="Sarah J." last="Lewis">Sarah J. Lewis</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Holly, Jeff" sort="Holly, Jeff" uniqKey="Holly J" first="Jeff" last="Holly">Jeff Holly</name><affiliation><nlm:aff id="Aff3">School of Clinical Sciences, University of Bristol, Bristol, BS10 5NB UK</nlm:aff></affiliation></author><author><name sortKey="Donovan, Jenny L" sort="Donovan, Jenny L" uniqKey="Donovan J" first="Jenny L." last="Donovan">Jenny L. Donovan</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Hamdy, Freddie C" sort="Hamdy, Freddie C" uniqKey="Hamdy F" first="Freddie C." last="Hamdy">Freddie C. Hamdy</name><affiliation><nlm:aff id="Aff4">Nuffield Department of Surgery, University of Oxford, Oxford, UK</nlm:aff></affiliation></author><author><name sortKey="Kemp, John P" sort="Kemp, John P" uniqKey="Kemp J" first="John P." last="Kemp">John P. Kemp</name><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff5">University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD Australia</nlm:aff></affiliation></author><author><name sortKey="Eeles, Rosalind" sort="Eeles, Rosalind" uniqKey="Eeles R" first="Rosalind" last="Eeles">Rosalind Eeles</name><affiliation><nlm:aff id="Aff6">The Institute of Cancer Research, London, SM2 5NG UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff7">The Royal Marsden NHS Foundation Trust, London, SW3 6JJ UK</nlm:aff></affiliation></author><author><name sortKey="Easton, Doug" sort="Easton, Doug" uniqKey="Easton D" first="Doug" last="Easton">Doug Easton</name><affiliation><nlm:aff id="Aff8">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Kote Jarai, Zsofia" sort="Kote Jarai, Zsofia" uniqKey="Kote Jarai Z" first="Zsofia" last="Kote-Jarai">Zsofia Kote-Jarai</name><affiliation><nlm:aff id="Aff6">The Institute of Cancer Research, London, SM2 5NG UK</nlm:aff></affiliation></author><author><name sortKey="Al Olama, Ali Amin" sort="Al Olama, Ali Amin" uniqKey="Al Olama A" first="Ali Amin" last="Al Olama">Ali Amin Al Olama</name><affiliation><nlm:aff id="Aff8">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Benlloch, Sara" sort="Benlloch, Sara" uniqKey="Benlloch S" first="Sara" last="Benlloch">Sara Benlloch</name><affiliation><nlm:aff id="Aff8">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Muir, Kenneth" sort="Muir, Kenneth" uniqKey="Muir K" first="Kenneth" last="Muir">Kenneth Muir</name><affiliation><nlm:aff id="Aff9">Institute of Population Health, University of Manchester, Manchester, UK</nlm:aff></affiliation></author><author><name sortKey="Giles, Graham G" sort="Giles, Graham G" uniqKey="Giles G" first="Graham G." last="Giles">Graham G. Giles</name><affiliation><nlm:aff id="Aff10">Cancer Epidemiology Centre, The Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC Australia</nlm:aff></affiliation><affiliation><nlm:aff id="Aff11">Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia</nlm:aff></affiliation></author><author><name sortKey="Wiklund, Fredrik" sort="Wiklund, Fredrik" uniqKey="Wiklund F" first="Fredrik" last="Wiklund">Fredrik Wiklund</name><affiliation><nlm:aff id="Aff12">Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden</nlm:aff></affiliation></author><author><name sortKey="Gronberg, Henrik" sort="Gronberg, Henrik" uniqKey="Gronberg H" first="Henrik" last="Gronberg">Henrik Gronberg</name><affiliation><nlm:aff id="Aff12">Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden</nlm:aff></affiliation></author><author><name sortKey="Haiman, Christopher A" sort="Haiman, Christopher A" uniqKey="Haiman C" first="Christopher A." last="Haiman">Christopher A. Haiman</name><affiliation><nlm:aff id="Aff13">Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA USA</nlm:aff></affiliation></author><author><name sortKey="Schleutker, Johanna" sort="Schleutker, Johanna" uniqKey="Schleutker J" first="Johanna" last="Schleutker">Johanna Schleutker</name><affiliation><nlm:aff id="Aff14">Department of Medical Biochemistry and Genetics, University of Turku, Turku, Finland</nlm:aff></affiliation><affiliation><nlm:aff id="Aff15">Institute of Biomedical Technology/BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland</nlm:aff></affiliation></author><author><name sortKey="Nordestgaard, B Rge G" sort="Nordestgaard, B Rge G" uniqKey="Nordestgaard B" first="B Rge G." last="Nordestgaard">B Rge G. Nordestgaard</name><affiliation><nlm:aff id="Aff16">Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev, Denmark</nlm:aff></affiliation></author><author><name sortKey="Travis, Ruth C" sort="Travis, Ruth C" uniqKey="Travis R" first="Ruth C." last="Travis">Ruth C. Travis</name><affiliation><nlm:aff id="Aff17">Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK</nlm:aff></affiliation></author><author><name sortKey="Neal, David" sort="Neal, David" uniqKey="Neal D" first="David" last="Neal">David Neal</name><affiliation><nlm:aff id="Aff18">Surgical Oncology (Uro-Oncology: S4), University of Cambridge, Addenbrooke’s Hospital, Hills Road, Box 279, Cambridge, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff19">Li Ka Shing Centre, Cancer Research UK Cambridge Research Institute, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Pashayan, Nora" sort="Pashayan, Nora" uniqKey="Pashayan N" first="Nora" last="Pashayan">Nora Pashayan</name><affiliation><nlm:aff id="Aff20">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff41">Department of Applied Health Research, University College London, 1-19 Torrington Place, London, WC1E 7HB UK</nlm:aff></affiliation></author><author><name sortKey="Khaw, Kay Tee" sort="Khaw, Kay Tee" uniqKey="Khaw K" first="Kay-Tee" last="Khaw">Kay-Tee Khaw</name><affiliation><nlm:aff id="Aff21">Cambridge Institute of Public Health, University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB2 0SR UK</nlm:aff></affiliation></author><author><name sortKey="Stanford, Janet L" sort="Stanford, Janet L" uniqKey="Stanford J" first="Janet L." last="Stanford">Janet L. Stanford</name><affiliation><nlm:aff id="Aff22">Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA USA</nlm:aff></affiliation><affiliation><nlm:aff id="Aff23">Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA USA</nlm:aff></affiliation></author><author><name sortKey="Blot, William J" sort="Blot, William J" uniqKey="Blot W" first="William J." last="Blot">William J. Blot</name><affiliation><nlm:aff id="Aff24">International Epidemiology Institute, 1455 Research Blvd., Suite 550, Rockville, MD 20850 USA</nlm:aff></affiliation></author><author><name sortKey="Thibodeau, Stephen" sort="Thibodeau, Stephen" uniqKey="Thibodeau S" first="Stephen" last="Thibodeau">Stephen Thibodeau</name><affiliation><nlm:aff id="Aff25">Mayo Clinic, Rochester, MN USA</nlm:aff></affiliation></author><author><name sortKey="Maier, Christiane" sort="Maier, Christiane" uniqKey="Maier C" first="Christiane" last="Maier">Christiane Maier</name><affiliation><nlm:aff id="Aff26">Department of Urology, University Hospital Ulm, Ulm, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="Aff27">Institute of Human Genetics, University Hospital Ulm, Ulm, Germany</nlm:aff></affiliation></author><author><name sortKey="Kibel, Adam S" sort="Kibel, Adam S" uniqKey="Kibel A" first="Adam S." last="Kibel">Adam S. Kibel</name><affiliation><nlm:aff id="Aff28">Brigham and Women’s Hospital/Dana-Farber Cancer Institute, 45 Francis Street-ASB II-3, Boston, MA 02115 USA</nlm:aff></affiliation><affiliation><nlm:aff id="Aff29">Washington University, St. Louis, Missouri</nlm:aff></affiliation></author><author><name sortKey="Cybulski, Cezary" sort="Cybulski, Cezary" uniqKey="Cybulski C" first="Cezary" last="Cybulski">Cezary Cybulski</name><affiliation><nlm:aff id="Aff30">International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland</nlm:aff></affiliation></author><author><name sortKey="Cannon Albright, Lisa" sort="Cannon Albright, Lisa" uniqKey="Cannon Albright L" first="Lisa" last="Cannon-Albright">Lisa Cannon-Albright</name><affiliation><nlm:aff id="Aff31">Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT USA</nlm:aff></affiliation></author><author><name sortKey="Brenner, Hermann" sort="Brenner, Hermann" uniqKey="Brenner H" first="Hermann" last="Brenner">Hermann Brenner</name><affiliation><nlm:aff id="Aff32">Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="Aff33">Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="Aff34">German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany</nlm:aff></affiliation></author><author><name sortKey="Park, Jong" sort="Park, Jong" uniqKey="Park J" first="Jong" last="Park">Jong Park</name><affiliation><nlm:aff id="Aff35">Division of Cancer Prevention and Control, H. Lee Moffitt Cancer Center, 12902 Magnolia Dr., Tampa, FL USA</nlm:aff></affiliation></author><author><name sortKey="Kaneva, Radka" sort="Kaneva, Radka" uniqKey="Kaneva R" first="Radka" last="Kaneva">Radka Kaneva</name><affiliation><nlm:aff id="Aff36">Molecular Medicine Center and Department of Medical Chemistry and Biochemistry, Medical University Sofia, 2 Zdrave St, 1431 Sofia, Bulgaria</nlm:aff></affiliation></author><author><name sortKey="Batra, Jyotsna" sort="Batra, Jyotsna" uniqKey="Batra J" first="Jyotsna" last="Batra">Jyotsna Batra</name><affiliation><nlm:aff id="Aff37">Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD Australia</nlm:aff></affiliation></author><author><name sortKey="Teixeira, Manuel R" sort="Teixeira, Manuel R" uniqKey="Teixeira M" first="Manuel R." last="Teixeira">Manuel R. Teixeira</name><affiliation><nlm:aff id="Aff38">Department of Genetics, Portuguese Oncology Institute, Porto, Portugal</nlm:aff></affiliation><affiliation><nlm:aff id="Aff39">Biomedical Sciences Institute (ICBAS), Porto University, Porto, Portugal</nlm:aff></affiliation></author><author><name sortKey="Pandha, Hardev" sort="Pandha, Hardev" uniqKey="Pandha H" first="Hardev" last="Pandha">Hardev Pandha</name><affiliation><nlm:aff id="Aff40">The University of Surrey, Guildford, Surrey GU2 7XH UK</nlm:aff></affiliation></author><author><name sortKey="Lathrop, Mark" sort="Lathrop, Mark" uniqKey="Lathrop M" first="Mark" last="Lathrop">Mark Lathrop</name><affiliation><nlm:aff id="Aff42">Commissariat à l’Energie Atomique, Center National de Génotypage, Evry, France</nlm:aff></affiliation><affiliation><nlm:aff id="Aff43">McGill University-Génome Québec Innovation Centre, Montreal, Canada</nlm:aff></affiliation></author><author><name sortKey="Smith, George Davey" sort="Smith, George Davey" uniqKey="Smith G" first="George Davey" last="Smith">George Davey Smith</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Martin, Richard M" sort="Martin, Richard M" uniqKey="Martin R" first="Richard M." last="Martin">Richard M. Martin</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff44">Bristol Nutrition Biomedical Research Unit, National Institute for Health Research, Bristol, UK</nlm:aff></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">26387087</idno><idno type="pmc">4596899</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4596899</idno><idno type="RBID">PMC:4596899</idno><idno type="doi">10.1007/s10552-015-0654-9</idno><date when="2015">2015</date><idno type="wicri:Area/Pmc/Corpus">000B49</idno><idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000B49</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">The effects of height and BMI on prostate cancer incidence and mortality: a Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium</title><author><name sortKey="Davies, Neil M" sort="Davies, Neil M" uniqKey="Davies N" first="Neil M." last="Davies">Neil M. Davies</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Gaunt, Tom R" sort="Gaunt, Tom R" uniqKey="Gaunt T" first="Tom R." last="Gaunt">Tom R. Gaunt</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Lewis, Sarah J" sort="Lewis, Sarah J" uniqKey="Lewis S" first="Sarah J." last="Lewis">Sarah J. Lewis</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Holly, Jeff" sort="Holly, Jeff" uniqKey="Holly J" first="Jeff" last="Holly">Jeff Holly</name><affiliation><nlm:aff id="Aff3">School of Clinical Sciences, University of Bristol, Bristol, BS10 5NB UK</nlm:aff></affiliation></author><author><name sortKey="Donovan, Jenny L" sort="Donovan, Jenny L" uniqKey="Donovan J" first="Jenny L." last="Donovan">Jenny L. Donovan</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Hamdy, Freddie C" sort="Hamdy, Freddie C" uniqKey="Hamdy F" first="Freddie C." last="Hamdy">Freddie C. Hamdy</name><affiliation><nlm:aff id="Aff4">Nuffield Department of Surgery, University of Oxford, Oxford, UK</nlm:aff></affiliation></author><author><name sortKey="Kemp, John P" sort="Kemp, John P" uniqKey="Kemp J" first="John P." last="Kemp">John P. Kemp</name><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff5">University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD Australia</nlm:aff></affiliation></author><author><name sortKey="Eeles, Rosalind" sort="Eeles, Rosalind" uniqKey="Eeles R" first="Rosalind" last="Eeles">Rosalind Eeles</name><affiliation><nlm:aff id="Aff6">The Institute of Cancer Research, London, SM2 5NG UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff7">The Royal Marsden NHS Foundation Trust, London, SW3 6JJ UK</nlm:aff></affiliation></author><author><name sortKey="Easton, Doug" sort="Easton, Doug" uniqKey="Easton D" first="Doug" last="Easton">Doug Easton</name><affiliation><nlm:aff id="Aff8">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Kote Jarai, Zsofia" sort="Kote Jarai, Zsofia" uniqKey="Kote Jarai Z" first="Zsofia" last="Kote-Jarai">Zsofia Kote-Jarai</name><affiliation><nlm:aff id="Aff6">The Institute of Cancer Research, London, SM2 5NG UK</nlm:aff></affiliation></author><author><name sortKey="Al Olama, Ali Amin" sort="Al Olama, Ali Amin" uniqKey="Al Olama A" first="Ali Amin" last="Al Olama">Ali Amin Al Olama</name><affiliation><nlm:aff id="Aff8">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Benlloch, Sara" sort="Benlloch, Sara" uniqKey="Benlloch S" first="Sara" last="Benlloch">Sara Benlloch</name><affiliation><nlm:aff id="Aff8">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Muir, Kenneth" sort="Muir, Kenneth" uniqKey="Muir K" first="Kenneth" last="Muir">Kenneth Muir</name><affiliation><nlm:aff id="Aff9">Institute of Population Health, University of Manchester, Manchester, UK</nlm:aff></affiliation></author><author><name sortKey="Giles, Graham G" sort="Giles, Graham G" uniqKey="Giles G" first="Graham G." last="Giles">Graham G. Giles</name><affiliation><nlm:aff id="Aff10">Cancer Epidemiology Centre, The Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC Australia</nlm:aff></affiliation><affiliation><nlm:aff id="Aff11">Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia</nlm:aff></affiliation></author><author><name sortKey="Wiklund, Fredrik" sort="Wiklund, Fredrik" uniqKey="Wiklund F" first="Fredrik" last="Wiklund">Fredrik Wiklund</name><affiliation><nlm:aff id="Aff12">Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden</nlm:aff></affiliation></author><author><name sortKey="Gronberg, Henrik" sort="Gronberg, Henrik" uniqKey="Gronberg H" first="Henrik" last="Gronberg">Henrik Gronberg</name><affiliation><nlm:aff id="Aff12">Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden</nlm:aff></affiliation></author><author><name sortKey="Haiman, Christopher A" sort="Haiman, Christopher A" uniqKey="Haiman C" first="Christopher A." last="Haiman">Christopher A. Haiman</name><affiliation><nlm:aff id="Aff13">Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA USA</nlm:aff></affiliation></author><author><name sortKey="Schleutker, Johanna" sort="Schleutker, Johanna" uniqKey="Schleutker J" first="Johanna" last="Schleutker">Johanna Schleutker</name><affiliation><nlm:aff id="Aff14">Department of Medical Biochemistry and Genetics, University of Turku, Turku, Finland</nlm:aff></affiliation><affiliation><nlm:aff id="Aff15">Institute of Biomedical Technology/BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland</nlm:aff></affiliation></author><author><name sortKey="Nordestgaard, B Rge G" sort="Nordestgaard, B Rge G" uniqKey="Nordestgaard B" first="B Rge G." last="Nordestgaard">B Rge G. Nordestgaard</name><affiliation><nlm:aff id="Aff16">Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev, Denmark</nlm:aff></affiliation></author><author><name sortKey="Travis, Ruth C" sort="Travis, Ruth C" uniqKey="Travis R" first="Ruth C." last="Travis">Ruth C. Travis</name><affiliation><nlm:aff id="Aff17">Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK</nlm:aff></affiliation></author><author><name sortKey="Neal, David" sort="Neal, David" uniqKey="Neal D" first="David" last="Neal">David Neal</name><affiliation><nlm:aff id="Aff18">Surgical Oncology (Uro-Oncology: S4), University of Cambridge, Addenbrooke’s Hospital, Hills Road, Box 279, Cambridge, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff19">Li Ka Shing Centre, Cancer Research UK Cambridge Research Institute, Cambridge, UK</nlm:aff></affiliation></author><author><name sortKey="Pashayan, Nora" sort="Pashayan, Nora" uniqKey="Pashayan N" first="Nora" last="Pashayan">Nora Pashayan</name><affiliation><nlm:aff id="Aff20">Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Worts Causeway, Cambridge, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff41">Department of Applied Health Research, University College London, 1-19 Torrington Place, London, WC1E 7HB UK</nlm:aff></affiliation></author><author><name sortKey="Khaw, Kay Tee" sort="Khaw, Kay Tee" uniqKey="Khaw K" first="Kay-Tee" last="Khaw">Kay-Tee Khaw</name><affiliation><nlm:aff id="Aff21">Cambridge Institute of Public Health, University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB2 0SR UK</nlm:aff></affiliation></author><author><name sortKey="Stanford, Janet L" sort="Stanford, Janet L" uniqKey="Stanford J" first="Janet L." last="Stanford">Janet L. Stanford</name><affiliation><nlm:aff id="Aff22">Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA USA</nlm:aff></affiliation><affiliation><nlm:aff id="Aff23">Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA USA</nlm:aff></affiliation></author><author><name sortKey="Blot, William J" sort="Blot, William J" uniqKey="Blot W" first="William J." last="Blot">William J. Blot</name><affiliation><nlm:aff id="Aff24">International Epidemiology Institute, 1455 Research Blvd., Suite 550, Rockville, MD 20850 USA</nlm:aff></affiliation></author><author><name sortKey="Thibodeau, Stephen" sort="Thibodeau, Stephen" uniqKey="Thibodeau S" first="Stephen" last="Thibodeau">Stephen Thibodeau</name><affiliation><nlm:aff id="Aff25">Mayo Clinic, Rochester, MN USA</nlm:aff></affiliation></author><author><name sortKey="Maier, Christiane" sort="Maier, Christiane" uniqKey="Maier C" first="Christiane" last="Maier">Christiane Maier</name><affiliation><nlm:aff id="Aff26">Department of Urology, University Hospital Ulm, Ulm, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="Aff27">Institute of Human Genetics, University Hospital Ulm, Ulm, Germany</nlm:aff></affiliation></author><author><name sortKey="Kibel, Adam S" sort="Kibel, Adam S" uniqKey="Kibel A" first="Adam S." last="Kibel">Adam S. Kibel</name><affiliation><nlm:aff id="Aff28">Brigham and Women’s Hospital/Dana-Farber Cancer Institute, 45 Francis Street-ASB II-3, Boston, MA 02115 USA</nlm:aff></affiliation><affiliation><nlm:aff id="Aff29">Washington University, St. Louis, Missouri</nlm:aff></affiliation></author><author><name sortKey="Cybulski, Cezary" sort="Cybulski, Cezary" uniqKey="Cybulski C" first="Cezary" last="Cybulski">Cezary Cybulski</name><affiliation><nlm:aff id="Aff30">International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland</nlm:aff></affiliation></author><author><name sortKey="Cannon Albright, Lisa" sort="Cannon Albright, Lisa" uniqKey="Cannon Albright L" first="Lisa" last="Cannon-Albright">Lisa Cannon-Albright</name><affiliation><nlm:aff id="Aff31">Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT USA</nlm:aff></affiliation></author><author><name sortKey="Brenner, Hermann" sort="Brenner, Hermann" uniqKey="Brenner H" first="Hermann" last="Brenner">Hermann