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36 results on '"Marchini, A."'

2. Genetic risk factors for COVID-19 and influenza are largely distinct

Author

Kosmicki, Jack A., Marcketta, Anthony, Sharma, Deepika, Di Gioia, Silvio Alessandro, Batista, Samantha, Yang, Xiao-Man, Tzoneva, Gannie, Martinez, Hector, Sidore, Carlo, Kessler, Michael D., Horowitz, Julie E., Roberts, Genevieve H. L., Justice, Anne E., Banerjee, Nilanjana, Coignet, Marie V., Leader, Joseph B., Park, Danny S., Lanche, Rouel, Maxwell, Evan, Knight, Spencer C., Bai, Xiaodong, Guturu, Harendra, Baltzell, Asher, Girshick, Ahna R., McCurdy, Shannon R., Partha, Raghavendran, Mansfield, Adam J., Turissini, David A., Zhang, Miao, Mbatchou, Joelle, Watanabe, Kyoko, Verma, Anurag, Sirugo, Giorgio, Ritchie, Marylyn D., Salerno, William J., Shuldiner, Alan R., Rader, Daniel J., Mirshahi, Tooraj, Marchini, Jonathan, Overton, John D., Carey, David J., Habegger, Lukas, Reid, Jeffrey G., Economides, Aris, Kyratsous, Christos, Karalis, Katia, Baum, Alina, Cantor, Michael N., Rand, Kristin A., Hong, Eurie L., Ball, Catherine A., Siminovitch, Katherine, Baras, Aris, Abecasis, Goncalo R., and Ferreira, Manuel A. R.

Published
2024
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3. Rare coding variants in CHRNB2 reduce the likelihood of smoking

Author

Rajagopal, Veera M., Watanabe, Kyoko, Mbatchou, Joelle, Ayer, Ariane, Quon, Peter, Sharma, Deepika, Kessler, Michael D., Praveen, Kavita, Gelfman, Sahar, Parikshak, Neelroop, Otto, Jacqueline M., Bao, Suying, Chim, Shek Man, Pavlopoulos, Elias, Avbersek, Andreja, Kapoor, Manav, Chen, Esteban, Jones, Marcus B., Leblanc, Michelle, Emberson, Jonathan, Collins, Rory, Torres, Jason, Morales, Pablo Kuri, Tapia-Conyer, Roberto, Alegre, Jesus, Berumen, Jaime, Shuldiner, Alan R., Balasubramanian, Suganthi, Abecasis, Gonçalo R., Kang, Hyun M., Marchini, Jonathan, Stahl, Eli A., Jorgenson, Eric, Sanchez, Robert, Liedtke, Wolfgang, Anderson, Matthew, Cantor, Michael, Lederer, David, Baras, Aris, and Coppola, Giovanni

Published
2023
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4. Genome-wide analysis provides genetic evidence that ACE2 influences COVID-19 risk and yields risk scores associated with severe disease

Author

Horowitz, Julie E., Kosmicki, Jack A., Damask, Amy, Sharma, Deepika, Roberts, Genevieve H. L., Justice, Anne E., Banerjee, Nilanjana, Coignet, Marie V., Yadav, Ashish, Leader, Joseph B., Marcketta, Anthony, Park, Danny S., Lanche, Rouel, Maxwell, Evan, Knight, Spencer C., Bai, Xiaodong, Guturu, Harendra, Sun, Dylan, Baltzell, Asher, Kury, Fabricio S. P., Backman, Joshua D., Girshick, Ahna R., O’Dushlaine, Colm, McCurdy, Shannon R., Partha, Raghavendran, Mansfield, Adam J., Turissini, David A., Li, Alexander H., Zhang, Miao, Mbatchou, Joelle, Watanabe, Kyoko, Gurski, Lauren, McCarthy, Shane E., Kang, Hyun M., Dobbyn, Lee, Stahl, Eli, Verma, Anurag, Sirugo, Giorgio, Ritchie, Marylyn D., Jones, Marcus, Balasubramanian, Suganthi, Siminovitch, Katherine, Salerno, William J., Shuldiner, Alan R., Rader, Daniel J., Mirshahi, Tooraj, Locke, Adam E., Marchini, Jonathan, Overton, John D., Carey, David J., Habegger, Lukas, Cantor, Michael N., Rand, Kristin A., Hong, Eurie L., Reid, Jeffrey G., Ball, Catherine A., Baras, Aris, Abecasis, Gonçalo R., and Ferreira, Manuel A. R.

Published
2022
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6. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps

Author

Mahajan, Anubha, Taliun, Daniel, Thurner, Matthias, Robertson, Neil R., Torres, Jason M., Rayner, N. William, Payne, Anthony J., Steinthorsdottir, Valgerdur, Scott, Robert A., Grarup, Niels, Cook, James P., Schmidt, Ellen M., Wuttke, Matthias, Sarnowski, Chloé, Mägi, Reedik, Nano, Jana, Gieger, Christian, Trompet, Stella, Lecoeur, Cécile, Preuss, Michael H., Prins, Bram Peter, Guo, Xiuqing, Bielak, Lawrence F., Below, Jennifer E., Bowden, Donald W., Chambers, John Campbell, Kim, Young Jin, Ng, Maggie C. Y., Petty, Lauren E., Sim, Xueling, Zhang, Weihua, Bennett, Amanda J., Bork-Jensen, Jette, Brummett, Chad M., Canouil, Mickaël, Ec kardt, Kai-Uwe, Fischer, Krista, Kardia, Sharon L. R., Kronenberg, Florian, Läll, Kristi, Liu, Ching-Ti, Locke, Adam E., Luan, Jian’an, Ntalla, Ioanna, Nylander, Vibe, Schönherr, Sebastian, Schurmann, Claudia, Yengo, Loïc, Bottinger, Erwin P., Brandslund, Ivan, Christensen, Cramer, Dedoussis, George, Florez, Jose C., Ford, Ian, Franco, Oscar H., Frayling, Timothy M., Giedraitis, Vilmantas, Hackinger, Sophie, Hattersley, Andrew T., Herder, Christian, Ikram, M. Arfan, Ingelsson, Martin, Jørgensen, Marit E., Jørgensen, Torben, Kriebel, Jennifer, Kuusisto, Johanna, Ligthart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Lyssenko, Valeriya, Mamakou, Vasiliki, Meitinger, Thomas, Mohlke, Karen L., Morris, Andrew D., Nadkarni, Girish, Pankow, James S., Peters, Annette, Sattar, Naveed, Stančáková, Alena, Strauch, Konstantin, Taylor, Kent D., Thorand, Barbara, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Tuomilehto, Jaakko, Witte, Daniel R., Dupuis, Josée, Peyser, Patricia A., Zeggini, Eleftheria, Loos, Ruth J. F., Froguel, Philippe, Ingelsson, Erik, Lind, Lars, Groop, Leif, Laakso, Markku, Collins, Francis S., Jukema, J. Wouter, Palmer, Colin N. A., Grallert, Harald, Metspalu, Andres, Dehghan, Abbas, Köttgen, Anna, Abecasis, Goncalo R., Meigs, James B., Rotter, Jerome I., Marchini, Jonathan, Pedersen, Oluf, Hansen, Torben, Langenberg, Claudia, Wareham, Nicholas J., Stefansson, Kari, Gloyn, Anna L., Morris, Andrew P., Boehnke, Michael, and McCarthy, Mark I.

Published
2018
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7. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

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 M. F., Bacanu, Silviu-Alin, Bækvad-Hansen, Marie, Beekman, Aartjan F. T., Bigdeli, Tim B., Binder, Elisabeth B., Blackwood, Douglas R. H., Bryois, Julien, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Cai, Na, Castelao, Enrique, Christensen, Jane Hvarregaard, Clarke, Toni-Kim, Coleman, Jonathan I. R., Colodro-Conde, Lucía, Couvy-Duchesne, Baptiste, Craddock, Nick, Crawford, Gregory E., Crowley, Cheynna A., Dashti, Hassan S., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Derks, Eske M., Direk, Nese, Dolan, Conor V., Dunn, Erin C., Eley, Thalia C., Eriksson, Nicholas, Escott-Price, Valentina, Kiadeh, Farnush Hassan Farhadi, Finucane, Hilary K., Forstner, Andreas J., Frank, Josef, Gaspar, Héléna A., Gill, Michael, Giusti-Rodríguez, Paola, Goes, Fernando S., Gordon, Scott D., Grove, Jakob, Hall, Lynsey S., Hannon, Eilis, Hansen, Christine Søholm, Hansen, Thomas F., Herms, Stefan, Hickie, Ian B., Hoffmann, Per, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Hougaard, David M., Hu, Ming, Hyde, Craig L., Ising, Marcus, Jansen, Rick, Jin, Fulai, Jorgenson, Eric, Knowles, James A., Kohane, Isaac S., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kutalik, Zoltán, Lane, Jacqueline M., Li, Yihan, Li, Yun, Lind, Penelope A., Liu, Xiaoxiao, Lu, Leina, 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, Mill, Jonathan, 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, Purcell, Shaun M., Quiroz, Jorge A., Qvist, Per, Rice, John P., Riley, Brien P., Rivera, Margarita, Saeed Mirza, Saira, Saxena, Richa, Schoevers, Robert, Schulte, Eva C., Shen, Ling, Shi, Jianxin, Shyn, Stanley I., Sigurdsson, Engilbert, Sinnamon, Grant B. C., Smit, Johannes H., Smith, Daniel J., Stefansson, Hreinn, Steinberg, Stacy, Stockmeier, Craig A., Streit, Fabian, Strohmaier, Jana, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Tian, Chao, 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, eQTLGen, 23andMe, Arolt, Volker, Baune, Bernhard T., Berger, Klaus, Boomsma, Dorret I., Cichon, Sven, Dannlowski, Udo, de Geus, E. C. J., DePaulo, J. Raymond, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Grabe, Hans J., Hamilton, Steven P., Hayward, Caroline, Heath, Andrew C., Hinds, David A., Kendler, Kenneth S., Kloiber, Stefan, Lewis, Glyn, Li, Qingqin S., Lucae, Susanne, Madden, Pamela F. A., 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, Winslow, Ashley R., Lewis, Cathryn M., Levinson, Douglas F., Breen, Gerome, Børglum, Anders D., Sullivan, Patrick F., and the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

