Author: "David Altshuler" / Journal: nature genetics - Searchworks@Jio Institute Digital Library Search Results

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42 results on '"David Altshuler"'

1. Structural forms of the human amylase locus and their relationships to SNPs, haplotypes and obesity

Author: Robert E. Handsaker, Christina L. Usher, Steven A. McCarroll, Han Cao, Tõnu Esko, Michael Boehnke, Alex Hastie, Marcus A. Tuke, Andres Metspalu, David Altshuler, Carlos N. Pato, Michael N. Weedon, Christian Fuchsberger, Michele T. Pato, Timothy M. Frayling, Jennifer E. Moon, Seva Kashin, Mark I. McCarthy, and Joel N. Hirschhorn
Subjects: Adult, Male, Adolescent, Genotype, Gene Dosage, Single-nucleotide polymorphism, Locus (genetics), Polymorphism, Single Nucleotide, Genome, Article, Body Mass Index, Cohort Studies, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Gene Frequency, Gene mapping, Genetics, Humans, Genetic Predisposition to Disease, Obesity, Amylase, Copy-number variation, Allele, 030304 developmental biology, 2. Zero hunger, Principal Component Analysis, 0303 health sciences, biology, Haplotype, Middle Aged, Haplotypes, Amylases, biology.protein, Female, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Hundreds of genes reside in structurally complex, poorly understood regions of the human genome. One such region contains the three amylase genes (AMY2B, AMY2A and AMY1) responsible for digesting starch into sugar. Copy number of AMY1 is reported to be the largest genomic influence on obesity, although genome-wide association studies for obesity have found this locus unremarkable. Using whole-genome sequence analysis, droplet digital PCR and genome mapping, we identified eight common structural haplotypes of the amylase locus that suggest its mutational history. We found that the AMY1 copy number in an individual's genome is generally even (rather than odd) and partially correlates with nearby SNPs, which do not associate with body mass index (BMI). We measured amylase gene copy number in 1,000 obese or lean Estonians and in 2 other cohorts totaling ∼3,500 individuals. We had 99% power to detect the lower bound of the reported effects on BMI, yet found no association.
Published: 2015

2. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author: Tazeen H. Jafar, Lars Lind, Peter Almgren, Wendy Winckler, Eitaro Nakashima, Young Min Cho, Annette Peters, Rona J. Strawbridge, Ananda R. Wickremasinghe, Katharine R. Owen, Lee-Ming Chuang, Tien-Jyun Chang, Graeme I. Bell, James B. Meigs, Bill Musk, Timo A. Lakka, Elin Grundberg, Wei Lu, Sarah Edkins, George Dedoussis, Weiping Jia, Danish Saleheen, Suthesh Sivapalaratnam, Maria Samuel, Tien Yin Wong, Lu Qi, Pierre Fontanillas, Momoko Horikoshi, Jirong Long, Abdul Basit, Anubha Mahajan, Andrew T. Hattersley, Markus M. Nöthen, Denis Rybin, Inger Njølstad, S. Krithika, Miguel Cruz, Delilah Zabaneh, Leena Peltonen, Jasmina Kravic, Sangsoo Kim, David Couper, Lori L. Bonnycastle, Heather M. Stringham, Yi-Cheng Chang, Paul Elliott, Eric J.G. Sijbrands, Nita G. Forouhi, Alena Stančáková, Ghazala Mirza, Robert W. Lawrence, Ruth J. F. Loos, Norman Klopp, Shiro Maeda, Martina Müller-Nurasyid, Jer-Yuarn Wu, Jianjun Liu, Kee Seng Chia, Elodie Eury, Loukianos S. Rallidis, Timothy M. Frayling, Ken Yamamoto, David Altshuler, Gunnar Sigurosson, Harald Grallert, Jackie F. Price, Barbara Thorand, Jouko Saramies, Malene M. Kristensen, Sonali Pechlivanis, Inês Barroso, Jong-Young Lee, Melissa Parkin, Josée Dupuis, Stéphane Lobbens, Jesús Kumate, Elena Tremoli, Sudhir Kowlessur, Xueling Sim, Norihiro Kato, Philippe Froguel, Kathleen Stirrups, Eero Lindholm, Alex S. F. Doney, Andres Metspalu, Yu-Tang Gao, Roman Wennauer, Xiao-Ou Shu, Marilyn C. Cornelis, Veikko Salomaa, Nanette R. Lee, Johanna Kuusisto, Caroline S. Fox, Man Li, James Scott, Wing-Yee So, Andrew R. Wood, Inga Prokopenko, Oddgeir L. Holmen, Tin Aung, Ryoichi Takayanagi, Chen Suo, Hara Kazuo, Carl G. P. Platou, Ann M. Kelly, Teresa Ferreira, Karl-Heinz Jöckel, Wei-Yen Lim, James F. Wilson, Tom Forsén, Qi Sun, Valur Emilsson, Gonçalo R. Abecasis, Fan Zhang, Timo Saaristo, Harry Campbell, Ying Wu, Mark Seielstad, Wei Zheng, Han Chen, Stavroula Kanoni, Yuqian Bao, Jose C. Florez, Wan Ting Tay, Ronald C. WMa, Gerald Steinbach, Min Jin Go, Rong Zhang, Junbin Liang, Vasiliki Lagou, Leif Groop, Emil Rehnberg, Nabi Shah, Weihua Zhang, Yun Li, Bengt Sennblad, Olle Melander, Nancy L. Pedersen, Muhammed Islam, Jaakko Tuomilehto, Young Jin Kim, Richard N. Bergman, Juliana C.N. Chan, Eleftheria Zeggini, Andrew D. Johnson, Kees Hovingh, Joban Sehmi, Rainer Rauramaa, Satu Männistö, Reedik Mägi, Samuel Liju, Mingyu Yang, Ayellet V. Segrè, Noël P. Burtt, Mozhgan Dorkhan, Beverley Balkau, Neelam Hassanali, Hyun Min Kang, Fabrizio Veglia, Eeva Korpi-Hyövälti, Loic Yengo, Elizabeth J. Rossin, Angela Silveira, Maggie C.Y. Ng, Yuan-Tsong Chen, Anders Hamsten, David R. Matthews, Mark J. Caulfield, Emmi Tikkanen, Tanya M. Teslovich, John R. B. Perry, Karen L. Mohlke, Sarah E. Hunt, Soo Heon Kwak, Jorge Escobedo, Christopher J. Groves, Ulf de Faire, Jeremy B M Jowett, Gudmar Thorleifsson, Michael Roden, Evelin Mihailov, Viswanathan Mohan, Craig L. Hanis, Thomas WMühleisen, Congrong Wang, Sonia Shah, Kyle J. Gaulton, Jaspal S. Kooner, Jiro Nakamura, Mustafa Atalay, Linda S. Adair, S Wiltshire, Tõnu Esko, Anna Jonsson, Antigone S. Dimas, Karin Leander, Li Ching Chang, George B. Grant, Bo Isomaa, Anne U. Jackson, Claudia Langenberg, Kristian Hveem, Yoon Shin Cho, Astradur B. Hreidarsson, Xu Wang, Keizo Ohnaka, Alexandra C. Nica, Simon D. Rees, Pau Navarro, Sekar Kathiresan, Rob M. van Dam, Zafar I. Hydrie, Bok Ghee Han, Francis S. Collins, Fuu Jen Tsai, Unnur Thorsteinsdottir, Ross M. Fraser, Caroline Hayward, Cornelia M. van Duijn, Samuli Ripatti, Mieke D. Trip, Hyung Lae Kim, Rafn Benediktsson, Candace Guiducci, Bruna Gigante, Kyong Soo Park, Wen Hong L. Kao, Tom Wilsgaard, Leena Kinnunen, John Danesh, Alan James, Alan R. Shuldiner, Mitsuhiro Yokota, Jen Mai Lee, Kari Stefansson, Erik Ingelsson, Colin N. A. Palmer, David J. Hunter, Paul Zimmet, Manickam Chidambaram, Sirkka Keinänen-Kiukaanniemi, Laura J. Scott, Susanne Moebus, Benjamin F. Voight, Wolfgang Rathmann, Hassan Khan, Thomas Illig, Prasad Katulanda, Christian Gieger, Andrew D. Morris, Yik Ying Teo, Andrew P. Morris, Venkatesan Radha, N. William Rayner, Johan G. Eriksson, Christian Dina, Igor Rudan, Sailaja Vedantam, Cheng Hu, James S. Pankow, Ann-Christine Syvänen, Karl Gertow, Valeriya Lyssenko, Guillaume Charpentier, Albert Hofman, Chiea Chuen Khor, Joseph Trakalo, Peter Kraft, Takashi Kadowaki, Qiuyin Cai, John C. Chambers, André G. Uitterlinden, Simon C. Potter, Nicholas J. Wareham, Soumya Raychaudhuri, Jian'an Luan, Tiinamaija Tuomi, Anthony H. Barnett, Juha Saltevo, Robert A. Scott, Valgerdur Steinthorsdottir, Peng Keat Ng, Mark I. McCarthy, Åsa K. Hedman, Kerrin S. Small, Julia Meyer, Frank B. Hu, Cecilia M. Lindgren, Jennifer E. Below, Nancy J. Cox, Jennie Hui, Andrew Crenshaw, Latonya F. Been, Nam H. Cho, Janani Pinidiyapathirage, A. Samad Shera, Bernhard OBoehm, Jason Carey, Augustine Kong, Twee Hee Ong, Philippe M. Frossard, Donald W. Bowden, Toshimasa Yamauchi, Steve E. Humphries, Cordelia Langford, Xinzhong Li, Hiroshi Ikegami, Stéphane Cauchi, Ching-Ti Liu, Michael Boehnke, Peter M. Nilsson, Debashish Das, John Beilby, Robin Young, Christian Herder, Asif Rasheed, Neil Robertson, Raimund Erbel, Fumihiko Takeuchi, Markku Laakso, Esteban J. Parra, Panos Deloukas, Eric Boerwinkle, Adan Valladares-Salgado, Chien-Hsiun Chen, Kay-Tee Khaw, Damiano Baldassarre, Ashok Kumar, E. Shyong Tai, Peter S. Chines, Dharambir KSanghera, Peter Donnelly, [ 1 ] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford, England [ 2 ] Natl Inst Hlth, Ctr Genome Sci, Gangoe Myeon, Yeonje Ri, South Korea [ 3 ] Univ London Imperial Coll Sci Technol & Med, London, England [ 4 ] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA [ 5 ] Univ Oxford, Oxford Ctr Diabet Endocrinol & Metab, Oxford OX1 2JD, England [ 6 ] NHLBI, Framingham Heart Study, Framingham, MA USA [ 7 ] Wake Forest Sch Med, Ctr Genom & Personalized Med Res, Winston Salem, NC USA [ 8 ] Wake Forest Sch Med, Ctr Diabet Res, Winston Salem, NC USA [ 9 ] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, London, England [ 10 ] Univ Cambridge, Dept Publ Hlth & Primary Care, Cambridge, England [ 11 ] Ctr Noncommunicable Dis Pakistan, Karachi, Pakistan [ 12 ] Natl Univ Singapore, Dept Epidemiol & Publ Hlth, Singapore 117548, Singapore [ 13 ] Wellcome Trust Sanger Inst, Cambridge, England [ 14 ] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA [ 15 ] Univ N Carolina, Dept Nutr, Chapel Hill, NC USA [ 16 ] Lund Univ, Scania Univ Hosp, Dept Clin Sci Malmo, Ctr Diabet, Malmo, Sweden [ 17 ] Univ Eastern Finland, Inst Biomed, Kuopio, Finland [ 18 ] Singapore Natl Eye Ctr, Singapore Eye Res Inst, Singapore, Singapore [ 19 ] Natl Univ Singapore, Dept Ophthalmol, Singapore 117548, Singapore [ 20 ] IRCCS, Ctr Cardiol Monzino, Milan, Italy [ 21 ] Univ Milan, Dept Pharmacol Sci, Milan, Italy [ 22 ] INSERM, Ctr Rech Epidemiol & Sante Populat CESP, U1018, Villejuif, France [ 23 ] Univ Paris 11, UMRS 1018, Villejuif, France [ 24 ] Shanghai Jiao Tong Univ, Affiliated Peoples Hosp 6, Dept Endocrinol & Metab, Shanghai Key Lab Diabet Mellitus,Shanghai Diabet, Shanghai 200030, Peoples R China [ 25 ] Univ Birmingham, Coll Med & Dent Sci, Birmingham, W Midlands, England [ 26 ] Heart England Natl Hlth Serv NHS Fdn Trust, Ctr Biomed Res, Birmingham, W Midlands, England [ 27 ] Univ Cambridge, Addenbrookes Hosp, Metab Res Labs, Inst Metab Sci, Cambridge CB2 2QQ, England [ 28 ] Addenbrookes Hosp, Inst Metab Sci, Cambridge Biomed Res Ctr, Natl Inst Hlth Res, Cambridge, England [ 29 ] Baqai Inst Diabetol & Endocrinol, Karachi, Pakistan [ 30 ] Univ Oklahoma, Hlth Sci Ctr, Coll Med, Dept Pediat,Sect Genet, Oklahoma City, OK 73190 USA [ 31 ] Sir Charles Gairdner Hosp, Busselton Populat Med Res Inst, Nedlands, WA 6009, Australia [ 32 ] Queen Elizabeth II Med Ctr, PathWest Lab Med Western Australia, Nedlands, WA, Australia [ 33 ] Univ Western Australia, Sch Pathol & Lab Med, Nedlands, WA 6009, Australia [ 34 ] Univ Chicago, Dept Med, Chicago, IL 60637 USA [ 35 ] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA [ 36 ] Univ Iceland, Fac Med, Reykjavik, Iceland [ 37 ] Landspitali Univ Hosp, Reykjavik, Iceland [ 38 ] Cedars Sinai Med Ctr, Diabet & Obes Res Inst, Los Angeles, CA 90048 USA [ 39 ] Univ Med Ctr Ulm, Div Endocrinol & Diabet, Dept Internal Med, Ulm, Germany [ 40 ] Nanyang Technol Univ, Lee Kong Chian LKC Sch Med, Singapore 639798, Singapore [ 41 ] Univ Texas Hlth Sci Ctr Houston, Ctr Human Genet, Houston, TX 77030 USA [ 42 ] Baylor Coll Med, Human Genome Sequencing Ctr, Houston, TX 77030 USA [ 43 ] NHGRI, NIH, Bethesda, MD 20892 USA [ 44 ] Broad Inst Harvard & Massachusetts Inst Technol M, Cambridge, MA USA [ 45 ] Vanderbilt Univ, Sch Med, Vanderbilt Ingram Canc Ctr, Vanderbilt Epidemiol Ctr,Dept Med, Nashville, TN 37212 USA [ 46 ] Univ Edinburgh, Ctr Populat Hlth Sci, Edinburgh, Midlothian, Scotland [ 47 ] Univ Edinburgh, Western Gen Hosp, MRC, Inst Genet & Mol Med, Edinburgh, Midlothian, Scotland [ 48 ] CNRS, Unite Mixte Rech UMR 8199, Inst Biol, Lille, France [ 49 ] Univ Lille 2, Inst Pasteur, Lille, France [ 50 ] Queen Mary Univ London, Barts & London Sch Med, William Harvey Res Inst, London, England [ 51 ] Queen Mary Univ London, Barts & London Sch Med, William Harvey Res Inst, Barts & London Genome Ctr, London, England [ 52 ] Chinese Univ Hong Kong, Prince Wales Hosp, Dept Med & Therapeut, Hong Kong, Hong Kong, Peoples R China [ 53 ] Acad Sinica, Inst Biomed Sci, Taipei, Taiwan [ 54 ] Natl Taiwan Univ Hosp, Dept Internal Med, Taipei 100, Taiwan [ 55 ] Corbeil Essonnes Hosp, Endocrinol Diabetol Unit, Corbeil Essonnes, France [ 56 ] China Med Univ, Sch Chinese Med, Taichung, Taiwan [ 57 ] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA USA [ 58 ] Natl Univ Singapore, Ctr Mol Epidemiol, Singapore 117548, Singapore [ 59 ] Indian Council Med Res, Adv Ctr Genom Diabet, Madras Diabet Res Fdn, Dept Mol Genet, Madras, Tamil Nadu, India [ 60 ] Ajou Univ, Sch Med, Dept Prevent Med, Suwon 441749, South Korea [ 61 ] Seoul Natl Univ, Coll Med, Dept Internal Med, Seoul 151, South Korea [ 62 ] Natl Taiwan Univ, Sch Med, Grad Inst Clin Med, Taipei 10764, Taiwan [ 63 ] Harvard Univ, Sch Publ Hlth, Dept Nutr & Epidemiol, Boston, MA 02115 USA [ 64 ] Univ N Carolina, Dept Biostat, Collaborat Studies Coordinating Ctr, Chapel Hill, NC USA [ 65 ] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore 117548, Singapore [ 66 ] Ealing Hosp NHS Trust, Southall, Middx, England [ 67 ] Karolinska Inst, Inst Environm Med, Divis Cardiovasc Epidemiol, S-10401 Stockholm, Sweden [ 68 ] Harokopio Univ, Dept Dietet Nutr, Athens, Greece [ 69 ] Univ Geneva, Sch Med, Dept Genet Med & Dev, CH-1211 Geneva, Switzerland [ 70 ] Biomed Sci Res Ctr Alexander Fleming, Vari, Greece [ 71 ] INSERM, UMR 1087, Nantes, France [ 72 ] CNRS, UMR 6291, Nantes, France [ 73 ] Univ Nantes, Nantes, France [ 74 ] Univ Dundee, Ninewells Hosp, Biomed Res Inst, Diabet Res Ctr, Dundee, Scotland [ 75 ] Univ Dundee, Ninewells Hosp, Biomed Res Inst, Pharmacogen Ctr, Dundee, Scotland [ 76 ] Univ Oxford, Dept Stat, Oxford OX1 3TG, England [ 77 ] Erasmus Univ, Med Ctr, Dept Epidemiol, Rotterdam, Netherlands [ 78 ] Netherlands Consortium Healthy Ageing, Netherland Genom Initiat, Rotterdam, Netherlands [ 79 ] Ctr Med Syst Biol, Rotterdam, Netherlands [ 80 ] Univ London Imperial Coll Sci Technol & Med, MRC, Hlth Protect Agcy, Ctr Environm & Hlth, London, England [ 81 ] Iceland Heart Assoc, Kopavogur, Iceland [ 82 ] Univ Duisburg Essen, Univ Hosp Essen, West German Heart Ctr, Clin Cardiol, Essen, Germany [ 83 ] Natl Inst Hlth & Welf, Dept Chron Dis Prevent, Helsinki, Finland [ 84 ] Univ Helsinki, Dept Gen Practice & Primary Hlth Care, Helsinki, Finland [ 85 ] Univ Helsinki, Gen Hosp, Unit Gen Practice, Helsinki, Finland [ 86 ] Folkhalsan Res Ctr, Helsinki, Finland [ 87 ] Inst Mexicano Seguro Social, Hosp Gen Reg 1, Unidad Invest Epidemiol Clin, Mexico City, DF, Mexico [ 88 ] Univ Tartu, Estonian Genome Ctr, EE-50090 Tartu, Estonia [ 89 ] Univ Tartu, Inst Mol & Cell Biol, EE-50090 Tartu, Estonia [ 90 ] Broad Inst, Program Med & Populat Genet, Cambridge, MA USA [ 91 ] Childrens Hosp, Div Genet & Endocrinol, Boston, MA 02115 USA [ 92 ] Harvard Univ, Sch Med, Dept Med, Boston, MA USA [ 93 ] Massachusetts Gen Hosp, Ctr Human Genet Res, Boston, MA 02114 USA [ 94 ] Massachusetts Gen Hosp, Diabet Res Ctr, Diabet Unit, Boston, MA 02114 USA [ 95 ] Addenbrookes Hosp, Inst Metab Sci, MRC, Epidemiol Unit, Cambridge, England [ 96 ] Vaasa Hlth Care Ctr, Vaasa, Finland [ 97 ] Brigham & Womens Hosp, Div Endocrinol & Metab, Boston, MA 02115 USA [ 98 ] Harvard Univ, Sch Med, Boston, MA USA [ 99 ] Univ Exeter, Peninsula Med Sch, Inst Biomed & Clin Sci, Exeter, Devon, England [ 100 ] Shanghai Canc Inst, Dept Epidemiol, Shanghai, Peoples R China [ 101 ] Karolinska Inst, Dept Med Solna, Atherosclerosis Res Unit, Stockholm, Sweden [ 102 ] Karolinska Univ, Hosp Solna, Ctr Mol Med, Stockholm, Sweden [ 103 ] Helmholtz Zentrum Muenchen, Inst Genet Epidemiol, Neuherberg, Germany [ 104 ] Helmholtz Zentrum Muenchen, Res Unit Mol Epidemiol, Neuherberg, Germany [ 105 ] Univ Munich, Clin Cooperat Grp Diabet, Munich, Germany [ 106 ] Helmholtz Zentrum Muenchen, Munich, Germany [ 107 ] Tech Univ Munich, Clin Cooperat Grp Nutrigen & Type Diabet 2, Munich, Germany [ 108 ] German Ctr Diabet Res DZD, Neuherberg, Germany [ 109 ] Kings Coll London, Dept Twin Res & Genet Epidemiol, London, England [ 110 ] Univ Tokyo, Grad Sch Med, Dept Diabet & Metab Dis, Tokyo, Japan [ 111 ] Univ Exeter, Peninsula Med Sch, Inst Biomed & Clin Sci, Exeter, Devon, England [ 112 ] Univ Dusseldorf, Leibniz Ctr Diabet Res, German Diabet Ctr, Inst Clin Diabetol, Dusseldorf, Germany [ 113 ] Norwegian Univ Sci & Technol, Dept Publ Hlth & Gen Practice, HUNT Res Ctr, Levanger, Norway [ 114 ] Univ Amsterdam, Acad Med Ctr, Dept Vasc Med, NL-1105 AZ Amsterdam, Netherlands [ 115 ] Brigham & Womens Hosp, Dept Med, Channing Lab, Boston, MA USA [ 116 ] Univ Western Australia, Sch Populat Hlth, Nedlands, WA 6009, Australia [ 117 ] UCL, Inst Cardiovasc Sci, London, England [ 118 ] Harvard Univ, Sch Publ Hlth, Program Mol & Genet Epidemiol, Boston, MA 02115 USA [ 119 ] Kinki Univ, Sch Med, Dept Diabet Endocrinol & Metab, Osaka 589, Japan [ 120 ] Hannover Med Sch, Hannover Unified Biobank, Hannover, Germany [ 121 ] Univ Uppsala Hosp, Dept Mol Sci, Mol Epidemiol & Sci Life Lab, Uppsala, Sweden [ 122 ] Aga Khan Univ, Dept Community Hlth Sci, Karachi, Pakistan [ 123 ] Dept Social Serv & Hlth Care, Pietarsaari, Finland [ 124 ] Aga Khan Univ, Dept Med, Karachi, Pakistan [ 125 ] Queen Elizabeth II Med Ctr, West Australian Sleep Disorders Res Inst, Dept Pulm Physiol & Sleep Med, Nedlands, WA, Australia [ 126 ] Univ Western Australia, Sch Med & Pharmacol, Nedlands, WA 6009, Australia [ 127 ] Univ Hosp Essen, Inst Med Informat Biometry & Epidemiol, Essen, Germany [ 128 ] Heart & Diabet Inst, Baker Int Diabet Inst IDI, Melbourne, Australia [ 129 ] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA [ 130 ] Massachusetts Gen Hosp, Cardiovasc Res Ctr, Boston, MA 02114 USA [ 131 ] Natl Ctr Global Hlth & Med, Res Inst, Shinjuku Ku, Tokyo, Japan [ 132 ] Univ Colombo, Dept Clin Med, Diabet Res Unit, Colombo, Sri Lanka [ 133 ] Univ Oulu, Inst Hlth Sci, Fac Med, Oulu, Finland [ 134 ] Oulu Univ Hosp, Unit Gen Practice, Oulu, Finland [ 135 ] Agcy Sci Technol & Res, Genome Inst Singapore, Singapore, Singapore [ 136 ] Ewha Womans Univ, Sch Med, Dept Biochem, Seoul, South Korea [ 137 ] Soongsil Univ, Sch Syst Biomed Sci, Seoul, South Korea [ 138 ] Natl Inst Hlth & Welf, Diabet Prevent Unit, Helsinki, Finland [ 139 ] deCODE Genet, Reykjavik, Iceland [ 140 ] South Ostrobothnia Cent Hosp, Seinajoki, Finland [ 141 ] Minist Hlth, Port Louis, Mauritius [ 142 ] Univ Toronto, Dept Anthropol, Mississauga, ON L5L 1C6, Canada [ 143 ] Fdn IMSS, Mexico City, DF, Mexico [ 144 ] Univ Eastern Finland, Dept Med, Kuopio, Finland [ 145 ] Kuopio Univ Hosp, SF-70210 Kuopio, Finland [ 146 ] Kuopio Res Inst Exercise Med, Kuopio, Finland [ 147 ] Univ Western Australia, Ctr Genet Epidemiol & Biostat, Nedlands, WA 6009, Australia [ 148 ] Univ San Carlos, Off Populat Studies Fdn Inc, Cebu, Philippines [ 149 ] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, Natl Heart & Lung Inst, London, England [ 150 ] Univ N Carolina, Dept Genet, Chapel Hill, NC USA [ 151 ] Univ N Carolina, Dept Biostat, Chapel Hill, NC USA [ 152 ] Beijing Genom Inst, Shenzhen, Peoples R China [ 153 ] Uppsala Univ, Akad Sjukhuset, Dept Med Sci, Uppsala, Sweden [ 154 ] Mt Sinai Sch Med, Charles R Bronfman Inst Personalized Med, New York, NY USA [ 155 ] Mt Sinai Sch Med, Child Hlth & Dev Inst, New York, NY USA [ 156 ] Mt Sinai Sch Med, Dept Prevent Med, New York, NY USA [ 157 ] Shanghai Inst Prevent Med, Shanghai, Peoples R China [ 158 ] Massachusetts Gen Hosp, Div Gen Med, Boston, MA 02114 USA [ 159 ] Dr Mohans Diabet Specialties Ctr, Madras, Tamil Nadu, India [ 160 ] Univ Bonn, Inst Human Genet, Bonn, Germany [ 161 ] Univ Bonn, Life & Brain Ctr, Dept Genom, Bonn, Germany [ 162 ] Univ Munich, Chair Genet Epidemiol, Inst Med Informat Biometry & Epidemiol, Munich, Germany [ 163 ] Univ Munich, Univ Hosp Grosshadern, Dept Med 1, Munich, Germany [ 164 ] Sir Charles Gairdner Hosp, Nedlands, WA 6009, Australia [ 165 ] Nagoya Univ, Grad Sch Med, Div Endocrinol & Diabet, Dept Internal Med, Nagoya, Aichi 4648601, Japan [ 166 ] Chubu Rosai Hosp, Dept Endocrinol & Diabet, Nagoya, Aichi, Japan [ 167 ] Univ Tromso, Fac Hlth Sci, Dept Community Med, Tromso, Norway [ 168 ] Kyushu Univ, Grad Sch Med Sci, Dept Geriatr Med, Higashi Ku, Fukuoka 812, Japan [ 169 ] Churchill Hosp, Hlth Res Biomed Res Ctr, Oxford Natl Inst, Oxford OX3 7LJ, England [ 170 ] Univ Minnesota, Div Epidemiol & Community Hlth, Minneapolis, MN USA [ 171 ] Seoul Natl Univ, Grad Sch Convergence Sci & Technol, Dept Mol Med & Biopharmaceut Sci, World Class Univ Program, Seoul, South Korea [ 172 ] Seoul Natl Univ, Coll Med, Seoul, South Korea [ 173 ] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden [ 174 ] Inst Mol Med Finland FIMM, Helsinki, Finland [ 175 ] Helmholtz Zentrum Muenchen, Inst Epidemiol 2, Neuherberg, Germany [ 176 ] Univ Kelaniya, Fac Med, Dept Publ Hlth, Ragama, Sri Lanka [ 177 ] Nord Trondelag Hlth Trust, Levanger Hosp, Dept Internal Med, Levanger, Norway [ 178 ] Univ Gen Hosp Attikon, Athens, Greece [ 179 ] Univ Dusseldorf, Leibniz Ctr Diabet Res, German Diabet Ctr, Inst Biometr & Epidemiol, Dusseldorf, Germany [ 180 ] Kuopio Univ Hosp, Dept Clin Physiol & Nucl Med, SF-70210 Kuopio, Finland [ 181 ] Harvard Univ, Brigham & Womens Hosp, Sch Med, Div Rheumatol Immunol & Allergy, Boston, MA 02115 USA [ 182 ] Partners Ctr Personalized Genom Med, Boston, MA USA [ 183 ] Univ Dusseldorf, Dept Endocrinol & Diabetol, Dusseldorf, Germany [ 184 ] Univ Dusseldorf, Dept Metab Dis, Dusseldorf, Germany [ 185 ] Harvard Univ, Hlth Sci & Technol MD Program, Boston, MA 02115 USA [ 186 ] MIT, Boston, MA USA [ 187 ] Harvard Univ, Harvard Biol & Biomed Sci Program, Boston, MA 02115 USA [ 188 ] Boston Univ, Data Coordinating Ctr, Boston, MA 02215 USA [ 189 ] Finnish Diabet Assoc, Tampere, Finland [ 190 ] Pirkanmaa Hosp Dist, Tampere, Finland [ 191 ] Cent Finland Cent Hosp, Dept Med, Jyvaskyla, Finland [ 192 ] South Karelia Cent Hosp, Lappeenranta, Finland [ 193 ] UCL, Dept Genet Evolut & Environm, Genet Inst, London, England [ 194 ] Diabet Assoc Pakistan, Karachi, Pakistan [ 195 ] Univ Maryland, Sch Med, Div Endocrinol Diabet & Nutr, Baltimore, MD 21201 USA [ 196 ] Baltimore Vet Adm Med Ctr, Geriatr Res Educ & Clin Ctr, Baltimore, MD USA [ 197 ] Univ Maryland, Sch Med, Program Personalised & Genom Med, Baltimore, MD 21201 USA [ 198 ] Erasmus Univ, Med Ctr, Dept Internal Med, Rotterdam, Netherlands [ 199 ] Univ Ulm, Dept Clin Chem, D-89069 Ulm, Germany [ 200 ] Univ Ulm, Cent Lab, D-89069 Ulm, Germany [ 201 ] Uppsala Univ, Dept Med Sci, Uppsala, Sweden [ 202 ] Kyushu Univ, Grad Sch Med Sci, Dept Internal Med & Bioregulatory Sci, Higashi Ku, Fukuoka 812, Japan [ 203 ] Univ Helsinki, Helsinki Univ Hosp, Dept Med, Helsinki, Finland [ 204 ] Hosp Univ LaPaz IdiPAZ, Inst Invest Sanitaria, Madrid, Spain [ 205 ] Danube Univ Krems, Ctr Vasc Prevent, Krems, Austria [ 206 ] King Abdulaziz Univ, Diabet Res Grp, Jeddah 21413, Saudi Arabia [ 207 ] IMSS, Ctr Med Nacl Siglo 21, Hosp Especialidades, Unidad Invest Med Bioquim, Mexico City, DF, Mexico [ 208 ] Univ Penn, Perelman Sch Med, Dept Pharmacol, Philadelphia, PA 19104 USA [ 209 ] Univ Melbourne, Ctr Eye Res Australia, East Melbourne, Vic, Australia [ 210 ] Kyushu Univ, Med Inst Bioregulat, Res Ctr Genet Informat, Div Genome Anal,Higashi Ku, Fukuoka 812, Japan [ 211 ] Univ Lille 1, Math Lab, CNRS UMR 8524, MODAL Team,INRIA Lille Nord Europe, F-59655 Villeneuve Dascq, France [ 212 ] Aichi Gakuin Univ, Sch Dent, Dept Genome Sci, Nagoya, Aichi 464, Japan [ 213 ] Harvard Univ, Sch Med, Dept Genet, Boston, MA USA [ 214 ] Harvard Univ, Sch Med, Dept Mol Biol, Boston, MA USA [ 215 ] Massachusetts Gen Hosp, Diabet Unit, Boston, MA 02114 USA [ 216 ] Wake Forest Sch Med, Dept Biochem, Winston Salem, NC USA [ 217 ] Wake Forest Sch Med, Dept Internal Med, Winston Salem, NC USA [ 218 ] Hallym Univ, Dept Biomed Sci, Chunchon, Gangwon Do, South Korea [ 219 ] Univ Texas Hlth Sci Ctr Houston, Ctr Human Genet, Houston, TX 77030 USA [ 220 ] Imperial Coll Healthcare NHS Trust, London, England [ 221 ] Univ Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA [ 222 ] Blood Syst Res Inst, San Francisco, CA USA [ 223 ] Natl Univ Singapore, Grad Sch Integrat Sci & Engn, Singapore 117548, Singapore [ 224 ] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117548, Singapore [ 225 ] Natl Univ Singapore, Dept Med, Singapore 117548, Singapore [ 226 ] Duke Natl Univ Singapore, Grad Sch Med, Singapore, Singapore [ 227 ] Univ Liverpool, Dept Biostat, Liverpool L69 3BX, Merseyside, England, Obstetrics & Gynecology, Radiology & Nuclear Medicine, Surgery, Epidemiology, Dermatology, Internal Medicine, Medical Microbiology & Infectious Diseases, Medical Research Council (MRC), National Institute for Health Research, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, and Cardiology
Subjects: CHROMATIN, endocrine system diseases, South Asian Type 2 Diabetes (SAT2D) Consortium, SCALE ASSOCIATION ANALYSIS, Medizin, LOCI, Genome-wide association study, VARIANTS, 0302 clinical medicine, Risk Factors, IMPUTATION, Glucose homeostasis, 11 Medical and Health Sciences, Genetics & Heredity, Genetics, 0303 health sciences, IDENTIFY, Hispanic or Latino, 3. Good health, MAP, POPULATIONS, Medical genetics, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Hispanic Americans, Life Sciences & Biomedicine, Asian Continental Ancestry Group, medicine.medical_specialty, European Continental Ancestry Group, TRANSETHNIC METAANALYSIS, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, White People, Sykursýki, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, Allele, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, Alleles, 030304 developmental biology, Genetic association, Science & Technology, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, 06 Biological Sciences, Arfgengi, Genetic architecture, INDIVIDUALS, Diabetes Mellitus, Type 2, Case-Control Studies, GLUCOSE-HOMEOSTASIS, ASSOCIATION ANALYSES, Imputation (genetics), Developmental Biology, Genome-Wide Association Study
Abstract: To access publisher's full text version of this article click on the hyperlink at the bottom of the page To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry. Canadian Institutes of Health Research Medical Research Council UK G0601261 Mexico Convocatoria SSA/IMMS/ISSSTE-CONACYT 2012-2 clave 150352 IMSS R-2011-785-018 CONACYT Salud-2007-C01-71068 US National Institutes of Health DK062370 HG000376 DK085584 DK085545 DK073541 DK085501 Wellcome Trust WT098017 WT090532 WT090367 WT098381 WT081682 WT085475 info:eu-repo/grantAgreement/EC/FP7/201413
Published: 2014

