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Turman, Constance

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Turman

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Constance

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Turman, Constance
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    Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants
    (Nature Publishing Group UK, 2018) Dadaev, Tokhir; Saunders, Edward J.; Newcombe, Paul J.; Anokian, Ezequiel; Leongamornlert, Daniel A.; Brook, Mark N.; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R.; Berndt, Sonja I.; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L.; Gapstur, Susan M.; Carter, Brian D.; Tangen, Catherine M.; Goodman, Phyllis; Thompson, Ian M.; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L. J.; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M.; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E. Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E.; Donovan, Jenny L.; Hamdy, Freddie C.; Martin, Richard M.; Travis, Ruth C.; Key, Tim J.; Hamilton, Robert J.; Fleshner, Neil E.; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C.; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G.; Southey, Melissa C.; MacInnis, Robert J.; FitzGerald, Liesel M.; Kibel, Adam S.; Drake, Bettina F.; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn; Stampfer, Meir; Park, Jong Y.; Sellers, Thomas A.; Lin, Hui-Yi; Stanford, Janet L.; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A.; Geybels, Milan S.; Nordestgaard, Børge G.; Nielsen, Sune F.; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J.; John, Esther M.; Teixeira, Manuel R.; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L.; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W.; Newcomb, Lisa F.; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A.; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J.; Jenster, Guido; van Schaik, Ron H. N.; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N.; McDonnell, Shannon K.; Schaid, Daniel J.; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N.; Le Marchand, Loic; Hoover, Robert N.; Machiela, Mitchell J.; Kraft, Phillip; Cook, Margaret; Thwaites, Alison; Guy, Michelle; Whitmore, Ian; Morgan, Angela; Fisher, Cyril; Hazel, Steve; Livni, Naomi; Spurdle, Amanda; Srinivasan, Srilakshmi; Kedda, Mary-Anne; Aitken, Joanne; Gardiner, Robert; Hayes, Vanessa; Butler, Lisa; Taylor, Renea; Yeadon, Trina; Eckert, Allison; Saunders, Pamela; Haynes, Anne-Maree; Papargiris, Melissa; Kujala, Paula; Talala, Kirsi; Murtola, Teemu; Taari, Kimmo; Dearnaley, David; Barnett, Gill; Bentzen, Søren; Elliott, Rebecca; Ranu, Hardeep; Hicks, Belynda; Vogt, Aurelie; Hutchinson, Amy; Cox, Angela; Davis, Michael; Brown, Paul; George, Anne; Marsden, Gemma; Lane, Athene; Lewis, Sarah J.; Berry, Clare; Kulkarni, Girish S.; Toi, Ants; Evans, Andrew; Zlotta, Alexandre R.; van der Kwast, Theodorus H.; Imai, Takashi; Saito, Shiro; Marzec, Jacek; Cao, Guangwen; Lin, Ji; Ling, Jin; Li, Meiling; Zhao, Shan-Chao; Ren, Guoping; Yu, Yongwei; Wu, Yudong; Wu, Ji; Zhou, Bo; Zhang, Yangling; Li, Jie; He, Weiyang; Guo, Jianming; Pedersen, John; Hopper, John L.; Milne, Roger; Klim, Aleksandra; Carballo, Ana; Lobato-Busto, Ramón; Peleteiro, Paula; Calvo, Patricia; Aguado, Miguel; Ruiz-Dominguez, José Manuel; Cecchini, Lluís; Mengual, Lourdes; Alcaraz, Antonio; Bustamante, Mariona; Gracia-Lavedan, Esther; Dierssen-Sotos, Trinidad; Gomez-Acebo, Ines; Pow-Sang, Julio; Park, Hyun; Zachariah, Babu; Kluzniak, Wojciech; Kolb, Suzanne; Klarskov, Peter; Stegmaier, Christa; Vogel, Walther; Herkommer, Kathleen; Bohnert, Philipp; Maia, Sofia; Silva, Maria P.; De Langhe, Sofie; Thierens, Hubert; Tan, Meng H.; Ong, Aik T.; Kastelan, Zeljko; Popov, Elenko; Kachakova, Darina; Mitkova, Atanaska; Vlahova, Aleksandrina; Dikov, Tihomir; Christova, Svetlana; Carracedo, Angel; Bangma, Christopher; Schroder, F. H.; Cenee, Sylvie; Tretarre, Brigitte; Rebillard, Xavier; Mulot, Claire; Sanchez, Marie; Adolfsson, Jan; Stattin, Par; Johansson, Jan-Erik; Cavalli-Bjoerkman, Carin; Karlsson, Ami; Broms, Michael; Wu, Huihai; Tillmans, Lori; Riska, Shaun; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E.; Easton, Douglas F.; Haiman, Christopher A.; Eeles, Rosalind A.; Conti, David V.; Kote-Jarai, Zsofia
    Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.
