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1. Smoking, blood cells and myeloproliferative neoplasms: meta-analysis and Mendelian randomization of 2·3 million people.

Author

Jayasuriya NA, Kjaergaard AD, Pedersen KM, Sørensen AL, Bak M, Larsen MK, Nordestgaard BG, Bojesen SE, Çolak Y, Skov V, Kjaer L, Tolstrup JS, Hasselbalch HC, and Ellervik C

Subjects
Adolescent, Adult, Aged, Aged, 80 and over, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Young Adult, Blood Cells chemistry, Mendelian Randomization Analysis methods, Myeloproliferative Disorders epidemiology, Smoking adverse effects
Abstract

Meta-analyses and Mendelian randomization (MR) may clarify the associations of smoking, blood cells and myeloproliferative neoplasms (MPN). We investigated the association of smoking with blood cells in the Danish General Suburban Population Study (GESUS, n = 11 083), by meta-analyses (including GESUS) of 92 studies (n = 531 741) and MR of smoking variant CHRNA3 (rs1051730[A]) in UK Biobank, and with MPN in a meta-analysis of six studies (n (total/cases):1 425 529/2187), totalling 2 307 745 participants. In the meta-analysis the random-effects standardized mean difference (SMD) in current smokers versus non-smokers was 0·82 (0·75-0·89, P = 2·0 * 10 -108 ) for leukocytes, 0·09 (-0·02 to 0·21, P = 0·12) for erythrocytes, 0·53 (0·42-0·64, P = 8·0 * 10 -22 ) for haematocrit, 0·42 (0·34-0·51, P = 7·1 * 10 -21 ) for haemoglobin, 0·19 (0·08-0·31, P = 1·2 * 10 -3 ) for mean corpuscular haemoglobin (MCH), 0·29 (0·19-0·39, P = 1·6 * 10 -8 ) for mean corpuscular volume (MCV), and 0·04 (-0·04 to 0·13, P = 0·34) for platelets with trends for ever/ex-/current smokers, light/heavy smokers and female/male smokers. Analyses presented high heterogeneity but low publication bias. Per allele in CHRNA3, cigarettes per day in current smokers was associated with increased blood cell counts (leukocytes, neutrophils), MCH, red cell distribution width (RDW) and MCV. The pooled fixed-effects odds ratio for MPN was 1·44 [95% confidence interval (CI): 1·33-1·56; P = 1·8 * 10 -19 ; I 2  = 0%] in current smokers, 1·29 (1·15-1·44; P = 8·0 * 10 -6 ; I 2  = 0%) in ex-smokers, 1·49 (1·26-1·77; P = 4·4 * 10 -6 ; I 2  = 0%) in light smokers and 2·04 (1·74-2·39, P = 2·3 * 10 -18 ; I 2  = 51%) in heavy smokers compared with non-smokers. Smoking is observationally and genetically associated with increased leukocyte counts and red blood cell indices (MCH, MCV, RDW) and observationally with risk of MPN in current and ex-smokers versus non/never-smokers., (© 2019 British Society for Haematology and John Wiley & Sons Ltd.)

Published
2020
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2. Smoking Reduces Plasma Bilirubin: Observational and Genetic Analyses in the Copenhagen General Population Study.

Author

Kodal JB, Çolak Y, Kobylecki CJ, Vedel-Krogh S, Nordestgaard BG, and Afzal S

Subjects
Adult, Aged, Aged, 80 and over, Alleles, Denmark epidemiology, Female, Genotype, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Prospective Studies, Risk Factors, Smokers psychology, Smoking epidemiology, Young Adult, Bilirubin blood, Polymorphism, Single Nucleotide, Receptors, Nicotinic genetics, Smoking blood, Smoking genetics, Smoking Cessation statistics & numerical data
Abstract

Introduction: Observational studies have found lower concentrations of plasma bilirubin in current smokers compared with former and never smokers. However, whether there is a causal relationship between smoking and bilirubin is unknown. In a Mendelian randomization analysis, we tested the hypothesis that higher tobacco consumption is causally associated with lower concentrations of plasma bilirubin., Methods: We genotyped 103 557 individuals aged 20-100 years from the Copenhagen General Population Study for the CHRNA3 rs1051730 genotype, known to be associated with higher tobacco consumption. Tobacco consumption was defined as daily and cumulative tobacco consumption., Results: In observational multivariable-adjusted analyses, a 10 g/day higher daily tobacco consumption was associated with a 0.28 µmol/L (95% confidence interval = 0.20 to 0.35) lower concentration of plasma bilirubin in current smokers, and a 10 pack-year higher cumulative tobacco consumption was associated with a 0.19 µmol/L (0.17 to 0.21) lower concentration of plasma bilirubin in former and current smokers. Using the CHRNA3 rs1051730 genotype as a proxy for daily and cumulative tobacco consumption, the difference in plasma bilirubin per T-allele was -0.12 µmol/L (-0.23 to -0.002) in current smokers and -0.09 µmol/L (-0.15 to -0.01) in current and former smokers combined. Furthermore, observationally bilirubin concentrations increased with time from smoking cessation in former smokers., Conclusion: Higher daily and cumulative tobacco consumption were associated with lower concentrations of plasma bilirubin in observational and genetic analyses, suggesting that the association is causal., Implications: Our results are compatible with two possible interpretations of previous observational studies, either that bilirubin is a mediator of smoking-induced respiratory disease or that the association between plasma bilirubin and respiratory disease stems from residual confounding because of smoking. Future studies should examine whether bilirubin is a causal risk factor for respiratory disease, or merely a marker of smoking status., (© The Author(s) 2018. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2020
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3. AHRR (cg05575921) hypomethylation marks smoking behaviour, morbidity and mortality.

Author

Bojesen SE, Timpson N, Relton C, Davey Smith G, and Nordestgaard BG

Subjects
Aged, Biomarkers, Cause of Death, Denmark epidemiology, Disease Progression, Female, Genotype, Humans, Lung Neoplasms diagnostic imaging, Lung Neoplasms mortality, Male, Middle Aged, Receptors, Nicotinic genetics, Risk Assessment, Risk-Taking, Smoking adverse effects, Basic Helix-Loop-Helix Transcription Factors genetics, DNA Methylation, Lung Neoplasms epidemiology, Pulmonary Disease, Chronic Obstructive etiology, Repressor Proteins genetics, Smoking genetics, Smoking mortality
Abstract

Rationale and Objectives: Self-reported smoking underestimates disease risk. Smoking affects DNA methylation, in particular the cg05575921 site in the aryl hydrocarbon receptor repressor (AHRR ) gene. We tested the hypothesis that AHRR cg05575921 hypomethylation is associated with risk of smoking-related morbidity and mortality., Methods: From the Copenhagen City Heart Study representing the Danish general population, we studied 9234 individuals. Using bisulphite treated leucocyte DNA, AHRR (cg05575921) methylation was measured. Rs1051730 ( CHRN3A ) genotype was used to evaluate smoking heaviness. Participants were followed for up to 22 years for exacerbations of COPD, event of lung cancer and all-cause mortality. Six-year lung cancer risk was calculated according to the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO M2012 )., Measurements and Main Results: AHRR (cg05575921) hypomethylation was associated with former and current smoking status, high daily and cumulative smoking, short time since smoking cessation (all p values <7×10 -31 ), and the smoking-related CHRN3A genotype (-0.48% per T-allele, p=0.002). The multifactorially adjusted HRs for the lowest versus highest methylation quintiles were 4.58 (95% CI 2.83 to 7.42) for COPD exacerbations, 4.87 (2.31 to 10.3) for lung cancer and 1.67 (1.48 to 1.88) for all-cause mortality. Finally, among 2576 high-risk smokers eligible for lung cancer screening by CT, observed cumulative incidences of lung cancer after 6 years for individuals in the lowest and highest methylation quintiles were 3.7% and 0.0% (p=2×10 -7 ), whereas predicted PLCO M2012 6-year risks were similar (4.3% and 4.4%, p=0.77)., Conclusion: AHRR (cg05575921) hypomethylation, a marker of smoking behaviour, provides potentially clinical relevant predictions of future smoking-related morbidity and mortality., Competing Interests: Competing interests: None declared., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)

Published
2017
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4. Does High Tobacco Consumption Cause Psychological Distress? A Mendelian Randomization Study.

Author

Skov-Ettrup LS, Nordestgaard BG, Petersen CB, and Tolstrup JS

Subjects
Adult, Aged, Aged, 80 and over, Cross-Sectional Studies, Denmark epidemiology, Diagnosis, Dual (Psychiatry), Female, Genotype, Heterozygote, Humans, Male, Mendelian Randomization Analysis methods, Middle Aged, Odds Ratio, Receptors, Nicotinic genetics, Smoking epidemiology, Smoking genetics, Smoking Cessation, Stress, Psychological epidemiology, Stress, Psychological genetics, Stress, Psychological psychology, Tobacco Use Disorder epidemiology, Tobacco Use Disorder genetics, Young Adult, Smoking psychology, Stress, Psychological etiology, Tobacco Use Disorder psychology
Abstract

Background: Increasing evidence suggests that smoking influences mental health negatively. This study investigated whether high tobacco consumption is causally related to psychological distress in a Mendelian randomization design, using a variant in the nicotine acetylcholine receptor gene CHRNA3-known to influence individual tobacco consumption-as instrumental variable for tobacco consumption., Methods: Data from 90 108 participants in the Copenhagen General Population Study was used. Exposures included self-reported cigarettes/day and pack years and the CHRNA3 rs1051730 genotype as instrumental variable for tobacco consumption. Three dimensions of psychological distress were studied: Stress, fatigue, and hopelessness. Analyses with the CHRNA3 genotype were stratified by smoking status., Results: Self-reported amount of smoking was associated with all three dimensions of psychological distress. For instance among participants smoking 30 cigarettes/day or more, the odds ratio (OR) for stress was 1.67 (95% confidence interval [CI] 1.47-1.89) compared to never-smokers. Corresponding ORs for fatigue and hopelessness were 2.18 (95% CI 1.92-2.47) and 3.08 (95% CI 2.62-3.62). Among current smokers, homozygotes and heterozygotes for the CHRNA3 genotype had higher tobacco consumption than noncarriers. Nevertheless, the CHRNA3 genotype was not associated with psychological distress neither in current nor in former or never-smokers. For instance among current smokers, the OR for stress was 1.02 (95% CI 0.91-1.15) among homozygotes compared to noncarriers of the CHRNA3 genotype., Conclusions: Though a strong association between tobacco consumption and psychological distress was found, there was no clear evidence that high tobacco consumption was causally related to psychological distress., Implications: Smoking is associated with several mental health outcomes and smoking cessation is associated with improved mental health. Causality in the association between smoking and mental health is difficult to establish using observational data. Using a genotype known to influence tobacco consumption as instrumental variable for amount of smoking, we found no clear evidence of a direct causal path between high tobacco consumption and psychological distress. Whatever causes the strong association between tobacco consumption and psychological distress, the co-occurrence is important to consider both in interventions for smoking prevention and cessation., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Published
2017
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5. Characteristics and Prognosis of Never-Smokers and Smokers with Asthma in the Copenhagen General Population Study. A Prospective Cohort Study.

Author

Çolak Y, Afzal S, Nordestgaard BG, and Lange P

Subjects
Adult, Aged, Aged, 80 and over, Asthma blood, Cohort Studies, Denmark epidemiology, Female, Humans, Hypersensitivity blood, Inflammation blood, Lung physiopathology, Male, Middle Aged, Prognosis, Prospective Studies, Respiratory Function Tests, Risk Factors, Smoking blood, Young Adult, Asthma complications, Asthma physiopathology, Smoking adverse effects, Smoking physiopathology
Abstract

Rationale: Asthma is associated with complications, cardiovascular comorbidities, and higher mortality in some individuals., Objectives: To test the hypothesis that, among individuals with asthma, never-smokers have different characteristics and a better prognosis than smokers., Methods: We recruited 94,079 individuals aged 20-100 years from the Copenhagen General Population Study, a prospective cohort study. Among these individuals, 5,691 (6%) had self-reported asthma (2,304 never-smokers, 2,467 former smokers, and 920 current smokers). We examined respiratory symptoms, lung function, and levels of inflammatory and allergic biomarkers in systemic circulation. Furthermore, we assessed prospectively the risk of asthma or chronic obstructive pulmonary disease (COPD) exacerbations, pneumonias, lung cancer, ischemic heart disease, ischemic stroke, and all-cause mortality during 4.5 years of follow-up., Measurements and Main Results: Compared with never-smokers without asthma, individuals with asthma had more respiratory symptoms and airflow limitation and higher levels of inflammatory and allergic biomarkers, which were most pronounced in smokers. Among individuals with asthma compared with never-smokers without asthma, multivariable adjusted hazard ratios for asthma exacerbations were 11 (95% confidence interval: 5.8-22) in never-smokers, 13 (6.2-29) in former smokers, and 18 (8.2-39) in current smokers. The corresponding values for other endpoints were, respectively, 8.9 (2.1-38), 23 (8.8-58), and 36 (12-105) for COPD exacerbations; 1.5 (0.9-2.2), 1.6 (1.0-2.4), and 2.4 (1.6-3.7) for pneumonias; 0.6 (0.1-5.1), 4.0 (1.3-12), and 13 (4.3-41) for lung cancer; 1.2 (0.9-1.6), 1.5 (1.2-2.0), and 2.0 (1.4-2.9) for ischemic heart disease; 1.4 (0.9-2.1), 1.2 (0.8-1.9), and 3.0 (1.7-5.3) for ischemic stroke; and 0.9 (0.6-1.3), 1.5 (1.1-2.0), and 2.7 (1.9-3.7) for all-cause mortality., Conclusions: Never-smokers with asthma had an increased risk of asthma and COPD exacerbations, and possibly pneumonias. Importantly, the risks for lung cancer, cardiovascular comorbidities, and death were restricted to smokers with asthma. Thus, tobacco smoking was the main explanation for poor prognosis in asthma.

Published
2015
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6. Myocardial infarction among Danish HIV-infected individuals: population-attributable fractions associated with smoking.

Author

Rasmussen LD, Helleberg M, May MT, Afzal S, Kronborg G, Larsen CS, Pedersen C, Gerstoft J, Nordestgaard BG, and Obel N

Subjects
Adult, Cohort Studies, Denmark epidemiology, Female, Humans, Incidence, Male, Middle Aged, Myocardial Infarction prevention & control, Prospective Studies, Registries, Risk Assessment, Risk Factors, Smoking Cessation, Time Factors, HIV Infections complications, Myocardial Infarction epidemiology, Myocardial Infarction etiology, Smoking adverse effects
Abstract

Background: Human immunodeficiency virus-infected individuals have increased risk of myocardial infarction (MI); however, the contribution from smoking and potentiating effects of HIV are controversial., Methods: From the Danish HIV Cohort Study and the Copenhagen General Population Study, we identified 3251 HIV-infected individuals and 13 004 population controls matched on age and gender. Data on MI were obtained from the National Hospital Registry and the National Registry of Causes of Death. We calculated adjusted incidence rate ratios (aIRR) for risk of MI and population-attributable fractions (PAF) of MI associated with smoking., Results: In never smokers, HIV was not associated with an increased risk of MI (aIRR, 1.01; 95% confidence interval [CI], .41-2.54). In previous and current smokers, HIV was associated with a substantially increased risk of MI (aIRR, 1.78; 95% CI, .75-4.24 and aIRR, 2.83; 95% CI, 1.71-4.70). The PAF associated with ever smoking (previous or current) was 72% (95% CI, 55%-82%) for HIV-infected individuals and 24% (95% CI, 3%-40%) for population controls. If all current smokers stopped smoking, 42% (95% CI, 21%-57%) and 21% (95% CI, 12%-28%) of all MIs could potentially be avoided in these 2 populations., Conclusions: Smoking is associated with a higher risk of MI in the HIV-infected population than in the general population. Approximately 3 of 4 MIs among HIV-infected individuals are associated with ever smoking compared with only 1 of 4 MIs among population controls. Smoking cessation could potentially prevent more than 40% of MIs among HIV-infected individuals, and smoking cessation should be a primary focus in modern HIV care., (© The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Published
2015
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7. High tobacco consumption lowers body weight: a Mendelian randomization study of the Copenhagen General Population Study.

Author

Winsløw UC, Rode L, and Nordestgaard BG

Subjects
Adult, Aged, Aged, 80 and over, Body Mass Index, Denmark epidemiology, Female, Heterozygote, Homozygote, Humans, Male, Mendelian Randomization Analysis, Middle Aged, Phenotype, Receptors, Nicotinic genetics, Smoking epidemiology, Tobacco Use epidemiology, Waist-Hip Ratio, Weight Gain genetics, Weight Gain physiology, Weight Loss physiology, Young Adult, Smoking genetics, Weight Loss genetics
Abstract

Background: Conflicting evidence has been found regarding the association between high tobacco consumption and body weight among smokers. We tested the hypothesis that high tobacco consumption is causally associated with low body weight., Methods: We conducted a Mendelian randomization study with a genetic variant in CHRNA3 (rs1051730) as proxy for high tobacco consumption. The cohort consisted of 80,342 participants from the Copenhagen General Population Study, with details on body weight, smoking habits and CHRNA3 genotype, including 15,220 current smokers., Results: In observational analyses, high tobacco consumption was associated with high body weight, body mass index, waist circumference, hip circumference and waist-hip ratio. In multivariable adjusted models a 1-cigarette/day higher tobacco consumption was associated with 0.05 kg (95% confidence interval 0.02; 0.08) higher body weight, 0.02 kg/m(2) (0.01; 0.02) higher body mass index, 0.10 cm (0.07; 0.12) higher waist circumference and 0.02 cm (0.001; 0.03) higher hip circumference. In contrast, the per-allele increase inCHRNA3 rs1051730 associated with high tobacco consumption was associated with 0.59 kg (0.96; 0.22) lower body weight, 0.23 kg/m(2) (0.33; 0.13) lower body mass index, 0.32 cm (0.74; 0.003) lower waist circumference and 0.45 cm (0.66; 0.24) lower hip circumference. No association was found between tobacco consumption and waist-hip ratio in genetic analysis, or among CHRNA3 genotype and any of the outcome variables in former or never smokers., Conclusions: High tobacco consumption causes lower body weight among current smokers. However, smoking does not seem to affect body shape or fat distribution causally. The lack of association between CHRNA3 genotype and body weight among former smokers and never smokers favours smoking as the causal factor for the observed associations., (© The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Published
2015
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8. A systematic review and meta-analysis of 130,000 individuals shows smoking does not modify the association of APOE genotype on risk of coronary heart disease.