Brenner</name><affiliation><nlm:aff id="Aff32">Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="Aff33">Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany</nlm:aff></affiliation><affiliation><nlm:aff id="Aff34">German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany</nlm:aff></affiliation></author><author><name sortKey="Park, Jong" sort="Park, Jong" uniqKey="Park J" first="Jong" last="Park">Jong Park</name><affiliation><nlm:aff id="Aff35">Division of Cancer Prevention and Control, H. Lee Moffitt Cancer Center, 12902 Magnolia Dr., Tampa, FL USA</nlm:aff></affiliation></author><author><name sortKey="Kaneva, Radka" sort="Kaneva, Radka" uniqKey="Kaneva R" first="Radka" last="Kaneva">Radka Kaneva</name><affiliation><nlm:aff id="Aff36">Molecular Medicine Center and Department of Medical Chemistry and Biochemistry, Medical University Sofia, 2 Zdrave St, 1431 Sofia, Bulgaria</nlm:aff></affiliation></author><author><name sortKey="Batra, Jyotsna" sort="Batra, Jyotsna" uniqKey="Batra J" first="Jyotsna" last="Batra">Jyotsna Batra</name><affiliation><nlm:aff id="Aff37">Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD Australia</nlm:aff></affiliation></author><author><name sortKey="Teixeira, Manuel R" sort="Teixeira, Manuel R" uniqKey="Teixeira M" first="Manuel R." last="Teixeira">Manuel R. Teixeira</name><affiliation><nlm:aff id="Aff38">Department of Genetics, Portuguese Oncology Institute, Porto, Portugal</nlm:aff></affiliation><affiliation><nlm:aff id="Aff39">Biomedical Sciences Institute (ICBAS), Porto University, Porto, Portugal</nlm:aff></affiliation></author><author><name sortKey="Pandha, Hardev" sort="Pandha, Hardev" uniqKey="Pandha H" first="Hardev" last="Pandha">Hardev Pandha</name><affiliation><nlm:aff id="Aff40">The University of Surrey, Guildford, Surrey GU2 7XH UK</nlm:aff></affiliation></author><author><name sortKey="Lathrop, Mark" sort="Lathrop, Mark" uniqKey="Lathrop M" first="Mark" last="Lathrop">Mark Lathrop</name><affiliation><nlm:aff id="Aff42">Commissariat à l’Energie Atomique, Center National de Génotypage, Evry, France</nlm:aff></affiliation><affiliation><nlm:aff id="Aff43">McGill University-Génome Québec Innovation Centre, Montreal, Canada</nlm:aff></affiliation></author><author><name sortKey="Smith, George Davey" sort="Smith, George Davey" uniqKey="Smith G" first="George Davey" last="Smith">George Davey Smith</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation></author><author><name sortKey="Martin, Richard M" sort="Martin, Richard M" uniqKey="Martin R" first="Richard M." last="Martin">Richard M. Martin</name><affiliation><nlm:aff id="Aff1">School of Social and Community Medicine, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff2">MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</nlm:aff></affiliation><affiliation><nlm:aff id="Aff44">Bristol Nutrition Biomedical Research Unit, National Institute for Health Research, Bristol, UK</nlm:aff></affiliation></author></analytic><series><title level="j">Cancer Causes & Control</title><idno type="ISSN">0957-5243</idno><idno type="eISSN">1573-7225</idno><imprint><date when="2015">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><sec><title>Background</title><p>Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality.</p></sec><sec><title>Methods</title><p>We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies.</p></sec><sec><title>Results</title><p>The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; <italic>p</italic> = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; <italic>p</italic> = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (<italic>p</italic> heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (<italic>p</italic> heterogeneity = 0.03).</p></sec><sec><title>Conclusions</title><p>We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1007/s10552-015-0654-9) contains supplementary material, which is available to authorized users.</p></sec></div></front><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Gronberg, H" uniqKey="Gronberg H">H Grönberg</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Discacciati, A" uniqKey="Discacciati A">A Discacciati</name></author><author><name sortKey="Orsini, N" uniqKey="Orsini N">N Orsini</name></author><author><name sortKey="Wolk, A" uniqKey="Wolk A">A Wolk</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Cao, Y" uniqKey="Cao Y">Y Cao</name></author><author><name sortKey="Ma, J" uniqKey="Ma J">J Ma</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Discacciati, A" uniqKey="Discacciati A">A Discacciati</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Macinnis, Rj" uniqKey="Macinnis R">RJ MacInnis</name></author><author><name sortKey="English, Dr" uniqKey="English D">DR English</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Zuccolo, L" uniqKey="Zuccolo L">L Zuccolo</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Littman, Aj" uniqKey="Littman A">AJ Littman</name></author><author><name sortKey="White, E" uniqKey="White E">E White</name></author><author><name sortKey="Kristal, Ar" uniqKey="Kristal A">AR Kristal</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Freedland, Sj" uniqKey="Freedland S">SJ Freedland</name></author><author><name sortKey="Platz, Ea" uniqKey="Platz E">EA Platz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Buschemeyer, Wc" uniqKey="Buschemeyer W">WC Buschemeyer</name></author><author><name sortKey="Freedland, Sj" uniqKey="Freedland S">SJ Freedland</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gong, Z" uniqKey="Gong Z">Z Gong</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Collaboration, Emerging Risk Factors" uniqKey="Collaboration E">Emerging Risk Factors Collaboration</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Epstein, Mm" uniqKey="Epstein M">MM Epstein</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rowlands, M A" uniqKey="Rowlands M">M-A Rowlands</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rowlands, M A" uniqKey="Rowlands M">M-A Rowlands</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lewis, Sj" uniqKey="Lewis S">SJ Lewis</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gunnell, Dj" uniqKey="Gunnell D">DJ Gunnell</name></author><author><name sortKey="Smith, Gd" uniqKey="Smith G">GD Smith</name></author><author><name sortKey="Frankel, Sj" uniqKey="Frankel S">SJ Frankel</name></author><author><name sortKey="Kemp, M" uniqKey="Kemp M">M Kemp</name></author><author><name sortKey="Peters, Tj" uniqKey="Peters T">TJ Peters</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gunnell, D" uniqKey="Gunnell D">D Gunnell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gunnell, D" uniqKey="Gunnell D">D Gunnell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Davey Smith, G" uniqKey="Davey Smith G">G Davey Smith</name></author><author><name sortKey="Ebrahim, S" uniqKey="Ebrahim S">S Ebrahim</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Davey Smith, G" uniqKey="Davey Smith G">G Davey Smith</name></author><author><name sortKey="Hemani, G" uniqKey="Hemani G">G Hemani</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Palmer, Tm" uniqKey="Palmer T">TM Palmer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Burgess, S" uniqKey="Burgess S">S Burgess</name></author><author><name sortKey="Thompson, Sg" uniqKey="Thompson S">SG Thompson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lango Allen, H" uniqKey="Lango Allen H">H Lango Allen</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Speliotes, Ek" uniqKey="Speliotes E">EK Speliotes</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Kote Jarai, Z" uniqKey="Kote Jarai Z">Z Kote-Jarai</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Eeles, Ra" uniqKey="Eeles R">RA Eeles</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Howie, Bn" uniqKey="Howie B">BN Howie</name></author><author><name sortKey="Donnelly, P" uniqKey="Donnelly P">P Donnelly</name></author><author><name sortKey="Marchini, J" uniqKey="Marchini J">J Marchini</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Lane, Ja" uniqKey="Lane J">JA Lane</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Burgess, S" uniqKey="Burgess S">S Burgess</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Collin, Sm" uniqKey="Collin S">SM Collin</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Didelez, V" uniqKey="Didelez V">V Didelez</name></author><author><name sortKey="Sheehan, N" uniqKey="Sheehan N">N Sheehan</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Vanderweele, Tj" uniqKey="Vanderweele T">TJ VanderWeele</name></author><author><name sortKey="Tchetgen Tchetgen, Ej" uniqKey="Tchetgen Tchetgen E">EJ Tchetgen Tchetgen</name></author><author><name sortKey="Cornelis, M" uniqKey="Cornelis M">M Cornelis</name></author><author><name sortKey="Kraft, P" uniqKey="Kraft P">P Kraft</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Altman, Dg" uniqKey="Altman D">DG Altman</name></author><author><name sortKey="Bland, Jm" uniqKey="Bland J">JM Bland</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Evans, Dm" uniqKey="Evans D">DM Evans</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Davey Smith, G" uniqKey="Davey Smith G">G Davey Smith</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Edwards, Tl" uniqKey="Edwards T">TL Edwards</name></author><author><name sortKey="Giri, A" uniqKey="Giri A">A Giri</name></author><author><name sortKey="Motley, S" uniqKey="Motley S">S Motley</name></author><author><name sortKey="Duong, W" uniqKey="Duong W">W Duong</name></author><author><name sortKey="Fowke, Jh" uniqKey="Fowke J">JH Fowke</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Sutcliffe, S" uniqKey="Sutcliffe S">S Sutcliffe</name></author><author><name sortKey="Colditz, Ga" uniqKey="Colditz G">GA Colditz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Giovannucci, E" uniqKey="Giovannucci E">E Giovannucci</name></author><author><name sortKey="Rimm, Eb" uniqKey="Rimm E">EB Rimm</name></author><author><name sortKey="Stampfer, Mj" uniqKey="Stampfer M">MJ Stampfer</name></author><author><name sortKey="Colditz, Ga" uniqKey="Colditz G">GA Colditz</name></author><author><name sortKey="Willett, Wc" uniqKey="Willett W">WC Willett</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Gunnell, D" uniqKey="Gunnell D">D Gunnell</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Calle, Ee" uniqKey="Calle E">EE Calle</name></author><author><name sortKey="Rodriguez, C" uniqKey="Rodriguez C">C Rodriguez</name></author><author><name sortKey="Walker Thurmond, K" uniqKey="Walker Thurmond K">K Walker-Thurmond</name></author><author><name sortKey="Thun, Mj" uniqKey="Thun M">MJ Thun</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rodriguez, C" uniqKey="Rodriguez C">C Rodriguez</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Freeman, Vl" uniqKey="Freeman V">VL Freeman</name></author><author><name sortKey="Liao, Y" uniqKey="Liao Y">Y Liao</name></author><author><name sortKey="Durazo Arvizu, R" uniqKey="Durazo Arvizu R">R Durazo-Arvizu</name></author><author><name sortKey="Cooper, Rs" uniqKey="Cooper R">RS Cooper</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Chen, H" uniqKey="Chen H">H Chen</name></author><author><name sortKey="Miller, Ba" uniqKey="Miller B">BA Miller</name></author><author><name sortKey="Giovannucci, E" uniqKey="Giovannucci E">E Giovannucci</name></author><author><name sortKey="Hayes, Rb" uniqKey="Hayes R">RB Hayes</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Rowlands, M A" uniqKey="Rowlands M">M-A Rowlands</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wurtz, P" uniqKey="Wurtz P">P Würtz</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Nelson, Cp" uniqKey="Nelson C">CP Nelson</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Von Hinke Kessler Scholder, S" uniqKey="Von Hinke Kessler Scholder S">S von Hinke Kessler Scholder</name></author><author><name sortKey="Davey Smith, G" uniqKey="Davey Smith G">G Davey Smith</name></author><author><name sortKey="Lawlor, Da" uniqKey="Lawlor D">DA Lawlor</name></author><author><name sortKey="Propper, C" uniqKey="Propper C">C Propper</name></author><author><name sortKey="Windmeijer, F" uniqKey="Windmeijer F">F Windmeijer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Von Hinke Kessler Scholder, S" uniqKey="Von Hinke Kessler Scholder S">S von Hinke Kessler Scholder</name></author><author><name sortKey="Davey Smith, G" uniqKey="Davey Smith G">G Davey Smith</name></author><author><name sortKey="Lawlor, Da" uniqKey="Lawlor D">DA Lawlor</name></author><author><name sortKey="Propper, C" uniqKey="Propper C">C Propper</name></author><author><name sortKey="Windmeijer, F" uniqKey="Windmeijer F">F Windmeijer</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Nordestgaard, Bg" uniqKey="Nordestgaard B">BG Nordestgaard</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Fowke, Jh" uniqKey="Fowke J">JH Fowke</name></author><author><name sortKey="Motley, S" uniqKey="Motley S">S Motley</name></author><author><name sortKey="Dai, Q" uniqKey="Dai Q">Q Dai</name></author><author><name sortKey="Concepcion, R" uniqKey="Concepcion R">R Concepcion</name></author><author><name sortKey="Barocas, Da" uniqKey="Barocas D">DA Barocas</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Cancer Causes Control</journal-id><journal-id journal-id-type="iso-abbrev">Cancer Causes Control</journal-id><journal-title-group><journal-title>Cancer Causes & Control</journal-title></journal-title-group><issn pub-type="ppub">0957-5243</issn><issn pub-type="epub">1573-7225</issn><publisher><publisher-name>Springer International Publishing</publisher-name><publisher-loc>Cham</publisher-loc></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">26387087</article-id><article-id pub-id-type="pmc">4596899</article-id><article-id pub-id-type="publisher-id">654</article-id><article-id pub-id-type="doi">10.1007/s10552-015-0654-9</article-id><article-categories><subj-group subj-group-type="heading"><subject>Original Paper</subject></subj-group></article-categories><title-group><article-title>The effects of height and BMI on prostate cancer incidence and mortality: a Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Davies</surname><given-names>Neil M.</given-names></name><address><email>neil.davies@bristol.ac.uk</email></address><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Gaunt</surname><given-names>Tom R.</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Lewis</surname><given-names>Sarah J.</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author"><name><surname>Holly</surname><given-names>Jeff</given-names></name><xref ref-type="aff" rid="Aff3"></xref></contrib><contrib contrib-type="author"><name><surname>Donovan</surname><given-names>Jenny L.</given-names></name><xref ref-type="aff" rid="Aff1"></xref></contrib><contrib contrib-type="author"><name><surname>Hamdy</surname><given-names>Freddie C.</given-names></name><xref ref-type="aff" rid="Aff4"></xref></contrib><contrib contrib-type="author"><name><surname>Kemp</surname><given-names>John P.</given-names></name><xref ref-type="aff" rid="Aff2"></xref><xref ref-type="aff" rid="Aff5"></xref></contrib><contrib contrib-type="author"><name><surname>Eeles</surname><given-names>Rosalind</given-names></name><xref ref-type="aff" rid="Aff6"></xref><xref ref-type="aff" rid="Aff7"></xref></contrib><contrib contrib-type="author"><name><surname>Easton</surname><given-names>Doug</given-names></name><xref ref-type="aff" rid="Aff8"></xref></contrib><contrib contrib-type="author"><name><surname>Kote-Jarai</surname><given-names>Zsofia</given-names></name><xref ref-type="aff" rid="Aff6"></xref></contrib><contrib contrib-type="author"><name><surname>Al Olama</surname><given-names>Ali Amin</given-names></name><xref ref-type="aff" rid="Aff8"></xref></contrib><contrib contrib-type="author"><name><surname>Benlloch</surname><given-names>Sara</given-names></name><xref ref-type="aff" rid="Aff8"></xref></contrib><contrib contrib-type="author"><name><surname>Muir</surname><given-names>Kenneth</given-names></name><xref ref-type="aff" rid="Aff9"></xref></contrib><contrib contrib-type="author"><name><surname>Giles</surname><given-names>Graham G.</given-names></name><xref ref-type="aff" rid="Aff10"></xref><xref ref-type="aff" rid="Aff11"></xref></contrib><contrib contrib-type="author"><name><surname>Wiklund</surname><given-names>Fredrik</given-names></name><xref ref-type="aff" rid="Aff12"></xref></contrib><contrib contrib-type="author"><name><surname>Gronberg</surname><given-names>Henrik</given-names></name><xref ref-type="aff" rid="Aff12"></xref></contrib><contrib contrib-type="author"><name><surname>Haiman</surname><given-names>Christopher A.</given-names></name><xref ref-type="aff" rid="Aff13"></xref></contrib><contrib contrib-type="author"><name><surname>Schleutker</surname><given-names>Johanna</given-names></name><xref ref-type="aff" rid="Aff14"></xref><xref ref-type="aff" rid="Aff15"></xref></contrib><contrib contrib-type="author"><name><surname>Nordestgaard</surname><given-names>Børge G.</given-names></name><xref ref-type="aff" rid="Aff16"></xref></contrib><contrib contrib-type="author"><name><surname>Travis</surname><given-names>Ruth C.</given-names></name><xref ref-type="aff" rid="Aff17"></xref></contrib><contrib contrib-type="author"><name><surname>Neal</surname><given-names>David</given-names></name><xref ref-type="aff" rid="Aff18"></xref><xref ref-type="aff" rid="Aff19"></xref></contrib><contrib contrib-type="author"><name><surname>Pashayan</surname><given-names>Nora</given-names></name><xref ref-type="aff" rid="Aff20"></xref><xref ref-type="aff" rid="Aff41"></xref></contrib><contrib contrib-type="author"><name><surname>Khaw</surname><given-names>Kay-Tee</given-names></name><xref ref-type="aff" rid="Aff21"></xref></contrib><contrib contrib-type="author"><name><surname>Stanford</surname><given-names>Janet L.</given-names></name><xref ref-type="aff" rid="Aff22"></xref><xref ref-type="aff" rid="Aff23"></xref></contrib><contrib contrib-type="author"><name><surname>Blot</surname><given-names>William J.</given-names></name><xref ref-type="aff" rid="Aff24"></xref></contrib><contrib contrib-type="author"><name><surname>Thibodeau</surname><given-names>Stephen</given-names></name><xref ref-type="aff" rid="Aff25"></xref></contrib><contrib contrib-type="author"><name><surname>Maier</surname><given-names>Christiane</given-names></name><xref ref-type="aff" rid="Aff26"></xref><xref ref-type="aff" rid="Aff27"></xref></contrib><contrib contrib-type="author"><name><surname>Kibel</surname><given-names>Adam S.</given-names></name><xref ref-type="aff" rid="Aff28"></xref><xref ref-type="aff" rid="Aff29"></xref></contrib><contrib contrib-type="author"><name><surname>Cybulski</surname><given-names>Cezary</given-names></name><xref ref-type="aff" rid="Aff30"></xref></contrib><contrib contrib-type="author"><name><surname>Cannon-Albright</surname><given-names>Lisa</given-names></name><xref ref-type="aff" rid="Aff31"></xref></contrib><contrib contrib-type="author"><name><surname>Brenner</surname><given-names>Hermann</given-names></name><xref ref-type="aff" rid="Aff32"></xref><xref ref-type="aff" rid="Aff33"></xref><xref ref-type="aff" rid="Aff34"></xref></contrib><contrib contrib-type="author"><name><surname>Park</surname><given-names>Jong</given-names></name><xref ref-type="aff" rid="Aff35"></xref></contrib><contrib contrib-type="author"><name><surname>Kaneva</surname><given-names>Radka</given-names></name><xref ref-type="aff" rid="Aff36"></xref></contrib><contrib contrib-type="author"><name><surname>Batra</surname><given-names>Jyotsna</given-names></name><xref ref-type="aff" rid="Aff37"></xref></contrib><contrib contrib-type="author"><name><surname>Teixeira</surname><given-names>Manuel R.