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1.  Y chromosome haplogroups and prostate cancer in populations of European and Ashkenazi Jewish ancestry 
Human Genetics  2012;131(7):1173-1185.
Genetic variation on the Y chromosome has not been convincingly implicated in prostate cancer risk. To comprehensively analyze the role of inherited Y chromosome variation in prostate cancer risk in individuals of European ancestry, we genotyped 34 binary Y chromosome markers in 3,995 prostate cancer cases and 3,815 control subjects drawn from four studies. In this set, we identified nominally significant association between a rare haplogroup, E1b1b1c, and prostate cancer in stage I (P = 0.012, OR = 0.51; 95% confidence interval 0.30–0.87). Population substructure of E1b1b1c carriers suggested Ashkenazi Jewish ancestry, prompting a replication phase in individuals of both European and Ashkenazi Jewish ancestry. The association was not significant for prostate cancer overall in studies of either Ashkenazi Jewish (1,686 cases and 1,597 control subjects) or European (686 cases and 734 control subjects) ancestry (Pmeta = 0.078), but a meta-analysis of stage I and II studies revealed a nominally significant association with prostate cancer risk (Pmeta = 0.010, OR = 0.77; 95% confidence interval 0.62–0.94). Comparing haplogroup frequencies between studies, we noted strong similarities between those conducted in the US and France, in which the majority of men carried R1 haplogroups, resembling Northwestern European populations. On the other hand, Finns had a remarkably different haplogroup distribution with a preponderance of N1c and I1 haplogroups. In summary, our results suggest that inherited Y chromosome variation plays a limited role in prostate cancer etiology in European populations but warrant follow-up in additional large and well characterized studies of multiple ethnic backgrounds.
Electronic supplementary material
The online version of this article (doi:10.1007/s00439-012-1139-5) contains supplementary material, which is available to authorized users.
doi:10.1007/s00439-012-1139-5
PMCID: PMC3374121  PMID: 22271044
2.  Fine Mapping of 14q24.1 Breast Cancer Susceptibility Locus 
Human genetics  2011;131(3):479-490.
In the National Cancer Institute Cancer Genetic Markers of Susceptibility (CGEMS) genome-wide association study of breast cancer, a single nucleotide polymorphism (SNP) marker, rs999737, in the 14q24.1 interval, was associated with breast cancer risk. In order to fine map this region, we imputed a 3.93MB region flanking rs999737 for Stages 1 and 2 of the CGEMS study (5,692 cases, 5,576 controls) using the combined reference panels of the HapMap 3 and the 1000 Genomes Project. Single-marker association testing and variable-sized sliding-window haplotype analysis were performed, and for both analyses the initial tagging SNP rs999737 retained the strongest association with breast cancer risk. Investigation of contiguous regions did not reveal evidence for an additional independent signal. Therefore, we conclude that rs999737 is an optimal tag SNP for common variants in the 14q24.1 region and thus narrow the candidate variants that should be investigated in follow-up laboratory evaluation.
doi:10.1007/s00439-011-1088-4
PMCID: PMC4159746  PMID: 21959381
RAD51L1; breast cancer; genome-wide association study; fine-mapping; imputation
3.  Public health benefits of strategies to reduce greenhouse-gas emissions: health implications of short-lived greenhouse pollutants 
Lancet  2009;374(9707):2091-2103.
In this report we review the health effects of three short-lived greenhouse pollutants—black carbon, ozone, and sulphates. We undertook new meta-analyses of existing time-series studies and an analysis of a cohort of 352 000 people in 66 US cities during 18 years of follow-up. This cohort study provides estimates of mortality effects from long-term exposure to elemental carbon, an indicator of black carbon mass, and evidence that ozone exerts an independent risk of mortality. Associations among these pollutants make drawing conclusions about their individual health effects difficult at present, but sulphate seems to have the most robust effects in multiple-pollutant models. Generally, the toxicology of the pure compounds and their epidemiology diverge because atmospheric black carbon, ozone, and sulphate are associated and could interact with related toxic species. Although sulphate is a cooling agent, black carbon and ozone could together exert nearly half as much global warming as carbon dioxide. The complexity of these health and climate effects needs to be recognised in mitigation policies.
doi:10.1016/S0140-6736(09)61716-5
PMCID: PMC4059357  PMID: 19942276
4.  Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution 
Context
Associations have been found between day-to-day particulate air pollution and increased risk of various adverse health outcomes, including cardiopulmonary mortality. However, studies of health effects of long-term particulate air pollution have been less conclusive.
Objective
To assess the relationship between long-term exposure to fine particulate air pollution and all-cause, lung cancer, and cardiopulmonary mortality.
Design, Setting, and Participants
Vital status and cause of death data were collected by the American Cancer Society as part of the Cancer Prevention II study, an ongoing prospective mortality study, which enrolled approximately 1.2 million adults in 1982. Participants completed a questionnaire detailing individual risk factor data (age, sex, race, weight, height, smoking history, education, marital status, diet, alcohol consumption, and occupational exposures). The risk factor data for approximately 500000 adults were linked with air pollution data for metropolitan areas throughout the United States and combined with vital status and cause of death data through December 31, 1998.
Main Outcome Measure
All-cause, lung cancer, and cardiopulmonary mortality.
Results
Fine particulate and sulfur oxide–related pollution were associated with all-cause, lung cancer, and cardiopulmonary mortality. Each 10-μg/m3 elevation in fine particulate air pollution was associated with approximately a 4%, 6%, and 8% increased risk of all-cause, cardiopulmonary, and lung cancer mortality, respectively. Measures of coarse particle fraction and total suspended particles were not consistently associated with mortality.
Conclusion
Long-term exposure to combustion-related fine particulate air pollution is an important environmental risk factor for cardiopulmonary and lung cancer mortality.