Published
2018
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8. Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes

Author

Mahajan, Anubha, Wessel, Jennifer, Willems, Sara M., Zhao, Wei, Robertson, Neil R., Chu, Audrey Y., Gan, Wei, Kitajima, Hidetoshi, Taliun, Daniel, Rayner, N. William, Guo, Xiuqing, Lu, Yingchang, Li, Man, Jensen, Richard A., Hu, Yao, Huo, Shaofeng, Lohman, Kurt K., Zhang, Weihua, Cook, James P., Prins, Bram Peter, Flannick, Jason, Grarup, Niels, Trubetskoy, Vassily Vladimirovich, Kravic, Jasmina, Kim, Young Jin, Rybin, Denis V., Yaghootkar, Hanieh, Müller-Nurasyid, Martina, Meidtner, Karina, Li-Gao, Ruifang, Varga, Tibor V., Marten, Jonathan, Li, Jin, Smith, Albert Vernon, An, Ping, Ligthart, Symen, Gustafsson, Stefan, Malerba, Giovanni, Demirkan, Ayse, Tajes, Juan Fernandez, Steinthorsdottir, Valgerdur, Wuttke, Matthias, Lecoeur, Cécile, Preuss, Michael, Bielak, Lawrence F., Graff, Marielisa, Highland, Heather M., Justice, Anne E., Liu, Dajiang J., Marouli, Eirini, Peloso, Gina Marie, Warren, Helen R., Afaq, Saima, Afzal, Shoaib, Ahlqvist, Emma, Almgren, Peter, Amin, Najaf, Bang, Lia B., Bertoni, Alain G., Bombieri, Cristina, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A., Burtt, Noël P., Canouil, Mickaël, Chen, Yii-Der Ida, Cho, Yoon Shin, Christensen, Cramer, Eastwood, Sophie V., Eckardt, Kai-Uwe, Fischer, Krista, Gambaro, Giovanni, Giedraitis, Vilmantas, Grove, Megan L., de Haan, Hugoline G., Hackinger, Sophie, Hai, Yang, Han, Sohee, Tybjærg-Hansen, Anne, Hivert, Marie-France, Isomaa, Bo, Jäger, Susanne, Jørgensen, Marit E., Jørgensen, Torben, Käräjämäki, Annemari, Kim, Bong-Jo, Kim, Sung Soo, Koistinen, Heikki A., Kovacs, Peter, Kriebel, Jennifer, Kronenberg, Florian, Läll, Kristi, Lange, Leslie A., Lee, Jung-Jin, Lehne, Benjamin, Li, Huaixing, Lin, Keng-Hung, Linneberg, Allan, Liu, Ching-Ti, Liu, Jun, Loh, Marie, Mägi, Reedik, Mamakou, Vasiliki, McKean-Cowdin, Roberta, Nadkarni, Girish, Neville, Matt, Nielsen, Sune F., Ntalla, Ioanna, Peyser, Patricia A., Rathmann, Wolfgang, Rice, Kenneth, Rich, Stephen S., Rode, Line, Rolandsson, Olov, Schönherr, Sebastian, Selvin, Elizabeth, Small, Kerrin S., Stančáková, Alena, Surendran, Praveen, Taylor, Kent D., Teslovich, Tanya M., Thorand, Barbara, Thorleifsson, Gudmar, Tin, Adrienne, Tönjes, Anke, Varbo, Anette, Witte, Daniel R., Wood, Andrew R., Yajnik, Pranav, Yao, Jie, Yengo, Loïc, Young, Robin, Amouyel, Philippe, Boeing, Heiner, Boerwinkle, Eric, Bottinger, Erwin P., Chowdhury, Rajiv, Collins, Francis S., Dedoussis, George, Dehghan, Abbas, Deloukas, Panos, Ferrario, Marco M., Ferrières, Jean, Florez, Jose C., Frossard, Philippe, Gudnason, Vilmundur, Harris, Tamara B., Heckbert, Susan R., Howson, Joanna M. M., Ingelsson, Martin, Kathiresan, Sekar, Kee, Frank, Kuusisto, Johanna, Langenberg, Claudia, Launer, Lenore J., Lindgren, Cecilia M., Männistö, Satu, Meitinger, Thomas, Melander, Olle, Mohlke, Karen L., Moitry, Marie, Morris, Andrew D., Murray, Alison D., de Mutsert, Renée, Orho-Melander, Marju, Owen, Katharine R., Perola, Markus, Peters, Annette, Province, Michael A., Rasheed, Asif, Ridker, Paul M., Rivadineira, Fernando, Rosendaal, Frits R., Rosengren, Anders H., Salomaa, Veikko, Sheu, Wayne H.-H., Sladek, Rob, Smith, Blair H., Strauch, Konstantin, Uitterlinden, André G., Varma, Rohit, Willer, Cristen J., Blüher, Matthias, Butterworth, Adam S., Chambers, John Campbell, Chasman, Daniel I., Danesh, John, van Duijn, Cornelia, Dupuis, Josée, Franco, Oscar H., Franks, Paul W., Froguel, Philippe, Grallert, Harald, Groop, Leif, Han, Bok-Ghee, Hansen, Torben, Hattersley, Andrew T., Hayward, Caroline, Ingelsson, Erik, Kardia, Sharon L. R., Karpe, Fredrik, Kooner, Jaspal Singh, Köttgen, Anna, Kuulasmaa, Kari, Laakso, Markku, Lin, Xu, Lind, Lars, Liu, Yongmei, Loos, Ruth J. F., Marchini, Jonathan, Metspalu, Andres, Mook-Kanamori, Dennis, Nordestgaard, Børge G., Palmer, Colin N. A., Pankow, James S., Pedersen, Oluf, Psaty, Bruce M., Rauramaa, Rainer, Sattar, Naveed, Schulze, Matthias B., Soranzo, Nicole, Spector, Timothy D., Stefansson, Kari, Stumvoll, Michael, Thorsteinsdottir, Unnur, Tuomi, Tiinamaija, Tuomilehto, Jaakko, Wareham, Nicholas J., Wilson, James G., Zeggini, Eleftheria, Scott, Robert A., Barroso, Inês, Frayling, Timothy M., Goodarzi, Mark O., Meigs, James B., Boehnke, Michael, Saleheen, Danish, Morris, Andrew P., Rotter, Jerome I., and McCarthy, Mark I.

Published
2018
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9. Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank

Author

Gaynor, Sheila M., Joseph, Tyler, Bai, Xiaodong, Zou, Yuxin, Boutkov, Boris, Maxwell, Evan K., Delaneau, Olivier, Hofmeister, Robin J., Krasheninina, Olga, Balasubramanian, Suganthi, Marcketta, Anthony, Backman, Joshua, Reid, Jeffrey G., Overton, John D., Lotta, Luca A., Marchini, Jonathan, Salerno, William J., Baras, Aris, Abecasis, Goncalo R., and Thornton, Timothy A.

Abstract

Whole-genome sequencing (WGS), whole-exome sequencing (WES) and array genotyping with imputation (IMP) are common strategies for assessing genetic variation and its association with medically relevant phenotypes. To date, there has been no systematic empirical assessment of the yield of these approaches when applied to hundreds of thousands of samples to enable the discovery of complex trait genetic signals. Using data for 100 complex traits from 149,195 individuals in the UK Biobank, we systematically compare the relative yield of these strategies in genetic association studies. We find that WGS and WES combined with arrays and imputation (WES + IMP) have the largest association yield. Although WGS results in an approximately fivefold increase in the total number of assayed variants over WES + IMP, the number of detected signals differed by only 1% for both single-variant and gene-based association analyses. Given that WES + IMP typically results in savings of lab and computational time and resources expended per sample, we evaluate the potential benefits of applying WES + IMP to larger samples. When we extend our WES + IMP analyses to 468,169 UK Biobank individuals, we observe an approximately fourfold increase in association signals with the threefold increase in sample size. We conclude that prioritizing WES + IMP and large sample sizes rather than contemporary short-read WGS alternatives will maximize the number of discoveries in genetic association studies.

Published
2024
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10. Computationally efficient whole-genome regression for quantitative and binary traits

Author

Lukas Habegger, Joshua D. Backman, Gonçalo R. Abecasis, Jack A. Kosmicki, Leland Barnard, Jeffrey S. Reid, Boris Boutkov, Andrey Ziyatdinov, Jonathan Marchini, Christian Benner, Evan Maxwell, Anthony Marcketta, Manuel A. R. Ferreira, Joelle Mbatchou, Aris Baras, Mathew Barber, and Colm O'Dushlaine

Subjects
Genotype, Binary number, Sample (statistics), Biology, computer.software_genre, Logistic regression, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Software, Genetics, Humans, 030304 developmental biology, 0303 health sciences, business.industry, Computational Biology, Reproducibility of Results, Contrast (statistics), Regression analysis, Genomics, Regression, Logistic Models, Phenotype, ComputingMethodologies_PATTERNRECOGNITION, Efficiency, Case-Control Studies, Data mining, business, computer, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Genome-wide association analysis of cohorts with thousands of phenotypes is computationally expensive, particularly when accounting for sample relatedness or population structure. Here we present a novel machine-learning method called REGENIE for fitting a whole-genome regression model for quantitative and binary phenotypes that is substantially faster than alternatives in multi-trait analyses while maintaining statistical efficiency. The method naturally accommodates parallel analysis of multiple phenotypes and requires only local segments of the genotype matrix to be loaded in memory, in contrast to existing alternatives, which must load genome-wide matrices into memory. This results in substantial savings in compute time and memory usage. We introduce a fast, approximate Firth logistic regression test for unbalanced case–control phenotypes. The method is ideally suited to take advantage of distributed computing frameworks. We demonstrate the accuracy and computational benefits of this approach using the UK Biobank dataset with up to 407,746 individuals. REGENIE is a whole-genome regression method based on ridge regression that enables highly parallelized analysis of quantitative and binary traits in biobank-scale data with reduced computational requirements.

