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77 results on '"Furlotte, Nicholas A."'

1. Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction

Author

Schormair, Barbara, Zhao, Chen, Bell, Steven, Didriksen, Maria, Nawaz, Muhammad S., Schandra, Nathalie, Stefani, Ambra, Högl, Birgit, Dauvilliers, Yves, Bachmann, Cornelius G., Kemlink, David, Sonka, Karel, Paulus, Walter, Trenkwalder, Claudia, Oertel, Wolfgang H., Hornyak, Magdolna, Teder-Laving, Maris, Metspalu, Andres, Hadjigeorgiou, Georgios M., Polo, Olli, Fietze, Ingo, Ross, Owen A., Wszolek, Zbigniew K., Ibrahim, Abubaker, Bergmann, Melanie, Kittke, Volker, Harrer, Philip, Dowsett, Joseph, Chenini, Sofiene, Ostrowski, Sisse Rye, Sørensen, Erik, Erikstrup, Christian, Pedersen, Ole B., Topholm Bruun, Mie, Nielsen, Kaspar R., Butterworth, Adam S., Soranzo, Nicole, Ouwehand, Willem H., Roberts, David J., Danesh, John, Burchell, Brendan, Furlotte, Nicholas A., Nandakumar, Priyanka, Earley, Christopher J., Ondo, William G., Xiong, Lan, Desautels, Alex, Perola, Markus, Vodicka, Pavel, Dina, Christian, Stoll, Monika, Franke, Andre, Lieb, Wolfgang, Stewart, Alexandre F. R., Shah, Svati H., Gieger, Christian, Peters, Annette, Rye, David B., Rouleau, Guy A., Berger, Klaus, Stefansson, Hreinn, Ullum, Henrik, Stefansson, Kari, Hinds, David A., Di Angelantonio, Emanuele, Oexle, Konrad, and Winkelmann, Juliane

Published
2024
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3. Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

Author

Bakker, Mark K., Kanning, Jos P., Abraham, Gad, Martinsen, Amy E., Winsvold, Bendik S., Zwart, John-Anker, Bourcier, Romain, Sawada, Tomonobu, Koido, Masaru, Kamatani, Yoichiro, Morel, Sandrine, Amouyel, Philippe, Debette, Stéphanie, Bijlenga, Philippe, Berrandou, Takiy, Ganesh, Santhi K., Bouatia-Naji, Nabila, Jones, Gregory, Bown, Matthew, Rinkel, Gabriel J.E., Veldink, Jan H., Ruigrok, Ynte M., Hege Aamodt, Anne, Heidi Skogholt, Anne, Brumpton, Ben M, Willer, Cristen J, Sandset, Else C, Kristoffersen, Espen S, Ellekjær, Hanne, Heuch, Ingrid, Nielsen, Jonas B, Hagen, Knut, Hveem, Kristian, Fritsche, Lars G, Thomas, Laurent F, Pedersen, Linda M, Gabrielsen, Maiken E, Holmen, Oddgeir L, Børte, Sigrid, Zhou, Wei, Abboud, Shérine, Pandolfo, Massimo, Thijs, Vincent, Leys, Didier, Bodenant, Marie, Louillet, Fabien, Touzé, Emmanuel, Mas, Jean-Louis, Samson, Yves, Leder, Sara, Léger, Anne, Deltour, Sandrine, Crozier, Sophie, Méresse, Isabelle, Canaple, Sandrine, Godefroy, Olivier, Giroud, Maurice, Béjot, Yannick, Decavel, Pierre, Medeiros, Elizabeth, Montiel, Paola, Moulin, Thierry, Vuillier, Fabrice, Dallongeville, Jean, Metso, Antti J, Metso, Tiina, Tatlisumak, Turgut, Grond-Ginsbach, Caspar, Lichy, Christoph, Kloss, Manja, Werner, Inge, Arnold, Marie-Luise, Dos Santos, Michael, Grau, Armin, Dichgans, Martin, Thomas-Feles, Constanze, Weber, Ralf, Brandt, Tobias, Pezzini, Alessandro, De Giuli, Valeria, Caria, Filomena, Poli, Loris, Padovani, Alessandro, Bersano, Anna, Lanfranconi, Silvia, Beretta, Simone, Ferrarese, Carlo, Giacolone, Giacomo, Paolucci, Stefano, Lyrer, Philippe, Engelter, Stefan, Fluri, Felix, Hatz, Florian, Gisler, Dominique, Bonati, Leo, Gensicke, Henrik, Amort, Margareth, Markus, Hugh, Majersik, Jennifer, Worrall, Bradford, Southerland, Andrew, Cole, John, Kittner, Steven, Evangelou, Evangelos, Warren, Helen R, Gao, He, Ntritsos, Georgios, Dimou, Niki, Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G, Jackson, Anne U, Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian’an, Mangino, Massimo, Oldmeadow, Christopher, Peter Prins, Bram, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M, Zhao, Jing-Hua, Connell, John, de Mutsert, Renée, Doney, Alex SF, Farrall, Martin, Menni, Cristina, Morris, Andrew D, Noordam, Raymond, Paré, Guillaume, Poulter, Neil R, Shields, Denis C, Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E, Ayers, Kristin L, Barbieri, Caterina M, Batini, Chiara, Bis, Joshua C, Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I, Bottinger, Erwin P, Braund, Peter S, Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C, Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J, Davies, Gail, de Borst, Martin H, de Geus, Eco J, Deary, Ian J, Deelen, Joris, Del Greco M, Fabiola, Yusuf Demirkale, Cumhur, Dörr, Marcus, Ehret, Georg B, Elosua, Roberto, Enroth, Stefan, Mesut Erzurumluoglu, A, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J, Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B, Harris, Sarah E, Hartman, Catharina A, Havulinna, Aki S, Hicks, Andrew A, Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D, Joshi, Peter K, Jousilahti, Pekka, Wouter Jukema, J, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D, Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S, Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J, Lehne, Benjamin, Lehtimäki, Terho, Liewald, David CM, Lin, Li, Lind, Lars, Lindgren, Cecilia M, Liu, YongMei, Loos, Ruth JF, Lopez, Lorna M, Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P, Morrison, Alanna C, Munson, Peter J, Nalls, Mike A, Nandakumar, Priyanka, Nelson, Christopher P, Niiranen, Teemu, Nolte, Ilja M, Nutile, Teresa, Oldehinkel, Albertine J, Oostra, Ben A, O’Reilly, Paul F, Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, WJH Penninx, Brenda, Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P, Tri Nguyen, Quang, Raitakari, Olli T, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M, Ried, Janina S, Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M, Rotter, Jerome I, Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F, Salomaa, Veikko, Samani, Nilesh J, Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V, Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M, Stott, David J, Strachan, David P, Strawbridge, Rona J, Sundström, Johan, Swertz, Morris A, Taylor, Kent D, Teumer, Alexander, Tobin, Martin D, Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G, Vaez, Ahmad, van der Most, Peter J, van Duijn, Cornelia M, Verwoert, Germaine C, Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H, Willemsen, Gonneke, Wilson, James F, Wright, Alan F, Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R, Butterworth, Adam S, Chasman, Daniel I, Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna MM, Laakso, Markku, Lakatta, Edward G, Langenberg, Claudia, Melander, Olle, Mook-Kanamori, Dennis O, Palmer, Colin NA, Risch, Lorenz, Scott, Robert A, Scott, Rodney J, Sever, Peter, Spector, Tim D, van der Harst, Pim, Wareham, Nicholas J, Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B, Newton-Cheh, Christopher, Brown, Morris J, Metspalu, Andres, Psaty, Bruce M., Wain, Louise V, Elliott, Paul, Caulfield, Mark J, Gormley, Padhraig, Anttila, Verneri, Palta, Priit, Esko, Tonu, Pers, Tune H, Farh, Kai-How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A, Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M, Kallela, Mikko, Freilinger, Tobias M, Ran, Caroline, Gordon, Scott G, Stam, Anine H, Steinberg, Stacy, Borck, Guntram, Koiranen, Markku, Quaye, Lydia, Adams, Hieab H H, Lehtimäki, Terho, Sarin, Antti-Pekka, Wedenoja, Juho, Hinds, David A, Buring, Julie E, Schürks, Markus, Ridker, Paul M, Gudlaug Hrafnsdottir, Maria, Stefansson, Hreinn, Ring, Susan M, Hottenga, Jouke-Jan, Penninx, Brenda W J H, Färkkilä, Markus, Artto, Ville, Kaunisto, Mari, Vepsäläinen, Salli, Malik, Rainer, Heath, Andrew C, Madden, Pamela A F, Martin, Nicholas G, Montgomery, Grant W, Kurki, Mitja I, Kals, Mart, Mägi, Reedik, Pärn, Kalle, Hämäläinen, Eija, Huang, Hailiang, Byrnes, Andrea E, Franke, Lude, Huang, Jie, Stergiakouli, Evie, Lee, Phil H, Sandor, Cynthia, Webber, Caleb, Cader, Zameel, Muller-Myhsok, Bertram, Schreiber, Stefan, Meitinger, Thomas, Eriksson, Johan G, Salomaa, Veikko, Heikkilä, Kauko, Loehrer, Elizabeth, Uitterlinden, Andre G, Hofman, Albert, van Duijn, Cornelia M, Cherkas, Lynn, Pedersen, Linda M, Stubhaug, Audun, Nielsen, Christopher S, Männikkö, Minna, Mihailov, Evelin, Milani, Lili, Göbel, Hartmut, Esserlind, Ann-Louise, Francke Christensen, Anne, Folkmann Hansen, Thomas, Werge, Thomas, Kaprio, Jaakko, Aromaa, Arpo J, Raitakari, Olli, Arfan Ikram, M, Spector, Tim, Järvelin, Marjo-Riitta, Metspalu, Andres, Kubisch, Christian, Strachan, David P, Ferrari, Michel D, Belin, Andrea C, Dichgans, Martin, Wessman, Maija, van den Maagdenberg, Arn M J M, Boomsma, Dorret I, Davey Smith, George, Stefansson, Kari, Eriksson, Nicholas, Daly, Mark J, Neale, Benjamin M, Olesen, Jes, Chasman, Daniel I, Nyholt, Dale R, Palotie, Aarno, Akiyama, Masato, Alg, Varinder S., Børte, Sigrid, Broderick, Joseph P., Brumpton, Ben M., Dauvillier, Jérôme, Desal, Hubert, Dina, Christian, Friedrich, Christoph M., Gaál-Paavola, Emília I., Gentric, Jean-Christophe, Hirsch, Sven, Hostettler, Isabel C., Houlden, Henry, Hveem, Kristian, Jääskeläinen, Juha E., Johnsen, Marianne Bakke, Li, Liming, Lin, Kuang, Lindgren, Antti, Martin, Olivier, Matsuda, Koichi, Millwood, Iona Y., Naggara, Olivier, Niemelä, Mika, Pera, Joanna, Redon, Richard, Rouleau, Guy A., Sandvei, Marie Søfteland, Schilling, Sabine, Shotar, Eimad, Slowik, Agnieszka, Terao, Chikashi, Verschuren, W. M. Monique, Walters, Robin G., Werring, David J., Willer, Cristen J., Woo, Daniel, Worrall, Bradford B., and Zhou, Sirui

