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2. Evaluation of association of HNF1B variants with diverse cancers: collaborative analysis of data from 19 genome-wide association studies.

Author

Elliott, Katherine S, Zeggini, Eleftheria, McCarthy, Mark I, Gudmundsson, Julius, Sulem, Patrick, Stacey, Simon N, Thorlacius, Steinunn, Amundadottir, Laufey, Grönberg, Henrik, Xu, Jianfeng, Gaborieau, Valerie, Eeles, Rosalind A, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Muir, Kenneth, Hwang, Shih-Jen, Spitz, Margaret R, Zanke, Brent, Carvajal-Carmona, Luis, Brown, Kevin M, Australian Melanoma Family Study Investigators, Hayward, Nicholas K, Macgregor, Stuart, Tomlinson, Ian PM, Lemire, Mathieu, Amos, Christopher I, Murabito, Joanne M, Isaacs, William B, Easton, Douglas F, Brennan, Paul, PanScan Consortium, Barkardottir, Rosa B, Gudbjartsson, Daniel F, Rafnar, Thorunn, Hunter, David J, Chanock, Stephen J, Stefansson, Kari, and Ioannidis, John PA

Subjects
Australian Melanoma Family Study Investigators, PanScan Consortium, Humans, Neoplasms, Genetic Predisposition to Disease, Cooperative Behavior, Polymorphism, Single Nucleotide, Databases, Genetic, Hepatocyte Nuclear Factor 1-beta, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Databases, Genetic, General Science & Technology
Abstract

BackgroundGenome-wide association studies have found type 2 diabetes-associated variants in the HNF1B gene to exhibit reciprocal associations with prostate cancer risk. We aimed to identify whether these variants may have an effect on cancer risk in general versus a specific effect on prostate cancer only.Methodology/principal findingsIn a collaborative analysis, we collected data from GWAS of cancer phenotypes for the frequently reported variants of HNF1B, rs4430796 and rs7501939, which are in linkage disequilibrium (r(2) = 0.76, HapMap CEU). Overall, the analysis included 16 datasets on rs4430796 with 19,640 cancer cases and 21,929 controls; and 21 datasets on rs7501939 with 26,923 cases and 49,085 controls. Malignancies other than prostate cancer included colorectal, breast, lung and pancreatic cancers, and melanoma. Meta-analysis showed large between-dataset heterogeneity that was driven by different effects in prostate cancer and other cancers. The per-T2D-risk-allele odds ratios (95% confidence intervals) for rs4430796 were 0.79 (0.76, 0.83)] per G allele for prostate cancer (p

Published
2010

5. A comprehensive survey of genetic variation in 20,691 subjects from four large cohorts

Author

Lindström, Sara, primary, Loomis, Stephanie, additional, Turman, Constance, additional, Huang, Hongyan, additional, Huang, Jinyan, additional, Aschard, Hugues, additional, Chan, Andrew T., additional, Choi, Hyon, additional, Cornelis, Marilyn, additional, Curhan, Gary, additional, De Vivo, Immaculata, additional, Eliassen, A. Heather, additional, Fuchs, Charles, additional, Gaziano, Michael, additional, Hankinson, Susan E., additional, Hu, Frank, additional, Jensen, Majken, additional, Kang, Jae H., additional, Kabrhel, Christopher, additional, Liang, Liming, additional, Pasquale, Louis R., additional, Rimm, Eric, additional, Stampfer, Meir J., additional, Tamimi, Rulla M., additional, Tworoger, Shelley S., additional, Wiggs, Janey L., additional, Hunter, David J., additional, and Kraft, Peter, additional

Published
2017
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7. Exome-Wide Association Study of Endometrial Cancer in a Multiethnic Population

