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1,876 results on '"Nordestgaard, Børge G"'

1. 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

2. 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

5. 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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6. 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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7. 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

8. 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

9. 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

10. 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

11. 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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12. 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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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

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

21. 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., and Kibel, Adam S.

Subjects
SINGLE nucleotide polymorphisms, GENE frequency
Abstract

Single nucleotide polymorphism (SNP) interactions are the key to improving polygenic risk scores. Previous studies reported several significant SNP–SNP interaction pairs that shared a common SNP to form a cluster, but some identified pairs might be false positives. This study aims to identify factors associated with the cluster effect of false positivity and develop strategies to enhance the accuracy of SNP–SNP interactions. The results showed the cluster effect is a major cause of false-positive findings of SNP–SNP interactions. This cluster effect is due to high correlations between a causal pair and null pairs in a cluster. The clusters with a hub SNP with a significant main effect and a large minor allele frequency (MAF) tended to have a higher false-positive rate. In addition, peripheral null SNPs in a cluster with a small MAF tended to enhance false positivity. We also demonstrated that using the modified significance criterion based on the 3 p-value rules and the bootstrap approach (3pRule + bootstrap) can reduce false positivity and maintain high true positivity. In addition, our results also showed that a pair without a significant main effect tends to have weak or no interaction. This study identified the cluster effect and suggested using the 3pRule + bootstrap approach to enhance SNP–SNP interaction detection accuracy. [ABSTRACT FROM AUTHOR]

Published
2024
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23. 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

24. 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

25. 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

26. 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

27. 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

28. 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

29. 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

30. 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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31. 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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32. 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

34. 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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36. 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

37. 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

38. 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

39. 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

40. 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. Observational and genetic associations between cardiorespiratory fitness and cancer : a UK Biobank and international consortia study

Author

Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, 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., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, 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, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., Brage, Soren, Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, 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., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, 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, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., and Brage, Soren

Abstract

Background: The association of fitness with cancer risk is not clear. Methods: We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of lung, colorectal, endometrial, breast, and prostate cancer in a subset of UK Biobank participants who completed a submaximal fitness test in 2009-12 (N = 72,572). We also investigated relationships using two-sample Mendelian randomisation (MR), odds ratios (ORs) were estimated using the inverse-variance weighted method. Results: After a median of 11 years of follow-up, 4290 cancers of interest were diagnosed. A 3.5 ml O2⋅min−1⋅kg−1 total-body mass increase in fitness (equivalent to 1 metabolic equivalent of task (MET), approximately 0.5 standard deviation (SD)) was associated with lower risks of endometrial (HR = 0.81, 95% CI: 0.73–0.89), colorectal (0.94, 0.90–0.99), and breast cancer (0.96, 0.92–0.99). In MR analyses, a 0.5 SD increase in genetically predicted O2⋅min−1⋅kg−1 fat-free mass was associated with a lower risk of breast cancer (OR = 0.92, 95% CI: 0.86–0.98). After adjusting for adiposity, both the observational and genetic associations were attenuated. Discussion: Higher fitness levels may reduce risks of endometrial, colorectal, and breast cancer, though relationships with adiposity are complex and may mediate these relationships. Increasing fitness, including via changes in body composition, may be an effective strategy for cancer prevention.

Published
2024
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43. Observational and genetic associations between cardiorespiratory fitness and cancer:a UK Biobank and international consortia study

Author

Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, Van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, 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., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, 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, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., Brage, Soren, Watts, Eleanor L., Gonzales, Tomas I., Strain, Tessa, Saint-Maurice, Pedro F., Bishop, D. Timothy, Chanock, Stephen J., Johansson, Mattias, Keku, Temitope O., Le Marchand, Loic, Moreno, Victor, Newcomb, Polly A., Newton, Christina C., Pai, Rish K., Purdue, Mark P., Ulrich, Cornelia M., Smith-Byrne, Karl, Van Guelpen, Bethany, Eeles, Rosalind A., Haiman, Christopher A., Kote-Jarai, Zsofia, Schumacher, Fredrick R., Benlloch, Sara, Olama, Ali Amin Al, Muir, Kenneth R., Berndt, Sonja I., Conti, David V., Wiklund, Fredrik, Wang, Ying, 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., Stanford, Janet L., Cybulski, Cezary, Nordestgaard, Børge G., Nielsen, Sune F., Brenner, Hermann, Maier, Christiane, Kim, Jeri, 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, Day, Felix R., Wijndaele, Katrien, Wareham, Nicholas J., Matthews, Charles E., Moore, Steven C., and Brage, Soren

Abstract

Background: The association of fitness with cancer risk is not clear. Methods: We used Cox proportional hazards models to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for risk of lung, colorectal, endometrial, breast, and prostate cancer in a subset of UK Biobank participants who completed a submaximal fitness test in 2009-12 (N = 72,572). We also investigated relationships using two-sample Mendelian randomisation (MR), odds ratios (ORs) were estimated using the inverse-variance weighted method.Results: After a median of 11 years of follow-up, 4290 cancers of interest were diagnosed. A 3.5 ml O2⋅min−1⋅kg−1 total-body mass increase in fitness (equivalent to 1 metabolic equivalent of task (MET), approximately 0.5 standard deviation (SD)) was associated with lower risks of endometrial (HR = 0.81, 95% CI: 0.73–0.89), colorectal (0.94, 0.90–0.99), and breast cancer (0.96, 0.92–0.99). In MR analyses, a 0.5 SD increase in genetically predicted O2⋅min−1⋅kg−1 fat-free mass was associated with a lower risk of breast cancer (OR = 0.92, 95% CI: 0.86–0.98). After adjusting for adiposity, both the observational and genetic associations were attenuated. Discussion: Higher fitness levels may reduce risks of endometrial, colorectal, and breast cancer, though relationships with adiposity are complex and may mediate these relationships. Increasing fitness, including via changes in body composition, may be an effective strategy for cancer prevention.

Published
2024

44. Remnant cholesterol, LDL cholesterol, and apoB absolute mass changes explain results of the PROMINENT trial

Author

Doi, Takahito, Langsted, Anne, Nordestgaard, Børge G., Doi, Takahito, Langsted, Anne, and Nordestgaard, Børge G.

Abstract

Background and aims The PROMINENT trial, a cardiovascular outcome trial of the triglyceride- and remnant cholesterol-lowering agent pemafibrate, has shown neutral results despite reduction in plasma triglycerides and remnant cholesterol. We tested the hypothesis that absolute mass changes in remnant cholesterol, LDL cholesterol, and apolipoprotein B explain the results of the PROMINENT trial. Methods Among 108,431 individuals from the Copenhagen General Population Study (CGPS), those who met the key inclusion criteria of the PROMINENT trial were analyzed to mimic the trial design. Endpoint atherosclerotic cardiovascular disease (ASCVD) was cardiovascular death, myocardial infarction, ischemic stroke, and coronary revascularization as defined in PROMINENT. Results In the PROMINENT trial, treatment with pemafibrate resulted in -7 mg/dL (−0.18 mmol/L; -18 %) change in remnant cholesterol, +10 mg/dL (+0.26 mmol/L; +12 %) LDL cholesterol, and +5 mg/dL (+0.05 g/L; +5 %) apolipoprotein B. In the CGPS mimicking PROMINENT, the estimated hazard ratios for ASCVD were 0.97 (95 % confidence interval: 0.94–0.99) for a -7 mg/dL (−0.18 mmol/L) change in remnant cholesterol, 1.04 (1.01–1.07) for a +10 mg/dL (+0.26 mmol/L) change in LDL cholesterol, and 1.02 (1.01–1.03) for a +5 mg/dL (+0.05 g/L) change in apolipoprotein B. When combining absolute changes in remnant cholesterol, LDL cholesterol, and apolipoprotein B, the estimated hazard ratio for ASCVD was 1.05 (0.96–1.14) in the CGPS mimicking PROMINENT compared to 1.03 (0.91–1.15) in the PROMINENT trial. Conclusions Absolute mass changes in remnant cholesterol, LDL cholesterol, and apolipoprotein B can explain results of the PROMINENT trial. The 3 mg/dL (0.08 mmol/L) higher total atherogenic cholesterol together with 5 mg/dL (0.05 g/L) higher apolipoprotein B seem to explain the trend toward more ASCVD in the pemafibrate arm., Background and aims: The PROMINENT trial, a cardiovascular outcome trial of the triglyceride- and remnant cholesterol-lowering agent pemafibrate, has shown neutral results despite reduction in plasma triglycerides and remnant cholesterol. We tested the hypothesis that absolute mass changes in remnant cholesterol, LDL cholesterol, and apolipoprotein B explain the results of the PROMINENT trial. Methods: Among 108,431 individuals from the Copenhagen General Population Study (CGPS), those who met the key inclusion criteria of the PROMINENT trial were analyzed to mimic the trial design. Endpoint atherosclerotic cardiovascular disease (ASCVD) was cardiovascular death, myocardial infarction, ischemic stroke, and coronary revascularization as defined in PROMINENT. Results: In the PROMINENT trial, treatment with pemafibrate resulted in -7 mg/dL (−0.18 mmol/L; -18 %) change in remnant cholesterol, +10 mg/dL (+0.26 mmol/L; +12 %) LDL cholesterol, and +5 mg/dL (+0.05 g/L; +5 %) apolipoprotein B. In the CGPS mimicking PROMINENT, the estimated hazard ratios for ASCVD were 0.97 (95 % confidence interval: 0.94–0.99) for a -7 mg/dL (−0.18 mmol/L) change in remnant cholesterol, 1.04 (1.01–1.07) for a +10 mg/dL (+0.26 mmol/L) change in LDL cholesterol, and 1.02 (1.01–1.03) for a +5 mg/dL (+0.05 g/L) change in apolipoprotein B. When combining absolute changes in remnant cholesterol, LDL cholesterol, and apolipoprotein B, the estimated hazard ratio for ASCVD was 1.05 (0.96–1.14) in the CGPS mimicking PROMINENT compared to 1.03 (0.91–1.15) in the PROMINENT trial. Conclusions: Absolute mass changes in remnant cholesterol, LDL cholesterol, and apolipoprotein B can explain results of the PROMINENT trial. The 3 mg/dL (0.08 mmol/L) higher total atherogenic cholesterol together with 5 mg/dL (0.05 g/L) higher apolipoprotein B seem to explain the trend toward more ASCVD in the pemafibrate arm.

Published
2024

45. Remnant Cholesterol, Not LDL Cholesterol, Explains Peripheral Artery Disease Risk Conferred by apoB:A Cohort Study

Author

Wadström, Benjamin N., Pedersen, Kasper M., Wulff, Anders B., Nordestgaard, Børge G., Wadström, Benjamin N., Pedersen, Kasper M., Wulff, Anders B., and Nordestgaard, Børge G.

Abstract

BACKGROUND: Elevated apoB-containing lipoproteins (=remnants+LDLs [low-density lipoproteins]) are a major risk factor for atherosclerotic cardiovascular disease, including peripheral artery disease (PAD) and myocardial infarction. We tested the hypothesis that remnants and LDL both explain part of the increased risk of PAD conferred by elevated apoB-containing lipoproteins. For comparison, we also studied the risk of chronic limb-threatening ischemia and myocardial infarction. METHODS: apoB, remnant cholesterol, and LDL cholesterol were measured in 93 461 individuals without statin use at baseline from the Copenhagen General Population Study (2003–2015). During up to 15 years of follow-up, 1207 had PAD, 552 had chronic limb-threatening ischemia, and 2022 had myocardial infarction in the Danish National Patient Registry. Remnant and LDL cholesterol were calculated from a standard lipid profile. Remnant and LDL particle counts were additionally measured with nuclear magnetic resonance spectroscopy in 25 347 of the individuals. Results were replicated in 302 167 individuals without statin use from the UK Biobank (2004–2010). RESULTS: In the Copenhagen General Population Study, multivariable adjusted hazard ratios for risk of PAD per 1 mmol/L (39 mg/dL) increment in remnant and LDL cholesterol were 1.9 (95% CI, 1.5–2.4) and 1.1 (95% CI, 1.0–1.2), respectively; corresponding results in the UK Biobank were 1.7 (95% CI, 1.4–2.1) and 0.9 (95% CI, 0.9–1.0), respectively. In the association from elevated apoB to increased risk of PAD, remnant and LDL cholesterol explained 73% (32%–100%) and 8% (0%–46%), respectively; corresponding results were 63% (30%–100%) and 0% (0%–33%) for risk of chronic limb-threatening ischemia and 41% (27%–55%) and 54% (38%–70%) for risk of myocardial infarction; results for remnant and LDL particle counts corroborated these findings. CONCLUSIONS: PAD risk conferred by elevated apoB-containing lipoproteins w, BACKGROUND: Elevated apoB-containing lipoproteins (=remnants+LDLs [low-density lipoproteins]) are a major risk factor for atherosclerotic cardiovascular disease, including peripheral artery disease (PAD) and myocardial infarction. We tested the hypothesis that remnants and LDL both explain part of the increased risk of PAD conferred by elevated apoB-containing lipoproteins. For comparison, we also studied the risk of chronic limb-threatening ischemia and myocardial infarction. METHODS: apoB, remnant cholesterol, and LDL cholesterol were measured in 93 461 individuals without statin use at baseline from the Copenhagen General Population Study (2003-2015). During up to 15 years of follow-up, 1207 had PAD, 552 had chronic limb-threatening ischemia, and 2022 had myocardial infarction in the Danish National Patient Registry. Remnant and LDL cholesterol were calculated from a standard lipid profile. Remnant and LDL particle counts were additionally measured with nuclear magnetic resonance spectroscopy in 25 347 of the individuals. Results were replicated in 302 167 individuals without statin use from the UK Biobank (2004-2010). RESULTS: In the Copenhagen General Population Study, multivariable adjusted hazard ratios for risk of PAD per 1 mmol/L (39 mg/dL) increment in remnant and LDL cholesterol were 1.9 (95% CI, 1.5-2.4) and 1.1 (95% CI, 1.0-1.2), respectively; corresponding results in the UK Biobank were 1.7 (95% CI, 1.4-2.1) and 0.9 (95% CI, 0.9-1.0), respectively. In the association from elevated apoB to increased risk of PAD, remnant and LDL cholesterol explained 73% (32%-100%) and 8% (0%-46%), respectively; corresponding results were 63% (30%-100%) and 0% (0%-33%) for risk of chronic limb-threatening ischemia and 41% (27%-55%) and 54% (38%-70%) for risk of myocardial infarction; results for remnant and LDL particle counts corroborated these findings. CONCLUSIONS: PAD risk conferred by elevated apoB-containing lipoproteins was explained mainly by elevated remnants

Published
2024

46. Worldwide trends in underweight and obesity from 1990 to 2022:a pooled analysis of 3663 population-representative studies with 222 million children, adolescents, and adults

Author

Phelps, Nowell H., Singleton, Rosie K., Zhou, Bin, Heap, Rachel A., Mishra, Anu, Bennett, James E., Paciorek, Christopher J., Lhoste, Victor PF, Carrillo-Larco, Rodrigo M., Stevens, Gretchen A., Rodriguez-Martinez, Andrea, Bixby, Honor, Baker, Jennifer L., Aarestrup, Julie, Afzal, Shoaib, Allin, Kristine, Andersen, Lars Bo, Ängquist, Lars, Bjerregaard, Peter, Bojesen, Stig E., Christensen, Kaare, Damsgaard, Camilla T., Dantoft, Thomas M., Eriksen, Louise, Giwercman, Aleksander, Halkjær, Jytte, Jørgensen, Torben, Kristensen, Peter Lund, Lind, Lars, Linneberg, Allan, Liu, Jing, Liu, Liping, Madsen, Anja L., Michaelsen, Kim F., Møllehave, Line T., Mortensen, Erik Lykke, Nordestgaard, Børge G., Osler, Merete, Overvad, Kim, Schmidt, Ida Maria, Schnohr, Peter, Schramm, Stine, Sobngwi, Eugène, Sodemann, Morten, Sørensen, Thorkild IA, Tjonneland, Anne, Tolstrup, Janne S., Wang, Qian, Wang, Ying Wei, Yang, Yang, Phelps, Nowell H., Singleton, Rosie K., Zhou, Bin, Heap, Rachel A., Mishra, Anu, Bennett, James E., Paciorek, Christopher J., Lhoste, Victor PF, Carrillo-Larco, Rodrigo M., Stevens, Gretchen A., Rodriguez-Martinez, Andrea, Bixby, Honor, Baker, Jennifer L., Aarestrup, Julie, Afzal, Shoaib, Allin, Kristine, Andersen, Lars Bo, Ängquist, Lars, Bjerregaard, Peter, Bojesen, Stig E., Christensen, Kaare, Damsgaard, Camilla T., Dantoft, Thomas M., Eriksen, Louise, Giwercman, Aleksander, Halkjær, Jytte, Jørgensen, Torben, Kristensen, Peter Lund, Lind, Lars, Linneberg, Allan, Liu, Jing, Liu, Liping, Madsen, Anja L., Michaelsen, Kim F., Møllehave, Line T., Mortensen, Erik Lykke, Nordestgaard, Børge G., Osler, Merete, Overvad, Kim, Schmidt, Ida Maria, Schnohr, Peter, Schramm, Stine, Sobngwi, Eugène, Sodemann, Morten, Sørensen, Thorkild IA, Tjonneland, Anne, Tolstrup, Janne S., Wang, Qian, Wang, Ying Wei, and Yang, Yang

Abstract

Background: Underweight and obesity are associated with adverse health outcomes throughout the life course. We estimated the individual and combined prevalence of underweight or thinness and obesity, and their changes, from 1990 to 2022 for adults and school-aged children and adolescents in 200 countries and territories. Methods: We used data from 3663 population-based studies with 222 million participants that measured height and weight in representative samples of the general population. We used a Bayesian hierarchical model to estimate trends in the prevalence of different BMI categories, separately for adults (age ≥20 years) and school-aged children and adolescents (age 5–19 years), from 1990 to 2022 for 200 countries and territories. For adults, we report the individual and combined prevalence of underweight (BMI <18·5 kg/m2) and obesity (BMI ≥30 kg/m2). For school-aged children and adolescents, we report thinness (BMI <2 SD below the median of the WHO growth reference) and obesity (BMI >2 SD above the median). Findings: From 1990 to 2022, the combined prevalence of underweight and obesity in adults decreased in 11 countries (6%) for women and 17 (9%) for men with a posterior probability of at least 0·80 that the observed changes were true decreases. The combined prevalence increased in 162 countries (81%) for women and 140 countries (70%) for men with a posterior probability of at least 0·80. In 2022, the combined prevalence of underweight and obesity was highest in island nations in the Caribbean and Polynesia and Micronesia, and countries in the Middle East and north Africa. Obesity prevalence was higher than underweight with posterior probability of at least 0·80 in 177 countries (89%) for women and 145 (73%) for men in 2022, whereas the converse was true in 16 countries (8%) for women, and 39 (20%) for men. From 1990 to 2022, the combined prevalence of thinness and obesity decreased among girls in five countries (3%) and a