Published
2023
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5. Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Author

Adarmes-Gómez, Astrid D, Aguilar, Miquel, Aitkulova, Akbota, Akhmetzhanov, Vadim, Alcalay, Roy N, Alvarez, Ignacio, Alvarez, Victoria, Bandres-Ciga, Sara, Barrero, Francisco Javier, Bergareche Yarza, Jesús Alberto, Bernal-Bernal, Inmaculada, Billingsley, Kimberley, Blauwendraat, Cornelis, Blazquez, Marta, Bonilla-Toribio, Marta, Botía, Juan A, Boungiorno, María Teresa, Bras, Jose, Brice, Alexis, Brockmann, Kathrin, Bubb, Vivien, Buiza-Rueda, Dolores, Cámara, Ana, Carrillo, Fátima, Carrión-Claro, Mario, Cerdan, Debora, Chelban, Viorica, Clarimón, Jordi, Clarke, Carl, Compta, Yaroslau, Cookson, Mark R, Corvol, Jean-Christophe, Craig, David W, Danjou, Fabrice, Diez-Fairen, Monica, Dols-Icardo, Oriol, Duarte, Jacinto, Duran, Raquel, Escamilla-Sevilla, Francisco, Escott-Price, Valentina, Ezquerra, Mario, Faghri, Faraz, Feliz, Cici, Fernández, Manel, Fernández-Santiago, Rubén, Finkbeiner, Steven, Foltynie, Thomas, Gan-Or, Ziv, Garcia, Ciara, García-Ruiz, Pedro, Gasser, Thomas, Gibbs, J Raphael, Gomez Heredia, Maria Jose, Gómez-Garre, Pilar, González, Manuel Menéndez, Gonzalez-Aramburu, Isabel, Guelfi, Sebastian, Guerreiro, Rita, Hardy, John, Hassin-Baer, Sharon, Hernandez, Dena G, Heutink, Peter, Hoenicka, Janet, Holmans, Peter, Houlden, Henry, Infante, Jon, Iwaki, Hirotaka, Jesús, Silvia, Jimenez-Escrig, Adriano, Kaishybayeva, Gulnaz, Kaiyrzhanov, Rauan, Karimova, Altynay, Kia, Demis A, Kinghorn, Kerri J, Koks, Sulev, Krohn, Lynne, Kulisevsky, Jaime, Labrador-Espinosa, Miguel A, Leonard, Hampton L, Lesage, Suzanne, Lewis, Patrick, Lopez-Sendon, Jose Luis, Lovering, Ruth, Lubbe, Steven, Lungu, Codrin, Macias, Daniel, Majamaa, Kari, Manzoni, Claudia, Marín, Juan, Marinus, Johan, Marti, Maria Jose, Martinez, Maria, Martínez Torres, Irene, Martínez-Castrillo, Juan Carlos, Mata, Marina, Mencacci, Niccolo E, Méndez-del-Barrio, Carlota, Middlehurst, Ben, Mínguez, Adolfo, Mir, Pablo, Mok, Kin Y, Morris, Huw R, Muñoz, Esteban, Nalls, Mike A, Narendra, Derek, Noyce, Alastair J, Ojo, Oluwadamilola O, Okubadejo, Njideka U, Pagola, Ana Gorostidi, Pastor, Pau, Perez Errazquin, Francisco, Periñán-Tocino, Teresa, Pihlstrom, Lasse, Plun-Favreau, Helene, Quinn, John, R'Bibo, Lea, Reed, Xylena, Rezola, Elisabet Mondragon, Rizig, Mie, Rizzu, Patrizia, Robak, Laurie, Rodriguez, Antonio Sanchez, Rouleau, Guy A, Ruiz-Martínez, Javier, Ruz, Clara, Ryten, Mina, Sadykova, Dinara, Scholz, Sonja W, Schreglmann, Sebastian, Schulte, Claudia, Sharma, Manu, Shashkin, Chingiz, Shulman, Joshua M, Sierra, María, Siitonen, Ari, Simón-Sánchez, Javier, Singleton, Andrew B, Suarez-Sanmartin, Esther, Taba, Pille, Tabernero, Cesar, Tan, Manuela X, Tartari, Juan Pablo, Tejera-Parrado, Cristina, Toft, Mathias, Tolosa, Eduard, Trabzuni, Daniah, Valldeoriola, Francesc, van Hilten, Jacobus J, Van Keuren-Jensen, Kendall, Vargas-González, Laura, Vela, Lydia, Vives, Francisco, Williams, Nigel, Wood, Nicholas W, Zharkinbekova, Nazira, Zharmukhanov, Zharkyn, Zholdybayeva, Elena, Zimprich, Alexander, Ylikotila, Pauli, Shulman, Lisa M., von Coelln, Rainer, Reich, Stephen, Savitt, Joseph, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Huber, Karen E., Hicks, Barry, Jewett, Ethan M., Jiang, Yunxuan, Kleinman, Aaron, Lin, Keng-Han, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., McManus, Kimberly F., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Poznik, G. David, Sathirapongsasuti, J. Fah, Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce, Vacic, Vladimir, Wang, Xin, Wilson, Catherine H., Anderson, Tim, Bentley, Steven, Dalrymple-Alford, John, Fowdar, Javed, Gratten, Jacob, Halliday, Glenda, Henders, Anjali K., Hickie, Ian, Kassam, Irfahan, Kennedy, Martin, Kwok, John, Lewis, Simon, Mellick, George, Montgomery, Grant, Pearson, John, Pitcher, Toni, Sidorenko, Julia, Silburn, Peter A., Vallerga, Costanza L., Visscher, Peter M., Wallace, Leanne, Wray, Naomi R., Xue, Angli, Yang, Jian, Zhang, Futao, Vallerga, Costanza L, Heilbron, Karl, Chang, Diana, Tan, Manuela, Young, Emily, Pihlstrøm, Lasse, Leonard, Hampton, Botia, Juan A, Jankovic, Joseph, Shulman, Lisa M, Sutherland, Margaret, Tienari, Pentti, Andreassen, Ole A, Bangale, Tushar, Hinds, David A, Hardy, John A, Visscher, Peter M, and Graham, Robert R

Published
2019
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6. Association of Whole-Genome and NETRIN1 Signaling Pathway–Derived Polygenic Risk Scores for Major Depressive Disorder and White Matter Microstructure in the UK Biobank

Author

Wray, Naomi R., Ripke, Stephan, Mattheisen, Manuel, Trzaskowski, Maciej, Byrne, Enda M., Abdellaoui, Abdel, Adams, Mark J., Agerbo, Esben, Air, Tracy M., Andlauer, Till F.M., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan T.F., Bigdeli, Tim B., Binder, Elisabeth B., Blackwood, Douglas H.R., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan R.I., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Escott-Price, Valentina, Hassan Kiadeh, Farnush Farhadi, Finucane, Hilary K., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Goes, Fernando S., Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Ising, Marcus, Jansen, Rick, Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kutalik, Zoltán, Li, Yihan, Lind, Penelope A., MacIntyre, Donald J., MacKinnon, Dean F., Maier, Robert M., Maier, Wolfgang, Marchini, Jonathan, Mbarek, Hamdi, McGrath, Patrick, McGuffin, Peter, Medland, Sarah E., Mehta, Divya, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mondimore, Francis M., Montgomery, Grant W., Mostafavi, Sara, Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nivard, Michel G., Nyholt, Dale R., O'Reilly, Paul F., Oskarsson, Hogni, Owen, Michael J., Painter, Jodie N., Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pistis, Giorgio, Posthuma, Danielle, Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Mirza, Saira Saeed, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant C.B., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Trubetskoy, Vassily, Uitterlinden, André G., Umbricht, Daniel, Van der Auwera, Sandra, van Hemert, Albert M., Viktorin, Alexander, Visscher, Peter M., Wang, Yunpeng, Webb, Bradley T., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Yang, Jian, Zhang, Futao, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E.J.C., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., McIntosh, Andrew M., Metspalu, Andres, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Paciga, Sara A., Pedersen, Nancy L., Penninx, Brenda W.J.H., Perlis, Roy H., Porteous, David J., Potash, James B., Preisig, Martin, Rietschel, Marcella, Schaefer, Catherine, Schulze, Thomas G., Smoller, Jordan W., Stefansson, Kari, Tiemeier, Henning, Uher, Rudolf, Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Sathirapongsasuti, J. Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, Wilson, Catherine H., Barbu, Miruna C., Zeng, Yanni, Shen, Xueyi, Cox, Simon R., Gibson, Jude, Johnstone, Mandy, Haley, Chris S., Lawrie, Stephen M., and Whalley, Heather C.

