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1.  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
2.  Discovery and Refinement of Loci Associated with Lipid Levels 
Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Do, Ron | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian’an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O’Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Ingi Eyjolfsson, Gudmundur | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Kathiresan, Sekar | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Gonçalo R.
Nature genetics  2013;45(11):10.1038/ng.2797.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
doi:10.1038/ng.2797
PMCID: PMC3838666  PMID: 24097068
3.  Common variants associated with plasma triglycerides and risk for coronary artery disease 
Do, Ron | Willer, Cristen J. | Schmidt, Ellen M. | Sengupta, Sebanti | Gao, Chi | Peloso, Gina M. | Gustafsson, Stefan | Kanoni, Stavroula | Ganna, Andrea | Chen, Jin | Buchkovich, Martin L. | Mora, Samia | Beckmann, Jacques S. | Bragg-Gresham, Jennifer L. | Chang, Hsing-Yi | Demirkan, Ayşe | Den Hertog, Heleen M. | Donnelly, Louise A. | Ehret, Georg B. | Esko, Tõnu | Feitosa, Mary F. | Ferreira, Teresa | Fischer, Krista | Fontanillas, Pierre | Fraser, Ross M. | Freitag, Daniel F. | Gurdasani, Deepti | Heikkilä, Kauko | Hyppönen, Elina | Isaacs, Aaron | Jackson, Anne U. | Johansson, Åsa | Johnson, Toby | Kaakinen, Marika | Kettunen, Johannes | Kleber, Marcus E. | Li, Xiaohui | Luan, Jian'an | Lyytikäinen, Leo-Pekka | Magnusson, Patrik K.E. | Mangino, Massimo | Mihailov, Evelin | Montasser, May E. | Müller-Nurasyid, Martina | Nolte, Ilja M. | O'Connell, Jeffrey R. | Palmer, Cameron D. | Perola, Markus | Petersen, Ann-Kristin | Sanna, Serena | Saxena, Richa | Service, Susan K. | Shah, Sonia | Shungin, Dmitry | Sidore, Carlo | Song, Ci | Strawbridge, Rona J. | Surakka, Ida | Tanaka, Toshiko | Teslovich, Tanya M. | Thorleifsson, Gudmar | Van den Herik, Evita G. | Voight, Benjamin F. | Volcik, Kelly A. | Waite, Lindsay L. | Wong, Andrew | Wu, Ying | Zhang, Weihua | Absher, Devin | Asiki, Gershim | Barroso, Inês | Been, Latonya F. | Bolton, Jennifer L. | Bonnycastle, Lori L | Brambilla, Paolo | Burnett, Mary S. | Cesana, Giancarlo | Dimitriou, Maria | Doney, Alex S.F. | Döring, Angela | Elliott, Paul | Epstein, Stephen E. | Eyjolfsson, Gudmundur Ingi | Gigante, Bruna | Goodarzi, Mark O. | Grallert, Harald | Gravito, Martha L. | Groves, Christopher J. | Hallmans, Göran | Hartikainen, Anna-Liisa | Hayward, Caroline | Hernandez, Dena | Hicks, Andrew A. | Holm, Hilma | Hung, Yi-Jen | Illig, Thomas | Jones, Michelle R. | Kaleebu, Pontiano | Kastelein, John J.P. | Khaw, Kay-Tee | Kim, Eric | Klopp, Norman | Komulainen, Pirjo | Kumari, Meena | Langenberg, Claudia | Lehtimäki, Terho | Lin, Shih-Yi | Lindström, Jaana | Loos, Ruth J.F. | Mach, François | McArdle, Wendy L | Meisinger, Christa | Mitchell, Braxton D. | Müller, Gabrielle | Nagaraja, Ramaiah | Narisu, Narisu | Nieminen, Tuomo V.M. | Nsubuga, Rebecca N. | Olafsson, Isleifur | Ong, Ken K. | Palotie, Aarno | Papamarkou, Theodore | Pomilla, Cristina | Pouta, Anneli | Rader, Daniel J. | Reilly, Muredach P. | Ridker, Paul M. | Rivadeneira, Fernando | Rudan, Igor | Ruokonen, Aimo | Samani, Nilesh | Scharnagl, Hubert | Seeley, Janet | Silander, Kaisa | Stančáková, Alena | Stirrups, Kathleen | Swift, Amy J. | Tiret, Laurence | Uitterlinden, Andre G. | van Pelt, L. Joost | Vedantam, Sailaja | Wainwright, Nicholas | Wijmenga, Cisca | Wild, Sarah H. | Willemsen, Gonneke | Wilsgaard, Tom | Wilson, James F. | Young, Elizabeth H. | Zhao, Jing Hua | Adair, Linda S. | Arveiler, Dominique | Assimes, Themistocles L. | Bandinelli, Stefania | Bennett, Franklyn | Bochud, Murielle | Boehm, Bernhard O. | Boomsma, Dorret I. | Borecki, Ingrid B. | Bornstein, Stefan R. | Bovet, Pascal | Burnier, Michel | Campbell, Harry | Chakravarti, Aravinda | Chambers, John C. | Chen, Yii-Der Ida | Collins, Francis S. | Cooper, Richard S. | Danesh, John | Dedoussis, George | de Faire, Ulf | Feranil, Alan B. | Ferrières, Jean | Ferrucci, Luigi | Freimer, Nelson B. | Gieger, Christian | Groop, Leif C. | Gudnason, Vilmundur | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hingorani, Aroon | Hirschhorn, Joel N. | Hofman, Albert | Hovingh, G. Kees | Hsiung, Chao Agnes | Humphries, Steve E. | Hunt, Steven C. | Hveem, Kristian | Iribarren, Carlos | Järvelin, Marjo-Riitta | Jula, Antti | Kähönen, Mika | Kaprio, Jaakko | Kesäniemi, Antero | Kivimaki, Mika | Kooner, Jaspal S. | Koudstaal, Peter J. | Krauss, Ronald M. | Kuh, Diana | Kuusisto, Johanna | Kyvik, Kirsten O. | Laakso, Markku | Lakka, Timo A. | Lind, Lars | Lindgren, Cecilia M. | Martin, Nicholas G. | März, Winfried | McCarthy, Mark I. | McKenzie, Colin A. | Meneton, Pierre | Metspalu, Andres | Moilanen, Leena | Morris, Andrew D. | Munroe, Patricia B. | Njølstad, Inger | Pedersen, Nancy L. | Power, Chris | Pramstaller, Peter P. | Price, Jackie F. | Psaty, Bruce M. | Quertermous, Thomas | Rauramaa, Rainer | Saleheen, Danish | Salomaa, Veikko | Sanghera, Dharambir K. | Saramies, Jouko | Schwarz, Peter E.H. | Sheu, Wayne H-H | Shuldiner, Alan R. | Siegbahn, Agneta | Spector, Tim D. | Stefansson, Kari | Strachan, David P. | Tayo, Bamidele O. | Tremoli, Elena | Tuomilehto, Jaakko | Uusitupa, Matti | van Duijn, Cornelia M. | Vollenweider, Peter | Wallentin, Lars | Wareham, Nicholas J. | Whitfield, John B. | Wolffenbuttel, Bruce H.R. | Altshuler, David | Ordovas, Jose M. | Boerwinkle, Eric | Palmer, Colin N.A. | Thorsteinsdottir, Unnur | Chasman, Daniel I. | Rotter, Jerome I. | Franks, Paul W. | Ripatti, Samuli | Cupples, L. Adrienne | Sandhu, Manjinder S. | Rich, Stephen S. | Boehnke, Michael | Deloukas, Panos | Mohlke, Karen L. | Ingelsson, Erik | Abecasis, Goncalo R. | Daly, Mark J. | Neale, Benjamin M. | Kathiresan, Sekar
Nature genetics  2013;45(11):1345-1352.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
doi:10.1038/ng.2795
PMCID: PMC3904346  PMID: 24097064
4.  Identification of seven loci affecting mean telomere length and their association with disease 
Codd, Veryan | Nelson, Christopher P. | Albrecht, Eva | Mangino, Massimo | Deelen, Joris | Buxton, Jessica L. | Jan Hottenga, Jouke | Fischer, Krista | Esko, Tõnu | Surakka, Ida | Broer, Linda | Nyholt, Dale R. | Mateo Leach, Irene | Salo, Perttu | Hägg, Sara | Matthews, Mary K. | Palmen, Jutta | Norata, Giuseppe D. | O’Reilly, Paul F. | Saleheen, Danish | Amin, Najaf | Balmforth, Anthony J. | Beekman, Marian | de Boer, Rudolf A. | Böhringer, Stefan | Braund, Peter S. | Burton, Paul R. | de Craen, Anton J. M. | Denniff, Matthew | Dong, Yanbin | Douroudis, Konstantinos | Dubinina, Elena | Eriksson, Johan G. | Garlaschelli, Katia | Guo, Dehuang | Hartikainen, Anna-Liisa | Henders, Anjali K. | Houwing-Duistermaat, Jeanine J. | Kananen, Laura | Karssen, Lennart C. | Kettunen, Johannes | Klopp, Norman | Lagou, Vasiliki | van Leeuwen, Elisabeth M. | Madden, Pamela A. | Mägi, Reedik | Magnusson, Patrik K.E. | Männistö, Satu | McCarthy, Mark I. | Medland, Sarah E. | Mihailov, Evelin | Montgomery, Grant W. | Oostra, Ben A. | Palotie, Aarno | Peters, Annette | Pollard, Helen | Pouta, Anneli | Prokopenko, Inga | Ripatti, Samuli | Salomaa, Veikko | Suchiman, H. Eka D. | Valdes, Ana M. | Verweij, Niek | Viñuela, Ana | Wang, Xiaoling | Wichmann, H.-Erich | Widen, Elisabeth | Willemsen, Gonneke | Wright, Margaret J. | Xia, Kai | Xiao, Xiangjun | van Veldhuisen, Dirk J. | Catapano, Alberico L. | Tobin, Martin D. | Hall, Alistair S. | Blakemore, Alexandra I.F. | van Gilst, Wiek H. | Zhu, Haidong | Erdmann, Jeanette | Reilly, Muredach P. | Kathiresan, Sekar | Schunkert, Heribert | Talmud, Philippa J. | Pedersen, Nancy L. | Perola, Markus | Ouwehand, Willem | Kaprio, Jaakko | Martin, Nicholas G. | van Duijn, Cornelia M. | Hovatta, Iiris | Gieger, Christian | Metspalu, Andres | Boomsma, Dorret I. | Jarvelin, Marjo-Riitta | Slagboom, P. Eline | Thompson, John R. | Spector, Tim D. | van der Harst, Pim | Samani, Nilesh J.
