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1.  New loci associated with birth weight identify genetic links between intrauterine growth and adult height and metabolism 
Horikoshi, Momoko | Yaghootkar, Hanieh | Mook-Kanamori, Dennis O. | Sovio, Ulla | Taal, H. Rob | Hennig, Branwen J. | Bradfield, Jonathan P. | St. Pourcain, Beate | Evans, David M. | Charoen, Pimphen | Kaakinen, Marika | Cousminer, Diana L. | Lehtimäki, Terho | Kreiner-Møller, Eskil | Warrington, Nicole M. | Bustamante, Mariona | Feenstra, Bjarke | Berry, Diane J. | Thiering, Elisabeth | Pfab, Thiemo | Barton, Sheila J. | Shields, Beverley M. | Kerkhof, Marjan | van Leeuwen, Elisabeth M. | Fulford, Anthony J. | Kutalik, Zoltán | Zhao, Jing Hua | den Hoed, Marcel | Mahajan, Anubha | Lindi, Virpi | Goh, Liang-Kee | Hottenga, Jouke-Jan | Wu, Ying | Raitakari, Olli T. | Harder, Marie N. | Meirhaeghe, Aline | Ntalla, Ioanna | Salem, Rany M. | Jameson, Karen A. | Zhou, Kaixin | Monies, Dorota M. | Lagou, Vasiliki | Kirin, Mirna | Heikkinen, Jani | Adair, Linda S. | Alkuraya, Fowzan S. | Al-Odaib, Ali | Amouyel, Philippe | Andersson, Ehm Astrid | Bennett, Amanda J. | Blakemore, Alexandra I.F. | Buxton, Jessica L. | Dallongeville, Jean | Das, Shikta | de Geus, Eco J. C. | Estivill, Xavier | Flexeder, Claudia | Froguel, Philippe | Geller, Frank | Godfrey, Keith M. | Gottrand, Frédéric | Groves, Christopher J. | Hansen, Torben | Hirschhorn, Joel N. | Hofman, Albert | Hollegaard, Mads V. | Hougaard, David M. | Hyppönen, Elina | Inskip, Hazel M. | Isaacs, Aaron | Jørgensen, Torben | Kanaka-Gantenbein, Christina | Kemp, John P. | Kiess, Wieland | Kilpeläinen, Tuomas O. | Klopp, Norman | Knight, Bridget A. | Kuzawa, Christopher W. | McMahon, George | Newnham, John P. | Niinikoski, Harri | Oostra, Ben A. | Pedersen, Louise | Postma, Dirkje S. | Ring, Susan M. | Rivadeneira, Fernando | Robertson, Neil R. | Sebert, Sylvain | Simell, Olli | Slowinski, Torsten | Tiesler, Carla M.T. | Tönjes, Anke | Vaag, Allan | Viikari, Jorma S. | Vink, Jacqueline M. | Vissing, Nadja Hawwa | Wareham, Nicholas J. | Willemsen, Gonneke | Witte, Daniel R. | Zhang, Haitao | Zhao, Jianhua | Wilson, James F. | Stumvoll, Michael | Prentice, Andrew M. | Meyer, Brian F. | Pearson, Ewan R. | Boreham, Colin A.G. | Cooper, Cyrus | Gillman, Matthew W. | Dedoussis, George V. | Moreno, Luis A | Pedersen, Oluf | Saarinen, Maiju | Mohlke, Karen L. | Boomsma, Dorret I. | Saw, Seang-Mei | Lakka, Timo A. | Körner, Antje | Loos, Ruth J.F. | Ong, Ken K. | Vollenweider, Peter | van Duijn, Cornelia M. | Koppelman, Gerard H. | Hattersley, Andrew T. | Holloway, John W. | Hocher, Berthold | Heinrich, Joachim | Power, Chris | Melbye, Mads | Guxens, Mònica | Pennell, Craig E. | Bønnelykke, Klaus | Bisgaard, Hans | Eriksson, Johan G. | Widén, Elisabeth | Hakonarson, Hakon | Uitterlinden, André G. | Pouta, Anneli | Lawlor, Debbie A. | Smith, George Davey | Frayling, Timothy M. | McCarthy, Mark I. | Grant, Struan F.A. | Jaddoe, Vincent W.V. | Jarvelin, Marjo-Riitta | Timpson, Nicholas J. | Prokopenko, Inga | Freathy, Rachel M.
Nature genetics  2012;45(1):76-82.
Birth weight within the normal range is associated with a variety of adult-onset diseases, but the mechanisms behind these associations are poorly understood1. Previous genome-wide association studies identified a variant in the ADCY5 gene associated both with birth weight and type 2 diabetes, and a second variant, near CCNL1, with no obvious link to adult traits2. In an expanded genome-wide association meta-analysis and follow-up study (up to 69,308 individuals of European descent from 43 studies), we have now extended the number of genome-wide significant loci to seven, accounting for a similar proportion of variance to maternal smoking. Five of the loci are known to be associated with other phenotypes: ADCY5 and CDKAL1 with type 2 diabetes; ADRB1 with adult blood pressure; and HMGA2 and LCORL with adult height. Our findings highlight genetic links between fetal growth and postnatal growth and metabolism.
doi:10.1038/ng.2477
PMCID: PMC3605762  PMID: 23202124
2.  Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways 
Scott, Robert A | Lagou, Vasiliki | Welch, Ryan P | Wheeler, Eleanor | Montasser, May E | Luan, Jian’an | Mägi, Reedik | Strawbridge, Rona J | Rehnberg, Emil | Gustafsson, Stefan | Kanoni, Stavroula | Rasmussen-Torvik, Laura J | Yengo, Loïc | Lecoeur, Cecile | Shungin, Dmitry | Sanna, Serena | Sidore, Carlo | Johnson, Paul C D | Jukema, J Wouter | Johnson, Toby | Mahajan, Anubha | Verweij, Niek | Thorleifsson, Gudmar | Hottenga, Jouke-Jan | Shah, Sonia | Smith, Albert V | Sennblad, Bengt | Gieger, Christian | Salo, Perttu | Perola, Markus | Timpson, Nicholas J | Evans, David M | Pourcain, Beate St | Wu, Ying | Andrews, Jeanette S | Hui, Jennie | Bielak, Lawrence F | Zhao, Wei | Horikoshi, Momoko | Navarro, Pau | Isaacs, Aaron | O’Connell, Jeffrey R | Stirrups, Kathleen | Vitart, Veronique | Hayward, Caroline | Esko, Tönu | Mihailov, Evelin | Fraser, Ross M | Fall, Tove | Voight, Benjamin F | Raychaudhuri, Soumya | Chen, Han | Lindgren, Cecilia M | Morris, Andrew P | Rayner, Nigel W | Robertson, Neil | Rybin, Denis | Liu, Ching-Ti | Beckmann, Jacques S | Willems, Sara M | Chines, Peter S | Jackson, Anne U | Kang, Hyun Min | Stringham, Heather M | Song, Kijoung | Tanaka, Toshiko | Peden, John F | Goel, Anuj | Hicks, Andrew A | An, Ping | Müller-Nurasyid, Martina | Franco-Cereceda, Anders | Folkersen, Lasse | Marullo, Letizia | Jansen, Hanneke | Oldehinkel, Albertine J | Bruinenberg, Marcel | Pankow, James S | North, Kari E | Forouhi, Nita G | Loos, Ruth J F | Edkins, Sarah | Varga, Tibor V | Hallmans, Göran | Oksa, Heikki | Antonella, Mulas | Nagaraja, Ramaiah | Trompet, Stella | Ford, Ian | Bakker, Stephan J L | Kong, Augustine | Kumari, Meena | Gigante, Bruna | Herder, Christian | Munroe, Patricia B | Caulfield, Mark | Antti, Jula | Mangino, Massimo | Small, Kerrin | Miljkovic, Iva | Liu, Yongmei | Atalay, Mustafa | Kiess, Wieland | James, Alan L | Rivadeneira, Fernando | Uitterlinden, Andre G | Palmer, Colin N A | Doney, Alex S F | Willemsen, Gonneke | Smit, Johannes H | Campbell, Susan | Polasek, Ozren | Bonnycastle, Lori L | Hercberg, Serge | Dimitriou, Maria | Bolton, Jennifer L | Fowkes, Gerard R | Kovacs, Peter | Lindström, Jaana | Zemunik, Tatijana | Bandinelli, Stefania | Wild, Sarah H | Basart, Hanneke V | Rathmann, Wolfgang | Grallert, Harald | Maerz, Winfried | Kleber, Marcus E | Boehm, Bernhard O | Peters, Annette | Pramstaller, Peter P | Province, Michael A | Borecki, Ingrid B | Hastie, Nicholas D | Rudan, Igor | Campbell, Harry | Watkins, Hugh | Farrall, Martin | Stumvoll, Michael | Ferrucci, Luigi | Waterworth, Dawn M | Bergman, Richard N | Collins, Francis S | Tuomilehto, Jaakko | Watanabe, Richard M | de Geus, Eco J C | Penninx, Brenda W | Hofman, Albert | Oostra, Ben A | Psaty, Bruce M | Vollenweider, Peter | Wilson, James F | Wright, Alan F | Hovingh, G Kees | Metspalu, Andres | Uusitupa, Matti | Magnusson, Patrik K E | Kyvik, Kirsten O | Kaprio, Jaakko | Price, Jackie F | Dedoussis, George V | Deloukas, Panos | Meneton, Pierre | Lind, Lars | Boehnke, Michael | Shuldiner, Alan R | van Duijn, Cornelia M | Morris, Andrew D | Toenjes, Anke | Peyser, Patricia A | Beilby, John P | Körner, Antje | Kuusisto, Johanna | Laakso, Markku | Bornstein, Stefan R | Schwarz, Peter E H | Lakka, Timo A | Rauramaa, Rainer | Adair, Linda S | Smith, George Davey | Spector, Tim D | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Gudnason, Vilmundur | Kivimaki, Mika | Hingorani, Aroon | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Boomsma, Dorret I | Stefansson, Kari | van der Harst, Pim | Dupuis, Josée | Pedersen, Nancy L | Sattar, Naveed | Harris, Tamara B | Cucca, Francesco | Ripatti, Samuli | Salomaa, Veikko | Mohlke, Karen L | Balkau, Beverley | Froguel, Philippe | Pouta, Anneli | Jarvelin, Marjo-Riitta | Wareham, Nicholas J | Bouatia-Naji, Nabila | McCarthy, Mark I | Franks, Paul W | Meigs, James B | Teslovich, Tanya M | Florez, Jose C | Langenberg, Claudia | Ingelsson, Erik | Prokopenko, Inga | Barroso, Inês
Nature genetics  2012;44(9):991-1005.
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.