</given-names></name><xref ref-type="aff" rid="Aff38"></xref><xref ref-type="aff" rid="Aff39"></xref></contrib><contrib contrib-type="author"><name><surname>Pandha</surname><given-names>Hardev</given-names></name><xref ref-type="aff" rid="Aff40"></xref></contrib><contrib contrib-type="author"><collab>PRACTICAL consortium</collab></contrib><contrib contrib-type="author"><name><surname>Lathrop</surname><given-names>Mark</given-names></name><xref ref-type="aff" rid="Aff42"></xref><xref ref-type="aff" rid="Aff43"></xref></contrib><contrib contrib-type="author"><name><surname>Smith</surname><given-names>George Davey</given-names></name><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Martin</surname><given-names>Richard M.</given-names></name><address><phone>0117 9287321</phone><email>richard.martin@bristol.ac.uk</email></address><xref ref-type="aff" rid="Aff1"></xref><xref ref-type="aff" rid="Aff2"></xref><xref ref-type="aff" rid="Aff44"></xref></contrib><aff id="Aff1"><label></label>School of Social and Community Medicine, University of Bristol, Bristol, UK</aff><aff id="Aff2"><label></label>MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK</aff><aff id="Aff3"><label></label>School of Clinical Sciences, University of Bristol, Bristol, BS10 5NB UK</aff><aff id="Aff4"><label></label>Nuffield Department of Surgery, University of Oxford, Oxford, UK</aff><aff id="Aff5"><label></label>University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD Australia</aff><aff id="Aff6"><label></label>The Institute of Cancer Research, London, SM2 5NG UK</aff><aff id="Aff7"><label></label>The Royal Marsden NHS Foundation Trust, London, SW3 6JJ UK</aff><aff id="Aff8"><label></label>Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Worts Causeway, Cambridge, UK</aff><aff id="Aff9"><label></label>Institute of Population Health, University of Manchester, Manchester, UK</aff><aff id="Aff10"><label></label>Cancer Epidemiology Centre, The Cancer Council Victoria, 615 St Kilda Road, Melbourne, VIC Australia</aff><aff id="Aff11"><label></label>Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC Australia</aff><aff id="Aff12"><label></label>Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden</aff><aff id="Aff13"><label></label>Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, CA USA</aff><aff id="Aff14"><label></label>Department of Medical Biochemistry and Genetics, University of Turku, Turku, Finland</aff><aff id="Aff15"><label></label>Institute of Biomedical Technology/BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland</aff><aff id="Aff16"><label></label>Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, 2730 Herlev, Denmark</aff><aff id="Aff17"><label></label>Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK</aff><aff id="Aff18"><label></label>Surgical Oncology (Uro-Oncology: S4), University of Cambridge, Addenbrooke’s Hospital, Hills Road, Box 279, Cambridge, UK</aff><aff id="Aff19"><label></label>Li Ka Shing Centre, Cancer Research UK Cambridge Research Institute, Cambridge, UK</aff><aff id="Aff20"><label></label>Strangeways Laboratory, Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Worts Causeway, Cambridge, UK</aff><aff id="Aff21"><label></label>Cambridge Institute of Public Health, University of Cambridge, Forvie Site, Robinson Way, Cambridge, CB2 0SR UK</aff><aff id="Aff22"><label></label>Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA USA</aff><aff id="Aff23"><label></label>Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA USA</aff><aff id="Aff24"><label></label>International Epidemiology Institute, 1455 Research Blvd., Suite 550, Rockville, MD 20850 USA</aff><aff id="Aff25"><label></label>Mayo Clinic, Rochester, MN USA</aff><aff id="Aff26"><label></label>Department of Urology, University Hospital Ulm, Ulm, Germany</aff><aff id="Aff27"><label></label>Institute of Human Genetics, University Hospital Ulm, Ulm, Germany</aff><aff id="Aff28"><label></label>Brigham and Women’s Hospital/Dana-Farber Cancer Institute, 45 Francis Street-ASB II-3, Boston, MA 02115 USA</aff><aff id="Aff29"><label></label>Washington University, St. Louis, Missouri</aff><aff id="Aff30"><label></label>International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland</aff><aff id="Aff31"><label></label>Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT USA</aff><aff id="Aff32"><label></label>Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany</aff><aff id="Aff33"><label></label>Division of Preventive Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany</aff><aff id="Aff34"><label></label>German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany</aff><aff id="Aff35"><label></label>Division of Cancer Prevention and Control, H. Lee Moffitt Cancer Center, 12902 Magnolia Dr., Tampa, FL USA</aff><aff id="Aff36"><label></label>Molecular Medicine Center and Department of Medical Chemistry and Biochemistry, Medical University Sofia, 2 Zdrave St, 1431 Sofia, Bulgaria</aff><aff id="Aff37"><label></label>Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD Australia</aff><aff id="Aff38"><label></label>Department of Genetics, Portuguese Oncology Institute, Porto, Portugal</aff><aff id="Aff39"><label></label>Biomedical Sciences Institute (ICBAS), Porto University, Porto, Portugal</aff><aff id="Aff40"><label></label>The University of Surrey, Guildford, Surrey GU2 7XH UK</aff><aff id="Aff41"><label></label>Department of Applied Health Research, University College London, 1-19 Torrington Place, London, WC1E 7HB UK</aff><aff id="Aff42"><label></label>Commissariat à l’Energie Atomique, Center National de Génotypage, Evry, France</aff><aff id="Aff43"><label></label>McGill University-Génome Québec Innovation Centre, Montreal, Canada</aff><aff id="Aff44"><label></label>Bristol Nutrition Biomedical Research Unit, National Institute for Health Research, Bristol, UK</aff></contrib-group><pub-date pub-type="epub"><day>19</day><month>9</month><year>2015</year></pub-date><pub-date pub-type="pmc-release"><day>19</day><month>9</month><year>2015</year></pub-date><pub-date pub-type="ppub"><year>2015</year></pub-date><volume>26</volume><issue>11</issue><fpage>1603</fpage><lpage>1616</lpage><history><date date-type="received"><day>9</day><month>4</month><year>2015</year></date><date date-type="accepted"><day>12</day><month>8</month><year>2015</year></date></history><permissions><copyright-statement>© The Author(s) 2015</copyright-statement><license license-type="OpenAccess"><license-p><bold>Open Access</bold>This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">http://creativecommons.org/licenses/by/4.0/</ext-link>), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.</license-p></license></permissions><abstract id="Abs1"><sec><title>Background</title><p>Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality.</p></sec><sec><title>Methods</title><p>We conducted a case–control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man’s number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies.</p></sec><sec><title>Results</title><p>The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; <italic>p</italic> = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95 % CI 0.97, 1.01; <italic>p</italic> = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (<italic>p</italic> heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (<italic>p</italic> heterogeneity = 0.03).</p></sec><sec><title>Conclusions</title><p>We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.</p></sec><sec><title>Electronic supplementary material</title><p>The online version of this article (doi:10.1007/s10552-015-0654-9) contains supplementary material, which is available to authorized users.</p></sec></abstract><kwd-group xml:lang="en"><title>Keywords</title><kwd>Height</kwd><kwd>Body mass index</kwd><kwd>Prostate cancer</kwd><kwd>Mendelian randomization</kwd><kwd>Single nucleotide polymorphisms</kwd><kwd>Instrumental variables analysis</kwd></kwd-group><custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name><meta-value>© Springer International Publishing Switzerland 2015</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="Sec1" sec-type="introduction"><title>Introduction</title><p>Prostate cancer is the most common male cancer in Europe and North America, but the robust identification of potentially modifiable risk factors has proven elusive [<xref ref-type="bibr" rid="CR1">1</xref>]. Epidemiological studies suggest a potential role for obesity [<xref ref-type="bibr" rid="CR2">2</xref>–<xref ref-type="bibr" rid="CR5">5</xref>] and determinants of adult stature [<xref ref-type="bibr" rid="CR6">6</xref>], but the relationships described in the literature are complex [<xref ref-type="bibr" rid="CR7">7</xref>–<xref ref-type="bibr" rid="CR9">9</xref>]. Inverse associations have generally been observed between adiposity and localized prostate cancer, but associations are largely positive with advanced or high-grade [<xref ref-type="bibr" rid="CR2">2</xref>, <xref ref-type="bibr" rid="CR10">10</xref>] and fatal [<xref ref-type="bibr" rid="CR3">3</xref>] cancer and may vary in direction depending on whether obesity was observed in early or middle to late adulthood [<xref ref-type="bibr" rid="CR4">4</xref>]. Adult stature is generally positively associated with prostate cancer, although associations may be stronger for fatal [<xref ref-type="bibr" rid="CR11">11</xref>] or high- compared with low-grade disease [<xref ref-type="bibr" rid="CR6">6</xref>].</p><p>The explanation for these associations is unclear. Observations regarding obesity could be due to confounding by common causes of both obesity and prostate cancer (e.g., calorie and dietary fat intake) [<xref ref-type="bibr" rid="CR12">12</xref>]; the mitogenic hormones insulin and insulin-like growth factor-I [<xref ref-type="bibr" rid="CR13">13</xref>, <xref ref-type="bibr" rid="CR14">14</xref>]; delayed detection in obese men [<xref ref-type="bibr" rid="CR8">8</xref>, <xref ref-type="bibr" rid="CR9">9</xref>]; or a real biological effect [<xref ref-type="bibr" rid="CR15">15</xref>]. Observed height associations could reflect early-life environmental (e.g., fetal, dietary, social, hormones, and psychological circumstances) or shared genetic contributions to stature and prostate cancer risk [<xref ref-type="bibr" rid="CR16">16</xref>–<xref ref-type="bibr" rid="CR18">18</xref>].</p><p>Genetic epidemiological studies are less susceptible to confounding than observational epidemiology. This is because conditional on population structure, genetic variants are more likely to be independent of later environment and lifestyle factors [<xref ref-type="bibr" rid="CR19">19</xref>]; they are also unlikely to be affected by reverse causation. Thus, the existence of genetic variation in obesity and height can provide robust evidence about how associations of phenotypes, in this case obesity and height, with diseases arise [<xref ref-type="bibr" rid="CR15">15</xref>]. We previously reported that a single nucleotide polymorphism (SNP) associated with obesity (<italic>FTO</italic> rs9939609-A) was inversely associated with low-grade prostate cancer (odds ratio, OR 0.90 per A allele; 95 % CI 0.81, 0.99; <italic>p</italic> = 0.03), but positively associated with high-grade cancer (OR 1.16; 0.99, 1.37; <italic>p</italic> = 0.07) [<xref ref-type="bibr" rid="CR15">15</xref>]. These data suggest that the comparable observational associations between adiposity phenotypes and prostate cancer outcomes are not confounded. However, the evidence for these effects was weak, originating from a single study of moderate size (1,550 cases) using only a single variant, and there is no evidence we are aware of linking genetic variation in height with prostate cancer. The results, therefore, require confirmation and extension in larger datasets, using height- and additional adiposity-related genetic variants.</p><p>Our aim was to use genetic variation in height and body mass index (BMI) as unconfounded exposures to investigate the causal associations of obesity and stature with prostate cancer risk and outcomes (Mendelian randomization [<xref ref-type="bibr" rid="CR20">20</xref>]). Instead of the single-variant, single-sample approach used previously, we employ a more powerful two-sample, multiple-variant approach [<xref ref-type="bibr" rid="CR21">21</xref>, <xref ref-type="bibr" rid="CR22">22</xref>] that combines several polymorphisms (based on confirmed genetic variant-intermediate phenotype associations [<xref ref-type="bibr" rid="CR23">23</xref>, <xref ref-type="bibr" rid="CR24">24</xref>]) into genetic risk scores in order to explain more of the variance in BMI and height exposures and thus increase power and avoid weak instrument bias [<xref ref-type="bibr" rid="CR21">21</xref>].</p></sec><sec id="Sec2" sec-type="materials|methods"><title>Methods</title><p>Participants in this study were men of European genotypic ancestry from 22 independent studies contributing to the international PRACTICAL Consortium (PRostate cancer AssoCiation group To Investigate Cancer-Associated aLterations in the genome, <ext-link ext-link-type="uri" xlink:href="http://www.practical.ccge.medschl.cam.ac.uk">http://www.practical.ccge.medschl.cam.ac.uk</ext-link>) [<xref ref-type="bibr" rid="CR25">25</xref>, <xref ref-type="bibr" rid="CR26">26</xref>]. The individual studies are described at <ext-link ext-link-type="uri" xlink:href="http://www.nature.com/ng/journal/v45/n4/extref/ng.2560-S1.pdf">http://www.nature.com/ng/journal/v45/n4/extref/ng.2560-S1.pdf</ext-link>, with summary data in Table <xref rid="Tab1" ref-type="table">1</xref>. Of the studies within the PRACTICAL Consortium at the time of data extraction, we excluded the EPIC-Norfolk, CAPS, and SEARCH studies (involving 3,005 cases and 2,825 controls), because they were included in the genome-wide studies that originally detected the height and BMI genetic variants [<xref ref-type="bibr" rid="CR23">23</xref>, <xref ref-type="bibr" rid="CR24">24</xref>]. Cancers were categorized as low grade (Gleason score ≤ 6) or high grade (Gleason score ≥ 7) and localized (T1 or T2 on TNM staging, or if not available, “localized” on SEER staging) or advanced (T3 or T4 on TNM staging, or if not available, “regional” or “distant” on SEER staging). All studies met the appropriate ethical criteria for each country in accordance with the principles embodied in the Declaration of Helsinki.<table-wrap id="Tab1"><label>Table 1</label><caption><p>Clinical characteristics of the men in each of the studies contributing to the PRACTICAL consortium (<italic>n</italic> = 41,062)</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2">Study</th><th align="left" rowspan="2">Country</th><th align="left" colspan="2"><italic>n</italic></th><th align="left" colspan="2">Mean</th><th align="left" colspan="5">%</th></tr><tr><th align="left">Controls</th><th align="left">Cases</th><th align="left">Age at diagnosis (years)</th><th align="left">PSA at diagnosis (ng/ml)</th><th align="left">Screen detected<sup>b</sup> (%)</th><th align="left">Family history prostate cancer</th><th align="left">Gleason score 8–10</th><th align="left">Advanced stage (T3 or T4)</th><th align="left">Distant spread (SEER)</th></tr></thead><tbody><tr><td align="left">CPCS1</td><td align="left">Denmark</td><td char="." align="char">2,771</td><td char="." align="char">848</td><td char="." align="char">69.5</td><td align="left">48.0</td><td align="left">0.0</td><td align="left">8.2</td><td char="." align="char">35.0</td><td align="left">–</td><td align="left">–</td></tr><tr><td align="left">CPCS2</td><td align="left">Denmark</td><td char="." align="char">1,009</td><td char="." align="char">265</td><td char="." align="char">64.9</td><td align="left">36.0</td><td align="left">0.0</td><td align="left">14.7</td><td char="." align="char">10.6</td><td align="left">–</td><td align="left">–</td></tr><tr><td align="left">EPIC</td><td align="left">Europe<sup>a</sup></td><td char="." align="char">1,079</td><td char="." align="char">722</td><td char="." align="char">64.9</td><td align="left">19.7</td><td align="left">0.0</td><td align="left">–</td><td char="." align="char">3.6</td><td align="left">3.8</td><td align="left">0.9</td></tr><tr><td align="left">ESTHER</td><td align="left">Germany</td><td char="." align="char">318</td><td char="." align="char">313</td><td char="." align="char">65.5</td><td align="left">58.7</td><td align="left">61.9</td><td align="left">8.9</td><td char="." align="char">9.1</td><td align="left">26.4</td><td align="left">3.4</td></tr><tr><td align="left">FHCRC</td><td align="left">USA</td><td char="." align="char">730</td><td char="." align="char">761</td><td char="." align="char">59.7</td><td align="left">16.1</td><td align="left">–</td><td align="left">21.7</td><td char="." align="char">10.4</td><td align="left">–</td><td align="left">2.6</td></tr><tr><td align="left">IPO-Porto</td><td align="left">Portugal</td><td char="." align="char">66</td><td char="." align="char">183</td><td char="." align="char">59.3</td><td align="left">8.3</td><td align="left">82.8</td><td align="left">20.0</td><td char="." align="char">15.8</td><td align="left">64.5</td><td align="left">0.0</td></tr><tr><td align="left">MAYO</td><td align="left">USA</td><td char="." align="char">488</td><td char="." align="char">767</td><td char="." align="char">65.2</td><td align="left">15.5</td><td align="left">73.7</td><td align="left">29.1</td><td char="." align="char">33.0</td><td align="left">44.4</td><td align="left">0.5</td></tr><tr><td align="left">MCCS</td><td align="left">Australia</td><td char="." align="char">1,169</td><td char="." align="char">1,698</td><td char="." align="char">58.5</td><td align="left">136.6</td><td align="left">–</td><td align="left">23.4</td><td char="." align="char">11.0</td><td align="left">14.0</td><td align="left">0.8</td></tr><tr><td align="left">MEC</td><td align="left">USA</td><td char="." align="char">829</td><td char="." align="char">819</td><td char="." align="char">69.5</td><td align="left">–</td><td align="left">–</td><td align="left">13.0</td><td char="." align="char">36.0</td><td align="left">–</td><td align="left">2.8</td></tr><tr><td align="left">MOFFITT</td><td align="left">USA</td><td char="." align="char">100</td><td char="." align="char">412</td><td char="." align="char">64.9</td><td align="left">7.3</td><td align="left">0.0</td><td align="left">22.9</td><td char="." align="char">11.2</td><td align="left">3.5</td><td align="left">0.5</td></tr><tr><td align="left">PCMUS</td><td align="left">Bulgaria</td><td char="." align="char">140</td><td char="." align="char">151</td><td char="." align="char">69.3</td><td align="left">32.5</td><td align="left">21.2</td><td align="left">5.3</td><td char="." align="char">29.8</td><td align="left">42.4</td><td align="left">18.5</td></tr><tr><td align="left">PPF-UNIS</td><td align="left">UK</td><td char="." align="char">176</td><td char="." align="char">244</td><td char="." align="char">68.9</td><td align="left">32.0</td><td align="left">–</td><td align="left">25.3</td><td char="." align="char">10.9</td><td align="left">25.7</td><td align="left">9.0</td></tr><tr><td align="left">Poland</td><td align="left">Poland</td><td char="." align="char">359</td><td char="." align="char">438</td><td char="." align="char">67.7</td><td align="left">40.2</td><td align="left">0.0</td><td align="left">10.6</td><td char="." align="char">14.0</td><td align="left">36.8</td><td align="left">2.8</td></tr><tr><td align="left">ProMPT</td><td align="left">UK</td><td char="." align="char">1</td><td char="." align="char">166</td><td char="." align="char">66.3</td><td align="left">33.0</td><td align="left">0.0</td><td align="left">34.6</td><td char="." align="char">18.9</td><td align="left">32.7</td><td align="left">7.8</td></tr><tr><td align="left">ProtecT</td><td align="left">UK</td><td char="." align="char">1,474</td><td char="." align="char">1,542</td><td char="." align="char">62.8</td><td align="left">9.6</td><td align="left">100.0</td><td align="left">7.9</td><td char="." align="char">5.7</td><td align="left">11.3</td><td align="left">0.4</td></tr><tr><td align="left">QLD/ProsCan</td><td align="left">Australia</td><td char="." align="char">87</td><td char="." align="char">186</td><td char="." align="char">61.3</td><td