Published
2019
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7. Replication and characterization of CADM2 and MSRA genes on human behavior

Author

Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., Hromatka, Bethann S., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McIntyre, Matthew H., Mountain, Joanna L., Northover, Carrie A.M., Sathirapongsasuti, J.Fah, Sazonova, Olga V., Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce Y., Vacic, Vladimir, Wilson, Catherine H., Boutwell, Brian, Hinds, David, Tielbeek, Jorim, Ong, Ken K., Day, Felix R., and Perry, John R.B.

Published
2017
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8. Genome-wide association meta-analysis highlights light-induced signaling as a driver for refractive error

Author

Tedja, Milly S., Wojciechowski, Robert, Hysi, Pirro G., Eriksson, Nicholas, Furlotte, Nicholas A., Verhoeven, Virginie J. M., Iglesias, Adriana I., Meester-Smoor, Magda A., Tompson, Stuart W., Fan, Qiao, Khawaja, Anthony P., Cheng, Ching-Yu, Höhn, René, Yamashiro, Kenji, Wenocur, Adam, Grazal, Clare, Haller, Toomas, Metspalu, Andres, Wedenoja, Juho, Jonas, Jost B., Wang, Ya Xing, Xie, Jing, Mitchell, Paul, Foster, Paul J., Klein, Barbara E. K., Klein, Ronald, Paterson, Andrew D., Hosseini, S. Mohsen, Shah, Rupal L., Williams, Cathy, Teo, Yik Ying, Tham, Yih Chung, Gupta, Preeti, Zhao, Wanting, Shi, Yuan, Saw, Woei-Yuh, Tai, E-Shyong, Sim, Xue Ling, Huffman, Jennifer E., Polašek, Ozren, Hayward, Caroline, Bencic, Goran, Rudan, Igor, Wilson, James F., The CREAM Consortium, 23andMe Research Team, UK Biobank Eye and Vision Consortium, Joshi, Peter K., Tsujikawa, Akitaka, Matsuda, Fumihiko, Whisenhunt, Kristina N., Zeller, Tanja, van der Spek, Peter J., Haak, Roxanna, Meijers-Heijboer, Hanne, van Leeuwen, Elisabeth M., Iyengar, Sudha K., Lass, Jonathan H., Hofman, Albert, Rivadeneira, Fernando, Uitterlinden, André G., Vingerling, Johannes R., Lehtimäki, Terho, Raitakari, Olli T., Biino, Ginevra, Concas, Maria Pina, Schwantes-An, Tae-Hwi, Igo, Jr, Robert P., Cuellar-Partida, Gabriel, Martin, Nicholas G., Craig, Jamie E., Gharahkhani, Puya, Williams, Katie M., Nag, Abhishek, Rahi, Jugnoo S., Cumberland, Phillippa M., Delcourt, Cécile, Bellenguez, Céline, Ried, Janina S., Bergen, Arthur A., Meitinger, Thomas, Gieger, Christian, Wong, Tien Yin, Hewitt, Alex W., Mackey, David A., Simpson, Claire L., Pfeiffer, Norbert, Pärssinen, Olavi, Baird, Paul N., Vitart, Veronique, Amin, Najaf, van Duijn, Cornelia M., Bailey-Wilson, Joan E., Young, Terri L., Saw, Seang-Mei, Stambolian, Dwight, MacGregor, Stuart, Guggenheim, Jeremy A., Tung, Joyce Y., Hammond, Christopher J., and Klaver, Caroline C. W.

Published
2018
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9. Genome-wide association meta-analysis of individuals of European ancestry identifies new loci explaining a substantial fraction of hair color variation and heritability

Author

Hysi, Pirro G., Valdes, Ana M., Liu, Fan, Furlotte, Nicholas A., Evans, David M., Bataille, Veronique, Visconti, Alessia, Hemani, Gibran, McMahon, George, Ring, Susan M., Smith, George Davey, Duffy, David L., Zhu, Gu, Gordon, Scott D., Medland, Sarah E., Lin, Bochao D., Willemsen, Gonneke, Jan Hottenga, Jouke, Vuckovic, Dragana, Girotto, Giorgia, Gandin, Ilaria, Sala, Cinzia, Concas, Maria Pina, Brumat, Marco, Gasparini, Paolo, Toniolo, Daniela, Cocca, Massimiliano, Robino, Antonietta, Yazar, Seyhan, Hewitt, Alex W., Chen, Yan, Zeng, Changqing, Uitterlinden, Andre G., Ikram, M. Arfan, Hamer, Merel A., van Duijn, Cornelia M., Nijsten, Tamar, Mackey, David A., Falchi, Mario, Boomsma, Dorret I., Martin, Nicholas G., The International Visible Trait Genetics Consortium, Hinds, David A., Kayser, Manfred, and Spector, Timothy D.

Published
2018
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12. Migraine, inflammatory bowel disease and celiac disease: A Mendelian randomization study.

Author

Welander, Nike Zoe, Rukh, Gull, Rask‐Andersen, Mathias, Harder, Aster V. E., Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai‐How, Cuenca‐Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, Terwindt, Gisela M., and Kallela, Mikko

Subjects
CROHN'S disease, ULCERATIVE colitis, INFLAMMATORY bowel diseases, SCIENTIFIC observation, CONFIDENCE intervals, MIGRAINE, CELIAC disease, RISK assessment, GENOME-wide association studies, ODDS ratio
Abstract

Objective: To assess whether migraine may be genetically and/or causally associated with inflammatory bowel disease (IBD) or celiac disease. Background: Migraine has been linked to IBD and celiac disease in observational studies, but whether this link may be explained by a shared genetic basis or could be causal has not been established. The presence of a causal association could be clinically relevant, as treating one of these medical conditions might mitigate the symptoms of a causally linked condition. Methods: Linkage disequilibrium score regression and two‐sample bidirectional Mendelian randomization analyses were performed using summary statistics from cohort‐based genome‐wide association studies of migraine (59,674 cases; 316,078 controls), IBD (25,042 cases; 34,915 controls) and celiac disease (11,812 or 4533 cases; 11,837 or 10,750 controls). Migraine with and without aura were analyzed separately, as were the two IBD subtypes Crohn's disease and ulcerative colitis. Positive control analyses and conventional Mendelian randomization sensitivity analyses were performed. Results: Migraine was not genetically correlated with IBD or celiac disease. No evidence was observed for IBD (odds ratio [OR] 1.00, 95% confidence interval [CI] 0.99–1.02, p = 0.703) or celiac disease (OR 1.00, 95% CI 0.99–1.02, p = 0.912) causing migraine or migraine causing either IBD (OR 1.08, 95% CI 0.96–1.22, p = 0.181) or celiac disease (OR 1.08, 95% CI 0.79–1.48, p = 0.614) when all participants with migraine were analyzed jointly. There was some indication of a causal association between celiac disease and migraine with aura (OR 1.04, 95% CI 1.00–1.08, p = 0.045), between celiac disease and migraine without aura (OR 0.95, 95% CI 0.92–0.99, p = 0.006), as well as between migraine without aura and ulcerative colitis (OR 1.15, 95% CI 1.02–1.29, p = 0.025). However, the results were not significant after multiple testing correction. Conclusions: We found no evidence of a shared genetic basis or of a causal association between migraine and either IBD or celiac disease, although we obtained some indications of causal associations with migraine subtypes. [ABSTRACT FROM AUTHOR]

Published
2023
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14. Genome-wide association study identifies 74 loci associated with educational attainment