doi:10.1038/ng.2385
PMCID: PMC3433394  PMID: 22885924
3.  Identification of heart rate–associated loci and their effects on cardiac conduction and rhythm disorders 
den Hoed, Marcel | Eijgelsheim, Mark | Esko, Tõnu | Brundel, Bianca J J M | Peal, David S | Evans, David M | Nolte, Ilja M | Segrè, Ayellet V | Holm, Hilma | Handsaker, Robert E | Westra, Harm-Jan | Johnson, Toby | Isaacs, Aaron | Yang, Jian | Lundby, Alicia | Zhao, Jing Hua | Kim, Young Jin | Go, Min Jin | Almgren, Peter | Bochud, Murielle | Boucher, Gabrielle | Cornelis, Marilyn C | Gudbjartsson, Daniel | Hadley, David | Van Der Harst, Pim | Hayward, Caroline | Heijer, Martin Den | Igl, Wilmar | Jackson, Anne U | Kutalik, Zoltán | Luan, Jian’an | Kemp, John P | Kristiansson, Kati | Ladenvall, Claes | Lorentzon, Mattias | Montasser, May E | Njajou, Omer T | O’Reilly, Paul F | Padmanabhan, Sandosh | Pourcain, Beate St. | Rankinen, Tuomo | Salo, Perttu | Tanaka, Toshiko | Timpson, Nicholas J | Vitart, Veronique | Waite, Lindsay | Wheeler, William | Zhang, Weihua | Draisma, Harmen H M | Feitosa, Mary F | Kerr, Kathleen F | Lind, Penelope A | Mihailov, Evelin | Onland-Moret, N Charlotte | Song, Ci | Weedon, Michael N | Xie, Weijia | Yengo, Loic | Absher, Devin | Albert, Christine M | Alonso, Alvaro | Arking, Dan E | de Bakker, Paul I W | Balkau, Beverley | Barlassina, Cristina | Benaglio, Paola | Bis, Joshua C | Bouatia-Naji, Nabila | Brage, Søren | Chanock, Stephen J | Chines, Peter S | Chung, Mina | Darbar, Dawood | Dina, Christian | Dörr, Marcus | Elliott, Paul | Felix, Stephan B | Fischer, Krista | Fuchsberger, Christian | de Geus, Eco J C | Goyette, Philippe | Gudnason, Vilmundur | Harris, Tamara B | Hartikainen, Anna-liisa | Havulinna, Aki S | Heckbert, Susan R | Hicks, Andrew A | Hofman, Albert | Holewijn, Suzanne | Hoogstra-Berends, Femke | Hottenga, Jouke-Jan | Jensen, Majken K | Johansson, Åsa | Junttila, Juhani | Kääb, Stefan | Kanon, Bart | Ketkar, Shamika | Khaw, Kay-Tee | Knowles, Joshua W | Kooner, Angrad S | Kors, Jan A | Kumari, Meena | Milani, Lili | Laiho, Päivi | Lakatta, Edward G | Langenberg, Claudia | Leusink, Maarten | Liu, Yongmei | Luben, Robert N | Lunetta, Kathryn L | Lynch, Stacey N | Markus, Marcello R P | Marques-Vidal, Pedro | Leach, Irene Mateo | McArdle, Wendy L | McCarroll, Steven A | Medland, Sarah E | Miller, Kathryn A | Montgomery, Grant W | Morrison, Alanna C | Müller-Nurasyid, Martina | Navarro, Pau | Nelis, Mari | O’Connell, Jeffrey R | O’Donnell, Christopher J | Ong, Ken K | Newman, Anne B | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P | Psaty, Bruce M | Rao, Dabeeru C | Ring, Susan M | Rossin, Elizabeth J | Rudan, Diana | Sanna, Serena | Scott, Robert A | Sehmi, Jaban S | Sharp, Stephen | Shin, Jordan T | Singleton, Andrew B | Smith, Albert V | Soranzo, Nicole | Spector, Tim D | Stewart, Chip | Stringham, Heather M | Tarasov, Kirill V | Uitterlinden, André G | Vandenput, Liesbeth | Hwang, Shih-Jen | Whitfield, John B | Wijmenga, Cisca | Wild, Sarah H | Willemsen, Gonneke | Wilson, James F | Witteman, Jacqueline C M | Wong, Andrew | Wong, Quenna | Jamshidi, Yalda | Zitting, Paavo | Boer, Jolanda M A | Boomsma, Dorret I | Borecki, Ingrid B | Van Duijn, Cornelia M | Ekelund, Ulf | Forouhi, Nita G | Froguel, Philippe | Hingorani, Aroon | Ingelsson, Erik | Kivimaki, Mika | Kronmal, Richard A | Kuh, Diana | Lind, Lars | Martin, Nicholas G | Oostra, Ben A | Pedersen, Nancy L | Quertermous, Thomas | Rotter, Jerome I | van der Schouw, Yvonne T | Verschuren, W M Monique | Walker, Mark | Albanes, Demetrius | Arnar, David O | Assimes, Themistocles L | Bandinelli, Stefania | Boehnke, Michael | de Boer, Rudolf A | Bouchard, Claude | Caulfield, W L Mark | Chambers, John C | Curhan, Gary | Cusi, Daniele | Eriksson, Johan | Ferrucci, Luigi | van Gilst, Wiek H | Glorioso, Nicola | de Graaf, Jacqueline | Groop, Leif | Gyllensten, Ulf | Hsueh, Wen-Chi | Hu, Frank B | Huikuri, Heikki V | Hunter, David J | Iribarren, Carlos | Isomaa, Bo | Jarvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kiemeney, Lambertus A | van der Klauw, Melanie M | Kooner, Jaspal S | Kraft, Peter | Iacoviello, Licia | Lehtimäki, Terho | Lokki, Marja-Liisa L | Mitchell, Braxton D | Navis, Gerjan | Nieminen, Markku S | Ohlsson, Claes | Poulter, Neil R | Qi, Lu | Raitakari, Olli T | Rimm, Eric B | Rioux, John D | Rizzi, Federica | Rudan, Igor | Salomaa, Veikko | Sever, Peter S | Shields, Denis C | Shuldiner, Alan R | Sinisalo, Juha | Stanton, Alice V | Stolk, Ronald P | Strachan, David P | Tardif, Jean-Claude | Thorsteinsdottir, Unnur | Tuomilehto, Jaako | van Veldhuisen, Dirk J | Virtamo, Jarmo | Viikari, Jorma | Vollenweider, Peter | Waeber, Gérard | Widen, Elisabeth | Cho, Yoon Shin | Olsen, Jesper V | Visscher, Peter M | Willer, Cristen | Franke, Lude | Erdmann, Jeanette | Thompson, John R | Pfeufer, Arne | Sotoodehnia, Nona | Newton-Cheh, Christopher | Ellinor, Patrick T | Stricker, Bruno H Ch | Metspalu, Andres | Perola, Markus | Beckmann, Jacques S | Smith, George Davey | Stefansson, Kari | Wareham, Nicholas J | Munroe, Patricia B | Sibon, Ody C M | Milan, David J | Snieder, Harold | Samani, Nilesh J | Loos, Ruth J F
Nature genetics  2013;45(6):621-631.
Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate–increasing and heart rate–decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
doi:10.1038/ng.2610
PMCID: PMC3696959  PMID: 23583979
4.  Association of Genetic Loci With Glucose Levels in Childhood and Adolescence 
Diabetes  2011;60(6):1805-1812.
OBJECTIVE
To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents.
RESEARCH DESIGN AND METHODS
A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9–16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose.
RESULTS
Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021–0.031) for each unit increase in the score.
CONCLUSIONS
Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.
doi:10.2337/db10-1575
PMCID: PMC3114379  PMID: 21515849
5.  Physical Activity Attenuates the Influence of FTO Variants on Obesity Risk: A Meta-Analysis of 218,166 Adults and 19,268 Children 
Kilpeläinen, Tuomas O. | Qi, Lu | Brage, Soren | Sharp, Stephen J. | Sonestedt, Emily | Demerath, Ellen | Ahmad, Tariq | Mora, Samia | Kaakinen, Marika | Sandholt, Camilla Helene | Holzapfel, Christina | Autenrieth, Christine S. | Hyppönen, Elina | Cauchi, Stéphane | He, Meian | Kutalik, Zoltan | Kumari, Meena | Stančáková, Alena | Meidtner, Karina | Balkau, Beverley | Tan, Jonathan T. | Mangino, Massimo | Timpson, Nicholas J. | Song, Yiqing | Zillikens, M. Carola | Jablonski, Kathleen A. | Garcia, Melissa E. | Johansson, Stefan | Bragg-Gresham, Jennifer L. | Wu, Ying | van Vliet-Ostaptchouk, Jana V. | Onland-Moret, N. Charlotte | Zimmermann, Esther | Rivera, Natalia V. | Tanaka, Toshiko | Stringham, Heather M. | Silbernagel, Günther | Kanoni, Stavroula | Feitosa, Mary F. | Snitker, Soren | Ruiz, Jonatan R. | Metter, Jeffery | Larrad, Maria Teresa Martinez | Atalay, Mustafa | Hakanen, Maarit | Amin, Najaf | Cavalcanti-Proença, Christine | Grøntved, Anders | Hallmans, Göran | Jansson, John-Olov | Kuusisto, Johanna | Kähönen, Mika | Lutsey, Pamela L. | Nolan, John J. | Palla, Luigi | Pedersen, Oluf | Pérusse, Louis | Renström, Frida | Scott, Robert A. | Shungin, Dmitry | Sovio, Ulla | Tammelin, Tuija H. | Rönnemaa, Tapani | Lakka, Timo A. | Uusitupa, Matti | Rios, Manuel Serrano | Ferrucci, Luigi | Bouchard, Claude | Meirhaeghe, Aline | Fu, Mao | Walker, Mark | Borecki, Ingrid B. | Dedoussis, George V. | Fritsche, Andreas | Ohlsson, Claes | Boehnke, Michael | Bandinelli, Stefania | van Duijn, Cornelia M. | Ebrahim, Shah | Lawlor, Debbie A. | Gudnason, Vilmundur | Harris, Tamara B. | Sørensen, Thorkild I. A. | Mohlke, Karen L. | Hofman, Albert | Uitterlinden, André G. | Tuomilehto, Jaakko | Lehtimäki, Terho | Raitakari, Olli | Isomaa, Bo | Njølstad, Pål R. | Florez, Jose C. | Liu, Simin | Ness, Andy | Spector, Timothy D. | Tai, E. Shyong | Froguel, Philippe | Boeing, Heiner | Laakso, Markku | Marmot, Michael | Bergmann, Sven | Power, Chris | Khaw, Kay-Tee | Chasman, Daniel | Ridker, Paul | Hansen, Torben | Monda, Keri L. | Illig, Thomas | Järvelin, Marjo-Riitta | Wareham, Nicholas J. | Hu, Frank B. | Groop, Leif C. | Orho-Melander, Marju | Ekelund, Ulf | Franks, Paul W. | Loos, Ruth J. F.
PLoS Medicine  2011;8(11):e1001116.
Ruth Loos and colleagues report findings from a meta-analysis of multiple studies examining the extent to which physical activity attenuates effects of a specific gene variant, FTO, on obesity in adults and children. They report a fairly substantial attenuation by physical activity on the effects of this genetic variant on the risk of obesity in adults.
Background
The FTO gene harbors the strongest known susceptibility locus for obesity. While many individual studies have suggested that physical activity (PA) may attenuate the effect of FTO on obesity risk, other studies have not been able to confirm this interaction. To confirm or refute unambiguously whether PA attenuates the association of FTO with obesity risk, we meta-analyzed data from 45 studies of adults (n = 218,166) and nine studies of children and adolescents (n = 19,268).
Methods and Findings
All studies identified to have data on the FTO rs9939609 variant (or any proxy [r2>0.8]) and PA were invited to participate, regardless of ethnicity or age of the participants. PA was standardized by categorizing it into a dichotomous variable (physically inactive versus active) in each study. Overall, 25% of adults and 13% of children were categorized as inactive. Interaction analyses were performed within each study by including the FTO×PA interaction term in an additive model, adjusting for age and sex. Subsequently, random effects meta-analysis was used to pool the interaction terms. In adults, the minor (A−) allele of rs9939609 increased the odds of obesity by 1.23-fold/allele (95% CI 1.20–1.26), but PA attenuated this effect (pinteraction  = 0.001). More specifically, the minor allele of rs9939609 increased the odds of obesity less in the physically active group (odds ratio  = 1.22/allele, 95% CI 1.19–1.25) than in the inactive group (odds ratio  = 1.30/allele, 95% CI 1.24–1.36). No such interaction was found in children and adolescents.
Conclusions
The association of the FTO risk allele with the odds of obesity is attenuated by 27% in physically active adults, highlighting the importance of PA in particular in those genetically predisposed to obesity.
Please see later in the article for the Editors' Summary
Editors’ Summary
Background
Two in three Americans are overweight, of whom half are obese, and the trend towards increasing obesity is now seen across developed and developing countries. There has long been interest in understanding the impact of genes and environment when it comes to apportioning responsibility for obesity. Carrying a change in the FTO gene is common (found in three-quarters of Europeans and North Americans) and is associated with a 20%–30% increased risk of obesity. Some overweight or obese individuals may feel that the dice are loaded and there is little point in fighting the fat; it has been reported that those made aware of their genetic susceptibility to obesity may still choose a poor diet. A similar fatalism may occur when overweight and obese people consider physical activity. But disentangling the influence of physical activity on those genetically susceptible to obesity from other factors that might impact weight is not straightforward, as it requires large sample sizes, could be subject to publication bias, and may rely on less than ideal self-reporting methods.
Why Was This Study Done?
The public health ramifications of understanding the interaction between genetic susceptibility to obesity and physical activity are considerable. Tackling the rising prevalence of obesity will inevitably include interventions principally aimed at changing dietary intake and/or increasing physical activity, but the evidence for these with regards to those genetically susceptible has been lacking to date. The authors of this paper set out to explore the interaction between the commonest genetic susceptibility trait and physical activity using a rigorous meta-analysis of a large number of studies.
What Did the Researchers Do and Find?
The authors were concerned that a meta-analysis of published studies would be limited both by the data available to them and by possible bias. Instead of this more widely used approach, they took the literature search as their starting point, identified other studies through their collaborators’ network, and then undertook a meta-analysis of all available studies using a new and standardized analysis plan. This entailed an extremely large number of authors mining their data afresh to extract the relevant data points to enable such a meta-analysis. Physical activity was identified in the original studies in many different ways, including by self-report or by using an external measure of activity or heart rate. In order to perform the meta-analysis, participants were labeled as physically active or inactive in each study. For studies that had used a continuous scale, the authors decided that the bottom 20% of the participants were inactive (10% for children and adolescents). Using data from over 218,000 adults, the authors found that carrying a copy of the susceptibility gene increased the odds of obesity by 1.23-fold. But the size of this influence was 27% less in the genetically susceptible adults who were physically active (1.22-fold) compared to those who were physically inactive (1.30-fold). In a smaller study of about 19,000 children, no such effect of physical activity was seen.