PMCID: PMC4037163  PMID: 11879110
5.  A meta-analysis of genome-wide association studies to identify prostate cancer susceptibility loci associated with aggressive and non-aggressive disease 
Amin Al Olama, Ali | Kote-Jarai, Zsofia | Schumacher, Fredrick R. | Wiklund, Fredrik | Berndt, Sonja I. | Benlloch, Sara | Giles, Graham G. | Severi, Gianluca | Neal, David E. | Hamdy, Freddie C. | Donovan, Jenny L. | Hunter, David J. | Henderson, Brian E. | Thun, Michael J. | Gaziano, Michael | Giovannucci, Edward L. | Siddiq, Afshan | Travis, Ruth C. | Cox, David G. | Canzian, Federico | Riboli, Elio | Key, Timothy J. | Andriole, Gerald | Albanes, Demetrius | Hayes, Richard B. | Schleutker, Johanna | Auvinen, Anssi | Tammela, Teuvo L.J. | Weischer, Maren | Stanford, Janet L. | Ostrander, Elaine A. | Cybulski, Cezary | Lubinski, Jan | Thibodeau, Stephen N. | Schaid, Daniel J. | Sorensen, Karina D. | Batra, Jyotsna | Clements, Judith A. | Chambers, Suzanne | Aitken, Joanne | Gardiner, Robert A. | Maier, Christiane | Vogel, Walther | Dörk, Thilo | Brenner, Hermann | Habuchi, Tomonori | Ingles, Sue | John, Esther M. | Dickinson, Joanne L. | Cannon-Albright, Lisa | Teixeira, Manuel R. | Kaneva, Radka | Zhang, Hong-Wei | Lu, Yong-Jie | Park, Jong Y. | Cooney, Kathleen A. | Muir, Kenneth R. | Leongamornlert, Daniel A. | Saunders, Edward | Tymrakiewicz, Malgorzata | Mahmud, Nadiya | Guy, Michelle | Govindasami, Koveela | O'Brien, Lynne T. | Wilkinson, Rosemary A. | Hall, Amanda L. | Sawyer, Emma J. | Dadaev, Tokhir | Morrison, Jonathan | Dearnaley, David P. | Horwich, Alan | Huddart, Robert A. | Khoo, Vincent S. | Parker, Christopher C. | Van As, Nicholas | Woodhouse, Christopher J. | Thompson, Alan | Dudderidge, Tim | Ogden, Chris | Cooper, Colin S. | Lophatonanon, Artitaya | Southey, Melissa C. | Hopper, John L. | English, Dallas | Virtamo, Jarmo | Le Marchand, Loic | Campa, Daniele | Kaaks, Rudolf | Lindstrom, Sara | Diver, W. Ryan | Gapstur, Susan | Yeager, Meredith | Cox, Angela | Stern, Mariana C. | Corral, Roman | Aly, Markus | Isaacs, William | Adolfsson, Jan | Xu, Jianfeng | Zheng, S. Lilly | Wahlfors, Tiina | Taari, Kimmo | Kujala, Paula | Klarskov, Peter | Nordestgaard, Børge G. | Røder, M. Andreas | Frikke-Schmidt, Ruth | Bojesen, Stig E. | FitzGerald, Liesel M. | Kolb, Suzanne | Kwon, Erika M. | Karyadi, Danielle M. | Orntoft, Torben Falck | Borre, Michael | Rinckleb, Antje | Luedeke, Manuel | Herkommer, Kathleen | Meyer, Andreas | Serth, Jürgen | Marthick, James R. | Patterson, Briony | Wokolorczyk, Dominika | Spurdle, Amanda | Lose, Felicity | McDonnell, Shannon K. | Joshi, Amit D. | Shahabi, Ahva | Pinto, Pedro | Santos, Joana | Ray, Ana | Sellers, Thomas A. | Lin, Hui-Yi | Stephenson, Robert A. | Teerlink, Craig | Muller, Heiko | Rothenbacher, Dietrich | Tsuchiya, Norihiko | Narita, Shintaro | Cao, Guang-Wen | Slavov, Chavdar | Mitev, Vanio | Chanock, Stephen | Gronberg, Henrik | Haiman, Christopher A. | Kraft, Peter | Easton, Douglas F. | Eeles, Rosalind A.
Human Molecular Genetics  2012;22(2):408-415.
Genome-wide association studies (GWAS) have identified multiple common genetic variants associated with an increased risk of prostate cancer (PrCa), but these explain less than one-third of the heritability. To identify further susceptibility alleles, we conducted a meta-analysis of four GWAS including 5953 cases of aggressive PrCa and 11 463 controls (men without PrCa). We computed association tests for approximately 2.6 million SNPs and followed up the most significant SNPs by genotyping 49 121 samples in 29 studies through the international PRACTICAL and BPC3 consortia. We not only confirmed the association of a PrCa susceptibility locus, rs11672691 on chromosome 19, but also showed an association with aggressive PrCa [odds ratio = 1.12 (95% confidence interval 1.03–1.21), P = 1.4 × 10−8]. This report describes a genetic variant which is associated with aggressive PrCa, which is a type of PrCa associated with a poorer prognosis.
doi:10.1093/hmg/dds425
PMCID: PMC3526158  PMID: 23065704
6.  A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11 
Siddiq, Afshan | Couch, Fergus J. | Chen, Gary K. | Lindström, Sara | Eccles, Diana | Millikan, Robert C. | Michailidou, Kyriaki | Stram, Daniel O. | Beckmann, Lars | Rhie, Suhn Kyong | Ambrosone, Christine B. | Aittomäki, Kristiina | Amiano, Pilar | Apicella, Carmel | Baglietto, Laura | Bandera, Elisa V. | Beckmann, Matthias W. | Berg, Christine D. | Bernstein, Leslie | Blomqvist, Carl | Brauch, Hiltrud | Brinton, Louise | Bui, Quang M. | Buring, Julie E. | Buys, Saundra S. | Campa, Daniele | Carpenter, Jane E. | Chasman, Daniel I. | Chang-Claude, Jenny | Chen, Constance | Clavel-Chapelon, Françoise | Cox, Angela | Cross, Simon S. | Czene, Kamila | Deming, Sandra L. | Diasio, Robert B. | Diver, W. Ryan | Dunning, Alison M. | Durcan, Lorraine | Ekici, Arif B. | Fasching, Peter A. | Feigelson, Heather Spencer | Fejerman, Laura | Figueroa, Jonine D. | Fletcher, Olivia | Flesch-Janys, Dieter | Gaudet, Mia M. | Gerty, Susan M. | Rodriguez-Gil, Jorge L. | Giles, Graham G. | van Gils, Carla H. | Godwin, Andrew K. | Graham, Nikki | Greco, Dario | Hall, Per | Hankinson, Susan E. | Hartmann, Arndt | Hein, Rebecca | Heinz, Judith | Hoover, Robert N. | Hopper, John L. | Hu, Jennifer J. | Huntsman, Scott | Ingles, Sue A. | Irwanto, Astrid | Isaacs, Claudine | Jacobs, Kevin B. | John, Esther M. | Justenhoven, Christina | Kaaks, Rudolf | Kolonel, Laurence N. | Coetzee, Gerhard A. | Lathrop, Mark | Le Marchand, Loic | Lee, Adam M. | Lee, I-Min | Lesnick, Timothy | Lichtner, Peter | Liu, Jianjun | Lund, Eiliv | Makalic, Enes | Martin, Nicholas G. | McLean, Catriona A. | Meijers-Heijboer, Hanne | Meindl, Alfons | Miron, Penelope | Monroe, Kristine R. | Montgomery, Grant W. | Müller-Myhsok, Bertram | Nickels, Stefan | Nyante, Sarah J. | Olswold, Curtis | Overvad, Kim | Palli, Domenico | Park, Daniel J. | Palmer, Julie R. | Pathak, Harsh | Peto, Julian | Pharoah, Paul | Rahman, Nazneen | Rivadeneira, Fernando | Schmidt, Daniel F. | Schmutzler, Rita K. | Slager, Susan | Southey, Melissa C. | Stevens, Kristen N. | Sinn, Hans-Peter | Press, Michael F. | Ross, Eric | Riboli, Elio | Ridker, Paul M. | Schumacher, Fredrick R. | Severi, Gianluca | dos Santos Silva, Isabel | Stone, Jennifer | Sund, Malin | Tapper, William J. | Thun, Michael J. | Travis, Ruth C. | Turnbull, Clare | Uitterlinden, Andre G. | Waisfisz, Quinten | Wang, Xianshu | Wang, Zhaoming | Weaver, JoEllen | Schulz-Wendtland, Rüdiger | Wilkens, Lynne R. | Van Den Berg, David | Zheng, Wei | Ziegler, Regina G. | Ziv, Elad | Nevanlinna, Heli | Easton, Douglas F. | Hunter, David J. | Henderson, Brian E. | Chanock, Stephen J. | Garcia-Closas, Montserrat | Kraft, Peter | Haiman, Christopher A. | Vachon, Celine M.
Human Molecular Genetics  2012;21(24):5373-5384.
Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10-5 in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10−8) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10–6) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10−9), and with both ER-positive (OR = 1.09; P = 1.5 × 10−5) and ER-negative (OR = 1.16, P = 2.5 × 10−7) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.
doi:10.1093/hmg/dds381
PMCID: PMC3510753  PMID: 22976474
7.  A Meta-Analysis Identifies New Loci Associated with Body Mass index in Individuals of African Ancestry 
Monda, Keri L. | Chen, Gary K. | Taylor, Kira C. | Palmer, Cameron | Edwards, Todd L. | Lange, Leslie A. | Ng, Maggie C.Y. | Adeyemo, Adebowale A. | Allison, Matthew A. | Bielak, Lawrence F. | Chen, Guanji | Graff, Mariaelisa | Irvin, Marguerite R. | Rhie, Suhn K. | Li, Guo | Liu, Yongmei | Liu, Youfang | Lu, Yingchang | Nalls, Michael A. | Sun, Yan V. | Wojczynski, Mary K. | Yanek, Lisa R. | Aldrich, Melinda C. | Ademola, Adeyinka | Amos, Christopher I. | Bandera, Elisa V. | Bock, Cathryn H. | Britton, Angela | Broeckel, Ulrich | Cai, Quiyin | Caporaso, Neil E. | Carlson, Chris | Carpten, John | Casey, Graham | Chen, Wei-Min | Chen, Fang | Chen, Yii-Der I. | Chiang, Charleston W.K. | Coetzee, Gerhard A. | Demerath, Ellen | Deming-Halverson, Sandra L. | Driver, Ryan W. | Dubbert, Patricia | Feitosa, Mary F. | Freedman, Barry I. | Gillanders, Elizabeth M. | Gottesman, Omri | Guo, Xiuqing | Haritunians, Talin | Harris, Tamara | Harris, Curtis C. | Hennis, Anselm JM | Hernandez, Dena G. | McNeill, Lorna H. | Howard, Timothy D. | Howard, Barbara V. | Howard, Virginia J. | Johnson, Karen C. | Kang, Sun J. | Keating, Brendan J. | Kolb, Suzanne | Kuller, Lewis H. | Kutlar, Abdullah | Langefeld, Carl D. | Lettre, Guillaume | Lohman, Kurt | Lotay, Vaneet | Lyon, Helen | Manson, JoAnn E. | Maixner, William | Meng, Yan A. | Monroe, Kristine R. | Morhason-Bello, Imran | Murphy, Adam B. | Mychaleckyj, Josyf C. | Nadukuru, Rajiv | Nathanson, Katherine L. | Nayak, Uma | N’Diaye, Amidou | Nemesure, Barbara | Wu, Suh-Yuh | Leske, M. Cristina | Neslund-Dudas, Christine | Neuhouser, Marian | Nyante, Sarah | Ochs-Balcom, Heather | Ogunniyi, Adesola | Ogundiran, Temidayo O. | Ojengbede, Oladosu | Olopade, Olufunmilayo I. | Palmer, Julie R. | Ruiz-Narvaez, Edward A. | Palmer, Nicholette D. | Press, Michael F. | Rampersaud, Evandine | Rasmussen-Torvik, Laura J. | Rodriguez-Gil, Jorge L. | Salako, Babatunde | Schadt, Eric E. | Schwartz, Ann G. | Shriner, Daniel A. | Siscovick, David | Smith, Shad B. | Wassertheil-Smoller, Sylvia | Speliotes, Elizabeth K. | Spitz, Margaret R. | Sucheston, Lara | Taylor, Herman | Tayo, Bamidele O. | Tucker, Margaret A. | Van Den Berg, David J. | Velez Edwards, Digna R. | Wang, Zhaoming | Wiencke, John K. | Winkler, Thomas W. | Witte, John S. | Wrensch, Margaret | Wu, Xifeng | Yang, James J. | Levin, Albert M. | Young, Taylor R. | Zakai, Neil A. | Cushman, Mary | Zanetti, Krista A. | Zhao, Jing Hua | Zhao, Wei | Zheng, Yonglan | Zhou, Jie | Ziegler, Regina G. | Zmuda, Joseph M. | Fernandes, Jyotika K. | Gilkeson, Gary S. | Kamen, Diane L. | Hunt, Kelly J. | Spruill, Ida J. | Ambrosone, Christine B. | Ambs, Stefan | Arnett, Donna K. | Atwood, Larry | Becker, Diane M. | Berndt, Sonja I. | Bernstein, Leslie | Blot, William J. | Borecki, Ingrid B. | Bottinger, Erwin P. | Bowden, Donald W. | Burke, Gregory | Chanock, Stephen J. | Cooper, Richard S. | Ding, Jingzhong | Duggan, David | Evans, Michele K. | Fox, Caroline | Garvey, W. Timothy | Bradfield, Jonathan P. | Hakonarson, Hakon | Grant, Struan F.A. | Hsing, Ann | Chu, Lisa | Hu, Jennifer J. | Huo, Dezheng | Ingles, Sue A. | John, Esther M. | Jordan, Joanne M. | Kabagambe, Edmond K. | Kardia, Sharon L.R. | Kittles, Rick A. | Goodman, Phyllis J. | Klein, Eric A. | Kolonel, Laurence N. | Le Marchand, Loic | Liu, Simin | McKnight, Barbara | Millikan, Robert C. | Mosley, Thomas H. | Padhukasahasram, Badri | Williams, L. Keoki | Patel, Sanjay R. | Peters, Ulrike | Pettaway, Curtis A. | Peyser, Patricia A. | Psaty, Bruce M. | Redline, Susan | Rotimi, Charles N. | Rybicki, Benjamin A. | Sale, Michèle M. | Schreiner, Pamela J. | Signorello, Lisa B. | Singleton, Andrew B. | Stanford, Janet L. | Strom, Sara S. | Thun, Michael J. | Vitolins, Mara | Zheng, Wei | Moore, Jason H. | Williams, Scott M. | Zhu, Xiaofeng | Zonderman, Alan B. | Kooperberg, Charles | Papanicolaou, George | Henderson, Brian E. | Reiner, Alex P. | Hirschhorn, Joel N. | Loos, Ruth JF | North, Kari E. | Haiman, Christopher A.
