27 results on '"Goddard, Michael"'
Search Results
2. Assessing the contribution of rare variants to complex trait heritability from whole-genome sequence data
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Wainschtein, Pierrick, Jain, Deepti, Zheng, Zhili, Cupples, L Adrienne, Shadyab, Aladdin H, McKnight, Barbara, Shoemaker, Benjamin M, Mitchell, Braxton D, Psaty, Bruce M, Kooperberg, Charles, Liu, Ching-Ti, Albert, Christine M, Roden, Dan, Chasman, Daniel I, Darbar, Dawood, Lloyd-Jones, Donald M, Arnett, Donna K, Regan, Elizabeth A, Boerwinkle, Eric, Rotter, Jerome I, O’Connell, Jeffrey R, Yanek, Lisa R, de Andrade, Mariza, Allison, Matthew A, McDonald, Merry-Lynn N, Chung, Mina K, Fornage, Myriam, Chami, Nathalie, Smith, Nicholas L, Ellinor, Patrick T, Vasan, Ramachandran S, Mathias, Rasika A, Loos, Ruth JF, Rich, Stephen S, Lubitz, Steven A, Heckbert, Susan R, Redline, Susan, Guo, Xiuqing, Chen, Y-D Ida, Laurie, Cecelia A, Hernandez, Ryan D, McGarvey, Stephen T, Goddard, Michael E, Laurie, Cathy C, North, Kari E, Lange, Leslie A, Weir, Bruce S, Yengo, Loic, Yang, Jian, and Visscher, Peter M
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Human Genome ,Genetics ,2.1 Biological and endogenous factors ,Aetiology ,Generic health relevance ,Alleles ,Genome-Wide Association Study ,Humans ,Linkage Disequilibrium ,Multifactorial Inheritance ,Polymorphism ,Single Nucleotide ,TOPMed Anthropometry Working Group ,NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium ,Biological Sciences ,Medical and Health Sciences ,Developmental Biology - Abstract
Analyses of data from genome-wide association studies on unrelated individuals have shown that, for human traits and diseases, approximately one-third to two-thirds of heritability is captured by common SNPs. However, it is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular whether the causal variants are rare, or whether it is overestimated due to bias in inference from pedigree data. Here we estimated heritability for height and body mass index (BMI) from whole-genome sequence data on 25,465 unrelated individuals of European ancestry. The estimated heritability was 0.68 (standard error 0.10) for height and 0.30 (standard error 0.10) for body mass index. Low minor allele frequency variants in low linkage disequilibrium (LD) with neighboring variants were enriched for heritability, to a greater extent for protein-altering variants, consistent with negative selection. Our results imply that rare variants, in particular those in regions of low linkage disequilibrium, are a major source of the still missing heritability of complex traits and disease.
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- 2022
3. From Mendel to quantitative genetics in the genome era: the scientific legacy of W. G. Hill
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Charlesworth, Brian, Goddard, Michael E., Meyer, Karin, Visscher, Peter M., Weir, Bruce S., and Wray, Naomi R.
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- 2022
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4. Author Correction: From Mendel to quantitative genetics in the genome era: the scientific legacy of W. G. Hill
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Charlesworth, Brian, Goddard, Michael E., Meyer, Karin, Visscher, Peter M., Weir, Bruce S., and Wray, Naomi R.
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- 2022
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5. Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
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Speliotes, Elizabeth K, Willer, Cristen J, Berndt, Sonja I, Monda, Keri L, Thorleifsson, Gudmar, Jackson, Anne U, Allen, Hana Lango, Lindgren, Cecilia M, Luan, Jian'an, Mägi, Reedik, Randall, Joshua C, Vedantam, Sailaja, Winkler, Thomas W, Qi, Lu, Workalemahu, Tsegaselassie, Heid, Iris M, Steinthorsdottir, Valgerdur, Stringham, Heather M, Weedon, Michael N, Wheeler, Eleanor, Wood, Andrew R, Ferreira, Teresa, Weyant, Robert J, Segrè, Ayellet V, Estrada, Karol, Liang, Liming, Nemesh, James, Park, Ju-Hyun, Gustafsson, Stefan, Kilpeläinen, Tuomas O, Yang, Jian, Bouatia-Naji, Nabila, Esko, Tõnu, Feitosa, Mary F, Kutalik, Zoltán, Mangino, Massimo, Raychaudhuri, Soumya, Scherag, Andre, Smith, Albert Vernon, Welch, Ryan, Zhao, Jing Hua, Aben, Katja K, Absher, Devin M, Amin, Najaf, Dixon, Anna L, Fisher, Eva, Glazer, Nicole L, Goddard, Michael E, Heard-Costa, Nancy L, Hoesel, Volker, Hottenga, Jouke-Jan, Johansson, Åsa, Johnson, Toby, Ketkar, Shamika, Lamina, Claudia, Li, Shengxu, Moffatt, Miriam F, Myers, Richard H, Narisu, Narisu, Perry, John RB, Peters, Marjolein J, Preuss, Michael, Ripatti, Samuli, Rivadeneira, Fernando, Sandholt, Camilla, Scott, Laura J, Timpson, Nicholas J, Tyrer, Jonathan P, van Wingerden, Sophie, Watanabe, Richard M, White, Charles C, Wiklund, Fredrik, Barlassina, Christina, Chasman, Daniel I, Cooper, Matthew N, Jansson, John-Olov, Lawrence, Robert W, Pellikka, Niina, Prokopenko, Inga, Shi, Jianxin, Thiering, Elisabeth, Alavere, Helene, Alibrandi, Maria TS, Almgren, Peter, Arnold, Alice M, Aspelund, Thor, Atwood, Larry D, Balkau, Beverley, Balmforth, Anthony J, Bennett, Amanda J, Ben-Shlomo, Yoav, Bergman, Richard N, Bergmann, Sven, Biebermann, Heike, Blakemore, Alexandra IF, Boes, Tanja, Bonnycastle, Lori L, Bornstein, Stefan R, Brown, Morris J, and Buchanan, Thomas A
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Biological Sciences ,Genetics ,Prevention ,Human Genome ,Body Height ,Body Mass Index ,Body Size ,Body Weight ,Chromosome Mapping ,Genetic Predisposition to Disease ,Genome-Wide Association Study ,Humans ,Obesity ,Polymorphism ,Single Nucleotide ,White People ,MAGIC ,Procardis Consortium ,Medical and Health Sciences ,Developmental Biology ,Agricultural biotechnology ,Bioinformatics and computational biology - Abstract
Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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- 2010
6. Comparison of methods that use whole genome data to estimate the heritability and genetic architecture of complex traits
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Evans, Luke M., Tahmasbi, Rasool, Vrieze, Scott I., Abecasis, Gonçalo R., Das, Sayantan, Gazal, Steven, Bjelland, Douglas W., de Candia, Teresa R., Haplotype Reference Consortium, Goddard, Michael E., Neale, Benjamin M., Yang, Jian, Visscher, Peter M., and Keller, Matthew C.