3. Common variants associated with plasma triglycerides and risk for coronary artery disease

Author: Richard S. Cooper, Angela Döring, Cisca Wijmenga, Jerome I. Rotter, Linda S. Adair, Tõnu Esko, Jennifer L. Bragg-Gresham, Danish Saleheen, Narisu Narisu, Xiaohui Li, Kathleen Stirrups, Ulf de Faire, Nicholas G. Martin, Dmitry Shungin, Peter Vollenweider, Yii-Der Ida Chen, Dharambir K. Sanghera, George Dedoussis, Toshiko Tanaka, Manjinder S. Sandhu, Anne U. Jackson, Nancy L. Pedersen, Maria Dimitriou, Shih-Yi Lin, David P. Strachan, Isleifur Olafsson, Ruth J. F. Loos, Kay-Tee Khaw, Antero Kesäniemi, Rainer Rauramaa, Wendy L. McArdle, Gonneke Willemsen, Dena G. Hernandez, May E. Montasser, Amy J. Swift, Colin A. McKenzie, Aaron Isaacs, Latonya F. Been, Leif Groop, Massimo Mangino, Martina Müller-Nurasyid, Karen L. Mohlke, Ci Song, Sailaja Vedantam, Anna-Liisa Hartikainen, Lori L. Bonnycastle, Ilja M. Nolte, Jaakko Kaprio, Anneli Pouta, Unnur Thorsteinsdottir, Paul Elliott, Muredach P. Reilly, Jean Ferrières, Daniel J. Rader, Elizabeth H. Young, Jaspal S. Kooner, Leena Moilanen, Markku Laakso, Albert Hofman, Kelly A. Volcik, Sekar Kathiresan, Tamara B. Harris, Eric Kim, Aimo Ruokonen, Andrea Ganna, Serena Sanna, John J.P. Kastelein, Martha L. Gravito, Ronald M. Krauss, Ken K. Ong, Paul M. Ridker, Kristian Hveem, Ayse Demirkan, Alena Stančáková, Pierre Meneton, Thomas Quertermous, John Danesh, Toby Johnson, Cornelia M. van Duijn, Samuli Ripatti, Christopher J. Groves, Jaakko Tuomilehto, Michael Boehnke, Jose M. Ordovas, Alan B. Feranil, Chao A. Hsiung, Wayne Huey-Herng Sheu, Igor Rudan, Christa Meisinger, Rebecca N. Nsubuga, Bruna Gigante, Inger Njølstad, Göran Hallmans, Aroon D. Hingorani, Jouko Saramies, Deepti Gurdasani, Fernando Rivadeneira, Andres Metspalu, Stephen E. Epstein, Gonçalo R. Abecasis, Braxton D. Mitchell, Devin Absher, Marcus E. Kleber, Sonia Shah, Pierre Fontanillas, Jeffrey R. O'Connell, Louise A. Donnelly, Jing Hua Zhao, Martin L. Buchkovich, Francis S. Collins, Gabrielle Müller, Matti Uusitupa, Evelin Mihailov, Nicholas J. Wareham, Andrew A. Hicks, Dorret I. Boomsma, Harry Campbell, Ellen M. Schmidt, Jaana Lindström, Mark I. McCarthy, Evita G. Van Den Herik, Kirsten Ohm Kyvik, Vilmundur Gudnason, Jackie F. Price, Joel N. Hirschhorn, Winfried März, Aravinda Chakravarti, Pontiano Kaleebu, James F. Wilson, Lindsay L. Waite, Leo-Pekka Lyytikäinen, Sebanti Sengupta, Mika Kivimäki, David Altshuler, Hilma Holm, Rona J. Strawbridge, Harald Grallert, Ramaiah Nagaraja, Laurence Tiret, G. Kees Hovingh, Meena Kumari, Nilesh J. Samani, Daniel F. Freitag, Nelson B. Freimer, Thomas Illig, Panos Deloukas, Bernhard O. Boehm, Nicholas W.J. Wainwright, Mark J. Daly, Mika Kähönen, Michel Burnier, Norman Klopp, L. Adrienne Cupples, Aarno Palotie, Markus Perola, Bamidele O. Tayo, Timo A. Lakka, Matthew Jones, Sarah H. Wild, Patricia B. Munroe, Antti Jula, François Mach, Peter J. Koudstaal, Pirjo Komulainen, Eric Boerwinkle, L. Joost van Pelt, Veikko Salomaa, Ann-Kristin Petersen, Ida Surakka, Andrew Wong, Caroline Hayward, Chi Gao, Cristen J. Willer, Stephen S. Rich, Yi Jen Hung, Peter P. Pramstaller, Diana Kuh, Ron Do, Dominique Arveiler, Mark O. Goodarzi, Ross M. Fraser, Ingrid B. Borecki, Steven C. Hunt, Weihua Zhang, Mary Susan Burnett, Patrik K. E. Magnusson, John C. Chambers, Benjamin M. Neale, Peter Schwarz, Jennifer L. Bolton, Murielle Bochud, Heleen M. den Hertog, Christian Gieger, Cristina Pomilla, Teresa Ferreira, Lars Wallentin, Richa Saxena, André G. Uitterlinden, Kaisa Silander, Ying Wu, Bruce M. Psaty, Jian'an Luan, Hsing-Yi Chang, Jin Chen, Daniel I. Chasman, Ulf Gyllensten, Kari Stefansson, Kauko Heikkilä, Tom Wilsgaard, Alan R. Shuldiner, Carlos Iribarren, Stavroula Kanoni, John Whitfield, Gershim Asiki, Marika Kaakinen, Georg Ehret, Elina Hyppönen, Claudia Langenberg, Gina M. Peloso, Cecilia M. Lindgren, Carlo Sidore, Gudmundur I. Eyjolfsson, Cameron D. Palmer, Jacques S. Beckmann, Hubert Scharnagl, Tanya M. Teslovich, Mary F. Feitosa, Terho Lehtimäki, Steve E. Humphries, Chris Power, Benjamin F. Voight, Stefania Bandinelli, Andrew D. Morris, Gudmar Thorleifsson, Tuomo Nieminen, Tim D. Spector, Paul W. Franks, Themistocles L. Assimes, Pascal Bovet, Luigi Ferrucci, Johannes Kettunen, Inês Barroso, Franklyn I. Bennett, Stefan Gustafsson, Paolo Brambilla, Theodore Papamarkou, Elena Tremoli, Janet Seeley, Alex S. F. Doney, Johanna Kuusisto, Giancarlo Cesana, Bruce H. R. Wolffenbuttel, Lars Lind, Stefan R. Bornstein, Åsa Johansson, Anders Hamsten, Marjo-Riitta Järvelin, Krista Fischer, Agneta Siegbahn, Samia Mora, Erik Ingelsson, Colin N. A. Palmer, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Lifestyle Medicine (LM), Center for Liver, Digestive and Metabolic Diseases (CLDM), Epidemiology, Surgery, Public Health, Ophthalmology, Neurology, Medical Microbiology & Infectious Diseases, Obstetrics & Gynecology, Internal Medicine, Do, Ron, Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Hyppönen, Elina, Kathiresan, Sekar, Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Do, R, Willer, C, Schmidt, E, Sengupta, S, Gao, C, Peloso, G, Gustafsson, S, Kanoni, S, Ganna, A, Chen, J, Buchkovich, M, Mora, S, Beckmann, J, Bragg Gresham, J, Chang, H, Demirkan, A, Den Hertog, H, Donnelly, L, Ehret, G, Esko, T, Feitosa, M, Ferreira, T, Fischer, K, Fontanillas, P, Fraser, R, Freitag, D, Gurdasani, D, Heikkilä, K, Hyppönen, E, Isaacs, A, Jackson, A, Johansson, A, Johnson, T, Kaakinen, M, Kettunen, J, Kleber, M, Li, X, Luan, J, Lyytikäinen, L, Magnusson, P, Mangino, M, Mihailov, E, Montasser, M, Müller Nurasyid, M, Nolte, I, O'Connell, J, Palmer, C, Perola, M, Petersen, A, Sanna, S, Saxena, R, Service, S, Shah, S, Shungin, D, Sidore, C, Song, C, Strawbridge, R, Surakka, I, Tanaka, T, Teslovich, T, Thorleifsson, G, Van den Herik, E, Voight, B, Volcik, K, Waite, L, Wong, A, Wu, Y, Zhang, W, Absher, D, Asiki, G, Barroso, I, Been, L, Bolton, J, Bonnycastle, L, Brambilla, P, Burnett, M, Cesana, G, Dimitriou, M, Doney, A, Döring, A, Elliott, P, Epstein, S, Eyjolfsson, G, Gigante, B, Goodarzi, M, Grallert, H, Gravito, M, Groves, C, Hallmans, G, Hartikainen, A, Hayward, C, Hernandez, D, Hicks, A, Holm, H, Hung, Y, Illig, T, Jones, M, Kaleebu, P, Kastelein, J, Khaw, K, Kim, E, Klopp, N, Komulainen, P, Kumari, M, Langenberg, C, Lehtimäki, T, Lin, S, Lindström, J, Loos, R, Mach, F, Mcardle, W, Meisinger, C, Mitchell, B, Müller, G, Nagaraja, R, Narisu, N, Nieminen, T, Nsubuga, R, Olafsson, I, Ong, K, Palotie, A, Papamarkou, T, Pomilla, C, Pouta, A, Rader, D, Reilly, M, Ridker, P, Rivadeneira, F, Rudan, I, Ruokonen, A, Samani, N, Scharnagl, H, Seeley, J, Silander, K, Stančáková, A, Stirrups, K, Swift, A, Tiret, L, Uitterlinden, A, van Pelt, L, Vedantam, S, Wainwright, N, Wijmenga, C, Wild, S, Willemsen, G, Wilsgaard, T, Wilson, J, Young, E, Zhao, J, Adair, L, Arveiler, D, Assimes, T, Bandinelli, S, Bennett, F, Bochud, M, Boehm, B, Boomsma, D, Borecki, I, Bornstein, S, Bovet, P, Burnier, M, Campbell, H, Chakravarti, A, Chambers, J, Chen, Y, Collins, F, Cooper, R, Danesh, J, Dedoussis, G, de Faire, U, Feranil, A, Ferrières, J, Ferrucci, L, Freimer, N, Gieger, C, Groop, L, Gudnason, V, Gyllensten, U, Hamsten, A, Harris, T, Hingorani, A, Hirschhorn, J, Hofman, A, Hovingh, G, Hsiung, C, Humphries, S, Hunt, S, Hveem, K, Iribarren, C, Järvelin, M, Jula, A, Kähönen, M, Kaprio, J, Kesäniemi, A, Kivimaki, M, Kooner, J, Koudstaal, P, Krauss, R, Kuh, D, Kuusisto, J, Kyvik, K, Laakso, M, Lakka, T, Lind, L, Lindgren, C, Martin, N, März, W, Mccarthy, M, Mckenzie, C, Meneton, P, Metspalu, A, Moilanen, L, Morris, A, Munroe, P, Njølstad, I, Pedersen, N, Power, C, Pramstaller, P, Price, J, Psaty, B, Quertermous, T, Rauramaa, R, Saleheen, D, Salomaa, V, Sanghera, D, Saramies, J, Schwarz, P, Sheu, W, Shuldiner, A, Siegbahn, A, Spector, T, Stefansson, K, Strachan, D, Tayo, B, Tremoli, E, Tuomilehto, J, Uusitupa, M, van Duijn, C, Vollenweider, P, Wallentin, L, Wareham, N, Whitfield, J, Wolffenbuttel, B, Altshuler, D, Ordovas, J, Boerwinkle, E, Thorsteinsdottir, U, Chasman, D, Rotter, J, Franks, P, Ripatti, S, Cupples, L, Sandhu, M, Rich, S, Boehnke, M, Deloukas, P, Mohlke, K, Ingelsson, E, Abecasis, G, Daly, M, Neale, B, and Kathiresan, S
Subjects: Netherlands Twin Register (NTR), BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, Heart disease, Genome-wide association study, Coronary Artery Disease, 030204 cardiovascular system & hematology, ISCHEMIC-HEART-DISEASE, Triglyceride, Coronary artery disease, chemistry.chemical_compound, 0302 clinical medicine, High-density lipoprotein, Polymorphism (computer science), Risk Factors, High-density-lipoprotein, Genetic epidemiology, 11 Medical and Health Sciences, Genetics & Heredity, 0303 health sciences, Cholesterol, HDL/blood, Cholesterol levels, Loci, Contribute, Single Nucleotide, LDL/blood, Triglycerides/blood, Cholesterol, Cholesterol, LDL/blood, HDL/blood, lipids (amino acids, peptides, and proteins), Life Sciences & Biomedicine, Human, medicine.medical_specialty, TYPE-2 DIABETES-MELLITUS, Biology, Polymorphism, Single Nucleotide, Article, HIGH-DENSITY-LIPOPROTEIN ISCHEMIC-HEART-DISEASE TYPE-2 DIABETES-MELLITUS MENDELIAN RANDOMIZATION CARDIOVASCULAR-DISEASE GENETIC EPIDEMIOLOGY CHOLESTEROL LEVELS LOCI CONTRIBUTE THERAPY, 03 medical and health sciences, Coronary Artery Disease/blood, SDG 3 - Good Health and Well-being, Cardiovascular-disease, Internal medicine, Mendelian randomization, Genetics, medicine, Humans, Polymorphism, plasma, Triglycerides, 030304 developmental biology, Science & Technology, Risk Factor, Cholesterol, HDL, Biological Transport, Cholesterol, LDL, 06 Biological Sciences, medicine.disease, Heart-disease, lipoproteins, Endocrinology, chemistry, Therapy, Developmental Biology
Abstract: Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10 -8 for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD. © 2013 Nature America, Inc. All rights reserved.
Published: 2013