Nature genetics  2013;45(4):422-427e2.
Inter-individual variation in mean leukocyte telomere length (LTL) is associated with cancer and several age-associated diseases. Here, in a genome-wide meta-analysis of 37,684 individuals with replication of selected variants in a further 10,739 individuals, we identified seven loci, including five novel loci, associated with mean LTL (P<5x10−8). Five of the loci contain genes (TERC, TERT, NAF1, OBFC1, RTEL1) that are known to be involved in telomere biology. Lead SNPs at two loci (TERC and TERT) associate with several cancers and other diseases, including idiopathic pulmonary fibrosis. Moreover, a genetic risk score analysis combining lead variants at all seven loci in 22,233 coronary artery disease cases and 64,762 controls showed an association of the alleles associated with shorter LTL with increased risk of CAD (21% (95% CI: 5–35%) per standard deviation in LTL, p=0.014). Our findings support a causal role of telomere length variation in some age-related diseases.
doi:10.1038/ng.2528
PMCID: PMC4006270  PMID: 23535734
5.  Re-sequencing Expands Our Understanding of the Phenotypic Impact of Variants at GWAS Loci 
PLoS Genetics  2014;10(1):e1004147.
Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20–30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5′ and 3′ untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.
Author Summary
Abnormal serum levels of various metabolites, including measures relevant to cholesterol, other fats, and sugars, are known to be risk factors for cardiovascular disease and type 2 diabetes. Identification of the genes that play a role in generating such abnormalities could advance the development of new treatment and prevention strategies for these disorders. Investigations of common genetic variants carried out in large sets of research subjects have successfully pinpointed such genes within many regions of the human genome. However, these studies often have not led to the identification of the specific genetic variations affecting metabolic traits. To attempt to detect such causal variations, we sequenced genes in 17 genomic regions implicated in metabolic traits in >6,000 people from Finland. By conducting statistical analyses relating specific variations (individually and grouped by gene) to the measures for these metabolic traits observed in the study subjects, we added to our understanding of how genotypes affect these traits. Our findings support a long-held hypothesis that the unique history of the Finnish population provides important advantages for analyzing the relationship between genetic variations and biomedically important traits.
doi:10.1371/journal.pgen.1004147
PMCID: PMC3907339  PMID: 24497850
6.  Genetic loci influencing kidney function and chronic kidney disease in man 
Chambers, John C | Zhang, Weihua | Lord, Graham M | van der Harst, Pim | Lawlor, Debbie A | Sehmi, Joban S | Gale, Daniel P | Wass, Mark N | Ahmadi, Kourosh R | Bakker, Stephan JL | Beckmann, Jacqui | Bilo, Henk JG | Bochud, Murielle | Brown, Morris J | Caulfield, Mark J | Connell, John M C | Cook, Terence | Cotlarciuc, Ioana | Smith, George Davey | de Silva, Ranil | Deng, Guohong | Devuyst, Olivier | Dikkeschei, Lambert D. | Dimkovic, Nada | Dockrell, Mark | Dominiczak, Anna | Ebrahim, Shah | Eggermann, Thomas | Farrall, Martin | Ferrucci, Luigi | Floege, Jurgen | Forouhi, Nita G | Gansevoort, Ron T | Han, Xijin | Hedblad, Bo | van der Heide, Jaap J Homan | Hepkema, Bouke G | Hernandez-Fuentes, Maria | Hypponen, Elina | Johnson, Toby | de Jong, Paul E | Kleefstra, Nanne | Lagou, Vasiliki | Lapsley, Marta | Li, Yun | Loos, Ruth J F | Luan, Jian'an | Luttropp, Karin | Maréchal, Céline | Melander, Olle | Munroe, Patricia B | Nordfors, Louise | Parsa, Afshin | Penninx, Brenda W. | Perucha, Esperanza | Pouta, Anneli | Prokopenko, Inga | Roderick, Paul J | Ruokonen, Aimo | Samani, Nilesh | Sanna, Serena | Schalling, Martin | Schlessinger, David | Schlieper, Georg | Seelen, Marc AJ | Shuldiner, Alan R | Sjögren, Marketa | Smit, Johannes H. | Snieder, Harold | Soranzo, Nicole | Spector, Timothy D | Stenvinkel, Peter | Sternberg, Michael JE | Swaminathan, Ramasamyiyer | Tanaka, Toshiko | Ubink-Veltmaat, Lielith J. | Uda, Manuela | Vollenweider, Peter | Wallace, Chris | Waterworth, Dawn | Zerres, Klaus | Waeber, Gerard | Wareham, Nicholas J | Maxwell, Patrick H | McCarthy, Mark I | Jarvelin, Marjo-Riitta | Mooser, Vincent | Abecasis, Goncalo R | Lightstone, Liz | Scott, James | Navis, Gerjan | Elliott, Paul | Kooner., Jaspal S
Nature genetics  2010;42(5):373-375.
Chronic kidney disease (CKD), the result of permanent loss of kidney function, is a major global problem. We identify common genetic variants at chr2p12-p13, chr6q26, chr17q23 and chr19q13 associated with serum creatinine, a marker of kidney function (P=10−10 to 10−15). SNPs rs10206899 (near NAT8, chr2p12-p13) and rs4805834 (near SLC7A9, chr19q13) were also associated with CKD. Our findings provide new insight into metabolic, solute and drug-transport pathways underlying susceptibility to CKD.
doi:10.1038/ng.566
PMCID: PMC3748585  PMID: 20383145
7.  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
8.  The Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis 
Fall, Tove | Hägg, Sara | Mägi, Reedik | Ploner, Alexander | Fischer, Krista | Horikoshi, Momoko | Sarin, Antti-Pekka | Thorleifsson, Gudmar | Ladenvall, Claes | Kals, Mart | Kuningas, Maris | Draisma, Harmen H. M. | Ried, Janina S. | van Zuydam, Natalie R. | Huikari, Ville | Mangino, Massimo | Sonestedt, Emily | Benyamin, Beben | Nelson, Christopher P. | Rivera, Natalia V. | Kristiansson, Kati | Shen, Huei-yi | Havulinna, Aki S. | Dehghan, Abbas | Donnelly, Louise A. | Kaakinen, Marika | Nuotio, Marja-Liisa | Robertson, Neil | de Bruijn, Renée F. A. G. | Ikram, M. Arfan | Amin, Najaf | Balmforth, Anthony J. | Braund, Peter S. | Doney, Alexander S. F. | Döring, Angela | Elliott, Paul | Esko, Tõnu | Franco, Oscar H. | Gretarsdottir, Solveig | Hartikainen, Anna-Liisa | Heikkilä, Kauko | Herzig, Karl-Heinz | Holm, Hilma | Hottenga, Jouke Jan | Hyppönen, Elina | Illig, Thomas | Isaacs, Aaron | Isomaa, Bo | Karssen, Lennart C. | Kettunen, Johannes | Koenig, Wolfgang | Kuulasmaa, Kari | Laatikainen, Tiina | Laitinen, Jaana | Lindgren, Cecilia | Lyssenko, Valeriya | Läärä, Esa | Rayner, Nigel W. | Männistö, Satu | Pouta, Anneli | Rathmann, Wolfgang | Rivadeneira, Fernando | Ruokonen, Aimo | Savolainen, Markku J. | Sijbrands, Eric J. G. | Small, Kerrin S. | Smit, Jan H. | Steinthorsdottir, Valgerdur | Syvänen, Ann-Christine | Taanila, Anja | Tobin, Martin D. | Uitterlinden, Andre G. | Willems, Sara M. | Willemsen, Gonneke | Witteman, Jacqueline | Perola, Markus | Evans, Alun | Ferrières, Jean | Virtamo, Jarmo | Kee, Frank | Tregouet, David-Alexandre | Arveiler, Dominique | Amouyel, Philippe | Ferrario, Marco M. | Brambilla, Paolo | Hall, Alistair S. | Heath, Andrew C. | Madden, Pamela A. F. | Martin, Nicholas G. | Montgomery, Grant W. | Whitfield, John B. | Jula, Antti | Knekt, Paul | Oostra, Ben | van Duijn, Cornelia M. | Penninx, Brenda W. J. H. | Davey Smith, George | Kaprio, Jaakko | Samani, Nilesh J. | Gieger, Christian | Peters, Annette | Wichmann, H.-Erich | Boomsma, Dorret I. | de Geus, Eco J. C. | Tuomi, TiinaMaija | Power, Chris | Hammond, Christopher J. | Spector, Tim D. | Lind, Lars | Orho-Melander, Marju | Palmer, Colin Neil Alexander | Morris, Andrew D. | Groop, Leif | Järvelin, Marjo-Riitta | Salomaa, Veikko | Vartiainen, Erkki | Hofman, Albert | Ripatti, Samuli | Metspalu, Andres | Thorsteinsdottir, Unnur | Stefansson, Kari | Pedersen, Nancy L. | McCarthy, Mark I. | Ingelsson, Erik | Prokopenko, Inga
PLoS Medicine  2013;10(6):e1001474.
