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1. Cluster effect for SNP–SNP interaction pairs for predicting complex traits

Author

Lin, Hui-Yi, Mazumder, Harun, Sarkar, Indrani, Huang, Po-Yu, Eeles, Rosalind A., Kote-Jarai, Zsofia, Muir, Kenneth R., Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, Neal, David E., Nielsen, Sune F., Nordestgaard, Børge G., Grönberg, Henrik, Wiklund, Fredrik, MacInnis, Robert J., Haiman, Christopher A., Travis, Ruth C., Stanford, Janet L., Kibel, Adam S., Cybulski, Cezary, Khaw, Kay-Tee, Maier, Christiane, Thibodeau, Stephen N., Teixeira, Manuel R., Cannon-Albright, Lisa, Brenner, Hermann, Kaneva, Radka, Pandha, Hardev, and Park, Jong Y.

Published
2024
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3. A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

Author

Middha, Pooja, Wang, Xiaoliang, Behrens, Sabine, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Michailidou, Kyriaki, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Arndt, Volker, Aronson, Kristan J, Auer, Paul L, Augustinsson, Annelie, Baert, Thaïs, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Benitez, Javier, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Brooks-Wilson, Angela, Campa, Daniele, Canzian, Federico, Carracedo, Angel, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Cordina-Duverger, Emilie, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dossus, Laure, Dugué, Pierre-Antoine, Eliassen, A Heather, Eriksson, Mikael, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine D, Fletcher, Olivia, Flyger, Henrik, Gabrielson, Marike, Gago-Dominguez, Manuela, Giles, Graham G, González-Neira, Anna, Grassmann, Felix, Grundy, Anne, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Hankinson, Susan E, Harkness, Elaine F, Holleczek, Bernd, Hoppe, Reiner, Hopper, John L, Houlston, Richard S, Howell, Anthony, Hunter, David J, Ingvar, Christian, Isaksson, Karolin, Jernström, Helena, John, Esther M, Jones, Michael E, Kaaks, Rudolf, Keeman, Renske, Kitahara, Cari M, Ko, Yon-Dschun, Koutros, Stella, Kurian, Allison W, Lacey, James V, Lambrechts, Diether, Larson, Nicole L, Larsson, Susanna, Le Marchand, Loic, Lejbkowicz, Flavio, Li, Shuai, Linet, Martha, Lissowska, Jolanta, Martinez, Maria Elena, Maurer, Tabea, Mulligan, Anna Marie, Mulot, Claire, Murphy, Rachel A, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Norman, Aaron, O’Brien, Katie M, Olson, Janet E, Patel, Alpa V, Prentice, Ross, Rees-Punia, Erika, Rennert, Gad, Rhenius, Valerie, Ruddy, Kathryn J, and Sandler, Dale P

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Cancer Genomics, Human Genome, Estrogen, Cancer, Women's Health, Genetics, Prevention, Aging, Breast Cancer, 2.1 Biological and endogenous factors, Adult, Female, Humans, Gene-Environment Interaction, Genetic Predisposition to Disease, Breast Neoplasms, Bayes Theorem, Genome-Wide Association Study, Risk Factors, Polymorphism, Single Nucleotide, Case-Control Studies, Breast cancer, Gene-environment interactions, Genetic epidemiology, European ancestry, CTS Consortium, ABCTB Investigators, kConFab Investigators, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundGenome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.MethodsAnalyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.ResultsAssuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability

Published
2023

4. Prostate cancer risk stratification improvement across multiple ancestries with new polygenic hazard score

Author

Huynh-Le, Minh-Phuong, Karunamuni, Roshan, Fan, Chun Chieh, Asona, Lui, Thompson, Wesley K, Martinez, Maria Elena, Eeles, Rosalind A, Kote-Jarai, Zsofia, Muir, Kenneth R, Lophatananon, Artitaya, Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, Grönberg, Henrik, Neal, David E, Nordestgaard, Børge G, Tangen, Catherine M, MacInnis, Robert J, Wolk, Alicja, Albanes, Demetrius, Haiman, Christopher A, Travis, Ruth C, Blot, William J, Stanford, Janet L, Mucci, Lorelei A, West, Catharine ML, Nielsen, Sune F, Kibel, Adam S, Cussenot, Olivier, Berndt, Sonja I, Koutros, Stella, Sørensen, Karina Dalsgaard, Cybulski, Cezary, Grindedal, Eli Marie, Menegaux, Florence, Park, Jong Y, Ingles, Sue A, Maier, Christiane, Hamilton, Robert J, Rosenstein, Barry S, Lu, Yong-Jie, Watya, Stephen, Vega, Ana, Kogevinas, Manolis, Wiklund, Fredrik, Penney, Kathryn L, Huff, Chad D, Teixeira, Manuel R, Multigner, Luc, Leach, Robin J, Brenner, Hermann, John, Esther M, Kaneva, Radka, Logothetis, Christopher J, Neuhausen, Susan L, De Ruyck, Kim, Ost, Piet, Razack, Azad, Newcomb, Lisa F, Fowke, Jay H, Gamulin, Marija, Abraham, Aswin, Claessens, Frank, Castelao, Jose Esteban, Townsend, Paul A, Crawford, Dana C, Petrovics, Gyorgy, van Schaik, Ron HN, Parent, Marie-Élise, Hu, Jennifer J, Zheng, Wei, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, and Seibert, Tyler M

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Aging, Prostate Cancer, Cancer, Urologic Diseases, Prevention, Genetics, Good Health and Well Being, Male, Humans, Prostate-Specific Antigen, Prostatic Neoplasms, Early Detection of Cancer, Polymorphism, Single Nucleotide, Risk Factors, Risk Assessment, Genetic Predisposition to Disease, UKGPCS collaborators, APCB, NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Urology & Nephrology, Clinical sciences, Oncology and carcinogenesis
Abstract

BackgroundProstate cancer risk stratification using single-nucleotide polymorphisms (SNPs) demonstrates considerable promise in men of European, Asian, and African genetic ancestries, but there is still need for increased accuracy. We evaluated whether including additional SNPs in a prostate cancer polygenic hazard score (PHS) would improve associations with clinically significant prostate cancer in multi-ancestry datasets.MethodsIn total, 299 SNPs previously associated with prostate cancer were evaluated for inclusion in a new PHS, using a LASSO-regularized Cox proportional hazards model in a training dataset of 72,181 men from the PRACTICAL Consortium. The PHS model was evaluated in four testing datasets: African ancestry, Asian ancestry, and two of European Ancestry-the Cohort of Swedish Men (COSM) and the ProtecT study. Hazard ratios (HRs) were estimated to compare men with high versus low PHS for association with clinically significant, with any, and with fatal prostate cancer. The impact of genetic risk stratification on the positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was also measured.ResultsThe final model (PHS290) had 290 SNPs with non-zero coefficients. Comparing, for example, the highest and lowest quintiles of PHS290, the hazard ratios (HRs) for clinically significant prostate cancer were 13.73 [95% CI: 12.43-15.16] in ProtecT, 7.07 [6.58-7.60] in African ancestry, 10.31 [9.58-11.11] in Asian ancestry, and 11.18 [10.34-12.09] in COSM. Similar results were seen for association with any and fatal prostate cancer. Without PHS stratification, the PPV of PSA testing for clinically significant prostate cancer in ProtecT was 0.12 (0.11-0.14). For the top 20% and top 5% of PHS290, the PPV of PSA testing was 0.19 (0.15-0.22) and 0.26 (0.19-0.33), respectively.ConclusionsWe demonstrate better genetic risk stratification for clinically significant prostate cancer than prior versions of PHS in multi-ancestry datasets. This is promising for implementing precision-medicine approaches to prostate cancer screening decisions in diverse populations.

Published
2022

6. Author Correction: Common variants in Alzheimer’s disease and risk stratification by polygenic risk scores

Author

de Rojas, Itziar, Moreno-Grau, Sonia, Tesi, Niccolo, Grenier-Boley, Benjamin, Andrade, Victor, Jansen, Iris E., Pedersen, Nancy L., Stringa, Najada, Zettergren, Anna, Hernández, Isabel, Montrreal, Laura, Antúnez, Carmen, Antonell, Anna, Tankard, Rick M., Bis, Joshua C., Sims, Rebecca, Bellenguez, Céline, Quintela, Inés, González-Perez, Antonio, Calero, Miguel, Franco-Macías, Emilio, Macías, Juan, Blesa, Rafael, Cervera-Carles, Laura, Menéndez-González, Manuel, Frank-García, Ana, Royo, Jose Luís, Moreno, Fermin, Huerto Vilas, Raquel, Baquero, Miquel, Diez-Fairen, Mónica, Lage, Carmen, García-Madrona, Sebastián, García-González, Pablo, Alarcón-Martín, Emilio, Valero, Sergi, Sotolongo-Grau, Oscar, Ullgren, Abbe, Naj, Adam C., Lemstra, Afina W., Benaque, Alba, Pérez-Cordón, Alba, Benussi, Alberto, Rábano, Alberto, Padovani, Alessandro, Squassina, Alessio, de Mendonça, Alexandre, Arias Pastor, Alfonso, Kok, Almar A. L., Meggy, Alun, Pastor, Ana Belén, Espinosa, Ana, Corma-Gómez, Anaïs, Martín Montes, Angel, Sanabria, Ángela, DeStefano, Anita L., Schneider, Anja, Haapasalo, Annakaisa, Kinhult Ståhlbom, Anne, Tybjærg-Hansen, Anne, Hartmann, Annette M., Spottke, Annika, Corbatón-Anchuelo, Arturo, Rongve, Arvid, Borroni, Barbara, Arosio, Beatrice, Nacmias, Benedetta, Nordestgaard, Børge G., Kunkle, Brian W., Charbonnier, Camille, Abdelnour, Carla, Masullo, Carlo, Martínez Rodríguez, Carmen, Muñoz-Fernandez, Carmen, Dufouil, Carole, Graff, Caroline, Ferreira, Catarina B., Chillotti, Caterina, Reynolds, Chandra A., Fenoglio, Chiara, Van Broeckhoven, Christine, Clark, Christopher, Pisanu, Claudia, Satizabal, Claudia L., Holmes, Clive, Buiza-Rueda, Dolores, Aarsland, Dag, Rujescu, Dan, Alcolea, Daniel, Galimberti, Daniela, Wallon, David, Seripa, Davide, Grünblatt, Edna, Dardiotis, Efthimios, Düzel, Emrah, Scarpini, Elio, Conti, Elisa, Rubino, Elisa, Gelpi, Ellen, Rodriguez-Rodriguez, Eloy, Duron, Emmanuelle, Boerwinkle, Eric, Ferri, Evelyn, Tagliavini, Fabrizio, Küçükali, Fahri, Pasquier, Florence, Sanchez-Garcia, Florentino, Mangialasche, Francesca, Jessen, Frank, Nicolas, Gaël, Selbæk, Geir, Ortega, Gemma, Chêne, Geneviève, Hadjigeorgiou, Georgios, Rossi, Giacomina, Spalletta, Gianfranco, Giaccone, Giorgio, Grande, Giulia, Binetti, Giuliano, Papenberg, Goran, Hampel, Harald, Bailly, Henri, Zetterberg, Henrik, Soininen, Hilkka, Karlsson, Ida K., Alvarez, Ignacio, Appollonio, Ildebrando, Giegling, Ina, Skoog, Ingmar, Saltvedt, Ingvild, Rainero, Innocenzo, Rosas Allende, Irene, Hort, Jakub, Diehl-Schmid, Janine, Van Dongen, Jasper, Vidal, Jean-Sebastien, Lehtisalo, Jenni, Wiltfang, Jens, Thomassen, Jesper Qvist, Kornhuber, Johannes, Haines, Jonathan L., Vogelgsang, Jonathan, Pineda, Juan A., Fortea, Juan, Popp, Julius, Deckert, Jürgen, Buerger, Katharina, Morgan, Kevin, Fließbach, Klaus, Sleegers, Kristel, Molina-Porcel, Laura, Kilander, Lena, Weinhold, Leonie, Farrer, Lindsay A., Wang, Li-San, Kleineidam, Luca, Farotti, Lucia, Parnetti, Lucilla, Tremolizzo, Lucio, Hausner, Lucrezia, Benussi, Luisa, Froelich, Lutz, Ikram, M. Arfan, Deniz-Naranjo, M. Candida, Tsolaki, Magda, Rosende-Roca, Maitée, Löwenmark, Malin, Hulsman, Marc, Spallazzi, Marco, Pericak-Vance, Margaret A., Esiri, Margaret, Bernal Sánchez-Arjona, María, Dalmasso, Maria Carolina, Martínez-Larrad, María Teresa, Arcaro, Marina, Nöthen, Markus M., Fernández-Fuertes, Marta, Dichgans, Martin, Ingelsson, Martin, Herrmann, Martin J., Scherer, Martin, Vyhnalek, Martin, Kosmidis, Mary H., Yannakoulia, Mary, Schmid, Matthias, Ewers, Michael, Heneka, Michael T., Wagner, Michael, Scamosci, Michela, Kivipelto, Miia, Hiltunen, Mikko, Zulaica, Miren, Alegret, Montserrat, Fornage, Myriam, Roberto, Natalia, van Schoor, Natasja M., Seidu, Nazib M., Banaj, Nerisa, Armstrong, Nicola J., Scarmeas, Nikolaos, Scherbaum, Norbert, Goldhardt, Oliver, Hanon, Oliver, Peters, Oliver, Skrobot, Olivia Anna, Quenez, Olivier, Lerch, Ondrej, Bossù, Paola, Caffarra, Paolo, Dionigi Rossi, Paolo, Sakka, Paraskevi, Mecocci, Patrizia, Hoffmann, Per, Holmans, Peter A., Fischer, Peter, Riederer, Peter, Yang, Qiong, Marshall, Rachel, Kalaria, Rajesh N., Mayeux, Richard, Vandenberghe, Rik, Cecchetti, Roberta, Ghidoni, Roberta, Frikke-Schmidt, Ruth, Sorbi, Sandro, Hägg, Sara, Engelborghs, Sebastiaan, Helisalmi, Seppo, Botne Sando, Sigrid, Kern, Silke, Archetti, Silvana, Boschi, Silvia, Fostinelli, Silvia, Gil, Silvia, Mendoza, Silvia, Mead, Simon, Ciccone, Simona, Djurovic, Srdjan, Heilmann-Heimbach, Stefanie, Riedel-Heller, Steffi, Kuulasmaa, Teemu, del Ser, Teodoro, Lebouvier, Thibaud, Polak, Thomas, Ngandu, Tiia, Grimmer, Timo, Bessi, Valentina, Escott-Price, Valentina, Giedraitis, Vilmantas, Deramecourt, Vincent, Maier, Wolfgang, Jian, Xueqiu, Pijnenburg, Yolande A. L., Kehoe, Patrick Gavin, Garcia-Ribas, Guillermo, Sánchez-Juan, Pascual, Pastor, Pau, Pérez-Tur, Jordi, Piñol-Ripoll, Gerard, Lopez de Munain, Adolfo, García-Alberca, Jose María, Bullido, María J., Álvarez, Victoria, Lleó, Alberto, Real, Luis M., Mir, Pablo, Medina, Miguel, Scheltens, Philip, Holstege, Henne, Marquié, Marta, Sáez, María Eugenia, Carracedo, Ángel, Amouyel, Philippe, Schellenberg, Gerard D., Williams, Julie, Seshadri, Sudha, van Duijn, Cornelia M., Mather, Karen A., Sánchez-Valle, Raquel, Serrano-Ríos, Manuel, Orellana, Adelina, Tárraga, Lluís, Blennow, Kaj, Huisman, Martijn, Andreassen, Ole A., Posthuma, Danielle, Clarimón, Jordi, Boada, Mercè, van der Flier, Wiesje M., Ramirez, Alfredo, Lambert, Jean-Charles, van der Lee, Sven J., and Ruiz, Agustín

