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1. Common clinical blood and urine biomarkers for ischemic stroke: an Estonian Electronic Health Records database study

Author

Siim Kurvits, Ainika Harro, Anu Reigo, Anne Ott, Sven Laur, Dage Särg, Ardi Tampuu, the Estonian Biobank Research Team, Kaur Alasoo, Jaak Vilo, Lili Milani, Toomas Haller, and the PRECISE4Q consortium

Subjects
Ischemic stroke, Electronic health records, Population health, Machine learning, Medicine
Abstract

Abstract Background Ischemic stroke (IS) is a major health risk without generally usable effective measures of primary prevention. Early warning signals that are easy to detect and widely available can save lives. Estonia has one nation-wide Electronic Health Record (EHR) database for the storage of medical information of patients from hospitals and primary care providers. Methods We extracted structured and unstructured data from the EHRs of participants of the Estonian Biobank (EstBB) and evaluated different formats of input data to understand how this continuously growing dataset should be prepared for best prediction. The utility of the EHR database for finding blood- and urine-based biomarkers for IS was demonstrated by applying different analytical and machine learning (ML) methods. Results Several early trends in common clinical laboratory parameter changes (set of red blood indices, lymphocyte/neutrophil ratio, etc.) were established for IS prediction. The developed ML models predicted the future occurrence of IS with very high accuracy and Random Forests was proved as the most applicable method to EHR data. Conclusions We conclude that the EHR database and the risk factors uncovered are valuable resources in screening the population for risk of IS as well as constructing disease risk scores and refining prediction models for IS by ML.

Published
2023
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2. Lacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond

Author

Sepideh Sadegh, James Skelton, Elisa Anastasi, Andreas Maier, Klaudia Adamowicz, Anna Möller, Nils M. Kriege, Jaanika Kronberg, Toomas Haller, Tim Kacprowski, Anil Wipat, Jan Baumbach, and David B. Blumenthal

Subjects
Science
Abstract

Large-scale disease-association data are widely used for pathomechanism mining, even if disease definitions used for annotation are mostly phenotype-based. Here, the authors show that this bias can lead to a blurred view on disease mechanisms, highlighting the need for close-up studies based on molecular data for well-characterized patient cohorts.

Published
2023
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3. Rare variant analyses across multiethnic cohorts identify novel genes for refractive error

Author

Anthony M. Musolf, Annechien E. G. Haarman, Robert N. Luben, Jue-Sheng Ong, Karina Patasova, Rolando Hernandez Trapero, Joseph Marsh, Ishika Jain, Riya Jain, Paul Zhiping Wang, Deyana D. Lewis, Milly S. Tedja, Adriana I. Iglesias, Hengtong Li, Cameron S. Cowan, Consortium for Refractive Error and Myopia (CREAM), Ginevra Biino, Alison P. Klein, Priya Duggal, David A. Mackey, Caroline Hayward, Toomas Haller, Andres Metspalu, Juho Wedenoja, Olavi Pärssinen, Ching-Yu Cheng, Seang-Mei Saw, Dwight Stambolian, Pirro G. Hysi, Anthony P. Khawaja, Veronique Vitart, Christopher J. Hammond, Cornelia M. van Duijn, Virginie J. M. Verhoeven, Caroline C. W. Klaver, and Joan E. Bailey-Wilson

Subjects
Biology (General), QH301-705.5
Abstract

A multi-ethnic meta-analysis of exome array data from over 27,000 participants identifies several rare variants that could contribute to risk of ocular refractive error.

Published
2023
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4. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author

Thomas W. Winkler, Humaira Rasheed, Alexander Teumer, Mathias Gorski, Bryce X. Rowan, Kira J. Stanzick, Laurent F. Thomas, Adrienne Tin, Anselm Hoppmann, Audrey Y. Chu, Bamidele Tayo, Chris H. L. Thio, Daniele Cusi, Jin-Fang Chai, Karsten B. Sieber, Katrin Horn, Man Li, Markus Scholz, Massimiliano Cocca, Matthias Wuttke, Peter J. van der Most, Qiong Yang, Sahar Ghasemi, Teresa Nutile, Yong Li, Giulia Pontali, Felix Günther, Abbas Dehghan, Adolfo Correa, Afshin Parsa, Agnese Feresin, Aiko P. J. de Vries, Alan B. Zonderman, Albert V. Smith, Albertine J. Oldehinkel, Alessandro De Grandi, Alexander R. Rosenkranz, Andre Franke, Andrej Teren, Andres Metspalu, Andrew A. Hicks, Andrew P. Morris, Anke Tönjes, Anna Morgan, Anna I. Podgornaia, Annette Peters, Antje Körner, Anubha Mahajan, Archie Campbell, Barry I. Freedman, Beatrice Spedicati, Belen Ponte, Ben Schöttker, Ben Brumpton, Bernhard Banas, Bernhard K. Krämer, Bettina Jung, Bjørn Olav Åsvold, Blair H. Smith, Boting Ning, Brenda W. J. H. Penninx, Brett R. Vanderwerff, Bruce M. Psaty, Candace M. Kammerer, Carl D. Langefeld, Caroline Hayward, Cassandra N. Spracklen, Cassianne Robinson-Cohen, Catharina A. Hartman, Cecilia M. Lindgren, Chaolong Wang, Charumathi Sabanayagam, Chew-Kiat Heng, Chiara Lanzani, Chiea-Chuen Khor, Ching-Yu Cheng, Christian Fuchsberger, Christian Gieger, Christian M. Shaffer, Christina-Alexandra Schulz, Cristen J. Willer, Daniel I. Chasman, Daniel F. Gudbjartsson, Daniela Ruggiero, Daniela Toniolo, Darina Czamara, David J. Porteous, Dawn M. Waterworth, Deborah Mascalzoni, Dennis O. Mook-Kanamori, Dermot F. Reilly, E. Warwick Daw, Edith Hofer, Eric Boerwinkle, Erika Salvi, Erwin P. Bottinger, E-Shyong Tai, Eulalia Catamo, Federica Rizzi, Feng Guo, Fernando Rivadeneira, Franco Guilianini, Gardar Sveinbjornsson, Georg Ehret, Gerard Waeber, Ginevra Biino, Giorgia Girotto, Giorgio Pistis, Girish N. Nadkarni, Graciela E. Delgado, Grant W. Montgomery, Harold Snieder, Harry Campbell, Harvey D. White, He Gao, Heather M. Stringham, Helena Schmidt, Hengtong Li, Hermann Brenner, Hilma Holm, Holgen Kirsten, Holly Kramer, Igor Rudan, Ilja M. Nolte, Ioanna Tzoulaki, Isleifur Olafsson, Jade Martins, James P. Cook, James F. Wilson, Jan Halbritter, Janine F. Felix, Jasmin Divers, Jaspal S. Kooner, Jeannette Jen-Mai Lee, Jeffrey O’Connell, Jerome I. Rotter, Jianjun Liu, Jie Xu, Joachim Thiery, Johan Ärnlöv, Johanna Kuusisto, Johanna Jakobsdottir, Johanne Tremblay, John C. Chambers, John B. Whitfield, John M. Gaziano, Jonathan Marten, Josef Coresh, Jost B. Jonas, Josyf C. Mychaleckyj, Kaare Christensen, Kai-Uwe Eckardt, Karen L. Mohlke, Karlhans Endlich, Katalin Dittrich, Kathleen A. Ryan, Kenneth M. Rice, Kent D. Taylor, Kevin Ho, Kjell Nikus, Koichi Matsuda, Konstantin Strauch, Kozeta Miliku, Kristian Hveem, Lars Lind, Lars Wallentin, Laura M. Yerges-Armstrong, Laura M. Raffield, Lawrence S. Phillips, Lenore J. Launer, Leo-Pekka Lyytikäinen, Leslie A. Lange, Lorena Citterio, Lucija Klaric, M. Arfan Ikram, Marcus Ising, Marcus E. Kleber, Margherita Francescatto, Maria Pina Concas, Marina Ciullo, Mario Piratsu, Marju Orho-Melander, Markku Laakso, Markus Loeffler, Markus Perola, Martin H. de Borst, Martin Gögele, Martina La Bianca, Mary Ann Lukas, Mary F. Feitosa, Mary L. Biggs, Mary K. Wojczynski, Maryam Kavousi, Masahiro Kanai, Masato Akiyama, Masayuki Yasuda, Matthias Nauck, Melanie Waldenberger, Miao-Li Chee, Miao-Ling Chee, Michael Boehnke, Michael H. Preuss, Michael Stumvoll, Michael A. Province, Michele K. Evans, Michelle L. O’Donoghue, Michiaki Kubo, Mika Kähönen, Mika Kastarinen, Mike A. Nalls, Mikko Kuokkanen, Mohsen Ghanbari, Murielle Bochud, Navya Shilpa Josyula, Nicholas G. Martin, Nicholas Y. Q. Tan, Nicholette D. Palmer, Nicola Pirastu, Nicole Schupf, Niek Verweij, Nina Hutri-Kähönen, Nina Mononen, Nisha Bansal, Olivier Devuyst, Olle Melander, Olli T. Raitakari, Ozren Polasek, Paolo Manunta, Paolo Gasparini, Pashupati P. Mishra, Patrick Sulem, Patrik K. E. Magnusson, Paul Elliott, Paul M. Ridker, Pavel Hamet, Per O. Svensson, Peter K. Joshi, Peter Kovacs, Peter P. Pramstaller, Peter Rossing, Peter Vollenweider, Pim van der Harst, Rajkumar Dorajoo, Ralene Z. H. Sim, Ralph Burkhardt, Ran Tao, Raymond Noordam, Reedik Mägi, Reinhold Schmidt, Renée de Mutsert, Rico Rueedi, Rob M. van Dam, Robert J. Carroll, Ron T. Gansevoort, Ruth J. F. Loos, Sala Cinzia Felicita, Sanaz Sedaghat, Sandosh Padmanabhan, Sandra Freitag-Wolf, Sarah A. Pendergrass, Sarah E. Graham, Scott D. Gordon, Shih-Jen Hwang, Shona M. Kerr, Simona Vaccargiu, Snehal B. Patil, Stein Hallan, Stephan J. L. Bakker, Su-Chi Lim, Susanne Lucae, Suzanne Vogelezang, Sven Bergmann, Tanguy Corre, Tarunveer S. Ahluwalia, Terho Lehtimäki, Thibaud S. Boutin, Thomas Meitinger, Tien-Yin Wong, Tobias Bergler, Ton J. Rabelink, Tõnu Esko, Toomas Haller, Unnur Thorsteinsdottir, Uwe Völker, Valencia Hui Xian Foo, Veikko Salomaa, Veronique Vitart, Vilmantas Giedraitis, Vilmundur Gudnason, Vincent W. V. Jaddoe, Wei Huang, Weihua Zhang, Wen Bin Wei, Wieland Kiess, Winfried März, Wolfgang Koenig, Wolfgang Lieb, Xin Gao, Xueling Sim, Ya Xing Wang, Yechiel Friedlander, Yih-Chung Tham, Yoichiro Kamatani, Yukinori Okada, Yuri Milaneschi, Zhi Yu, Lifelines cohort study, DiscovEHR/MyCode study, VA Million Veteran Program, Klaus J. Stark, Kari Stefansson, Carsten A. Böger, Adriana M. Hung, Florian Kronenberg, Anna Köttgen, Cristian Pattaro, and Iris M. Heid

Subjects
Biology (General), QH301-705.5
Abstract

A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.

Published
2022
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5. Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals

Author

Davide Marnetto, Katri Pärna, Kristi Läll, Ludovica Molinaro, Francesco Montinaro, Toomas Haller, Mait Metspalu, Reedik Mägi, Krista Fischer, and Luca Pagani

Subjects
Science
Abstract

Polygenic scores are believed to hold future promise for trait prediction and personalized medicine, but are sensitive to demographic history. Here, Marnetto et al. develop partial polygenic scores supplemented with local ancestry deconvolution which improves prediction accuracy into recently admixed European populations.

Published
2020
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6. The blood metabolome of incident kidney cancer: A case-control study nested within the MetKid consortium.

Author

Florence Guida, Vanessa Y Tan, Laura J Corbin, Karl Smith-Byrne, Karine Alcala, Claudia Langenberg, Isobel D Stewart, Adam S Butterworth, Praveen Surendran, David Achaintre, Jerzy Adamski, Pilar Amiano, Manuela M Bergmann, Caroline J Bull, Christina C Dahm, Audrey Gicquiau, Graham G Giles, Marc J Gunter, Toomas Haller, Arnulf Langhammer, Tricia L Larose, Börje Ljungberg, Andres Metspalu, Roger L Milne, David C Muller, Therese H Nøst, Elin Pettersen Sørgjerd, Cornelia Prehn, Elio Riboli, Sabina Rinaldi, Joseph A Rothwell, Augustin Scalbert, Julie A Schmidt, Gianluca Severi, Sabina Sieri, Roel Vermeulen, Emma E Vincent, Melanie Waldenberger, Nicholas J Timpson, and Mattias Johansson

Subjects
Medicine
Abstract

BackgroundExcess bodyweight and related metabolic perturbations have been implicated in kidney cancer aetiology, but the specific molecular mechanisms underlying these relationships are poorly understood. In this study, we sought to identify circulating metabolites that predispose kidney cancer and to evaluate the extent to which they are influenced by body mass index (BMI).Methods and findingsWe assessed the association between circulating levels of 1,416 metabolites and incident kidney cancer using pre-diagnostic blood samples from up to 1,305 kidney cancer case-control pairs from 5 prospective cohort studies. Cases were diagnosed on average 8 years after blood collection. We found 25 metabolites robustly associated with kidney cancer risk. In particular, 14 glycerophospholipids (GPLs) were inversely associated with risk, including 8 phosphatidylcholines (PCs) and 2 plasmalogens. The PC with the strongest association was PC ae C34:3 with an odds ratio (OR) for 1 standard deviation (SD) increment of 0.75 (95% confidence interval [CI]: 0.68 to 0.83, p = 2.6 × 10-8). In contrast, 4 amino acids, including glutamate (OR for 1 SD = 1.39, 95% CI: 1.20 to 1.60, p = 1.6 × 10-5), were positively associated with risk. Adjusting for BMI partly attenuated the risk association for some-but not all-metabolites, whereas other known risk factors of kidney cancer, such as smoking and alcohol consumption, had minimal impact on the observed associations. A mendelian randomisation (MR) analysis of the influence of BMI on the blood metabolome highlighted that some metabolites associated with kidney cancer risk are influenced by BMI. Specifically, elevated BMI appeared to decrease levels of several GPLs that were also found inversely associated with kidney cancer risk (e.g., -0.17 SD change [ßBMI] in 1-(1-enyl-palmitoyl)-2-linoleoyl-GPC (P-16:0/18:2) levels per SD change in BMI, p = 3.4 × 10-5). BMI was also associated with increased levels of glutamate (ßBMI: 0.12, p = 1.5 × 10-3). While our results were robust across the participating studies, they were limited to study participants of European descent, and it will, therefore, be important to evaluate if our findings can be generalised to populations with different genetic backgrounds.ConclusionsThis study suggests a potentially important role of the blood metabolome in kidney cancer aetiology by highlighting a wide range of metabolites associated with the risk of developing kidney cancer and the extent to which changes in levels of these metabolites are driven by BMI-the principal modifiable risk factor of kidney cancer.

Published
2021
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7. Manhattan Harvester and Cropper: a system for GWAS peak detection

Author

Toomas Haller, Tõnis Tasa, and Andres Metspalu

Subjects
GWAS, Manhattan plots, Peak detection, Peak quality score, Software, Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. Results We developed Manhattan Harvester, a tool designed for “peak extraction” from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. Conclusions We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available.

Published
2019
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8. Meta-analysis of gene–environment-wide association scans accounting for education level identifies additional loci for refractive error

Author

Qiao Fan, Virginie J. M. Verhoeven, Robert Wojciechowski, Veluchamy A. Barathi, Pirro G. Hysi, Jeremy A. Guggenheim, René Höhn, Veronique Vitart, Anthony P. Khawaja, Kenji Yamashiro, S Mohsen Hosseini, Terho Lehtimäki, Yi Lu, Toomas Haller, Jing Xie, Cécile Delcourt, Mario Pirastu, Juho Wedenoja, Puya Gharahkhani, Cristina Venturini, Masahiro Miyake, Alex W. Hewitt, Xiaobo Guo, Johanna Mazur, Jenifer E. Huffman, Katie M. Williams, Ozren Polasek, Harry Campbell, Igor Rudan, Zoran Vatavuk, James F. Wilson, Peter K. Joshi, George McMahon, Beate St Pourcain, David M. Evans, Claire L. Simpson, Tae-Hwi Schwantes-An, Robert P. Igo, Alireza Mirshahi, Audrey Cougnard-Gregoire, Céline Bellenguez, Maria Blettner, Olli Raitakari, Mika Kähönen, Ilkka Seppälä, Tanja Zeller, Thomas Meitinger, Janina S. Ried, Christian Gieger, Laura Portas, Elisabeth M. van Leeuwen, Najaf Amin, André G. Uitterlinden, Fernando Rivadeneira, Albert Hofman, Johannes R. Vingerling, Ya Xing Wang, Xu Wang, Eileen Tai-Hui Boh, M. Kamran Ikram, Charumathi Sabanayagam, Preeti Gupta, Vincent Tan, Lei Zhou, Candice E. H. Ho, Wan’e Lim, Roger W. Beuerman, Rosalynn Siantar, E-Shyong Tai, Eranga Vithana, Evelin Mihailov, Chiea-Chuen Khor, Caroline Hayward, Robert N. Luben, Paul J. Foster, Barbara E. K. Klein, Ronald Klein, Hoi-Suen Wong, Paul Mitchell, Andres Metspalu, Tin Aung, Terri L. Young, Mingguang He, Olavi Pärssinen, Cornelia M. van Duijn, Jie Jin Wang, Cathy Williams, Jost B. Jonas, Yik-Ying Teo, David A. Mackey, Konrad Oexle, Nagahisa Yoshimura, Andrew D. Paterson, Norbert Pfeiffer, Tien-Yin Wong, Paul N. Baird, Dwight Stambolian, Joan E. Bailey Wilson, Ching-Yu Cheng, Christopher J. Hammond, Caroline C. W. Klaver, Seang-Mei Saw, and Consortium for Refractive Error and Myopia (CREAM)

Subjects
Science
Abstract

This report by the Consortium for Refractive Error and Myopia uses gene-environment-wide interaction study (GEWIS) to identify genetic loci that affect environmental influence in myopia development, and identifies ethnic specific genetic loci that attribute to eye refractive errors.

Published
2016
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9. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Author

Johannes Kettunen, Ayşe Demirkan, Peter Würtz, Harmen H.M. Draisma, Toomas Haller, Rajesh Rawal, Anika Vaarhorst, Antti J. Kangas, Leo-Pekka Lyytikäinen, Matti Pirinen, René Pool, Antti-Pekka Sarin, Pasi Soininen, Taru Tukiainen, Qin Wang, Mika Tiainen, Tuulia Tynkkynen, Najaf Amin, Tanja Zeller, Marian Beekman, Joris Deelen, Ko Willems van Dijk, Tõnu Esko, Jouke-Jan Hottenga, Elisabeth M van Leeuwen, Terho Lehtimäki, Evelin Mihailov, Richard J. Rose, Anton J.M. de Craen, Christian Gieger, Mika Kähönen, Markus Perola, Stefan Blankenberg, Markku J. Savolainen, Aswin Verhoeven, Jorma Viikari, Gonneke Willemsen, Dorret I. Boomsma, Cornelia M. van Duijn, Johan Eriksson, Antti Jula, Marjo-Riitta Järvelin, Jaakko Kaprio, Andres Metspalu, Olli Raitakari, Veikko Salomaa, P. Eline Slagboom, Melanie Waldenberger, Samuli Ripatti, and Mika Ala-Korpela

Subjects
Science
Abstract

Circulating metabolites reflect human health and disease. Here, Kettunen et al. perform a genome-wide association study on 123 circulating metabolic traits and identify novel genetic loci influencing systemic metabolism. They also link new molecular pathways with a known cardiovascular risk factor Lp(a).

Published
2016
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10. Correction: Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author

Mariaelisa Graff, Robert A Scott, Anne E Justice, Kristin L Young, Mary F Feitosa, Llilda Barata, Thomas W Winkler, Audrey Y Chu, Anubha Mahajan, David Hadley, Luting Xue, Tsegaselassie Workalemahu, Nancy L Heard-Costa, Marcel den Hoed, Tarunveer S Ahluwalia, Qibin Qi, Julius S Ngwa, Frida Renström, Lydia Quaye, John D Eicher, James E Hayes, Marilyn Cornelis, Zoltan Kutalik, Elise Lim, Jian'an Luan, Jennifer E Huffman, Weihua Zhang, Wei Zhao, Paula J Griffin, Toomas Haller, Shafqat Ahmad, Pedro M Marques-Vidal, Stephanie Bien, Loic Yengo, Alexander Teumer, Albert Vernon Smith, Meena Kumari, Marie Neergaard Harder, Johanne Marie Justesen, Marcus E Kleber, Mette Hollensted, Kurt Lohman, Natalia V Rivera, John B Whitfield, Jing Hua Zhao, Heather M Stringham, Leo-Pekka Lyytikäinen, Charlotte Huppertz, Gonneke Willemsen, Wouter J Peyrot, Ying Wu, Kati Kristiansson, Ayse Demirkan, Myriam Fornage, Maija Hassinen, Lawrence F Bielak, Gemma Cadby, Toshiko Tanaka, Reedik Mägi, Peter J van der Most, Anne U Jackson, Jennifer L Bragg-Gresham, Veronique Vitart, Jonathan Marten, Pau Navarro, Claire Bellis, Dorota Pasko, Åsa Johansson, Søren Snitker, Yu-Ching Cheng, Joel Eriksson, Unhee Lim, Mette Aadahl, Linda S Adair, Najaf Amin, Beverley Balkau, Juha Auvinen, John Beilby, Richard N Bergman, Sven Bergmann, Alain G Bertoni, John Blangero, Amélie Bonnefond, Lori L Bonnycastle, Judith B Borja, Søren Brage, Fabio Busonero, Steve Buyske, Harry Campbell, Peter S Chines, Francis S Collins, Tanguy Corre, George Davey Smith, Graciela E Delgado, Nicole Dueker, Marcus Dörr, Tapani Ebeling, Gudny Eiriksdottir, Tõnu Esko, Jessica D Faul, Mao Fu, Kristine Færch, Christian Gieger, Sven Gläser, Jian Gong, Penny Gordon-Larsen, Harald Grallert, Tanja B Grammer, Niels Grarup, Gerard van Grootheest, Kennet Harald, Nicholas D Hastie, Aki S Havulinna, Dena Hernandez, Lucia Hindorff, Lynne J Hocking, Oddgeir L Holmens, Christina Holzapfel, Jouke Jan Hottenga, Jie Huang, Tao Huang, Jennie Hui, Cornelia Huth, Nina Hutri-Kähönen, Alan L James, John-Olov Jansson, Min A Jhun, Markus Juonala, Leena Kinnunen, Heikki A Koistinen, Ivana Kolcic, Pirjo Komulainen, Johanna Kuusisto, Kirsti Kvaløy, Mika Kähönen, Timo A Lakka, Lenore J Launer, Benjamin Lehne, Cecilia M Lindgren, Mattias Lorentzon, Robert Luben, Michel Marre, Yuri Milaneschi, Keri L Monda, Grant W Montgomery, Marleen H M De Moor, Antonella Mulas, Martina Müller-Nurasyid, A W Musk, Reija Männikkö, Satu Männistö, Narisu Narisu, Matthias Nauck, Jennifer A Nettleton, Ilja M Nolte, Albertine J Oldehinkel, Matthias Olden, Ken K Ong, Sandosh Padmanabhan, Lavinia Paternoster, Jeremiah Perez, Markus Perola, Annette Peters, Ulrike Peters, Patricia A Peyser, Inga Prokopenko, Hannu Puolijoki, Olli T Raitakari, Tuomo Rankinen, Laura J Rasmussen-Torvik, Rajesh Rawal, Paul M Ridker, Lynda M Rose, Igor Rudan, Cinzia Sarti, Mark A Sarzynski, Kai Savonen, William R Scott, Serena Sanna, Alan R Shuldiner, Steve Sidney, Günther Silbernagel, Blair H Smith, Jennifer A Smith, Harold Snieder, Alena Stančáková, Barbara Sternfeld, Amy J Swift, Tuija Tammelin, Sian-Tsung Tan, Barbara Thorand, Dorothée Thuillier, Liesbeth Vandenput, Henrik Vestergaard, Jana V van Vliet-Ostaptchouk, Marie-Claude Vohl, Uwe Völker, Gérard Waeber, Mark Walker, Sarah Wild, Andrew Wong, Alan F Wright, M Carola Zillikens, Niha Zubair, Christopher A Haiman, Loic Lemarchand, Ulf Gyllensten, Claes Ohlsson, Albert Hofman, Fernando Rivadeneira, André G Uitterlinden, Louis Pérusse, James F Wilson, Caroline Hayward, Ozren Polasek, Francesco Cucca, Kristian Hveem, Catharina A Hartman, Anke Tönjes, Stefania Bandinelli, Lyle J Palmer, Sharon L R Kardia, Rainer Rauramaa, Thorkild I A Sørensen, Jaakko Tuomilehto, Veikko Salomaa, Brenda W J H Penninx, Eco J C de Geus, Dorret I Boomsma, Terho Lehtimäki, Massimo Mangino, Markku Laakso, Claude Bouchard, Nicholas G Martin, Diana Kuh, Yongmei Liu, Allan Linneberg, Winfried März, Konstantin Strauch, Mika Kivimäki, Tamara B Harris, Vilmundur Gudnason, Henry Völzke, Lu Qi, Marjo-Riitta Järvelin, John C Chambers, Jaspal S Kooner, Philippe Froguel, Charles Kooperberg, Peter Vollenweider, Göran Hallmans, Torben Hansen, Oluf Pedersen, Andres Metspalu, Nicholas J Wareham, Claudia Langenberg, David R Weir, David J Porteous, Eric Boerwinkle, Daniel I Chasman, CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Gonçalo R Abecasis, Inês Barroso, Mark I McCarthy, Timothy M Frayling, Jeffrey R O'Connell, Cornelia M van Duijn, Michael Boehnke, Iris M Heid, Karen L Mohlke, David P Strachan, Caroline S Fox, Ching-Ti Liu, Joel N Hirschhorn, Robert J Klein, Andrew D Johnson, Ingrid B Borecki, Paul W Franks, Kari E North, L Adrienne Cupples, Ruth J F Loos, and Tuomas O Kilpeläinen

Subjects
Genetics, QH426-470
Abstract

[This corrects the article DOI: 10.1371/journal.pgen.1006528.].