In this study, Prokopenko and colleagues provide novel evidence for causal relationship between adiposity and heart failure and increased liver enzymes using a Mendelian randomization study design.
Please see later in the article for the Editors' Summary
Background
The association between adiposity and cardiometabolic traits is well known from epidemiological studies. Whilst the causal relationship is clear for some of these traits, for others it is not. We aimed to determine whether adiposity is causally related to various cardiometabolic traits using the Mendelian randomization approach.
Methods and Findings
We used the adiposity-associated variant rs9939609 at the FTO locus as an instrumental variable (IV) for body mass index (BMI) in a Mendelian randomization design. Thirty-six population-based studies of individuals of European descent contributed to the analyses.
Age- and sex-adjusted regression models were fitted to test for association between (i) rs9939609 and BMI (n = 198,502), (ii) rs9939609 and 24 traits, and (iii) BMI and 24 traits. The causal effect of BMI on the outcome measures was quantified by IV estimators. The estimators were compared to the BMI–trait associations derived from the same individuals. In the IV analysis, we demonstrated novel evidence for a causal relationship between adiposity and incident heart failure (hazard ratio, 1.19 per BMI-unit increase; 95% CI, 1.03–1.39) and replicated earlier reports of a causal association with type 2 diabetes, metabolic syndrome, dyslipidemia, and hypertension (odds ratio for IV estimator, 1.1–1.4; all p<0.05). For quantitative traits, our results provide novel evidence for a causal effect of adiposity on the liver enzymes alanine aminotransferase and gamma-glutamyl transferase and confirm previous reports of a causal effect of adiposity on systolic and diastolic blood pressure, fasting insulin, 2-h post-load glucose from the oral glucose tolerance test, C-reactive protein, triglycerides, and high-density lipoprotein cholesterol levels (all p<0.05). The estimated causal effects were in agreement with traditional observational measures in all instances except for type 2 diabetes, where the causal estimate was larger than the observational estimate (p = 0.001).
Conclusions
We provide novel evidence for a causal relationship between adiposity and heart failure as well as between adiposity and increased liver enzymes.
Please see later in the article for the Editors' Summary
Editors' Summary
Cardiovascular disease (CVD)—disease that affects the heart and/or the blood vessels—is a major cause of illness and death worldwide. In the US, for example, coronary heart disease—a CVD in which narrowing of the heart's blood vessels by fatty deposits slows the blood supply to the heart and may eventually cause a heart attack—is the leading cause of death, and stroke—a CVD in which the brain's blood supply is interrupted—is the fourth leading cause of death. Globally, both the incidence of CVD (the number of new cases in a population every year) and its prevalence (the proportion of the population with CVD) are increasing, particularly in low- and middle-income countries. This increasing burden of CVD is occurring in parallel with a global increase in the incidence and prevalence of obesity—having an unhealthy amount of body fat (adiposity)—and of metabolic diseases—conditions such as diabetes in which metabolism (the processes that the body uses to make energy from food) is disrupted, with resulting high blood sugar and damage to the blood vessels.
Why Was This Study Done?
Epidemiological studies—investigations that record the patterns and causes of disease in populations—have reported an association between adiposity (indicated by an increased body mass index [BMI], which is calculated by dividing body weight in kilograms by height in meters squared) and cardiometabolic traits such as coronary heart disease, stroke, heart failure (a condition in which the heart is incapable of pumping sufficient amounts of blood around the body), diabetes, high blood pressure (hypertension), and high blood cholesterol (dyslipidemia). However, observational studies cannot prove that adiposity causes any particular cardiometabolic trait because overweight individuals may share other characteristics (confounding factors) that are the real causes of both obesity and the cardiometabolic disease. Moreover, it is possible that having CVD or a metabolic disease causes obesity (reverse causation). For example, individuals with heart failure cannot do much exercise, so heart failure may cause obesity rather than vice versa. Here, the researchers use “Mendelian randomization” to examine whether adiposity is causally related to various cardiometabolic traits. Because gene variants are inherited randomly, they are not prone to confounding and are free from reverse causation. It is known that a genetic variant (rs9939609) within the genome region that encodes the fat-mass- and obesity-associated gene (FTO) is associated with increased BMI. Thus, an investigation of the associations between rs9939609 and cardiometabolic traits can indicate whether obesity is causally related to these traits.
What Did the Researchers Do and Find?
The researchers analyzed the association between rs9939609 (the “instrumental variable,” or IV) and BMI, between rs9939609 and 24 cardiometabolic traits, and between BMI and the same traits using genetic and health data collected in 36 population-based studies of nearly 200,000 individuals of European descent. They then quantified the strength of the causal association between BMI and the cardiometabolic traits by calculating “IV estimators.” Higher BMI showed a causal relationship with heart failure, metabolic syndrome (a combination of medical disorders that increases the risk of developing CVD), type 2 diabetes, dyslipidemia, hypertension, increased blood levels of liver enzymes (an indicator of liver damage; some metabolic disorders involve liver damage), and several other cardiometabolic traits. All the IV estimators were similar to the BMI–cardiovascular trait associations (observational estimates) derived from the same individuals, with the exception of diabetes, where the causal estimate was higher than the observational estimate, probably because the observational estimate is based on a single BMI measurement, whereas the causal estimate considers lifetime changes in BMI.
What Do These Findings Mean?
Like all Mendelian randomization studies, the reliability of the causal associations reported here depends on several assumptions made by the researchers. Nevertheless, these findings provide support for many previously suspected and biologically plausible causal relationships, such as that between adiposity and hypertension. They also provide new insights into the causal effect of obesity on liver enzyme levels and on heart failure. In the latter case, these findings suggest that a one-unit increase in BMI might increase the incidence of heart failure by 17%. In the US, this corresponds to 113,000 additional cases of heart failure for every unit increase in BMI at the population level. Although additional studies are needed to confirm and extend these findings, these results suggest that global efforts to reduce the burden of obesity will likely also reduce the occurrence of CVD and metabolic disorders.
Additional Information
Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001474.
The American Heart Association provides information on all aspects of cardiovascular disease and tips on keeping the heart healthy, including weight management (in several languages); its website includes personal stories about stroke and heart attacks
The US Centers for Disease Control and Prevention has information on heart disease, stroke, and all aspects of overweight and obesity (in English and Spanish)
The UK National Health Service Choices website provides information about cardiovascular disease and obesity, including a personal story about losing weight
The World Health Organization provides information on obesity (in several languages)
The International Obesity Taskforce provides information about the global obesity epidemic
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
MedlinePlus provides links to other sources of information on heart disease, on vascular disease, on obesity, and on metabolic disorders (in English and Spanish)
The International Association for the Study of Obesity provides maps and information about obesity worldwide
The International Diabetes Federation has a web page that describes types, complications, and risk factors of diabetes
doi:10.1371/journal.pmed.1001474
PMCID: PMC3692470  PMID: 23824655
9.  FTO genotype is associated with phenotypic variability of body mass index 
Yang, Jian | Loos, Ruth J. F. | Powell, Joseph E. | Medland, Sarah E. | Speliotes, Elizabeth K. | Chasman, Daniel I. | Rose, Lynda M. | Thorleifsson, Gudmar | Steinthorsdottir, Valgerdur | Mägi, Reedik | Waite, Lindsay | Smith, Albert Vernon | Yerges-Armstrong, Laura M. | Monda, Keri L. | Hadley, David | Mahajan, Anubha | Li, Guo | Kapur, Karen | Vitart, Veronique | Huffman, Jennifer E. | Wang, Sophie R. | Palmer, Cameron | Esko, Tõnu | Fischer, Krista | Zhao, Jing Hua | Demirkan, Ayşe | Isaacs, Aaron | Feitosa, Mary F. | Luan, Jian’an | Heard-Costa, Nancy L. | White, Charles | Jackson, Anne U. | Preuss, Michael | Ziegler, Andreas | Eriksson, Joel | Kutalik, Zoltán | Frau, Francesca | Nolte, Ilja M. | Van Vliet-Ostaptchouk, Jana V. | Hottenga, Jouke-Jan | Jacobs, Kevin B. | Verweij, Niek | Goel, Anuj | Medina-Gomez, Carolina | Estrada, Karol | Bragg-Gresham, Jennifer Lynn | Sanna, Serena | Sidore, Carlo | Tyrer, Jonathan | Teumer, Alexander | Prokopenko, Inga | Mangino, Massimo | Lindgren, Cecilia M. | Assimes, Themistocles L. | Shuldiner, Alan R. | Hui, Jennie | Beilby, John P. | McArdle, Wendy L. | Hall, Per | Haritunians, Talin | Zgaga, Lina | Kolcic, Ivana | Polasek, Ozren | Zemunik, Tatijana | Oostra, Ben A. | Junttila, M. Juhani | Grönberg, Henrik | Schreiber, Stefan | Peters, Annette | Hicks, Andrew A. | Stephens, Jonathan | Foad, Nicola S. | Laitinen, Jaana | Pouta, Anneli | Kaakinen, Marika | Willemsen, Gonneke | Vink, Jacqueline M. | Wild, Sarah H. | Navis, Gerjan | Asselbergs, Folkert W. | Homuth, Georg | John, Ulrich | Iribarren, Carlos | Harris, Tamara | Launer, Lenore | Gudnason, Vilmundur | O’Connell, Jeffrey R. | Boerwinkle, Eric | Cadby, Gemma | Palmer, Lyle J. | James, Alan L. | Musk, Arthur W. | Ingelsson, Erik | Psaty, Bruce M. | Beckmann, Jacques S. | Waeber, Gerard | Vollenweider, Peter | Hayward, Caroline | Wright, Alan F. | Rudan, Igor | Groop, Leif C. | Metspalu, Andres | Khaw, Kay Tee | van Duijn, Cornelia M. | Borecki, Ingrid B. | Province, Michael A. | Wareham, Nicholas J. | Tardif, Jean-Claude | Huikuri, Heikki V. | Cupples, L. Adrienne | Atwood, Larry D. | Fox, Caroline S. | Boehnke, Michael | Collins, Francis S. | Mohlke, Karen L. | Erdmann, Jeanette | Schunkert, Heribert | Hengstenberg, Christian | Stark, Klaus | Lorentzon, Mattias | Ohlsson, Claes | Cusi, Daniele | Staessen, Jan A. | Van der Klauw, Melanie M. | Pramstaller, Peter P. | Kathiresan, Sekar | Jolley, Jennifer D. | Ripatti, Samuli | Jarvelin, Marjo-Riitta | de Geus, Eco J. C. | Boomsma, Dorret I. | Penninx, Brenda | Wilson, James F. | Campbell, Harry | Chanock, Stephen J. | van der Harst, Pim | Hamsten, Anders | Watkins, Hugh | Hofman, Albert | Witteman, Jacqueline C. | Zillikens, M. Carola | Uitterlinden, André G. | Rivadeneira, Fernando | Zillikens, M. Carola | Kiemeney, Lambertus A. | Vermeulen, Sita H. | Abecasis, Goncalo R. | Schlessinger, David | Schipf, Sabine | Stumvoll, Michael | Tönjes, Anke | Spector, Tim D. | North, Kari E. | Lettre, Guillaume | McCarthy, Mark I. | Berndt, Sonja I. | Heath, Andrew C. | Madden, Pamela A. F. | Nyholt, Dale R. | Montgomery, Grant W. | Martin, Nicholas G. | McKnight, Barbara | Strachan, David P. | Hill, William G. | Snieder, Harold | Ridker, Paul M. | Thorsteinsdottir, Unnur | Stefansson, Kari | Frayling, Timothy M. | Hirschhorn, Joel N. | Goddard, Michael E. | Visscher, Peter M.