Author

Chen, Maxine M., primary, Crous-Bou, Marta, additional, Setiawan, Veronica W., additional, Prescott, Jennifer, additional, Olson, Sara H., additional, Wentzensen, Nicolas, additional, Black, Amanda, additional, Brinton, Louise, additional, Chen, Chu, additional, Chen, Constance, additional, Cook, Linda S., additional, Doherty, Jennifer, additional, Friedenreich, Christine M., additional, Hankinson, Susan E., additional, Hartge, Patricia, additional, Henderson, Brian E., additional, Hunter, David J., additional, Le Marchand, Loic, additional, Liang, Xiaolin, additional, Lissowska, Jolanta, additional, Lu, Lingeng, additional, Orlow, Irene, additional, Petruzella, Stacey, additional, Polidoro, Silvia, additional, Pooler, Loreall, additional, Rebbeck, Timothy R., additional, Risch, Harvey, additional, Sacerdote, Carlotta, additional, Schumacher, Frederick, additional, Sheng, Xin, additional, Shu, Xiao-ou, additional, Weiss, Noel S., additional, Xia, Lucy, additional, Van Den Berg, David, additional, Yang, Hannah P., additional, Yu, Herbert, additional, Chanock, Stephen, additional, Haiman, Christopher, additional, Kraft, Peter, additional, and De Vivo, Immaculata, additional

Published
2014
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8. A Genome-Wide “Pleiotropy Scan” Does Not Identify New Susceptibility Loci for Estrogen Receptor Negative Breast Cancer

Author

Campa, Daniele, primary, Barrdahl, Myrto, additional, Tsilidis, Konstantinos K., additional, Severi, Gianluca, additional, Diver, W. Ryan, additional, Siddiq, Afshan, additional, Chanock, Stephen, additional, Hoover, Robert N., additional, Ziegler, Regina G., additional, Berg, Christine D., additional, Buys, Saundra S., additional, Haiman, Christopher A., additional, Henderson, Brian E., additional, Schumacher, Fredrick R., additional, Le Marchand, Loïc, additional, Flesch-Janys, Dieter, additional, Lindström, Sara, additional, Hunter, David J., additional, Hankinson, Susan E., additional, Willett, Walter C., additional, Kraft, Peter, additional, Cox, David G., additional, Khaw, Kay-Tee, additional, Tjønneland, Anne, additional, Dossus, Laure, additional, Trichopoulos, Dimitrios, additional, Panico, Salvatore, additional, van Gils, Carla H., additional, Weiderpass, Elisabete, additional, Barricarte, Aurelio, additional, Sund, Malin, additional, Gaudet, Mia M., additional, Giles, Graham, additional, Southey, Melissa, additional, Baglietto, Laura, additional, Chang-Claude, Jenny, additional, Kaaks, Rudolf, additional, and Canzian, Federico, additional

Published
2014
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9. An Absolute Risk Model to Identify Individuals at Elevated Risk for Pancreatic Cancer in the General Population

Author

Klein, Alison P., primary, Lindström, Sara, additional, Mendelsohn, Julie B., additional, Steplowski, Emily, additional, Arslan, Alan A., additional, Bueno-de-Mesquita, H. Bas, additional, Fuchs, Charles S., additional, Gallinger, Steven, additional, Gross, Myron, additional, Helzlsouer, Kathy, additional, Holly, Elizabeth A., additional, Jacobs, Eric J., additional, LaCroix, Andrea, additional, Li, Donghui, additional, Mandelson, Margaret T., additional, Olson, Sara H., additional, Petersen, Gloria M., additional, Risch, Harvey A., additional, Stolzenberg-Solomon, Rachael Z., additional, Zheng, Wei, additional, Amundadottir, Laufey, additional, Albanes, Demetrius, additional, Allen, Naomi E., additional, Bamlet, William R., additional, Boutron-Ruault, Marie-Christine, additional, Buring, Julie E., additional, Bracci, Paige M., additional, Canzian, Federico, additional, Clipp, Sandra, additional, Cotterchio, Michelle, additional, Duell, Eric J., additional, Elena, Joanne, additional, Gaziano, J. Michael, additional, Giovannucci, Edward L., additional, Goggins, Michael, additional, Hallmans, Göran, additional, Hassan, Manal, additional, Hutchinson, Amy, additional, Hunter, David J., additional, Kooperberg, Charles, additional, Kurtz, Robert C., additional, Liu, Simin, additional, Overvad, Kim, additional, Palli, Domenico, additional, Patel, Alpa V., additional, Rabe, Kari G., additional, Shu, Xiao-Ou, additional, Slimani, Nadia, additional, Tobias, Geoffrey S., additional, Trichopoulos, Dimitrios, additional, Van Den Eeden, Stephen K., additional, Vineis, Paolo, additional, Virtamo, Jarmo, additional, Wactawski-Wende, Jean, additional, Wolpin, Brian M., additional, Yu, Herbert, additional, Yu, Kai, additional, Zeleniuch-Jacquotte, Anne, additional, Chanock, Stephen J., additional, Hoover, Robert N., additional, Hartge, Patricia, additional, and Kraft, Peter, additional

