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1.  Additive Interactions Between Susceptibility Single-Nucleotide Polymorphisms Identified in Genome-Wide Association Studies and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium 
Joshi, Amit D. | Lindström, Sara | Hüsing, Anika | Barrdahl, Myrto | VanderWeele, Tyler J. | Campa, Daniele | Canzian, Federico | Gaudet, Mia M. | Figueroa, Jonine D. | Baglietto, Laura | Berg, Christine D. | Buring, Julie E. | Chanock, Stephen J. | Chirlaque, María-Dolores | Diver, W. Ryan | Dossus, Laure | Giles, Graham G. | Haiman, Christopher A. | Hankinson, Susan E. | Henderson, Brian E. | Hoover, Robert N. | Hunter, David J. | Isaacs, Claudine | Kaaks, Rudolf | Kolonel, Laurence N. | Krogh, Vittorio | Le Marchand, Loic | Lee, I-Min | Lund, Eiliv | McCarty, Catherine A. | Overvad, Kim | Peeters, Petra H. | Riboli, Elio | Schumacher, Fredrick | Severi, Gianluca | Stram, Daniel O. | Sund, Malin | Thun, Michael J. | Travis, Ruth C. | Trichopoulos, Dimitrios | Willett, Walter C. | Zhang, Shumin | Ziegler, Regina G. | Kraft, Peter | Joshi, Amit D. | Lindström, Sara | Hunter, David J. | Kraft, Peter | Hüsing, Anika | Barrdahl, Myrto | Kaaks, Rudolf | Kraft, Peter | VanderWeele, Tyler J. | Trichopoulos, Dimitrios | Campa, Daniele | VanderWeele, Tyler J. | Campa, Daniele | Canzian, Federico | Gaudet, Mia M. | Figueroa, Jonine D. | Chanock, Stephen J. | Hoover, Robert N. | Ziegler, Regina G. | Baglietto, Laura | Giles, Graham G. | Severi, Gianluca | Baglietto, Laura | Giles, Graham G. | Severi, Gianluca | Berg, Christine D. | Buring, Julie E. | Lee, I-Min | Zhang, Shumin | Chirlaque, María-Dolores | Chirlaque, María-Dolores | Diver, W. Ryan | Thun, Michael J. | Dossus, Laure | Dossus, Laure | Giles, Graham G. | Haiman, Christopher A. | Schumacher, Fredrick | Stram, Daniel O. | Henderson, Brian E. | Hankinson, Susan E. | Isaacs, Claudine | Kolonel, Laurence N. | Krogh, Vittorio | Marchand, Loic Le | Lund, Eiliv | McCarty, Catherine A. | Overvad, Kim | Peeters, Petra H. | Peeters, Petra H. | Riboli, Elio | Sund, Malin | Travis, Ruth C. | Trichopoulos, Dimitrios | Trichopoulos, Dimitrios | Willett, Walter C.
American Journal of Epidemiology  2014;180(10):1018-1027.
Additive interactions can have public health and etiological implications but are infrequently reported. We assessed departures from additivity on the absolute risk scale between 9 established breast cancer risk factors and 23 susceptibility single-nucleotide polymorphisms (SNPs) identified from genome-wide association studies among 10,146 non-Hispanic white breast cancer cases and 12,760 controls within the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium. We estimated the relative excess risk due to interaction and its 95% confidence interval for each pairwise combination of SNPs and nongenetic risk factors using age- and cohort-adjusted logistic regression models. After correction for multiple comparisons, we identified a statistically significant relative excess risk due to interaction (uncorrected P = 4.51 × 10−5) between a SNP in the DNA repair protein RAD51 homolog 2 gene (RAD51L1; rs10483813) and body mass index (weight (kg)/height (m)2). We also compared additive and multiplicative polygenic risk prediction models using per-allele odds ratio estimates from previous studies for breast-cancer susceptibility SNPs and observed that the multiplicative model had a substantially better goodness of fit than the additive model.
PMCID: PMC4224360  PMID: 25255808
additive interactions; breast cancer; genome-wide association studies; single-nucleotide polymorphisms
2.  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.
PMCID: PMC3374121  PMID: 22271044
3.  Body Mass Index and Risk of Death in Asian Americans 
American journal of public health  2014;104(3):520-525.
To investigate the association between body mass index (BMI) and mortality among Asian Americans
We pooled data from prospective cohort studies that included 20,672 Asian American adults with no history of cancer or heart disease at baseline. Hazard ratios and 95% confidence intervals (CI) were estimated using Cox proportional hazards models.
A high, but not low, BMI was associated with an increased risk of total mortality among individuals 35–69 years old. BMI was not related to total mortality among individuals ≥70 years old. With a BMI 22.5–<25 as the reference category among 35–69 year old never smokers the hazard ratios (95% CI) for total mortality were 0.83 (0.47–1.47) for BMI 15–<18.5, 0.91 (0.62–1.32) for BMI 18.5–<20, 1.08 (0.86–1.36) for BMI 20–<22.5, 1.14 (0.90–1.44) for BMI 25–<27.5, 1.13 (0.79–1.62) for BMI 27.5–<30, 1.82 (1.25–2.64) for BMI 30–<35, and 2.09 (1.06–4.11) for BMI 35–50. Higher BMI was also related to an increased mortality from cardiovascular disease and cancer.