Published
2021

11. Rare coding variants in CHRNB2reduce the likelihood of smoking

Author

Rajagopal, Veera M., Watanabe, Kyoko, Mbatchou, Joelle, Ayer, Ariane, Quon, Peter, Sharma, Deepika, Kessler, Michael D., Praveen, Kavita, Gelfman, Sahar, Parikshak, Neelroop, Otto, Jacqueline M., Bao, Suying, Chim, Shek Man, Pavlopoulos, Elias, Avbersek, Andreja, Kapoor, Manav, Chen, Esteban, Jones, Marcus B., Leblanc, Michelle, Emberson, Jonathan, Collins, Rory, Torres, Jason, Morales, Pablo Kuri, Tapia-Conyer, Roberto, Alegre, Jesus, Berumen, Jaime, Shuldiner, Alan R., Balasubramanian, Suganthi, Abecasis, Gonçalo R., Kang, Hyun M., Marchini, Jonathan, Stahl, Eli A., Jorgenson, Eric, Sanchez, Robert, Liedtke, Wolfgang, Anderson, Matthew, Cantor, Michael, Lederer, David, Baras, Aris, and Coppola, Giovanni

Abstract

Human genetic studies of smoking behavior have been thus far largely limited to common variants. Studying rare coding variants has the potential to identify drug targets. We performed an exome-wide association study of smoking phenotypes in up to 749,459 individuals and discovered a protective association in CHRNB2, encoding the β2 subunit of the α4β2 nicotine acetylcholine receptor. Rare predicted loss-of-function and likely deleterious missense variants in CHRNB2in aggregate were associated with a 35% decreased odds for smoking heavily (odds ratio (OR) = 0.65, confidence interval (CI) = 0.56–0.76, P= 1.9 × 10−8). An independent common variant association in the protective direction (rs2072659; OR = 0.96; CI = 0.94–0.98; P= 5.3 × 10−6) was also evident, suggesting an allelic series. Our findings in humans align with decades-old experimental observations in mice that β2 loss abolishes nicotine-mediated neuronal responses and attenuates nicotine self-administration. Our genetic discovery will inspire future drug designs targeting CHRNB2in the brain for the treatment of nicotine addiction.

Published
2023
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12. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression

Author

Jens Treutlein, James B. Potash, Cheynna A. Crowley, Paul F. O'Reilly, Francis M. Mondimore, Nicholas G. Martin, Jodie N. Painter, Qingqin S. Li, Tõnu Esko, Michael Conlon O'Donovan, Markus M. Nöthen, Toni-Kim Clarke, Roseann E. Peterson, Shantel Weinsheimer, Naomi R. Wray, Marie Bækvad-Hansen, Pamela F.A. Madden, Johannes H. Smit, Gonneke Willemsen, Thomas Hansen, Andrew C. Heath, Carsten Horn, Udo Dannlowski, Fulai Jin, Robert A. Schoevers, Jian Yang, Nicholas Eriksson, Marianne Giørtz Pedersen, Patrik K. E. Magnusson, Hans J. Grabe, Michael Gill, Lili Milani, Caroline Hayward, Shaun Purcell, Stanley I. Shyn, Penelope A. Lind, Giorgio Pistis, Michel G. Nivard, Thorgeir E. Thorgeirsson, Abdel Abdellaoui, Andres Metspalu, David J. Porteous, Anders D. Børglum, Christine Søholm Hansen, Scott D. Gordon, Nicholas John Craddock, Susanne Lucae, Douglas Blackwood, Jürgen Wellmann, Till M.F. Andlauer, Wesley K. Thompson, Chao Tian, Rudolf Uher, Nese Direk, Yuri Milaneschi, Paola Giusti-Rodríguez, Rick Jansen, Marcus Ising, Yang Wu, Jesper Krogh, Merete Nordentoft, Jouke-Jan Hottenga, Robert Maier, Ming Hu, Kari Stefansson, Glyn Lewis, Peter McGuffin, Wolfgang Maier, Erin C. Dunn, Bradley T. Webb, Gerome Breen, Henning Teismann, Eric Jorgenson, Jorge A. Quiroz, Brenda W.J.H. Penninx, Jonas Bybjerg-Grauholm, Warren W. Kretzschmar, Dean F. MacKinnon, Craig A. Stockmeier, Wouter J. Peyrot, Enrico Domenici, E. C.J. De Geus, Alexander Teumer, Henry Völzke, Yihan Li, Michael John Owen, Manuel Mattheisen, Bernard Ng, Baptiste Couvy-Duchesne, Daniel J. Smith, Jana Strohmaier, Vassily Trubetskoy, Volker Arolt, Douglas F. Levinson, Futao Zhang, Daniel Umbricht, Aartjan F.T. Beekman, David A. Hinds, Bernhard T. Baune, Henning Tiemeier, Hualin S. Xi, Hamdi Mbarek, Steven P. Hamilton, Stefan Kloiber, Fernando S. Goes, Jianxin Shi, Marcella Rietschel, Dale R. Nyholt, Zoltán Kutalik, Niamh Mullins, Grant W. Montgomery, Henriette N. Buttenschøn, Georg Homuth, Katharina Domschke, Alexander Viktorin, Hilary K. Finucane, Ashley R. Winslow, Saira Saeed Mirza, Fabian Streit, Erik Pettersson, Martin Preisig, Danielle Posthuma, Stephan Ripke, Lucía Colodro-Conde, Thalia C. Eley, Pippa A. Thomson, Thomas Werge, Enrique Castelao, Klaus Berger, Yun Li, Stacy Steinberg, Dorret I. Boomsma, Matthias Nauck, Sara Mostafavi, Jacqueline M. Lane, Katherine E. Tansey, Divya Mehta, Gregory E. Crawford, Andreas J. Forstner, Jane H. Christensen, Silviu Alin Bacanu, Julia Kraft, David M. Hougaard, Peter M. Visscher, Valentina Escott-Price, Donald J. MacIntyre, Sarah E. Medland, Per Qvist, Kenneth S. Kendler, Jordan W. Smoller, J. Raymond DePaulo, Ian J. Deary, Thomas G. Schulze, Julien Bryois, Ian B. Hickie, Helena Gaspar, Jonathan Mill, James A. Knowles, Cathryn M. Lewis, Hassan S. Dashti, Stefan Herms, Margarita Rivera, John P. Rice, Lynsey S. Hall, Eilis Hannon, Nancy L. Pedersen, Eva C. Schulte, Hreinn Stefansson, Maciej Trzaskowski, André G. Uitterlinden, Bertram Müller-Myhsok, Gail Davies, Mark Adams, Jakob Grove, Eske M. Derks, Sven Cichon, Jonathan I.R. Coleman, Sandra Van der Auwera, Myrna M. Weissman, Preben Bo Mortensen, Josef Frank, Enda M. Byrne, Esben Agerbo, Engilbert Sigurdsson, Xiaoxiao Liu, Patrick F. Sullivan, Carsten Bøcker Pedersen, Ole Mors, Catherine Schaefer, Richa Saxena, Albert M. van Hemert, Jonathan Marchini, Hogni Oskarsson, Franziska Degenhardt, Tracy Air, Elisabeth B. Binder, Christel M. Middeldorp, Farnush Hassan Farhadi Kiadeh, Conor V. Dolan, Sara A. Paciga, Per Hoffmann, Leina Lu, Andrew M. McIntosh, Tim B. Bigdeli, Stephanie H. Witt, Matthew Traylor, Grant Sinnamon, Brien P. Riley, Roy H. Perlis, Patrick J. McGrath, Craig L. Hyde, Ling Shen, Na Cai, Yunpeng Wang, Evelin Mihailov, Isaac S. Kohane, APH - Mental Health, Adult Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Biological Psychology, APH - Methodology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Integrative Neurophysiology, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, Amsterdam Reproduction & Development (AR&D), Human genetics, Epidemiology and Data Science, APH - Digital Health, Epidemiology, Child and Adolescent Psychiatry / Psychology, Internal Medicine, eQTLGen, 23andMe, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Perceptual and Cognitive Neuroscience (PCN), and Clinical Cognitive Neuropsychiatry Research Program (CCNP)

Subjects
0301 basic medicine, Male, Netherlands Twin Register (NTR), Multifactorial Inheritance, Schizophrenia/genetics, LD SCORE REGRESSION, LOCI, Genome-wide association study, Bioinformatics, 0302 clinical medicine, Risk Factors, POLYGENIC RISK, Depression (differential diagnoses), 3. Good health, Phenotype, Schizophrenia, Meta-analysis, MENDELIAN RANDOMIZATION, Genome-Wide Association Study/methods, Major depressive disorder, Female, Depressive Disorder, Major/genetics, EUROPE 2010, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, SDG 3 - Good Health and Well-being, ddc:570, MENTAL-DISORDERS, Mendelian randomization, SYSTEMATIC ANALYSIS, Genetics, medicine, Journal Article, Humans, Genetic Predisposition to Disease, METAANALYSIS, EDUCATIONAL-ATTAINMENT, Depressive Disorder, Major, Case-control study, Case-Control Studies, medicine.disease, Genetic architecture, BODY-MASS INDEX, 030104 developmental biology, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened\ud risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified\ud 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and\ud implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved\ud in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression\ud with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were\ud putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry\ud lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression\ud and imply that a continuous measure of risk underlies the clinical phenotype.