Published
2023
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7. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Landi, Maria Teresa, Stevens, Victoria, Wang, Ying, Albanes, Demetrios, Caporaso, Neil, Brennan, Paul, Amos, Christopher I., Shete, Sanjay, Hung, Rayjean J., Bickeböller, Heike, Risch, Angela, Houlston, Richard, Lam, Stephen, Tardon, Adonina, Chen, Chu, Bojesen, Stig E., Johansson, Mattias, Wichmann, H-Erich, Christiani, David, Rennert, Gadi, Arnold, Susanne, Field, John K., Le Marchand, Loic, Melander, Olle, Brunnström, Hans, Liu, Geoffrey, Andrew, Angeline, Kiemeney, Lambertus A., Shen, Hongbing, Zienolddiny, Shan, Grankvist, Kjell, Johansson, Mikael, Teare, M. Dawn, Hong, Yun-Chul, Yuan, Jian-Min, Lazarus, Philip, Schabath, Matthew B., Aldrich, Melinda C., Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Al Olama, Ali Amin, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Chanock, Stephen, Tangen, Catherine M., Batra, Jyotsna, Clements, Judith A., Grönberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Albanes, Demetrius, Weinstein, Stephanie J., Wolk, Alicja, West, Catharine M.L., Mucci, Lorelei A., Cancel-Tassin, Géraldine, Koutros, Stella, Sørensen, Karina Dalsgaard, Grindedal, Eli Marie, Neal, David E., Hamdy, Freddie C., Donovan, Jenny L., Travis, Ruth C., Hamilton, Robert J., Ingles, Sue Ann, Rosenstein, Barry S., Lu, Yong-Jie, Giles, Graham G., MacInnis, Robert J., Kibel, Adam S., Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L., Park, Jong Y., Stanfrod, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Logothetis, Christopher J., John, Esther M., Teixeira, Manuel R., Neuhausen, Susan L., De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F., Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A., Castelao, Jose Esteban, Roobol, Monique J., Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa, Pandha, Hardev, Thibodeau, Stephen N., Hunter, David J., Kraft, Peter, Blot, William J., Riboli, Elio, Yarmolinsky, James, Robinson, Jamie W., Mariosa, Daniela, Karhunen, Ville, Huang, Jian, Dimou, Niki, Murphy, Neil, Burrows, Kimberley, Bouras, Emmanouil, Smith-Byrne, Karl, Lewis, Sarah J., Galesloot, Tessel E., Vermeulen, Sita, Martin, Paul, Hou, Lifang, Newcomb, Polly A., White, Emily, Wu, Anna H., Le Marchand, Loïc, Phipps, Amanda I., Buchanan, Daniel D., Zhao, Sizheng Steven, Gill, Dipender, Chanock, Stephen J., Purdue, Mark P., Davey Smith, George, Herzig, Karl-Heinz, Järvelin, Marjo-Riitta, Amos, Chris I., Dehghan, Abbas, Gunter, Marc J., Tsilidis, Kostas K., and Martin, Richard M.

Published
2024
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8. Additional SNPs improve risk stratification of a polygenic hazard score for prostate cancer.

Author

Karunamuni, Roshan A, Huynh-Le, Minh-Phuong, Fan, Chun C, Thompson, Wesley, Eeles, Rosalind A, Kote-Jarai, Zsofia, Muir, Kenneth, Lophatananon, Artitaya, UKGPCS collaborators, Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, APCB BioResource (Australian Prostate Cancer BioResource), Grönberg, Henrik, Walsh, Eleanor I, Turner, Emma L, Lane, Athene, Martin, Richard M, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Nordestgaard, Børge G, Tangen, Catherine M, MacInnis, Robert J, Wolk, Alicja, Albanes, Demetrius, Haiman, Christopher A, Travis, Ruth C, Stanford, Janet L, Mucci, Lorelei A, West, Catharine ML, Nielsen, Sune F, Kibel, Adam S, Wiklund, Fredrik, Cussenot, Olivier, Berndt, Sonja I, Koutros, Stella, Sørensen, Karina Dalsgaard, Cybulski, Cezary, Grindedal, Eli Marie, Park, Jong Y, Ingles, Sue A, Maier, Christiane, Hamilton, Robert J, Rosenstein, Barry S, Vega, Ana, IMPACT Study Steering Committee and Collaborators, Kogevinas, Manolis, Penney, Kathryn L, Teixeira, Manuel R, Brenner, Hermann, John, Esther M, Kaneva, Radka, Logothetis, Christopher J, Neuhausen, Susan L, Razack, Azad, Newcomb, Lisa F, Canary PASS Investigators, Gamulin, Marija, Usmani, Nawaid, Claessens, Frank, Gago-Dominguez, Manuela, Townsend, Paul A, Roobol, Monique J, Zheng, Wei, Profile Study Steering Committee, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, and PRACTICAL Consortium

Subjects
UKGPCS collaborators, APCB BioResource, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Prevention, Urologic Diseases, Cancer, Prostate Cancer, Aging, Urology & Nephrology, Oncology and Carcinogenesis
Abstract

BackgroundPolygenic hazard scores (PHS) can identify individuals with increased risk of prostate cancer. We estimated the benefit of additional SNPs on performance of a previously validated PHS (PHS46).Materials and method180 SNPs, shown to be previously associated with prostate cancer, were used to develop a PHS model in men with European ancestry. A machine-learning approach, LASSO-regularized Cox regression, was used to select SNPs and to estimate their coefficients in the training set (75,596 men). Performance of the resulting model was evaluated in the testing/validation set (6,411 men) with two metrics: (1) hazard ratios (HRs) and (2) positive predictive value (PPV) of prostate-specific antigen (PSA) testing. HRs were estimated between individuals with PHS in the top 5% to those in the middle 40% (HR95/50), top 20% to bottom 20% (HR80/20), and bottom 20% to middle 40% (HR20/50). PPV was calculated for the top 20% (PPV80) and top 5% (PPV95) of PHS as the fraction of individuals with elevated PSA that were diagnosed with clinically significant prostate cancer on biopsy.Results166 SNPs had non-zero coefficients in the Cox model (PHS166). All HR metrics showed significant improvements for PHS166 compared to PHS46: HR95/50 increased from 3.72 to 5.09, HR80/20 increased from 6.12 to 9.45, and HR20/50 decreased from 0.41 to 0.34. By contrast, no significant differences were observed in PPV of PSA testing for clinically significant prostate cancer.ConclusionsIncorporating 120 additional SNPs (PHS166 vs PHS46) significantly improved HRs for prostate cancer, while PPV of PSA testing remained the same.

Published
2021

9. Breast Cancer Risk Factors and Survival by Tumor Subtype: Pooled Analyses from the Breast Cancer Association ConsortiumBreast Cancer Risk Factors and Survival By Tumor Subtype

Author

Morra, Anna, Jung, Audrey Y, Behrens, Sabine, Keeman, Renske, Ahearn, Thomas U, Anton-Culver, Hoda, Arndt, Volker, Augustinsson, Annelie, Auvinen, Päivi K, Freeman, Laura E Beane, Becher, Heiko, Beckmann, Matthias W, Blomqvist, Carl, Bojesen, Stig E, Bolla, Manjeet K, Brenner, Hermann, Briceno, Ignacio, Brucker, Sara Y, Camp, Nicola J, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Choi, Ji-Yeob, Clarke, Christine L, Investigators, for the ABCTB, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dörk, Thilo, Dunning, Alison M, Dwek, Miriam, Easton, Douglas F, Eccles, Diana M, Egan, Kathleen M, Evans, D Gareth, Fasching, Peter A, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Sáenz, José A, Gaudet, Mia M, Giles, Graham G, Grip, Mervi, Guénel, Pascal, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Han, Sileny N, Hart, Steven N, Hartman, Mikael, Heyworth, Jane S, Hoppe, Reiner, Hopper, John L, Hunter, David J, Ito, Hidemi, Jager, Agnes, Jakimovska, Milena, Jakubowska, Anna, Janni, Wolfgang, Kaaks, Rudolf, Kang, Daehee, Kapoor, Pooja Middha, Kitahara, Cari M, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Collaborators, for the NBCS, Lacey, James V, Lambrechts, Diether, Le Marchand, Loic, Li, Jingmei, Lindblom, Annika, Lubiński, Jan, Lush, Michael, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Mariapun, Shivaani, Matsuo, Keitaro, Mavroudis, Dimitrios, Milne, Roger L, Muranen, Taru A, Newman, William G, Noh, Dong-Young, Nordestgaard, Børge G, Obi, Nadia, Olshan, Andrew F, Olsson, Håkan, Park-Simon, Tjoung-Won, Petridis, Christos, Pharoah, Paul DP, Plaseska-Karanfilska, Dijana, Presneau, Nadege, Rashid, Muhammad U, Rennert, Gad, Rennert, Hedy S, and Rhenius, Valerie

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Oncology and Carcinogenesis, Clinical Research, Aging, Estrogen, Cancer, Prevention, Breast Cancer, Good Health and Well Being, Adult, Aged, Breast Neoplasms, Cause of Death, Female, Humans, Life Style, Middle Aged, Neoplasm Invasiveness, Neoplasm Staging, Prospective Studies, Risk Factors, Survival Analysis, ABCTB Investigators, NBCS Collaborators, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundIt is not known whether modifiable lifestyle factors that predict survival after invasive breast cancer differ by subtype.MethodsWe analyzed data for 121,435 women diagnosed with breast cancer from 67 studies in the Breast Cancer Association Consortium with 16,890 deaths (8,554 breast cancer specific) over 10 years. Cox regression was used to estimate associations between risk factors and 10-year all-cause mortality and breast cancer-specific mortality overall, by estrogen receptor (ER) status, and by intrinsic-like subtype.ResultsThere was no evidence of heterogeneous associations between risk factors and mortality by subtype (P adj > 0.30). The strongest associations were between all-cause mortality and BMI ≥30 versus 18.5-25 kg/m2 [HR (95% confidence interval (CI), 1.19 (1.06-1.34)]; current versus never smoking [1.37 (1.27-1.47)], high versus low physical activity [0.43 (0.21-0.86)], age ≥30 years versus 0-

Published
2021

10. Polygenic hazard score is associated with prostate cancer in multi-ethnic populations.

Author

Huynh-Le, Minh-Phuong, Fan, Chun Chieh, Karunamuni, Roshan, Thompson, Wesley K, Martinez, Maria Elena, Eeles, Rosalind A, Kote-Jarai, Zsofia, Muir, Kenneth, Schleutker, Johanna, Pashayan, Nora, Batra, Jyotsna, Grönberg, Henrik, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Martin, Richard M, Nielsen, Sune F, Nordestgaard, Børge G, Wiklund, Fredrik, Tangen, Catherine M, Giles, Graham G, Wolk, Alicja, Albanes, Demetrius, Travis, Ruth C, Blot, William J, Zheng, Wei, Sanderson, Maureen, Stanford, Janet L, Mucci, Lorelei A, West, Catharine ML, Kibel, Adam S, Cussenot, Olivier, Berndt, Sonja I, Koutros, Stella, Sørensen, Karina Dalsgaard, Cybulski, Cezary, Grindedal, Eli Marie, Menegaux, Florence, Khaw, Kay-Tee, Park, Jong Y, Ingles, Sue A, Maier, Christiane, Hamilton, Robert J, Thibodeau, Stephen N, Rosenstein, Barry S, Lu, Yong-Jie, Watya, Stephen, Vega, Ana, Kogevinas, Manolis, Penney, Kathryn L, Huff, Chad, Teixeira, Manuel R, Multigner, Luc, Leach, Robin J, Cannon-Albright, Lisa, Brenner, Hermann, John, Esther M, Kaneva, Radka, Logothetis, Christopher J, Neuhausen, Susan L, De Ruyck, Kim, Pandha, Hardev, Razack, Azad, Newcomb, Lisa F, Fowke, Jay H, Gamulin, Marija, Usmani, Nawaid, Claessens, Frank, Gago-Dominguez, Manuela, Townsend, Paul A, Bush, William S, Roobol, Monique J, Parent, Marie-Élise, Hu, Jennifer J, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, Seibert, Tyler M, UKGPCS collaborators, APCB (Australian Prostate Cancer BioResource), NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, and PRACTICAL Consortium

Subjects
UKGPCS collaborators, APCB, NC-LA PCaP Investigators, IMPACT Study Steering Committee and Collaborators, Canary PASS Investigators, Profile Study Steering Committee, PRACTICAL Consortium, Humans, Prostatic Neoplasms, Neoplasm Invasiveness, Multivariate Analysis, Multifactorial Inheritance, Aged, Middle Aged, Ethnic Groups, Male, Self Report, Aging, Urologic Diseases, Cancer, Prostate Cancer
Abstract