What Do these Findings Mean?
This study demonstrates that people who carry the susceptibility gene for obesity can benefit from physical activity. This should inform health care professionals and the wider public that the view of genetically determined obesity not being amenable to exercise is incorrect and should be challenged. Dissemination, implementation, and ensuring uptake of effective physical activity programs remains a challenge and deserves further consideration. That the researchers treated “physically active” as a yes/no category, and how they categorized individuals, could be criticized, but this was done for pragmatic reasons, as a variety of means of assessing physical activity were used across the studies. It is unlikely that the findings would have changed if the authors had used a different method of defining physically active. Most of the studies included in the meta-analysis looked at one time point only; information about the influence of physical activity on weight changes over time in genetically susceptible individuals is only beginning to emerge.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001116.
This study is further discussed in a PLoS Medicine Perspective by Lennert Veerman
The US Centers for Disease Control and Prevention provides obesity-related statistics, details of prevention programs, and an overview on public health strategy in the United States
A more worldwide view is given by the World Health Organization
The UK National Health Service website gives information on physical activity guidelines for different age groups, while similar information can also be found from US sources
doi:10.1371/journal.pmed.1001116
PMCID: PMC3206047  PMID: 22069379
6.  Genetic Markers of Adult Obesity Risk Are Associated with Greater Early Infancy Weight Gain and Growth 
PLoS Medicine  2010;7(5):e1000284.
Ken Ong and colleagues genotyped children from the ALSPAC birth cohort and showed an association between greater early infancy gains in weight and length and genetic markers for adult obesity risk.
Background
Genome-wide studies have identified several common genetic variants that are robustly associated with adult obesity risk. Exploration of these genotype associations in children may provide insights into the timing of weight changes leading to adult obesity.
Methods and Findings
Children from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort were genotyped for ten genetic variants previously associated with adult BMI. Eight variants that showed individual associations with childhood BMI (in/near: FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, and ETV5) were used to derive an “obesity-risk-allele score” comprising the total number of risk alleles (range: 2–15 alleles) in each child with complete genotype data (n = 7,146). Repeated measurements of weight, length/height, and body mass index from birth to age 11 years were expressed as standard deviation scores (SDS). Early infancy was defined as birth to age 6 weeks, and early infancy failure to thrive was defined as weight gain between below the 5th centile, adjusted for birth weight. The obesity-risk-allele score showed little association with birth weight (regression coefficient: 0.01 SDS per allele; 95% CI 0.00–0.02), but had an apparently much larger positive effect on early infancy weight gain (0.119 SDS/allele/year; 0.023–0.216) than on subsequent childhood weight gain (0.004 SDS/allele/year; 0.004–0.005). The obesity-risk-allele score was also positively associated with early infancy length gain (0.158 SDS/allele/year; 0.032–0.284) and with reduced risk of early infancy failure to thrive (odds ratio  = 0.92 per allele; 0.86–0.98; p = 0.009).
Conclusions
The use of robust genetic markers identified greater early infancy gains in weight and length as being on the pathway to adult obesity risk in a contemporary birth cohort.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The proportion of overweight and obese children is increasing across the globe. In the US, the Surgeon General estimates that, compared with 1980, twice as many children and three times the number of adolescents are now overweight. Worldwide, 22 million children under five years old are considered by the World Health Organization to be overweight.
Being overweight or obese in childhood is associated with poor physical and mental health. In addition, childhood obesity is considered a major risk factor for adult obesity, which is itself a major risk factor for cancer, heart disease, diabetes, osteoarthritis, and other chronic conditions.
The most commonly used measure of whether an adult is a healthy weight is body mass index (BMI), defined as weight in kilograms/(height in metres)2. However, adult categories of obese (>30) and overweight (>25) BMI are not directly applicable to children, whose BMI naturally varies as they grow. BMI can be used to screen children for being overweight and or obese but a diagnosis requires further information.
Why Was This Study Done?
As the numbers of obese and overweight children increase, a corresponding rise in future numbers of overweight and obese adults is also expected. This in turn is expected to lead to an increasing incidence of poor health. As a result, there is great interest among health professionals in possible pathways between childhood and adult obesity. It has been proposed that certain periods in childhood may be critical for the development of obesity.
In the last few years, ten genetic variants have been found to be more common in overweight or obese adults. Eight of these have also been linked to childhood BMI and/or obesity. The authors wanted to identify the timing of childhood weight changes that may be associated with adult obesity. Knowledge of obesity risk genetic variants gave them an opportunity to do so now, without following a set of children to adulthood.
What Did the Researchers Do and Find?
The authors analysed data gathered from a subset of 7,146 singleton white European children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, which is investigating associations between genetics, lifestyle, and health outcomes for a group of children in Bristol whose due date of birth fell between April 1991 and December 1992. They used knowledge of the children's genetic makeup to find associations between an obesity risk allele score—a measure of how many of the obesity risk genetic variants a child possessed—and the children's weight, height, BMI, levels of body fat (at nine years old), and rate of weight gain, up to age 11 years.
They found that, at birth, children with a higher obesity risk allele score were not any heavier, but in the immediate postnatal period they were less likely to be in the bottom 5% of the population for weight gain (adjusted for birthweight), often termed “failure to thrive.” At six weeks of age, children with a higher obesity risk allele score tended to be longer and heavier, even allowing for weight at birth.
After six weeks of age, the obesity risk allele score was not associated with any further increase in length/height, but it was associated with a more rapid weight gain between birth and age 11 years. BMI is derived from height and weight measurements, and the association between the obesity risk allele score and BMI was weak between birth and age three-and-a-half years, but after that age the association with BMI increased rapidly. By age nine, children with a higher obesity risk allele score tended to be heavier and taller, with more fat on their bodies.
What Do These Findings Mean?
The combined obesity allele risk score is associated with higher rates of weight gain and adult obesity, and so the authors conclude that weight gain and growth even in the first few weeks after birth may be the beginning of a pathway of greater adult obesity risk.
A study that tracks a population over time can find associations but it cannot show cause and effect. In addition, only a relatively small proportion (1.7%) of the variation in BMI at nine years of age is explained by the obesity risk allele score.
The authors' method of finding associations between childhood events and adult outcomes via genetic markers of risk of disease as an adult has a significant advantage: the authors did not have to follow the children themselves to adulthood, so their findings are more likely to be relevant to current populations. Despite this, this research does not yield advice for parents how to reduce their children's obesity risk. It does suggest that “failure to thrive” in the first six weeks of life is not simply due to a lack of provision of food by the baby's caregiver but that genetic factors also contribute to early weight gain and growth.
The study looked at the combined obesity risk allele score and the authors did not attempt to identify which individual alleles have greater or weaker associations with weight gain and overweight or obesity. This would require further research based on far larger numbers of babies and children. The findings may also not be relevant to children in other types of setting because of the effects of different nutrition and lifestyles.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1000284.
Further information is available on the ALSPAC study
The UK National Health Service and other partners provide guidance on establishing a healthy lifestyle for children and families in their Change4Life programme
The International Obesity Taskforce is a global network of expertise and the advocacy arm of the International Association for the Study of Obesity. It works with the World Health Organization, other NGOs, and stakeholders and provides information on overweight and obesity
The Centers for Disease Control and Prevention (CDC) in the US provide guidance and tips on maintaining a healthy weight, including BMI calculators in both metric and Imperial measurements for both adults and children. They also provide BMI growth charts for boys and girls showing how healthy ranges vary for each sex at with age
The Royal College of Paediatrics and Child Health provides growth charts for weight and length/height from birth to age 4 years that are based on WHO 2006 growth standards and have been adapted for use in the UK
The CDC Web site provides information on overweight and obesity in adults and children, including definitions, causes, and data
The CDC also provide information on the role of genes in causing obesity.
The World Health Organization publishes a fact sheet on obesity, overweight and weight management, including links to childhood overweight and obesity
Wikipedia includes an article on childhood obesity (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
doi:10.1371/journal.pmed.1000284
PMCID: PMC2876048  PMID: 20520848
7.  Correction: Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution 
Lindgren, Cecilia M. | Heid, Iris M. | Randall, Joshua C. | Lamina, Claudia | Steinthorsdottir, Valgerdur | Qi, Lu | Speliotes, Elizabeth K. | Thorleifsson, Gudmar | Willer, Cristen J. | Herrera, Blanca M. | Jackson, Anne U. | Lim, Noha | Scheet, Paul | Soranzo, Nicole | Amin, Najaf | Aulchenko, Yurii S. | Chambers, John C. | Drong, Alexander | Luan, Jian'an | Lyon, Helen N. | Rivadeneira, Fernando | Sanna, Serena | Timpson, Nicholas J. | Zillikens, M. Carola | Zhao, Jing Hua | Almgren, Peter | Bandinelli, Stefania | Bennett, Amanda J. | Bergman, Richard N. | Bonnycastle, Lori L. | Bumpstead, Suzannah J. | Chanock, Stephen J. | Cherkas, Lynn | Chines, Peter | Coin, Lachlan | Cooper, Cyrus | Crawford, Gabriel | Doering, Angela | Dominiczak, Anna | Doney, Alex S. F. | Ebrahim, Shah | Elliott, Paul | Erdos, Michael R. | Estrada, Karol | Ferrucci, Luigi | Fischer, Guido | Forouhi, Nita G. | Gieger, Christian | Grallert, Harald | Groves, Christopher J. | Grundy, Scott | Guiducci, Candace | Hadley, David | Hamsten, Anders | Havulinna, Aki S. | Hofman, Albert | Holle, Rolf | Holloway, John W. | Illig, Thomas | Isomaa, Bo | Jacobs, Leonie C. | Jameson, Karen | Jousilahti, Pekka | Karpe, Fredrik | Kuusisto, Johanna | Laitinen, Jaana | Lathrop, G. Mark | Lawlor, Debbie A. | Mangino, Massimo | McArdle, Wendy L. | Meitinger, Thomas | Morken, Mario A. | Morris, Andrew P. | Munroe, Patricia | Narisu, Narisu | Nordström, Anna | Nordström, Peter | Oostra, Ben A. | Palmer, Colin N. A. | Payne, Felicity | Peden, John F. | Prokopenko, Inga | Renström, Frida | Ruokonen, Aimo | Salomaa, Veikko | Sandhu, Manjinder S. | Scott, Laura J. | Scuteri, Angelo | Silander, Kaisa | Song, Kijoung | Yuan, Xin | Stringham, Heather M. | Swift, Amy J. | Tuomi, Tiinamaija | Uda, Manuela | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Walters, G. Bragi | Weedon, Michael N. | Witteman, Jacqueline C. M. | Zhang, Cuilin | Zhang, Weihua | Caulfield, Mark J. | Collins, Francis S. | Davey Smith, George | Day, Ian N. M. | Franks, Paul W. | Hattersley, Andrew T. | Hu, Frank B. | Jarvelin, Marjo-Riitta | Kong, Augustine | Kooner, Jaspal S. | Laakso, Markku | Lakatta, Edward | Mooser, Vincent | Morris, Andrew D. | Peltonen, Leena | Samani, Nilesh J. | Spector, Timothy D. | Strachan, David P. | Tanaka, Toshiko | Tuomilehto, Jaakko | Uitterlinden, André G. | van Duijn, Cornelia M. | Wareham, Nicholas J. | Watkins for the PROCARDIS consortia, Hugh | Waterworth, Dawn M. | Boehnke, Michael | Deloukas, Panos | Groop, Leif | Hunter, David J. | Thorsteinsdottir, Unnur | Schlessinger, David | Wichmann, H.-Erich | Frayling, Timothy M. | Abecasis, Gonçalo R. | Hirschhorn, Joel N. | Loos, Ruth J. F. | Stefansson, Kari | Mohlke, Karen L. | Barroso, Inês | McCarthy for the GIANT consortium, Mark I.