Nature genetics  2013;45(6):690-696.
Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of >3.2 million SNPs with BMI in 39,144 men and women of African ancestry, and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one novel locus at 5q33 (GALNT10, rs7708584, p=3.4×10−11) and another at 7p15 when combined with data from the Giant consortium (MIR148A/NFE2L3, rs10261878, p=1.2×10−10). We also found suggestive evidence of an association at a third locus at 6q16 in the African ancestry sample (KLHL32, rs974417, p=6.9×10−8). Thirty-two of the 36 previously established BMI variants displayed directionally consistent effect estimates in our GWAS (binomial p=9.7×10−7), of which five reached genome-wide significance. These findings provide strong support for shared BMI loci across populations as well as for the utility of studying ancestrally diverse populations.
doi:10.1038/ng.2608
PMCID: PMC3694490  PMID: 23583978
8.  Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status 
Journal of medical genetics  2012;49(9):601-608.
Objective
There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumors with different hormone receptor status.
Material and Methods
Within the Breast and Prostate Cancer Cohort Consortium (BPC3), we analyzed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age- and cohort-adjusted concordance statistic (AUROCa). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement (IDI) was used to measure improvements in risk prediction.
Results
We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROCa going from 2.7 to 4%). Discriminatory ability for all models varied strongly by hormone receptor status
Discussion and Conclusion
Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor positive cases, but the gain in discriminatory quality is not sufficient for clinical application.
doi:10.1136/jmedgenet-2011-100716
PMCID: PMC3793888  PMID: 22972951
breast cancer; risk prediction; genetic factors; hormone receptor status
9.  Non-steroidal anti-inflammatory drugs and Amyotrophic Lateral Sclerosis: Results from 5 prospective cohort studies 
Objective
Animal and pathological studies suggest that inflammation may contribute to amyotrophic lateral sclerosis (ALS) pathology and that non-steroidal anti-inflammatory drugs (NSAIDs) might be protective. However, there are no prospective data on the relation between NSAID use and ALS risk in humans.
Methods
The relation between NSAID use and ALS risk was explored in five large prospective cohort studies (the Nurses’ Health Study, the Health Professionals Follow-up Study, the Cancer Prevention Study II Nutrition Cohort, the Multiethnic Cohort Study, and the National Institutes of Health – AARP Diet and Health Study). Detailed NSAID information was sought from 780,000 participants, 708 of whom developed ALS during follow-up. Cox proportional hazards models were used within each cohort and cohort-specific estimates were pooled with random effects models.
Results
Neither non-aspirin NSAID use, nor aspirin use was associated with ALS risk overall. The multivariable, pooled relative risk was 0.96 (95% CI 0.76-1.22) among non-aspirin NSAID users compared with non-users. Duration of NSAID use in years and frequency of NSAID use were not associated with ALS risk overall.
Conclusion
The results do not support an overall effect of NSAIDs on ALS risk, but because NSAIDs have heterogeneous effects, a role of individual compounds cannot be excluded.
doi:10.3109/17482968.2012.703209
PMCID: PMC3474335  PMID: 22871075
ALS; NSAID; cohort; epidemiology
10.  50-Year Trends in Smoking-Related Mortality in the United States 
The New England journal of medicine  2013;368(4):351-364.
BACKGROUND
The disease risks from cigarette smoking increased in the United States over most of the 20th century, first among male smokers and later among female smokers. Whether these risks have continued to increase during the past 20 years is unclear.
METHODS
We measured temporal trends in mortality across three time periods (1959–1965, 1982–1988, and 2000–2010), comparing absolute and relative risks according to sex and self-reported smoking status in two historical cohort studies and in five pooled contemporary cohort studies, among participants who became 55 years of age or older during follow-up.
RESULTS
For women who were current smokers, as compared with women who had never smoked, the relative risks of death from lung cancer were 2.73, 12.65, and 25.66 in the 1960s, 1980s, and contemporary cohorts, respectively; corresponding relative risks for male current smokers, as compared with men who had never smoked, were 12.22, 23.81, and 24.97. In the contemporary cohorts, male and female current smokers also had similar relative risks for death from chronic obstructive pulmonary disease (COPD) (25.61 for men and 22.35 for women), ischemic heart disease (2.50 for men and 2.86 for women), any type of stroke (1.92 for men and 2.10 for women), and all causes combined (2.80 for men and 2.76 for women). Mortality from COPD among male smokers continued to increase in the contemporary cohorts in nearly all the age groups represented in the study and within each stratum of duration and intensity of smoking. Among men 55 to 74 years of age and women 60 to 74 years of age, all-cause mortality was at least three times as high among current smokers as among those who had never smoked. Smoking cessation at any age dramatically reduced death rates.