Published
2013
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10. Mannose-Binding Lectin 2 Gene and Risk of Adult Glioma

Author

Michaud, Dominique S., primary, Siddiq, Afshan, additional, Cox, David G., additional, Backes, Danielle M., additional, Calboli, Federico C. F., additional, Sughrue, Michael E., additional, Gaziano, J. Michael, additional, Ma, Jing, additional, Stampfer, Meir, additional, Tworoger, Shelley S., additional, Hunter, David J., additional, Camargo, Carlos A., additional, and Parsa, Andrew T., additional

Published
2013
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11. Genome-Wide Association Study of Circulating Estradiol, Testosterone, and Sex Hormone-Binding Globulin in Postmenopausal Women

Author

Prescott, Jennifer, primary, Thompson, Deborah J., additional, Kraft, Peter, additional, Chanock, Stephen J., additional, Audley, Tina, additional, Brown, Judith, additional, Leyland, Jean, additional, Folkerd, Elizabeth, additional, Doody, Deborah, additional, Hankinson, Susan E., additional, Hunter, David J., additional, Jacobs, Kevin B., additional, Dowsett, Mitch, additional, Cox, David G., additional, Easton, Douglas F., additional, and De Vivo, Immaculata, additional

Published
2012
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12. Genome-Wide Association Study of Relative Telomere Length

Author

Prescott, Jennifer, primary, Kraft, Peter, additional, Chasman, Daniel I., additional, Savage, Sharon A., additional, Mirabello, Lisa, additional, Berndt, Sonja I., additional, Weissfeld, Joel L., additional, Han, Jiali, additional, Hayes, Richard B., additional, Chanock, Stephen J., additional, Hunter, David J., additional, and De Vivo, Immaculata, additional

Published
2011
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13. Characterizing Associations and SNP-Environment Interactions for GWAS-Identified Prostate Cancer Risk Markers—Results from BPC3

Author

Lindstrom, Sara, primary, Schumacher, Fredrick, additional, Siddiq, Afshan, additional, Travis, Ruth C., additional, Campa, Daniele, additional, Berndt, Sonja I., additional, Diver, W. Ryan, additional, Severi, Gianluca, additional, Allen, Naomi, additional, Andriole, Gerald, additional, Bueno-de-Mesquita, Bas, additional, Chanock, Stephen J., additional, Crawford, David, additional, Gaziano, J. Michael, additional, Giles, Graham G., additional, Giovannucci, Edward, additional, Guo, Carolyn, additional, Haiman, Christopher A., additional, Hayes, Richard B., additional, Halkjaer, Jytte, additional, Hunter, David J., additional, Johansson, Mattias, additional, Kaaks, Rudolf, additional, Kolonel, Laurence N., additional, Navarro, Carmen, additional, Riboli, Elio, additional, Sacerdote, Carlotta, additional, Stampfer, Meir, additional, Stram, Daniel O., additional, Thun, Michael J., additional, Trichopoulos, Dimitrios, additional, Virtamo, Jarmo, additional, Weinstein, Stephanie J., additional, Yeager, Meredith, additional, Henderson, Brian, additional, Ma, Jing, additional, Le Marchand, Loic, additional, Albanes, Demetrius, additional, and Kraft, Peter, additional