Author

Okbay, Aysu, Beauchamp, Jonathan P., Fontana, Mark Alan, Lee, James J., Pers, Tune H., Rietveld, Cornelius A., Turley, Patrick, Chen, Guo-Bo, Emilsson, Valur, Meddens, S. Fleur W., Oskarsson, Sven, Pickrell, Joseph K., Thom, Kevin, Timshel, Pascal, de Vlaming, Ronald, Abdellaoui, Abdel, Ahluwalia, Tarunveer S., Bacelis, Jonas, Baumbach, Clemens, Bjornsdottir, Gyda, Brandsma, Johannes H., Pina Concas, Maria, Derringer, Jaime, Furlotte, Nicholas A., Galesloot, Tessel E., Girotto, Giorgia, Gupta, Richa, Hall, Leanne M., Harris, Sarah E., Hofer, Edith, Horikoshi, Momoko, Huffman, Jennifer E., Kaasik, Kadri, Kalafati, Ioanna P., Karlsson, Robert, Kong, Augustine, Lahti, Jari, Lee, Sven J. van der, deLeeuw, Christiaan, Lind, Penelope A., Lindgren, Karl-Oskar, Liu, Tian, Mangino, Massimo, Marten, Jonathan, Mihailov, Evelin, Miller, Michael B., van der Most, Peter J., Oldmeadow, Christopher, Payton, Antony, Pervjakova, Natalia, Peyrot, Wouter J., Qian, Yong, Raitakari, Olli, Rueedi, Rico, Salvi, Erika, Schmidt, Börge, Schraut, Katharina E., Shi, Jianxin, Smith, Albert V., Poot, Raymond A., St Pourcain, Beate, Teumer, Alexander, Thorleifsson, Gudmar, Verweij, Niek, Vuckovic, Dragana, Wellmann, Juergen, Westra, Harm-Jan, Yang, Jingyun, Zhao, Wei, Zhu, Zhihong, Alizadeh, Behrooz Z., Amin, Najaf, Bakshi, Andrew, Baumeister, Sebastian E., Biino, Ginevra, Bønnelykke, Klaus, Boyle, Patricia A., Campbell, Harry, Cappuccio, Francesco P., Davies, Gail, De Neve, Jan-Emmanuel, Deloukas, Panos, Demuth, Ilja, Ding, Jun, Eibich, Peter, Eisele, Lewin, Eklund, Niina, Evans, David M., Faul, Jessica D., Feitosa, Mary F., Forstner, Andreas J., Gandin, Ilaria, Gunnarsson, Bjarni, Halldórsson, Bjarni V., Harris, Tamara B., Heath, Andrew C., Hocking, Lynne J., Holliday, Elizabeth G., Homuth, Georg, Horan, Michael A., Hottenga, Jouke-Jan, de Jager, Philip L., Joshi, Peter K., Jugessur, Astanand, Kaakinen, Marika A., Kähönen, Mika, Kanoni, Stavroula, Keltigangas-Järvinen, Liisa, Kiemeney, Lambertus A. L. M., Kolcic, Ivana, Koskinen, Seppo, Kraja, Aldi T., Kroh, Martin, Kutalik, Zoltan, Latvala, Antti, Launer, Lenore J., Lebreton, Maël P., Levinson, Douglas F., Lichtenstein, Paul, Lichtner, Peter, Liewald, David C. M., Cohort Study, LifeLines, Loukola, Anu, Madden, Pamela A., Mägi, Reedik, Mäki-Opas, Tomi, Marioni, Riccardo E., Marques-Vidal, Pedro, Meddens, Gerardus A., McMahon, George, Meisinger, Christa, Meitinger, Thomas, Milaneschi, Yusplitri, Milani, Lili, Montgomery, Grant W., Myhre, Ronny, Nelson, Christopher P., Nyholt, Dale R., Ollier, William E. R., Palotie, Aarno, Paternoster, Lavinia, Pedersen, Nancy L., Petrovic, Katja E., Porteous, David J., Räikkönen, Katri, Ring, Susan M., Robino, Antonietta, Rostapshova, Olga, Rudan, Igor, Rustichini, Aldo, Salomaa, Veikko, Sanders, Alan R., Sarin, Antti-Pekka, Schmidt, Helena, Scott, Rodney J., Smith, Blair H., Smith, Jennifer A., Staessen, Jan A., Steinhagen-Thiessen, Elisabeth, Strauch, Konstantin, Terracciano, Antonio, Tobin, Martin D., Ulivi, Sheila, Vaccargiu, Simona, Quaye, Lydia, van Rooij, Frank J. A., Venturini, Cristina, Vinkhuyzen, Anna A. E., Völker, Uwe, Völzke, Henry, Vonk, Judith M., Vozzi, Diego, Waage, Johannes, Ware, Erin B., Willemsen, Gonneke, Attia, John R., Bennett, David A., Berger, Klaus, Bertram, Lars, Bisgaard, Hans, Boomsma, Dorret I., Borecki, Ingrid B., Bültmann, Ute, Chabris, Christopher F., Cucca, Francesco, Cusi, Daniele, Deary, Ian J., Dedoussis, George V., van Duijn, Cornelia M., Eriksson, Johan G., Franke, Barbara, Franke, Lude, Gasparini, Paolo, Gejman, Pablo V., Gieger, Christian, Grabe, Hans-Jörgen, Gratten, Jacob, Groenen, Patrick J. F., Gudnason, Vilmundur, van der Harst, Pim, Hayward, Caroline, Hinds, David A., Hoffmann, Wolfgang, Hyppönen, Elina, Iacono, William G., Jacobsson, Bo, Järvelin, Marjo-Riitta, Jöckel, Karl-Heinz, Kaprio, Jaakko, Kardia, Sharon L. R., Lehtimäki, Terho, Lehrer, Steven F., Magnusson, Patrik K. E., Martin, Nicholas G., McGue, Matt, Metspalu, Andres, Pendleton, Neil, Penninx, Brenda W. J. H., Perola, Markus, Pirastu, Nicola, Pirastu, Mario, Polasek, Ozren, Posthuma, Danielle, Power, Christine, Province, Michael A., Samani, Nilesh J., Schlessinger, David, Schmidt, Reinhold, Sørensen, Thorkild I. A., Spector, Tim D., Stefansson, Kari, Thorsteinsdottir, Unnur, Thurik, A. Roy, Timpson, Nicholas J., Tiemeier, Henning, Tung, Joyce Y., Uitterlinden, André G., Vitart, Veronique, Vollenweider, Peter, Weir, David R., Wilson, James F., Wright, Alan F., Conley, Dalton C., Krueger, Robert F., Davey Smith, George, Hofman, Albert, Laibson, David I., Medland, Sarah E., Meyer, Michelle N., Yang, Jian, Johannesson, Magnus, Visscher, Peter M., Esko, Tõnu, Koellinger, Philipp D., Cesarini, David, and Benjamin, Daniel J.

Published
2016
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15. Genome-wide association study of musical beat synchronization demonstrates high polygenicity.

Author

Niarchou, Maria, Gustavson, Daniel E., Sathirapongsasuti, J. Fah, Anglada-Tort, Manuel, Eising, Else, Bell, Eamonn, McArthur, Evonne, Straub, Peter, 23andMe Research Team, Aslibekyan, Stella, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Clark, Sarah K., Elson, Sarah L., Fletez-Brant, Kipper, Fontanillas, Pierre, Furlotte, Nicholas A., Gandhi, Pooja M., and Heilbron, Karl

Published
2022
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16. The genetic architecture of pneumonia susceptibility implicates mucin biology and a relationship with psychiatric illness.

Author

Reay, William R., Geaghan, Michael P., 23andMe Research Team, Agee, Michelle, Alipanahi, Babak, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hicks, Barry, Hinds, David A., Huber, Karen E., Jewett, Ethan M., Jiang, Yunxuan, Kleinman, Aaron, Lin, Keng-Han, Litterman, Nadia K., McCreight, Jey C., and McIntyre, Matthew H.

Subjects
MUCINS, PNEUMONIA, MAJOR histocompatibility complex, BIOLOGY, DRUG repositioning, TUMOR necrosis factors
Abstract

Pneumonia remains one of the leading causes of death worldwide. In this study, we use genome-wide meta-analysis of lifetime pneumonia diagnosis (N = 391,044) to identify four association signals outside of the previously implicated major histocompatibility complex region. Integrative analyses and finemapping of these signals support clinically tractable targets, including the mucin MUC5AC and tumour necrosis factor receptor superfamily member TNFRSF1A. Moreover, we demonstrate widespread evidence of genetic overlap with pneumonia susceptibility across the human phenome, including particularly significant correlations with psychiatric phenotypes that remain significant after testing differing phenotype definitions for pneumonia or genetically conditioning on smoking behaviour. Finally, we show how polygenic risk could be utilised for precision treatment formulation or drug repurposing through pneumonia risk scores constructed using variants mapped to pathways with known drug targets. In summary, we provide insights into the genetic architecture of pneumonia susceptibility and genetics informed targets for drug development or repositioning. Susceptibility to pneumonia has a genetic component, but specific genes involved remain poorly understood. In this study, genetic signals associated with pneumonia susceptibility are identified, providing information about disease biology and potential targets for treatment. [ABSTRACT FROM AUTHOR]

Published
2022
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17. Genome-wide association analysis and replication in 810,625 individuals with varicose veins.

Author

Ahmed, Waheed-Ul-Rahman, Kleeman, Sam, Ng, Michael, Wang, Wei, Auton, Adam, 23andMe Research Team, Agee, Michelle, Aslibekyan, Stella, Bell, Robert K., Bryc, Katarzyna, Clark, Sarah K., Elson, Sarah L., Fletez-Brant, Kipper, Fontanillas, Pierre, Furlotte, Nicholas A., Gandhi, Pooja M., Heilbron, Karl, Hicks, Barry, Hinds, David A., and Huber, Karen E.

Subjects
VARICOSE veins, GENOME-wide association studies, GENE targeting, DISEASE risk factors, VASCULAR smooth muscle, COMPRESSION stockings
Abstract

Varicose veins affect one-third of Western society, with a significant subset of patients developing venous ulceration, costing $14.9 billion annually in the USA. Current management consists of either compression stockings, or surgical ablation for more advanced disease. Most varicose veins patients report a positive family history, and heritability is ~17%. We describe the largest two-stage genome-wide association study of varicose veins in 401,656 individuals from UK Biobank, and replication in 408,969 individuals from 23andMe (total 135,514 cases and 675,111 controls). Forty-nine signals at 46 susceptibility loci were discovered. We map 237 genes to these loci, several of which are biologically plausible and tractable to therapeutic targeting. Pathway analysis identified enrichment in extracellular matrix biology, inflammation, (lymph)angiogenesis, vascular smooth muscle cell migration, and apoptosis. Using a polygenic risk score (PRS) derived in an independent cohort, we demonstrate its predictive utility and correlation with varicose veins surgery. Although varicose veins are a common condition, the genetic basis is not well understood. Here, the authors find genetic variants associated with varicose veins and show that a higher polygenic risk score for varicose veins correlates with a greater likelihood of patients undergoing surgical treatment. [ABSTRACT FROM AUTHOR]

Published
2022
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18. Mouse genomic variation and its effect on phenotypes and gene regulation

Author

Keane, Thomas M., Goodstadt, Leo, Danecek, Petr, White, Michael A., Wong, Kim, Yalcin, Binnaz, Heger, Andreas, Agam, Avigail, Slater, Guy, Goodson, Martin, Furlotte, Nicholas A., Eskin, Eleazar, Nellåker, Christoffer, Whitley, Helen, Cleak, James, Janowitz, Deborah, Hernandez-Pliego, Polinka, Edwards, Andrew, Belgard, Grant T., Oliver, Peter L., McIntyre, Rebecca E., Bhomra, Amarjit, Nicod, Jérôme, Gan, Xiangchao, Yuan, Wei, van der Weyden, Louise, Steward, Charles A., Bala, Sendu, Stalker, Jim, Mott, Richard, Durbin, Richard, Jackson, Ian J., Czechanski, Anne, Guerra-Assunção, José Afonso, Donahue, Leah Rae, Reinholdt, Laura G., Payseur, Bret A., Ponting, Chris P., Birney, Ewan, Flint, Jonathan, and Adams, David J.