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    Genome-wide association study of endometrial cancer in E2C2
    (Springer Berlin Heidelberg, 2013) De Vivo, Immaculata; Prescott, Jennifer; Setiawan, Veronica Wendy; Olson, Sara H.; Wentzensen, Nicolas; Attia, John; Black, Amanda; Brinton, Louise; Chen, Chu; Turman, Constance; Cook, Linda S.; Crous-Bou, Marta; Doherty, Jennifer; Dunning, Alison M.; Easton, Douglas F.; Friedenreich, Christine M.; Garcia-Closas, Montserrat; Gaudet, Mia M.; Haiman, Christopher; Hankinson, Susan; Hartge, Patricia; Henderson, Brian E.; Holliday, Elizabeth; Horn-Ross, Pamela L.; Hunter, David; Le Marchand, Loic; Liang, Xiaolin; Lissowska, Jolanta; Long, Jirong; Lu, Lingeng; Magliocco, Anthony M.; McEvoy, Mark; O’Mara, Tracy A.; Orlow, Irene; Painter, Jodie N.; Pooler, Loreall; Rastogi, Radhai; Rebbeck, Timothy R.; Risch, Harvey; Sacerdote, Carlotta; Schumacher, Fredrick; Scott, Rodney J.; Sheng, Xin; Shu, Xiao-ou; Spurdle, Amanda B.; Thompson, Deborah; VanDen Berg, David; Weiss, Noel S.; Xia, Lucy; Xiang, Yong-Bing; Yang, Hannah P.; Yu, Herbert; Zheng, Wei; Chanock, Stephen; Kraft, Phillip
    Endometrial cancer (EC), a neoplasm of the uterine epithelial lining, is the most common gynecological malignancy in developed countries and the fourth most common cancer among US women. Women with a family history of EC have an increased risk for the disease, suggesting that inherited genetic factors play a role. We conducted a two-stage genome-wide association study of Type I EC. Stage 1 included 5,472 women (2,695 cases and 2,777 controls) of European ancestry from seven studies. We selected independent single-nucleotide polymorphisms (SNPs) that displayed the most significant associations with EC in Stage 1 for replication among 17,948 women (4,382 cases and 13,566 controls) in a multiethnic population (African America, Asian, Latina, Hawaiian and European ancestry), from nine studies. Although no novel variants reached genome-wide significance, we replicated previously identified associations with genetic markers near the HNF1B locus. Our findings suggest that larger studies with specific tumor classification are necessary to identify novel genetic polymorphisms associated with EC susceptibility. Electronic supplementary material The online version of this article (doi:10.1007/s00439-013-1369-1) contains supplementary material, which is available to authorized users.