Nature  2012;490(7419):267-272.
There is evidence across several species for genetic control of phenotypic variation of complex traits1–4, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using 170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype)5–7, is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of 0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI8, possibly mediated by DNA methylation9,10. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.
doi:10.1038/nature11401
PMCID: PMC3564953  PMID: 22982992
10.  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
11.  Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts 
PLoS Medicine  2013;10(2):e1001383.
A mendelian randomization study based on data from multiple cohorts conducted by Karani Santhanakrishnan Vimaleswaran and colleagues re-examines the causal nature of the relationship between vitamin D levels and obesity.
Background
Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis.
Methods and Findings
We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects.
Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) and 25(OH)D (−0.06% [95% CI −0.10 to −0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10−57 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: −4.2 [95% CI −7.1 to −1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores).
Conclusions
On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency.
Please see later in the article for the Editors' Summary
Editors' Summary
Background
Obesity—having an unhealthy amount of body fat—is increasing worldwide. In the US, for example, a third of the adult population is now obese. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Although there is a genetic contribution to obesity, people generally become obese by consuming food and drink that contains more energy than they need for their daily activities. Thus, obesity can be prevented by having a healthy diet and exercising regularly. Compared to people with a healthy weight, obese individuals have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. They also have a higher risk of vitamin D deficiency, another increasingly common public health concern. Vitamin D, which is essential for healthy bones as well as other functions, is made in the skin after exposure to sunlight but can also be obtained through the diet and through supplements.
Why Was This Study Done?
Observational studies cannot prove that obesity causes vitamin D deficiency because obese individuals may share other characteristics that reduce their circulating 25-hydroxy vitamin D [25(OH)D] levels (referred to as confounding). Moreover, observational studies cannot indicate whether the larger vitamin D storage capacity of obese individuals (vitamin D is stored in fatty tissues) lowers their 25(OH)D levels or whether 25(OH)D levels influence fat accumulation (reverse causation). If obesity causes vitamin D deficiency, monitoring and treating vitamin D deficiency might alleviate some of the adverse health effects of obesity. Conversely, if low vitamin D levels cause obesity, encouraging people to take vitamin D supplements might help to control the obesity epidemic. Here, the researchers use bi-directional “Mendelian randomization” to examine the direction and causality of the relationship between BMI and 25(OH)D. In Mendelian randomization, causality is inferred from associations between genetic variants that mimic the influence of a modifiable environmental exposure and the outcome of interest. Because gene variants do not change over time and are inherited randomly, they are not prone to confounding and are free from reverse causation. Thus, if a lower vitamin D status leads to obesity, genetic variants associated with lower 25(OH)D concentrations should be associated with higher BMI, and if obesity leads to a lower vitamin D status, then genetic variants associated with higher BMI should be associated with lower 25(OH)D concentrations.
What Did the Researchers Do and Find?
The researchers created a “BMI allele score” based on 12 BMI-related gene variants and two “25(OH)D allele scores,” which are based on gene variants that affect either 25(OH)D synthesis or breakdown. Using information on up to 42,024 participants from 21 studies, the researchers showed that the BMI allele score was associated with both BMI and with 25(OH)D levels among the study participants. Based on this information, they calculated that each 10% increase in BMI will lead to a 4.2% decrease in 25(OH)D concentrations. By contrast, although both 25(OH)D allele scores were strongly associated with 25(OH)D levels, neither score was associated with BMI. This lack of an association between 25(OH)D allele scores and obesity was confirmed using data from more than 100,000 individuals involved in 46 studies that has been collected by the GIANT (Genetic Investigation of Anthropometric Traits) consortium.
What Do These Findings Mean?
These findings suggest that a higher BMI leads to a lower vitamin D status whereas any effects of low vitamin D status on BMI are likely to be small. That is, these findings provide evidence for obesity as a causal factor in the development of vitamin D deficiency but not for vitamin D deficiency as a causal factor in the development of obesity. These findings suggest that population-level interventions to reduce obesity should lead to a reduction in the prevalence of vitamin D deficiency and highlight the importance of monitoring and treating vitamin D deficiency as a means of alleviating the adverse influences of obesity on health.
Additional Information
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001383.
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish); a data brief provides information about the vitamin D status of the US population
The World Health Organization provides information on obesity (in several languages)
The UK National Health Service Choices website provides detailed information about obesity and a link to a personal story about losing weight; it also provides information about vitamin D
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's ChooseMyPlate.gov website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
The US Office of Dietary Supplements provides information about vitamin D (in English and Spanish)
MedlinePlus has links to further information about obesity and about vitamin D (in English and Spanish)
Wikipedia has a page on Mendelian randomization (note: Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
Overview and details of the collaborative large-scale genetic association study (D-CarDia) provide information about vitamin D and the risk of cardiovascular disease, diabetes and related traits
doi:10.1371/journal.pmed.1001383
PMCID: PMC3564800  PMID: 23393431
12.  Variants in MTNR1B influence fasting glucose levels 
Prokopenko, Inga | Langenberg, Claudia | Florez, Jose C | Saxena, Richa | Soranzo, Nicole | Thorleifsson, Gudmar | Loos, Ruth J F | Manning, Alisa K | Jackson, Anne U | Aulchenko, Yurii | Potter, Simon C | Erdos, Michael R | Sanna, Serena | Hottenga, Jouke-Jan | Wheeler, Eleanor | Kaakinen, Marika | Lyssenko, Valeriya | Chen, Wei-Min | Ahmadi, Kourosh | Beckmann, Jacques S | Bergman, Richard N | Bochud, Murielle | Bonnycastle, Lori L | Buchanan, Thomas A | Cao, Antonio | Cervino, Alessandra | Coin, Lachlan | Collins, Francis S | Crisponi, Laura | de Geus, Eco J C | Dehghan, Abbas | Deloukas, Panos | Doney, Alex S F | Elliott, Paul | Freimer, Nelson | Gateva, Vesela | Herder, Christian | Hofman, Albert | Hughes, Thomas E | Hunt, Sarah | Illig, Thomas | Inouye, Michael | Isomaa, Bo | Johnson, Toby | Kong, Augustine | Krestyaninova, Maria | Kuusisto, Johanna | Laakso, Markku | Lim, Noha | Lindblad, Ulf | Lindgren, Cecilia M | McCann, Owen T | Mohlke, Karen L | Morris, Andrew D | Naitza, Silvia | Orrù, Marco | Palmer, Colin N A | Pouta, Anneli | Randall, Joshua | Rathmann, Wolfgang | Saramies, Jouko | Scheet, Paul | Scott, Laura J | Scuteri, Angelo | Sharp, Stephen | Sijbrands, Eric | Smit, Jan H | Song, Kijoung | Steinthorsdottir, Valgerdur | Stringham, Heather M | Tuomi, Tiinamaija | Tuomilehto, Jaakko | Uitterlinden, André G | Voight, Benjamin F | Waterworth, Dawn | Wichmann, H-Erich | Willemsen, Gonneke | Witteman, Jacqueline C M | Yuan, Xin | Zhao, Jing Hua | Zeggini, Eleftheria | Schlessinger, David | Sandhu, Manjinder | Boomsma, Dorret I | Uda, Manuela | Spector, Tim D | Penninx, Brenda WJH | Altshuler, David | Vollenweider, Peter | Jarvelin, Marjo Riitta | Lakatta, Edward | Waeber, Gerard | Fox, Caroline S | Peltonen, Leena | Groop, Leif C | Mooser, Vincent | Cupples, L Adrienne | Thorsteinsdottir, Unnur | Boehnke, Michael | Barroso, Inês | Van Duijn, Cornelia | Dupuis, Josée | Watanabe, Richard M | Stefansson, Kari | McCarthy, Mark I | Wareham, Nicholas J | Meigs, James B | Abecasis, Gonçalo R
Nature genetics  2008;41(1):77-81.
To identify previously unknown genetic loci associated with fasting glucose concentrations, we examined the leading association signals in ten genome-wide association scans involving a total of 36,610 individuals of European descent. Variants in the gene encoding melatonin receptor 1B (MTNR1B) were consistently associated with fasting glucose across all ten studies. The strongest signal was observed at rs10830963, where each G allele (frequency 0.30 in HapMap CEU) was associated with an increase of 0.07 (95% CI = 0.06-0.08) mmol/l in fasting glucose levels (P = 3.2 = × 10−50) and reduced beta-cell function as measured by homeostasis model assessment (HOMA-B, P = 1.1 × 10−15). The same allele was associated with an increased risk of type 2 diabetes (odds ratio = 1.09 (1.05-1.12), per G allele P = 3.3 × 10−7) in a meta-analysis of 13 case-control studies totaling 18,236 cases and 64,453 controls. Our analyses also confirm previous associations of fasting glucose with variants at the G6PC2 (rs560887, P = 1.1 × 10−57) and GCK (rs4607517, P = 1.0 × 10−25) loci.
doi:10.1038/ng.290
PMCID: PMC2682768  PMID: 19060907
13.  Genome-wide association study identifies loci influencing concentrations of liver enzymes in plasma 
Chambers, John C | Zhang, Weihua | Sehmi, Joban | Li, Xinzhong | Wass, Mark N | Van der Harst, Pim | Holm, Hilma | Sanna, Serena | Kavousi, Maryam | Baumeister, Sebastian E | Coin, Lachlan J | Deng, Guohong | Gieger, Christian | Heard-Costa, Nancy L | Hottenga, Jouke-Jan | Kühnel, Brigitte | Kumar, Vinod | Lagou, Vasiliki | Liang, Liming | Luan, Jian’an | Vidal, Pedro Marques | Leach, Irene Mateo | O’Reilly, Paul F | Peden, John F | Rahmioglu, Nilufer | Soininen, Pasi | Speliotes, Elizabeth K | Yuan, Xin | Thorleifsson, Gudmar | Alizadeh, Behrooz Z | Atwood, Larry D | Borecki, Ingrid B | Brown, Morris J | Charoen, Pimphen | Cucca, Francesco | Das, Debashish | de Geus, Eco J C | Dixon, Anna L | Döring, Angela | Ehret, Georg | Eyjolfsson, Gudmundur I | Farrall, Martin | Forouhi, Nita G | Friedrich, Nele | Goessling, Wolfram | Gudbjartsson, Daniel F | Harris, Tamara B | Hartikainen, Anna-Liisa | Heath, Simon | Hirschfield, Gideon M | Hofman, Albert | Homuth, Georg | Hyppönen, Elina | Janssen, Harry L A | Johnson, Toby | Kangas, Antti J | Kema, Ido P | Kühn, Jens P | Lai, Sandra | Lathrop, Mark | Lerch, Markus M | Li, Yun | Liang, T Jake | Lin, Jing-Ping | Loos, Ruth J F | Martin, Nicholas G | Moffatt, Miriam F | Montgomery, Grant W | Munroe, Patricia B | Musunuru, Kiran | Nakamura, Yusuke | O’Donnell, Christopher J | Olafsson, Isleifur | Penninx, Brenda W | Pouta, Anneli | Prins, Bram P | Prokopenko, Inga | Puls, Ralf | Ruokonen, Aimo | Savolainen, Markku J | Schlessinger, David | Schouten, Jeoffrey N L | Seedorf, Udo | Sen-Chowdhry, Srijita | Siminovitch, Katherine A | Smit, Johannes H | Spector, Timothy D | Tan, Wenting | Teslovich, Tanya M | Tukiainen, Taru | Uitterlinden, Andre G | Van der Klauw, Melanie M | Vasan, Ramachandran S | Wallace, Chris | Wallaschofski, Henri | Wichmann, H-Erich | Willemsen, Gonneke | Würtz, Peter | Xu, Chun | Yerges-Armstrong, Laura M | Abecasis, Goncalo R | Ahmadi, Kourosh R | Boomsma, Dorret I | Caulfield, Mark | Cookson, William O | van Duijn, Cornelia M | Froguel, Philippe | Matsuda, Koichi | McCarthy, Mark I | Meisinger, Christa | Mooser, Vincent | Pietiläinen, Kirsi H | Schumann, Gunter | Snieder, Harold | Sternberg, Michael J E | Stolk, Ronald P | Thomas, Howard C | Thorsteinsdottir, Unnur | Uda, Manuela | Waeber, Gérard | Wareham, Nicholas J | Waterworth, Dawn M | Watkins, Hugh | Whitfield, John B | Witteman, Jacqueline C M | Wolffenbuttel, Bruce H R | Fox, Caroline S | Ala-Korpela, Mika | Stefansson, Kari | Vollenweider, Peter | Völzke, Henry | Schadt, Eric E | Scott, James | Järvelin, Marjo-Riitta | Elliott, Paul | Kooner, Jaspal S
Nature genetics  2011;43(11):1131-1138.
Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10−8 to P = 10−190). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.
doi:10.1038/ng.970
PMCID: PMC3482372  PMID: 22001757
14.  Evidence of Inbreeding Depression on Human Height 
McQuillan, Ruth | Eklund, Niina | Pirastu, Nicola | Kuningas, Maris | McEvoy, Brian P. | Esko, Tõnu | Corre, Tanguy | Davies, Gail | Kaakinen, Marika | Lyytikäinen, Leo-Pekka | Kristiansson, Kati | Havulinna, Aki S. | Gögele, Martin | Vitart, Veronique | Tenesa, Albert | Aulchenko, Yurii | Hayward, Caroline | Johansson, Åsa | Boban, Mladen | Ulivi, Sheila | Robino, Antonietta | Boraska, Vesna | Igl, Wilmar | Wild, Sarah H. | Zgaga, Lina | Amin, Najaf | Theodoratou, Evropi | Polašek, Ozren | Girotto, Giorgia | Lopez, Lorna M. | Sala, Cinzia | Lahti, Jari | Laatikainen, Tiina | Prokopenko, Inga | Kals, Mart | Viikari, Jorma | Yang, Jian | Pouta, Anneli | Estrada, Karol | Hofman, Albert | Freimer, Nelson | Martin, Nicholas G. | Kähönen, Mika | Milani, Lili | Heliövaara, Markku | Vartiainen, Erkki | Räikkönen, Katri | Masciullo, Corrado | Starr, John M. | Hicks, Andrew A. | Esposito, Laura | Kolčić, Ivana | Farrington, Susan M. | Oostra, Ben | Zemunik, Tatijana | Campbell, Harry | Kirin, Mirna | Pehlic, Marina | Faletra, Flavio | Porteous, David | Pistis, Giorgio | Widén, Elisabeth | Salomaa, Veikko | Koskinen, Seppo | Fischer, Krista | Lehtimäki, Terho | Heath, Andrew | McCarthy, Mark I. | Rivadeneira, Fernando | Montgomery, Grant W. | Tiemeier, Henning | Hartikainen, Anna-Liisa | Madden, Pamela A. F. | d'Adamo, Pio | Hastie, Nicholas D. | Gyllensten, Ulf | Wright, Alan F. | van Duijn, Cornelia M. | Dunlop, Malcolm | Rudan, Igor | Gasparini, Paolo | Pramstaller, Peter P. | Deary, Ian J. | Toniolo, Daniela | Eriksson, Johan G. | Jula, Antti | Raitakari, Olli T. | Metspalu, Andres | Perola, Markus | Järvelin, Marjo-Riitta | Uitterlinden, André | Visscher, Peter M. | Wilson, James F.
PLoS Genetics  2012;8(7):e1002655.
Stature is a classical and highly heritable complex trait, with 80%–90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ2 = 83.89, df = 1; p = 5.2×10−20). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.
Author Summary
Studies investigating the extent to which genetics influences human characteristics such as height have concentrated mainly on common variants of genes, where having one or two copies of a given variant influences the trait or risk of disease. This study explores whether a different type of genetic variant might also be important. We investigate the role of recessive genetic variants, where two identical copies of a variant are required to have an effect. By measuring genome-wide homozygosity—the phenomenon of inheriting two identical copies at a given point of the genome—in 35,000 individuals from 21 European populations, and by comparing this to individual height, we found that the more homozygous the genome, the shorter the individual. The offspring of first cousins (who have increased homozygosity) were predicted to be up to 3 cm shorter on average than the offspring of unrelated parents. Height is influenced by the combined effect of many recessive variants dispersed across the genome. This may also be true for other human characteristics and diseases, opening up a new way to understand how genetic variation influences our health.
