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1.  Genetic association study of QT interval highlights role for calcium signaling pathways in myocardial repolarization 
Arking, Dan E. | Pulit, Sara L. | Crotti, Lia | van der Harst, Pim | Munroe, Patricia B. | Koopmann, Tamara T. | Sotoodehnia, Nona | Rossin, Elizabeth J. | Morley, Michael | Wang, Xinchen | Johnson, Andrew D. | Lundby, Alicia | Gudbjartsson, Daníel F. | Noseworthy, Peter A. | Eijgelsheim, Mark | Bradford, Yuki | Tarasov, Kirill V. | Dörr, Marcus | Müller-Nurasyid, Martina | Lahtinen, Annukka M. | Nolte, Ilja M. | Smith, Albert Vernon | Bis, Joshua C. | Isaacs, Aaron | Newhouse, Stephen J. | Evans, Daniel S. | Post, Wendy S. | Waggott, Daryl | Lyytikäinen, Leo-Pekka | Hicks, Andrew A. | Eisele, Lewin | Ellinghaus, David | Hayward, Caroline | Navarro, Pau | Ulivi, Sheila | Tanaka, Toshiko | Tester, David J. | Chatel, Stéphanie | Gustafsson, Stefan | Kumari, Meena | Morris, Richard W. | Naluai, Åsa T. | Padmanabhan, Sandosh | Kluttig, Alexander | Strohmer, Bernhard | Panayiotou, Andrie G. | Torres, Maria | Knoflach, Michael | Hubacek, Jaroslav A. | Slowikowski, Kamil | Raychaudhuri, Soumya | Kumar, Runjun D. | Harris, Tamara B. | Launer, Lenore J. | Shuldiner, Alan R. | Alonso, Alvaro | Bader, Joel S. | Ehret, Georg | Huang, Hailiang | Kao, W.H. Linda | Strait, James B. | Macfarlane, Peter W. | Brown, Morris | Caulfield, Mark J. | Samani, Nilesh J. | Kronenberg, Florian | Willeit, Johann | Smith, J. Gustav | Greiser, Karin H. | zu Schwabedissen, Henriette Meyer | Werdan, Karl | Carella, Massimo | Zelante, Leopoldo | Heckbert, Susan R. | Psaty, Bruce M. | Rotter, Jerome I. | Kolcic, Ivana | Polašek, Ozren | Wright, Alan F. | Griffin, Maura | Daly, Mark J. | Arnar, David O. | Hólm, Hilma | Thorsteinsdottir, Unnur | Denny, Joshua C. | Roden, Dan M. | Zuvich, Rebecca L. | Emilsson, Valur | Plump, Andrew S. | Larson, Martin G. | O'Donnell, Christopher J. | Yin, Xiaoyan | Bobbo, Marco | D'Adamo, Adamo P. | Iorio, Annamaria | Sinagra, Gianfranco | Carracedo, Angel | Cummings, Steven R. | Nalls, Michael A. | Jula, Antti | Kontula, Kimmo K. | Marjamaa, Annukka | Oikarinen, Lasse | Perola, Markus | Porthan, Kimmo | Erbel, Raimund | Hoffmann, Per | Jöckel, Karl-Heinz | Kälsch, Hagen | Nöthen, Markus M. | consortium, HRGEN | den Hoed, Marcel | Loos, Ruth J.F. | Thelle, Dag S. | Gieger, Christian | Meitinger, Thomas | Perz, Siegfried | Peters, Annette | Prucha, Hanna | Sinner, Moritz F. | Waldenberger, Melanie | de Boer, Rudolf A. | Franke, Lude | van der Vleuten, Pieter A. | Beckmann, Britt Maria | Martens, Eimo | Bardai, Abdennasser | Hofman, Nynke | Wilde, Arthur A.M. | Behr, Elijah R. | Dalageorgou, Chrysoula | Giudicessi, John R. | Medeiros-Domingo, Argelia | Barc, Julien | Kyndt, Florence | Probst, Vincent | Ghidoni, Alice | Insolia, Roberto | Hamilton, Robert M. | Scherer, Stephen W. | Brandimarto, Jeffrey | Margulies, Kenneth | Moravec, Christine E. | Fabiola Del, Greco M. | Fuchsberger, Christian | O'Connell, Jeffrey R. | Lee, Wai K. | Watt, Graham C.M. | Campbell, Harry | Wild, Sarah H. | El Mokhtari, Nour E. | Frey, Norbert | Asselbergs, Folkert W. | Leach, Irene Mateo | Navis, Gerjan | van den Berg, Maarten P. | van Veldhuisen, Dirk J. | Kellis, Manolis | Krijthe, Bouwe P. | Franco, Oscar H. | Hofman, Albert | Kors, Jan A. | Uitterlinden, André G. | Witteman, Jacqueline C.M. | Kedenko, Lyudmyla | Lamina, Claudia | Oostra, Ben A. | Abecasis, Gonçalo R. | Lakatta, Edward G. | Mulas, Antonella | Orrú, Marco | Schlessinger, David | Uda, Manuela | Markus, Marcello R.P. | Völker, Uwe | Snieder, Harold | Spector, Timothy D. | Ärnlöv, Johan | Lind, Lars | Sundström, Johan | Syvänen, Ann-Christine | Kivimaki, Mika | Kähönen, Mika | Mononen, Nina | Raitakari, Olli T. | Viikari, Jorma S. | Adamkova, Vera | Kiechl, Stefan | Brion, Maria | Nicolaides, Andrew N. | Paulweber, Bernhard | Haerting, Johannes | Dominiczak, Anna F. | Nyberg, Fredrik | Whincup, Peter H. | Hingorani, Aroon | Schott, Jean-Jacques | Bezzina, Connie R. | Ingelsson, Erik | Ferrucci, Luigi | Gasparini, Paolo | Wilson, James F. | Rudan, Igor | Franke, Andre | Mühleisen, Thomas W. | Pramstaller, Peter P. | Lehtimäki, Terho J. | Paterson, Andrew D. | Parsa, Afshin | Liu, Yongmei | van Duijn, Cornelia | Siscovick, David S. | Gudnason, Vilmundur | Jamshidi, Yalda | Salomaa, Veikko | Felix, Stephan B. | Sanna, Serena | Ritchie, Marylyn D. | Stricker, Bruno H. | Stefansson, Kari | Boyer, Laurie A. | Cappola, Thomas P. | Olsen, Jesper V. | Lage, Kasper | Schwartz, Peter J. | Kääb, Stefan | Chakravarti, Aravinda | Ackerman, Michael J. | Pfeufer, Arne | de Bakker, Paul I.W. | Newton-Cheh, Christopher
Nature genetics  2014;46(8):826-836.
The QT interval, an electrocardiographic measure reflecting myocardial repolarization, is a heritable trait. QT prolongation is a risk factor for ventricular arrhythmias and sudden cardiac death (SCD) and could indicate the presence of the potentially lethal Mendelian Long QT Syndrome (LQTS). Using a genome-wide association and replication study in up to 100,000 individuals we identified 35 common variant QT interval loci, that collectively explain ∼8-10% of QT variation and highlight the importance of calcium regulation in myocardial repolarization. Rare variant analysis of 6 novel QT loci in 298 unrelated LQTS probands identified coding variants not found in controls but of uncertain causality and therefore requiring validation. Several newly identified loci encode for proteins that physically interact with other recognized repolarization proteins. Our integration of common variant association, expression and orthogonal protein-protein interaction screens provides new insights into cardiac electrophysiology and identifies novel candidate genes for ventricular arrhythmias, LQTS,and SCD.