Published
2018

13. Haplotype estimation for biobank-scale data sets

Author

Jean-François Zagury, Nick Shrine, Jonathan Marchini, Martin D. Tobin, Jared O'Connell, Kevin Sharp, Olivier Delaneau, Ian P. Hall, and Louise V. Wain

Subjects
0301 basic medicine, Population, Datasets as Topic, Scale (descriptive set theory), Biology, Polymorphism, Single Nucleotide, White People, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Statistics, Genetics, Humans, education, Biological Specimen Banks, education.field_of_study, Genome, Human, Computational Biology, High-Throughput Nucleotide Sequencing, Genomics, Sequence Analysis, DNA, Biobank, United Kingdom, Genetics, Population, 030104 developmental biology, Haplotypes, Sample size determination, Haplotype estimation, Algorithms, 030217 neurology & neurosurgery
Abstract

The UK Biobank (UKB) has recently released genotypes on 152,328 individuals together with extensive phenotypic and lifestyle information. We present a new phasing method, SHAPEIT3, that can handle such biobank-scale data sets and results in switch error rates as low as ∼0.3%. The method exhibits O(NlogN) scaling with sample size N, enabling fast and accurate phasing of even larger cohorts.

Published
2016

14. A multiple-phenotype imputation method for genetic studies

Author

Andrew Dahl, Nicole Soranzo, Andreas Kranis, Jonathan Marchini, Valentina Iotchkova, Richard Mott, Åsa Johansson, Ulf Gyllensten, and Amelie Baud

Subjects
Blood Platelets, Male, 0301 basic medicine, Mixed model, T-Lymphocytes, Population genetics, Genome-wide association study, Biology, Bioinformatics, Machine learning, computer.software_genre, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Bayes' theorem, 0302 clinical medicine, Animals, Outbred Strains, Genetics, Animals, Humans, SNP, Triticum, Genetic association, Models, Genetic, business.industry, Bayes Theorem, Rats, ComputingMethodologies_PATTERNRECOGNITION, Phenotype, 030104 developmental biology, Trait, Female, Artificial intelligence, business, Chickens, computer, Algorithms, 030217 neurology & neurosurgery, Imputation (genetics), Genome-Wide Association Study
Abstract

Genetic association studies have yielded a wealth of biological discoveries. However, these studies have mostly analyzed one trait and one SNP at a time, thus failing to capture the underlying complexity of the data sets. Joint genotype-phenotype analyses of complex, high-dimensional data sets represent an important way to move beyond simple genome-wide association studies (GWAS) with great potential. The move to high-dimensional phenotypes will raise many new statistical problems. Here we address the central issue of missing phenotypes in studies with any level of relatedness between samples. We propose a multiple-phenotype mixed model and use a computationally efficient variational Bayesian algorithm to fit the model. On a variety of simulated and real data sets from a range of organisms and trait types, we show that our method outperforms existing state-of-the-art methods from the statistics and machine learning literature and can boost signals of association.

Published
2016

15. Genome-wide association study identifies eight loci associated with blood pressure

Author

Peter Holmans, Udo Seedorf, Beverley M. Shields, Peter McGruffin, Arne Pfeufer, Steve Eyre, Nathalie J. Prescott, Michael Boehnke, Valentina Moskovina, Abiodun Onipinla, Leena Peltonen, Nadira Yuldasheva, Peter M. Nilsson, Valeria Romanazzi, Vincent Mooser, Göran Berglund, Alistair S. Hall, Dominic P. Kwiatkowski, Barry Widmer, Benjamin F. Voight, Stefania Bandinelli, Mark M. Iles, Sven Bergmann, Thomas Meitinger, James P. Boorman, Simonetta Guarrera, Nazneen Rahman, Murielle Bochud, Graham A. Hitman, Emma Keniry, Nelson B. Freimer, Richard Dobson, Francis S. Collins, Gerjan Navis, Jennifer L. Pointon, Richard N. Bergman, Ruth J. F. Loos, Roberto Lorbeer, Carolina A. Braga Marcano, Christian Gieger, Florian Ernst, Xin Yuan, Catherine Potter, Hazel E. Drummond, Allan H. Young, George Kirov, John F. Peden, Helen Stevens, David Clayton, Mattijs E. Numans, Katherine Gordon-Smith, Anne Farmer, Alastair Forbes, M. Khalid Mohiuddin, John A. Todd, Christopher G. Mathew, David A. Collier, Mark I. McCarthy, Francesca Bredin, Clive M. Onnie, Dan Davidson, Markus Perola, Pamela Whittaker, Yvonne T. van der Schouw, Rathi Ravindrarajan, I. C.A. Spencer, Teresa Ferreira, Nilesh J. Samani, Serge Hercberg, Gonçalo R. Abecasis, Christopher J. Groves, Nicholas John Craddock, Angela Döring, Edward G. Lakatta, Muminatou Jallow, Wendy L. McArdle, David Bentley, Susana Eyheramendy, Uwe Völker, Christopher Newton-Cheh, Jaspal S. Kooner, Hugh Watkins, Gavin Lucas, H. T. Leung, Marjo Ritta Jarvelin, Johanna Kuusisto, Wiek H. van Gilst, Wendy Thomson, Lou R. Cardon, Harold Snieder, Marju Orho-Melander, Patricia B. Munroe, Toshiko Tanaka, Jeffrey C. Barrett, Azhar Maqbool, Henry Völzke, John M. C. Connell, Elaine R. Nimmo, John R. B. Perry, Michael R. Stratton, Ralph McGinnis, Pekka Jousilahti, Michiel L. Bots, Ian Jones, Elizabeth Meech, Matthew A. Brown, Johannie Gungadoo, Jian'an Luan, Jilur Ghori, Richard J. Dixon, N. Charlotte Onland-Moret, Fulvio Ricceri, Anthony J. Balmforth, Catherine E. Todhunter, Inês Barroso, Sheila Bingham, Timo T. Valle, Fredrik O. Vannberg, Diana Zelenika, Stephen Sawcer, Anneli Pouta, David M. Evans, Cuno S. P. M. Uiterwaal, Pilar Galan, Georg Homuth, Hannah Donovan, David J. Conway, Paul Elliott, Alessandra Allione, Paul E. de Jong, Miles Parkes, Amy Chaney, John C. Chambers, Toby Johnson, Isaac Subirana, Vesela Gateva, Cathryn M. Lewis, Christopher J. O'Donnell, Hana Lango, David Schlessinger, Mark J. Caulfield, Thorsten Reffelmann, Jamie Barbour, Karen L. Mohlke, Sarah E. Hunt, Thilo Winzer, Frances M K Williams, Christopher Mathew, I. Wallace, Anuj Goel, Jaakko Tuomilehto, Louise V. Wain, Gabriel Crawford, Samantha L. Hider, Detelinea Grozeva, Elaine K. Green, Paul D. Gilbert, Peter S. Braund, Jaume Marrugat, Rainer Rettig, Pim van der Harst, Yik Ying Teo, Andrew P. Morris, Guiseppe Matullo, Serena Sanna, Cristen J. Willer, Suzannah Bumpstead, Niall C. Taylor, Jacques S. Beckmann, Pierre Meneton, Elin Org, Luigi Ferrucci, Doug Easton, Sheila Seal, Joanne M. Heward, Anne U. Jackson, Eleftheria Zeggini, Rachel M. Freathy, Maris Laan, Paul Wordsworth, Sarah Nutland, Kerstin Koch, Sian Ceasar, Anders Hamsten, Judith M. Hussey, Tariq Ahmad, Derek P. Jewell, Paul Scheet, Charlie W. Lees, C Farrar, Christopher Prowse, Markku Laakso, David St Clair, Kate Downes, Diederick E. Grobbee, Paul Burton, Simon C. Potter, Ian N. Bruce, Tim D. Spector, Anne Barton, H.-Erich Wichmann, Matthew J. Simmonds, David Hadley, Cecilia M. Lindgren, Gérard Waeber, Nigel W. Rayner, Melanie J. Newport, Manjinder S. Sandhu, Audrey Duncanson, Guangju Zhai, Simon Heath, Susan M. Ring, Alessandra Di Gregorio, Richard Williamson, Nicholas J. Wareham, Zhan Su, Olle Melander, John R. Thompson, Alexander Teumer, Sheila A. Fisher, Lachlan J. M. Coin, Leif Groop, Giovanni Tognoni, Amanda Elkin, Alan J. Silman, Jack Satsangi, Jane Worthington, Martin Farrall, John Webster, Niall Cardin, Neil Walker, Anna F. Dominiczak, Jeremy D. Sanderson, Damjan Vukcevic, Bryan Howie, Silvia Polidoro, Stephen G. Ball, Mark Tremelling, Stephen Newhouse, Stephen M. Schwartz, Lori L. Bonnycastle, Chris Wallace, Kijoung Song, Mario A. Morken, I. Nicol Ferrier, Beverley Barke, Paolo Vineis, Manuela Uda, Deborah P M Symmons, Emily J. Lyons, Mingzhan Xue, Timothy M. Frayling, Stephen C.L. Cough, David Withers, Adrian V. S. Hill, Suzanne Stevens, Jennifer Jolley, Marcus Dörr, Kirk A. Rockett, David B. Dunger, Mark Walker, Jayne A. Franklyn, Lisa Jones, David S. Siscovick, Ann-Christine Syvänen, Laura J. Scott, Morris J. Brown, Barbera Cant, Michael Inouye, Feng Zhang, Carlotta Sacerdote, Katherine S. Elliott, Jonathan Marchini, Peter Donnely, Michael John Owen, An Goris, Marcus Prembey, Andrew T. Hattersley, Gerome Breen, Marian L. Hamshere, Thomas Illig, Samer S. Najjar, Nicole Soranzo, Kay-Tee Khaw, Graham R. Walters, Willem H. Ouwehand, David P. Strachan, Martin D. Tobin, Alastair Compston, John C. Mansfield, David Altshuler, Salvatore Panico, Sekar Kathiresan, Dawn M. Waterworth, Michael N. Weedon, D. Timothy Bishop, Claire Bryan, Alexandra S. Knight, Kate L. Lee, Paul F. O'Reilly, Massimo Mangino, Michael Conlon O'Donovan, Jing Hua Zhao, Konstantinos A. Papadakis, Jennifer H. Barrett, Joanne Pereira-Gale, N J Timpson, Stephan B. Felix, Panos Deloukas, Nicholas A. Watkins, Anna-Liisa Hartikainen, Peter Vollenweider, Richard Jones, Anne Hinks, Fraser Cummings, Noha Lim, Linda A. Bradbury, Rhian G. William, Nita G. Forouhi, Roberto Eluosa, Ingeleif B. Hallgrimsdottir, Giorgio Sirugo, Robert Luben, Veikko Salomaa, Robert Clarke, Sally John, Ursula Everson, Emma King, Ivan Nikolov, Heather M. Stringham, Antony P. Attwood, Angelo Scuteri, Wellcome Trust Case Control Consortium, Burton, PR., Clayton, DG., Cardon, LR., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, DP., McCarthy, MI., Ouwehand, WH., Samani, NJ., Todd, JA., Donnelly, P., Barrett, JC., Davison, D., Easton, D., Evans, D., Leung, HT., Marchini, JL., Morris, AP., Spencer, IC., Tobin, MD., Attwood, AP., Boorman, JP., Cant, B., Everson, U., Hussey, JM., Jolley, JD., Knight, AS., Koch, K., Meech, E., Nutland, S., Prowse, CV., Stevens, HE., Taylor, NC., Walters, GR., Walker, NM., Watkins, NA., Winzer, T., Jones, RW., McArdle, WL., Ring, SM., Strachan, DP., Pembrey, M., Breen, G., St Clair, D., Caesar, S., Gordon-Smith, K., Jones, L., Fraser, C., Green, EK., Grozeva, D., Hamshere, ML., Holmans, PA., Jones, IR., Kirov, G., Moskvina, V., Nikolov, I., O'Donovan, MC., Owen, MJ., Collier, DA., Elkin, A., Farmer, A., Williamson, R., McGuffin, P., Young, AH., Ferrier, IN., Ball, SG., Balmforth, AJ., Barrett, JH., Bishop, DT., Iles, MM., Maqbool, A., Yuldasheva, N., Hall, AS., Braund, PS., Dixon, RJ., Mangino, M., Stevens, S., Thompson, JR., Bredin, F., Tremelling, M., Parkes, M., Drummond, H., Lees, CW., Nimmo, ER., Satsangi, J., Fisher, SA., Forbes, A., Lewis, CM., Onnie, CM., Prescott, NJ., Sanderson, J., Mathew, CG., Barbour, J., Mohiuddin, MK., Todhunter, CE., Mansfield, JC., Ahmad, T., Cummings, FR., Jewell, DP., Webster, J., Brown, MJ., Lathrop, GM., Connell, J., Dominiczak, A., Braga Marcano, CA., Burke, B., Dobson, R., Gungadoo, J., Lee, KL., Munroe, PB., Newhouse, SJ., Onipinla, A., Wallace, I., Xue, M., Caulfield, M., Farrall, M., Barton, A., Bruce, IN., Donovan, H., Eyre, S., Gilbert, PD., Hider, SL., Hinks, AM., John, SL., Potter, C., Silman, AJ., Symmons, DP., Thomson, W., Worthington, J., Dunger, DB., Widmer, B., Frayling, TM., Freathy, RM., Lango, H., Perry, JR., Shields, BM., Weedon, MN., Hattersley, AT., Hitman, GA., Walker, M., Elliott, KS., Groves, CJ., Lindgren, CM., Rayner, NW., Timpson, NJ., Zeggini, E., Newport, M., Sirugo, G., Lyons, E., Vannberg, F., Hill, AV., Bradbury, LA., Farrar, C., Pointon, JJ., Wordsworth, P., Brown, MA., Franklyn, JA., Heward, JM., Simmonds, MJ., Gough, SC., Seal, S., Stratton, MR., Rahman, N., Ban, M., Goris, A., Sawcer, SJ., Compston, A., Conway, D., Jallow, M., Rockett, KA., Bryan, C., Bumpstead, SJ., Chaney, A., Downes, K., Ghori, J., Gwilliam, R., Hunt, SE., Inouye, M., Keniry, A., King, E., McGinnis, R., Potter, S., Ravindrarajah, R., Whittaker, P., Withers, D., Cardin, NJ., Ferreira, T., Pereira-Gale, J., Hallgrimsdóttir, IB., Howie, BN., Su, Z., Teo, YY., Vukcevic, D., Bentley, D., Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Vascular Ageing Programme (VAP), and Medical Research Council (MRC)