Published
2017
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11. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults.

Author

Mariaelisa Graff, Robert A Scott, Anne E Justice, Kristin L Young, Mary F Feitosa, Llilda Barata, Thomas W Winkler, Audrey Y Chu, Anubha Mahajan, David Hadley, Luting Xue, Tsegaselassie Workalemahu, Nancy L Heard-Costa, Marcel den Hoed, Tarunveer S Ahluwalia, Qibin Qi, Julius S Ngwa, Frida Renström, Lydia Quaye, John D Eicher, James E Hayes, Marilyn Cornelis, Zoltan Kutalik, Elise Lim, Jian'an Luan, Jennifer E Huffman, Weihua Zhang, Wei Zhao, Paula J Griffin, Toomas Haller, Shafqat Ahmad, Pedro M Marques-Vidal, Stephanie Bien, Loic Yengo, Alexander Teumer, Albert Vernon Smith, Meena Kumari, Marie Neergaard Harder, Johanne Marie Justesen, Marcus E Kleber, Mette Hollensted, Kurt Lohman, Natalia V Rivera, John B Whitfield, Jing Hua Zhao, Heather M Stringham, Leo-Pekka Lyytikäinen, Charlotte Huppertz, Gonneke Willemsen, Wouter J Peyrot, Ying Wu, Kati Kristiansson, Ayse Demirkan, Myriam Fornage, Maija Hassinen, Lawrence F Bielak, Gemma Cadby, Toshiko Tanaka, Reedik Mägi, Peter J van der Most, Anne U Jackson, Jennifer L Bragg-Gresham, Veronique Vitart, Jonathan Marten, Pau Navarro, Claire Bellis, Dorota Pasko, Åsa Johansson, Søren Snitker, Yu-Ching Cheng, Joel Eriksson, Unhee Lim, Mette Aadahl, Linda S Adair, Najaf Amin, Beverley Balkau, Juha Auvinen, John Beilby, Richard N Bergman, Sven Bergmann, Alain G Bertoni, John Blangero, Amélie Bonnefond, Lori L Bonnycastle, Judith B Borja, Søren Brage, Fabio Busonero, Steve Buyske, Harry Campbell, Peter S Chines, Francis S Collins, Tanguy Corre, George Davey Smith, Graciela E Delgado, Nicole Dueker, Marcus Dörr, Tapani Ebeling, Gudny Eiriksdottir, Tõnu Esko, Jessica D Faul, Mao Fu, Kristine Færch, Christian Gieger, Sven Gläser, Jian Gong, Penny Gordon-Larsen, Harald Grallert, Tanja B Grammer, Niels Grarup, Gerard van Grootheest, Kennet Harald, Nicholas D Hastie, Aki S Havulinna, Dena Hernandez, Lucia Hindorff, Lynne J Hocking, Oddgeir L Holmens, Christina Holzapfel, Jouke Jan Hottenga, Jie Huang, Tao Huang, Jennie Hui, Cornelia Huth, Nina Hutri-Kähönen, Alan L James, John-Olov Jansson, Min A Jhun, Markus Juonala, Leena Kinnunen, Heikki A Koistinen, Ivana Kolcic, Pirjo Komulainen, Johanna Kuusisto, Kirsti Kvaløy, Mika Kähönen, Timo A Lakka, Lenore J Launer, Benjamin Lehne, Cecilia M Lindgren, Mattias Lorentzon, Robert Luben, Michel Marre, Yuri Milaneschi, Keri L Monda, Grant W Montgomery, Marleen H M De Moor, Antonella Mulas, Martina Müller-Nurasyid, A W Musk, Reija Männikkö, Satu Männistö, Narisu Narisu, Matthias Nauck, Jennifer A Nettleton, Ilja M Nolte, Albertine J Oldehinkel, Matthias Olden, Ken K Ong, Sandosh Padmanabhan, Lavinia Paternoster, Jeremiah Perez, Markus Perola, Annette Peters, Ulrike Peters, Patricia A Peyser, Inga Prokopenko, Hannu Puolijoki, Olli T Raitakari, Tuomo Rankinen, Laura J Rasmussen-Torvik, Rajesh Rawal, Paul M Ridker, Lynda M Rose, Igor Rudan, Cinzia Sarti, Mark A Sarzynski, Kai Savonen, William R Scott, Serena Sanna, Alan R Shuldiner, Steve Sidney, Günther Silbernagel, Blair H Smith, Jennifer A Smith, Harold Snieder, Alena Stančáková, Barbara Sternfeld, Amy J Swift, Tuija Tammelin, Sian-Tsung Tan, Barbara Thorand, Dorothée Thuillier, Liesbeth Vandenput, Henrik Vestergaard, Jana V van Vliet-Ostaptchouk, Marie-Claude Vohl, Uwe Völker, Gérard Waeber, Mark Walker, Sarah Wild, Andrew Wong, Alan F Wright, M Carola Zillikens, Niha Zubair, Christopher A Haiman, Loic Lemarchand, Ulf Gyllensten, Claes Ohlsson, Albert Hofman, Fernando Rivadeneira, André G Uitterlinden, Louis Pérusse, James F Wilson, Caroline Hayward, Ozren Polasek, Francesco Cucca, Kristian Hveem, Catharina A Hartman, Anke Tönjes, Stefania Bandinelli, Lyle J Palmer, Sharon L R Kardia, Rainer Rauramaa, Thorkild I A Sørensen, Jaakko Tuomilehto, Veikko Salomaa, Brenda W J H Penninx, Eco J C de Geus, Dorret I Boomsma, Terho Lehtimäki, Massimo Mangino, Markku Laakso, Claude Bouchard, Nicholas G Martin, Diana Kuh, Yongmei Liu, Allan Linneberg, Winfried März, Konstantin Strauch, Mika Kivimäki, Tamara B Harris, Vilmundur Gudnason, Henry Völzke, Lu Qi, Marjo-Riitta Järvelin, John C Chambers, Jaspal S Kooner, Philippe Froguel, Charles Kooperberg, Peter Vollenweider, Göran Hallmans, Torben Hansen, Oluf Pedersen, Andres Metspalu, Nicholas J Wareham, Claudia Langenberg, David R Weir, David J Porteous, Eric Boerwinkle, Daniel I Chasman, CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Gonçalo R Abecasis, Inês Barroso, Mark I McCarthy, Timothy M Frayling, Jeffrey R O'Connell, Cornelia M van Duijn, Michael Boehnke, Iris M Heid, Karen L Mohlke, David P Strachan, Caroline S Fox, Ching-Ti Liu, Joel N Hirschhorn, Robert J Klein, Andrew D Johnson, Ingrid B Borecki, Paul W Franks, Kari E North, L Adrienne Cupples, Ruth J F Loos, and Tuomas O Kilpeläinen

Subjects
Genetics, QH426-470
Abstract

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Published
2017
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12. MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies.

Author

Toomas Haller, Liis Leitsalu, Krista Fischer, Marja-Liisa Nuotio, Tõnu Esko, Dorothea Irene Boomsma, Kirsten Ohm Kyvik, Tim D Spector, Markus Perola, and Andres Metspalu

Subjects
Medicine, Science
Abstract

Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

Published
2017
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13. Modulation of genetic associations with serum urate levels by body-mass-index in humans.

Author

Jennifer E Huffman, Eva Albrecht, Alexander Teumer, Massimo Mangino, Karen Kapur, Toby Johnson, Zoltán Kutalik, Nicola Pirastu, Giorgio Pistis, Lorna M Lopez, Toomas Haller, Perttu Salo, Anuj Goel, Man Li, Toshiko Tanaka, Abbas Dehghan, Daniela Ruggiero, Giovanni Malerba, Albert V Smith, Ilja M Nolte, Laura Portas, Amanda Phipps-Green, Lora Boteva, Pau Navarro, Asa Johansson, Andrew A Hicks, Ozren Polasek, Tõnu Esko, John F Peden, Sarah E Harris, Federico Murgia, Sarah H Wild, Albert Tenesa, Adrienne Tin, Evelin Mihailov, Anne Grotevendt, Gauti K Gislason, Josef Coresh, Pio D'Adamo, Sheila Ulivi, Peter Vollenweider, Gerard Waeber, Susan Campbell, Ivana Kolcic, Krista Fisher, Margus Viigimaa, Jeffrey E Metter, Corrado Masciullo, Elisabetta Trabetti, Cristina Bombieri, Rossella Sorice, Angela Döring, Eva Reischl, Konstantin Strauch, Albert Hofman, Andre G Uitterlinden, Melanie Waldenberger, H-Erich Wichmann, Gail Davies, Alan J Gow, Nicola Dalbeth, Lisa Stamp, Johannes H Smit, Mirna Kirin, Ramaiah Nagaraja, Matthias Nauck, Claudia Schurmann, Kathrin Budde, Susan M Farrington, Evropi Theodoratou, Antti Jula, Veikko Salomaa, Cinzia Sala, Christian Hengstenberg, Michel Burnier, Reedik Mägi, Norman Klopp, Stefan Kloiber, Sabine Schipf, Samuli Ripatti, Stefano Cabras, Nicole Soranzo, Georg Homuth, Teresa Nutile, Patricia B Munroe, Nicholas Hastie, Harry Campbell, Igor Rudan, Claudia Cabrera, Chris Haley, Oscar H Franco, Tony R Merriman, Vilmundur Gudnason, Mario Pirastu, Brenda W Penninx, Harold Snieder, Andres Metspalu, Marina Ciullo, Peter P Pramstaller, Cornelia M van Duijn, Luigi Ferrucci, Giovanni Gambaro, Ian J Deary, Malcolm G Dunlop, James F Wilson, Paolo Gasparini, Ulf Gyllensten, Tim D Spector, Alan F Wright, Caroline Hayward, Hugh Watkins, Markus Perola, Murielle Bochud, W H Linda Kao, Mark Caulfield, Daniela Toniolo, Henry Völzke, Christian Gieger, Anna Köttgen, and Veronique Vitart

Subjects
Medicine, Science
Abstract

We tested for interactions between body mass index (BMI) and common genetic variants affecting serum urate levels, genome-wide, in up to 42569 participants. Both stratified genome-wide association (GWAS) analyses, in lean, overweight and obese individuals, and regression-type analyses in a non BMI-stratified overall sample were performed. The former did not uncover any novel locus with a major main effect, but supported modulation of effects for some known and potentially new urate loci. The latter highlighted a SNP at RBFOX3 reaching genome-wide significant level (effect size 0.014, 95% CI 0.008-0.02, Pinter= 2.6 x 10-8). Two top loci in interaction term analyses, RBFOX3 and ERO1LB-EDARADD, also displayed suggestive differences in main effect size between the lean and obese strata. All top ranking loci for urate effect differences between BMI categories were novel and most had small magnitude but opposite direction effects between strata. They include the locus RBMS1-TANK (men, Pdifflean-overweight= 4.7 x 10-8), a region that has been associated with several obesity related traits, and TSPYL5 (men, Pdifflean-overweight= 9.1 x 10-8), regulating adipocytes-produced estradiol. The top-ranking known urate loci was ABCG2, the strongest known gout risk locus, with an effect halved in obese compared to lean men (Pdifflean-obese= 2 x 10-4). Finally, pathway analysis suggested a role for N-glycan biosynthesis as a prominent urate-associated pathway in the lean stratum. These results illustrate a potentially powerful way to monitor changes occurring in obesogenic environment.

Published
2015
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14. Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17,345 persons.

Author

Krista Fischer, Johannes Kettunen, Peter Würtz, Toomas Haller, Aki S Havulinna, Antti J Kangas, Pasi Soininen, Tõnu Esko, Mari-Liis Tammesoo, Reedik Mägi, Steven Smit, Aarno Palotie, Samuli Ripatti, Veikko Salomaa, Mika Ala-Korpela, Markus Perola, and Andres Metspalu

Subjects
Medicine
Abstract

BackgroundEarly identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts.Methods and findings106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18-103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1-standard deviation increment, 95% CI 1.53-1.82, p = 5×10⁻³¹), albumin (HR 0.70, 95% CI 0.65-0.76, p = 2×10⁻¹⁸), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62-0.77, p = 3×10⁻¹²), and citrate (HR 1.33, 95% CI 1.21-1.45, p = 5×10⁻¹⁰). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001).ConclusionsBiomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention.

Published
2014
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15. A new polygenic score for refractive error improves detection of children at risk of high myopia but not the prediction of those at risk of myopic macular degeneration

Author

Rosie Clark, Samantha Sze-Yee Lee, Ran Du, Yining Wang, Sander C.M. Kneepkens, Jason Charng, Yu Huang, Michael L. Hunter, Chen Jiang, J.Willem L. Tideman, Ronald B. Melles, Caroline C.W. Klaver, David A. Mackey, Cathy Williams, Hélène Choquet, Kyoko Ohno-Matsui, Jeremy A. Guggenheim, Joan E. Bailey-Wilson, Paul N. Baird, Veluchamy A. Barathi, Ginevra Biino, Kathryn P. Burdon, Harry Campbell, Li Jia Chen, Ching-Yu Cheng, Emily Y. Chew, Jamie E. Craig, Margaret M. Deangelis, Cécile Delcourt, Xiaohu Ding, Qiao Fan, Maurizio Fossarello, Paul J. Foster, Puya Gharahkhani, Xiaobo Guo, Annechien E.G. Haarman, Toomas Haller, Christopher J. Hammond, Xikun Han, Caroline Hayward, Mingguang He, Alex W. Hewitt, Quan Hoang, Pirro G. Hysi, Adriana I. Iglesias, Robert P. Igo, Sudha K. Iyengar, Jost B. Jonas, Mika Kähönen, Jaakko Kaprio, Anthony P. Khawaja, Barbara E. Klein, Jonathan H. Lass, Kris Lee, Terho Lehtimäki, Deyana Lewis, Qing Li, Shi-Ming Li, Leo-Pekka Lyytikäinen, Stuart MacGregor, Nicholas G. Martin, Akira Meguro, Andres Metspalu, Candace Middlebrooks, Masahiro Miyake, Nobuhisa Mizuki, Anthony Musolf, Stefan Nickels, Konrad Oexle, Chi Pui Pang, Olavi Pärssinen, Andrew D. Paterson, Norbert Pfeiffer, Ozren Polasek, Jugnoo S. Rahi, Olli Raitakari, Igor Rudan, Srujana Sahebjada, Seang-Mei Saw, Claire L. Simpson, Dwight Stambolian, E-Shyong Tai, Milly S. Tedja, J. Willem L. Tideman, Akitaka Tsujikawa, Cornelia M. van Duijn, Virginie J.M. Verhoeven, Veronique Vitart, Ningli Wang, Ya Xing Wang, Juho Wedenoja, Wen Bin Wei, Katie M. Williams, James F. Wilson, Robert Wojciechowski, Jason C.S. Yam, Kenji Yamashiro, Maurice K.H. Yap, Seyhan Yazar, Shea Ping Yip, Terri L. Young, Xiangtian Zhou, Naomi Allen, Tariq Aslam, Denize Atan, Sarah Barman, Jenny Barrett, Paul Bishop, Graeme Black, Catey Bunce, Roxana Carare, Usha Chakravarthy, Michelle Chan, Sharon Chua, Valentina Cipriani, Alexander Day, Parul Desai, Bal Dhillon, Andrew Dick, Alexander Doney, Cathy Egan, Sarah Ennis, Paul Foster, Marcus Fruttiger, John Gallacher, David Garway-Heath, Jane Gibson, Dan Gore, Jeremy Guggenheim, Chris Hammond, Alison Hardcastle, Simon Harding, Ruth Hogg, Pirro Hysi, Pearse A. Keane, Peng Tee Khaw, Anthony Khawaja, Gerassimos Lascaratos, Thomas Littlejohns, Andrew Lotery, Phil Luthert, Tom MacGillivray, Sarah Mackie, Bernadette McGuinness, Gareth McKay, Martin McKibbin, Danny Mitry, Tony Moore, James Morgan, Zaynah Muthy, Eoin O'Sullivan, Chris Owen, Praveen Patel, Euan Paterson, Tunde Peto, Axel Petzold, Nikolas Pontikos, Jugnoo Rahi, Alicja Rudnicka, Jay Self, Panagiotis Sergouniotis, Sobha Sivaprasad, David Steel, Irene Stratton, Nicholas Strouthidis, Cathie Sudlow, Robyn Tapp, Caroline Thaung, Dhanes Thomas, Emanuele Trucco, Adnan Tufail, Stephen Vernon, Ananth Viswanathan, Katie Williams, Jayne Woodside, Max Yates, Jennifer Yip, Yalin Zheng, Neurology, Ophthalmology, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Neuroinfection & -inflammation, Epidemiology, Clinical Genetics, and Erasmus MC other

Subjects
All institutes and research themes of the Radboud University Medical Center, General Medicine, General Biochemistry, Genetics and Molecular Biology, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12]
Abstract

Contains fulltext : 292919.pdf (Publisher’s version ) (Open Access) BACKGROUND: High myopia (HM), defined as a spherical equivalent refractive error (SER) ≤ -6.00 diopters (D), is a leading cause of sight impairment, through myopic macular degeneration (MMD). We aimed to derive an improved polygenic score (PGS) for predicting children at risk of HM and to test if a PGS is predictive of MMD after accounting for SER. METHODS: The PGS was derived from genome-wide association studies in participants of UK Biobank, CREAM Consortium, and Genetic Epidemiology Research on Adult Health and Aging. MMD severity was quantified by a deep learning algorithm. Prediction of HM was quantified as the area under the receiver operating curve (AUROC). Prediction of severe MMD was assessed by logistic regression. FINDINGS: In independent samples of European, African, South Asian and East Asian ancestry, the PGS explained 19% (95% confidence interval 17-21%), 2% (1-3%), 8% (7-10%) and 6% (3-9%) of the variation in SER, respectively. The AUROC for HM in these samples was 0.78 (0.75-0.81), 0.58 (0.53-0.64), 0.71 (0.69-0.74) and 0.67 (0.62-0.72), respectively. The PGS was not associated with the risk of MMD after accounting for SER: OR = 1.07 (0.92-1.24). INTERPRETATION: Performance of the PGS approached the level required for clinical utility in Europeans but not in other ancestries. A PGS for refractive error was not predictive of MMD risk once SER was accounted for. FUNDING: Supported by the Welsh Government and Fight for Sight (24WG201).

Published
2023

16. Mapping of the gene network that regulates glycan clock of ageing

Author

Azra Frkatović-Hodžić, Karlo Miškec, Anika Mijakovac, Arina Nostaeva, Sodbo Z. Sharapov, Arianna Landini, Toomas Haller, Erik van den Akker, Sapna Sharma, Rafael R. C. Cuadrat, Massimo Mangino, Yong Li, Toma Keser, Najda Rudman, Tamara Štambuk, Maja Pučić-Baković, Irena Trbojević-Akmačić, Ivan Gudelj, Jerko Štambuk, Tea Pribić, Barbara Radovani, Petra Tominac, Krista Fischer, Marian Beekman, Manfred Wuhrer, Christian Gieger, Matthias B. Schulze, Clemens Wittenbecher, Ozren Polasek, Caroline Hayward, James F. Wilson, Tim D. Spector, Anna Köttgen, Frano Vučković, Yurii S. Aulchenko, Aleksandar Vojta, Jasminka Krištić, Lucija Klarić, Vlatka Zoldoš, and Gordan Lauc

Abstract

Glycans are an essential structural component of Immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation). We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in thein vitroIgG expression system. Up- and downregulation of three genes,EEF1A1, MANBAandTNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in thisin vitroexpression system.

Published
2023

17. Untargeted metabolomics profiling in pediatric patients and adult populations indicates a connection between lipid imbalance and epilepsy

Author

Kaisa Teele Oja, Mihkel Ilisson, Karit Reinson, Kai Muru, Tiia Reimand, Hedi Peterson, Dmytro Fishman, Tõnu Esko, Toomas Haller, Jaanika Kronberg, Monica H. Wojcik, Adam Kennedy, Gregory Michelotti, Anne O’Donnell-Luria, Eve Õiglane-Šlik, Sander Pajusalu, and Katrin Õunap

Subjects
Article
Abstract

IntroductionEpilepsy is a common central nervous system disorder characterized by abnormal brain electrical activity. We aimed to compare the metabolic profiles of plasma from patients with epilepsy across different etiologies, seizure frequency, seizure type, and patient age to try to identify common disrupted pathways.Material and methodsWe used data from three separate cohorts. The first cohort (PED-C) consisted of 31 pediatric patients with suspicion of a genetic disorder with unclear etiology; the second cohort (AD-C) consisted of 250 adults from the Estonian Biobank (EstBB), and the third cohort consisted of 583 adults ≥ 69 years of age from the EstBB (ELD-C). We compared untargeted metabolomics and lipidomics data between individuals with and without epilepsy in each cohort.ResultsIn the PED-C, significant alterations (p-value ConclusionOur results suggest that cell membrane fluidity may have a significant role in the mechanism of epilepsy, and changes in lipid balance may indicate epilepsy. However, further studies are needed to evaluate whether untargeted metabolomics analysis could prove helpful in diagnosing epilepsy earlier.

Published
2023

19. Ancestry deconvolution and partial polygenic score can improve susceptibility predictions in recently admixed individuals

Author

Kristi Läll, Luca Pagani, Davide Marnetto, Francesco Montinaro, Katri Pärna, Krista Fischer, Reedik Mägi, Ludovica Molinaro, Toomas Haller, and Mait Metspalu

Subjects
0301 basic medicine, Multifactorial Inheritance, Genotype, Science, Population, Predictive medicine, General Physics and Astronomy, GENETIC RISK, Biology, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, 0302 clinical medicine, Genetic, Models, Genetics, Humans, Genetic Predisposition to Disease, Genetic variation, Allele, education, lcsh:Science, Genetic association study, education.field_of_study, Multidisciplinary, Models, Genetic, RISK PREDICTION, General Chemistry, ASSOCIATION, eye diseases, 3. Good health, 030104 developmental biology, Genetics, Population, Phenotype, Evolutionary biology, Trait, lcsh:Q, Deconvolution, 030217 neurology & neurosurgery
Abstract

Polygenic Scores (PSs) describe the genetic component of an individual’s quantitative phenotype or their susceptibility to diseases with a genetic basis. Currently, PSs rely on population-dependent contributions of many associated alleles, with limited applicability to understudied populations and recently admixed individuals. Here we introduce a combination of local ancestry deconvolution and partial PS computation to account for the population-specific nature of the association signals in individuals with admixed ancestry. We demonstrate partial PS to be a proxy for the total PS and that a portion of the genome is enough to improve susceptibility predictions for the traits we test. By combining partial PSs from different populations, we are able to improve trait predictability in admixed individuals with some European ancestry. These results may extend the applicability of PSs to subjects with a complex history of admixture, where current methods cannot be applied., Polygenic scores are believed to hold future promise for trait prediction and personalized medicine, but are sensitive to demographic history. Here, Marnetto et al. develop partial polygenic scores supplemented with local ancestry deconvolution which improves prediction accuracy into recently admixed European populations.

Published
2020

20. Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example

Author

Harold Snieder, Liis Leitsalu, Toomas Haller, Bram P. Prins, Katri Pärna, Krista Fischer, Andres Metspalu, Prins, Bram Peter [0000-0001-5774-034X], Leitsalu, Liis [0000-0001-7616-5440], Pärna, Katri [0000-0002-0013-6077], Fischer, Krista [0000-0002-3521-0599], Snieder, Harold [0000-0003-1949-2298], and Apollo - University of Cambridge Repository

Subjects
Estonia, GENETICS, DATABASE, CHROMOSOME, Computer science, Genomic data, Genomic research, Medicine (miscellaneous), Review, Disease, VARIANTS, SUSCEPTIBILITY, GWAS DATA, 03 medical and health sciences, 0302 clinical medicine, Health care, patient communication, 030304 developmental biology, 0303 health sciences, business.industry, ASSOCIATION, FRAMEWORK, Data science, Biobank, return of results, biobank, genomic medicine, Medicine, Patient communication, HEALTH, Personalized medicine, business, Return of results, genetic discovery, 030217 neurology & neurosurgery
Abstract

The current paradigm of personalized medicine envisages the use of genomic data to provide predictive information on the health course of an individual with the aim of prevention and individualized care. However, substantial efforts are required to realize the concept: enhanced genetic discoveries, translation into intervention strategies, and a systematic implementation in healthcare. Here we review how further genetic discoveries are improving personalized prediction and advance functional insights into the link between genetics and disease. In the second part we give our perspective on the way these advances in genomic research will transform the future of personalized prevention and medicine using Estonia as a primer.

Published
2021
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21. Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics

Author

Toomas Haller, Gert-Jan B. van Ommen, B. H. C. Stricker, Andres Metspalu, Eivind Ness-Jensen, Satu Männistö, Jelle J. Goeman, Kairit Mikkel, Olga Veth, Neeme Tõnisson, Rikje Ruiter, Cornelia M. van Duijn, Casper H.J. van Eijck, Jesse Fest, Kristian Hveem, Markus Perola, Peter A C 't Hoen, Arfan Ikram, Anni Joensuu, Lisanne S. Vijfhuizen, Surgery, Neurology, Epidemiology, Quantitative Genetics, CAMM - Research Program for Clinical and Molecular Metabolism, Research Programs Unit, University of Helsinki, Faculty of Medicine, and University Management

Subjects
0301 basic medicine, Oncology, Male, LIVER, Magnetic Resonance Spectroscopy, Glutamine, Logistic regression, Rotterdam Study, Endocrinology, 0302 clinical medicine, EPIDEMIOLOGY, Hormones and Cancer, Stage (cooking), Research Articles, Biological Specimen Banks, 2. Zero hunger, 0303 health sciences, education.field_of_study, Middle Aged, Biobank, 3. Good health, Europe, 030220 oncology & carcinogenesis, Cohort, SURVIVAL, Biomarker (medicine), Female, medicine.medical_specialty, Population, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Internal medicine, Pancreatic cancer, medicine, Biomarkers, Tumor, Humans, Metabolomics, Histidine, education, 030304 developmental biology, Aged, business.industry, Case-control study, ROTTERDAM, medicine.disease, Pancreatic Neoplasms, 030104 developmental biology, Early Diagnosis, Case-Control Studies, 3111 Biomedicine, business, Body mass index, Nanomedicine Radboud Institute for Molecular Life Sciences [Radboudumc 19], Blood sampling
Abstract

Background and aimMost patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer.MethodsThe low incidence rate complicates prospective biomarker studies. Here, we took advantage of the availability of biobanked samples from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian biobank, Rotterdam Study) and identified prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between one month and seventeen years after blood sampling, and compared these with age- and gender-matched controls from the same cohorts. We applied1H-NMR-based metabolomics on the Nightingale platform on these samples and applied logistic regression to assess the predictive value of individual metabolite concentrations, with gender, age, body mass index, smoking status, type 2 diabetes mellitus status, fasting status, and cohort as covariates.ResultsAfter quality assessment, we retained 356 cases and 887 controls. We identified two interesting hits, glutamine (p=0.011) and histidine (p=0.012), and obtained Westfall-Young family-wise error rate adjusted p-values of 0.43 for both. Stratification in quintiles showed a 1.5x elevated risk for the lowest 20% of glutamine and a 2.2x increased risk for the lowest 20% of histidine. Stratification by time to diagnosis (5 years) suggested glutamine to be involved in an earlier process, tapering out closer to onset, and histidine in a process closer to the actual onset. Lasso-penalized logistic regression showed a slight improvement of the area under the Receiver Operator Curves when including glutamine and histidine in the model. Finally, our data did not support the earlier identified branched-chain amino acids as potential biomarkers for pancreatic cancer in several American cohorts.ConclusionWhile identifying glutamine and histidine as early biomarkers of potential biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically usefulper seas prognostic biomarkers.