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p

Published
2021

11. CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers

Author

Johnson, Nichola, Maguire, Sarah, Morra, Anna, Kapoor, Pooja Middha, Tomczyk, Katarzyna, Jones, Michael E, Schoemaker, Minouk J, Gilham, Clare, Bolla, Manjeet K, Wang, Qin, Dennis, Joe, Ahearn, Thomas U, Andrulis, Irene L, Anton-Culver, Hoda, Antonenkova, Natalia N, Arndt, Volker, Aronson, Kristan J, Augustinsson, Annelie, Baynes, Caroline, Freeman, Laura E Beane, Beckmann, Matthias W, Benitez, Javier, Bermisheva, Marina, Blomqvist, Carl, Boeckx, Bram, Bogdanova, Natalia V, Bojesen, Stig E, Brauch, Hiltrud, Brenner, Hermann, Burwinkel, Barbara, Campa, Daniele, Canzian, Federico, Castelao, Jose E, Chanock, Stephen J, Chenevix-Trench, Georgia, Clarke, Christine L, Conroy, Don M, Couch, Fergus J, Cox, Angela, Cross, Simon S, Czene, Kamila, Dörk, Thilo, Eliassen, A Heather, Engel, Christoph, Evans, D Gareth, Fasching, Peter A, Figueroa, Jonine, Floris, Giuseppe, Flyger, Henrik, Gago-Dominguez, Manuela, Gapstur, Susan M, García-Closas, Montserrat, Gaudet, Mia M, Giles, Graham G, Goldberg, Mark S, González-Neira, Anna, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A, Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A, Hart, Steven N, Hooning, Maartje J, Hopper, John L, Howell, Anthony, Hunter, David J, Jager, Agnes, Jakubowska, Anna, John, Esther M, Kaaks, Rudolf, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M, Kosma, Veli-Matti, Koutros, Stella, Kraft, Peter, Kristensen, Vessela N, Kurian, Allison W, Lambrechts, Diether, Le Marchand, Loic, Linet, Martha, Lubiński, Jan, Mannermaa, Arto, Manoukian, Siranoush, Margolin, Sara, Martens, John WM, Mavroudis, Dimitrios, Mayes, Rebecca, Meindl, Alfons, Milne, Roger L, Neuhausen, Susan L, Nevanlinna, Heli, Newman, William G, Nielsen, Sune F, Nordestgaard, Børge G, Obi, Nadia, Olshan, Andrew F, and Olson, Janet E

Subjects
Estrogen, Human Genome, Clinical Research, Cancer, Aging, Breast Cancer, Genetics, 2.1 Biological and endogenous factors, Aetiology, Alleles, Breast Neoplasms, Case-Control Studies, Cytochrome P-450 CYP3A, Estrone, Female, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Pregnanediol, Premenopause, Progesterone, Receptors, Estrogen, Receptors, Progesterone, NBCS Collaborators, AOCS Group, ABCTB Investigators, kConFab Investigators, Oncology and Carcinogenesis, Public Health and Health Services, Oncology & Carcinogenesis
Abstract

BackgroundEpidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk.MethodsWe carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry.ResultsFor pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8).ConclusionsThe CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.

Published
2021

12. Pharmacologic and Genetic Downregulation of Proprotein Convertase Subtilisin/Kexin Type 9 and Survival From Sepsis

Author

Lawler, Patrick R., Manvelian, Garen, Coppi, Alida, Damask, Amy, Cantor, Michael N., Ferreira, Manuel A. R., Paulding, Charles, Banerjee, Nilanjana, Li, Dadong, Jorgensen, Susan, Attre, Richa, Carey, David J., Krebs, Kristi, Milani, Lili, Hveem, Kristian, Damås, Jan K., Solligård, Erik, Stender, Stefan, Tybjærg-Hansen, Anne, Nordestgaard, Børge G., Hernandez-Beeftink, Tamara, Rogne, Tormod, Flores, Carlos, Villar, Jesús, Walley, Keith R., Liu, Vincent X., Fohner, Alison E., Lotta, Luca A., Kyratsous, Christos A., Sleeman, Mark W., Scemama, Michel, DelGizzi, Richard, Pordy, Robert, Horowitz, Julie E., Baras, Aris, Martin, Greg S., Steg, Philippe Gabriel, Schwartz, Gregory G., Szarek, Michael, and Goodman, Shaun G.

Published
2023
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13. The effect of sample size on polygenic hazard models for prostate cancer

Author

Karunamuni, Roshan A, Huynh-Le, Minh-Phuong, Fan, Chun C, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, ZSofia, Amin Al Olama, Ali, Benlloch Garcia, Sara, Muir, Kenneth, Gronberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo LJ, Nordestgaard, Børge G, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Brenner, Hermann, Schöttker, Ben, Holleczek, Bernd, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, and Seibert, Tyler M

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Cancer, Aging, Urologic Diseases, Clinical Trials as Topic, Genome-Wide Association Study, Humans, Male, Models, Genetic, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Proportional Hazards Models, Prostatic Neoplasms, Sample Size, Australian Prostate Cancer BioResource, PRACTICAL Consortium, Genetics, Clinical Sciences, Genetics & Heredity, Clinical sciences
Abstract

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

Published
2020

14. Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, Aniket, Malik, Rainer, Hachiya, Tsuyoshi, Jürgenson, Tuuli, Namba, Shinichi, Posner, Daniel C., Kamanu, Frederick K., Koido, Masaru, Le Grand, Quentin, Shi, Mingyang, He, Yunye, Georgakis, Marios K., Caro, Ilana, Krebs, Kristi, Liaw, Yi-Ching, Vaura, Felix C., Lin, Kuang, Winsvold, Bendik Slagsvold, Srinivasasainagendra, Vinodh, Parodi, Livia, Bae, Hee-Joon, Chauhan, Ganesh, Chong, Michael R., Tomppo, Liisa, Akinyemi, Rufus, Roshchupkin, Gennady V., Habib, Naomi, Jee, Yon Ho, Thomassen, Jesper Qvist, Abedi, Vida, Cárcel-Márquez, Jara, Nygaard, Marianne, Leonard, Hampton L., Yang, Chaojie, Yonova-Doing, Ekaterina, Knol, Maria J., Lewis, Adam J., Judy, Renae L., Ago, Tetsuro, Amouyel, Philippe, Armstrong, Nicole D., Bakker, Mark K., Bartz, Traci M., Bennett, David A., Bis, Joshua C., Bordes, Constance, Børte, Sigrid, Cain, Anael, Ridker, Paul M., Cho, Kelly, Chen, Zhengming, Cruchaga, Carlos, Cole, John W., de Jager, Phil L., de Cid, Rafael, Endres, Matthias, Ferreira, Leslie E., Geerlings, Mirjam I., Gasca, Natalie C., Gudnason, Vilmundur, Hata, Jun, He, Jing, Heath, Alicia K., Ho, Yuk-Lam, Havulinna, Aki S., Hopewell, Jemma C., Hyacinth, Hyacinth I., Inouye, Michael, Jacob, Mina A., Jeon, Christina E., Jern, Christina, Kamouchi, Masahiro, Keene, Keith L., Kitazono, Takanari, Kittner, Steven J., Konuma, Takahiro, Kumar, Amit, Lacaze, Paul, Launer, Lenore J., Lee, Keon-Joo, Lepik, Kaido, Li, Jiang, Li, Liming, Manichaikul, Ani, Markus, Hugh S., Marston, Nicholas A., Meitinger, Thomas, Mitchell, Braxton D., Montellano, Felipe A., Morisaki, Takayuki, Mosley, Thomas H., Nalls, Mike A., Nordestgaard, Børge G., O’Donnell, Martin J., Okada, Yukinori, Onland-Moret, N. Charlotte, Ovbiagele, Bruce, Peters, Annette, Psaty, Bruce M., Rich, Stephen S., Rosand, Jonathan, Sabatine, Marc S., Sacco, Ralph L., Saleheen, Danish, Sandset, Else Charlotte, Salomaa, Veikko, Sargurupremraj, Muralidharan, Sasaki, Makoto, Satizabal, Claudia L., Schmidt, Carsten O., Shimizu, Atsushi, Smith, Nicholas L., Sloane, Kelly L., Sutoh, Yoichi, Sun, Yan V., Tanno, Kozo, Tiedt, Steffen, Tatlisumak, Turgut, Torres-Aguila, Nuria P., Tiwari, Hemant K., Trégouët, David-Alexandre, Trompet, Stella, Tuladhar, Anil Man, Tybjærg-Hansen, Anne, van Vugt, Marion, Vibo, Riina, Verma, Shefali S., Wiggins, Kerri L., Wennberg, Patrik, Woo, Daniel, Wilson, Peter W. F., Xu, Huichun, Yang, Qiong, Yoon, Kyungheon, Millwood, Iona Y., Gieger, Christian, Ninomiya, Toshiharu, Grabe, Hans J., Jukema, J. Wouter, Rissanen, Ina L., Strbian, Daniel, Kim, Young Jin, Chen, Pei-Hsin, Mayerhofer, Ernst, Howson, Joanna M. M., Irvin, Marguerite R., Adams, Hieab, Wassertheil-Smoller, Sylvia, Christensen, Kaare, Ikram, Mohammad A., Rundek, Tatjana, Worrall, Bradford B., Lathrop, G. Mark, Riaz, Moeen, Simonsick, Eleanor M., Kõrv, Janika, França, Paulo H. C., Zand, Ramin, Prasad, Kameshwar, Frikke-Schmidt, Ruth, de Leeuw, Frank-Erik, Liman, Thomas, Haeusler, Karl Georg, Ruigrok, Ynte M., Heuschmann, Peter Ulrich, Longstreth, W. T., Jung, Keum Ji, Bastarache, Lisa, Paré, Guillaume, Damrauer, Scott M., Chasman, Daniel I., Rotter, Jerome I., Anderson, Christopher D., Zwart, John-Anker, Niiranen, Teemu J., Fornage, Myriam, Liaw, Yung-Po, Seshadri, Sudha, Fernández-Cadenas, Israel, Walters, Robin G., Ruff, Christian T., Owolabi, Mayowa O., Huffman, Jennifer E., Milani, Lili, Kamatani, Yoichiro, Dichgans, Martin, and Debette, Stephanie

Published
2022
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15. Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry.

Author

Matejcic, Marco, Saunders, Edward J, Dadaev, Tokhir, Brook, Mark N, Wang, Kan, Sheng, Xin, Olama, Ali Amin Al, Schumacher, Fredrick R, Ingles, Sue A, Govindasami, Koveela, Benlloch, Sara, Berndt, Sonja I, Albanes, Demetrius, Koutros, Stella, Muir, Kenneth, Stevens, Victoria L, Gapstur, Susan M, Tangen, Catherine M, Batra, Jyotsna, Clements, Judith, Gronberg, Henrik, Pashayan, Nora, Schleutker, Johanna, Wolk, Alicja, West, Catharine, Mucci, Lorelei, Kraft, Peter, Cancel-Tassin, Géraldine, Sorensen, Karina D, Maehle, Lovise, Grindedal, Eli M, Strom, Sara S, Neal, David E, Hamdy, Freddie C, Donovan, Jenny L, Travis, Ruth C, Hamilton, Robert J, Rosenstein, Barry, Lu, Yong-Jie, Giles, Graham G, Kibel, Adam S, Vega, Ana, Bensen, Jeanette T, Kogevinas, Manolis, Penney, Kathryn L, Park, Jong Y, Stanford, Janet L, Cybulski, Cezary, Nordestgaard, Børge G, Brenner, Hermann, Maier, Christiane, Kim, Jeri, Teixeira, Manuel R, Neuhausen, Susan L, De Ruyck, Kim, Razack, Azad, Newcomb, Lisa F, Lessel, Davor, Kaneva, Radka, Usmani, Nawaid, Claessens, Frank, Townsend, Paul A, Gago-Dominguez, Manuela, Roobol, Monique J, Menegaux, Florence, Khaw, Kay-Tee, Cannon-Albright, Lisa A, Pandha, Hardev, Thibodeau, Stephen N, Schaid, Daniel J, PRACTICAL Consortium, Wiklund, Fredrik, Chanock, Stephen J, Easton, Douglas F, Eeles, Rosalind A, Kote-Jarai, Zsofia, Conti, David V, and Haiman, Christopher A

Subjects
PRACTICAL Consortium
Abstract

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Published
2019

22. Normal values of myocardial blood flow measured with dynamic myocardial computed tomography perfusion.

Author

Møller, Mathias B, Linde, Jesper J, Fuchs, Andreas, Køber, Lars V, Nordestgaard, Børge G, and Kofoed, Klaus F

Subjects
CORONARY arterial radiography, REFERENCE values, SINGLE-photon emission computed tomography, BLOOD vessels, COMPUTED tomography, CORONARY circulation, SEX distribution, HEART function tests, SCIENTIFIC observation, POSITRON emission tomography, HEMODYNAMICS, AGE distribution, DESCRIPTIVE statistics, MANN Whitney U Test, PERFUSION imaging, LONGITUDINAL method, MYOCARDIUM, BLOOD flow measurement, PERFUSION, CORONARY angiography
Abstract

Aims Dynamic myocardial computed tomography (CT) perfusion (DM-CTP) can, in combination with coronary CT angiography (CCTA), provide anatomical and functional evaluation of coronary artery disease (CAD). However, normal values of myocardial blood flow (MBF) are needed to identify impaired myocardial blood supply in patients with suspected CAD. We aimed to establish normal values for MBF measured using DM-CTP, to assess the effects of age and sex, and to assess regional distribution of MBF. Methods and results A total of 82 healthy individuals (46 women) aged 45–78 years with normal coronary arteries by CCTA underwent either rest and adenosine stress DM-CTP (n = 30) or adenosine-induced stress DM-CTP only (n = 52). Global and segmental MBF were assessed. Global MBF at rest and during stress were 0.93 ± 0.42 and 3.58 ± 1.14 mL/min/g, respectively. MBF was not different between the sexes (P = 0.88 at rest and P = 0.61 during stress), and no correlation was observed between MBF and age (P = 0.08 at rest and P = 0.82 during stress). Among the 16 myocardial segments, significant intersegmental differences were found (P < 0.01), which was not related to age, sex, or coronary dominance. Conclusion MBF assessed by DM-CTP in healthy individuals with normal coronary arteries displays significant intersegmental heterogeneity which does not seem to be affected by age, sex, or coronary dominance. Normal values of MBF may be helpful in the clinical evaluation of suspected myocardial ischaemia using DM-CTP. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Mendelian randomisation study of smoking exposure in relation to breast cancer risk