Published
2011
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21. Resource profile and user guide of the Polygenic Index Repository.

Author

Becker, Joel, Burik, Casper A. P., Goldman, Grant, Wang, Nancy, Jayashankar, Hariharan, Bennett, Michael, Belsky, Daniel W., Karlsson Linnér, Richard, Ahlskog, Rafael, Kleinman, Aaron, Hinds, David A., 23andMe Research Group, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, and Furlotte, Nicholas A.

Published
2021
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23. Distinct clinical phenotypes for Crohn's disease derived from patient surveys.

Author

Liu, Tianyun, Han, Lichy, Tilley, Mera, Afzelius, Lovisa, Maciejewski, Mateusz, Jelinsky, Scott, Tian, Chao, McIntyre, Matthew, the 23andMe Research Team, Agee, Michelle, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., Huber, Karen E., Kleinman, Aaron, and Litterman, Nadia K.

Subjects
CROHN'S disease, INFLAMMATORY bowel diseases, PATIENT surveys, CATEGORIES (Mathematics), PHENOTYPES
Abstract

Background: Defining clinical phenotypes provides opportunities for new diagnostics and may provide insights into early intervention and disease prevention. There is increasing evidence that patient-derived health data may contain information that complements traditional methods of clinical phenotyping. The utility of these data for defining meaningful phenotypic groups is of great interest because social media and online resources make it possible to query large cohorts of patients with health conditions.Methods: We evaluated the degree to which patient-reported categorical data is useful for discovering subclinical phenotypes and evaluated its utility for discovering new measures of disease severity, treatment response and genetic architecture. Specifically, we examined the responses of 1961 patients with inflammatory bowel disease to questionnaires in search of sub-phenotypes. We applied machine learning methods to identify novel subtypes of Crohn's disease and studied their associations with drug responses.Results: Using the patients' self-reported information, we identified two subpopulations of Crohn's disease; these subpopulations differ in disease severity, associations with smoking, and genetic transmission patterns. We also identified distinct features of drug response for the two Crohn's disease subtypes. These subtypes show a trend towards differential genotype signatures.Conclusion: Our findings suggest that patient-defined data can have unplanned utility for defining disease subtypes and may be useful for guiding treatment approaches. [ABSTRACT FROM AUTHOR]

Published
2021
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24. Genetic determinants of daytime napping and effects on cardiometabolic health.

Author

Dashti, Hassan S., Daghlas, Iyas, Lane, Jacqueline M., Huang, Yunru, Udler, Miriam S., Wang, Heming, Ollila, Hanna M., Jones, Samuel E., Kim, Jaegil, Wood, Andrew R., 23andMe Research Team, Agee, Michelle, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Clark, Sarah K., Elson, Sarah L., Fletez-Brant, Kipper, Fontanillas, Pierre, and Furlotte, Nicholas A.

Subjects
GENES, HYPERTENSION, WAIST circumference, CLUSTER analysis (Statistics), SLEEP disorders
Abstract

Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference. The genetic basis of daytime napping and the directional effect of daytime napping on cardiometabolic health are unknown. Here, the authors perform a genome-wide association study on self-reported daytime napping in the UK Biobank and Mendelian randomization to explore causal associations. [ABSTRACT FROM AUTHOR]

Published
2021
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25. Disease risk scores for skin cancers.

Author

Fontanillas, Pierre, Alipanahi, Babak, Furlotte, Nicholas A., Johnson, Michaela, Wilson, Catherine H., 23andMe Research Team, Agee, Michelle, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Hinds, David A., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A. M., and Sathirapongsasuti, J. Fah

Subjects
SKIN cancer, BASAL cell carcinoma, SQUAMOUS cell carcinoma
Abstract

We trained and validated risk prediction models for the three major types of skin cancer— basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma—on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure. We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors. Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile. To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA. Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer. High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer. Predicting who will develop skin cancer is difficult. Here, the authors from 23andMe developed a polygenic risk score for skin cancer based on a questionnaire and genetic data from more than 210,000 individuals and suggest that the score could be used in early screening programmes. [ABSTRACT FROM AUTHOR]

Published
2021
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26. Habitual sleep disturbances and migraine: a Mendelian randomization study.

Author

Daghlas, Iyas, Vgontzas, Angeliki, Guo, Yanjun, Chasman, Daniel I., Saxena, Richa, Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai‐How, Cuenca‐Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, and Terwindt, Gisela M.

Subjects
MIGRAINE, SLEEP, GENETIC correlations, SYMPTOMS, GENETIC testing
Abstract

Objective: Sleep disturbances are associated with increased risk of migraine, however the extent of shared underlying biology and the direction of causal relationships between these traits is unclear. Delineating causality between sleep patterns and migraine may offer new pathophysiologic insights and inform subsequent intervention studies. Here, we used genetic approaches to test for shared genetic influences between sleep patterns and migraine, and to test whether habitual sleep patterns may be causal risk factors for migraine and vice versa. Methods: To quantify genetic overlap, we performed genome‐wide genetic correlation analyses using genome‐wide association studies of nine sleep traits in the UK Biobank (n ≥ 237,627), and migraine from the International Headache Genetics Consortium (59,674 cases and 316,078 controls). We then tested for potential causal effects between sleep traits and migraine using bidirectional, two‐sample Mendelian randomization. Results: Seven sleep traits demonstrated genetic overlap with migraine, including insomnia symptoms (rg = 0.29, P < 10−31) and difficulty awakening (rg = 0.11, P < 10−4). Mendelian randomization analyses provided evidence for potential causal effects of difficulty awakening on risk of migraine (OR [95% CI] = 1.37 [1.12–1.68], P = 0.002), and nominal evidence that liability to insomnia symptoms increased the risk of migraine (1.09 [1.02–1.16], P = 0.02). In contrast, there was minimal evidence for an effect of migraine liability on sleep patterns or disturbances. Interpretation: These data support a shared genetic basis between several sleep traits and migraine, and support potential causal effects of difficulty awakening and insomnia symptoms on migraine risk. Treatment of sleep disturbances may therefore be a promising clinical intervention in the management of migraine. [ABSTRACT FROM AUTHOR]

Published
2020
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27. Direct‐to‐consumer genetic testing for factor V Leiden and prothrombin 20210G>A: the consumer experience.

Author

Elson, Sarah L., Furlotte, Nicholas A., Hromatka, Bethann S., Wilson, Catherine H., Mountain, Joanna L., Rowbotham, Helen M., Varga, Elizabeth A., and Francke, Uta

Subjects
*FACTOR V Leiden, *RISK perception, *GENETIC testing, *BLOOD coagulation factor X, *BEHAVIOR, *THROMBOEMBOLISM
Abstract

Background: Clinical genetic testing for inherited predisposition to venous thromboembolism (VTE) is common among patients and their families. However, there is incomplete consensus about which individuals should receive testing, and the relative risks and benefits. Methods: We assessed outcomes of receiving direct‐to‐consumer (DTC) results for the two most common genetic risk factors for VTE, factor V Leiden in the F5 gene (FVL) and prothrombin 20210G>A in the F2 gene (PT). Two thousand three hundred fifty‐four customers (1244 variant‐positive and 1110 variant‐negative individuals) of the personal genetics company 23andMe, Inc., who had received results online for F5 and F2 variants, participated in an online survey‐based study. Participants responded to questions about perception of VTE risk, discussion of results with healthcare providers (HCPs) and recommendations received, actions taken to control risk, emotional responses to receiving risk results, and perceived value of the information. Results: Most participants (90% of variant‐positive individuals, 99% of variant‐negative individuals) had not previously been tested for F5 and/or F2 variants. The majority of variant‐positive individuals correctly perceived that they were at higher than average risk for developing VTE. These individuals reported moderate rates of discussing results with HCPs (41%); receiving prevention advice from HCPs (31%), and making behavioral changes to control risk (e.g., exercising more, 30%). A minority (36%) of variant‐positive individuals worried more after receiving VTE results. Nevertheless, most participants reported that knowing their risk had been an advantage (78% variant‐positive and 58% variant‐negative) and were satisfied knowing their genetic probability for VTE (81% variant‐positive and 67% variant‐negative). Conclusion: Consumers reported moderate rates of behavioral change and perceived personal benefit from receiving DTC genetic results for VTE risk. We assessed the consumer experience receiving direct‐to‐consumer (DTC) genetic risk for venous thromboembolism (VTE). 2354 customers (1244 variant‐positive and 1110 variant‐negative individuals) of the personal genetics company 23andMe, Inc., who had received results online for risk variants in clotting factor genes F2 and F5, participated in an online survey‐based study. Participants responded to questions about perception of VTE risk, discussion of results with healthcare providers and recommendations received, actions taken to control risk, emotional responses to receiving risk results, and perceived value of the information. [ABSTRACT FROM AUTHOR]

Published
2020
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28. A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine.