Subjects
Hemodynamics, Genome-wide association study, Blood Pressure, 030204 cardiovascular system & hematology, 0302 clinical medicine, Diastole, 11 Medical and Health Sciences, POPULATION, Genetics, Genetics & Heredity, RISK, 0303 health sciences, education.field_of_study, Econometric and Statistical Methods: General, CELL-DIFFERENTIATION, biology, Intracellular Signaling Peptides and Proteins, Chromosome Mapping, Steroid 17-alpha-Hydroxylase, COMMON VARIANTS, 3. Good health, DNA-Binding Proteins, Europe, Cardiovascular Diseases, PUBLIC-HEALTH, BARTTERS-SYNDROME, Blood Pressure/genetics, Cardiovascular Diseases/genetics, Cardiovascular Diseases/physiopathology, Cytochrome P-450 CYP1A2/genetics, DNA-Binding Proteins/genetics, Diastole/genetics, European Continental Ancestry Group/genetics, Fibroblast Growth Factor 5/genetics, Genetic Variation, Genome-Wide Association Study, Humans, India, Methylenetetrahydrofolate Reductase (NADPH2)/genetics, Open Reading Frames/genetics, Phospholipase C delta/genetics, Polymorphism, Single Nucleotide, Proteins/genetics, Steroid 17-alpha-Hydroxylase/genetics, Systole/genetics, Wellcome Trust Case Control Consortium, Life Sciences & Biomedicine, hypertension, Fibroblast Growth Factor 5, Systole, Population, European Continental Ancestry Group, METHYLENETETRAHYDROFOLATE REDUCTASE GENE, Single-nucleotide polymorphism, LOW-RENIN HYPERTENSION, White People, Article, 03 medical and health sciences, Open Reading Frames, Fibroblast growth factor-5, Cytochrome P-450 CYP1A2, Geneeskunde(GENK), education, Methylenetetrahydrofolate Reductase (NADPH2), Adaptor Proteins, Signal Transducing, 030304 developmental biology, Genetic association, genome-wide association, Science & Technology, MUTATIONS, Proteins, 06 Biological Sciences, POLYMORPHISM, Blood pressure, Methylenetetrahydrofolate reductase, biology.protein, biology.gene, Phospholipase C delta, Developmental Biology
Abstract

Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10(-24)), CYP1A2 (P = 1 × 10(-23)), FGF5 (P = 1 × 10(-21)), SH2B3 (P = 3 × 10(-18)), MTHFR (P = 2 × 10(-13)), c10orf107 (P = 1 × 10(-9)), ZNF652 (P = 5 × 10(-9)) and PLCD3 (P = 1 × 10(-8)) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.