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    Deep targeted sequencing of 12 breast cancer susceptibility regions in 4611 women across four different ethnicities
    (BioMed Central, 2016) Lindström, Sara; Ablorh, Akweley; Chapman, Brad; Gusev, Alexander; Chen, Gary; Turman, Constance; Eliassen, A; Price, Alkes; Henderson, Brian E.; Le Marchand, Loic; Hofmann, Oliver; Haiman, Christopher A.; Kraft, Phillip
    Background: Although genome-wide association studies (GWASs) have identified thousands of disease susceptibility regions, the underlying causal mechanism in these regions is not fully known. It is likely that the GWAS signal originates from one or many as yet unidentified causal variants. Methods: Using next-generation sequencing, we characterized 12 breast cancer susceptibility regions identified by GWASs in 2288 breast cancer cases and 2323 controls across four populations of African American, European, Japanese, and Hispanic ancestry. Results: After genotype calling and quality control, we identified 137,530 single-nucleotide variants (SNVs); of those, 87.2 % had a minor allele frequency (MAF) <0.005. For SNVs with MAF >0.005, we calculated the smallest number of SNVs needed to obtain a posterior probability set (PPS) such that there is 90 % probability that the causal SNV is included. We found that the PPS for two regions, 2q35 and 11q13, contained less than 5 % of the original SNVs, dramatically decreasing the number of potentially causal SNVs. However, we did not find strong evidence supporting a causal role for any individual SNV. In addition, there were no significant gene-based rare SNV associations after correcting for multiple testing. Conclusions: This study illustrates some of the challenges faced in fine-mapping studies in the post-GWAS era, most importantly the large sample sizes needed to identify rare-variant associations or to distinguish the effects of strongly correlated common SNVs. Electronic supplementary material The online version of this article (doi:10.1186/s13058-016-0772-7) contains supplementary material, which is available to authorized users.
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    Common germline polymorphisms associated with breast cancer-specific survival
    (BioMed Central, 2015) Pirie, Ailith; Guo, Qi; Kraft, Phillip; Canisius, Sander; Eccles, Diana M; Rahman, Nazneen; Nevanlinna, Heli; Turman, Constance; Khan, Sofia; Tyrer, Jonathan; Bolla, Manjeet K; Wang, Qin; Dennis, Joe; Michailidou, Kyriaki; Lush, Michael; Dunning, Alison M; Shah, Mitul; Czene, Kamila; Darabi, Hatef; Eriksson, Mikael; Lambrechts, Dieter; Weltens, Caroline; Leunen, Karin; van Ongeval, Chantal; Nordestgaard, Børge G; Nielsen, Sune F; Flyger, Henrik; Rudolph, Anja; Seibold, Petra; Flesch-Janys, Dieter; Blomqvist, Carl; Aittomäki, Kristiina; Fagerholm, Rainer; Muranen, Taru A; Olsen, Janet E; Hallberg, Emily; Vachon, Celine; Knight, Julia A; Glendon, Gord; Mulligan, Anna Marie; Broeks, Annegien; Cornelissen, Sten; Haiman, Christopher A; Henderson, Brian E; Schumacher, Frederick; Le Marchand, Loic; Hopper, John L; Tsimiklis, Helen; Apicella, Carmel; Southey, Melissa C; Cross, Simon S; Reed, Malcolm WR; Giles, Graham G; Milne, Roger L; McLean, Catriona; Winqvist, Robert; Pylkäs, Katri; Jukkola-Vuorinen, Arja; Grip, Mervi; Hooning, Maartje J; Hollestelle, Antoinette; Martens, John WM; van den Ouweland, Ans MW; Marme, Federick; Schneeweiss, Andreas; Yang, Rongxi; Burwinkel, Barbara; Figueroa, Jonine; Chanock, Stephen J; Lissowska, Jolanta; Sawyer, Elinor J; Tomlinson, Ian; Kerin, Michael