Author

Holmes MV, Frikke-Schmidt R, Melis D, Luben R, Asselbergs FW, Boer JM, Cooper J, Palmen J, Horvat P, Engmann J, Li KW, Onland-Moret NC, Hofker MH, Kumari M, Keating BJ, Hubacek JA, Adamkova V, Kubinova R, Bobak M, Khaw KT, Nordestgaard BG, Wareham N, Humphries SE, Langenberg C, Tybjaerg-Hansen A, and Talmud PJ

Subjects
Adult, Aged, Alleles, Cohort Studies, Female, Gene-Environment Interaction, Heterozygote, Humans, Male, Middle Aged, Risk Factors, Apolipoprotein E4 genetics, Coronary Disease genetics, Genotype, Smoking adverse effects
Abstract

Background: Conflicting evidence exists on whether smoking acts as an effect modifier of the association between APOE genotype and risk of coronary heart disease (CHD)., Methods and Results: We searched PubMed and EMBASE to June 11, 2013 for published studies reporting APOE genotype, smoking status and CHD events and added unpublished data from population cohorts. We tested for presence of effect modification by smoking status in the relationship between APOE genotype and risk of CHD using likelihood ratio test. In total 13 studies (including unpublished data from eight cohorts) with 10,134 CHD events in 130,004 individuals of European descent were identified. The odds ratio (OR) for CHD risk from APOE genotype (ε4 carriers versus non-carriers) was 1.06 (95% confidence interval (CI): 1.01, 1.12) and for smoking (present vs. past/never smokers) was OR 2.05 (95%CI: 1.95, 2.14). When the association between APOE genotype and CHD was stratified by smoking status, compared to non-ε4 carriers, ε4 carriers had an OR of 1.11 (95%CI: 1.02, 1.21) in 28,789 present smokers and an OR of 1.04 (95%CI 0.98, 1.10) in 101,215 previous/never smokers, with no evidence of effect modification (P-value for heterogeneity = 0.19). Analysis of pack years in individual participant data of >60,000 with adjustment for cardiovascular traits also failed to identify evidence of effect modification., Conclusions: In the largest analysis to date, we identified no evidence for effect modification by smoking status in the association between APOE genotype and risk of CHD., (Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.)

Published
2014
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9. High tobacco consumption is causally associated with increased all-cause mortality in a general population sample of 55,568 individuals, but not with short telomeres: a Mendelian randomization study.

Author

Rode L, Bojesen SE, Weischer M, and Nordestgaard BG

Subjects
Denmark epidemiology, Female, Follow-Up Studies, Genotype, Humans, Incidence, Male, Multivariate Analysis, Polymorphism, Genetic, Risk Factors, Smoking mortality, Tobacco Use Disorder mortality, Mendelian Randomization Analysis, Mortality, Smoking genetics, Telomere genetics, Tobacco Use Disorder genetics
Abstract

Background: High cumulative tobacco consumption is associated with short telomeres and with increased all-cause mortality. We tested the hypothesis that high tobacco consumption is causally associated with short telomeres and with increased all-cause mortality., Methods: We studied 55,568 individuals including 32,823 ever smokers from the Danish general population, of whom 3430 died during 10 years of follow-up. All had telomere length measured, detailed information on smoking history, and CHRNA3 rs1051730 genotype, which is associated with tobacco consumption, determined. In a Mendelian randomization study, we conducted observational, genetic, and mediation analyses., Results: First, tobacco consumption was 21.1 pack-years in non-carriers, 22.8 in heterozygotes and 24.8 in homozygotes (P-trend<0.001). Second, the observational multivariable adjusted hazard ratio for all-cause mortality was 1.12 [95% confidence interval (CI): 1.09, 1.15] per doubling in tobacco consumption. In Mendelian randomization analysis, the hazard ratio was 1.08 (1.02, 1.14) per minor CHRNA3 allele in ever smokers. Third, in observational analysis telomeres shortened with -13 base pairs (-18, -8) per doubling in tobacco consumption. In Mendelian randomization analysis, the estimate was +3 base pairs (-10, +15) per minor CHRNA3 allele. Finally, individuals with the shortest vs longest telomeres had a multivariable adjusted hazard ratio of 1.30 (1.13, 1.50) for all-cause mortality; however, in mediation analysis short telomeres explained only +0.4% (-3.5%, +4.3%) of the association between high tobacco consumption and increased all-cause mortality., Conclusions: High tobacco consumption is causally associated with increased all-cause mortality. High cumulative tobacco consumption is associated with short telomeres observationally, but there is no clear genetic association., (© The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.)

Published
2014
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10. Risk of cancer among HIV-infected individuals compared to the background population: impact of smoking and HIV.

Author

Helleberg M, Gerstoft J, Afzal S, Kronborg G, Larsen CS, Pedersen C, Bojesen SE, Nordestgaard BG, and Obel N

Subjects
Adult, CD4 Lymphocyte Count, Cohort Studies, Denmark, Female, Humans, Incidence, Male, Middle Aged, Prospective Studies, Risk Assessment, Risk Factors, HIV Infections complications, Neoplasms epidemiology, Smoking adverse effects
Abstract

Background: The relative impact of immune deficiency and lifestyle-related factors on risk of cancer in the HIV-infected population is controversial. We aimed to estimate the population-attributable fractions (PAFs) associated with smoking, being HIV-infected and with immune deficiency., Methods: In a Danish, nationwide, population-based cohort study (1995-2011), incidences of cancer were compared between an HIV-infected cohort and a population-based matched cohort in analyses stratified on cancer category, smoking status and for HIV patients: low CD4 cell count., Results: We included 3503 HIV patients [baseline CD4+ 450 cells/μl (inter-quartile range 310-630)] and 12,979 population controls. Smoking-related and virological cancers accounted for 23 and 43% of cancers in the HIV-infected population. The risk of these cancers were higher among HIV patients compared to controls [incidence rate ratio (IRR) 2.8, 95% confidence interval (CI) 1.6-4.9; and IRR 11.5, 95% CI 6.5-20.5], whereas the risk of other cancers did not differ (IRR 1.0, 95% CI 0.7-1.3). Non-smoking HIV patients did not have increased risk of non-virological cancers compared to non-smoking controls (IRR 1.2, 95% CI 0.7-2.1). The PAFs of cancer associated with smoking and with being HIV-infected were 27 and 49%, respectively. For cancers not strongly related to smoking or viral infections, the PAFs associated with being HIV-infected and with immune deficiency were 0%., Conclusion: The risk of cancer is increased in HIV patients compared to the background population. In absence of smoking, the increase in risk is confined to cancers related to viral infections, whereas the risk of other cancers is not elevated and does not seem to be associated with immune deficiency.

Published
2014
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11. CHRNA3 and CYP3A5*3 genotype, lung function and chronic obstructive pulmonary disease in the general population.

Author

Kaur-Knudsen D, Bojesen SE, and Nordestgaard BG

Subjects
Adult, Aged, Denmark, Forced Expiratory Volume, Genetic Variation, Genome-Wide Association Study, Humans, Middle Aged, Polymorphism, Single Nucleotide, Cytochrome P-450 CYP3A genetics, Lung physiology, Pulmonary Disease, Chronic Obstructive genetics, Receptors, Nicotinic genetics, Smoking adverse effects
Abstract

Objective: Genetic variations are most likely an additional risk factor besides tobacco smoking per se for the risk of chronic obstructive pulmonary disease (COPD). In this study, we compared genetic variants influencing the effect of smoking on COPD, that is, the effect of the well-known splicing defect polymorphism, CYP3A5*3 (rs776746), identified before genome-wide association studies, with the genome-wide association studies identified CHRNA3 (rs1051730) polymorphism on the risk of decreased lung function and COPD., Materials and Methods: In all, 10 605 participants from the general population were genotyped. Information on spirometry, hospital admissions and smoking behaviour was recorded. Endpoints were lung function and COPD., Results: For CHRNA3, the percentage of forced expiratory volume in 1 s (FEV1%) predicted was 89.3, 90.6 and 92.4% in homozygous, heterozygous and noncarrier ever-smokers (P-trend<0.001). The corresponding values for forced vital capacity percentage (FVC%) predicted were 94.5, 95.2 and 96.7% (P-trend<0.001), and for FEV1/FVC ratio, the values were 0.753, 0.760 and 0.764 (P-trend=0.008). The odds ratio for COPD in homozygous versus noncarrier ever-smokers was 1.5 [95% confidence interval (CI) 1.3-1.9] for COPD hospitalization, 1.3 (95% CI 1.1-1.6) for COPD defined as FEV1/FVC less than lower limit of normal, 1.3 (95% CI 1.0-1.5) for the Global Initiative for Chronic Obstructive Lung Disease category 1-4 (GOLD 1-4), 1.2 (95% CI 1.0-1.5) for GOLD 2-4 and 1.5 (95% CI 1.1-2.2) for GOLD 3-4. This association could not be found in never-smokers. No association was found for CYP3A5*3., Conclusion: The CHRNA3 genotype is associated with decreased lung function and risk of COPD among ever-smokers, whereas this was not the case for CYP3A5*3.

Published
2014
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12. Telomere shortening unrelated to smoking, body weight, physical activity, and alcohol intake: 4,576 general population individuals with repeat measurements 10 years apart.

Author

Weischer M, Bojesen SE, and Nordestgaard BG

Subjects
Adult, Body Mass Index, Female, Genetics, Population, Humans, Leukocytes cytology, Male, Middle Aged, Risk Factors, Telomere genetics, Alcohol Drinking genetics, Body Weight genetics, Motor Activity genetics, Smoking genetics, Telomere Shortening genetics
Abstract

Cross-sectional studies have associated short telomere length with smoking, body weight, physical activity, and possibly alcohol intake; however, whether these associations are due to confounding is unknown. We tested these hypotheses in 4,576 individuals from the general population cross-sectionally, and with repeat measurement of relative telomere length 10 years apart. We also tested whether change in telomere length is associated with mortality and morbidity in the general population. Relative telomere length was measured with quantitative polymerase chain reaction. Cross-sectionally at the first examination, short telomere length was associated with increased age (P for trend across quartiles = 3 × 10(-77)), current smoking (P = 8 × 10(-3)), increased body mass index (P = 7 × 10(-14)), physical inactivity (P = 4 × 10(-17)), but not with increased alcohol intake (P = 0.10). At the second examination 10 years later, 56% of participants had lost and 44% gained telomere length with a mean loss of 193 basepairs. Change in leukocyte telomere length during 10 years was associated inversely with baseline telomere length (P<1 × 10(-300)) and age at baseline (P = 1 × 10(-27)), but not with baseline or 10-year inter-observational tobacco consumption, body weight, physical activity, or alcohol intake. Prospectively during a further 10 years follow-up after the second examination, quartiles of telomere length change did not associate with risk of all-cause mortality, cancer, chronic obstructive pulmonary disease, diabetes mellitus, ischemic cerebrovascular disease, or ischemic heart disease. In conclusion, smoking, increased body weight, and physical inactivity were associated with short telomere length cross-sectionally, but not with telomere length change during 10 years observation, and alcohol intake was associated with neither. Also, change in telomere length did not associate prospectively with mortality or morbidity in the general population.

Published
2014
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13. Tobacco smoking and aortic aneurysm: two population-based studies.

Author

Sode BF, Nordestgaard BG, Grønbæk M, and Dahl M

Subjects
Adult, Aged, Cohort Studies, Denmark epidemiology, Female, Follow-Up Studies, Hospitalization trends, Humans, Male, Middle Aged, Risk Factors, Aortic Aneurysm diagnosis, Aortic Aneurysm epidemiology, Population Surveillance methods, Smoking adverse effects, Smoking epidemiology
Abstract

Background: We determined the predictive power of tobacco smoking on aortic aneurysm as opposed to other risk factors in the general population., Methods: We recorded tobacco smoking and other risk factors at baseline, and assessed hospitalization and death from aortic aneurysm in 15,072 individuals from the Copenhagen City Heart Study followed for up to 34 years and in 56,211 individuals from the Copenhagen General Population Study followed for up to 7 years., Results: During follow-up, 335 and 169 individuals developed aortic aneurysm outcomes in the Copenhagen City Heart Study and Copenhagen General Population Study, respectively. According to the magnitude of the hazard ratios, tobacco consumption was the most important risk factor for hospitalization and death from aortic aneurysm, followed by male sex and hypertension in both cohorts. The population attributable risk of aortic aneurysm outcomes due to tobacco consumption was 64% and 47% in the Copenhagen City Heart Study and Copenhagen General Population Study, respectively, and ranked highest among population attributable risks of aortic aneurysm in both cohorts. The absolute 10-year risk for hospitalization or death from aortic aneurysm in males and females consuming above 20 g tobacco daily was 3.5% and 1.3%, among those >60 years with plasma cholesterol >5 mmol/L and a systolic blood pressure >140 mmHg., Conclusions: Tobacco smoking is the most important predictor of future aortic aneurysm outcomes in the general population, with population attributable risks at or above 47%., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

Published
2013
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14. Low plasma 25-hydroxyvitamin D and risk of tobacco-related cancer.

Author

Afzal S, Bojesen SE, and Nordestgaard BG

Subjects
Aged, Denmark epidemiology, Female, Follow-Up Studies, Humans, Male, Middle Aged, Neoplasms epidemiology, Proportional Hazards Models, Prospective Studies, Risk, Vitamin D blood, Neoplasms blood, Neoplasms etiology, Smoking adverse effects, Vitamin D analogs & derivatives
Abstract

Background: Tobacco smoke chemicals may influence vitamin D metabolism and function, and conversely vitamin D may modify the carcinogenicity of tobacco smoke chemicals. We tested the hypothesis that lower plasma 25-hydroxyvitamin D [25(OH)D] is associated with a higher risk of tobacco-related cancer in the general population., Methods: A prospective population-based cohort of 9791 individuals from the Copenhagen City Heart Study who were free of cancer at baseline was followed from 1981-1983 until December 2008 with 100% complete follow-up., Results: During up to 28 years of follow-up, 1081 participants developed a tobacco-related cancer and 1506 developed other cancers. Decreasing 25(OH)D concentrations, subdivided by clinical categories or by seasonally adjusted percentile categories, were associated with increasing cumulative incidence of tobacco-related cancer (log-rank trend P = 2 × 10(-6) and P = 5 × 10(-9)). Multivariable adjusted hazard ratios of tobacco-related cancer were 1.75 (95% CI, 1.33-2.30) for 25(OH)D <5 vs ≥20 ng/mL, and 2.07 (1.63-2.62) for ≤5th vs >66th percentile. Also, multivariable adjusted hazard ratios for a 50% reduction in 25(OH)D were 1.20 (1.13-1.28) for any tobacco-related cancer, 1.19 (95% CI, 1.09-1.31) for lung cancer, 1.44 (1.19-1.73) for head and neck cancer, 1.28 (1.06-1.54) for bladder cancer, 1.34 (1.04-1.73) for kidney cancer, and 0.95 (0.89-1.01) for other cancers., Conclusions: Lower plasma 25(OH)D was associated with higher risk of tobacco-related cancers, but not with risk of other cancers., (© 2013 American Association for Clinical Chemistry.)

Published
2013
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15. Mortality attributable to smoking among HIV-1-infected individuals: a nationwide, population-based cohort study.

Author

Helleberg M, Afzal S, Kronborg G, Larsen CS, Pedersen G, Pedersen C, Gerstoft J, Nordestgaard BG, and Obel N

Subjects
Adult, Cause of Death, Cohort Studies, Denmark epidemiology, Female, HIV-1 pathogenicity, Humans, Kaplan-Meier Estimate, Life Expectancy, Male, Middle Aged, Risk Factors, HIV Infections mortality, Smoking mortality
Abstract

Background: We assessed mortality attributable to smoking among patients with human immunodeficiency virus (HIV)., Methods: We estimated mortality rates (MRs), mortality rate ratios (MRRs), life expectancies, life-years lost, and population-attributable risk of death associated with smoking and with HIV among current and nonsmoking individuals from a population-based, nationwide HIV cohort and a cohort of matched HIV-negative individuals., Results: A total of 2921 HIV patients and 10 642 controls were followed for 14 281 and 45 122 person-years, respectively. All-cause and non-AIDS-related mortality was substantially increased among smoking compared to nonsmoking HIV patients (MRR, 4.4 [95% confidence interval {CI}, 3.0-6.7] and 5.3 [95% CI, 3.2-8.8], respectively). Excess MR per 1000 person-years among current vs nonsmokers was 17.6 (95% CI, 13.3-21.9) for HIV patients and 4.8 (95% CI, 3.2-6.4) for controls. A 35-year-old HIV patient had a median life expectancy of 62.6 years (95% CI, 59.9-64.6) for smokers and 78.4 years (95% CI, 70.8-84.0) for nonsmokers; the numbers of life-years lost in association with smoking and HIV were 12.3 (95% CI, 8.1-16.4) and 5.1 (95% CI, 1.6-8.5). The population-attributable risk of death associated with smoking was 61.5% among HIV patients and 34.2% among controls., Conclusions: In a setting where HIV care is well organized and antiretroviral therapy is free of charge, HIV-infected smokers lose more life-years to smoking than to HIV. The excess mortality of smokers is tripled and the population-attributable risk of death associated with smoking is doubled among HIV patients compared to the background population.

Published
2013
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16. Genetically lowered microsomal epoxide hydrolase activity and tobacco-related cancer in 47,000 individuals.