Published
2019

22. Genome-Wide Association Scan of Serum Urea in European Populations Identifies Two Novel Loci

Author

Peter J. van der Most, Zoha Kamali, Johannes H. Smit, Toomas Haller, Brenda W.J.H. Penninx, Evelin Mihailov, Anna Reznichenko, Harold Snieder, Jeffrey Damman, Ahmad Vaez, Pim van der Harst, Gerjan Navis, Martin H. de Borst, Chris H. L. Thio, Ron T. Gansevoort, Niek Verweij, Andres Metspalu, Ilja M. Nolte, Groningen Kidney Center (GKC), Lifestyle Medicine (LM), Cardiovascular Centre (CVC), Value, Affordability and Sustainability (VALUE), Life Course Epidemiology (LCE), Groningen Institute for Organ Transplantation (GIOT), Psychiatry, APH - Mental Health, APH - Methodology, and APH - Digital Health

Subjects
RENAL-FUNCTION, Quantitative Trait Loci, 030232 urology & nephrology, Renal function, Genome-wide association study, Single-nucleotide polymorphism, SUSCEPTIBILITY, 030204 cardiovascular system & hematology, Kidney, Genome-wide association studies, Polymorphism, Single Nucleotide, Serum urea, KIDNEY-FUNCTION, White People, 03 medical and health sciences, Kidney function, 0302 clinical medicine, Reference Values, TOOL, Humans, Urea, Medicine, Gene, METAANALYSIS, Genetic association, Genetics, business.industry, Haplotype, Computational Biology, TARGET, Nephrology, Expression quantitative trait loci, MAP, Trait, HAPLOTYPES, business, TRAITS, Metabolic Networks and Pathways, Genome-Wide Association Study
Abstract

Background: Serum urea level is a heritable trait, commonly used as a diagnostic marker for kidney function. Genome-wide association studies (GWAS) in East-Asian populations identified a number of genetic loci related to serum urea, however there is a paucity of data for European populations. Methods: We performed a two-stage meta-analysis of GWASs on serum urea in 13,312 participants, with independent replication in 7,379 participants of European ancestry. Results: We identified 6 genome-wide significant single nucleotide polymorphisms (SNPs) in or near 6 loci, of which 2 were novel (POU2AF1 and ADAMTS9-AS2). Replication of East-Asian and Scottish data provided evidence for an additional 8 loci. SNPs tag regions previously associated with anthropometric traits, serum magnesium, and urinary albumin-to-creatinine ratio, as well as expression quantitative trait loci for genes preferentially expressed in kidney and gastro-intestinal tissues. Conclusions: Our findings provide insights into the genetic underpinnings of urea metabolism, with potential relevance to kidney function.

Published
2019

23. Manhattan Harvester and Cropper: a system for GWAS peak detection

Author

Andres Metspalu, Toomas Haller, and Tõnis Tasa

Subjects
Computer science, computer.software_genre, lcsh:Computer applications to medicine. Medical informatics, Polymorphism, Single Nucleotide, Biochemistry, Manhattan plot, Manhattan plots, 03 medical and health sciences, 0302 clinical medicine, Structural Biology, Computer Graphics, Data Mining, Humans, GWAS, Molecular Biology, lcsh:QH301-705.5, 030304 developmental biology, 0303 health sciences, Peak detection, Peak quality score, Applied Mathematics, Genomics, Computer Science Applications, Phenotype, lcsh:Biology (General), Data Interpretation, Statistical, 030220 oncology & carcinogenesis, lcsh:R858-859.7, Data mining, computer, Software, Genome-Wide Association Study
Abstract

Background Selection of interesting regions from genome wide association studies (GWAS) is typically performed by eyeballing of Manhattan Plots. This is no longer possible with thousands of different phenotypes. There is a need for tools that can automatically detect genomic regions that correspond to what the experienced researcher perceives as peaks worthwhile of further study. Results We developed Manhattan Harvester, a tool designed for “peak extraction” from GWAS summary files and computation of parameters characterizing various aspects of individual peaks. We present the algorithms used and a model for creating a general quality score that evaluates peaks similarly to that of a human researcher. Our tool Cropper utilizes a graphical interface for inspecting, cropping and subsetting Manhattan Plot regions. Cropper is used to validate and visualize the regions detected by Manhattan Harvester. Conclusions We conclude that our tools fill the current void in automatically screening large number of GWAS output files in batch mode. The interesting regions are detected and quantified by various parameters by Manhattan Harvester. Cropper offers graphical tools for in-depth inspection of the regions. The tools are open source and freely available. Electronic supplementary material The online version of this article (10.1186/s12859-019-2600-4) contains supplementary material, which is available to authorized users.

Published
2019

24. Association analysis of juvenile idiopathic arthritis genetic susceptibility factors in Estonian patients

Author

Chris Pruunsild, Mare Saag, Toomas Haller, Priit Niibo, Andres Metspalu, Tiit Nikopensius, Triin Jagomägi, Neeme Tõnisson, and Ülle Voog-Oras

Subjects
0301 basic medicine, musculoskeletal diseases, Estonia, medicine.medical_specialty, Genome-wide association study, genetic structures, Arthritis, Human leukocyte antigen, CLEC16A, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, Rheumatology, immune system diseases, Internal medicine, medicine, Genetic predisposition, Humans, Genetic Predisposition to Disease, Rheumatoid arthritis, skin and connective tissue diseases, Genetic association, 030203 arthritis & rheumatology, business.industry, General Medicine, Juvenile idiopathic arthritis, medicine.disease, Arthritis, Juvenile, 030104 developmental biology, Case-Control Studies, Immunology, Original Article, business
Abstract

Background Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition of childhood. Genetic association studies have revealed several JIA susceptibility loci with the strongest effect size observed in the human leukocyte antigen (HLA) region. Genome-wide association studies have augmented the number of JIA-associated loci, particularly for non-HLA genes. The aim of this study was to identify new associations at non-HLA loci predisposing to the risk of JIA development in Estonian patients. Methods We performed genome-wide association analyses in an entire JIA case–control sample (All-JIA) and in a case–control sample for oligoarticular JIA, the most prevalent JIA subtype. The entire cohort was genotyped using the Illumina HumanOmniExpress BeadChip arrays. After imputation, 16,583,468 variants were analyzed in 263 cases and 6956 controls. Results We demonstrated nominal evidence of association for 12 novel non-HLA loci not previously implicated in JIA predisposition. We replicated known JIA associations in CLEC16A and VCTN1 regions in the oligoarticular JIA sample. The strongest associations in the All-JIA analysis were identified at PRKG1 (P = 2,54 × 10−6), LTBP1 (P = 9,45 × 10−6), and ELMO1 (P = 1,05 × 10−5). In the oligoarticular JIA analysis, the strongest associations were identified at NFIA (P = 5,05 × 10−6), LTBP1 (P = 9,95 × 10−6), MX1 (P = 1,65 × 10−5), and CD200R1 (P = 2,59 × 10−5). Conclusion This study increases the number of known JIA risk loci and provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis. The reported loci are involved in molecular pathways of immunological relevance and likely represent genomic regions that confer susceptibility to JIA in Estonian patients. Key Points• Juvenile idiopathic arthritis (JIA) is the most common childhood rheumatic disease with heterogeneous presentation and genetic predisposition.• Present genome-wide association study for Estonian JIA patients is first of its kind in Northern and Northeastern Europe.• The results of the present study increase the knowledge about JIA risk loci replicating some previously described associations, so adding weight to their relevance and describing novel loci.• The study provides additional evidence for the existence of overlapping genetic risk loci between JIA and other autoimmune diseases, particularly rheumatoid arthritis.

Published
2021

25. Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium

Author

Krista Fischer, P. Eline Slagboom, Massimo Mangino, Aaron Isaacs, Christian Gieger, Marian Beekman, Joris Deelen, Diana van Heemst, Sarah E. Medland, Nilesh J. Samani, Nicholas G. Martin, Toomas Haller, Veryan Codd, Cornelia M. van Duijn, René Pool, Najaf Amin, Dale R. Nyholt, Ashley van der Spek, Idil Yet, Rui Wang-Sattler, Dorret I. Boomsma, Harmen Draisma, Ayse Demirkan, Linda Broer, Eva Albrecht, Andres Metspalu, Simon P. Mooijaart, Tim D. Spector, H. Eka D. Suchiman, Anjali K. Henders, John Whitfield, Konstantin Strauch, Anika A. M. Vaarhorst, Mait Raag, Harish Dharuri, Margaret J. Wright, Gonneke Willemsen, Eco J. C. de Geus, Grant W. Montgomery, RS: FHML MaCSBio, RS: CARIM - R1 - Thrombosis and haemostasis, Biochemie, RS: Carim - B01 Blood proteins & engineering, Epidemiology, Internal Medicine, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, Biological Psychology, and APH - Methodology

Subjects
Netherlands Twin Register (NTR), Male, 0301 basic medicine, Homocysteine, Metabolite, lcsh:Medicine, 0601 Biochemistry and Cell Biology, medicine.disease_cause, METHIONINE RESTRICTION, Cohort Studies, chemistry.chemical_compound, 0302 clinical medicine, PLASMA TOTAL HOMOCYSTEINE, Leukocytes, lcsh:Science, Telomere Shortening, LIFE-SPAN, Multidisciplinary, Middle Aged, Telomere, 3. Good health, Multidisciplinary Sciences, Telomeres, Lysophosphatidylcholine, CARDIOVASCULAR-DISEASE, Low-density lipoprotein, Science & Technology - Other Topics, Female, Adult, medicine.medical_specialty, 0299 Other Physical Sciences, LOW-DENSITY-LIPOPROTEIN, HEART-DISEASE, Biology, FAMILIAL LONGEVITY, Article, WHITE BLOOD-CELLS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Diabetes mellitus, Internal medicine, medicine, Metabolomics, Humans, Aged, Science & Technology, Methionine, MORTALITY, lcsh:R, Lipid metabolism, Lipid Metabolism, medicine.disease, ENDOTHELIAL-CELLS, 030104 developmental biology, Endocrinology, chemistry, lcsh:Q, 030217 neurology & neurosurgery, Oxidative stress
Abstract

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10−6), methionine (p-value = 9.2 × 10−5), tyrosine (p-value = 2.1 × 10−4), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10−4), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10−4), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10−4). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.

Published
2019

26. Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records

Author

Mart Kals, Maido Remm, Tarmo Puurand, Jaak Vilo, Tõnu Esko, Volker M. Lauschke, Lili Milani, Tõnis Tasa, Andres Metspalu, Toomas Haller, Kristi Krebs, and Reedik Mägi

Subjects
Estonia, Candidate gene, medicine.medical_specialty, Pharmacogenomic Variants, Population, Anti-Inflammatory Agents, Mutation, Missense, Computational biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Mutation Rate, Loss of Function Mutation, Genetics, Medicine, Electronic Health Records, Humans, Allele, education, Genetics (clinical), Genetic association, Medicinsk genetik, 0303 health sciences, education.field_of_study, business.industry, 030305 genetics & heredity, 16. Peace & justice, Biobank, 3. Good health, Pharmacogenomics, Medical genetics, business, Medical Genetics, Pharmacogenetics, alpha Catenin
Abstract

Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel loss-of-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.

Published
2019

27. Genome-wide physical activity interactions in adiposity - A meta-analysis of 200,452 adults

Author

Amélie Bonnefond, Nancy L. Heard-Costa, Julius S. Ngwa, Jennifer E. Huffman, Tanja B. Grammer, Jaakko Tuomilehto, Lu Qi, Nicholas G. Martin, Massimo Mangino, Henrik Vestergaard, Penny Gordon-Larsen, Reedik Mägi, Natalia V. Rivera, Charles Kooperberg, Alain G. Bertoni, Sarah H. Wild, Robert Luben, Veikko Salomaa, Claude Bouchard, Lynda M. Rose, Patricia A. Peyser, Graciela E. Delgado, Jessica D. Faul, Tuija Tammelin, John C. Chambers, Tsegaselassie Workalemahu, Kari E. North, David J. Porteous, Peter Vollenweider, Kennet Harald, Claire Bellis, Serena Sanna, Nicholas D. Hastie, Robert J. Klein, Marie-Claude Vohl, Ruth J. F. Loos, Jian Gong, Igor Rudan, Unhee Lim, Christopher A. Haiman, Martina Müller-Nurasyid, Konstantin Strauch, Mark A. Sarzynski, Albert V. Smith, Mark Walker, Tapani Ebeling, Göran Hallmans, Nicole Dueker, Caroline S. Fox, Sven Bergmann, Keri L. Monda, Thorkild I. A. Sørensen, André G. Uitterlinden, Johanne Marie Justesen, Aki S. Havulinna, Torben Hansen, Ivana Kolcic, Cecilia M. Lindgren, Marcel den Hoed, Richard N. Bergman, Mariaelisa Graff, Alan R. Shuldiner, Dorota Pasko, James F. Wilson, John Whitfield, Joel Eriksson, Jaspal S. Kooner, Mette Hollensted, Winfried März, Gonçalo R. Abecasis, Weihua Zhang, Harold Snieder, Rajesh Rawal, Tao Huang, Åsa Johansson, Lydia Quaye, Ying Wu, Benjamin Lehne, Matthias Nauck, Caroline Hayward, Linda S. Adair, Michel Marre, Tanguy Corre, Alan James, Frida Renström, Jian'an Luan, Zoltán Kutalik, Kurt Lohman, Jennifer A. Smith, Mao Fu, Jennifer L. Bragg-Gresham, Tamara B. Harris, Claudia Langenberg, Tõnu Esko, Mattias Lorentzon, Ken K. Ong, Blair H. Smith, Fabio Busonero, Alan F. Wright, Gemma Cadby, Andrew D. Johnson, Steve Buyske, Anubha Mahajan, Antonella Mulas, Gérard Waeber, Lori L. Bonnycastle, Daniel I. Chasman, Jennie Hui, Audrey Y. Chu, Uwe Völker, Albertine J. Oldehinkel, Jing Hua Zhao, Robert A. Scott, Ilja M. Nolte, Loic LeMarchand, Yu-Ching Cheng, David P. Strachan, Jie Huang, Gerard van Grootheest, John D. Eicher, Marcus E. Kleber, Francis S. Collins, Cornelia M. van Duijn, Timothy M. Frayling, Pau Navarro, Leo-Pekka Lyytikäinen, Cinzia Sarti, Paul M. Ridker, John-Olov Jansson, Shafqat Ahmad, Philippe Froguel, Albert Hofman, Inga Prokopenko, Vilmundur Gudnason, Anne U. Jackson, David R. Weir, Lyle J. Palmer, Alexander Teumer, Ulf Gyllensten, Mette Aadahl, Niels Grarup, Beverley Balkau, Oluf Pedersen, Cornelia Huth, Dorret I. Boomsma, Harry Campbell, Charlotte Huppertz, Ingrid B. Borecki, Juha Auvinen, Soren Snitker, Yuri Milaneschi, Iris M. Heid, Barbara Thorand, Wouter J. Peyrot, Lavinia Paternoster, Sian-Tsung Tan, Anne E. Justice, Dena G. Hernandez, Marcus Dörr, Nicholas J. Wareham, Marilyn C. Cornelis, Claes Ohlsson, Amy J. Swift, Ozren Polasek, Brenda W.J.H. Penninx, James E. Hayes, Stephanie A. Bien, Jana V. van Vliet-Ostaptchouk, Eric Boerwinkle, Louis Pérusse, Peter J. van der Most, Ulrike Peters, Pirjo Komulainen, Lynne J. Hocking, Catharina A. Hartman, William R. Scott, Jeffrey R. O'Connell, Stefania Bandinelli, Tuomo Rankinen, Timo A. Lakka, Leena Kinnunen, Markus Perola, John Blangero, Sharon L.R. Kardia, Veronique Vitart, Mika Kähönen, Marie Neergaard Harder, Diana Kuh, Kai Savonen, Kristin L. Young, Jeremiah Perez, Nina Hutri-Kähönen, George Davey Smith, Toshiko Tanaka, Barbara Sternfeld, Jennifer A. Nettleton, Jouke-Jan Hottenga, Christian Gieger, Gonneke Willemsen, Soren Brage, Mika Kivimäki, Lucia A. Hindorff, Steve Sidney, Tarunveer S. Ahluwalia, Liesbeth Vandenput, Loic Yengo, Markku Laakso, Yongmei Liu, Arthur W. Musk, Harald Grallert, Kirsti Kvaløy, Rainer Rauramaa, Satu Männistö, Tuomas O. Kilpeläinen, M. Carola Zillikens, Hannu Puolijoki, Luting Xue, Oddgeir L. Holmens, Sandosh Padmanabhan, Inês Barroso, Ching-Ti Liu, L. Adrienne Cupples, Judith B. Borja, Karen L. Mohlke, Matthias Olden, Henry Völzke, Myriam Fornage, Michael Boehnke, Pedro Marques-Vidal, John Beilby, Fernando Rivadeneira, Maija Hassinen, Najaf Amin, Kristian Hveem, Gudny Eiriksdottir, Lenore J. Launer, Johanna Kuusisto, Dorothée Thuillier, Heather M. Stringham, Sven Gläser, Min A. Jhun, Marjo-Riitta Järvelin, Niha Zubair, Annette Peters, Llilda Barata, Paula J. Griffin, Markus Juonala, Wei Zhao, Andres Metspalu, Christina Holzapfel, Lawrence F. Bielak, Thomas W. Winkler, Alena Stančáková, Anke Tönjes, Narisu Narisu, David Hadley, Peter S. Chines, Andrew Wong, Günther Silbernagel, Kati Kristiansson, Eco J. C. de Geus, Grant W. Montgomery, Elise Lim, Laura J. Rasmussen-Torvik, Terho Lehtimäki, Heikki A. Koistinen, Meena Kumari, Qibin Qi, Ayse Demirkan, Francesco Cucca, Allan Linneberg, Reija Männikkö, Jonathan Marten, Olli T. Raitakari, Mary F. Feitosa, Paul W. Franks, Kristine Færch, Mark I. McCarthy, Marleen H.M. de Moor, Joel N. Hirschhorn, Toomas Haller, Graff, Mariaelisa [0000-0001-6380-1735], Young, Kristin L [0000-0003-0070-6145], Winkler, Thomas W [0000-0003-0292-5421], Heard-Costa, Nancy L [0000-0001-9730-0306], Renström, Frida [0000-0001-6053-298X], Barroso, Inês [0000-0001-5800-4520], Strachan, David P [0000-0001-7854-1366], Liu, Ching-Ti [0000-0002-0703-0742], Klein, Robert J [0000-0003-3539-5391], Apollo - University of Cambridge Repository, University of Helsinki, Institute for Molecular Medicine Finland, Quantitative Genetics, Clinicum, Department of Medicine, Endokrinologian yksikkö, HUS Internal Medicine and Rehabilitation, Complex Disease Genetics, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, CHARGE Consortium, EPIC-InterAct Consortium, PAGE Consortium, Edwards, Todd L., Biological Psychology, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Clinical Child and Family Studies, APH - Methodology, School of Medicine / Biomedicine, Public and occupational health, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, APH - Digital Health, Life Course Epidemiology (LCE), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Center for Liver, Digestive and Metabolic Diseases (CLDM), Epidemiology, Medical Microbiology & Infectious Diseases, Erasmus MC other, Child and Adolescent Psychiatry / Psychology, and Internal Medicine

Subjects
Netherlands Twin Register (NTR), Epigenomics, Male, Genome-wide association study, genome, obesity, BMI, Body Mass Index, 0302 clinical medicine, Cell Signaling, Public and Occupational Health, GENE-EXPRESSION, Adiposity, Genetics & Heredity, ADIPOCYTE DIFFERENTIATION, 1184 Genetics, developmental biology, physiology, Genomics, Functional Genomics, 3. Good health, Meta-analysis, Physical Sciences, REACTIVE PROTEIN-LEVELS, Waist Circumference, Statistics (Mathematics), Waist, Genotype, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Single-nucleotide polymorphism, Locus (genetics), BINDING PROTEIN, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Genome-Wide Association Studies, Genetics, Humans, Statistical Methods, Molecular Biology, Exercise, Ecology, Evolution, Behavior and Systematics, 0604 Genetics, Science & Technology, ASSOCIATION METAANALYSIS, Physical activity, ta1184, Biology and Life Sciences, Computational Biology, Physical Activity, 030104 developmental biology, Genetic Loci, Body mass index, Mathematics, 030217 neurology & neurosurgery, Meta-Analysis, Developmental Biology, BODY-MASS INDEX, IDENTICAL-TWINS, ACTIVITY QUESTIONNAIRES, FAT DISTRIBUTION, FOOD-INTAKE, 0301 basic medicine, Cancer Research, Medicin och hälsovetenskap, Offita, Physiology, FTO gene, Genome-wide association studies, Medical and Health Sciences, Mathematical and Statistical Techniques, Waist–hip ratio, Medicine and Health Sciences, Genetics (clinical), Public Health, Global Health, Social Medicine and Epidemiology, Physiological Parameters, Female, Genomic Signal Processing, Life Sciences & Biomedicine, Research Article, Signal Transduction, lcsh:QH426-470, Biology, Research and Analysis Methods, Hreyfing (heilsurækt), Journal Article, Erfðafræði, Genetic Predisposition to Disease, Obesity, Waist-Hip Ratio, Body Weight, Human Genetics, Cell Biology, Rannsóknir, Genome Analysis, lcsh:Genetics, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, 3111 Biomedicine, Genome-Wide Association Study
Abstract