align="left">6.7</td><td align="left">–</td><td align="left">36.2</td><td char="." align="char">4.0</td><td align="left">0.0</td><td align="left">0.0</td></tr><tr><td align="left">STHMI</td><td align="left">Sweden</td><td char="." align="char">2,224</td><td char="." align="char">2,002</td><td char="." align="char">66.2</td><td align="left">–</td><td align="left">–</td><td align="left">20.2</td><td char="." align="char">10.2</td><td align="left">14.2</td><td align="left">1.6</td></tr><tr><td align="left">TAMPERE</td><td align="left">Finland</td><td char="." align="char">2,413</td><td char="." align="char">2,753</td><td char="." align="char">68.2</td><td align="left">69.1</td><td align="left">46.8</td><td align="left">–</td><td char="." align="char">15.4</td><td align="left">21.0</td><td align="left">7.3</td></tr><tr><td align="left">UKGPCS</td><td align="left">UK</td><td char="." align="char">4,182</td><td char="." align="char">4,549</td><td char="." align="char">63.8</td><td align="left">83.9</td><td align="left">28.9</td><td align="left">23.4</td><td char="." align="char">17.2</td><td align="left">32.9</td><td align="left">10.7</td></tr><tr><td align="left">ULM</td><td align="left">Germany</td><td char="." align="char">354</td><td char="." align="char">601</td><td char="." align="char">63.8</td><td align="left">19.1</td><td align="left">–</td><td align="left">44.9</td><td char="." align="char">15.5</td><td align="left">39.9</td><td align="left">1.1</td></tr><tr><td align="left">UTAH</td><td align="left">USA</td><td char="." align="char">245</td><td char="." align="char">440</td><td char="." align="char">62.6</td><td align="left">–</td><td align="left">–</td><td align="left">51.4</td><td char="." align="char">16.1</td><td align="left">–</td><td align="left">4.7</td></tr><tr><td align="left">WUGS</td><td align="left">USA</td><td char="." align="char">0</td><td char="." align="char">988</td><td char="." align="char">60.8</td><td align="left">6.2</td><td align="left">–</td><td align="left">42.3</td><td char="." align="char">7.9</td><td align="left">24.2</td><td align="left">0.1</td></tr></tbody></table><table-wrap-foot><p>Studies: Copenhagen Prostate Cancer Study 1 (CPCS1); Copenhagen Prostate Cancer Study 2 (CPCS2); European Prospective Investigation Into Cancer and Nutrition (EPIC); Epidemiological investigations of the chances of preventing, recognizing early and optimally treating chronic diseases in an elderly population (ESTHER); Fred Hutchinson Cancer Research Center (FHCRC); Portuguese Oncology Institute, Porto (IPO-Porto); Mayo Clinic (MAYO); Melbourne Collaborative Cohort Study (MCCS); Multiethnic Cohort Study (MEC); The Moffitt Group (MOFFITT); Prostate Cancer study Medical University Sofia (PCMUS); Prostate Project Foundation-Postgraduate Medical School, Surrey (PPF-UNIS); The Poland Group (Poland); Prostate cancer: Mechanisms of progression and Treatment (ProMPT); Prostate testing for cancer and Treatment (ProtecT); Retrospective Queensland Study (QLD) and the Prostate Cancer Supportive Care and Patient Outcomes Project (ProsCan); Stockholm 1 (STHMI); Finnish Genetic Predisposition to Prostate Cancer Study (TAMPERE); U.K. Genetic Prostate Cancer Study and The Prostate Cancer Research Foundation Study (UKGPCS); Familial Prostate Cancer Study Ulm (ULM); UTAH Study (UTAH); Washington University Genetics Study (WUGS)</p><p><sup>a</sup>Germany, Greece, Italy, Netherlands, Spain, Sweden, Oxford</p><p><sup>b</sup>Studies with 0 % screen detected are entirely based on clinically detected cases, and studies with no information about method of detection have a missing value; 12,231 individuals have information of method of detection</p></table-wrap-foot></table-wrap></p><sec id="Sec3"><title>Genotyping</title><p>Genotyping was carried out using an Illumina Custom Infinium genotyping array (iCOGS), designed for the Collaborative Oncological Gene-environment Study (COGS), and consisted of 211,155 SNPs (details at <ext-link ext-link-type="uri" xlink:href="http://ec.europa.eu/research/health/medical-research/cancer/fp7-projects/cogs_en.html">http://ec.europa.eu/research/health/medical-research/cancer/fp7-projects/cogs_en.html</ext-link>) [<xref ref-type="bibr" rid="CR25">25</xref>, <xref ref-type="bibr" rid="CR26">26</xref>]. This array was devised to evaluate genetic variants for associations with breast, ovarian, and prostate cancer; 68,638 were specifically chosen for their potential relevance to prostate cancer. The remaining 125,877 SNPs measured by the array were chosen for relevance to other cancers and common SNPs which had been previously associated with any trait. Participants with low call rates (<95 %) and high or low heterozygosity (<italic>p</italic> < 1 × 10<sup>−5</sup>) were excluded; 201,598 SNPs passed quality control for the European ancestry samples. We used these genotypic data to impute 2.6 million SNPs based on the HapMap 2 CEU reference panel and using IMPUTE2 software [<xref ref-type="bibr" rid="CR27">27</xref>]. We excluded poorly imputed SNPs (<italic>R</italic><sup>2</sup> < 0.3).</p></sec><sec id="Sec4"><title>Constructing genetic risk scores for BMI and height</title><p>We constructed genetic risk scores [<xref ref-type="bibr" rid="CR21">21</xref>] for height and BMI using 179 and 32 variants, respectively, previously reported in genome-wide association studies (GWAS) to be associated with height [<xref ref-type="bibr" rid="CR23">23</xref>] and BMI [<xref ref-type="bibr" rid="CR24">24</xref>]. We used allele dosages from the imputation to construct the genetic risk score. The dosages code each SNP continuously from 0 to 2, and the dosages across all SNPs are summed to estimate the number of height or BMI increasing risk alleles per man. Each genetic variant was given a weight equal to the effect of the variant on height or BMI reported by the previous GWASs [<xref ref-type="bibr" rid="CR23">23</xref>, <xref ref-type="bibr" rid="CR24">24</xref>]. The genetic risk score is therefore a weighted sum of the estimated number of risk alleles across several genotypes, which can improve the precision of the results compared to an unweighted score [<xref ref-type="bibr" rid="CR21">21</xref>]. Supplementary Tables 1 and 2 provide details of the variants used and weights assigned.</p></sec><sec id="Sec5"><title>Statistical analysis</title><p>We estimated associations of the genetic risk scores with measured height and BMI using linear regression based on 1,270 men without prostate cancer [i.e., prostate-specific antigen (PSA) level <3.0 ng/ml or men with a raised PSA but who were biopsy negative] from the ProtecT population-based study [<xref ref-type="bibr" rid="CR15">15</xref>, <xref ref-type="bibr" rid="CR28">28</xref>], one of the PRACTICAL studies with the relevant phenotypic data in a well-defined control group. We computed <italic>F</italic> statistics and <italic>R</italic><sup>2</sup> values (the proportion of variation in height and BMI explained by the genetic risk score) from the linear regression to evaluate the strength of the genetic risk score instruments in a population of men at increased risk of cancer. We had 82 and 78 % power to detect an odds ratio of 1.12 and 1.25 for the effects of height and BMI on prostate cancer risk, assuming a sample size of 41,062 and that the genetic risk scores explained 6.31 and 1.46 % of the variation in height and BMI, respectively [<xref ref-type="bibr" rid="CR29">29</xref>].</p><p>We investigated associations of the phenotypes (height and BMI) and the genetic risk scores (for height and BMI) with measured covariables in the ProtecT cases to assess whether the scores were likely to be independent of potential environmental confounding factors and to assess the potential for pleiotropy (genetic confounding). We included the following potential confounders: diabetes; occupation (managerial vs. nonmanagerial); exercise (strenuous; moderate or strenuous, vs. light); alcohol intake (three or more drinks a week vs. two or less); smoking (passive, current, or ex-smoker vs. never); diagnostic PSA level; and age at recruitment. We investigated whether the scores predicted circulating insulin-like growth factor (IGF-I) levels (a potential mechanism linking size with prostate cancer [<xref ref-type="bibr" rid="CR13">13</xref>, <xref ref-type="bibr" rid="CR14">14</xref>]) and benign prostatic hyperplasia (a potential cause of detection bias [<xref ref-type="bibr" rid="CR30">30</xref>]).</p><p>We assessed the relationship of the height and BMI genetic risk scores with prostate cancer risk, stage, and grade across all 22 eligible studies contributing to PRACTICAL using logistic regression to compute ORs, with robust standard errors to account for within-study clustering. The genetic risk score was standardized to mean zero and standard deviation one, and the ORs were parameterized as the change in outcome per standard deviation increase in genetic risk score. In a secondary analysis, we also computed ORs comparing the highest versus the lowest quintile of each genetic risk score to illustrate the differences in outcomes between the extremes of the BMI or height allele score distributions. This reduced form, the association of the instrument (the genetic risk score) with the outcome, is a valid test of the direction of the effect of a phenotype on an outcome [<xref ref-type="bibr" rid="CR31">31</xref>, <xref ref-type="bibr" rid="CR32">32</xref>]. We investigated between-study heterogeneity by estimating the logistic regressions individually for each study and using the Stata <italic>metan</italic> command to estimate the <italic>I</italic><sup>2</sup> statistic assuming a fixed-effect model. As we found little evidence of heterogeneity, we report the ORs from the logistic regression analyses conducted across the 22 included studies.</p><p>We calculated ORs for all prostate cancers and then separately for localized versus advanced and low-grade (Gleason score ≤ 6) versus high-grade (Gleason score ≥ 7) cancers. Among men with prostate cancer (case-only analysis), we estimated associations of the standardized height and BMI weighted genetic risk scores with all-cause and prostate cancer-specific mortality using Cox proportional hazards regression, with age at diagnosis as the start date and age at death or final follow-up time-point as the exit date, with standard errors clustered by study (there was no evidence that the proportional hazards assumption was violated). We tested for heterogeneity in association of the genetic risk scores with localized versus advanced and low- versus high-grade prostate cancer risk using a multivariate logistic regression. We tested for heterogeneity in the association of the genetic risk scores and survival of patients with localized versus advanced and low versus high grade using the test proposed by Altman and Bland [<xref ref-type="bibr" rid="CR33">33</xref>].</p></sec><sec id="Sec6"><title>Sensitivity analyses</title><p>We assessed the potential for pleiotropy, since it is possible that variants identified in the genome-wide scans are not specific for height or BMI and have effects on the prostate cancer outcomes independent of their effects on the exposures (height or BMI) [<xref ref-type="bibr" rid="CR34">34</xref>]. If the no-effect modification assumption holds, similar instrumental variable estimates acquired using independent instruments would provide suggestive evidence against an influence of pleiotropic effects, as it is unlikely that they have shared pleiotropy [<xref ref-type="bibr" rid="CR21">21</xref>, <xref ref-type="bibr" rid="CR35">35</xref>]. Therefore, as a sensitivity analysis we tested for evidence of heterogeneity across different SNPs for each of our baseline results which differed from the null. We generated two independent genetic instruments for BMI using (1) rs1558902 in <italic>FTO</italic>, the individual SNP with the largest effect size in the meta-analysis of GWASs for BMI [<xref ref-type="bibr" rid="CR24">24</xref>] and (2) a weighted allelic score constructed from the remaining BMI-associated SNPs. We randomly split the height allele score into two independent weighted scores containing 89 and 90 SNPs (for details of the SNPs in each score see Supplementary Table 3). The height SNPs were in linkage equilibrium, and hence, these scores were statistically independent. We estimated the association of each instrument with prostate cancer and tested for heterogeneity [<xref ref-type="bibr" rid="CR33">33</xref>].</p><p>The top eight principal components that reflect the population’s genetic structure were estimated and included as covariates in adjusted regression models to account for confounding by population stratification. We also report the associations of the genetic risk scores with survival additionally adjusted for PSA level, grade, and stage. We ran all statistical analyses in Stata version 13.1 (StataCorp LP, 2014, College Station, TX).</p></sec></sec><sec id="Sec7" sec-type="results"><title>Results</title><p>Our sample consisted of 20,848 cases and 20,214 controls of European genetic descent, with genotypic data from the iCOGs array that had passed quality control and was not included in the GIANT consortium used to generate the genetic risk scores (EPIC-Norfolk, CAPS, and SEARCH studies) (Table <xref rid="Tab1" ref-type="table">1</xref>). The percentage of high-grade cancers reported varied between studies (3.6–35.0 %), as did the proportion of advanced stage cancers (3.5–64.5 %). The case-only survival analysis was based on 15,491 men, because 5,357 of the 20,848 men with prostate cancer did not have age at entry or exit in the dataset.</p><sec id="Sec8"><title>Associations of genetic risk scores with measured height and BMI in ProtecT</title><p>Associations of the weighted genetic risk scores with height and BMI in the ProtecT sub-sample are shown in Table <xref rid="Tab2" ref-type="table">2</xref>. The results with the unweighted score were similar, but less precise (results not shown). The genetic risk scores explained 6.31 and 1.46 % of the variability in height and BMI, respectively, consistent with previous studies [<xref ref-type="bibr" rid="CR23">23</xref>, <xref ref-type="bibr" rid="CR24">24</xref>], which suggest that the genetic risk scores are strong instruments for the phenotypes.<table-wrap id="Tab2"><label>Table 2</label><caption><p>Association of weighted height and BMI genetic risk scores with measured height and weight in 907 controls in ProtecT [<xref ref-type="bibr" rid="CR28">28</xref>]</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2"></th><th align="left" rowspan="2"><italic>n</italic></th><th align="left" rowspan="2">Mean difference</th><th align="left" colspan="2">95 % CI</th><th align="left" rowspan="2"><italic>r</italic><sup>2</sup> (%)</th><th align="left" rowspan="2"><italic>F</italic>-statistic</th></tr><tr><th align="left">Lower limit</th><th align="left">Upper limit</th></tr></thead><tbody><tr><td align="left">Height</td><td char="." align="char">907</td><td char="." align="char">0.26</td><td char="." align="char">0.20</td><td char="." align="char">0.33</td><td char="." align="char">6.31</td><td char="." align="char">67.6</td></tr><tr><td align="left">BMI</td><td char="." align="char">901</td><td char="." align="char">0.12</td><td char="." align="char">0.06</td><td char="." align="char">0.19</td><td char="." align="char">1.46</td><td char="." align="char">13.6</td></tr></tbody></table><table-wrap-foot><p>To allow direct comparison of effect sizes, BMI and height phenotypic measurements and the genetic risk scores were normalized to mean zero and standard deviation one</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec9"><title>Associations of genetic risk scores with potential confounders in ProtecT</title><p>Taller men were more likely to have managerial jobs, have lower PSA levels, and have joined the ProtecT study at a younger age (Table <xref rid="Tab3" ref-type="table">3</xref>), but there was little evidence that the height genetic risk score was associated with any of the confounders except benign hypertrophy of the prostate (all <italic>p</italic> values >0.05). Heavier men were more likely to have diabetes; be inactive; drink fewer than 3 drinks a week; be a nonsmoker; and have lower IGF-I levels (Table <xref rid="Tab3" ref-type="table">3</xref>), but we found little evidence that the BMI genetic risk score was associated with any of the potential confounders (all <italic>p</italic> values >0.05).<table-wrap id="Tab3"><label>Table 3</label><caption><p>Odds ratio or change in continuous variable covariates per standard deviation change in either height and BMI (phenotypes) or genetic risk scores for height and BMI (instruments) in the ProtecT study cases [<xref ref-type="bibr" rid="CR28">28</xref>]</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="3"></th><th align="left" rowspan="3"><italic>n</italic></th><th align="left" colspan="4">Observed phenotype<sup>a</sup></th><th align="left" colspan="4">Genetic risk scores<sup>a</sup></th></tr><tr><th align="left" rowspan="2">Effect estimate</th><th align="left" colspan="2">Confidence interval<sup>b</sup></th><th align="left" rowspan="2"><italic>p</italic> value</th><th align="left" rowspan="2">Effect estimate</th><th align="left" colspan="2">Confidence interval<sup>b</sup></th><th align="left" rowspan="2"><italic>p</italic> value</th></tr><tr><th align="left">Lower</th><th align="left">Upper</th><th align="left">Lower</th><th align="left">Upper</th></tr><tr><th align="left">Standardized height</th><th align="left"></th><th align="left" colspan="3">Odds ratio<sup>c</sup></th><th align="left"></th><th align="left" colspan="3">Odds ratio<sup>c</sup></th><th align="left"></th></tr></thead><tbody><tr><td align="left" colspan="10">Binary variables</td></tr><tr><td align="left"> Diabetes</td><td char="." align="char">726</td><td char="." align="char">0.91</td><td char="." align="char">0.64</td><td char="." align="char">1.30</td><td char="." align="char">0.62</td><td char="." align="char">0.94</td><td char="." align="char">0.70</td><td char="." align="char">1.25</td><td char="." align="char">0.66</td></tr><tr><td align="left"> Managerial occupation</td><td char="." align="char">818</td><td char="." align="char">1.21</td><td char="." align="char">1.06</td><td char="." align="char">1.40</td><td char="." align="char">0.006</td><td char="." align="char">0.91</td><td char="." align="char">0.79</td><td char="." align="char">1.04</td><td char="." align="char">0.17</td></tr><tr><td align="left"> Strenuous exercise</td><td char="." align="char">621</td><td char="." align="char">1.13</td><td char="." align="char">0.96</td><td char="." align="char">1.33</td><td char="." align="char">0.13</td><td char="." align="char">1.03</td><td char="." align="char">0.87</td><td char="." align="char">1.21</td><td char="." align="char">0.75</td></tr><tr><td align="left"> Moderate or strenuous exercise</td><td char="." align="char">621</td><td char="." align="char">1.15</td><td char="." align="char">0.96</td><td char="." align="char">1.37</td><td char="." align="char">0.12</td><td char="." align="char">1.01</td><td char="." align="char">0.85</td><td char="." align="char">1.20</td><td char="." align="char">0.90</td></tr><tr><td align="left"> ≥3 drinks in the last week</td><td char="." align="char">820</td><td char="." align="char">1.13</td><td char="." align="char">0.98</td><td char="." align="char">1.30</td><td char="." align="char">0.09</td><td char="." align="char">1.05</td><td char="." align="char">0.91</td><td char="." align="char">1.22</td><td char="." align="char">0.47</td></tr><tr><td align="left"> Passive smoker</td><td char="." align="char">752</td><td char="." align="char">1.03</td><td char="." align="char">0.89</td><td char="." align="char">1.19</td><td char="." align="char">0.72</td><td char="." align="char">1.00</td><td char="." align="char">0.86</td><td char="." align="char">1.16</td><td char="." align="char">0.99</td></tr><tr><td