doi:10.1038/ng.3014
PMCID: PMC4124521  PMID: 24952745
genome-wide association study; QT interval; Long QT Syndrome; sudden cardiac death; myocardial repolarization; arrhythmias
2.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segrè, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian'an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John RB | Platou, Carl GP | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden89-, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922
3.  Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes 
Morris, Andrew P | Voight, Benjamin F | Teslovich, Tanya M | Ferreira, Teresa | Segré, Ayellet V | Steinthorsdottir, Valgerdur | Strawbridge, Rona J | Khan, Hassan | Grallert, Harald | Mahajan, Anubha | Prokopenko, Inga | Kang, Hyun Min | Dina, Christian | Esko, Tonu | Fraser, Ross M | Kanoni, Stavroula | Kumar, Ashish | Lagou, Vasiliki | Langenberg, Claudia | Luan, Jian’an | Lindgren, Cecilia M | Müller-Nurasyid, Martina | Pechlivanis, Sonali | Rayner, N William | Scott, Laura J | Wiltshire, Steven | Yengo, Loic | Kinnunen, Leena | Rossin, Elizabeth J | Raychaudhuri, Soumya | Johnson, Andrew D | Dimas, Antigone S | Loos, Ruth J F | Vedantam, Sailaja | Chen, Han | Florez, Jose C | Fox, Caroline | Liu, Ching-Ti | Rybin, Denis | Couper, David J | Kao, Wen Hong L | Li, Man | Cornelis, Marilyn C | Kraft, Peter | Sun, Qi | van Dam, Rob M | Stringham, Heather M | Chines, Peter S | Fischer, Krista | Fontanillas, Pierre | Holmen, Oddgeir L | Hunt, Sarah E | Jackson, Anne U | Kong, Augustine | Lawrence, Robert | Meyer, Julia | Perry, John R B | Platou, Carl G P | Potter, Simon | Rehnberg, Emil | Robertson, Neil | Sivapalaratnam, Suthesh | Stančáková, Alena | Stirrups, Kathleen | Thorleifsson, Gudmar | Tikkanen, Emmi | Wood, Andrew R | Almgren, Peter | Atalay, Mustafa | Benediktsson, Rafn | Bonnycastle, Lori L | Burtt, Noël | Carey, Jason | Charpentier, Guillaume | Crenshaw, Andrew T | Doney, Alex S F | Dorkhan, Mozhgan | Edkins, Sarah | Emilsson, Valur | Eury, Elodie | Forsen, Tom | Gertow, Karl | Gigante, Bruna | Grant, George B | Groves, Christopher J | Guiducci, Candace | Herder, Christian | Hreidarsson, Astradur B | Hui, Jennie | James, Alan | Jonsson, Anna | Rathmann, Wolfgang | Klopp, Norman | Kravic, Jasmina | Krjutškov, Kaarel | Langford, Cordelia | Leander, Karin | Lindholm, Eero | Lobbens, Stéphane | Männistö, Satu | Mirza, Ghazala | Mühleisen, Thomas W | Musk, Bill | Parkin, Melissa | Rallidis, Loukianos | Saramies, Jouko | Sennblad, Bengt | Shah, Sonia | Sigurðsson, Gunnar | Silveira, Angela | Steinbach, Gerald | Thorand, Barbara | Trakalo, Joseph | Veglia, Fabrizio | Wennauer, Roman | Winckler, Wendy | Zabaneh, Delilah | Campbell, Harry | van Duijn, Cornelia | Uitterlinden, Andre G | Hofman, Albert | Sijbrands, Eric | Abecasis, Goncalo R | Owen, Katharine R | Zeggini, Eleftheria | Trip, Mieke D | Forouhi, Nita G | Syvänen, Ann-Christine | Eriksson, Johan G | Peltonen, Leena | Nöthen, Markus M | Balkau, Beverley | Palmer, Colin N A | Lyssenko, Valeriya | Tuomi, Tiinamaija | Isomaa, Bo | Hunter, David J | Qi, Lu | Shuldiner, Alan R | Roden, Michael | Barroso, Ines | Wilsgaard, Tom | Beilby, John | Hovingh, Kees | Price, Jackie F | Wilson, James F | Rauramaa, Rainer | Lakka, Timo A | Lind, Lars | Dedoussis, George | Njølstad, Inger | Pedersen, Nancy L | Khaw, Kay-Tee | Wareham, Nicholas J | Keinanen-Kiukaanniemi, Sirkka M | Saaristo, Timo E | Korpi-Hyövälti, Eeva | Saltevo, Juha | Laakso, Markku | Kuusisto, Johanna | Metspalu, Andres | Collins, Francis S | Mohlke, Karen L | Bergman, Richard N | Tuomilehto, Jaakko | Boehm, Bernhard O | Gieger, Christian | Hveem, Kristian | Cauchi, Stephane | Froguel, Philippe | Baldassarre, Damiano | Tremoli, Elena | Humphries, Steve E | Saleheen, Danish | Danesh, John | Ingelsson, Erik | Ripatti, Samuli | Salomaa, Veikko | Erbel, Raimund | Jöckel, Karl-Heinz | Moebus, Susanne | Peters, Annette | Illig, Thomas | de Faire, Ulf | Hamsten, Anders | Morris, Andrew D | Donnelly, Peter J | Frayling, Timothy M | Hattersley, Andrew T | Boerwinkle, Eric | Melander, Olle | Kathiresan, Sekar | Nilsson, Peter M | Deloukas, Panos | Thorsteinsdottir, Unnur | Groop, Leif C | Stefansson, Kari | Hu, Frank | Pankow, James S | Dupuis, Josée | Meigs, James B | Altshuler, David | Boehnke, Michael | McCarthy, Mark I
Nature genetics  2012;44(9):981-990.
To extend understanding of the genetic architecture and molecular basis of type 2 diabetes (T2D), we conducted a meta-analysis of genetic variants on the Metabochip involving 34,840 cases and 114,981 controls, overwhelmingly of European descent. We identified ten previously unreported T2D susceptibility loci, including two demonstrating sex-differentiated association. Genome-wide analyses of these data are consistent with a long tail of further common variant loci explaining much of the variation in susceptibility to T2D. Exploration of the enlarged set of susceptibility loci implicates several processes, including CREBBP-related transcription, adipocytokine signalling and cell cycle regulation, in diabetes pathogenesis.
doi:10.1038/ng.2383
PMCID: PMC3442244  PMID: 22885922
4.  Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases 
Perry, John R. B. | Voight, Benjamin F. | Yengo, Loïc | Amin, Najaf | Dupuis, Josée | Ganser, Martha | Grallert, Harald | Navarro, Pau | Li, Man | Qi, Lu | Steinthorsdottir, Valgerdur | Scott, Robert A. | Almgren, Peter | Arking, Dan E. | Aulchenko, Yurii | Balkau, Beverley | Benediktsson, Rafn | Bergman, Richard N. | Boerwinkle, Eric | Bonnycastle, Lori | Burtt, Noël P. | Campbell, Harry | Charpentier, Guillaume | Collins, Francis S. | Gieger, Christian | Green, Todd | Hadjadj, Samy | Hattersley, Andrew T. | Herder, Christian | Hofman, Albert | Johnson, Andrew D. | Kottgen, Anna | Kraft, Peter | Labrune, Yann | Langenberg, Claudia | Manning, Alisa K. | Mohlke, Karen L. | Morris, Andrew P. | Oostra, Ben | Pankow, James | Petersen, Ann-Kristin | Pramstaller, Peter P. | Prokopenko, Inga | Rathmann, Wolfgang | Rayner, William | Roden, Michael | Rudan, Igor | Rybin, Denis | Scott, Laura J. | Sigurdsson, Gunnar | Sladek, Rob | Thorleifsson, Gudmar | Thorsteinsdottir, Unnur | Tuomilehto, Jaakko | Uitterlinden, Andre G. | Vivequin, Sidonie | Weedon, Michael N. | Wright, Alan F. | Hu, Frank B. | Illig, Thomas | Kao, Linda | Meigs, James B. | Wilson, James F. | Stefansson, Kari | van Duijn, Cornelia | Altschuler, David | Morris, Andrew D. | Boehnke, Michael | McCarthy, Mark I. | Froguel, Philippe | Palmer, Colin N. A. | Wareham, Nicholas J. | Groop, Leif | Frayling, Timothy M. | Cauchi, Stéphane
PLoS Genetics  2012;8(5):e1002741.
Common diseases such as type 2 diabetes are phenotypically heterogeneous. Obesity is a major risk factor for type 2 diabetes, but patients vary appreciably in body mass index. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m2) compared to obese cases (BMI≥30 Kg/m2). We performed two case-control genome-wide studies using two accepted cut-offs for defining individuals as overweight or obese. We used 2,112 lean type 2 diabetes cases (BMI<25 kg/m2) or 4,123 obese cases (BMI≥30 kg/m2), and 54,412 un-stratified controls. Replication was performed in 2,881 lean cases or 8,702 obese cases, and 18,957 un-stratified controls. To assess the effects of known signals, we tested the individual and combined effects of SNPs representing 36 type 2 diabetes loci. After combining data from discovery and replication datasets, we identified two signals not previously reported in Europeans. A variant (rs8090011) in the LAMA1 gene was associated with type 2 diabetes in lean cases (P = 8.4×10−9, OR = 1.13 [95% CI 1.09–1.18]), and this association was stronger than that in obese cases (P = 0.04, OR = 1.03 [95% CI 1.00–1.06]). A variant in HMG20A—previously identified in South Asians but not Europeans—was associated with type 2 diabetes in obese cases (P = 1.3×10−8, OR = 1.11 [95% CI 1.07–1.15]), although this association was not significantly stronger than that in lean cases (P = 0.02, OR = 1.09 [95% CI 1.02–1.17]). For 36 known type 2 diabetes loci, 29 had a larger odds ratio in the lean compared to obese (binomial P = 0.0002). In the lean analysis, we observed a weighted per-risk allele OR = 1.13 [95% CI 1.10–1.17], P = 3.2×10−14. This was larger than the same model fitted in the obese analysis where the OR = 1.06 [95% CI 1.05–1.08], P = 2.2×10−16. This study provides evidence that stratification of type 2 diabetes cases by BMI may help identify additional risk variants and that lean cases may have a stronger genetic predisposition to type 2 diabetes.