Published
2011
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15. Genome-Wide and Candidate Gene Association Study of Cigarette Smoking Behaviors

Author

Caporaso, Neil, primary, Gu, Fangyi, additional, Chatterjee, Nilanjan, additional, Sheng-Chih, Jin, additional, Yu, Kai, additional, Yeager, Meredith, additional, Chen, Constance, additional, Jacobs, Kevin, additional, Wheeler, William, additional, Landi, Maria Teresa, additional, Ziegler, Regina G., additional, Hunter, David J., additional, Chanock, Stephen, additional, Hankinson, Susan, additional, Kraft, Peter, additional, and Bergen, Andrew W., additional

Published
2009
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16. Comprehensive Biostatistical Analysis of CpG Island Methylator Phenotype in Colorectal Cancer Using a Large Population-Based Sample

Author

Nosho, Katsuhiko, primary, Irahara, Natsumi, additional, Shima, Kaori, additional, Kure, Shoko, additional, Kirkner, Gregory J., additional, Schernhammer, Eva S., additional, Hazra, Aditi, additional, Hunter, David J., additional, Quackenbush, John, additional, Spiegelman, Donna, additional, Giovannucci, Edward L., additional, Fuchs, Charles S., additional, and Ogino, Shuji, additional

Published
2008
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18. IGF-1, IGFBP-1, and IGFBP-3 Polymorphisms Predict Circulating IGF Levels but Not Breast Cancer Risk: Findings from the Breast and Prostate Cancer Cohort Consortium (BPC3)

Author

Patel, Alpa V., primary, Cheng, Iona, additional, Canzian, Federico, additional, Le Marchand, Loïc, additional, Thun, Michael J., additional, Berg, Christine D., additional, Buring, Julie, additional, Calle, Eugenia E., additional, Chanock, Stephen, additional, Clavel-Chapelon, Francoise, additional, Cox, David G., additional, Dorronsoro, Miren, additional, Dossus, Laure, additional, Haiman, Christopher A., additional, Hankinson, Susan E., additional, Henderson, Brian E., additional, Hoover, Robert, additional, Hunter, David J., additional, Kaaks, Rudolf, additional, Kolonel, Laurence N., additional, Kraft, Peter, additional, Linseisen, Jakob, additional, Lund, Eiliv, additional, Manjer, Jonas, additional, McCarty, Catherine, additional, Peeters, Petra H. M., additional, Pike, Malcolm C., additional, Pollak, Michael, additional, Riboli, Elio, additional, Stram, Daniel O., additional, Tjonneland, Anne, additional, Travis, Ruth C., additional, Trichopoulos, Dimitrios, additional, Tumino, Rosario, additional, Yeager, Meredith, additional, Ziegler, Regina G., additional, and Feigelson, Heather Spencer, additional

Published
2008
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19. A Genome-Wide “Pleiotropy Scan” Does Not Identify New Susceptibility Loci for Estrogen Receptor Negative Breast Cancer.

Author

Campa, Daniele, Barrdahl, Myrto, Tsilidis, Konstantinos K., Severi, Gianluca, Diver, W. Ryan, Siddiq, Afshan, Chanock, Stephen, Hoover, Robert N., Ziegler, Regina G., Berg, Christine D., Buys, Saundra S., Haiman, Christopher A., Henderson, Brian E., Schumacher, Fredrick R., Le Marchand, Loïc, Flesch-Janys, Dieter, Lindström, Sara, Hunter, David J., Hankinson, Susan E., and Willett, Walter C.