align="left"> Ever smoker</td><td char="." align="char">780</td><td char="." align="char">1.10</td><td char="." align="char">0.95</td><td char="." align="char">1.27</td><td char="." align="char">0.21</td><td char="." align="char">1.08</td><td char="." align="char">0.93</td><td char="." align="char">1.25</td><td char="." align="char">0.33</td></tr><tr><td align="left"> Current smoker</td><td char="." align="char">552</td><td char="." align="char">1.09</td><td char="." align="char">0.89</td><td char="." align="char">1.35</td><td char="." align="char">0.40</td><td char="." align="char">1.21</td><td char="." align="char">0.97</td><td char="." align="char">1.51</td><td char="." align="char">0.08</td></tr><tr><td align="left"> Benign hypertrophy of the prostate</td><td char="." align="char">704</td><td char="." align="char">0.77</td><td char="." align="char">0.58</td><td char="." align="char">1.02</td><td char="." align="char">0.07</td><td char="." align="char">1.38</td><td char="." align="char">1.01</td><td char="." align="char">1.88</td><td char="." align="char">0.05</td></tr></tbody></table><table frame="hsides" rules="groups"><thead><tr><th align="left"></th><th align="left"></th><th align="left" colspan="3">Regression coefficient<sup>c</sup></th><th align="left"></th><th align="left" colspan="3">Regression coefficient<sup>c</sup></th><th align="left"></th></tr></thead><tbody><tr><td align="left" colspan="10">Continuous variables</td></tr><tr><td align="left"> PSA (ng/ml)</td><td char="." align="char">828</td><td align="left">−1.15</td><td align="left">−2.01</td><td align="left">−0.29</td><td align="left">0.009</td><td align="left">−0.31</td><td align="left">−1.32</td><td align="left">0.70</td><td align="left">0.55</td></tr><tr><td align="left"> IGF-I (ng/ml)</td><td char="." align="char">718</td><td align="left">1.80</td><td align="left">−2.23</td><td align="left">5.83</td><td align="left">0.38</td><td align="left">−2.53</td><td align="left">−6.31</td><td align="left">1.25</td><td align="left">0.19</td></tr><tr><td align="left"> Age (years)</td><td char="." align="char">1,109</td><td align="left">−0.53</td><td align="left">−0.83</td><td align="left">−0.24</td><td align="left"><0.001</td><td align="left">0.07</td><td align="left">−0.23</td><td align="left">0.38</td><td align="left">0.64</td></tr></tbody></table><table frame="hsides" rules="groups"><thead><tr><th align="left">Standardized BMI</th><th align="left"></th><th align="left" colspan="3">Odds ratio<sup>c</sup></th><th align="left"></th><th align="left" colspan="3">Odds ratio<sup>c</sup></th><th align="left"></th></tr></thead><tbody><tr><td align="left" colspan="10">Binary variables</td></tr><tr><td align="left"> Diabetes</td><td char="." align="char">724</td><td align="left">1.90</td><td align="left">1.45</td><td align="left">2.48</td><td align="left"><0.001</td><td align="left">1.16</td><td align="left">0.86</td><td align="left">1.57</td><td align="left">0.33</td></tr><tr><td align="left"> Managerial occupation</td><td char="." align="char">813</td><td align="left">0.96</td><td align="left">0.83</td><td align="left">1.10</td><td align="left">0.54</td><td align="left">0.91</td><td align="left">0.79</td><td align="left">1.05</td><td align="left">0.20</td></tr><tr><td align="left"> Strenuous exercise</td><td char="." align="char">617</td><td align="left">0.91</td><td align="left">0.77</td><td align="left">1.08</td><td align="left">0.28</td><td align="left">1.05</td><td align="left">0.89</td><td align="left">1.23</td><td align="left">0.57</td></tr><tr><td align="left"> Moderate or strenuous exercise</td><td char="." align="char">617</td><td align="left">0.80</td><td align="left">0.66</td><td align="left">0.96</td><td align="left">0.02</td><td align="left">1.01</td><td align="left">0.85</td><td align="left">1.20</td><td align="left">0.94</td></tr><tr><td align="left"> ≥3 drinks in the last week</td><td char="." align="char">814</td><td align="left">0.87</td><td align="left">0.75</td><td align="left">1.01</td><td align="left">0.07</td><td align="left">0.90</td><td align="left">0.78</td><td align="left">1.04</td><td align="left">0.17</td></tr><tr><td align="left"> Passive smoker</td><td char="." align="char">748</td><td align="left">1.12</td><td align="left">0.97</td><td align="left">1.30</td><td align="left">0.13</td><td align="left">0.97</td><td align="left">0.84</td><td align="left">1.12</td><td align="left">0.65</td></tr><tr><td align="left"> Ever smoker</td><td char="." align="char">776</td><td align="left">1.09</td><td align="left">0.93</td><td align="left">1.27</td><td align="left">0.29</td><td align="left">1.09</td><td align="left">0.94</td><td align="left">1.27</td><td align="left">0.25</td></tr><tr><td align="left"> Current smoker</td><td char="." align="char">548</td><td align="left">0.71</td><td align="left">0.54</td><td align="left">0.94</td><td align="left">0.02</td><td align="left">1.18</td><td align="left">0.95</td><td align="left">1.48</td><td align="left">0.13</td></tr><tr><td align="left"> Benign hypertrophy of the prostate</td><td char="." align="char">700</td><td align="left">0.92</td><td align="left">0.69</td><td align="left">1.23</td><td align="left">0.56</td><td align="left">0.94</td><td align="left">0.71</td><td align="left">1.25</td><td align="left">0.66</td></tr></tbody></table><table frame="hsides" rules="groups"><thead><tr><th align="left"></th><th align="left"></th><th align="left" colspan="3">Regression coefficient<sup>c</sup></th><th align="left"></th><th align="left" colspan="3">Regression coefficient<sup>c</sup></th><th align="left"></th></tr></thead><tbody><tr><td align="left" colspan="10">Continuous variables</td></tr><tr><td align="left"> PSA (ng/ml)</td><td align="left">822</td><td align="left">−0.25</td><td align="left">−1.55</td><td align="left">1.05</td><td align="left">0.70</td><td align="left">−0.21</td><td align="left">−0.96</td><td align="left">0.54</td><td align="left">0.58</td></tr><tr><td align="left"> IGF-I (ng/ml)</td><td align="left">714</td><td align="left">−5.38</td><td align="left">−9.12</td><td align="left">−1.64</td><td align="left">0.005</td><td align="left">1.77</td><td align="left">−1.97</td><td align="left">5.51</td><td align="left">0.35</td></tr><tr><td align="left"> Age (years)</td><td align="left">1,101</td><td align="left">−0.28</td><td align="left">−0.60</td><td align="left">0.04</td><td align="left">0.08</td><td align="left">−0.04</td><td align="left">−0.33</td><td align="left">0.25</td><td align="left">0.79</td></tr></tbody></table><table-wrap-foot><p><sup>a</sup>Observed phenotypes and genetic risk scores normalized to mean zero and standard deviation one</p><p><sup>b</sup>Robust standard errors</p><p><sup>c</sup>Odds ratio or change in continuous variable per standard deviation change in height and BMI (phenotype or genetic risk score)</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec10"><title>Association of the genetic risk scores and prostate cancer risk and mortality</title><p>Associations of the genetic risk scores for height and BMI with prostate cancer risk are shown in Table <xref rid="Tab4" ref-type="table">4</xref>, with the study-specific estimates in Supplementary Figures 1–10. There was little consistent evidence that the genetic risk score for height was associated with prostate cancer, although there was weak evidence of an inverse association with advanced prostate cancer [OR, per standard deviation increase in height genetic score 0.96; 95 % CI 0.93, 0.99, <italic>p</italic> = 0.01; <italic>p</italic> heterogeneity, advanced vs. localized 0.05]. There was weak evidence that the genetic risk score for BMI was associated with a reduced prostate cancer risk (OR per standard deviation increase in BMI genetic score 0.98; 95 % CI 0.96, 1.00; <italic>p</italic> = 0.07), but little evidence of variation by stage or grade (<italic>p</italic> heterogeneity 0.64 and 0.13, respectively).<table-wrap id="Tab4"><label>Table 4</label><caption><p>Odds ratio of prostate cancer per one standard deviation change in height or BMI genetic score</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="3"></th><th align="left" rowspan="3"><italic>n</italic></th><th align="left" colspan="4">Unadjusted</th><th align="left" colspan="5">Adjusted<sup>a</sup></th></tr><tr><th align="left" rowspan="2">Odds ratio<sup><italic>c</italic></sup></th><th align="left" colspan="2">Confidence interval<sup>b</sup></th><th align="left" rowspan="2"><italic>p</italic> value</th><th align="left" rowspan="2">Odds ratio<sup><italic>c</italic></sup></th><th align="left" colspan="2">Confidence interval<sup>b</sup></th><th align="left" rowspan="2"><italic>p</italic> value</th><th align="left" rowspan="2"><italic>p</italic> heterogeneity<sup><italic>d</italic></sup></th></tr><tr><th align="left">Lower</th><th align="left">Upper</th><th align="left">Lower</th><th align="left">Upper</th></tr></thead><tbody><tr><td align="left" colspan="11"><italic>Height</italic></td></tr><tr><td align="left">Controls</td><td char="." align="char">20,214</td><td char="." align="char">1.00</td><td align="left">–</td><td align="left">–</td><td align="left">–</td><td char="." align="char">1.00</td><td align="left">–</td><td align="left">–</td><td align="left">–</td><td align="left">–</td></tr><tr><td align="left">All prostate cancers</td><td char="." align="char">20,848</td><td char="." align="char">0.96</td><td align="left">0.91</td><td align="left">1.01</td><td align="left">0.12</td><td char="." align="char">0.99</td><td align="left">0.97</td><td align="left">1.01</td><td align="left">0.23</td><td align="left"></td></tr><tr><td align="left">Localized prostate cancer</td><td char="." align="char">12,975</td><td char="." align="char">0.96</td><td align="left">0.88</td><td align="left">1.03</td><td align="left">0.27</td><td char="." align="char">1.00</td><td align="left">0.98</td><td align="left">1.02</td><td align="left">0.72</td><td align="left">0.05</td></tr><tr><td align="left">Advanced prostate cancer</td><td char="." align="char">4,325</td><td char="." align="char">0.90</td><td align="left">0.83</td><td align="left">0.98</td><td align="left">0.02</td><td char="." align="char">0.96</td><td align="left">0.93</td><td align="left">0.99</td><td align="left">0.01</td><td align="left"></td></tr><tr><td align="left">Low-grade prostate cancer</td><td char="." align="char">8,784</td><td char="." align="char">0.96</td><td align="left">0.90</td><td align="left">1.02</td><td align="left">0.20</td><td char="." align="char">0.99</td><td align="left">0.96</td><td align="left">1.01</td><td align="left">0.30</td><td align="left">0.55</td></tr><tr><td align="left">High-grade prostate cancer</td><td char="." align="char">8,230</td><td char="." align="char">0.97</td><td align="left">0.92</td><td align="left">1.02</td><td align="left">0.26</td><td char="." align="char">1.00</td><td align="left">0.98</td><td align="left">1.02</td><td align="left">0.85</td><td align="left"></td></tr><tr><td align="left" colspan="11"><italic>BMI</italic></td></tr><tr><td align="left">Controls</td><td char="." align="char">20,214</td><td char="." align="char">1.00</td><td align="left">–</td><td align="left">–</td><td align="left">–</td><td char="." align="char">1.00</td><td align="left">–</td><td align="left">–</td><td align="left">–</td><td align="left">–</td></tr><tr><td align="left">All prostate cancers</td><td char="." align="char">20,848</td><td char="." align="char">0.98</td><td align="left">0.96</td><td align="left">1.01</td><td align="left">0.15</td><td char="." align="char">0.98</td><td align="left">0.96</td><td align="left">1.00</td><td align="left">0.07</td><td align="left"></td></tr><tr><td align="left">Localized prostate cancer</td><td char="." align="char">12,975</td><td char="." align="char">0.98</td><td align="left">0.96</td><td align="left">1.00</td><td align="left">0.10</td><td char="." align="char">0.98</td><td align="left">0.96</td><td align="left">1.00</td><td align="left">0.05</td><td align="left">0.64</td></tr><tr><td align="left">Advanced prostate cancer</td><td char="." align="char">4,325</td><td char="." align="char">1.01</td><td align="left">0.97</td><td align="left">1.05</td><td align="left">0.69</td><td char="." align="char">1.01</td><td align="left">0.97</td><td align="left">1.05</td><td align="left">0.62</td><td align="left"></td></tr><tr><td align="left">Low-grade prostate cancer</td><td char="." align="char">8,784</td><td char="." align="char">0.98</td><td align="left">0.94</td><td align="left">1.02</td><td align="left">0.25</td><td char="." align="char">0.97</td><td align="left">0.94</td><td align="left">1.00</td><td align="left">0.09</td><td align="left">0.13</td></tr><tr><td align="left">High-grade prostate cancer</td><td char="." align="char">8,230</td><td char="." align="char">1.00</td><td align="left">0.97</td><td align="left">1.02</td><td align="left">0.69</td><td char="." align="char">1.00</td><td align="left">0.98</td><td align="left">1.01</td><td align="left">0.65</td><td align="left"></td></tr></tbody></table><table-wrap-foot><p><sup>a</sup>Adjusted for the eight principal components of population stratification</p><p><sup>b</sup>Based in robust standard errors to account for within-study clustering</p><p><sup>c</sup>Change in odds ratio per standard deviation change in height and BMI genetic risk score (standardized to mean zero standard deviation one)</p><p><sup>d</sup>Localized versus advanced, or high- versus low-grade using multivariate logistic regression</p></table-wrap-foot></table-wrap></p><p>The height genetic risk score was associated with an increase in prostate cancer-specific mortality among men with low-grade disease (OR per standard deviation increase in the height score 1.13; 95 % CI 1.08, 1.20, <italic>p</italic> heterogeneity, low vs. high grade <0.001), but there was little evidence of associations with all-cause mortality (Table <xref rid="Tab5" ref-type="table">5</xref>). The BMI genetic risk score was associated with higher all-cause mortality among low-grade disease (OR per standard deviation increase in the BMI score 1.08; 95 % CI 1.03, 1.14, <italic>p</italic> heterogeneity low vs. high grade = 0.03), but there was little evidence of associations with prostate cancer-specific mortality.<table-wrap id="Tab5"><label>Table 5</label><caption><p>Hazard ratio of all-cause and prostate cancer-specific mortality among men with prostate cancer per one standard change in height or BMI genetic score</p></caption><table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="3"></th><th align="left" rowspan="3">Number of participants</th><th align="left" rowspan="3">Number of failures</th><th align="left" rowspan="3">Years at risk (1000s)</th><th align="left" colspan="4">Unadjusted</th><th align="left" colspan="5">Adjusted<sup>a</sup></th></tr><tr><th align="left" rowspan="2">Hazard ratio<sup><italic>c</italic></sup></th><th align="left" colspan="2">Confidence interval<sup><italic>b</italic></sup></th><th align="left" rowspan="2"><italic>p</italic> value</th><th align="left" rowspan="2">Hazard ratio<sup><italic>c</italic></sup></th><th align="left" colspan="2">Confidence interval<sup><italic>b</italic></sup></th><th align="left" rowspan="2"><italic>p</italic> value</th><th align="left" rowspan="2"><italic>p</italic> heterogeneity<sup><italic>d</italic></sup></th></tr><tr><th align="left">Lower</th><th align="left">Upper</th><th align="left">Lower</th><th align="left">Upper</th></tr></thead><tbody><tr><td align="left" colspan="13"><italic>All-cause mortality</italic></td></tr><tr><td align="left" colspan="13">Height</td></tr><tr><td align="left"> All cases</td><td char="." align="char">14,649</td><td char="." align="char">3,591</td><td char="." align="char">105</td><td char="." align="char">1.02</td><td char="." align="char">0.97</td><td char="." align="char">1.08</td><td char="." align="char">0.47</td><td char="." align="char">1.00</td><td char="." align="char">0.96</td><td char="." align="char">1.04</td><td char="." align="char">0.88</td><td align="left"></td></tr><tr><td align="left"> Localized</td><td char="." align="char">8,553</td><td char="." align="char">1,447</td><td char="." align="char">65</td><td char="." align="char">1.01</td><td char="." align="char">0.93</td><td char="." align="char">1.09</td><td char="." align="char">0.81</td><td char="." align="char">1.00</td><td char="." align="char">0.93</td><td char="." align="char">1.07</td><td char="." align="char">0.97</td><td align="left">0.20</td></tr><tr><td align="left"> Advanced</td><td char="." align="char">3,435</td><td char="." align="char">1,332</td><td char="." align="char">25</td><td char="." align="char">1.08</td><td char="." align="char">0.98</td><td char="." align="char">1.18</td><td char="." align="char">0.11</td><td char="." align="char">1.07</td><td char="." align="char">0.99</td><td char="." align="char">1.14</td><td char="." align="char">0.07</td><td align="left"></td></tr><tr><td align="left"> Low grade</td><td char="." align="char">5,684</td><td char="." align="char">905</td><td char="." align="char">43</td><td char="." align="char">1.04</td><td char="." align="char">0.97</td><td char="." align="char">1.11</td><td char="." align="char">0.32</td><td char="." align="char">1.02</td><td char="." align="char">0.95</td><td char="." align="char">1.09</td><td char="." align="char">0.57</td><td align="left">0.80</td></tr><tr><td align="left"> High grade</td><td char="." align="char">5,892</td><td char="." align="char">1,365</td><td char="." align="char">36</td><td char="." align="char">1.02</td><td char="." align="char">0.97</td><td char="." align="char">1.08</td><td char="." align="char">0.36</td><td char="." align="char">1.01</td><td char="." align="char">0.96</td><td char="." align="char">1.06</td><td char="." align="char">0.71</td><td align="left"></td></tr><tr><td align="left" colspan="13">BMI</td></tr><tr><td align="left"> All cases</td><td char="." align="char">14,649</td><td char="." align="char">3,591</td><td char="." align="char">105</td><td char="." align="char">1.02</td><td char="." align="char">0.99</td><td char="." align="char">1.05</td><td char="." align="char">0.18</td><td char="." align="char">1.02</td><td char="." align="char">0.99</td><td char="." align="char">1.05</td><td char="." align="char">0.23</td><td align="left"></td></tr><tr><td align="left"> Localized</td><td char="." align="char">8,553</td><td char="." align="char">1,447</td><td char="." align="char">65</td><td char="." align="char">1.04</td><td char="." align="char">0.99</td><td char="." align="char">1.10</td><td char="." align="char">0.09</td><td char="." align="char">1.04</td><td char="." align="char">0.99</td><td char="." align="char">1.10</td><td char="." align="char">0.09</td><td align="left">0.28</td></tr><tr><td align="left"> Advanced</td><td char="." align="char">3,435</td><td char="." align="char">1,332</td><td char="." align="char">25</td><td char="." align="char">1.01</td><td char="." align="char">0.98</td><td char="." align="char">1.04</td><td char="." align="char">0.50</td><td char="." align="char">1.01</td><td char="." align="char">0.98</td><td char="." align="char">1.05</td><td char="." align="char">0.59</td><td align="left"></td></tr><tr><td align="left"> Low grade</td><td char="." align="char">5,684</td><td char="." align="char">905</td><td char="." align="char">43</td><td char="." align="char">1.09</td><td char="." align="char">1.04</td><td char="." align="char">1.15</td><td char="." align="char">0.001</td><td char="." align="char">1.08</td><td char="." align="char">1.03</td><td char="." align="char">1.14</td><td char="." align="char">0.002</td><td align="left">0.03</td></tr><tr><td align="left"> High grade</td><td char="." align="char">5,892</td><td char="." align="char">1,365</td><td char="." align="char">36</td><td char="." align="char">1.00</td><td char="." align="char">0.96</td><td char="." align="char">1.05</td><td char="." align="char">0.89</td><td char="." align="char">1.00</td><td