Author

Lee J, Dahl M, and Nordestgaard BG

Subjects
Aged, Denmark epidemiology, Epoxide Hydrolases metabolism, Female, Genetic Predisposition to Disease, Genotype, Humans, Male, Middle Aged, Neoplasms enzymology, Neoplasms epidemiology, Neoplasms genetics, Smoking adverse effects, Smoking epidemiology, Smoking metabolism, Surveys and Questionnaires, Cocarcinogenesis, Epoxide Hydrolases genetics, Neoplasms etiology, Smoking genetics
Abstract

Background: Two functional polymorphisms of the microsomal epoxide hydrolase (mEH) gene (EPHX1), Tyr113His (rs1051740) and His139Arg (rs2234922), have variably been found to influence susceptibility to various cancer forms. We tested whether genetically lowered mEH activity affects risk of developing cancer in the general population., Methods: We genotyped 47,089 individuals from the Danish general population for the Tyr113His and His139Arg polymorphisms in the EPHX1 gene and divided them into groups with predicted fast, intermediate, and slow mEH activity. Using Cox proportional hazards models, we calculated HRs for 26 individual cancer diagnoses and for groups of any cancer, tobacco-related cancers, estrogen-related female cancers, and other cancers., Results: Of the 47,089 individuals, 7,590 experienced a cancer event, and of these, 1,466 were tobacco-related. After multifactorial adjustment, the HRs (95% CI) for tobacco-related cancer were 1.1 (0.8-1.5) and 1.5 (1.1-2.0) in individuals with intermediate and slow mEH activity versus individuals with the fast phenotype (P(trend) = 0.003). The corresponding HRs among ever-smokers were 1.1 (0.8-1.5) and 1.5 (1.1-2.0; P(trend) = 0.003), whereas HRs among never-smokers did not differ from 1.0., Conclusions: Our results indicate that genetically lowered mEH activity is associated with increased risk of developing tobacco-related cancer among smokers in the general population; however, additional studies are needed to confirm our findings., Impact: To our knowledge, this is the largest study to investigate the association of mEH phenotype and genotype with tobacco-related cancers combined in the general population., (©2011 AACR.)

Published
2011
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17. Nicotinic acetylcholine receptor polymorphism, smoking behavior, and tobacco-related cancer and lung and cardiovascular diseases: a cohort study.

Author

Kaur-Knudsen D, Bojesen SE, Tybjærg-Hansen A, and Nordestgaard BG

Subjects
Aged, Brain Ischemia etiology, Brain Ischemia genetics, Cardiovascular Diseases epidemiology, Cardiovascular Diseases genetics, Chi-Square Distribution, Denmark epidemiology, Female, Genetic Predisposition to Disease, Humans, Incidence, Lung Neoplasms epidemiology, Lung Neoplasms genetics, Male, Middle Aged, Myocardial Ischemia etiology, Myocardial Ischemia genetics, Nerve Tissue Proteins genetics, Proportional Hazards Models, Prospective Studies, Pulmonary Disease, Chronic Obstructive epidemiology, Pulmonary Disease, Chronic Obstructive genetics, Risk Assessment, Risk Factors, Stroke etiology, Stroke genetics, Time Factors, Urinary Bladder Neoplasms epidemiology, Urinary Bladder Neoplasms genetics, Cardiovascular Diseases etiology, Lung Neoplasms etiology, Polymorphism, Single Nucleotide, Pulmonary Disease, Chronic Obstructive etiology, Receptors, Nicotinic genetics, Smoking adverse effects, Urinary Bladder Neoplasms etiology
Abstract

Purpose: We examined the associations between the nicotinic acetylcholine receptor polymorphism (rs1051730) on chromosome 15q25 marking the gene cluster CHRNA3-CHRNB4-CHRNA5, smoking behavior, and tobacco-related cancer and lung and cardiovascular diseases in the general population., Methods: Ten thousand three hundred thirty participants from the Copenhagen City Heart Study were genotyped and observed prospectively with up to 18 years of 100% complete follow-up. Smoking behavior was measured at baseline. End points were lung cancer, bladder cancer, chronic obstructive pulmonary disease, ischemic heart disease, and ischemic stroke., Results: Multifactorially adjusted and genotype-adjusted subhazard ratios for a cumulative tobacco consumption above 40 pack-years versus 0 pack-years were 32.5 (95% CI, 12.0 to 87.7) for lung cancer, 2.2 (95% CI, 1.1 to 4.5) for bladder cancer, 9.4 (95% CI, 6.9 to 12.7) for chronic obstructive pulmonary disease, 1.5 (95% CI, 1.3 to 1.8) for ischemic heart disease, and 1.1 (95% CI, 0.8 to 1.4) for ischemic stroke. Among smoking noncarriers and homozygotes, daily tobacco consumption was 16 and 18 g/d (P < .001), cumulative tobacco consumption was 28 and 31 pack-years (P = .003), and smoking inhalation was 71.9% and 78.1% (P < .001), respectively. Multifactorially adjusted and smoking behavior-adjusted subhazard ratios for homozygotes versus noncarriers were 1.6 (95% CI, 1.1 to 2.2) for lung cancer, 1.7 (95% CI, 1.0 to 3.0) for bladder cancer, 1.3 (95% CI, 1.1 to 1.6) for chronic obstructive pulmonary disease, 0.9 (95% CI, 0.7 to 1.0) for ischemic heart disease, and 1.1 (95% CI, 0.8 to 1.4) for ischemic stroke., Conclusion: Although smoking is associated with major tobacco-related diseases in the general population, the nicotinic acetylcholine receptor polymorphism is associated with additional increased risk of lung cancer, bladder cancer, and chronic obstructive pulmonary disease after adjustment for smoking.

Published
2011
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18. Surfactant protein-B 121ins2 heterozygosity, reduced pulmonary function, and chronic obstructive pulmonary disease in smokers.

Author

Baekvad-Hansen M, Dahl M, Tybjaerg-Hansen A, and Nordestgaard BG

Subjects
Adult, Aged, Aged, 80 and over, Case-Control Studies, Female, Forced Expiratory Volume, Humans, Male, Middle Aged, Young Adult, Heterozygote, INDEL Mutation, Pulmonary Disease, Chronic Obstructive genetics, Pulmonary Surfactant-Associated Protein B genetics, Smoking adverse effects
Abstract

Rationale: Hereditary surfactant protein-B deficiency is an autosomal recessive disorder that causes fatal respiratory distress syndrome in newborns. Seventy percent of the cases of hereditary surfactant protein-B deficiency are caused by homozygosity for the 121ins2 mutation in the surfactant protein-B gene. Individuals heterozygous for this mutation have partial absence of surfactant protein-B and could be at risk of lung disease when exposed to additional risk factors for impaired surfactant function such as tobacco smoking., Objectives: To test whether individuals heterozygous for the 121ins2 mutation have reduced lung function and increased risk for chronic obstructive pulmonary disease (COPD) among smokers., Methods: We genotyped 47,600 individuals from the adult Danish general population and recorded smoking habits, spirometry, and hospital admissions due to COPD. The study and findings are limited to Danes/Europeans., Measurements and Main Results: We identified 85 individuals heterozygous for the 121ins2 mutation. Smoking interacted statistically with the 121ins2 genotype in predicting FEV(1) % predicted (P = 0.006), FVC % predicted (P = 0.02) and FEV(1)/FVC (P = 0.002), indicating that the effect of genotype differ by smoking status. Among smokers, 121ins2 heterozygous individuals had 9% reduced FEV(1)% predicted (P = 0.0008), 6% reduced FVC % predicted (P = 0.01) and 6% reduced FEV(1)/FVC (P = 0.00007), compared with wild-types. Also among smokers, 121ins2 heterozygous individuals had odds ratios of 2.4 (95% CI, 1.2-4.8) for spirometry-defined COPD and 2.2 (1.0-5.1) for hospitalization due to COPD. Among never-smokers, 121ins2 heterozygous individuals did not differ from wild-types in lung function or risk of COPD., Conclusions: Surfactant protein-B 121ins2 heterozygosity is associated with reduced lung function and increased risk for COPD among smokers.

Published
2010
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20. Self-reported and genetically predicted coffee consumption and smoking in dementia: A Mendelian randomization study.

Author

Nordestgaard, Ask T., Nordestgaard, Børge G., Frikke-Schmidt, Ruth, Juul Rasmussen, Ida, and Bojesen, Stig E.

Subjects
*ALZHEIMER'S disease, *DISEASE risk factors, *DEMENTIA, *SMOKING, *COFFEE
Abstract

Studies of self-reported coffee consumption and smoking on risk of dementia have shown results conflicting with two-sample Mendelian randomization studies. We tested the hypotheses that coffee consumption and smoking influence risk of dementia using observational and one-sample Mendelian randomization designs with individual level data. We included 114,551 individuals from two Danish general population cohorts (median age 58 years). First, we tested whether high self-reported coffee consumption/smoking were associated with risk of dementia. Second, whether genetically predicted high coffee consumption/smoking due to variation near CYP1A1/AHR/CHRNA3 genes were associated with risk of dementia. We observed 3,784 dementia events. Moderate self-reported coffee consumption was associated with low risk of all dementia and non-Alzheimer's dementia, with a similar trend for Alzheimer's disease. Genetically predicted high coffee consumption was associated with high risk of all dementia (hazard ratio [95% confidence interval] per +1 cup/day: 1.20 [1.01–1.42]), with a similar trend for non-Alzheimer's dementia (1.23 [0.95–1.53]). High self-reported smoking was associated with high risk of non-Alzheimer's dementia. High genetically predicted smoking was associated with a trend towards high risk of all dementia and Alzheimer's disease (hazard ratios per +1 pack-year: 1.04 [0.96–1.11]) and 1.06 [0.97–1.16]). Moderate self-reported coffee consumption was associated with low risk of all and non-Alzheimer's dementia, while high genetically predicted coffee consumption was associated with a trend towards the opposite. High self-reported smoking was associated with high risk of non-Alzheimer's dementia, with a similar trend for genetically predicted smoking on all dementia and Alzheimer's disease. [Display omitted] • Moderate self-reported coffee consumption was associated with low risk of dementia. • High genetic coffee consumption showed a trend towards high risk of some dementia. • High self-reported smoking was associated with some dementia. • High genetic smoking showed a trend towards high risk of dementia. • High coffee consumption and smoking are unlikely to protect against dementia. [ABSTRACT FROM AUTHOR]

Published
2022
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21. Smoking does not accelerate leukocyte telomere attrition: a meta-analysis of 18 longitudinal cohorts

Author

Bateson, Melissa, Aviv, Abraham, Bendix, Laila, Benetos, Athanase, Ben-Shlomo, Yoav, Bojesen, Stig E., Cooper, Cyrus, Cooper, Rachel, Deary, Ian J., Hägg, Sara, Harris, Sarah E., Kark, Jeremy D., Kronenberg, Florian, Kuh, Diana, Labat, Carlos, Martin-Ruiz, Carmen M., Meyer, Craig, Nordestgaard, Børge G., Penninx, Brenda WJH, Pepper, Gillian V, Révész, Dóra, Said, M Abdullah, Starr, John M, Syddall, Holly, Thompson, William Murray, van der Harst, Pim, Whooley, Mary, von Zglinicki, Thomas, Willeit, Peter, Zhan, Yiqiang, and Nettle, Daniel

Subjects
longitudinal, behavior and behavior mechanisms, telomere length, telomere attrition, smoking, biological age
Abstract

Preprint of mansuscript currently submitted for publication. Abstract: Smoking is associated with shorter leukocyte telomere length (LTL), a biomarker of increased morbidity and reduced longevity. This association is widely interpreted as evidence that smoking accelerates LTL attrition. However, an alternative hypothesis is that individuals with shorter telomeres are more likely to start smoking. Both hypotheses predict a cross-sectional difference in LTL between smokers and non-smokers, but the acceleration hypothesis additionally predicts an association between smoking and LTL attrition. We analysed the association between smoking and LTL dynamics in 18 longitudinal cohorts. The dataset included data from 12,579 adults (4678 current smokers and 7901 non-smokers) over a mean follow-up interval of 8.6 years. Meta-analysis confirmed a cross-sectional difference in LTL between smokers and non-smokers, with mean LTL 78.83 bp shorter in smokers (95% CI: 21.09 to 136.58). However, LTL attrition was a negligible 0.44 bp/year faster in smokers than in non-smokers (95% CI: -1.83 to 0.95), a difference that equates to only 1.23% of the estimated age-related loss of 35.71 bp/year. Assuming a linear effect of smoking, at least 177 years of smoking would be required to generate the observed cross-sectional difference in LTL. It is therefore unlikely that smoking causes the difference in LTL between smokers and non-smokers.

Published
2018
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22. Importance of Early COPD in Young Adults for Development of Clinical COPD: Findings from the Copenhagen General Population Study.

Author

Çolak, Yunus, Afzal, Shoaib, Nordestgaard, Børge G., Lange, Peter, and Vestbo, Jørgen

Subjects
EARLY diagnosis, OBSTRUCTIVE lung disease diagnosis, OBSTRUCTIVE lung disease treatment, OBSTRUCTIVE lung diseases patients, HOSPITAL care, RESEARCH, AGE distribution, RESEARCH methodology, RESPIRATORY measurements, MEDICAL cooperation, EVALUATION research, COMPARATIVE studies, OBSTRUCTIVE lung diseases, FORCED expiratory volume, QUESTIONNAIRES, SPIROMETRY, SMOKING, LONGITUDINAL method
Abstract

Rationale: Individuals who will develop chronic obstructive pulmonary disease (COPD) could be identified at an early age before clinical manifestations appear. Objectives: We investigated risk of clinical COPD 10 years later in young adults from the general population with and without early COPD with a focus on smoking exposure. Methods: We included 14,870 individuals aged 20-100 years from the Copenhagen General Population Study with spirometry 10 years apart. Early COPD was defined as baseline FEV1/FVC less than the lower limit of normal in individuals aged <50 years. Outcomes included clinical COPD at final examination 10 years later (chronic respiratory symptoms with FEV1/FVC <0.70 and FEV1 <80% predicted) and acute exacerbation hospitalizations during follow-up. Measurements and Main Results: Among 5,497 individuals aged <50 years at baseline with FEV1/FVC ≥0.70, 104 (3%) developed clinical COPD 10 years later; 4% of smokers with ≥10 pack-years had early COPD; 3% of smokers with <10 pack-years had early COPD; and 2% of never-smokers had early COPD. Among smokers with ≥10 pack-years, 24% developed clinical COPD in those with early COPD versus 4% in those without early COPD. Corresponding numbers were 10% and 1% in smokers with <10 pack-years and 3% and <1% in never-smokers, respectively. Among individuals with early COPD, odds ratios for clinical COPD 10 years later were 7.77 (95% confidence interval [CI], 4.10-14.7) in smokers with ≥10 pack-years and 8.56 (95% CI, 4.92-14.9) in all smokers, whereas hazard ratios for acute exacerbation hospitalizations were 4.16 (95% CI, 1.66-10.5) and 4.33 (95% CI, 1.89-9.93), respectively. Results were validated in the Copenhagen City Heart Study. Conclusions: Depending on amount of smoking exposure, <24% of young adults in the general population with early COPD develop clinical COPD 10 years later. A smoking exposure threshold for early COPD should be reconsidered, as younger individuals are less represented in those with high smoking exposure. [ABSTRACT FROM AUTHOR]

Published
2021
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23. AHRR (cg05575921) hypomethylation marks smoking behaviour, morbidity and mortality

Author

Bojesen, Stig E, Timpson, Nicholas, Relton, Caroline, Davey Smith, George, and Nordestgaard, Børge G

Subjects
Risk, Male, Tobacco and the lung, Lung Neoplasms, Genotype, Denmark, Receptors, Nicotinic, Risk Assessment, Pulmonary Disease, Chronic Obstructive, Risk-Taking, Cause of Death, Basic Helix-Loop-Helix Transcription Factors, Journal Article, Humans, Aged, Lung Cancer, Smoking, Genomics, DNA Methylation, Middle Aged, Repressor Proteins, Disease Progression, Female, COPD epidemiology, Biomarkers
Abstract

RATIONALE AND OBJECTIVES: Self-reported smoking underestimates disease risk. Smoking affects DNA methylation, in particular the cg05575921 site in the aryl hydrocarbon receptor repressor (AHRR) gene. We tested the hypothesis that AHRR cg05575921 hypomethylation is associated with risk of smoking-related morbidity and mortality.METHODS: From the Copenhagen City Heart Study representing the Danish general population, we studied 9234 individuals. Using bisulphite treated leucocyte DNA, AHRR (cg05575921) methylation was measured. Rs1051730 (CHRN3A) genotype was used to evaluate smoking heaviness. Participants were followed for up to 22 years for exacerbations of COPD, event of lung cancer and all-cause mortality. Six-year lung cancer risk was calculated according to the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCOM2012).MEASUREMENTS AND MAIN RESULTS: AHRR (cg05575921) hypomethylation was associated with former and current smoking status, high daily and cumulative smoking, short time since smoking cessation (all p values CONCLUSION: AHRR (cg05575921) hypomethylation, a marker of smoking behaviour, provides potentially clinical relevant predictions of future smoking-related morbidity and mortality.

Published
2017

24. Prevalence, Characteristics, and Prognosis of Early Chronic Obstructive Pulmonary Disease. The Copenhagen General Population Study.

Author

Çolak, Yunus, Afzal, Shoaib, Nordestgaard, Børge G., Vestbo, Jørgen, and Lange, Peter

Subjects
OBSTRUCTIVE lung diseases, RESPIRATORY obstructions, CHRONIC bronchitis, PULMONARY emphysema, OBSTRUCTIVE lung disease diagnosis, SMOKING, FORCED expiratory volume, VITAL capacity (Respiration), PUBLIC health surveillance, RESEARCH, AGE distribution, RESEARCH methodology, PROGNOSIS, EVALUATION research, MEDICAL cooperation, COMPARATIVE studies, DISEASE prevalence, EARLY diagnosis, LONGITUDINAL method, PROPORTIONAL hazards models
Abstract

Rationale: Identification of younger adults at high risk of developing chronic obstructive pulmonary disease (COPD) could lead to implementation of preventive measures before disease onset and halt progression.Objectives: To investigate the prevalence, characteristics, and prognosis of individuals with early COPD in the general population.Methods: We investigated 105,630 randomly chosen adults from a Danish contemporary population-based cohort. Early COPD was defined as FEV1/FVC less than the lower limit of normal in individuals under 50 years of age with 10 pack-years or greater of tobacco consumption.Measurements and Main Results: Among 8,064 individuals under 50 years of age with 10 pack-years or greater of tobacco consumption, 1,175 (15%) had early COPD, of whom 58% were current smokers. Individuals with early COPD more often had chronic respiratory symptoms, severe lung function impairment, asthma, and a history with bronchitis/pneumonia. During the 14.4-year follow-up, we observed 117 acute hospitalizations with obstructive lung disease, 227 acute hospitalizations with pneumonia, and 185 deaths among the 8,064 younger adults. Compared with individuals without COPD, those with early COPD had multivariable adjusted hazard ratios of 6.42 (95% confidence interval, 3.39-12.2) for acute obstructive lung disease hospitalizations, 2.03 (1.43-2.88) for acute pneumonia hospitalizations, and 1.79 (1.28-2.52) for all-cause mortality.Conclusions: Among individuals under 50 years of age and 10 pack-years or greater of tobacco consumption from the general population, 15% fulfill criteria of early COPD. Individuals with early COPD more often have chronic respiratory symptoms and severe lung function impairment, and an increased risk of acute respiratory hospitalizations and early death. [ABSTRACT FROM AUTHOR]

Published
2020
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25. Relationship between patient presentation and morphology of coronary atherosclerosis by quantitative multidetector computed tomography.