4. Prospective functional classification of all possible missense variants in PPARG

Author: Keerthana Gnanapradeepan, Xiaolan Zhang, Robert H. Rice, Jose C. Florez, Marjoleine F. Broekema, Maura Agostini, Stephen O'Rahilly, Amit R. Majithia, Ben Tsuda, Inês Barroso, Kashyap A. Patel, Krishna Chatterjee, Tarjei S. Mikkelsen, Sekar Kathiresan, Eric Kalkhoven, Gina M. Peloso, Evan D. Rosen, Ted Sharpe, David Altshuler, David B. Savage, Marc Duby, Nick Patterson, and Sian Ellard
Subjects: 0301 basic medicine, Male, Peroxisome proliferator-activated receptor gamma, Lipodystrophy, Population, Mutation, Missense, Myocardial Infarction, Biology, Article, 03 medical and health sciences, symbols.namesake, Genetics, Missense mutation, Humans, Prospective Studies, Saturated mutagenesis, education, Gene, Exome sequencing, education.field_of_study, Macrophages, Case-control study, 3. Good health, PPAR gamma, 030104 developmental biology, Amino Acid Substitution, Diabetes Mellitus, Type 2, Case-Control Studies, Mendelian inheritance, symbols, Female
Abstract: Amit Majithia and colleagues employ a pooled assay in human macrophages to assess the functional effects of all possible missense variants in PPARG. Their study shows the value of saturation mutagenesis and prospective experimental characterization to support diagnostic interpretation of newly discovered missense variants in disease-related genes. Clinical exome sequencing routinely identifies missense variants in disease-related genes, but functional characterization is rarely undertaken, leading to diagnostic uncertainty1,2. For example, mutations in PPARG cause Mendelian lipodystrophy3,4 and increase risk of type 2 diabetes (T2D)5. Although approximately 1 in 500 people harbor missense variants in PPARG, most are of unknown consequence. To prospectively characterize PPARγ variants, we used highly parallel oligonucleotide synthesis to construct a library encoding all 9,595 possible single–amino acid substitutions. We developed a pooled functional assay in human macrophages, experimentally evaluated all protein variants, and used the experimental data to train a variant classifier by supervised machine learning. When applied to 55 new missense variants identified in population-based and clinical sequencing, the classifier annotated 6 variants as pathogenic; these were subsequently validated by single-variant assays. Saturation mutagenesis and prospective experimental characterization can support immediate diagnostic interpretation of newly discovered missense variants in disease-related genes.
Published: 2016

5. Large-scale association analysis identifies new risk loci for coronary artery disease

Author: Benjamin F. Voight, Andrew D. Morris, G. Kees Hovingh, Anthony J. Balmforth, Hanneke Basart, Alistair S. Hall, Dominique Gauguier, Bok Ghee Han, Martina Müller-Nurasyid, Sarah Parish, Jarmo Virtamo, Christa Meisinger, Peter Wagner, George Dedoussis, Philipp S. Wild, Kari Stefansson, Jean-Baptiste Cazier, Kathleen Stirrups, Jiyoung Lee, Adrienne Cupples, Stavroula Kanoni, Danish Saleheen, Christian Hengstenberg, Svati H. Shah, Panos Deloukas, Anuj Goel, Stefan Blankenberg, Sian Tsung Tan, Alison H. Goodall, Tõnu Esko, Eric Boerwinkle, Gudmundur Thorgeirsson, Peter S. Braund, Joshua W. Knowles, Olle Melander, C. Ellen van der Schoot, Silke Rosinger, Maria Dimitriou, Wolfgang Koenig, Michael Boehnke, François Cambien, Per Lundmark, Dmitry Shungin, Wolfgang Kratzer, Pierre Zalloua, Reijo Laaksonen, Jean Ferrières, Villi Gudnason, Thorsten Kessler, Daniel J. Rader, Niclas Eriksson, Dominique Arveiler, Natalie R. van Zuydam, Kari Kuulasmaa, N. William Rayner, Sarah E. Hunt, Gudmar Thorleifsson, Jeanette Erdmann, Samuli Ripatti, Tsun-Po Yang, George A. Wells, Terho Lehtimäki, Kjell Nikus, Pierre Fontanillas, Jorg Hager, Martin Farrall, Jemma C. Hopewell, Frank Kee, Juha Sinisalo, Christopher J. O'Donnell, Asif Rasheed, Mika Kähönen, Genovefa Kolovou, Seraya Maouche, Suzanne Rafelt, Cordelia Langford, Winfried März, Leo-Pekka Lyytikäinen, Christina Willenborg, Weihua Zhang, Kati Kristiansson, Hyo-Soo Kim, Weang K. Ho, Jeong E. Park, Mohan U. Sivananthan, Moritz P. Rumpf, Markku Laakso, Klaus Stark, Philippe Amouyel, Paul W. Franks, Andres Metspalu, Anders Franco-Cereceda, Manjinder S. Sandhu, Nour Eddine El Mokhtari, Nicholas J. Wareham, Robert Roberts, Veikko Salomaa, Thomas Illig, Tomi Pastinen, Robert Clarke, Christof Burgdorf, Leif Groop, Devin Absher, Yangsoo Jang, Mark I. McCarthy, Bernhard O. Boehm, Per Eriksson, Nilesh J. Samani, Inke R. König, Stefan Schreiber, Karin Leander, Simone Claudi-Boehm, Ci Song, Benjamin A. Goldstein, Stephen E. Epstein, Andreas Ziegler, Stanley L. Hazen, Arne Schäfer, Elin Grundberg, Sekar Kathiresan, John R. Thompson, Unnur Thorsteinsdottir, Muredach P. Reilly, Heribert Schunkert, Rory Collins, Thomas Quertermous, Jong-Young Lee, John Danesh, John C. Chambers, Marco M Ferrario, Carlos Iribarren, Claudia Langenberg, Hilma Holm, Rona J. Strawbridge, Alan S. Go, Cristen J. Willer, Ron Do, Emmi Tikkanen, Abbas Dehghan, Evelin Mihailov, Lindsay L. Waite, Patrick Diemert, Willem H. Ouwehand, Eric E. Schadt, Diana Rubin, David Altshuler, Marcus E. Kleber, Markus Perola, Alexandre F.R. Stewart, Jaspal S. Kooner, Themistocles L. Assimes, Inês Barroso, Bruna Gigante, Göran Hallmans, Marja-Liisa Lokki, Aki S. Havulinna, Anders Hamsten, Agneta Siegbahn, Lasse Folkersen, Erik Ingelsson, Martina E. Zimmermann, Colin N. A. Palmer, Paolo Brambilla, Ann-Christine Syvänen, Alun Evans, Åsa Johansson, John F. Peden, Alex S. F. Doney, Hugh Watkins, Johanna Kuusisto, Anders Lundmark, David G. Cox, Hyun Min Kang, Lars Lind, Krista Fischer, Markku S. Nieminen, Annette Peters, Norman Klopp, Stefan Gustafsson, Lars Wallentin, Nancy L. Pedersen, David-Alexandre Trégouët, Ulf de Faire, Deloukas, P, Kanoni, S, Willenborg, C, Farrall, M, Assimes, T, Thompson, J, Ingelsson, E, Saleheen, D, Erdmann, J, Goldstein, B, Stirrups, K, König, I, Cazier, J, Johansson, Å, Hall, A, Lee, J, Willer, C, Chambers, J, Esko, T, Folkersen, L, Goel, A, Grundberg, E, Havulinna, A, Ho, W, Hopewell, J, Eriksson, N, Kleber, M, Kristiansson, K, Lundmark, P, Lyytikäinen, L, Rafelt, S, Shungin, D, Strawbridge, R, Thorleifsson, G, Tikkanen, E, Van Zuydam, N, Voight, B, Waite, L, Zhang, W, Ziegler, A, Absher, D, Altshuler, D, Balmforth, A, Barroso, I, Braund, P, Burgdorf, C, Claudi Boehm, S, Cox, D, Dimitriou, M, Do, R, Doney, A, El Mokhtari, N, Eriksson, P, Fischer, K, Fontanillas, P, Franco Cereceda, A, Gigante, B, Groop, L, Gustafsson, S, Hager, J, Hallmans, G, Han, B, Hunt, S, Kang, H, Illig, T, Kessler, T, Knowles, J, Kolovou, J, Kuusisto, J, Langenberg, C, Langford, C, Leander, K, Lokki, M, Lundmark, A, Mccarthy, M, Meisinger, C, Melander, O, Mihailov, E, Maouche, S, Morris, A, Müller Nurasyid, M, Nikus, K, Peden, J, Rayner, N, Rasheed, A, Rosinger, S, Rubin, D, Rumpf, M, Schäfer, A, Sivananthan, M, Song, C, Stewart, A, Tan, S, Thorgeirsson, G, van der Schoot, C, Wagner, P, Wells, G, Wild, P, Yang, T, Amouyel, P, Arveiler, D, Basart, H, Boehnke, M, Boerwinkle, E, Brambilla, P, Cambien, F, Cupples, A, de Faire, U, Dehghan, A, Diemert, P, Epstein, S, Evans, A, Ferrario, M, Ferrières, J, Gauguier, D, Go, A, Goodall, A, Gudnason, V, Hazen, S, Holm, H, Iribarren, C, Jang, Y, Kähönen, M, Kee, F, Kim, H, Klopp, N, Koenig, W, Kratzer, W, Kuulasmaa, K, Laakso, M, Laaksonen, R, Lind, L, Ouwehand, W, Parish, S, Park, J, Pedersen, N, Peters, A, Quertermous, T, Rader, D, Salomaa, V, Schadt, E, Shah, S, Sinisalo, J, Stark, K, Stefansson, K, Trégouët, D, Virtamo, J, Wallentin, L, Wareham, N, Zimmermann, M, Nieminen, M, Hengstenberg, C, Sandhu, M, Pastinen, T, Syvänen, A, Hovingh, G, Dedoussis, G, Franks, P, Lehtimäki, T, Metspalu, A, Zalloua, P, Siegbahn, A, Schreiber, S, Ripatti, S, Blankenberg, S, Perola, M, Clarke, R, Boehm, B, O’Donnell, C, Reilly, M, März, W, Collins, R, Kathiresan, S, Hamsten, A, Kooner, J, Thorsteinsdottir, U, Danesh, J, Palmer, C, Roberts, R, Watkins, H, Schunkert, H, Samani, N, Landsteiner Laboratory, Clinical Haematology, Other departments, ACS - Amsterdam Cardiovascular Sciences, and Vascular Medicine
Subjects: Adult, Asian Continental Ancestry Group, Male, Candidate gene, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, Population, European Continental Ancestry Group, Quantitative Trait Loci, CAD, Genome-wide association study, Single-nucleotide polymorphism, Coronary Artery Disease, 030204 cardiovascular system & hematology, Biology, Quantitative trait locus, Bioinformatics, Polymorphism, Single Nucleotide, Article, White People, coronary artery disease, risk loci, Cell Line, Coronary artery disease, 03 medical and health sciences, 0302 clinical medicine, Asian People, Risk Factors, medicine, Humans, genetics, Gene Regulatory Networks, Genetic Predisposition to Disease, cardiovascular diseases, Polymorphism, education, 030304 developmental biology, Genetic association, Aged, Genetics, 0303 health sciences, education.field_of_study, Adult, Aged, Asian Continental Ancestry Group, Cell Line, Coronary Artery Disease, genetics, European Continental Ancestry Group, genetics, Female, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Risk Factors, Single Nucleotide, Middle Aged, medicine.disease, 3. Good health, Female, Genome-Wide Association Study
Abstract: Coronary artery disease (CAD) is the commonest cause of death. Here, we report an association analysis in 63,746 CAD cases and 130,681 controls identifying 15 loci reaching genome-wide significance, taking the number of susceptibility loci for CAD to 46, and a further 104 independent variants (r 2 < 0.2) strongly associated with CAD at a 5% false discovery rate (FDR). Together, these variants explain approximately 10.6% of CAD heritability. Of the 46 genome-wide significant lead SNPs, 12 show a significant association with a lipid trait, and 5 show a significant association with blood pressure, but none is significantly associated with diabetes. Network analysis with 233 candidate genes (loci at 10% FDR) generated 5 interaction networks comprising 85% of these putative genes involved in CAD. The four most significant pathways mapping to these networks are linked to lipid metabolism and inflammation, underscoring the causal role of these activities in the genetic etiology of CAD. Our study provides insights into the genetic basis of CAD and identifies key biological pathways. © 2013 Nature America, Inc. All rights reserved.
Published: 2012
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6. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease

Author: Mélissa Beaudoin, Stephan Ripke, Jonas Halfvarson, Leif Törkvist, Dermot P.B. McGovern, Caroline Lagacé, Todd Green, David Ellinghaus, Mauro D'Amato, Andrew Kirby, Manuel A. Rivas, Steven R. Brant, Ramnik J. Xavier, Stacey Gabriel, Guillaume Lettre, Joshua M. Korn, Philippe Goyette, Finny G Kuruvilla, Clarence K. Zhang, Noël P. Burtt, Agnes Gardet, Richard H. Duerr, Timothy Fennell, Yashoda Sharma, Benjamin M. Neale, Andre Franke, Ken Sin Lo, David Altshuler, Gabrielle Boucher, Talin Haritunians, Marla Dubinsky, Phil Schumm, John D. Rioux, Mark J. Daly, Judy H. Cho, Mark S. Silverberg, Anna Latiano, Christine Stevens, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, and Gastroenterology and Hepatology
Subjects: RNA Splicing, Nod2 Signaling Adaptor Protein, Genome-wide association study, Biology, Molecular gastro-enterology and hepatology Pathogenesis and modulation of inflammation [IGMD 2], Inflammatory bowel disease, Article, Cell Line, PTPN22, 03 medical and health sciences, 0302 clinical medicine, Genetics, medicine, Humans, Genetic Predisposition to Disease, Genotyping, 030304 developmental biology, Genetic association, 0303 health sciences, Case-control study, Receptors, Interleukin, Sequence Analysis, DNA, Odds ratio, Inflammatory Bowel Diseases, medicine.disease, 3. Good health, Case-Control Studies, 030220 oncology & carcinogenesis, Genome-Wide Association Study, Common disease-common variant
Abstract: Item does not contain fulltext More than 1,000 susceptibility loci have been identified through genome-wide association studies (GWAS) of common variants; however, the specific genes and full allelic spectrum of causal variants underlying these findings have not yet been defined. Here we used pooled next-generation sequencing to study 56 genes from regions associated with Crohn's disease in 350 cases and 350 controls. Through follow-up genotyping of 70 rare and low-frequency protein-altering variants in nine independent case-control series (16,054 Crohn's disease cases, 12,153 ulcerative colitis cases and 17,575 healthy controls), we identified four additional independent risk factors in NOD2, two additional protective variants in IL23R, a highly significant association with a protective splice variant in CARD9 (P < 1 x 10(-16), odds ratio approximately 0.29) and additional associations with coding variants in IL18RAP, CUL2, C1orf106, PTPN22 and MUC19. We extend the results of successful GWAS by identifying new, rare and probably functional variants that could aid functional experiments and predictive models. 01 november 2011
Published: 2011

7. A framework for variation discovery and genotyping using next-generation DNA sequencing data

Author: Guillermo del Angel, Manuel A. Rivas, Ryan Poplin, Kiran V. Garimella, Matt Hanna, Aaron McKenna, Andrey Sivachenko, David Altshuler, Mark A. DePristo, Christopher Hartl, Kristian Cibulskis, Timothy Fennell, Jared Maguire, Stacey Gabriel, Anthony A. Philippakis, Eric Banks, Andrew Kernytsky, and Mark J. Daly
Subjects: Genotype, Population, Computational biology, Biology, Polymorphism, Single Nucleotide, Genome, Article, DNA sequencing, 03 medical and health sciences, 0302 clinical medicine, Genetics, Humans, 1000 Genomes Project, education, Genotyping, 030304 developmental biology, 0303 health sciences, education.field_of_study, Variant Call Format, Genome, Human, Genetic Variation, DNA sequencing theory, Exons, Sequence Analysis, DNA, Genetics, Population, Data Interpretation, Statistical, 030220 oncology & carcinogenesis, Quality Score, Databases, Nucleic Acid, Sequence Alignment, Software
Abstract: Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (∼4×) 1000 Genomes Project datasets.
Published: 2011

8. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

Author: Kenneth Rice, Amy J. Swift, Veronique Vitart, Lu Qi, Kaisa Silander, Olivier Le Bacquer, Laura Crisponi, David S. Siscovick, Bo Isomaa, Anne U. Jackson, Anke Tönjes, Richard N. Bergman, Rosa Maria Roccasecca, Luigi Ferrucci, Narisu Narisu, Kari Stefansson, Holly E. Syddall, Giuseppe Paolisso, Kim L. Ward, Paul Elliott, Scott M. Grundy, Paul Johnson, Jerome I. Rotter, Philippe Froguel, James B. Meigs, George Davey Smith, Andrew T. Hattersley, Leena Peltonen, Eric J.G. Sijbrands, Serena Sanna, María TeresaMartínez-Larrad, David Altshuler, Harald Grallert, Caroline S. Fox, Nita G. Forouhi, Dorret I. Boomsma, Harry Campbell, Jean Tichet, Angelo Scuteri, Aroon D. Hingorani, Daniel S. Pearson, Meena Kumari, Silvia Naitza, Shah Ebrahim, Manjinder S. Sandhu, Jose C. Florez, Cyrus Cooper, David M. Nathan, Joseph Hung, Fredrik Karpe, Ozren Polasek, Philip J. Barter, Ruth McPherson, Benjamin F. Voight, Wolfgang Rathmann, Abbas Dehghan, Udo Seedorf, Beverley M. Shields, Antti Jula, Pau Navarro, Josephine M. Egan, Rune R. Frants, Leif Groop, Gunnar Sigursson, Seppo Koskinen, Vincent Mooser, François Pattou, Jing Hua Zhao, Irene Pichler, John F. Peden, Göran Hallmans, Toshiko Tanaka, Ruth J. F. Loos, Peter Kovacs, Andrew D. Morris, Cécile Lecoeur, Jeffrey R. O'Connell, Massimo Mangino, Nicole Vogelzangs, Rhian Gwilliam, Gordon H. Williams, Carina Zabena, Naomi Hammond, Amélie Bonnefond, Björn Zethelius, Joachim Spranger, Nancy L. Pedersen, Christopher J. Groves, Nicholas J. Timpson, George Dedoussis, Veikko Salomaa, Peter Henneman, Andrew Walley, Serge Hercberg, Ian N. M. Day, Simon Heath, Matt Neville, Alex S. F. Doney, Robert Clarke, Olov Rolandsson, Panos Deloukas, Eric Boerwinkle, Y. AnteroKesaniemi, Mike Sampson, Gerard Waeber, Sven Bergmann, Ben A. Oostra, Manuel Serrano-Ríos, Mandy van Hoek, Christine Cavalcanti-Proença, Anna L. Gloyn, Ulla Sovio, Andrew P. Morris, Anneli Pouta, Amanda J. Bennett, Paul Scheet, Peter Schwarz, Jaakko Tuomilehto, Hugh Watkins, Johanna Kuusisto, Denis Rybin, Anna LiisaHartikainen, Maria GraziaFranzosi, Unnur Thorsteinsdottir, Rafn Benediktsson, Alan F. Wright, Colin N. Apalmer, Anuj Goel, Yavuz Ariyurek, Lars Lind, Robert Sladek, Stefan R. Bornstein, Reedik Mägi, Laila Simpson, Tim D. Spector, Paul W. Franks, Nicholas L. Smith, John R. B. Perry, Peter Vollenweider, Suzannah Bumpstead, Ruth E. Pakyz, Christa Meisinger, Alan R. Shuldiner, Josée Dupuis, Man Li, Eric J. Brunner, Francis S. Collins, Torben Hansen, James F. Wilson, Guangju Zhai, Igor Rudan, Nicole L. Glazer, Marco Orrù, Pierre Meneton, Knut Borch-Johnsen, Eleanor Wheeler, Gonçalo R. Abecasis, Mark I. McCarthy, Jouke JanHottenga, Inga Prokopenko, Ping An, Jérôme Delplanque, Albert Hofman, Andrew B. Singleton, Gabe Crawford, Thomas A. Buchanan, Avan Aihie Sayer, Richard M. Watanabe, David Schlessinger, A C Fedson, André G. Uitterlinden, Frank B. Hu, Jaqueline C. MWitteman, Dhiraj Varma, Ingrid B. Borecki, Sutapa Mukherjee, Murielle Bochud, Barbara Thorand, Christian Gieger, Lori L. Bonnycastle, Stephen J. Sharp, Markus Perola, Caroline Hayward, Kristin Ardlie, J. Graessler, Robert W. Mahley, Toby Johnson, Jian'an Luan, Joshua C. Randall, Cornelia M. van Duijn, Samuli Ripatti, Ko Willems van Dijk, Valgerdur Steinthorsdottir, Yurii S. Aulchenko, G. Mark Lathrop, Christian Dina, Eleftheria Zeggini, Cecilia M. Lindgren, Stavroula Kanoni, Timothy M. Frayling, Dawn M. Waterworth, Marika Kaakinen, Timo T. Valle, Diana Zelenika, Yii Der IdaChen, Angela Silveira, Nigel W. Rayner, Aimo Ruokonen, Yun Li, Cristian Pattaro, Annelli Sandbæk, Richa Saxena, Danielle Posthuma, Steven A. McCarroll, Niels Grarup, Samy Hadjadj, Pilar Galan, Xijing Han, Lyle J. Palmer, Ulf Gyllensten, Peter P. Pramstaller, Manuela Uda, Jarred B. McAteer, Brenda W.J.H. Penninx, Debbie A Lawlor, Torben Jørgensen, Beatrice Knight, Yvonne Böttcher, Claudia Langenberg, Nicole Soranzo, Ghislain Rocheleau, Erik Ingelsson, Mario A. Morken, Michael Roden, Felicity Payne, David R. Hillman, Michael Marmot, Karen L. Mohlke, Heather M. Stringham, Bruce M. Psaty, Gudmar Thorleifsson, Yoav Ben-Shlomo, Inês Barroso, W. H. Linda Kao, James S. Pankow, Valeriya Lyssenko, Nicholas J. Wareham, Tiinamaija Tuomi, Ann ChristineSyvänen, Braxton D. Mitchell, Alisa K. Manning, Mika Kivimäki, Peter Wagner, Praveen Sethupathy, G. BragiWalters, Jaakko Kaprio, Kijoung Song, Marjo Riitta-Järvelin, Michael A. Province, Andrew A. Hicks, Marilyn C. Cornelis, Sarah H. Wild, David Meyre, Guillaume Charpentier, Patrik K. E. Magnusson, David Melzer, Jennie Hui, Peter Shrader, Michael Stumvoll, Mark O. Goodarzi, Michael R. Erdos, Oluf Pedersen, Andreas Pfeiffer, Augustine Kong, Christian Herder, Laura J. Scott, John W. GYarnell, Kirsten Ohm Kyvik, Beverley Balkau, Antje Fischer-Rosinsky, Gonneke Willemsen, Thomas Illig, Neelam Hassanali, Markku Laakso, Michael Boehnke, John Beilby, Christopher S. Franklin, Fernando Rivadeneira, M. Carola Zillikens, Michael N. Weedon, Antonio Cao, Mark E. Cooper, Simon C. Potter, Eco J. C. de Geus, H.-Erich Wichmann, Amanda F. Elliott, Lachlan J. McOin, Sophie Visvikis-Siest, Thomas Sparsø, Laura J. McCulloch, Taina K. Lajunen, Peter S. Chines, Nabila Bouatia-Naji, Medical Research Council (MRC), Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Anxiety & Depression, Neuroscience Campus Amsterdam - Attention & Cognition, EMGO+ - Mental Health, Ophthalmology, Epidemiology, Clinical Genetics, Dermatology, Internal Medicine, DIAGRAM Consortium, GIANT Consortium, Global BPgen Consortium, Anders Hamsten on behalf of Procardis Consortium, MAGIC investigators, Human genetics, Psychiatry, EMGO - Mental health, NCA - Attention & Cognition, and NCA - Anxiety & Depression
Subjects: Blood Glucose, Netherlands Twin Register (NTR), Candidate gene, Genome-wide association study, Type 2 diabetes, CIRCADIAN CLOCK, TRIGLYCERIDE LEVELS, 0302 clinical medicine, Delta-5 Fatty Acid Desaturase, Databases, Genetic, Homeostasis, GENETICS & HEREDITY, Anders Hamsten on behalf of Procardis Consortium, Child, Genetics, PLASMA-GLUCOSE, 0303 health sciences, Glucokinase regulatory protein, COMMON VARIANTS, 11 Medical And Health Sciences, Fasting, MAGIC investigators, 3. Good health, MODEL ASSESSMENT, Life Sciences & Biomedicine, Adult, medicine.medical_specialty, ESSENTIAL COMPONENTS, Adolescent, DNA Copy Number Variations, Alleles, Blood Glucose/genetics, Blood Glucose/metabolism, DNA Copy Number Variations/genetics, Diabetes Mellitus, Type 2/genetics, Fasting/blood, Gene Expression Regulation, Genetic Loci/genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Homeostasis/genetics, Humans, Meta-Analysis as Topic, Polymorphism, Single Nucleotide/genetics, Quantitative Trait Loci/genetics, Quantitative Trait, Heritable, Reproducibility of Results, Quantitative Trait Loci, 030209 endocrinology & metabolism, Biology, DIAGRAM Consortium, INSULIN-SECRETION, Polymorphism, Single Nucleotide, Article, Fasting glucose, 03 medical and health sciences, Insulin resistance, SDG 3 - Good Health and Well-being, Diabetes mellitus, Internal medicine, genome wide association study, glucose, diabetes type 2, medicine, GIANT Consortium, Allele, GENOME-WIDE ASSOCIATION, Global BPgen Consortium, 030304 developmental biology, Glycemic, Science & Technology, genome-wide association beta-cell dysfunction plasma-glucose insulin-secretion triglyceride levels essential components model assessment common variants circadian clock disease risk, DISEASE RISK, 06 Biological Sciences, medicine.disease, Endocrinology, Diabetes Mellitus, Type 2, Genetic Loci, biology.protein, BETA-CELL DYSFUNCTION, Developmental Biology
Abstract: Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46, 186 nondiabetic participants. Follow-up of 25 loci in up to 76, 558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.
Published: 2010
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9. Donor-recipient mismatch for common gene deletion polymorphisms in graft-versus-host disease