Published
2009

16. Genome-wide and fine-resolution association analysis of malaria in West Africa

Author

Muminatou, Jallow, Yik Ying Teo, Small, Kerrin S., Rockett, Kirk A., Panos, Deloukas, Clark, Taane G., Katja, Kivinen, Bojang, Kalifa A., Conway, David J., Margaret, Pinder, Giorgio, Sirugo, Fatou Sisay Joof, Stanley, Usen, Sarah, Auburn, Bumpstead, Suzannah J., Susana, Campino, Alison, Coffey, Andrew, Dunham, Fry, Andrew E., Angela, Green, Rhian, Gwilliam, Hunt, Sarah E., Michael, Inouye, Jeffreys, Anna E., Alieu, Mendy, Aarno, Palotie, Simon, Potter, Jiannis, Ragoussis, Jane, Rogers, Kate, Rowlands, Elilan, Somaskantharajah, Pamela, Whittaker, Claire, Widden, Peter, Donnelly, Bryan, Howie, Jonathan, Marchini, Andrew, Morris, Miguel, Sanjoaquin, Eric Akum Achidi, Tsiri, Agbenyega, Angela, Allen, Olukemi, Amodu, Patrick, Corran, Abdoulaye, Djimde, Amagana, Dolo, Doumbo, Ogobara K., Chris, Drakeley, Sarah, Dunstan, Jennifer, Evans, Jeremy, Farrar, Hien Tt, Fernando D., Horstmann, R. D., Ibrahim, M., Karunaweera, N., Kokwaro, G., Koram, K. A., Lemnge, M., Makani, J., Marsh, K., Michon, P., David, Modiano, Molyneux, M. E., Mueller, I., Parker, M., Peshu, N., Plowe, C. V., Puijalon, O., Reeder, J., Reyburn, H., Riley, E. M., Sakuntabhai, A., Singhasivanon, P., Sirima, S., Tall, A., Taylor, T. E., Thera, M., Troye Blomberg, M., Williams, T. N., Wilson, M., Wellcome Trust Case Control Consortium Kwiatkowski, D. P., Epidemiology Network: Achidi, Malaria Genomic E. A., Agbenyega, T., Ahmad, T., Alcock, D., Allen, S., Amenga Etego, L., Amodu, O., Apinjoh, T. O., Attwood, A. P., Auburn, S., Ball, S. G., Balmforth, A. J., Ban, M., Barbour, J., Barnwell, D., Barrett, J. C., Barrett, J. H., Barton, A., Bentley, D., Bishop, D. T., Bojang, K., Boorman, J. P., Bougouma, E., Bradbury, L. A., Braga Marcano, C. A., Braund, P. S., Bredin, F., Breen, G., Brown, M. A., Brown, M. J., Bruce, I. N., Bryan, C., Bull, S., Bumpstead, S. J., Burke, B., Burton, P. R., Caesar, S., Campino, S., Cant, B., Cardin, N. J., Cardon, L. R., Carucci, D., Caulfield, M., Chaney, A., Clark, T., Clayton, D. G., Collier, D. A., Compston, A., Compston, D. A., Connell, J., Conway, D., Cook, K., Corran, P., Craddock, N., Cummings, F. R., Davison, D., Deloukas, P., Devries, J., Dewasurendra, R., Diakite, M., Dixon, R. J., Djimde, A., Dobson, R., Dolo, A., Dominiczak, A., Donnelly, P., Donovan, H., Doumbo, O., Downes, K., Doyle, A., Drakeley, C., Drummond, H., Duffy, P., Duncanson, A., Dunger, D. B., Dunstan, S., Duombo, O., Easton, D., Elkin, A., Elliott, K. S., Elzein, A., Enimil, A., Evans, D., Evans, J., Everson, U., Eyre, S., Farmer, A., Farrall, M., Farrar, C., Farrar, J., Fernando, D., Ferreira, T., Ferrier, I. N., Fisher, S. A., Fitzpatrick, K., Forbes, A., Franklyn, J. A., Fraser, C., Frayling, T. M., Freathy, R. M., Ghansah, A., Ghori, J., Gilbert, P. D., Gordon Smith, K., Goris, A., Gottlieb, M., Gough, S. C., Green, A., Green, E. K., Groves, C. J., Grozeva, D., Gungadoo, J., Gwilliam, R., Hall, A. S., Hallgrimsdóttir, I. B., Hamshere, M. L., Hart, L., Hattersley, A. T., Heward, J. M., Hider, S. L., Tran Tinh Hien, Hill, A. V., Hilton, E., Hinks, A. M., Hitman, G. A., Holmans, P. A., Horstmann, Rolf D., Howie, B. N., Hubbart, C., Hughes, C., Hunt, S. E., Hussein, A., Hussey, J. M., Muntaser, Ibrahim, Iles, M. M., Inouye, M., Ishengoma, D., Jallow, M., Jeffreys, A. E., Jewell, D. P., John, Sl, Jolley, J. D., Jones, I. R., Jones, L., Jones, R. W., Nadira, Karunaweera, Keniry, A., King, E., Kirov, G., Kivinen, K., Knight, A. S., Koch, K., Gilbert, Kokwaro, Koram, Kwadwo A., Lango, H., Lathrop, G. M., Lee, K. L., Lees, C. W., Martha, Lemnge, Leung, H. T., Lewis, C. M., Lin, E., Lindgren, C. M., Ly, A., Macinnis, B., Julie, Makani, Mangano, Valentina, Mangino, M., Manjurano, A., Manning, L., Mansfield, J. C., Manske, M., Maqbool, A., Marchini, J. L., Kevin, Marsh, Maslen, G., Mathew, C. G., Mcardle, W. L., Mccarthy, M. I., Mccreight, M., Mcginnis, R., Mcguffin, P., Meech, E., Mendy, A., Pascal, Michon, Mohiuddin, M. K., Molyneux, Malcolm E., Morris, A. P., Moskvina, V., Moyes, C., Ivo, Mueller, Munroe, P. B., Mutabingwa, T., Ndila, C. M., Newhouse, S. J., Newport, M., Nikolov, I., Nimmo, E. R., Nutland, S., Nyirongo, V., O'Donovan, M. C., Oluoch, T., Onipinla, A., Onnie, C. M., Ouwehand, W. H., Owen, M. J., Michael, Parker, Parkes, M., Pembrey, M., Pereira Gale, J., Perry, J. R., Norbert, Peshu, Plowe, Christopher V., Pointon, J. J., Potter, C., Potter, S., Prescott, N. J., Prowse, C. V., Odile, Puijalon, Quyen, N. T., Ragoussis, J., Rahman, N., Ravindrarajah, R., Rayner, N. W., John, Reeder, Hugh, Reyburn, Riley, Eleanor M., Ring, S. M., Risley, P., Rockett, K. A., Rogers, J., Rowlands, K., Anavaj, Sakuntabhai, Samani, N. J., Sanderson, J., Sanjoaquin, M., Satsangi, J., Sawcer, S. J., Seal, S., Shields, B. M., Silman, A. J., Simmonds, M. J., Pratap, Singhasivanon, Sodiomon, Sirima, Sirugo, G., Small, K. S., Somaskantharajah, E., Spencer, C. C., St Clair, D., Stevens, H. E., Stevens, M., Stevens, S., Strachan, D. P., Stratton, M. R., Su, Z., Suriyaphol, P., Symmons, D. P., Adama, Tall, Taylor, N. C., Taylor, Terrie E., Teo, Y., Teo, Y. Y., Mahamadou, Thera, Thompson, J. R., Thomson, W., Timpson, N. J., Tobin, M. D., Todd, J. A., Todhunter, C. E., Toure, O., Tremelling, M., Marita Troye Blomberg, Vanderwal, A., Vukcevic, D., Walker, M., Walker, N. M., Wallace, C., Walters, G. R., Walton, R., Watkins, N. A., Watson, R., Webster, J., Weedon, M. N., Whittaker, P., Widmer, B., Williams, Thomas N., Williamson, R., Michael, Wilson, Winzer, T., Withers, D., Wordsworth, P., Worthington, J., Wrigley, R., Xue, M., Young, A. H., Yuldasheva, N., and Zeggini, E.

Subjects
Linkage disequilibrium, Hemoglobin, Sickle, Population, Genome-wide association study, Locus (genetics), Biology, Population stratification, Polymorphism, Single Nucleotide, Severity of Illness Index, Linkage Disequilibrium, Article, Gene mapping, Reference Values, Ethnicity, Genetics, Humans, education, Genetic association, education.field_of_study, Polymorphism, Genetic, Chromosome Mapping, Genetic Variation, Malaria, Gambia, Imputation (genetics), Genome-Wide Association Study
Abstract

We report a genome-wide association (GWA) study of severe malaria in The Gambia. The initial GWA scan included 2,500 children genotyped on the Affymetrix 500K GeneChip, and a replication study included 3,400 children. We used this to examine the performance of GWA methods in Africa. We found considerable population stratification, and also that signals of association at known malaria resistance loci were greatly attenuated owing to weak linkage disequilibrium (LD). To investigate possible solutions to the problem of low LD, we focused on the HbS locus, sequencing this region of the genome in 62 Gambian individuals and then using these data to conduct multipoint imputation in the GWA samples. This increased the signal of association, from P = 4 × 10(-7) to P = 4 × 10(-14), with the peak of the signal located precisely at the HbS causal variant. Our findings provide proof of principle that fine-resolution multipoint imputation, based on population-specific sequencing data, can substantially boost authentic GWA signals and enable fine mapping of causal variants in African populations.

Published
2009

17. Fast and accurate genotype imputation in genome-wide association studies through pre-phasing

Author

Bryan Howie, Gonçalo R. Abecasis, Christian Fuchsberger, Matthew Stephens, and Jonathan Marchini

Subjects
Genetics, Genotype imputation, Genotype, Computational Biology, Genome-wide association study, Computational biology, Biology, Phaser, Article, Haplotypes, Databases, Genetic, Human Genome Project, Humans, Haplotype estimation, Imputation (genetics), Genome-Wide Association Study
Abstract

The 1000 Genomes Project and disease-specific sequencing efforts are producing large collections of haplotypes that can be used as reference panels for genotype imputation in genome-wide association studies (GWAS). However, imputing from large reference panels with existing methods imposes a high computational burden. We introduce a strategy called 'pre-phasing' that maintains the accuracy of leading methods while reducing computational costs. We first statistically estimate the haplotypes for each individual within the GWAS sample (pre-phasing) and then impute missing genotypes into these estimated haplotypes. This reduces the computational cost because (i) the GWAS samples must be phased only once, whereas standard methods would implicitly repeat phasing with each reference panel update, and (ii) it is much faster to match a phased GWAS haplotype to one reference haplotype than to match two unphased GWAS genotypes to a pair of reference haplotypes. We implemented our approach in the MaCH and IMPUTE2 frameworks, and we tested it on data sets from the Wellcome Trust Case Control Consortium 2 (WTCCC2), the Genetic Association Information Network (GAIN), the Women's Health Initiative (WHI) and the 1000 Genomes Project. This strategy will be particularly valuable for repeated imputation as reference panels evolve.