Author

Knegt, Martina C de, Linde, Jesper J, Fuchs, Andreas, Pham, Michael H C, Jensen, Andreas K, Nordestgaard, Børge G, Kelbæk, Henning, Køber, Lars V, Heitmann, Merete, Fornitz, Gitte, Hove, Jens D, Kofoed, Klaus F, and CGPS

Subjects
CORONARY heart disease risk factors, AGE distribution, CHEST pain, CONFIDENCE intervals, CORONARY disease, DIABETES, HYPERTENSION, LONGITUDINAL method, MULTIVARIATE analysis, RADIONUCLIDE imaging, RISK assessment, SEX distribution, SMOKING, OPERATIVE surgery, STATINS (Cardiovascular agents), BODY surface area, FAMILY history (Medicine), ACUTE coronary syndrome, MULTIDETECTOR computed tomography, DISEASE complications
Abstract

Aims Quantitative computed tomography (QCT) allows assessment of morphological features of coronary atherosclerosis. We aimed to test the hypothesis that clinical patient presentation is associated with distinct morphological features of coronary atherosclerosis. Methods and results A total of 1652 participants, representing a spectrum of clinical risk profiles [787 asymptomatic individuals from the general population, 468 patients with acute chest pain without acute coronary syndrome (ACS), and 397 patients with acute chest pain and ACS], underwent multidetector computed tomography. Of these, 274 asymptomatic individuals, 254 patients with acute chest pain without ACS, and 327 patients with acute chest pain and ACS underwent QCT to assess coronary plaque volumes and proportions of dense calcium (DC), fibrous, fibro fatty (FF), and necrotic core (NC) tissue. Furthermore, the presence of vulnerable plaques, defined by plaque volume and tissue composition, was examined. Coronary plaque volume increased significantly with worsening clinical risk profile [geometric mean (95% confidence interval): 148 (129–166) mm3, 257 (224–295) mm3, and 407 (363–457) mm3, respectively, P  <   0.001]. Plaque composition differed significantly across cohorts, P  <   0.0001. The proportion of DC decreased, whereas FF and NC increased with worsening clinical risk profile (mean proportions DC: 33%, 23%, 23%; FF: 50%, 61%, 57%; and NC: 17%, 17%, 20%, respectively). Significant differences in plaque composition persisted after multivariable adjustment for age, gender, body surface area, hypertension, statin use at baseline, diabetes, smoking, family history of ischaemic heart disease, total plaque volume, and tube voltage, P  <   0.01. Conclusion Coronary atherosclerotic plaque volume and composition are strongly associated to clinical presentation. [ABSTRACT FROM AUTHOR]

Published
2019
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26. Smoking, Systemic Inflammation, and Airflow Limitation: A Mendelian Randomization Analysis of 98 085 Individuals From the General Population.

Author

Çolak, Yunus, Afzal, Shoaib, Lange, Peter, and Nordestgaard, Børge G

Subjects
OBSTRUCTIVE lung diseases, SMOKING
Abstract

Introduction: Smoking is associated with systemic and local inflammation in the lungs. Furthermore, in chronic obstructive pulmonary disease, which is often caused by smoking, there is often systemic inflammation that is linked to lung function impairment. However, the causal pathways linking smoking, systemic inflammation, and airflow limitation are still unknown. We tested whether higher tobacco consumption is associated with higher systemic inflammation, observationally and genetically and whether genetically higher systemic inflammation is associated with airflow limitation.Methods: We included 98 085 individuals aged 20-100 years from the Copenhagen General Population Study; 36589 were former smokers and 16172 were current smokers. CHRNA3 rs1051730 genotype was used as a proxy for higher tobacco consumption and the IL6R rs2228145 genotype was used for higher systemic inflammation. Airflow limitation was defined as forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) <70%.Results: Difference in plasma level of C-reactive protein was 4.8% (95% CI = 4.4% to 5.2%) per 10 pack-year increase and 1.6% (95% CI = 0.4% to 2.8%) per T allele. Corresponding differences were 1.2% (95% CI = 1.1% to 1.3%) and 0.5% (95% CI = 0.3% to 0.8%) for fibrinogen, 1.2% (95% CI = 1.2% to 1.3%) and 0.7% (95% CI = 0.5% to 1.0%) for α1-antitrypsin, 2.0% (95% CI = 1.8% to 2.1%) and 0.7% (95% CI = 0.4% to 1.1%) for leukocytes, 1.9% (95% CI = 1.8% to 2.1%) and 0.8% (95% CI = 0.4% to 1.2%) for neutrophils, and 0.8% (95% CI = 0.7% to 1.0%) and 0.4% (95% CI = 0.1% to 0.7%) for thrombocytes. The differences in these levels were lower for former smokers compared with current smokers. The IL6R rs2228145 genotype was associated with higher plasma acute-phase reactants but not with airflow limitation. Compared with the C/C genotype, the odds ratio for airflow limitation was 0.95 (95% CI = 0.89 to 1.02) for A/C genotype and 0.94 (95% CI = 0.87 to 1.01) for A/A genotype.Conclusions: Higher tobacco consumption is associated with higher systemic inflammation both genetically and observationally, whereas systemic inflammation was not associated with airflow limitation genetically.Implications: The association between higher tobacco consumption and higher systemic inflammation may be causal, and the association is stronger among current smokers compared to former smokers, indicating that smoking cessation may reduce the effects of smoking on systemic inflammation. Systemic inflammation does not seem to be a causal driver in development of airflow limitation. These findings can help to understand the pathogenic effects of smoking and the interplay between smoking, systemic inflammation, and airflow limitation and hence development and progression of chronic obstructive pulmonary disease. [ABSTRACT FROM AUTHOR]

Published
2019
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27. Low concentrations of 25-hydroxyvitamin D and long-term prognosis of COPD: a prospective cohort study.

Author

Færk, Gitte, Çolak, Yunus, Afzal, Shoaib, and Nordestgaard, Børge G.

Subjects
OBSTRUCTIVE lung diseases patients, CARDIOVASCULAR diseases, SMOKING, EPIDEMIOLOGY, VITAMIN D deficiency
Abstract

Role and importance of vitamin D deficiency in long-term prognosis of chronic obstructive pulmonary disease (COPD) still remains undetermined. We tested the hypothesis that among individuals with COPD, those with low concentrations of 25-hydroxyvitamin D have a poorer prognosis compared to those with normal concentrations. We studied 35,153 individuals from the general population aged 20-100 years with 25-hydroxyvitamin D measurements and spirometry, the Copenhagen City Heart Study [median follow-up 21 years (range 13 days-36 years)] and the Copenhagen General Population Study [7.1 years (3 days-13 years)]. Spirometric COPD (n = 5178; 15% of all) was defined as forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) < 0.70 in individuals without asthma and clinical COPD (n = 2033; 6%) as FEV1/FVC < 0.70 and FEV1 < 80% of predicted in ever-smokers aged > 40 years without asthma and with cumulative tobacco consumption ≥ 10 pack-years. In spirometric COPD, median age at death in years was 70.2 (95% confidence interval [CI] 64.4-71.2) for individuals with 25-hydroxyvitamin D < 12.5 nmol/L and 80.3 (74.4-83.4) for those with ≥ 50 nmol/L. In clinical COPD, corresponding values were 69.0 (63.3-70.9) and 76.2 (73.8-78.0). In spirometric COPD, multivariable adjusted hazard ratios for individuals with 25-hydroxyvitamin D < 12.5 nmol/L versus those with ≥ 50 nmol/L were 1.35 (95% CI 1.09-1.67) for all-cause mortality, 1.63 (1.00-2.64) for respiratory mortality, 1.14 (0.76-1.70) for cardiovascular mortality, 1.37 (0.90-2.06) for cancer mortality, and 1.61 (1.04-2.49) for other mortality. In clinical COPD, corresponding values were 1.39 (1.07-1.82), 1.57 (0.91-2.72), 0.88 (0.51-1.53), 1.63 (0.99-2.67), and 2.00 (1.12-3.56). Low concentrations of 25-hydroxyvitamin D were associated with an increased risk of death in individuals with COPD. No clear pattern of association could be observed for cause of death; however, there may be an increased risk of respiratory, cancer, and other mortality. It is likely that low concentrations of 25-hydroxyvitamin D is a marker of poor health in COPD. [ABSTRACT FROM AUTHOR]

Published
2018
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28. Risk Factors for Chronic Cough Among 14,669 Individuals From the General Population.

Author

Çolak, Yunus, Nordestgaard, Børge G., Laursen, Lars C., Afzal, Shoaib, Lange, Peter, and Dahl, Morten

Abstract

Background Risk factors for chronic cough in the general population have not been described systematically. We identified and ranked chronic cough risk factors at the individual and community level using data from 14,669 individuals from the Copenhagen General Population Study. Methods Severity of chronic cough was assessed using the Leicester Cough Questionnaire (LCQ). We ranked chronic cough risk factors based on magnitude of age-adjusted ORs at the individual level and of the population attributable risks (PARs) at the community level. Results Prevalence of chronic cough in the general population was 4% overall and 3% in never smokers, 4% in former smokers, and 8% in current smokers. Median score of the LCQ was 5.8 (25th-75th percentile, 5.0-6.3) for physical domain, 5.6 (25th-75th percentile, 4.6-6.3) for psychologic domain, 6.3 (25th-75th percentile, 5.5-6.8) for social domain, and 17.3 (25th- 75th percentile, 15.4-18.9) in total. At the level of the individual, age-adjusted ORs for the three top-ranked risk factors were 5.0 (95% CI, 1.4-18) for bronchiectasis, 2.6 (95% CI, 1.7-3.9) for asthma and 2.3 (95% CI, 1.5-3.4) for gastroesophageal reflux disease in never smokers, 7.1 (95% CI, 2.6-20) for bronchiectasis, 3.1 (95% CI, 2.2-4.4) for asthma and 2.2 (95% CI, 1.5-3.2) for occupational exposure to dust/fumes in former smokers, and 1.9 (95% CI, 1.3-2.9) for airflow limitation in current smokers. At the level of the community, the three top-ranked risk factors were female sex (PAR, 19%), asthma (PAR, 10%), and gastroesophageal reflux disease (PAR, 8%) in never smokers; abdominal obesity (PAR, 20%), low income (PAR, 20%), and asthma (PAR, 13%) in former smokers; and airflow limitation (PAR, 23%) in current smokers. Conclusions Risk factors for chronic cough differ at the level of the individual and community, and by smoking status. Strategies to prevent and treat modifiable chronic cough risk factors should be tailored accordingly. [ABSTRACT FROM AUTHOR]

Published
2017
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29. (cg05575921) hypomethylation marks smoking behaviour, morbidity and mortality.

Author

Bojesen, Stig E., Timpson, Nicholas, Relton, Caroline, Smith, George Davey, Nordestgaard, Børge G., and Davey Smith, George

Subjects
SMOKING, PHYSIOLOGICAL effects of hydrocarbons, LEUCOCYTES, DNA methylation, OBSTRUCTIVE lung diseases, GENETICS, CHOLINERGIC receptors, CAUSES of death, LUNG tumors, PROTEINS, QUESTIONNAIRES, RESEARCH funding, RISK assessment, RISK-taking behavior, DISEASE progression, GENOTYPES
Abstract

Rationale and Objectives: Self-reported smoking underestimates disease risk. Smoking affects DNA methylation, in particular the cg05575921 site in the aryl hydrocarbon receptor repressor (AHRR) gene. We tested the hypothesis that AHRR cg05575921 hypomethylation is associated with risk of smoking-related morbidity and mortality.Methods: From the Copenhagen City Heart Study representing the Danish general population, we studied 9234 individuals. Using bisulphite treated leucocyte DNA, AHRR (cg05575921) methylation was measured. Rs1051730 (CHRN3A) genotype was used to evaluate smoking heaviness. Participants were followed for up to 22 years for exacerbations of COPD, event of lung cancer and all-cause mortality. Six-year lung cancer risk was calculated according to the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCOM2012).Measurements and Main Results: AHRR (cg05575921) hypomethylation was associated with former and current smoking status, high daily and cumulative smoking, short time since smoking cessation (all p values <7×10-31), and the smoking-related CHRN3A genotype (-0.48% per T-allele, p=0.002). The multifactorially adjusted HRs for the lowest versus highest methylation quintiles were 4.58 (95% CI 2.83 to 7.42) for COPD exacerbations, 4.87 (2.31 to 10.3) for lung cancer and 1.67 (1.48 to 1.88) for all-cause mortality. Finally, among 2576 high-risk smokers eligible for lung cancer screening by CT, observed cumulative incidences of lung cancer after 6 years for individuals in the lowest and highest methylation quintiles were 3.7% and 0.0% (p=2×10-7), whereas predicted PLCOM2012 6-year risks were similar (4.3% and 4.4%, p=0.77).Conclusion: AHRR (cg05575921) hypomethylation, a marker of smoking behaviour, provides potentially clinical relevant predictions of future smoking-related morbidity and mortality. [ABSTRACT FROM AUTHOR]

Published
2017
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30. Majority of never-smokers with airflow limitation do not have asthma: the Copenhagen General Population Study.

Author

Çolak, Yunus, Afzal, Shoaib, Nordestgaard, Børge G., and Lange, Peter

Subjects
CIGARETTE smokers, RESPIRATORY organs, ASTHMA, OBSTRUCTIVE lung diseases, PNEUMONIA, LONGITUDINAL method, PULMONARY function tests, RESPIRATORY obstructions, SMOKING
Abstract

Background: A substantial proportion of individuals with airflow limitation are never-smokers. However, whether never-smokers with airflow limitation have undiagnosed asthma is unknown. We hypothesised that the majority of never-smokers with respiratory symptoms and airflow limitation but without known asthma have undiagnosed asthma by comparing characteristics and prognosis in never-smokers with airflow limitation and asthma (NS+AFL+A) with never-smokers with airflow limitation but without asthma (NS+AFL-A).Methods: Among 94 079 participants aged 20-100 years from the general population, 39 102 (42%) were never-smokers. In this group, 13 719 (35%) reported to have respiratory symptoms of whom 1610 (12%) had airflow limitation. We investigated characteristics and risk of complications (asthma or COPD exacerbations, pneumonias and all-cause mortality) and comorbidities (lung cancer, ischaemic heart disease, myocardial infarction, deep venous thrombosis and PE) during 4.5 years median follow-up.Results: NS+AFL-A compared with NS+AFL+A reported less allergy and respiratory symptoms, and had higher FEV1 and lower levels of eosinophils and IgE in peripheral blood. NS+AFL+A had increased risk of asthma and COPD exacerbations, but not of pneumonias; adjusted HRs in NS+AFL+A compared with NS+AFL-A were 16 (95% CI 3.7 to 73) for asthma exacerbations and 15 (2.8 to 80) for COPD exacerbations. Still, NS+AFL-A had increased risk of COPD exacerbations and pneumonias, but not of asthma exacerbations; adjusted HRs in NS+AFL-A compared with never-smokers without airflow limitation or asthma (NS-AFL-A) were 7.7 (2.8 to 21) for COPD exacerbations and 1.7 (1.3 to 2.3) for pneumonias. Risk of comorbidities or all-cause mortality was not increased in NS+AFL-A or NS+AFL+A compared with NS-AFL-A.Conclusions: Majority of NS+AFL-A do not seem to have undiagnosed asthma and may instead have airflow limitation caused by other risk factors. [ABSTRACT FROM AUTHOR]

Published
2016
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31. High tobacco consumption is causally associated with increased all-cause mortality in a general population sample of 55 568 individuals, but not with short telomeres: a Mendelian randomization study.

Author

Rode, Line, Bojesen, Stig E, Weischer, Maren, and Nordestgaard, Børge G

Subjects
TOBACCO & health, TELOMERES, STATISTICAL hypothesis testing, RANDOMIZATION (Statistics), CONFIDENCE intervals
Abstract

Background: High cumulative tobacco consumption is associated with short telomeres and with increased all-cause mortality. We tested the hypothesis that high tobacco consumption is causally associated with short telomeres and with increased all-cause mortality.Methods: We studied 55 568 individuals including 32 823 ever smokers from the Danish general population, of whom 3430 died during 10 years of follow-up. All had telomere length measured, detailed information on smoking history, and CHRNA3 rs1051730 genotype, which is associated with tobacco consumption, determined. In a Mendelian randomization study, we conducted observational, genetic, and mediation analyses.Results: First, tobacco consumption was 21.1 pack-years in non-carriers, 22.8 in heterozygotes and 24.8 in homozygotes (P-trend <0.001). Second, the observational multivariable adjusted hazard ratio for all-cause mortality was 1.12 [95% confidence interval (CI): 1.09, 1.15] per doubling in tobacco consumption. In Mendelian randomization analysis, the hazard ratio was 1.08 (1.02, 1.14) per minor CHRNA3 allele in ever smokers. Third, in observational analysis telomeres shortened with −13 base pairs (−18, −8) per doubling in tobacco consumption. In Mendelian randomization analysis, the estimate was +3 base pairs (−10, +15) per minor CHRNA3 allele. Finally, individuals with the shortest vs longest telomeres had a multivariable adjusted hazard ratio of 1.30 (1.13, 1.50) for all-cause mortality; however, in mediation analysis short telomeres explained only +0.4% (−3.5%, +4.3%) of the association between high tobacco consumption and increased all-cause mortality.Conclusions: High tobacco consumption is causally associated with increased all-cause mortality. High cumulative tobacco consumption is associated with short telomeres observationally, but there is no clear genetic association. [ABSTRACT FROM AUTHOR]

Published
2014
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32. Characteristics of Undertreatment in COPD in the General Population.

Author

Ingebrigtsen, Truls S., Marott, Jacob L., Vestbo, Jørgen, Hallas, Jesper, Nordestgaard, Børge G., Dahl, Morten, and Lange, Peter

Subjects
OBSTRUCTIVE lung diseases, LUNG diseases, RESPIRATORY obstructions, RESPIRATORY infections, SMOKING, HEALTH
Abstract

The article discusses the results of a study that examined the undertreatment in chronic obstructive pulmonary disease (COPD). The study identified predictors of treatment and medication including breathlessness, low forced expiratory volume (FEV) and former smoking. It concluded that previous reported respiratory infections led to treatment with medications, indicating that most COPD treatment is done due to acute exacerbations.

Published
2013
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33. Copy Number Variation in Glutathione S-Transferases M1 and T1 and Ischemic Vascular Disease.

Author

Nerskøv, Marianne S., Frikke-Schmidt, Ruth, Loft, Steffen, Sillesen, Henrik, Grande, Peer, Nordestgaard, Børge G., and Tybjærg-Hansen, Anne

Subjects
GLUTATHIONE transferase, ISCHEMIA, MEDICAL genetics, CARDIOVASCULAR diseases, POLYMERASE chain reaction, META-analysis, INFLAMMATION, DISEASE risk factors
Abstract

The article presents studies aimed at testing the hypothesis supposing the ability of the copy number variation (CNV) in glutathione S-transferases (GSTs) T1 (GSTT1) and GSTM1 genes to predict ischemic vascular disease (IVD) risk. The study made use of a real-time polymerase chain reaction technique and carried out meta-analyses. Results indicate the absence of the association of CNV in GSTT1 and GSTM1 genes with IVD risk nor with inflammation markers.

Published
2011
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35. Cardiovascular Risk Factors Associated With Venous Thromboembolism

Author

Gregson, John, Kaptoge, Stephen, Bolton, Thomas, Pennells, Lisa, Willeit, Peter, Burgess, Stephen, Bell, Steven, Sweeting, Michael, Rimm, Eric B, Kabrhel, Christopher, Zöller, Bengt, Assmann, Gerd, Gudnason, Vilmundur, Folsom, Aaron R, Arndt, Volker, Fletcher, Astrid, Norman, Paul E, Nordestgaard, Børge G, Kitamura, Akihiko, Mahmoodi, Bakhtawar K, Whincup, Peter H, Knuiman, Matthew, Salomaa, Veikko, Meisinger, Christa, Koenig, Wolfgang, Kavousi, Maryam, Völzke, Henry, Cooper, Jackie A, Ninomiya, Toshiharu, Casiglia, Edoardo, Rodriguez, Beatriz, Ben-Shlomo, Yoav, Després, Jean-Pierre, Simons, Leon, Barrett-Connor, Elizabeth, Björkelund, Cecilia, Notdurfter, Marlene, Kromhout, Daan, Price, Jackie, Sutherland, Susan E, Sundström, Johan, Kauhanen, Jussi, Gallacher, John, Beulens, Joline WJ, Dankner, Rachel, Cooper, Cyrus, Giampaoli, Simona, Deen, Jason F, Gómez De La Cámara, Agustín, Kuller, Lewis H, Rosengren, Annika, Svensson, Peter J, Nagel, Dorothea, Crespo, Carlos J, Brenner, Hermann, Albertorio-Diaz, Juan R, Atkins, Robert, Brunner, Eric J, Shipley, Martin, Njølstad, Inger, Lawlor, Deborah A, Van Der Schouw, Yvonne T, Selmer, Randi Marie, Trevisan, Maurizio, Verschuren, WM Monique, Greenland, Philip, Wassertheil-Smoller, Sylvia, Lowe, Gordon DO, Wood, Angela M, Butterworth, Adam S, Thompson, Simon G, Danesh, John, Di Angelantonio, Emanuele, Meade, Tom, and Emerging Risk Factors Collaboration

Subjects
2. Zero hunger, Adult, Male, Venous Thrombosis, Smoking, Coronary Disease, Venous Thromboembolism, Middle Aged, 16. Peace & justice, United Kingdom, 3. Good health, Body Mass Index, Cardiovascular Diseases, Risk Factors, Outcome Assessment, Health Care, Diabetes Mellitus, Humans, Female, Obesity, Prospective Studies, Pulmonary Embolism
Abstract

IMPORTANCE: It is uncertain to what extent established cardiovascular risk factors are associated with venous thromboembolism (VTE). OBJECTIVE: To estimate the associations of major cardiovascular risk factors with VTE, ie, deep vein thrombosis and pulmonary embolism. DESIGN, SETTING, AND PARTICIPANTS: This study included individual participant data mostly from essentially population-based cohort studies from the Emerging Risk Factors Collaboration (ERFC; 731 728 participants; 75 cohorts; years of baseline surveys, February 1960 to June 2008; latest date of follow-up, December 2015) and the UK Biobank (421 537 participants; years of baseline surveys, March 2006 to September 2010; latest date of follow-up, February 2016). Participants without cardiovascular disease at baseline were included. Data were analyzed from June 2017 to September 2018. EXPOSURES: A panel of several established cardiovascular risk factors. MAIN OUTCOMES AND MEASURES: Hazard ratios (HRs) per 1-SD higher usual risk factor levels (or presence/absence). Incident fatal outcomes in ERFC (VTE, 1041; coronary heart disease [CHD], 25 131) and incident fatal/nonfatal outcomes in UK Biobank (VTE, 2321; CHD, 3385). Hazard ratios were adjusted for age, sex, smoking status, diabetes, and body mass index (BMI). RESULTS: Of the 731 728 participants from the ERFC, 403 396 (55.1%) were female, and the mean (SD) age at the time of the survey was 51.9 (9.0) years; of the 421 537 participants from the UK Biobank, 233 699 (55.4%) were female, and the mean (SD) age at the time of the survey was 56.4 (8.1) years. Risk factors for VTE included older age (ERFC: HR per decade, 2.67; 95% CI, 2.45-2.91; UK Biobank: HR, 1.81; 95% CI, 1.71-1.92), current smoking (ERFC: HR, 1.38; 95% CI, 1.20-1.58; UK Biobank: HR, 1.23; 95% CI, 1.08-1.40), and BMI (ERFC: HR per 1-SD higher BMI, 1.43; 95% CI, 1.35-1.50; UK Biobank: HR, 1.37; 95% CI, 1.32-1.41). For these factors, there were similar HRs for pulmonary embolism and deep vein thrombosis in UK Biobank (except adiposity was more strongly associated with pulmonary embolism) and similar HRs for unprovoked vs provoked VTE. Apart from adiposity, these risk factors were less strongly associated with VTE than CHD. There were inconsistent associations of VTEs with diabetes and blood pressure across ERFC and UK Biobank, and there was limited ability to study lipid and inflammation markers. CONCLUSIONS AND RELEVANCE: Older age, smoking, and adiposity were consistently associated with higher VTE risk.

36. Shared heritability and functional enrichment across six solid cancers

Author

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

Subjects
Male, Ovarian Neoplasms, Lung Neoplasms, Mental Disorders, Smoking, Inheritance Patterns, Prostatic Neoplasms, Breast Neoplasms, Polymorphism, Single Nucleotide, White People, 3. Good health, Neoplasm Proteins, Phenotype, Head and Neck Neoplasms, Case-Control Studies, Humans, Female, Genetic Predisposition to Disease, Colorectal Neoplasms, Genome-Wide Association Study
Abstract

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

37. Shared heritability and functional enrichment across six solid cancers

Author

Graham G. Giles, Diana Eccles, Cezary Cybulski, Catherine M. Tangen, Leon Raskin, Per Hall, Ana Vega, Hedy S. Rennert, Andrew T. Chan, Stephan Lam, Michael Hoffmeister, Angeline S. Andrew, Claudine Isaacs, Matthias W. Beckmann, Vessela N. Kristensen, Julia A. Knight, Mark S. Goldberg, Jonathan Tyrer, Jane C. Figueiredo, Katherine L. Nathanson, Anna deFazio, Ian G. Campbell, Nora Pashayan, Liene Nikitina-Zake, Goska Leslie, Rosalind A. Eeles, Line Bjørge, Adonina Tardón, Angela Cox, Gregory Idos, Evgeny N. Imyanitov, Manolis Kogevinas, Marc Tischkowitz, Hilary K. Finucane, Hardev Pandha, Rayjean J. Hung, Davor Lessel, Richard S. Houlston, Andrew F. Olshan, André Lopes Carvalho, James D. McKay, Kenneth Offit, Penelope M. Webb, Barry S. Rosenstein, Melinda C. Aldrich, Alice S. Whittemore, Austin Miller, Miguel E. Aguado-Barrera, Amanda E. Toland, Anna Marie Mulligan, Catharine M L West, Susan J. Ramus, Jennifer Stone, David C. Christiani, Clarice R. Weinberg, Olivia Fletcher, Kyriaki Michailidou, Demetrius Albanes, Chu Chen, Jenny L Donovan, Linda E. Kelemen, Carolina Ellberg, Hermann Brenner, Eitan Friedman, Sara Margolin, Jacek Gronwald, Argyrios Ziogas, Elisa V. Bandera, Qin Wang, Christopher I. Amos, Swe-Brca, Douglas F. Easton, Karin Sundfeldt, John L. Hopper, Jong Y. Park, Børge G. Nordestgaard, Johanna Schleutker, Freddie C. Hamdy, Alicja Wolk, Graham Casey, Radka Kaneva, Joe Dennis, Francesmary Modugno, Paolo Radice, Aage Haugen, Ralf Bützow, Barbara Burwinkel, Maria A. Caligo, Paul A. Townsend, Daniel D. Buchanan, Håkan Olsson, Li Li, Elza Khusnutdinova, Karina Dalsgaard Sørensen, Marco Montagna, Patricia A. Ganz, Kirsten B. Moysich, Stephen B. Gruber, Geraldine Cancel-Tassin, Mary Anne Rossing, Mads Thomassen, Manuela Gago-Dominguez, Marjanka K. Schmidt, Jolanta Kupryjanczyk, Melissa C. Southey, Finn Cilius Nielsen, Sara Benlloch, Roger L. Milne, Manuel R. Teixeira, Taymaa May, David V. Conti, Thilo Dörk, Kathleen Claes, Manjeet K. Bolla, Douglas A. Levine, Lorelei A. Mucci, Irene L. Andrulis, Carl Blomqvist, Sara Lindström, Marjorie J. Riggan, Ellen L. Goode, Jenny Lester, Jack A. Taylor, Adam S. Kibel, Jyotsna Batra, Stephen N. Thibodeau, Elinor J. Sawyer, Stefania Boccia, Jacques Simard, Robert J. MacInnis, Fredrik Wiklund, Geoffrey Liu, Robert Winqvist, Robert J. Hamilton, Joan Brunet, Olufunmilayo I. Olopade, Jeffrey N. Weitzel, Susan L. Neuhausen, Robert L. Ferris, Georgia Chenevix-Trench, Elizabeth J. van Rensburg, Amanda B. Spurdle, Jeroen R. Huyghe, Stig E. Bojesen, Eric J. Duell, Christopher A. Haiman, Bogdan Pasaniuc, Wilbert H.M. Peters, M. Dawn Teare, Marc T. Goodman, Richa Saxena, Renée T. Fortner, Shanbeh Zienolddiny, Mia M. Gaudet, Stephanie J. Weinstein, Mikael Johansson, Heli Nevanlinna, Nhu D. Le, Rolando Herrero, Peter Kraft, Steven Gallinger, David E. Goldgar, Anna Jakubowska, Paul D.P. Pharoah, Erin M. Siegel, Gabriella Cadoni, Weiva Sieh, Esther M. John, Rebecca Sutphen, Kari Stefansson, Loic Le Marchand, David J. Hunter, Alkes L. Price, Judy Garber, Mary B. Daly, Flavio Lejbkowicz, Lambertus A. Kiemeney, Martha L. Slattery, Arto Mannermaa, Christian F. Singer, Daniele Campa, Hans Brunnström, Hongbing Shen, Els Van Nieuwenhuysen, V. Wendy Setiawan, Penella J. Woll, Catherine M. Phelan, Christopher I. Li, Robert L. Nussbaum, Niclas Håkansson, Triantafillos Liloglou, Stella Koutros, Kjell Grankvist, James D. Brenton, Annika Lindblom, Gad Rennert, Karoline Kuchenbaecker, Martin Lacko, Gary E. Goodman, Fredrick R. Schumacher, Henrik Grönberg, Diana Torres, J. Margriet Collée, Rosa B. Barkardottir, Amit Joshi, Trinidad Caldés, Mary Beth Terry, Jenny Chang-Claude, Paul Brennan, Simon A. Gayther, Mark H. Greene, Daniel R. Barnes, Janet L. Stanford, Miriam Dwek, Christiane Maier, Susanne K. Kjaer, Florentia Fostira, Miranda Pring, Noralane M. Lindor, Harvey A. Risch, David G. Huntsman, Kim De Ruyck, Judith A. Clements, Pooja Middha, Alison M. Dunning, Nadine Tung, Sebastian Stintzing, Michael O. Woods, Stephen J. Chanock, Andrew K. Godwin, Kenneth Muir, Eloiza H. Tajara, Silvia Franceschi, Xia Jiang, Li Hsu, Emily White, Peter T. Campbell, Paul A. James, Josef Heinz-Lenz, Ali Amin Al Olama, Victoria L. Stevens, Lovise Maehle, Fotios Loupakis, Peter Devilee, Orland Diez, Kristin K. Zorn, Stephanie A. Bien, Maria Teresa Landi, Mark A. Jenkins, Amanda I. Phipps, Alfons Meindl, Frank Claessens, Mark N. Brook, Kathryn L. Penney, Digna R. Velez Edwards, Montserrat Garcia-Closas, Diether Lambrechts, Zsofia Kote-Jarai, Fergus J. Couch, Duncan Thomas, Kathryn L. Terry, Ute Hamann, Heike Bickeböller, Christopher K. Edlund, Ana Osorio, Younghun Han, Jochen Hampe, Tee Kay-Khaw, Corina Lesseur, Peter A. Fasching, Lesley McGuffog, Eunjung Lee, Tabea Kühl, Andy R Ness, Kamila Czene, Angela Risch, Aocs Mod SQuaD, Jeri Kim, Anna H. Wu, Jacqueline M. Lane, Brenda Diergaarde, Ruth C. Travis, Julie M. Cunningham, Philip Lazarus, Shelley S. Tworoger, Natalia Antonenkova, Emmanouil Saloustros, Wei Zheng, Javier Benitez, Dijana Plaseska-Karanfilska, Mark C. Weissler, Marcia Cruz Correa, Hoda Anton-Culver, Neil E. Caporaso, Cornelia M. Ulrich, Stephanie L. Schmit, Antonis C. Antoniou, Victor Moreno, David E. Neal, Tanja Pejovic, Erich H-Wichmann, Pascal Guénel, Mattias Johansson, Florian Heitz, Beth Y. Karlan, Sonja I. Berndt, Anthony J. Swerdlow, Estrid Høgdall, Hiltrud Brauch, Ulrike Peters, D. Gareth Evans, Celine M. Vachon, Edith Olah, Dale P. Sandler, Lisa F. Newcomb, Michael T. Parsons, Lisa A. Cannon-Albright, Peter J. Hulick, José A. García-Sáenz, Sue A. Ingles, Andrew Berchuck, Peter Hillemanns, Matthew B. Schabath, Polly A. Newcomb, Banu Arun, Xifeng Wu, Darya Prokofyeva, Jan Lubinski, Susanne M. Arnold, Natalia Bogdanova, Drakoulis Yannoukakos, Nawaid Usmani, Kristan J. Aronson, Chul Yun-Hong, Monique J. Roobol, Clinical Genetics, Urology, Læknadeild (HÍ), Faculty of Medicine (UI), Lífvísindasetur (HÍ), Biomedical Center (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Finucane, Hilary K [0000-0003-3864-9828], Schumacher, Fredrick R [0000-0002-3073-7463], Schmit, Stephanie L [0000-0001-5931-1194], Michailidou, Kyriaki [0000-0001-7065-1237], Kuchenbaecker, Karoline B [0000-0001-9726-603X], Dennis, Joe [0000-0003-4591-1214], Huyghe, Jeroen R [0000-0001-6027-9806], Andrulis, Irene L [0000-0002-4226-6435], Arnold, Susanne M [0000-0001-6542-9551], Barnes, Daniel R [0000-0002-3781-7570], Batra, Jyotsna [0000-0003-4646-6247], Bojesen, Stig E [0000-0002-4061-4133], Brauch, Hiltrud [0000-0001-7531-2736], Brenton, James D [0000-0002-5738-6683], Brook, Mark N [0000-0002-8969-2378], Brunet, Joan [0000-0003-1945-3512], Brunnström, Hans [0000-0001-7402-138X], Buchanan, Daniel D [0000-0003-2225-6675], Campbell, Ian [0000-0002-7773-4155], Cancel-Tassin, Géraldine [0000-0002-9583-6382], Chan, Andrew T [0000-0001-7284-6767], Chanock, Stephen J [0000-0002-2324-3393], Claes, Kathleen BM [0000-0003-0841-7372], Cunningham, Julie M [0000-0002-8159-3025], Devilee, Peter [0000-0002-8023-2009], Ellberg, Carolina [0000-0001-7297-0645], Fasching, Peter A [0000-0003-4885-8471], Liloglou, Triantafillos [0000-0003-0460-1404], Fletcher, Olivia [0000-0001-9387-7116], García-Sáenz, José A [0000-0001-6880-0301], Grankvist, Kjell [0000-0003-4289-2097], Greene, Mark H [0000-0003-1852-9239], Gronberg, Henrik [0000-0002-1073-2753], Guénel, Pascal [0000-0002-8359-518X], Hampe, Jochen [0000-0002-2421-6127], Houlston, Richard [0000-0002-5268-0242], Hulick, Peter J [0000-0001-8397-4078], James, Paul [0000-0002-4361-4657], Jenkins, Mark A [0000-0002-8964-6160], Joshi, Amit D [0000-0001-7581-6934], Lambrechts, Diether [0000-0002-3429-302X], Leslie, Goska [0000-0001-5756-6222], Lessel, Davor [0000-0003-4496-244X], Levine, Douglas A [0000-0003-1038-8232], Miller, Austin [0000-0001-9739-8462], Milne, Roger L [0000-0001-5764-7268], Moreno, Victor [0000-0002-2818-5487], Muir, Kenneth [0000-0001-6429-988X], Nathanson, Katherine L [0000-0002-6740-0901], Nevanlinna, Heli [0000-0002-0916-2976], Newcomb, Polly A [0000-0001-8786-0043], Nikitina-Zake, Liene [0000-0003-2491-5187], Nordestgaard, Børge G [0000-0002-1954-7220], Olama, Ali Amin Al [0000-0002-7178-3431], Olopade, Olufunmilayo I [0000-0002-9936-1599], Pashayan, Nora [0000-0003-0843-2468], Parsons, Michael T [0000-0003-3242-8477], Plaseska-Karanfilska, Dijana [0000-0001-8877-2416], Raskin, Leon [0000-0003-1195-7214], Rennert, Gad [0000-0002-8512-068X], Risch, Angela [0000-0002-8026-5505], Roobol, Monique J [0000-0001-6967-1708], Saloustros, Emmanouil [0000-0002-0485-0120], Schabath, Matthew B [0000-0003-3241-3216], Schleutker, Johanna [0000-0002-1863-0305], Schmidt, Marjanka K [0000-0002-2228-429X], Sorensen, Karina Dalsgaard [0000-0002-4902-5490], Stintzing, Sebastian [0000-0002-3297-5801], Stone, Jennifer [0000-0001-5077-0124], Tardon, Adonina [0000-0001-5150-1209], Teixeira, Manuel R [0000-0002-4896-5982], Toland, Amanda E [0000-0002-0271-1792], Aguado-Barrera, Miguel Elías [0000-0002-7822-6726], Webb, Penelope M [0000-0003-0733-5930], Wolk, Alicja [0000-0001-7387-6845], Yannoukakos, Drakoulis [0000-0001-7509-3510], Zheng, Wei [0000-0003-1226-070X], Ziogas, Argyrios [0000-0003-4529-3727], Peters, Ulrike [0000-0001-5666-9318], Eeles, Rosalind A [0000-0002-3698-6241], Brennan, Paul J [0000-0002-0518-8714], Easton, Douglas F [0000-0003-2444-3247], Pharoah, Paul DP [0000-0001-8494-732X], Price, Alkes L [0000-0002-2971-7975], Apollo - University of Cambridge Repository, Institut Català de la Salut, [Jiang X] Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. [Finucane HK] Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. [Schumacher FR] Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA. Seidman Cancer Center, University Hospitals, Cleveland, OH, USA. [Schmit SL] Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA. Department of Gastrointestinal Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA. [Tyrer JP] Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK. [Han Y] Department of Biomedical Data Science, The Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. [Diez O] Grup d'Oncogenètica, Vall d'Hebron Institut d'Oncologia, Barcelona, Spain. Hospital Universitari Vall d'Hebron, Barcelona, Spain, Hospital Universitari Vall d'Hebron, Lääketieteen ja terveysteknologian tiedekunta - Faculty of Medicine and Health Technology, Tampere University, Cancer Research UK (Reino Unido), NIHR - Comprehensive Biomedical Research Centre, Guy ’ s & St. Thomas ’ NHS Foundation Trust, NIHR - Oxford Biomedical Research Centre (Reino Unido), German Cancer Research Center, Consejo Nacional de Ciencia y Tecnología (CONACyT), King College London, National Health and Medical Research Council (Australia), Canadian Institutes of Health Research, The BREast Oncology GAlician Network (BREOGAN, Dietmar-Hopp Foundation, Helmholtz Society and the German Cancer Research Center (DKFZ), Asociación Española Contra el Cáncer, Vall d'Hebron Barcelona Hospital Campus, Clinicum, Department of Oncology, University of Helsinki, Department of Pathology, Medicum, Department of Obstetrics and Gynecology, and HUS Comprehensive Cancer Center