Author: Edus H. Warren, Steven A. McCarroll, Paul J. Martin, Liisa Volin, Barry E. Storer, Stephanie J. Lee, Jukka Partanen, Robert J. Soiffer, Lue Ping Zhao, James E. Bradner, David Altshuler, Jerome Ritz, Hannu Turpeinen, Joseph H. Antin, David Ginsburg, John A. Hansen, Aarno Palotie, Tapani Ruutu, Bo Zhang, and Shannon D Chilewski
Subjects: Male, medicine.medical_treatment, Graft vs Host Disease, Locus (genetics), Hematopoietic stem cell transplantation, Human leukocyte antigen, Biology, Article, Cohort Studies, Minor Histocompatibility Antigens, 03 medical and health sciences, 0302 clinical medicine, HLA Antigens, Genetics, Minor histocompatibility antigen, medicine, Humans, Glucuronosyltransferase, Bone Marrow Transplantation, 030304 developmental biology, 0303 health sciences, Polymorphism, Genetic, Genome, Human, Alloimmunity, Hematopoietic Stem Cell Transplantation, medicine.disease, 3. Good health, Histocompatibility, Transplantation, surgical procedures, operative, Graft-versus-host disease, Immunology, Female, Gene Deletion, 030215 immunology
Abstract: Transplantation and pregnancy, in which two diploid genomes reside in one body, can each lead to diseases in which immune cells from one individual target antigens encoded in the other's genome. One such disease, graft-versus-host disease (GVHD) after hematopoietic stem cell transplantation (HSCT, or bone marrow transplant), is common even after transplants between HLA-identical siblings, indicating that cryptic histocompatibility loci exist outside the HLA locus. The immune system of an individual whose genome is homozygous for a gene deletion could recognize epitopes encoded by that gene as alloantigens. Analyzing common gene deletions in three HSCT cohorts (1,345 HLA-identical sibling donor-recipient pairs), we found that risk of acute GVHD was greater (odds ratio (OR) = 2.5; 95% confidence interval (CI) 1.4-4.6) when donor and recipient were mismatched for homozygous deletion of UGT2B17, a gene expressed in GVHD-affected tissues and giving rise to multiple histocompatibility antigens. Human genome structural variation merits investigation as a potential mechanism in diseases of alloimmunity.
Published: 2009

10. Genome-wide association study identifies eight loci associated with blood pressure

Author: Peter Holmans, Udo Seedorf, Beverley M. Shields, Peter McGruffin, Arne Pfeufer, Steve Eyre, Nathalie J. Prescott, Michael Boehnke, Valentina Moskovina, Abiodun Onipinla, Leena Peltonen, Nadira Yuldasheva, Peter M. Nilsson, Valeria Romanazzi, Vincent Mooser, Göran Berglund, Alistair S. Hall, Dominic P. Kwiatkowski, Barry Widmer, Benjamin F. Voight, Stefania Bandinelli, Mark M. Iles, Sven Bergmann, Thomas Meitinger, James P. Boorman, Simonetta Guarrera, Nazneen Rahman, Murielle Bochud, Graham A. Hitman, Emma Keniry, Nelson B. Freimer, Richard Dobson, Francis S. Collins, Gerjan Navis, Jennifer L. Pointon, Richard N. Bergman, Ruth J. F. Loos, Roberto Lorbeer, Carolina A. Braga Marcano, Christian Gieger, Florian Ernst, Xin Yuan, Catherine Potter, Hazel E. Drummond, Allan H. Young, George Kirov, John F. Peden, Helen Stevens, David Clayton, Mattijs E. Numans, Katherine Gordon-Smith, Anne Farmer, Alastair Forbes, M. Khalid Mohiuddin, John A. Todd, Christopher G. Mathew, David A. Collier, Mark I. McCarthy, Francesca Bredin, Clive M. Onnie, Dan Davidson, Markus Perola, Pamela Whittaker, Yvonne T. van der Schouw, Rathi Ravindrarajan, I. C.A. Spencer, Teresa Ferreira, Nilesh J. Samani, Serge Hercberg, Gonçalo R. Abecasis, Christopher J. Groves, Nicholas John Craddock, Angela Döring, Edward G. Lakatta, Muminatou Jallow, Wendy L. McArdle, David Bentley, Susana Eyheramendy, Uwe Völker, Christopher Newton-Cheh, Jaspal S. Kooner, Hugh Watkins, Gavin Lucas, H. T. Leung, Marjo Ritta Jarvelin, Johanna Kuusisto, Wiek H. van Gilst, Wendy Thomson, Lou R. Cardon, Harold Snieder, Marju Orho-Melander, Patricia B. Munroe, Toshiko Tanaka, Jeffrey C. Barrett, Azhar Maqbool, Henry Völzke, John M. C. Connell, Elaine R. Nimmo, John R. B. Perry, Michael R. Stratton, Ralph McGinnis, Pekka Jousilahti, Michiel L. Bots, Ian Jones, Elizabeth Meech, Matthew A. Brown, Johannie Gungadoo, Jian'an Luan, Jilur Ghori, Richard J. Dixon, N. Charlotte Onland-Moret, Fulvio Ricceri, Anthony J. Balmforth, Catherine E. Todhunter, Inês Barroso, Sheila Bingham, Timo T. Valle, Fredrik O. Vannberg, Diana Zelenika, Stephen Sawcer, Anneli Pouta, David M. Evans, Cuno S. P. M. Uiterwaal, Pilar Galan, Georg Homuth, Hannah Donovan, David J. Conway, Paul Elliott, Alessandra Allione, Paul E. de Jong, Miles Parkes, Amy Chaney, John C. Chambers, Toby Johnson, Isaac Subirana, Vesela Gateva, Cathryn M. Lewis, Christopher J. O'Donnell, Hana Lango, David Schlessinger, Mark J. Caulfield, Thorsten Reffelmann, Jamie Barbour, Karen L. Mohlke, Sarah E. Hunt, Thilo Winzer, Frances M K Williams, Christopher Mathew, I. Wallace, Anuj Goel, Jaakko Tuomilehto, Louise V. Wain, Gabriel Crawford, Samantha L. Hider, Detelinea Grozeva, Elaine K. Green, Paul D. Gilbert, Peter S. Braund, Jaume Marrugat, Rainer Rettig, Pim van der Harst, Yik Ying Teo, Andrew P. Morris, Guiseppe Matullo, Serena Sanna, Cristen J. Willer, Suzannah Bumpstead, Niall C. Taylor, Jacques S. Beckmann, Pierre Meneton, Elin Org, Luigi Ferrucci, Doug Easton, Sheila Seal, Joanne M. Heward, Anne U. Jackson, Eleftheria Zeggini, Rachel M. Freathy, Maris Laan, Paul Wordsworth, Sarah Nutland, Kerstin Koch, Sian Ceasar, Anders Hamsten, Judith M. Hussey, Tariq Ahmad, Derek P. Jewell, Paul Scheet, Charlie W. Lees, C Farrar, Christopher Prowse, Markku Laakso, David St Clair, Kate Downes, Diederick E. Grobbee, Paul Burton, Simon C. Potter, Ian N. Bruce, Tim D. Spector, Anne Barton, H.-Erich Wichmann, Matthew J. Simmonds, David Hadley, Cecilia M. Lindgren, Gérard Waeber, Nigel W. Rayner, Melanie J. Newport, Manjinder S. Sandhu, Audrey Duncanson, Guangju Zhai, Simon Heath, Susan M. Ring, Alessandra Di Gregorio, Richard Williamson, Nicholas J. Wareham, Zhan Su, Olle Melander, John R. Thompson, Alexander Teumer, Sheila A. Fisher, Lachlan J. M. Coin, Leif Groop, Giovanni Tognoni, Amanda Elkin, Alan J. Silman, Jack Satsangi, Jane Worthington, Martin Farrall, John Webster, Niall Cardin, Neil Walker, Anna F. Dominiczak, Jeremy D. Sanderson, Damjan Vukcevic, Bryan Howie, Silvia Polidoro, Stephen G. Ball, Mark Tremelling, Stephen Newhouse, Stephen M. Schwartz, Lori L. Bonnycastle, Chris Wallace, Kijoung Song, Mario A. Morken, I. Nicol Ferrier, Beverley Barke, Paolo Vineis, Manuela Uda, Deborah P M Symmons, Emily J. Lyons, Mingzhan Xue, Timothy M. Frayling, Stephen C.L. Cough, David Withers, Adrian V. S. Hill, Suzanne Stevens, Jennifer Jolley, Marcus Dörr, Kirk A. Rockett, David B. Dunger, Mark Walker, Jayne A. Franklyn, Lisa Jones, David S. Siscovick, Ann-Christine Syvänen, Laura J. Scott, Morris J. Brown, Barbera Cant, Michael Inouye, Feng Zhang, Carlotta Sacerdote, Katherine S. Elliott, Jonathan Marchini, Peter Donnely, Michael John Owen, An Goris, Marcus Prembey, Andrew T. Hattersley, Gerome Breen, Marian L. Hamshere, Thomas Illig, Samer S. Najjar, Nicole Soranzo, Kay-Tee Khaw, Graham R. Walters, Willem H. Ouwehand, David P. Strachan, Martin D. Tobin, Alastair Compston, John C. Mansfield, David Altshuler, Salvatore Panico, Sekar Kathiresan, Dawn M. Waterworth, Michael N. Weedon, D. Timothy Bishop, Claire Bryan, Alexandra S. Knight, Kate L. Lee, Paul F. O'Reilly, Massimo Mangino, Michael Conlon O'Donovan, Jing Hua Zhao, Konstantinos A. Papadakis, Jennifer H. Barrett, Joanne Pereira-Gale, N J Timpson, Stephan B. Felix, Panos Deloukas, Nicholas A. Watkins, Anna-Liisa Hartikainen, Peter Vollenweider, Richard Jones, Anne Hinks, Fraser Cummings, Noha Lim, Linda A. Bradbury, Rhian G. William, Nita G. Forouhi, Roberto Eluosa, Ingeleif B. Hallgrimsdottir, Giorgio Sirugo, Robert Luben, Veikko Salomaa, Robert Clarke, Sally John, Ursula Everson, Emma King, Ivan Nikolov, Heather M. Stringham, Antony P. Attwood, Angelo Scuteri, Wellcome Trust Case Control Consortium, Burton, PR., Clayton, DG., Cardon, LR., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, DP., McCarthy, MI., Ouwehand, WH., Samani, NJ., Todd, JA., Donnelly, P., Barrett, JC., Davison, D., Easton, D., Evans, D., Leung, HT., Marchini, JL., Morris, AP., Spencer, IC., Tobin, MD., Attwood, AP., Boorman, JP., Cant, B., Everson, U., Hussey, JM., Jolley, JD., Knight, AS., Koch, K., Meech, E., Nutland, S., Prowse, CV., Stevens, HE., Taylor, NC., Walters, GR., Walker, NM., Watkins, NA., Winzer, T., Jones, RW., McArdle, WL., Ring, SM., Strachan, DP., Pembrey, M., Breen, G., St Clair, D., Caesar, S., Gordon-Smith, K., Jones, L., Fraser, C., Green, EK., Grozeva, D., Hamshere, ML., Holmans, PA., Jones, IR., Kirov, G., Moskvina, V., Nikolov, I., O'Donovan, MC., Owen, MJ., Collier, DA., Elkin, A., Farmer, A., Williamson, R., McGuffin, P., Young, AH., Ferrier, IN., Ball, SG., Balmforth, AJ., Barrett, JH., Bishop, DT., Iles, MM., Maqbool, A., Yuldasheva, N., Hall, AS., Braund, PS., Dixon, RJ., Mangino, M., Stevens, S., Thompson, JR., Bredin, F., Tremelling, M., Parkes, M., Drummond, H., Lees, CW., Nimmo, ER., Satsangi, J., Fisher, SA., Forbes, A., Lewis, CM., Onnie, CM., Prescott, NJ., Sanderson, J., Mathew, CG., Barbour, J., Mohiuddin, MK., Todhunter, CE., Mansfield, JC., Ahmad, T., Cummings, FR., Jewell, DP., Webster, J., Brown, MJ., Lathrop, GM., Connell, J., Dominiczak, A., Braga Marcano, CA., Burke, B., Dobson, R., Gungadoo, J., Lee, KL., Munroe, PB., Newhouse, SJ., Onipinla, A., Wallace, I., Xue, M., Caulfield, M., Farrall, M., Barton, A., Bruce, IN., Donovan, H., Eyre, S., Gilbert, PD., Hider, SL., Hinks, AM., John, SL., Potter, C., Silman, AJ., Symmons, DP., Thomson, W., Worthington, J., Dunger, DB., Widmer, B., Frayling, TM., Freathy, RM., Lango, H., Perry, JR., Shields, BM., Weedon, MN., Hattersley, AT., Hitman, GA., Walker, M., Elliott, KS., Groves, CJ., Lindgren, CM., Rayner, NW., Timpson, NJ., Zeggini, E., Newport, M., Sirugo, G., Lyons, E., Vannberg, F., Hill, AV., Bradbury, LA., Farrar, C., Pointon, JJ., Wordsworth, P., Brown, MA., Franklyn, JA., Heward, JM., Simmonds, MJ., Gough, SC., Seal, S., Stratton, MR., Rahman, N., Ban, M., Goris, A., Sawcer, SJ., Compston, A., Conway, D., Jallow, M., Rockett, KA., Bryan, C., Bumpstead, SJ., Chaney, A., Downes, K., Ghori, J., Gwilliam, R., Hunt, SE., Inouye, M., Keniry, A., King, E., McGinnis, R., Potter, S., Ravindrarajah, R., Whittaker, P., Withers, D., Cardin, NJ., Ferreira, T., Pereira-Gale, J., Hallgrimsdóttir, IB., Howie, BN., Su, Z., Teo, YY., Vukcevic, D., Bentley, D., Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Vascular Ageing Programme (VAP), and Medical Research Council (MRC)
Subjects: Hemodynamics, Genome-wide association study, Blood Pressure, 030204 cardiovascular system & hematology, 0302 clinical medicine, Diastole, 11 Medical and Health Sciences, POPULATION, Genetics, Genetics & Heredity, RISK, 0303 health sciences, education.field_of_study, Econometric and Statistical Methods: General, CELL-DIFFERENTIATION, biology, Intracellular Signaling Peptides and Proteins, Chromosome Mapping, Steroid 17-alpha-Hydroxylase, COMMON VARIANTS, 3. Good health, DNA-Binding Proteins, Europe, Cardiovascular Diseases, PUBLIC-HEALTH, BARTTERS-SYNDROME, Blood Pressure/genetics, Cardiovascular Diseases/genetics, Cardiovascular Diseases/physiopathology, Cytochrome P-450 CYP1A2/genetics, DNA-Binding Proteins/genetics, Diastole/genetics, European Continental Ancestry Group/genetics, Fibroblast Growth Factor 5/genetics, Genetic Variation, Genome-Wide Association Study, Humans, India, Methylenetetrahydrofolate Reductase (NADPH2)/genetics, Open Reading Frames/genetics, Phospholipase C delta/genetics, Polymorphism, Single Nucleotide, Proteins/genetics, Steroid 17-alpha-Hydroxylase/genetics, Systole/genetics, Wellcome Trust Case Control Consortium, Life Sciences & Biomedicine, hypertension, Fibroblast Growth Factor 5, Systole, Population, European Continental Ancestry Group, METHYLENETETRAHYDROFOLATE REDUCTASE GENE, Single-nucleotide polymorphism, LOW-RENIN HYPERTENSION, White People, Article, 03 medical and health sciences, Open Reading Frames, Fibroblast growth factor-5, Cytochrome P-450 CYP1A2, Geneeskunde(GENK), education, Methylenetetrahydrofolate Reductase (NADPH2), Adaptor Proteins, Signal Transducing, 030304 developmental biology, Genetic association, genome-wide association, Science & Technology, MUTATIONS, Proteins, 06 Biological Sciences, POLYMORPHISM, Blood pressure, Methylenetetrahydrofolate reductase, biology.protein, biology.gene, Phospholipase C delta, Developmental Biology
Abstract: Elevated blood pressure is a common, heritable cause of cardiovascular disease worldwide. To date, identification of common genetic variants influencing blood pressure has proven challenging. We tested 2.5 million genotyped and imputed SNPs for association with systolic and diastolic blood pressure in 34,433 subjects of European ancestry from the Global BPgen consortium and followed up findings with direct genotyping (N ≤ 71,225 European ancestry, N ≤ 12,889 Indian Asian ancestry) and in silico comparison (CHARGE consortium, N = 29,136). We identified association between systolic or diastolic blood pressure and common variants in eight regions near the CYP17A1 (P = 7 × 10(-24)), CYP1A2 (P = 1 × 10(-23)), FGF5 (P = 1 × 10(-21)), SH2B3 (P = 3 × 10(-18)), MTHFR (P = 2 × 10(-13)), c10orf107 (P = 1 × 10(-9)), ZNF652 (P = 5 × 10(-9)) and PLCD3 (P = 1 × 10(-8)) genes. All variants associated with continuous blood pressure were associated with dichotomous hypertension. These associations between common variants and blood pressure and hypertension offer mechanistic insights into the regulation of blood pressure and may point to novel targets for interventions to prevent cardiovascular disease.
Published: 2009

11. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes

Author: Andrew Paterson, Neeraj Kumar, Luis Castaño, Jinny Willis, Valdis Pirags, David Altshuler, Farren Briggs, Neil Walker, Ondrej Cinek, Helen Schuilenburg, Francisco Javier Ampudia Blasco, Claire Vandiedonck, Mark A. Hall, Ana M Wägner, Xiaoying Li, Flemming Pociot, Didac Mauricio, Vaidotas Urbanavicius, Jennifer Couper, Adam Kretowski, Deborah Smyth, Professor David Dunger, Federico Vázquez, Ian Nicholson, Ellen Schofield, John Todd, Angela Simpson, Ingrid Kockum, Mikael Knip, Tadej Battelino, Thomas Brodnicki, Patrick Concannon, Jesús Argente, Johnny Ludvigsson, Peter Colman, Gurvinder Kaur, Vincent Plagnol, Oliver Burren, Rohana Abdul Ghani, Marta Hernández, William McLaren, Alessandro Doria, Raquel Corripio, Stephen Rich, Daniel Metzger, Jesper Johannesen, Steven Willi, Cécile JULIER, Vallo Tillmann, Bart Van der Auwera, Pathology/molecular and cellular medicine, and Diabetes Pathology & Therapy
Subjects: Male, Candidate gene, Interferon-Induced Helicase, IFIH1, Endocrinology, Diabetes and Metabolism, Genome-wide association study, Protein Tyrosine Phosphatase, Non-Receptor Type 22/genetics, DEAD-box RNA Helicases, 0302 clinical medicine, Chromosomes, Human, Pair 17/genetics, HLA Antigens, Genotype, CTLA-4 Antigen, Chromosomes, Human, Pair 2/genetics, Genetics, 0303 health sciences, Antigens, CD/genetics, Chromosome Mapping, HLA Antigens/genetics, Polymorphism, Single Nucleotide/genetics, 3. Good health, Chromosomes, Human, Pair 1/genetics, DEAD-box RNA Helicases/genetics, Chromosomes, Human, Pair 1, Chromosomes, Human, Pair 2, Meta-analysis, Female, Algorithms, 030209 endocrinology & metabolism, Locus (genetics), CLEC16A, DNA/genetics, Biology, Polymorphism, Single Nucleotide, Risk Assessment, Article, PTPN22, 03 medical and health sciences, Meta-Analysis as Topic, Antigens, CD, medicine, Humans, Family, 030304 developmental biology, Type 1 diabetes, Siblings, Protein Tyrosine Phosphatase, Non-Receptor Type 22, DNA, medicine.disease, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 1/epidemiology, Chromosome Mapping/methods, Chromosomes, Human, Pair 17, Genome-Wide Association Study
Abstract: Type 1 diabetes (T1D) is a common autoimmune disorder that arises from the action of multiple genetic and environmental risk factors. We report the findings of a new genome-wide association study of T1D, combined in a meta-analysis with two previously published studies. The total sample set included 7,514 cases and 9,045 reference samples. Forty-one distinct genomic locations provided evidence for association to T1D in the meta-analysis (P < 10-6). After excluding previously reported associations, 27 regions were further tested in an independent set of 4,267 cases, 4,463 controls and 2,319 affected sib-pair (ASP) families. Of these, 18 regions were replicated (P < 0.01; overall P < 5 × 10-8) and four additional regions provided nominal evidence of replication (P < 0.05). The many new candidate genes suggested by these results include IL10, IL19, IL20, GLIS3, CD69 and IL27.
Published: 2009

12. Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion

Author: Michael Boehnke, Peter M. Nilsson, Marco Bugliani, Malin Fex, Johan G. Eriksson, Jaakko Tuomilehto, Nicolo Pulizzi, Richard M. Watanabe, Markku Laakso, Piero Marchetti, Peter Spégel, Cecilia Nagorny, Anna Jonsson, Valeriya Lyssenko, Bo Isomaa, Anne U. Jackson, Nils Wierup, Tiinamaija Tuomi, Hindrik Mulder, Richa Saxena, Frank Sundler, Michael R. Erdos, Leif Groop, Johanna Kuusisto, and David Altshuler
Subjects: Male, endocrine system, medicine.medical_specialty, endocrine system diseases, medicine.medical_treatment, Receptors, Melatonin, 030209 endocrinology & metabolism, Type 2 diabetes, Biology, Polymorphism, Single Nucleotide, Article, Cohort Studies, Melatonin, Islets of Langerhans, Mice, 03 medical and health sciences, Pineal gland, 0302 clinical medicine, Internal medicine, Diabetes mellitus, Insulin Secretion, Genetics, medicine, Animals, Humans, Insulin, Genetic Predisposition to Disease, Aged, 030304 developmental biology, 0303 health sciences, Receptor, Melatonin, MT2, Middle Aged, medicine.disease, Rats, Insulin oscillation, Protein Transport, Endocrinology, medicine.anatomical_structure, Diabetes Mellitus, Type 2, Gene Expression Regulation, Melatonin receptor 1B, Female, Hormone, medicine.drug
Abstract: Genome wide association studies revealed that variation in the Melatonin Receptor 1B gene (MTNR1B) is associated with insulin and glucose concentrations. Here we show that the risk genotype of this SNP predicts future type 2 diabetes (T2D) in two large prospective studies. Specifically, the risk genotype was associated with impairment of early insulin response to both oral and intravenous glucose and with faster deterioration of insulin secretion over time. We also show that the Melatonin Receptor 1B mRNA is expressed in human islets, and immunocytochemistry confirms that it is primarily localized in β-cells in islets. Non-diabetic individuals carrying the risk allele and patients with T2D showed increased expression of the receptor in islets. Insulin release from clonal β-cells in response to glucose was inhibited in the presence of melatonin. These data suggest that the circulating hormone melatonin, which is predominantly released from the pineal gland in the brain, is involved in the pathogenesis of T2D. Given the increased expression of Melatonin Receptor 1B in individuals at risk of T2D, the pathogenic effects are likely exerted via a direct inhibitory effect on β-cells. In view of these results, blocking the melatonin ligand-receptor system could be a therapeutic avenue in T2D.
Published: 2009
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13. Integrated detection and population-genetic analysis of SNPs and copy number variation

Author: John E. Blume, James Nemesh, Andrew Kirby, Julian Maller, Rui Mei, Steven A. McCarroll, Earl Hubbell, Joshua M. Korn, Steve Lincoln, Paul I.W. de Bakker, Stacey Gabriel, Marcia M. Nizzari, Amanda F. Elliott, Rich Rava, Patrick J Collins, Melissa Parkin, Finny G Kuruvilla, Mark J. Daly, Michael H. Shapero, Teresa Webster, Simon Cawley, Keith W. Jones, Robert E. Handsaker, Alec Wysoker, James Veitch, and David Altshuler
Subjects: Genetics, education.field_of_study, Linkage disequilibrium, Genome, Human, Population, Gene Dosage, Genetic Variation, Single-nucleotide polymorphism, DNA, Biology, Polymerase Chain Reaction, Polymorphism, Single Nucleotide, SNP genotyping, Haplotypes, Population Groups, Genetic variation, Chromosomes, Human, Humans, Copy-number variation, International HapMap Project, education, Allele frequency, Oligonucleotide Array Sequence Analysis
Abstract: Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.
Published: 2008

14. Common variants at CD40 and other loci confer risk of rheumatoid arthritis

Author: Robert M. Plenge, J. Bart A. Crusius, Niek de Vries, Soumya Raychaudhuri, Mark Seielstad, Tom W J Huizinga, Ann B. Begovich, Lars Klareskog, Peter K. Gregersen, Benjamin D. Korman, René E. M. Toes, Elizabeth W. Karlson, Annette Lee, Lindsey A. Criswell, Monica Chang, Candace Guiducci, Sandra Wong, Nancy A. Shadick, Karen H. Costenbader, Joseph J. Catanese, Michael F. Seldin, David Altshuler, Lauren Gianniny, Daniel L. Kastner, Elaine F. Remmers, Jane Worthington, Paul P. Tak, Annette H M van der Helm-van Mil, Michael E. Weinblatt, Kristin G. Ardlie, Jing Cui, Rachel Hackett, Fina A S Kurreeman, Gertjan Wolbink, Mark J. Daly, Benjamin M. Neale, Bo Ding, Irene E. van der Horst-Bruinsma, Jonathan S. Coblyn, Lars Alfredsson, Christopher I. Amos, Noël P. Burtt, Leonid Padyukov, Rheumatology, CCA - Disease profiling, Pathology, AII - Amsterdam institute for Infection and Immunity, Clinical Immunology and Rheumatology, and Landsteiner Laboratory
Subjects: PRKCQ, Genetic Linkage, Single-nucleotide polymorphism, Locus (genetics), Biology, TNFAIP3, Polymorphism, Single Nucleotide, Article, Arthritis, Rheumatoid, Genetic linkage, Genetics, medicine, Chromosomes, Human, Humans, Genetic Predisposition to Disease, CD40 Antigens, Gene, Genome, Human, Haplotype, Chromosome Mapping, medicine.disease, Haplotypes, Rheumatoid arthritis, Case-Control Studies, Immunology
Abstract: To identify rheumatoid arthritis risk loci in European populations, we conducted a meta-analysis of two published genome-wide association (GWA) studies totaling 3,393 cases and 12,462 controls. We genotyped 31 top-ranked SNPs not previously associated with rheumatoid arthritis in an independent replication of 3,929 autoantibody-positive rheumatoid arthritis cases and 5,807 matched controls from eight separate collections. We identified a common variant at the CD40 gene locus (rs4810485, P = 0.0032 replication, P = 8.2 x 10(-9) overall, OR = 0.87). Along with other associations near TRAF1 (refs. 2,3) and TNFAIP3 (refs. 4,5), this implies a central role for the CD40 signaling pathway in rheumatoid arthritis pathogenesis. We also identified association at the CCL21 gene locus (rs2812378, P = 0.00097 replication, P = 2.8 x 10(-7) overall), a gene involved in lymphocyte trafficking. Finally, we identified evidence of association at four additional gene loci: MMEL1-TNFRSF14 (rs3890745, P = 0.0035 replication, P = 1.1 x 10(-7) overall), CDK6 (rs42041, P = 0.010 replication, P = 4.0 x 10(-6) overall), PRKCQ (rs4750316, P = 0.0078 replication, P = 4.4 x 10(-6) overall), and KIF5A-PIP4K2C (rs1678542, P = 0.0026 replication, P = 8.8 x 10(-8) overall).
Published: 2008

15. Polymorphism at the TNF superfamily gene TNFSF4 confers susceptibility to systemic lupus erythematosus

Author: Timothy W. Behrens, Kathy L. Moser, Deborah S. Cunninghame Graham, Timothy J. Vyse, Patrick M. Gaffney, Andrew Wong, Harinder Manku, Robert R. Graham, David Altshuler, John C. Whittaker, and John D. Rioux
Subjects: medicine.medical_treatment, T cell, OX40 Ligand, Biology, Polymorphism, Single Nucleotide, Article, Genetics, medicine, Lupus Erythematosus, Systemic, Genetic Predisposition to Disease, Promoter Regions, Genetic, skin and connective tissue diseases, Receptor, Cells, Cultured, Autoimmune disease, Polymorphism, Genetic, Haplotype, FCGR3B, medicine.disease, United Kingdom, Cytokine, medicine.anatomical_structure, Haplotypes, Immunology, Tumor necrosis factor alpha, IRF5
Abstract: Systemic lupus erythematosus (SLE) is a multisystem complex autoimmune disease of uncertain etiology (OMIM 152700). Over recent years a genetic component to SLE susceptibility has been established1–3. Recent successes with association studies in SLE have identified genes including IRF5 (refs. 4,5) and FCGR3B6. Two tumor necrosis factor (TNF) superfamily members located within intervals showing genetic linkage with SLE are TNFSF4 (also known as OX40L; 1q25), which is expressed on activated antigen-presenting cells (APCs)7,8 and vascular endothelial cells9, and also its unique receptor, TNFRSF4 (also known as OX40; 1p36), which is primarily expressed on activated CD4+ T cells10. TNFSF4 produces a potent co-stimulatory signal for activated CD4+ T cells after engagement of TNFRSF4 (ref. 11). Using both a family-based and a case-control study design, we show that the upstream region of TNFSF4 contains a single risk haplotype for SLE, which is correlated with increased expression of both cell-surface TNFSF4 and the TNFSF4 transcript. We hypothesize that increased expression of TNFSF4 predisposes to SLE either by quantitatively augmenting T cell–APC interaction or by influencing the functional consequences of T cell activation via TNFRSF4.
Published: 2007

16. Copy-number variation and association studies of human disease

Author: Steven A. McCarroll and David Altshuler
Subjects: Genetics, Linkage disequilibrium, Genotype, Genetics, Medical, Gene Dosage, Genetic Diseases, Inborn, Genetic Variation, Single-nucleotide polymorphism, Disease, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Human genetics, symbols.namesake, Phenotype, Bias, Mendelian inheritance, symbols, Humans, Copy-number variation, Genotyping, Genetic association
Abstract: The central goal of human genetics is to understand the inherited basis of human variation in phenotypes, elucidating human physiology, evolution and disease. Rare mutations have been found underlying two thousand mendelian diseases; more recently, it has become possible to assess systematically the contribution of common SNPs to complex disease. The known role of copy-number alterations in sporadic genomic disorders, combined with emerging information about inherited copy-number variation, indicate the importance of systematically assessing copy-number variants (CNVs), including common copy-number polymorphisms (CNPs), in disease. Here we discuss evidence that CNVs affect phenotypes, directions for basic knowledge to support clinical study of CNVs, the challenge of genotyping CNPs in clinical cohorts, the use of SNPs as markers for CNPs and statistical challenges in testing CNVs for association with disease. Critical needs are high-resolution maps of common CNPs and techniques that accurately determine the allelic state of affected individuals.
Published: 2007