Published
2012

18. Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function

Author

Arthur W. Musk, Ernst Omenaas, Dana B. Hancock, Jennie Hui, John W. Holloway, Nora Franceschini, Alan F. Wright, Ma'en Obeidat, Judith M. Vonk, Norman Klopp, Shah Ebrahim, R. Graham Barr, Jerome I. Rotter, Albert Hofman, Jennifer E. Huffman, Kirsi H. Pietiläinen, John Beilby, Bruno H. Ch. Stricker, Xiangjun Gu, Fernando Rivadeneira, James F. Wilson, Fredrik Nyberg, Peter D. Sly, María Soler Artigas, Bonnie R. Joubert, Marjo-Riitta Järvelin, Medea Imboden, Veronique Vitart, Albert V. Smith, Ida Surakka, C.M. Jackson, Susan R. Heckbert, Avan Aihie Sayer, Craig E. Pennell, Matthias Wjst, Ivana Kolcic, Cyrus Cooper, Wei Ang, Ian Sayers, John Britton, George T. O'Connor, Patrick G. Holt, Anna-Liisa Hartikainen, Adaikalavan Ramasamy, Jing Hua Zhao, Jonathan Marchini, Bernd Meibohm, Laura R. Loehr, Mark Eijgelsheim, David Couper, Massimo Mangino, Santosh Dahgam, Vilmundur Gudnason, David P. Strachan, Martin D. Tobin, Rebecca Hardy, Nicole Probst-Hensch, Stephen B. Kritchevsky, George Davey Smith, Tatijana Zemunik, Toby Johnson, Samuli Ripatti, Georg Homuth, Debbie A Lawlor, Thor Aspelund, Henry Völzke, John M. Starr, Aroon D. Hingorani, Khalid A. Al Balushi, Ivan Curjuric, John Henderson, Diana Kuh, Ruth J. F. Loos, Joachim Heinrich, Ozren Polasek, Yongmei Liu, Dirkje S. Postma, Raquel Granell, Akshay Sood, Kari E. North, Beate Koch, Christian Gieger, Tamara B. Harris, Anneli Pouta, David J. Porteous, Daan W. Loth, Sarah H. Wild, Gudny Eiriksdottir, Mladen Boban, Markku Heliövaara, Jonas Brisman, Mika Kähönen, Eva Albrecht, Pirro G. Hysi, Paul Elliott, Stephanie J. London, Guy Brusselle, Myriam Fornage, Thierry Rochat, Kurt Lohman, Ani Manichaikul, David M. Evans, Florian Kronenberg, Caroline Hayward, Harry Campbell, Tricia M. McKeever, So-Youn Shin, Deborah Jarvis, Alanna C. Morrison, Nicole M. Warrington, Holger Schulz, Karen A. Jameson, Stefan Karrasch, Cisca Wijmenga, Richard W Morris, Gauti Kjartan Gislason, Lina Zgaga, Ivica Grković, Alan James, Amanda P. Henry, O. Dale Williams, Jaakko Kaprio, Gemma Cadby, Susan M. Ring, Peter H. Whincup, Thomas Lumley, Nicholas J. Wareham, Lorna M. Lopez, John L. Hankinson, Christopher J Hammond, André G. Uitterlinden, Isabelle Pin, Shona M. Kerr, Alicja R. Rudnicka, Ian J. Deary, Taina Rantanen, Sven Gläser, Wendy L. McArdle, Andrew Wong, Ins Barroso, Lenore J. Launer, S. Goya Wannamethee, Wenbo Tang, Ian P. Hall, Sina A. Gharib, Louise V. Wain, Vesna Boraska, John D Blakey, H.-Erich Wichmann, Anna-Carin Olin, Patricia A. Cassano, H. Marike Boezen, Stipan Janković, Igor Rudan, Andrew D. Morris, Jason Z. Liu, Sarah E. Harris, Clyde Francks, Michael Hunter, Kristin D. Marciante, Stephen S. Rich, Darya Gaysina, Bruce M. Psaty, Melinda C. Aldrich, Melissa E. Garcia, Jemma B. Wilk, Tim D. Spector, Lyle J. Palmer, Guangju Zhai, Epidemiology, Internal Medicine, Public Health, Medical Research Council (MRC), The International Lung Cancer Consortium, Giant consortium, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), and Groningen Research Institute for Asthma and COPD (GRIAC)

Subjects
Oncology, Vital capacity, PROTEIN, Genome-wide association study, BLOOD-PRESSURE, VARIANTS, Pulmonary function testing, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, Epidemiology, IMPUTATION, Child, 11 Medical and Health Sciences, POPULATION, Genetics & Heredity, RISK, 0303 health sciences, education.field_of_study, WOMEN, GENETIC-VARIATION, 3. Good health, Respiratory Function Tests, medicine.anatomical_structure, Medical genetics, Life Sciences & Biomedicine, EXPRESSION, medicine.medical_specialty, MECOM, Population, European Continental Ancestry Group, Biology, OBSTRUCTIVE PULMONARY-DISEASE, Article, White People, 03 medical and health sciences, Internal medicine, Genetics, medicine, Humans, education, METAANALYSIS, POLYMORPHISMS, 030304 developmental biology, Lung, Science & Technology, MORTALITY, GIANT consortium, International Lung Cancer Consortium, 06 Biological Sciences, 030228 respiratory system, Immunology, lung, gene, gwas, Genome-Wide Association Study, Developmental Biology
Abstract

Pulmonary function measures reflect respiratory health and are used in the diagnosis of chronic obstructive pulmonary disease. We tested genome-wide association with forced expiratory volume in 1 second and the ratio of forced expiratory volume in 1 second to forced vital capacity in 48,201 individuals of European ancestry with follow up of the top associations in up to an additional 46,411 individuals. We identified new regions showing association (combined P < 5 x 10(-8)) with pulmonary function in or near MFAP2, TGFB2, HDAC4, RARB, MECOM (also known as EVI1), SPATA9, ARMC2, NCR3, ZKSCAN3, CDC123, C10orf11, LRP1, CCDC38, MMP15, CFDP1 and KCNE2. Identification of these 16 new loci may provide insight into the molecular mechanisms regulating pulmonary function and into molecular targets for future therapy to alleviate reduced lung function.

Published
2011

19. Meta-analysis and imputation refines the association of 15q25 with smoking quantity

Author

Mark J. Caulfield, Paul Scheet, Ruth J. F. Loos, Ozren Polasek, Vincent Mooser, Michael Wittig, Stephen E. Epstein, James F. Wilson, Gonçalo R. Abecasis, Jennifer E. Huffman, Augusto D. Pichard, Mary Susan Burnett, Rajesh Rawal, Federica Tozzi, Nilesh J. Samani, Hans J. Grabe, Robert L. Wilensky, Miles Parkes, Jing Hua Zhao, Jaspal S. Kooner, Daniel J. Rader, Wade H. Berrettini, Per Bakke, Robert W. Mahley, Astrid Petersmann, Alan F. Wright, Kenneth M. Kent, Lowell F. Satler, Alistair S. Hall, Xin Yuan, Hakon Hakonarson, Henry Völzke, Peter Vollenweider, Xiangjun Xiao, John B. Vincent, Joseph M. Lindsay, Scott M. Grundy, Christopher G. Mathew, Caroline Hayward, Susan Campbell, John R. Thompson, Alexander Teumer, Ins Barroso, David Schlessinger, Jack Satsangi, Benjamin J. Wright, Carl A. Anderson, Fabio Busonero, James L. Kennedy, Harry Campbell, Dan Rujescu, Anne Barton, H.-Erich Wichmann, Philip J. Barter, Veronique Vitart, Antonio Terracciano, Ruth McPherson, S. Horstmann, Anna F. Dominiczak, Martin Preisig, Susanne Lucae, David St Clair, Lina Zgaga, Jane Worthington, Joseph M. Devaney, Wendy Thomson, Anne Farmer, Antero Kesäniemi, Ulrich John, Tariq Ahmad, William H. Matthai, Jason Z. Liu, Muredach P. Reilly, Ivana Kolcic, Igor Rudan, Norbert Dahmen, Martin Farrall, Anthony J. Balmforth, Nicholas J. Wareham, Steve Eyre, T. Brueckl, Kay-Tee Khaw, Liming Qu, Christopher W. Knouff, Sarah H. Wild, Patricia B. Munroe, Claudia Lamina, Dawn M. Waterworth, John Strauss, John C. Chambers, Marcus Ising, Richard O. Day, Amund Gulsvik, Gérard Waeber, Arne Schäfer, Andre Franke, Clyde Francks, Pierandrea Muglia, Mingyao Li, Peter McGuffin, Keith Matthews, Manuela Uda, Sreekumar G. Pillai, Jonathan Marchini, Lefkos T. Middleton, Ron Waksman, and Wellcome Trust Case Control Consortium

Subjects
Genetics, 0303 health sciences, education.field_of_study, Population, Single-nucleotide polymorphism, Genome-wide association study, Locus (genetics), Biology, Article, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Genome-Wide Association, Nicotine Dependence, Lung-Cancer, Susceptibility Locus, Risk-Factors, Disease, Genes, SNPS, Colaus Study, SNP, 1000 Genomes Project, Allele, education, 030217 neurology & neurosurgery, Imputation (genetics), genome-wide association study, smoking initiation, smoking quantity, 030304 developmental biology
Abstract

Smoking is a leading global cause of disease and mortality(1). We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.

Published
2010
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20. A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC

Author

John Hart, John A. Todd, Xiaojiang Gao, Paul I.W. de Bakker, Alienke J. Monsuur, Marcos Mateo Miretti, Mark J. Daly, Pardis C. Sabeti, Jonathan Marchini, Luana Galver, Cisca Wijmenga, Xiayi Ke, Mary Carrington, John Trowsdale, Panos Deloukas, David A. Hafler, Jonathan Morrison, Sarah S. Murray, Margaret A. Pericak-Vance, Simon G. Gregory, Emily C. Walsh, Timothy J. Vyse, Pamela Whittaker, Todd Green, Marcos Delgado, Stephan Beck, Gil McVean, Angela Richardson, and John D. Rioux

Subjects
Genetics, Linkage disequilibrium, education.field_of_study, Polymorphism, Genetic, Genetics, Medical, Racial Groups, Haplotype, Population, Single-nucleotide polymorphism, Human leukocyte antigen, Biology, Major histocompatibility complex, Polymorphism, Single Nucleotide, Article, Histocompatibility, Haplotypes, HLA Antigens, Histocompatibility Antigens, biology.protein, Humans, SNP, Genetic Predisposition to Disease, education
Abstract

The proteins encoded by the classical HLA class I and class II genes in the major histocompatibility complex (MHC) are highly polymorphic and play an essential role in self/non-self immune recognition. HLA variation is a crucial determinant of transplant rejection and susceptibility to a large number of infectious and autoimmune disease1. Yet identification of causal variants is problematic due to linkage disequilibrium (LD) that extends across multiple HLA and non-HLA genes in the MHC2,3. We therefore set out to characterize the LD patterns between the highly polymorphic HLA genes and background variation by typing the classical HLA genes and >7,500 common single nucleotide polymorphisms (SNPs) and deletion/insertion polymorphisms (DIPs) across four population samples. The analysis provides informative tag SNPs that capture some of the variation in the MHC region and that could be used in initial disease association studies, and provides new insight into the evolutionary dynamics and ancestral origins of the HLA loci and their haplotypes.