Subjects
Oncology, Male, Lung Neoplasms, Colorectal cancer, Epidemiology, Inheritance Patterns, Genome-wide association study, 02 engineering and technology, Colorectal Neoplasms/diagnosis, Càncer - Aspectes genètics, 0302 clinical medicine, Neoplasm Proteins/genetics, Brjóstakrabbamein, PARTITIONING HERITABILITY, lcsh:Science, Càncer, Cancer genetics, Cancer, Càncer - Estudi de casos, Ovarian Neoplasms, Prostatic Neoplasms/diagnosis, 0303 health sciences, Otros calificadores::Otros calificadores::/genética [Otros calificadores], 1184 Genetics, developmental biology, physiology, Genomics, Publisher Correction, ddc, 3. Good health, Neoplasm Proteins, Head and Neck Neoplasms, 030220 oncology & carcinogenesis, Etiologia, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Neoplasias [ENFERMEDADES], ICEP, Erfðarannsóknir, 0210 nano-technology, Genetic Phenomena::Inheritance Patterns [PHENOMENA AND PROCESSES], medicine.medical_specialty, Biolääketieteet - Biomedicine, Science, Lung Neoplasms/diagnosis, European Continental Ancestry Group, Genetic correlation, Article, General Biochemistry, Genetics and Molecular Biology, White People, GENETIC ARCHITECTURE, 03 medical and health sciences, Breast cancer, SDG 3 - Good Health and Well-being, Syöpätaudit - Cancers, BREAST-CANCER, Humans, Otros calificadores::Otros calificadores::Otros calificadores::/etnología [Otros calificadores], Polymorphism, GENOME-WIDE ASSOCIATION, solid cancers, heritability, enrichment, Settore MED/42 - IGIENE GENERALE E APPLICATA, ResearchInstitutes_Networks_Beacons/mcrc, Fenómenos Genéticos::Patrón de Herencia [FENÓMENOS Y PROCESOS], ANALYSES IDENTIFY, Biology and Life Sciences, fenómenos genéticos::patrones de herencia [FENÓMENOS Y PROCESOS], medicine.disease, Càncer -- Etiologia, 030104 developmental biology, Case-Control Studies, RISK-FACTORS, lcsh:Q, 0301 basic medicine, Etiology, Medizin, General Physics and Astronomy, técnicas de investigación::métodos epidemiológicos::características de los estudios epidemiológicos::estudios epidemiológicos::estudios de casos y controles [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS], head and neck, Prostate cancer, Medicine and Health Sciences, Càncer -- Aspectes genètics, Multidisciplinary, Manchester Cancer Research Centre, Mental Disorders, Codi genètic, Smoking, Single Nucleotide, 021001 nanoscience & nanotechnology, Phenotype, Centre for Surgical Research, Cancer -- Etiology, MENDELIAN RANDOMIZATION, Female, Smoking/ethnology, Colorectal Neoplasms, Mental Disorders/ethnology, Medical Genetics, Investigative Techniques::Epidemiologic Methods::Epidemiologic Study Characteristics::Epidemiologic Studies::Case-Control Studies [ANALYTICAL, DIAGNOSTIC AND THERAPEUTIC TECHNIQUES AND EQUIPMENT], Cancer Etiology, Técnicas de Investigación::Métodos Epidemiológicos::Características de Estudios Epidemiológicos::Estudios Epidemiológicos::Estudios de Casos y Controles [TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS], SUSCEPTIBILITY LOCI, 3122 Cancers, Breast Neoplasms, Biology, Polymorphism, Single Nucleotide, LUNG-CANCER, All institutes and research themes of the Radboud University Medical Center, Internal medicine, MD Multidisciplinary, Other subheadings::Other subheadings::/genetics [Other subheadings], medicine, Erfðafræði, Genetic Predisposition to Disease, CELL-TYPES, Lung cancer, Krabbamein, Medicinsk genetik, 030304 developmental biology, Ovarian Neoplasms/diagnosis, Faraldsfræði, Prostatic Neoplasms, Breast Neoplasms/diagnosis, General Chemistry, Heritability, Head and Neck Neoplasms/diagnosis, Neoplasms [DISEASES], Genome-Wide Association Study, 3111 Biomedicine, Ovarian cancer, Other subheadings::Other subheadings::Other subheadings::/ethnology [Other subheadings]
Abstract