17. Transferability of tag SNPs in genetic association studies in multiple populations

Author: Jared A. Drake, Christopher A. Haiman, Noël P. Burtt, Daniel O. Stram, Robert C. Onofrio, Johannah L. Butler, Helen N. Lyon, Robert R. Graham, Xiaofeng Zhu, Laurence N. Kolonel, Matthew L. Freedman, David Altshuler, Leif Groop, Brian E. Henderson, Mark J. Daly, Todd Bersaglieri, Candace Guiducci, Roman Yelensky, Stanton Young, Kathryn L. Penney, Richard S. Cooper, Paul I.W. de Bakker, and Joel N. Hirschhorn
Subjects: Genetics, 0303 health sciences, education.field_of_study, Linkage disequilibrium, 030305 genetics & heredity, Population, Single-nucleotide polymorphism, Computational biology, Biology, 03 medical and health sciences, Genetic variation, Genotype, International HapMap Project, education, Imputation (genetics), 030304 developmental biology, Genetic association
Abstract: A general question for linkage disequilibrium-based association studies is how power to detect an association is compromised when tag SNPs are chosen from data in one population sample and then deployed in another sample. Specifically, it is important to know how well tags picked from the HapMap DNA samples capture the variation in other samples. To address this, we collected dense data uniformly across the four HapMap population samples and eleven other population samples. We picked tag SNPs using genotype data we collected in the HapMap samples and then evaluated the effective coverage of these tags in comparison to the entire set of common variants observed in the other samples. We simulated case-control association studies in the non-HapMap samples under a disease model of modest risk, and we observed little loss in power. These results demonstrate that the HapMap DNA samples can be used to select tags for genome-wide association studies in many samples around the world.
Published: 2006

18. Evaluating and improving power in whole-genome association studies using fixed marker sets

Author: Julian Maller, Paul I.W. de Bakker, Itsik Pe'er, Mark J. Daly, Roman Yelensky, and David Altshuler
Subjects: Genetic Markers, Genetics, Likelihood Functions, Linkage disequilibrium, Genome, Human, Haplotype, Single-nucleotide polymorphism, Computational biology, Tag SNP, Biology, Polymorphism, Single Nucleotide, Humans, International HapMap Project, Haplotype estimation, Genotyping, Genetic association
Abstract: Emerging technologies make it possible for the first time to genotype hundreds of thousands of SNPs simultaneously, enabling whole-genome association studies. Using empirical genotype data from the International HapMap Project, we evaluate the extent to which the sets of SNPs contained on three whole-genome genotyping arrays capture common SNPs across the genome, and we find that the majority of common SNPs are well captured by these products either directly or through linkage disequilibrium. We explore analytical strategies that use HapMap data to improve power of association studies conducted with these fixed sets of markers and show that limited inclusion of specific haplotype tests in association analysis can increase the fraction of common variants captured by 25-100%. Finally, we introduce a Bayesian approach to association analysis by weighting the likelihood of each statistical test to reflect the number of putative causal alleles to which it is correlated.
Published: 2006

19. Common deletion polymorphisms in the human genome

Author: David Altshuler, George H. Perry, Michael C. Zody, Mark J. Daly, Pardis C. Sabeti, Jeffrey C Barrett, Charles Lee, Stephanie Dallaire, Tracy N. Hadnott, Stacey Gabriel, and Steven A. McCarroll
Subjects: Genetics, Linkage disequilibrium, SNP, Single-nucleotide polymorphism, Human genome, International HapMap Project, Biology, Genome, Gene, Genetic association
Abstract: The locations and properties of common deletion variants in the human genome are largely unknown. We describe a systematic method for using dense SNP genotype data to discover deletions and its application to data from the International HapMap Consortium to characterize and catalogue segregating deletion variants across the human genome. We identified 541 deletion variants (94% novel) ranging from 1 kb to 745 kb in size; 278 of these variants were observed in multiple, unrelated individuals, 120 in the homozygous state. The coding exons of ten expressed genes were found to be commonly deleted, including multiple genes with roles in sex steroid metabolism, olfaction and drug response. These common deletion polymorphisms typically represent ancestral mutations that are in linkage disequilibrium with nearby SNPs, meaning that their association to disease can often be evaluated in the course of SNP-based whole-genome association studies.
Published: 2005

20. Demonstrating stratification in a European American population

Author: Kristin G. Ardlie, Leif Groop, Kathryn L. Lunetta, Elizabeth L. Ogburn, Matthew L. Freedman, David Altshuler, Catarina D. Campbell, Helen N. Lyon, and Joel N. Hirschhorn
Subjects: education.field_of_study, Genotype, Population, Single-nucleotide polymorphism, Biology, Population stratification, Polymorphism, Single Nucleotide, White People, Stratification (mathematics), Genetics, Population, Genetics, Humans, SNP, education, Allele frequency, Genotyping, Genetic association, Demography
Abstract: Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.
Published: 2005

21. Assessing the impact of population stratification on genetic association studies

Author: Stacey Gabriel, Laurence N. Kolonel, Matthew L. Freedman, David Altshuler, Michele T. Pato, Eric J. Topol, Andre A. Mignault, Pamela Sklar, Carlos N. Pato, Gavin J. McDonald, Brian E. Henderson, Nick Patterson, Tracey L. Petryshen, Joel N. Hirschhorn, Jordan W. Smoller, David Reich, Eric S. Lander, and Kathryn L. Penney
Subjects: Genetics, Mutation, Missense, Population genetics, Disease, Biology, Population stratification, Polymorphism, Single Nucleotide, Stratification (mathematics), Cohort Studies, Genetics, Population, Genetic marker, Case-Control Studies, Humans, Genotyping, Allele frequency, Genetic association, Demography
Abstract: Population stratification refers to differences in allele frequencies between cases and controls due to systematic differences in ancestry rather than association of genes with disease. It has been proposed that false positive associations due to stratification can be controlled by genotyping a few dozen unlinked genetic markers. To assess stratification empirically, we analyzed data from 11 case-control and case-cohort association studies. We did not detect statistically significant evidence for stratification but did observe that assessments based on a few dozen markers lack power to rule out moderate levels of stratification that could cause false positive associations in studies designed to detect modest genetic risk factors. After increasing the number of markers and samples in a case-cohort study (the design most immune to stratification), we found that stratification was in fact present. Our results suggest that modest amounts of stratification can exist even in well designed studies.
Published: 2004

22. Human genome sequence variation and the influence of gene history, mutation and recombination

Author: David Altshuler, Gil McVean, James C. Mullikin, Daniel J. Richter, John M. Higgins, Stephen F. Schaffner, Mark J. Daly, David Reich, and Eric S. Lander
Subjects: Recombination, Genetic, Genetics, Mutation rate, Linkage disequilibrium, education.field_of_study, Pan troglodytes, Genome, Human, Population, Genetic Variation, Biology, Polymorphism, Single Nucleotide, Genome, Linkage Disequilibrium, Evolution, Molecular, Mutation, Genetic variation, Mutation (genetic algorithm), Animals, Humans, Computer Simulation, Human genome, education, Sequence (medicine)
Abstract: Variation in the human genome sequence is key to understanding susceptibility to disease in modern populations and the history of ancestral populations. Unlocking this information requires knowledge of the patterns and underlying causes of human sequence diversity. By applying a new population-genetic framework to two genome-wide polymorphism surveys, we find that the human genome contains sizeable regions (stretching over tens of thousands of base pairs) that have intrinsically high and low rates of sequence variation. We show that the primary determinant of these patterns is shared genealogical history. Only a fraction of the variation (at most 25%) is due to the local mutation rate. By measuring the average distance over which genealogical histories are typically preserved, these data provide the first genome-wide estimate of the average extent of correlation among variants (linkage disequilibrium). The results are best explained by extreme variability in the recombination rate at a fine scale, and provide the first empirical evidence that such recombination 'hot spots' are a general feature of the human genome and have a principal role in shaping genetic variation in the human population.
Published: 2002

23. A novel member of the F-box/WD40 gene family, encoding dactylin, is disrupted in the mouse dactylaplasia mutant

Author: Monique S. Bulotsky, David Altshuler, Rudolf Jaenisch, Arend Sidow, Kenneth R. Johnson, Eric S. Lander, Anne W. Kerrebrock, and Bruce W. Birren
Subjects: Apical ectodermal ridge, Heterozygote, Time Factors, Positional cloning, Molecular Sequence Data, Mutant, Limb Deformities, Congenital, Biology, Homology (biology), Mesoderm, Mice, Chromosome 19, Genetics, Animals, Humans, Gene family, Tissue Distribution, Amino Acid Sequence, Gene, Progress zone, Mice, Inbred BALB C, Base Sequence, Models, Genetic, Sequence Homology, Amino Acid, F-Box Proteins, Chromosome Mapping, Proteins, Extremities, Multigene Family, Mutation
Abstract: Early outgrowth of the vertebrate embryonic limb requires signalling by the apical ectodermal ridge (AER) to the progress zone (PZ), which in response proliferates and lays down the pattern of the presumptive limb in a proximal to distal progression1. Signals from the PZ maintain the AER until the anlagen for the distal phalanges have been formed2. The semidominant mouse mutant dactylaplasia (Dac) disrupts the maintenance of the AER, leading to truncation of distal structures of the developing footplate, or autopod3,4,5. Adult Dac homozygotes thus lack hands and feet except for malformed single digits, whereas heterozygotes lack phalanges of the three middle digits. Dac resembles the human autosomal dominant split hand/foot malformation (SHFM) diseases. One of these, SHFM3, maps to chromosome 10q24 (Refs 6,7), which is syntenic to the Dac region on chromosome 19, and may disrupt the orthologue of Dac. We report here the positional cloning of Dac and show that it belongs to the F-box/WD40 gene family, which encodes adapters that target specific proteins for destruction by presenting them to the ubiquitination machinery8. In conjuction with recent biochemical studies9,10,11,12, this report demonstrates the importance of this gene family in vertebrate embryonic development.
Published: 1999

24. Guilt beyond a reasonable doubt

Author: Mark J. Daly and David Altshuler
Subjects: Cognitive science, Reasonable doubt, medicine.diagnostic_test, Genetics, medicine, Biology, Genetic architecture, Genetic testing
Abstract: Genome-wide association studies, exemplified by the Wellcome Trust Case Control Consortium and follow-up studies, have identified dozens of common variants robustly associated with common diseases, providing new clues about genetic architecture in humans. Finding all such loci, and fully defining genotype-phenotype correlation, will be a key to translating initial clues into pathophysiological understanding and clinical prediction.
Published: 2007

25. Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction

Author: Jared Maguire, Mark DePristo, Eric Banks, Leif Groop, Mark J. Daly, Robert C. Onofrio, Stacey Gabriel, Vineeta Agarwala, Brian Thomson, Anthony A. Philippakis, David Altshuler, Jessica Shea, Noël P. Burtt, Sekar Kathiresan, and Candace Guiducci
Subjects: Genetics, Genome, Human, Myocardial Infarction, Chromosome Mapping, Genetic Variation, Genome-wide association study, Single-nucleotide polymorphism, Type 2 diabetes, Biology, medicine.disease, Genome, Polymorphism, Single Nucleotide, Diabetes Mellitus, Type 2, Haplotypes, CDKN2A, Genetic variation, medicine, Humans, 1000 Genomes Project, Chromosomes, Human, Pair 9, Imputation (genetics), Genome-Wide Association Study
Abstract: Noncoding variants at human chromosome 9p21 near CDKN2A and CDKN2B are associated with type 2 diabetes, myocardial infarction, aneurysm, vertical cup disc ratio and at least five cancers. Here we compare approaches to more comprehensively assess genetic variation in the region. We carried out targeted sequencing at high coverage in 47 individuals and compared the results to pilot data from the 1000 Genomes Project. We imputed variants into type 2 diabetes and myocardial infarction cohorts directly from targeted sequencing, from a genotyped reference panel derived from sequencing and from 1000 Genomes Project low-coverage data. Polymorphisms with frequency >5% were captured well by all strategies. Imputation of intermediate-frequency polymorphisms required a higher density of tag SNPs in disease samples than is available on first-generation genome-wide association study (GWAS) arrays. Our association analyses identified more comprehensive sets of variants showing equivalent statistical association with type 2 diabetes or myocardial infarction, but did not identify stronger associations than the original GWAS signals.
Published: 2011

26. High-throughput, pooled sequencing identifies mutations in NUBPL and FOXRED1 in human complex I deficiency

Author: Vamsi K. Mootha, Michelle C Redman, Olga Goldberger, Damien L. Bruno, Sarah E. Calvo, Candace Guiducci, Manuel A. Rivas, Esko Wiltshire, Elena J. Tucker, Noël P. Burtt, David R. Thorburn, David Altshuler, Callum Wilson, Mark J. Daly, Gabriel Crawford, Alison G. Compton, Stacey Gabriel, and Denise M. Kirby
Subjects: Candidate gene, Nuclear gene, Mitochondrial Diseases, Sequence analysis, Blotting, Western, Gene Dosage, Biology, medicine.disease_cause, Deep sequencing, Article, Mitochondrial Proteins, 03 medical and health sciences, 0302 clinical medicine, Genetics, medicine, Humans, RNA, Messenger, Exome sequencing, Genetic Association Studies, 030304 developmental biology, 0303 health sciences, Mutation, Electron Transport Complex I, Reverse Transcriptase Polymerase Chain Reaction, Sequence Analysis, DNA, 3. Good health, Complementation, Mitochondrial respiratory chain, Case-Control Studies, 030217 neurology & neurosurgery
Abstract: Discovering the molecular basis of mitochondrial respiratory chain disease is challenging given the large number of both mitochondrial and nuclear genes that are involved. We report a strategy of focused candidate gene prediction, high-throughput sequencing and experimental validation to uncover the molecular basis of mitochondrial complex I disorders. We created seven pools of DNA from a cohort of 103 cases and 42 healthy controls and then performed deep sequencing of 103 candidate genes to identify 151 rare variants that were predicted to affect protein function. We established genetic diagnoses in 13 of 60 previously unsolved cases using confirmatory experiments, including cDNA complementation to show that mutations in NUBPL and FOXRED1 can cause complex I deficiency. Our study illustrates how large-scale sequencing, coupled with functional prediction and experimental validation, can be used to identify causal mutations in individual cases.
Published: 2010

27. Guilt by association

Author: Mark J. Daly, David Altshuler, and Leonid Kruglyak
Subjects: Genetics, Positional cloning, Genotype, medicine, Locus (genetics), Type 2 diabetes, Causation, Biology, medicine.disease, Guilt by association, Phenotype, Gene
Abstract: Positional cloning of common disease genes is a central but elusive goal of human geneticists. Progress is now reported by Bell and colleagues in their study of NIDDM1, a locus implicated in type 2 diabetes. The complex nature of the reported association illustrates the challenge of implicating a specific gene and mutation in the causation of polygenic disease.
Published: 2000

28. De novo copy number variants identify new genes and loci in isolated sporadic tetralogy of Fallot

Author: Michael E. Weinblatt, Maria A. Artunduaga, Steven C. Greenway, Steven R. DePalma, Philip L. De Jager, Robert M. Plenge, Jonathan G. Seidman, Roger E. Breitbart, Sonia M Mesquita, Maria de Lourdes Quintanilla-Dieck, Joshua M. Korn, Joshua M. Gorham, Roland D. