Blar i NTNU Open på forfatter "Munafo, Marcus R."

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    • Heavier smoking may lead to a relative increase in waist circumference: Evidence for a causal relationship from a Mendelian randomisation meta-analysis. The CARTA consortium 

      Morris, Richard W.; Taylor, Amy E.; Fluharty, Meg E.; Bjørngaard, Johan Håkon; Åsvold, Bjørn Olav; Gabrielsen, Maiken Elvestad; Campbell, Archie; Marioni, Riccardo; Kumari, Meena; Korhonen, Tellervo; Männistö, Satu; Marques-Vidal, Pedro; Kaakinen, Marika; Cavadino, Alana; Postmus, Iris; Husemoen, Lise Lotte N.; Skaaby, Tea; Ahluwalia, Tarun Veer Singh; Treur, Jorien L.; Willemsen, Gonneke; Dale, Caroline; Wannamethee, S. Goya; Lahti, Jari; Palotie, Aarno; Räikkönen, Katri; McConnachie, Alex; Padmanabhan, Sandosh; Wong, Andrew; Dalgård, Christine; Paternoster, Lavinia; Ben-Shlomo, Yoav; Tyrrell, Jessica; Horwood, John; Fergusson, David M.; Kennedy, Martin A.; Nohr, Ellen A.; Christiansen, Lene; Kyvik, Kirsten Ohm; Kuh, Diana; Watt, Graham; Eriksson, Johan G.; Whincup, Peter H.; Vink, Jacqueline M.; Boomsma, Dorret I.; Smith, George Davey; Lawlor, Debbie; Linneberg, Allan; Ford, Ian; Jukema, J. Wouter; Power, Chris; Hyppönen, Elina; Jarvelin, Marjo-Riitta; Preisig, Martin; Borodulin, Katja; Kaprio, Jaakko; Kivimaki, Mika; Smith, Blair H.; Hayward, Caroline; Romundstad, Pål Richard; Sørensen, Thorkild I.A.; Munafo, Marcus R.; Sattar, Naveed (Journal article; Peer reviewed, 2015)
      Objectives: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity. Design: ...

    • Model-based assessment of replicability for genome-wide association meta-analysis 

      McGuire, Daniel; Jiang, Yu; Liu, Mengzhen; Weissenkampen, J. Dylan; Eckert, Scott; Yang, Lina; Chen, Fang; Liu, MengZhen; Wedow, Robbee; Li, Yue; Brazel, David M.; Datta, Gargi; Davila-Velderrain, Jose; Tian, Chao; Zhan, Xiaowei; Choquet, H. éléne; Docherty, Anna R.; Faul, Jessica D.; Foerster, Johanna R.; Fritsche, Lars; Gabrielsen, Maiken Elvestad; Gordon, Scott D.; Haessler, Jeffrey; Hottenga, Jouke-Jan; Huang, Hongyan; Jang, Seon-Kyeong; Jansen, Philip R.; Ling, Yueh; Ma ̈gi, Reedik; Matoba, Nana; McMahon, George; Mulas, Antonella; Orru, Valeria; Palviainen, Teemu; Pandit, Anita; Reginsson, Gunnar W.; Skogholt, Anne Heidi; Smith, Jennifer A.; Taylor, Amy E.; Turman, Constance; Willemsen, Gonneke; Young, Hannah; Young, Kendra A.; Zajac, Gregory J. M.; Zhao, Wei; Zhou, Wei; Bjornsdottir, Gyda; Boardman, Jason D.; Boehnke, Michael; Boomsma, Dorret I.; Chen, Chu; Cucca, Francesco; Davies, Gareth E.; Eaton, Charles B.; Ehringer, Marissa A.; Esko, Tõnu; Fiorillo, Edoardo; Gillespie, Nathan A.; Gudbjartsson, Daniel F.; Haller, Toomas; Harris, Kathleen Mullan; Heath, Andrew C.; Hewitt, John K.; Hickie, Ian B.; Hokanson, John E.; Hopfer, Christian J.; Hunter, David J.; Iacono, William G.; Johnson, Eric O.; Kamatani, Yoichiro; Kardia, Sharon L. R.; Keller, Matthew C.; Kellis, Manolis; Kooperberg, Charles; Kraft, Peter; Krauter, Kenneth S.; Laakso, Markku; Lind, Penelope A.; Loukola, Anu; Lutz, Sharon M.; Madden, Pamela A. F.; Martin, Nicholas G.; McGue, Matt; McQueen, Matthew B.; Medland, Sarah E.; Metspalu, Andres; Mohlke, Karen L.; Nielsen, Jonas B.; Okada, Yukinori; Peters, Ulrike; Polderman, Tinca J. C.; Posthuma, Danielle; Reiner, Alexander P.; Rice, JP; Rimm, Eric; Rose, Richard J.; Runarsdottir, Valgerdur; Stallings, Michael C.; Stanˇca ́kova, Alena; Stefansson, Hreinn; Thai, Khanh K.; Tindle, Hilary A.; Tyrfingsson, Thorarinn; Wall, Tamara L.; Weir, David R.; Weisner, Constance M; Whitfield, John B.; Winsvold, Bendik K S; Yin, Jie; Zuccolo, Luisa; Bierut, Laura J.; Hveem, Kristian; Lee, James J.; Munafo, Marcus R.; Saccone, Nancy L.; Willer, Cristen J; Cornelis, Marilyn C.; David, Sean P.; Hinds, David; Jorgenson, Eric; Kaprio, Jaakko; Stitzel, Jerry A.; Stefansson, Kari; Thorgeirsson, Thorgeir E.; Abecasis, Goncalo; Liu, Dajiang J.; Vrieze, Scott; Berg, Arthur; Jiang, Bibo; Li, Qunhua (Peer reviewed; Journal article, 2021)
      Genome-wide association meta-analysis (GWAMA) is an effective approach to enlarge sample sizes and empower the discovery of novel associations between genotype and phenotype. Independent replication has been used as a ...