doi:10.1371/journal.pgen.1002655
PMCID: PMC3400549  PMID: 22829771
15.  A Genome-Wide Association Meta-Analysis of Circulating Sex Hormone–Binding Globulin Reveals Multiple Loci Implicated in Sex Steroid Hormone Regulation 
Coviello, Andrea D. | Haring, Robin | Wellons, Melissa | Vaidya, Dhananjay | Lehtimäki, Terho | Keildson, Sarah | Lunetta, Kathryn L. | He, Chunyan | Fornage, Myriam | Lagou, Vasiliki | Mangino, Massimo | Onland-Moret, N. Charlotte | Chen, Brian | Eriksson, Joel | Garcia, Melissa | Liu, Yong Mei | Koster, Annemarie | Lohman, Kurt | Lyytikäinen, Leo-Pekka | Petersen, Ann-Kristin | Prescott, Jennifer | Stolk, Lisette | Vandenput, Liesbeth | Wood, Andrew R. | Zhuang, Wei Vivian | Ruokonen, Aimo | Hartikainen, Anna-Liisa | Pouta, Anneli | Bandinelli, Stefania | Biffar, Reiner | Brabant, Georg | Cox, David G. | Chen, Yuhui | Cummings, Steven | Ferrucci, Luigi | Gunter, Marc J. | Hankinson, Susan E. | Martikainen, Hannu | Hofman, Albert | Homuth, Georg | Illig, Thomas | Jansson, John-Olov | Johnson, Andrew D. | Karasik, David | Karlsson, Magnus | Kettunen, Johannes | Kiel, Douglas P. | Kraft, Peter | Liu, Jingmin | Ljunggren, Östen | Lorentzon, Mattias | Maggio, Marcello | Markus, Marcello R. P. | Mellström, Dan | Miljkovic, Iva | Mirel, Daniel | Nelson, Sarah | Morin Papunen, Laure | Peeters, Petra H. M. | Prokopenko, Inga | Raffel, Leslie | Reincke, Martin | Reiner, Alex P. | Rexrode, Kathryn | Rivadeneira, Fernando | Schwartz, Stephen M. | Siscovick, David | Soranzo, Nicole | Stöckl, Doris | Tworoger, Shelley | Uitterlinden, André G. | van Gils, Carla H. | Vasan, Ramachandran S. | Wichmann, H.-Erich | Zhai, Guangju | Bhasin, Shalender | Bidlingmaier, Martin | Chanock, Stephen J. | De Vivo, Immaculata | Harris, Tamara B. | Hunter, David J. | Kähönen, Mika | Liu, Simin | Ouyang, Pamela | Spector, Tim D. | van der Schouw, Yvonne T. | Viikari, Jorma | Wallaschofski, Henri | McCarthy, Mark I. | Frayling, Timothy M. | Murray, Anna | Franks, Steve | Järvelin, Marjo-Riitta | de Jong, Frank H. | Raitakari, Olli | Teumer, Alexander | Ohlsson, Claes | Murabito, Joanne M. | Perry, John R. B.
PLoS Genetics  2012;8(7):e1002805.
Sex hormone-binding globulin (SHBG) is a glycoprotein responsible for the transport and biologic availability of sex steroid hormones, primarily testosterone and estradiol. SHBG has been associated with chronic diseases including type 2 diabetes (T2D) and with hormone-sensitive cancers such as breast and prostate cancer. We performed a genome-wide association study (GWAS) meta-analysis of 21,791 individuals from 10 epidemiologic studies and validated these findings in 7,046 individuals in an additional six studies. We identified twelve genomic regions (SNPs) associated with circulating SHBG concentrations. Loci near the identified SNPs included SHBG (rs12150660, 17p13.1, p = 1.8×10−106), PRMT6 (rs17496332, 1p13.3, p = 1.4×10−11), GCKR (rs780093, 2p23.3, p = 2.2×10−16), ZBTB10 (rs440837, 8q21.13, p = 3.4×10−09), JMJD1C (rs7910927, 10q21.3, p = 6.1×10−35), SLCO1B1 (rs4149056, 12p12.1, p = 1.9×10−08), NR2F2 (rs8023580, 15q26.2, p = 8.3×10−12), ZNF652 (rs2411984, 17q21.32, p = 3.5×10−14), TDGF3 (rs1573036, Xq22.3, p = 4.1×10−14), LHCGR (rs10454142, 2p16.3, p = 1.3×10−07), BAIAP2L1 (rs3779195, 7q21.3, p = 2.7×10−08), and UGT2B15 (rs293428, 4q13.2, p = 5.5×10−06). These genes encompass multiple biologic pathways, including hepatic function, lipid metabolism, carbohydrate metabolism and T2D, androgen and estrogen receptor function, epigenetic effects, and the biology of sex steroid hormone-responsive cancers including breast and prostate cancer. We found evidence of sex-differentiated genetic influences on SHBG. In a sex-specific GWAS, the loci 4q13.2-UGT2B15 was significant in men only (men p = 2.5×10−08, women p = 0.66, heterogeneity p = 0.003). Additionally, three loci showed strong sex-differentiated effects: 17p13.1-SHBG and Xq22.3-TDGF3 were stronger in men, whereas 8q21.12-ZBTB10 was stronger in women. Conditional analyses identified additional signals at the SHBG gene that together almost double the proportion of variance explained at the locus. Using an independent study of 1,129 individuals, all SNPs identified in the overall or sex-differentiated or conditional analyses explained ∼15.6% and ∼8.4% of the genetic variation of SHBG concentrations in men and women, respectively. The evidence for sex-differentiated effects and allelic heterogeneity highlight the importance of considering these features when estimating complex trait variance.
Author Summary
Sex hormone-binding globulin (SHBG) is the key protein responsible for binding and transporting the sex steroid hormones, testosterone and estradiol, in the circulatory system. SHBG regulates their bioavailability and therefore their effects in the body. SHBG has been linked to chronic diseases including type 2 diabetes and to hormone-sensitive cancers such as breast and prostate cancer. SHBG concentrations are approximately 50% heritable in family studies, suggesting SHBG concentrations are under significant genetic control; yet, little is known about the specific genes that influence SHBG. We conducted a large study of the association of SHBG concentrations with markers in the human genome in ∼22,000 white men and women to determine which loci influence SHBG concentrations. Genes near the identified genomic markers in addition to the SHBG protein coding gene included PRMT6, GCKR, ZBTB10, JMJD1C, SLCO1B1, NR2F2, ZNF652, TDGF3, LHCGR, BAIAP2L1, and UGT2B15. These genes represent a wide range of biologic pathways that may relate to SHBG function and sex steroid hormone biology, including liver function, lipid metabolism, carbohydrate metabolism and type 2 diabetes, and the development and progression of sex steroid hormone-responsive cancers.
doi:10.1371/journal.pgen.1002805
PMCID: PMC3400553  PMID: 22829776
16.  A genome-wide association meta-analysis identifies new childhood obesity loci 
Bradfield, Jonathan P. | Taal, H. Rob | Timpson, Nicholas J. | Scherag, André | Lecoeur, Cecile | Warrington, Nicole M. | Hypponen, Elina | Holst, Claus | Valcarcel, Beatriz | Thiering, Elisabeth | Salem, Rany M. | Schumacher, Fredrick R. | Cousminer, Diana L. | Sleiman, Patrick M.A. | Zhao, Jianhua | Berkowitz, Robert I. | Vimaleswaran, Karani S. | Jarick, Ivonne | Pennell, Craig E. | Evans, David M. | St. Pourcain, Beate | Berry, Diane J. | Mook-Kanamori, Dennis O | Hofman, Albert | Rivadeinera, Fernando | Uitterlinden, André G. | van Duijn, Cornelia M. | van der Valk, Ralf J.P. | de Jongste, Johan C. | Postma, Dirkje S. | Boomsma, Dorret I. | Gauderman, William J. | Hassanein, Mohamed T. | Lindgren, Cecilia M. | Mägi, Reedik | Boreham, Colin A.G. | Neville, Charlotte E. | Moreno, Luis A. | Elliott, Paul | Pouta, Anneli | Hartikainen, Anna-Liisa | Li, Mingyao | Raitakari, Olli | Lehtimäki, Terho | Eriksson, Johan G. | Palotie, Aarno | Dallongeville, Jean | Das, Shikta | Deloukas, Panos | McMahon, George | Ring, Susan M. | Kemp, John P. | Buxton, Jessica L. | Blakemore, Alexandra I.F. | Bustamante, Mariona | Guxens, Mònica | Hirschhorn, Joel N. | Gillman, Matthew W. | Kreiner-Møller, Eskil | Bisgaard, Hans | Gilliland, Frank D. | Heinrich, Joachim | Wheeler, Eleanor | Barroso, Inês | O'Rahilly, Stephen | Meirhaeghe, Aline | Sørensen, Thorkild I.A. | Power, Chris | Palmer, Lyle J. | Hinney, Anke | Widen, Elisabeth | Farooqi, I. Sadaf | McCarthy, Mark I. | Froguel, Philippe | Meyre, David | Hebebrand, Johannes | Jarvelin, Marjo-Riitta | Jaddoe, Vincent W.V. | Smith, George Davey | Hakonarson, Hakon | Grant, Struan F.A.
Nature Genetics  2012;44(5):526-531.
Multiple genetic variants have been associated with adult obesity and a few with severe obesity in childhood; however, less progress has been made to establish genetic influences on common early-onset obesity. We performed a North American-Australian-European collaborative meta-analysis of fourteen studies consisting of 5,530 cases (≥95th percentile of body mass index (BMI)) and 8,318 controls (<50th percentile of BMI) of European ancestry. Taking forward the eight novel signals yielding association with P < 5×10−6 in to nine independent datasets (n = 2,818 cases and 4,083 controls) we observed two loci that yielded a genome wide significant combined P-value, namely near OLFM4 on 13q14 (rs9568856; P=1.82×10−9; OR=1.22) and within HOXB5 on 17q21 (rs9299; P=3.54×10−9; OR=1.14). Both loci continued to show association when including two extreme childhood obesity cohorts (n = 2,214 cases and 2,674 controls). Finally, these two loci yielded directionally consistent associations in the GIANT meta-analysis of adult BMI1.