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery., The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute; the National Institutes of Health; or the U.S. Department of Health and Human Services. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (102318; 104781, 120315, 123885, 129619, 286284, 134309, 126925, 121584, 124282, 129378, 117787, 250207, 258753, 41071, 77299, 124243, 1114194, 24300796); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la Recherche; Agency for Health Care Policy Research (HS06516); Age UK Research into Ageing Fund; Åke Wiberg Foundation; ALF/LUA Research Grant in Gothenburg; ALFEDIAM; ALK-Abello´ A/S (Hørsholm, Denmark); American Heart Association (13POST16500011, 10SDG269004); Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; AstraZeneca; Australian Associated Brewers; Australian National Health and Medical Research Council (241944, 339462, 389927, 389875, 389891, 389892, 389938, 442915, 442981, 496739, 552485, 552498); Avera Research Institute; Bayer Diagnostics; Becton Dickinson; Biobanking and Biomolecular Resources Research Infrastructure (BBMRI –NL, 184.021.007); Biocentrum Helsinki; Boston Obesity Nutrition Research Center (DK46200); British Heart Foundation (RG/10/12/28456, SP/04/002); Canada Foundation for Innovation; Canadian Institutes of Health Research (FRN-CCT-83028); Cancer Research UK; Cardionics; Center for Medical Systems Biology; Center of Excellence in Complex Disease Genetics and SALVECenter of Excellence in Genomics (EXCEGEN); Chief Scientist Office of the Scottish Government; City of Kuopio; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF–1333-00124, DFF–1331-007308); Danish Diabetes Academy; Danish Medical Research Council; Department of Psychology and Education of the VU University Amsterdam; Diabetes Hilfs- und Forschungsfonds Deutschland; Dutch Brain Foundation; Dutch Ministry of Justice; Emil Aaltonen Foundation; Erasmus Medical Center; Erasmus University; Estonian Government (IUT20-60, IUT24-6); Estonian Ministry of Education and Research (3.2.0304.11-0312); European Commission (230374, 284167, 323195, 692145, FP7 EurHEALTHAgeing-277849, FP7 BBMRI-LPC 313010, nr 602633, HEALTH-F2-2008-201865-GEFOS, HEALTH-F4-2007-201413, FP6 LSHM-CT-2004-005272, FP5 QLG2-CT-2002-01254, FP6 LSHG-CT-2006-01947, FP7 HEALTH-F4-2007-201413, FP7 279143, FP7 201668, FP7 305739, FP6 LSHG-CT-2006-018947, HEALTH-F4-2007-201413, QLG1-CT-2001-01252); European Regional Development Fund; European Science Foundation (EuroSTRESS project FP-006, ESF, EU/QLRT-2001-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ9603, 01ZZ0103, 01ZZ0403, 03ZIK012, 03IS2061A); Federal State of Mecklenburg - West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Food Standards Agency; Fondation de France; Fonds Santé; Genetic Association Information Network of the Foundation for the National Institutes of Health; German Diabetes Association; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); German Research Council (SFB-1052, SPP 1629 TO 718/2-1); GlaxoSmithKline; Göran Gustafssons Foundation; Göteborg Medical Society; Health and Safety Executive; Heart Foundation of Northern Sweden; Icelandic Heart Association; Icelandic Parliament; Imperial College Healthcare NHS Trust; INSERM, Réseaux en Santé Publique, Interactions entre les déterminants de la santé; Interreg IV Oberrhein Program (A28); Italian Ministry of Economy and Finance; Italian Ministry of Health (ICS110.1/RF97.71); John D and Catherine T MacArthur Foundation; Juho Vainio Foundation; King's College London; Kjell och Märta Beijers Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); Leiden University Medical Center; Lilly; LMUinnovativ; Lundbeck Foundation; Lundberg Foundation; Medical Research Council of Canada; MEKOS Laboratories (Denmark); Merck Santé; Mid-Atlantic Nutrition Obesity Research Center (P30 DK72488); Ministère de l’Économie, de l’Innovation et des Exportations; Ministry for Health, Welfare and Sports of the Netherlands; Ministry of Cultural Affairs of the Federal State of Mecklenburg-West Pomerania; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science of the Netherlands; MRC Human Genetics Unit; MRC-GlaxoSmithKline Pilot Programme Grant (G0701863); Municipality of Rotterdam; Netherlands Bioinformatics Centre (2008.024); Netherlands Consortium for Healthy Aging (050-060-810); Netherlands Genomics Initiative; Netherlands Organisation for Health Research and Development (904-61-090, 985-10-002, 904-61-193, 480-04-004, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192); Netherlands Organisation for Health Research and Development (2010/31471/ZONMW); Netherlands Organisation for Scientific Research (10-000-1002, GB-MW 940-38-011, 100-001-004, 60-60600-97-118, 261-98-710, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MaGW 452-04-314, GB-MaGW 452-06-004, 175.010.2003.005, 175.010.2005.011, 481-08-013, 480-05-003, 911-03-012); Neuroscience Campus Amsterdam; NHS Foundation Trust; Novartis Pharmaceuticals; Novo Nordisk; Office National Interprofessionel des Vins; Paavo Nurmi Foundation; Påhlssons Foundation; Päivikki and Sakari Sohlberg Foundation; Pierre Fabre; Republic of Croatia Ministry of Science, Education and Sport (108-1080315-0302); Research Centre for Prevention and Health, the Capital Region for Denmark; Research Institute for Diseases in the Elderly (014-93-015, RIDE2); Roche; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Executive Health Department (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du Diabète; State of Bavaria; Stroke Association; Swedish Diabetes Association; Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20140543); Swedish Research Council (2015-03657); Swedish Medical Research Council (K2007-66X-20270-01-3, 2011-2354); Swedish Society for Medical Research; Swiss National Science Foundation (33CSCO-122661, 33CS30-139468, 33CS30-148401); Tampere Tuberculosis Foundation; The Marcus Borgström Foundation; The Royal Society; The Wellcome Trust (084723/Z/08/Z, 088869/B/09/Z); Timber Merchant Vilhelm Bangs Foundation; Topcon; Torsten and Ragnar Söderberg's Foundation; UK Department of Health; UK Diabetes Association; UK Medical Research Council (MC_U106179471, G0500539, G0600705, G0601966, G0700931, G1002319, K013351, MC_UU_12019/1); UK National Institute for Health Research BioResource Clinical Research Facility and Biomedical Research Centre; UK National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre; UK National Institute for Health Research (RP-PG-0407-10371); Umeå University Career Development Award; United States – Israel Binational Science Foundation Grant (2011036); University Hospital Oulu (75617); University Medical Center Groningen; University of Tartu (SP1GVARENG); National Institutes of Health (AG13196, CA047988, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSC271201100004C, HHSN268200900041C, HHSN268201300025C, HHSN268201300026C, HHSN268201300027C, HHSN268201300028C, HHSN268201300029C, HHSN268201500001I, HL36310, HG002651, HL034594, HL054457, HL054481, HL071981, HL084729, HL119443, HL126024, N01-AG12100, N01-AG12109, N01-HC25195, N01-HC55015, N01-HC55016, N01-HC55018, N01-HC55019, N01-HC55020, N01-HC55021, N01-HC55022, N01-HD95159, N01-HD95160, N01-HD95161, N01-HD95162, N01-HD95163, N01-HD95164, N01-HD95165, N01-HD95166, N01-HD95167, N01-HD95168, N01-HD95169, N01-HG65403, N02-HL64278, R01-HD057194, R01-HL087641, R01-HL59367, R01HL-086694, R01-HL088451, R24-HD050924, U01-HG-004402, HHSN268200625226C, UL1-RR025005, UL1-RR025005, UL1-TR-001079, UL1-TR-00040, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, DA12854, MH081802, MH66206, R01-D004215701A, R01-DK075787, R01-DK089256, R01-DK8925601, R01-HL088451, R01-HL117078, R01-DK062370, R01-DK072193, DK091718, DK100383, DK078616, 1Z01-HG000024, HL087660, HL100245, R01DK089256, 2T32HL007055-36, U01-HL072515-06, U01-HL84756, NIA-U01AG009740, RC2-AG036495, RC4-AG039029, R03 AG046389, 263-MA-410953, 263-MD-9164, 263-MD-821336, U01-HG004802, R37CA54281, R01CA63, P01CA33619, U01-CA136792, U01-CA98758, RC2-MH089951, MH085520, R01-D0042157-01A, MH081802, 1RC2-MH089951, 1RC2-MH089995, 1RL1MH08326801, U01-HG007376, 5R01-HL08767902, 5R01MH63706:02, HG004790, N01-WH22110, U01-HG007033, UM1CA182913, 24152, 32100-2, 32105-6, 32108-9, 32111-13, 32115, 32118-32119, 32122, 42107-26, 42129-32, 44221); USDA National Institute of Food and Agriculture (2007-35205-17883); Västra Götaland Foundation; Velux Foundation; Veterans Affairs (1 IK2 BX001823); Vleugels Foundation; VU University’s Institute for Health and Care Research (EMGO+, HEALTH-F4-2007-201413) and Neuroscience Campus Amsterdam; Wellcome Trust (090532, 091551, 098051, 098381); Wissenschaftsoffensive TMO; and Yrjö Jahnsson Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Published
2017

28. MixFit: Methodology for Computing Ancestry-Related Genetic Scores at the Individual Level and Its Application to the Estonian and Finnish Population Studies

Author

Tõnu Esko, Kirsten Ohm Kyvik, Tim D. Spector, Andres Metspalu, Dorothea Irene Boomsma, Marja-Liisa Nuotio, Liis Leitsalu, Markus Perola, Krista Fischer, Toomas Haller, Institute for Molecular Medicine Finland, Quantitative Genetics, Biological Psychology, APH - Mental Health, APH - Methodology, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
Netherlands Twin Register (NTR), 0301 basic medicine, lcsh:Medicine, Genome-wide association study, computer.software_genre, Geographical Locations, Cohort Studies, Resource (project management), Latvians, Ethnicities, lcsh:Science, education.field_of_study, Multidisciplinary, Genomics, FINLAND, 3. Good health, Europe, Estonians, Geography, language, Natural language processing, Research Article, Estonia, Genetic genealogy, Population, Context (language use), 03 medical and health sciences, Genetics, Journal Article, Humans, GENOME-WIDE ASSOCIATION, education, Evolutionary Biology, Population Biology, business.industry, lcsh:R, Biology and Life Sciences, Computational Biology, Genome Analysis, Latvia, Pipeline (software), Estonian, language.human_language, Genetics, Population, 030104 developmental biology, People and Places, lcsh:Q, Population Groupings, Artificial intelligence, Personalized medicine, 3111 Biomedicine, business, computer, Finns, Population Genetics, Genealogy and Heraldry
Abstract

Ancestry information at the individual level can be a valuable resource for personalized medicine, medical, demographical and history research, as well as for tracing back personal history. We report a new method for quantitatively determining personal genetic ancestry based on genome-wide data. Numerical ancestry component scores are assigned to individuals based on comparisons with reference populations. These comparisons are conducted with an existing analytical pipeline making use of genotype phasing, similarity matrix computation and our addition-multidimensional best fitting by MixFit. The method is demonstrated by studying Estonian and Finnish populations in geographical context. We show the main differences in the genetic composition of these otherwise close European populations and how they have influenced each other. The components of our analytical pipeline are freely available computer programs and scripts one of which was developed in house (available at: www.geenivaramu.ee/en/tools/mixfit).

Published
2017
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29. RegScan: a GWAS tool for quick estimation of allele effects on continuous traits and their combinations

Author

Krista Fischer, Tõnu Esko, Reedik Mägi, Toomas Haller, and Mart Kals

Subjects
Source code, Computer science, media_common.quotation_subject, Genome wide analysis, Genome-wide association study, computer.software_genre, Gene Frequency, Humans, GWAS, Allele, Molecular Biology, Allele frequency, continuous traits, media_common, combinatorial traits, Computational Biology, metabolomics, Data Interpretation, Statistical, Papers, Linear Models, linear regression, Trait, Data mining, Fast methods, computer, Genome-Wide Association Study, genome-wide analysis, Information Systems
Abstract

UNLABELLED Genome-wide association studies are becoming computationally more demanding with the growing amounts of data. Combinatorial traits can increase the data dimensions beyond the computational capabilities of the current tools. We addressed this issue by creating an application for quick association analysis that is ten to hundreds of times faster than the leading fast methods. Our tool (RegScan) is designed for performing basic linear regression analysis with continuous traits maximally fast on large data sets. RegScan specifically targets association analysis of combinatorial traits in metabolomics. It can both generate and analyze the combinatorial traits efficiently. RegScan is capable of analyzing any number of traits together without the need to specify each trait individually. The main goal of the article is to show that RegScan can be the preferred analytical tool when large amounts of data need to be analyzed quickly using the allele frequency test. AVAILABILITY Precompiled RegScan (all major platforms), source code, user guide and examples are freely available at www.biobank.ee/regscan. REQUIREMENTS Qt 4.4.3 or newer for dynamic compilations.

Published
2013

30. Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia

Author

Beate St Pourcain, Abhishek Nag, Federico Murgia, Emily Y. Chew, Veluchamy A. Barathi, James F. Wilson, Jamie E Craig, Veronique Vitart, Myopia (Cream), Olavi Pärssinen, Cathy Williams, Sarayut Janmahasatian, Alex W. Hewitt, Felicia Hawthorne, Norbert Pfeiffer, Yik Ying Teo, Johannes R. Vingerling, Shea Ping Yip, Alan F. Wright, Tanja Zeller, Robert P. Igo, David M. Evans, Maria Schache, Nicholas J. Timpson, Fernando Rivadeneira, E-Shyong Tai, Craig E. Pennell, Ozren Polasek, Olli T. Raitakari, Tin Aung, Christian P. Müller, René Höhn, Paul Mitchell, Lennart C. Karssen, George McMahon, Mika Kähönen, Juho Wedenoja, Tien Yin Wong, Angela Döring, Jost B. Jonas, Albert Hofman, Konrad Oexle, Jugnoo S Rahi, Complications Trial, Ben A. Oostra, Kathryn P. Burdon, Pirro G. Hysi, Sudha K. Iyengar, Tim D. Spector, Li Jia Chen, Claire L. Simpson, S. Mohsen Hosseini, Dwight Stambolian, Alireza Mirshahi, Arthur A.B. Bergen, Terri L. Young, Rick Twee-Hee Ong, Andres Metspalu, Ioana Cotlarciuc, Liang Xu, Xin Zhou, Toomas Haller, Virginie J. M. Verhoeven, David A. Mackey, Brian W Fleck, André G. Uitterlinden, John P. Kemp, Chi Pui Pang, Seang-Mei Saw, Thomas Meitinger, Gabriëlle H.S. Buitendijk, Peng Chen, Joan E. Bailey-Wilson, Wei Ang, Stuart MacGregor, Caroline Hayward, Andrew D. Paterson, Jie Jin Wang, Ruoying Li, Cornelia M. van Duijn, Ching-Yu Cheng, Jiemin Liao, Theo G. M. F. Gorgels, Annemieke J.M.H. Verkerk, Mario Pirastu, Robert Wojciechowski, Christopher J Hammond, Paul N. Baird, Qiao Fan, Grant W. Montgomery, Jeremy A. Guggenheim, Wan Ting Tay, M. Kamran Ikram, Terho Lehtimäki, Ekaterina Yonova-Doing, Najaf Amin, Ronald Klein, Kari-Matti Mäkelä, Chiea Chuen Khor, Barbara E.K. Klein, Eranga N. Vithana, Yingfeng Zheng, Phillippa M. Cumberland, Caroline C W Klaver, Hoi Suen Wong, Aniket Mishra, Daniel W.H. Ho, Igor Rudan, Complications (Dcct), Jonathan H. Lass, Zoran Vatavuk, Other departments, ANS - Amsterdam Neuroscience, Human Genetics, Ophthalmology, Pathology, Epidemiology, Cell biology, Anesthesiology, Internal Medicine, Clinical Genetics, Obstetrics & Gynecology, Amsterdam Neuroscience, and Netherlands Institute for Neuroscience (NIN)

Subjects
Candidate gene, Refractive error, Bone Morphogenetic Protein 2, Genome-wide association study, VARIANTS, Genome, Genome-wide association studies, 0302 clinical medicine, Risk Factors, Myopia, GRIA4, Genetics, 0303 health sciences, KCNQ Potassium Channels, Disease genetics, EYE GROWTH, ASSOCIATION, RETINAL-PIGMENT EPITHELIUM, Refractive Errors, Genetic load, 3. Good health, ADAPTED MOUSE RETINA, Meta-analysis, ACID, POTASSIUM CHANNEL, EXPRESSION, Single-nucleotide polymorphism, Biology, White People, Article, 03 medical and health sciences, Asian People, medicine, Humans, Genetic Predisposition to Disease, Receptors, AMPA, gene, myopia, refractive, 030304 developmental biology, Homeodomain Proteins, ta1184, ta3121, medicine.disease, GENE, Alcohol Oxidoreductases, SERINE-PROTEASE, biology.protein, 030221 ophthalmology & optometry, Susceptibility locus, Trans-Activators, Eye disorder, Laminin, Serine Proteases, GWAS, meta-analyses, refractive error, Genome-Wide Association Study
Abstract

Author version made available in accordance with the publisher's policy., Refractive error is the most common eye disorder worldwide and is a prominent cause of blindness. Myopia affects over 30% of Western populations and up to 80% of Asians. The CREAM consortium conducted genome-wide meta-analyses, including 37,382 individuals from 27 studies of European ancestry and 8,376 from 5 Asian cohorts. We identified 16 new loci for refractive error in individuals of European ancestry, of which 8 were shared with Asians. Combined analysis identified 8 additional associated loci. The new loci include candidate genes with functions in neurotransmission (GRIA4), ion transport (KCNQ5), retinoic acid metabolism (RDH5), extracellular matrix remodeling (LAMA2 and BMP2) and eye development (SIX6 and PRSS56). We also confirmed previously reported associations with GJD2 and RASGRF1. Risk score analysis using associated SNPs showed a tenfold increased risk of myopia for individuals carrying the highest genetic load. Our results, based on a large meta-analysis across independent multiancestry studies, considerably advance understanding of the mechanisms involved in refractive error and myopia., Australian National Health and Medical Research Council.

Published
2013

31. Genome-wide study for circulating metabolites identifies 62 loci and reveals novel systemic effects of LPA

Author

Antti J. Kangas, Joris Deelen, Rajesh Rawal, Tuulia Tynkkynen, Anton J. M. de Craen, Gonneke Willemsen, Antti Jula, Taru Tukiainen, Anika A. M. Vaarhorst, Aswin Verhoeven, Johannes Kettunen, Cornelia M. van Duijn, Samuli Ripatti, Ko Willems van Dijk, René Pool, Pasi Soininen, Stefan Blankenberg, Mika Kähönen, Qin Wang, Markus Perola, Marjo-Riitta Järvelin, Markku J. Savolainen, Mika Ala-Korpela, Antti-Pekka Sarin, Veikko Salomaa, Najaf Amin, Terho Lehtimäki, Jaakko Kaprio, Melanie Waldenberger, P. Eline Slagboom, Mika Tiainen, Leo-Pekka Lyytikäinen, Jouke-Jan Hottenga, Jorma Viikari, Tanja Zeller, Toomas Haller, Johan G. Eriksson, Ayse Demirkan, Olli T. Raitakari, Elisabeth M. van Leeuwen, Evelin Mihailov, Marian Beekman, Harmen H.M. Draisma, Andres Metspalu, Matti Pirinen, Dorret I. Boomsma, Christian Gieger, Richard J. Rose, Peter Würtz, Tõnu Esko, Epidemiology, Institute for Molecular Medicine Finland, Clinicum, Johan Eriksson / Principal Investigator, Department of General Practice and Primary Health Care, Jaakko Kaprio / Principal Investigator, Department of Public Health, Samuli Olli Ripatti / Principal Investigator, Biostatistics Helsinki, Quantitative Genetics, Complex Disease Genetics, Genetic Epidemiology, Statistical and population genetics, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
Male, 0301 basic medicine, Netherlands Twin Register (NTR), Magnetic Resonance Spectroscopy, General Physics and Astronomy, Genome-wide association study, Lipoproteins, VLDL, Genome-wide association studies, THERAPY, RISK, Genetics, Multidisciplinary, JUPITER TRIAL, Chromosome Mapping, Mendelian Randomization Analysis, ASSOCIATION, Lipoprotein(a), Middle Aged, 3. Good health, Multidisciplinary Sciences, Cardiovascular Diseases, Science & Technology - Other Topics, CORONARY-ARTERY-DISEASE, Medical genetics, Female, Adult, medicine.medical_specialty, medical genetics, Science, Locus (genetics), Biology, Article, General Biochemistry, Genetics and Molecular Biology, JUSTIFICATION, Young Adult, 03 medical and health sciences, Metabolomics, SDG 3 - Good Health and Well-being, MD Multidisciplinary, Mendelian randomization, medicine, Humans, Genetic Predisposition to Disease, EVALUATING ROSUVASTATIN, Triglycerides, Aged, Genetic association, INTERVENTION TRIAL, Science & Technology, General Chemistry, ta3121, 030104 developmental biology, 3121 General medicine, internal medicine and other clinical medicine, biology.protein, GENETIC-DETERMINANTS, Genome-Wide Association Study
Abstract

Genome-wide association studies have identified numerous loci linked with complex diseases, for which the molecular mechanisms remain largely unclear. Comprehensive molecular profiling of circulating metabolites captures highly heritable traits, which can help to uncover metabolic pathophysiology underlying established disease variants. We conduct an extended genome-wide association study of genetic influences on 123 circulating metabolic traits quantified by nuclear magnetic resonance metabolomics from up to 24,925 individuals and identify eight novel loci for amino acids, pyruvate and fatty acids. The LPA locus link with cardiovascular risk exemplifies how detailed metabolic profiling may inform underlying aetiology via extensive associations with very-low-density lipoprotein and triglyceride metabolism. Genetic fine mapping and Mendelian randomization uncover wide-spread causal effects of lipoprotein(a) on overall lipoprotein metabolism and we assess potential pleiotropic consequences of genetically elevated lipoprotein(a) on diverse morbidities via electronic health-care records. Our findings strengthen the argument for safe LPA-targeted intervention to reduce cardiovascular risk., Circulating metabolites reflect human health and disease. Here, Kettunen et al. perform a genome-wide association study on 123 circulating metabolic traits and identify novel genetic loci influencing systemic metabolism. They also link new molecular pathways with a known cardiovascular risk factor Lp(a).

Published
2016

32. Effects of Metformin on Metabolite Profiles and LDL Cholesterol in Patients With Type 2 Diabetes

Author

Christian Herder, Thomas Illig, Gonneke Willemsen, Yixue Li, Tao Xu, Anne S. Quante, Toomas Haller, Janina S. Ried, Konstantin Strauch, Ana C. Messias, Werner Roemisch-Margl, Jerzy Adamski, Barbara Thorand, Martin Hrabé de Angelis, Ying He, Ayse Demirkan, Gabi Kastenmüller, Katarina Kasa, Annette Peters, Wolfgang Rathmann, Jonathan Adam, Tommaso Panni, Zhonghao Yu, Markus Rotter, Gisela Fobo, Bernd Stratmann, Dorret I. Boomsma, Karsten Suhre, Shen Chi, Michael Roden, Thomas Meitinger, Cornelia M. van Duijn, Ko Willems van Dijk, René Pool, Cornelia Prehn, Monica Campillos, Christa Meisinger, Stefan Brandmaier, Christian Gieger, Andres Metspalu, Christina Holzapfel, Harmen H.M. Draisma, Thomas Hankemeier, Margit Heier, H.-Erich Wichmann, Rui Wang-Sattler, Renee Stark, Andreas Ruepp, Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Lifestyle, Overweight and Diabetes, Dermatology, and Epidemiology

Subjects
Fatty Acid Desaturases, Male, Netherlands Twin Register (NTR), medicine.medical_specialty, Genotype, endocrine system diseases, Endocrinology, Diabetes and Metabolism, Metabolite, Population, Blood lipids, Type 2 diabetes, chemistry.chemical_compound, Delta-5 Fatty Acid Desaturase, SDG 3 - Good Health and Well-being, Risk Factors, Diabetes mellitus, Internal medicine, Internal Medicine, medicine, Humans, Hypoglycemic Agents, Metabolomics, education, Aged, Advanced and Specialized Nursing, education.field_of_study, Cholesterol, business.industry, AMPK, nutritional and metabolic diseases, Cholesterol, LDL, Fasting, Genomics, Middle Aged, Lipid Metabolism, medicine.disease, Metformin, 3. Good health, Cross-Sectional Studies, Endocrinology, Diabetes Mellitus, Type 2, chemistry, Female, business, Diabetic Angiopathies, medicine.drug
Abstract

OBJECTIVE Metformin is used as a first-line oral treatment for type 2 diabetes (T2D). However, the underlying mechanism is not fully understood. Here, we aimed to comprehensively investigate the pleiotropic effects of metformin. RESEARCH DESIGN AND METHODS We analyzed both metabolomic and genomic data of the population-based KORA cohort. To evaluate the effect of metformin treatment on metabolite concentrations, we quantified 131 metabolites in fasting serum samples and used multivariable linear regression models in three independent cross-sectional studies (n = 151 patients with T2D treated with metformin [mt-T2D]). Additionally, we used linear mixed-effect models to study the longitudinal KORA samples (n = 912) and performed mediation analyses to investigate the effects of metformin intake on blood lipid profiles. We combined genotyping data with the identified metformin-associated metabolites in KORA individuals (n = 1,809) and explored the underlying pathways. RESULTS We found significantly lower (P < 5.0E-06) concentrations of three metabolites (acyl-alkyl phosphatidylcholines [PCs]) when comparing mt-T2D with four control groups who were not using glucose-lowering oral medication. These findings were controlled for conventional risk factors of T2D and replicated in two independent studies. Furthermore, we observed that the levels of these metabolites decreased significantly in patients after they started metformin treatment during 7 years’ follow-up. The reduction of these metabolites was also associated with a lowered blood level of LDL cholesterol (LDL-C). Variations of these three metabolites were significantly associated with 17 genes (including FADS1 and FADS2) and controlled by AMPK, a metformin target. CONCLUSIONS Our results indicate that metformin intake activates AMPK and consequently suppresses FADS, which leads to reduced levels of the three acyl-alkyl PCs and LDL-C. Our findings suggest potential beneficial effects of metformin in the prevention of cardiovascular disease.

Published
2015

33. Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels

Author

Mark I. McCarthy, Lude Franke, Toomas Haller, Eco J. C. de Geus, Grant W. Montgomery, Gu Zhu, Brenda W.J.H. Penninx, John Whitfield, Karsten Suhre, Nicholas G. Martin, Konstantin Strauch, Christian Gieger, Anika A. M. Vaarhorst, Anjali K. Henders, Ayse Demirkan, Anton J. M. de Craen, Aaron Isaacs, Marian Beekman, Harmen H.M. Draisma, Tõnu Esko, Gonneke Willemsen, Dorret I. Boomsma, Tim D. Spector, Elisabeth M. van Leeuwen, Harm-Jan Westra, P. Eline Slagboom, Massimo Mangino, Harish Dharuri, Werner Römisch-Margl, Thomas Illig, Michael Kobl, Jouke-Jan Hottenga, Jordana T. Bell, Peter A C 't Hoen, Gert-Jan B. van Ommen, Cornelia Prehn, Andres Metspalu, Ann-Kristin Petersen, Jan B. van Klinken, Rick Jansen, Cornelia M. van Duijn, Ko Willems van Dijk, René Pool, Stefan Böhringer, Najaf Amin, Dale R. Nyholt, Jerzy Adamski, Idil Yet, Biochemistry, Epidemiology, General Practice, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Stem Cell Aging Leukemia and Lymphoma (SALL), Psychiatry, NCA - Neurobiology of mental health, EMGO - Lifestyle, overweight and diabetes, Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, and EMGO+ - Lifestyle, Overweight and Diabetes

Subjects
Netherlands Twin Register (NTR), Metabolite, Population, LOCI, General Physics and Astronomy, Genome-wide association study, Single-nucleotide polymorphism, SOFTWARE, Biology, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, SERUM, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Blood serum, Metabolomics, Genetic variation, MD Multidisciplinary, Metabolome, Humans, Polymorphism, education, METAANALYSIS, POPULATION, 030304 developmental biology, Genetics, RISK, 0303 health sciences, education.field_of_study, Multidisciplinary, Science & Technology, COMMON VARIANTS, General Chemistry, Single Nucleotide, 3. Good health, ddc, Multidisciplinary Sciences, Blood, chemistry, Blood/metabolism, Science & Technology - Other Topics, CORONARY-ARTERY-DISEASE, ARGININE BIOAVAILABILITY, 030217 neurology & neurosurgery, TRAITS, Genome-Wide Association Study
Abstract

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P-9) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N=1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.