Author

Guo, Yanjun, Rist, Pamela M., Daghlas, Iyas, Giulianini, Franco, The International Headache Genetics Consortium, Gormley, Padhraig, Anttila, Verneri, Winsvold, Bendik S., Palta, Priit, Esko, Tonu, Pers, Tune H., Farh, Kai-How, Cuenca-Leon, Ester, Muona, Mikko, Furlotte, Nicholas A., Kurth, Tobias, Ingason, Andres, McMahon, George, Ligthart, Lannie, and Terwindt, Gisela M.

Subjects
BLOOD pressure, MIGRAINE, DIASTOLE (Cardiac cycle), META-analysis
Abstract

Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (Ncases/Ncontrols = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, rg = 0.11, P = 3.56 × 10−06) and systolic BP (SBP, rg = 0.06, P = 0.01), but not pulse pressure (PP, rg = −0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P ≤ 5 × 10−08), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15–1.25]/10 mmHg; P = 5.57 × 10−25) on migraine than SBP (1.05 [1.03–1.07]/10 mmHg; P = 2.60 × 10−07) and a corresponding opposite effect for PP (0.92 [0.88–0.95]/10 mmHg; P = 3.65 × 10−07). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine. The association between blood pressure (BP) and migraine is poorly understood. Here, the authors explore this relationship using summary-level GWAS data for BP and migraine. Cross-trait meta-analysis reveals shared loci between BP and migraine, while Mendelian randomization suggests that diastolic BP specifically plays a key role in migraine susceptibility. [ABSTRACT FROM AUTHOR]

Published
2020
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29. Fox Insight collects online, longitudinal patient-reported outcomes and genetic data on Parkinson's disease.

Author

Smolensky, Luba, Amondikar, Ninad, Crawford, Karen, Neu, Scott, Kopil, Catherine M., Daeschler, Margaret, Riley, Lindsey, 23andMe Research Team, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Cannon, Paul, Clarke, Sarah, Elson, Sarah L., Fonseca, Peter, Fontanillas, Pierre, Furlotte, Nicholas A., and Hicks, Barry

Subjects
PARKINSON'S disease & genetics, HISTORY of medicine, GERIATRIC Depression Scale, ACQUISITION of data, QUESTIONNAIRES
Abstract

Fox Insight is an online, longitudinal health study of people with and without Parkinson's disease with targeted enrollment set to at least 125,000 individuals. Fox Insight data is a rich data set facilitating discovery, validation, and reproducibility in Parkinson's disease research. The dataset is generated through routine longitudinal assessments (health and medical questionnaires evaluated at regular cycles), one-time questionnaires about environmental exposure and healthcare preferences, and genetic data collection. Qualified Researchers can explore, analyze, and download patient-reported outcomes (PROs) data and Parkinson's disease- related genetic variants at https://foxden.michaeljfox.org. The full Fox Insight genetic data set, including approximately 600,000 single nucleotide polymorphisms (SNPs), can be requested separately with institutional review and are described outside of this data descriptor. Measurement(s) Parkinson's disease • Patient Reported Outcome • SNP Technology Type(s) questionnaire • crowd sourced data generation • single-nucleotide polymorphism analysis Factor Type(s) cohort • data acquisition source • temporal interval • environmental risk factor • mds updrs • geriatric depression scale • medical history • family neurological history • sleep disorder • handedness • demographics • physical activities • caregiver • daily living • LRRK2 • APOE • SNCA • GBA Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11794011 [ABSTRACT FROM AUTHOR]

Published
2020
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30. Overlapping genetic architecture between Parkinson disease and melanoma.

Author

Dube, Umber, Ibanez, Laura, Budde, John P., Benitez, Bruno A., Davis, Albert A., Harari, Oscar, Iles, Mark M., Law, Matthew H., Brown, Kevin M., 23andMe Research Team, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Hinds, David A., and Huber, Karen E.

Subjects
PARKINSON'S disease, MELANOMA, GENETIC correlations, CYCLIN-dependent kinase inhibitor-2A, GENE expression
Abstract

Epidemiologic studies have reported inconsistent results regarding an association between Parkinson disease (PD) and cutaneous melanoma (melanoma). Identifying shared genetic architecture between these diseases can support epidemiologic findings and identify common risk genes and biological pathways. Here, we apply polygenic, linkage disequilibrium-informed methods to the largest available case–control, genome-wide association study summary statistic data for melanoma and PD. We identify positive and significant genetic correlation (correlation: 0.17, 95% CI 0.10–0.24; P = 4.09 × 10−06) between melanoma and PD. We further demonstrate melanoma and PD-inferred gene expression to overlap across tissues (correlation: 0.14, 95% CI 0.06 to 0.22; P = 7.87 × 10−04) and highlight seven genes including PIEZO1, TRAPPC2L, and SOX6 as potential mediators of the genetic correlation between melanoma and PD. These findings demonstrate specific, shared genetic architecture between PD and melanoma that manifests at the level of gene expression. [ABSTRACT FROM AUTHOR]

Published
2020
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31. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways.

Author

Howard, David M., Adams, Mark J., Shirali, Masoud, Clarke, Toni-Kim, Marioni, Riccardo E., Davies, Gail, Coleman, Jonathan R. I., Alloza, Clara, Shen, Xueyi, Barbu, Miruna C., Wigmore, Eleanor M., Gibson, Jude, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, and Furlotte, Nicholas A.

Abstract

Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated (P < 5 × 10−8) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression.The UK Biobank provides data for three depression-related phenotypes. Here, Howard et al. perform a genome-association study for broad depression, probable major depressive disorder (MDD) and hospital record-coded MDD in up to 322,580 UK Biobank participants which highlights excitatory synaptic pathways. [ABSTRACT FROM AUTHOR]

Published
2018
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33. Efficient Multiple-Trait Association and Estimation of Genetic Correlation Using the Matrix-Variate Linear Mixed Model.

Author

Furlotte, Nicholas A. and Eskin, Eleazar

Subjects
*GENETIC correlations, *GENETICS, *HERITABILITY, *MULTIVARIATE analysis, *INSECTS
Abstract

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. [ABSTRACT FROM AUTHOR]

Published
2015
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35. Quantifying the uncertainty in heritability.

Author

Furlotte, Nicholas A, Heckerman, David, and Lippert, Christoph

Subjects
*HERITABILITY, *ATHEROSCLEROSIS risk factors, *SINGLE nucleotide polymorphisms, *MAXIMUM likelihood statistics, *BAYESIAN analysis, *SAMPLE size (Statistics)
Abstract

The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large. [ABSTRACT FROM AUTHOR]

Published
2014
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36. Meta-Analysis Identifies Gene-by-Environment Interactions as Demonstrated in a Study of 4,965 Mice.

Author

Kang, Eun Yong, Han, Buhm, Furlotte, Nicholas, Joo, Jong Wha J., Shih, Diana, Davis, Richard C., Lusis, Aldons J., and Eskin, Eleazar

Subjects
GENOTYPE-environment interaction, META-analysis, PHYSIOLOGICAL effects of cholesterol, LABORATORY mice, HIGH density lipoproteins
Abstract

Identifying environmentally-specific genetic effects is a key challenge in understanding the structure of complex traits. Model organisms play a crucial role in the identification of such gene-by-environment interactions, as a result of the unique ability to observe genetically similar individuals across multiple distinct environments. Many model organism studies examine the same traits but under varying environmental conditions. For example, knock-out or diet-controlled studies are often used to examine cholesterol in mice. These studies, when examined in aggregate, provide an opportunity to identify genomic loci exhibiting environmentally-dependent effects. However, the straightforward application of traditional methodologies to aggregate separate studies suffers from several problems. First, environmental conditions are often variable and do not fit the standard univariate model for interactions. Additionally, applying a multivariate model results in increased degrees of freedom and low statistical power. In this paper, we jointly analyze multiple studies with varying environmental conditions using a meta-analytic approach based on a random effects model to identify loci involved in gene-by-environment interactions. Our approach is motivated by the observation that methods for discovering gene-by-environment interactions are closely related to random effects models for meta-analysis. We show that interactions can be interpreted as heterogeneity and can be detected without utilizing the traditional uni- or multi-variate approaches for discovery of gene-by-environment interactions. We apply our new method to combine 17 mouse studies containing in aggregate 4,965 distinct animals. We identify 26 significant loci involved in High-density lipoprotein (HDL) cholesterol, many of which are consistent with previous findings. Several of these loci show significant evidence of involvement in gene-by-environment interactions. An additional advantage of our meta-analysis approach is that our combined study has significantly higher power and improved resolution compared to any single study thus explaining the large number of loci discovered in the combined study. [ABSTRACT FROM AUTHOR]

Published
2014
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37. Genetic variants associated with subjective well-being, depressive symptoms and neuroticism identified through genome-wide analyses