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- 2018
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7. Concepts, estimation and interpretation of SNP-based heritability
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Yang, Jian, primary, Zeng, Jian, additional, Goddard, Michael E, additional, Wray, Naomi R, additional, and Visscher, Peter M, additional
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- 2017
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8. Risk of psychiatric illness from advanced paternal age is not predominantly from de novo mutations
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Gratten, Jacob, primary, Wray, Naomi R, additional, Peyrot, Wouter J, additional, McGrath, John J, additional, Visscher, Peter M, additional, and Goddard, Michael E, additional
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- 2016
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9. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets
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Zhu, Zhihong, primary, Zhang, Futao, additional, Hu, Han, additional, Bakshi, Andrew, additional, Robinson, Matthew R, additional, Powell, Joseph E, additional, Montgomery, Grant W, additional, Goddard, Michael E, additional, Wray, Naomi R, additional, Visscher, Peter M, additional, and Yang, Jian, additional
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- 2016
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10. Population genetic differentiation of height and body mass index across Europe
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Robinson, Matthew R, primary, Hemani, Gibran, additional, Medina-Gomez, Carolina, additional, Mezzavilla, Massimo, additional, Esko, Tonu, additional, Shakhbazov, Konstantin, additional, Powell, Joseph E, additional, Vinkhuyzen, Anna, additional, Berndt, Sonja I, additional, Gustafsson, Stefan, additional, Justice, Anne E, additional, Kahali, Bratati, additional, Locke, Adam E, additional, Pers, Tune H, additional, Vedantam, Sailaja, additional, Wood, Andrew R, additional, van Rheenen, Wouter, additional, Andreassen, Ole A, additional, Gasparini, Paolo, additional, Metspalu, Andres, additional, Berg, Leonard H van den, additional, Veldink, Jan H, additional, Rivadeneira, Fernando, additional, Werge, Thomas M, additional, Abecasis, Goncalo R, additional, Boomsma, Dorret I, additional, Chasman, Daniel I, additional, de Geus, Eco J C, additional, Frayling, Timothy M, additional, Hirschhorn, Joel N, additional, Hottenga, Jouke Jan, additional, Ingelsson, Erik, additional, Loos, Ruth J F, additional, Magnusson, Patrik K E, additional, Martin, Nicholas G, additional, Montgomery, Grant W, additional, North, Kari E, additional, Pedersen, Nancy L, additional, Spector, Timothy D, additional, Speliotes, Elizabeth K, additional, Goddard, Michael E, additional, Yang, Jian, additional, and Visscher, Peter M, additional
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- 2015
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11. Advantages and pitfalls in the application of mixed-model association methods
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Yang, Jian, primary, Zaitlen, Noah A, additional, Goddard, Michael E, additional, Visscher, Peter M, additional, and Price, Alkes L, additional
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- 2014
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12. Population genetic differentiation of height and body mass index across Europe.
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Mezzavilla, Massimo, Esko, Tonu, Powell, Joseph E, Kahali, Bratati, Pers, Tune H, Vedantam, Sailaja, Gasparini, Paolo, Werge, Thomas M, Boomsma, Dorret I, Chasman, Daniel I, de Geus, Eco J C, Hirschhorn, Joel N, Hottenga, Jouke Jan, Ingelsson, Erik, Loos, Ruth J F, North, Kari E, Goddard, Michael E, Yang, Jian, Visscher, Peter M, and Robinson, Matthew R
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BODY mass index ,GENETIC correlations ,HEIGHT measurement ,HUMAN phenotype ,POPULATION - Abstract
Across-nation differences in the mean values for complex traits are common, but the reasons for these differences are unknown. Here we find that many independent loci contribute to population genetic differences in height and body mass index (BMI) in 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased effect size estimates from 17,500 sibling pairs, we estimate that 24% (95% credible interval (CI) = 9%, 41%) and 8% (95% CI = 4%, 16%) of the captured additive genetic variance for height and BMI, respectively, reflect population genetic differences. Population genetic divergence differed significantly from that in a null model (height, P < 3.94 × 10
−8 ; BMI, P < 5.95 × 10−4 ), and we find an among-population genetic correlation for tall and slender individuals (r = −0.80, 95% CI = −0.95, −0.60), consistent with correlated selection for both phenotypes. Observed differences in height among populations reflected the predicted genetic means (r = 0.51; P < 0.001), but environmental differences across Europe masked genetic differentiation for BMI (P < 0.58). [ABSTRACT FROM AUTHOR]- Published
- 2015
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13. Erratum: Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