Author Summary
Individuals with Type 2 diabetes (T2D) can present with variable clinical characteristics. It is well known that obesity is a major risk factor for type 2 diabetes, yet patients can vary considerably—there are many lean diabetes patients and many overweight people without diabetes. We hypothesized that the genetic predisposition to the disease may be different in lean (BMI<25 Kg/m2) compared to obese cases (BMI≥30 Kg/m2). Specifically, as lean T2D patients had lower risk than obese patients, they must have been more genetically susceptible. Using genetic data from multiple genome-wide association studies, we tested genetic markers across the genome in 2,112 lean type 2 diabetes cases (BMI<25 kg/m2), 4,123 obese cases (BMI≥30 kg/m2), and 54,412 healthy controls. We confirmed our results in an additional 2,881 lean cases, 8,702 obese cases, and 18,957 healthy controls. Using these data we found differences in genetic enrichment between lean and obese cases, supporting our original hypothesis. We also searched for genetic variants that may be risk factors only in lean or obese patients and found two novel gene regions not previously reported in European individuals. These findings may influence future study design for type 2 diabetes and provide further insight into the biology of the disease.
doi:10.1371/journal.pgen.1002741
PMCID: PMC3364960  PMID: 22693455
5.  Stochastic specification of primordial germ cells from mesoderm precursors in axolotl embryos 
Development (Cambridge, England)  2014;141(12):2429-2440.
A common feature of development in most vertebrate models is the early segregation of the germ line from the soma. For example, in Xenopus and zebrafish embryos primordial germ cells (PGCs) are specified by germ plasm that is inherited from the egg; in mice, Blimp1 expression in the epiblast mediates the commitment of cells to the germ line. How these disparate mechanisms of PGC specification evolved is unknown. Here, in order to identify the ancestral mechanism of PGC specification in vertebrates, we studied PGC specification in embryos from the axolotl (Mexican salamander), a model for the tetrapod ancestor. In the axolotl, PGCs develop within mesoderm, and classic studies have reported their induction from primitive ectoderm (animal cap). We used an axolotl animal cap system to demonstrate that signalling through FGF and BMP4 induces PGCs. The role of FGF was then confirmed in vivo. We also showed PGC induction by Brachyury, in the presence of BMP4. These conditions induced pluripotent mesodermal precursors that give rise to a variety of somatic cell types, in addition to PGCs. Irreversible restriction of the germ line did not occur until the mid-tailbud stage, days after the somatic germ layers are established. Before this, germline potential was maintained by MAP kinase signalling. We propose that this stochastic mechanism of PGC specification, from mesodermal precursors, is conserved in vertebrates.
doi:10.1242/dev.105346
PMCID: PMC4050694  PMID: 24917499
Evolution; Primordial germ cell; PGC; Axolotl; Germ plasm; Mesoderm; Pluripotency
6.  Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins 
Postmus, Iris | Trompet, Stella | Deshmukh, Harshal A. | Barnes, Michael R. | Li, Xiaohui | Warren, Helen R. | Chasman, Daniel I. | Zhou, Kaixin | Arsenault, Benoit J. | Donnelly, Louise A. | Wiggins, Kerri L. | Avery, Christy L. | Griffin, Paula | Feng, QiPing | Taylor, Kent D. | Li, Guo | Evans, Daniel S. | Smith, Albert V. | de Keyser, Catherine E. | Johnson, Andrew D. | de Craen, Anton J. M. | Stott, David J. | Buckley, Brendan M. | Ford, Ian | Westendorp, Rudi G. J. | Eline Slagboom, P. | Sattar, Naveed | Munroe, Patricia B. | Sever, Peter | Poulter, Neil | Stanton, Alice | Shields, Denis C. | O’Brien, Eoin | Shaw-Hawkins, Sue | Ida Chen, Y.-D. | Nickerson, Deborah A. | Smith, Joshua D. | Pierre Dubé, Marie | Matthijs Boekholdt, S. | Kees Hovingh, G. | Kastelein, John J. P. | McKeigue, Paul M. | Betteridge, John | Neil, Andrew | Durrington, Paul N. | Doney, Alex | Carr, Fiona | Morris, Andrew | McCarthy, Mark I. | Groop, Leif | Ahlqvist, Emma | Bis, Joshua C. | Rice, Kenneth | Smith, Nicholas L. | Lumley, Thomas | Whitsel, Eric A. | Stürmer, Til | Boerwinkle, Eric | Ngwa, Julius S. | O’Donnell, Christopher J. | Vasan, Ramachandran S. | Wei, Wei-Qi | Wilke, Russell A. | Liu, Ching-Ti | Sun, Fangui | Guo, Xiuqing | Heckbert, Susan R | Post, Wendy | Sotoodehnia, Nona | Arnold, Alice M. | Stafford, Jeanette M. | Ding, Jingzhong | Herrington, David M. | Kritchevsky, Stephen B. | Eiriksdottir, Gudny | Launer, Leonore J. | Harris, Tamara B. | Chu, Audrey Y. | Giulianini, Franco | MacFadyen, Jean G. | Barratt, Bryan J. | Nyberg, Fredrik | Stricker, Bruno H. | Uitterlinden, André G. | Hofman, Albert | Rivadeneira, Fernando | Emilsson, Valur | Franco, Oscar H. | Ridker, Paul M. | Gudnason, Vilmundur | Liu, Yongmei | Denny, Joshua C. | Ballantyne, Christie M. | Rotter, Jerome I. | Adrienne Cupples, L. | Psaty, Bruce M. | Palmer, Colin N. A. | Tardif, Jean-Claude | Colhoun, Helen M. | Hitman, Graham | Krauss, Ronald M. | Wouter Jukema, J | Caulfield, Mark J.
Nature Communications  2014;5:5068.
Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.
Statins are effectively used to prevent and manage cardiovascular disease, but patient response to these drugs is highly variable. Here, the authors identify two new genes associated with the response of LDL cholesterol to statins and advance our understanding of the genetic basis of drug response.
doi:10.1038/ncomms6068
PMCID: PMC4220464  PMID: 25350695
7.  A Multi-Ethnic Meta-Analysis of Genome-Wide Association Studies in Over 100,000 Subjects Identifies 23 Fibrinogen-Associated Loci but no Strong Evidence of a Causal Association between Circulating Fibrinogen and Cardiovascular Disease 
Sabater-Lleal, Maria | Huang, Jie | Chasman, Daniel | Naitza, Silvia | Dehghan, Abbas | Johnson, Andrew D | Teumer, Alexander | Reiner, Alex P | Folkersen, Lasse | Basu, Saonli | Rudnicka, Alicja R | Trompet, Stella | Mälarstig, Anders | Baumert, Jens | Bis, Joshua C. | Guo, Xiuqing | Hottenga, Jouke J | Shin, So-Youn | Lopez, Lorna M | Lahti, Jari | Tanaka, Toshiko | Yanek, Lisa R | Oudot-Mellakh, Tiphaine | Wilson, James F | Navarro, Pau | Huffman, Jennifer E | Zemunik, Tatijana | Redline, Susan | Mehra, Reena | Pulanic, Drazen | Rudan, Igor | Wright, Alan F | Kolcic, Ivana | Polasek, Ozren | Wild, Sarah H | Campbell, Harry | Curb, J David | Wallace, Robert | Liu, Simin | Eaton, Charles B. | Becker, Diane M. | Becker, Lewis C. | Bandinelli, Stefania | Räikkönen, Katri | Widen, Elisabeth | Palotie, Aarno | Fornage, Myriam | Green, David | Gross, Myron | Davies, Gail | Harris, Sarah E | Liewald, David C | Starr, John M | Williams, Frances M.K. | Grant, P.J. | Spector, Timothy D. | Strawbridge, Rona J | Silveira, Angela | Sennblad, Bengt | Rivadeneira, Fernando | Uitterlinden, Andre G | Franco, Oscar H | Hofman, Albert | van Dongen, Jenny | Willemsen, G | Boomsma, Dorret I | Yao, Jie | Jenny, Nancy Swords | Haritunians, Talin | McKnight, Barbara | Lumley, Thomas | Taylor, Kent D | Rotter, Jerome I | Psaty, Bruce M | Peters, Annette | Gieger, Christian | Illig, Thomas | Grotevendt, Anne | Homuth, Georg | Völzke, Henry | Kocher, Thomas | Goel, Anuj | Franzosi, Maria Grazia | Seedorf, Udo | Clarke, Robert | Steri, Maristella | Tarasov, Kirill V | Sanna, Serena | Schlessinger, David | Stott, David J | Sattar, Naveed | Buckley, Brendan M | Rumley, Ann | Lowe, Gordon D | McArdle, Wendy L | Chen, Ming-Huei | Tofler, Geoffrey H | Song, Jaejoon | Boerwinkle, Eric | Folsom, Aaron R. | Rose, Lynda M. | Franco-Cereceda, Anders | Teichert, Martina | Ikram, M Arfan | Mosley, Thomas H | Bevan, Steve | Dichgans, Martin | Rothwell, Peter M. | Sudlow, Cathie L M | Hopewell, Jemma C. | Chambers, John C. | Saleheen, Danish | Kooner, Jaspal S. | Danesh, John | Nelson, Christopher P | Erdmann, Jeanette | Reilly, Muredach P. | Kathiresan, Sekar | Schunkert, Heribert | Morange, Pierre-Emmanuel | Ferrucci, Luigi | Eriksson, Johan G | Jacobs, David | Deary, Ian J | Soranzo, Nicole | Witteman, Jacqueline CM | de Geus, Eco JC | Tracy, Russell P. | Hayward, Caroline | Koenig, Wolfgang | Cucca, Francesco | Jukema, J Wouter | Eriksson, Per | Seshadri, Sudha | Markus, Hugh S. | Watkins, Hugh | Samani, Nilesh J | Wallaschofski, Henri | Smith, Nicholas L. | Tregouet, David | Ridker, Paul M. | Tang, Weihong | Strachan, David P. | Hamsten, Anders | O’Donnell, Christopher J.