Published
2015

34. Meta-analyses identify 13 loci associated with age at menopause and highlight DNA repair and immune pathways

Author

Sophie H. Van Wingerden, Wei V. Zhuang, Mladen Boban, John R. B. Perry, Joop S.E. Laven, Shah Ebrahim, Andrea D. Coviello, Barbara McKnight, Laura Crisponi, Sharon L.R. Kardia, Daniel I. Chasman, Lorna M. Lopez, George Dedoussis, Stefania Bandinelli, Nora Franceschini, Florian Ernst, A. Cecile J.W. Janssens, Yvonne T. van der Schouw, Henri Wallaschofski, Jari Lahti, Triin Laisk, Elizabeth A. Streeten, Joanne M. Murabito, Liana Ferreli, Harold Snieder, Dale R. Nyholt, Lenore J. Launer, Panagiotis Deloukas, Melissa E. Garcia, Eco J. C. de Geus, H.-Erich Wichmann, John M. Starr, Eva Albrecht, Paul M. Ridker, N. Charlotte Onland-Moret, Petra H.M. Peeters, Massimo Mangino, Jacques S. Beckmann, Stephen J. Chanock, Grant W. Montgomery, Julie E. Buring, Barbara Thorand, Diederick E. Grobbee, Irena Martinović Klarić, Constance Chen, So-Youn Shin, Ozren Polasek, Daniel F. Gudbjartsson, Patrick Sulem, Carla H. van Gils, Eleonora Porcu, Cinzia Sala, Tim D. Spector, Alexander N. Parker, Ellen W. Demerath, Guillaume Paré, Krista Fischer, Simon N. Stacey, Mara Marongiu, Lina Zgaga, Jouke-Jan Hottenga, Unnur Styrkarsdottir, Debbie A Lawlor, Douglas P. Kiel, Guangju Zhai, Kari Stefansson, Lisette Stolk, Igor Rudan, David Schlessinger, Katri R Currency Signikkönen, Z. Kutalik, Ian J. Deary, Frank J.M. Broekmans, Ulf de Faire, Vincent Mooser, Luigi Ferrucci, Maria G. Stathopoulou, Pio D'Adamo, Marek Zygmunt, Linda Broer, James F. Wilson, Lovorka Barać Lauc, Angelo Scuteri, Patrik K. E. Magnusson, Frank B. Hu, Jennifer A. Smith, Toomas Haller, Giorgio Pistis, Colette J M Wijnands-van Gent, Emil Rehnberg, Marlies Voorhuis, Anna Murray, David Melzer, Chunyan He, Tamara B. Harris, Merli Hass, Patrick F. McArdle, Valur Emilsson, Gérard Waeber, Manuela Uda, Nancy L. Pedersen, Jenny A. Visser, Behrooz Z. Alizadeh, Andres Salumets, Andrew D. Johnson, Gonneke Willemsen, Sheila Ulivi, Tmu Esko, Vilmundur Gudnason, Bart C.J.M. Fauser, Maja Barbalić, Henry Völzke, Ronald P. Stolk, Aarno Palotie, Peter Van Nierop, Thor Aspelund, Elisabeth Widen, Caroline Hayward, Johan G. Eriksson, Alan F. Wright, Marilyn C. Cornelis, Tanguy Corre, Eric Boerwinkle, Ben A. Oostra, Alice M. Arnold, Kathleen Stirrups, Yvonne V. Louwers, M. Carola Zillikens, Anne B. Newman, Jerome I. Rotter, Jianjun Liu, Per Hall, Aaron R. Folsom, David Karasik, Yan V. Sun, Albert Hofman, Gudny Eiriksdottir, Andrew B. Singleton, Victor J M Pop, Pau Navarro, Tatijana Zemunik, Andres Metspalu, Andrew S. Plump, Cornelia M. van Duijn, Dorret I. Boomsma, Harry Campbell, Nicole Soranzo, Bruce M. Psaty, Enda M. Byrne, Christian Gieger, Albert Tenesa, Nicholas G. Martin, Unnur Thorsteinsdottir, Kathryn L. Lunetta, Laufey Tryggvadottir, Serena Sanna, Kim Tsui, Ivana Kolcic, Laura M. Yerges-Armstrong, Jacqueline M. Vink, Bruce H. R. Wolffenbuttel, Daniela Toniolo, Peter M. Visscher, Rob M. van Dam, Erik Ingelsson, Sandra Lai, Corrado Masciullo, Albert V. Smith, Paolo Gasparini, Sarah E. Medland, Nicole L. Glazer, Peter Kraft, André G. Uitterlinden, David J. Hunter, Andrea Burri, Jules J. Keyzer, Susan E. Hankinson, Gail Davies, Andrew C. Heath, Biological Psychology, EMGO+ - Mental Health, Internal Medicine, Epidemiology, Obstetrics & Gynecology, Surgery, Hematology, Clinical Genetics, Study T.L., Lisette, Stolk, John R. B., Perry, Daniel I., Chasman, Chunyan, He, Massimo, Mangino, Patrick, Sulem, Maja, Barbalic, Linda, Broer, Enda M., Byrne, Florian, Ernst, Tõnu, Esko, Nora, Franceschini, Daniel F., Gudbjartsson, Jouke Jan, Hottenga, Peter, Kraft, Patrick F., Mcardle, Eleonora, Porcu, So Youn, Shin, Albert V., Smith, Sophie van, Wingerden, Guangju, Zhai, Wei V., Zhuang, Eva, Albrecht, Behrooz Z., Alizadeh, Thor, Aspelund, Stefania, Bandinelli, Lovorka Barac, Lauc, Jacques S., Beckmann, Mladen, Boban, Eric, Boerwinkle, Frank J., Broekman, Andrea, Burri, Harry, Campbell, Stephen J., Chanock, Constance, Chen, Marilyn C., Corneli, Tanguy, Corre, Andrea D., Coviello, D'Adamo, ADAMO PIO, Gail, Davie, Ulf de, Faire, Eco J. C., de Geu, Ian J., Deary, George V. Z., Dedoussi, Panagiotis, Delouka, Shah, Ebrahim, Gudny, Eiriksdottir, Valur, Emilsson, Johan G., Eriksson, Bart C. J. M., Fauser, Liana, Ferreli, Luigi, Ferrucci, Krista, Fischer, Aaron R., Folsom, Melissa E., Garcia, Gasparini, Paolo, Christian, Gieger, Nicole, Glazer, Diederick E., Grobbee, Per, Hall, Toomas, Haller, Susan E., Hankinson, Merli, Ha, Caroline, Hayward, Andrew C., Heath, Albert, Hofman, Erik, Ingelsson, A. Cecile J. W., Janssen, Andrew D., Johnson, David, Karasik, Sharon L. R., Kardia, Jules, Keyzer, Douglas P., Kiel, Ivana, Kolcic, Zoltán, Kutalik, Jari, Lahti, Sandra, Lai, Triin, Laisk, Joop S. E., Laven, Debbie A., Lawlor, Jianjun, Liu, Lorna M., Lopez, Yvonne V., Louwer, Patrik K. E., Magnusson, Mara, Marongiu, Nicholas G., Martin, Irena Martinovic, Klaric, Corrado, Masciullo, Barbara, Mcknight, Sarah E., Medland, David, Melzer, Vincent, Mooser, Pau, Navarro, Anne B., Newman, Dale R., Nyholt, N., Charlotte Onland Moret, Aarno, Palotie, Guillaume, Paré, Alex N., Parker, Nancy L., Pedersen, Petra H. M., Peeter, Giorgio, Pisti, Andrew S., Plump, Ozren, Polasek, Victor J. M., Pop, Bruce M., Psaty, Katri, Räikkönen, Emil, Rehnberg, Jerome I., Rotter, Igor, Rudan, Cinzia, Sala, Andres, Salumet, Angelo, Scuteri, Andrew, Singleton, Jennifer A., Smith, Harold, Snieder, Nicole, Soranzo, Simon N., Stacey, John M., Starr, Maria G., Stathopoulou, Kathleen, Stirrup, Ronald P., Stolk, Unnur, Styrkarsdottir, Yan V., Sun, Albert, Tenesa, Barbara, Thorand, Daniela, Toniolo, Laufey, Tryggvadottir, Kim, Tsui, Sheila, Ulivi, Rob M., van Dam, Yvonne T., van der Schouw, Carla H., van Gil, Peter van, Nierop, Jacqueline M., Vink, Peter M., Visscher, Marlies, Voorhui, Gérard, Waeber, Henri, Wallaschofski, H., Erich Wichmann, Elisabeth, Widen, Colette J. M., Wijnands van Gent, Gonneke, Willemsen, James F., Wilson, Bruce H. R., Wolffenbuttel, Alan F., Wright, Laura M., Yerges Armstrong, Tatijana, Zemunik, Lina, Zgaga, M., Carola Zilliken, Marek, Zygmunt, The LifeLines Cohort, Study, Alice M., Arnold, Dorret I., Boomsma, Julie E., Buring, Laura, Crisponi, Ellen W., Demerath, Vilmundur, Gudnason, Tamara B., Harri, Frank B., Hu, David J., Hunter, Lenore J., Launer, Andres, Metspalu, Grant W., Montgomery, Ben A., Oostra, Paul M., Ridker, Serena, Sanna, David, Schlessinger, Tim D., Spector, Kari, Stefansson, Elizabeth A., Streeten, Unnur, Thorsteinsdottir, Manuela, Uda, André G., Uitterlinden, Cornelia M., van Duijn, Henry, Völzke, Anna, Murray, Joanne M., Murabito, Jenny A., Visser, Kathryn L., Lunetta, Faculteit Medische Wetenschappen/UMCG, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Lifestyle Medicine (LM), and Center for Liver, Digestive and Metabolic Diseases (CLDM)

Subjects
Netherlands Twin Register (NTR), Candidate gene, Menopause, dna repair, DNA Repair, PROTEIN, Genome-wide association study, DNA-Directed DNA Polymerase, medicine.disease_cause, Bioinformatics, DISEASE, PREMATURE OVARIAN FAILURE, 0302 clinical medicine, NATURAL MENOPAUSE, MUTATION, GENE-EXPRESSION, Genetics, 0303 health sciences, Mutation, 030219 obstetrics & reproductive medicine, Age Factors, 3. Good health, Premature ovarian failure, DNA Polymerase gamma, menopause, loci, genetics, Female, DNA repair, DNA Primase, Biology, Polymorphism, Single Nucleotide, White People, Article, 03 medical and health sciences, FOLLICLE-STIMULATING-HORMONEPREMATURE OVARIAN FAILUREGENOME-WIDE ASSOCIATIONGENE-EXPRESSIONONSETPOLYMORPHISMSMUTATIONHERITABILITYCHROMOSOMEMENARCHE, medicine, Humans, GENOME-WIDE ASSOCIATION, Gene, POLYMORPHISMS, 030304 developmental biology, Genetic association, DNA Helicases, Immunity, Proteins, medicine.disease, FOLLICLE-STIMULATING-HORMONE, DNA Repair Enzymes, Exodeoxyribonucleases, Genetic Loci, ONSET, Genome-Wide Association Study
Abstract

To newly identify loci for age at natural menopause, we carried out a meta-analysis of 22 genome-wide association studies (GWAS) in 38,968 women of European descent, with replication in up to 14,435 women. In addition to four known loci, we identified 13 loci newly associated with age at natural menopause (at P < 5 - 10 g8). Candidate genes located at these newly associated loci include genes implicated in DNA repair (EXO1, HELQ, UIMC1, FAM175A, FANCI, TLK1, POLG and PRIM1) and immune function (IL11, NLRP11 and PRRC2A (also known as BAT2)). Gene-set enrichment pathway analyses using the full GWAS data set identified exoDNase, NF-I °B signaling and mitochondrial dysfunction as biological processes related to timing of menopause. © 2012 Nature America, Inc. All rights reserved.

Published
2012

35. Abstract 49: A Genome-wide Meta-analysis of the Combined Influence of Physical Activity and Genetic Variants on Body Fat Distribution in 94,779 Individuals of European Descent

Author

Mariaelisa Graff, L Xue, Tuomas O Kilpeläinen, Anne Justice, Thomas Winkler, Kristin L Young, Robert Scott, Qibin Qi, David Hadley, Anubha Mahajan, Tarunveer S Ahluwalia, Audrey Y Chu, Jacek Czajkowski, Lu Qi, Julius Ngwa, Toomas Haller, Keri L Monda, M. C Zillikens, Megan Grove, Nancy L Heard-Costa, Paul W Franks, Ingrid B Borecki, Ruth J Loos, Kari E North, and L A Cupples

Subjects
Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

Central adiposity, assessed by waist-to-hip ratio (WHR), has been associated with increased risk for cardiovascular disease. Both genetic and lifestyle factors, including physical inactivity, have been independently associated with WHR adjusted for BMI (WHRadjBMI). Physical activity (PA) is an important component of interventions for reducing or preventing central adiposity and has been shown to attenuate genetic influences on adiposity. However, the influence of PA on loci associated with central fat, independent of total body fat, is unknown. Our objective was to identify genetic variants whose effects on WHRadjBMI are modified by PA. To this end, we performed a meta-analysis of 36 genome-wide association studies, including 94,779 individuals of European ancestry. PA was standardized within each study (physically active and inactive) with the lowest quintile being defined as inactive. WHR was adjusted for BMI, age, and age 2 in men and women separately. Each study tested the SNP x PA interaction alone, and also tested the joint effects of both the interaction and SNP main effect using a two degree of freedom (2df) test. We pooled the results from individual studies using fixed-effects inverse variance weighted meta-analysis in men and women combined and separately. The 2df joint test reached genome-wide significance (p-8 ) for 23 loci, which included 11 novel loci for WHRadjBMI. Of these 11 loci, 7 were identified in women only, and one in men only. For each of the 23 loci, the association of the joint test was primarily driven by the SNP main effect on WHRadjBMI, rather than its interaction with PA. When we examined the interaction effects of the 23 loci, separately from main effect, the interaction reached nominal significance for 11 loci (5 of these were novel): e.g. established loci in/near LYPLAL1 (p=1.0e -7 ), VEGFA (p=3.8e -4 ), TBX15 (p=2.1e -5 in women), and RSPO3 (p=5.5e -3 ), and novel (in women only), in/near TMEM131 (p =3.2e -4 ), FAM186A (p=4.1e -4 ), and FLJ45974 (p=1.9e -3 ). In each case, the effect of the WHRadjBMI-increasing allele was smaller in the active group than in the inactive group; e.g. for the SNP near LYPLAL1 , in the active versus inactive: β[SE] = 0.024(0.036) vs 0.215(0.084), respectively. For the interaction term alone, no loci reached genome-wide significance, but a search at P-6 revealed 3 additional novel loci; 2 in men and women combined (in/near MYO18B and COX11P ) and 1 in men only (in SNW1 ). Our findings suggest that joint tests of main and interaction effects help elucidate the genetic basis of abdominal obesity and that genetic effects are larger in physically inactive compared to active individuals. To follow-up our initial findings, we are currently collecting data from 25 additional studies with genome-wide or Metabochip data.

Published
2014

36. Abstract 21: Accounting For Smoking Behavior In Genome-wide Analysis Of Obesity Phenotypes: The Giant (genetic Investigation Of Anthropometric Traits) Consortium

Author

Anne Justice, Thomas Winkler, Julius Ngwa, Jacek Czajkowski, Kristin Young, David Hadley, Mariaelisa Graf, Daniel Chasman, Qibin Qi, M. Carola Zillikens, Mary F Feitosa, Tarunveer S Ahluwalia, Paul Franks, Tuomas O Kilpeläinen, Toomas Haller, Keri Monda, Claude Bouchard, Nancy L Heard-Costa, Nese Direk, Henning Tiemeier, Ingrid Borecki, Ruth Loos, Kari North, and L. Adrienne Cupples

Subjects
Physiology (medical), Cardiology and Cardiovascular Medicine
Abstract

Obesity, especially central obesity, and cigarette smoking (SMK) are both important risk factors for cardiovascular disease (CVD). Yet, smokers often exhibit lower body mass index (BMI) and higher waist circumference (WC) compared to non-smokers; also, smoking cessation leads to weight gain. Genome-wide association (GWA) studies have identified genetic loci that are associated with risk of overall and central obesity; yet little is known about whether and how SMK influences the genetic susceptibility to obesity. This study aims to discover genetic loci that are associated with obesity, measured as BMI and WC adjusted for BMI (WC a ), and where the effects are hidden by SMK. We used results from 42 studies including up to 126,767 subjects with GWA data available through the GIANT Consortium. Each study employed three association models while considering smoking status (current vs. not current smokers): 1) SNP effects adjusted for SMK (SNPadjSmk), 2) SNP by SMK interaction effects (SNPxSMK), and 3) joint effect of SNP and the SNP x SMK interaction effect (SNPxSMK J ). Study specific results were combined by inverse-variance weighted fixed-effects meta-analyses of the study specific results in men and women separately and then combined sexes. A total of 53 SNPs for WC a reached genome-wide significance (GWS) (pJ ), 27 of these loci are novel for WC a . Additionally, SNPadjSMK and SNPxSMK J models identified a total of 49 SNPs associated with BMI that reached GWS, including 15 novel loci. While no loci reached GWS for SNPxSMK on BMI, one novel SNPxSMK association with WC a near PRNP reached GWS in women. PRNP is highly expressed throughout the CNS and especially the hippocampus, as are many obesity-related genes. PRNP also plays a role in the body’s response to oxidative stress, making it a likely candidate gene for interaction with smoking as well. Of the GWS SNPs, 47 WC a and 41 BMI loci are nearby (

Published
2014

37. The Crotonase Superfamily: Divergently Related Enzymes That Catalyze Different Reactions Involving Acyl Coenzyme A Thioesters

Author

Matthew M. Benning, Hazel M. Holden, John A. Gerlt, and Toomas Haller

Subjects
Models, Molecular, Protein Conformation, Stereochemistry, Molecular Sequence Data, Mitochondria, Liver, Isomerase, Cleavage (embryo), Catalysis, Protein structure, Pseudomonas, Escherichia coli, Animals, Amino Acid Sequence, Enoyl-CoA Hydratase, Peptide sequence, Dehalogenase, chemistry.chemical_classification, Sequence Homology, Amino Acid, Substrate (chemistry), Esters, General Medicine, General Chemistry, Enoyl-CoA hydratase, Rats, Enzyme, chemistry, Biochemistry, Acyl Coenzyme A
Abstract

Synergistic investigations of the reactions catalyzed by several members of an enzyme superfamily provide a more complete understanding of the relationships between structure and function than is possible from focused studies of a single enzyme alone. The crotonase (or enoyl-CoA hydratase) superfamily is such an example whereby members catalyze a wide range of metabolic reactions but share a common structural solution to a mechanistic problem. Some enzymes in the superfamily have been shown to display dehalogenase, hydratase, and isomerase activities. Others have been implicated in carbon-carbon bond formation and cleavage as well as the hydrolysis of thioesters. While seemingly unrelated mechanistically, the common theme in this superfamily is the need to stabilize an enolate anion intermediate derived from an acyl-CoA substrate. This apparently is accomplished by two structurally conserved peptidic NH groups that provide hydrogen bonds to the carbonyl moieties of the acyl-CoA substrates and form an "oxyanion hole".

Published
2000

38. Discovering New Enzymes and Metabolic Pathways: Conversion of Succinate to Propionate by Escherichia coli

Author

Toomas Haller, Thomas Buckel, János Rétey, and John A. Gerlt

Subjects
Methylmalonyl-CoA Decarboxylase, Carboxy-Lyases, Molecular Sequence Data, Racemases and Epimerases, Succinic Acid, Propionyl-CoA carboxylase, Biology, medicine.disease_cause, Biochemistry, Catalysis, chemistry.chemical_compound, Methylmalonyl-CoA, Operon, Escherichia coli, medicine, Propionyl-CoA, Amino Acid Sequence, Cloning, Molecular, Enoyl-CoA Hydratase, Sequence Homology, Amino Acid, Methylmalonyl-CoA mutase, Methylmalonyl-CoA Mutase, Enoyl-CoA hydratase, Molecular biology, Kinetics, Metabolic pathway, chemistry, Genes, Bacterial, Multigene Family, lipids (amino acids, peptides, and proteins), Cobamides, Coenzyme A-Transferases, Propionates, Protein Kinases, Sequence Alignment, Methylmalonyl-CoA decarboxylase, Genome, Bacterial
Abstract

The Escherichia coli genome encodes seven paralogues of the crotonase (enoyl CoA hydratase) superfamily. Four of these have unknown or uncertain functions; their existence was unknown prior to the completion of the E. coli genome sequencing project. The gene encoding one of these, YgfG, is located in a four-gene operon that encodes homologues of methylmalonyl CoA mutases (Sbm) and acyl CoA transferases (YgfH) as well as a putative protein kinase (YgfD/ArgK). We have determined that YgfG is methylmalonyl CoA decarboxylase, YgfH is propionyl CoA:succinate CoA transferase, and Sbm is methylmalonyl CoA mutase. These reactions are sufficient to form a metabolic cycle by which E. coli can catalyze the decarboxylation of succinate to propionate, although the metabolic context of this cycle is unknown. The identification of YgfG as methylmalonyl CoA decarboxylase expands the range of reactions catalyzed by members of the crotonase superfamily.

Published
2000

39. New Reactions in the Crotonase Superfamily: Structure of Methylmalonyl CoA Decarboxylase from Escherichia coli

Author

John A. Gerlt, Toomas Haller, Matthew M. Benning, and Hazel M. Holden

Subjects
Models, Molecular, Methylmalonyl-CoA Decarboxylase, Carboxy-Lyases, Hydrolases, Protein Conformation, Stereochemistry, Protein subunit, Molecular Sequence Data, Isomerase, Sulfides, Random hexamer, Crystallography, X-Ray, Ligands, Biochemistry, Catalysis, Structure-Activity Relationship, chemistry.chemical_compound, Apoenzymes, Methylmalonyl-CoA, Escherichia coli, Least-Squares Analysis, Structural motif, Enoyl-CoA Hydratase, Binding Sites, biology, Active site, Hydrogen Bonding, Lyase, Models, Chemical, chemistry, Multigene Family, biology.protein, Acyl Coenzyme A, Methylmalonyl-CoA decarboxylase, Protein Binding
Abstract

The molecular structure of methylmalonyl CoA decarboxylase (MMCD), a newly defined member of the crotonase superfamily encoded by the Escherichia coli genome, has been solved by X-ray crystallographic analyses to a resolution of 1.85 A for the unliganded form and to a resolution of 2.7 A for a complex with an inert thioether analogue of methylmalonyl CoA. Like two other structurally characterized members of the crotonase superfamily (crotonase and dienoyl CoA isomerase), MMCD is a hexamer (dimer of trimers) with each polypeptide chain composed of two structural motifs. The larger N-terminal domain contains the active site while the smaller C-terminal motif is alpha-helical and involved primarily in trimerization. Unlike the other members of the crotonase superfamily, however, the C-terminal motif is folded back onto the N-terminal domain such that each active site is wholly contained within a single subunit. The carboxylate group of the thioether analogue of methylmalonyl CoA is hydrogen bonded to the peptidic NH group of Gly 110 and the imidazole ring of His 66. From modeling studies, it appears that Tyr 140 is positioned within the active site to participate in the decarboxylation reaction by orienting the carboxylate group of methylmalonyl CoA so that it is orthogonal to the plane of the thioester carbonyl group. Surprisingly, while the active site of MMCD contains Glu 113, which is homologous to the general acid/base Glu 144 in the active site of crotonase, its carboxylate side chain is hydrogen bonded to Arg 86, suggesting that it is not directly involved in catalysis. The new constellation of putative functional groups observed in the active site of MMCD underscores the diversity of function in this superfamily.