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Heid, Iris M, primary, Jackson, Anne U, additional, Randall, Joshua C, additional, Winkler, Thomas W, additional, Qi, Lu, additional, Steinthorsdottir, Valgerdur, additional, Thorleifsson, Gudmar, additional, Zillikens, M Carola, additional, Speliotes, Elizabeth K, additional, Mägi, Reedik, additional, Workalemahu, Tsegaselassie, additional, White, Charles C, additional, Bouatia-Naji, Nabila, additional, Harris, Tamara B, additional, Berndt, Sonja I, additional, Ingelsson, Erik, additional, Willer, Cristen J, additional, Weedon, Michael N, additional, Luan, Jian'an, additional, Vedantam, Sailaja, additional, Esko, Tõnu, additional, Kilpeläinen, Tuomas O, additional, Kutalik, Zoltán, additional, Li, Shengxu, additional, Monda, Keri L, additional, Dixon, Anna L, additional, Holmes, Christopher C, additional, Kaplan, Lee M, additional, Liang, Liming, additional, Min, Josine L, additional, Moffatt, Miriam F, additional, Molony, Cliona, additional, Nicholson, George, additional, Schadt, Eric E, additional, Zondervan, Krina T, additional, Feitosa, Mary F, additional, Ferreira, Teresa, additional, Allen, Hana Lango, additional, Weyant, Robert J, additional, Wheeler, Eleanor, additional, Wood, Andrew R, additional, Estrada, Karol, additional, Goddard, Michael E, additional, Lettre, Guillaume, additional, Mangino, Massimo, additional, Nyholt, Dale R, additional, Purcell, Shaun, additional, Vernon Smith, Albert, additional, Visscher, Peter M, additional, Yang, Jian, additional, McCarroll, Steven A, additional, Nemesh, James, additional, Voight, Benjamin F, additional, Absher, Devin, additional, Amin, Najaf, additional, Aspelund, Thor, additional, Coin, Lachlan, additional, Glazer, Nicole L, additional, Hayward, Caroline, additional, Heard-Costa, Nancy L, additional, Hottenga, Jouke-Jan, additional, Johansson, Åsa, additional, Johnson, Toby, additional, Kaakinen, Marika, additional, Kapur, Karen, additional, Ketkar, Shamika, additional, Knowles, Joshua W, additional, Kraft, Peter, additional, Kraja, Aldi T, additional, Lamina, Claudia, additional, Leitzmann, Michael F, additional, McKnight, Barbara, additional, Morris, Andrew P, additional, Ong, Ken K, additional, Perry, John R B, additional, Peters, Marjolein J, additional, Polasek, Ozren, additional, Prokopenko, Inga, additional, Rayner, Nigel W, additional, Ripatti, Samuli, additional, Rivadeneira, Fernando, additional, Robertson, Neil R, additional, Sanna, Serena, additional, Sovio, Ulla, additional, Surakka, Ida, additional, Teumer, Alexander, additional, van Wingerden, Sophie, additional, Vitart, Veronique, additional, Zhao, Jing Hua, additional, Cavalcanti-Proença, Christine, additional, Chines, Peter S, additional, Fisher, Eva, additional, Kulzer, Jennifer R, additional, Lecoeur, Cecile, additional, Narisu, Narisu, additional, Sandholt, Camilla, additional, Scott, Laura J, additional, Silander, Kaisa, additional, Stark, Klaus, additional, Tammesoo, Mari-Liis, additional, Teslovich, Tanya M, additional, Timpson, Nicholas John, additional, Watanabe, Richard M, additional, Welch, Ryan, additional, Chasman, Daniel I, additional, Cooper, Matthew N, additional, Jansson, John-Olov, additional, Kettunen, Johannes, additional, Lawrence, Robert W, additional, Pellikka, Niina, additional, Perola, Markus, additional, Vandenput, Liesbeth, additional, Alavere, Helene, additional, Almgren, Peter, additional, Atwood, Larry D, additional, Bennett, Amanda J, additional, Biffar, Reiner, additional, Bonnycastle, Lori L, additional, Bornstein, Stefan R, additional, Buchanan, Thomas A, additional, Campbell, Harry, additional, Day, Ian N M, additional, Dei, Mariano, additional, Dörr, Marcus, additional, Elliott, Paul, additional, Erdos, Michael R, additional, Eriksson, Johan G, additional, Freimer, Nelson B, additional, Fu, Mao, additional, Gaget, Stefan, additional, Geus, Eco J C, additional, Gjesing, Anette P, additional, Grallert, Harald, additional, Gräßler, Jürgen, additional, Groves, Christopher J, additional, Guiducci, Candace, additional, Hartikainen, Anna-Liisa, additional, Hassanali, Neelam, additional, Havulinna, Aki S, additional, Herzig, Karl-Heinz, additional, Hicks, Andrew A, additional, Hui, Jennie, additional, Igl, Wilmar, additional, Jousilahti, Pekka, additional, Jula, Antti, additional, Kajantie, Eero, additional, Kinnunen, Leena, additional, Kolcic, Ivana, additional, Koskinen, Seppo, additional, Kovacs, Peter, additional, Kroemer, Heyo K, additional, Krzelj, Vjekoslav, additional, Kuusisto, Johanna, additional, Kvaloy, Kirsti, additional, Laitinen, Jaana, additional, Lantieri, Olivier, additional, Lathrop, G Mark, additional, Lokki, Marja-Liisa, additional, Luben, Robert N, additional, Ludwig, Barbara, additional, McArdle, Wendy L, additional, McCarthy, Anne, additional, Morken, Mario A, additional, Nelis, Mari, additional, Neville, Matt J, additional, Paré, Guillaume, additional, Parker, Alex N, additional, Peden, John F, additional, Pichler, Irene, additional, Pietiläinen, Kirsi H, additional, Platou, Carl G P, additional, Pouta, Anneli, additional, Ridderstråle, Martin, additional, Samani, Nilesh J, additional, Saramies, Jouko, additional, Sinisalo, Juha, additional, Smit, Jan H, additional, Strawbridge, Rona J, additional, Stringham, Heather M, additional, Swift, Amy J, additional, Teder-Laving, Maris, additional, Thomson, Brian, additional, Usala, Gianluca, additional, van Meurs, Joyce B J, additional, van Ommen, Gert-Jan, additional, Vatin, Vincent, additional, Volpato, Claudia B, additional, Wallaschofski, Henri, additional, Walters, G Bragi, additional, Widen, Elisabeth, additional, Wild, Sarah H, additional, Willemsen, Gonneke, additional, Witte, Daniel R, additional, Zgaga, Lina, additional, Zitting, Paavo, additional, Beilby, John P, additional, James, Alan L, additional, Kähönen, Mika, additional, Lehtimäki, Terho, additional, Nieminen, Markku S, additional, Ohlsson, Claes, additional, Palmer, Lyle J, additional, Raitakari, Olli, additional, Ridker, Paul M, additional, Stumvoll, Michael, additional, Tönjes, Anke, additional, Viikari, Jorma, additional, Balkau, Beverley, additional, Ben-Shlomo, Yoav, additional, Bergman, Richard N, additional, Boeing, Heiner, additional, Smith, George Davey, additional, Ebrahim, Shah, additional, Froguel, Philippe, additional, Hansen, Torben, additional, Hengstenberg, Christian, additional, Hveem, Kristian, additional, Isomaa, Bo, additional, Jørgensen, Torben, additional, Karpe, Fredrik, additional, Khaw, Kay-Tee, additional, Laakso, Markku, additional, Lawlor, Debbie A, additional, Marre, Michel, additional, Meitinger, Thomas, additional, Metspalu, Andres, additional, Midthjell, Kristian, additional, Pedersen, Oluf, additional, Salomaa, Veikko, additional, Schwarz, Peter E H, additional, Tuomi, Tiinamaija, additional, Tuomilehto, Jaakko, additional, Valle, Timo T, additional, Wareham, Nicholas J, additional, Arnold, Alice M, additional, Beckmann, Jacques