Author

Park, Hanla A., Neumeyer, Sonja, Michailidou, Kyriaki, Bolla, Manjeet K., Wang, Qin, Dennis, Joe, Ahearn, Thomas U., Andrulis, Irene L., Anton-Culver, Hoda, Antonenkova, Natalia N., Arndt, Volker, Aronson, Kristan J., Augustinsson, Annelie, Baten, Adinda, Beane Freeman, Laura E., Becher, Heiko, Beckmann, Matthias W., Behrens, Sabine, Benitez, Javier, Bermisheva, Marina, Bogdanova, Natalia V., Bojesen, Stig E., Brauch, Hiltrud, Brenner, Hermann, Brucker, Sara Y., Burwinkel, Barbara, Campa, Daniele, Canzian, Federico, Castelao, Jose E., Chanock, Stephen J., Chenevix-Trench, Georgia, Clarke, Christine L., Conroy, Don M., Couch, Fergus J., Cox, Angela, Cross, Simon S., Czene, Kamila, Daly, Mary B., Devilee, Peter, Dörk, Thilo, dos-Santos-Silva, Isabel, Dwek, Miriam, Eccles, Diana M., Eliassen, A. Heather, Engel, Christoph, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Flyger, Henrik, Fritschi, Lin, García-Closas, Montserrat, García-Sáenz, José A., Gaudet, Mia M., Giles, Graham G., Glendon, Gord, Goldberg, Mark S., Goldgar, David E., González-Neira, Anna, Grip, Mervi, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A., Håkansson, Niclas, Hall, Per, Hamann, Ute, Han, Sileny, Harkness, Elaine F., Hart, Steven N., He, Wei, Heemskerk-Gerritsen, Bernadette A. M., Hopper, John L., Hunter, David J., Jager, Agnes, Jakubowska, Anna, John, Esther M., Jung, Audrey, Kaaks, Rudolf, Kapoor, Pooja Middha, Keeman, Renske, Khusnutdinova, Elza, Kitahara, Cari M., Koppert, Linetta B., Koutros, Stella, Kristensen, Vessela N., Kurian, Allison W., Lacey, James, Lambrechts, Diether, Le Marchand, Loic, Lo, Wing-Yee, Lubiński, Jan, Mannermaa, Arto, Manoochehri, Mehdi, Margolin, Sara, Martinez, Maria Elena, Mavroudis, Dimitrios, Meindl, Alfons, Menon, Usha, Milne, Roger L., Muranen, Taru A., Nevanlinna, Heli, Newman, William G., Nordestgaard, Børge G., Offit, Kenneth, Olshan, Andrew F., Olsson, Håkan, Park-Simon, Tjoung-Won, Peterlongo, Paolo, Peto, Julian, Plaseska-Karanfilska, Dijana, Presneau, Nadege, Radice, Paolo, Rennert, Gad, Rennert, Hedy S., Romero, Atocha, Saloustros, Emmanouil, Sawyer, Elinor J., Schmidt, Marjanka K., Schmutzler, Rita K., Schoemaker, Minouk J., Schwentner, Lukas, Scott, Christopher, Shah, Mitul, Shu, Xiao-Ou, Simard, Jacques, Smeets, Ann, Southey, Melissa C., Spinelli, John J., Stevens, Victoria, Swerdlow, Anthony J., Tamimi, Rulla M., Tapper, William J., Taylor, Jack A., Terry, Mary Beth, Tomlinson, Ian, Troester, Melissa A., Truong, Thérèse, Vachon, Celine M., van Veen, Elke M., Vijai, Joseph, Wang, Sophia, Wendt, Camilla, Winqvist, Robert, Wolk, Alicja, Ziogas, Argyrios, Dunning, Alison M., Pharoah, Paul D. P., Easton, Douglas F., Zheng, Wei, Kraft, Peter, and Chang-Claude, Jenny

Published
2021
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24. Adverse effects of statin therapy: perception vs. the evidence – focus on glucose homeostasis, cognitive, renal and hepatic function, haemorrhagic stroke and cataract

Author

Mach, François, Ray, Kausik K, Wiklund, Olov, Corsini, Alberto, Catapano, Alberico L, Bruckert, Eric, De Backer, Guy, Hegele, Robert A, Hovingh, G Kees, Jacobson, Terry A, Krauss, Ronald M, Laufs, Ulrich, Leiter, Lawrence A, März, Winfried, Nordestgaard, Børge G, Raal, Frederick J, Roden, Michael, Santos, Raul D, Stein, Evan A, Stroes, Erik S, Thompson, Paul D, Tokgözoğlu, Lale, Vladutiu, Georgirene D, Gencer, Baris, Stock, Jane K, Ginsberg, Henry N, and Chapman, M John

Subjects
Aging, Brain Disorders, Prevention, Patient Safety, Liver Disease, Clinical Trials and Supportive Activities, Digestive Diseases, Stroke, Clinical Research, Evaluation of treatments and therapeutic interventions, Aetiology, 2.1 Biological and endogenous factors, 6.1 Pharmaceuticals, Cataract, Cerebral Hemorrhage, Chemical and Drug Induced Liver Injury, Cognition Disorders, Glucose, Homeostasis, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Kidney Diseases, European Atherosclerosis Society Consensus Panel, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

AimsTo objectively appraise evidence for possible adverse effects of long-term statin therapy on glucose homeostasis, cognitive, renal and hepatic function, and risk for haemorrhagic stroke or cataract.Methods and resultsA literature search covering 2000-2017 was performed. The Panel critically appraised the data and agreed by consensus on the categorization of reported adverse effects. Randomized controlled trials (RCTs) and genetic studies show that statin therapy is associated with a modest increase in the risk of new-onset diabetes mellitus (about one per thousand patient-years), generally defined by laboratory findings (glycated haemoglobin ≥6.5); this risk is significantly higher in the metabolic syndrome or prediabetes. Statin treatment does not adversely affect cognitive function, even at very low levels of low-density lipoprotein cholesterol and is not associated with clinically significant deterioration of renal function, or development of cataract. Transient increases in liver enzymes occur in 0.5-2% of patients taking statins but are not clinically relevant; idiosyncratic liver injury due to statins is very rare and causality difficult to prove. The evidence base does not support an increased risk of haemorrhagic stroke in individuals without cerebrovascular disease; a small increase in risk was suggested by the Stroke Prevention by Aggressive Reduction of Cholesterol Levels study in subjects with prior stroke but has not been confirmed in the substantive evidence base of RCTs, cohort studies and case-control studies.ConclusionLong-term statin treatment is remarkably safe with a low risk of clinically relevant adverse effects as defined above; statin-associated muscle symptoms were discussed in a previous Consensus Statement. Importantly, the established cardiovascular benefits of statin therapy far outweigh the risk of adverse effects.

Published
2018

25. Relationship between genetic variation at PPP1R3B and levels of liver glycogen and triglyceride

Author

Stender, Stefan, Smagris, Eriks, Lauridsen, Bo K, Kofoed, Klaus F, Nordestgaard, Børge G, Tybjærg‐Hansen, Anne, Pennacchio, Len A, Dickel, Diane E, Cohen, Jonathan C, and Hobbs, Helen H

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Immunology, Chronic Liver Disease and Cirrhosis, Digestive Diseases, Liver Disease, Genetics, 2.1 Biological and endogenous factors, Aetiology, Oral and gastrointestinal, Adult, Aged, Animals, Female, Genetic Variation, Humans, Liver, Liver Glycogen, Male, Mice, Middle Aged, Protein Phosphatase 1, Triglycerides, Medical Biochemistry and Metabolomics, Gastroenterology & Hepatology, Clinical sciences
Abstract

Genetic variation at rs4240624 on chromosome 8 is associated with an attenuated signal on hepatic computerized tomography, which has been attributed to changes in hepatic fat. The closest coding gene to rs4240624, PPP1R3B, encodes a protein that promotes hepatic glycogen synthesis. Here, we performed studies to determine whether the x-ray attenuation associated with rs4240624 is due to differences in hepatic glycogen or hepatic triglyceride content (HTGC). A sequence variant in complete linkage disequilibrium with rs4240624, rs4841132, was genotyped in the Dallas Heart Study (DHS), the Dallas Liver Study, and the Copenhagen Cohort (n = 112,428) of whom 1,539 had nonviral liver disease. The minor A-allele of rs4841132 was associated with increased hepatic x-ray attenuation (n = 1,572; P = 4 × 10-5 ), but not with HTGC (n = 2,674; P = 0.58). Rs4841132-A was associated with modest, but significant, elevations in serum alanine aminotransferase (ALT) in the Copenhagen Cohort (P = 3 × 10-4 ) and the DHS (P = 0.004), and with odds ratios for liver disease of 1.13 (95% CI, 0.97-1.31) and 1.23 (1.01-1.51), respectively. Mice lacking protein phosphatase 1 regulatory subunit 3B (PPP1R3B) were deficient in hepatic glycogen, whereas HTGC was unchanged. Hepatic overexpression of PPP1R3B caused accumulation of hepatic glycogen and elevated plasma levels of ALT, but did not change HTGC.ConclusionThese observations are consistent with the notion that the minor allele of rs4841132 promotes a mild form of hepatic glycogenosis that is associated with hepatic injury. (Hepatology 2018;67:2182-2195).

Published
2018

26. Publisher Correction: Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation.

Author

Ghoussaini, Maya, Edwards, Stacey L, Michailidou, Kyriaki, Nord, Silje, Cowper-Sal Lari, Richard, Desai, Kinjal, Kar, Siddhartha, Hillman, Kristine M, Kaufmann, Susanne, Glubb, Dylan M, Beesley, Jonathan, Dennis, Joe, Bolla, Manjeet K, Wang, Qin, Dicks, Ed, Guo, Qi, Schmidt, Marjanka K, Shah, Mitul, Luben, Robert, Brown, Judith, Czene, Kamila, Darabi, Hatef, Eriksson, Mikael, Klevebring, Daniel, Bojesen, Stig E, Nordestgaard, Børge G, Nielsen, Sune F, Flyger, Henrik, Lambrechts, Diether, Thienpont, Bernard, Neven, Patrick, Wildiers, Hans, Broeks, Annegien, Van't Veer, Laura J, Rutgers, Emiel J Th, Couch, Fergus J, Olson, Janet E, Hallberg, Emily, Vachon, Celine, Chang-Claude, Jenny, Rudolph, Anja, Seibold, Petra, Flesch-Janys, Dieter, Peto, Julian, Dos-Santos-Silva, Isabel, Gibson, Lorna, Nevanlinna, Heli, Muranen, Taru A, Aittomäki, Kristiina, Blomqvist, Carl, Hall, Per, Li, Jingmei, Liu, Jianjun, Humphreys, Keith, Kang, Daehee, Choi, Ji-Yeob, Park, Sue K, Noh, Dong-Young, Matsuo, Keitaro, Ito, Hidemi, Iwata, Hiroji, Yatabe, Yasushi, Guénel, Pascal, Truong, Thérèse, Menegaux, Florence, Sanchez, Marie, Burwinkel, Barbara, Marme, Frederik, Schneeweiss, Andreas, Sohn, Christof, Wu, Anna H, Tseng, Chiu-Chen, Van Den Berg, David, Stram, Daniel O, Benitez, Javier, Pilar Zamora, M, Perez, Jose Ignacio Arias, Menéndez, Primitiva, Shu, Xiao-Ou, Lu, Wei, Gao, Yu-Tang, Cai, Qiuyin, Cox, Angela, Cross, Simon S, Reed, Malcolm WR, Andrulis, Irene L, Knight, Julia A, Glendon, Gord, Tchatchou, Sandrine, Sawyer, Elinor J, Tomlinson, Ian, Kerin, Michael J, Miller, Nicola, Haiman, Christopher A, Henderson, Brian E, Schumacher, Fredrick, Le Marchand, Loic, Lindblom, Annika, Margolin, Sara, and Teo, Soo Hwang

Abstract

This corrects the article DOI: 10.1038/ncomms5999.

Published
2018

27. Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

Author

Seibert, Tyler M, Fan, Chun Chieh, Wang, Yunpeng, Zuber, Verena, Karunamuni, Roshan, Parsons, J Kellogg, Eeles, Rosalind A, Easton, Douglas F, Kote-Jarai, ZSofia, Al Olama, Ali Amin, Garcia, Sara Benlloch, Muir, Kenneth, Grönberg, Henrik, Wiklund, Fredrik, Aly, Markus, Schleutker, Johanna, Sipeky, Csilla, Tammela, Teuvo Lj, Nordestgaard, Børge G, Nielsen, Sune F, Weischer, Maren, Bisbjerg, Rasmus, Røder, M Andreas, Iversen, Peter, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Brenner, Hermann, Cuk, Katarina, Saum, Kai-Uwe, Park, Jong Y, Sellers, Thomas A, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Clements, Judith A, Spurdle, Amanda, Teixeira, Manuel R, Paulo, Paula, Maia, Sofia, Pandha, Hardev, Michael, Agnieszka, Kierzek, Andrzej, Karow, David S, Mills, Ian G, Andreassen, Ole A, Dale, Anders M, and PRACTICAL Consortium*

Subjects
PRACTICAL Consortium*, Humans, Prostatic Neoplasms, Kallikreins, Prostate-Specific Antigen, Disease-Free Survival, Risk Assessment, Survival Analysis, Cohort Studies, Predictive Value of Tests, Age of Onset, Genotype, Polymorphism, Single Nucleotide, Aged, Middle Aged, European Continental Ancestry Group, Male, Early Detection of Cancer, Outcome Assessment, Health Care, Polymorphism, Single Nucleotide, Outcome Assessment, Health Care, Aging, Urologic Diseases, Cancer, Genetic Testing, Prevention, Prostate Cancer, Genetics, 2.1 Biological and endogenous factors, General & Internal Medicine, Public Health and Health Services, Clinical Sciences
Abstract

ObjectivesTo develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age.DesignAnalysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa.SettingMultiple institutions that were members of international PRACTICAL consortium.ParticipantsAll consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men.Main outcome measuresPrediction with hazard score of age of onset of aggressive cancer in validation set.ResultsIn the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score.ConclusionsPolygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Published
2018

28. Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes

Author

Gusarova, Viktoria, O’Dushlaine, Colm, Teslovich, Tanya M, Benotti, Peter N, Mirshahi, Tooraj, Gottesman, Omri, Van Hout, Cristopher V, Murray, Michael F, Mahajan, Anubha, Nielsen, Jonas B, Fritsche, Lars, Wulff, Anders Berg, Gudbjartsson, Daniel F, Sjögren, Marketa, Emdin, Connor A, Scott, Robert A, Lee, Wen-Jane, Small, Aeron, Kwee, Lydia C, Dwivedi, Om Prakash, Prasad, Rashmi B, Bruse, Shannon, Lopez, Alexander E, Penn, John, Marcketta, Anthony, Leader, Joseph B, Still, Christopher D, Kirchner, H Lester, Mirshahi, Uyenlinh L, Wardeh, Amr H, Hartle, Cassandra M, Habegger, Lukas, Fetterolf, Samantha N, Tusie-Luna, Teresa, Morris, Andrew P, Holm, Hilma, Steinthorsdottir, Valgerdur, Sulem, Patrick, Thorsteinsdottir, Unnur, Rotter, Jerome I, Chuang, Lee-Ming, Damrauer, Scott, Birtwell, David, Brummett, Chad M, Khera, Amit V, Natarajan, Pradeep, Orho-Melander, Marju, Flannick, Jason, Lotta, Luca A, Willer, Cristen J, Holmen, Oddgeir L, Ritchie, Marylyn D, Ledbetter, David H, Murphy, Andrew J, Borecki, Ingrid B, Reid, Jeffrey G, Overton, John D, Hansson, Ola, Groop, Leif, Shah, Svati H, Kraus, William E, Rader, Daniel J, Chen, Yii-Der I, Hveem, Kristian, Wareham, Nicholas J, Kathiresan, Sekar, Melander, Olle, Stefansson, Kari, Nordestgaard, Børge G, Tybjærg-Hansen, Anne, Abecasis, Goncalo R, Altshuler, David, Florez, Jose C, Boehnke, Michael, McCarthy, Mark I, Yancopoulos, George D, Carey, David J, Shuldiner, Alan R, Baras, Aris, Dewey, Frederick E, and Gromada, Jesper

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Diabetes, Atherosclerosis, Cardiovascular, Metabolic and endocrine, Amino Acid Substitution, Angiopoietin-Like Protein 4, Animals, Blood Glucose, Case-Control Studies, Diabetes Mellitus, Type 2, Female, Gene Silencing, Genetic Association Studies, Genetic Variation, Heterozygote, Homeostasis, Humans, Insulin Resistance, Lipoprotein Lipase, Male, Mice, Mice, Inbred C57BL, Mice, Knockout, Risk Factors, Exome Sequencing
Abstract

Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85-0.92, p = 6.3 × 10-10), lower fasting glucose, and greater insulin sensitivity. Predicted loss-of-function variants are associated with lower odds of T2D among 32,015 cases and 84,006 controls (odds ratio 0.71, 95% confidence interval 0.49-0.99, p = 0.041). Functional studies in Angptl4-deficient mice confirm improved insulin sensitivity and glucose homeostasis. In conclusion, genetic inactivation of ANGPTL4 is associated with improved glucose homeostasis and reduced risk of T2D.

Published
2018

29. Dairy Consumption and Body Mass Index Among Adults: Mendelian Randomization Analysis of 184802 Individuals from 25 Studies

Author

Huang, Tao, Ding, Ming, Bergholdt Helle, KM, Wang, Tiange, Heianza, Yoriko, Sun, Dianjianyi, Frazier-Wood Alexis, C, Aslibekyan, Stella, North Kari, E, Voortman, Trudy, Graff, Mariaelisa, Smith Caren, E, Lai, Chao-Qiang, Varbo, Anette, Lemaitre, Rozenn N, de Jonge, M Ester AL, Fumeron, Frédéric, Corella, Dolores, Wang, Carol A, Tjønneland, Anne, Overvad, Kim, Sørensen, Thorkild IA, Feitosa, Mary F, Wojczynski, Mary K, Kähönen, Mika, Renström, Frida, Psaty, Bruce M, Siscovick, David S, Barroso, Inês, Johansson, Ingegerd, Hernandez, Dena, Ferrucci, Luigi, Bandinelli, Stefania, Linneberg, Allan, Zillikens, M Carola, Sandholt, Camilla Helene, Pedersen, Oluf, Hansen, Torben, Schulz, Christina-Alexandra, Sonestedt, Emily, Orho-Melander, Marju, Chen, Tzu-An, Rotter, Jerome I, Allison, Mathew A, Rich, Stephen S, Sorlí, Jose V, Coltell, Oscar, Pennell, Craig E, Eastwood, Peter, Hofman, Albert, Uitterlinden, Andre G, van Rooij, Frank JA, Chu, Audrey Y, Rose, Lynda M, Ridker, Paul M, Viikari, Jorma, Raitakari, Olli, Lehtimäki, Terho, Mikkilä, Vera, Willett, Walter C, Wang, Yujie, Tucker, Katherine L, Ordovas, Jose M, Kilpeläinen, Tuomas O, Province, Michael A, Franks, Paul W, Arnett, Donna K, Tanaka, Toshiko, Toft, Ulla, Ericson, Ulrika, Franco, Oscar H, Mozaffarian, Dariush, Hu, Frank B, Chasman, Daniel I, Nordestgaard, Børge G, Ellervik, Christina, and Qi, Lu

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Prevention, Genetics, Adult, Body Mass Index, Body Weight, Cross-Sectional Studies, Dairy Products, Genotype, Humans, Mendelian Randomization Analysis, Polymorphism, Genetic, Polymorphism, Single Nucleotide, Prospective Studies, Mendelian Randomization of Dairy Consumption Working Group, Medical Biotechnology, Medical Biochemistry and Metabolomics, Clinical Sciences, General Clinical Medicine, Clinical sciences, Medical biochemistry and metabolomics
Abstract

BackgroundAssociations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined.MethodsWe performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies.ResultsHigher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00-0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14-0.25) serving/day higher dairy intake (P = 3.15 × 10-12) and 0.12 (95% CI, 0.06-0.17) kg/m2 higher BMI (P = 2.11 × 10-5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27-0.92; P = 3.0 × 10-4).ConclusionsThe present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.

Published
2018

30. Correction: Publisher Correction: Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation

Author

Ghoussaini, Maya, Edwards, Stacey L, Michailidou, Kyriaki, Nord, Silje, Cowper-Sal·lari, Richard, Desai, Kinjal, Kar, Siddhartha, Hillman, Kristine M, Kaufmann, Susanne, Glubb, Dylan M, Beesley, Jonathan, Dennis, Joe, Bolla, Manjeet K, Wang, Qin, Dicks, Ed, Guo, Qi, Schmidt, Marjanka K, Shah, Mitul, Luben, Robert, Brown, Judith, Czene, Kamila, Darabi, Hatef, Eriksson, Mikael, Klevebring, Daniel, Bojesen, Stig E, Nordestgaard, Børge G, Nielsen, Sune F, Flyger, Henrik, Lambrechts, Diether, Thienpont, Bernard, Neven, Patrick, Wildiers, Hans, Broeks, Annegien, Van’t Veer, Laura J, Rutgers, Emiel J Th, Couch, Fergus J, Olson, Janet E, Hallberg, Emily, Vachon, Celine, Chang-Claude, Jenny, Rudolph, Anja, Seibold, Petra, Flesch-Janys, Dieter, Peto, Julian, dos-Santos-Silva, Isabel, Gibson, Lorna, Nevanlinna, Heli, Muranen, Taru A, Aittomäki, Kristiina, Blomqvist, Carl, Hall, Per, Li, Jingmei, Liu, Jianjun, Humphreys, Keith, Kang, Daehee, Choi, Ji-Yeob, Park, Sue K, Noh, Dong-Young, Matsuo, Keitaro, Ito, Hidemi, Iwata, Hiroji, Yatabe, Yasushi, Guénel, Pascal, Truong, Thérèse, Menegaux, Florence, Sanchez, Marie, Burwinkel, Barbara, Marme, Frederik, Schneeweiss, Andreas, Sohn, Christof, Wu, Anna H, Tseng, Chiu-chen, Van Den Berg, David, Stram, Daniel O, Benitez, Javier, Pilar Zamora, M, Perez, Jose Ignacio Arias, Menéndez, Primitiva, Shu, Xiao-Ou, Lu, Wei, Gao, Yu-Tang, Cai, Qiuyin, Cox, Angela, Cross, Simon S, Reed, Malcolm WR, Andrulis, Irene L, Knight, Julia A, Glendon, Gord, Tchatchou, Sandrine, Sawyer, Elinor J, Tomlinson, Ian, Kerin, Michael J, Miller, Nicola, Haiman, Christopher A, Henderson, Brian E, Schumacher, Fredrick, Le Marchand, Loic, Lindblom, Annika, Margolin, Sara, and Teo, Soo Hwang

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Breast Cancer, Cancer
Abstract

This corrects the article DOI: 10.1038/ncomms5999.

Published
2018

31. Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease

Author

Zhao, Wei, Rasheed, Asif, Tikkanen, Emmi, Lee, Jung-Jin, Butterworth, Adam S, Howson, Joanna MM, Assimes, Themistocles L, Chowdhury, Rajiv, Orho-Melander, Marju, Damrauer, Scott, Small, Aeron, Asma, Senay, Imamura, Minako, Yamauch, Toshimasa, Chambers, John C, Chen, Peng, Sapkota, Bishwa R, Shah, Nabi, Jabeen, Sehrish, Surendran, Praveen, Lu, Yingchang, Zhang, Weihua, Imran, Atif, Abbas, Shahid, Majeed, Faisal, Trindade, Kevin, Qamar, Nadeem, Mallick, Nadeem Hayyat, Yaqoob, Zia, Saghir, Tahir, Rizvi, Syed Nadeem Hasan, Memon, Anis, Rasheed, Syed Zahed, Memon, Fazal-ur-Rehman, Mehmood, Khalid, Ahmed, Naveeduddin, Qureshi, Irshad Hussain, Tanveer-us-Salam, Iqbal, Wasim, Malik, Uzma, Mehra, Narinder, Kuo, Jane Z, Sheu, Wayne H-H, Guo, Xiuqing, Hsiung, Chao A, Juang, Jyh-Ming J, Taylor, Kent D, Hung, Yi-Jen, Lee, Wen-Jane, Quertermous, Thomas, Lee, I-Te, Hsu, Chih-Cheng, Bottinger, Erwin P, Ralhan, Sarju, Teo, Yik Ying, Wang, Tzung-Dau, Alam, Dewan S, Di Angelantonio, Emanuele, Epstein, Steve, Nielsen, Sune F, Nordestgaard, Børge G, Tybjaerg-Hansen, Anne, Young, Robin, Benn, Marianne, Frikke-Schmidt, Ruth, Kamstrup, Pia R, Jukema, J Wouter, Sattar, Naveed, Smit, Roelof, Chung, Ren-Hua, Liang, Kae-Woei, Anand, Sonia, Sanghera, Dharambir K, Ripatti, Samuli, Loos, Ruth JF, Kooner, Jaspal S, Tai, E Shyong, Rotter, Jerome I, Chen, Yii-Der Ida, Frossard, Philippe, Maeda, Shiro, Kadowaki, Takashi, Reilly, Muredach, Pare, Guillaume, Melander, Olle, Salomaa, Veikko, Rader, Daniel J, Danesh, John, Voight, Benjamin F, and Saleheen, Danish

Subjects
Biological Sciences, Genetics, Obesity, Human Genome, Heart Disease - Coronary Heart Disease, Clinical Research, Heart Disease, Diabetes, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Metabolic and endocrine, Asia, Asian People, Biomarkers, Comorbidity, Coronary Disease, Diabetes Mellitus, Type 2, Europe, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, HLA-DRB5 Chains, Humans, Metabolic Networks and Pathways, Metabolic Syndrome, Molecular Targeted Therapy, Mutation, Missense, Polymorphism, Single Nucleotide, Risk Factors, White People, CHD Exome+ Consortium, EPIC-CVD Consortium, EPIC-Interact Consortium, Michigan Biobank, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

To evaluate the shared genetic etiology of type 2 diabetes (T2D) and coronary heart disease (CHD), we conducted a genome-wide, multi-ancestry study of genetic variation for both diseases in up to 265,678 subjects for T2D and 260,365 subjects for CHD. We identify 16 previously unreported loci for T2D and 1 locus for CHD, including a new T2D association at a missense variant in HLA-DRB5 (odds ratio (OR) = 1.29). We show that genetically mediated increase in T2D risk also confers higher CHD risk. Joint T2D-CHD analysis identified eight variants-two of which are coding-where T2D and CHD associations appear to colocalize, including a new joint T2D-CHD association at the CCDC92 locus that also replicated for T2D. The variants associated with both outcomes implicate new pathways as well as targets of existing drugs, including icosapent ethyl and adipocyte fatty-acid-binding protein.

