ARTICLES
45 Article(s)
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Document(s)
Title
Observational studies on smoking and risk of hay fever and asthma have shown inconsistent results. However, observational studies may be biased by confounding and reverse causation. Mendelian randomization uses genetic variants as markers of exposure...
Observational studies on smoking and risk of hay fever and asthma have shown inconsistent results. However, observational studies may be biased by confounding and reverse causation. Mendelian randomization uses genetic variants as markers of exposure...
Observational studies on smoking and risk of hay fever and asthma have shown inconsistent results. However, observational studies may be biased by confounding and reverse causation. Mendelian randomization uses genetic variants as markers of exposure...
Motivation: Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data ...
Motivation: Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data ...
Motivation: Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data ...
Motivation: Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data ...
Motivation: Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data ...
Motivation: Fine mapping is a widely used approach for identifying the causal variant(s) at disease-associated loci. Standard methods (e.g. multiple regression) require individual level genotypes. Recent fine mapping methods using summary-level data ...
Asselbergs, Folkert W.;Guo, Yiran;van Iperen, Erik P. A.;Sivapalaratnam, Suthesh;Tragante, Vinicius;Lanktree, Matthew B.;Lange, Leslie A.;Almoguera, Berta;Appelman, Yolande E.;Barnard, John;Baumert, Jens;Beitelshees, Amber L.;Bhangale, Tushar R.;Chen, Yii-Der Ida;Gaunt, Tom R.;Gong, Yan;Hopewell, Jemma C.;Johnson, Toby;Kleber, Marcus E.;Langaee, Taimour Y.;Li, Mingyao;Li, Yun R.;Liu, Kiang;McDonough, Caitrin W.;Meijs, Matthijs El.;Middelberg, Rita P. S.;Musunuru, Kiran;Nelson, Christopher P.;O'Connell, Jeffery R.;Padmanabhan, Sandosh;Pankow, James S.;Pankratz, Nathan;Rafelt, Suzanne;Rajagopalan, Ramakrishnan;Romaine, Simon P. R.;Schork, Nicholas J.;Shaffer, Jonathan;Shen, Haiqing;Smith, Erin N.;Tischfield, Sam E.;van der Most, Peter J.;van Vliet-Ostaptchouk, Jana V.;Verweij, Niek;Volcik, Kelly A.;Zhang, Li;Bailey, Kent R.;Bailey, Kristian M.;Bauer, Florianne;Boer, Jolanda M. A.;Braund, Peter S.;Burt, Amber;Burton, Paul R.;Buxbaum, Sarah G.;Chen, Wei;Cooper-DeHoff, Rhonda M.;Cupples, L. Adrienne;deJong, Jonas S.;Delles, Christian;Duggan, David;Fornage, Myriam;Furlong, Clement E.;Glazer, Nicole;Gums, John G.;Hastie, Claire;Holmes, Michael V.;Illig, Thomas;Kirkland, Susan A.;Kivimaki, Mika;Klein, Ronald;Klein, Barbara E.;Kooperberg, Charles;Kottke-Marchant, Kandice;Kumari, Meena;LaCroix, Andrea Z.;Mallela, Laya;Murugesan, Gurunathan;Ordovas, Jose;Ouwehand, Willem H.;Post, Wendy S.;Saxena, Richa;Scharnagl, Hubert;Schreiner, Pamela J.;Shah, Tina;Shields, Denis C.;Shimbo, Daichi;Srinivasan, Sathanur R.;Stolk, Ronald P.;Swerdlow, Daniel I.;Taylor, Herman A.;Topo, Eric J.;Toskala, Elina;van Pelt, Joost L.;van Setten, Jessica;Yusuf, Salim;Whittaker, John C.;Zwinderman, A. H.;Anand, Sonia S.;Balmforth, Anthony J.;Berenson, Gerald S.;Bezzina, Connie R.;Boehm, Bernhard O.;Boerwinkle, Eric;Casas, Juan P.;Caulfield, Mark J.;Clarke, Robert;Connell, John M.;Cruickshanks, Karen J.;Davidson, Karina W.;Day, Ian N. M.;de Bakker, Paul I. W.;Doevendans, Pieter A.;Dominiczak, Anna E.;Hall, Alistair S.;Hartman, Catharina A.;Hengstenberg, Christian;Hillege, Hans L.;Hofker, Marten H.;Humphries, Steve E.;Jarvik, Gail P.;Johnson, Julie A.;Kaess, Bernhard M.;Kathiresan, Sekar;Koenig, Wolfgang;Lawlor, Debbie A.;Maerz, Winfried;Melander, Olle;Mitchell, Braxton D.;Montgomery, Grant W.;Munroe, Patricia B.;Murray, Sarah S.;Newhouse, Stephen J.;Onland-Moret, N. Charlotte;Poulter, Neil;Psaty, Bruce;Redline, Susan;Rich, Stephen S.;Rotter, Jerome I.;Schunkert, Heribert;Sever, Peter;Shuldiner, Alan R.;Silverstein, Roy L.;Stanton, Alice;Thorand, Barbara;Trip, Mieke D.;Tsai, Michael Y.;van der Harst, Pim;van der Schoot, Ellen;van der Schouw, Yvonne T.;Verschuren, W. M. Monique;Watkins, Hugh;Wilde, Arthur A. M.;Wolffenbuttel, Bruce H. R.;Whitfield, John B.;Hovingh, G. Kees;Ballantyne, Christie M.;Wijmenga, Cisca;Reilly, Muredach P.;Martin, Nicholas G.;Wilson, James G.;Rader, Daniel J.;Samani, Nilesh J.;Reiner, Alex P.;Hegele, Robert A.;Kastelein, John J. P.;Hingorani, Aroon D.;Talmud, Philippa J.;Hakonarson, Hakon;Elbers, Clara C.;Keating, Brendan J.;Drenos, Fotios;LifeLines Cohort Study
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