char="." align="char">0.95</td><td char="." align="char">1.05</td><td char="." align="char">0.98</td><td align="left"></td></tr><tr><td align="left" colspan="13"><italic>Prostate cancer-specific mortality</italic></td></tr><tr><td align="left" colspan="13">Height</td></tr><tr><td align="left"> All cases</td><td char="." align="char">14,649</td><td char="." align="char">1,483</td><td char="." align="char">105</td><td char="." align="char">1.02</td><td char="." align="char">0.98</td><td char="." align="char">1.06</td><td char="." align="char">0.44</td><td char="." align="char">1.00</td><td char="." align="char">0.97</td><td char="." align="char">1.04</td><td char="." align="char">0.87</td><td align="left"></td></tr><tr><td align="left"> Localized</td><td char="." align="char">8,553</td><td char="." align="char">363</td><td char="." align="char">65</td><td char="." align="char">0.98</td><td char="." align="char">0.91</td><td char="." align="char">1.07</td><td char="." align="char">0.72</td><td char="." align="char">0.99</td><td char="." align="char">0.91</td><td char="." align="char">1.08</td><td char="." align="char">0.79</td><td align="left">0.29</td></tr><tr><td align="left"> Advanced</td><td char="." align="char">3,435</td><td char="." align="char">745</td><td char="." align="char">25</td><td char="." align="char">1.05</td><td char="." align="char">1.00</td><td char="." align="char">1.10</td><td char="." align="char">0.06</td><td char="." align="char">1.04</td><td char="." align="char">1.00</td><td char="." align="char">1.09</td><td char="." align="char">0.07</td><td align="left"></td></tr><tr><td align="left"> Low grade</td><td char="." align="char">5,684</td><td char="." align="char">188</td><td char="." align="char">43</td><td char="." align="char">1.13</td><td char="." align="char">1.06</td><td char="." align="char">1.21</td><td char="." align="char"><0.001</td><td char="." align="char">1.13</td><td char="." align="char">1.08</td><td char="." align="char">1.20</td><td char="." align="char"><0.001</td><td align="left"><0.001</td></tr><tr><td align="left"> High grade</td><td char="." align="char">5,892</td><td char="." align="char">678</td><td char="." align="char">36</td><td char="." align="char">0.97</td><td char="." align="char">0.93</td><td char="." align="char">1.02</td><td char="." align="char">0.20</td><td char="." align="char">0.97</td><td char="." align="char">0.93</td><td char="." align="char">1.01</td><td char="." align="char">0.19</td><td align="left"></td></tr><tr><td align="left" colspan="13">BMI</td></tr><tr><td align="left"> All cases</td><td char="." align="char">14,649</td><td char="." align="char">1,483</td><td char="." align="char">105</td><td char="." align="char">0.99</td><td char="." align="char">0.96</td><td char="." align="char">1.03</td><td char="." align="char">0.76</td><td char="." align="char">1.00</td><td char="." align="char">0.96</td><td char="." align="char">1.04</td><td char="." align="char">0.94</td><td align="left"></td></tr><tr><td align="left"> Localized</td><td char="." align="char">8,553</td><td char="." align="char">363</td><td char="." align="char">65</td><td char="." align="char">0.95</td><td char="." align="char">0.88</td><td char="." align="char">1.03</td><td char="." align="char">0.22</td><td char="." align="char">0.95</td><td char="." align="char">0.87</td><td char="." align="char">1.05</td><td char="." align="char">0.31</td><td align="left">0.09</td></tr><tr><td align="left"> Advanced</td><td char="." align="char">3,435</td><td char="." align="char">745</td><td char="." align="char">25</td><td char="." align="char">1.04</td><td char="." align="char">0.98</td><td char="." align="char">1.10</td><td char="." align="char">0.18</td><td char="." align="char">1.05</td><td char="." align="char">0.99</td><td char="." align="char">1.10</td><td char="." align="char">0.11</td><td align="left"></td></tr><tr><td align="left"> Low grade</td><td char="." align="char">5,684</td><td char="." align="char">188</td><td char="." align="char">43</td><td char="." align="char">0.95</td><td char="." align="char">0.89</td><td char="." align="char">1.01</td><td char="." align="char">0.08</td><td char="." align="char">0.95</td><td char="." align="char">0.88</td><td char="." align="char">1.01</td><td char="." align="char">0.12</td><td align="left">0.03</td></tr><tr><td align="left"> High grade</td><td char="." align="char">5,892</td><td char="." align="char">678</td><td char="." align="char">36</td><td char="." align="char">1.05</td><td char="." align="char">0.99</td><td char="." align="char">1.11</td><td char="." align="char">0.12</td><td char="." align="char">1.05</td><td char="." align="char">0.98</td><td char="." align="char">1.13</td><td char="." align="char">0.14</td><td align="left"></td></tr></tbody></table><table-wrap-foot><p><sup>a</sup>Adjusted for the first eight principal components of population stratification</p><p><sup>b</sup>Based in robust standard errors to account for within-study clustering</p><p><sup>c</sup>Change in hazard ratio per standard deviation change in height and BMI genetic risk score (standardized to mean zero standard deviation one)</p><p><sup>d</sup>Localized versus advanced, or high- versus low-grade using Bland–Altman tests</p></table-wrap-foot></table-wrap></p></sec><sec id="Sec11"><title>Sensitivity analysis</title><sec id="Sec12"><title>Prostate cancer risk</title><p>There was little evidence that men with height variants with larger effects on the height phenotype were more or less likely to be diagnosed with prostate cancer (<italic>r</italic><sup>2</sup> = 0.0071) (Fig. <xref rid="Fig1" ref-type="fig">1</xref>; see Supplementary Table 4 for associations of each of the height variants with prostate cancer risk). There was some evidence that BMI variants with the largest effect on BMI were most strongly inversely associated with prostate cancer (<italic>r</italic><sup>2</sup> = 0.0231) (Fig. <xref rid="Fig2" ref-type="fig">2</xref>; Supplementary Table 5 for associations of each of the BMI variants with prostate cancer risk). We found little evidence of heterogeneity in the effect of BMI proxied by independent instruments based on independent genetic scores made up of different sets of SNPs. Individuals with more BMI increasing <italic>FTO</italic> alleles were less likely to be diagnosed with prostate cancer (OR per BMI increasing allele rs1558902-A 0.97; 95 % CI 0.94, 1.01, <italic>p</italic> = 0.10). In line with this, the allele score based on the remaining 31 BMI SNPs was also inversely associated with prostate cancer (OR per standard deviation increase in BMI genetic score excluding FTO 0.99; 95 % CI 0.97, 1.01, <italic>p</italic> = 0.33; <italic>p</italic> value for heterogeneity between the two independent instruments = 0.38).<fig id="Fig1"><label>Fig. 1</label><caption><p>Scatter plot of effects of SNPs on prostate cancer risk by their effects on height</p></caption><graphic xlink:href="10552_2015_654_Fig1_HTML" id="MO1"></graphic></fig><fig id="Fig2"><label>Fig. 2</label><caption><p>Scatter plot of effects of SNPs on prostate cancer risk by their effects on BMI</p></caption><graphic xlink:href="10552_2015_654_Fig2_HTML" id="MO2"></graphic></fig></p></sec><sec id="Sec13"><title>All-cause mortality</title><p>There was little evidence that the two sets of independent height or BMI allele scores were associated with an increased risk of all-cause mortality in men diagnosed with prostate cancer (see Supplementary Table 10 for associations of all 179 height SNPs and all-cause mortality and Supplementary Table 7 for associations of each of the 32 BMI SNPs with all-cause mortality and prostate cancer-specific mortality).</p></sec><sec id="Sec14"><title>Prostate cancer-specific mortality</title><p>Both sets of independent height allele scores were associated with an increased risk of prostate cancer-specific mortality in men diagnosed with low-grade prostate cancer (hazard ratio per one standard deviation increase in the first height allele score 1.10; 95 % CI 1.03, 1.19, <italic>p</italic> = 0.008; and in the second height allele score 1.09; 95 % CI 1.05, 1.13, <italic>p</italic> < 0.001; <italic>p</italic> value for heterogeneity = 0.86; see Supplementary Table 8 for the association of prostate cancer-specific mortality and each of the 179 height SNPs). None of the BMI independent instruments or individual SNPs were associated with prostate cancer-specific mortality (Supplementary Table 9). Further adjusting the associations of the genetic risk scores and survival for PSA level, grade, and stage made no substantial differences to the results (Supplementary Table 10).</p></sec></sec></sec><sec id="Sec15" sec-type="discussion"><title>Discussion</title><p>We found weak evidence that genetically elevated BMI was associated with a reduced risk of prostate cancer, but that genetically elevated height was not associated with prostate cancer risk. The height and BMI allele scores were positively associated with prostate cancer-specific and all-cause mortality, respectively, but only among men with low-grade disease (<italic>p</italic> heterogeneity, low- vs. high-grade prostate cancer <0.05).</p><p>Although evidence for these associations was relatively weak, the inverse relationship of BMI with prostate cancer risk is in line with both observational data [<xref ref-type="bibr" rid="CR8">8</xref>] and our previous genetic study [<xref ref-type="bibr" rid="CR15">15</xref>]. The latter report showed an inverse relationship of a single obesity-related SNP (<italic>FTO</italic> rs9939609) with overall- and low-grade prostate cancer in ProtecT, a much smaller population-based sample of 1,550 screen-detected prostate cancers and 1,815 controls [<xref ref-type="bibr" rid="CR15">15</xref>]. We found inverse associations of a related SNP in <italic>FTO</italic> (rs1558902, which is in linkage disequilibrium with rs9939609 at <italic>r</italic><sup>2</sup> = 0.90) with overall and low-grade prostate cancer risk (individuals with more BMI increasing alleles had a reduced risk of all prostate cancer and low-grade prostate cancer, respectively (OR 0.97; 95 % CI 0.94, 1.00; <italic>p</italic> = 0.10, and OR 0.95; 95 % CI 0.90, 1.00; <italic>p</italic> = 0.06). A previous study that created genetic risk scores for BMI using 24 of the 32 SNPs from the BMI GWAS [<xref ref-type="bibr" rid="CR40">36</xref>] observed ORs for the BMI risk scores of 1.00 (95 % CI 0.97, 1.04; <italic>p</italic> = 0.94) for the unweighted score and 1.07 (95 % CI 0.91, 1.25; <italic>p</italic> = 0.41) for the weighted score, but the effect estimates were imprecise as the study only included 871 cases and 906 controls.</p><p>To determine whether our findings reflect clinically important differences in disease risk, we rescaled the results to report the effects of one standard deviation changes in height and one kg/m<sup>2</sup> increases in BMI using the coefficients for the effects of the SNPs on height and BMI reported by Lango Allen et al. [<xref ref-type="bibr" rid="CR23">23</xref>] and Speliotes et al. [<xref ref-type="bibr" rid="CR24">24</xref>], respectively. Our results imply that a one standard deviation increase in height was associated with a 49 % (95 % CI 26 %, 76 %, <italic>p</italic> < 0.001) increase in prostate cancer mortality among those with low-grade disease, assuming that the height allele score explains 10 % of the variation in height [<xref ref-type="bibr" rid="CR23">23</xref>]. A 1 kg/m<sup>2</sup> increase in BMI was associated with a 4 % (95 % CI 0 %, 8 %, <italic>p</italic> = 0.07) reduced risk of any prostate cancer diagnosis (assuming that the BMI allele score explains 1.45 % of the variation in BMI [<xref ref-type="bibr" rid="CR24">24</xref>] and a standard deviation of BMI of 3.5 kg/m<sup>2</sup>). The risk of all-cause mortality was increased by 21 % (95 % CI 7 %, 37 %) per kg/m<sup>2</sup> increase in BMI among men with low-grade disease.</p><p>Our finding that genetic variation in height was not associated with an increase in prostate cancer risk is in contrast to the majority of the observational literature [<xref ref-type="bibr" rid="CR6">6</xref>]. Indeed, we found weak evidence of an inverse association of genetic variation in height with advanced prostate cancer. However, there is some evidence of reporting bias in the previous literature; 12 of 30 prospective studies that reported effects of height on prostate cancer only in the body of the manuscript, and which were not highlighted in the title or abstract, were null (pooled OR 1.01; 0.95–1.07; <italic>I</italic><sup>2</sup> 0 %) [<xref ref-type="bibr" rid="CR6">6</xref>]. The absence of a positive association of genetic variation in height with prostate cancer risk in the current study may reflect that there is no real effect of height on prostate cancer risk or that it is the environmental (especially early-life factors [<xref ref-type="bibr" rid="CR41">37</xref>, <xref ref-type="bibr" rid="CR42">38</xref>]) and not genetic component of height variation that explains its positive link in some studies with incident prostate cancer [<xref ref-type="bibr" rid="CR16">16</xref>–<xref ref-type="bibr" rid="CR18">18</xref>, <xref ref-type="bibr" rid="CR43">39</xref>]. Alternatively, if height is associated with very early case-fatality in men with prostate cancer, then this will remove cases from the pool available for case–control studies and could theoretically lead to selection bias causing null findings. However, prostate cancer is not generally so rapidly fatal as to preclude significant numbers of men from being included in case–control studies.</p><p>The height and BMI allele scores were positively associated, respectively, with prostate cancer-specific and all-cause mortality, but only strongly among men with low-grade disease. The positive association of BMI and height with mortality among men with prostate cancer is in line with earlier studies [<xref ref-type="bibr" rid="CR9">9</xref>, <xref ref-type="bibr" rid="CR11">11</xref>, <xref ref-type="bibr" rid="CR44">40</xref>], although previous findings for height have been inconsistent [<xref ref-type="bibr" rid="CR45">41</xref>, <xref ref-type="bibr" rid="CR46">42</xref>], and one study observed that taller men with prostate cancer had improved survival [<xref ref-type="bibr" rid="CR47">43</xref>]. Our data suggest that only height is associated with prostate cancer-specific, rather than all-cause, mortality, and that BMI causes a broader range of deaths among men with prostate cancer.</p><p>The difference in the magnitude of effect estimates by grade does not appear to have been reported in the past and could simply be a chance finding. However, the p values for heterogeneity for the association of the BMI allele score with all-cause mortality and the height allele score with prostate cancer-specific mortality by grade were 0.03 and <0.001, respectively. The findings could, therefore, reflect differing determinants of progression depending on grade. This highlights the potential for modifying BMI in people with low-grade disease; however, it is likely that the genetic contribution to height explains the association of the height genetic score with prostate cancer progression. Such genetic influences could include effects on insulin-like growth factors (IGFs), which have been associated with progression of prostate cancer [<xref ref-type="bibr" rid="CR48">44</xref>].</p><p>The strengths of the study include (1) the robust instruments developed from previous GWAS that explained a reasonable proportion of the variance in the phenotypes of interest, (2) the large sample size, and (3) the potential confounders which were associated with measured height and BMI within the ProtecT study were not associated with the genetic risk scores for height and BMI. The final point suggests that association of genetic risk scores with prostate cancer outcomes is unlikely to be explained by confounders. Evidence from genetic variation is less likely to suffer from biases that affect conventional observational studies. The generalizability of our findings is supported by broadly consistent results across the 22 studies. There are limitations to our Mendelian randomization approach, and our results could be explained by bias or confounding. For example, we used combinations of genome-wide genetic variants to proxy BMI and height, but these variants may not be specific for BMI or height and may influence prostate cancer through biological pathways other than through the phenotypes that they are acting as proxies for (genetic confounding or pleiotropy). This is plausible since even single SNPs can exert pleiotropic effects across a range of different variables [<xref ref-type="bibr" rid="CR49">45</xref>]; for example, many BMI-associated SNPs are present at quite low levels of significance in a GWAS of c-reactive protein (CRP) [<xref ref-type="bibr" rid="CR34">34</xref>]. However, we found similar results when we used two independent instruments for each phenotype, suggesting these results may not be due pleiotropy of a single SNP. We assumed a similar qualitative effect of the SNPs in our sample as the GIANT consortium, which is highly plausible but may not be true. We found little evidence that the genetic risk scores were associated with baseline covariates in the ProtecT study, and this is consistent with findings from the broader literature [<xref ref-type="bibr" rid="CR36">46</xref>–<xref ref-type="bibr" rid="CR39">49</xref>].</p><p>A reduced risk of prostate cancer associated with BMI is biologically plausible, with proposed mechanisms including the increase in estrogens (aromatase inhibitors) secondary to adiposity. However, we cannot rule out detection bias [<xref ref-type="bibr" rid="CR50">50</xref>] arising from delayed diagnosis and more advanced stage at diagnosis in obese men; this may arise due to lower accuracy of digital rectal examination in obese men or lower PSA values caused by obesity-related hemodilution [<xref ref-type="bibr" rid="CR8">8</xref>, <xref ref-type="bibr" rid="CR9">9</xref>].</p><p>In conclusion, our genetic data provide some evidence (albeit weak) that an elevated BMI may protect against prostate cancer risk or reduce the likelihood of it being detected (in particular, low-grade cancer), but may increase the likelihood of death in men with low-grade prostate cancer. These observations support epidemiological findings that obesity protects against a diagnosis of localized prostate cancer but increases prostate cancer mortality [<xref ref-type="bibr" rid="CR8">8</xref>]. Previously observed positive associations of height with prostate cancer risk may reflect the environmental determinants of height. In contrast, observed positive associations of height with prostate cancer mortality may reflect the genetic determinants of height or of height determining phenotypes (e.g., IGF [<xref ref-type="bibr" rid="CR43">39</xref>]). The findings for mortality that were only observed among men with low-grade disease are novel, and potentially clinically important, but do require replication.</p></sec><sec sec-type="supplementary-material"><sec id="Sec17"><title>Electronic supplementary material</title><supplementary-material content-type="local-data" id="MOESM1"><media xlink:href="10552_2015_654_MOESM1_ESM.docx"><caption><p>Supplementary material 1 (DOCX 247 kb)</p></caption></media></supplementary-material></sec></sec></body><back><app-group><app id="App1"><sec id="Sec16"><title>The PRACTICAL CONSORTIUM (in addition to those named in the author list)</title><p>Information on the consortium can be found at <ext-link ext-link-type="uri" xlink:href="http://practical.ccge.medschl.cam.ac.uk/">http://practical.ccge.medschl.cam.ac.uk/</ext-link>.