PLoS Genetics  2009;5(7):10.1371/annotation/b6e8f9f6-2496-4a40-b0e3-e1d1390c1928.
doi:10.1371/annotation/b6e8f9f6-2496-4a40-b0e3-e1d1390c1928
PMCID: PMC2722420
8.  Six new loci associated with body mass index highlight a neuronal influence on body weight regulation 
Willer, Cristen J | Speliotes, Elizabeth K | Loos, Ruth J F | Li, Shengxu | Lindgren, Cecilia M | Heid, Iris M | Berndt, Sonja I | Elliott, Amanda L | Jackson, Anne U | Lamina, Claudia | Lettre, Guillaume | Lim, Noha | Lyon, Helen N | McCarroll, Steven A | Papadakis, Konstantinos | Qi, Lu | Randall, Joshua C | Roccasecca, Rosa Maria | Sanna, Serena | Scheet, Paul | Weedon, Michael N | Wheeler, Eleanor | Zhao, Jing Hua | Jacobs, Leonie C | Prokopenko, Inga | Soranzo, Nicole | Tanaka, Toshiko | Timpson, Nicholas J | Almgren, Peter | Bennett, Amanda | Bergman, Richard N | Bingham, Sheila A | Bonnycastle, Lori L | Brown, Morris | Burtt, Noël P | Chines, Peter | Coin, Lachlan | Collins, Francis S | Connell, John M | Cooper, Cyrus | Smith, George Davey | Dennison, Elaine M | Deodhar, Parimal | Elliott, Paul | Erdos, Michael R | Estrada, Karol | Evans, David M | Gianniny, Lauren | Gieger, Christian | Gillson, Christopher J | Guiducci, Candace | Hackett, Rachel | Hadley, David | Hall, Alistair S | Havulinna, Aki S | Hebebrand, Johannes | Hofman, Albert | Isomaa, Bo | Jacobs, Kevin B | Johnson, Toby | Jousilahti, Pekka | Jovanovic, Zorica | Khaw, Kay-Tee | Kraft, Peter | Kuokkanen, Mikko | Kuusisto, Johanna | Laitinen, Jaana | Lakatta, Edward G | Luan, Jian'an | Luben, Robert N | Mangino, Massimo | McArdle, Wendy L | Meitinger, Thomas | Mulas, Antonella | Munroe, Patricia B | Narisu, Narisu | Ness, Andrew R | Northstone, Kate | O'Rahilly, Stephen | Purmann, Carolin | Rees, Matthew G | Ridderstråle, Martin | Ring, Susan M | Rivadeneira, Fernando | Ruokonen, Aimo | Sandhu, Manjinder S | Saramies, Jouko | Scott, Laura J | Scuteri, Angelo | Silander, Kaisa | Sims, Matthew A | Song, Kijoung | Stephens, Jonathan | Stevens, Suzanne | Stringham, Heather M | Tung, Y C Loraine | Valle, Timo T | Van Duijn, Cornelia M | Vimaleswaran, Karani S | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Watanabe, Richard M | Waterworth, Dawn M | Watkins, Nicholas | Witteman, Jacqueline C M | Zeggini, Eleftheria | Zhai, Guangju | Zillikens, M Carola | Altshuler, David | Caulfield, Mark J | Chanock, Stephen J | Farooqi, I Sadaf | Ferrucci, Luigi | Guralnik, Jack M | Hattersley, Andrew T | Hu, Frank B | Jarvelin, Marjo-Riitta | Laakso, Markku | Mooser, Vincent | Ong, Ken K | Ouwehand, Willem H | Salomaa, Veikko | Samani, Nilesh J | Spector, Timothy D | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uda, Manuela | Uitterlinden, André G | Wareham, Nicholas J | Deloukas, Panagiotis | Frayling, Timothy M | Groop, Leif C | Hayes, Richard B | Hunter, David J | Mohlke, Karen L | Peltonen, Leena | Schlessinger, David | Strachan, David P | Wichmann, H-Erich | McCarthy, Mark I | Boehnke, Michael | Barroso, Inês | Abecasis, Gonçalo R | Hirschhorn, Joel N
Nature genetics  2008;41(1):25-34.
Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10−8): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.
doi:10.1038/ng.287
PMCID: PMC2695662  PMID: 19079261
9.  Genome-Wide Association Scan Meta-Analysis Identifies Three Loci Influencing Adiposity and Fat Distribution 
Lindgren, Cecilia M. | Heid, Iris M. | Randall, Joshua C. | Lamina, Claudia | Steinthorsdottir, Valgerdur | Qi, Lu | Speliotes, Elizabeth K. | Thorleifsson, Gudmar | Willer, Cristen J. | Herrera, Blanca M. | Jackson, Anne U. | Lim, Noha | Scheet, Paul | Soranzo, Nicole | Amin, Najaf | Aulchenko, Yurii S. | Chambers, John C. | Drong, Alexander | Luan, Jian'an | Lyon, Helen N. | Rivadeneira, Fernando | Sanna, Serena | Timpson, Nicholas J. | Zillikens, M. Carola | Zhao, Jing Hua | Almgren, Peter | Bandinelli, Stefania | Bennett, Amanda J. | Bergman, Richard N. | Bonnycastle, Lori L. | Bumpstead, Suzannah J. | Chanock, Stephen J. | Cherkas, Lynn | Chines, Peter | Coin, Lachlan | Cooper, Cyrus | Crawford, Gabriel | Doering, Angela | Dominiczak, Anna | Doney, Alex S. F. | Ebrahim, Shah | Elliott, Paul | Erdos, Michael R. | Estrada, Karol | Ferrucci, Luigi | Fischer, Guido | Forouhi, Nita G. | Gieger, Christian | Grallert, Harald | Groves, Christopher J. | Grundy, Scott | Guiducci, Candace | Hadley, David | Hamsten, Anders | Havulinna, Aki S. | Hofman, Albert | Holle, Rolf | Holloway, John W. | Illig, Thomas | Isomaa, Bo | Jacobs, Leonie C. | Jameson, Karen | Jousilahti, Pekka | Karpe, Fredrik | Kuusisto, Johanna | Laitinen, Jaana | Lathrop, G. Mark | Lawlor, Debbie A. | Mangino, Massimo | McArdle, Wendy L. | Meitinger, Thomas | Morken, Mario A. | Morris, Andrew P. | Munroe, Patricia | Narisu, Narisu | Nordström, Anna | Nordström, Peter | Oostra, Ben A. | Palmer, Colin N. A. | Payne, Felicity | Peden, John F. | Prokopenko, Inga | Renström, Frida | Ruokonen, Aimo | Salomaa, Veikko | Sandhu, Manjinder S. | Scott, Laura J. | Scuteri, Angelo | Silander, Kaisa | Song, Kijoung | Yuan, Xin | Stringham, Heather M. | Swift, Amy J. | Tuomi, Tiinamaija | Uda, Manuela | Vollenweider, Peter | Waeber, Gerard | Wallace, Chris | Walters, G. Bragi | Weedon, Michael N. | Witteman, Jacqueline C. M. | Zhang, Cuilin | Zhang, Weihua | Caulfield, Mark J. | Collins, Francis S. | Davey Smith, George | Day, Ian N. M. | Franks, Paul W. | Hattersley, Andrew T. | Hu, Frank B. | Jarvelin, Marjo-Riitta | Kong, Augustine | Kooner, Jaspal S. | Laakso, Markku | Lakatta, Edward | Mooser, Vincent | Morris, Andrew D. | Peltonen, Leena | Samani, Nilesh J. | Spector, Timothy D. | Strachan, David P. | Tanaka, Toshiko | Tuomilehto, Jaakko | Uitterlinden, André G. | van Duijn, Cornelia M. | Wareham, Nicholas J. | Watkins for the PROCARDIS consortia, Hugh | Waterworth, Dawn M. | Boehnke, Michael | Deloukas, Panos | Groop, Leif | Hunter, David J. | Thorsteinsdottir, Unnur | Schlessinger, David | Wichmann, H.-Erich | Frayling, Timothy M. | Abecasis, Gonçalo R. | Hirschhorn, Joel N. | Loos, Ruth J. F. | Stefansson, Kari | Mohlke, Karen L. | Barroso, Inês | McCarthy for the GIANT consortium, Mark I.
PLoS Genetics  2009;5(6):e1000508.
To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist–hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9×10−11) and MSRA (WC, P = 8.9×10−9). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6×10−8). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.
Author Summary
Here, we describe a meta-analysis of genome-wide association data from 38,580 individuals, followed by large-scale replication (in up to 70,689 individuals) designed to uncover variants influencing anthropometric measures of central obesity and fat distribution, namely waist circumference (WC) and waist–hip ratio (WHR). This work complements parallel efforts that have been successful in defining variants impacting overall adiposity and focuses on the visceral fat accumulation which has particularly strong relationships to metabolic and cardiovascular disease. Our analyses have identified two loci (TFAP2B and MSRA) associated with WC, and a further locus, near LYPLAL1, which shows gender-specific relationships with WHR (all to levels of genome-wide significance). These loci vary in the strength of their associations with overall adiposity, and LYPLAL1 in particular appears to have a specific effect on patterns of fat distribution. All in all, these three loci provide novel insights into human physiology and the development of obesity.
doi:10.1371/journal.pgen.1000508
PMCID: PMC2695778  PMID: 19557161
10.  Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes 
Zeggini, Eleftheria | Scott, Laura J. | Saxena, Richa | Voight, Benjamin F. | Marchini, Jonathan L | Hu, Tainle | de Bakker, Paul IW | Abecasis, Gonçalo R | Almgren, Peter | Andersen, Gitte | Ardlie, Kristin | Boström, Kristina Bengtsson | Bergman, Richard N | Bonnycastle, Lori L | Borch-Johnsen, Knut | Burtt, Noël P | Chen, Hong | Chines, Peter S | Daly, Mark J | Deodhar, Parimal | Ding, Charles | Doney, Alex S F | Duren, William L | Elliott, Katherine S | Erdos, Michael R | Frayling, Timothy M | Freathy, Rachel M | Gianniny, Lauren | Grallert, Harald | Grarup, Niels | Groves, Christopher J | Guiducci, Candace | Hansen, Torben | Herder, Christian | Hitman, Graham A | Hughes, Thomas E | Isomaa, Bo | Jackson, Anne U | Jørgensen, Torben | Kong, Augustine | Kubalanza, Kari | Kuruvilla, Finny G | Kuusisto, Johanna | Langenberg, Claudia | Lango, Hana | Lauritzen, Torsten | Li, Yun | Lindgren, Cecilia M | Lyssenko, Valeriya | Marvelle, Amanda F | Meisinger, Christa | Midthjell, Kristian | Mohlke, Karen L | Morken, Mario A | Morris, Andrew D | Narisu, Narisu | Nilsson, Peter | Owen, Katharine R | Palmer, Colin NA | Payne, Felicity | Perry, John RB | Pettersen, Elin | Platou, Carl | Prokopenko, Inga | Qi, Lu | Qin, Li | Rayner, Nigel W | Rees, Matthew | Roix, Jeffrey J | Sandbæk, Anelli | Shields, Beverley | Sjögren, Marketa | Steinthorsdottir, Valgerdur | Stringham, Heather M | Swift, Amy J | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Timpson, Nicholas J | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Walker, Mark | Watanabe, Richard M | Weedon, Michael N | Willer, Cristen J | Illig, Thomas | Hveem, Kristian | Hu, Frank B | Laakso, Markku | Stefansson, Kari | Pedersen, Oluf | Wareham, Nicholas J | Barroso, Inês | Hattersley, Andrew T | Collins, Francis S | Groop, Leif | McCarthy, Mark I | Boehnke, Michael | Altshuler, David
Nature genetics  2008;40(5):638-645.