Published
2000

40. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations

Author

Jacqueline C.M. Witteman, Nicole Probst-Hensch, Gail Davies, Anna Köttgen, Qunyuan Zhang, Pio D'Adamo, Nicholas G. Martin, Silvia Tore, Stephan J. L. Bakker, Gian Andri Thun, Cinzia Sala, Peter P. Pramstaller, Tamara B. Harris, Aaron Isaacs, Sheila Ulivi, Rossella Sorice, Xuan Liu, Andrew A. Hicks, Henry Völzke, Daniela Ruggiero, Arnold von Eckardstein, Yukinori Okada, Andres Metspalu, Jeffrey Metter, Serena Sanna, Jennifer E. Huffman, Philipp S. Wild, Florian Ernst, Eva Albrecht, Mary F. Feitosa, Claudia Schurmann, Kathrin Budde, Veikko Salomaa, Darina Czamara, Elizabeth G. Holliday, Marcel Bruinenberg, Laura Portas, Maris Laan, Alan J. Gow, Caroline Hayward, Tim D. Spector, Ozren Polasek, Ilja M. Nolte, Rodney J. Scott, Massimo Mangino, David S. Siscovick, Nilesh J. Samani, Toomas Haller, Laura Frogheri, A. Jula, Mika Kähönen, Bruce H. R. Wolffenbuttel, Caroline S. Fox, David R. Jacobs, Julia Shi, Yusuke Nakamura, Daniel I. Chasman, Fabian J. Theis, Alan F. Wright, Ayse Demirkan, Francesco Cucca, Paolo Gasparini, Paul M. Ridker, Olli T. Raitakari, Daniela Toniolo, Maristella Steri, Mario Pirastu, Susan Campbell, Maksim Struchalin, So-Youn Shin, Mark J. Caulfield, H.-Erich Wichmann, Grant W. Montgomery, Åsa Johansson, Alexander Teumer, Ulf Gyllensten, Robert M. Plenge, Michel Burnier, Michael Schallert, Jan Krumsiek, Jing Hua Zhao, Andres Salumets, Poorva Mudgal, Anke Tönjes, James F. Meschia, Gauti Kjartan Gislason, Perttu Salo, Angela Döring, Afshin Parsa, Vilmundur Gudnason, Patrick F. McArdle, Rita P. S. Middelberg, W. H. Linda Kao, Aldi Kraja, Christopher Oldmeadow, Adrienne Tin, Loic Yengo, Murielle Bochud, Gerjan Navis, Christian Gieger, Toshiko Tanaka, Cornelia M. van Duijn, Samuli Ripatti, Terho Lehtimäki, Claudia Langenberg, Bernhard O. Boehm, Conall M. O'Seaghdha, Eric Boerwinkle, Nicole Soranzo, Tõnu Esko, Susan M. Farrington, Mike A. Nalls, John F. Peden, Hyon K. Choi, Anuj Goel, Andrew D. Johnson, Norman Klopp, Anne Grotevendt, Halit Ongen, Marcus E. Kleber, Myriam Fornage, Malcolm G. Dunlop, Igor Rudan, Federico Murgia, Beverley Balkau, Jorma Viikari, Christopher P. Nelson, Gérard Waeber, Lenore J. Launer, Ivana Persico, Inga Prokopenko, Guo Li, Tatijana Zemunik, Elisabetta Trabetti, Tanja Zeller, Hugh Watkins, Qiong Yang, James F. Wilson, Peter Vollenweider, Veronique Vitart, Markus Perola, Nicola Pirastu, Olivier Devuyst, Irene Mateo Leach, John Attia, Bruce M. Psaty, Nicholas J. Wareham, Susanne Lucae, Josef Coresh, Ingrid B. Borecki, Claudia Hundertmark, Weihua Zhang, Luigi Ferrucci, Jaspal S. Kooner, Stefan Kloiber, Lynda M. Rose, Naoyuki Kamatani, Zoltán Kutalik, Giovanni Malerba, Ian J. Deary, Albert V. Smith, Helena Schmidt, Eva Lattka, Philippe Froguel, Harry Campbell, Medea Imboden, Antonio Lupo, Angelo L. Gaffo, Vasiliki Lagou, Alan R. Shuldiner, John Whitfield, Abbas Dehghan, Winfried März, Elin Org, Albert Hofman, Margus Viigimaa, Konstantin Strauch, Toshihiro Tanaka, Andrew B. Singleton, Stefania Bandinelli, Christian Hengstenberg, Xinzhong Li, Wiek H. van Gilst, Pim van der Harst, Giorgio Pistis, Jerome I. Rotter, Maria Grazia Piras, Gary C. Curhan, Brenda W.J.H. Penninx, Ramaiah Nagaraja, Nabila Bouatia-Naji, Christian Müller, Ronald P. Stolk, Pau Navarro, Lorna M. Lopez, Ruth J. F. Loos, Albert Tenesa, Johannes H. Smit, Peter Kraft, Giovanni Gambaro, Sarah H. Wild, Patricia B. Munroe, André G. Uitterlinden, Ivana Kolcic, Bernhard R. Winkelmann, Pankaj Sharma, John C. Chambers, Nicholas D. Hastie, Matthias Nauck, Harold Snieder, Michael Stumvoll, Reinhold Schmidt, Hans L. Hillege, Kiang Liu, Fernando Rivadeneira, Owen M. Woodward, Morris J. Brown, Margus Putku, Sabine Schipf, Mirna Kirin, Kay-Tee Khaw, Melanie Waldenberger, Evropi Theodoratou, Marina Ciullo, Michiaki Kubo, Köttgen, A, Albrecht, E, Teumer, A, Vitart, V, Krumsiek, J, Hundertmark, C, Pistis, G, Ruggiero, D, O'Seaghdha, Cm, Haller, T, Yang, Q, Tanaka, T, Johnson, Ad, Kutalik, Z, Smith, Av, Shi, J, Struchalin, M, Middelberg, Rp, Brown, Mj, Gaffo, Al, Pirastu, Nicola, Li, G, Hayward, C, Zemunik, T, Huffman, J, Yengo, L, Zhao, Jh, Demirkan, A, Feitosa, Mf, Liu, X, Malerba, G, Lopez, Lm, van der Harst, P, Li, X, Kleber, Me, Hicks, Aa, Nolte, Im, Johansson, A, Murgia, F, Wild, Sh, Bakker, Sj, Peden, Jf, Dehghan, A, Steri, M, Tenesa, A, Lagou, V, Salo, P, Mangino, M, Rose, Lm, Lehtimäki, T, Woodward, Om, Okada, Y, Tin, A, Müller, C, Oldmeadow, C, Putku, M, Czamara, D, Kraft, P, Frogheri, L, Thun, Ga, Grotevendt, A, Gislason, Gk, Harris, Tb, Launer, Lj, Mcardle, P, Shuldiner, Ar, Boerwinkle, E, Coresh, J, Schmidt, H, Schallert, M, Martin, Ng, Montgomery, Gw, Kubo, M, Nakamura, Y, Munroe, Pb, Samani, Nj, Jacobs DR, Jr, Liu, K, D'Adamo, ADAMO PIO, Ulivi, S, Rotter, Ji, Psaty, Bm, Vollenweider, P, Waeber, G, Campbell, S, Devuyst, O, Navarro, P, Kolcic, I, Hastie, N, Balkau, B, Froguel, P, Esko, T, Salumets, A, Khaw, Kt, Langenberg, C, Wareham, Nj, Isaacs, A, Kraja, A, Zhang, Q, Wild, P, Scott, Rj, Holliday, Eg, Org, E, Viigimaa, M, Bandinelli, S, Metter, Je, Lupo, A, Trabetti, E, Sorice, R, Döring, A, Lattka, E, Strauch, K, Theis, F, Waldenberger, M, Wichmann, He, Davies, G, Gow, Aj, Bruinenberg, M, Stolk, Rp, Kooner, J, Zhang, W, Winkelmann, Br, Boehm, Bo, Lucae, S, Penninx, Bw, Smit, Jh, Curhan, G, Mudgal, P, Plenge, Rm, Portas, L, Persico, I, Kirin, M, Wilson, Jf, Leach, Im, van Gilst, Wh, Goel, A, Ongen, H, Hofman, A, Rivadeneira, F, Uitterlinden, Ag, Imboden, M, von Eckardstein, A, Cucca, F, Nagaraja, R, Piras, Mg, Nauck, M, Schurmann, C, Budde, K, Ernst, F, Farrington, Sm, Theodoratou, E, Prokopenko, I, Stumvoll, M, Jula, A, Perola, M, Salomaa, V, Shin, Sy, Spector, Td, Sala, C, Ridker, Pm, Kähönen, M, Viikari, J, Hengstenberg, C, Nelson, Cp, Meschia, Jf, Nalls, Ma, Sharma, P, Singleton, Ab, Kamatani, N, Zeller, T, Burnier, M, Attia, J, Laan, M, Klopp, N, Hillege, Hl, Kloiber, S, Choi, H, Pirastu, M, Tore, S, Probst Hensch, Nm, Völzke, H, Gudnason, V, Parsa, A, Schmidt, R, Whitfield, Jb, Fornage, M, Gasparini, Paolo, Siscovick, D, Polašek, O, Campbell, H, Rudan, I, Bouatia Naji, N, Metspalu, A, Loos, Rj, van Duijn, Cm, Borecki, Ib, Ferrucci, L, Gambaro, G, Deary, Ij, Wolffenbuttel, Bh, Chambers, Jc, März, W, Pramstaller, Pp, Snieder, H, Gyllensten, U, Wright, Af, Navis, G, Watkins, H, Witteman, Jc, Sanna, S, Schipf, S, Dunlop, Mg, Tönjes, A, Ripatti, S, Soranzo, N, Toniolo, D, Chasman, Di, Raitakari, O, Kao, Wh, Ciullo, M, Fox, C, Caulfield, M, Bochud, M, Gieger, C, LifeLines Cohort, Study, Cardiogram, Consortium, Diagram, Consortium, Icbp, Consortium, Magic, Consortium, Cardiovascular Centre (CVC), Life Course Epidemiology (LCE), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Vascular Ageing Programme (VAP), Center for Liver, Digestive and Metabolic Diseases (CLDM), Psychiatry, EMGO - Mental health, EMGO+ - Mental Health, LifeLines Cohort Study, CARDIoGRAM Consortium, DIAGRAM Consortium, ICBP Consortium, MAGIC Consortium, Epidemiology, Public Health, and Internal Medicine

Subjects
Candidate gene, Inhibins/genetics, Genome-wide association study, GENETIC-LOCI, chemistry.chemical_compound, 0302 clinical medicine, serum urate, Gene Frequency, Gout/blood, association analysis, serum urate, Glucose/metabolism, Settore MED/14 - NEFROLOGIA, Hyperuricemia, serum, urate, gene, POPULATION, METABOLIC SYNDROME, Genetics, 0303 health sciences, education.field_of_study, biology, Polymorphism, Single Nucleotide/genetics, 3. Good health, HYPERURICEMIA, Genetic Loci/genetics, SLC22A12, Single Nucleotide/genetics, SNPs, Signal Transduction, MOLECULAR PHYSIOLOGY, serum urate concentrations, gout, genome-wide meta-analysis, European Continental Ancestry Group, Population, Polymorphism, Single Nucleotide, White People, Uric Acid/blood, serum urate concentrations, genome-wide meta-analysis, 03 medical and health sciences, SDG 3 - Good Health and Well-being, uric acid, medicine, Humans, Inhibins, Polymorphism, education, 030304 developmental biology, 030203 arthritis & rheumatology, Analysis of Variance, GOUT, IDENTIFICATION, TRANSPORTER, CARDIOVASCULAR-DISEASE RISK, ta3121, medicine.disease, association analysis, Gout, meta-analysis, Glucose, chemistry, Genetic Loci, genome-wide association studies, biology.protein, Signal Transduction/genetics, Uric acid, URIC-ACID LEVELS, Genome-Wide Association Study, SLC2A9
Abstract

Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SFMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout. © 2013 Nature America, Inc. All rights reserved.

Published
2013

41. Nine Loci for Ocular Axial Length Identified through Genome-wide Association Studies, Including Shared Loci with Refractive Error

Author

Ching-Yu Cheng, Maria Schache, M. Kamran Ikram, Terri L. Young, Jeremy A. Guggenheim, Veronique Vitart, Stuart MacGregor, Virginie J.M. Verhoeven, Veluchamy A. Barathi, Jiemin Liao, Pirro G. Hysi, Joan E. Bailey-Wilson, Beate St. Pourcain, John P. Kemp, George McMahon, Nicholas J. Timpson, David M. Evans, Grant W. Montgomery, Aniket Mishra, Ya Xing Wang, Jie Jin Wang, Elena Rochtchina, Ozren Polasek, Alan F. Wright, Najaf Amin, Elisabeth M. van Leeuwen, James F. Wilson, Craig E. Pennell, Cornelia M. van Duijn, Paulus T.V.M. de Jong, Johannes R. Vingerling, Xin Zhou, Peng Chen, Ruoying Li, Wan-Ting Tay, Yingfeng Zheng, Merwyn Chew, Kathryn P. Burdon, Jamie E. Craig, Sudha K. Iyengar, Robert P. Igo, Jonathan H. Lass, Emily Y. Chew, Toomas Haller, Evelin Mihailov, Andres Metspalu, Juho Wedenoja, Claire L. Simpson, Robert Wojciechowski, René Höhn, Alireza Mirshahi, Tanja Zeller, Norbert Pfeiffer, Karl J. Lackner, Thomas Bettecken, Thomas Meitinger, Konrad Oexle, Mario Pirastu, Laura Portas, Abhishek Nag, Katie M. Williams, Ekaterina Yonova-Doing, Ronald Klein, Barbara E. Klein, S. Mohsen Hosseini, Andrew D. Paterson, Kari-Matti Makela, Terho Lehtimaki, Mika Kahonen, Olli Raitakari, Nagahisa Yoshimura, Fumihiko Matsuda, Li Jia Chen, Chi Pui Pang, Shea Ping Yip, Maurice K.H. Yap, Akira Meguro, Nobuhisa Mizuki, Hidetoshi Inoko, Paul J. Foster, Jing Hua Zhao, Eranga Vithana, E-Shyong Tai, Qiao Fan, Liang Xu, Harry Campbell, Brian Fleck, Igor Rudan, Tin Aung, Albert Hofman, André G. Uitterlinden, Goran Bencic, Chiea-Chuen Khor, Hannah Forward, Olavi Pärssinen, Paul Mitchell, Fernando Rivadeneira, Alex W. Hewitt, Cathy Williams, Ben A. Oostra, Yik-Ying Teo, Christopher J. Hammond, Dwight Stambolian, David A. Mackey, Caroline C.W. Klaver, Tien-Yin Wong, Seang-Mei Saw, Paul N. Baird, William Reinhart, Michael W. Belin, Robert L. Schultze, Todd Morason, Alan Sugar, Shahzad Mian, Hunson Kaz Soong, Kathryn Colby, Ula Jurkunas, Richard Yee, Mark Vital, Eduardo Alfonso, Carol Karp, Yunhee Lee, Sonia Yoo, Kristin Hammersmith, Elisabeth Cohen, Peter Laibson, Christopher Rapuano, Brandon Ayres, Christopher Croasdale, James Caudill, Sanjay Patel, Keith Baratz, William Bourne, Leo Maguire, Joel Sugar, Elmer Tu, Ali Djalilian, Vinod Mootha, James McCulley, Wayne Bowman, H. Dwight Cavanaugh, Steven Verity, David Verdier, Ann Renucci, Matt Oliva, Walter Rotkis, David R. Hardten, Ahmad Fahmy, Marlene Brown, Sherman Reeves, Elizabeth A. Davis, Richard Lindstrom, Scott Hauswirth, Stephen Hamilton, W. Barry Lee, Francis Price, Marianne Price, Kathleen Kelly, Faye Peters, Michael Shaughnessy, Thomas Steinemann, B.J. Dupps, David M. Meisler, Mark Mifflin, Randal Olson, Anthony Aldave, Gary Holland, Bartly J. Mondino, George Rosenwasser, Mark Gorovoy, Steven P. Dunn, David G. Heidemann, Mark Terry, Neda Shamie, Steven I. Rosenfeld, Brandon Suedekum, David Hwang, Donald Stone, James Chodosh, Paul G. Galentine, David Bardenstein, Katrina Goddard, Hemin Chin, Mark Mannis, Rohit Varma, Ingrid Borecki, Ophthalmology, Epidemiology, Internal Medicine, Clinical Genetics, Obstetrics & Gynecology, and Netherlands Institute for Neuroscience (NIN)

Subjects
Adult, Male, Refractive error, Adolescent, Gene Expression, Locus (genetics), Genome-wide association study, Biology, Ocular Axial Length, Polymorphism, Single Nucleotide, White People, Article, 03 medical and health sciences, 0302 clinical medicine, Asian People, SDG 3 - Good Health and Well-being, medicine, Genetics, Humans, GWAS, Genetic Predisposition to Disease, Genetics(clinical), RSPO1, Eye Proteins, Gene, Genetics (clinical), 030304 developmental biology, Genetic association, Aged, 0303 health sciences, ta1184, Heritability, Middle Aged, ta3121, medicine.disease, Refractive Errors, Axial Length, Eye, Genetic Loci, 030221 ophthalmology & optometry, Eye disorder, Female, Genome-Wide Association Study, Signal Transduction
Abstract

Refractive errors are common eye disorders of public health importance worldwide. Ocular axial length (AL) is the major determinant of refraction and thus of myopia and hyperopia. We conducted a meta-analysis of genome-wide association studies for AL, combining 12,531 Europeans and 8,216 Asians. We identified eight genome-wide significant loci for AL (RSPO1, C3orf26, LAMA2, GJD2, ZNRF3, CD55, MIP, and ALPPL2) and confirmed one previously reported AL locus (ZC3H11B). Of the nine loci, five (LAMA2, GJD2, CD55, ALPPL2, and ZC3H11B) were associated with refraction in 18 independent cohorts (n = 23,591). Differential gene expression was observed for these loci in minus-lens-induced myopia mouse experiments and human ocular tissues. Two of the AL genes, RSPO1 and ZNRF3, are involved in Wnt signaling, a pathway playing a major role in the regulation of eyeball size. This study provides evidence of shared genes between AL and refraction, but importantly also suggests that these traits may have unique pathways.

Published
2013

42. Meta-analysis of gene-environment-wide association scans accounting for education level identifies additional loci for refractive error

Author

Nicholas G. Martin, René Höhn, Nagahisa Yoshimura, Jonathan H. Lass, Ilkka Seppälä, Masahiro Miyake, Kay-Tee Khaw, Pirro G. Hysi, Rhys Fogarty, Yi Lu, Zoran Vatavuk, Cécile Delcourt, Andrew D. Paterson, John P. Kemp, Jeremy A. Guggenheim, Jaakko Kaprio, Robert P. Igo, James F. Wilson, Stuart MacGregor, Anthony P Khawaja, Beate St Pourcain, Margaret M. DeAngelis, Jing Hua Zhao, Cornelia M. van Duijn, Olavi Pärssinen, Terho Lehtimäki, Roger W. Beuerman, Leslie J. Raffel, Eranga N. Vithana, Caroline Hayward, Cathy Williams, Thomas Meitinger, Lei Zhou, Candice E H Ho, Ozren Polasek, Hoi Suen Wong, Jie Jin Wang, Nicholas J. Timpson, Norbert Pfeiffer, Toomas Haller, Akira Meguro, Wei Chen, Ching-Yu Cheng, Vishal Jhanji, Johannes R. Vingerling, Mika Kähönen, Puya Gharahkhani, Sheng Feng, Nobuhisa Mizuki, Maurice Yap, Katie M Williams, Vincent Tan, Paul Mitchell, Taina Rantanen, Sudha K. Iyengar, Seang-Mei Saw, Christopher J Hammond, Kathryn P. Burdon, Harry Campbell, Sarayut Janmahasatian, Andres Metspalu, Caroline C W Klaver, Jugnoo S Rahi, Kenji Yamashiro, Laura Portas, Céline Bellenguez, Igor Rudan, Robert Luben, Virginie J. M. Verhoeven, Mary Frances Cotch, Paul N. Baird, Qiao Fan, Najaf Amin, David A. Mackey, Jenifer E. Huffman, Emily Y. Chew, Veluchamy A. Barathi, Tien Yin Wong, Ronald Klein, Jeremy Fondran, Mario Pirastu, Alan F. Wright, Jamie E Craig, Brian W Fleck, Paul J. Foster, Alvin L. Young, Alex W. Hewitt, Tin Aung, Maurizio Fossarello, Kari-Matti Mäkelä, Tanja Zeller, Maria Blettner, Xu Wang, Eileen Tai-Hui Boh, Terri L. Young, Mingguang He, Joan E. Bailey Wilson, Olli T. Raitakari, Shea Ping Yip, M. Kamran Ikram, Seyhan Yazar, Albert Hofman, Alireza Mirshahi, Tae Hwi Schwantes-An, Charumathi Sabanayagam, Pancy O. S. Tam, Ginevra Biino, Xiaobo Guo, Angela Döring, Audrey Cougnard-Gregoire, David M. Evans, Xiaohui Li, Christian Gieger, Songhomitra Panda-Jonas, Jost B. Jonas, Jan Willem L Tideman, Maria Schache, Chi Pui Pang, Barbara E.K. Klein, Simona Vaccargiu, Veronique Vitart, Jing Xie, Claire L. Simpson, S. Mohsen Hosseini, Chiea Chuen Khor, Dwight Stambolian, E. Shyong Tai, Xiangtian Zhou, Li Jia Chen, Milly S. Tedja, Margaux A. Morrison, Janina S. Ried, Yik Ying Teo, Konrad Oexle, Robert Wojciechowski, Nicholas J. Wareham, André G. Uitterlinden, Peter K. Joshi, Ya Xing Wang, Jean-François Korobelnik, George McMahon, Vinay Nangia, Elisabeth M. van Leeuwen, Lindsay A. Farrer, Preeti Gupta, Johanna Mazur, Evelin Mihailov, Wan’E. Lim, George Davey Smith, Liang Xu, Rosalynn Grace Siantar, Juho Wedenoja, Cristina Venturini, Fernando Rivadeneira, Clinicum, Department of Public Health, Silmäklinikka, Jaakko Kaprio / Principal Investigator, Institute for Molecular Medicine Finland, Genetic Epidemiology, Consortium for Refractive Error and Myopia (CREAM), Clinical Genetics, Erasmus MC other, Epidemiology, Internal Medicine, Ophthalmology, and Obstetrics & Gynecology

Subjects
0301 basic medicine, Refractive error, genetic structures, General Physics and Astronomy, Genome-wide association study, VARIANTS, refractive error, gene, EYE, Bioinformatics, INCIDENT MYOPIA, Genome-wide association studies, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], 0302 clinical medicine, Polymorphism (computer science), 10. No inequality, POPULATION, education.field_of_study, Multidisciplinary, ACTIVATED PROTEIN-KINASE, ta3142, single-nucleotide polymorphism, RETINAL-PIGMENT EPITHELIUM, OUTDOOR ACTIVITY, 3142 Public health care science, environmental and occupational health, 3. Good health, Refractive errors, Meta-analysis, loci, Educational Status, Science, Population, 610 Medicine & health, Environment, Biology, ta3111, Polymorphism, Single Nucleotide, Article, White People, General Biochemistry, Genetics and Molecular Biology, Education, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, Genetic variation, medicine, Humans, SNP, Genetic Predisposition to Disease, myopia, 3125 Otorhinolaryngology, ophthalmology, education, RECEPTOR, Gene Expression Profiling, ta1184, General Chemistry, Heritability, medicine.disease, eye diseases, ta3125, TIME OUTDOORS, 030104 developmental biology, Genetic Loci, Evolutionary biology, RISK-FACTORS, 030221 ophthalmology & optometry, RE, sense organs, 3111 Biomedicine, Genome-Wide Association Study
Abstract

Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P, This report by the Consortium for Refractive Error and Myopia uses gene-environment-wide interaction study (GEWIS) to identify genetic loci that affect environmental influence in myopia development, and identifies ethnic specific genetic loci that attribute to eye refractive errors.

Published
2016

43. A Voxel-Based Monte Carlo Model of Drug Release from Bulk Eroding Nanoparticles

Author

David A. Eavarone, Venkataramanan Soundararajan, Ram Sasisekharan, Toomas Haller, Harvard University--MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology. Department of Biological Engineering, Koch Institute for Integrative Cancer Research at MIT, Eavarone, David A., Soundararajan, Venkataramanan, Haller, Toomas, and Sasisekharan, Ram

Subjects
Materials science, Monte Carlo method, Biomedical Engineering, Nanoparticle, Bioengineering, Nanotechnology, Model parameters, In Vitro Techniques, computer.software_genre, Models, Biological, Article, Dexamethasone, Drug Delivery Systems, Polylactic Acid-Polyglycolic Acid Copolymer, Voxel, Humans, General Materials Science, Lactic Acid, General Chemistry, Condensed Matter Physics, Polymeric nanoparticles, Drug delivery, Drug release, Particle, Nanoparticles, computer, Monte Carlo Method, Polyglycolic Acid
Abstract

The use of polymeric nanoparticles as drug delivery devices is becoming increasingly prevalent in a variety of therapeutic applications. Despite their widespread clinical use, the factors influencing the release profiles of nanoparticle-encapsulated drugs are still not quantitatively understood. We present here a new, semi-empirical model of drug release from polymeric nanoparticles using a formulation of dexamethasone encapsulated within poly(lactic-co-glycolic acid) to set model parameters. We introduce a three-dimensional voxel-based framework for Monte Carlo simulations that enables direct investigation of the entire spherical nanoparticle during particle degradation and drug release. Due to implementation of this model at the nanoscale, we utilize assumptions that simplify the model while still allowing multi-phase drug release to be simulated with good correlation to experimental results. In the future, emerging mechanistic understandings of nanoparticle drug release may be integrated into this simulation framework to increase predictive power., National Institutes of Health (U.S.) (GM57073)

Published
2010

44. Biomarker Profiling by Nuclear Magnetic Resonance Spectroscopy for the Prediction of All-Cause Mortality: An Observational Study of 17,345 Persons

Author

Steven Smit, Andres Metspalu, Pasi Soininen, Johannes Kettunen, Markus Perola, Krista Fischer, Mika Ala-Korpela, Aki S. Havulinna, Aarno Palotie, Antti J. Kangas, Reedik Mägi, Veikko Salomaa, Samuli Ripatti, Peter Würtz, Tõnu Esko, Toomas Haller, Mari-Liis Tammesoo, Institute for Molecular Medicine Finland, Hjelt Institute (-2014), Biostatistics Helsinki, Quantitative Genetics, Complex Disease Genetics, and Genomics of Neurological and Neuropsychiatric Disorders

Subjects
Male, Oncology, Pathology, Magnetic Resonance Spectroscopy, Time Factors, Epidemiology, Kaplan-Meier Estimate, ISCHEMIC-HEART-DISEASE, 030204 cardiovascular system & hematology, Biochemistry, Lipoprotein particle, SERUM-ALBUMIN, 0302 clinical medicine, Risk Factors, Cause of Death, ALPHA-1-ACID GLYCOPROTEIN, Finland, Biological Specimen Banks, Cause of death, Aged, 80 and over, RISK, Clinical Chemistry, Molecular Epidemiology, 0303 health sciences, education.field_of_study, Mortality rate, Hazard ratio, DEATH, Epidemiology of Aging, MEN, Orosomucoid, ASSOCIATION, General Medicine, Middle Aged, Prognosis, CANCER, Clinical Laboratory Sciences, 3. Good health, Lipoproteins, LDL, Blood Chemistry, Cohort, Medicine, Biomarker (medicine), Female, Public Health, Risk assessment, Research Article, Biotechnology, Adult, Estonia, medicine.medical_specialty, Adolescent, education, Population, Serum Albumin, Human, Risk Assessment, Citric Acid, Young Adult, 03 medical and health sciences, INFLAMMATION, Diagnostic Medicine, Predictive Value of Tests, Internal medicine, medicine, Humans, Particle Size, Biology, Serum Albumin, Aged, Proportional Hazards Models, 030304 developmental biology, business.industry, Reproducibility of Results, High-Throughput Screening Assays, Biomarker Epidemiology, Metabolism, MYOCARDIAL-INFARCTION, 3121 General medicine, internal medicine and other clinical medicine, Preventive Medicine, business, Biomarkers
Abstract