A high BMI is associated with increased risk of mortality among Asian Americans.
PMCID: PMC3953786  PMID: 24432919
4.  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.
PMCID: PMC4159746  PMID: 21959381
RAD51L1; breast cancer; genome-wide association study; fine-mapping; imputation
5.  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.
PMCID: PMC4059357  PMID: 19942276
6.  Lung Cancer, Cardiopulmonary Mortality, and Long-term Exposure to Fine Particulate Air Pollution 
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.
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.
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.
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
7.  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.
PMCID: PMC3526158  PMID: 23065704
8.  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.
PMCID: PMC3510753  PMID: 22976474
9.  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.
PMCID: PMC3694490  PMID: 23583978
10.  Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status 
Journal of medical genetics  2012;49(9):601-608.
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.
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.
PMCID: PMC3793888  PMID: 22972951
breast cancer; risk prediction; genetic factors; hormone receptor status
11.  Non-steroidal anti-inflammatory drugs and Amyotrophic Lateral Sclerosis: Results from 5 prospective cohort studies 
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.
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.
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.
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.
PMCID: PMC3474335  PMID: 22871075
ALS; NSAID; cohort; epidemiology
12.  Linking tobacco control policies and practices to early cancer endpoints: Surveillance as an agent for change 
State tobacco control programs provide an important laboratory for the development, implementation, and evaluation of comprehensive tobacco control interventions. Studies have demonstrated that states and municipalities with aggressive tobacco control programs have experienced more rapid decreases in per capita cigarette sales, smoking prevalence, lung cancer, and heart disease than entities without such programs. Despite strong evidence that population-level interventions are critical in achieving large and sustained reductions in tobacco use, states do not fund tobacco control efforts at levels recommended by the CDC. Research on the effectiveness and cost-effectiveness of these activities is essential to inform and strengthen tobacco control at the state-level. A workshop, co-organized by ACS, NCI, AACR, and CDC, was held in Philadelphia in December, 2007 to discuss the topic “Linking tobacco control policies and practices to early cancer endpoints: Surveillance as an agent for change”. Participants represented three different disciplines. Tobacco surveillance researchers described the data currently collected on state-level tobacco control policies, pro-tobacco countermeasures by the industry, public attitudes towards tobacco use and measures of smoking prevalence and consumption. Cancer registry experts described the geographic coverage of high quality, population-based cancer registries. Mathematical modeling experts discussed various modeling approaches that can be used to relate upstream tobacco promotion and control activities to downstream measures such as public attitudes, changes in tobacco use, and trends in tobacco-related diseases. The most important recommendation of the Workshop was a call for national leadership to enhance the collection and integration of data from multiple sources as a resource to further study and strengthen the scientific basis for tobacco control.
PMCID: PMC2768308  PMID: 18768485
13.  50-Year Trends in Smoking-Related Mortality in the United States 
The New England journal of medicine  2013;368(4):351-364.
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.
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.
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.
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.
PMCID: PMC3632080  PMID: 23343064
14.  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
PMCID: PMC2563648  PMID: 16998161
attributable mortality; cancer; smoking; tobacco
15.  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.
PMCID: PMC3594098  PMID: 22882890
Life Tables; Competing Risks; Lung Cancer and Smoking
16.  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.
PMCID: PMC3630792  PMID: 19723915
17.  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.
PMCID: PMC3277315  PMID: 22113997
18.  Common genetic variants in prostate cancer risk prediction – Results from the NCI Breast and Prostate Cancer Cohort Consortium (BPC3) 
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.
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.
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).
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.
Although adding genetic risk markers improves model performance, the clinical utility of these genetic risk models is limited.
PMCID: PMC3318963  PMID: 22237985
Prostate cancer; polymorphism; risk prediction model
19.  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.
PMCID: PMC3276284  PMID: 22010048
20.  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.
PMCID: PMC3390163  PMID: 22074863
arylamine N-acetyltransferase; breast neoplasms; NAT2 protein, human; polymorphism, single nucleotide; smoking
21.  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.
PMCID: PMC3493132  PMID: 17529973
22.  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.
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.
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.
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.
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.
PMCID: PMC3242702  PMID: 22086326
Gene-gene interaction; Score test; Prostate cancer
23.  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.
PMCID: PMC3168287  PMID: 21743057
24.  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.
PMCID: PMC3430510  PMID: 19767755
25.  Interactions Between Genetic Variants and Breast Cancer Risk Factors in the Breast and Prostate Cancer Cohort Consortium 
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.
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.
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).
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.
PMCID: PMC3156803  PMID: 21791674

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