J; Miller, Nicola; Brenner, Hermann; Butterbach, Katja; Holleczek, Bernd; Kataja, Vesa; Kosma, Veli-Matti; Hartikainen, Jaana M; Li, Jingmei; Brand, Judith S; Humphreys, Keith; Devilee, Peter; Tollenaar, Robert AEM; Seynaeve, Caroline; Radice, Paolo; Peterlongo, Paolo; Manoukian, Siranoush; Ficarazzi, Filomena; Beckmann, Matthias W; Hein, Alexander; Ekici, Arif B; Balleine, Rosemary; Phillips, Kelly-Anne; Benitez, Javier; Zamora, M Pilar; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Jakubowska, Anna; Lubinski, Jan; Gronwald, Jacek; Durda, Katarzyna; Hamann, Ute; Kabisch, Maria; Ulmer, Hans Ulrich; Rüdiger, Thomas; Margolin, Sara; Kristensen, Vessela; Nord, Siljie; Evans, D Gareth; Abraham, Jean; Earl, Helena; Poole, Christopher J; Hiller, Louise; Dunn, Janet A; Bowden, Sarah; Yang, Rose; Campa, Daniele; Diver, W Ryan; Gapstur, Susan M; Gaudet, Mia M; Hankinson, Susan; Hoover, Robert N; Hüsing, Anika; Kaaks, Rudolf; Machiela, Mitchell J; Willett, Walter; Barrdahl, Myrto; Canzian, Federico; Chin, Suet-Feung; Caldas, Carlos; Hunter, David; Lindstrom, Sara; Garcia-Closas, Montserrat; Couch, Fergus J; Chenevix-Trench, Georgia; Mannermaa, Arto; Andrulis, Irene L; Hall, Per; Chang-Claude, Jenny; Easton, Douglas F; Bojesen, Stig E; Cox, Angela; Fasching, Peter A; Pharoah, Paul DP; Schmidt, Marjanka K
    Introduction: Previous studies have identified common germline variants nominally associated with breast cancer survival. These associations have not been widely replicated in further studies. The purpose of this study was to evaluate the association of previously reported SNPs with breast cancer-specific survival using data from a pooled analysis of eight breast cancer survival genome-wide association studies (GWAS) from the Breast Cancer Association Consortium. Methods: A literature review was conducted of all previously published associations between common germline variants and three survival outcomes: breast cancer-specific survival, overall survival and disease-free survival. All associations that reached the nominal significance level of P value <0.05 were included. Single nucleotide polymorphisms that had been previously reported as nominally associated with at least one survival outcome were evaluated in the pooled analysis of over 37,000 breast cancer cases for association with breast cancer-specific survival. Previous associations were evaluated using a one-sided test based on the reported direction of effect. Results: Fifty-six variants from 45 previous publications were evaluated in the meta-analysis. Fifty-four of these were evaluated in the full set of 37,954 breast cancer cases with 2,900 events and the two additional variants were evaluated in a reduced sample size of 30,000 samples in order to ensure independence from the previously published studies. Five variants reached nominal significance (P <0.05) in the pooled GWAS data compared to 2.8 expected under the null hypothesis. Seven additional variants were associated (P <0.05) with ER-positive disease. Conclusions: Although no variants reached genome-wide significance (P <5 x 10−8), these results suggest that there is some evidence of association between candidate common germline variants and breast cancer prognosis. Larger studies from multinational collaborations are necessary to increase the power to detect associations, between common variants and prognosis, at more stringent significance levels. Electronic supplementary material The online version of this article (doi:10.1186/s13058-015-0570-7) contains supplementary material, which is available to authorized users.