Subjects
BREAST cancer, GENETIC pleiotropy, DISEASE susceptibility, ESTROGEN receptors, SINGLE nucleotide polymorphisms, GENETIC epidemiology
Abstract

Approximately 15–30% of all breast cancer tumors are estrogen receptor negative (ER−). Compared with ER-positive (ER+) disease they have an earlier age at onset and worse prognosis. Despite the vast number of risk variants identified for numerous cancer types, only seven loci have been unambiguously identified for ER-negative breast cancer. With the aim of identifying new susceptibility SNPs for this disease we performed a pleiotropic genome-wide association study (GWAS). We selected 3079 SNPs associated with a human complex trait or disease at genome-wide significance level (P<5×10−8) to perform a secondary analysis of an ER-negative GWAS from the National Cancer Institute's Breast and Prostate Cancer Cohort Consortium (BPC3), including 1998 cases and 2305 controls from prospective studies. We then tested the top ten associations (i.e. with the lowest P-values) using three additional populations with a total sample size of 3509 ER+ cases, 2543 ER− cases and 7031 healthy controls. None of the 3079 selected variants in the BPC3 ER-GWAS were significant at the adjusted threshold. 186 variants were associated with ER− breast cancer risk at a conventional threshold of P<0.05, with P-values ranging from 0.049 to 2.3×10−4. None of the variants reached statistical significance in the replication phase. In conclusion, this study did not identify any novel susceptibility loci for ER-breast cancer using a “pleiotropic approach”. [ABSTRACT FROM AUTHOR]

Published
2014
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20. Population Substructure and Control Selection in Genome-Wide Association Studies.

Author

Kai Yu, Zhaoming Wang, Qizhai Li, Wacholder, Sholom, Hunter, David J., Hoover, Robert N., Chanock, Stephen, and Thomas, Gilles

Subjects
EUROPEAN Americans, PROSTATE cancer, PERMUTATIONS, GENOMES, COST effectiveness, BIOMARKERS, GENETIC polymorphisms, ETIOLOGY of diseases, EMPIRICAL research
Abstract

Determination of the relevance of both demanding classical epidemiologic criteria for control selection and robust handling of population stratification (PS) represents a major challenge in the design and analysis of genome-wide association studies (GWAS). Empirical data from two GWAS in European Americans of the Cancer Genetic Markers of Susceptibility (CGEMS) project were used to evaluate the impact of PS in studies with different control selection strategies. In each of the two original case-control studies nested in corresponding prospective cohorts, a minor confounding effect due to PS (inflation factor λ of 1.025 and 1.005) was observed. In contrast, when the control groups were exchanged to mimic a cost-effective but theoretically less desirable control selection strategy, the confounding effects were larger (l of 1.090 and 1.062). A panel of 12,898 autosomal SNPs common to both the Illumina and Affymetrix commercial platforms and with low local background linkage disequilibrium (pair-wise r2,0.004) was selected to infer population substructure with principal component analysis. A novel permutation procedure was developed for the correction of PS that identified a smaller set of principal components and achieved a better control of type I error (to l of 1.032 and 1.006, respectively) than currently used methods. The overlap between sets of SNPs in the bottom 5% of p-values based on the new test and the test without PS correction was about 80%, with the majority of discordant SNPs having both ranks close to the threshold. Thus, for the CGEMS GWAS of prostate and breast cancer conducted in European Americans, PS does not appear to be a major problem in well-designed studies. A study using suboptimal controls can have acceptable type I error when an effective strategy for the correction of PS is employed. [ABSTRACT FROM AUTHOR]

Published
2008
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21. MicroRNA related polymorphisms and breast cancer risk.