doi:10.1038/ng.2247
PMCID: PMC3370100  PMID: 22484627
17.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture 
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
doi:10.1038/ng.2606
PMCID: PMC3973018  PMID: 23563607
18.  Sequence variants at CHRNB3-CHRNA6 and CYP2A6 affect smoking behavior 
Thorgeirsson, Thorgeir E. | Gudbjartsson, Daniel F. | Surakka, Ida | Vink, Jacqueline M. | Amin, Najaf | Geller, Frank | Sulem, Patrick | Rafnar, Thorunn | Esko, Tõnu | Walter, Stefan | Gieger, Christian | Rawal, Rajesh | Mangino, Massimo | Prokopenko, Inga | Mägi, Reedik | Keskitalo, Kaisu | Gudjonsdottir, Iris H. | Gretarsdottir, Solveig | Stefansson, Hreinn | Thompson, John R. | Aulchenko, Yurii S. | Nelis, Mari | Aben, Katja K. | den Heijer, Martin | Dirksen, Asger | Ashraf, Haseem | Soranzo, Nicole | Valdes, Ana M | Steves, Claire | Uitterlinden, André G | Hofman, Albert | Tönjes, Anke | Kovacs, Peter | Hottenga, Jouke Jan | Willemsen, Gonneke | Vogelzangs, Nicole | Döring, Angela | Dahmen, Norbert | Nitz, Barbara | Pergadia, Michele L. | Saez, Berta | De Diego, Veronica | Lezcano, Victoria | Garcia-Prats, Maria D. | Ripatti, Samuli | Perola, Markus | Kettunen, Johannes | Hartikainen, Anna-Liisa | Pouta, Anneli | Laitinen, Jaana | Isohanni, Matti | Huei-Yi, Shen | Allen, Maxine | Krestyaninova, Maria | Hall, Alistair S | Jones, Gregory T. | van Rij, Andre M. | Mueller, Thomas | Dieplinger, Benjamin | Haltmayer, Meinhard | Jonsson, Steinn | Matthiasson, Stefan E. | Oskarsson, Hogni | Tyrfingsson, Thorarinn | Kiemeney, Lambertus A. | Mayordomo, Jose I. | Lindholt, Jes S | Pedersen, Jesper Holst | Franklin, Wilbur A. | Wolf, Holly | Montgomery, Grant W. | Heath, Andrew C. | Martin, Nicholas G. | Madden, Pamela A.F. | Giegling, Ina | Rujescu, Dan | Järvelin, Marjo-Riitta | Salomaa, Veikko | Stumvoll, Michael | Spector, Tim D | Wichmann, H-Erich | Metspalu, Andres | Samani, Nilesh J. | Penninx, Brenda W. | Oostra, Ben A. | Boomsma, Dorret I. | Tiemeier, Henning | van Duijn, Cornelia M. | Kaprio, Jaakko | Gulcher, Jeffrey R. | McCarthy, Mark I. | Peltonen, Leena | Thorsteinsdottir, Unnur | Stefansson, Kari
Nature genetics  2010;42(5):448-453.
Smoking is a risk factor for most of the diseases leading in mortality1. We conducted genome-wide association (GWA) meta-analyses of smoking data within the ENGAGE consortium to search for common alleles associating with the number of cigarettes smoked per day (CPD) in smokers (N=31,266) and smoking initiation (N=46,481). We tested selected SNPs in a second stage (N=45,691 smokers), and assessed some in a third sample (N=9,040). Variants in three genomic regions associated with CPD (P< 5·10−8), including previously identified SNPs at 15q25 represented by rs1051730-A (0.80 CPD,P=2.4·10−69), and SNPs at 19q13 and 8p11, represented by rs4105144-C (0.39 CPD, P=2.2·10−12) and rs6474412-T (0.29 CPD,P= 1.4·10−8), respectively. Among the genes at the two novel loci, are genes encoding nicotine-metabolizing enzymes (CYP2A6 and CYP2B6), and nicotinic acetylcholine receptor subunits (CHRNB3 and CHRNA6) highlighted in previous studies of nicotine dependence2-3. Nominal associations with lung cancer were observed at both 8p11 (rs6474412-T,OR=1.09,P=0.04) and 19q13 (rs4105144-C,OR=1.12,P=0.0006).
doi:10.1038/ng.573
PMCID: PMC3080600  PMID: 20418888
19.  Common Variation in the FTO Gene Alters Diabetes-Related Metabolic Traits to the Extent Expected Given Its Effect on BMI 
Diabetes  2008;57(5):1419-1426.
OBJECTIVE
Common variation in the FTO gene is associated with BMI and type 2 diabetes. Increased BMI is associated with diabetes risk factors, including raised insulin, glucose, and triglycerides. We aimed to test whether FTO genotype is associated with variation in these metabolic traits.
RESEARCH DESIGN AND METHODS
We tested the association between FTO genotype and 10 metabolic traits using data from 17,037 white European individuals. We compared the observed effect of FTO genotype on each trait to that expected given the FTO-BMI and BMI-trait associations.
RESULTS
Each copy of the FTO rs9939609 A allele was associated with higher fasting insulin (0.039 SD [95% CI 0.013–0.064]; P = 0.003), glucose (0.024 [0.001– 0.048]; P = 0.044), and triglycerides (0.028 [0.003– 0.052]; P = 0.025) and lower HDL cholesterol (0.032 [0.008 – 0.057]; P = 0.009). There was no evidence of these associations when adjusting for BMI. Associations with fasting alanine aminotransferase, γ-glutamyl-transferase, LDL cholesterol, A1C, and systolic and diastolic blood pressure were in the expected direction but did not reach P < 0.05. For all metabolic traits, effect sizes were consistent with those expected for the per allele change in BMI. FTO genotype was associated with a higher odds of metabolic syndrome (odds ratio 1.17 [95% CI 1.10 –1.25]; P = 3 × 10−6).
CONCLUSIONS
FTO genotype is associated with metabolic traits to an extent entirely consistent with its effect on BMI. Sample sizes of >12,000 individuals were needed to detect associations at P < 0.05. Our findings highlight the importance of using appropriately powered studies to assess the effects of a known diabetes or obesity variant on secondary traits correlated with these conditions.
doi:10.2337/db07-1466
PMCID: PMC3073395  PMID: 18346983
20.  Association between Common Variation at the FTO Locus and Changes in Body Mass Index from Infancy to Late Childhood: The Complex Nature of Genetic Association through Growth and Development 
PLoS Genetics  2011;7(2):e1001307.
An age-dependent association between variation at the FTO locus and BMI in children has been suggested. We meta-analyzed associations between the FTO locus (rs9939609) and BMI in samples, aged from early infancy to 13 years, from 8 cohorts of European ancestry. We found a positive association between additional minor (A) alleles and BMI from 5.5 years onwards, but an inverse association below age 2.5 years. Modelling median BMI curves for each genotype using the LMS method, we found that carriers of minor alleles showed lower BMI in infancy, earlier adiposity rebound (AR), and higher BMI later in childhood. Differences by allele were consistent with two independent processes: earlier AR equivalent to accelerating developmental age by 2.37% (95% CI 1.87, 2.87, p = 10−20) per A allele and a positive age by genotype interaction such that BMI increased faster with age (p = 10−23). We also fitted a linear mixed effects model to relate genotype to the BMI curve inflection points adiposity peak (AP) in infancy and AR. Carriage of two minor alleles at rs9939609 was associated with lower BMI at AP (−0.40% (95% CI: −0.74, −0.06), p = 0.02), higher BMI at AR (0.93% (95% CI: 0.22, 1.64), p = 0.01), and earlier AR (−4.72% (−5.81, −3.63), p = 10−17), supporting cross-sectional results. Overall, we confirm the expected association between variation at rs9939609 and BMI in childhood, but only after an inverse association between the same variant and BMI in infancy. Patterns are consistent with a shift on the developmental scale, which is reflected in association with the timing of AR rather than just a global increase in BMI. Results provide important information about longitudinal gene effects and about the role of FTO in adiposity. The associated shifts in developmental timing have clinical importance with respect to known relationships between AR and both later-life BMI and metabolic disease risk.
Author Summary
Variation at the FTO locus is reliably associated with BMI and adiposity-related traits, but little is still known about the effects of variation at this gene, particularly in children. We have examined a large collection of samples for which both genotypes at rs9939609 and multiple measurements of BMI are available. We observe a positive association between the minor allele (A) at rs9939609 and BMI emerging in childhood that has the characteristics of a shift in the age scale leading simultaneously to lower BMI during infancy and higher BMI in childhood. Assessed in cross section and longitudinally, we find evidence of variation at rs9939609 being associated with the timing of AR and the concert of events expected with such a change to the BMI curve. Importantly, the apparently negative association between the minor allele (A) and BMI in early life, which is then followed by an earlier AR and greater BMI in childhood, is a pattern known to be associated with both the risk of adult BMI and metabolic disorders such as type 2 diabetes (T2D). These findings are important in our understanding of the contribution of FTO to adiposity, but also in light of efforts to appreciate genetic effects in a lifecourse context.
doi:10.1371/journal.pgen.1001307
PMCID: PMC3040655  PMID: 21379325
21.  Variants in ADCY5 and near CCNL1 are associated with fetal growth and birth weight 
Freathy, Rachel M | Mook-Kanamori, Dennis O | Sovio, Ulla | Prokopenko, Inga | Timpson, Nicholas J | Berry, Diane J | Warrington, Nicole M | Widen, Elisabeth | Hottenga, Jouke Jan | Kaakinen, Marika | Lange, Leslie A | Bradfield, Jonathan P | Kerkhof, Marjan | Marsh, Julie A | Mägi, Reedik | Chen, Chih-Mei | Lyon, Helen N | Kirin, Mirna | Adair, Linda S | Aulchenko, Yurii S | Bennett, Amanda J | Borja, Judith B | Bouatia-Naji, Nabila | Charoen, Pimphen | Coin, Lachlan J M | Cousminer, Diana L | de Geus, Eco J. C. | Deloukas, Panos | Elliott, Paul | Evans, David M | Froguel, Philippe | Glaser, Beate | Groves, Christopher J | Hartikainen, Anna-Liisa | Hassanali, Neelam | Hirschhorn, Joel N | Hofman, Albert | Holly, Jeff M P | Hyppönen, Elina | Kanoni, Stavroula | Knight, Bridget A | Laitinen, Jaana | Lindgren, Cecilia M | McArdle, Wendy L | O'Reilly, Paul F | Pennell, Craig E | Postma, Dirkje S | Pouta, Anneli | Ramasamy, Adaikalavan | Rayner, Nigel W | Ring, Susan M | Rivadeneira, Fernando | Shields, Beverley M | Strachan, David P | Surakka, Ida | Taanila, Anja | Tiesler, Carla | Uitterlinden, Andre G | van Duijn, Cornelia M | Wijga, Alet H | Willemsen, Gonneke | Zhang, Haitao | Zhao, Jianhua | Wilson, James F | Steegers, Eric A P | Hattersley, Andrew T | Eriksson, Johan G | Peltonen, Leena | Mohlke, Karen L | Grant, Struan F A | Hakonarson, Hakon | Koppelman, Gerard H | Dedoussis, George V | Heinrich, Joachim | Gillman, Matthew W | Palmer, Lyle J | Frayling, Timothy M | Boomsma, Dorret I | Smith, George Davey | Power, Chris | Jaddoe, Vincent W V | Jarvelin, Marjo-Riitta | McCarthy, Mark I
Nature genetics  2010;42(5):430-435.