</p><p>Additional members from the consortium are: Margaret Cook<sup>1</sup>, Angela Morgan<sup>2</sup>, Artitaya Lophatananon<sup>3,4</sup>, Cyril Fisher<sup>2</sup>, Daniel Leongamornlert<sup>2</sup>, Edward J. Saunders<sup>2</sup>, Emma J. Sawyer<sup>2</sup>, Koveela Govindasami<sup>2</sup>, Malgorzata Tymrakiewicz<sup>2</sup>, Michelle Guy<sup>2</sup>, Naomi Livni<sup>2</sup>, Rosemary Wilkinson<sup>2</sup>, Sara Jugurnauth-Little<sup>2</sup>, Steve Hazel<sup>2</sup>, Tokhir Dadaev<sup>2</sup>, Melissa C. Southey<sup>5</sup>, Liesel M. Fitzgerald<sup>6</sup>, John Pedersen<sup>7</sup>, John Hopper<sup>8</sup>, Ami Karlsson<sup>9</sup>, Carin Cavalli-Bjoerkman<sup>9</sup>, Jan-Erik Johansson<sup>9</sup>, Jan Adolfson<sup>9</sup>, Markus Aly<sup>9,10</sup>, Michael Broms<sup>9</sup>, Paer Stattin<sup>9</sup>, Brian E. Henderson<sup>11</sup>, Fredrick Schumacher<sup>11</sup>, Anssi Auvinen<sup>12</sup>, Kimmo Taari<sup>13</sup>, Liisa Maeaettaenen<sup>14</sup>, Paula Kujala<sup>15</sup>, Teemu Murtola<sup>16,17</sup>, Teuvo LJ Tammela<sup>17</sup>, Tiina Wahlfors<sup>18</sup>, Andreas Roder<sup>19</sup>, Peter Iversen<sup>19</sup>, Peter Klarskov<sup>20</sup>, Sune F. Nielsen<sup>21,22</sup>, Tim J. Key<sup>23</sup>, Hans Wallinder<sup>24</sup>, Sven Gustafsson<sup>24</sup>, Jenny L. Donovan<sup>25</sup>, Freddie Hamdy<sup>26</sup>, Angela Cox<sup>27</sup>, Anne George<sup>28</sup>, Athene Lane<sup>28</sup>, Gemma Marsden<sup>26</sup>, Michael Davis<sup>25</sup>, Paul Brown<sup>25</sup>, Paul Pharoah<sup>29</sup>, Lisa B. Signorello<sup>31,30</sup>, Wei Zheng<sup>32</sup>, Shannon K. McDonnell<sup>33</sup>, Daniel J. Schaid<sup>33</sup>, Liang Wang<sup>33</sup>, Lori Tillmans<sup>33</sup>, Shaun Riska<sup>33</sup>, Thomas Schnoeller<sup>34</sup>, Kathleen Herkommer<sup>35</sup>, Manuel Luedeke<sup>34</sup>, Walther Vogel<sup>36</sup>, Dominika Wokozorczyk<sup>37</sup>, Jan Lubiski<sup>37</sup>, Wojciech Kluzniak<sup>37</sup>, Katja Butterbach<sup>38</sup>, Christa Stegmaier<sup>39</sup>, Bernd Holleczek<sup>39</sup>, Babu Zachariah<sup>40</sup>, Hui-Yi Lim<sup>41</sup>, Hyun Park<sup>40</sup>, James Haley<sup>40</sup>, Julio Pow-Sang<sup>40</sup>, Maria Rincon<sup>40</sup>, Selina Radlein<sup>40</sup>, Thomas Sellers<sup>40</sup>, Chavdar Slavov<sup>42</sup>, Aleksandrina Vlahova<sup>43</sup>, Atanaska Mitkova<sup>44</sup>, Darina Kachakova<sup>44</sup>, Elenko Popov<sup>42</sup>, Svetlana Christova<sup>43</sup>, Tihomir Dikov<sup>43</sup>, Vanio Mitev<sup>44</sup>, Allison Eckert<sup>45</sup>, Amanda Spurdle<sup>46</sup>, Angus Collins<sup>45</sup>, Glenn Wood<sup>45</sup>, Greg Malone<sup>45</sup>, Judith A. Clements<sup>45</sup>, Kris Kerr<sup>45</sup>, Megan Turner<sup>45</sup>, Pamela Saunders<sup>45</sup>, Peter Heathcote<sup>45</sup>, Srilakshmi Srinivasan<sup>45</sup>, Leire Moya<sup>45</sup>, Trina Yeadon<sup>45</sup>, Australian Prostate Cancer BioResource<sup>45</sup>, Joana Santos<sup>47</sup>, Carmen Jerónimo<sup>47</sup>, Paula Paulo<sup>47</sup>, Pedro Pinto<sup>47</sup>, Rui Henrique<sup>47</sup>, Sofia Maia<sup>47</sup>, Agnieszka Michael<sup>48</sup>, Andrzej Kierzek<sup>48</sup>, Huihai Wu<sup>48</sup></p><p><sup>1</sup>Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Laboratory, Worts Causeway, Cambridge CB1 8RN, UK, <sup>2</sup>The Institute of Cancer Research, Sutton, UK, <sup>3</sup>Institute of Population Health, University of Manchester, Manchester, UK, <sup>4</sup>Warwick Medical School, University of Warwick, Coventry, UK, <sup>5</sup>Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Grattan Street, Parkville, Victoria 3010, Australia, <sup>6</sup>Cancer Epidemiology Centre, The Cancer Council Victoria, 615 St Kilda Road, Melbourne, Victoria, Australia, <sup>7</sup> Tissupath Pty Ltd., Melbourne,Victoria 3122, Australia, <sup>8</sup>Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia, <sup>9</sup>Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden, <sup>10</sup>Department of Clinical Sciences at Danderyds Hospital, Stockholm, Sweden, <sup>11</sup>Department of Preventive Medicine, Keck School of Medicine, University of Southern California/Norris Comprehensive Cancer Center, Los Angeles, California, USA, <sup>12</sup>Department of Epidemiology, School of Health Sciences, University of Tampere, Tampere, Finland, <sup>13</sup>Department of Urology, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland, <sup>14</sup>Finnish Cancer Registry, Helsinki, Finland, <sup>15</sup>Fimlab Laboratories, Tampere University Hospital, Tampere, Finland, <sup>16</sup>School of Medicine, University of Tampere, Tampere, Finland, <sup>17</sup>Department of Urology, Tampere University Hospital and Medical School, University of Tampere, Finland, <sup>18</sup>BioMediTech, University of Tampere and FimLab Laboratories, Tampere, Finland, <sup>19</sup>Copenhagen Prostate Cancer Center, Department of Urology, Rigshospitalet, Copenhagen University Hospital, Tagensvej 20, 7521, DK-2200 Copenhagen, Denmark, <sup>20</sup>Department of Urology, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-230 Herlev, Denmark, <sup>21</sup>Department of Clinical Biochemistry, Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 75, DK-230 Herlev, Denmark, <sup>22</sup>Faculty of Health and Medical Sciences, University of Copenhagen, <sup>23</sup>Cancer Epidemiology Unit, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK, <sup>24</sup>Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK, <sup>25</sup>School of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK, <sup>26</sup>Nuffield Department of Surgical Sciences, University of Oxford, Oxford, UK, Faculty of Medical Science, University of Oxford, John Radcliffe Hospital, Oxford, UK, <sup>27</sup>CR-UK/YCR Sheffield Cancer Research Centre, University of Sheffield, Sheffield, UK, <sup>28</sup>University of Cambridge, Department of Oncology, Box 279, Addenbrooke’s Hospital, Hills Road Cambridge CB2 0QQ, UK, <sup>29</sup>Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Strangeways Laboratory, Worts Causeway, Cambridge, UK, <sup>30</sup>International Epidemiology Institute, 1555 Research Blvd., Suite 550, Rockville, MD 20850, USA, <sup>31</sup>Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA, <sup>32</sup>Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, 2525 West End Avenue, Suite 800, Nashville, TN 37232 USA, <sup>33</sup>Mayo Clinic, Rochester, Minnesota, USA, <sup>34</sup>Department of Urology, University Hospital Ulm, Germany, <sup>35</sup>Department of Urology, Klinikum rechts der Isar der Technischen Universitaet Muenchen, Munich, Germany, <sup>36</sup>Institute of Human Genetics, University Hospital Ulm, Germany, <sup>37</sup>International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland, <sup>38</sup>Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany, <sup>39</sup>Saarland Cancer Registry, 66119 Saarbruecken, Germany, <sup>40</sup>Department of Cancer Epidemiology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, USA, <sup>41</sup>Biostatistics Program, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL 33612, USA, <sup>42</sup>Department of Urology and Alexandrovska University Hospital, Medical University, Sofia, Bulgaria, <sup>43</sup>Department of General and Clinical Pathology, Medical University, Sofia, Bulgaria, <sup>44</sup>Department of Medical Chemistry and Biochemistry, Molecular Medicine Center, Medical University, Sofia, 2 Zdrave Str., 1431 Sofia, Bulgaria, <sup>45</sup>Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, Australia, <sup>46</sup>Molecular Cancer Epidemiology Laboratory, Queensland Institute of Medical Research, Brisbane, Australia, <sup>47</sup>Department of Genetics, Portuguese Oncology Institute, Porto, Portugal, <sup>48</sup>The University of Surrey, Guildford, Surrey, GU2 7XH, UK.</p></sec></app></app-group><fn-group><fn><p>PRACTICAL consortium is provided in appendix section.</p></fn></fn-group><ack><p>The Collaborative Oncological Gene-environment Study (COGS), within which the PRACTICAL consortium was assembled, would not have been possible without the contributions of the following: Per Hall (COGS); Douglas F. Easton, Paul Pharoah, Kyriaki Michailidou, Manjeet K. Bolla, Qin Wang (BCAC), Andrew Berchuck (OCAC), Rosalind A. Eeles, Douglas F. Easton, Ali Amin Al Olama, Zsofia Kote-Jarai, Sara Benlloch (PRACTICAL), Georgia Chenevix-Trench, Antonis Antoniou, Lesley McGuffog, Fergus Couch and Ken Offit (CIMBA), Joe Dennis, Alison M. Dunning, Andrew Lee, and Ed Dicks, Craig Luccarini and the staff of the Centre for Genetic Epidemiology Laboratory, Javier Benitez, Anna Gonzalez-Neira and the staff of the CNIO genotyping unit, Jacques Simard and Daniel C. Tessier, Francois Bacot, Daniel Vincent, Sylvie LaBoissière and Frederic Robidoux and the staff of the McGill University and Génome Québec Innovation Centre, Stig E. Bojesen, Sune F. Nielsen, Borge G. Nordestgaard, and the staff of the Copenhagen DNA laboratory, and Julie M. Cunningham, Sharon A. Windebank, Christopher A. Hilker, Jeffrey Meyer and the staff of Mayo Clinic Genotyping Core Facility. Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement no 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund.</p><sec id="d30e5008"><title>Funding</title><p>Support for the analysis was provided by the World Cancer Research Fund (2011/419) and Cancer Research UK (C18281/A19169). The CRUK study and the PRACTICAL consortium were supported by the Canadian Institutes of Health Research; the European Commission’s Seventh Framework Programme Grant agreement number 223175 (HEALTH-F2-2009-223175); Cancer Research UK Grants C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, C16913/A6135; and the National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative Grant No. 1 U19 CA 148537-01 (the GAME-ON initiative). The ProtecT study is funded by the UK Health Technology Assessment (HTA) Programme of the NIH Research (HTA 96/20/99; ISRCTN20141297). The authors thank the provision of the additional epidemiological data by the NHS R&D Directorate supported Prodigal study and the ProMPT (Prostate Mechanisms of Progression and Treatment) collaboration which is supported by the National Cancer Research Institute (NCRI) formed by the Department of Health, the Medical Research Council and Cancer Research UK (G0500966/75466). RAE and ZKJ are supported by Cancer Research UK Grant C5047/A7357 and the NIHR Biomedical Research Centre at The Institute of Cancer Research and Royal Marsden NHS Foundation Trust. RMM was supported by the National Institute for Health Research Bristol Nutrition Biomedical Research Unit based at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. FCH, DEN and JLD are NIHR Senior Investigators. The Integrative Epidemiology Unit is supported by the MRC and the University of Bristol (G0600705, MC_UU_12013/1,9). No funding body has influenced data collection, analysis, or its interpretations. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health. This publication is the work of the authors, who serve as the guarantors for the contents of this paper.</p></sec></ack><notes notes-type="conflict-interest"><title>Compliance with ethical standards</title><sec id="d30e5016"><title>Conflict of interest</title><p>The authors declare no conflicts of interest.</p></sec></notes><ref-list id="Bib1"><title>References</title><ref id="CR1"><label>1.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Grönberg</surname><given-names>H</given-names></name></person-group><article-title>Prostate cancer epidemiology</article-title><source>Lancet Lond Engl</source><year>2003</year><volume>361</volume><fpage>859</fpage><lpage>864</lpage><pub-id pub-id-type="doi">10.1016/S0140-6736(03)12713-4</pub-id></element-citation></ref><ref id="CR2"><label>2.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Discacciati</surname><given-names>A</given-names></name><name><surname>Orsini</surname><given-names>N</given-names></name><name><surname>Wolk</surname><given-names>A</given-names></name></person-group><article-title>Body mass index and incidence of localized and advanced prostate cancer: a dose–response meta-analysis of prospective studies</article-title><source>Ann Oncol</source><year>2012</year><volume>23</volume><fpage>1665</fpage><lpage>1671</lpage><pub-id pub-id-type="doi">10.1093/annonc/mdr603</pub-id><pub-id pub-id-type="pmid">22228452</pub-id></element-citation></ref><ref id="CR3"><label>3.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Cao</surname><given-names>Y</given-names></name><name><surname>Ma</surname><given-names>J</given-names></name></person-group><article-title>Body mass index, prostate cancer-specific mortality, and biochemical recurrence: a systematic review and meta-analysis</article-title><source>Cancer Prev Res</source><year>2011</year><volume>4</volume><fpage>486</fpage><lpage>501</lpage><pub-id pub-id-type="doi">10.1158/1940-6207.CAPR-10-0229</pub-id></element-citation></ref><ref id="CR4"><label>4.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Discacciati</surname><given-names>A</given-names></name><etal></etal></person-group><article-title>Body mass index in early and middle-late adulthood and risk of localised, advanced and fatal prostate cancer: a population-based prospective study</article-title><source>Br J Cancer</source><year>2011</year><volume>105</volume><fpage>1061</fpage><lpage>1068</lpage><pub-id pub-id-type="doi">10.1038/bjc.2011.319</pub-id><pub-id pub-id-type="pmid">21847119</pub-id></element-citation></ref><ref id="CR5"><label>5.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>MacInnis</surname><given-names>RJ</given-names></name><name><surname>English</surname><given-names>DR</given-names></name></person-group><article-title>Body size and composition and prostate cancer risk: systematic review and meta-regression analysis</article-title><source>Cancer Causes Control CCC</source><year>2006</year><volume>17</volume><fpage>989</fpage><lpage>1003</lpage><pub-id pub-id-type="doi">10.1007/s10552-006-0049-z</pub-id><pub-id pub-id-type="pmid">16933050</pub-id></element-citation></ref><ref id="CR6"><label>6.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zuccolo</surname><given-names>L</given-names></name><etal></etal></person-group><article-title>Height and prostate cancer risk: a large nested case-control study (ProtecT) and meta-analysis</article-title><source>Cancer Epidemiol Biomark Prev</source><year>2008</year><volume>17</volume><fpage>2325</fpage><lpage>2336</lpage><pub-id pub-id-type="doi">10.1158/1055-9965.EPI-08-0342</pub-id></element-citation></ref><ref id="CR7"><label>7.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Littman</surname><given-names>AJ</given-names></name><name><surname>White</surname><given-names>E</given-names></name><name><surname>Kristal</surname><given-names>AR</given-names></name></person-group><article-title>Anthropometrics and prostate cancer risk</article-title><source>Am J Epidemiol</source><year>2007</year><volume>165</volume><fpage>1271</fpage><lpage>1279</lpage><pub-id pub-id-type="doi">10.1093/aje/kwm013</pub-id><pub-id pub-id-type="pmid">17395597</pub-id></element-citation></ref><ref id="CR8"><label>8.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Freedland</surname><given-names>SJ</given-names></name><name><surname>Platz</surname><given-names>EA</given-names></name></person-group><article-title>Obesity and prostate cancer: making sense out of apparently conflicting data</article-title><source>Epidemiol Rev</source><year>2007</year><volume>29</volume><fpage>88</fpage><lpage>97</lpage><pub-id pub-id-type="doi">10.1093/epirev/mxm006</pub-id><pub-id pub-id-type="pmid">17478439</pub-id></element-citation></ref><ref id="CR9"><label>9.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Buschemeyer</surname><given-names>WC</given-names></name><name><surname>Freedland</surname><given-names>SJ</given-names></name></person-group><article-title>Obesity and prostate cancer: epidemiology and clinical implications</article-title><source>Eur Urol</source><year>2007</year><volume>52</volume><fpage>331</fpage><lpage>343</lpage><pub-id pub-id-type="doi">10.1016/j.eururo.2007.04.069</pub-id><pub-id pub-id-type="pmid">17507151</pub-id></element-citation></ref><ref id="CR10"><label>10.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gong</surname><given-names>Z</given-names></name><etal></etal></person-group><article-title>Obesity, diabetes, and risk of prostate cancer: results from the prostate cancer prevention trial</article-title><source>Cancer Epidemiol Biomark Prev</source><year>2006</year><volume>15</volume><fpage>1977</fpage><lpage>1983</lpage><pub-id pub-id-type="doi">10.1158/1055-9965.EPI-06-0477</pub-id></element-citation></ref><ref id="CR11"><label>11.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Collaboration</surname><given-names>Emerging Risk Factors</given-names></name></person-group><article-title>Adult height and the risk of cause-specific death and vascular morbidity in 1 million people: individual participant meta-analysis</article-title><source>Int J Epidemiol</source><year>2012</year><volume>41</volume><fpage>1419</fpage><lpage>1433</lpage><pub-id pub-id-type="doi">10.1093/ije/dys086</pub-id><pub-id pub-id-type="pmid">22825588</pub-id></element-citation></ref><ref id="CR12"><label>12.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Epstein</surname><given-names>MM</given-names></name><etal></etal></person-group><article-title>Dietary fatty acid intake and prostate cancer survival in Örebro County, Sweden</article-title><source>Am J Epidemiol</source><year>2012</year><volume>176</volume><fpage>240</fpage><lpage>252</lpage><pub-id pub-id-type="doi">10.1093/aje/kwr520</pub-id><pub-id pub-id-type="pmid">22781428</pub-id></element-citation></ref><ref id="CR13"><label>13.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Rowlands</surname><given-names>M-A</given-names></name><etal></etal></person-group><article-title>Circulating insulin-like growth factors and IGF-binding proteins in PSA-detected prostate cancer: the large case–control study ProtecT</article-title><source>Cancer Res</source><year>2012</year><volume>72</volume><fpage>503</fpage><lpage>515</lpage><pub-id pub-id-type="doi">10.1158/0008-5472.CAN-11-1601</pub-id><pub-id pub-id-type="pmid">22106399</pub-id></element-citation></ref><ref id="CR14"><label>14.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Rowlands</surname><given-names>M-A</given-names></name><etal></etal></person-group><article-title>The relation between adiposity throughout the life course and variation in IGFs and IGFBPs: evidence from the ProtecT (Prostate testing for cancer and Treatment) study</article-title><source>Cancer Causes Control CCC</source><year>2010</year><volume>21</volume><fpage>1829</fpage><lpage>1842</lpage><pub-id pub-id-type="doi">10.1007/s10552-010-9610-x</pub-id><pub-id pub-id-type="pmid">20652394</pub-id></element-citation></ref><ref id="CR15"><label>15.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lewis</surname><given-names>SJ</given-names></name><etal></etal></person-group><article-title>Associations between an obesity related genetic variant (FTO rs9939609) and prostate cancer risk</article-title><source>PLoS One</source><year>2010</year><volume>5</volume><fpage>e13485</fpage><pub-id pub-id-type="doi">10.1371/journal.pone.0013485</pub-id><pub-id pub-id-type="pmid">20976066</pub-id></element-citation></ref><ref id="CR16"><label>16.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gunnell</surname><given-names>DJ</given-names></name><name><surname>Smith</surname><given-names>GD</given-names></name><name><surname>Frankel</surname><given-names>SJ</given-names></name><name><surname>Kemp</surname><given-names>M</given-names></name><name><surname>Peters</surname><given-names>TJ</given-names></name></person-group><article-title>Socio-economic and dietary influences on leg length and trunk length in childhood: a reanalysis of the Carnegie (Boyd Orr) survey of diet and health in prewar Britain (1937–39)</article-title><source>Paediatr Perinat Epidemiol</source><year>1998</year><volume>12</volume><issue>Suppl 1</issue><fpage>96</fpage><lpage>113</lpage><pub-id pub-id-type="doi">10.1046/j.1365-3016.1998.0120s1096.x</pub-id><pub-id pub-id-type="pmid">9690276</pub-id></element-citation></ref><ref id="CR17"><label>17.