Circulation  2013;128(12):10.1161/CIRCULATIONAHA.113.002251.
Background
Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease (CVD), range from 34 to 50%. Genetic variants so far identified by genome-wide association (GWA) studies only explain a small proportion (< 2%) of its variation.
Methods and Results
We conducted a meta-analysis of 28 GWA studies, including more than 90,000 subjects of European ancestry, the first GWA meta-analysis of fibrinogen levels in 7 African Americans studies totaling 8,289 samples, and a GWA study in Hispanic-Americans totaling 1,366 samples. Evaluation for association of SNPs with clinical outcomes included a total of 40,695 cases and 85,582 controls for coronary artery disease (CAD), 4,752 cases and 24,030 controls for stroke, and 3,208 cases and 46,167 controls for venous thromboembolism (VTE). Overall, we identified 24 genome-wide significant (P<5×10−8) independent signals in 23 loci, including 15 novel associations, together accounting for 3.7% of plasma fibrinogen variation. Gene-set enrichment analysis highlighted key roles in fibrinogen regulation for the three structural fibrinogen genes and pathways related to inflammation, adipocytokines and thyrotrophin-releasing hormone signaling. Whereas lead SNPs in a few loci were significantly associated with CAD, the combined effect of all 24 fibrinogen-associated lead SNPs was not significant for CAD, stroke or VTE.
Conclusion
We identify 23 robustly associated fibrinogen loci, 15 of which are new. Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and CAD, stroke or VTE.
doi:10.1161/CIRCULATIONAHA.113.002251
PMCID: PMC3842025  PMID: 23969696
Fibrinogen; cardiovascular disease; genome-wide association study
8.  Syntaxin-binding protein STXBP5 inhibits endothelial exocytosis and promotes platelet secretion 
The Journal of Clinical Investigation  2014;124(10):4503-4516.
In humans, vWF levels predict the risk of myocardial infarction and thrombosis; however, the factors that influence vWF levels are not completely understood. Recent genome-wide association studies (GWAS) have identified syntaxin-binding protein 5 (STXBP5) as a candidate gene linked to changes in vWF plasma levels, though the functional relationship between STXBP5 and vWF is unknown. We hypothesized that STXBP5 inhibits endothelial cell exocytosis. We found that STXBP5 is expressed in human endothelial cells and colocalizes with and interacts with syntaxin 4. In human endothelial cells reduction of STXBP5 increased exocytosis of vWF and P-selectin. Mice lacking Stxbp5 had higher levels of vWF in the plasma, increased P-selectin translocation, and more platelet-endothelial interactions, which suggests that STXBP5 inhibits endothelial exocytosis. However, Stxbp5 KO mice also displayed hemostasis defects, including prolonged tail bleeding times and impaired mesenteric arteriole and carotid artery thrombosis. Furthermore, platelets from Stxbp5 KO mice had defects in platelet secretion and activation; thus, STXBP5 inhibits endothelial exocytosis but promotes platelet secretion. Our study reveals a vascular function for STXBP5, validates the functional relevance of a candidate gene identified by GWAS, and suggests that variation within STXBP5 is a genetic risk for venous thromboembolic disease.
doi:10.1172/JCI71245
PMCID: PMC4191049  PMID: 25244095
9.  Association of Levels of Fasting Glucose and Insulin with Rare Variants at the Chromosome 11p11.2-MADD Locus: the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Targeted Sequencing Study 
Background
Common variation at the 11p11.2 locus, encompassing MADD, ACP2, NR1H3, MYBPC3 and SPI1, has been associated in genome-wide association studies with fasting glucose (FG) and insulin (FI). In the Cohorts for Heart and Aging Research in Genomic Epidemiology Targeted Sequencing Study, we sequenced five gene regions at 11p11.2 to identify rare, potentially functional variants influencing FG or FI levels.
Method & Results
Sequencing (mean depth 38×) across 16.1kb in 3,566 non-diabetic individuals identified 653 variants, 79.9% of which were rare (MAF <1%) and novel. We analyzed rare variants in five gene regions with FI or FG using the Sequence Kernel Association Test (SKAT). At NR1H3, 53 rare variants were jointly associated with FI (p=2.73 × 10−3); of these, seven were predicted to have regulatory function and showed association with FI (p=1.28 × 10−3). Conditioning on two previously associated variants at MADD (rs7944584, rs10838687) did not attenuate this association, suggesting that there are more than two independent signals at 11p11.2. One predicted regulatory variant, chr11:47227430 (hg18; MAF 0.00068), contributed 20.6% to the overall SKAT score at NR1H3, lies in intron 2 of NR1H3 and is a predicted binding site for FOXA1, a transcription factor associated with insulin regulation. In human HepG2 hepatoma cells, the rare chr11:47227430 A allele disrupted FOXA1 binding and reduced FOXA1-dependent transcriptional activity.
Conclusion
Sequencing at 11p11.2- NR1H3 identified rare variation associated with FI. One variant, chr11:47227430, appears to be functional, with the rare A allele reducing transcription factor FOXA1 binding and FOXA1-dependent transcriptional activity.
doi:10.1161/CIRCGENETICS.113.000169
PMCID: PMC4066205  PMID: 24951664
fasting glucose; fasting insulin; chr11p11.2; target sequencing; next-generation sequencing
10.  Clinical and Genetic Correlates of Growth Differentiation Factor-15 in the Community 
Clinical chemistry  2012;58(11):1582-1591.
BACKGROUND
Growth differentiation factor-15 (GDF-15) is a stress-responsive cytokine produced in cardiovascular cells under conditions of inflammation and oxidative stress, and is emerging as an important prognostic marker in individuals with and without existing cardiovascular disease. Thus, we examined the clinical and genetic correlates of circulating GDF-15 levels, which have not been collectively investigated.
METHODS
A total of 2,991 participants of the Framingham Offspring Study free of clinically overt cardiovascular disease underwent measurement of plasma GDF-15 levels (mean age 59 years, 56% women). Clinical correlates of GDF-15 were examined in multivariable analyses. A genome-wide association study of GDF-15 levels was then conducted, including participants of the Framingham Offspring Study and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) study.
RESULTS
GDF-15 was positively associated with age, smoking, antihypertensive treatment, diabetes, worse kidney function, and non-steroidal anti-inflammatory drug use, but it was negatively associated with total and high-density lipoprotein cholesterol. Clinical correlates accounted for 38% of inter-individual variation in circulating GDF-15, whereas genetic factors account for up to 38% of residual variability (h2=0.38; P=2.5 × 10−11). We identified one genome-wide significant locus, which included the GDF15 gene, on chromosome 19p13.11 associated with GDF-15 concentrations (smallest P=2.74−32 for rs888663). Conditional analyses revealed two independent association signals at this locus (rs888663 and rs1054564), which were associated with altered cis-gene expression in blood cell lines.