S, additional, Bergmann, Sven, additional, Boerwinkle, Eric, additional, Boomsma, Dorret I, additional, Caulfield, Mark J, additional, Collins, Francis S, additional, Eiriksdottir, Gudny, additional, Gudnason, Vilmundur, additional, Gyllensten, Ulf, additional, Hamsten, Anders, additional, Hattersley, Andrew T, additional, Hofman, Albert, additional, Hu, Frank B, additional, Illig, Thomas, additional, Iribarren, Carlos, additional, Jarvelin, Marjo-Riitta, additional, Kao, W H Linda, additional, Kaprio, Jaakko, additional, Launer, Lenore J, additional, Munroe, Patricia B, additional, Oostra, Ben, additional, Penninx, Brenda W, additional, Pramstaller, Peter P, additional, Psaty, Bruce M, additional, Quertermous, Thomas, additional, Rissanen, Aila, additional, Rudan, Igor, additional, Shuldiner, Alan R, additional, Soranzo, Nicole, additional, Spector, Timothy D, additional, Syvanen, Ann-Christine, additional, Uda, Manuela, additional, Uitterlinden, André, additional, Völzke, Henry, additional, Vollenweider, Peter, additional, Wilson, James F, additional, Witteman, Jacqueline C, additional, Wright, Alan F, additional, Abecasis, Gonçalo R, additional, Boehnke, Michael, additional, Borecki, Ingrid B, additional, Deloukas, Panos, additional, Frayling, Timothy M, additional, Groop, Leif C, additional, Haritunians, Talin, additional, Hunter, David J, additional, Kaplan, Robert C, additional, North, Kari E, additional, O'Connell, Jeffrey R, additional, Peltonen, Leena, additional, Schlessinger, David, additional, Strachan, David P, additional, Hirschhorn, Joel N, additional, Assimes, Themistocles L, additional, Wichmann, H-Erich, additional, Thorsteinsdottir, Unnur, additional, van Duijn, Cornelia M, additional, Stefansson, Kari, additional, Cupples, L Adrienne, additional, Loos, Ruth J F, additional, Barroso, Inês, additional, McCarthy, Mark I, additional, Fox, Caroline S, additional, Mohlke, Karen L, additional, and Lindgren, Cecilia M, additional
- Published
- 2011
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14. Genome partitioning of genetic variation for complex traits using common SNPs
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Yang, Jian, primary, Manolio, Teri A, additional, Pasquale, Louis R, additional, Boerwinkle, Eric, additional, Caporaso, Neil, additional, Cunningham, Julie M, additional, de Andrade, Mariza, additional, Feenstra, Bjarke, additional, Feingold, Eleanor, additional, Hayes, M Geoffrey, additional, Hill, William G, additional, Landi, Maria Teresa, additional, Alonso, Alvaro, additional, Lettre, Guillaume, additional, Lin, Peng, additional, Ling, Hua, additional, Lowe, William, additional, Mathias, Rasika A, additional, Melbye, Mads, additional, Pugh, Elizabeth, additional, Cornelis, Marilyn C, additional, Weir, Bruce S, additional, Goddard, Michael E, additional, and Visscher, Peter M, additional
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- 2011
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15. Cattle gain stature
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Visscher, Peter M, primary and Goddard, Michael E, additional
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- 2011
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16. Common SNPs explain a large proportion of the heritability for human height
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Yang, Jian, primary, Benyamin, Beben, additional, McEvoy, Brian P, additional, Gordon, Scott, additional, Henders, Anjali K, additional, Nyholt, Dale R, additional, Madden, Pamela A, additional, Heath, Andrew C, additional, Martin, Nicholas G, additional, Montgomery, Grant W, additional, Goddard, Michael E, additional, and Visscher, Peter M, additional
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- 2010
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17. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.
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Perry, John R B, Nolte, Ilja M, Snieder, Harold, Milani, Lili, Mägi, Reedik, Hamsten, Anders, Esko, Tonu, Metspalu, Andres, Ingelsson, Erik, Soranzo, Nicole, Keller, Matthew C, Goddard, Michael E, Visscher, Peter M, Bakshi, Andrew, Zhu, Zhihong, Vinkhuyzen, Anna A E, Robinson, Matthew R, Wray, Naomi R, Magnusson, Patrik K E, and Pedersen, Nancy L
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HERITABILITY ,BODY mass index ,GENOME editing ,STATURE ,HUMAN genetics - Abstract
We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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18. Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs.
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Lee, S Hong, Ripke, Stephan, Neale, Benjamin M, Faraone, Stephen V, Purcell, Shaun M, Perlis, Roy H, Mowry, Bryan J, Thapar, Anita, Goddard, Michael E, Witte, John S, Absher, Devin, Agartz, Ingrid, Akil, Huda, Amin, Farooq, Andreassen, Ole A, Anjorin, Adebayo, Anney, Richard, Anttila, Verneri, Arking, Dan E, and Asherson, Philip
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MENTAL illness genetics ,PATHOLOGICAL physiology ,SINGLE nucleotide polymorphisms ,HUMAN genetic variation ,ETIOLOGY of diseases ,EMPIRICAL research - Abstract
Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders. [ABSTRACT FROM AUTHOR]
- Published
- 2013
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19. Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits.
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Yang, Jian, Ferreira, Teresa, Morris, Andrew P, Medland, Sarah E, Madden, Pamela A F, Heath, Andrew C, Martin, Nicholas G, Montgomery, Grant W, Weedon, Michael N, Loos, Ruth J, Frayling, Timothy M, McCarthy, Mark I, Hirschhorn, Joel N, Goddard, Michael E, and Visscher, Peter M
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GENETICS of type 2 diabetes ,GENOMICS ,LINKAGE disequilibrium ,META-analysis ,GENOTYPE-environment interaction ,BODY mass index - Abstract
We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium. [ABSTRACT FROM AUTHOR]
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- 2012
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20. Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs.