INTRODUCTORY PARAGRAPH
To identify genetic variants associated with birth weight, we meta-analyzed six genome-wide association (GWA) studies (N=10,623 Europeans from pregnancy/birth cohorts) and followed up two lead signals in thirteen replication studies (N=27,591). Rs900400 near LEKR1 and CCNL1 (P=2×10−35), and rs9883204 in ADCY5 (P=7×10−15) were robustly associated with birth weight. Correlated SNPs in ADCY5 were recently implicated in regulation of glucose levels and type 2 diabetes susceptibility,1 providing evidence that the well described association between lower birth weight and subsequent type 2 diabetes2,3 has a genetic component, distinct from the proposed role of programming by maternal nutrition. Using data from both SNPs, the 9% of Europeans with 4 birth weight-lowering alleles were, on average, 113g (95%CI 89-137g) lighter at birth than the 24% with 0 or 1 allele (Ptrend=7×10−30). The impact on birth weight is similar to that of a mother smoking 4-5 cigarettes per day in the third trimester of pregnancy.4
doi:10.1038/ng.567
PMCID: PMC2862164  PMID: 20372150
22.  Eight blood pressure loci identified by genome-wide association study of 34,433 people of European ancestry 
Newton-Cheh, Christopher | Johnson, Toby | Gateva, Vesela | Tobin, Martin D | Bochud, Murielle | Coin, Lachlan | Najjar, Samer S | Zhao, Jing Hua | Heath, Simon C | Eyheramendy, Susana | Papadakis, Konstantinos | Voight, Benjamin F | Scott, Laura J | Zhang, Feng | Farrall, Martin | Tanaka, Toshiko | Wallace, Chris | Chambers, John C | Khaw, Kay-Tee | Nilsson, Peter | van der Harst, Pim | Polidoro, Silvia | Grobbee, Diederick E | Onland-Moret, N Charlotte | Bots, Michiel L | Wain, Louise V | Elliott, Katherine S | Teumer, Alexander | Luan, Jian’an | Lucas, Gavin | Kuusisto, Johanna | Burton, Paul R | Hadley, David | McArdle, Wendy L | Brown, Morris | Dominiczak, Anna | Newhouse, Stephen J | Samani, Nilesh J | Webster, John | Zeggini, Eleftheria | Beckmann, Jacques S | Bergmann, Sven | Lim, Noha | Song, Kijoung | Vollenweider, Peter | Waeber, Gerard | Waterworth, Dawn M | Yuan, Xin | Groop, Leif | Orho-Melander, Marju | Allione, Alessandra | Di Gregorio, Alessandra | Guarrera, Simonetta | Panico, Salvatore | Ricceri, Fulvio | Romanazzi, Valeria | Sacerdote, Carlotta | Vineis, Paolo | Barroso, Inês | Sandhu, Manjinder S | Luben, Robert N | Crawford, Gabriel J. | Jousilahti, Pekka | Perola, Markus | Boehnke, Michael | Bonnycastle, Lori L | Collins, Francis S | Jackson, Anne U | Mohlke, Karen L | Stringham, Heather M | Valle, Timo T | Willer, Cristen J | Bergman, Richard N | Morken, Mario A | Döring, Angela | Gieger, Christian | Illig, Thomas | Meitinger, Thomas | Org, Elin | Pfeufer, Arne | Wichmann, H Erich | Kathiresan, Sekar | Marrugat, Jaume | O’Donnell, Christopher J | Schwartz, Stephen M | Siscovick, David S | Subirana, Isaac | Freimer, Nelson B | Hartikainen, Anna-Liisa | McCarthy, Mark I | O’Reilly, Paul F | Peltonen, Leena | Pouta, Anneli | de Jong, Paul E | Snieder, Harold | van Gilst, Wiek H | Clarke, Robert | Goel, Anuj | Hamsten, Anders | Peden, John F | Seedorf, Udo | Syvänen, Ann-Christine | Tognoni, Giovanni | Lakatta, Edward G | Sanna, Serena | Scheet, Paul | Schlessinger, David | Scuteri, Angelo | Dörr, Marcus | Ernst, Florian | Felix, Stephan B | Homuth, Georg | Lorbeer, Roberto | Reffelmann, Thorsten | Rettig, Rainer | Völker, Uwe | Galan, Pilar | Gut, Ivo G | Hercberg, Serge | Lathrop, G Mark | Zeleneka, Diana | Deloukas, Panos | Soranzo, Nicole | Williams, Frances M | Zhai, Guangju | Salomaa, Veikko | Laakso, Markku | Elosua, Roberto | Forouhi, Nita G | Völzke, Henry | Uiterwaal, Cuno S | van der Schouw, Yvonne T | Numans, Mattijs E | Matullo, Giuseppe | Navis, Gerjan | Berglund, Göran | Bingham, Sheila A | Kooner, Jaspal S | Paterson, Andrew D | Connell, John M | Bandinelli, Stefania | Ferrucci, Luigi | Watkins, Hugh | Spector, Tim D | Tuomilehto, Jaakko | Altshuler, David | Strachan, David P | Laan, Maris | Meneton, Pierre | Wareham, Nicholas J | Uda, Manuela | Jarvelin, Marjo-Riitta | Mooser, Vincent | Melander, Olle | Loos, Ruth JF | Elliott, Paul | Abecasis, Goncalo R | Caulfield, Mark | Munroe, Patricia B
Nature genetics  2009;41(6):666-676.
Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5m genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N≤71,225 European ancestry, N=12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N=29,136). We identified association between systolic or diastolic blood pressure and common variants in 8 regions near the CYP17A1 (P=7×10−24), CYP1A2 (P=1×10−23), FGF5 (P=1×10−21), SH2B3 (P=3×10−18), MTHFR (P=2×10−13), c10orf107 (P=1×10−9), ZNF652 (P=5×10−9) and PLCD3 (P=1×10−8) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
doi:10.1038/ng.361
PMCID: PMC2891673  PMID: 19430483
23.  Life-Course Analysis of a Fat Mass and Obesity-Associated (FTO) Gene Variant and Body Mass Index in the Northern Finland Birth Cohort 1966 Using Structural Equation Modeling 
American Journal of Epidemiology  2010;172(6):653-665.
The association between variation in the fat mass and obesity-associated (FTO) gene and adulthood body mass index (BMI; weight (kg)/height (m)2) is well-replicated. More thorough analyses utilizing phenotypic data over the life course may deepen our understanding of the development of BMI and thus help in the prevention of obesity. The authors used a structural equation modeling approach to explore the network of variables associated with BMI from the prenatal period to age 31 years (1965–1997) in 4,435 subjects from the Northern Finland Birth Cohort 1966. The use of structural equation modeling permitted the easy inclusion of variables with missing values in the analyses without separate imputation steps, as well as differentiation between direct and indirect effects. There was an association between the FTO single nucleotide polymorphism rs9939609 and BMI at age 31 years that persisted after controlling for several relevant factors during the life course. The total effect of the FTO variant on adult BMI was mostly composed of the direct effect, but a notable part was also arising indirectly via its effects on earlier BMI development. In addition to well-established genetic determinants, many life-course factors such as physical activity, in spite of not showing mediation or interaction, had a strong independent effect on BMI.
doi:10.1093/aje/kwq178
PMCID: PMC2938267  PMID: 20702506
body mass index; molecular epidemiology; structural equation model
24.  Type 2 Diabetes Risk Alleles Are Associated With Reduced Size at Birth 
Diabetes  2009;58(6):1428-1433.
OBJECTIVE
Low birth weight is associated with an increased risk of type 2 diabetes. The mechanisms underlying this association are unknown and may represent intrauterine programming or two phenotypes of one genotype. The fetal insulin hypothesis proposes that common genetic variants that reduce insulin secretion or action may predispose to type 2 diabetes and also reduce birth weight, since insulin is a key fetal growth factor. We tested whether common genetic variants that predispose to type 2 diabetes also reduce birth weight.
RESEARCH DESIGN AND METHODS
We genotyped single-nucleotide polymorphisms (SNPs) at five recently identified type 2 diabetes loci (CDKAL1, CDKN2A/B, HHEX-IDE, IGF2BP2, and SLC30A8) in 7,986 mothers and 19,200 offspring from four studies of white Europeans. We tested the association between maternal or fetal genotype at each locus and birth weight of the offspring.
RESULTS
We found that type 2 diabetes risk alleles at the CDKAL1 and HHEX-IDE loci were associated with reduced birth weight when inherited by the fetus (21 g [95% CI 11–31], P = 2 × 10−5, and 14 g [4–23], P = 0.004, lower birth weight per risk allele, respectively). The 4% of offspring carrying four risk alleles at these two loci were 80 g (95% CI 39–120) lighter at birth than the 8% carrying none (Ptrend = 5 × 10−7). There were no associations between birth weight and fetal genotypes at the three other loci or maternal genotypes at any locus.
CONCLUSIONS
Our results are in keeping with the fetal insulin hypothesis and provide robust evidence that common disease-associated variants can alter size at birth directly through the fetal genotype.
doi:10.2337/db08-1739
PMCID: PMC2682672  PMID: 19228808

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