Author

Okbay, Aysu, Baselmans, Bart M.L., De Neve, Jan-Emmanuel, Turley, Patrick, Nivard, Michel G., Fontana, Mark Alan, Meddens, S. Fleur W., Linnér, Richard Karlsson, Rietveld, Cornelius A., Derringer, Jaime, Gratten, Jacob, Lee, James J., Liu, Jimmy Z., de Vlaming, Ronald, Ahluwalia, Tarunveer S., Buchwald, Jadwiga, Cavadino, Alana, Frazier-Wood, Alexis C., Furlotte, Nicholas A., Garfield, Victoria, Geisel, Marie Henrike, Gonzalez, Juan R., Haitjema, Saskia, Karlsson, Robert, van der Laan, Sander W., Ladwig, Karl-Heinz, Lahti, Jari, van der Lee, Sven J., Lind, Penelope A., Liu, Tian, Matteson, Lindsay, Mihailov, Evelin, Miller, Michael B., Minica, Camelia C., Nolte, Ilja M., Mook-Kanamori, Dennis, van der Most, Peter J., Oldmeadow, Christopher, Qian, Yong, Raitakari, Olli, Rawal, Rajesh, Realo, Anu, Rueedi, Rico, Schmidt, Börge, Smith, Albert V., Stergiakouli, Evie, Tanaka, Toshiko, Taylor, Kent, Wedenoja, Juho, Wellmann, Juergen, Westra, Harm-Jan, Willems, Sara M., Zhao, Wei, Amin, Najaf, Bakshi, Andrew, Boyle, Patricia A., Cherney, Samantha, Cox, Simon R., Davies, Gail, Davis, Oliver S.P., Ding, Jun, Direk, Nese, Eibich, Peter, Emeny, Rebecca T., Fatemifar, Ghazaleh, Faul, Jessica D., Ferrucci, Luigi, Forstner, Andreas, Gieger, Christian, Gupta, Richa, Harris, Tamara B., Harris, Juliette M., Holliday, Elizabeth G., Hottenga, Jouke-Jan, De Jager, Philip L., Kaakinen, Marika A., Kajantie, Eero, Karhunen, Ville, Kolcic, Ivana, Kumari, Meena, Launer, Lenore J., Franke, Lude, Li-Gao, Ruifang, Koini, Marisa, Loukola, Anu, Marques-Vidal, Pedro, Montgomery, Grant W., Mosing, Miriam A., Paternoster, Lavinia, Pattie, Alison, Petrovic, Katja E., Pulkki-Råback, Laura, Quaye, Lydia, Räikkönen, Katri, Rudan, Igor, Scott, Rodney J., Smith, Jennifer A., Sutin, Angelina R., Trzaskowski, Maciej, Vinkhuyzen, Anna E., Yu, Lei, Zabaneh, Delilah, Attia, John R., Bennett, David A., Berger, Klaus, Bertram, Lars, Boomsma, Dorret I., Snieder, Harold, Chang, Shun-Chiao, Cucca, Francesco, Deary, Ian J., van Duijn, Cornelia M., Eriksson, Johan G., Bültmann, Ute, de Geus, Eco J.C., Groenen, Patrick J.F., Gudnason, Vilmundur, Hansen, Torben, Hartman, Catharine A., Haworth, Claire M.A., Hayward, Caroline, Heath, Andrew C., Hinds, David A., Hyppönen, Elina, Iacono, William G., Järvelin, Marjo-Riitta, Jöckel, Karl-Heinz, Kaprio, Jaakko, Kardia, Sharon L.R., Keltikangas-Järvinen, Liisa, Kraft, Peter, Kubzansky, Laura D., Lehtimäki, Terho, Magnusson, Patrik K.E., Martin, Nicholas G., McGue, Matt, Metspalu, Andres, Mills, Melinda, de Mutsert, Renée, Oldehinkel, Albertine J., Pasterkamp, Gerard, Pedersen, Nancy L., Plomin, Robert, Polasek, Ozren, Power, Christine, Rich, Stephen S., Rosendaal, Frits R., den Ruijter, Hester M., Schlessinger, David, Schmidt, Helena, Svento, Rauli, Schmidt, Reinhold, Alizadeh, Behrooz Z., Sørensen, Thorkild I.A., Spector, Tim D., Steptoe, Andrew, Terracciano, Antonio, Thurik, A. Roy, Timpson, Nicholas J., Tiemeier, Henning, Uitterlinden, André G., Vollenweider, Peter, Wagner, Gert G., Weir, David R., Yang, Jian, Conley, Dalton C., Smith, George Davey, Hofman, Albert, Johannesson, Magnus, Laibson, David I., Medland, Sarah E., Meyer, Michelle N., Pickrell, Joseph K., Esko, Tõnu, Krueger, Robert F., Beauchamp, Jonathan P., Koellinger, Philipp D., Benjamin, Daniel J., Bartels, Meike, and Cesarini, David

Abstract

We conducted genome-wide association studies of three phenotypes: subjective well-being (N = 298,420), depressive symptoms (N = 161,460), and neuroticism (N = 170,910). We identified three variants associated with subjective well-being, two with depressive symptoms, and eleven with neuroticism, including two inversion polymorphisms. The two depressive symptoms loci replicate in an independent depression sample. Joint analyses that exploit the high genetic correlations between the phenotypes (|ρ̂| ≈ 0.8) strengthen the overall credibility of the findings, and allow us to identify additional variants. Across our phenotypes, loci regulating expression in central nervous system and adrenal/pancreas tissues are strongly enriched for association.

Published
2016
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39. Comparative Analysis of Proteome and Transcriptome Variation in Mouse.

Author

Ghazalpour, Anatole, Bennett, Brian, Petyuk, Vladislav A., Orozco, Luz, Hagopian, Raffi, Mungrue, Imran N., Farber, Charles R., Sinsheimer, Janet, Kang, Hyun M., Furlotte, Nicholas, Park, Christopher C., Ping-Zi Wen, Brewer, Heather, Weitz, Karl, Camp II, David G., Pan, Calvin, Yordanova, Roumyana, Neuhaus, Isaac, Tilford, Charles, and Siemers, Nathan

Subjects
BIOLOGICAL variation, PROTEOMICS, COMPARATIVE studies, GENETIC code, LIQUID chromatography, RADIOLABELING, STATISTICAL correlation
Abstract

The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels and protein levels among inbred strains of mice. We quantified over 5,000 peptides and over 22,000 transcripts in livers of 97 inbred and recombinant inbred strains and focused on the 7,185 most heritable transcripts and 486 most reliable proteins. The transcript levels were quantified by microarray analysis in three replicates and the proteins were quantified by Liquid Chromatography-Mass Spectrometry using O(18)-reference-based isotope labeling approach. We show that the levels of transcripts and proteins correlate significantly for only about half of the genes tested, with an average correlation of 0.27, and the correlations of transcripts and proteins varied depending on the cellular location and biological function of the gene. We examined technical and biological factors that could contribute to the modest correlation. For example, differential splicing clearly affects the analyses for certain genes; but, based on deep sequencing, this does not substantially contribute to the overall estimate of the correlation. We also employed genome-wide association analyses to map loci controlling both transcript and protein levels. Surprisingly, little overlap was observed between the protein- and transcript- mapped loci. We have typed numerous clinically relevant traits among the strains, including adiposity, lipoprotein levels, and tissue parameters. Using correlation analysis, we found that a low number of clinical trait relationships are preserved between the protein and mRNA gene products and that the majority of such relationships are specific to either the protein levels or transcript levels. Surprisingly, transcript levels were more strongly correlated with clinical traits than protein levels. In light of the widespread use of high-throughput technologies in both clinical and basic research, the results presented have practical as well as basic implications. [ABSTRACT FROM AUTHOR]

Published
2011
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40. Functional Cohesion of Gene Sets Determined by Latent Semantic Indexing of PubMed Abstracts.

Author

Lijing Xu, Furlotte, Nicholas, Yunyue Lin, Heinrich, Kevin, Berry, Michael W., George, Ebenezer O., and Homayouni, Ramin

Subjects
*LATENT semantic analysis, *INFORMATION retrieval, *DATA mining, *DNA microarrays, *MICROARRAY technology, *ANALYSIS of variance, *REAL-time computing
Abstract

High-throughput genomic technologies enable researchers to identify genes that are co-regulated with respect to specific experimental conditions. Numerous statistical approaches have been developed to identify differentially expressed genes. Because each approach can produce distinct gene sets, it is difficult for biologists to determine which statistical approach yields biologically relevant gene sets and is appropriate for their study. To address this issue, we implemented Latent Semantic Indexing (LSI) to determine the functional coherence of gene sets. An LSI model was built using over 1 million Medline abstracts for over 20,000 mouse and human genes annotated in Entrez Gene. The gene-to-gene LSI-derived similarities were used to calculate a literature cohesion p-value (LPv) for a given gene set using a Fisher's exact test. We tested this method against genes in more than 6,000 functional pathways annotated in Gene Ontology (GO) and found that approximately 75% of gene sets in GO biological process category and 90% of the gene sets in GO molecular function and cellular component categories were functionally cohesive (LPv,0.05). These results indicate that the LPv methodology is both robust and accurate. Application of this method to previously published microarray datasets demonstrated that LPv can be helpful in selecting the appropriate feature extraction methods. To enable real-time calculation of LPv for mouse or human gene sets, we developed a web tool called Gene-set Cohesion Analysis Tool (GCAT). GCAT can complement other gene set enrichment approaches by determining the overall functional cohesion of data sets, taking into account both explicit and implicit gene interactions reported in the biomedical literature. [ABSTRACT FROM AUTHOR]

Published
2011
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41. Mouse Genome-Wide Association and Systems Genetics Identify Asxl2 As a Regulator of Bone Mineral Density and Osteoclastogenesis.

Author

Farber, Charles R., Bennett, Brian J., Orozco, Luz, Wei Zou, Lira, Ana, Kostem, Emrah, Hyun Min Kang, Furlotte, Nicholas, Berberyan, Ani, Ghazalpour, Anatole, Suwanwela, Jaijam, Drake, Thomas A., Eskin, Eleazar, Wang, Q. Tian, Teitelbaum, Steven L., and Lusis, Aldons J.

Subjects
BONE density, GENETIC regulation, OSTEOPETROSIS, BONE resorption, BONE cells, LABORATORY mice, GENETICS education
Published
2011
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42. Detection and reconstruction of tandemly organized de novo copy number variations.