Author

Khan S, Greco D, Michailidou K, Milne RL, Muranen TA, Heikkinen T, Aaltonen K, Dennis J, Bolla MK, Liu J, Hall P, Irwanto A, Humphreys K, Li J, Czene K, Chang-Claude J, Hein R, Rudolph A, Seibold P, Flesch-Janys D, Fletcher O, Peto J, dos Santos Silva I, Johnson N, Gibson L, Aitken Z, Hopper JL, Tsimiklis H, Bui M, Makalic E, Schmidt DF, Southey MC, Apicella C, Stone J, Waisfisz Q, Meijers-Heijboer H, Adank MA, van der Luijt RB, Meindl A, Schmutzler RK, Müller-Myhsok B, Lichtner P, Turnbull C, Rahman N, Chanock SJ, Hunter DJ, Cox A, Cross SS, Reed MW, Schmidt MK, Broeks A, Van't Veer LJ, Hogervorst FB, Fasching PA, Schrauder MG, Ekici AB, Beckmann MW, Bojesen SE, Nordestgaard BG, Nielsen SF, Flyger H, Benitez J, Zamora PM, Perez JI, Haiman CA, Henderson BE, Schumacher F, Le Marchand L, Pharoah PD, Dunning AM, Shah M, Luben R, Brown J, Couch FJ, Wang X, Vachon C, Olson JE, Lambrechts D, Moisse M, Paridaens R, Christiaens MR, Guénel P, Truong T, Laurent-Puig P, Mulot C, Marme F, Burwinkel B, Schneeweiss A, Sohn C, Sawyer EJ, Tomlinson I, Kerin MJ, Miller N, Andrulis IL, Knight JA, Tchatchou S, Mulligan AM, Dörk T, Bogdanova NV, Antonenkova NN, Anton-Culver H, Darabi H, Eriksson M, Garcia-Closas M, Figueroa J, Lissowska J, Brinton L, Devilee P, Tollenaar RA, Seynaeve C, van Asperen CJ, Kristensen VN, Slager S, Toland AE, Ambrosone CB, Yannoukakos D, Lindblom A, Margolin S, Radice P, Peterlongo P, Barile M, Mariani P, Hooning MJ, Martens JW, Collée JM, Jager A, Jakubowska A, Lubinski J, Jaworska-Bieniek K, Durda K, Giles GG, McLean C, Brauch H, Brüning T, Ko YD, Brenner H, Dieffenbach AK, Arndt V, Stegmaier C, Swerdlow A, Ashworth A, Orr N, Jones M, Simard J, Goldberg MS, Labrèche F, Dumont M, Winqvist R, Pylkäs K, Jukkola-Vuorinen A, Grip M, Kataja V, Kosma VM, Hartikainen JM, Mannermaa A, Hamann U, Chenevix-Trench G, Blomqvist C, Aittomäki K, Easton DF, and Nevanlinna H

Subjects
3' Untranslated Regions, Binding Sites, Case-Control Studies, Chromosome Mapping, Computational Biology, Female, Genome-Wide Association Study, Genotype, Humans, Receptors, Estrogen metabolism, Breast Neoplasms diagnosis, Breast Neoplasms genetics, MicroRNAs genetics, Polymorphism, Single Nucleotide
Abstract

Genetic variations, such as single nucleotide polymorphisms (SNPs) in microRNAs (miRNA) or in the miRNA binding sites may affect the miRNA dependent gene expression regulation, which has been implicated in various cancers, including breast cancer, and may alter individual susceptibility to cancer. We investigated associations between miRNA related SNPs and breast cancer risk. First we evaluated 2,196 SNPs in a case-control study combining nine genome wide association studies (GWAS). Second, we further investigated 42 SNPs with suggestive evidence for association using 41,785 cases and 41,880 controls from 41 studies included in the Breast Cancer Association Consortium (BCAC). Combining the GWAS and BCAC data within a meta-analysis, we estimated main effects on breast cancer risk as well as risks for estrogen receptor (ER) and age defined subgroups. Five miRNA binding site SNPs associated significantly with breast cancer risk: rs1045494 (odds ratio (OR) 0.92; 95% confidence interval (CI): 0.88-0.96), rs1052532 (OR 0.97; 95% CI: 0.95-0.99), rs10719 (OR 0.97; 95% CI: 0.94-0.99), rs4687554 (OR 0.97; 95% CI: 0.95-0.99, and rs3134615 (OR 1.03; 95% CI: 1.01-1.05) located in the 3' UTR of CASP8, HDDC3, DROSHA, MUSTN1, and MYCL1, respectively. DROSHA belongs to miRNA machinery genes and has a central role in initial miRNA processing. The remaining genes are involved in different molecular functions, including apoptosis and gene expression regulation. Further studies are warranted to elucidate whether the miRNA binding site SNPs are the causative variants for the observed risk effects.