Published
2024

47. Lipoprotein(a) and cardiovascular disease:sifting the evidence to guide future research

Author

Kamstrup, Pia R., Neely, R. Dermot G., Nissen, Steven, Landmesser, Ulf, Haghikia, Arash, Costa-Scharplatz, Madlaina, Abbas, Cheryl, Nordestgaard, Børge G, Kamstrup, Pia R., Neely, R. Dermot G., Nissen, Steven, Landmesser, Ulf, Haghikia, Arash, Costa-Scharplatz, Madlaina, Abbas, Cheryl, and Nordestgaard, Børge G

Abstract

Lipoprotein(a) (Lp(a)) is a genetically determined causal risk factor for cardiovascular disease including coronary heart disease, peripheral arterial disease, ischaemic stroke, and calcific aortic valve stenosis. Clinical trials of specific and potent Lp(a)-lowering drugs are currently underway. However, in clinical practice, widespread assessment of Lp(a) is still lacking despite several guideline recommendations to measure Lp(a) at least once in a lifetime in all adults to identify those at high or very high risk due to elevated levels. The present review provides an overview of key findings from observational and genetic Lp(a) studies, highlights the main challenges in observational Lp(a) studies, and proposes a minimum set of requirements to enhance the quality and harmonize the collection of Lp(a)-related data. Adherence to the recommendations set forth in the present manuscript is intended to enhance the quality of future observational Lp(a) studies, to better define thresholds for increased risk, and to better inform clinical trial design. The recommendations can also potentially assist in the interpretation and generalization of clinical trial findings, to improve care of patients with elevated Lp(a) and optimize treatment and prevention of cardiovascular disease., Lipoprotein(a) (Lp(a)) is a genetically determined causal risk factor for cardiovascular disease including coronary heart disease, peripheral arterial disease, ischaemic stroke, and calcific aortic valve stenosis. Clinical trials of specific and potent Lp(a)-lowering drugs are currently underway. However, in clinical practice, widespread assessment of Lp(a) is still lacking despite several guideline recommendations to measure Lp(a) at least once in a lifetime in all adults to identify those at high or very high risk due to elevated levels. The present review provides an overview of key findings from observational and genetic Lp(a) studies, highlights the main challenges in observational Lp(a) studies, and proposes a minimum set of requirements to enhance the quality and harmonize the collection of Lp(a)-related data. Adherence to the recommendations set forth in the present manuscript is intended to enhance the quality of future observational Lp(a) studies, to better define thresholds for increased risk, and to better inform clinical trial design. The recommendations can also potentially assist in the interpretation and generalization of clinical trial findings, to improve care of patients with elevated Lp(a) and optimize treatment and prevention of cardiovascular disease.

Published
2024

48. Elevated plasma apolipoprotein E levels in people living with HIV:Associations with biomarkers and HIV-specific risk factors

Author

Reimer Jensen, Anne Marie, Frikke-Schmidt, Ruth, Gelpi, Marco, Knudsen, Andreas D., Benfield, Thomas, Nordestgaard, Børge G., Afzal, Shoaib, Biering-Sørensen, Tor, Nielsen, Susanne Dam, Reimer Jensen, Anne Marie, Frikke-Schmidt, Ruth, Gelpi, Marco, Knudsen, Andreas D., Benfield, Thomas, Nordestgaard, Børge G., Afzal, Shoaib, Biering-Sørensen, Tor, and Nielsen, Susanne Dam