Genome-wide association (GWA) studies have identified multiple new genomic loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D)1-11. Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to discover loci at which common alleles have modest effects, we performed meta-analysis of three T2D GWA scans encompassing 10,128 individuals of European-descent and ~2.2 million SNPs (directly genotyped and imputed). Replication testing was performed in an independent sample with an effective sample size of up to 53,975. At least six new loci with robust evidence for association were detected, including the JAZF1 (p=5.0×10−14), CDC123/CAMK1D (p=1.2×10−10), TSPAN8/LGR5 (p=1.1×10−9), THADA (p=1.1×10−9), ADAMTS9 (p=1.2×10−8), and NOTCH2 (p=4.1×10−8) gene regions. The large number of loci with relatively small effects indicates the value of large discovery and follow-up samples in identifying additional clues about the inherited basis of T2D.
doi:10.1038/ng.120
PMCID: PMC2672416  PMID: 18372903
11.  Common variants near MC4R are associated with fat mass, weight and risk of obesity 
Loos, Ruth J F | Lindgren, Cecilia M | Li, Shengxu | Wheeler, Eleanor | Zhao, Jing Hua | Prokopenko, Inga | Inouye, Michael | Freathy, Rachel M | Attwood, Antony P | Beckmann, Jacques S | Berndt, Sonja I | Bergmann, Sven | Bennett, Amanda J | Bingham, Sheila A | Bochud, Murielle | Brown, Morris | Cauchi, Stéphane | Connell, John M | Cooper, Cyrus | Smith, George Davey | Day, Ian | Dina, Christian | De, Subhajyoti | Dermitzakis, Emmanouil T | Doney, Alex S F | Elliott, Katherine S | Elliott, Paul | Evans, David M | Farooqi, I Sadaf | Froguel, Philippe | Ghori, Jilur | Groves, Christopher J | Gwilliam, Rhian | Hadley, David | Hall, Alistair S | Hattersley, Andrew T | Hebebrand, Johannes | Heid, Iris M | Herrera, Blanca | Hinney, Anke | Hunt, Sarah E | Jarvelin, Marjo-Riitta | Johnson, Toby | Jolley, Jennifer D M | Karpe, Fredrik | Keniry, Andrew | Khaw, Kay-Tee | Luben, Robert N | Mangino, Massimo | Marchini, Jonathan | McArdle, Wendy L | McGinnis, Ralph | Meyre, David | Munroe, Patricia B | Morris, Andrew D | Ness, Andrew R | Neville, Matthew J | Nica, Alexandra C | Ong, Ken K | O'Rahilly, Stephen | Owen, Katharine R | Palmer, Colin N A | Papadakis, Konstantinos | Potter, Simon | Pouta, Anneli | Qi, Lu | Randall, Joshua C | Rayner, Nigel W | Ring, Susan M | Sandhu, Manjinder S | Scherag, André | Sims, Matthew A | Song, Kijoung | Soranzo, Nicole | Speliotes, Elizabeth K | Syddall, Holly E | Teichmann, Sarah A | Timpson, Nicholas J | Tobias, Jonathan H | Uda, Manuela | Vogel, Carla I Ganz | Wallace, Chris | Waterworth, Dawn M | Weedon, Michael N | Willer, Cristen J | Wraight, Vicki L | Yuan, Xin | Zeggini, Eleftheria | Hirschhorn, Joel N | Strachan, David P | Ouwehand, Willem H | Caulfield, Mark J | Samani, Nilesh J | Frayling, Timothy M | Vollenweider, Peter | Waeber, Gerard | Mooser, Vincent | Deloukas, Panos | McCarthy, Mark I | Wareham, Nicholas J | Barroso, Inês | Jacobs, Kevin B | Chanock, Stephen J | Hayes, Richard B | Lamina, Claudia | Gieger, Christian | Illig, Thomas | Meitinger, Thomas | Wichmann, H-Erich | Kraft, Peter | Hankinson, Susan E | Hunter, David J | Hu, Frank B | Lyon, Helen N | Voight, Benjamin F | Ridderstrale, Martin | Groop, Leif | Scheet, Paul | Sanna, Serena | Abecasis, Goncalo R | Albai, Giuseppe | Nagaraja, Ramaiah | Schlessinger, David | Jackson, Anne U | Tuomilehto, Jaakko | Collins, Francis S | Boehnke, Michael | Mohlke, Karen L
Nature genetics  2008;40(6):768-775.
To identify common variants influencing body mass index (BMI), we analyzed genome-wide association data from 16,876 individuals of European descent. After previously reported variants in FTO, the strongest association signal (rs17782313, P = 2.9 × 10−6) mapped 188 kb downstream of MC4R (melanocortin-4 receptor), mutations of which are the leading cause of monogenic severe childhood-onset obesity. We confirmed the BMI association in 60,352 adults (per-allele effect = 0.05 Z-score units; P = 2.8 × 10−15) and 5,988 children aged 7–11 (0.13 Z-score units; P = 1.5 × 10−8). In case-control analyses (n = 10,583), the odds for severe childhood obesity reached 1.30 (P = 8.0 × 10−11). Furthermore, we observed overtransmission of the risk allele to obese offspring in 660 families (P (pedigree disequilibrium test average; PDT-avg) = 2.4 × 10−4). The SNP location and patterns of phenotypic associations are consistent with effects mediated through altered MC4R function. Our findings establish that common variants near MC4R influence fat mass, weight and obesity risk at the population level and reinforce the need for large-scale data integration to identify variants influencing continuous biomedical traits.
doi:10.1038/ng.140
PMCID: PMC2669167  PMID: 18454148
12.  A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity 
Science (New York, N.Y.)  2007;316(5826):889-894.
Obesity is a serious international health problem that increases the risk of several common diseases. The genetic factors predisposing to obesity are poorly understood. A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI). An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.
doi:10.1126/science.1141634
PMCID: PMC2646098  PMID: 17434869
13.  Association analyses of 249,796 individuals reveal eighteen new loci associated with body mass index 
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. | Segré, 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 R.B. | 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 T. S. | 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 I.F. | Boes, Tanja | Bonnycastle, Lori L. | Bornstein, Stefan R. | Brown, Morris J. | Buchanan, Thomas A. | Busonero, Fabio | Campbell, Harry | Cappuccio, Francesco P. | Cavalcanti-Proença, Christine | Chen, Yii-Der Ida | Chen, Chih-Mei | Chines, Peter S. | Clarke, Robert | Coin, Lachlan | Connell, John | Day, Ian N.M. | Heijer, Martin den | Duan, Jubao | Ebrahim, Shah | Elliott, Paul | Elosua, Roberto | Eiriksdottir, Gudny | Erdos, Michael R. | Eriksson, Johan G. | Facheris, Maurizio F. | Felix, Stephan B. | Fischer-Posovszky, Pamela | Folsom, Aaron R. | Friedrich, Nele | Freimer, Nelson B. | Fu, Mao | Gaget, Stefan | Gejman, Pablo V. | Geus, Eco J.C. | Gieger, Christian | Gjesing, Anette P. | Goel, Anuj | Goyette, Philippe | Grallert, Harald | Gräßler, Jürgen | Greenawalt, Danielle M. | Groves, Christopher J. | Gudnason, Vilmundur | Guiducci, Candace | Hartikainen, Anna-Liisa | Hassanali, Neelam | Hall, Alistair S. | Havulinna, Aki S. | Hayward, Caroline | Heath, Andrew C. | Hengstenberg, Christian | Hicks, Andrew A. | Hinney, Anke | Hofman, Albert | Homuth, Georg | Hui, Jennie | Igl, Wilmar | Iribarren, Carlos | Isomaa, Bo | Jacobs, Kevin B. | Jarick, Ivonne | Jewell, Elizabeth | John, Ulrich | Jørgensen, Torben | Jousilahti, Pekka | Jula, Antti | Kaakinen, Marika | Kajantie, Eero | Kaplan, Lee M. | Kathiresan, Sekar | Kettunen, Johannes | Kinnunen, Leena | Knowles, Joshua W. | Kolcic, Ivana | König, Inke R. | Koskinen, Seppo | Kovacs, Peter | Kuusisto, Johanna | Kraft, Peter | Kvaløy, Kirsti | Laitinen, Jaana | Lantieri, Olivier | Lanzani, Chiara | Launer, Lenore J. | Lecoeur, Cecile | Lehtimäki, Terho | Lettre, Guillaume | Liu, Jianjun | Lokki, Marja-Liisa | Lorentzon, Mattias | Luben, Robert N. | Ludwig, Barbara | Manunta, Paolo | Marek, Diana | Marre, Michel | Martin, Nicholas G. | McArdle, Wendy L. | McCarthy, Anne | McKnight, Barbara | Meitinger, Thomas | Melander, Olle | Meyre, David | Midthjell, Kristian | Montgomery, Grant W. | Morken, Mario A. | Morris, Andrew P. | Mulic, Rosanda | Ngwa, Julius S. | Nelis, Mari | Neville, Matt J. | Nyholt, Dale R. | O’Donnell, Christopher J. | O’Rahilly, Stephen | Ong, Ken K. | Oostra, Ben | Paré, Guillaume | Parker, Alex N. | Perola, Markus | Pichler, Irene | Pietiläinen, Kirsi H. | Platou, Carl G.P. | Polasek, Ozren | Pouta, Anneli | Rafelt, Suzanne | Raitakari, Olli | Rayner, Nigel W. | Ridderstråle, Martin | Rief, Winfried | Ruokonen, Aimo | Robertson, Neil R. | Rzehak, Peter | Salomaa, Veikko | Sanders, Alan R. | Sandhu, Manjinder S. | Sanna, Serena | Saramies, Jouko | Savolainen, Markku J. | Scherag, Susann | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Silander, Kaisa | Sinisalo, Juha | Siscovick, David S. | Smit, Jan H. | Soranzo, Nicole | Sovio, Ulla | Stephens, Jonathan | Surakka, Ida | Swift, Amy J. | Tammesoo, Mari-Liis | Tardif, Jean-Claude | Teder-Laving, Maris | Teslovich, Tanya M. | Thompson, John R. | Thomson, Brian | Tönjes, Anke | Tuomi, Tiinamaija | van Meurs, Joyce B.J. | van Ommen, Gert-Jan | Vatin, Vincent | Viikari, Jorma | Visvikis-Siest, Sophie | Vitart, Veronique | Vogel, Carla I. G. | Voight, Benjamin F. | Waite, Lindsay L. | Wallaschofski, Henri | Walters, G. Bragi | Widen, Elisabeth | Wiegand, Susanna | Wild, Sarah H. | Willemsen, Gonneke | Witte, Daniel R. | Witteman, Jacqueline C. | Xu, Jianfeng | Zhang, Qunyuan | Zgaga, Lina | Ziegler, Andreas | Zitting, Paavo | Beilby, John P. | Farooqi, I. Sadaf | Hebebrand, Johannes | Huikuri, Heikki V. | James, Alan L. | Kähönen, Mika | Levinson, Douglas F. | Macciardi, Fabio | Nieminen, Markku S. | Ohlsson, Claes | Palmer, Lyle J. | Ridker, Paul M. | Stumvoll, Michael | Beckmann, Jacques S. | Boeing, Heiner | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Collins, Francis S. | Cupples, L. Adrienne | Smith, George Davey | Erdmann, Jeanette | Froguel, Philippe | Grönberg, Henrik | Gyllensten, Ulf | Hall, Per | Hansen, Torben | Harris, Tamara B. | Hattersley, Andrew T. | Hayes, Richard B. | Heinrich, Joachim | Hu, Frank B. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Kaprio, Jaakko | Karpe, Fredrik | Khaw, Kay-Tee | Kiemeney, Lambertus A. | Krude, Heiko | Laakso, Markku | Lawlor, Debbie A. | Metspalu, Andres | Munroe, Patricia B. | Ouwehand, Willem H. | Pedersen, Oluf | Penninx, Brenda W. | Peters, Annette | Pramstaller, Peter P. | Quertermous, Thomas | Reinehr, Thomas | Rissanen, Aila | Rudan, Igor | Samani, Nilesh J. | Schwarz, Peter E.H. | Shuldiner, Alan R. | Spector, Timothy D. | Tuomilehto, Jaakko | Uda, Manuela | Uitterlinden, André | Valle, Timo T. | Wabitsch, Martin | Waeber, Gérard | Wareham, Nicholas J. | Watkins, Hugh | Wilson, James F. | Wright, Alan F. | Zillikens, M. Carola | Chatterjee, Nilanjan | McCarroll, Steven A. | Purcell, Shaun | Schadt, Eric E. | Visscher, Peter M. | Assimes, Themistocles L. | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Groop, Leif C. | Haritunians, Talin | Hunter, David J. | Kaplan, Robert C. | Mohlke, Karen L. | O’Connell, Jeffrey R. | Peltonen, Leena | Schlessinger, David | Strachan, David P. | van Duijn, Cornelia M. | Wichmann, H.-Erich | Frayling, Timothy M. | Thorsteinsdottir, Unnur | Abecasis, Gonçalo R. | Barroso, Inês | Boehnke, Michael | Stefansson, Kari | North, Kari E. | McCarthy, Mark I. | Hirschhorn, Joel N. | Ingelsson, Erik | Loos, Ruth J.F.
Nature genetics  2010;42(11):937-948.