CONCLUSIONS
The risk of death from cigarette smoking continues to increase among women and the increased risks are now nearly identical for men and women, as compared with persons who have never smoked. Among men, the risks associated with smoking have plateaued at the high levels seen in the 1980s, except for a continuing, unexplained increase in mortality from COPD.
doi:10.1056/NEJMsa1211127
PMCID: PMC3632080  PMID: 23343064
11.  Cohort Life Tables By Smoking Status Removing Lung Cancer as a Cause of Death 
The purpose of this study was to develop life tables by smoking status removing lung cancer as a cause of death. These life tables are inputs to studies that compare the effectiveness of lung cancer treatments or interventions, and provide a way to quantify time until death from causes other than lung cancer. The study combined actuarial and statistical smoothing methods, as well as data from multiple sources, to develop separate life tables by smoking status, birth cohort, by single year of age, and by sex. For current smokers, separate life tables by smoking quintiles were developed based on the average number of cigarettes smoked per day by birth cohort. The end product is the creation of six non-lung cancer life tables for males and six tables for females: five current smoker quintiles and one for never smokers. Tables for former smokers are linear combinations of the appropriate table based on the current smoker quintile prior to quitting smoking and the never smoker probabilities, plus added covariates for the smoking quit age and time since quitting.
doi:10.1111/j.1539-6924.2011.01662.x
PMCID: PMC3594098  PMID: 22882890
Life Tables; Competing Risks; Lung Cancer and Smoking
12.  Are Racial Disparities in Pancreatic Cancer Explained by Smoking and Overweight/Obesity? 
Between 2001–2005, U.S. Blacks experienced a 32% higher pancreatic cancer death rate than Whites. Smoking, diabetes, and family history may explain some of this disparity, but prospective analyses are warranted. From 1984–2004, there were 6,243 pancreatic cancer deaths among Blacks (n=48,252) and Whites (n=1,011,864) in the Cancer Prevention Study II cohort. Multivariate Cox proportional hazards models yielded hazards ratios for known and suspected risk factors. Population attributable risks were computed and their impact on age-standardized mortality rates evaluated. Blacks in this cohort had a 42% increased risk of pancreatic cancer mortality compared to Whites (HR=1.42; 95% CI 1.28 to 1.58). Current smoking increased risk by >60% in both races; although Blacks smoked less intensely, risks were similar to Whites (HRBlack=1.67, 95% CI 1.28 to 2.18; HRWhite=1.82, 95%CI 1.7 to 1.95). Obesity was significantly associated with pancreatic cancer mortality in Black men (HR=1.66, 95% CI 1.05 to 2.63), White men (HR=1.42; 95% CI 1.25 to 1.60) and White women (HR=1.37; 95% CI 1.22 to 1.54); results were null in Black women. The PAR due to smoking, family history, diabetes, cholecystectomy, and overweight/obesity was 24.3% in Whites and 21.8% in Blacks. Smoking and overweight/obesity play a substantial a role in pancreatic cancer. Variation in the impact of these factors underscores the need to evaluate disease on the race-sex level. The inability to attribute excess disease in Blacks to currently known risk factors, even when combined with suspected risks, points to yet undetermined factors that play a role in the disease process.
doi:10.1158/1055-9965.EPI-09-0080
PMCID: PMC3630792  PMID: 19723915
13.  The chromosome 2p21 region harbors a complex genetic architecture for association with risk for renal cell carcinoma 
Human Molecular Genetics  2011;21(5):1190-1200.
In follow-up of a recent genome-wide association study (GWAS) that identified a locus in chromosome 2p21 associated with risk for renal cell carcinoma (RCC), we conducted a fine mapping analysis of a 120 kb region that includes EPAS1. We genotyped 59 tagged common single-nucleotide polymorphisms (SNPs) in 2278 RCC and 3719 controls of European background and observed a novel signal for rs9679290 [P = 5.75 × 10−8, per-allele odds ratio (OR) = 1.27, 95% confidence interval (CI): 1.17–1.39]. Imputation of common SNPs surrounding rs9679290 using HapMap 3 and 1000 Genomes data yielded two additional signals, rs4953346 (P = 4.09 × 10−14) and rs12617313 (P = 7.48 × 10−12), both highly correlated with rs9679290 (r2 > 0.95), but interestingly not correlated with the two SNPs reported in the GWAS: rs11894252 and rs7579899 (r2 < 0.1 with rs9679290). Genotype analysis of rs12617313 confirmed an association with RCC risk (P = 1.72 × 10−9, per-allele OR = 1.28, 95% CI: 1.18–1.39) In conclusion, we report that chromosome 2p21 harbors a complex genetic architecture for common RCC risk variants.
doi:10.1093/hmg/ddr551
PMCID: PMC3277315  PMID: 22113997
14.  Common genetic variants in prostate cancer risk prediction – Results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3) 
Background
One of the goals of personalized medicine is to generate individual risk profiles that could identify individuals in the population that exhibit high risk. The discovery of more than two-dozen independent SNP markers in prostate cancer has raised the possibility for such risk stratification. In this study, we evaluated the discriminative and predictive ability for prostate cancer risk models incorporating 25 common prostate cancer genetic markers, family history of prostate cancer and age.
Methods
We fit a series of risk models and estimated their performance in 7,509 prostate cancer cases and 7,652 controls within the NCI Breast and Prostate Cancer Cohort Consortium (BPC3). We also calculated absolute risks based on SEER incidence data.
Results
The best risk model (C-statistic=0.642) included individual genetic markers and family history of prostate cancer. We observed a decreasing trend in discriminative ability with advancing age (P=0.009), with highest accuracy in men younger than 60 years (C-statistic=0.679). The absolute ten-year risk for 50-year old men with a family history ranged from 1.6% (10th percentile of genetic risk) to 6.7% (90th percentile of genetic risk). For men without family history, the risk ranged from 0.8% (10th percentile) to 3.4% (90th percentile).
Conclusions
Our results indicate that incorporating genetic information and family history in prostate cancer risk models can be particularly useful for identifying younger men that might benefit from PSA screening.