Abstract

Background and aims: Apolipoprotein E (apoE) plays a crucial role in cholesterol metabolism, and high levels of apoE in plasma are associated with cardiovascular disease and all-cause mortality. We aimed to assess if HIV is independently associated with high plasma apoE and to determine HIV-related risk factors for high plasma apoE. Methods: We included 661 people with HIV (PWH) from the Copenhagen Comorbidity in HIV (COCOMO) study with available measurement of plasma apoE. COCOMO participants were frequency matched 1:1 on age and sex with controls from the Copenhagen General Population Study. High plasma apoE was defined as levels above the 90th percentile (66.2 mg/L). The association between HIV and high plasma apoE was assessed using logistic regression models. Among PWH, both linear and logistic regression models were used to determine HIV-specific risk factors for high plasma apoE. Results: Mean age was 52 years and 89 % were male. Median plasma apoE was 49.0 mg/L in PWH and 43.3 mg/L in controls, p < 0.001. HIV was associated with higher plasma apoE after adjusting for potential confounders, including triglycerides (odds ratio 2.14 [95 % CI: 1.39–3.29], p < 0.001). In PWH, higher plasma apoE was associated with a previous AIDS-defining condition in linear models before adjustment for triglycerides and integrase strand transfer inhibitor use in fully adjusted linear models. Conclusions: PWH had higher plasma apoE than controls even after adjusting for triglycerides. Further studies are needed to elucidate the clinical impact of high plasma apoE in PWH.

Published
2024

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

Abstract

Background: Fraction of exhaled nitric oxide with an expiratory flow of 50 mL/s (FENO50) is a biomarker of eosinophilic airway inflammation. Liver transplant recipients have an increased risk of pulmonary infections, but little is known about the burden of chronic pulmonary diseases in this group. We aimed to assess the prevalence of elevated FENO50 in liver transplant recipients and compare it to controls from the general population. Methods: FENO50 was measured in 271 liver transplant recipients from The Danish Comorbidity in Liver Transplant Recipients (DACOLT) study and 1,018 age- and sex-matched controls from The Copenhagen General Population Study (CGPS). Elevated FENO50 was defined as ≥25 or ≥50 parts per billion (ppb). The analyses were adjusted for known and suspected confounders. Results: The median age of the liver transplant recipients was 55 years (interquartile range (IQR) 46–64), and 58% were men. The liver transplant recipients had a higher median FENO50 than the controls [16 ppb (IQR 10–26) vs. 13 ppb (IQR 8–18.), p < 0.001]. Furthermore, the liver transplant recipients had a higher prevalence of elevated FENO50 (for FENO50 ≥25 ppb 27% vs. 11%, p < 0.001 and ≥50 ppb 4% vs. 2%, p = 0.02). The results were similar after adjusting for age, sex, smoking status, use of airway medication, and blood eosinophil counts [the adjusted odds ratio (OR) for FENO50 ≥25 ppb was 3.58 (95% CI: 2.50–5.15, p < 0.0001) and the adjusted OR for FENO50 ≥50 ppb was 3.14 (95% CI: 1.37–7.20, p = 0.007)]. Conclusion: The liver transplant recipients had elevated FENO50, implying increased eosinophilic airway inflammation. The clinical impact of this finding needs further investigation., Background: Fraction of exhaled nitric oxide with an expiratory flow of 50 mL/s (FENO50) is a biomarker of eosinophilic airway inflammation. Liver transplant recipients have an increased risk of pulmonary infections, but little is known about the burden of chronic pulmonary diseases in this group. We aimed to assess the prevalence of elevated FENO50 in liver transplant recipients and compare it to controls from the general population. Methods: FENO50 was measured in 271 liver transplant recipients from The Danish Comorbidity in Liver Transplant Recipients (DACOLT) study and 1,018 age- and sex-matched controls from The Copenhagen General Population Study (CGPS). Elevated FENO50 was defined as ≥25 or ≥50 parts per billion (ppb). The analyses were adjusted for known and suspected confounders. Results: The median age of the liver transplant recipients was 55 years (interquartile range (IQR) 46–64), and 58% were men. The liver transplant recipients had a higher median FENO50 than the controls [16 ppb (IQR 10–26) vs. 13 ppb (IQR 8–18.), p < 0.001]. Furthermore, the liver transplant recipients had a higher prevalence of elevated FENO50 (for FENO50 ≥25 ppb 27% vs. 11%, p < 0.001 and ≥50 ppb 4% vs. 2%, p = 0.02). The results were similar after adjusting for age, sex, smoking status, use of airway medication, and blood eosinophil counts [the adjusted odds ratio (OR) for FENO50 ≥25 ppb was 3.58 (95% CI: 2.50–5.15, p < 0.0001) and the adjusted OR for FENO50 ≥50 ppb was 3.14 (95% CI: 1.37–7.20, p = 0.007)]. Conclusion: The liver transplant recipients had elevated FENO50, implying increased eosinophilic airway inflammation. The clinical impact of this finding needs further investigation.