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    A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts
    (Public Library of Science, 2017) Lindström, Sara; Loomis, Stephanie; Turman, Constance; Huang, Hongyan; Huang, Jinyan; Aschard, Hugues; Chan, Andrew; Choi, Hyon; Cornelis, Marilyn; Curhan, Gary; De Vivo, Immaculata; Eliassen, A; Fuchs, Charles; Gaziano, Michael; Hankinson, Susan; Hu, Frank; Jensen, Majken; Kang, Jae Hee; Kabrhel, Christopher; Liang, Liming; Pasquale, Louis; Rimm, Eric; Stampfer, Meir; Tamimi, Rulla; Tworoger, Shelley; Wiggs, Janey; Hunter, David; Kraft, Phillip
    The Nurses’ Health Study (NHS), Nurses’ Health Study II (NHSII), Health Professionals Follow Up Study (HPFS) and the Physicians Health Study (PHS) have collected detailed longitudinal data on multiple exposures and traits for approximately 310,000 study participants over the last 35 years. Over 160,000 study participants across the cohorts have donated a DNA sample and to date, 20,691 subjects have been genotyped as part of genome-wide association studies (GWAS) of twelve primary outcomes. However, these studies utilized six different GWAS arrays making it difficult to conduct analyses of secondary phenotypes or share controls across studies. To allow for secondary analyses of these data, we have created three new datasets merged by platform family and performed imputation using a common reference panel, the 1,000 Genomes Phase I release. Here, we describe the methodology behind the data merging and imputation and present imputation quality statistics and association results from two GWAS of secondary phenotypes (body mass index (BMI) and venous thromboembolism (VTE)). We observed the strongest BMI association for the FTO SNP rs55872725 (β = 0.45, p = 3.48x10-22), and using a significance level of p = 0.05, we replicated 19 out of 32 known BMI SNPs. For VTE, we observed the strongest association for the rs2040445 SNP (OR = 2.17, 95% CI: 1.79–2.63, p = 2.70x10-15), located downstream of F5 and also observed significant associations for the known ABO and F11 regions. This pooled resource can be used to maximize power in GWAS of phenotypes collected across the cohorts and for studying gene-environment interactions as well as rare phenotypes and genotypes.
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    Genome-Wide Association Studies of Multiple Keratinocyte Cancers
    (Public Library of Science, 2017) Pardo, Luba M.; Li, Wen-Qing; Hwang, Shih-Jen; Verkouteren, Joris A. C.; Hofman, Albert; Uitterlinden, André G.; Kraft, Phillip; Turman, Constance; Han, Jiali; Cho, Eunyoung; Murabito, Joanne M.; Levy, Daniel; Qureshi, Abrar A.; Nijsten, Tamar
    There is strong evidence for a role of environmental risk factors involved in susceptibility to develop multiple keratinocyte cancers (mKCs), but whether genes are also involved in mKCs susceptibility has not been thoroughly investigated. We investigated whether single nucleotide polymorphisms (SNPs) are associated with susceptibility for mKCs. A genome-wide association study (GWAS) of 1,666 cases with mKCs and 1,950 cases with single KC (sKCs; controls) from Harvard cohorts (the Nurses' Health Study [NHS], NHS II, and the Health Professionals Follow-Up Study) and the Framingham Heart Study was carried-out using over 8 million SNPs (stage-1). We sought to replicate the most significant statistical associations (p-value≤ 5.5x10-6) in an independent cohort of 574 mKCs and 872 sKCs from the Rotterdam Study. In the discovery stage, 40 SNPs with suggestive associations (p-value ≤5.5x10-6) were identified, with eight independent SNPs tagging all 40 SNPs. The most significant SNP was located at chromosome 9 (rs7468390; p-value = 3.92x10-7). In stage-2, none of these SNPs replicated and only two of them were associated with mKCs in the same direction in the combined meta-analysis. We tested the associations for 19 previously reported basal cell carcinoma-related SNPs (candidate gene association analysis), and found that rs1805007 (MC1R locus) was significantly associated with risk of mKCs (p-value = 2.80x10-4). Although the suggestive SNPs with susceptibility for mKCs were not replicated, we found that previously identified BCC variants may also be associated with mKC, which the most significant association (rs1805007) located at the MC1R gene.