Published
2014
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22. A genome-wide association search for type 2 diabetes genes in African Americans.

Author

Palmer ND, McDonough CW, Hicks PJ, Roh BH, Wing MR, An SS, Hester JM, Cooke JN, Bostrom MA, Rudock ME, Talbert ME, Lewis JP, Ferrara A, Lu L, Ziegler JT, Sale MM, Divers J, Shriner D, Adeyemo A, Rotimi CN, Ng MC, Langefeld CD, Freedman BI, Bowden DW, Voight BF, Scott LJ, Steinthorsdottir V, Morris AP, Dina C, Welch RP, Zeggini E, Huth C, Aulchenko YS, Thorleifsson G, McCulloch LJ, Ferreira T, Grallert H, Amin N, Wu G, Willer CJ, Raychaudhuri S, McCarroll SA, Langenberg C, Hofmann OM, Dupuis J, Qi L, Segrè AV, van Hoek M, Navarro P, Ardlie K, Balkau B, Benediktsson R, Bennett AJ, Blagieva R, Boerwinkle E, Bonnycastle LL, Boström KB, Bravenboer B, Bumpstead S, Burtt NP, Charpentier G, Chines PS, Cornelis M, Couper DJ, Crawford G, Doney AS, Elliott KS, Elliott AL, Erdos MR, Fox CS, Franklin CS, Ganser M, Gieger C, Grarup N, Green T, Griffin S, Groves CJ, Guiducci C, Hadjadj S, Hassanali N, Herder C, Isomaa B, Jackson AU, Johnson PR, Jørgensen T, Kao WH, Klopp N, Kong A, Kraft P, Kuusisto J, Lauritzen T, Li M, Lieverse A, Lindgren CM, Lyssenko V, Marre M, Meitinger T, Midthjell K, Morken MA, Narisu N, Nilsson P, Owen KR, Payne F, Perry JR, Petersen AK, Platou C, Proença C, Prokopenko I, Rathmann W, Rayner NW, Robertson NR, Rocheleau G, Roden M, Sampson MJ, Saxena R, Shields BM, Shrader P, Sigurdsson G, Sparsø T, Strassburger K, Stringham HM, Sun Q, Swift AJ, Thorand B, Tichet J, Tuomi T, van Dam RM, van Haeften TW, van Herpt T, van Vliet-Ostaptchouk JV, Walters GB, Weedon MN, Wijmenga C, Witteman J, Bergman RN, Cauchi S, Collins FS, Gloyn AL, Gyllensten U, Hansen T, Hide WA, Hitman GA, Hofman A, Hunter DJ, Hveem K, Laakso M, Mohlke KL, Morris AD, Palmer CN, Pramstaller PP, Rudan I, Sijbrands E, Stein LD, Tuomilehto J, Uitterlinden A, Walker M, Wareham NJ, Watanabe RM, Abecasis GR, Boehm BO, Campbell H, Daly MJ, Hattersley AT, Hu FB, Meigs JB, Pankow JS, Pedersen O, Wichmann HE, Barroso I, Florez JC, Frayling TM, Groop L, Sladek R, Thorsteinsdottir U, Wilson JF, Illig T, Froguel P, van Duijn CM, Stefansson K, Altshuler D, Boehnke M, McCarthy MI, Soranzo N, Wheeler E, Glazer NL, Bouatia-Naji N, Mägi R, Randall J, Johnson T, Elliott P, Rybin D, Henneman P, Dehghan A, Hottenga JJ, Song K, Goel A, Egan JM, Lajunen T, Doney A, Kanoni S, Cavalcanti-Proença C, Kumari M, Timpson NJ, Zabena C, Ingelsson E, An P, O'Connell J, Luan J, Elliott A, McCarroll SA, Roccasecca