Impact
Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
doi:10.1158/1055-9965.EPI-11-1038
PMCID: PMC3318963  PMID: 22237985
Prostate cancer; polymorphism; risk prediction model
15.  A genome-wide association study identifies a novel susceptibility locus for renal cell carcinoma on 12p11.23 
Wu, Xifeng | Scelo, Ghislaine | Purdue, Mark P. | Rothman, Nathaniel | Johansson, Mattias | Ye, Yuanqing | Wang, Zhaoming | Zelenika, Diana | Moore, Lee E. | Wood, Christopher G. | Prokhortchouk, Egor | Gaborieau, Valerie | Jacobs, Kevin B. | Chow, Wong-Ho | Toro, Jorge R. | Zaridze, David | Lin, Jie | Lubinski, Jan | Trubicka, Joanna | Szeszenia-Dabrowska, Neonilia | Lissowska, Jolanta | Rudnai, Peter | Fabianova, Eleonora | Mates, Dana | Jinga, Viorel | Bencko, Vladimir | Slamova, Alena | Holcatova, Ivana | Navratilova, Marie | Janout, Vladimir | Boffetta, Paolo | Colt, Joanne S. | Davis, Faith G. | Schwartz, Kendra L. | Banks, Rosamonde E. | Selby, Peter J. | Harnden, Patricia | Berg, Christine D. | Hsing, Ann W. | Grubb, Robert L. | Boeing, Heiner | Vineis, Paolo | Clavel-Chapelon, Françoise | Palli, Domenico | Tumino, Rosario | Krogh, Vittorio | Panico, Salvatore | Duell, Eric J. | Quirós, José Ramón | Sanchez, Maria-José | Navarro, Carmen | Ardanaz, Eva | Dorronsoro, Miren | Khaw, Kay-Tee | Allen, Naomi E. | Bueno-de-Mesquita, H. Bas | Peeters, Petra H.M. | Trichopoulos, Dimitrios | Linseisen, Jakob | Ljungberg, Börje | Overvad, Kim | Tjønneland, Anne | Romieu, Isabelle | Riboli, Elio | Stevens, Victoria L | Thun, Michael J | Diver, W. Ryan | Gapstur, Susan M. | Pharoah, Paul D. | Easton, Douglas F. | Albanes, Demetrius | Virtamo, Jarmo | Vatten, Lars | Hveem, Kristian | Fletcher, Tony | Koppova, Kvetoslava | Cussenot, Olivier | Cancel-Tassin, Geraldine | Benhamou, Simone | Hildebrandt, Michelle A. | Pu, Xia | Foglio, Mario | Lechner, Doris | Hutchinson, Amy | Yeager, Meredith | Fraumeni, Joseph F. | Lathrop, Mark | Skryabin, Konstantin G. | McKay, James D. | Gu, Jian | Brennan, Paul | Chanock, Stephen J.
Human Molecular Genetics  2011;21(2):456-462.
Renal cell carcinoma (RCC) is the most lethal urologic cancer. Only two common susceptibility loci for RCC have been confirmed to date. To identify additional RCC common susceptibility loci, we conducted an independent genome-wide association study (GWAS). We analyzed 533 191 single nucleotide polymorphisms (SNPs) for association with RCC in 894 cases and 1516 controls of European descent recruited from MD Anderson Cancer Center in the primary scan, and validated the top 500 SNPs in silico in 3772 cases and 8505 controls of European descent involved in the only published GWAS of RCC. We identified two common variants in linkage disequilibrium, rs718314 and rs1049380 (r2 = 0.64, D ′ = 0.84), in the inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) gene on 12p11.23 as novel susceptibility loci for RCC (P = 8.89 × 10−10 and P = 6.07 × 10−9, respectively, in meta-analysis) with an allelic odds ratio of 1.19 [95% confidence interval (CI): 1.13–1.26] for rs718314 and 1.18 (95% CI: 1.12–1.25) for rs1049380. It has been recently identified that rs718314 in ITPR2 is associated with waist–hip ratio (WHR) phenotype. To our knowledge, this is the first genetic locus associated with both cancer risk and WHR.
doi:10.1093/hmg/ddr479
PMCID: PMC3276284  PMID: 22010048
16.  N-Acetyltransferase 2 Polymorphisms, Tobacco Smoking, and Breast Cancer Risk in the Breast and Prostate Cancer Cohort Consortium 
American Journal of Epidemiology  2011;174(11):1316-1322.
Common polymorphisms in the N-acetyltransferase 2 gene (NAT2) modify the association between cigarette smoking and bladder cancer and have been hypothesized to determine whether active cigarette smoking increases breast cancer risk. The authors sought to replicate the latter hypothesis in a prospective analysis of 6,900 breast cancer cases and 9,903 matched controls drawn from 6 cohorts (1989–2006) in the National Cancer Institute’s Breast and Prostate Cancer Cohort Consortium. Standardized methods were used to genotype the 3 most common polymorphisms that define NAT2 acetylation phenotype (rs1799930, rs1799931, and rs1801280). In unconditional logistic regression analyses, breast cancer risk was higher in women with more than 20 pack-years of active cigarette smoking than in never smokers (odds ratio (OR) = 1.28, 95% confidence interval (CI): 1.17, 1.39), after controlling for established risk factors other than alcohol consumption and physical inactivity. However, associations were similar for the slow (OR = 1.25, 95% CI: 1.11, 1.39) and rapid/intermediate (OR = 1.24, 95% CI: 1.08, 1.42) acetylation phenotypes, with no evidence of interaction (P = 0.87). These results provide some support for the hypothesis that long-term cigarette smoking may be causally associated with breast cancer risk but underscore the need for caution when interpreting sparse data on gene-environment interactions.
doi:10.1093/aje/kwr257
PMCID: PMC3390163  PMID: 22074863
arylamine N-acetyltransferase; breast neoplasms; NAT2 protein, human; polymorphism, single nucleotide; smoking
17.  How much of the decrease in cancer death rates in the United States is attributable to reductions in tobacco smoking? 
Tobacco Control  2006;15(5):345-347.
Reductions in tobacco smoking are a major factor in the decrease in cancer mortality rates
doi:10.1136/tc.2006.017749
PMCID: PMC2563648  PMID: 16998161
attributable mortality; cancer; smoking; tobacco
18.  A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer 
Nature genetics  2007;39(7):870-874.