CONCLUSIONS
In ambulatory individuals, both cardiometabolic risk factors and genetic factors play an important role in determining circulating GDF-15 concentrations, and contribute similarly to overall variation.
doi:10.1373/clinchem.2012.190322
PMCID: PMC4150608  PMID: 22997280
Epidemiology; Genetics; Risk factors; Cardiovascular diseases
11.  Loci influencing blood pressure identified using a cardiovascular gene-centric array 
Ganesh, Santhi K. | Tragante, Vinicius | Guo, Wei | Guo, Yiran | Lanktree, Matthew B. | Smith, Erin N. | Johnson, Toby | Castillo, Berta Almoguera | Barnard, John | Baumert, Jens | Chang, Yen-Pei Christy | Elbers, Clara C. | Farrall, Martin | Fischer, Mary E. | Franceschini, Nora | Gaunt, Tom R. | Gho, Johannes M.I.H. | Gieger, Christian | Gong, Yan | Isaacs, Aaron | Kleber, Marcus E. | Leach, Irene Mateo | McDonough, Caitrin W. | Meijs, Matthijs F.L. | Mellander, Olle | Molony, Cliona M. | Nolte, Ilja M. | Padmanabhan, Sandosh | Price, Tom S. | Rajagopalan, Ramakrishnan | Shaffer, Jonathan | Shah, Sonia | Shen, Haiqing | Soranzo, Nicole | van der Most, Peter J. | Van Iperen, Erik P.A. | Van Setten, Jessica | Vonk, Judith M. | Zhang, Li | Beitelshees, Amber L. | Berenson, Gerald S. | Bhatt, Deepak L. | Boer, Jolanda M.A. | Boerwinkle, Eric | Burkley, Ben | Burt, Amber | Chakravarti, Aravinda | Chen, Wei | Cooper-DeHoff, Rhonda M. | Curtis, Sean P. | Dreisbach, Albert | Duggan, David | Ehret, Georg B. | Fabsitz, Richard R. | Fornage, Myriam | Fox, Ervin | Furlong, Clement E. | Gansevoort, Ron T. | Hofker, Marten H. | Hovingh, G. Kees | Kirkland, Susan A. | Kottke-Marchant, Kandice | Kutlar, Abdullah | LaCroix, Andrea Z. | Langaee, Taimour Y. | Li, Yun R. | Lin, Honghuang | Liu, Kiang | Maiwald, Steffi | Malik, Rainer | Murugesan, Gurunathan | Newton-Cheh, Christopher | O'Connell, Jeffery R. | Onland-Moret, N. Charlotte | Ouwehand, Willem H. | Palmas, Walter | Penninx, Brenda W. | Pepine, Carl J. | Pettinger, Mary | Polak, Joseph F. | Ramachandran, Vasan S. | Ranchalis, Jane | Redline, Susan | Ridker, Paul M. | Rose, Lynda M. | Scharnag, Hubert | Schork, Nicholas J. | Shimbo, Daichi | Shuldiner, Alan R. | Srinivasan, Sathanur R. | Stolk, Ronald P. | Taylor, Herman A. | Thorand, Barbara | Trip, Mieke D. | van Duijn, Cornelia M. | Verschuren, W. Monique | Wijmenga, Cisca | Winkelmann, Bernhard R. | Wyatt, Sharon | Young, J. Hunter | Boehm, Bernhard O. | Caulfield, Mark J. | Chasman, Daniel I. | Davidson, Karina W. | Doevendans, Pieter A. | FitzGerald, Garret A. | Gums, John G. | Hakonarson, Hakon | Hillege, Hans L. | Illig, Thomas | Jarvik, Gail P. | Johnson, Julie A. | Kastelein, John J.P. | Koenig, Wolfgang | März, Winfried | Mitchell, Braxton D. | Murray, Sarah S. | Oldehinkel, Albertine J. | Rader, Daniel J. | Reilly, Muredach P. | Reiner, Alex P. | Schadt, Eric E. | Silverstein, Roy L. | Snieder, Harold | Stanton, Alice V. | Uitterlinden, André G. | van der Harst, Pim | van der Schouw, Yvonne T. | Samani, Nilesh J. | Johnson, Andrew D. | Munroe, Patricia B. | de Bakker, Paul I.W. | Zhu, Xiaofeng | Levy, Daniel | Keating, Brendan J. | Asselbergs, Folkert W.
Human Molecular Genetics  2013;22(16):3394-3395.
doi:10.1093/hmg/ddt177
PMCID: PMC3888295
12.  Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases 
Molecular Systems Biology  2014;10(7):743.
Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10−12), while Dnmt3a KO signature does not (P = 0.017).
doi:10.15252/msb.20145304
PMCID: PMC4299500  PMID: 25080494
differential co-expression; dysregulatory gene networks; epigenetic regulation of neural differentiation; network alignment; neurodegenerative diseases
13.  Synthesis of 53 tissue and cell line expression QTL datasets reveals master eQTLs 
BMC Genomics  2014;15(1):532.
Background
Gene expression genetic studies in human tissues and cells identify cis- and trans-acting expression quantitative trait loci (eQTLs). These eQTLs provide insights into regulatory mechanisms underlying disease risk. However, few studies systematically characterized eQTL results across cell and tissues types. We synthesized eQTL results from >50 datasets, including new primary data from human brain, peripheral plaque and kidney samples, in order to discover features of human eQTLs.
Results
We find a substantial number of robust cis-eQTLs and far fewer trans-eQTLs consistent across tissues. Analysis of 45 full human GWAS scans indicates eQTLs are enriched overall, and above nSNPs, among positive statistical signals in genetic mapping studies, and account for a significant fraction of the strongest human trait effects. Expression QTLs are enriched for gene centricity, higher population allele frequencies, in housekeeping genes, and for coincidence with regulatory features, though there is little evidence of 5′ or 3′ positional bias. Several regulatory categories are not enriched including microRNAs and their predicted binding sites and long, intergenic non-coding RNAs. Among the most tissue-ubiquitous cis-eQTLs, there is enrichment for genes involved in xenobiotic metabolism and mitochondrial function, suggesting these eQTLs may have adaptive origins. Several strong eQTLs (CDK5RAP2, NBPFs) coincide with regions of reported human lineage selection. The intersection of new kidney and plaque eQTLs with related GWAS suggest possible gene prioritization. For example, butyrophilins are now linked to arterial pathogenesis via multiple genetic and expression studies. Expression QTL and GWAS results are made available as a community resource through the NHLBI GRASP database [http://apps.nhlbi.nih.gov/grasp/].
Conclusions
Expression QTLs inform the interpretation of human trait variability, and may account for a greater fraction of phenotypic variability than protein-coding variants. The synthesis of available tissue eQTL data highlights many strong cis-eQTLs that may have important biologic roles and could serve as positive controls in future studies. Our results indicate some strong tissue-ubiquitous eQTLs may have adaptive origins in humans. Efforts to expand the genetic, splicing and tissue coverage of known eQTLs will provide further insights into human gene regulation.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-532) contains supplementary material, which is available to authorized users.
doi:10.1186/1471-2164-15-532
PMCID: PMC4102726  PMID: 24973796
eQTL; RNA; Gene expression; Genomics; Transcriptome; GWAS; Genome-wide; Tissue; Cis; Trans
14.  Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease 
Escott-Price, Valentina | Bellenguez, Céline | Wang, Li-San | Choi, Seung-Hoan | Harold, Denise | Jones, Lesley | Holmans, Peter | Gerrish, Amy | Vedernikov, Alexey | Richards, Alexander | DeStefano, Anita L. | Lambert, Jean-Charles | Ibrahim-Verbaas, Carla A. | Naj, Adam C. | Sims, Rebecca | Jun, Gyungah | Bis, Joshua C. | Beecham, Gary W. | Grenier-Boley, Benjamin | Russo, Giancarlo | Thornton-Wells, Tricia A. | Denning, Nicola | Smith, Albert V. | Chouraki, Vincent | Thomas, Charlene | Ikram, M. Arfan | Zelenika, Diana | Vardarajan, Badri N. | Kamatani, Yoichiro | Lin, Chiao-Feng | Schmidt, Helena | Kunkle, Brian | Dunstan, Melanie L. | Vronskaya, Maria | Johnson, Andrew D. | Ruiz, Agustin | Bihoreau, Marie-Thérèse | Reitz, Christiane | Pasquier, Florence | Hollingworth, Paul | Hanon, Olivier | Fitzpatrick, Annette L. | Buxbaum, Joseph D. | Campion, Dominique | Crane, Paul K. | Baldwin, Clinton | Becker, Tim | Gudnason, Vilmundur | Cruchaga, Carlos | Craig, David | Amin, Najaf | Berr, Claudine | Lopez, Oscar L. | De Jager, Philip L. | Deramecourt, Vincent | Johnston, Janet A. | Evans, Denis | Lovestone, Simon | Letenneur, Luc | Hernández, Isabel | Rubinsztein, David C. | Eiriksdottir, Gudny | Sleegers, Kristel | Goate, Alison M. | Fiévet, Nathalie | Huentelman, Matthew J. | Gill, Michael | Brown, Kristelle | Kamboh, M. Ilyas | Keller, Lina | Barberger-Gateau, Pascale | McGuinness, Bernadette | Larson, Eric B. | Myers, Amanda J. | Dufouil, Carole | Todd, Stephen | Wallon, David | Love, Seth | Rogaeva, Ekaterina | Gallacher, John | George-Hyslop, Peter St | Clarimon, Jordi | Lleo, Alberto | Bayer, Anthony | Tsuang, Debby W. | Yu, Lei | Tsolaki, Magda | Bossù, Paola | Spalletta, Gianfranco | Proitsi, Petra | Collinge, John | Sorbi, Sandro | Garcia, Florentino Sanchez | Fox, Nick C. | Hardy, John | Naranjo, Maria Candida Deniz | Bosco, Paolo | Clarke, Robert | Brayne, Carol | Galimberti, Daniela | Scarpini, Elio | Bonuccelli, Ubaldo | Mancuso, Michelangelo | Siciliano, Gabriele | Moebus, Susanne | Mecocci, Patrizia | Zompo, Maria Del | Maier, Wolfgang | Hampel, Harald | Pilotto, Alberto | Frank-García, Ana | Panza, Francesco | Solfrizzi, Vincenzo | Caffarra, Paolo | Nacmias, Benedetta | Perry, William | Mayhaus, Manuel | Lannfelt, Lars | Hakonarson, Hakon | Pichler, Sabrina | Carrasquillo, Minerva M. | Ingelsson, Martin | Beekly, Duane | Alvarez, Victoria | Zou, Fanggeng | Valladares, Otto | Younkin, Steven G. | Coto, Eliecer | Hamilton-Nelson, Kara L. | Gu, Wei | Razquin, Cristina | Pastor, Pau | Mateo, Ignacio | Owen, Michael J. | Faber, Kelley M. | Jonsson, Palmi V. | Combarros, Onofre | O'Donovan, Michael C. | Cantwell, Laura B. | Soininen, Hilkka | Blacker, Deborah | Mead, Simon | Mosley, Thomas H. | Bennett, David A. | Harris, Tamara B. | Fratiglioni, Laura | Holmes, Clive | de Bruijn, Renee F. A. G. | Passmore, Peter | Montine, Thomas J. | Bettens, Karolien | Rotter, Jerome I. | Brice, Alexis | Morgan, Kevin | Foroud, Tatiana M. | Kukull, Walter A. | Hannequin, Didier | Powell, John F. | Nalls, Michael A. | Ritchie, Karen | Lunetta, Kathryn L. | Kauwe, John S. K. | Boerwinkle, Eric | Riemenschneider, Matthias | Boada, Mercè | Hiltunen, Mikko | Martin, Eden R. | Schmidt, Reinhold | Rujescu, Dan | Dartigues, Jean-François | Mayeux, Richard | Tzourio, Christophe | Hofman, Albert | Nöthen, Markus M. | Graff, Caroline | Psaty, Bruce M. | Haines, Jonathan L. | Lathrop, Mark | Pericak-Vance, Margaret A. | Launer, Lenore J. | Van Broeckhoven, Christine | Farrer, Lindsay A. | van Duijn, Cornelia M. | Ramirez, Alfredo | Seshadri, Sudha | Schellenberg, Gerard D. | Amouyel, Philippe | Williams, Julie
PLoS ONE  2014;9(6):e94661.