In this study, Würtz and colleagues conducted high-throughput profiling of blood specimens in two large population-based cohorts in order to identify biomarkers for all-cause mortality and enhance risk prediction. The authors found that biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. However, further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers to guide screening and prevention. Please see later in the article for the Editors' Summary, Background Early identification of ambulatory persons at high short-term risk of death could benefit targeted prevention. To identify biomarkers for all-cause mortality and enhance risk prediction, we conducted high-throughput profiling of blood specimens in two large population-based cohorts. Methods and Findings 106 candidate biomarkers were quantified by nuclear magnetic resonance spectroscopy of non-fasting plasma samples from a random subset of the Estonian Biobank (n = 9,842; age range 18–103 y; 508 deaths during a median of 5.4 y of follow-up). Biomarkers for all-cause mortality were examined using stepwise proportional hazards models. Significant biomarkers were validated and incremental predictive utility assessed in a population-based cohort from Finland (n = 7,503; 176 deaths during 5 y of follow-up). Four circulating biomarkers predicted the risk of all-cause mortality among participants from the Estonian Biobank after adjusting for conventional risk factors: alpha-1-acid glycoprotein (hazard ratio [HR] 1.67 per 1–standard deviation increment, 95% CI 1.53–1.82, p = 5×10−31), albumin (HR 0.70, 95% CI 0.65–0.76, p = 2×10−18), very-low-density lipoprotein particle size (HR 0.69, 95% CI 0.62–0.77, p = 3×10−12), and citrate (HR 1.33, 95% CI 1.21–1.45, p = 5×10−10). All four biomarkers were predictive of cardiovascular mortality, as well as death from cancer and other nonvascular diseases. One in five participants in the Estonian Biobank cohort with a biomarker summary score within the highest percentile died during the first year of follow-up, indicating prominent systemic reflections of frailty. The biomarker associations all replicated in the Finnish validation cohort. Including the four biomarkers in a risk prediction score improved risk assessment for 5-y mortality (increase in C-statistics 0.031, p = 0.01; continuous reclassification improvement 26.3%, p = 0.001). Conclusions Biomarker associations with cardiovascular, nonvascular, and cancer mortality suggest novel systemic connectivities across seemingly disparate morbidities. The biomarker profiling improved prediction of the short-term risk of death from all causes above established risk factors. Further investigations are needed to clarify the biological mechanisms and the utility of these biomarkers for guiding screening and prevention. Please see later in the article for the Editors' Summary, Editors' Summary Background A biomarker is a biological molecule found in blood, body fluids, or tissues that may signal an abnormal process, a condition, or a disease. The level of a particular biomarker may indicate a patient's risk of disease, or likely response to a treatment. For example, cholesterol levels are measured to assess the risk of heart disease. Most current biomarkers are used to test an individual's risk of developing a specific condition. There are none that accurately assess whether a person is at risk of ill health generally, or likely to die soon from a disease. Early and accurate identification of people who appear healthy but in fact have an underlying serious illness would provide valuable opportunities for preventative treatment. While most tests measure the levels of a specific biomarker, there are some technologies that allow blood samples to be screened for a wide range of biomarkers. These include nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry. These tools have the potential to be used to screen the general population for a range of different biomarkers. Why Was This Study Done? Identifying new biomarkers that provide insight into the risk of death from all causes could be an important step in linking different diseases and assessing patient risk. The authors in this study screened patient samples using NMR spectroscopy for biomarkers that accurately predict the risk of death particularly amongst the general population, rather than amongst people already known to be ill. What Did the Researchers Do and Find? The researchers studied two large groups of people, one in Estonia and one in Finland. Both countries have set up health registries that collect and store blood samples and health records over many years. The registries include large numbers of people who are representative of the wider population. The researchers first tested blood samples from a representative subset of the Estonian group, testing 9,842 samples in total. They looked at 106 different biomarkers in each sample using NMR spectroscopy. They also looked at the health records of this group and found that 508 people died during the follow-up period after the blood sample was taken, the majority from heart disease, cancer, and other diseases. Using statistical analysis, they looked for any links between the levels of different biomarkers in the blood and people's short-term risk of dying. They found that the levels of four biomarkers—plasma albumin, alpha-1-acid glycoprotein, very-low-density lipoprotein (VLDL) particle size, and citrate—appeared to accurately predict short-term risk of death. They repeated this study with the Finnish group, this time with 7,503 individuals (176 of whom died during the five-year follow-up period after giving a blood sample) and found similar results. The researchers carried out further statistical analyses to take into account other known factors that might have contributed to the risk of life-threatening illness. These included factors such as age, weight, tobacco and alcohol use, cholesterol levels, and pre-existing illness, such as diabetes and cancer. The association between the four biomarkers and short-term risk of death remained the same even when controlling for these other factors. The analysis also showed that combining the test results for all four biomarkers, to produce a biomarker score, provided a more accurate measure of risk than any of the biomarkers individually. This biomarker score also proved to be the strongest predictor of short-term risk of dying in the Estonian group. Individuals with a biomarker score in the top 20% had a risk of dying within five years that was 19 times greater than that of individuals with a score in the bottom 20% (288 versus 15 deaths). What Do These Findings Mean? This study suggests that there are four biomarkers in the blood—alpha-1-acid glycoprotein, albumin, VLDL particle size, and citrate—that can be measured by NMR spectroscopy to assess whether otherwise healthy people are at short-term risk of dying from heart disease, cancer, and other illnesses. However, further validation of these findings is still required, and additional studies should examine the biomarker specificity and associations in settings closer to clinical practice. The combined biomarker score appears to be a more accurate predictor of risk than tests for more commonly known risk factors. Identifying individuals who are at high risk using these biomarkers might help to target preventative medical treatments to those with the greatest need. However, there are several limitations to this study. As an observational study, it provides evidence of only a correlation between a biomarker score and ill health. It does not identify any underlying causes. Other factors, not detectable by NMR spectroscopy, might be the true cause of serious health problems and would provide a more accurate assessment of risk. Nor does this study identify what kinds of treatment might prove successful in reducing the risks. Therefore, more research is needed to determine whether testing for these biomarkers would provide any clinical benefit. There were also some technical limitations to the study. NMR spectroscopy does not detect as many biomarkers as mass spectrometry, which might therefore identify further biomarkers for a more accurate risk assessment. In addition, because both study groups were northern European, it is not yet known whether the results would be the same in other ethnic groups or populations with different lifestyles. In spite of these limitations, the fact that the same four biomarkers are associated with a short-term risk of death from a variety of diseases does suggest that similar underlying mechanisms are taking place. This observation points to some potentially valuable areas of research to understand precisely what's contributing to the increased risk. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001606 The US National Institute of Environmental Health Sciences has information on biomarkers The US Food and Drug Administration has a Biomarker Qualification Program to help researchers in identifying and evaluating new biomarkers Further information on the Estonian Biobank is available The Computational Medicine Research Team of the University of Oulu and the University of Bristol have a webpage that provides further information on high-throughput biomarker profiling by NMR spectroscopy

Published
2014

45. ChemInform Abstract: The Crotonase Superfamily: Divergently Related Enzymes that Catalyze Different Reactions Involving Acyl Coenzyme A Thioesters

Author

John A. Gerlt, Matthew M. Benning, Toomas Haller, and Hazel M. Holden

Subjects
chemistry.chemical_classification, Hydrolysis, Enzyme, chemistry, Stereochemistry, Hydrogen bond, Substrate (chemistry), General Medicine, Isomerase, Cleavage (embryo), Catalysis, Dehalogenase
Abstract

Synergistic investigations of the reactions catalyzed by several members of an enzyme superfamily provide a more complete understanding of the relationships between structure and function than is possible from focused studies of a single enzyme alone. The crotonase (or enoyl-CoA hydratase) superfamily is such an example whereby members catalyze a wide range of metabolic reactions but share a common structural solution to a mechanistic problem. Some enzymes in the superfamily have been shown to display dehalogenase, hydratase, and isomerase activities. Others have been implicated in carbon−carbon bond formation and cleavage as well as the hydrolysis of thioesters. While seemingly unrelated mechanistically, the common theme in this superfamily is the need to stabilize an enolate anion intermediate derived from an acyl-CoA substrate. This apparently is accomplished by two structurally conserved peptidic NH groups that provide hydrogen bonds to the carbonyl moieties of the acyl-CoA substrates and form an “oxy...

Published
2001

46. Circulating metabolites and general cognitive ability and dementia: Evidence from 11 cohort studies

Author

Francisca A. de Leeuw, Jenny van Dongen, Wiesje M. van der Flier, Leonie Weinhold, Andres Metspalu, Toomas Haller, Catharina E. M. van Beijsterveldt, Mika Kivimäki, Sven J. van der Lee, Martin J. Shipley, Michael Wagner, Johannes Hertel, Aswin Verhoeven, Cornelia M. van Duijn, Krista Fischer, Robert E. Gertzen, Kathrin Budde, Nele Friedrich, Qiong Yang, P. Eline Slagboom, Sudha Seshadri, Maik Pietzner, Vincent Chouraki, Jussi Hernesniemi, Alexander Teumer, Charlotte E. Teunissen, Sarah Egert, Ayse Demirkan, M. Arfan Ikram, Wolfgang Maier, Shuo Li, Philip Scheltens, Juho Tynkkynen, Gonneke Willemsen, Ko Willems van Dijk, Carel F.W. Peeters, René Pool, Dorret I. Boomsma, Veikko Salomaa, Holger Wagner, Najaf Amin, Thomas Hankemeier, Archana Singh-Manoux, Ramachandran S. Vasan, Hans Joergen Grabe, Markus Perola, Debora Melo van Lent, Alfredo Ramirez, Epidemiology, Radiology & Nuclear Medicine, Biological Psychology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, APH - Mental Health, APH - Methodology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Neurodegeneration, Neurology, Laboratory Medicine, Division 6, Epidemiology and Data Science, Institute for Molecular Medicine Finland, and University of Helsinki

Subjects
0301 basic medicine, Oncology, Apolipoprotein E, Netherlands Twin Register (NTR), Male, Epidemiology, Genome-wide association study, Disease, LOTHIAN BIRTH COHORT, Lifestyle factors, 3124 Neurology and psychiatry, FATTY-ACID-COMPOSITION, Cohort Studies, metabolism [Cognitive Dysfunction], 0302 clinical medicine, Risk Factors, Metabolites, Cognitive decline, Health Policy, Cognition, Alzheimer's disease, Middle Aged, 3. Good health, ALZHEIMERS-DISEASE, Psychiatry and Mental health, Female, Cognitive function, ERASMUS RUCPHEN FAMILY, metabolism [Alzheimer Disease], metabolism [Biomarkers], Cohort study, Adult, medicine.medical_specialty, HDL, General cognitive ability, UNITED-STATES, 03 medical and health sciences, Cellular and Molecular Neuroscience, Developmental Neuroscience, SDG 3 - Good Health and Well-being, Alzheimer Disease, Internal medicine, mental disorders, medicine, Dementia, Metabolomics, Humans, Cognitive Dysfunction, ddc:610, metabolism [Dementia], GENOME-WIDE ASSOCIATION, SERUM-CHOLESTEROL, Life Style, Aged, BLOOD-BRAIN-BARRIER, business.industry, 3112 Neurosciences, Reproducibility of Results, ROTTERDAM, medicine.disease, NMR, 030104 developmental biology, Neurology (clinical), Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, Biomarkers, Lipoprotein
Abstract

Correction: Volume: 15 Issue: 2 Pages: 319-319 DOI: 10.1016/j.jalz.2019.01.002 WOS:000457693500015 Introduction: Identifying circulating metabolites that are associated with cognition and dementia may improve our understanding of the pathogenesis of dementia and provide crucial readouts for preventive and therapeutic interventions. Methods: We studied 299 metabolites in relation to cognition (general cognitive ability) in two discovery cohorts (N total = 5658). Metabolites significantly associated with cognition after adjusting for multiple testing were replicated in four independent cohorts (N total = 6652), and the associations with dementia and Alzheimer's disease (N = 25,872) and lifestyle factors (N = 5168) were examined. Results: We discovered and replicated 15 metabolites associated with cognition including subfractions of high-density lipoprotein, docosahexaenoic acid, ornithine, glutamine, and glycoprotein acetyls. These associations were independent of classical risk factors including high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, triglycerides, glucose, and apolipoprotein E (APOE) genotypes. Six of the cognition-associated metabolites were related to the risk of dementia and lifestyle factors. Discussion: Circulating metabolites were consistently associated with cognition, dementia, and lifestyle factors, opening new avenues for prevention of cognitive decline and dementia. (C) 2018 The Authors. Published by Elsevier Inc. on behalf of the Alzheimer's Association.

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47. Genome-wide analysis of nuclear magnetic resonance metabolites revealed parent-of-origin effect on triglycerides in medium very low-density lipoprotein in PTPRD gene

Author

Viktorija Kukushkina, Reedik Mägi, Toomas Haller, Veikko Salomaa, Natalia Pervjakova, Markus Perola, Anni Joensuu, Silva Kasela, Pekka Jousilahti, Tarmo Annilo, Kati Kristiansson, Andres Metspalu, Quantitative Genetics, Institute for Molecular Medicine Finland, and University of Helsinki

Subjects
Adult, Male, 0301 basic medicine, Very low-density lipoprotein, HOMEOSTASIS, Magnetic Resonance Spectroscopy, Genotype, Metabolite, Clinical Biochemistry, Genome wide analysis, LOCI, Lipoproteins, VLDL, EGCUT, DISEASE, 03 medical and health sciences, chemistry.chemical_compound, Nuclear magnetic resonance, Missing heritability problem, MISSING HERITABILITY, Drug Discovery, NMR metabolites, CARDIOVASCULAR RISK-FACTORS, Humans, Metabolomics, Medicine, FINRISK, PERSPECTIVE, Triglycerides, ARCHITECTURE, business.industry, Biochemistry (medical), Receptor-Like Protein Tyrosine Phosphatases, Class 2, Genetic variants, PTPRD, Genomics, ASSOCIATION, FINLAND, PTPRD Gene, 030104 developmental biology, chemistry, RICH LIPOPROTEINS, Female, 3111 Biomedicine, parent-of-origin effects, business, VLDL, Lipoprotein
Abstract

Aim: The aim of the study was to explore the parent-of-origin effects (POEs) on a range of human nuclear magnetic resonance metabolites. Materials & methods: We search for POEs in 14,815 unrelated individuals from Estonian and Finnish cohorts using POE method for the genotype data imputed with 1000 G reference panel and 82 nuclear magnetic resonance metabolites. Results: Meta-analysis revealed the evidence of POE for the variant rs1412727 in PTPRD gene for the metabolite: triglycerides in medium very low-density lipoprotein. No POEs were detected for genetic variants that were previously known to have main effect on circulating metabolites. Conclusion: We demonstrated possibility to detect POEs for human metabolites, but the POEs are weak, and therefore it is hard to detect those using currently available sample sizes.

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48. Metabolites of milk intake: a metabolomic approach in UK twins with findings replicated in two European cohorts

Author

Tiphaine Martin, Barbara Thorand, Alex J. MacGregor, Aedin Cassidy, Robert P. Mohney, Cristina Menni, Tess Pallister, Gabi Kastenmüller, Andres Metspalu, Christian Gieger, Amy Jennings, Tim D. Spector, Elisabeth Altmaier, and Toomas Haller

Subjects
0301 basic medicine, Male, Metabolite, Twins, Physiology, Medicine (miscellaneous), Urine, Bioinformatics, Body Mass Index, Cohort Studies, chemistry.chemical_compound, Surveys and Questionnaires, Epidemiology, Micronutrients, 2. Zero hunger, Nutrition and Dietetics, Original Contribution, Middle Aged, Micronutrient, Milk, Cohort, Metabolome, Female, Dietary Proteins, Cohort study, Adult, medicine.medical_specialty, Models, Biological, Sensitivity and Specificity, 03 medical and health sciences, Young Adult, Journal Article, medicine, Dietary Carbohydrates, Valerates, Animals, Humans, Metabolomics, Biomarkers, Nutrition, Uridine, Aged, 030109 nutrition & dietetics, business.industry, Dietary Fats, United Kingdom, Diet, 030104 developmental biology, Nutrition Assessment, chemistry, business, Body mass index
Abstract

PURPOSE: Milk provides a significant source of calcium, protein, vitamins and other minerals to Western populations throughout life. Due to its widespread use, the metabolic and health impact of milk consumption warrants further investigation and biomarkers would aid epidemiological studies. METHODS: Milk intake assessed by a validated food frequency questionnaire was analyzed against fasting blood metabolomic profiles from two metabolomic platforms in females from the TwinsUK cohort (n=3559). The top metabolites were then replicated in two independent populations (EGCUT, n=1109 and KORA, n=1593), and the results from all cohorts were meta-analyzed. RESULTS: Four metabolites were significantly associated with milk intake in the TwinsUK cohort after adjustment for multiple testing (P&nbsp

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49. The Application for Visualizing Data Inquiries

Author

Joosep, Tanel, Toomas Haller, and Tõnis Tasa

Abstract

Käesoleva bakalaureusetöö kirjutamise käigus valmis andmepäringute visualiseerimise rakendus, mille loomisel kasutati Java 8 ning sellesse sisseehitatud lisateeke – JavaFX, Nashorn JavaScript Engine. Paremate kasutajaliidese komponentide lisamiseks kasutati ControlsFX teeki. Jõudlustestide täpsemaks hindamiseks kasutati vastavatesse rakendustesse sisse ehitatud ajamõõtmise funktsioone. Rakendus loodi ideega lihtsustada programmeerimisega igapäevaselt mitte tegelevate inimeste tööd andmete esmases analüüsis. Rakenduse eesmärk on pakkuda lõppkasutajale mugavat ja intuitiivse lähenemisega andmetöötlust. Rakendus on vabavaraline ning mõeldud kõigile kasutamiseks., The purpose of this Bachelors thesis is to develop a desktop application that helps to visualize data inquiries and provides an intuitive overview of data. The following technologies were used: Java 8, JavaFX, Nashorn JavaScript Engine and ControlsFX library for better user interface design. The application was created with the idea of simplifying the work of people without programming skills and statistical background. The main aim of the application was to provide the end user a convenient a toll for data queries. The application is freeware and publicly available.