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    A meta-analysis of 87,040 individuals identifies 23 new susceptibility loci for prostate cancer
    (2014) Al Olama, Ali Amin; Kote-Jarai, Zsofia; Berndt, Sonja I.; Conti, David V.; Schumacher, Fredrick; Han, Ying; Benlloch, Sara; Hazelett, Dennis J.; Wang, Zhaoming; Saunders, Ed; Leongamornlert, Daniel; Lindstrom, Sara; Jugurnauth-Little, Sara; Dadaev, Tokhir; Tymrakiewicz, Malgorzata; Stram, Daniel O.; Rand, Kristin; Wan, Peggy; Stram, Alex; Sheng, Xin; Pooler, Loreall C.; Park, Karen; Xia, Lucy; Tyrer, Jonathan; Kolonel, Laurence N.; Le Marchand, Loic; Hoover, Robert N.; Machiela, Mitchell J.; Yeager, Merideth; Burdette, Laurie; Chung, Charles C.; Hutchinson, Amy; Yu, Kai; Goh, Chee; Ahmed, Mahbubl; Govindasami, Koveela; Guy, Michelle; Tammela, Teuvo L.J.; Auvinen, Anssi; Wahlfors, Tiina; Schleutker, Johanna; Visakorpi, Tapio; Leinonen, Katri A.; Xu, Jianfeng; Aly, Markus; Donovan, Jenny; Travis, Ruth C.; Key, Tim J.; Siddiq, Afshan; Canzian, Federico; Khaw, Kay-Tee; Takahashi, Atsushi; Kubo, Michiaki; Pharoah, Paul; Pashayan, Nora; Weischer, Maren; Nordestgaard, Borge G.; Nielsen, Sune F.; Klarskov, Peter; Røder, Martin Andreas; Iversen, Peter; Thibodeau, Stephen N.; McDonnell, Shannon K; Schaid, Daniel J; Stanford, Janet L.; Kolb, Suzanne; Holt, Sarah; Knudsen, Beatrice; Coll, Antonio Hurtado; Gapstur, Susan M.; Diver, W. Ryan; Stevens, Victoria L.; Maier, Christiane; Luedeke, Manuel; Herkommer, Kathleen; Rinckleb, Antje E.; Strom, Sara S.; Pettaway, Curtis; Yeboah, Edward D.; Tettey, Yao; Biritwum, Richard B.; Adjei, Andrew A.; Tay, Evelyn; Truelove, Ann; Niwa, Shelley; Chokkalingam, Anand P.; Cannon-Albright, Lisa; Cybulski, Cezary; Wokołorczyk, Dominika; Kluźniak, Wojciech; Park, Jong; Sellers, Thomas; Lin, Hui-Yi; Isaacs, William B.; Partin, Alan W.; Brenner, Hermann; Dieffenbach, Aida Karina; Stegmaier, Christa; Turman, Constance; Giovannucci, Edward; Ma, Jing; Stampfer, Meir; Penney, Kathryn; Mucci, Lorelei; John, Esther M.; Ingles, Sue A.; Kittles, Rick A.; Murphy, Adam B.; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej M.; Blot, William; Signorello, Lisa B; Zheng, Wei; Albanes, Demetrius; Virtamo, Jarmo; Weinstein, Stephanie; Nemesure, Barbara; Carpten, John; Leske, Cristina; Wu, Suh-Yuh; Hennis, Anselm; Kibel, Adam S.; Rybicki, Benjamin A.; Neslund-Dudas, Christine; Hsing, Ann W.; Chu, Lisa; Goodman, Phyllis J.; Klein, Eric A; Zheng, S. Lilly; Batra, Jyotsna; Clements, Judith; Spurdle, Amanda; Teixeira, Manuel R.; Paulo, Paula; Maia, Sofia; Slavov, Chavdar; Kaneva, Radka; Mitev, Vanio; Witte, John S.; Casey, Graham; Gillanders, Elizabeth M.; Seminara, Daniella; Riboli, Elio; Hamdy, Freddie C.; Coetzee, Gerhard A.; Li, Qiyuan; Freedman, Matthew L.; Hunter, David; Muir, Kenneth; Gronberg, Henrik; Neal, David E.; Southey, Melissa; Giles, Graham G.; Severi, Gianluca; Cook, Michael B.; Nakagawa, Hidewaki; Wiklund, Fredrik; Kraft, Phillip; Chanock, Stephen J.; Henderson, Brian E.; Easton, Douglas F.; Eeles, Rosalind A.; Haiman, Christopher A.
    Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of >10 million SNPs in 43,303prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three novel susceptibility loci were revealed at P<5×10-8; 15 variants were identified among men of European ancestry, 7 from multiethnic analyses and one was associated with early-onset prostate cancer. These 23 variants, in combination with the known prostate cancer risk variants, explain 33% of the familial risk of the disease in European ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the utility of combining ancestrally diverse populations to discover risk loci for disease.
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    A genome-wide association study of early menopause and the combined impact of identified variants
    (Oxford University Press, 2013) Perry, John R. B.; Corre, Tanguy; Esko, Tõnu; Chasman, Daniel; Fischer, Krista; Franceschini, Nora; He, Chunyan; Kutalik, Zoltan; Mangino, Massimo; Rose, Lynda M.; Vernon Smith, Albert; Stolk, Lisette; Sulem, Patrick; Weedon, Michael N.; Zhuang, Wei V.; Arnold, Alice; Ashworth, Alan; Bergmann, Sven; Buring, Julie; Burri, Andrea; Turman, Constance; Cornelis, Marilyn; Couper, David J.; Goodarzi, Mark O.; Gudnason, Vilmundur; Harris, Tamara; Hofman, Albert; Jones, Michael; Kraft, Phillip; Launer, Lenore; Laven, Joop S. E.; Li, Guoan; McKnight, Barbara; Masciullo, Corrado; Milani, Lili; Orr, Nicholas; Psaty, Bruce M.; Ridker, Paul; Rivadeneira, Fernando; Sala, Cinzia; Salumets, Andres; Schoemaker, Minouk; Traglia, Michela; Waeber, Gérard; Chanock, Stephen J.; Demerath, Ellen W.; Garcia, Melissa; Hankinson, Susan; Hu, Frank; Hunter, David; Lunetta, Kathryn L.; Metspalu, Andres; Montgomery, Grant W.; Murabito, Joanne M.; Newman, Anne B.; Ong, Ken K.; Spector, Tim D.; Stefansson, Kari; Swerdlow, Anthony J.; Thorsteinsdottir, Unnur; Van Dam, Rob; Uitterlinden, André G.; Visser, Jenny A.; Vollenweider, Peter; Toniolo, Daniela; Murray, Anna
    Early menopause (EM) affects up to 10% of the female population, reducing reproductive lifespan considerably. Currently, it constitutes the leading cause of infertility in the western world, affecting mainly those women who postpone their first pregnancy beyond the age of 30 years. The genetic aetiology of EM is largely unknown in the majority of cases. We have undertaken a meta-analysis of genome-wide association studies (GWASs) in 3493 EM cases and 13 598 controls from 10 independent studies. No novel genetic variants were discovered, but the 17 variants previously associated with normal age at natural menopause as a quantitative trait (QT) were also associated with EM and primary ovarian insufficiency (POI). Thus, EM has a genetic aetiology which overlaps variation in normal age at menopause and is at least partly explained by the additive effects of the same polygenic variants. The combined effect of the common variants captured by the single nucleotide polymorphism arrays was estimated to account for ∼30% of the variance in EM. The association between the combined 17 variants and the risk of EM was greater than the best validated non-genetic risk factor, smoking.