Background
Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
Principal Findings
In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
Significance
The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
doi:10.1371/journal.pone.0094661
PMCID: PMC4055488  PMID: 24922517
15.  GRASP: analysis of genotype–phenotype results from 1390 genome-wide association studies and corresponding open access database 
Bioinformatics  2014;30(12):i185-i194.
Summary: We created a deeply extracted and annotated database of genome-wide association studies (GWAS) results. GRASP v1.0 contains >6.2 million SNP-phenotype association from among 1390 GWAS studies. We re-annotated GWAS results with 16 annotation sources including some rarely compared to GWAS results (e.g. RNAediting sites, lincRNAs, PTMs).
Motivation: To create a high-quality resource to facilitate further use and interpretation of human GWAS results in order to address important scientific questions.
Results: GWAS have grown exponentially, with increases in sample sizes and markers tested, and continuing bias toward European ancestry samples. GRASP contains >100 000 phenotypes, roughly: eQTLs (71.5%), metabolite QTLs (21.2%), methylation QTLs (4.4%) and diseases, biomarkers and other traits (2.8%). cis-eQTLs, meQTLs, mQTLs and MHC region SNPs are highly enriched among significant results. After removing these categories, GRASP still contains a greater proportion of studies and results than comparable GWAS catalogs. Cardiovascular disease and related risk factors pre-dominate remaining GWAS results, followed by immunological, neurological and cancer traits. Significant results in GWAS display a highly gene-centric tendency. Sex chromosome X (OR = 0.18[0.16-0.20]) and Y (OR = 0.003[0.001-0.01]) genes are depleted for GWAS results. Gene length is correlated with GWAS results at nominal significance (P ≤ 0.05) levels. We show this gene-length correlation decays at increasingly more stringent P-value thresholds. Potential pleotropic genes and SNPs enriched for multi-phenotype association in GWAS are identified. However, we note possible population stratification at some of these loci. Finally, via re-annotation we identify compelling functional hypotheses at GWAS loci, in some cases unrealized in studies to date.
Conclusion: Pooling summary-level GWAS results and re-annotating with bioinformatics predictions and molecular features provides a good platform for new insights.
Availability: The GRASP database is available at http://apps.nhlbi.nih.gov/grasp.
Contact: johnsonad2@nhlbi.nih.gov
doi:10.1093/bioinformatics/btu273
PMCID: PMC4072913  PMID: 24931982
16.  Gene Expression Signatures of Coronary Heart Disease 
Objective
To identify transcriptomic biomarkers of coronary heart disease (CHD) in 188 CHD cases and 188 age- and sex-matched controls who were participants in the Framingham Heart Study.
Approach and results
A total of 35 genes were differentially expressed in CHD cases vs. controls at FDR<0.5 including GZMB, TMEM56 and GUK1. Cluster analysis revealed three gene clusters associated with CHD, two linked to increased erythrocyte production and a third to reduced natural killer (NK) and T cell activity in CHD cases. Exon-level results corroborated and extended the gene-level results. Alternative splicing analysis suggested that GUK1 and 38 other genes were differentially spliced in CHD cases vs. controls. Gene ontology analysis linked ubiquitination and T-cell-related pathways with CHD.
Conclusion
Two bioinformatically defined groups of genes show consistent associations with CHD. Our findings are consistent with the hypotheses that hematopoesis is up-regulated in CHD, possibly reflecting a compensatory mechanism, and that innate immune activity is disrupted in CHD or altered by its treatment. Transcriptomic signatures may be useful in identifying pathways associated with CHD and point toward novel therapeutic targets for its treatment and prevention.
doi:10.1161/ATVBAHA.112.301169
PMCID: PMC3684247  PMID: 23539218
Gene expression; coronary heart disease; myocardial infarction; coronary artery disease; transcriptomics; biomarkers
17.  A Systems Biology Framework Identifies Molecular Underpinnings of Coronary Heart Disease 
Objective
Genetic approaches have identified numerous loci associated with coronary heart disease (CHD). The molecular mechanisms underlying CHD gene-disease associations, however, remain unclear. We hypothesized that genetic variants with both strong and subtle effects drive gene subnetworks that in turn affect CHD.
Approach and Results
We surveyed CHD-associated molecular interactions by constructing coexpression networks using whole blood gene expression profiles from 188 CHD cases and 188 age- and sex-matched controls. 24 coexpression modules were identified including one case-specific and one control-specific differential module (DM). The DMs were enriched for genes involved in B-cell activation, immune response, and ion transport. By integrating the DMs with altered gene expression associated SNPs (eSNPs) and with results of GWAS of CHD and its risk factors, the control-specific DM was implicated as CHD-causal based on its significant enrichment for both CHD and lipid eSNPs. This causal DM was further integrated with tissue-specific Bayesian networks and protein-protein interaction networks to identify regulatory key driver (KD) genes. Multi-tissue KDs (SPIB and TNFRSF13C) and tissue-specific KDs (e.g. EBF1) were identified.
Conclusions
Our network-driven integrative analysis not only identified CHD-related genes, but also defined network structure that sheds light on the molecular interactions of genes associated with CHD risk.
doi:10.1161/ATVBAHA.112.300112
PMCID: PMC3752786  PMID: 23539213
Gene expression; coronary heart disease; systems biology; coexpression network
18.  Whole Genome Sequence-Based Analysis of a Model Complex Trait, High Density Lipoprotein Cholesterol 
Nature genetics  2013;45(8):899-901.