Published
2024

50. Chronic cough associated with COPD exacerbation, pneumonia and death in the general population

Author

Landt, Eskild M, Çolak, Yunus, Nordestgaard, Børge G, Lange, Peter, Dahl, Morten, Landt, Eskild M, Çolak, Yunus, Nordestgaard, Børge G, Lange, Peter, and Dahl, Morten

Abstract

Background Chronic cough affects up to 10% of the general population and was previously perceived as a comorbidity of underlying conditions, but is nowadays classified as a disease in its own entity that could confer increased risk of morbidity and mortality. We tested the hypothesis that chronic cough is associated with increased risk of COPD exacerbation, pneumonia and all-cause mortality in the general population. Methods We identified 2801 individuals with chronic cough, defined as cough lasting >8 weeks, among 44 756 randomly selected individuals from the Copenhagen General Population Study, and recorded COPD exacerbations, pneumonia and all-cause mortality during follow-up. Results During up to 5.9 years of follow-up (median 3.4 years), 173 individuals experienced COPD exacerbation, 767 experienced pneumonia and 894 individuals died. Individuals with chronic cough versus those without had cumulative incidences at age 80 years of 12% versus 3% for COPD exacerbation, 30% versus 15% for pneumonia, and 25% versus 13% for death from all causes. After adjustment for age, sex and smoking, individuals with chronic cough versus those without had adjusted hazard ratios of 4.6 (95% CI 2.9–7.2) for COPD exacerbation, 2.2 (1.7–2.7) for pneumonia and 1.7 (1.4–2.0) for all-cause mortality. Among current smokers aged >60 years with airflow limitation, those with versus without chronic cough had an absolute 5-year risk of 10% versus 4% for COPD exacerbation, 16% versus 8% for pneumonia and 19% versus 12% for all-cause mortality. Conclusion Chronic cough is associated with higher risks of COPD exacerbation, pneumonia and death, independent of airflow limitation and smoking., BACKGROUND: Chronic cough affects up to 10% of the general population and was previously perceived as a comorbidity of underlying conditions, but is nowadays classified as a disease in its own entity that could confer increased risk of morbidity and mortality. We tested the hypothesis that chronic cough is associated with increased risk of COPD exacerbation, pneumonia and all-cause mortality in the general population.METHODS: We identified 2801 individuals with chronic cough, defined as cough lasting >8 weeks, among 44 756 randomly selected individuals from the Copenhagen General Population Study, and recorded COPD exacerbations, pneumonia and all-cause mortality during follow-up.RESULTS: During up to 5.9 years of follow-up (median 3.4 years), 173 individuals experienced COPD exacerbation, 767 experienced pneumonia and 894 individuals died. Individuals with chronic cough versus those without had cumulative incidences at age 80 years of 12% versus 3% for COPD exacerbation, 30% versus 15% for pneumonia, and 25% versus 13% for death from all causes. After adjustment for age, sex and smoking, individuals with chronic cough versus those without had adjusted hazard ratios of 4.6 (95% CI 2.9-7.2) for COPD exacerbation, 2.2 (1.7-2.7) for pneumonia and 1.7 (1.4-2.0) for all-cause mortality. Among current smokers aged >60 years with airflow limitation, those with versus without chronic cough had an absolute 5-year risk of 10% versus 4% for COPD exacerbation, 16% versus 8% for pneumonia and 19% versus 12% for all-cause mortality.CONCLUSION: Chronic cough is associated with higher risks of COPD exacerbation, pneumonia and death, independent of airflow limitation and smoking.

Published
2024

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