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1.  Comparative Analysis of Metabolic Syndrome Components in over 15,000 African Americans Identifies Pleiotropic Variants: Results from the PAGE Study 
Background
Metabolic syndrome (MetS) refers to the clustering of cardio-metabolic risk factors including dyslipidemia, central adiposity, hypertension and hyperglycemia in individuals. Identification of pleiotropic genetic factors associated with MetS traits may shed light on key pathways or mediators underlying MetS.
Methods and Results
Using the Metabochip array in 15,148 African Americans (AA) from the PAGE Study, we identify susceptibility loci and investigate pleiotropy among genetic variants using a subset-based meta-analysis method, ASsociation-analysis-based-on-subSETs (ASSET). Unlike conventional models which lack power when associations for MetS components are null or have opposite effects, ASSET uses one-sided tests to detect positive and negative associations for components separately and combines tests accounting for correlations among components. With ASSET, we identify 27 SNPs in 1 glucose and 4 lipids loci (TCF7L2, LPL, APOA5, CETP, LPL, APOC1/APOE/TOMM40) significantly associated with MetS components overall, all P< 2.5e-7, the Bonferroni adjusted P-value. Three loci replicate in a Hispanic population, n=5172. A novel AA-specific variant, rs12721054/APOC1, and rs10096633/LPL are associated with ≥3 MetS components. We find additional evidence of pleiotropy for APOE, TOMM40, TCF7L2 and CETP variants, many with opposing effects; e.g. the same rs7901695/TCF7L2 allele is associated with increased odds of high glucose and decreased odds of central adiposity.
Conclusions
We highlight a method to increase power in large-scale genomic association analyses, and report a novel variant associated with all MetS components in AA. We also identify pleiotropic associations that may be clinically useful in patient risk profiling and for informing translational research of potential gene targets and medications.
doi:10.1161/CIRCGENETICS.113.000386
PMCID: PMC4142758  PMID: 25023634
metabolic syndrome; population studies; high-density lipoprotein cholesterol; genetic variation; hyperglycemia; ASSET; PAGE Study; African Americans; cardio-metabolic traits; Metabochip
2.  Pleiotropic effects of genetic risk variants for other cancers on colorectal cancer risk: PAGE, GECCO, and CCFR Consortia 
Gut  2013;63(5):800-807.
Objective
Genome-wide association studies (GWAS) have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesized that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer.
Design
We examined 13,338 colorectal cancer cases and 40,967 controls from three consortia: Population Architecture using Genetics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p-value of 2.92×10−4 was used to determine statistical significance of the associations.
Results
Two correlated SNPs— rs10090154 and rs4242382—in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI: 1.07–1.18; P=1.74×10−5), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites.
Conclusion
This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer, thus adding colorectal cancer to the list of cancer sites linked to this particular multi-cancer risk region at 8q24.
doi:10.1136/gutjnl-2013-305189
PMCID: PMC3918490  PMID: 23935004
colorectal cancer; pleiotropy; genome-wide association study; single nucleotide polymorphism
3.  Defining the role of common variation in the genomic and biological architecture of adult human height 
Wood, Andrew R | Esko, Tonu | Yang, Jian | Vedantam, Sailaja | Pers, Tune H | Gustafsson, Stefan | Chu, Audrey Y | Estrada, Karol | Luan, Jian’an | Kutalik, Zoltán | Amin, Najaf | Buchkovich, Martin L | Croteau-Chonka, Damien C | Day, Felix R | Duan, Yanan | Fall, Tove | Fehrmann, Rudolf | Ferreira, Teresa | Jackson, Anne U | Karjalainen, Juha | Lo, Ken Sin | Locke, Adam E | Mägi, Reedik | Mihailov, Evelin | Porcu, Eleonora | Randall, Joshua C | Scherag, André | Vinkhuyzen, Anna AE | Westra, Harm-Jan | Winkler, Thomas W | Workalemahu, Tsegaselassie | Zhao, Jing Hua | Absher, Devin | Albrecht, Eva | Anderson, Denise | Baron, Jeffrey | Beekman, Marian | Demirkan, Ayse | Ehret, Georg B | Feenstra, Bjarke | Feitosa, Mary F | Fischer, Krista | Fraser, Ross M | Goel, Anuj | Gong, Jian | Justice, Anne E | Kanoni, Stavroula | Kleber, Marcus E | Kristiansson, Kati | Lim, Unhee | Lotay, Vaneet | Lui, Julian C | Mangino, Massimo | Leach, Irene Mateo | Medina-Gomez, Carolina | Nalls, Michael A | Nyholt, Dale R | Palmer, Cameron D | Pasko, Dorota | Pechlivanis, Sonali | Prokopenko, Inga | Ried, Janina S | Ripke, Stephan | Shungin, Dmitry | Stancáková, Alena | Strawbridge, Rona J | Sung, Yun Ju | Tanaka, Toshiko | Teumer, Alexander | Trompet, Stella | van der Laan, Sander W | van Setten, Jessica | Van Vliet-Ostaptchouk, Jana V | Wang, Zhaoming | Yengo, Loïc | Zhang, Weihua | Afzal, Uzma | Ärnlöv, Johan | Arscott, Gillian M | Bandinelli, Stefania | Barrett, Amy | Bellis, Claire | Bennett, Amanda J | Berne, Christian | Blüher, Matthias | Bolton, Jennifer L | Böttcher, Yvonne | Boyd, Heather A | Bruinenberg, Marcel | Buckley, Brendan M | Buyske, Steven | Caspersen, Ida H | Chines, Peter S | Clarke, Robert | Claudi-Boehm, Simone | Cooper, Matthew | Daw, E Warwick | De Jong, Pim A | Deelen, Joris | Delgado, Graciela | Denny, Josh C | Dhonukshe-Rutten, Rosalie | Dimitriou, Maria | Doney, Alex SF | Dörr, Marcus | Eklund, Niina | Eury, Elodie | Folkersen, Lasse | Garcia, Melissa E | Geller, Frank | Giedraitis, Vilmantas | Go, Alan S | Grallert, Harald | Grammer, Tanja B | Gräßler, Jürgen | Grönberg, Henrik | de Groot, Lisette C.P.G.M. | Groves, Christopher J | Haessler, Jeffrey | Hall, Per | Haller, Toomas | Hallmans, Goran | Hannemann, Anke | Hartman, Catharina A | Hassinen, Maija | Hayward, Caroline | Heard-Costa, Nancy L | Helmer, Quinta | Hemani, Gibran | Henders, Anjali K | Hillege, Hans L | Hlatky, Mark A | Hoffmann, Wolfgang | Hoffmann, Per | Holmen, Oddgeir | Houwing-Duistermaat, Jeanine J | Illig, Thomas | Isaacs, Aaron | James, Alan L | Jeff, Janina | Johansen, Berit | Johansson, Åsa | Jolley, Jennifer | Juliusdottir, Thorhildur | Junttila, Juhani | Kho, Abel N | Kinnunen, Leena | Klopp, Norman | Kocher, Thomas | Kratzer, Wolfgang | Lichtner, Peter | Lind, Lars | Lindström, Jaana | Lobbens, Stéphane | Lorentzon, Mattias | Lu, Yingchang | Lyssenko, Valeriya | Magnusson, Patrik KE | Mahajan, Anubha | Maillard, Marc | McArdle, Wendy L | McKenzie, Colin A | McLachlan, Stela | McLaren, Paul J | Menni, Cristina | Merger, Sigrun | Milani, Lili | Moayyeri, Alireza | Monda, Keri L | Morken, Mario A | Müller, Gabriele | Müller-Nurasyid, Martina | Musk, Arthur W | Narisu, Narisu | Nauck, Matthias | Nolte, Ilja M | Nöthen, Markus M | Oozageer, Laticia | Pilz, Stefan | Rayner, Nigel W | Renstrom, Frida | Robertson, Neil R | Rose, Lynda M | Roussel, Ronan | Sanna, Serena | Scharnagl, Hubert | Scholtens, Salome | Schumacher, Fredrick R | Schunkert, Heribert | Scott, Robert A | Sehmi, Joban | Seufferlein, Thomas | Shi, Jianxin | Silventoinen, Karri | Smit, Johannes H | Smith, Albert Vernon | Smolonska, Joanna | Stanton, Alice V | Stirrups, Kathleen | Stott, David J | Stringham, Heather M | Sundström, Johan | Swertz, Morris A | Syvänen, Ann-Christine | Tayo, Bamidele O | Thorleifsson, Gudmar | Tyrer, Jonathan P | van Dijk, Suzanne | van Schoor, Natasja M | van der Velde, Nathalie | van Heemst, Diana | van Oort, Floor VA | Vermeulen, Sita H | Verweij, Niek | Vonk, Judith M | Waite, Lindsay L | Waldenberger, Melanie | Wennauer, Roman | Wilkens, Lynne R | Willenborg, Christina | Wilsgaard, Tom | Wojczynski, Mary K | Wong, Andrew | Wright, Alan F | Zhang, Qunyuan | Arveiler, Dominique | Bakker, Stephan JL | Beilby, John | Bergman, Richard N | Bergmann, Sven | Biffar, Reiner | Blangero, John | Boomsma, Dorret I | Bornstein, Stefan R | Bovet, Pascal | Brambilla, Paolo | Brown, Morris J | Campbell, Harry | Caulfield, Mark J | Chakravarti, Aravinda | Collins, Rory | Collins, Francis S | Crawford, Dana C | Cupples, L Adrienne | Danesh, John | de Faire, Ulf | den Ruijter, Hester M | Erbel, Raimund | Erdmann, Jeanette | Eriksson, Johan G | Farrall, Martin | Ferrannini, Ele | Ferrières, Jean | Ford, Ian | Forouhi, Nita G | Forrester, Terrence | Gansevoort, Ron T | Gejman, Pablo V | Gieger, Christian | Golay, Alain | Gottesman, Omri | Gudnason, Vilmundur | Gyllensten, Ulf | Haas, David W | Hall, Alistair S | Harris, Tamara B | Hattersley, Andrew T | Heath, Andrew C | Hengstenberg, Christian | Hicks, Andrew A | Hindorff, Lucia A | Hingorani, Aroon D | Hofman, Albert | Hovingh, G Kees | Humphries, Steve E | Hunt, Steven C | Hypponen, Elina | Jacobs, Kevin B | Jarvelin, Marjo-Riitta | Jousilahti, Pekka | Jula, Antti M | Kaprio, Jaakko | Kastelein, John JP | Kayser, Manfred | Kee, Frank | Keinanen-Kiukaanniemi, Sirkka M | Kiemeney, Lambertus A | Kooner, Jaspal S | Kooperberg, Charles | Koskinen, Seppo | Kovacs, Peter | Kraja, Aldi T | Kumari, Meena | Kuusisto, Johanna | Lakka, Timo A | Langenberg, Claudia | Le Marchand, Loic | Lehtimäki, Terho | Lupoli, Sara | Madden, Pamela AF | Männistö, Satu | Manunta, Paolo | Marette, André | Matise, Tara C | McKnight, Barbara | Meitinger, Thomas | Moll, Frans L | Montgomery, Grant W | Morris, Andrew D | Morris, Andrew P | Murray, Jeffrey C | Nelis, Mari | Ohlsson, Claes | Oldehinkel, Albertine J | Ong, Ken K | Ouwehand, Willem H | Pasterkamp, Gerard | Peters, Annette | Pramstaller, Peter P | Price, Jackie F | Qi, Lu | Raitakari, Olli T | Rankinen, Tuomo | Rao, DC | Rice, Treva K | Ritchie, Marylyn | Rudan, Igor | Salomaa, Veikko | Samani, Nilesh J | Saramies, Jouko | Sarzynski, Mark A | Schwarz, Peter EH | Sebert, Sylvain | Sever, Peter | Shuldiner, Alan R | Sinisalo, Juha | Steinthorsdottir, Valgerdur | Stolk, Ronald P | Tardif, Jean-Claude | Tönjes, Anke | Tremblay, Angelo | Tremoli, Elena | Virtamo, Jarmo | Vohl, Marie-Claude | Amouyel, Philippe | Asselbergs, Folkert W | Assimes, Themistocles L | Bochud, Murielle | Boehm, Bernhard O | Boerwinkle, Eric | Bottinger, Erwin P | Bouchard, Claude | Cauchi, Stéphane | Chambers, John C | Chanock, Stephen J | Cooper, Richard S | de Bakker, Paul IW | Dedoussis, George | Ferrucci, Luigi | Franks, Paul W | Froguel, Philippe | Groop, Leif C | Haiman, Christopher A | Hamsten, Anders | Hayes, M Geoffrey | Hui, Jennie | Hunter, David J. | Hveem, Kristian | Jukema, J Wouter | Kaplan, Robert C | Kivimaki, Mika | Kuh, Diana | Laakso, Markku | Liu, Yongmei | Martin, Nicholas G | März, Winfried | Melbye, Mads | Moebus, Susanne | Munroe, Patricia B | Njølstad, Inger | Oostra, Ben A | Palmer, Colin NA | Pedersen, Nancy L | Perola, Markus | Pérusse, Louis | Peters, Ulrike | Powell, Joseph E | Power, Chris | Quertermous, Thomas | Rauramaa, Rainer | Reinmaa, Eva | Ridker, Paul M | Rivadeneira, Fernando | Rotter, Jerome I | Saaristo, Timo E | Saleheen, Danish | Schlessinger, David | Slagboom, P Eline | Snieder, Harold | Spector, Tim D | Strauch, Konstantin | Stumvoll, Michael | Tuomilehto, Jaakko | Uusitupa, Matti | van der Harst, Pim | Völzke, Henry | Walker, Mark | Wareham, Nicholas J | Watkins, Hugh | Wichmann, H-Erich | Wilson, James F | Zanen, Pieter | Deloukas, Panos | Heid, Iris M | Lindgren, Cecilia M | Mohlke, Karen L | Speliotes, Elizabeth K | Thorsteinsdottir, Unnur | Barroso, Inês | Fox, Caroline S | North, Kari E | Strachan, David P | Beckmann, Jacques S. | Berndt, Sonja I | Boehnke, Michael | Borecki, Ingrid B | McCarthy, Mark I | Metspalu, Andres | Stefansson, Kari | Uitterlinden, André G | van Duijn, Cornelia M | Franke, Lude | Willer, Cristen J | Price, Alkes L. | Lettre, Guillaume | Loos, Ruth JF | Weedon, Michael N | Ingelsson, Erik | O’Connell, Jeffrey R | Abecasis, Goncalo R | Chasman, Daniel I | Goddard, Michael E | Visscher, Peter M | Hirschhorn, Joel N | Frayling, Timothy M
Nature genetics  2014;46(11):1173-1186.
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explain one-fifth of heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured the majority (60%) of heritability. The 697 variants clustered in 423 loci enriched for genes, pathways, and tissue-types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin, and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
doi:10.1038/ng.3097
PMCID: PMC4250049  PMID: 25282103
4.  Defining the role of common variation in the genomic and biological architecture of adult human height 
Wood, Andrew R | Esko, Tonu | Yang, Jian | Vedantam, Sailaja | Pers, Tune H | Gustafsson, Stefan | Chu, Audrey Y | Estrada, Karol | Luan, Jian’an | Kutalik, Zoltán | Amin, Najaf | Buchkovich, Martin L | Croteau-Chonka, Damien C | Day, Felix R | Duan, Yanan | Fall, Tove | Fehrmann, Rudolf | Ferreira, Teresa | Jackson, Anne U | Karjalainen, Juha | Lo, Ken Sin | Locke, Adam E | Mägi, Reedik | Mihailov, Evelin | Porcu, Eleonora | Randall, Joshua C | Scherag, André | Vinkhuyzen, Anna AE | Westra, Harm-Jan | Winkler, Thomas W | Workalemahu, Tsegaselassie | Zhao, Jing Hua | Absher, Devin | Albrecht, Eva | Anderson, Denise | Baron, Jeffrey | Beekman, Marian | Demirkan, Ayse | Ehret, Georg B | Feenstra, Bjarke | Feitosa, Mary F | Fischer, Krista | Fraser, Ross M | Goel, Anuj | Gong, Jian | Justice, Anne E | Kanoni, Stavroula | Kleber, Marcus E | Kristiansson, Kati | Lim, Unhee | Lotay, Vaneet | Lui, Julian C | Mangino, Massimo | Leach, Irene Mateo | Medina-Gomez, Carolina | Nalls, Michael A | Nyholt, Dale R | Palmer, Cameron D | Pasko, Dorota | Pechlivanis, Sonali | Prokopenko, Inga | Ried, Janina S | Ripke, Stephan | Shungin, Dmitry | Stancáková, Alena | Strawbridge, Rona J | Sung, Yun Ju | Tanaka, Toshiko | Teumer, Alexander | Trompet, Stella | van der Laan, Sander W | van Setten, Jessica | Van Vliet-Ostaptchouk, Jana V | Wang, Zhaoming | Yengo, Loïc | Zhang, Weihua | Afzal, Uzma | Ärnlöv, Johan | Arscott, Gillian M | Bandinelli, Stefania | Barrett, Amy | Bellis, Claire | Bennett, Amanda J | Berne, Christian | Blüher, Matthias | Bolton, Jennifer L | Böttcher, Yvonne | Boyd, Heather A | Bruinenberg, Marcel | Buckley, Brendan M | Buyske, Steven | Caspersen, Ida H | Chines, Peter S | Clarke, Robert | Claudi-Boehm, Simone | Cooper, Matthew | Daw, E Warwick | De Jong, Pim A | Deelen, Joris | Delgado, Graciela | Denny, Josh C | Dhonukshe-Rutten, Rosalie | Dimitriou, Maria | Doney, Alex SF | Dörr, Marcus | Eklund, Niina | Eury, Elodie | Folkersen, Lasse | Garcia, Melissa E | Geller, Frank | Giedraitis, Vilmantas | Go, Alan S | Grallert, Harald | Grammer, Tanja B | Gräßler, Jürgen | Grönberg, Henrik | de Groot, Lisette C.P.G.M. | Groves, Christopher J | Haessler, Jeffrey | Hall, Per | Haller, Toomas | Hallmans, Goran | Hannemann, Anke | Hartman, Catharina A | Hassinen, Maija | Hayward, Caroline | Heard-Costa, Nancy L | Helmer, Quinta | Hemani, Gibran | Henders, Anjali K | Hillege, Hans L | Hlatky, Mark A | Hoffmann, Wolfgang | Hoffmann, Per | Holmen, Oddgeir | Houwing-Duistermaat, Jeanine J | Illig, Thomas | Isaacs, Aaron | James, Alan L | Jeff, Janina | Johansen, Berit | Johansson, Åsa | Jolley, Jennifer | Juliusdottir, Thorhildur | Junttila, Juhani | Kho, Abel N | Kinnunen, Leena | Klopp, Norman | Kocher, Thomas | Kratzer, Wolfgang | Lichtner, Peter | Lind, Lars | Lindström, Jaana | Lobbens, Stéphane | Lorentzon, Mattias | Lu, Yingchang | Lyssenko, Valeriya | Magnusson, Patrik KE | Mahajan, Anubha | Maillard, Marc | McArdle, Wendy L | McKenzie, Colin A | McLachlan, Stela | McLaren, Paul J | Menni, Cristina | Merger, Sigrun | Milani, Lili | Moayyeri, Alireza | Monda, Keri L | Morken, Mario A | Müller, Gabriele | Müller-Nurasyid, Martina | Musk, Arthur W | Narisu, Narisu | Nauck, Matthias | Nolte, Ilja M | Nöthen, Markus M | Oozageer, Laticia | Pilz, Stefan | Rayner, Nigel W | Renstrom, Frida | Robertson, Neil R | Rose, Lynda M | Roussel, Ronan | Sanna, Serena | Scharnagl, Hubert | Scholtens, Salome | Schumacher, Fredrick R | Schunkert, Heribert | Scott, Robert A | Sehmi, Joban | Seufferlein, Thomas | Shi, Jianxin | Silventoinen, Karri | Smit, Johannes H | Smith, Albert Vernon | Smolonska, Joanna | Stanton, Alice V | Stirrups, Kathleen | Stott, David J | Stringham, Heather M | Sundström, Johan | Swertz, Morris A | Syvänen, Ann-Christine | Tayo, Bamidele O | Thorleifsson, Gudmar | Tyrer, Jonathan P | van Dijk, Suzanne | van Schoor, Natasja M | van der Velde, Nathalie | van Heemst, Diana | van Oort, Floor VA | Vermeulen, Sita H | Verweij, Niek | Vonk, Judith M | Waite, Lindsay L | Waldenberger, Melanie | Wennauer, Roman | Wilkens, Lynne R | Willenborg, Christina | Wilsgaard, Tom | Wojczynski, Mary K | Wong, Andrew | Wright, Alan F | Zhang, Qunyuan | Arveiler, Dominique | Bakker, Stephan JL | Beilby, John | Bergman, Richard N | Bergmann, Sven | Biffar, Reiner | Blangero, John | Boomsma, Dorret I | Bornstein, Stefan R | Bovet, Pascal | Brambilla, Paolo | Brown, Morris J | Campbell, Harry | Caulfield, Mark J | Chakravarti, Aravinda | Collins, Rory | Collins, Francis S | Crawford, Dana C | Cupples, L Adrienne | Danesh, John | de Faire, Ulf | den Ruijter, Hester M | Erbel, Raimund | Erdmann, Jeanette | Eriksson, Johan G | Farrall, Martin | Ferrannini, Ele | Ferrières, Jean | Ford, Ian | Forouhi, Nita G | Forrester, Terrence | Gansevoort, Ron T | Gejman, Pablo V | Gieger, Christian | Golay, Alain | Gottesman, Omri | Gudnason, Vilmundur | Gyllensten, Ulf | Haas, David W | Hall, Alistair S | Harris, Tamara B | Hattersley, Andrew T | Heath, Andrew C | Hengstenberg, Christian | Hicks, Andrew A | Hindorff, Lucia A | Hingorani, Aroon D | Hofman, Albert | Hovingh, G Kees | Humphries, Steve E | Hunt, Steven C | Hypponen, Elina | Jacobs, Kevin B | Jarvelin, Marjo-Riitta | Jousilahti, Pekka | Jula, Antti M | Kaprio, Jaakko | Kastelein, John JP | Kayser, Manfred | Kee, Frank | Keinanen-Kiukaanniemi, Sirkka M | Kiemeney, Lambertus A | Kooner, Jaspal S | Kooperberg, Charles | Koskinen, Seppo | Kovacs, Peter | Kraja, Aldi T | Kumari, Meena | Kuusisto, Johanna | Lakka, Timo A | Langenberg, Claudia | Le Marchand, Loic | Lehtimäki, Terho | Lupoli, Sara | Madden, Pamela AF | Männistö, Satu | Manunta, Paolo | Marette, André | Matise, Tara C | McKnight, Barbara | Meitinger, Thomas | Moll, Frans L | Montgomery, Grant W | Morris, Andrew D | Morris, Andrew P | Murray, Jeffrey C | Nelis, Mari | Ohlsson, Claes | Oldehinkel, Albertine J | Ong, Ken K | Ouwehand, Willem H | Pasterkamp, Gerard | Peters, Annette | Pramstaller, Peter P | Price, Jackie F | Qi, Lu | Raitakari, Olli T | Rankinen, Tuomo | Rao, DC | Rice, Treva K | Ritchie, Marylyn | Rudan, Igor | Salomaa, Veikko | Samani, Nilesh J | Saramies, Jouko | Sarzynski, Mark A | Schwarz, Peter EH | Sebert, Sylvain | Sever, Peter | Shuldiner, Alan R | Sinisalo, Juha | Steinthorsdottir, Valgerdur | Stolk, Ronald P | Tardif, Jean-Claude | Tönjes, Anke | Tremblay, Angelo | Tremoli, Elena | Virtamo, Jarmo | Vohl, Marie-Claude | Amouyel, Philippe | Asselbergs, Folkert W | Assimes, Themistocles L | Bochud, Murielle | Boehm, Bernhard O | Boerwinkle, Eric | Bottinger, Erwin P | Bouchard, Claude | Cauchi, Stéphane | Chambers, John C | Chanock, Stephen J | Cooper, Richard S | de Bakker, Paul IW | Dedoussis, George | Ferrucci, Luigi | Franks, Paul W | Froguel, Philippe | Groop, Leif C | Haiman, Christopher A | Hamsten, Anders | Hayes, M Geoffrey | Hui, Jennie | Hunter, David J. | Hveem, Kristian | Jukema, J Wouter | Kaplan, Robert C | Kivimaki, Mika | Kuh, Diana | Laakso, Markku | Liu, Yongmei | Martin, Nicholas G | März, Winfried | Melbye, Mads | Moebus, Susanne | Munroe, Patricia B | Njølstad, Inger | Oostra, Ben A | Palmer, Colin NA | Pedersen, Nancy L | Perola, Markus | Pérusse, Louis | Peters, Ulrike | Powell, Joseph E | Power, Chris | Quertermous, Thomas | Rauramaa, Rainer | Reinmaa, Eva | Ridker, Paul M | Rivadeneira, Fernando | Rotter, Jerome I | Saaristo, Timo E | Saleheen, Danish | Schlessinger, David | Slagboom, P Eline | Snieder, Harold | Spector, Tim D | Strauch, Konstantin | Stumvoll, Michael | Tuomilehto, Jaakko | Uusitupa, Matti | van der Harst, Pim | Völzke, Henry | Walker, Mark | Wareham, Nicholas J | Watkins, Hugh | Wichmann, H-Erich | Wilson, James F | Zanen, Pieter | Deloukas, Panos | Heid, Iris M | Lindgren, Cecilia M | Mohlke, Karen L | Speliotes, Elizabeth K | Thorsteinsdottir, Unnur | Barroso, Inês | Fox, Caroline S | North, Kari E | Strachan, David P | Beckmann, Jacques S. | Berndt, Sonja I | Boehnke, Michael | Borecki, Ingrid B | McCarthy, Mark I | Metspalu, Andres | Stefansson, Kari | Uitterlinden, André G | van Duijn, Cornelia M | Franke, Lude | Willer, Cristen J | Price, Alkes L. | Lettre, Guillaume | Loos, Ruth JF | Weedon, Michael N | Ingelsson, Erik | O’Connell, Jeffrey R | Abecasis, Goncalo R | Chasman, Daniel I | Goddard, Michael E | Visscher, Peter M | Hirschhorn, Joel N | Frayling, Timothy M
Nature genetics  2014;46(11):1173-1186.
Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explain one-fifth of heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ~2,000, ~3,700 and ~9,500 SNPs explained ~21%, ~24% and ~29% of phenotypic variance. Furthermore, all common variants together captured the majority (60%) of heritability. The 697 variants clustered in 423 loci enriched for genes, pathways, and tissue-types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/beta-catenin, and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.
doi:10.1038/ng.3097
PMCID: PMC4250049  PMID: 25282103
5.  Multi-Ancestral Analysis of Inflammation-Related Genetic Variants and C-Reactive Protein in the Population Architecture using Genomics and Epidemiology (PAGE) Study 
Background
C-reactive protein (CRP) is a biomarker of inflammation. Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with CRP concentrations and inflammation-related traits such as cardiovascular disease, type 2 diabetes, and obesity. We aimed to replicate previous CRP-SNP associations, assess whether these associations generalize to additional race/ethnicity groups, and evaluate inflammation-related SNPs for a potentially pleiotropic association with CRP.
Methods and Results
We selected and analyzed 16 CRP-associated and 250 inflammation-related GWAS SNPs among 40,473 African American, American Indian, Asian/Pacific Islander, European American, and Hispanic participants from 7 studies collaborating in the Population Architecture using Genomics and Epidemiology (PAGE) study. Fixed-effect meta-analyses combined study-specific race/ethnicity-stratified linear regression estimates to evaluate the association between each SNP and high-sensitivity CRP. Overall, 18 SNPs in 8 loci were significantly associated with CRP (Bonferroni-corrected p<3.1×10−3 for replication, p<2.0×10−4 for pleiotropy): Seven of these were specific to European Americans, while 9 additionally generalized to African Americans (1), Hispanics (5), or both (3); 1 SNP was seen only in African Americans and Hispanics. Two SNPs in the CELSR2/PSRC1/SORT1 locus showed a potentially novel association with CRP: rs599839 (p=2.0×10−6) and rs646776 (p=3.1×10−5).
Conclusions
We replicated 16 SNP-CRP associations, 10 of which generalized to African Americans and/or Hispanics. We also identified potentially novel pleiotropic associations with CRP for two SNPs previously associated with coronary artery disease and LDL cholesterol. These findings demonstrate the benefit of evaluating genotype-phenotype associations in multiple race/ethnicity groups, and of looking for pleiotropic relationships among SNPs previously associated with related phenotypes.
doi:10.1161/CIRCGENETICS.113.000173
PMCID: PMC4104750  PMID: 24622110
genetic epidemiology; inflammation; C-reactive protein; race and ethnicity; single nucleotide polymorphism; pleiotropy
6.  Genetic Determinants of Age-Related Macular Degeneration in Diverse Populations From the PAGE Study 
Purpose.
Substantial progress has been made in identifying susceptibility variants for AMD in European populations; however, few studies have been conducted to understand the role these variants play in AMD risk in diverse populations. The present study aims to examine AMD risk across diverse populations in known and suspected AMD complement factor and lipid-related loci.
Methods.
Targeted genotyping was performed across study sites for AMD and lipid trait-associated single nucleotide polymorphism (SNPs). Genetic association tests were performed at individual sites and then meta-analyzed using logistic regression assuming an additive genetic model stratified by self-described race/ethnicity. Participants included cases with early or late AMD and controls with no signs of AMD as determined by fundus photography. Populations included in this study were European Americans, African Americans, Mexican Americans, and Singaporeans from the Population Architecture using Genomics and Epidemiology (PAGE) study.
Results.
Index variants of AMD, rs1061170 (CFH) and rs10490924 (ARMS2), were associated with AMD at P = 3.05 × 10−8 and P = 6.36 × 10−6, respectively, in European Americans. In general, none of the major AMD index variants generalized to our non-European populations with the exception of rs10490924 in Mexican Americans at an uncorrected P value < 0.05. Four lipid-associated SNPS (LPL rs328, TRIB1 rs6987702, CETP rs1800775, and KCTD10/MVK rs2338104) were associated with AMD in African Americans and Mexican Americans (P < 0.05), but these associations did not survive strict corrections for multiple testing.
Conclusions.
While most associations did not generalize in the non-European populations, variants within lipid-related genes were found to be associated with AMD. This study highlights the need for larger well-powered studies in non-European populations.
The Population Architecture using Genomics and Epidemiology (PAGE) I Study characterized known age-related macular degeneration risk variants previously identified in European populations in ethnically/racially diverse populations. Major AMD variants did not generalize in diverse populations.
doi:10.1167/iovs.14-14246
PMCID: PMC4214207  PMID: 25205864
age-related macular degeneration; CFH Y402H; ARMS2 A69S; PAGE Study; genetic epidemiology
7.  Genetic studies of body mass index yield new insights for obesity biology 
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W. | Dedoussis, George | Ferrucci, Luigi | Franks, Paul W. | Froguel, Philippe | Groop, Leif C. | Haiman, Christopher A. | Hamsten, Anders | Hui, Jennie | Hunter, David J. | Hveem, Kristian | Kaplan, Robert C. | Kivimaki, Mika | Kuh, Diana | Laakso, Markku | Liu, Yongmei | Martin, Nicholas G. | März, Winfried | Melbye, Mads | Metspalu, Andres | Moebus, Susanne | Munroe, Patricia B. | Njølstad, Inger | Oostra, Ben A. | Palmer, Colin N. A. | Pedersen, Nancy L. | Perola, Markus | Pérusse, Louis | Peters, Ulrike | Power, Chris | Quertermous, Thomas | Rauramaa, Rainer | Rivadeneira, Fernando | Saaristo, Timo E. | Saleheen, Danish | Sattar, Naveed | Schadt, Eric E. | Schlessinger, David | Slagboom, P. Eline | Snieder, Harold | Spector, Tim D. | Thorsteinsdottir, Unnur | Stumvoll, Michael | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Walker, Mark | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Weir, David R. | Wichmann, H-Erich | Wilson, James F. | Zanen, Pieter | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Heid, Iris M. | O’Connell, Jeffrey R. | Strachan, David P. | Stefansson, Kari | van Duijn, Cornelia M. | Abecasis, Gonçalo R. | Franke, Lude | Frayling, Timothy M. | McCarthy, Mark I. | Visscher, Peter M. | Scherag, André | Willer, Cristen J. | Boehnke, Michael | Mohlke, Karen L. | Lindgren, Cecilia M. | Beckmann, Jacques S. | Barroso, Inês | North, Kari E. | Ingelsson, Erik | Hirschhorn, Joel N. | Loos, Ruth J. F. | Speliotes, Elizabeth K.
Nature  2015;518(7538):197-206.
Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 × 10−8), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for ~2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.
doi:10.1038/nature14177
PMCID: PMC4382211  PMID: 25673413
8.  Evidence of Heterogeneity by Race/Ethnicity in Genetic Determinants of QT Interval 
Epidemiology (Cambridge, Mass.)  2014;25(6):790-798.
Background
QT-interval (QT) prolongation is an established risk factor for ventricular tachyarrhythmia and sudden cardiac death. Previous genome-wide association studies in populations of the European descent have identified multiple genetic loci that influence QT, but few have examined these loci in ethnically diverse populations.
Methods
Here, we examine the direction, magnitude, and precision of effect sizes for 21 previously reported SNPs from 12 QT loci, in populations of European (n=16,398), African (n=5,437), American Indian (n=5,032), Hispanic (n=1,143), and Asian (n=932) descent as part of the Population Architecture using Genomics and Epidemiology (PAGE) study. Estimates obtained from linear regression models stratified by race/ethnicity were combined using inverse-variance weighted meta-analysis. Heterogeneity was evaluated using Cochran's Q test.
Results
Of 21 SNPs, seven showed consistent direction of effect across all five populations, and an additional nine had estimated effects that were consistent across four populations. Despite consistent direction of effect, nine of 16 SNPs had evidence (P < 0.05) of heterogeneity by race/ethnicity. For these 9 SNPs, linkage disequilibrium plots often indicated substantial variation in linkage disequilibrium patterns among the various racial/ethnic groups, as well as possible allelic heterogeneity.
Conclusions
These results emphasize the importance of analyzing racial/ethnic groups separately in genetic studies. Furthermore, they underscore the possible utility of trans-ethnic studies to pinpoint underlying casual variants influencing heritable traits such as QT.
doi:10.1097/EDE.0000000000000168
PMCID: PMC4380285  PMID: 25166880
9.  Pleiotropic and Sex-Specific Effects of Cancer GWAS SNPs on Melanoma Risk in the Population Architecture Using Genomics and Epidemiology (PAGE) Study 
PLoS ONE  2015;10(3):e0120491.
Background
Several regions of the genome show pleiotropic associations with multiple cancers. We sought to evaluate whether 181 single-nucleotide polymorphisms previously associated with various cancers in genome-wide association studies were also associated with melanoma risk.
Methods
We evaluated 2,131 melanoma cases and 20,353 controls from three studies in the Population Architecture using Genomics and Epidemiology (PAGE) study (EAGLE-BioVU, MEC, WHI) and two collaborating studies (HPFS, NHS). Overall and sex-stratified analyses were performed across studies.
Results
We observed statistically significant associations with melanoma for two lung cancer SNPs in the TERT-CLPTM1L locus (Bonferroni-corrected p<2.8x10-4), replicating known pleiotropic effects at this locus. In sex-stratified analyses, we also observed a potential male-specific association between prostate cancer risk variant rs12418451 and melanoma risk (OR=1.22, p=8.0x10-4). No other variants in our study were associated with melanoma after multiple comparisons adjustment (p>2.8e-4).
Conclusions
We provide confirmatory evidence of pleiotropic associations with melanoma for two SNPs previously associated with lung cancer, and provide suggestive evidence for a male-specific association with melanoma for prostate cancer variant rs12418451. This SNP is located near TPCN2, an ion transport gene containing SNPs which have been previously associated with hair pigmentation but not melanoma risk. Previous evidence provides biological plausibility for this association, and suggests a complex interplay between ion transport, pigmentation, and melanoma risk that may vary by sex. If confirmed, these pleiotropic relationships may help elucidate shared molecular pathways between cancers and related phenotypes.
doi:10.1371/journal.pone.0120491
PMCID: PMC4366224  PMID: 25789475
10.  Phenotype–Genotype Integrator (PheGenI): synthesizing genome-wide association study (GWAS) data with existing genomic resources 
Rapidly accumulating data from genome-wide association studies (GWASs) and other large-scale studies are most useful when synthesized with existing databases. To address this opportunity, we developed the Phenotype–Genotype Integrator (PheGenI), a user-friendly web interface that integrates various National Center for Biotechnology Information (NCBI) genomic databases with association data from the National Human Genome Research Institute GWAS Catalog and supports downloads of search results. Here, we describe the rationale for and development of this resource. Integrating over 66 000 association records with extensive single nucleotide polymorphism (SNP), gene, and expression quantitative trait loci data already available from the NCBI, PheGenI enables deeper investigation and interrogation of SNPs associated with a wide range of traits, facilitating the examination of the relationships between genetic variation and human diseases.
doi:10.1038/ejhg.2013.96
PMCID: PMC3865418  PMID: 23695286
database; data integration; genome sequence; genome-wide association study; phenotype; single nucleotide polymorphism
12.  Prospective Associations of Coronary Heart Disease Loci in African Americans Using the MetaboChip: The PAGE Study 
PLoS ONE  2014;9(12):e113203.
Background
Coronary heart disease (CHD) is a leading cause of morbidity and mortality in African Americans. However, there is a paucity of studies assessing genetic determinants of CHD in African Americans. We examined the association of published variants in CHD loci with incident CHD, attempted to fine map these loci, and characterize novel variants influencing CHD risk in African Americans.
Methods and Results
Up to 8,201 African Americans (including 546 first CHD events) were genotyped using the MetaboChip array in the Atherosclerosis Risk in Communities (ARIC) study and Women's Health Initiative (WHI). We tested associations using Cox proportional hazard models in sex- and study-stratified analyses and combined results using meta-analysis. Among 44 validated CHD loci available in the array, we replicated and fine-mapped the SORT1 locus, and showed same direction of effects as reported in studies of individuals of European ancestry for SNPs in 22 additional published loci. We also identified a SNP achieving array wide significance (MYC: rs2070583, allele frequency 0.02, P = 8.1×10−8), but the association did not replicate in an additional 8,059 African Americans (577 events) from the WHI, HealthABC and GeneSTAR studies, and in a meta-analysis of 5 cohort studies of European ancestry (24,024 individuals including 1,570 cases of MI and 2,406 cases of CHD) from the CHARGE Consortium.
Conclusions
Our findings suggest that some CHD loci previously identified in individuals of European ancestry may be relevant to incident CHD in African Americans.
doi:10.1371/journal.pone.0113203
PMCID: PMC4277270  PMID: 25542012
13.  No evidence of interaction between known lipid-associated genetic variants and smoking in the multi-ethnic PAGE population 
Human genetics  2013;132(12):1427-1431.
Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype–phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.
doi:10.1007/s00439-013-1375-3
PMCID: PMC3895337  PMID: 24100633
14.  Imputation of coding variants in African Americans: better performance using data from the exome sequencing project 
Bioinformatics  2013;29(21):2744-2749.
Summary: Although the 1000 Genomes haplotypes are the most commonly used reference panel for imputation, medical sequencing projects are generating large alternate sets of sequenced samples. Imputation in African Americans using 3384 haplotypes from the Exome Sequencing Project, compared with 2184 haplotypes from 1000 Genomes Project, increased effective sample size by 8.3–11.4% for coding variants with minor allele frequency <1%. No loss of imputation quality was observed using a panel built from phenotypic extremes. We recommend using haplotypes from Exome Sequencing Project alone or concatenation of the two panels over quality score-based post-imputation selection or IMPUTE2’s two-panel combination.
Contact: yunli@med.unc.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
doi:10.1093/bioinformatics/btt477
PMCID: PMC3799474  PMID: 23956302
15.  Association of the FTO Obesity Risk Variant rs8050136 With Percentage of Energy Intake From Fat in Multiple Racial/Ethnic Populations 
American Journal of Epidemiology  2013;178(5):780-790.
Common obesity risk variants have been associated with macronutrient intake; however, these associations' generalizability across populations has not been demonstrated. We investigated the associations between 6 obesity risk variants in (or near) the NEGR1, TMEM18, BDNF, FTO, MC4R, and KCTD15 genes and macronutrient intake (carbohydrate, protein, ethanol, and fat) in 3 Population Architecture using Genomics and Epidemiology (PAGE) studies: the Multiethnic Cohort Study (1993–2006) (n = 19,529), the Atherosclerosis Risk in Communities Study (1987–1989) (n = 11,114), and the Epidemiologic Architecture for Genes Linked to Environment (EAGLE) Study, which accesses data from the Third National Health and Nutrition Examination Survey (1991–1994) (n = 6,347). We used linear regression, with adjustment for age, sex, and ethnicity, to estimate the associations between obesity risk genotypes and macronutrient intake. A fixed-effects meta-analysis model showed that the FTO rs8050136 A allele (n = 36,973) was positively associated with percentage of calories derived from fat (βmeta = 0.2244 (standard error, 0.0548); P = 4 × 10−5) and inversely associated with percentage of calories derived from carbohydrate (βmeta = −0.2796 (standard error, 0.0709); P = 8 × 10−5). In the Multiethnic Cohort Study, percentage of calories from fat assessed at baseline was a partial mediator of the rs8050136 effect on body mass index (weight (kg)/height (m)2) obtained at 10 years of follow-up (mediation of effect = 0.0823 kg/m2, 95% confidence interval: 0.0559, 0.1128). Our data provide additional evidence that the association of FTO with obesity is partially mediated by dietary intake.
doi:10.1093/aje/kwt028
PMCID: PMC3755639  PMID: 23820787
energy intake; fat mass and obesity-associated (FTO) gene; obesity; percent calories from fat; race/ethnicity
16.  Post genome-wide association study challenges for lipid traits: describing age as a modifier of gene-lipid associations in the Population Architecture using Genomics and Epidemiology (PAGE) study 
Annals of human genetics  2013;77(5):416-425.
Summary
Numerous common genetic variants that influence plasma high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglyceride (TG) distributions have been identified via genome-wide association studies (GWAS). However, whether or not these associations are age dependent has largely been overlooked. We conducted an association study and meta-analysis in more than 22,000 European Americans between 49 previously identified GWAS variants and the three lipid traits, stratified by age (males: <50 or ≥50 years of age; females: pre- or post-menopausal). For each variant, a test of heterogeneity was performed between the two age strata and significant Phet values were used as evidence of age-specific genetic effects. We identified seven associations in females and eight in males that displayed suggestive heterogeneity by age (Phet<0.05). The association between rs174547 (FADS1) and LDL-C in males displayed the most evidence for heterogeneity between age groups (Phet=1.74E-03, I2=89.8), with a significant association in older males (P=1.39E-06) but not younger males (P=0.99). However, none of the suggestive modifying effects survived adjustment for multiple testing, highlighting the challenges of identifying modifiers of modest SNP-trait associations despite large sample sizes.
doi:10.1111/ahg.12027
PMCID: PMC3796061  PMID: 23808484
PAGE; modifier; age; lipids; genetic association
17.  Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index 
Frontiers in Genetics  2014;5:250.
Phenome-wide association studies (PheWAS) have demonstrated utility in validating genetic associations derived from traditional genetic studies as well as identifying novel genetic associations. Here we used an electronic health record (EHR)-based PheWAS to explore pleiotropy of genetic variants in the fat mass and obesity associated gene (FTO), some of which have been previously associated with obesity and type 2 diabetes (T2D). We used a population of 10,487 individuals of European ancestry with genome-wide genotyping from the Electronic Medical Records and Genomics (eMERGE) Network and another population of 13,711 individuals of European ancestry from the BioVU DNA biobank at Vanderbilt genotyped using Illumina HumanExome BeadChip. A meta-analysis of the two study populations replicated the well-described associations between FTO variants and obesity (odds ratio [OR] = 1.25, 95% Confidence Interval = 1.11–1.24, p = 2.10 × 10−9) and FTO variants and T2D (OR = 1.14, 95% CI = 1.08–1.21, p = 2.34 × 10−6). The meta-analysis also demonstrated that FTO variant rs8050136 was significantly associated with sleep apnea (OR = 1.14, 95% CI = 1.07–1.22, p = 3.33 × 10−5); however, the association was attenuated after adjustment for body mass index (BMI). Novel phenotype associations with obesity-associated FTO variants included fibrocystic breast disease (rs9941349, OR = 0.81, 95% CI = 0.74–0.91, p = 5.41 × 10−5) and trends toward associations with non-alcoholic liver disease and gram-positive bacterial infections. FTO variants not associated with obesity demonstrated other potential disease associations including non-inflammatory disorders of the cervix and chronic periodontitis. These results suggest that genetic variants in FTO may have pleiotropic associations, some of which are not mediated by obesity.
doi:10.3389/fgene.2014.00250
PMCID: PMC4134007  PMID: 25177340
PheWAS; genetic association; pleiotropy; Exome chip; FTO; BMI
18.  The Influence of Obesity-Related Single Nucleotide Polymorphisms on BMI Across the Life Course 
Diabetes  2013;62(5):1763-1767.
Evidence is limited as to whether heritable risk of obesity varies throughout adulthood. Among >34,000 European Americans, aged 18–100 years, from multiple U.S. studies in the Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we examined evidence for heterogeneity in the associations of five established obesity risk variants (near FTO, GNPDA2, MTCH2, TMEM18, and NEGR1) with BMI across four distinct epochs of adulthood: 1) young adulthood (ages 18–25 years), adulthood (ages 26–49 years), middle-age adulthood (ages 50–69 years), and older adulthood (ages ≥70 years); or 2) by menopausal status in women and stratification by age 50 years in men. Summary-effect estimates from each meta-analysis were compared for heterogeneity across the life epochs. We found heterogeneity in the association of the FTO (rs8050136) variant with BMI across the four adulthood epochs (P = 0.0006), with larger effects in young adults relative to older adults (β [SE] = 1.17 [0.45] vs. 0.09 [0.09] kg/m2, respectively, per A allele) and smaller intermediate effects. We found no evidence for heterogeneity in the association of GNPDA2, MTCH2, TMEM18, and NEGR1 with BMI across adulthood. Genetic predisposition to obesity may have greater effects on body weight in young compared with older adulthood for FTO, suggesting changes by age, generation, or secular trends. Future research should compare and contrast our findings with results using longitudinal data.
doi:10.2337/db12-0863
PMCID: PMC3636619  PMID: 23300277
19.  WikiGWA: an open platform for collecting and using genome-wide association results 
The number of discovered genetic variants from genome-wide association (GWA) studies (GWAS) has been growing rapidly. Centralized efforts such as the National Human Genome Research Institute's GWAS catalog provide regular updates and a convenient interface for quick lookup. However, the catalog entries are manually curated and rely on data from published articles. Other tools such as SNPedia (http://www.snpedia.com) collect published results regarding functional consequences of genetic variations. Here, we propose an approach that allows individual investigators to share their GWA results through an open platform. Unlike GWAS catalog or SNPedia, wikiGWA collects first-hand GWAS results and in a much larger scale. Investigators are not only able to post a much larger amount of results, but also post results from unpublished studies, which could alleviate publication bias and facilitate identification of weak signals. Our interface allows for flexible and fast queries, and the query results are formatted to work seamlessly with the LocusZoom program for visualization and annotation. We here describe wikiGWA, made publically available at http://www.wikiGWA.org.
doi:10.1038/ejhg.2012.187
PMCID: PMC3598322  PMID: 22929026
genome-wide association; open platform; bioinformatics
20.  Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data 
Nature biotechnology  2013;31(12):1102-1110.
Candidate gene and genome-wide association studies (GWAS) have identified genetic variants that modulate risk for human disease; many of these associations require further study to replicate the results. Here we report the first large-scale application of the phenome-wide association study (PheWAS) paradigm within electronic medical records (EMRs), an unbiased approach to replication and discovery that interrogates relationships between targeted genotypes and multiple phenotypes. We scanned for associations between 3,144 single-nucleotide polymorphisms (previously implicated by GWAS as mediators of human traits) and 1,358 EMR-derived phenotypes in 13,835 individuals of European ancestry. This PheWAS replicated 66% (51/77) of sufficiently powered prior GWAS associations and revealed 63 potentially pleiotropic associations with P < 4.6 × 10−6 (false discovery rate < 0.1); the strongest of these novel associations were replicated in an independent cohort (n = 7,406). These findings validate PheWAS as a tool to allow unbiased interrogation across multiple phenotypes in EMR-based cohorts and to enhance analysis of the genomic basis of human disease.
doi:10.1038/nbt.2749
PMCID: PMC3969265  PMID: 24270849
21.  Pleiotropic Associations of Risk Variants Identified for Other Cancers With Lung Cancer Risk: The PAGE and TRICL Consortia 
Background
Genome-wide association studies have identified hundreds of genetic variants associated with specific cancers. A few of these risk regions have been associated with more than one cancer site; however, a systematic evaluation of the associations between risk variants for other cancers and lung cancer risk has yet to be performed.
Methods
We included 18023 patients with lung cancer and 60543 control subjects from two consortia, Population Architecture using Genomics and Epidemiology (PAGE) and Transdisciplinary Research in Cancer of the Lung (TRICL). We examined 165 single-nucleotide polymorphisms (SNPs) that were previously associated with at least one of 16 non–lung cancer sites. Study-specific logistic regression results underwent meta-analysis, and associations were also examined by race/ethnicity, histological cell type, sex, and smoking status. A Bonferroni-corrected P value of 2.5×10–5 was used to assign statistical significance.
Results
The breast cancer SNP LSP1 rs3817198 was associated with an increased risk of lung cancer (odds ratio [OR] = 1.10; 95% confidence interval [CI] = 1.05 to 1.14; P = 2.8×10–6). This association was strongest for women with adenocarcinoma (P = 1.2×10–4) and not statistically significant in men (P = .14) with this cell type (P het by sex = .10). Two glioma risk variants, TERT rs2853676 and CDKN2BAS1 rs4977756, which are located in regions previously associated with lung cancer, were associated with increased risk of adenocarcinoma (OR = 1.16; 95% CI = 1.10 to 1.22; P = 1.1×10–8) and squamous cell carcinoma (OR = 1.13; CI = 1.07 to 1.19; P = 2.5×10–5), respectively.
Conclusions
Our findings demonstrate a novel pleiotropic association between the breast cancer LSP1 risk region marked by variant rs3817198 and lung cancer risk.
doi:10.1093/jnci/dju061
PMCID: PMC3982896  PMID: 24681604
22.  A survey of informatics approaches to whole-exome and whole-genome clinical reporting in the electronic health record 
Purpose
Genome-scale clinical sequencing is being adopted more broadly in medical practice. The National Institutes of Health developed the Clinical Sequencing Exploratory Research (CSER) program to guide implementation and dissemination of best practices for the integration of sequencing into clinical care. This study describes and compares the state of the art of incorporating whole-exome and whole-genome sequencing results into the electronic health record, including approaches to decision support across the six current CSER sites.
Methods
The CSER Medical Record Working Group collaboratively developed and completed an in-depth survey to assess the communication of genome-scale data into the electronic health record. We summarized commonalities and divergent approaches.
Results
Despite common sequencing platform (Illumina) adoptions, there is a great diversity of approaches to annotation tools and workflow, as well as to report generation. At all sites, reports are human-readable structured documents available as passive decision support in the electronic health record. Active decision support is in early implementation at two sites.
Conclusion
The parallel efforts across CSER sites in the creation of systems for report generation and integration of reports into the electronic health record, as well as the lack of standardized approaches to interfacing with variant databases to create active clinical decision support, create opportunities for cross-site and vendor collaborations.
doi:10.1038/gim.2013.120
PMCID: PMC3951437  PMID: 24071794
clinical decision support; clinical sequencing; decision support rules; electronic health record; electronic medical record; next-generation sequencing
23.  Pleiotropy of Cancer Susceptibility Variants on the Risk of Non-Hodgkin Lymphoma: The PAGE Consortium 
PLoS ONE  2014;9(3):e89791.
Background
Risk of non-Hodgkin lymphoma (NHL) is higher among individuals with a family history or a prior diagnosis of other cancers. Genome-wide association studies (GWAS) have suggested that some genetic susceptibility variants are associated with multiple complex traits (pleiotropy).
Objective
We investigated whether common risk variants identified in cancer GWAS may also increase the risk of developing NHL as the first primary cancer.
Methods
As part of the Population Architecture using Genomics and Epidemiology (PAGE) consortium, 113 cancer risk variants were analyzed in 1,441 NHL cases and 24,183 controls from three studies (BioVU, Multiethnic Cohort Study, Women's Health Initiative) for their association with the risk of overall NHL and common subtypes [diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), chronic lymphocytic leukemia or small lymphocytic lymphoma (CLL/SLL)] using an additive genetic model adjusted for age, sex and ethnicity. Study-specific results for each variant were meta-analyzed across studies.
Results
The analysis of NHL subtype-specific GWAS SNPs and overall NHL suggested a shared genetic susceptibility between FL and DLBCL, particularly involving variants in the major histocompatibility complex region (rs6457327 in 6p21.33: FL OR = 1.29, p = 0.013; DLBCL OR = 1.23, p = 0.013; NHL OR = 1.22, p = 5.9×E-05). In the pleiotropy analysis, six risk variants for other cancers were associated with NHL risk, including variants for lung (rs401681 in TERT: OR per C allele = 0.89, p = 3.7×E-03; rs4975616 in TERT: OR per A allele = 0.90, p = 0.01; rs3131379 in MSH5: OR per T allele = 1.16, p = 0.03), prostate (rs7679673 in TET2: OR per C allele = 0.89, p = 5.7×E-03; rs10993994 in MSMB: OR per T allele = 1.09, p = 0.04), and breast (rs3817198 in LSP1: OR per C allele = 1.12, p = 0.01) cancers, but none of these associations remained significant after multiple test correction.
Conclusion
This study does not support strong pleiotropic effects of non-NHL cancer risk variants in NHL etiology; however, larger studies are warranted.
doi:10.1371/journal.pone.0089791
PMCID: PMC3943855  PMID: 24598796
24.  The NHGRI GWAS Catalog, a curated resource of SNP-trait associations 
Nucleic Acids Research  2013;42(Database issue):D1001-D1006.
The National Human Genome Research Institute (NHGRI) Catalog of Published Genome-Wide Association Studies (GWAS) Catalog provides a publicly available manually curated collection of published GWAS assaying at least 100 000 single-nucleotide polymorphisms (SNPs) and all SNP-trait associations with P <1 × 10−5. The Catalog includes 1751 curated publications of 11 912 SNPs. In addition to the SNP-trait association data, the Catalog also publishes a quarterly diagram of all SNP-trait associations mapped to the SNPs’ chromosomal locations. The Catalog can be accessed via a tabular web interface, via a dynamic visualization on the human karyotype, as a downloadable tab-delimited file and as an OWL knowledge base. This article presents a number of recent improvements to the Catalog, including novel ways for users to interact with the Catalog and changes to the curation infrastructure.
doi:10.1093/nar/gkt1229
PMCID: PMC3965119  PMID: 24316577
25.  Genetic variants associated with fasting glucose and insulin concentrations in an ethnically diverse population: results from the Population Architecture using Genomics and Epidemiology (PAGE) study 
BMC Medical Genetics  2013;14:98.
Background
Multiple genome-wide association studies (GWAS) within European populations have implicated common genetic variants associated with insulin and glucose concentrations. In contrast, few studies have been conducted within minority groups, which carry the highest burden of impaired glucose homeostasis and type 2 diabetes in the U.S.
Methods
As part of the 'Population Architecture using Genomics and Epidemiology (PAGE) Consortium, we investigated the association of up to 10 GWAS-identified single nucleotide polymorphisms (SNPs) in 8 genetic regions with glucose or insulin concentrations in up to 36,579 non-diabetic subjects including 23,323 European Americans (EA) and 7,526 African Americans (AA), 3,140 Hispanics, 1,779 American Indians (AI), and 811 Asians. We estimated the association between each SNP and fasting glucose or log-transformed fasting insulin, followed by meta-analysis to combine results across PAGE sites.
Results
Overall, our results show that 9/9 GWAS SNPs are associated with glucose in EA (p = 0.04 to 9 × 10-15), versus 3/9 in AA (p= 0.03 to 6 × 10-5), 3/4 SNPs in Hispanics, 2/4 SNPs in AI, and 1/2 SNPs in Asians. For insulin we observed a significant association with rs780094/GCKR in EA, Hispanics and AI only.
Conclusions
Generalization of results across multiple racial/ethnic groups helps confirm the relevance of some of these loci for glucose and insulin metabolism. Lack of association in non-EA groups may be due to insufficient power, or to unique patterns of linkage disequilibrium.
doi:10.1186/1471-2350-14-98
PMCID: PMC3849560  PMID: 24063630

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