We describe initial steps for interrogating whole genome sequence (WGS) data to characterize the genetic architecture of a complex trait, such as high density lipoprotein cholesterol (HDL-C). We estimate that common variation contributes more to HDL-C heritability than rare variation, and screening for Mendelian dyslipidemia variants identified individuals with extreme HDL-C. WGS analyses highlight the value of regulatory and non-protein coding regions of the genome in addition to protein coding regions.
doi:10.1038/ng.2671
PMCID: PMC4030301  PMID: 23770607
19.  Loci influencing blood pressure identified using a cardiovascular gene-centric array 
Ganesh, Santhi K. | Tragante, Vinicius | Guo, Wei | Guo, Yiran | Lanktree, Matthew B. | Smith, Erin N. | Johnson, Toby | Castillo, Berta Almoguera | Barnard, John | Baumert, Jens | Chang, Yen-Pei Christy | Elbers, Clara C. | Farrall, Martin | Fischer, Mary E. | Franceschini, Nora | Gaunt, Tom R. | Gho, Johannes M.I.H. | Gieger, Christian | Gong, Yan | Isaacs, Aaron | Kleber, Marcus E. | Leach, Irene Mateo | McDonough, Caitrin W. | Meijs, Matthijs F.L. | Mellander, Olle | Molony, Cliona M. | Nolte, Ilja M. | Padmanabhan, Sandosh | Price, Tom S. | Rajagopalan, Ramakrishnan | Shaffer, Jonathan | Shah, Sonia | Shen, Haiqing | Soranzo, Nicole | van der Most, Peter J. | Van Iperen, Erik P.A. | Van Setten, Jessic A. | Vonk, Judith M. | Zhang, Li | Beitelshees, Amber L. | Berenson, Gerald S. | Bhatt, Deepak L. | Boer, Jolanda M.A. | Boerwinkle, Eric | Burkley, Ben | Burt, Amber | Chakravarti, Aravinda | Chen, Wei | Cooper-DeHoff, Rhonda M. | Curtis, Sean P. | Dreisbach, Albert | Duggan, David | Ehret, Georg B. | Fabsitz, Richard R. | Fornage, Myriam | Fox, Ervin | Furlong, Clement E. | Gansevoort, Ron T. | Hofker, Marten H. | Hovingh, G. Kees | Kirkland, Susan A. | Kottke-Marchant, Kandice | Kutlar, Abdullah | LaCroix, Andrea Z. | Langaee, Taimour Y. | Li, Yun R. | Lin, Honghuang | Liu, Kiang | Maiwald, Steffi | Malik, Rainer | Murugesan, Gurunathan | Newton-Cheh, Christopher | O'Connell, Jeffery R. | Onland-Moret, N. Charlotte | Ouwehand, Willem H. | Palmas, Walter | Penninx, Brenda W. | Pepine, Carl J. | Pettinger, Mary | Polak, Joseph F. | Ramachandran, Vasan S. | Ranchalis, Jane | Redline, Susan | Ridker, Paul M. | Rose, Lynda M. | Scharnag, Hubert | Schork, Nicholas J. | Shimbo, Daichi | Shuldiner, Alan R. | Srinivasan, Sathanur R. | Stolk, Ronald P. | Taylor, Herman A. | Thorand, Barbara | Trip, Mieke D. | van Duijn, Cornelia M. | Verschuren, W. Monique | Wijmenga, Cisca | Winkelmann, Bernhard R. | Wyatt, Sharon | Young, J. Hunter | Boehm, Bernhard O. | Caulfield, Mark J. | Chasman, Daniel I. | Davidson, Karina W. | Doevendans, Pieter A. | FitzGerald, Garret A. | Gums, John G. | Hakonarson, Hakon | Hillege, Hans L. | Illig, Thomas | Jarvik, Gail P. | Johnson, Julie A. | Kastelein, John J.P. | Koenig, Wolfgang | März, Winfried | Mitchell, Braxton D. | Murray, Sarah S. | Oldehinkel, Albertine J. | Rader, Daniel J. | Reilly, Muredach P. | Reiner, Alex P. | Schadt, Eric E. | Silverstein, Roy L. | Snieder, Harold | Stanton, Alice V. | Uitterlinden, André G. | van der Harst, Pim | van der Schouw, Yvonne T. | Samani, Nilesh J. | Johnson, Andrew D. | Munroe, Patricia B. | de Bakker, Paul I.W. | Zhu, Xiaofeng | Levy, Daniel | Keating, Brendan J. | Asselbergs, Folkert W.
Human Molecular Genetics  2013;22(8):1663-1678.
Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10−6). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
doi:10.1093/hmg/dds555
PMCID: PMC3657476  PMID: 23303523
20.  The Genetics of Common Variation affecting Platelet Development, Function and Pharmaceutical Targeting 
Summary
Common variant effects on human platelet function and response to anti-platelet treatment have traditionally been studied using candidate gene approaches involving a limited number of variants and genes. These studies have often been undertaken in clinically defined cohorts. More recently, studies have applied genome-wide scans in larger population samples than prior candidate studies, in some cases scanning relatively healthy individuals. These studies demonstrate synergy with some prior candidate gene findings (e.g., GP6, ADRA2A) but also uncover novel loci involved in platelet function. Here, I summarise findings on common genetic variation influencing platelet development, function and therapeutics. Taken together, candidate gene and genome-wide studies begin to account for common variation in platelet function and provide information that may ultimately be useful in pharmacogenetic applications in the clinic. More than 50 loci have been identified with consistent associations with platelet phenotypes in ≥2 populations. Several variants are under further study in clinical trials relating to anti-platelet therapies. In order to have useful clinical applications, variants must have large effects on a modifiable outcome. Regardless of clinical applications, studies of common genetic influences, even of small effect, offer additional insights into platelet biology including the importance of intracellular signalling and novel receptors. Understanding of common platelet-related genetics remains behind parallel fields (e.g., lipids, blood pressure) due to challenges in phenotype ascertainment. Further work is necessary to discover and characterise loci for platelet function, and to assess whether these loci contribute to disease aetiologies or response to therapeutics.
doi:10.1111/j.1538-7836.2011.04359.x
PMCID: PMC3151008  PMID: 21781261
platelet; aggregation; polymorphism; genome; GWAS; SNP
21.  DNA mismatch repair gene MSH6 implicated in determining age at natural menopause 
Perry, John R.B. | Hsu, Yi-Hsiang | Chasman, Daniel I. | Johnson, Andrew D. | Elks, Cathy | Albrecht, Eva | Andrulis, Irene L. | Beesley, Jonathan | Berenson, Gerald S. | Bergmann, Sven | Bojesen, Stig E. | Bolla, Manjeet K. | Brown, Judith | Buring, Julie E. | Campbell, Harry | Chang-Claude, Jenny | Chenevix-Trench, Georgia | Corre, Tanguy | Couch, Fergus J. | Cox, Angela | Czene, Kamila | D'adamo, Adamo Pio | Davies, Gail | Deary, Ian J. | Dennis, Joe | Easton, Douglas F. | Engelhardt, Ellen G. | Eriksson, Johan G. | Esko, Tõnu | Fasching, Peter A. | Figueroa, Jonine D. | Flyger, Henrik | Fraser, Abigail | Garcia-Closas, Montse | Gasparini, Paolo | Gieger, Christian | Giles, Graham | Guenel, Pascal | Hägg, Sara | Hall, Per | Hayward, Caroline | Hopper, John | Ingelsson, Erik | Kardia, Sharon L.R. | Kasiman, Katherine | Knight, Julia A. | Lahti, Jari | Lawlor, Debbie A. | Magnusson, Patrik K.E. | Margolin, Sara | Marsh, Julie A. | Metspalu, Andres | Olson, Janet E. | Pennell, Craig E. | Polasek, Ozren | Rahman, Iffat | Ridker, Paul M. | Robino, Antonietta | Rudan, Igor | Rudolph, Anja | Salumets, Andres | Schmidt, Marjanka K. | Schoemaker, Minouk J. | Smith, Erin N. | Smith, Jennifer A. | Southey, Melissa | Stöckl, Doris | Swerdlow, Anthony J. | Thompson, Deborah J. | Truong, Therese | Ulivi, Sheila | Waldenberger, Melanie | Wang, Qin | Wild, Sarah | Wilson, James F | Wright, Alan F. | Zgaga, Lina | Ong, Ken K. | Murabito, Joanne M. | Karasik, David | Murray, Anna
Human Molecular Genetics  2013;23(9):2490-2497.
The length of female reproductive lifespan is associated with multiple adverse outcomes, including breast cancer, cardiovascular disease and infertility. The biological processes that govern the timing of the beginning and end of reproductive life are not well understood. Genetic variants are known to contribute to ∼50% of the variation in both age at menarche and menopause, but to date the known genes explain <15% of the genetic component. We have used genome-wide association in a bivariate meta-analysis of both traits to identify genes involved in determining reproductive lifespan. We observed significant genetic correlation between the two traits using genome-wide complex trait analysis. However, we found no robust statistical evidence for individual variants with an effect on both traits. A novel association with age at menopause was detected for a variant rs1800932 in the mismatch repair gene MSH6 (P = 1.9 × 10−9), which was also associated with altered expression levels of MSH6 mRNA in multiple tissues. This study contributes to the growing evidence that DNA repair processes play a key role in ovarian ageing and could be an important therapeutic target for infertility.