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Lee, S Hong, DeCandia, Teresa R, Ripke, Stephan, Yang, Jian, Sullivan, Patrick F, Goddard, Michael E, Keller, Matthew C, Visscher, Peter M, and Wray, Naomi R
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DISEASE susceptibility ,SCHIZOPHRENIA ,GENETICS ,GENOMES ,CENTRAL nervous system - Abstract
Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (PGC-SCZ), we estimate that 23% (s.e. = 1%) of variation in liability to schizophrenia is captured by SNPs. We show that a substantial proportion of this variation must be the result of common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, P = 2.6 × 10
?8 ), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2,725 genes expressed in the central nervous system (CNS; P = 7.6 × 10?8 ). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases. [ABSTRACT FROM AUTHOR]- Published
- 2012
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- View/download PDF
21. Common SNPs explain a large proportion of the heritability for human height.
- Author
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Jian Yang, Benyamin, Beben, McEvoy, Brian P, Gordon, Scott, Henders, Anjali K, Nyholt, Dale R, Madden, Pamela A, Heath, Andrew C, Martin, Nicholas G, Montgomery, Grant W, Goddard, Michael E, and Visscher, Peter M
- Subjects
HERITABILITY ,HUMAN genetic variation ,GENOMICS ,STATURE ,LINEAR statistical models ,SIMULATION methods & models - Abstract
SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date. [ABSTRACT FROM AUTHOR]
- Published
- 2010
- Full Text
- View/download PDF
22. Estimating the proportion of variation in susceptibility to schizophrenia captured by common SNPs
- Author
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Stephan Ripke, Patrick F. Sullivan, Teresa R. DeCandia, Matthew C. Keller, Naomi R. Wray, Peter M. Visscher, Michael E. Goddard, S. Hong Lee, Jian Yang, Lee, S Hong, DeCandia, Teresa R, Ripke, Stephan, Yang, Jian, Sullivan, Patrick F, Goddard, Michael E, Keller, Matthew C, Visscher, Peter M, Wray, Naomi R, Schizophrenia Psychiatric Genome-Wide Association Study Consortium (PGC-SCZ), International Schizophrenia Consortium (ISC), and Molecular Genetics of Schizophrenia Collaboration (MGS)
- Subjects
Central Nervous System ,Male ,Multifactorial Inheritance ,SNP ,Single-nucleotide polymorphism ,Genome-wide association study ,Biology ,heritability ,genomic variance ,Polymorphism, Single Nucleotide ,Article ,03 medical and health sciences ,0302 clinical medicine ,Polymorphism (computer science) ,Genetic variation ,Genetics ,medicine ,GWAS ,Chromosomes, Human ,Humans ,Computer Simulation ,Genetic Predisposition to Disease ,Human height ,030304 developmental biology ,Genetics & Heredity ,0303 health sciences ,Analysis of Variance ,Likelihood Functions ,Models, Genetic ,Genetic Variation ,Molecular Sequence Annotation ,medicine.disease ,Explained variation ,schizophrenia ,multiple rare alleles ,Schizophrenia ,missing heritability ,Linear Models ,disease genetics ,Female ,Analysis of variance ,030217 neurology & neurosurgery ,SNPs ,Genome-Wide Association Study - Abstract
Schizophrenia is a complex disorder caused by both genetic and environmental factors. Using 9,087 affected individuals, 12,171 controls and 915,354 imputed SNPs from the Schizophrenia Psychiatric Genome-Wide Association Study (GWAS) Consortium (PGC-SCZ), we estimate that 23% (s.e. = 1%) of variation in liability to schizophrenia is captured by SNPs. We show that a substantial proportion of this variation must be the result of common causal variants, that the variance explained by each chromosome is linearly related to its length (r = 0.89, P = 2.6 x 10(-8)), that the genetic basis of schizophrenia is the same in males and females, and that a disproportionate proportion of variation is attributable to a set of 2,725 genes expressed in the central nervous system (CNS; P = 7.6 x 10(-8)). These results are consistent with a polygenic genetic architecture and imply more individual SNP associations will be detected for this disease as sample size increases. Refereed/Peer-reviewed
- Published
- 2012
23. Common SNPs explain a large proportion of the heritability for human height
- Author
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Pamela A. F. Madden, Beben Benyamin, Andrew C. Heath, Scott D. Gordon, Jian Yang, Grant W. Montgomery, Brian P. McEvoy, Dale R. Nyholt, Michael E. Goddard, Anjali K. Henders, Peter M. Visscher, Nicholas G. Martin, Yang, Jian, Benyamin, Beben, McEvoy, Brian P, Gordon, Scott, Henders, Anjali K, Nyholt, Dale R, Madden, Pamela A, Heath, Andrew C, Martin, Nicholas G, Montgomery, Grant W, Goddard, Michael E, and Visscher, Peter M
- Subjects
Adult ,Male ,Linkage disequilibrium ,Adolescent ,Genotype ,Genome-wide association study ,Biology ,Polymorphism, Single Nucleotide ,Article ,Linkage Disequilibrium ,Young Adult ,Gene Frequency ,Missing heritability problem ,Genetics ,Humans ,Genetic Predisposition to Disease ,Human height ,Allele frequency ,Aged ,Genetic association ,Aged, 80 and over ,Models, Genetic ,Genome, Human ,Middle Aged ,Heritability ,Body Height ,Minor allele frequency ,Logistic Models ,Female ,Algorithms ,Genome-Wide Association Study - Abstract
Recently a paper authored by ourselves and a number of co-authors about the proportion of phenotypic variation in height that is explained by common SNPs was published in Nature Genetics (Yang et al., 2010). Common SNPs explain a large proportion of the heritability for human height (Yang et al.). During the refereeing process (the paper was rejected by two other journals before publication in Nature Genetics) and following the publication of Yang et al. (2010) it became clear to us that the methodology we applied, the interpretation of the results and the consequences of the findings on the genetic architecture of human height and that for other traits such as complex disease are not well understood or appreciated. Here we explain some of these issues in a style that is different from the primary publication, that is, in the form of a number of comments and questions and answers. We also report a number of additional results that show that the estimates of additive genetic variation are not driven by population structure.