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gunnell</surname><given-names>D</given-names></name><etal></etal></person-group><article-title>Height, leg length, and cancer risk: a systematic review</article-title><source>Epidemiol Rev</source><year>2001</year><volume>23</volume><fpage>313</fpage><lpage>342</lpage><pub-id pub-id-type="doi">10.1093/oxfordjournals.epirev.a000809</pub-id><pub-id pub-id-type="pmid">12192740</pub-id></element-citation></ref><ref id="CR18"><label>18.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gunnell</surname><given-names>D</given-names></name></person-group><article-title>Can adult anthropometry be used as a “biomarker” for prenatal and childhood exposures?</article-title><source>Int J Epidemiol</source><year>2002</year><volume>31</volume><fpage>390</fpage><lpage>394</lpage><pub-id pub-id-type="doi">10.1093/ije/31.2.390</pub-id><pub-id pub-id-type="pmid">11980801</pub-id></element-citation></ref><ref id="CR19"><label>19.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Davey Smith</surname><given-names>G</given-names></name><name><surname>Ebrahim</surname><given-names>S</given-names></name></person-group><article-title>Mendelian randomization: can genetic epidemiology contribute to understanding environmental determinants of disease?</article-title><source>Int J Epidemiol</source><year>2003</year><volume>32</volume><fpage>1</fpage><lpage>22</lpage><pub-id pub-id-type="doi">10.1093/ije/dyg070</pub-id><pub-id pub-id-type="pmid">12689998</pub-id></element-citation></ref><ref id="CR20"><label>20.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Davey Smith</surname><given-names>G</given-names></name><name><surname>Hemani</surname><given-names>G</given-names></name></person-group><article-title>Mendelian randomization: genetic anchors for causal inference in epidemiological studies</article-title><source>Hum Mol Genet</source><year>2014</year><volume>23</volume><fpage>R89</fpage><lpage>R98</lpage><pub-id pub-id-type="doi">10.1093/hmg/ddu328</pub-id><pub-id pub-id-type="pmid">25064373</pub-id></element-citation></ref><ref id="CR21"><label>21.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Palmer</surname><given-names>TM</given-names></name><etal></etal></person-group><article-title>Using multiple genetic variants as instrumental variables for modifiable risk factors</article-title><source>Stat Methods Med Res</source><year>2012</year><volume>21</volume><fpage>223</fpage><lpage>242</lpage><pub-id pub-id-type="doi">10.1177/0962280210394459</pub-id><pub-id pub-id-type="pmid">21216802</pub-id></element-citation></ref><ref id="CR22"><label>22.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Burgess</surname><given-names>S</given-names></name><name><surname>Thompson</surname><given-names>SG</given-names></name></person-group><article-title>Use of allele scores as instrumental variables for Mendelian randomization</article-title><source>Int J Epidemiol</source><year>2013</year><volume>42</volume><fpage>1134</fpage><lpage>1144</lpage><pub-id pub-id-type="doi">10.1093/ije/dyt093</pub-id><pub-id pub-id-type="pmid">24062299</pub-id></element-citation></ref><ref id="CR23"><label>23.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lango Allen</surname><given-names>H</given-names></name><etal></etal></person-group><article-title>Hundreds of variants clustered in genomic loci and biological pathways affect human height</article-title><source>Nature</source><year>2010</year><volume>467</volume><fpage>832</fpage><lpage>838</lpage><pub-id pub-id-type="doi">10.1038/nature09410</pub-id><pub-id pub-id-type="pmid">20881960</pub-id></element-citation></ref><ref id="CR24"><label>24.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Speliotes</surname><given-names>EK</given-names></name><etal></etal></person-group><article-title>Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index</article-title><source>Nat Genet</source><year>2010</year><volume>42</volume><fpage>937</fpage><lpage>948</lpage><pub-id pub-id-type="doi">10.1038/ng.686</pub-id><pub-id pub-id-type="pmid">20935630</pub-id></element-citation></ref><ref id="CR25"><label>25.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Kote-Jarai</surname><given-names>Z</given-names></name><etal></etal></person-group><article-title>Multiple novel prostate cancer predisposition loci confirmed by an international study: the PRACTICAL Consortium</article-title><source>Cancer Epidemiol Biomark Prev</source><year>2008</year><volume>17</volume><fpage>2052</fpage><lpage>2061</lpage><pub-id pub-id-type="doi">10.1158/1055-9965.EPI-08-0317</pub-id></element-citation></ref><ref id="CR26"><label>26.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Eeles</surname><given-names>RA</given-names></name><etal></etal></person-group><article-title>Identification of 23 new prostate cancer susceptibility loci using the iCOGS custom genotyping array</article-title><source>Nat Genet</source><year>2013</year><volume>45</volume><fpage>385</fpage><lpage>391</lpage><pub-id pub-id-type="doi">10.1038/ng.2560</pub-id><pub-id pub-id-type="pmid">23535732</pub-id></element-citation></ref><ref id="CR27"><label>27.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Howie</surname><given-names>BN</given-names></name><name><surname>Donnelly</surname><given-names>P</given-names></name><name><surname>Marchini</surname><given-names>J</given-names></name></person-group><article-title>A flexible and accurate genotype imputation method for the next generation of genome-wide association studies</article-title><source>PLoS Genet</source><year>2009</year><volume>5</volume><fpage>e1000529</fpage><pub-id pub-id-type="doi">10.1371/journal.pgen.1000529</pub-id><pub-id pub-id-type="pmid">19543373</pub-id></element-citation></ref><ref id="CR28"><label>28.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lane</surname><given-names>JA</given-names></name><etal></etal></person-group><article-title>Latest results from the UK trials evaluating prostate cancer screening and treatment: the CAP and ProtecT studies</article-title><source>Eur J Cancer</source><year>2010</year><volume>46</volume><fpage>3095</fpage><lpage>3101</lpage><pub-id pub-id-type="doi">10.1016/j.ejca.2010.09.016</pub-id><pub-id pub-id-type="pmid">21047592</pub-id></element-citation></ref><ref id="CR29"><label>29.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Burgess</surname><given-names>S</given-names></name></person-group><article-title>Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome</article-title><source>Int J Epidemiol</source><year>2014</year><volume>43</volume><fpage>922</fpage><lpage>929</lpage><pub-id pub-id-type="doi">10.1093/ije/dyu005</pub-id><pub-id pub-id-type="pmid">24608958</pub-id></element-citation></ref><ref id="CR30"><label>30.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Collin</surname><given-names>SM</given-names></name><etal></etal></person-group><article-title>Associations of lower urinary tract symptoms with prostate-specific antigen levels, and screen-detected localized and advanced prostate cancer: a case–control study nested within the UK population-based ProtecT (Prostate testing for cancer and Treatment) study</article-title><source>BJU Int</source><year>2008</year><volume>102</volume><fpage>1400</fpage><lpage>1406</lpage><pub-id pub-id-type="pmid">18540932</pub-id></element-citation></ref><ref id="CR31"><label>31.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Didelez</surname><given-names>V</given-names></name><name><surname>Sheehan</surname><given-names>N</given-names></name></person-group><article-title>Mendelian randomization as an instrumental variable approach to causal inference</article-title><source>Stat Methods Med Res</source><year>2007</year><volume>16</volume><fpage>309</fpage><lpage>330</lpage><pub-id pub-id-type="doi">10.1177/0962280206077743</pub-id><pub-id pub-id-type="pmid">17715159</pub-id></element-citation></ref><ref id="CR32"><label>32.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>VanderWeele</surname><given-names>TJ</given-names></name><name><surname>Tchetgen Tchetgen</surname><given-names>EJ</given-names></name><name><surname>Cornelis</surname><given-names>M</given-names></name><name><surname>Kraft</surname><given-names>P</given-names></name></person-group><article-title>Methodological challenges in Mendelian randomization</article-title><source>Epidemiology</source><year>2014</year><volume>25</volume><fpage>427</fpage><lpage>435</lpage><pub-id pub-id-type="doi">10.1097/EDE.0000000000000081</pub-id><pub-id pub-id-type="pmid">24681576</pub-id></element-citation></ref><ref id="CR33"><label>33.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Altman</surname><given-names>DG</given-names></name><name><surname>Bland</surname><given-names>JM</given-names></name></person-group><article-title>Statistics Notes: interaction revisited: the difference between two estimates</article-title><source>Br Med J</source><year>2003</year><volume>326</volume><fpage>219</fpage><pub-id pub-id-type="doi">10.1136/bmj.326.7382.219</pub-id><pub-id pub-id-type="pmid">12543843</pub-id></element-citation></ref><ref id="CR34"><label>34.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Evans</surname><given-names>DM</given-names></name><etal></etal></person-group><article-title>Mining the human phenome using allelic scores that index biological intermediates</article-title><source>PLoS Genet</source><year>2013</year><volume>9</volume><fpage>e1003919</fpage><pub-id pub-id-type="doi">10.1371/journal.pgen.1003919</pub-id><pub-id pub-id-type="pmid">24204319</pub-id></element-citation></ref><ref id="CR35"><label>35.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Davey Smith</surname><given-names>G</given-names></name></person-group><article-title>Use of genetic markers and gene–diet interactions for interrogating population-level causal influences of diet on health</article-title><source>Genes Nutr</source><year>2011</year><volume>6</volume><fpage>27</fpage><lpage>43</lpage><pub-id pub-id-type="doi">10.1007/s12263-010-0181-y</pub-id><pub-id pub-id-type="pmid">21437028</pub-id></element-citation></ref><ref id="CR40"><label>36.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Edwards</surname><given-names>TL</given-names></name><name><surname>Giri</surname><given-names>A</given-names></name><name><surname>Motley</surname><given-names>S</given-names></name><name><surname>Duong</surname><given-names>W</given-names></name><name><surname>Fowke</surname><given-names>JH</given-names></name></person-group><article-title>Pleiotropy between genetic markers of obesity and risk of prostate cancer</article-title><source>Cancer Epidemiol Biomark Prev</source><year>2013</year><volume>22</volume><fpage>1538</fpage><lpage>1546</lpage><pub-id pub-id-type="doi">10.1158/1055-9965.EPI-13-0123</pub-id></element-citation></ref><ref id="CR41"><label>37.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Sutcliffe</surname><given-names>S</given-names></name><name><surname>Colditz</surname><given-names>GA</given-names></name></person-group><article-title>Prostate cancer: is it time to expand the research focus to early-life exposures?</article-title><source>Nat Rev Cancer</source><year>2013</year><volume>13</volume><fpage>208</fpage><lpage>518</lpage><pub-id pub-id-type="doi">10.1038/nrc3434</pub-id><pub-id pub-id-type="pmid">23363989</pub-id></element-citation></ref><ref id="CR42"><label>38.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Giovannucci</surname><given-names>E</given-names></name><name><surname>Rimm</surname><given-names>EB</given-names></name><name><surname>Stampfer</surname><given-names>MJ</given-names></name><name><surname>Colditz</surname><given-names>GA</given-names></name><name><surname>Willett</surname><given-names>WC</given-names></name></person-group><article-title>Height, body weight, and risk of prostate cancer</article-title><source>Cancer Epidemiol Biomark Prev</source><year>1997</year><volume>6</volume><fpage>557</fpage><lpage>563</lpage></element-citation></ref><ref id="CR43"><label>39.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Gunnell</surname><given-names>D</given-names></name><etal></etal></person-group><article-title>Do height-related variations in insulin-like growth factors underlie the associations of stature with adult chronic disease?</article-title><source>J Clin Endocrinol Metab</source><year>2004</year><volume>89</volume><fpage>213</fpage><lpage>218</lpage><pub-id pub-id-type="doi">10.1210/jc.2003-030507</pub-id><pub-id pub-id-type="pmid">14715852</pub-id></element-citation></ref><ref id="CR44"><label>40.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Calle</surname><given-names>EE</given-names></name><name><surname>Rodriguez</surname><given-names>C</given-names></name><name><surname>Walker-Thurmond</surname><given-names>K</given-names></name><name><surname>Thun</surname><given-names>MJ</given-names></name></person-group><article-title>Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults</article-title><source>N Engl J Med</source><year>2003</year><volume>348</volume><fpage>1625</fpage><lpage>1638</lpage><pub-id pub-id-type="doi">10.1056/NEJMoa021423</pub-id><pub-id pub-id-type="pmid">12711737</pub-id></element-citation></ref><ref id="CR45"><label>41.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Rodriguez</surname><given-names>C</given-names></name><etal></etal></person-group><article-title>Body mass index, height, and prostate cancer mortality in two large cohorts of adult men in the United States</article-title><source>Cancer Epidemiol Biomark Prev</source><year>2001</year><volume>10</volume><fpage>345</fpage><lpage>353</lpage></element-citation></ref><ref id="CR46"><label>42.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Freeman</surname><given-names>VL</given-names></name><name><surname>Liao</surname><given-names>Y</given-names></name><name><surname>Durazo-Arvizu</surname><given-names>R</given-names></name><name><surname>Cooper</surname><given-names>RS</given-names></name></person-group><article-title>Height and risk of fatal prostate cancer: findings from the National Health Interview Survey (1986 to 1994)</article-title><source>Ann Epidemiol</source><year>2001</year><volume>11</volume><fpage>22</fpage><lpage>27</lpage><pub-id pub-id-type="doi">10.1016/S1047-2797(00)00172-1</pub-id><pub-id pub-id-type="pmid">11164116</pub-id></element-citation></ref><ref id="CR47"><label>43.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chen</surname><given-names>H</given-names></name><name><surname>Miller</surname><given-names>BA</given-names></name><name><surname>Giovannucci</surname><given-names>E</given-names></name><name><surname>Hayes</surname><given-names>RB</given-names></name></person-group><article-title>Height and the survival of prostate cancer patients</article-title><source>Cancer Epidemiol Biomark Prev</source><year>2003</year><volume>12</volume><fpage>215</fpage><lpage>218</lpage></element-citation></ref><ref id="CR48"><label>44.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Rowlands</surname><given-names>M-A</given-names></name><etal></etal></person-group><article-title>Serum insulin-like growth factors and mortality in localised and advanced clinically detected prostate cancer</article-title><source>Cancer Causes Control CCC</source><year>2012</year><volume>23</volume><fpage>347</fpage><lpage>354</lpage><pub-id pub-id-type="doi">10.1007/s10552-011-9883-8</pub-id><pub-id pub-id-type="pmid">22183619</pub-id></element-citation></ref><ref id="CR49"><label>45.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Würtz</surname><given-names>P</given-names></name><etal></etal></person-group><article-title>Lipoprotein subclass profiling reveals pleiotropy in the genetic variants of lipid risk factors for coronary heart disease: a note on Mendelian randomization studies</article-title><source>J Am Coll Cardiol</source><year>2013</year><volume>62</volume><fpage>1906</fpage><lpage>1908</lpage><pub-id pub-id-type="doi">10.1016/j.jacc.2013.07.085</pub-id><pub-id pub-id-type="pmid">24055740</pub-id></element-citation></ref><ref id="CR36"><label>46.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Nelson</surname><given-names>CP</given-names></name><etal></etal></person-group><article-title>Genetically determined height and coronary artery disease</article-title><source>N Engl J Med</source><year>2015</year><volume>372</volume><fpage>1608</fpage><lpage>1618</lpage><pub-id pub-id-type="doi">10.1056/NEJMoa1404881</pub-id><pub-id pub-id-type="pmid">25853659</pub-id></element-citation></ref><ref id="CR37"><label>47.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>von Hinke Kessler Scholder</surname><given-names>S</given-names></name><name><surname>Davey Smith</surname><given-names>G</given-names></name><name><surname>Lawlor</surname><given-names>DA</given-names></name><name><surname>Propper</surname><given-names>C</given-names></name><name><surname>Windmeijer</surname><given-names>F</given-names></name></person-group><article-title>The effect of fat mass on educational attainment: examining the sensitivity to different identification strategies</article-title><source>Econ Hum Biol</source><year>2012</year><volume>10</volume><fpage>405</fpage><lpage>418</lpage><pub-id pub-id-type="doi">10.1016/j.ehb.2012.04.015</pub-id><pub-id pub-id-type="pmid">22709667</pub-id></element-citation></ref><ref id="CR38"><label>48.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>von Hinke Kessler Scholder</surname><given-names>S</given-names></name><name><surname>Davey Smith</surname><given-names>G</given-names></name><name><surname>Lawlor</surname><given-names>DA</given-names></name><name><surname>Propper</surname><given-names>C</given-names></name><name><surname>Windmeijer</surname><given-names>F</given-names></name></person-group><article-title>Child height, health and human capital: evidence using genetic markers</article-title><source>Eur Econ Rev</source><year>2013</year><volume>57</volume><fpage>1</fpage><lpage>22</lpage><pub-id pub-id-type="doi">10.1016/j.euroecorev.2012.09.009</pub-id><pub-id pub-id-type="pmid">25673883</pub-id></element-citation></ref><ref id="CR39"><label>49.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Nordestgaard</surname><given-names>BG</given-names></name><etal></etal></person-group><article-title>The effect of elevated body mass index on ischemic heart disease risk: causal estimates from a Mendelian randomisation approach</article-title><source>PLoS Med</source><year>2012</year><volume>9</volume><fpage>e1001212</fpage><pub-id pub-id-type="doi">10.1371/journal.pmed.1001212</pub-id><pub-id pub-id-type="pmid">22563304</pub-id></element-citation></ref><ref id="CR50"><label>50.</label><element-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Fowke</surname><given-names>JH</given-names></name><name><surname>Motley</surname><given-names>S</given-names></name><name><surname>Dai</surname><given-names>Q</given-names></name><name><surname>Concepcion</surname><given-names>R</given-names></name><name><surname>Barocas</surname><given-names>DA</given-names></name></person-group><article-title>Association between biomarkers of obesity and risk of high-grade prostatic intraepithelial neoplasia and prostate cancer-evidence of effect modification by prostate size</article-title><source>Cancer Lett</source><year>2013</year><volume>328</volume><fpage>345</fpage><lpage>352</lpage><pub-id pub-id-type="doi">10.1016/j.canlet.2012.10.010</pub-id><pub-id pub-id-type="pmid">23079532</pub-id></element-citation></ref></ref-list></back></pmc></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Wicri/Asie/explor/AustralieFrV1/Data/Pmc/Corpus
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000B490 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Pmc/Corpus/biblio.hfd -nk 000B490 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Wicri/Asie
|area= AustralieFrV1
|flux= Pmc
|étape= Corpus
|type= RBID
|clé=
|texte=
}}
| This area was generated with Dilib version V0.6.33. |  |