Published
2017

50. Genome-wide association study identifies six new loci influencing pulse pressure and mean arterial pressure

Author

Wain, Louise V., Verwoert, Germaine C., O'Reilly, Paul F., Shi, Gang, Johnson, Toby, Johnson, Andrew D., Bochud, Murielle, Rice, Kenneth M., Henneman, Peter, Smith, Albert V., Ehret, Georg B., Amin, Najaf, Larson, Martin G., Mooser, Vincent, Hadley, David, Dörr, Marcus, Bis, Joshua C, Aspelund, Thor, Esko, Tõnu, Janssens, A Cecile J. W., Zhao, Jing Hua, Heath, Simon, Laan, Maris, Fu, Jingyuan, Pistis, Giorgio, Luan, Jian'An, Arora, Pankaj, Lucas, Gavin, Pirastu, Nicola, Pichler, Irene, Jackson, Anne U., Webster, Rebecca J., Zhang, Feng, Peden, John F., Schmidt, Helena, Tanaka, Toshiko, Campbell, Harry, Igl, Wilmar, Milaneschi, Yuri, Hottenga, Jouke-Jan, Vitart, Veronique, Chasman, Daniel I., Trompet, Stella, Bragg-Gresham, Jennifer L., Alizadeh, Behrooz Z., Chambers, John C., Guo, Xiuqing, Lehtimäki, Terho, Kühnel, Brigitte, Lopez, Lorna M., Polašek, Ozren, Boban, Mladen, Nelson, Christopher P., Morrison, Alanna C., Pihur, Vasyl, Ganesh, Santhi K., Hofman, Albert, Kundu, Suman, Mattace-Raso, Francesco U. S., Rivadeneira, Fernando, Sijbrands, Eric J. G., Uitterlinden, Andre G., Hwang, Shih-Jen, Vasan, Ramachandran S., Wang, Thomas J., Bergmann, Sven, Vollenweider, Peter, Waeber, Gérard, Laitinen, Jaana, Pouta, Anneli, Zitting, Paavo, McArdle, Wendy L., Kroemer, Heyo K., Völker, Uwe, Völzke, Henry, Glazer, Nicole L., Taylor, Kent D., Harris, Tamara B., Alavere, Helene, Haller, Toomas, Keis, Aime, Tammesoo, Mari-Liis, Aulchenko, Yurii, Barroso, In S., Khaw, Kay-Tee, Galan, Pilar, Hercberg, Serge, Lathrop, Mark, Eyheramendy, Susana, Org, Elin, Sõber, Siim, Lu, Xiaowen, Nolte, Ilja M., Penninx, Brenda W., Corre, Tanguy, Masciullo, Corrado, Sala, Cinzia, Groop, Leif, Voight, Benjamin F, Melander, Olle, O'Donnell, Christopher J, Salomaa, Veikko, D'Adamo, Adamo Pio, Fabretto, Antonella, Faletra, Flavio, Ulivi, Sheila, Del Greco M, Fabiola, Facheris, Maurizio, Collins, Francis S., Bergman, Richard N., Beilby, John P., Hung, Joseph, Musk, A William, Mangino, Massimo, Shin, So-Youn, Soranzo, Nicole, Watkins, Hugh, Goel, Anuj, Hamsten, Anders, Gider, Pierre, Loitfelder, Marisa, Zeginigg, Marion, Hernandez, Dena, Najjar, Samer S., Navarro, Pau, Wild, Sarah H., Corsi, Anna Maria, Singleton, Andrew, De Geus, Eco J. C., Willemsen, Gonneke, Parker, Alex N., Rose, Lynda M., Buckley, Brendan, Stott, David, Orru, Marco, Uda, Manuela, Van Der Klauw, Melanie M., Zhang, Weihua, Li, Xinzhong, Scott, James, Chen, Yii-Der Ida, Burke, Gregory L, Kähönen, Mika, Viikari, Jorma, Döring, Angela, Meitinger, Thomas, Davies, Gail, Starr, John M., Emilsson, Valur, Plump, Andrew, Lindeman, Jan H., Hoen, Peter A. C. T., König, Inke R., Felix, Janine F., Clarke, Robert, Hopewell, Jemma C., Ongen, Halit, Breteler, Monique, Debette, Stéphanie, Destefano, Anita L., Fornage, Myriam, Mitchell, Gary F., Smith, Nicholas L., Holm, Hilma, Stefansson, Kari, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Samani, Nilesh J., Preuss, Michael, Rudan, Igor, Hayward, Caroline, Deary, Ian J., Wichmann, H-Erich, Raitakari, Olli T., Palmas, Walter, Kooner, Jaspal S., Stolk, Ronald P., Jukema, J Wouter, Wright, Alan F., Boomsma, Dorret I., Bandinelli, Stefania, Gyllensten, Ulf B., Wilson, James F., Ferrucci, Luigi, Schmidt, Reinhold, Farrall, Martin, Spector, Tim D., Palmer, Lyle J., Tuomilehto, Jaakko, Pfeufer, Arne, Gasparini, Paolo, Siscovick, David, Altshuler, David, Loos, Ruth J. F., Toniolo, Daniela, Snieder, Harold, Gieger, Christian, Meneton, Pierre, Wareham, Nicholas J., Oostra, Ben A., Metspalu, Andres, Launer, Lenore, Rettig, Rainer, Strachan, David P., Beckmann, Jacques S., Witteman, Jacqueline C. M., Erdmann, Jeanette, Van Dijk, Ko Willems, Boerwinkle, Eric, Boehnke, Michael, Ridker, Paul M., Jarvelin, Marjo-Riitta, Chakravarti, Aravinda, Abecasis, Goncalo R., Gudnason, Vilmundur, Newton-Cheh, Christopher, Levy, Daniel, Munroe, Patricia B., Psaty, Bruce M., Caulfield, Mark J., Rao, Dabeeru C., Tobin, Martin D., Elliott, Paul, Van Duijn, Cornelia M. McEniery CM, Wilkinson IB, Cockcroft JR, O'Shaughnessy KM, Newhouse SJ, Yasmin, Smith AV, Eiriksdottir G, Launer LJ, Sigurdsson S, Aspelund T, Gudnason V, De Bacquer D, Rietzschel ER, De Backer GG, Van Bortel L, De Buyzere ML, Segers P, Bekaert S, Gillebert TC, De Meyer T, Ferrucci L, Tanaka T, Johnson AD, Levy D, Benjamin EJ, Mitchell GF, Vita JA, Larson MG, Hamburg NM, Vasan RS, Isaacs A, Schut AF, Oostra BA, van Duijn CM, van Rijn MJ, Sie MP, Newman AB, Herrington DM, Andrews JS, Ding J, Sutton-Tyrrell KC, Harris TB, Howard TD, Liu Y, Parsa A, Shuldiner AR, McArdle PF, Gibson Q, Post WS, Dehghan A, Hofman A, Uitterlinden AG, Sijbrands EJ, Rivadeneira F, Mattace-Raso FU, Verwoert GC, Witteman JC, Scuteri A, Lakatta EG, Jewell E, Abecasis GR, Tarasov KV, Uda M, Najjar SS, Sanna S, Attwood T, Belz S, Braund P, Cambien F, Cooper J, Crisp-Hihn A, Deloukas P, Foad N, Eardman J, Goodall AH, Gracey J, Gray E, Gulde S, Gwilliams R, Heimerl S, Hengstenberg C, Jolley J, Krishnan U, Linsel-Nitschke P, Lloyd-Jones H, Lugauer I, Lundmark P, Maouche S, Moore JS, Muir D, Murray E, Nelson CP, Neudert J, Niblett D, O'Leary K, Ouwehand WH, Pollard H, Rankin A, Rice CM, Sager H, Samani NJ, Sambrook J, Schmitz G, Scholz M, Schroeder L, Schunkert H, Syvannen AC, Wallace C, Kathiresan S, Reilly MP, Erdmann J, Assimes TL, Boerwinkle E, Hall A, König IR, Laaksonen R, McPherson R, Thompson JR, Thorsteinsdottir U, Ziegler A, Absher D, Chen L, Cupples LA, Halperin E, Li M, Musunuru K, Preuss M, Schillert A, Thorleifsson G, Voight BF, Wells GA, Assime TL, Holm H, Roberts R, Stewart AF, Fortmann S, Go A, Hlatky M, Iribarren C, Knowles J, Myers R, Quertermous T, Sidney S, Risch N, Tang H, Blankenberg S, Zeller T, Wild P, Schnabel R, Sinning C, Lackner K, Tiret L, Nicaud V, Bickel C, Rupprecht HJ, Perret C, Proust C, Münzel T, Barbalic M, Bis J, Chen IY, Cupples L, Demissie-Banjaw S, Folsom A, Glazer N, Harris T, Heckbert S, Lumley T, Marciante K, Morrison A, O' Donnell CJ, Psaty BM, Rice K, Rotter JI, Siscovick DS, Smith N, Smith A, Taylor KD, van Duijn C, Volcik K, Whitteman J, Ramachandran V, Uitterlinden A, Gretarsdottir S, Gulcher JR, Kong A, Stefansson K, Thorgeirsson G, Andersen K, Fischer M, Grosshennig A, Lieb W, Stark K, Schreiber S, Wichmann HE, Aherrahrou Z, Bruse P, Doering A, Illig T, Klopp N, Loley C, Medack A, Meisinger C, Meitinger T, Nahrstedt J, Peters A, Wagner AK, Willenborg C, Böhm BO, Dobnig H, Grammer TB, Hoffmann MM, Kleber M, März W, Meinitzer A, Winkelmann BR, Pilz S, Renner W, Scharnagl H, Stojakovic T, Tomaschitz A, Winkler K, Guiducci C, Burtt N, Gabriel SB, O'Donnell CJ, Elosua R, Peltonen L, Salomaa V, Schwartz SM, Melander O, Altshuler D, Dandona S, Jarinova O, Qu L, Wilensky R, Matthai W, Hakonarson HH, Devaney J, Burnett MS, Pichard AD, Kent KM, Satler L, Lindsay JM, Waksman R, Knouff CW, Waterworth DM, Walker MC, Mooser V, Epstein SE, Rader DJ, Braund PS, Wright BJ, Balmforth AJ, Ball SG, Hall AS, Smith NL, Felix JF, Morrison AC, Demissie S, Glazer NL, Loehr LR, Rosamond WD, Bis JC, Folsom AR, Benjamin E, Aulchenko YS, Haritunians T, Couper D, Murabito J, Yang YA, Stricker BH, Gottdiener JS, Chang PP, Wang TJ, Rice KM, Heckbert SR, Fox ER, Willerson JT, Köttgen A, Pattaro C, Böger CA, Fuchsberger C, Olden M, Gao X, Yang Q, O'Connell JR, Schmidt H, Ketkar S, Hwang SJ, Teumer A, Paré G, Atkinson EJ, Lohman K, Cornelis MC, Probst-Hensch NM, Kronenberg F, Tönjes A, Hayward C, Rampersaud E, Mitchell BD, Arking DE, Struchalin M, Cavalieri M, Singleton A, Giallauria F, Metter J, de Boer IH, Siscovick D, Zillikens MC, Feitosa M, Province M, de Andrade M, Turner ST, Wild PS, Schnabel RB, Wilde S, Munzel TF, Leak TS, Koenig W, Zgaga L, Zemunik T, Kolcic I, Minelli C, Hu FB, Johansson A, Igl W, Zaboli G, Wild SH, Wright AF, Campbell H, Ellinghaus D, Imboden M, Nitsch D, Brandstätter A, Kollerits B, Kedenko L, Mägi R, Stumvoll M, Kovacs P, Boban M, Campbell S, Endlich K, Völzke H, Kroemer HK, Nauck M, Völker U, Polasek O, Vitart V, Badola S, Parker AN, Ridker PM, Kardia SL, Curhan GC, Franke A, Rochat T, Paulweber B, Prokopenko I, Wang W, Coresh J, Schmidt R, Shlipak MG, Borecki I, Krämer BK, Rudan I, Gyllensten U, Wilson JF, Pramstaller PP, Rettig R, Hastie N, Chasman DI, Kao WH, Heid IM, Fox CS, Felix SB, Watzinger N, Homuth G, Aragam J, Dörr M, Zweiker R, Lind L, Rodeheffer RJ, Greiser KH, Deckers JW, Stritzke J, Lackner KJ, Ingelsson E, Kullo I, Haerting J, Reffelmann T, Redfield MM, Werdan K, Arnett DK, Blettner M, Friedrich N, Chambers JC, Zhang W, Lord GM, van der Harst P, Lawlor DA, Sehmi JS, Gale DP, Wass MN, Ahmadi KR, Bakker SJ, Beckmann J, Bilo HJ, Bochud M, Brown MJ, Caulfield MJ, Connell JM, Cook HT, Cotlarciuc I, Davey Smith G, de Silva R, Deng G, Devuyst O, Dikkeschei LD, Dimkovic N, Dockrell M, Dominiczak A, Ebrahim S, Eggermann T, Farrall M, Floege J, Forouhi NG, Gansevoort RT, Han X, Hedblad B, Homan van der Heide JJ, Hepkema BG, Hernandez-Fuentes M, Hypponen E, Johnson T, de Jong PE, Kleefstra N, Lagou V, Lapsley M, Li Y, Loos RJ, Luan J, Luttropp K, Maréchal C, Munroe PB, Nordfors L, Penninx BW, Perucha E, Pouta A, Roderick PJ, Ruokonen A, Schalling M, Schlessinger D, Schlieper G, Seelen MA, Sjögren M, Smit JH, Snieder H, Soranzo N, Spector TD, Stenvinkel P, Sternberg MJ, Swaminathan R, Ubink-Veltmaat LJ, Vollenweider P, Waterworth D, Zerres K, Waeber G, Wareham NJ, Maxwell PH, McCarthy MI, Jarvelin MR, Lightstone L, Scott J, Navis G, Elliott P, Kooner JS., Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Life Course Epidemiology (LCE), Lifestyle Medicine (LM), Center for Liver, Digestive and Metabolic Diseases (CLDM), University of Leicester, Department of Genetics [Leicester], Erasmus University Rotterdam, Netherlands Genomics Initiative, Department of Epidemiology and Biostatistics, School of Public Health, Zahedan University of Medical Sciences, Washington University in Saint Louis (WUSTL), Queen Mary University of London (QMUL), National Heart, Lung and Blood Institute, Partenaires INRAE, Centre Hospitalier Universitaire Vaudois (CHUV), Université de Lausanne = University of Lausanne (UNIL), Department of Biostatistics [Oslo], Institute of Basic Medical Sciences [Oslo], Faculty of Medicine [Oslo], University of Oslo (UiO)-University of Oslo (UiO)-Faculty of Medicine [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Leiden University Medical Center (LUMC), Universiteit Leiden, Icelandic Heart Association, Heart Preventive Clinic and Research Institute, University of Iceland [Reykjavik], Johns Hopkins University, School of Medicine, Hôpitaux Universitaires de Genève (HUG), Department of Epidemiology, The Netherlands Cancer Institute, Department of Mathematics, Boston University [Boston] (BU), GlaxoSmithKline, Division of Community Health Sciences, St. George's, University of South Florida [Tampa] (USF), Universität Greifswald - University of Greifswald, University of Washington [Seattle], University of Tartu, Institute of Molecular and Cell Biology, Medical Research Council, Institut de Génomique, Centre National de Génotypage, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University Medical Center Groningen, Department of Genetics, University Medical Center Groningen [Groningen] (UMCG), Universita Vita Salute San Raffaele = Vita-Salute San Raffaele University [Milan, Italie] (UniSR), Massachusetts General Hospital [Boston], Centro de Regulación Genómica (CRG), Universitat Pompeu Fabra [Barcelona] (UPF), Università degli studi di Trieste = University of Trieste, Universität zu Lübeck = University of Lübeck [Lübeck], Department of Biostatistics, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, The University of Western Australia (UWA), Department of Twin Research and Genetic Epidemiology, King's College London, London, University of Oxford, Medical University Graz, National Institute on Aging, Centre for population Health Sciences, University of Edinburgh, Uppsala University, Vrije Universiteit Amsterdam [Amsterdam] (VU), Western General Hospital, Harvard Medical School [Boston] (HMS), Brigham and Women's Hospital [Boston], University of Michigan System, University of Groningen, Ealing Hospital, School of Public Health - Department of Epidemiology and Biostatistics, Imperial College London, Medical Genetics Institute, Cedars-Sinai Medical Center, University of Tampere, German Research Center for Environmental Health - Helmholtz Center München (GmbH), Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Split, The University of Texas Health Science Center at Houston (UTHealth), Johns Hopkins University (JHU), Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Swiss Institute of Bioinformatics [Lausanne] (SIB), Finnish Institute of Occupational Health, National Institute of Health and Welfare, University of Oulu, Lapland Central Hospital, University of Bristol [Bristol], Institute for Community Medicine, Unité de Recherche en Epidémiologie Nutritionnelle (UREN), Université Paris 13 (UP13)-Institut National de la Recherche Agronomique (INRA)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), US National Institutes of Health, National Heart, Lung, and Blood Institute, European, Epidemiology, Internal Medicine, Public Health, Clinical Genetics, Université de Lausanne (UNIL), LeidenUniversity Medical Centre, University of Iceland, Università degli studi di Trieste, Universität zu Lübeck [Lübeck], University of Western Australia, University of Oxford [Oxford], VU University Amsterdam, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Sorbonne Paris Cité (USPC)-Université Paris 13 (UP13)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut National de la Recherche Agronomique (INRA), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Human genetics, Psychiatry, EMGO - Mental health, NCA - Anxiety & Depression, Epidemiology and Data Science, Medical Research Council (MRC), Louise V., Wain, Germaine C., Verwoert, Paul F., O'Reilly, Gang, Shi, Toby, Johnson, Andrew D., Johnson, Murielle, Bochud, Kenneth M., Rice, Peter, Henneman, Albert V., Smith, Georg B., Ehret, Najaf, Amin, Martin G., Larson, Vincent, Mooser, David, Hadley, Marcus, Dörr, Joshua C., Bi, Thor, Aspelund, Tõnu, Esko, A. Cecile J. W., Janssen, Jing Hua, Zhao, Simon, Heath, Maris, Laan, Jingyuan, Fu, Giorgio, Pisti, Jian'An, Luan, Pankaj, Arora, Gavin, Luca, Pirastu, Nicola, Irene, Pichler, Anne U., Jackson, Rebecca J., Webster, Feng, Zhang, John F., Peden, Helena, Schmidt, Toshiko, Tanaka, Harry, Campbell, Wilmar, Igl, Yuri, Milaneschi, Jouke Jan, Hottenga, Veronique, Vitart, Daniel I., Chasman, Stella, Trompet, Jennifer L., Bragg Gresham, Behrooz Z., Alizadeh, John C., Chamber, Xiuqing, Guo, Terho, Lehtimäki, Brigitte, Kühnel, Lorna M., Lopez, Ozren, Polašek, Mladen, Boban, Christopher P., Nelson, Alanna C., Morrison, Vasyl, Pihur, Santhi K., Ganesh, Albert, Hofman, Suman, Kundu, Francesco U. S., Mattace Raso, Fernando, Rivadeneira, Eric J. G., Sijbrand, Andre G., Uitterlinden, Shih Jen, Hwang, Ramachandran S., Vasan, Thomas J., Wang, Sven, Bergmann, Peter, Vollenweider, Gérard, Waeber, Jaana, Laitinen, Anneli, Pouta, Paavo, Zitting, Wendy L., Mcardle, Heyo K., Kroemer, Uwe, Völker, Henry, Völzke, Nicole L., Glazer, Kent D., Taylor, Tamara B., Harri, Helene, Alavere, Toomas, Haller, Aime, Kei, Mari Liis, Tammesoo, Yurii, Aulchenko, Inês, Barroso, Kay Tee, Khaw, Pilar, Galan, Serge, Hercberg, Mark, Lathrop, Susana, Eyheramendy, Elin, Org, Siim, Sõber, Xiaowen, Lu, Ilja M., Nolte, Brenda W., Penninx, Tanguy, Corre, Corrado, Masciullo, Cinzia, Sala, Leif, Groop, Benjamin F., Voight, Olle, Melander, Christopher J., O'Donnell, Veikko, Salomaa, D'Adamo, ADAMO PIO, Antonella, Fabretto, Flavio, Faletra, Sheila, Ulivi, Fabiola Del Greco, M, Maurizio, Facheri, Francis S., Collin, Richard N., Bergman, John P., Beilby, Joseph, Hung, A., William Musk, Massimo, Mangino, So Youn, Shin, Nicole, Soranzo, Hugh, Watkin, Anuj, Goel, Anders, Hamsten, Pierre, Gider, Marisa, Loitfelder, Marion, Zeginigg, Dena, Hernandez, Samer S., Najjar, Pau, Navarro, Sarah H., Wild, Anna Maria, Corsi, Andrew, Singleton, Eco J. C., de Geu, Gonneke, Willemsen, Alex N., Parker, Lynda M., Rose, Brendan, Buckley, David, Stott, Marco, Orru, Manuela, Uda, Melanie M., van der Klauw, Weihua, Zhang, Xinzhong, Li, James, Scott, Yii Der Ida, Chen, Gregory L., Burke, Mika, Kähönen, Jorma, Viikari, Angela, Döring, Thomas, Meitinger, Gail, Davie, John M., Starr, Valur, Emilsson, Andrew, Plump, Jan H., Lindeman, Peter A. C., 't Hoen, Inke R., König, Janine F., Felix, Robert, Clarke, Jemma C., Hopewell, Halit, Ongen, Monique, Breteler, Stéphanie, Debette, Anita L., Destefano, Myriam, Fornage, Gary F., Mitchell, Nicholas L., Smith, Hilma, Holm, Kari, Stefansson, Gudmar, Thorleifsson, Unnur, Thorsteinsdottir, Nilesh J., Samani, Michael, Preu, Igor, Rudan, Caroline, Hayward, Ian J., Deary, H., Erich Wichmann, Olli T., Raitakari, Walter, Palma, Jaspal S., Kooner, Ronald P., Stolk, J., Wouter Jukema, Alan F., Wright, Dorret I., Boomsma, Stefania, Bandinelli, Ulf B., Gyllensten, James F., Wilson, Luigi, Ferrucci, Reinhold, Schmidt, Martin, Farrall, Tim D., Spector, Lyle J., Palmer, Jaakko, Tuomilehto, Arne, Pfeufer, Gasparini, Paolo, David, Siscovick, David, Altshuler, Ruth J. F., Loo, Daniela, Toniolo, Harold, Snieder, Christian, Gieger, Pierre, Meneton, Nicholas J., Wareham, Ben A., Oostra, Andres, Metspalu, Lenore, Launer, Rainer, Rettig, David P., Strachan, Jacques S., Beckmann, Jacqueline C. M., Witteman, Jeanette, Erdmann, Ko Willems van, Dijk, Eric, Boerwinkle, Michael, Boehnke, Paul M., Ridker, Marjo Riitta, Jarvelin, Aravinda, Chakravarti, Goncalo R., Abecasi, Vilmundur, Gudnason, Christopher Newton, Cheh, Daniel, Levy, Patricia B., Munroe, Bruce M., Psaty, Mark J., Caulfield, Dabeeru C., Rao, Martin D., Tobin, Paul, Elliott, Cornelia M., van Duijn, Biological Psychology, Neuroscience Campus Amsterdam - Anxiety & Depression, EMGO+ - Mental Health, Wain, Louise V., Verwoert, Germaine C., O'Reilly, Paul F., Shi, Gang, Johnson, Toby, Johnson, Andrew D., Bochud, Murielle, Rice, Kenneth M., Henneman, Peter, Smith, Albert V., Ehret, Georg B., Amin, Najaf, Larson, Martin G., Mooser, Vincent, Hadley, David, Dörr, Marcu, Bis, Joshua C, Aspelund, Thor, Esko, Tõnu, Janssens, A Cecile J. W., Zhao, Jing Hua, Heath, Simon, Laan, Mari, Fu, Jingyuan, Pistis, Giorgio, Luan, Jian'An, Arora, Pankaj, Lucas, Gavin, Pichler, Irene, Jackson, Anne U., Webster, Rebecca J., Zhang, Feng, Peden, John F., Schmidt, Helena, Tanaka, Toshiko, Campbell, Harry, Igl, Wilmar, Milaneschi, Yuri, Hottenga, Jouke-Jan, Vitart, Veronique, Chasman, Daniel I., Trompet, Stella, Bragg-Gresham, Jennifer L., Alizadeh, Behrooz Z., Chambers, John C., Guo, Xiuqing, Lehtimäki, Terho, Kühnel, Brigitte, Lopez, Lorna M., Polašek, Ozren, Boban, Mladen, Nelson, Christopher P., Morrison, Alanna C., Pihur, Vasyl, Ganesh, Santhi K., Hofman, Albert, Kundu, Suman, Mattace-Raso, Francesco U. S., Rivadeneira, Fernando, Sijbrands, Eric J. G., Uitterlinden, Andre G., Hwang, Shih-Jen, Vasan, Ramachandran S., Wang, Thomas J., Bergmann, Sven, Vollenweider, Peter, Waeber, Gérard, Laitinen, Jaana, Pouta, Anneli, Zitting, Paavo, Mcardle, Wendy L., Kroemer, Heyo K., Völker, Uwe, Völzke, Henry, Glazer, Nicole L., Taylor, Kent D., Harris, Tamara B., Alavere, Helene, Haller, Tooma, Keis, Aime, Tammesoo, Mari-Lii, Aulchenko, Yurii, Barroso, In S., Khaw, Kay-Tee, Galan, Pilar, Hercberg, Serge, Lathrop, Mark, Eyheramendy, Susana, Org, Elin, Sõber, Siim, Lu, Xiaowen, Nolte, Ilja M., Penninx, Brenda W., Corre, Tanguy, Masciullo, Corrado, Sala, Cinzia, Groop, Leif, Voight, Benjamin F, Melander, Olle, O'Donnell, Christopher J, Salomaa, Veikko, D'Adamo, Adamo Pio, Fabretto, Antonella, Faletra, Flavio, Ulivi, Sheila, Del Greco M, Fabiola, Facheris, Maurizio, Collins, Francis S., Bergman, Richard N., Beilby, John P., Hung, Joseph, Musk, A William, Mangino, Massimo, Shin, So-Youn, Soranzo, Nicole, Watkins, Hugh, Goel, Anuj, Hamsten, Ander, Gider, Pierre, Loitfelder, Marisa, Zeginigg, Marion, Hernandez, Dena, Najjar, Samer S., Navarro, Pau, Wild, Sarah H., Corsi, Anna Maria, Singleton, Andrew, De Geus, Eco J. C., Willemsen, Gonneke, Parker, Alex N., Rose, Lynda M., Buckley, Brendan, Stott, David, Orru, Marco, Uda, Manuela, Van Der Klauw, Melanie M., Zhang, Weihua, Li, Xinzhong, Scott, Jame, Chen, Yii-Der Ida, Burke, Gregory L, Kähönen, Mika, Viikari, Jorma, Döring, Angela, Meitinger, Thoma, Davies, Gail, Starr, John M., Emilsson, Valur, Plump, Andrew, Lindeman, Jan H., Hoen, Peter A. C. T., König, Inke R., Felix, Janine F., Clarke, Robert, Hopewell, Jemma C., Ongen, Halit, Breteler, Monique, Debette, Stéphanie, Destefano, Anita L., Fornage, Myriam, Mitchell, Gary F., Smith, Nicholas L., Holm, Hilma, Stefansson, Kari, Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Samani, Nilesh J., Preuss, Michael, Rudan, Igor, Hayward, Caroline, Deary, Ian J., Wichmann, H-Erich, Raitakari, Olli T., Palmas, Walter, Kooner, Jaspal S., Stolk, Ronald P., Jukema, J Wouter, Wright, Alan F., Boomsma, Dorret I., Bandinelli, Stefania, Gyllensten, Ulf B., Wilson, James F., Ferrucci, Luigi, Schmidt, Reinhold, Farrall, Martin, Spector, Tim D., Palmer, Lyle J., Tuomilehto, Jaakko, Pfeufer, Arne, Siscovick, David, Altshuler, David, Loos, Ruth J. F., Toniolo, Daniela, Snieder, Harold, Gieger, Christian, Meneton, Pierre, Wareham, Nicholas J., Oostra, Ben A., Metspalu, Andre, Launer, Lenore, Rettig, Rainer, Strachan, David P., Beckmann, Jacques S., Witteman, Jacqueline C. M., Erdmann, Jeanette, Van Dijk, Ko Willem, Boerwinkle, Eric, Boehnke, Michael, Ridker, Paul M., Jarvelin, Marjo-Riitta, Chakravarti, Aravinda, Abecasis, Goncalo R., Gudnason, Vilmundur, Newton-Cheh, Christopher, Levy, Daniel, Munroe, Patricia B., Psaty, Bruce M., Caulfield, Mark J., Rao, Dabeeru C., Tobin, Martin D., Elliott, Paul, Van, Duijn, Cornelia M., McEniery CM, Wilkinson, Ib, Cockcroft, Jr, O'Shaughnessy, Km, Newhouse, Sj, Yasmin, Smith, Av, Eiriksdottir, G, Launer, Lj, Sigurdsson, S, Aspelund, T, Gudnason, V, De Bacquer, D, Rietzschel, Er, De Backer, Gg, Van Bortel, L, De Buyzere, Ml, Segers, P, Bekaert, S, Gillebert, Tc, De Meyer, T, Ferrucci, L, Tanaka, T, Johnson, Ad, Levy, D, Benjamin, Ej, Mitchell, Gf, Vita, Ja, Larson, Mg, Hamburg, Nm, Vasan, R, Isaacs, A, Schut, Af, Oostra, Ba, van Duijn, Cm, van Rijn, Mj, Sie, Mp, Newman, Ab, Herrington, Dm, Andrews, J, Ding, J, Sutton-Tyrrell, Kc, Harris, Tb, Howard, Td, Liu, Y, Parsa, A, Shuldiner, Ar, Mcardle, Pf, Gibson, Q, Post, W, Dehghan, A, Hofman, A, Uitterlinden, Ag, Sijbrands, Ej, Rivadeneira, F, Mattace-Raso, Fu, Verwoert, Gc, Witteman, Jc, Scuteri, A, Lakatta, Eg, Jewell, E, Abecasis, Gr, Tarasov, Kv, Uda, M, Najjar, S, Sanna, S, Attwood, T, Belz, S, Braund, P, Cambien, F, Cooper, J, Crisp-Hihn, A, Deloukas, P, Foad, N, Eardman, J, Goodall, Ah, Gracey, J, Gray, E, Gulde, S, Gwilliams, R, Heimerl, S, Hengstenberg, C, Jolley, J, Krishnan, U, Linsel-Nitschke, P, Lloyd-Jones, H, Lugauer, I, Lundmark, P, Maouche, S, Moore, J, Muir, D, Murray, E, Nelson, Cp, Neudert, J, Niblett, D, O'Leary, K, Ouwehand, Wh, Pollard, H, Rankin, A, Rice, Cm, Sager, H, Samani, Nj, Sambrook, J, Schmitz, G, Scholz, M, Schroeder, L, Schunkert, H, Syvannen, Ac, Wallace, C, Kathiresan, S, Reilly, Mp, Erdmann, J, Assimes, Tl, Boerwinkle, E, Hall, A, König, Ir, Laaksonen, R, Mcpherson, R, Thompson, Jr, Thorsteinsdottir, U, Ziegler, A, Absher, D, Chen, L, Cupples, La, Halperin, E, Li, M, Musunuru, K, Preuss, M, Schillert, A, Thorleifsson, G, Voight, Bf, Wells, Ga, Assime, Tl, Holm, H, Roberts, R, Stewart, Af, Fortmann, S, Go, A, Hlatky, M, Iribarren, C, Knowles, J, Myers, R, Quertermous, T, Sidney, S, Risch, N, Tang, H, Blankenberg, S, Zeller, T, Wild, P, Schnabel, R, Sinning, C, Lackner, K, Tiret, L, Nicaud, V, Bickel, C, Rupprecht, Hj, Perret, C, Proust, C, Münzel, T, Barbalic, M, Bis, J, Chen, Iy, Cupples, L, Demissie-Banjaw, S, Folsom, A, Glazer, N, Harris, T, Heckbert, S, Lumley, T, Marciante, K, Morrison, A, O' Donnell, Cj, Psaty, Bm, Rice, K, Rotter, Ji, Siscovick, D, Smith, N, Smith, A, Taylor, Kd, van Duijn, C, Volcik, K, Whitteman, J, Ramachandran, V, Uitterlinden, A, Gretarsdottir, S, Gulcher, Jr, Kong, A, Stefansson, K, Thorgeirsson, G, Andersen, K, Fischer, M, Grosshennig, A, Lieb, W, Stark, K, Schreiber, S, Wichmann, He, Aherrahrou, Z, Bruse, P, Doering, A, Illig, T, Klopp, N, Loley, C, Medack, A, Meisinger, C, Meitinger, T, Nahrstedt, J, Peters, A, Wagner, Ak, Willenborg, C, Böhm, Bo, Dobnig, H, Grammer, Tb, Hoffmann, Mm, Kleber, M, März, W, Meinitzer, A, Winkelmann, Br, Pilz, S, Renner, W, Scharnagl, H, Stojakovic, T, Tomaschitz, A, Winkler, K, Guiducci, C, Burtt, N, Gabriel, Sb, O'Donnell, Cj, Elosua, R, Peltonen, L, Salomaa, V, Schwartz, Sm, Melander, O, Altshuler, D, Dandona, S, Jarinova, O, Qu, L, Wilensky, R, Matthai, W, Hakonarson, Hh, Devaney, J, Burnett, M, Pichard, Ad, Kent, Km, Satler, L, Lindsay, Jm, Waksman, R, Knouff, Cw, Waterworth, Dm, Walker, Mc, Mooser, V, Epstein, Se, Rader, Dj, Wright, Bj, Balmforth, Aj, Ball, Sg, Smith, Nl, Felix, Jf, Morrison, Ac, Demissie, S, Glazer, Nl, Loehr, Lr, Rosamond, Wd, Bis, Jc, Folsom, Ar, Benjamin, E, Aulchenko, Y, Haritunians, T, Couper, D, Murabito, J, Yang, Ya, Stricker, Bh, Gottdiener, J, Chang, Pp, Wang, Tj, Rice, Km, Heckbert, Sr, Fox, Er, Willerson, Jt, Köttgen, A, Pattaro, C, Böger, Ca, Fuchsberger, C, Olden, M, Gao, X, Yang, Q, O'Connell, Jr, Schmidt, H, Ketkar, S, Hwang, Sj, Teumer, A, Paré, G, Atkinson, 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Subjects
Netherlands Twin Register (NTR), Linkage disequilibrium, pulse pressure, mean arterial pressure, genome-wide, [SDV]Life Sciences [q-bio], Genome-wide association study, BLOOD-PRESSURE, Blood Pressure, 030204 cardiovascular system & hematology, Linkage Disequilibrium, 0302 clinical medicine, RELEVANCE, CardioGram, Medicine and Health Sciences, Genetics & Heredity, ddc:616, Genetics, 0303 health sciences, Genome-wide association, 11 Medical And Health Sciences, Arteries, ADRENERGIC-RECEPTOR TRAFFICKING, Pulse pressure, EchoGen consortium, Hypertension, HEART-FAILURE, arterial pressure, Case-Control Studie, Life Sciences & Biomedicine, Human, circulatory and respiratory physiology, medicine.medical_specialty, Mean arterial pressure, Arterie, AortaGen Consortium, Cardiogenics consortium, Locus (genetics), Biology, Polymorphism, Single Nucleotide, Article, Follow-Up Studie, 03 medical and health sciences, Internal medicine, medicine, Humans, cardiovascular diseases, METAANALYSIS, 030304 developmental biology, Genetic association, Science & Technology, HYPERTENSION, MORTALITY, Case-control study, CARDIOVASCULAR-DISEASE RISK, 06 Biological Sciences, GENE, MICE, Endocrinology, Blood pressure, CKDGen consortium, Genetic Loci, Case-Control Studies, KidneyGen consortium, CHARGE Consortium Heart Failure Working Group, LifeLines Cohort Study, Developmental Biology, Follow-Up Studies, Genome-Wide Association Study
Abstract

Les affiliations des 100 premiers auteurs sont renseignées dans la notice. Les affiliations des autres auteurs sont disponibles à la fin de la publication.; International audience; Numerous genetic loci have been associated with systolic blood pressure (SBP) and diastolic blood pressure (DBP) in Europeans(1-3). We now report genome-wide association studies of pulse pressure (PP) and mean arterial pressure (MAP). In discovery (N = 74,064) and follow-up studies (N = 48,607), we identified at genome-wide significance (P = 2.7 x 10(-8) to P = 2.3 x 10(-13)) four new PP loci (at 4q12 near CHIC2, 7q22.3 near PIK3CG, 8q24.12 in NOV and 11q24.3 near ADAMTS8), two new MAP loci (3p21.31 in MAP4 and 10q25.3 near ADRB1) and one locus associated with both of these traits (2q24.3 near FIGN) that has also recently been associated with SBP in east Asians. For three of the new PP loci, the estimated effect for SBP was opposite of that for DBP, in contrast to the majority of common SBP- and DBP-associated variants, which show concordant effects on both traits. These findings suggest new genetic pathways underlying blood pressure variation, some of which may differentially influence SBP and DBP.

Published
2016

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