Published
2017

32. Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

Author

Yarmolinsky, James, primary, Robinson, Jamie W., additional, Mariosa, Daniela, additional, Karhunen, Ville, additional, Huang, Jian, additional, Dimou, Niki, additional, Murphy, Neil, additional, Burrows, Kimberley, additional, Bouras, Emmanouil, additional, Smith-Byrne, Karl, additional, Lewis, Sarah J., additional, Galesloot, Tessel E., additional, Kiemeney, Lambertus A., additional, Vermeulen, Sita, additional, Martin, Paul, additional, Albanes, Demetrius, additional, Hou, Lifang, additional, Newcomb, Polly A., additional, White, Emily, additional, Wolk, Alicja, additional, Wu, Anna H., additional, Le Marchand, Loïc, additional, Phipps, Amanda I., additional, Buchanan, Daniel D., additional, Zhao, Sizheng Steven, additional, Gill, Dipender, additional, Chanock, Stephen J., additional, Purdue, Mark P., additional, Davey Smith, George, additional, Brennan, Paul, additional, Herzig, Karl-Heinz, additional, Järvelin, Marjo-Riitta, additional, Amos, Chris I., additional, Hung, Rayjean J., additional, Dehghan, Abbas, additional, Johansson, Mattias, additional, Gunter, Marc J., additional, Tsilidis, Kostas K., additional, Martin, Richard M., additional, Landi, Maria Teresa, additional, Stevens, Victoria, additional, Wang, Ying, additional, Albanes, Demetrios, additional, Caporaso, Neil, additional, Amos, Christopher I., additional, Shete, Sanjay, additional, Bickeböller, Heike, additional, Risch, Angela, additional, Houlston, Richard, additional, Lam, Stephen, additional, Tardon, Adonina, additional, Chen, Chu, additional, Bojesen, Stig E., additional, Wichmann, H-Erich, additional, Christiani, David, additional, Rennert, Gadi, additional, Arnold, Susanne, additional, Field, John K., additional, Le Marchand, Loic, additional, Melander, Olle, additional, Brunnström, Hans, additional, Liu, Geoffrey, additional, Andrew, Angeline, additional, Shen, Hongbing, additional, Zienolddiny, Shan, additional, Grankvist, Kjell, additional, Johansson, Mikael, additional, Teare, M. Dawn, additional, Hong, Yun-Chul, additional, Yuan, Jian-Min, additional, Lazarus, Philip, additional, Schabath, Matthew B., additional, Aldrich, Melinda C., additional, Eeles, Rosalind A., additional, Haiman, Christopher A., additional, Kote-Jarai, Zsofia, additional, Schumacher, Fredrick R., additional, Benlloch, Sara, additional, Al Olama, Ali Amin, additional, Muir, Kenneth R., additional, Berndt, Sonja I., additional, Conti, David V., additional, Wiklund, Fredrik, additional, Chanock, Stephen, additional, Tangen, Catherine M., additional, Batra, Jyotsna, additional, Clements, Judith A., additional, Grönberg, Henrik, additional, Pashayan, Nora, additional, Schleutker, Johanna, additional, Weinstein, Stephanie J., additional, West, Catharine M.L., additional, Mucci, Lorelei A., additional, Cancel-Tassin, Géraldine, additional, Koutros, Stella, additional, Sørensen, Karina Dalsgaard, additional, Grindedal, Eli Marie, additional, Neal, David E., additional, Hamdy, Freddie C., additional, Donovan, Jenny L., additional, Travis, Ruth C., additional, Hamilton, Robert J., additional, Ingles, Sue Ann, additional, Rosenstein, Barry S., additional, Lu, Yong-Jie, additional, Giles, Graham G., additional, MacInnis, Robert J., additional, Kibel, Adam S., additional, Vega, Ana, additional, Kogevinas, Manolis, additional, Penney, Kathryn L., additional, Park, Jong Y., additional, Stanfrod, Janet L., additional, Cybulski, Cezary, additional, Nordestgaard, Børge G., additional, Nielsen, Sune F., additional, Brenner, Hermann, additional, Maier, Christiane, additional, Logothetis, Christopher J., additional, John, Esther M., additional, Teixeira, Manuel R., additional, Neuhausen, Susan L., additional, De Ruyck, Kim, additional, Razack, Azad, additional, Newcomb, Lisa F., additional, Lessel, Davor, additional, Kaneva, Radka, additional, Usmani, Nawaid, additional, Claessens, Frank, additional, Townsend, Paul A., additional, Castelao, Jose Esteban, additional, Roobol, Monique J., additional, Menegaux, Florence, additional, Khaw, Kay-Tee, additional, Cannon-Albright, Lisa, additional, Pandha, Hardev, additional, Thibodeau, Stephen N., additional, Hunter, David J., additional, Kraft, Peter, additional, Blot, William J., additional, and Riboli, Elio, additional

Published
2024
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33. Fraction of exhaled nitric oxide is higher in liver transplant recipients than in controls from the general population: a cohort study

Author

Arentoft, Nicoline S., primary, Fialla, Annette D., additional, Krohn, Paul S., additional, Patursson, Magda T., additional, Thudium, Rebekka F., additional, Suarez-Zdunek, Moises A., additional, Høgh, Julie, additional, Lauridsen, Emilie H. E., additional, Hansen, Jesper B., additional, Jensen, Jens-Ulrik S., additional, Perch, Michael, additional, Møller, Dina L., additional, Pommergaard, Hans-Christian, additional, Aagaard, Niels K., additional, Davidsen, Jesper R., additional, Lange, Peter, additional, Çolak, Yunus, additional, Afzal, Shoaib, additional, Nordestgaard, Børge G., additional, Rasmussen, Allan, additional, and Nielsen, Susanne D., additional

Published
2024
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34. Sedentary work and risk of venous thromboembolism

Author

Johannesen, Camilla Ditlev Lindhardt, Flachs, Esben Meulengracht, Ebbehøj, Niels E, Marott, Jacob Louis, Jensen, Gorm Boje, Nordestgaard, Børge G, Schnohr, Peter, and Bonde, Jens Peter E

Published
2020

38. Low-density lipoproteins cause atherosclerotic cardiovascular disease. 1. Evidence from genetic, epidemiologic, and clinical studies. A consensus statement from the European Atherosclerosis Society Consensus Panel

Author

Ference, Brian A, Ginsberg, Henry N, Graham, Ian, Ray, Kausik K, Packard, Chris J, Bruckert, Eric, Hegele, Robert A, Krauss, Ronald M, Raal, Frederick J, Schunkert, Heribert, Watts, Gerald F, Borén, Jan, Fazio, Sergio, Horton, Jay D, Masana, Luis, Nicholls, Stephen J, Nordestgaard, Børge G, van de Sluis, Bart, Taskinen, Marja-Riitta, Tokgözoğlu, Lale, Landmesser, Ulf, Laufs, Ulrich, Wiklund, Olov, Stock, Jane K, Chapman, M John, and Catapano, Alberico L

Subjects
Cardiovascular, Atherosclerosis, Clinical Trials and Supportive Activities, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Anticholesteremic Agents, Cholesterol, HDL, Cholesterol, LDL, Consensus, Epidemiologic Methods, Ezetimibe, Genetic Predisposition to Disease, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Hyperlipidemias, Lipoproteins, LDL, PCSK9 Inhibitors, Cardiovascular disease, Causality, Clinical trials, Low-density lipoprotein, Mendelian randomization, PCSK9, Recommendations, Statin, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Cardiovascular System & Hematology
Abstract

AimsTo appraise the clinical and genetic evidence that low-density lipoproteins (LDLs) cause atherosclerotic cardiovascular disease (ASCVD).Methods and resultsWe assessed whether the association between LDL and ASCVD fulfils the criteria for causality by evaluating the totality of evidence from genetic studies, prospective epidemiologic cohort studies, Mendelian randomization studies, and randomized trials of LDL-lowering therapies. In clinical studies, plasma LDL burden is usually estimated by determination of plasma LDL cholesterol level (LDL-C). Rare genetic mutations that cause reduced LDL receptor function lead to markedly higher LDL-C and a dose-dependent increase in the risk of ASCVD, whereas rare variants leading to lower LDL-C are associated with a correspondingly lower risk of ASCVD. Separate meta-analyses of over 200 prospective cohort studies, Mendelian randomization studies, and randomized trials including more than 2 million participants with over 20 million person-years of follow-up and over 150 000 cardiovascular events demonstrate a remarkably consistent dose-dependent log-linear association between the absolute magnitude of exposure of the vasculature to LDL-C and the risk of ASCVD; and this effect appears to increase with increasing duration of exposure to LDL-C. Both the naturally randomized genetic studies and the randomized intervention trials consistently demonstrate that any mechanism of lowering plasma LDL particle concentration should reduce the risk of ASCVD events proportional to the absolute reduction in LDL-C and the cumulative duration of exposure to lower LDL-C, provided that the achieved reduction in LDL-C is concordant with the reduction in LDL particle number and that there are no competing deleterious off-target effects.ConclusionConsistent evidence from numerous and multiple different types of clinical and genetic studies unequivocally establishes that LDL causes ASCVD.

Published
2017

39. Genetic and Pharmacologic Inactivation of ANGPTL3 and Cardiovascular Disease

Author

Dewey, Frederick E, Gusarova, Viktoria, Dunbar, Richard L, O'Dushlaine, Colm, Schurmann, Claudia, Gottesman, Omri, McCarthy, Shane, Van Hout, Cristopher V, Bruse, Shannon, Dansky, Hayes M, Leader, Joseph B, Murray, Michael F, Ritchie, Marylyn D, Kirchner, H Lester, Habegger, Lukas, Lopez, Alex, Penn, John, Zhao, An, Shao, Weiping, Stahl, Neil, Murphy, Andrew J, Hamon, Sara, Bouzelmat, Aurelie, Zhang, Rick, Shumel, Brad, Pordy, Robert, Gipe, Daniel, Herman, Gary A, Sheu, Wayne HH, Lee, I-Te, Liang, Kae-Woei, Guo, Xiuqing, Rotter, Jerome I, Chen, Yii-Der I, Kraus, William E, Shah, Svati H, Damrauer, Scott, Small, Aeron, Rader, Daniel J, Wulff, Anders Berg, Nordestgaard, Børge G, Tybjærg-Hansen, Anne, van den Hoek, Anita M, Princen, Hans MG, Ledbetter, David H, Carey, David J, Overton, John D, Reid, Jeffrey G, Sasiela, William J, Banerjee, Poulabi, Shuldiner, Alan R, Borecki, Ingrid B, Teslovich, Tanya M, Yancopoulos, George D, Mellis, Scott J, Gromada, Jesper, and Baras, Aris

Subjects
Genetics, Heart Disease, Clinical Research, Atherosclerosis, Heart Disease - Coronary Heart Disease, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Aged, Angiopoietin-Like Protein 3, Angiopoietin-like Proteins, Angiopoietins, Animals, Antibodies, Monoclonal, Cardiovascular Diseases, Coronary Artery Disease, Disease Models, Animal, Dose-Response Relationship, Drug, Double-Blind Method, Dyslipidemias, Female, Humans, Lipid Metabolism, Lipids, Male, Mice, Mice, Inbred Strains, Middle Aged, Mutation, Medical and Health Sciences, General & Internal Medicine
Abstract

BackgroundLoss-of-function variants in the angiopoietin-like 3 gene (ANGPTL3) have been associated with decreased plasma levels of triglycerides, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol. It is not known whether such variants or therapeutic antagonism of ANGPTL3 are associated with a reduced risk of atherosclerotic cardiovascular disease.MethodsWe sequenced the exons of ANGPTL3 in 58,335 participants in the DiscovEHR human genetics study. We performed tests of association for loss-of-function variants in ANGPTL3 with lipid levels and with coronary artery disease in 13,102 case patients and 40,430 controls from the DiscovEHR study, with follow-up studies involving 23,317 case patients and 107,166 controls from four population studies. We also tested the effects of a human monoclonal antibody, evinacumab, against Angptl3 in dyslipidemic mice and against ANGPTL3 in healthy human volunteers with elevated levels of triglycerides or LDL cholesterol.ResultsIn the DiscovEHR study, participants with heterozygous loss-of-function variants in ANGPTL3 had significantly lower serum levels of triglycerides, HDL cholesterol, and LDL cholesterol than participants without these variants. Loss-of-function variants were found in 0.33% of case patients with coronary artery disease and in 0.45% of controls (adjusted odds ratio, 0.59; 95% confidence interval, 0.41 to 0.85; P=0.004). These results were confirmed in the follow-up studies. In dyslipidemic mice, inhibition of Angptl3 with evinacumab resulted in a greater decrease in atherosclerotic lesion area and necrotic content than a control antibody. In humans, evinacumab caused a dose-dependent placebo-adjusted reduction in fasting triglyceride levels of up to 76% and LDL cholesterol levels of up to 23%.ConclusionsGenetic and therapeutic antagonism of ANGPTL3 in humans and of Angptl3 in mice was associated with decreased levels of all three major lipid fractions and decreased odds of atherosclerotic cardiovascular disease. (Funded by Regeneron Pharmaceuticals and others; ClinicalTrials.gov number, NCT01749878 .).

Published
2017

40. Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Author

Howson, Joanna MM, Zhao, Wei, Barnes, Daniel R, Ho, Weang-Kee, Young, Robin, Paul, Dirk S, Waite, Lindsay L, Freitag, Daniel F, Fauman, Eric B, Salfati, Elias L, Sun, Benjamin B, Eicher, John D, Johnson, Andrew D, Sheu, Wayne HH, Nielsen, Sune F, Lin, Wei-Yu, Surendran, Praveen, Malarstig, Anders, Wilk, Jemma B, Tybjærg-Hansen, Anne, Rasmussen, Katrine L, Kamstrup, Pia R, Deloukas, Panos, Erdmann, Jeanette, Kathiresan, Sekar, Samani, Nilesh J, Schunkert, Heribert, Watkins, Hugh, Do, Ron, Rader, Daniel J, Johnson, Julie A, Hazen, Stanley L, Quyyumi, Arshed A, Spertus, John A, Pepine, Carl J, Franceschini, Nora, Justice, Anne, Reiner, Alex P, Buyske, Steven, Hindorff, Lucia A, Carty, Cara L, North, Kari E, Kooperberg, Charles, Boerwinkle, Eric, Young, Kristin, Graff, Mariaelisa, Peters, Ulrike, Absher, Devin, Hsiung, Chao A, Lee, Wen-Jane, Taylor, Kent D, Chen, Ying-Hsiang, Lee, I-Te, Guo, Xiuqing, Chung, Ren-Hua, Hung, Yi-Jen, Rotter, Jerome I, Juang, Jyh-Ming J, Quertermous, Thomas, Wang, Tzung-Dau, Rasheed, Asif, Frossard, Philippe, Alam, Dewan S, Majumder, Abdulla al Shafi, Di Angelantonio, Emanuele, Chowdhury, Rajiv, Chen, Yii-Der Ida, Nordestgaard, Børge G, Assimes, Themistocles L, Danesh, John, Butterworth, Adam S, and Saleheen, Danish

Subjects
Biological Sciences, Genetics, Atherosclerosis, Cardiovascular, Human Genome, Heart Disease, Heart Disease - Coronary Heart Disease, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Arteries, Cell Adhesion, Chemotaxis, Leukocyte, Coronary Artery Disease, Energy Metabolism, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Histone Code, Humans, Male, Muscle, Smooth, Vascular, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, CARDIoGRAMplusC4D, EPIC-CVD, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP-CAD associations (P < 5 × 10-8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.