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    Genome-Wide and Candidate Gene Association Study of Cigarette Smoking Behaviors
    (Public Library of Science, 2009) Caporaso, Neil; Gu, Fangyi; Chatterjee, Nilanjan; Sheng-Chih, Jin; Yu, Kai; Yeager, Meredith; Jacobs, Kevin; Landi, Maria Teresa; Ziegler, Regina G.; Chanock, Stephen; Kraft, Peter; Bergen, Andrew W.; Turman, Constance; Wheeler, William; Hunter, David; Hankinson, Susan
    The contribution of common genetic variation to one or more established smoking behaviors was investigated in a joint analysis of two genome wide association studies (GWAS) performed as part of the Cancer Genetic Markers of Susceptibility (CGEMS) project in 2,329 men from the Prostate, Lung, Colon and Ovarian (PLCO) Trial, and 2,282 women from the Nurses' Health Study (NHS). We analyzed seven measures of smoking behavior, four continuous (cigarettes per day [CPD], age at initiation of smoking, duration of smoking, and pack years), and three binary (ever versus never smoking, ≤10 versus >10 cigarettes per day [CPDBI], and current versus former smoking). Association testing for each single nucleotide polymorphism (SNP) was conducted by study and adjusted for age, cohabitation/marital status, education, site, and principal components of population substructure. None of the SNPs achieved genome-wide significance (p<10\(^{-7}\)) in any combined analysis pooling evidence for association across the two studies; we observed between two and seven SNPs with p<10\(^{-5}\) for each of the seven measures. In the chr15q25.1 region spanning the nicotinic receptors CHRNA3 and CHRNA5, we identified multiple SNPs associated with CPD (p<10\(^{-3}\)), including rs1051730, which has been associated with nicotine dependence, smoking intensity and lung cancer risk. In parallel, we selected 11,199 SNPs drawn from 359 a priori candidate genes and performed individual-gene and gene-group analyses. After adjusting for multiple tests conducted within each gene, we identified between two and five genes associated with each measure of smoking behavior. Besides CHRNA3 and CHRNA5, MAOA was associated with CPDBI (gene-level p<5.4×10\(^{-5}\)), our analysis provides independent replication of the association between the chr15q25.1 region and smoking intensity and data for multiple other loci associated with smoking behavior that merit further follow-up.
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    A Genome-Wide Association Study Identifies Novel Alleles Associated with Hair Color and Skin Pigmentation
    (Public Library of Science, 2008) Kraft, Peter; Guo, Qun; Qureshi, Abrar; Duffy, David L.; Montgomery, Grant W.; Hayward, Nicholas K.; Thomas, Gilles; Hoover, Robert N.; Chanock, Stephen; Han, Jiali; Nan, Hongmei; Turman, Constance; Hankinson, Susan; Hu, Frank; Zhao, Zhen Zhen; Martin, Nicholas G.; Hunter, David
    We conducted a multi-stage genome-wide association study of natural hair color in more than 10,000 men and women of European ancestry from the United States and Australia. An initial analysis of 528,173 single nucleotide polymorphisms (SNPs) genotyped on 2,287 women identified IRF4 and SLC24A4 as loci highly associated with hair color, along with three other regions encompassing known pigmentation genes. We confirmed these associations in 7,028 individuals from three additional studies. Across these four studies, SLC24A4 rs12896399 andIRF4 rs12203592 showed strong associations with hair color, with \(p = 6.0×10^{−62}\) and \(p = 7.46×10^{−127}\), respectively. The IRF4 SNP was also associated with skin color \((p = 6.2×10^{−14})\), eye color \((p = 6.1×10^{−13})\), and skin tanning response to sunlight \((p = 3.9×10^{−89})\). A multivariable analysis pooling data from the initial GWAS and an additional 1,440 individuals suggested that the association between rs12203592 and hair color was independent of rs1540771, a SNP between the IRF4 and EXOC2 genes previously found to be associated with hair color. After adjustment for rs12203592, the association between rs1540771 and hair color was not significant (p = 0.52). One variant in the MATP gene was associated with hair color. A variant in the HERC2 gene upstream of the OCA2 gene showed the strongest and independent association with hair color compared with other SNPs in this region, including three previously reported SNPs. The signals detected in a region around the MC1R gene were explained byMC1R red hair color alleles. Our results suggest that the IRF4 and SLC24A4 loci are associated with human hair color and skin pigmentation.