Obesity is globally prevalent and highly heritable, but the underlying genetic factors remain largely elusive. To identify genetic loci for obesity-susceptibility, we examined associations between body mass index (BMI) 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 BMI (P<5×10−8), one of which includes a copy number variant near GPRC5B. Some loci (MC4R, POMC, SH2B1, BDNF) map near key hypothalamic regulators of energy balance, and one is near GIPR, an incretin receptor. Furthermore, genes in other newly-associated loci may provide novel insights into human body weight regulation.
doi:10.1038/ng.686
PMCID: PMC3014648  PMID: 20935630
14.  New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk 
Dupuis, Josée | Langenberg, Claudia | Prokopenko, Inga | Saxena, Richa | Soranzo, Nicole | Jackson, Anne U | Wheeler, Eleanor | Glazer, Nicole L | Bouatia-Naji, Nabila | Gloyn, Anna L | Lindgren, Cecilia M | Mägi, Reedik | Morris, Andrew P | Randall, Joshua | Johnson, Toby | Elliott, Paul | Rybin, Denis | Thorleifsson, Gudmar | Steinthorsdottir, Valgerdur | Henneman, Peter | Grallert, Harald | Dehghan, Abbas | Hottenga, Jouke Jan | Franklin, Christopher S | Navarro, Pau | Song, Kijoung | Goel, Anuj | Perry, John R B | Egan, Josephine M | Lajunen, Taina | Grarup, Niels | Sparsø, Thomas | Doney, Alex | Voight, Benjamin F | Stringham, Heather M | Li, Man | Kanoni, Stavroula | Shrader, Peter | Cavalcanti-Proença, Christine | Kumari, Meena | Qi, Lu | Timpson, Nicholas J | Gieger, Christian | Zabena, Carina | Rocheleau, Ghislain | Ingelsson, Erik | An, Ping | O’Connell, Jeffrey | Luan, Jian'an | Elliott, Amanda | McCarroll, Steven A | Payne, Felicity | Roccasecca, Rosa Maria | Pattou, François | Sethupathy, Praveen | Ardlie, Kristin | Ariyurek, Yavuz | Balkau, Beverley | Barter, Philip | Beilby, John P | Ben-Shlomo, Yoav | Benediktsson, Rafn | Bennett, Amanda J | Bergmann, Sven | Bochud, Murielle | Boerwinkle, Eric | Bonnefond, Amélie | Bonnycastle, Lori L | Borch-Johnsen, Knut | Böttcher, Yvonne | Brunner, Eric | Bumpstead, Suzannah J | Charpentier, Guillaume | Chen, Yii-Der Ida | Chines, Peter | Clarke, Robert | Coin, Lachlan J M | Cooper, Matthew N | Cornelis, Marilyn | Crawford, Gabe | Crisponi, Laura | Day, Ian N M | de Geus, Eco | Delplanque, Jerome | Dina, Christian | Erdos, Michael R | Fedson, Annette C | Fischer-Rosinsky, Antje | Forouhi, Nita G | Fox, Caroline S | Frants, Rune | Franzosi, Maria Grazia | Galan, Pilar | Goodarzi, Mark O | Graessler, Jürgen | Groves, Christopher J | Grundy, Scott | Gwilliam, Rhian | Gyllensten, Ulf | Hadjadj, Samy | Hallmans, Göran | Hammond, Naomi | Han, Xijing | Hartikainen, Anna-Liisa | Hassanali, Neelam | Hayward, Caroline | Heath, Simon C | Hercberg, Serge | Herder, Christian | Hicks, Andrew A | Hillman, David R | Hingorani, Aroon D | Hofman, Albert | Hui, Jennie | Hung, Joe | Isomaa, Bo | Johnson, Paul R V | Jørgensen, Torben | Jula, Antti | Kaakinen, Marika | Kaprio, Jaakko | Kesaniemi, Y Antero | Kivimaki, Mika | Knight, Beatrice | Koskinen, Seppo | Kovacs, Peter | Kyvik, Kirsten Ohm | Lathrop, G Mark | Lawlor, Debbie A | Le Bacquer, Olivier | Lecoeur, Cécile | Li, Yun | Lyssenko, Valeriya | Mahley, Robert | Mangino, Massimo | Manning, Alisa K | Martínez-Larrad, María Teresa | McAteer, Jarred B | McCulloch, Laura J | McPherson, Ruth | Meisinger, Christa | Melzer, David | Meyre, David | Mitchell, Braxton D | Morken, Mario A | Mukherjee, Sutapa | Naitza, Silvia | Narisu, Narisu | Neville, Matthew J | Oostra, Ben A | Orrù, Marco | Pakyz, Ruth | Palmer, Colin N A | Paolisso, Giuseppe | Pattaro, Cristian | Pearson, Daniel | Peden, John F | Pedersen, Nancy L. | Perola, Markus | Pfeiffer, Andreas F H | Pichler, Irene | Polasek, Ozren | Posthuma, Danielle | Potter, Simon C | Pouta, Anneli | Province, Michael A | Psaty, Bruce M | Rathmann, Wolfgang | Rayner, Nigel W | Rice, Kenneth | Ripatti, Samuli | Rivadeneira, Fernando | Roden, Michael | Rolandsson, Olov | Sandbaek, Annelli | Sandhu, Manjinder | Sanna, Serena | Sayer, Avan Aihie | Scheet, Paul | Scott, Laura J | Seedorf, Udo | Sharp, Stephen J | Shields, Beverley | Sigurðsson, Gunnar | Sijbrands, Erik J G | Silveira, Angela | Simpson, Laila | Singleton, Andrew | Smith, Nicholas L | Sovio, Ulla | Swift, Amy | Syddall, Holly | Syvänen, Ann-Christine | Tanaka, Toshiko | Thorand, Barbara | Tichet, Jean | Tönjes, Anke | Tuomi, Tiinamaija | Uitterlinden, André G | van Dijk, Ko Willems | van Hoek, Mandy | Varma, Dhiraj | Visvikis-Siest, Sophie | Vitart, Veronique | Vogelzangs, Nicole | Waeber, Gérard | Wagner, Peter J | Walley, Andrew | Walters, G Bragi | Ward, Kim L | Watkins, Hugh | Weedon, Michael N | Wild, Sarah H | Willemsen, Gonneke | Witteman, Jaqueline C M | Yarnell, John W G | Zeggini, Eleftheria | Zelenika, Diana | Zethelius, Björn | Zhai, Guangju | Zhao, Jing Hua | Zillikens, M Carola | Borecki, Ingrid B | Loos, Ruth J F | Meneton, Pierre | Magnusson, Patrik K E | Nathan, David M | Williams, Gordon H | Hattersley, Andrew T | Silander, Kaisa | Salomaa, Veikko | Smith, George Davey | Bornstein, Stefan R | Schwarz, Peter | Spranger, Joachim | Karpe, Fredrik | Shuldiner, Alan R | Cooper, Cyrus | Dedoussis, George V | Serrano-Ríos, Manuel | Morris, Andrew D | Lind, Lars | Palmer, Lyle J | Hu, Frank B. | Franks, Paul W | Ebrahim, Shah | Marmot, Michael | Kao, W H Linda | Pankow, James S | Sampson, Michael J | Kuusisto, Johanna | Laakso, Markku | Hansen, Torben | Pedersen, Oluf | Pramstaller, Peter Paul | Wichmann, H Erich | Illig, Thomas | Rudan, Igor | Wright, Alan F | Stumvoll, Michael | Campbell, Harry | Wilson, James F | Hamsten, Anders | Bergman, Richard N | Buchanan, Thomas A | Collins, Francis S | Mohlke, Karen L | Tuomilehto, Jaakko | Valle, Timo T | Altshuler, David | Rotter, Jerome I | Siscovick, David S | Penninx, Brenda W J H | Boomsma, Dorret | Deloukas, Panos | Spector, Timothy D | Frayling, Timothy M | Ferrucci, Luigi | Kong, Augustine | Thorsteinsdottir, Unnur | Stefansson, Kari | van Duijn, Cornelia M | Aulchenko, Yurii S | Cao, Antonio | Scuteri, Angelo | Schlessinger, David | Uda, Manuela | Ruokonen, Aimo | Jarvelin, Marjo-Riitta | Waterworth, Dawn M | Vollenweider, Peter | Peltonen, Leena | Mooser, Vincent | Abecasis, Goncalo R | Wareham, Nicholas J | Sladek, Robert | Froguel, Philippe | Watanabe, Richard M | Meigs, James B | Groop, Leif | Boehnke, Michael | McCarthy, Mark I | Florez, Jose C | Barroso, Inês
Nature genetics  2010;42(2):105-116.
Circulating glucose levels are tightly regulated. To identify novel glycemic loci, we performed meta-analyses of 21 genome-wide associations studies informative for fasting glucose (FG), fasting insulin (FI) and indices of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 non-diabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with FG/HOMA-B and two associated with FI/HOMA-IR. These include nine new FG loci (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and FAM148B) and one influencing FI/HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB/TMEM195 with type 2 diabetes (T2D). Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify T2D risk loci, as well as loci that elevate FG modestly, but do not cause overt diabetes.
doi:10.1038/ng.520
PMCID: PMC3018764  PMID: 20081858
15.  Using inactivating mutations to provide insight into drug action 
Genome Medicine  2015;7(1):7.
The role of ezetimibe in lowering plasma cholesterol has been established; however, controversy remains about its clinical benefit. A recent study utilizes naturally occurring genetic variation within the NPC1-like 1 gene (NPC1L1) to demonstrate the potential for pharmacologic inhibition of the protein to reduce the risk of coronary heart disease. This research demonstrates the application of the concept of genocopy to a population-based validation of NPC1L1 as a therapeutic target.
doi:10.1186/s13073-015-0130-x
PMCID: PMC4307143  PMID: 25628760
16.  HMG-coenzyme A reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials 
Swerdlow, Daniel I | Preiss, David | Kuchenbaecker, Karoline B | Holmes, Michael V | Engmann, Jorgen E L | Shah, Tina | Sofat, Reecha | Stender, Stefan | Johnson, Paul C D | Scott, Robert A | Leusink, Maarten | Verweij, Niek | Sharp, Stephen J | Guo, Yiran | Giambartolomei, Claudia | Chung, Christina | Peasey, Anne | Amuzu, Antoinette | Li, KaWah | Palmen, Jutta | Howard, Philip | Cooper, Jackie A | Drenos, Fotios | Li, Yun R | Lowe, Gordon | Gallacher, John | Stewart, Marlene C W | Tzoulaki, Ioanna | Buxbaum, Sarah G | van der A, Daphne L | Forouhi, Nita G | Onland-Moret, N Charlotte | van der Schouw, Yvonne T | Schnabel, Renate B | Hubacek, Jaroslav A | Kubinova, Ruzena | Baceviciene, Migle | Tamosiunas, Abdonas | Pajak, Andrzej | Topor-Madry, Romanvan | Stepaniak, Urszula | Malyutina, Sofia | Baldassarre, Damiano | Sennblad, Bengt | Tremoli, Elena | de Faire, Ulf | Veglia, Fabrizio | Ford, Ian | Jukema, J Wouter | Westendorp, Rudi G J | de Borst, Gert Jan | de Jong, Pim A | Algra, Ale | Spiering, Wilko | der Zee, Anke H Maitland-van | Klungel, Olaf H | de Boer, Anthonius | Doevendans, Pieter A | Eaton, Charles B | Robinson, Jennifer G | Duggan, David | Kjekshus, John | Downs, John R | Gotto, Antonio M | Keech, Anthony C | Marchioli, Roberto | Tognoni, Gianni | Sever, Peter S | Poulter, Neil R | Waters, David D | Pedersen, Terje R | Amarenco, Pierre | Nakamura, Haruo | McMurray, John J V | Lewsey, James D | Chasman, Daniel I | Ridker, Paul M | Maggioni, Aldo P | Tavazzi, Luigi | Ray, Kausik K | Seshasai, Sreenivasa Rao Kondapally | Manson, JoAnn E | Price, Jackie F | Whincup, Peter H | Morris, Richard W | Lawlor, Debbie A | Smith, George Davey | Ben-Shlomo, Yoav | Schreiner, Pamela J | Fornage, Myriam | Siscovick, David S | Cushman, Mary | Kumari, Meena | Wareham, Nick J | Verschuren, W M Monique | Redline, Susan | Patel, Sanjay R | Whittaker, John C | Hamsten, Anders | Delaney, Joseph A | Dale, Caroline | Gaunt, Tom R | Wong, Andrew | Kuh, Diana | Hardy, Rebecca | Kathiresan, Sekar | Castillo, Berta A | van der Harst, Pim | Brunner, Eric J | Tybjaerg-Hansen, Anne | Marmot, Michael G | Krauss, Ronald M | Tsai, Michael | Coresh, Josef | Hoogeveen, Ronald C | Psaty, Bruce M | Lange, Leslie A | Hakonarson, Hakon | Dudbridge, Frank | Humphries, Steve E | Talmud, Philippa J | Kivimäki, Mika | Timpson, Nicholas J | Langenberg, Claudia | Asselbergs, Folkert W | Voevoda, Mikhail | Bobak, Martin | Pikhart, Hynek | Wilson, James G | Reiner, Alex P | Keating, Brendan J | Hingorani, Aroon D | Sattar, Naveed
Lancet  2015;385(9965):351-361.
Summary
Background
Statins increase the risk of new-onset type 2 diabetes mellitus. We aimed to assess whether this increase in risk is a consequence of inhibition of 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), the intended drug target.