Published
2017

41. Genetic modifiers of CHEK2*1100delC-associated breast cancer risk

Author

Muranen, Taru A, Greco, Dario, Blomqvist, Carl, Aittomäki, Kristiina, Khan, Sofia, Hogervorst, Frans, Verhoef, Senno, Pharoah, Paul DP, Dunning, Alison M, Shah, Mitul, Luben, Robert, Bojesen, Stig E, Nordestgaard, Børge G, Schoemaker, Minouk, Swerdlow, Anthony, García-Closas, Montserrat, Figueroa, Jonine, Dörk, Thilo, Bogdanova, Natalia V, Hall, Per, Li, Jingmei, Khusnutdinova, Elza, Bermisheva, Marina, Kristensen, Vessela, Borresen-Dale, Anne-Lise, Investigators, NBCS, Peto, Julian, dos Santos Silva, Isabel, Couch, Fergus J, Olson, Janet E, Hillemans, Peter, Park-Simon, Tjoung-Won, Brauch, Hiltrud, Hamann, Ute, Burwinkel, Barbara, Marme, Frederik, Meindl, Alfons, Schmutzler, Rita K, Cox, Angela, Cross, Simon S, Sawyer, Elinor J, Tomlinson, Ian, Lambrechts, Diether, Moisse, Matthieu, Lindblom, Annika, Margolin, Sara, Hollestelle, Antoinette, Martens, John WM, Fasching, Peter A, Beckmann, Matthias W, Andrulis, Irene L, Knight, Julia A, Investigators, kConFab AOCS, Anton-Culver, Hoda, Ziogas, Argyrios, Giles, Graham G, Milne, Roger L, Brenner, Hermann, Arndt, Volker, Mannermaa, Arto, Kosma, Veli-Matti, Chang-Claude, Jenny, Rudolph, Anja, Devilee, Peter, Seynaeve, Caroline, Hopper, John L, Southey, Melissa C, John, Esther M, Whittemore, Alice S, Bolla, Manjeet K, Wang, Qin, Michailidou, Kyriaki, Dennis, Joe, Easton, Douglas F, Schmidt, Marjanka K, and Nevanlinna, Heli

Subjects
Cancer, Prevention, Breast Cancer, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, Checkpoint Kinase 2, Female, Genes, Modifier, Genetic Predisposition to Disease, Humans, Odds Ratio, Penetrance, Sequence Deletion, breast cancer, Breast Cancer Association Consortium, CHEK2*1100delC, common variants, polygenic risk score, NBCS Investigators, kConFab/AOCS Investigators, Genetics, Clinical Sciences, Genetics & Heredity
Abstract

PurposeCHEK2*1100delC is a founder variant in European populations that confers a two- to threefold increased risk of breast cancer (BC). Epidemiologic and family studies have suggested that the risk associated with CHEK2*1100delC is modified by other genetic factors in a multiplicative fashion. We have investigated this empirically using data from the Breast Cancer Association Consortium (BCAC).MethodsUsing genotype data from 39,139 (624 1100delC carriers) BC patients and 40,063 (224) healthy controls from 32 BCAC studies, we analyzed the combined risk effects of CHEK2*1100delC and 77 common variants in terms of a polygenic risk score (PRS) and pairwise interaction.ResultsThe PRS conferred odds ratios (OR) of 1.59 (95% CI: 1.21-2.09) per standard deviation for BC for CHEK2*1100delC carriers and 1.58 (1.55-1.62) for noncarriers. No evidence of deviation from the multiplicative model was found. The OR for the highest quintile of the PRS was 2.03 (0.86-4.78) for CHEK2*1100delC carriers, placing them in the high risk category according to UK NICE guidelines. The OR for the lowest quintile was 0.52 (0.16-1.74), indicating a lifetime risk close to the population average.ConclusionOur results confirm the multiplicative nature of risk effects conferred by CHEK2*1100delC and the common susceptibility variants. Furthermore, the PRS could identify carriers at a high lifetime risk for clinical actions.Genet Med advance online publication 06 October 2016.

Published
2017

42. Epigenetic Regulation of F2RL3 Associates with Myocardial Infarction and Platelet Function

Author

Corbin, Laura J., White, Stephen J., Taylor, Amy E., Williams, Christopher M., Taylor, Kurt, van den Bosch, Marion T., Teasdale, Jack E., Jones, Matthew, Bond, Mark, Harper, Matthew T., Falk, Louise, Groom, Alix, Hazell, Georgina G J, Paternoster, Lavinia, Munafò, Marcus R., Nordestgaard, Børge G., Tybjærg-Hansen, Anne, Bojesen, Stig E., Relton, Caroline, Min, Josine L., Smith, George Davey, Mumford, Andrew D., Poole, Alastair W., and Timpson, Nicholas J.

Published
2022
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44. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, Aniket, Malik, Rainer, Hachiya, Tsuyoshi, Jürgenson, Tuuli, Namba, Shinichi, Posner, Daniel C., Kamanu, Frederick K., Koido, Masaru, Le Grand, Quentin, Shi, Mingyang, He, Yunye, Georgakis, Marios K., Caro, Ilana, Krebs, Kristi, Liaw, Yi-Ching, Vaura, Felix C., Lin, Kuang, Winsvold, Bendik Slagsvold, Srinivasasainagendra, Vinodh, Parodi, Livia, Bae, Hee-Joon, Chauhan, Ganesh, Chong, Michael R., Tomppo, Liisa, Akinyemi, Rufus, Roshchupkin, Gennady V., Habib, Naomi, Jee, Yon Ho, Thomassen, Jesper Qvist, Abedi, Vida, Cárcel-Márquez, Jara, Nygaard, Marianne, Leonard, Hampton L., Yang, Chaojie, Yonova-Doing, Ekaterina, Knol, Maria J., Lewis, Adam J., Judy, Renae L., Ago, Tetsuro, Amouyel, Philippe, Armstrong, Nicole D., Bakker, Mark K., Bartz, Traci M., Bennett, David A., Bis, Joshua C., Bordes, Constance, Børte, Sigrid, Cain, Anael, Ridker, Paul M., Cho, Kelly, Chen, Zhengming, Cruchaga, Carlos, Cole, John W., de Jager, Phil L., de Cid, Rafael, Endres, Matthias, Ferreira, Leslie E., Geerlings, Mirjam I., Gasca, Natalie C., Gudnason, Vilmundur, Hata, Jun, He, Jing, Heath, Alicia K., Ho, Yuk-Lam, Havulinna, Aki S., Hopewell, Jemma C., Hyacinth, Hyacinth I., Inouye, Michael, Jacob, Mina A., Jeon, Christina E., Jern, Christina, Kamouchi, Masahiro, Keene, Keith L., Kitazono, Takanari, Kittner, Steven J., Konuma, Takahiro, Kumar, Amit, Lacaze, Paul, Launer, Lenore J., Lee, Keon-Joo, Lepik, Kaido, Li, Jiang, Li, Liming, Manichaikul, Ani, Markus, Hugh S., Marston, Nicholas A., Meitinger, Thomas, Mitchell, Braxton D., Montellano, Felipe A., Morisaki, Takayuki, Mosley, Thomas H., Nalls, Mike A., Nordestgaard, Børge G., O’Donnell, Martin J., Okada, Yukinori, Onland-Moret, N. Charlotte, Ovbiagele, Bruce, Peters, Annette, Psaty, Bruce M., Rich, Stephen S., Rosand, Jonathan, Sabatine, Marc S., Sacco, Ralph L., Saleheen, Danish, Sandset, Else Charlotte, Salomaa, Veikko, Sargurupremraj, Muralidharan, Sasaki, Makoto, Satizabal, Claudia L., Schmidt, Carsten O., Shimizu, Atsushi, Smith, Nicholas L., Sloane, Kelly L., Sutoh, Yoichi, Sun, Yan V., Tanno, Kozo, Tiedt, Steffen, Tatlisumak, Turgut, Torres-Aguila, Nuria P., Tiwari, Hemant K., Trégouët, David-Alexandre, Trompet, Stella, Tuladhar, Anil Man, Tybjærg-Hansen, Anne, van Vugt, Marion, Vibo, Riina, Verma, Shefali S., Wiggins, Kerri L., Wennberg, Patrik, Woo, Daniel, Wilson, Peter W. F., Xu, Huichun, Yang, Qiong, Yoon, Kyungheon, Millwood, Iona Y., Gieger, Christian, Ninomiya, Toshiharu, Grabe, Hans J., Jukema, J. Wouter, Rissanen, Ina L., Strbian, Daniel, Kim, Young Jin, Chen, Pei-Hsin, Mayerhofer, Ernst, Howson, Joanna M. M., Irvin, Marguerite R., Adams, Hieab, Wassertheil-Smoller, Sylvia, Christensen, Kaare, Ikram, Mohammad A., Rundek, Tatjana, Worrall, Bradford B., Lathrop, G. Mark, Riaz, Moeen, Simonsick, Eleanor M., Kõrv, Janika, França, Paulo H. C., Zand, Ramin, Prasad, Kameshwar, Frikke-Schmidt, Ruth, de Leeuw, Frank-Erik, Liman, Thomas, Haeusler, Karl Georg, Ruigrok, Ynte M., Heuschmann, Peter Ulrich, Longstreth, W. T., Jung, Keum Ji, Bastarache, Lisa, Paré, Guillaume, Damrauer, Scott M., Chasman, Daniel I., Rotter, Jerome I., Anderson, Christopher D., Zwart, John-Anker, Niiranen, Teemu J., Fornage, Myriam, Liaw, Yung-Po, Seshadri, Sudha, Fernández-Cadenas, Israel, Walters, Robin G., Ruff, Christian T., Owolabi, Mayowa O., Huffman, Jennifer E., Milani, Lili, Kamatani, Yoichiro, Dichgans, Martin, and Debette, Stephanie

Published
2022
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45. Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

Author

Kar, Siddhartha P, Beesley, Jonathan, Olama, Ali Amin Al, Michailidou, Kyriaki, Tyrer, Jonathan, Kote-Jarai, ZSofia, Lawrenson, Kate, Lindstrom, Sara, Ramus, Susan J, Thompson, Deborah J, Investigators, ABCTB, Kibel, Adam S, Dansonka-Mieszkowska, Agnieszka, Michael, Agnieszka, Dieffenbach, Aida K, Gentry-Maharaj, Aleksandra, Whittemore, Alice S, Wolk, Alicja, Monteiro, Alvaro, Peixoto, Ana, Kierzek, Andrzej, Cox, Angela, Rudolph, Anja, Gonzalez-Neira, Anna, Wu, Anna H, Lindblom, Annika, Swerdlow, Anthony, Study, AOCS Study Group amp Australian Cancer, BioResource, APCB, Ziogas, Argyrios, Ekici, Arif B, Burwinkel, Barbara, Karlan, Beth Y, Nordestgaard, Børge G, Blomqvist, Carl, Phelan, Catherine, McLean, Catriona, Pearce, Celeste Leigh, Vachon, Celine, Cybulski, Cezary, Slavov, Chavdar, Stegmaier, Christa, Maier, Christiane, Ambrosone, Christine B, Høgdall, Claus K, Teerlink, Craig C, Kang, Daehee, Tessier, Daniel C, Schaid, Daniel J, Stram, Daniel O, Cramer, Daniel W, Neal, David E, Eccles, Diana, Flesch-Janys, Dieter, Edwards, Digna R Velez, Wokozorczyk, Dominika, Levine, Douglas A, Yannoukakos, Drakoulis, Sawyer, Elinor J, Bandera, Elisa V, Poole, Elizabeth M, Goode, Ellen L, Khusnutdinova, Elza, Høgdall, Estrid, Song, Fengju, Bruinsma, Fiona, Heitz, Florian, Modugno, Francesmary, Hamdy, Freddie C, Wiklund, Fredrik, Giles, Graham G, Olsson, Håkan, Wildiers, Hans, Ulmer, Hans-Ulrich, Pandha, Hardev, Risch, Harvey A, Darabi, Hatef, Salvesen, Helga B, Nevanlinna, Heli, Gronberg, Henrik, Brenner, Hermann, Brauch, Hiltrud, Anton-Culver, Hoda, Song, Honglin, Lim, Hui-Yi, McNeish, Iain, Campbell, Ian, Vergote, Ignace, Gronwald, Jacek, Lubiński, Jan, Stanford, Janet L, Benítez, Javier, Doherty, Jennifer A, Permuth, Jennifer B, Chang-Claude, Jenny, Donovan, Jenny L, Dennis, Joe, Schildkraut, Joellen M, Schleutker, Johanna, and Hopper, John L

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Oncology and Carcinogenesis, Breast Cancer, Aging, Urologic Diseases, Prostate Cancer, Ovarian Cancer, Rare Diseases, Human Genome, Cancer, Aetiology, 2.1 Biological and endogenous factors, Breast Neoplasms, Case-Control Studies, Chromosome Mapping, Datasets as Topic, Enhancer Elements, Genetic, Female, Gene Regulatory Networks, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Meta-Analysis as Topic, Organ Specificity, Ovarian Neoplasms, Polymorphism, Single Nucleotide, Prostatic Neoplasms, Quantitative Trait Loci, Signal Transduction, ABCTB Investigators, AOCS Study Group & Australian Cancer Study, APCB BioResource, kConFab Investigators, NBCS Investigators, GENICA Network, PRACTICAL consortium, Biochemistry and cell biology, Oncology and carcinogenesis
Abstract

UnlabelledBreast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P < 10(-8) seven new cross-cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P < 10(-5) in the three-cancer meta-analysis.SignificanceWe demonstrate that combining large-scale GWA meta-analysis findings across cancer types can identify completely new risk loci common to breast, ovarian, and prostate cancers. We show that the identification of such cross-cancer risk loci has the potential to shed new light on the shared biology underlying these hormone-related cancers. Cancer Discov; 6(9); 1052-67. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 932.