We conducted a genome-wide association study (GWAS) of breast cancer by genotyping 528,173 single nucleotide polymorphisms (SNPs) in 1,145 cases of invasive breast cancer among postmenopausal white women, and 1,142 controls. We identified a set of four SNPs in intron 2 of FGFR2, a tyrosine kinase receptor previously shown to be amplified and/or over-expressed in some breast cancers, as highly associated with breast cancer and we confirmed this association in 1,776 cases and 2,072 controls from three additional studies. In both association testing and ancestral recombination graph analysis, FGFR2 haplotypes were associated with risk of breast cancer. Across the four studies the association with all four SNPs was highly statistically significant (Ptrend for the most strongly associated SNP, rs1219648 = 1.1 × 10−10; population attributable risk = 16%). Four SNPs at other chromosomal loci most strongly associated with breast cancer in the initial GWAS were not associated with risk in the three replication studies. Our summary results from the GWAS are freely available online in a form that should speed the identification of additional loci conferring risk.
doi:10.1038/ng2075
PMCID: PMC3493132  PMID: 17529973
19.  Application of a Novel Score Test for Genetic Association Incorporating Gene-Gene Interaction Suggests Functionality for Prostate Cancer Susceptibility Regions 
Human Heredity  2011;72(3):182-193.
Aims
We introduce an innovative multilocus test for disease association. It is an extension of an existing score test that gains power over alternative methods by incorporating a parsimonious one-degree-of-freedom model for interaction. We use our method in applications designed to detect interactions that generate hypotheses about the functionality of prostate cancer (PRCA) susceptibility regions.
Methods
Our proposed score test is designed to gain additional power through the use of a retrospective likelihood that exploits an assumption of independence between unlinked loci in the underlying population. Its performance is validated through simulation. The method is used in conditional scans with data from stage II of the Cancer Genetic Markers of Susceptibility PRCA genome-wide association study.
Results
Our proposed method increases power to detect susceptibility loci in diverse settings. It identified two high-ranking, biologically interesting interactions: (1) rs748120 of NR2C2 and subregions of 8q24 that contain independent susceptibility loci specific to PRCA and (2) rs4810671 of SULF2 and both JAZF1 and HNF1B that are associated with PRCA and type 2 diabetes.
Conclusions
Our score test is a promising multilocus tool for genetic epidemiology. The results of our applications suggest functionality for poorly understood PRCA susceptibility regions. They motivate replication study.
doi:10.1159/000331222
PMCID: PMC3242702  PMID: 22086326
Gene-gene interaction; Score test; Prostate cancer
20.  Genome-wide association study identifies new prostate cancer susceptibility loci 
Human Molecular Genetics  2011;20(19):3867-3875.
Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10−8). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10−9). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.
doi:10.1093/hmg/ddr295
PMCID: PMC3168287  PMID: 21743057
21.  Identification of a novel prostate cancer susceptibility locus on chromosome 8q24 
Nature genetics  2009;41(10):1055-1057.
We report a genome-wide association study in 10,286 cases and 9,135 controls of European ancestry, in the Cancer Genetic Markers of Susceptibility (CGEMS) initiative, identifying a new association with prostate cancer risk on chromosome 8q24 (rs620861, p=1.3×10-10, heterozygote OR = 1.17, 95% CI 1.10 – 1.24; homozygote OR = 1.33; 95% CI 1.21 – 1.45). This defines a new prostate locus on 8q24, Region 4, previously associated with breast cancer.
doi:10.1038/ng.444
PMCID: PMC3430510  PMID: 19767755
22.  Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium 
Background
Recently, several genome-wide association studies have identified various genetic susceptibility loci for breast cancer. Relatively little is known about the possible interactions between these loci and the established risk factors for breast cancer.
Methods
To assess interactions between single-nucleotide polymorphisms (SNPs) and established risk factors, we prospectively collected DNA samples and questionnaire data from 8576 breast cancer case subjects and 11 892 control subjects nested within the National Cancer Institute’s Breast and Prostate Cancer Cohort Consortium (BPC3). We genotyped 17 germline SNPs (FGFR2-rs2981582, FGFR2-rs3750817, TNRC9-rs3803662, 2q35-rs13387042, MAP3K1-rs889312, 8q24-rs13281615, CASP8-rs1045485, LSP1-rs3817198, COL1A1-rs2075555, COX11-rs6504950, RNF146-rs2180341, 6q25-rs2046210, SLC4A7-rs4973768, NOTCH2-rs11249433, 5p12-rs4415084, 5p12-rs10941679, RAD51L1-rs999737), and odds ratios were estimated by logistic regression to confirm previously reported associations with breast cancer risk. We performed likelihood ratio test to assess interactions between 17 SNPs and nine established risk factors (age at menarche, parity, age at menopause, use of hormone replacement therapy, family history, height, body mass index, smoking status, and alcohol consumption), and a correction for multiple testing of 153 tests (adjusted P value threshold = .05/153 = 3 × 10−4) was done. Case–case comparisons were performed for possible differential associations of polymorphisms by subgroups of tumor stage, estrogen and progesterone receptor status, and age at diagnosis. All statistical tests were two-sided.
Results
We confirmed the association of 14 SNPs with breast cancer risk (Ptrend = 2.57 × 10−3 –3.96 × 10−19). Three SNPs (LSP1-rs3817198, COL1A1-rs2075555, and RNF146-rs2180341) did not show association with breast cancer risk. After accounting for multiple testing, no statistically significant interactions were detected between the 17 SNPs and the nine risk factors. We also confirmed that SNPs in FGFR2 and TNRC9 were associated with greater risk of estrogen receptor–positive than estrogen receptor–negative breast cancer (Pheterogeneity = .0016 for FGFR2-rs2981582 and Pheterogeneity = .0053 for TNRC9-rs3803662). SNP 5p12-rs10941679 was statistically significantly associated with greater risk of progesterone receptor–positive than progesterone receptor–negative breast cancer (Pheterogeneity = .0028).
Conclusion
This study does not support the hypothesis that known common breast cancer susceptibility loci strongly modify the associations between established risk factors and breast cancer.
doi:10.1093/jnci/djr265
PMCID: PMC3156803  PMID: 21791674
23.  Large-scale fine mapping of the HNF1B locus and prostate cancer risk 
Human Molecular Genetics  2011;20(16):3322-3329.