Author

Dan He, Furlotte, Nicholas, and Eskin, Eleazar

Subjects
*GENE expression, *GENETICS, *GENOMES, *BIOINFORMATICS, *SOFTWARE sequencers
Abstract

Background: The characterization of structural variations (SV) such as insertions, deletions and copy number variations is a critical step in the process of understanding the full genetic architecture of organisms. Copy number variations (CNV) have attracted much recent attention due to their effects on gene expression and disease status. Results: In this paper, we present a method that utilizes next-generation sequencing technologies (NGS), in order to both detect and reconstruct CNVs. We focus on a special type of CNV, namely tandemly organized de novo CNVs, which have been shown to occur with high frequency in the mouse genome. Conclusions: We apply our method to CNV regions randomly inserted into the reference mouse genome and show that our method achieves good performance for both detection and reconstruction of tandemly organized de novo CNVs. [ABSTRACT FROM AUTHOR]

Published
2010
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43. Biomedical Informatics Unit (BMIU): Slim-Prim System Bridges the Gap Between Laboratory Discovery and Practice.

Author

Viangteeravat, Teeradache, Brooks, Ian M., Ketcherside, W. Joseph, Houmayouni, Ramin, Furlotte, Nicholas, Vuthipadadon, Somchan, and McDonald, Chanchai S.

Subjects
MEDICAL informatics, TRANSLATIONAL research, CLINICAL trials, COMPUTERS, MEDICAL research, HEALTH insurance, UNIVERSITIES & colleges
Abstract

With current national emphasis on translational research, data exchange systems are needed that bridge basic science and clinical research. To meet this challenge, an electronic system was developed by the Biomedical Informatics Unit (BMIU) of the University of Tennessee Clinical Translation Science Institute (UT CTSI). This integrated data system collects, processes, archives, and distributes basic, clinical, and translational research data. The system provides information via web-based applications in a secure and Health Insurance Portability and Accountability Act (HIPAA)-compliant manner to facilitate data sharing and analysis across domains. The system is currently in use by a number of studies and has proven to be an effective tool for data collection and processing in clinical studies. [ABSTRACT FROM AUTHOR]

Published
2009
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44. Identification and Functional Validation of the Novel Antimalarial Resistance Locus PF10_0355 in Plasmodium falciparum

Author

Van Tyne, Daria Natalie, Park, Daniel John, Schaffner, Stephen, Neafsey, Daniel Edward, Angelino, Elaine Lee, Cortese, Joseph F., Barnes, Kayla G., Rosen, David M., Lukens, Amanda Kathleen, Daniels, Rachel Fath, Milner, Danny Arnold, Johnson, Charles A., Shlyakhter, Ilya, Grossman, Sharon Rachel, Becker, Justin S., Yamins, Daniel Louis Kanef, Karlsson, Elinor Kathryn, Ndiaye, Daouda, Sarr, Ousmane, Mboup, Souleymane, Happi, Christian Tientcha, Furlotte, Nicholas A., Eskin, Eleazar, Kang, Hyun Min, Hartl, Daniel L., Birren, Bruce W., Wiegand, Roger C., Lander, Eric Steven, Wirth, Dyann Fergus, Cooke, Sarah Volkman, and Sabeti, Pardis Christine

Subjects
population structure, haplotype structure, positive selection, malaria parasites, drug-resistance, genome sequence, copy number, gene, susceptibility, association
Abstract

The Plasmodium falciparum parasite's ability to adapt to environmental pressures, such as the human immune system and antimalarial drugs, makes malaria an enduring burden to public health. Understanding the genetic basis of these adaptations is critical to intervening successfully against malaria. To that end, we created a high-density genotyping array that assays over 17,000 single nucleotide polymorphisms (~1 SNP/kb), and applied it to 57 culture-adapted parasites from three continents. We characterized genome-wide genetic diversity within and between populations and identified numerous loci with signals of natural selection, suggesting their role in recent adaptation. In addition, we performed a genome-wide association study (GWAS), searching for loci correlated with resistance to thirteen antimalarials; we detected both known and novel resistance loci, including a new halofantrine resistance locus, PF10_0355. Through functional testing we demonstrated that PF10_0355 overexpression decreases sensitivity to halofantrine, mefloquine, and lumefantrine, but not to structurally unrelated antimalarials, and that increased gene copy number mediates resistance. Our GWAS and follow-on functional validation demonstrate the potential of genome-wide studies to elucidate functionally important loci in the malaria parasite genome., Organismic and Evolutionary Biology, Other Research Unit

Published
2011
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45. Genome-wide association studies of antidepressant class response and treatment-resistant depression.

Author

Li, Qingqin S., Tian, Chao, Hinds, David, 23andMe Research Team, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Huber, Karen E., Kleinman, Aaron, Litterman, Nadia K., McIntyre, Matthew H., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A. M., and Pitts, Steven J.

Published
2020
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47. An Association Mapping Framework To Account for Potential Sex Difference in Genetic Architectures.

Author

Eun Yong Kang, Cue Hyunkyu Lee, Furlotte, Nicholas A., Joo, Jong Wha J., Kostem, Emrah, Zaitlen, Noah, Eskin, Eleazar, and Han, Buhm

Subjects
*GENE mapping, *GENETIC polymorphisms, *STATISTICS, *DATA analysis, *EFFECT sizes (Statistics)
Abstract

Over the past few years, genome-wide association studies have identified many trait-associated loci that have different effects on females and males, which increased attention to the genetic architecture differences between the sexes. The between-sex differences in genetic architectures can cause a variety of phenomena such as differences in the effect sizes at trait-associated loci, differences in the magnitudes of polygenic background effects, and differences in the phenotypic variances. However, current association testing approaches for dealing with sex, such as including sex as a covariate, cannot fully account for these phenomena and can be suboptimal in statistical power. We present a novel association mapping framework, MetaSex, that can comprehensively account for the genetic architecture differences between the sexes. Through simulations and applications to real data, we show that our framework has superior performance than previous approaches in association mapping. [ABSTRACT FROM AUTHOR]

Published
2018
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48. Increasing Association Mapping Power and Resolution in Mouse Genetic Studies Through the Use of Meta-Analysis for Structured Populations.

Author

Furlotte, Nicholas A., Eun Yong Kang, Van Nas, Atila, Farber, Charles R., Lusis, Aldons J., and Eskin, Eleazar

Subjects
*GENE mapping, *POPULATION genetics, *META-analysis, *GENOMICS, *MICE genetics, *MICE genome mapping
Abstract

Genetic studies in mouse models have played an integral role in the discovery of the mechanisms underlying many human diseases. The primary mode of discovery has been the application of linkage analysis to mouse crosses. This approach results in high power to identify regions that affect traits, but in low resolution, making it difficult to identify the precise genomic location harboring the causal variant. Recently, a panel of mice referred to as the hybrid mouse diversity panel (HMDP) has been developed to overcome this problem. However, power in this panel is limited by the availability of inbred strains. Previous studies have suggested combining results across multiple panels as a means to increase power, but the methods employed may not be well suited to structured populations, such as the HMDP. In this article, we introduce a meta-analysis-based method that may be used to combine HMDP studies with F2 cross studies to gain power, while increasing resolution. Due to the drastically different genetic structure of F2s and the HMDP, the best way to combine two studies for a given SNP depends on the strain distribution pattern in each study. We show that combining results, while accounting for these patterns, leads to increased power and resolution. Using our method to map bone mineral density, we find that two previously implicated loci are replicated with increased significance and that the size of the associated is decreased. We also map HDL cholesterol and show a dramatic increase in the significance of a previously identified result. [ABSTRACT FROM AUTHOR]

Published
2012
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49. Genome-wide association study in almost 195,000 individuals identifies 50 previously unidentified genetic loci for eye color.

Author

Simcoe, Mark, Valdes, Ana, Fan Liu, Furlotte, Nicholas A., Evans, David M., Hemani, Gibran, Ring, Susan M., Smith, George Davey, Duffy, David L., Gu Zhu, Gordon, Scott D., Medland, Sarah E., Vuckovic, Dragana, Girotto, Giorgia, Sala, Cinzia, Catamo, Eulalia, Concas, Maria Pina, Brumat, Marco, Gasparini, Paolo, and Toniolo, Daniela

Subjects
*EYE color, *HUMAN skin color, *MELANINS
Abstract

The article presents the results of a genome-wide association study for eye color which involved up to 192,986 European participants from ten populations. Topics discussed include evidence for genes involved in melanin pigmentation, associations with genes involved in iris morphology and structure, and eye color as a genetically high complex human trait.

Published
2021
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50. R/qtl2: Software for Mapping Quantitative Trait Loci with High-Dimensional Data and Multiparent Populations.

Author

Broman, Karl W., Gatti, Daniel M., Simecek, Petr, Furlotte, Nicholas A., Prins, Pjotr, Sen, Śaunak, Yandell, Brian S., and Churchill, Gary A.

Abstract

R/qtl2 is an interactive software environment for mapping quantitative trait loci (QTL) in experimental populations. The R/qtl2 software expands the scope of the widely used R/qtl software package to include multiparent populations derived from more than two founder strains, such as the Collaborative Cross and Diversity Outbred mice, heterogeneous stocks, and MAGIC plant populations. R/qtl2 is designed to handle modern high-density genotyping data and high-dimensional molecular phenotypes, including gene expression and proteomics. R/qtl2 includes the ability to perform genome scans using a linear mixed model to account for population structure, and also includes features to impute SNPs based on founder strain genomes and to carry out association mapping. The R/qtl2 software provides all of the basic features needed for QTL mapping, including graphical displays and summary reports, and it can be extended through the creation of add-on packages. R/qtl2, which is free and open source software written in the R and C++ programming languages, comes with a test framework. [ABSTRACT FROM AUTHOR]

Published
2019
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