doi:10.1093/hmg/ddt620
PMCID: PMC3976329  PMID: 24357391
22.  Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function 
Chasman, Daniel I. | Fuchsberger, Christian | Pattaro, Cristian | Teumer, Alexander | Böger, Carsten A. | Endlich, Karlhans | Olden, Matthias | Chen, Ming-Huei | Tin, Adrienne | Taliun, Daniel | Li, Man | Gao, Xiaoyi | Gorski, Mathias | Yang, Qiong | Hundertmark, Claudia | Foster, Meredith C. | O'Seaghdha, Conall M. | Glazer, Nicole | Isaacs, Aaron | Liu, Ching-Ti | Smith, Albert V. | O'Connell, Jeffrey R. | Struchalin, Maksim | Tanaka, Toshiko | Li, Guo | Johnson, Andrew D. | Gierman, Hinco J. | Feitosa, Mary F. | Hwang, Shih-Jen | Atkinson, Elizabeth J. | Lohman, Kurt | Cornelis, Marilyn C. | Johansson, Åsa | Tönjes, Anke | Dehghan, Abbas | Lambert, Jean-Charles | Holliday, Elizabeth G. | Sorice, Rossella | Kutalik, Zoltan | Lehtimäki, Terho | Esko, Tõnu | Deshmukh, Harshal | Ulivi, Sheila | Chu, Audrey Y. | Murgia, Federico | Trompet, Stella | Imboden, Medea | Coassin, Stefan | Pistis, Giorgio | Harris, Tamara B. | Launer, Lenore J. | Aspelund, Thor | Eiriksdottir, Gudny | Mitchell, Braxton D. | Boerwinkle, Eric | Schmidt, Helena | Cavalieri, Margherita | Rao, Madhumathi | Hu, Frank | Demirkan, Ayse | Oostra, Ben A. | de Andrade, Mariza | Turner, Stephen T. | Ding, Jingzhong | Andrews, Jeanette S. | Freedman, Barry I. | Giulianini, Franco | Koenig, Wolfgang | Illig, Thomas | Meisinger, Christa | Gieger, Christian | Zgaga, Lina | Zemunik, Tatijana | Boban, Mladen | Minelli, Cosetta | Wheeler, Heather E. | Igl, Wilmar | Zaboli, Ghazal | Wild, Sarah H. | Wright, Alan F. | Campbell, Harry | Ellinghaus, David | Nöthlings, Ute | Jacobs, Gunnar | Biffar, Reiner | Ernst, Florian | Homuth, Georg | Kroemer, Heyo K. | Nauck, Matthias | Stracke, Sylvia | Völker, Uwe | Völzke, Henry | Kovacs, Peter | Stumvoll, Michael | Mägi, Reedik | Hofman, Albert | Uitterlinden, Andre G. | Rivadeneira, Fernando | Aulchenko, Yurii S. | Polasek, Ozren | Hastie, Nick | Vitart, Veronique | Helmer, Catherine | Wang, Jie Jin | Stengel, Bénédicte | Ruggiero, Daniela | Bergmann, Sven | Kähönen, Mika | Viikari, Jorma | Nikopensius, Tiit | Province, Michael | Ketkar, Shamika | Colhoun, Helen | Doney, Alex | Robino, Antonietta | Krämer, Bernhard K. | Portas, Laura | Ford, Ian | Buckley, Brendan M. | Adam, Martin | Thun, Gian-Andri | Paulweber, Bernhard | Haun, Margot | Sala, Cinzia | Mitchell, Paul | Ciullo, Marina | Kim, Stuart K. | Vollenweider, Peter | Raitakari, Olli | Metspalu, Andres | Palmer, Colin | Gasparini, Paolo | Pirastu, Mario | Jukema, J. Wouter | Probst-Hensch, Nicole M. | Kronenberg, Florian | Toniolo, Daniela | Gudnason, Vilmundur | Shuldiner, Alan R. | Coresh, Josef | Schmidt, Reinhold | Ferrucci, Luigi | Siscovick, David S. | van Duijn, Cornelia M. | Borecki, Ingrid B. | Kardia, Sharon L.R. | Liu, Yongmei | Curhan, Gary C. | Rudan, Igor | Gyllensten, Ulf | Wilson, James F. | Franke, Andre | Pramstaller, Peter P. | Rettig, Rainer | Prokopenko, Inga | Witteman, Jacqueline | Hayward, Caroline | Ridker, Paul M | Parsa, Afshin | Bochud, Murielle | Heid, Iris M. | Kao, W.H. Linda | Fox, Caroline S. | Köttgen, Anna
Human Molecular Genetics  2012;21(24):5329-5343.
In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4–2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.
doi:10.1093/hmg/dds369
PMCID: PMC3607468  PMID: 22962313
23.  Association of Genetic Variation in the Mitochondrial Genome with Blood Pressure and Metabolic Traits 
Hypertension  2012;60(4):949-956.
Elevated blood pressure (BP) is a major risk factor for cardiovascular disease. Several studies have noted a consistent maternal effect on BP; consequently, mitochondrial DNA (mtDNA) variation has become an additional target of investigation of the missing BP heritability. Analyses of common mtDNA polymorphisms, however, have not found evidence of association with hypertension. To explore associations of relatively rare (frequency < 5%) mtDNA variants with BP, we identified uncommon/rare variants through sequencing the entire mitochondrial genome in 32 unrelated individuals with extreme-high BP in the Framingham Heart Study (FHS) and genotyped 40 mtSNPs in 7,219 FHS participants. The nonsynonymous mtSNP 5913G>A (Asp4Asn) in the cytochrome c oxidase subunit 1 of Complex IV demonstrated significant associations with BP and fasting blood glucose (FBG) levels. Individuals with the rare 5913A allele had, on average, 7 mm Hg higher systolic BP at baseline (Pempirical = 0.05) and 17 mg/dL higher mean FBG over 25 years of follow up (Pempirical = 0.009). Significant associations with FBG levels were also detected for nonsynonymous mtSNP 3316G>A (Ala4Thr) in the NADH dehydrogenase subunit 1 of Complex I. On average, individuals with rare allele 3316A had 17 and 25 mg/dL higher FBG at baseline (Pempirical = 0.01) and over 25 years of follow up (Pempirical = 0.007). Our findings provide the first evidence of putative association of variants in the mitochondrial genome with SBP and FBG in the general population. Replication in independent samples, however, is needed to confirm these putative associations.
doi:10.1161/HYPERTENSIONAHA.112.196519
PMCID: PMC3753106  PMID: 22949535
Mitochondrial genome; Association study; Genetics; Hypertension; Diabetes
24.  Epigenetic reprogramming of breast cancer cells with oocyte extracts 
Molecular Cancer  2011;10:7.
Background
Breast cancer is a disease characterised by both genetic and epigenetic alterations. Epigenetic silencing of tumour suppressor genes is an early event in breast carcinogenesis and reversion of gene silencing by epigenetic reprogramming can provide clues to the mechanisms responsible for tumour initiation and progression. In this study we apply the reprogramming capacity of oocytes to cancer cells in order to study breast oncogenesis.
Results
We show that breast cancer cells can be directly reprogrammed by amphibian oocyte extracts. The reprogramming effect, after six hours of treatment, in the absence of DNA replication, includes DNA demethylation and removal of repressive histone marks at the promoters of tumour suppressor genes; also, expression of the silenced genes is re-activated in response to treatment. This activity is specific to oocytes as it is not elicited by extracts from ovulated eggs, and is present at very limited levels in extracts from mouse embryonic stem cells. Epigenetic reprogramming in oocyte extracts results in reduction of cancer cell growth under anchorage independent conditions and a reduction in tumour growth in mouse xenografts.
Conclusions
This study presents a new method to investigate tumour reversion by epigenetic reprogramming. After testing extracts from different sources, we found that axolotl oocyte extracts possess superior reprogramming ability, which reverses epigenetic silencing of tumour suppressor genes and tumorigenicity of breast cancer cells in a mouse xenograft model. Therefore this system can be extremely valuable for dissecting the mechanisms involved in tumour suppressor gene silencing and identifying molecular activities capable of arresting tumour growth. These applications can ultimately shed light on the contribution of epigenetic alterations in breast cancer and advance the development of epigenetic therapies.
doi:10.1186/1476-4598-10-7
PMCID: PMC3034708  PMID: 21232089
25.  Common genetic variation at the IL1RL1 locus regulates IL-33/ST2 signaling  
The Journal of Clinical Investigation  2013;123(10):4208-4218.
The suppression of tumorigenicity 2/IL-33 (ST2/IL-33) pathway has been implicated in several immune and inflammatory diseases. ST2 is produced as 2 isoforms. The membrane-bound isoform (ST2L) induces an immune response when bound to its ligand, IL-33. The other isoform is a soluble protein (sST2) that is thought to be a decoy receptor for IL-33 signaling. Elevated sST2 levels in serum are associated with an increased risk for cardiovascular disease. We investigated the determinants of sST2 plasma concentrations in 2,991 Framingham Offspring Cohort participants. While clinical and environmental factors explained some variation in sST2 levels, much of the variation in sST2 production was driven by genetic factors. In a genome-wide association study (GWAS), multiple SNPs within IL1RL1 (the gene encoding ST2) demonstrated associations with sST2 concentrations. Five missense variants of IL1RL1 correlated with higher sST2 levels in the GWAS and mapped to the intracellular domain of ST2, which is absent in sST2. In a cell culture model, IL1RL1 missense variants increased sST2 expression by inducing IL-33 expression and enhancing IL-33 responsiveness (via ST2L). Our data suggest that genetic variation in IL1RL1 can result in increased levels of sST2 and alter immune and inflammatory signaling through the ST2/IL-33 pathway.
doi:10.1172/JCI67119
PMCID: PMC3784527  PMID: 23999434

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