Methods
We used single nucleotide polymorphisms in the HMGCR gene, rs17238484 (for the main analysis) and rs12916 (for a subsidiary analysis) as proxies for HMGCR inhibition by statins. We examined associations of these variants with plasma lipid, glucose, and insulin concentrations; bodyweight; waist circumference; and prevalent and incident type 2 diabetes. Study-specific effect estimates per copy of each LDL-lowering allele were pooled by meta-analysis. These findings were compared with a meta-analysis of new-onset type 2 diabetes and bodyweight change data from randomised trials of statin drugs. The effects of statins in each randomised trial were assessed using meta-analysis.
Findings
Data were available for up to 223 463 individuals from 43 genetic studies. Each additional rs17238484-G allele was associated with a mean 0·06 mmol/L (95% CI 0·05–0·07) lower LDL cholesterol and higher body weight (0·30 kg, 0·18–0·43), waist circumference (0·32 cm, 0·16–0·47), plasma insulin concentration (1·62%, 0·53–2·72), and plasma glucose concentration (0·23%, 0·02–0·44). The rs12916 SNP had similar effects on LDL cholesterol, bodyweight, and waist circumference. The rs17238484-G allele seemed to be associated with higher risk of type 2 diabetes (odds ratio [OR] per allele 1·02, 95% CI 1·00–1·05); the rs12916-T allele association was consistent (1·06, 1·03–1·09). In 129 170 individuals in randomised trials, statins lowered LDL cholesterol by 0·92 mmol/L (95% CI 0·18–1·67) at 1-year of follow-up, increased bodyweight by 0·24 kg (95% CI 0·10–0·38 in all trials; 0·33 kg, 95% CI 0·24–0·42 in placebo or standard care controlled trials and −0·15 kg, 95% CI −0·39 to 0·08 in intensive-dose vs moderate-dose trials) at a mean of 4·2 years (range 1·9–6·7) of follow-up, and increased the odds of new-onset type 2 diabetes (OR 1·12, 95% CI 1·06–1·18 in all trials; 1·11, 95% CI 1·03–1·20 in placebo or standard care controlled trials and 1·12, 95% CI 1·04–1·22 in intensive-dose vs moderate dose trials).
Interpretation
The increased risk of type 2 diabetes noted with statins is at least partially explained by HMGCR inhibition.
Funding
The funding sources are cited at the end of the paper.
doi:10.1016/S0140-6736(14)61183-1
PMCID: PMC4322187  PMID: 25262344
17.  Variation in the SLC23A1 gene does not influence cardiometabolic outcomes to the extent expected given its association with l-ascorbic acid1234 
Background: Observational studies showed that circulating l-ascorbic acid (vitamin C) is inversely associated with cardiometabolic traits. However, these studies were susceptible to confounding and reverse causation.
Objectives: We assessed the relation between l-ascorbic acid and 10 cardiometabolic traits by using a single nucleotide polymorphism in the solute carrier family 23 member 1 (SLC23A1) gene (rs33972313) associated with circulating l-ascorbic acid concentrations. The observed association between rs33972313 and cardiometabolic outcomes was compared with that expected given the rs33972313-l-ascorbic acid and l-ascorbic acid–outcome associations.
Design: A meta-analysis was performed in the following 5 independent studies: the British Women's Heart and Health Study (n = 1833), the MIDSPAN study (n = 1138), the Ten Towns study (n = 1324), the British Regional Heart Study (n = 2521), and the European Prospective Investigation into Cancer (n = 3737).
Results: With the use of a meta-analysis of observational estimates, inverse associations were shown between l-ascorbic acid and systolic blood pressure, triglycerides, and the waist-hip ratio [the strongest of which was the waist-hip ratio (−0.13-SD change; 95% CI: −0.20-, −0.07-SD change; P = 0.0001) per SD increase in l-ascorbic acid], and a positive association was shown with high-density lipoprotein (HDL) cholesterol. The variation at rs33972313 was associated with a 0.18-SD (95% CI: 0.10-, 0.25-SD; P = 3.34 × 10−6) increase in l-ascorbic acid per effect allele. There was no evidence of a relation between the variation at rs33972313 and any cardiometabolic outcome. Although observed estimates were not statistically different from expected associations between rs33972313 and cardiometabolic outcomes, estimates for low-density lipoprotein cholesterol, HDL cholesterol, triglycerides, glucose, and body mass index were in the opposite direction to those expected.
Conclusions: The nature of the genetic association exploited in this study led to limited statistical application, but despite this, when all cardiometabolic traits were assessed, there was no evidence of any trend supporting a protective role of l-ascorbic acid. In the context of existing work, these results add to the suggestion that observational relations between l-ascorbic acid and cardiometabolic health may be attributable to confounding and reverse causation.
doi:10.3945/ajcn.114.092981
PMCID: PMC4266888  PMID: 25527764
l-ascorbic acid; cardiometabolic traits; confounding; genetic variants; reverse causation
18.  Genome-wide association study identifies loci affecting blood copper, selenium and zinc 
Human Molecular Genetics  2013;22(19):3998-4006.
Genetic variation affecting absorption, distribution or excretion of essential trace elements may lead to health effects related to sub-clinical deficiency. We have tested for allelic effects of single-nucleotide polymorphisms (SNPs) on blood copper, selenium and zinc in a genome-wide association study using two adult cohorts from Australia and the UK. Participants were recruited in Australia from twins and their families and in the UK from pregnant women. We measured erythrocyte Cu, Se and Zn (Australian samples) or whole blood Se (UK samples) using inductively coupled plasma mass spectrometry. Genotyping was performed with Illumina chips and >2.5 m SNPs were imputed from HapMap data. Genome-wide significant associations were found for each element. For Cu, there were two loci on chromosome 1 (most significant SNPs rs1175550, P = 5.03 × 10−10, and rs2769264, P = 2.63 × 10−20); for Se, a locus on chromosome 5 was significant in both cohorts (combined P = 9.40 × 10−28 at rs921943); and for Zn three loci on chromosomes 8, 15 and X showed significant results (rs1532423, P = 6.40 × 10−12; rs2120019, P = 1.55 × 10−18; and rs4826508, P = 1.40 × 10−12, respectively). The Se locus covers three genes involved in metabolism of sulphur-containing amino acids and potentially of the analogous Se compounds; the chromosome 8 locus for Zn contains multiple genes for the Zn-containing enzyme carbonic anhydrase. Where potentially relevant genes were identified, they relate to metabolism of the element (Se) or to the presence at high concentration of a metal-containing protein (Cu).
doi:10.1093/hmg/ddt239
PMCID: PMC3766178  PMID: 23720494
19.  Genetic Variation Associated with Differential Educational Attainment in Adults Has Anticipated Associations with School Performance in Children 
PLoS ONE  2014;9(7):e100248.
Genome-wide association study results have yielded evidence for the association of common genetic variants with crude measures of completed educational attainment in adults. Whilst informative, these results do not inform as to the mechanism of these effects or their presence at earlier ages and where educational performance is more routinely and more precisely assessed. Single nucleotide polymorphisms exhibiting genome-wide significant associations with adult educational attainment were combined to derive an unweighted allele score in 5,979 and 6,145 young participants from the Avon Longitudinal Study of Parents and Children with key stage 3 national curriculum test results (SATS results) available at age 13 to 14 years in English and mathematics respectively. Standardised (z-scored) results for English and mathematics showed an expected relationship with sex, with girls exhibiting an advantage over boys in English (0.433 SD (95%CI 0.395, 0.470), p<10−10) with more similar results (though in the opposite direction) in mathematics (0.042 SD (95%CI 0.004, 0.080), p = 0.030). Each additional adult educational attainment increasing allele was associated with 0.041 SD (95%CI 0.020, 0.063), p = 1.79×10−04 and 0.028 SD (95%CI 0.007, 0.050), p = 0.01 increases in standardised SATS score for English and mathematics respectively. Educational attainment is a complex multifactorial behavioural trait which has not had heritable contributions to it fully characterised. We were able to apply the results from a large study of adult educational attainment to a study of child exam performance marking events in the process of learning rather than realised adult end product. Our results support evidence for common, small genetic contributions to educational attainment, but also emphasise the likely lifecourse nature of this genetic effect. Results here also, by an alternative route, suggest that existing methods for child examination are able to recognise early life variation likely to be related to ultimate educational attainment.
doi:10.1371/journal.pone.0100248
PMCID: PMC4102483  PMID: 25032841
20.  Genome Wide Association Identifies Common Variants at the SERPINA6/SERPINA1 Locus Influencing Plasma Cortisol and Corticosteroid Binding Globulin 
PLoS Genetics  2014;10(7):e1004474.
Variation in plasma levels of cortisol, an essential hormone in the stress response, is associated in population-based studies with cardio-metabolic, inflammatory and neuro-cognitive traits and diseases. Heritability of plasma cortisol is estimated at 30–60% but no common genetic contribution has been identified. The CORtisol NETwork (CORNET) consortium undertook genome wide association meta-analysis for plasma cortisol in 12,597 Caucasian participants, replicated in 2,795 participants. The results indicate that <1% of variance in plasma cortisol is accounted for by genetic variation in a single region of chromosome 14. This locus spans SERPINA6, encoding corticosteroid binding globulin (CBG, the major cortisol-binding protein in plasma), and SERPINA1, encoding α1-antitrypsin (which inhibits cleavage of the reactive centre loop that releases cortisol from CBG). Three partially independent signals were identified within the region, represented by common SNPs; detailed biochemical investigation in a nested sub-cohort showed all these SNPs were associated with variation in total cortisol binding activity in plasma, but some variants influenced total CBG concentrations while the top hit (rs12589136) influenced the immunoreactivity of the reactive centre loop of CBG. Exome chip and 1000 Genomes imputation analysis of this locus in the CROATIA-Korcula cohort identified missense mutations in SERPINA6 and SERPINA1 that did not account for the effects of common variants. These findings reveal a novel common genetic source of variation in binding of cortisol by CBG, and reinforce the key role of CBG in determining plasma cortisol levels. In turn this genetic variation may contribute to cortisol-associated degenerative diseases.
Author Summary
Cortisol is a steroid hormone from the adrenal glands that is essential in the response to stress. Most cortisol in blood is bound to corticosteroid binding globulin (CBG). Diseases causing cortisol deficiency (Addison's disease) or excess (Cushing's syndrome) are life-threatening. Variations in plasma cortisol have been associated with cardiovascular and psychiatric diseases and their risk factors. To dissect the genetic contribution to variation in plasma cortisol, we formed the CORtisol NETwork (CORNET) consortium and recruited collaborators with suitable samples from more than 15,000 people. The results reveal that the major genetic influence on plasma cortisol is mediated by variations in the binding capacity of CBG. This is determined by differences in the circulating concentrations of CBG and also in the immunoreactivity of its ‘reactive centre loop’, potentially influencing not only binding affinity for cortisol but also the stability of CBG and hence the tissue delivery of cortisol. These findings provide the first evidence for a common genetic effect on levels of this clinically important hormone, suggest that differences in CBG between individuals are biologically important, and pave the way for further research to dissect causality in the associations of plasma cortisol with common diseases.
doi:10.1371/journal.pgen.1004474
PMCID: PMC4091794  PMID: 25010111
21.  Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity 
Human Molecular Genetics  2013;22(13):2735-2747.
The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10−8) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
doi:10.1093/hmg/ddt104
PMCID: PMC3674797  PMID: 23449627
22.  Phenotypic Dissection of Bone Mineral Density Reveals Skeletal Site Specificity and Facilitates the Identification of Novel Loci in the Genetic Regulation of Bone Mass Attainment 
PLoS Genetics  2014;10(6):e1004423.
Heritability of bone mineral density (BMD) varies across skeletal sites, reflecting different relative contributions of genetic and environmental influences. To quantify the degree to which common genetic variants tag and environmental factors influence BMD, at different sites, we estimated the genetic (rg) and residual (re) correlations between BMD measured at the upper limbs (UL-BMD), lower limbs (LL-BMD) and skull (SK-BMD), using total-body DXA scans of ∼4,890 participants recruited by the Avon Longitudinal Study of Parents and their Children (ALSPAC). Point estimates of rg indicated that appendicular sites have a greater proportion of shared genetic architecture (LL-/UL-BMD rg = 0.78) between them, than with the skull (UL-/SK-BMD rg = 0.58 and LL-/SK-BMD rg = 0.43). Likewise, the residual correlation between BMD at appendicular sites (re = 0.55) was higher than the residual correlation between SK-BMD and BMD at appendicular sites (re = 0.20–0.24). To explore the basis for the observed differences in rg and re, genome-wide association meta-analyses were performed (n∼9,395), combining data from ALSPAC and the Generation R Study identifying 15 independent signals from 13 loci associated at genome-wide significant level across different skeletal regions. Results suggested that previously identified BMD-associated variants may exert site-specific effects (i.e. differ in the strength of their association and magnitude of effect across different skeletal sites). In particular, variants at CPED1 exerted a larger influence on SK-BMD and UL-BMD when compared to LL-BMD (P = 2.01×10−37), whilst variants at WNT16 influenced UL-BMD to a greater degree when compared to SK- and LL-BMD (P = 2.31×10−14). In addition, we report a novel association between RIN3 (previously associated with Paget's disease) and LL-BMD (rs754388: β = 0.13, SE = 0.02, P = 1.4×10−10). Our results suggest that BMD at different skeletal sites is under a mixture of shared and specific genetic and environmental influences. Allowing for these differences by performing genome-wide association at different skeletal sites may help uncover new genetic influences on BMD.
Author Summary
The heritability of bone mineral density (BMD) varies across skeletal sites, reflecting different relative contributions of genetic and environmental influences. To investigate whether the genes underlying bone acquisition act in a site-specific manner, we quantified the shared genetic influences across axial and appendicular skeletal sites by estimating the genetic and residual correlation of BMD at the upper limb, lower limb and the skull. Our results suggest that different skeletal sites as measured by total-body Dual-Energy X-Ray Absorptiometry are to a certain extent under distinct genetic and environmental influences. To further explore the basis for these differences, genome-wide association meta-analyses were performed to identify genetic loci that are preferentially associated with one or more skeletal regions. Variants at 13 loci (including RIN3, a novel BMD associated locus) reached genome-wide significance and several displayed evidence of differential association with BMD across the different skeletal sites in particular CPED1 and WNT16. Our results suggest that it may be advantageous to decompose the total-body BMD measures and perform GWAS at separate skeletal regions. By allowing for site-specific differences, new genetic variants affecting BMD and future risk of osteoporosis may be uncovered.
doi:10.1371/journal.pgen.1004423
PMCID: PMC4063697  PMID: 24945404
23.  Assessing Causality in the Association between Child Adiposity and Physical Activity Levels: A Mendelian Randomization Analysis 
PLoS Medicine  2014;11(3):e1001618.
Here, Timpson and colleagues performed a Mendelian Randomization analysis to determine whether childhood adiposity causally influences levels of physical activity. The results suggest that increased adiposity causes a reduction in physical activity in children; however, this study does not exclude lower physical activity also leading to increasing adiposity.
Please see later in the article for the Editors' Summary
Background
Cross-sectional studies have shown that objectively measured physical activity is associated with childhood adiposity, and a strong inverse dose–response association with body mass index (BMI) has been found. However, few studies have explored the extent to which this association reflects reverse causation. We aimed to determine whether childhood adiposity causally influences levels of physical activity using genetic variants reliably associated with adiposity to estimate causal effects.
Methods and Findings
The Avon Longitudinal Study of Parents and Children collected data on objectively assessed activity levels of 4,296 children at age 11 y with recorded BMI and genotypic data. We used 32 established genetic correlates of BMI combined in a weighted allelic score as an instrumental variable for adiposity to estimate the causal effect of adiposity on activity.
In observational analysis, a 3.3 kg/m2 (one standard deviation) higher BMI was associated with 22.3 (95% CI, 17.0, 27.6) movement counts/min less total physical activity (p = 1.6×10−16), 2.6 (2.1, 3.1) min/d less moderate-to-vigorous-intensity activity (p = 3.7×10−29), and 3.5 (1.5, 5.5) min/d more sedentary time (p = 5.0×10−4). In Mendelian randomization analyses, the same difference in BMI was associated with 32.4 (0.9, 63.9) movement counts/min less total physical activity (p = 0.04) (∼5.3% of the mean counts/minute), 2.8 (0.1, 5.5) min/d less moderate-to-vigorous-intensity activity (p = 0.04), and 13.2 (1.3, 25.2) min/d more sedentary time (p = 0.03). There was no strong evidence for a difference between variable estimates from observational estimates. Similar results were obtained using fat mass index. Low power and poor instrumentation of activity limited causal analysis of the influence of physical activity on BMI.
Conclusions
Our results suggest that increased adiposity causes a reduction in physical activity in children and support research into the targeting of BMI in efforts to increase childhood activity levels. Importantly, this does not exclude lower physical activity also leading to increased adiposity, i.e., bidirectional causation.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
The World Health Organization estimates that globally at least 42 million children under the age of five are obese. The World Health Organization recommends that all children undertake at least one hour of physical activity daily, on the basis that increased physical activity will reduce or prevent excessive weight gain in children and adolescents. In practice, while numerous studies have shown that body mass index (BMI) shows a strong inverse correlation with physical activity (i.e., active children are thinner than sedentary ones), exercise programs specifically targeted at obese children have had only very limited success in reducing weight. The reasons for this are not clear, although environmental factors such as watching television and lack of exercise facilities are traditionally blamed.
Why Was This Study Done?
One of the reasons why obese children do not lose weight through exercise might be that being fat in itself leads to a decrease in physical activity. This is termed reverse causation, i.e., obesity causes sedentary behavior, rather than the other way around. The potential influence of environmental factors (e.g., lack of opportunity to exercise) makes it difficult to prove this argument. Recent research has demonstrated that specific genotypes are related to obesity in children. Specific variations within the DNA of individual genes (single nucleotide polymorphisms, or SNPs) are more common in obese individuals and predispose to greater adiposity across the weight distribution. While adiposity itself can be influenced by many environmental factors that complicate the interpretation of observed associations, at the population level, genetic variation is not related to the same factors, and over the life course cannot be changed. Investigations that exploit these properties of genetic associations to inform the interpretation of observed associations are termed Mendelian randomization studies. This research technique is used to reduce the influence of confounding environmental factors on an observed clinical condition. The authors of this study use Mendelian randomization to determine whether a genetic tendency towards high BMI and fat mass is correlated with reduced levels of physical activity in a large cohort of children.
What Did the Researchers Do and Find?
The researchers looked at a cohort of children from a large long-term health research project (the Avon Longitudinal Study of Parents and Children). BMI and total body fat were recorded. Total daily activity was measured via a small movement-counting device. In addition, the participants underwent genotyping to detect the presence of several SNPs known to be linked to obesity. For each child a total BMI allelic score was determined based on the number of obesity-related genetic variants carried by that individual. The association between obesity and reduced physical activity was then studied in two ways. Direct correlation between actual BMI and physical activity was measured (observational data). Separately, the link between BMI allelic score and physical activity was also determined (Mendelian randomization or instrumental variable analysis). The observational data showed that boys were more active than girls and had lower BMI. Across both sexes, a higher-than-average BMI was associated with lower daily activity. In genetic analyses, allelic score had a positive correlation with BMI, with one particular SNP being most strongly linked to high BMI and total fat mass. A high allelic score for BMI was also correlated with lower levels of daily physical activity. The authors conclude that children who are obese and have an inherent predisposition to high BMI also have a propensity to reduced levels of physical activity, which may compound their weight gain.
What Do These Findings Mean?
This study provides evidence that being fat is in itself a risk factor for low activity levels, separately from external environmental influences. This may be an example of “reverse causation,” i.e., high BMI causes a reduction in physical activity. Alternatively, there may be a bidirectional causality, so that those with a genetic predisposition to high fat mass exercise less, leading to higher BMI, and so on, in a vicious circle. A significant limitation of the study is that validated allelic scores for physical activity are not available. Thus, it is not possible to determine whether individuals with a high allelic score for BMI also have a propensity to exercise less, or whether it is simply the circumstance of being overweight that discourages activity. This study does suggest that trying to persuade obese children to lose weight by exercising more is likely to be ineffective unless additional strategies to reduce BMI, such as strict diet control, are also implemented.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001618.
The US Centers for Disease Control and Prevention provides obesity-related statistics, details of prevention programs, and an overview on public health strategy in the United States
A more worldwide view is given by the World Health Organization
The UK National Health Service website gives information on physical activity guidelines for different age groups
The International Obesity Task Force is a network of organizations that seeks to alert the world to the growing health crisis threatened by soaring levels of obesity
MedlinePlus—which brings together authoritative information from the US National Library of Medicine, National Institutes of Health, and other government agencies and health-related organizations—has a page on obesity
Additional information on the Avon Longitudinal Study of Parents and Children is available
The British Medical Journal has an article that describes Mendelian randomization
doi:10.1371/journal.pmed.1001618
PMCID: PMC3958348  PMID: 24642734
24.  META-ANALYSIS OF GENOME-WIDE STUDIES IDENTIFIES WNT16 AND ESR1 SNPS ASSOCIATED WITH BONE MINERAL DENSITY IN PREMENOPAUSAL WOMEN 
Previous genome-wide association studies (GWAS) have identified common variants in genes associated with variation in bone mineral density (BMD), although most have been carried out in combined samples of older women and men. Meta-analyses of these results have identified numerous SNPs of modest effect at genome-wide significance levels in genes involved in both bone formation and resorption, as well as other pathways. We performed a meta-analysis restricted to premenopausal white women from four cohorts (n= 4,061 women, ages 20 to 45) to identify genes influencing peak bone mass at the lumbar spine and femoral neck. Following imputation, age- and weight-adjusted BMD values were tested for association with each SNP. Association of a SNP in the WNT16 gene (rs3801387; p=1.7 × 10−9) and multiple SNPs in the ESR1/C6orf97 (rs4870044; p=1.3 × 10−8) achieved genome-wide significance levels for lumbar spine BMD. These SNPs, along with others demonstrating suggestive evidence of association, were then tested for association in seven Replication cohorts that included premenopausal women of European, Hispanic-American, and African-American descent (combined n=5,597 for femoral neck; 4,744 for lumbar spine). When the data from the Discovery and Replication cohorts were analyzed jointly, the evidence was more significant (WNT16 joint p=1.3 × 10−11; ESR1/C6orf97 joint p= 1.4 × 10−10). Multiple independent association signals were observed with spine BMD at the ESR1 region after conditioning on the primary signal. Analyses of femoral neck BMD also supported association with SNPs in WNT16 and ESR1/C6orf97 (p< 1 × 10−5). Our results confirm that several of the genes contributing to BMD variation across a broad age range in both sexes have effects of similar magnitude on BMD of the spine in premenopausal women. These data support the hypothesis that variants in these genes of known skeletal function also affect BMD during the premenopausal period.
doi:10.1002/jbmr.1796
PMCID: PMC3691010  PMID: 23074152
Bone mineral density; GWAS; premenopausal; meta-analysis; genetics
25.  Variability in the common genetic architecture of social-communication spectrum phenotypes during childhood and adolescence 
Molecular Autism  2014;5:18.
Background
Social-communication abilities are heritable traits, and their impairments overlap with the autism continuum. To characterise the genetic architecture of social-communication difficulties developmentally and identify genetic links with the autistic dimension, we conducted a genome-wide screen of social-communication problems at multiple time-points during childhood and adolescence.
Methods
Social-communication difficulties were ascertained at ages 8, 11, 14 and 17 years in a UK population-based birth cohort (Avon Longitudinal Study of Parents and Children; N ≤ 5,628) using mother-reported Social Communication Disorder Checklist scores. Genome-wide Complex Trait Analysis (GCTA) was conducted for all phenotypes. The time-points with the highest GCTA heritability were subsequently analysed for single SNP association genome-wide. Type I error in the presence of measurement relatedness and the likelihood of observing SNP signals near known autism susceptibility loci (co-location) were assessed via large-scale, genome-wide permutations. Association signals (P ≤ 10−5) were also followed up in Autism Genetic Resource Exchange pedigrees (N = 793) and the Autism Case Control cohort (Ncases/Ncontrols = 1,204/6,491).
Results
GCTA heritability was strongest in childhood (h2(8 years) = 0.24) and especially in later adolescence (h2(17 years) = 0.45), with a marked drop during early to middle adolescence (h2(11 years) = 0.16 and h2(14 years) = 0.08). Genome-wide screens at ages 8 and 17 years identified for the latter time-point evidence for association at 3p22.2 near SCN11A (rs4453791, P = 9.3 × 10−9; genome-wide empirical P = 0.011) and suggestive evidence at 20p12.3 at PLCB1 (rs3761168, P = 7.9 × 10−8; genome-wide empirical P = 0.085). None of these signals contributed to risk for autism. However, the co-location of population-based signals and autism susceptibility loci harbouring rare mutations, such as PLCB1, is unlikely to be due to chance (genome-wide empirical Pco-location = 0.007).
Conclusions
Our findings suggest that measurable common genetic effects for social-communication difficulties vary developmentally and that these changes may affect detectable overlaps with the autism spectrum.
doi:10.1186/2040-2392-5-18
PMCID: PMC3940728  PMID: 24564958
ALSPAC; ASD; Autism; GCTA heritability; GWAS; Social communication

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