Previous genome-wide association studies have identified two independent variants in HNF1B as susceptibility loci for prostate cancer risk. To fine-map common genetic variation in this region, we genotyped 79 single nucleotide polymorphisms (SNPs) in the 17q12 region harboring HNF1B in 10 272 prostate cancer cases and 9123 controls of European ancestry from 10 case–control studies as part of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. Ten SNPs were significantly related to prostate cancer risk at a genome-wide significance level of P < 5 × 10−8 with the most significant association with rs4430796 (P = 1.62 × 10−24). However, risk within this first locus was not entirely explained by rs4430796. Although modestly correlated (r2= 0.64), rs7405696 was also associated with risk (P = 9.35 × 10−23) even after adjustment for rs4430769 (P = 0.007). As expected, rs11649743 was related to prostate cancer risk (P = 3.54 × 10−8); however, the association within this second locus was stronger for rs4794758 (P = 4.95 × 10−10), which explained all of the risk observed with rs11649743 when both SNPs were included in the same model (P = 0.32 for rs11649743; P = 0.002 for rs4794758). Sequential conditional analyses indicated that five SNPs (rs4430796, rs7405696, rs4794758, rs1016990 and rs3094509) together comprise the best model for risk in this region. This study demonstrates a complex relationship between variants in the HNF1B region and prostate cancer risk. Further studies are needed to investigate the biological basis of the association of variants in 17q12 with prostate cancer.
doi:10.1093/hmg/ddr213
PMCID: PMC3140817  PMID: 21576123
24.  Seven novel prostate cancer susceptibility loci identified by a multi-stage genome-wide association study 
Kote-Jarai, Zsofia | Olama, Ali Amin Al | Giles, Graham G. | Severi, Gianluca | Schleutker, Johanna | Weischer, Maren | Canzian, Frederico | Riboli, Elio | Key, Tim | Gronberg, Henrik | Hunter, David J. | Kraft, Peter | Thun, Michael J | Ingles, Sue | Chanock, Stephen | Albanes, Demetrius | Hayes, Richard B | Neal, David E. | Hamdy, Freddie C. | Donovan, Jenny L. | Pharoah, Paul | Schumacher, Fredrick | Henderson, Brian E. | Stanford, Janet L. | Ostrander, Elaine A. | Sorensen, Karina Dalsgaard | Dörk, Thilo | Andriole, Gerald | Dickinson, Joanne L. | Cybulski, Cezary | Lubinski, Jan | Spurdle, Amanda | Clements, Judith A. | Chambers, Suzanne | Aitken, Joanne | Frank Gardiner, R. A. | Thibodeau, Stephen N. | Schaid, Dan | John, Esther M. | Maier, Christiane | Vogel, Walther | Cooney, Kathleen A. | Park, Jong Y. | Cannon-Albright, Lisa | Brenner, Hermann | Habuchi, Tomonori | Zhang, Hong-Wei | Lu, Yong-Jie | Kaneva, Radka | Muir, Ken | Benlloch, Sara | Leongamornlert, Daniel A. | Saunders, Edward J. | Tymrakiewicz, Malgorzata | Mahmud, Nadiya | Guy, Michelle | O’Brien, Lynne T. | Wilkinson, Rosemary A. | Hall, Amanda L. | Sawyer, Emma J. | Dadaev, Tokhir | Morrison, Jonathan | Dearnaley, David P. | Horwich, Alan | Huddart, Robert A. | Khoo, Vincent S. | Parker, Christopher C. | Van As, Nicholas | Woodhouse, Christopher J. | Thompson, Alan | Christmas, Tim | Ogden, Chris | Cooper, Colin S. | Lophatonanon, Aritaya | Southey, Melissa C. | Hopper, John L. | English, Dallas | Wahlfors, Tiina | Tammela, Teuvo LJ | Klarskov, Peter | Nordestgaard, Børge G. | Røder, M. Andreas | Tybjærg-Hansen, Anne | Bojesen, Stig E. | Travis, Ruth | Campa, Daniele | Kaaks, Rudolf | Wiklund, Fredrik | Aly, Markus | Lindstrom, Sara | Diver, W Ryan | Gapstur, Susan | Stern, Mariana C | Corral, Roman | Virtamo, Jarmo | Cox, Angela | Haiman, Christopher A. | Le Marchand, Loic | FitzGerald, Liesel | Kolb, Suzanne | Kwon, Erika M. | Karyadi, Danielle M. | Orntoft, Torben Falck | Borre, Michael | Meyer, Andreas | Serth, Jürgen | Yeager, Meredith | Berndt, Sonja I. | Marthick, James R | Patterson, Briony | Wokolorczyk, Dominika | Batra, Jyotsna | Lose, Felicity | McDonnell, Shannon K | Joshi, Amit D. | Shahabi, Ahva | Rinckleb, Antje E. | Ray, Ana | Sellers, Thomas A. | Lin, Huo-Yi | Stephenson, Robert A | Farnham, James | Muller, Heiko | Rothenbacher, Dietrich | Tsuchiya, Norihiko | Narita, Shintaro | Cao, Guang-Wen | Slavov, Chavdar | Mitev, Vanio | Easton, Douglas F. | Eeles, Rosalind A.
Nature Genetics  2011;43(8):785-791.
Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. To identify common PrCa susceptibility alleles, we conducted a multi-stage genome-wide association study and previously reported the results of the first two stages, which identified 16 novel susceptibility loci for PrCa. Here we report the results of stage 3 in which we evaluated 1,536 SNPs in 4,574 cases and 4,164 controls. Ten novel association signals were followed up through genotyping in 51,311 samples in 30 studies through the international PRACTICAL consortium. In addition to previously reported loci, we identified a further seven new prostate cancer susceptibility loci on chromosomes 2p, 3q, 5p, 6p, 12q and Xq (P=4.0 ×10−8 to P=2.7 ×10−24). We also identified a SNP in TERT more strongly associated with PrCa than that previously reported. More than 40 PrCa susceptibility loci, explaining ~25% of the familial risk in this disease, have now been identified.
doi:10.1038/ng.882
PMCID: PMC3396006  PMID: 21743467
25.  Fine mapping of a region of chromosome 11q13 reveals multiple independent loci associated with risk of prostate cancer 
Human Molecular Genetics  2011;20(14):2869-2878.
Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P< 10−8) with rs10896449 the most significant (P= 7.94 × 10−19). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P= 4.76 × 10−5, adjusted P= 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r2= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P= 5.92 × 10−3, adjusted P= 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449–rs12793759, r2= 0.17; rs10896449–rs10896438, r2= 0.10; rs12793759–rs10896438, r2= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ∼123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n= 31), rs10896438 (n= 24) and rs12793759 (n= 8). Our results indicate that a complex architecture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals.
doi:10.1093/hmg/ddr189
PMCID: PMC3118760  PMID: 21531787

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