RM, Pattou F, Sethupathy P, Ariyurek Y, Barter P, Beilby JP, Ben-Shlomo Y, Bergmann S, Bochud M, Bonnefond A, Borch-Johnsen K, Böttcher Y, Brunner E, Bumpstead SJ, Chen YD, Chines P, Clarke R, Coin LJ, Cooper MN, Crisponi L, Day IN, de Geus EJ, Delplanque J, Fedson AC, Fischer-Rosinsky A, Forouhi NG, Frants R, Franzosi MG, Galan P, Goodarzi MO, Graessler J, Grundy S, Gwilliam R, Hallmans G, Hammond N, Han X, Hartikainen AL, Hayward C, Heath SC, Hercberg S, Hicks AA, Hillman DR, Hingorani AD, Hui J, Hung J, Jula A, Kaakinen M, Kaprio J, Kesaniemi YA, Kivimaki M, Knight B, Koskinen S, Kovacs P, Kyvik KO, Lathrop GM, Lawlor DA, Le Bacquer O, Lecoeur C, Li Y, Mahley R, Mangino M, Manning AK, Martínez-Larrad MT, McAteer JB, McPherson R, Meisinger C, Melzer D, Meyre D, Mitchell BD, Mukherjee S, Naitza S, Neville MJ, Oostra BA, Orrù M, Pakyz R, Paolisso G, Pattaro C, Pearson D, Peden JF, Pedersen NL, Perola M, Pfeiffer AF, Pichler I, Polasek O, Posthuma D, Potter SC, Pouta A, Province MA, Psaty BM, Rayner NW, Rice K, Ripatti S, Rivadeneira F, Rolandsson O, Sandbaek A, Sandhu M, Sanna S, Sayer AA, Scheet P, Seedorf U, Sharp SJ, Shields B, Sijbrands EJ, Silveira A, Simpson L, Singleton A, Smith NL, Sovio U, Swift A, Syddall H, Syvänen AC, Tanaka T, Tönjes A, Uitterlinden AG, van Dijk KW, Varma D, Visvikis-Siest S, Vitart V, Vogelzangs N, Waeber G, Wagner PJ, Walley A, Ward KL, Watkins H, Wild SH, Willemsen G, Witteman JC, Yarnell JW, Zelenika D, Zethelius B, Zhai G, Zhao JH, Zillikens MC, Borecki IB, Loos RJ, Meneton P, Magnusson PK, Nathan DM, Williams GH, Silander K, Salomaa V, Smith GD, Bornstein SR, Schwarz P, Spranger J, Karpe F, Shuldiner AR, Cooper C, Dedoussis GV, Serrano-Ríos M, Lind L, Palmer LJ, Franks PW, Ebrahim S, Marmot M, Kao WH, Pramstaller PP, Wright AF, Stumvoll M, Hamsten A, Buchanan TA, Valle TT, Rotter JI, Siscovick DS, Penninx BW, Boomsma DI, Deloukas P, Spector TD, Ferrucci L, Cao A, Scuteri A, Schlessinger D, Uda M, Ruokonen A, Jarvelin MR, Waterworth DM, Vollenweider P, Peltonen L, Mooser V, and Sladek R

Subjects
Adult, Aged, Case-Control Studies, Cohort Studies, Female, Genetic Predisposition to Disease, Genotype, Humans, Male, Meta-Analysis as Topic, Middle Aged, Polymorphism, Single Nucleotide, Validation Studies as Topic, Black or African American genetics, Diabetes Mellitus, Type 2 ethnology, Diabetes Mellitus, Type 2 genetics, Genome-Wide Association Study
Abstract

African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations.

Published
2012
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