Publisher's version (útgefin grein)., Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10−8), breast and ovarian cancer (rg = 0.24, p = 7 × 10−5), breast and lung cancer (rg = 0.18, p =1.5 × 10−6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10−4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis., The authors in this manuscript were working on behalf of BCAC, CCFR, CIMBA, CORECT, GECCO, OCAC, PRACTICAL, CRUK, BPC3, CAPS, PEGASUS, TRICL-ILCCO, ABCTB, APCB, BCFR, CONSIT TEAM, EMBRACE, GC-HBOC, GEMO, HEBON, kConFab/AOCS Mod SQuaD, and SWE-BRCA. The breast cancer genome-wide association analyses: BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST, respectively), and by the European Community’s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation, or writing of the report. Genotyping of the OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/A16563 and the PERSPECTIVE project supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344) and, the Ministère de l’Économie, Science et Innovation du Québec through Genome Québec and the PSR-SIIRI-701 grant, and the Quebec Breast Cancer Foundation. Funding for the iCOGS infrastructure came from: the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), 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, and Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. The DRIVE Consortium was funded by U19 CA148065. The Australian Breast Cancer Family Study (ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia), and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]. The Australian Breast Cancer Tissue Bank (ABCTB) is generously supported by the National Health and Medical Research Council of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation. The ACP study is funded by the Breast Cancer Research Trust, UK. The AHS study is supported by the intramural research program of the National Institutes of Health, the National Cancer Institute (grant number Z01-CP010119), and the National Institute of Environmental Health Sciences (grant number Z01-ES049030). The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). The BCEES was funded by the National Health and Medical Research Council, Australia and the Cancer Council Western Australia and acknowledges funding from the National Breast Cancer Foundation (JS). For the BCFR-NY, BCFR-PA, and BCFR-UT this work was supported by grant UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. For BIGGS, ES is supported by NIHR Comprehensive Biomedical Research Centre, Guy’s & St. Thomas’ NHS Foundation Trust in partnership with King’s College London, United Kingdom. IT is supported by the Oxford Biomedical Research Centre. BOCS is supported by funds from Cancer Research UK (C8620/A8372/A15106) and the Institute of Cancer Research (UK). BOCS acknowledges NHS funding to the Royal Marsden/Institute of Cancer Research NIHR Specialist Cancer Biomedical Research Centre. The BREast Oncology GAlician Network (BREOGAN) is funded by Acción Estratégica de Salud del Instituto de Salud Carlos III FIS PI12/02125/Cofinanciado FEDER; Acción Estratégica de Salud del Instituto de Salud Carlos III FIS Intrasalud (PI13/01136); Programa Grupos Emergentes, Cancer Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur. Xerencia de Xestion Integrada de Vigo-SERGAS, Instituto de Salud Carlos III, Spain; Grant 10CSA012E, Consellería de Industria Programa Sectorial de Investigación Aplicada, PEME I + D e I + D Suma del Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia, Spain; Grant EC11-192. Fomento de la Investigación Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and Grant FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). The CAMA study was funded by Consejo Nacional de Ciencia y Tecnología (CONACyT) (SALUD-2002-C01-7462). Sample collection and processing was funded in part by grants from the National Cancer Institute (NCI R01CA120120 and K24CA169004). CBCS is funded by the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health Research. CCGP is supported by funding from the University of Crete. The CECILE study was supported by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l’Alimentation, de l’Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council, and Herlev and Gentofte Hospital. The CNIO-BCS was supported by the Instituto de Salud Carlos III, the Red Temática de Investigación Cooperativa en Cáncer and grants from the Asociación Española Contra el Cáncer and the Fondo de Investigación Sanitario (PI11/00923 and PI12/00070). COLBCCC is supported by the German Cancer Research Center (DKFZ), Heidelberg, Germany. D.T. was in part supported by a postdoctoral fellowship from the Alexander von Humboldt Foundation. The American Cancer Society funds the creation, maintenance, and updating of the CPS-II cohort. The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398, UM1 CA164917, and U01 CA199277). Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. H.A.C eceives support from the Lon V Smith Foundation (LVS39420). The University of Westminster curates the DietCompLyf database funded by Against Breast Cancer Registered Charity No. 1121258 and the NCRN. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by: Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation, the Stavros Niarchos Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). FHRISK is funded from NIHR grant PGfAR 0707-10031. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: Rita K. Schmutzler, Cologne). This work was also funded by the European Regional Development Fund and Free State of Saxony, Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-241202, 713-241202, 14505/2470, and 14575/2470). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0, and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The GEPARSIXTO study was conducted by the German Breast Group GmbH. The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and the German Cancer Research Center (DKFZ). GLACIER was supported by Breast Cancer Now, CRUK and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The HABCS study was supported by the Claudia von Schilling Foundation for Breast Cancer Research, by the Lower Saxonian Cancer Society, and by the Rudolf-Bartling Foundation. The HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, and the Sigrid Juselius Foundation. The HERPACC was supported by MEXT Kakenhi (No. 170150181 and 26253041) from the Ministry of Education, Science, Sports, Culture and Technology of Japan, by a Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from Ministry Health, Labour and Welfare of Japan, by Health and Labour Sciences Research Grants for Research on Applying Health Technology from Ministry Health, Labour and Welfare of Japan, by National Cancer Center Research and Development Fund, and “Practical Research for Innovative Cancer Control (15ck0106177h0001)” from Japan Agency for Medical Research and development, AMED, and Cancer Bio Bank Aichi. The HMBCS was supported by a grant from the Friends of Hannover Medical School and by the Rudolf Bartling Foundation. The HUBCS was supported by a grant from the German Federal Ministry of Research and Education (RUS08/017), and by the Russian Foundation for Basic Research and the Federal Agency for Scientific Organizations for support the Bioresource collections and RFBR grants 14-04-97088, 17-29-06014, and 17-44-020498. ICICLE was supported by Breast Cancer Now, CRUK, and Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (A.L.F.) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer Society, The Gustav V Jubilee foundation and Bert von Kantzows foundation. The KARMA study was supported by Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (E.V.O.) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, and by the strategic funding of the University of Eastern Finland. kConFab is supported by a grant from the National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. Financial support for the AOCS was provided by the United States Army Medical Research and Materiel Command [DAMD17-01-1-0729], Cancer Council Victoria, Queensland Cancer Fund, Cancer Council New South Wales, Cancer Council South Australia, The Cancer Foundation of Western Australia, Cancer Council Tasmania and the National Health and Medical Research Council of Australia (NHMRC; 400413, 400281, 199600). G.C.-T. and P.W. are supported by the NHMRC. RB was a Cancer Institute NSW Clinical Research Fellow. The KOHBRA study was partially supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). LAABC is supported by grants (1RB-0287, 3PB-0102, 5PB-0018, 10PB-0098) from the California Breast Cancer Research Program. Incident breast cancer cases were collected by the USC Cancer Surveillance Program (CSP) which is supported under subcontract by the California Department of Health. The CSP is also part of the National Cancer Institute’s Division of Cancer Prevention and Control Surveillance, Epidemiology, and End Results Program, under contract number N01CN25403. L.M.B.C. is supported by the ‘Stichting tegen Kanker’. D.L. is supported by the FWO. The MABCS study is funded by the Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov” and supported by the German Academic Exchange Program, DAAD. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419, 110826, 110828], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. MBCSG is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5 × 1000”). The MCBCS was supported by the NIH grants CA192393, CA116167, CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], and the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057 and 396414, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. The MEC was support by NIH grants CA63464, CA54281, CA098758, CA132839, and CA164973. The MISS study is supported by funding from ERC-2011-294576 Advanced grant, Swedish Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foundation, Gunnar Nilsson. The MMHS study was supported by NIH grants CA97396, CA128931, CA116201, CA140286, and CA177150. MSKCC is supported by grants from the Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer Genetics Initiative. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. MYBRCA is funded by research grants from the Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Malaysia. MYMAMMO is supported by research grants from Yayasan Sime Darby LPGA Tournament and Malaysian Ministry of Higher Education (RP046B-15HTM). The NBCS has been supported by the Research Council of Norway grant 193387/V50 (to A.-L. Børresen-Dale and V.N. Kristensen) and grant 193387/H10 (to A.-L. Børresen-Dale and V.N. Kristensen), South Eastern Norway Health Authority (grant 39346 to A.-L. Børresen-Dale and 27208 to V.N. Kristensen) and the Norwegian Cancer Society (to A.-L. Børresen-Dale and 419616 - 71248 - PR-2006-0282 to V.N. Kristensen). It has received funding from the K.G. Jebsen Centre for Breast Cancer Research (2012-2015). The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The Northern California Breast Cancer Family Registry (NC-BCFR) and Ontario Familial Breast Cancer Registry (OFBCR) were supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The Carolina Breast Cancer Study was funded by Komen Foundation, the National Cancer Institute (P50 CA058223, U54 CA156733, and U01 CA179715), and the North Carolina University Cancer Research Fund. The NGOBCS was supported by Grants-in-Aid for the Third Term Comprehensive Ten-Year Strategy for Cancer Control from the Ministry of Health, Labor and Welfare of Japan, and for Scientific Research on Priority Areas, 17015049 and for Scientific Research on Innovative Areas, 221S0001, from the Ministry of Education, Culture, Sports, Science, and Technology of Japan. The NHS was supported by NIH grants P01 CA87969, UM1 CA186107, and U19 CA148065. The NHS2 was supported by NIH grants UM1 CA176726 and U19 CA148065. The OBCS was supported by research grants from the Finnish Cancer Foundation, the Academy of Finland (grant number 250083, 122715 and Center of Excellence grant number 251314), the Finnish Cancer Foundation, the Sigrid Juselius Foundation, the University of Oulu, the University of Oulu Support Foundation, and the special Governmental EVO funds for Oulu University Hospital-based research activities. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. Genotyping for PLCO was supported by the Intramural Research Program of the National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. The PLCO is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, National Institutes of Health. The POSH study is funded by Cancer Research UK (grants C1275/A11699, C1275/C22524, C1275/A19187, C1275/A15956, and Breast Cancer Campaign 2010PR62, 2013PR044. PROCAS is funded from NIHR grant PGfAR 0707-10031. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). The SASBAC study was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institute of Health (NIH) and the Susan G. Komen Breast Cancer Foundation. The SBCGS was supported primarily by NIH grants R01CA64277, R01CA148667, UMCA182910, and R37CA70867. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The scientific development and funding of this project were, in part, supported by the Genetic Associations and Mechanisms in Oncology (GAME-ON) Network U19 CA148065. The SBCS was supported by Sheffield Experimental Cancer Medicine Centre and Breast Cancer Now Tissue Bank. The SCCS is supported by a grant from the National Institutes of Health (R01 CA092447). Data on SCCS cancer cases used in this publication were provided by the Alabama Statewide Cancer Registry; Kentucky Cancer Registry, Lexington, KY; Tennessee Department of Health, Office of Cancer Surveillance; Florida Cancer Data System; North Carolina Central Cancer Registry, North Carolina Division of Public Health; Georgia Comprehensive Cancer Registry; Louisiana Tumor Registry; Mississippi Cancer Registry; South Carolina Central Cancer Registry; Virginia Department of Health, Virginia Cancer Registry; Arkansas Department of Health, Cancer Registry, 4815 W. Markham, Little Rock, AR 72205. The Arkansas Central Cancer Registry is fully funded by a grant from National Program of Cancer Registries, Centers for Disease Control and Prevention (CDC). Data on SCCS cancer cases from Mississippi were collected by the Mississippi Cancer Registry which participates in the National Program of Cancer Registries (NPCR) of the Centers for Disease Control and Prevention (CDC). The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the CDC or the Mississippi Cancer Registry. SEARCH is funded by Cancer Research UK [C490/A10124, C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. SEBCS was supported by the BRL (Basic Research Laboratory) program through the National Research Foundation of Korea funded by the Ministry of Education, Science and Technology (2012-0000347). SGBCC is funded by the NUS start-up Grant, National University Cancer Institute Singapore (NCIS) Centre Grant and the NMRC Clinician Scientist Award. Additional controls were recruited by the Singapore Consortium of Cohort Studies-Multi-ethnic cohort (SCCS-MEC), which was funded by the Biomedical Research Council, grant number: 05/1/21/19/425. The Sister Study (SISTER) is supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES049033). The Two Sister Study (2SISTER) was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES102245), and, also by a grant from Susan G. Komen for the Cure, grant FAS0703856. SKKDKFZS is supported by the DKFZ. The SMC is funded by the Swedish Cancer Foundation. The SZBCS was supported by Grant PBZ_KBN_122/P05/2004. The TBCS was funded by The National Cancer Institute, Thailand. The TNBCC was supported by a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation. The TWBCS is supported by the Taiwan Biobank project of the Institute of Biomedical Sciences, Academia Sinica, Taiwan. The UCIBCS component of this research was supported by the NIH [CA58860, CA92044] and the Lon V Smith Foundation [LVS39420]. The UKBGS is funded by Breast Cancer Now and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The US3SS study was supported by Massachusetts (K.M.E., R01CA47305), Wisconsin (P.A.N., R01 CA47147) and New Hampshire (L.T.-E., R01CA69664) centers, and Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The USRT Study was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. The WAABCS study was supported by grants from the National Cancer Institute of the National Institutes of Health (R01 CA89085 and P50 CA125183 and the D43 TW009112 grant), Susan G. Komen (SAC110026), the Dr. Ralph and Marian Falk Medical Research Trust, and the Avon Foundation for Women. The WHI program is funded by the National Heart, Lung, and Blood Institute, the US National Institutes of Health and the US Department of Health and Human Services (HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C). This work was also funded by NCI U19 CA148065-01. D.G.E. is supported by the all Manchester NIHR Biomedical research center Manchester (IS-BRC-1215-20007). HUNBOCS, Hungarian Breast and Ovarian Cancer Study was supported by Hungarian Research Grant KTIA-OTKA CK-80745, NKFI_OTKA K-112228. C.I. received support from the Nontherapeutic Subject Registry Shared Resource at Georgetown University (NIH/NCI P30-CA-51008) and the Jess and Mildred Fisher Center for Hereditary Cancer and Clinical Genomics Research. K.M. is supported by CRUK C18281/A19169. City of Hope Clinical Cancer Community Research Network and the Hereditary Cancer Research Registry, supported in part by Award Number RC4CA153828 (PI: J Weitzel) from the National Cancer Institute and the office of the Directory, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The colorectal cancer genome-wide association analyses: Colorectal Transdisciplinary Study (CORECT): The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CORECT Consortium, nor does mention of trade names, commercial products or organizations imply endorsement by the US Government or the CORECT Consortium. We are incredibly grateful for the contributions of Dr. Brian Henderson and Dr. Roger Green over the course of this study and acknowledge them in memoriam. We are also grateful for support from Daniel and Maryann Fong. ColoCare: we thank the many investigators and staff who made this research possible in ColoCare Seattle and ColoCare Heidelberg. ColoCare was initiated and developed at the Fred Hutchinson Cancer Research Center by Drs. Ulrich and Grady. CCFR: the Colon CFR graciously thanks the generous contributions of their study participants, dedication of study staff, and financial support from the U.S. National Cancer Institute, without which this important registry would not exist. Galeon: GALEON wishes to thank the Department of Surgery of University Hospital of Santiago (CHUS), Sara Miranda Ponte, Carmen M Redondo, and the staff of the Department of Pathology and Biobank of CHUS, Instituto de Investigación Sanitaria de Santiago (IDIS), Instituto de Investigación Sanitaria Galicia Sur (IISGS), SERGAS, Vigo, Spain, and Programa Grupos Emergentes, Cancer Genetics Unit, CHUVI Vigo Hospital, Instituto de Salud Carlos III, Spain. MCCS: this study was made possible by the contribution of many people, including the original investigators and the diligent team who recruited participants and continue to work on follow-up. We would also like to express our gratitude to the many thousands of Melbourne residents who took part in the study and provided blood samples. SEARCH: We acknowledge the contributions of Mitul Shah, Val Rhenius, Sue Irvine, Craig Luccarini, Patricia Harrington, Don Conroy, Rebecca Mayes, and Caroline Baynes. The Swedish low-risk colorectal cancer study: we thank Berith Wejderot and the Swedish low-risk colorectal cancer study group. Genetics & Epidemiology of Colorectal Cancer Consortium (GECCO): we thank all those at the GECCO Coordinating Center for helping bring together the data and people that made this project possible. ASTERISK: we are very grateful to Dr. Bruno Buecher without whom this project would not have existed. We also thank all those who agreed to participate in this study, including the patients and the healthy control persons, as well as all the physicians, technicians and students. DACHS: we thank all participants and cooperating clinicians, and Ute Handte-Daub, Renate Hettler-Jensen, Utz Benscheid, Muhabbet Celik, and Ursula Eilber for excellent technical assistance. HPFS, NHS and PHS: we acknowledge Patrice Soule and Hardeep Ranu of the Dana-Farber Harvard Cancer Center High-Throughput Polymorphism Core who assisted in the genotyping for NHS, HPFS, and PHS under the supervision of Dr. Immaculata Devivo and Dr. David Hunter, Qin (Carolyn) Guo, and Lixue Zhu who assisted in programming for NHS and HPFS and Haiyan Zhang who assisted in programming for the PHS. We thank the participants and staff of the Nurses’ Health Study and the Health Professionals Follow-Up Study, for their valuable contributions as well as the following state cancer registries for their help: A.L., A.Z., A.R., C.A., C.O., C.T., D.E., F.L., G.A., I.D., I.L., I.N., I.A., K.Y., L.A., M.E., M.D., M.A., M.I., N.E., N.H., N.J., N.Y., N.C., N.D., O.H., O.K., O.R., P.A., R.I., S.C., T.N., T.X., V.A., W.A., W.Y. In addition, this study was approved by the Connecticut Department of Public Health (DPH) Human Investigations Committee. Certain data used in this publication were obtained from the DPH. We assume full responsibility for analyses and interpretation of these data. PLCO: we thank Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention, National Cancer Institute, the Screening Center investigators and staff or the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial, Mr. Tom Riley and staff, Information Management Services Inc., Ms. Barbara O’Brien and staff, Westat Inc. and Drs. Bill Kopp, Wen Shao and staff, SAIC-Frederick. Most importantly, we acknowledge the study participants for their contributions for making this study possible. The statements contained herein are solely those of the authors and do not represent or imply concurrence or endorsement by NCI. PMH: we thank the study participants and staff of the Hormones and Colon Cancer study. WHI: we thank the WHI investigators and staff for their dedication, and the study participants for making the program possible. A full listing of WHI investigators can be found at https://cleo.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Short20List.pdf. CORECT: The CORECT Study was supported by the National Cancer Institute, National Institutes of Health (NCI/NIH), U.S. Department of Health and Human Services (grant numbers U19 CA148107, R01 CA81488, P30 CA014089, R01 CA197350; P01 CA196569; and R01 CA201407) and National Institutes of Environmental Health Sciences, National Institutes of Health (grant number T32 ES013678). The ATBC Study was supported by the US Public Health Service contracts (N01-CN-45165, N01-RC-45035, N01-RC-37004, and HHSN261201000006C) from the National Cancer Institute. The Cancer Prevention Study-II Nutrition Cohort is funded by the American Cancer Society. ColoCare: This work was supported by the National Institutes of Health (grant numbers R01 CA189184, U01 CA206110, 2P30CA015704-40 (Gilliland)), the Matthias Lackas-Foundation, the German Consortium for Translational Cancer Research, and the EU TRANSCAN initiative. Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO): funding for GECCO was provided by the National Cancer Institute, National Institutes of Health, U.S. Department of Health and Human Services (grant numbers U01 CA137088, R01 CA059045, and U01 CA164930). This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA015704. The Colon Cancer Family Registry (CFR) Illumina GWAS was supported by funding from the National Cancer Institute, National Institutes of Health (grant numbers U01 CA122839, R01 CA143247). The Colon CFR/CORECT Affymetrix Axiom GWAS and OncoArray GWAS were supported by funding from National Cancer Institute, National Institutes of Health (grant number U19 CA148107 to S.G.). The Colon CFR participant recruitment and collection of data and biospecimens used in this study were supported by the National Cancer Institute, National Institutes of Health (grant number UM1 CA167551) and through cooperative agreements with the following Colon CFR centers: Australasian Colorectal Cancer Family Registry (NCI/NIH grant numbers U01 CA074778 and U01/U24 CA097735), USC Consortium Colorectal Cancer Family Registry (NCI/NIH grant numbers U01/U24 CA074799), Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (NCI/NIH grant number U01/U24 CA074800), Ontario Familial Colorectal Cancer Registry (NCI/NIH grant number U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074794), and University of Hawaii Colorectal Cancer Family Registry (NCI/NIH grant number U01/U24 CA074806), Additional support for case ascertainment was provided from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute to Fred Hutchinson Cancer Research Center (Control Nos. N01-CN-67009 and N01-PC-35142, and Contract No. HHSN2612013000121), the Hawai’i Department of Health (Control Nos. N01-PC-67001 and N01-PC-35137, and Contract No. HHSN26120100037C, and the California Department of Public Health (contracts HHSN261201000035C awarded to the University of Southern California, and the following state cancer registries: A.Z., C.O., M.N., N.C., N.H., and by the Victoria Cancer Registry and Ontario Cancer Registry. ESTHER/VERDI was supported by grants from the Baden–Württemberg Ministry of Science, Research and Arts and the German Cancer Aid. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. GALEON: FIS Intrasalud (PI13/01136). The MCCS was further supported by Australian NHMRC grants 509348, 209057, 251553, and 504711 and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. MSKCC: the work at Sloan Kettering in New York was supported by the Robert and Kate Niehaus Center for Inherited Cancer Genomics and the Romeo Milio Foundation. Moffitt: This work was supported by funding from the National Institutes of Health (grant numbers R01 CA189184, P30 CA076292), Florida Department of Health Bankhead-Coley Grant 09BN-13, and the University of South Florida Oehler Foundation. Moffitt contributions were supported in part by the Total Cancer Care Initiative, Collaborative Data Services Core, and Tissue Core at the H. Lee Moffitt Cancer Center & Research Institute, a National Cancer Institute-designated Comprehensive Cancer Center (grant number P30 CA076292). SEARCH: Cancer Research UK (C490/A16561). The Spanish study was supported by Instituto de Salud Carlos III, co-funded by FEDER funds –a way to build Europe– (grants PI14-613 and PI09-1286), Catalan Government DURSI (grant 2014SGR647), and Junta de Castilla y León (grant LE22A10-2). The Swedish Low-risk Colorectal Cancer Study: the study was supported by grants from the Swedish research council; K2015-55 × -22674-01-4, K2008-55 × -20157-03-3, K2006-72 × -20157-01-2 and the Stockholm County Council (ALF project). CIDR genotyping for the Oncoarray was conducted under contract 268201200008I (to K.D.), through grant 101HG007491-01 (to C.I.A.). The Norris Cotton Cancer Center - P30CA023108, The Quantitative Biology Research Institute - P20GM103534, and the Coordinating Center for Screen Detected Lesions - U01CA196386 also supported efforts of C.I.A. This work was also supported by the National Cancer Institute (grant numbers U01 CA1817700, R01 CA144040). ASTERISK: a Hospital Clinical Research Program (PHRC) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC). COLO2&3: National Institutes of Health (grant number R01 CA060987). DACHS: This work was supported by the German Research Council (BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1, HO 5117/2-1, HE 5998/2-1, KL 2354/3-1, RO 2270/8-1, and BR 1704/17-1), the Interdisciplinary Research Program of the National Center for Tumor Diseases (NCT), Germany, and the German Federal Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01ER1505A, and 01ER1505B). DALS: National Institutes of Health (grant number R01 CA048998 to M.L.S). HPFS is supported by National Institutes of Health (grant numbers P01 CA055075, UM1 CA167552, R01 137178, and P50 CA127003), NHS by the National Institutes of Health (grant numbers UM1 CA186107, R01 CA137178, P01 CA087969, and P50 CA127003), NHSII by the National Institutes of Health (grant numbers R01 050385CA and UM1 CA176726), and PHS by the National Institutes of Health (grant number R01 CA042182). MEC: National Institutes of Health (grant numbers R37 CA054281, P01 CA033619, and R01 CA063464). OFCCR: National Institutes of Health, through funding allocated to the Ontario Registry for Studies of Familial Colorectal Cancer (grant number U01 CA074783); see Colon CFR section above. As subset of ARCTIC, OFCCR is supported by a GL2 grant from the Ontario Research Fund, the Canadian Institutes of Health Research, and the Cancer Risk Evaluation (CaRE) Program grant from the Canadian Cancer Society Research Institute. T.J.H. and B.W.Z. are recipients of Senior Investigator Awards from the Ontario Institute for Cancer Research, through generous support from the Ontario Ministry of Research and Innovation. PLCO: Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Additionally, a subset of control samples was genotyped as part of the Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer GWAS, Colon CGEMS pancreatic cancer scan (PanScan), and the Lung Cancer and Smoking study. The prostate and PanScan study datasets were accessed with appropriate approval through the dbGaP online resource (http://cgems.cancer.gov/data/) accession numbers phs000207.v1.p1 and phs000206.v3.p2, respectively, and the lung datasets were accessed from the dbGaP website (http://www.ncbi.nlm.nih.gov/gap) through accession number phs000093.v2.p2. Funding for the Lung Cancer and Smoking study was provided by National Institutes of Health (NIH), Genes, Environment and Health Initiative (GEI) Z01 CP 010200, NIH U01 HG004446, and NIH GEI U01 HG 004438. For the lung study, the GENEVA Coordinating Center provided assistance with genotype cleaning and general study coordination, 23 and the Johns Hopkins University Center for Inherited Disease Research conducted genotyping. PMH: National Institutes of Health (grant number R01 CA076366). VITAL: National Institutes of Health (grant number K05-CA154337). WHI: The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. The head and neck cancer genome-wide association analyses: The study was supported by NIH/NCI: P50 CA097190, and P30 CA047904, Canadian Cancer Society Research Institute (no. 020214) and Cancer Care Ontario Research Chair to R.H. The Princess Margaret Hospital Head and Neck Cancer Translational Research Program is funded by the Wharton family, Joe’s Team, Gordon Tozer, Bruce Galloway and the Elia family. Geoffrey Liu was supported by the Posluns Family Fund and the Lusi Wong Family Fund at the Princess Margaret Foundation, and the Alan B. Brown Chair in Molecular Genomics. This publication presents data from Head and Neck 5000 (H&N5000). H&N5000 was a component of independent research funded by the UK National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034). The views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. Human papillomavirus (HPV) in H&N5000 serology was supported by a Cancer Research UK Programme Grant, the Integrative Cancer Epidemiology Programme (grant number: C18281/A19169). National Cancer Institute (R01-CA90731); National Institute of Environmental Health Sciences (P30ES10126). The authors thank all the members of the GENCAPO team/The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). CPS-II recruitment and maintenance is supported with intramural research funding from the American Cancer Society. Genotyping performed at the Center for Inherited Disease Research (CIDR) was funded through the U.S. National Institute of Dental and Craniofacial Research (NIDCR) grant 1 × 01HG007780-0. The University of Pittsburgh head and neck cancer case-control study is supported by National Institutes of Health grants P50 CA097190 and P30 CA047904. The Carolina Head and Neck Cancer Study (CHANCE) was supported by the National Cancer Institute (R01-CA90731). The Head and Neck Genome Project (GENCAPO) was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (Grant numbers 04/12054-9 and 10/51168-0). The authors thank all the members of the GENCAPO team. The HN5000 study was funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research scheme (RP-PG-0707-10034), the views expressed in this publication are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. The Toronto study was funded by the Canadian Cancer Society Research Institute (020214) and the National Cancer Institute (U19-CA148127) and the Cancer Care Ontario Research Chair. The alcohol-related cancers and genetic susceptibility study in Europe (ARCAGE) was funded by the European Commission’s 5th Framework Program (QLK1-2001-00182), the Italian Association for Cancer Research, Compagnia di San Paolo/FIRMS, Region Piemonte, and Padova University (CPDA057222). The Rome Study was supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC) IG 2011 10491 and IG2013 14220 to S.B., and Fondazione Veronesi to S.B. The IARC Latin American study was funded by the European Commission INCO-DC programme (IC18-CT97-0222), with additional funding from Fondo para la Investigacion Cientifica y Tecnologica (Argentina) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (01/01768-2). We thank Leticia Fernandez, Instituto Nacional de Oncologia y Radiobiologia, La Habana, Cuba and Sergio and Rosalina Koifman, for their efforts with the IARC Latin America study São Paulo center. The IARC Central Europe study was supported by European Commission’s INCO-COPERNICUS Program (IC15- CT98-0332), NIH/National Cancer Institute grant CA92039, and the World Cancer Research Foundation grant WCRF 99A28. The IARC Oral Cancer Multicenter study was funded by grant S06 96 202489 05F02 from Europe against Cancer; grants FIS 97/0024, FIS 97/0662, and BAE 01/5013 from Fondo de Investigaciones Sanitarias, Spain; the UICC Yamagiwa-Yoshida Memorial International Cancer Study; the National Cancer Institute of Canada; Associazione Italiana per la Ricerca sul Cancro; and the Pan-American Health Organization. Coordination of the EPIC study is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The lung cancer genome-wide association analyses: Transdisciplinary Research for Cancer in Lung (TRICL) of the International Lung Cancer Consortium (ILCCO) was supported by (U19-CA148127, CA148127S1, U19CA203654, and Cancer Prevention Research Institute of Texas RR170048). The ILCCO data harmonization is supported by Cancer Care Ontario Research Chair of Population Studies to R. H. and Lunenfeld-Tanenbaum Research Institute, Sinai Health System. The TRICL-ILCCO OncoArray was supported by in-kind genotyping by the Centre for Inherited Disease Research (26820120008i-0-26800068-1). The CAPUA study was supported by FIS-FEDER/Spain grant numbers FIS-01/310, FIS-PI03-0365, and FIS-07-BI060604, FICYT/Asturias grant numbers FICYT PB02-67 and FICYT IB09-133, and the University Institute of Oncology (IUOPA), of the University of Oviedo and the Ciber de Epidemiologia y Salud Pública. CIBERESP, SPAIN. The work performed in the CARET study was supported by the National Institute of Health/National Cancer Institute: UM1 CA167462 (PI: Goodman), National Institute of Health UO1-CA6367307 (PIs Omen, Goodman); National Institute of Health R01 CA111703 (PI Chen), National Institute of Health 5R01 CA151989-01A1(PI Doherty). The Liverpool Lung project is supported by the Roy Castle Lung Cancer Foundation. The Harvard Lung Cancer Study was supported by the NIH (National Cancer Institute) grants CA092824, CA090578, CA074386. The Multi-ethnic Cohort Study was partially supported by NIH Grants CA164973, CA033619, CA63464, and CA148127. The work performed in MSH-PMH study was supported by The Canadian Cancer Society Research Institute (020214), Ontario Institute of Cancer and Cancer Care Ontario Chair Award to R.J.H. and G.L. and the Alan Brown Chair and Lusi Wong Programs at the Princess Margaret Hospital Foundation. NJLCS was funded by the State Key Program of National Natural Science of China (81230067), the National Key Basic Research Program Grant (2011CB503805), the Major Program of the National Natural Science Foundation of China (81390543). The Norway study was supported by Norwegian Cancer Society, Norwegian Research Council. The Shanghai Cohort Study (SCS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The Singapore Chinese Health Study (SCHS) was supported by National Institutes of Health R01 CA144034 (PI: Yuan) and UM1 CA182876 (PI: Yuan). The work in TLC study has been supported in part the James & Esther King Biomedical Research Program (09KN-15), National Institutes of Health Specialized Programs of Research Excellence (SPORE) Grant (P50 CA119997), and by a Cancer Center Support Grant (CCSG) at the H. Lee Moffitt Cancer Center and Research Institute, an NCI designated Comprehensive Cancer Center (grant number P30-CA76292). The Vanderbilt Lung Cancer Study—BioVU dataset used for the analyses described was obtained from Vanderbilt University Medical Center’s BioVU, which is supported by institutional funding, the 1S10RR025141-01 instrumentation award, and by the Vanderbilt CTSA grant UL1TR000445 from NCATS/NIH. Dr. Aldrich was supported by NIH/National Cancer Institute K07CA172294 (PI: Aldrich) and Dr. Bush was supported by NHGRI/NIH U01HG004798 (PI: Crawford). The Copenhagen General Population Study (CGPS) was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council and Herlev Hospital. The NELCS study: Grant Number P20RR018787 from the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). The Kentucky Lung Cancer Research Initiative was supported by the Department of Defense [Congressionally Directed Medical Research Program, U.S. Army Medical Research and Materiel Command Program] under award number: 10153006 (W81XWH-11-1-0781). Views and opinions of, and endorsements by the author(s) do not reflect those of the US Army or the Department of Defense. This research was also supported by unrestricted infrastructure funds from the UK Center for Clinical and Translational Science, NIH grant UL1TR000117 and Markey Cancer Center NCI Cancer Center Support Grant (P30 CA177558) Shared Resource Facilities: Cancer Research Informatics, Biospecimen and Tissue Procurement, and Biostatistics and Bioinformatics. The M.D. Anderson Cancer Center study was supported in part by grants from the NIH (P50 CA070907, R01 CA176568) (to X.W.), Cancer Prevention & Research Institute of Texas (RP130502) (to X.W.), and The University of Texas MD Anderson Cancer Center institutional support for the Center for Translational and Public Health Genomics. The deCODE study of smoking and nicotine dependence was funded in part by a grant from NIDA (R01- DA017932). The study in Lodz center was partially funded by Nofer Institute of Occupational Medicine, under task NIOM 10.13: Predictors of mortality from non-small cell lung cancer—field study. Genetic sharing analysis was funded by NIH grant CA194393. The research undertaken by M.D.T., L.V.W., and M.S.A. was partly funded by the National Institute for Health Research (NIHR). The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. M.D.T. holds a Medical Research Council Senior Clinical Fellowship (G0902313). The work to assemble the FTND GWAS meta-analysis was supported by the National Institutes of Health (NIH), National Institute on Drug Abuse (NIDA) grant number R01 DA035825 (Principal Investigator [PI]: DBH). The study populations included COGEND (dbGaP phs000092.v1.p1 and phs000404.v1.p1), COPDGene (dbGaP phs000179.v3.p2), deCODE Genetics, EAGLE (dbGaP phs000093.vs.p2), and SAGE. dbGaP phs000092.v1.p1). See Hancock et al. Transl Psychiatry 2015 (PMCID: PMC4930126) for the full listing of funding sources and other acknowledgments. The Resource for the Study of Lung Cancer Epidemiology in North Trent (ReSoLuCENT)study was funded by the Sheffield Hospitals Charity, Sheffield Experimental Cancer Medicine Centre and Weston Park Hospital Cancer Charity. The ovarian cancer genome-wide association analysis: The Ovarian Cancer Association Consortium (OCAC) is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were in part supported by the US National Cancer Institute GAME-ON Post-GWAS Initiative (U19-CA148112). This study made use of data generated by the Wellcome Trust Case Control consortium that was funded by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute (dbGap accession number phs000178.v8.p7). The OCAC OncoArray genotyping project was funded through grants from the U.S. National Institutes of Health (CA1X01HG007491-01 (C.I.A.), U19-CA148112 (T.A.S.), R01-CA149429 (C.M.P.), and R01-CA058598 (M.T.G.); Canadian Institutes of Health Research (MOP-86727 (L.E.K.) and the Ovarian Cancer Research Fund (A.B.). The COGS project was funded through a European Commission’s Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175) and through a grant from the U.S. National Institutes of Health (R01-CA122443 (E.L.G)). Funding for individual studies: AAS: National Institutes of Health (RO1-CA142081); AOV: The Canadian Institutes for Health Research (MOP-86727); AUS: The Australian Ovarian Cancer Study Group was supported by the U.S. Army Medical Research and Materiel Command (DAMD17-01-1-0729), National Health & Medical Research Council of Australia (199600, 400413 and 400281), Cancer Councils of New South Wales, Victoria, Queensland, South Australia and Tasmania and Cancer Foundation of Western Australia (Multi-State Applications 191, 211, and 182). The Australian Ovarian Cancer Study gratefully acknowledges additional support from Ovarian Cancer Australia and the Peter MacCallum Foundation; BAV: ELAN Funds of the University of Erlangen-Nuremberg; BEL: National Kankerplan; BGS: Breast Cancer Now, Institute of Cancer Research; BVU: Vanderbilt CTSA grant from the National Institutes of Health (NIH)/National Center for Advancing Translational Sciences (NCATS) (ULTR000445); CAM: National Institutes of Health Research Cambridge Biomedical Research Centre and Cancer Research UK Cambridge Cancer Centre; CHA: Innovative Research Team in University (PCSIRT) in China (IRT1076); CNI: Instituto de Salud Carlos III (PI12/01319); Ministerio de Economía y Competitividad (SAF2012); COE: Department of Defense (W81XWH-11-2-0131); CON: National Institutes of Health (R01-CA063678, R01-CA074850; and R01-CA080742); DKE: Ovarian Cancer Research Fund; DOV: National Institutes of Health R01-CA112523 and R01-CA87538; EMC: Dutch Cancer Society (EMC 2014-6699); EPC: The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); ERC-2009-AdG 232997 and Nordforsk, Nordic Centre of Excellence programme on Food, Nutrition and Health (Norway); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom); GER: German Federal Ministry of Education and Research, Programme of Clinical Biomedical Research (01 GB 9401) and the German Cancer Research Center (DKFZ); GRC: This research has been co-financed by the European Union (European Social Fund—ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)—Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund; GRR: Roswell Park Cancer Institute Alliance Foundation, P30 CA016056; HAW: U.S. National Institutes of Health (R01-CA58598, N01-CN-55424, and N01-PC-67001); HJO: Intramural funding; Rudolf-Bartling Foundation; HMO: Intramural funding; Rudolf-Bartling Foundation; HOC: Helsinki University Research Fund; HOP: Department of Defense (DAMD17-02-1-0669) and NCI (K07-CA080668, R01-CA95023, P50-CA159981 MO1-RR000056 R01-CA126841); HUO: Intramural funding; Rudolf-Bartling Foundation; JGO: JSPS KAKENHI grant; JPN: Grant-in-Aid for the Third Term Comprehensive 10-Year Strategy for Cancer Control from the Ministry of Health, Labour and Welfare; KRA: This study (Ko-EVE) was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 0920010); LAX: American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124; LUN: ERC-2011-AdG 294576-risk factors cancer, Swedish Cancer Society, Swedish Research Council, Beta Kamprad Foundation; MAC: National Institutes of Health (R01-CA122443, P30-CA15083, P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; Fraternal Order of Eagles; MAL: Funding for this study was provided by research grant R01- CA61107 from the National Cancer Institute, Bethesda, MD, research grant 94 222 52 from the Danish Cancer Society, Copenhagen, Denmark; and the Mermaid I project; MAS: Malaysian Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation; MAY: National Institutes of Health (R01-CA122443, P30-CA15083, and P50-CA136393); Mayo Foundation; Minnesota Ovarian Cancer Alliance; Fred C. and Katherine B. Andersen Foundation; MCC: Cancer Council Victoria, National Health and Medical Research Council of Australia (NHMRC) grants number 209057, 251533, 396414, and 504715; MDA: DOD Ovarian Cancer Research Program (W81XWH-07-0449); MEC: NIH (CA54281, CA164973, CA63464); MOF: Moffitt Cancer Center, Merck Pharmaceuticals, the state of Florida, Hillsborough County, and the city of Tampa; NCO: National Institutes of Health (R01-CA76016) and the Department of Defense (DAMD17-02-1-0666); NEC: National Institutes of Health R01-CA54419 and P50-CA105009 and Department of Defense W81XWH-10-1-02802; NHS: UM1 CA186107, P01 CA87969, R01 CA49449, R01-CA67262, UM1 CA176726; NJO: National Cancer Institute (NIH-K07 CA095666, R01-CA83918, NIH-K22-CA138563, and P30-CA072720) and the Cancer Institute of New Jersey; If Sara Olson and/or Irene Orlow is a co-author, please add NCI CCSG award (P30-CA008748) to the funding sources; NOR: Helse Vest, The Norwegian Cancer Society, The Research Council of Norway; NTH: Radboud University Medical Centre; OPL: National Health and Medical Research Council (NHMRC) of Australia (APP1025142) and Brisbane Women’s Club; ORE: OHSU Foundation; OVA: This work was supported by Canadian Institutes of Health Research grant (MOP-86727) and by NIH/NCI 1 R01CA160669-01A1; PLC: Intramural Research Program of the National Cancer Institute; POC: Pomeranian Medical University; POL: Intramural Research Program of the National Cancer Institute; PVD: Canadian Cancer Society and Cancer Research Society GRePEC Program; RBH: National Health and Medical Research Council of Australia; RMH: Cancer Research UK, Royal Marsden Hospital; RPC: National Institute of Health (P50-CA159981, R01-CA126841); SEA: Cancer Research UK (C490/A10119 C490/A10124); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; SIS: NIH, National Institute of Environmental Health Sciences, Z01-ES044005 and Z01-ES049033; SMC: The bbSwedish Research Council-SIMPLER infrastructure; the Swedish Cancer Foundation; SON: National Health Research and Development Program, Health Canada, grant 6613-1415-53; SRO: Cancer Research UK (C536/A13086, C536/A6689) and Imperial Experimental Cancer Research Centre (C1312/A15589); STA: NIH grants U01 CA71966 and U01 CA69417; SWE: Swedish Cancer foundation, WeCanCureCancer and VårKampMotCancer foundation; SWH: NIH (NCI) grant R37-CA070867; TBO: National Institutes of Health (R01-CA106414-A2), American Cancer Society (CRTG-00-196-01-CCE), Department of Defense (DAMD17-98-1-8659), Celma Mastery Ovarian Cancer Foundation; TOR: NIH grants R01-CA063678 and R01 CA063682; UCI: NIH R01-CA058860 and the Lon V Smith Foundation grant LVS39420; UHN: Princess Margaret Cancer Centre Foundation-Bridge for the Cure; UKO: The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre; UKR: Cancer Research UK (C490/A6187), UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge; USC: P01CA17054, P30CA14089, R01CA61132, N01PC67010, R03CA113148, R03CA115195, N01CN025403, and California Cancer Research Program (00-01389V-20170, 2II0200); VAN: BC Cancer Foundation, VGH & UBC Hospital Foundation; VTL: NIH K05-CA154337; WMH: National Health and Medical Research Council of Australia, Enabling Grants ID 310670 & ID 628903. Cancer Institute NSW Grants 12/RIG/1-17 & 15/RIG/1-16; WOC: National Science Centren (N N301 5645 40). The Maria Sklodowska-Curie Memorial Cancer Center and Institute of Oncology, Warsaw, Poland. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academia Reserve. The prostate cancer genome-wide association analyses: we pay tribute to Brian Henderson, who was a driving force behind the OncoArray project, for his vision and leadership, and who sadly passed away before seeing its fruition. We also thank the individuals who participated in these studies enabling this work. The ELLIPSE/PRACTICAL (http//:practical.icr.ac.uk) prostate cancer consortium and his collaborating partners were supported by multiple funding mechanisms enabling this current work. ELLIPSE/PRACTICAL Genotyping of the OncoArray was funded by the US National Institutes of Health (NIH) (U19 CA148537 for ELucidating Loci Involved in Prostate Cancer SuscEptibility (ELLIPSE) project and X01HG007492 to the Center for Inherited Disease Research (CIDR) under contract number HHSN268201200008I). Additional analytical support was provided by NIH NCI U01 CA188392 (F.R.S.). Funding for the iCOGS infrastructure came from the European Community’s Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, and C8197/A16565), 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 Defense (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. This work was supported by the Canadian Institutes of Health Research, European Commission’s Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C1287/A16563, C5047/A3354, C5047/A10692, C16913/A6135, C5047/A21332 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative grant: No. 1 U19 CA148537-01 (the GAME-ON initiative). We also thank the following for funding support: The Institute of Cancer Research and The Everyman Campaign, The Prostate Cancer Research Foundation, Prostate Research Campaign UK (now Prostate Action), The Orchid Cancer Appeal, The National Cancer Research Network UK, and The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The Prostate Cancer Program of Cancer Council Victoria also acknowledge grant support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394, and 614296), VicHealth, Cancer Council Victoria, The Prostate Cancer Foundation of Australia, The Whitten Foundation, PricewaterhouseCoopers, and Tattersall’s. E.A.O., D.M.K., and E.M.K. acknowledge the Intramural Program of the National Human Genome Research Institute for their support. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01-CA98233 to D.J.H., U01-CA98710 to S.M.G., U01-CA98216 to E.R., and U01-CA98758 to B.E.H., and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). CAPS GWAS study was supported by the Swedish Cancer Foundation (grant no 09-0677, 11-484, 12-823), the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant no K2010-70 × -20430-04-3, 2014-2269). The Hannover Prostate Cancer Study was supported by the Lower Saxonian Cancer Society. PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. RAPPER was supported by the NIHR Manchester Biomedical Research Center, Cancer Research UK (C147/A25254, C1094/A18504) and the EU’s 7th Framework Programme Grant/Agreement no 60186. Overall: this research has been conducted using the UK Biobank Resource (application number 16549). NHS is supported by UM1 CA186107 (NHS cohort infrastructure grant), P01 CA87969, and R01 CA49449. NHSII is supported by UM1 CA176726 (NHSII cohort infrastructure grant), and R01-CA67262. A.L.K. is supported by R01 MH107649. We would like to thank the participants and staff of the NHS and NHSII for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data.

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2019

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