Published
2006

21. Genome-wide strategies for detecting multiple loci that influence complex diseases

Author

Peter Donnelly, Jonathan Marchini, and Lon R. Cardon

Subjects
Genetic Markers, Genetics, Models, Genetic, Genetic Linkage, Genome, Human, Genetic Diseases, Inborn, Biology, Genome, Genetics, Population, Evolutionary biology, Multiple comparisons problem, Humans, Genetic Predisposition to Disease, Allele frequency, Alleles, Genetic association
Abstract

After nearly 10 years of intense academic and commercial research effort, large genome-wide association studies for common complex diseases are now imminent. Although these conditions involve a complex relationship between genotype and phenotype, including interactions between unlinked loci1, the prevailing strategies for analysis of such studies focus on the locus-by-locus paradigm. Here we consider analytical methods that explicitly look for statistical interactions between loci. We show first that they are computationally feasible, even for studies of hundreds of thousands of loci, and second that even with a conservative correction for multiple testing, they can be more powerful than traditional analyses under a range of models for interlocus interactions. We also show that plausible variations across populations in allele frequencies among interacting loci can markedly affect the power to detect their marginal effects, which may account in part for the well-known difficulties in replicating association results. These results suggest that searching for interactions among genetic loci can be fruitfully incorporated into analysis strategies for genome-wide association studies.

Published
2005

22. The effects of human population structure on large genetic association studies

Author

Jonathan Marchini, Lon R. Cardon, Peter Donnelly, and Michael S. Phillips

Subjects
Genetic Markers, Genetics, Linkage disequilibrium, education.field_of_study, Models, Genetic, Population, Genetic Variation, Population genetics, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Genetics, Population, Quantitative Trait, Heritable, Evolutionary biology, Genetic marker, Sample size determination, Genetic variation, Humans, Genetic Predisposition to Disease, education, Genetic association
Abstract

Large-scale association studies hold substantial promise for unraveling the genetic basis of common human diseases. A well-known problem with such studies is the presence of undetected population structure, which can lead to both false positive results and failures to detect genuine associations. Here we examine approximately 15,000 genome-wide single-nucleotide polymorphisms typed in three population groups to assess the consequences of population structure on the coming generation of association studies. The consequences of population structure on association outcomes increase markedly with sample size. For the size of study needed to detect typical genetic effects in common diseases, even the modest levels of population structure within population groups cannot safely be ignored. We also examine one method for correcting for population structure (Genomic Control). Although it often performs well, it may not correct for structure if too few loci are used and may overcorrect in other settings, leading to substantial loss of power. The results of our analysis can guide the design of large-scale association studies.

Published
2004

24. Haplotype estimation for biobank-scale data sets

Author

O'Connell, Jared, primary, Sharp, Kevin, additional, Shrine, Nick, additional, Wain, Louise, additional, Hall, Ian, additional, Tobin, Martin, additional, Zagury, Jean-Francois, additional, Delaneau, Olivier, additional, and Marchini, Jonathan, additional

Published
2016
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25. A multiple-phenotype imputation method for genetic studies

Author

Dahl, Andrew, primary, Iotchkova, Valentina, additional, Baud, Amelie, additional, Johansson, Åsa, additional, Gyllensten, Ulf, additional, Soranzo, Nicole, additional, Mott, Richard, additional, Kranis, Andreas, additional, and Marchini, Jonathan, additional

Published
2016
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26. Identification of loci associated with schizophrenia by genome-wide association and follow-up

Author

Nancy G. Buccola, Bryan Howie, Dan Rujescu, Thomas G. Schulze, Stanley Zammit, Robert Freedman, Wolfgang Maier, William Byerley, Annette M. Hartmann, Chris C. A. Spencer, Hans-Jürgen Möller, H. T. Leung, Michael Conlon O'Donovan, Catalina Vasilescu, Markus M. Nöthen, Nigel Williams, Peter Propping, Jubao Duan, C. Robert Cloninger, Ivan Nikolov, Sven Cichon, Ariel Darvasi, Pablo V. Gejman, Yongyong Shi, Nadine Norton, Nakao Iwata, Jeremy M. Silverman, Emma M. Quinn, George Kirov, Alan R. Sanders, Derek W. Morris, Sarah Dwyer, Ina Giegling, Liam S. Carroll, Sagiv Shifman, Lyudmila Georgieva, Marcella Rietschel, Per Hoffmann, Michael John Owen, Hywel Williams, Bryan J. Mowry, Johannes Schumacher, Michael Gill, Masashi Ikeda, Lin He, Donald W. Black, Marian L. Hamshere, Aiden Corvin, Nicholas John Craddock, Jonathan Marchini, Farooq Amin, Guo Yin Feng, Valentina Moskvina, Peter Holmans, Douglas F. Levinson, and T. Peirce

Subjects
Genetics, Psychosis, Bipolar Disorder, biology, Kruppel-Like Transcription Factors, Case-control study, Chromosome Mapping, Genome-wide association study, Locus (genetics), medicine.disease, Polymorphism, Single Nucleotide, Phenotype, Case-Control Studies, Schizophrenia, biology.protein, medicine, Humans, Genetic Predisposition to Disease, ANK3, Bipolar disorder, Zinc finger protein 804A, Follow-Up Studies, Genome-Wide Association Study
Abstract

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10-5 in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 × 10-4), and the overall pattern of replication was unlikely to occur by chance (P = 9 × 10-8). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 × 10-7) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 × 10-9). © 2008 Nature Publishing Group.

Published
2008

27. A robust statistical method for case-control association testing with copy number variation

Author

David Clayton, Matthew E. Hurles, Vincent Plagnol, Richard Redon, Chris P. Barnes, Tomas W Fitzgerald, and Jonathan Marchini

Subjects
Linkage disequilibrium, genetic structures, Quantitative Trait Loci, Gene Dosage, Single-nucleotide polymorphism, Genome-wide association study, Biology, Quantitative trait locus, computer.software_genre, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, Article, Structural variation, Cohort Studies, Genetics, Chromosomes, Human, Humans, Computer Simulation, Copy-number variation, Association (psychology), Genetic association, Oligonucleotide Array Sequence Analysis, Models, Genetic, Genome, Human, DNA, eye diseases, Diabetes Mellitus, Type 1, Haplotypes, Case-Control Studies, Data mining, sense organs, computer
Abstract

Copy number variation (CNV) is pervasive in the human genome and can play a causal role in genetic diseases. The functional impact of CNV cannot be fully captured through linkage disequilibrium with SNPs. These observations motivate the development of statistical methods for performing direct CNV association studies. We show through simulation that current tests for CNV association are prone to false-positive associations in the presence of differential errors between cases and controls, especially if quantitative CNV measurements are noisy. We present a statistical framework for performing case-control CNV association studies that applies likelihood ratio testing of quantitative CNV measurements in cases and controls. We show that our methods are robust to differential errors and noisy data and can achieve maximal theoretical power. We illustrate the power of these methods for testing for association with binary and quantitative traits, and have made this software available as the R package CNVtools.

Published
2008

31. A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC

Author

de Bakker, Paul I W, primary, McVean, Gil, additional, Sabeti, Pardis C, additional, Miretti, Marcos M, additional, Green, Todd, additional, Marchini, Jonathan, additional, Ke, Xiayi, additional, Monsuur, Alienke J, additional, Whittaker, Pamela, additional, Delgado, Marcos, additional, Morrison, Jonathan, additional, Richardson, Angela, additional, Walsh, Emily C, additional, Gao, Xiaojiang, additional, Galver, Luana, additional, Hart, John, additional, Hafler, David A, additional, Pericak-Vance, Margaret, additional, Todd, John A, additional, Daly, Mark J, additional, Trowsdale, John, additional, Wijmenga, Cisca, additional, Vyse, Tim J, additional, Beck, Stephan, additional, Murray, Sarah Shaw, additional, Carrington, Mary, additional, Gregory, Simon, additional, Deloukas, Panos, additional, and Rioux, John D, additional

Published
2006
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34. Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants.

Author

Burton, Paul R, Clayton, David G, Cardon, Lon R, Craddock, Nick, Deloukas, Panos, Duncanson, Audrey, Kwiatkowski, Dominic P, McCarthy, Mark I, Ouwehand, Willem H, Samani, Nilesh J, Todd, John A, Donnelly (Chair), Peter, Barrett, Jeffrey C, Davison, Dan, Donnelly, Peter, Easton, Doug, Evans, David M, Leung, Hin-Tak, Marchini, Jonathan L, and Morris, Andrew P

Subjects
MAJOR histocompatibility complex, IMMUNOGENETICS, ANKYLOSING spondylitis, AUTOIMMUNE thyroiditis, MULTIPLE sclerosis, BREAST cancer
Abstract

We have genotyped 14,436 nonsynonymous SNPs (nsSNPs) and 897 major histocompatibility complex (MHC) tag SNPs from 1,000 independent cases of ankylosing spondylitis (AS), autoimmune thyroid disease (AITD), multiple sclerosis (MS) and breast cancer (BC). Comparing these data against a common control dataset derived from 1,500 randomly selected healthy British individuals, we report initial association and independent replication in a North American sample of two new loci related to ankylosing spondylitis, ARTS1 and IL23R, and confirmation of the previously reported association of AITD with TSHR and FCRL3. These findings, enabled in part by increased statistical power resulting from the expansion of the control reference group to include individuals from the other disease groups, highlight notable new possibilities for autoimmune regulation and suggest that IL23R may be a common susceptibility factor for the major 'seronegative' diseases. [ABSTRACT FROM AUTHOR]

Published
2007
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35. Identification of loci associated with schizophrenia by genome-wide association and follow-up.

Author

Michael C. O'Donovan, Nicholas Craddock, Nadine Norton, Hywel Williams, Timothy Peirce, Valentina Moskvina, Ivan Nikolov, Marian Hamshere, Liam Carroll, Lyudmila Georgieva, Sarah Dwyer, Peter Holmans, Jonathan L. Marchini, Chris C. A. Spencer, Bryan Howie, Hin-Tak Leung, Annette M. Hartmann, Hans-Jürgen Möller, Derek W. Morris, and YongYong Shi

Subjects
PSYCHOSES, SCHIZOPHRENIA, BIPOLAR disorder, META-analysis, GENETICS
Abstract

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10−5 in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 × 10−4), and the overall pattern of replication was unlikely to occur by chance (P = 9 × 10−8). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 × 10−7) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 × 10−9). [ABSTRACT FROM AUTHOR]

Published
2008
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