Published
2016

46. A genomic approach to therapeutic target validation identifies a glucose-lowering GLP1R variant protective for coronary heart disease

Author

Scott, Robert A, Freitag, Daniel F, Li, Li, Chu, Audrey Y, Surendran, Praveen, Young, Robin, Grarup, Niels, Stancáková, Alena, Chen, Yuning, Varga, Tibor V, Yaghootkar, Hanieh, Luan, Jian’an, Zhao, Jing Hua, Willems, Sara M, Wessel, Jennifer, Wang, Shuai, Maruthur, Nisa, Michailidou, Kyriaki, Pirie, Ailith, van der Lee, Sven J, Gillson, Christopher, Al Olama, Ali Amin, Amouyel, Philippe, Arriola, Larraitz, Arveiler, Dominique, Aviles-Olmos, Iciar, Balkau, Beverley, Barricarte, Aurelio, Barroso, Inês, Garcia, Sara Benlloch, Bis, Joshua C, Blankenberg, Stefan, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Borecki, Ingrid B, Bork-Jensen, Jette, Bowden, Sarah, Caldas, Carlos, Caslake, Muriel, consortium, The CVD50, Cupples, L Adrienne, Cruchaga, Carlos, Czajkowski, Jacek, Hoed, Marcel den, Dunn, Janet A, Earl, Helena M, Ehret, Georg B, Ferrannini, Ele, Ferrieres, Jean, Foltynie, Thomas, Ford, Ian, Forouhi, Nita G, Gianfagna, Francesco, Gonzalez, Carlos, Grioni, Sara, Hiller, Louise, Jansson, Jan-Håkan, Jørgensen, Marit E, Jukema, J Wouter, Kaaks, Rudolf, Kee, Frank, Kerrison, Nicola D, Key, Timothy J, Kontto, Jukka, Kote-Jarai, Zsofia, Kraja, Aldi T, Kuulasmaa, Kari, Kuusisto, Johanna, Linneberg, Allan, Liu, Chunyu, Marenne, Gaëlle, Mohlke, Karen L, Morris, Andrew P, Muir, Kenneth, Müller-Nurasyid, Martina, Munroe, Patricia B, Navarro, Carmen, Nielsen, Sune F, Nilsson, Peter M, Nordestgaard, Børge G, Packard, Chris J, Palli, Domenico, Panico, Salvatore, Peloso, Gina M, Perola, Markus, Peters, Annette, Poole, Christopher J, Quirós, J Ramón, Rolandsson, Olov, Sacerdote, Carlotta, Salomaa, Veikko, Sánchez, María-José, Sattar, Naveed, Sharp, Stephen J, Sims, Rebecca, Slimani, Nadia, Smith, Jennifer A, Thompson, Deborah J, and Trompet, Stella

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Clinical Research, Diabetes, Human Genome, Cardiovascular, Prevention, Obesity, Genetics, Heart Disease, Heart Disease - Coronary Heart Disease, Clinical Trials and Supportive Activities, Aetiology, Development of treatments and therapeutic interventions, 5.1 Pharmaceuticals, 2.1 Biological and endogenous factors, Metabolic and endocrine, Good Health and Well Being, Alleles, Coronary Disease, Diabetes Mellitus, Type 2, Dipeptidyl Peptidase 4, Genotype, Glucagon-Like Peptide-1 Receptor, Humans, Receptor, Cannabinoid, CB2, Receptor, Serotonin, 5-HT2C, Receptors, Somatostatin, Sodium-Glucose Transporter 1, CVD50 consortium, GERAD_EC Consortium, Neurology Working Group of the Cohorts for Heart, Aging Research in Genomic Epidemiology, Alzheimer’s Disease Genetics Consortium, Pancreatic Cancer Cohort Consortium, European Prospective Investigation into Cancer and Nutrition–Cardiovascular Disease, EPIC-InterAct, CHARGE consortium, CHD Exome+ Consortium, CARDIOGRAM Exome Consortium, Biological Sciences, Medical and Health Sciences, Medical biotechnology, Biomedical engineering
Abstract

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process.

Published
2016

47. Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.

Author

Gusev, Alexander, Shi, Huwenbo, Kichaev, Gleb, Pomerantz, Mark, Li, Fugen, Long, Henry W, Ingles, Sue A, Kittles, Rick A, Strom, Sara S, Rybicki, Benjamin A, Nemesure, Barbara, Isaacs, William B, Zheng, Wei, Pettaway, Curtis A, Yeboah, Edward D, Tettey, Yao, Biritwum, Richard B, Adjei, Andrew A, Tay, Evelyn, Truelove, Ann, Niwa, Shelley, Chokkalingam, Anand P, John, Esther M, Murphy, Adam B, Signorello, Lisa B, Carpten, John, Leske, M Cristina, Wu, Suh-Yuh, Hennis, Anslem JM, Neslund-Dudas, Christine, Hsing, Ann W, Chu, Lisa, Goodman, Phyllis J, Klein, Eric A, Witte, John S, Casey, Graham, Kaggwa, Sam, Cook, Michael B, Stram, Daniel O, Blot, William J, Eeles, Rosalind A, Easton, Douglas, Kote-Jarai, Zsofia, Al Olama, Ali Amin, Benlloch, Sara, Muir, Kenneth, Giles, Graham G, Southey, Melissa C, Fitzgerald, Liesel M, Gronberg, Henrik, Wiklund, Fredrik, Aly, Markus, Henderson, Brian E, Schleutker, Johanna, Wahlfors, Tiina, Tammela, Teuvo LJ, Nordestgaard, Børge G, Key, Tim J, Travis, Ruth C, Neal, David E, Donovan, Jenny L, Hamdy, Freddie C, Pharoah, Paul, Pashayan, Nora, Khaw, Kay-Tee, Stanford, Janet L, Thibodeau, Stephen N, McDonnell, Shannon K, Schaid, Daniel J, Maier, Christiane, Vogel, Walther, Luedeke, Manuel, Herkommer, Kathleen, Kibel, Adam S, Cybulski, Cezary, Wokolorczyk, Dominika, Kluzniak, Wojciech, Cannon-Albright, Lisa, Teerlink, Craig, Brenner, Hermann, Dieffenbach, Aida K, Arndt, Volker, Park, Jong Y, Sellers, Thomas A, Lin, Hui-Yi, Slavov, Chavdar, Kaneva, Radka, Mitev, Vanio, Batra, Jyotsna, Spurdle, Amanda, Clements, Judith A, Teixeira, Manuel R, Pandha, Hardev, Michael, Agnieszka, Paulo, Paula, Maia, Sofia, Kierzek, Andrzej, PRACTICAL consortium, Conti, David V, and Albanes, Demetrius

Subjects
PRACTICAL consortium, Cell Line, Tumor, Humans, Prostatic Neoplasms, Genetic Predisposition to Disease, Histones, Epigenesis, Genetic, Acetylation, Inheritance Patterns, Linkage Disequilibrium, Polymorphism, Single Nucleotide, African Americans, European Continental Ancestry Group, Male, Atlases as Topic, Genome-Wide Association Study, Genetic Loci, Cell Line, Tumor, Epigenesis, Genetic, Polymorphism, Single Nucleotide
Abstract

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.

Published
2016

48. Genetic variation in the immunosuppression pathway genes and breast cancer susceptibility: a pooled analysis of 42,510 cases and 40,577 controls from the Breast Cancer Association Consortium

Author

Lei, Jieping, Rudolph, Anja, Moysich, Kirsten B, Behrens, Sabine, Goode, Ellen L, Bolla, Manjeet K, Dennis, Joe, Dunning, Alison M, Easton, Douglas F, Wang, Qin, Benitez, Javier, Hopper, John L, Southey, Melissa C, Schmidt, Marjanka K, Broeks, Annegien, Fasching, Peter A, Haeberle, Lothar, Peto, Julian, dos-Santos-Silva, Isabel, Sawyer, Elinor J, Tomlinson, Ian, Burwinkel, Barbara, Marmé, Frederik, Guénel, Pascal, Truong, Thérèse, Bojesen, Stig E, Flyger, Henrik, Nielsen, Sune F, Nordestgaard, Børge G, González-Neira, Anna, Menéndez, Primitiva, Anton-Culver, Hoda, Neuhausen, Susan L, Brenner, Hermann, Arndt, Volker, Meindl, Alfons, Schmutzler, Rita K, Brauch, Hiltrud, Hamann, Ute, Nevanlinna, Heli, Fagerholm, Rainer, Dörk, Thilo, Bogdanova, Natalia V, Mannermaa, Arto, Hartikainen, Jaana M, Australian Ovarian Study Group, kConFab Investigators, Van Dijck, Laurien, Smeets, Ann, Flesch-Janys, Dieter, Eilber, Ursula, Radice, Paolo, Peterlongo, Paolo, Couch, Fergus J, Hallberg, Emily, Giles, Graham G, Milne, Roger L, Haiman, Christopher A, Schumacher, Fredrick, Simard, Jacques, Goldberg, Mark S, Kristensen, Vessela, Borresen-Dale, Anne-Lise, Zheng, Wei, Beeghly-Fadiel, Alicia, Winqvist, Robert, Grip, Mervi, Andrulis, Irene L, Glendon, Gord, García-Closas, Montserrat, Figueroa, Jonine, Czene, Kamila, Brand, Judith S, Darabi, Hatef, Eriksson, Mikael, Hall, Per, Li, Jingmei, Cox, Angela, Cross, Simon S, Pharoah, Paul DP, Shah, Mitul, Kabisch, Maria, Torres, Diana, Jakubowska, Anna, Lubinski, Jan, Ademuyiwa, Foluso, Ambrosone, Christine B, Swerdlow, Anthony, Jones, Michael, and Chang-Claude, Jenny

Subjects
Breast Cancer, Genetics, Human Genome, Cancer, 2.1 Biological and endogenous factors, Aetiology, Breast Neoplasms, Case-Control Studies, Female, Genetic Predisposition to Disease, Humans, Immune Tolerance, Polymorphism, Single Nucleotide, Australian Ovarian Study Group, kConFab Investigators, Complementary and Alternative Medicine, Paediatrics and Reproductive Medicine, Genetics & Heredity
Abstract

Immunosuppression plays a pivotal role in assisting tumors to evade immune destruction and promoting tumor development. We hypothesized that genetic variation in the immunosuppression pathway genes may be implicated in breast cancer tumorigenesis. We included 42,510 female breast cancer cases and 40,577 controls of European ancestry from 37 studies in the Breast Cancer Association Consortium (2015) with available genotype data for 3595 single nucleotide polymorphisms (SNPs) in 133 candidate genes. Associations between genotyped SNPs and overall breast cancer risk, and secondarily according to estrogen receptor (ER) status, were assessed using multiple logistic regression models. Gene-level associations were assessed based on principal component analysis. Gene expression analyses were conducted using RNA sequencing level 3 data from The Cancer Genome Atlas for 989 breast tumor samples and 113 matched normal tissue samples. SNP rs1905339 (A>G) in the STAT3 region was associated with an increased breast cancer risk (per allele odds ratio 1.05, 95 % confidence interval 1.03-1.08; p value = 1.4 × 10(-6)). The association did not differ significantly by ER status. On the gene level, in addition to TGFBR2 and CCND1, IL5 and GM-CSF showed the strongest associations with overall breast cancer risk (p value = 1.0 × 10(-3) and 7.0 × 10(-3), respectively). Furthermore, STAT3 and IL5 but not GM-CSF were differentially expressed between breast tumor tissue and normal tissue (p value = 2.5 × 10(-3), 4.5 × 10(-4) and 0.63, respectively). Our data provide evidence that the immunosuppression pathway genes STAT3, IL5, and GM-CSF may be novel susceptibility loci for breast cancer in women of European ancestry.

Published
2016

49. RAD51B in Familial Breast Cancer.

Author

Pelttari, Liisa M, Khan, Sofia, Vuorela, Mikko, Kiiski, Johanna I, Vilske, Sara, Nevanlinna, Viivi, Ranta, Salla, Schleutker, Johanna, Winqvist, Robert, Kallioniemi, Anne, Dörk, Thilo, Bogdanova, Natalia V, Figueroa, Jonine, Pharoah, Paul DP, Schmidt, Marjanka K, Dunning, Alison M, García-Closas, Montserrat, Bolla, Manjeet K, Dennis, Joe, Michailidou, Kyriaki, Wang, Qin, Hopper, John L, Southey, Melissa C, Rosenberg, Efraim H, Fasching, Peter A, Beckmann, Matthias W, Peto, Julian, Dos-Santos-Silva, Isabel, Sawyer, Elinor J, Tomlinson, Ian, Burwinkel, Barbara, Surowy, Harald, Guénel, Pascal, Truong, Thérèse, Bojesen, Stig E, Nordestgaard, Børge G, Benitez, Javier, González-Neira, Anna, Neuhausen, Susan L, Anton-Culver, Hoda, Brenner, Hermann, Arndt, Volker, Meindl, Alfons, Schmutzler, Rita K, Brauch, Hiltrud, Brüning, Thomas, Lindblom, Annika, Margolin, Sara, Mannermaa, Arto, Hartikainen, Jaana M, Chenevix-Trench, Georgia, kConFab/AOCS Investigators, Van Dyck, Laurien, Janssen, Hilde, Chang-Claude, Jenny, Rudolph, Anja, Radice, Paolo, Peterlongo, Paolo, Hallberg, Emily, Olson, Janet E, Giles, Graham G, Milne, Roger L, Haiman, Christopher A, Schumacher, Fredrick, Simard, Jacques, Dumont, Martine, Kristensen, Vessela, Borresen-Dale, Anne-Lise, Zheng, Wei, Beeghly-Fadiel, Alicia, Grip, Mervi, Andrulis, Irene L, Glendon, Gord, Devilee, Peter, Seynaeve, Caroline, Hooning, Maartje J, Collée, Margriet, Cox, Angela, Cross, Simon S, Shah, Mitul, Luben, Robert N, Hamann, Ute, Torres, Diana, Jakubowska, Anna, Lubinski, Jan, Couch, Fergus J, Yannoukakos, Drakoulis, Orr, Nick, Swerdlow, Anthony, Darabi, Hatef, Li, Jingmei, Czene, Kamila, Hall, Per, Easton, Douglas F, Mattson, Johanna, Blomqvist, Carl, Aittomäki, Kristiina, and Nevanlinna, Heli

Subjects
kConFab/AOCS Investigators, Humans, Breast Neoplasms, Genetic Predisposition to Disease, DNA-Binding Proteins, Haplotypes, Heterozygote, Mutation, Missense, Polymorphism, Single Nucleotide, Middle Aged, Finland, Female, Male, Genotyping Techniques, General Science & Technology
Abstract

Common variation on 14q24.1, close to RAD51B, has been associated with breast cancer: rs999737 and rs2588809 with the risk of female breast cancer and rs1314913 with the risk of male breast cancer. The aim of this study was to investigate the role of RAD51B variants in breast cancer predisposition, particularly in the context of familial breast cancer in Finland. We sequenced the coding region of RAD51B in 168 Finnish breast cancer patients from the Helsinki region for identification of possible recurrent founder mutations. In addition, we studied the known rs999737, rs2588809, and rs1314913 SNPs and RAD51B haplotypes in 44,791 breast cancer cases and 43,583 controls from 40 studies participating in the Breast Cancer Association Consortium (BCAC) that were genotyped on a custom chip (iCOGS). We identified one putatively pathogenic missense mutation c.541C>T among the Finnish cancer patients and subsequently genotyped the mutation in additional breast cancer cases (n = 5259) and population controls (n = 3586) from Finland and Belarus. No significant association with breast cancer risk was seen in the meta-analysis of the Finnish datasets or in the large BCAC dataset. The association with previously identified risk variants rs999737, rs2588809, and rs1314913 was replicated among all breast cancer cases and also among familial cases in the BCAC dataset. The most significant association was observed for the haplotype carrying the risk-alleles of all the three SNPs both among all cases (odds ratio (OR): 1.15, 95% confidence interval (CI): 1.11-1.19, P = 8.88 x 10-16) and among familial cases (OR: 1.24, 95% CI: 1.16-1.32, P = 6.19 x 10-11), compared to the haplotype with the respective protective alleles. Our results suggest that loss-of-function mutations in RAD51B are rare, but common variation at the RAD51B region is significantly associated with familial breast cancer risk.

Published
2016

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