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- 2010
24. Population genetic differentiation of height and body mass index across Europe
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Joel N. Hirschhorn, Elizabeth K. Speliotes, Michael E. Goddard, Anne E. Justice, Sonja I. Berndt, Peter M. Visscher, Leonard H. van den Berg, Erik Ingelsson, Sailaja Vedantam, Jan H. Veldink, Kari E. North, Matthew R. Robinson, Dorret I. Boomsma, Ruth J. F. Loos, Konstantin Shakhbazov, Gibran Hemani, Carolina Medina-Gomez, Andrew R. Wood, Joseph E. Powell, Massimo Mezzavilla, Jouke-Jan Hottenga, Gonçalo R. Abecasis, Tõnu Esko, Paolo Gasparini, Adam E. Locke, Tim D. Spector, Nancy L. Pedersen, Stefan Gustafsson, Jian Yang, Eco J. C. de Geus, Timothy M. Frayling, Grant W. Montgomery, Nicholas G. Martin, Thomas Werge, Tune H. Pers, Fernando Rivadeneira, Anna A. E. Vinkhuyzen, Andres Metspalu, Wouter van Rheenen, Patrik K. E. Magnusson, Bratati Kahali, Ole A. Andreassen, Daniel I. Chasman, Robinson, Matthew R, Hemani, Gibran, Medina Gomez, Carolina, Mezzavilla, Massimo, Esko, Tonu, Shakhbazov, Konstantin, Powell, Joseph E., Vinkhuyzen, Anna, Berndt, Sonja I., Gustafsson, Stefan, Justice, Anne E., Kahali, Bratati, Locke, Adam E., Pers, Tune H., Vedantam, Sailaja, Wood, Andrew R., Van Rheenen, Wouter, Andreassen, Ole A., Gasparini, Paolo, Metspalu, Andre, Van Den Berg, Leonard H., Veldink, Jan H., Rivadeneira, Fernando, Werge, Thomas M., Abecasis, Goncalo R., Boomsma, Dorret I., Chasman, Daniel I., De Geus, Eco J. C., Frayling, Timothy M., Hirschhorn, Joel N., Hottenga, Jouke Jan, Ingelsson, Erik, Loos, Ruth J. F., Magnusson, Patrik K. E., Martin, Nicholas G., Montgomery, Grant W., North, Kari E., Pedersen, Nancy L., Spector, Timothy D., Speliotes, Elizabeth K., Goddard, Michael E., Yang, Jian, Visscher, Peter M., Internal Medicine, Epidemiology, Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, and EMGO+ - Lifestyle, Overweight and Diabetes
- Subjects
Netherlands Twin Register (NTR) ,Population genetics ,Genome-wide association study ,Body Mass Index ,0302 clinical medicine ,Models ,Principal Component Analysi ,Gene–environment interaction ,2. Zero hunger ,Genetics ,0303 health sciences ,education.field_of_study ,Principal Component Analysis ,Geography ,Algorithms ,Body Height ,Europe ,Gene Expression Profiling ,Gene-Environment Interaction ,Genetics, Population ,Genome-Wide Association Study ,Genotype ,Humans ,Models, Genetic ,Phenotype ,Polymorphism, Single Nucleotide ,Genetic Variation ,Single Nucleotide ,Algorithm ,Medical Genetics ,Human ,Population ,Biology ,Genetic correlation ,Article ,03 medical and health sciences ,Genetic ,Genetic variation ,Polymorphism ,education ,030304 developmental biology ,Medicinsk genetik ,Genetic divergence ,Body mass index ,030217 neurology & neurosurgery ,Demography - Abstract
Across-nation differences in the mean of complex traits such as obesity and stature are common1–8, but the reasons for these differences are not known. Here, we find evidence that many independent loci of small effect combine to create population genetic differences in height and body mass index (BMI) in a sample of 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased estimates of effect sizes from 17,500 sib pairs, we estimate that 24% (95% CI: 9%, 41%) and 8% (95% CI: 4%, 16%) of the captured additive genetic variance for height and BMI across Europe are attributed to among-population genetic differences. Population genetic divergence differed significantly from that expected under a null model (P
- Published
- 2015
25. Genetic variance estimation with imputed variants finds negligible missing heritability for human height and body mass index.
- Author
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Yang J, Bakshi A, Zhu Z, Hemani G, Vinkhuyzen AA, Lee SH, Robinson MR, Perry JR, Nolte IM, van Vliet-Ostaptchouk JV, Snieder H, Esko T, Milani L, Mägi R, Metspalu A, Hamsten A, Magnusson PK, Pedersen NL, Ingelsson E, Soranzo N, Keller MC, Wray NR, Goddard ME, and Visscher PM
- Subjects
- Genome, Human, Humans, Body Height genetics, Body Mass Index, Genetic Variation
- Abstract
We propose a method (GREML-LDMS) to estimate heritability for human complex traits in unrelated individuals using whole-genome sequencing data. We demonstrate using simulations based on whole-genome sequencing data that ∼97% and ∼68% of variation at common and rare variants, respectively, can be captured by imputation. Using the GREML-LDMS method, we estimate from 44,126 unrelated individuals that all ∼17 million imputed variants explain 56% (standard error (s.e.) = 2.3%) of variance for height and 27% (s.e. = 2.5%) of variance for body mass index (BMI), and we find evidence that height- and BMI-associated variants have been under natural selection. Considering the imperfect tagging of imputation and potential overestimation of heritability from previous family-based studies, heritability is likely to be 60-70% for height and 30-40% for BMI. Therefore, the missing heritability is small for both traits. For further discovery of genes associated with complex traits, a study design with SNP arrays followed by imputation is more cost-effective than whole-genome sequencing at current prices.
- Published
- 2015
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26. Defining the role of common variation in the genomic and biological architecture of adult human height.
- Author
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Wood AR, Esko T, Yang J, Vedantam S, Pers TH, Gustafsson S, Chu AY, Estrada K, Luan J, Kutalik Z, Amin N, Buchkovich ML, Croteau-Chonka DC, Day FR, Duan Y, Fall T, Fehrmann R, Ferreira T, Jackson AU, Karjalainen J, Lo KS, Locke AE, Mägi R, Mihailov E, Porcu E, Randall JC, Scherag A, Vinkhuyzen AA, Westra HJ, Winkler TW, Workalemahu T, Zhao JH, Absher D, Albrecht E, Anderson D, Baron J, Beekman M, Demirkan A, Ehret GB, Feenstra B, Feitosa MF, Fischer K, Fraser RM, Goel A, Gong J, Justice AE, Kanoni S, Kleber ME, Kristiansson K, Lim U, Lotay V, Lui JC, Mangino M, Mateo Leach I, Medina-Gomez C, Nalls MA, Nyholt DR, Palmer CD, Pasko D, Pechlivanis S, Prokopenko I, Ried JS, Ripke S, Shungin D, Stancáková A, Strawbridge RJ, Sung YJ, Tanaka T, Teumer A, Trompet S, van der Laan SW, van Setten J, Van Vliet-Ostaptchouk JV, Wang Z, Yengo L, Zhang W, Afzal U, Arnlöv J, Arscott GM, Bandinelli S, Barrett A, Bellis C, Bennett AJ, Berne C, Blüher M, Bolton JL, Böttcher Y, Boyd HA, Bruinenberg M, Buckley BM, Buyske S, Caspersen IH, Chines PS, Clarke R, Claudi-Boehm S, Cooper M, Daw EW, De Jong PA, Deelen J, Delgado G, Denny JC, Dhonukshe-Rutten R, Dimitriou M, Doney AS, Dörr M, Eklund N, Eury E, Folkersen L, Garcia ME, Geller F, Giedraitis V, Go AS, Grallert H, Grammer TB, Gräßler J, Grönberg H, de Groot LC, Groves CJ, Haessler J, Hall P, Haller T, Hallmans G, Hannemann A, Hartman CA, Hassinen M, Hayward C, Heard-Costa NL, Helmer Q, Hemani G, Henders AK, Hillege HL, Hlatky MA, Hoffmann W, Hoffmann P, Holmen O, Houwing-Duistermaat JJ, Illig T, Isaacs A, James AL, Jeff J, Johansen B, Johansson Å, Jolley J, Juliusdottir T, Junttila J, Kho AN, Kinnunen L, Klopp N, Kocher T, Kratzer W, Lichtner P, Lind L, Lindström J, Lobbens S, Lorentzon M, Lu Y, Lyssenko V, Magnusson PK, Mahajan A, Maillard M, McArdle WL, McKenzie CA, McLachlan S, McLaren PJ, Menni C, Merger S, Milani L, Moayyeri A, Monda KL, Morken MA, Müller G, Müller-Nurasyid M, Musk AW, Narisu N, Nauck M, Nolte IM, Nöthen MM, Oozageer L, Pilz S, Rayner NW, Renstrom F, Robertson NR, Rose LM, Roussel R, Sanna S, Scharnagl H, Scholtens S, Schumacher FR, Schunkert H, Scott RA, Sehmi J, Seufferlein T, Shi J, Silventoinen K, Smit JH, Smith AV, Smolonska J, Stanton AV, Stirrups K, Stott DJ, Stringham HM, Sundström J, Swertz MA, Syvänen AC, Tayo BO, Thorleifsson G, Tyrer JP, van Dijk S, van Schoor NM, van der Velde N, van Heemst D, van Oort FV, Vermeulen SH, Verweij N, Vonk JM, Waite LL, Waldenberger M, Wennauer R, Wilkens LR, Willenborg C, Wilsgaard T, Wojczynski MK, Wong A, Wright AF, Zhang Q, Arveiler D, Bakker SJ, Beilby J, Bergman RN, Bergmann S, Biffar R, Blangero J, Boomsma DI, Bornstein SR, Bovet P, Brambilla P, Brown MJ, Campbell H, Caulfield MJ, Chakravarti A, Collins R, Collins FS, Crawford DC, Cupples LA, Danesh J, de Faire U, den Ruijter HM, Erbel R, Erdmann J, Eriksson JG, Farrall M, Ferrannini E, Ferrières J, Ford I, Forouhi NG, Forrester T, Gansevoort RT, Gejman PV, Gieger C, Golay A, Gottesman O, Gudnason V, Gyllensten U, Haas DW, Hall AS, Harris TB, Hattersley AT, Heath AC, Hengstenberg C, Hicks AA, Hindorff LA, Hingorani AD, Hofman A, Hovingh GK, Humphries SE, Hunt SC, Hypponen E, Jacobs KB, Jarvelin MR, Jousilahti P, Jula AM, Kaprio J, Kastelein JJ, Kayser M, Kee F, Keinanen-Kiukaanniemi SM, Kiemeney LA, Kooner JS, Kooperberg C, Koskinen S, Kovacs P, Kraja AT, Kumari M, Kuusisto J, Lakka TA, Langenberg C, Le Marchand L, Lehtimäki T, Lupoli S, Madden PA, Männistö S, Manunta P, Marette A, Matise TC, McKnight B, Meitinger T, Moll FL, Montgomery GW, Morris AD, Morris AP, Murray JC, Nelis M, Ohlsson C, Oldehinkel AJ, Ong KK, Ouwehand WH, Pasterkamp G, Peters A, Pramstaller PP, Price JF, Qi L, Raitakari OT, Rankinen T, Rao DC, Rice TK, Ritchie M, Rudan I, Salomaa V, Samani NJ, Saramies J, Sarzynski MA, Schwarz PE, Sebert S, Sever P, Shuldiner AR, Sinisalo J, Steinthorsdottir V, Stolk RP, Tardif JC, Tönjes A, Tremblay A, Tremoli E, Virtamo J, Vohl MC, Amouyel P, Asselbergs FW, Assimes TL, Bochud M, Boehm BO, Boerwinkle E, Bottinger EP, Bouchard C, Cauchi S, Chambers JC, Chanock SJ, Cooper RS, de Bakker PI, Dedoussis G, Ferrucci L, Franks PW, Froguel P, Groop LC, Haiman CA, Hamsten A, Hayes MG, Hui J, Hunter DJ, Hveem K, Jukema JW, Kaplan RC, Kivimaki M, Kuh D, Laakso M, Liu Y, Martin NG, März W, Melbye M, Moebus S, Munroe PB, Njølstad I, Oostra BA, Palmer CN, Pedersen NL, Perola M, Pérusse L, Peters U, Powell JE, Power C, Quertermous T, Rauramaa R, Reinmaa E, Ridker PM, Rivadeneira F, Rotter JI, Saaristo TE, Saleheen D, Schlessinger D, Slagboom PE, Snieder H, Spector TD, Strauch K, Stumvoll M, Tuomilehto J, Uusitupa M, van der Harst P, Völzke H, Walker M, Wareham NJ, Watkins H, Wichmann HE, Wilson JF, Zanen P, Deloukas P, Heid IM, Lindgren CM, Mohlke KL, Speliotes EK, Thorsteinsdottir U, Barroso I, Fox CS, North KE, Strachan DP, Beckmann JS, Berndt SI, Boehnke M, Borecki IB, McCarthy MI, Metspalu A, Stefansson K, Uitterlinden AG, van Duijn CM, Franke L, Willer CJ, Price AL, Lettre G, Loos RJ, Weedon MN, Ingelsson E, O'Connell JR, Abecasis GR, Chasman DI, Goddard ME, Visscher PM, Hirschhorn JN, and Frayling TM
- Subjects
- Adult, Analysis of Variance, Genetics, Population, Genome-Wide Association Study methods, Humans, Oligonucleotide Array Sequence Analysis, Body Height genetics, Genetic Variation genetics, Polymorphism, Single Nucleotide genetics, White People genetics
- Abstract
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
- Published
- 2014
- Full Text
- View/download PDF
27. Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution.
- Author
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Heid IM, Jackson AU, Randall JC, Winkler TW, Qi L, Steinthorsdottir V, Thorleifsson G, Zillikens MC, Speliotes EK, Mägi R, Workalemahu T, White CC, Bouatia-Naji N, Harris TB, Berndt SI, Ingelsson E, Willer CJ, Weedon MN, Luan J, Vedantam S, Esko T, Kilpeläinen TO, Kutalik Z, Li S, Monda KL, Dixon AL, Holmes CC, Kaplan LM, Liang L, Min JL, Moffatt MF, Molony C, Nicholson G, Schadt EE, Zondervan KT, Feitosa MF, Ferreira T, Lango Allen H, Weyant RJ, Wheeler E, Wood AR, Estrada K, Goddard ME, Lettre G, Mangino M, Nyholt DR, Purcell S, Smith AV, Visscher PM, Yang J, McCarroll SA, Nemesh J, Voight BF, Absher D, Amin N, Aspelund T, Coin L, Glazer NL, Hayward C, Heard-Costa NL, Hottenga JJ, Johansson A, Johnson T, Kaakinen M, Kapur K, Ketkar S, Knowles JW, Kraft P, Kraja AT, Lamina C, Leitzmann MF, McKnight B, Morris AP, Ong KK, Perry JR, Peters MJ, Polasek O, Prokopenko I, Rayner NW, Ripatti S, Rivadeneira F, Robertson NR, Sanna S, Sovio U, Surakka I, Teumer A, van Wingerden S, Vitart V, Zhao JH, Cavalcanti-Proença C, Chines PS, Fisher E, Kulzer JR, Lecoeur C, Narisu N, Sandholt C, Scott LJ, Silander K, Stark K, Tammesoo ML, Teslovich TM, Timpson NJ, Watanabe RM, Welch R, Chasman DI, Cooper MN, Jansson JO, Kettunen J, Lawrence RW, Pellikka N, Perola M, Vandenput L, Alavere H, Almgren P, Atwood LD, Bennett AJ, Biffar R, Bonnycastle LL, Bornstein SR, Buchanan TA, Campbell H, Day IN, Dei M, Dörr M, Elliott P, Erdos MR, Eriksson JG, Freimer NB, Fu M, Gaget S, Geus EJ, Gjesing AP, Grallert H, Grässler J, Groves CJ, Guiducci C, Hartikainen AL, Hassanali N, Havulinna AS, Herzig KH, Hicks AA, Hui J, Igl W, Jousilahti P, Jula A, Kajantie E, Kinnunen L, Kolcic I, Koskinen S, Kovacs P, Kroemer HK, Krzelj V, Kuusisto J, Kvaloy K, Laitinen J, Lantieri O, Lathrop GM, Lokki ML, Luben RN, Ludwig B, McArdle WL, McCarthy A, Morken MA, Nelis M, Neville MJ, Paré G, Parker AN, Peden JF, Pichler I, Pietiläinen KH, Platou CG, Pouta A, Ridderstråle M, Samani NJ, Saramies J, Sinisalo J, Smit JH, Strawbridge RJ, Stringham HM, Swift AJ, Teder-Laving M, Thomson B, Usala G, van Meurs JB, van Ommen GJ, Vatin V, Volpato CB, Wallaschofski H, Walters GB, Widen E, Wild SH, Willemsen G, Witte DR, Zgaga L, Zitting P, Beilby JP, James AL, Kähönen M, Lehtimäki T, Nieminen MS, Ohlsson C, Palmer LJ, Raitakari O, Ridker PM, Stumvoll M, Tönjes A, Viikari J, Balkau B, Ben-Shlomo Y, Bergman RN, Boeing H, Smith GD, Ebrahim S, Froguel P, Hansen T, Hengstenberg C, Hveem K, Isomaa B, Jørgensen T, Karpe F, Khaw KT, Laakso M, Lawlor DA, Marre M, Meitinger T, Metspalu A, Midthjell K, Pedersen O, Salomaa V, Schwarz PE, Tuomi T, Tuomilehto J, Valle TT, Wareham NJ, Arnold AM, Beckmann JS, Bergmann S, Boerwinkle E, Boomsma DI, Caulfield MJ, Collins FS, Eiriksdottir G, Gudnason V, Gyllensten U, Hamsten A, Hattersley AT, Hofman A, Hu FB, Illig T, Iribarren C, Jarvelin MR, Kao WH, Kaprio J, Launer LJ, Munroe PB, Oostra B, Penninx BW, Pramstaller PP, Psaty BM, Quertermous T, Rissanen A, Rudan I, Shuldiner AR, Soranzo N, Spector TD, Syvanen AC, Uda M, Uitterlinden A, Völzke H, Vollenweider P, Wilson JF, Witteman JC, Wright AF, Abecasis GR, Boehnke M, Borecki IB, Deloukas P, Frayling TM, Groop LC, Haritunians T, Hunter DJ, Kaplan RC, North KE, O'Connell JR, Peltonen L, Schlessinger D, Strachan DP, Hirschhorn JN, Assimes TL, Wichmann HE, Thorsteinsdottir U, van Duijn CM, Stefansson K, Cupples LA, Loos RJ, Barroso I, McCarthy MI, Fox CS, Mohlke KL, and Lindgren CM
- Subjects
- Adipose Tissue anatomy & histology, Age Factors, Chromosome Mapping, Female, Genome, Human, Humans, Male, Meta-Analysis as Topic, Sex Characteristics, Genome-Wide Association Study, Polymorphism, Single Nucleotide, Waist-Hip Ratio
- Abstract
Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
- Published
- 2010
- Full Text
- View/download PDF
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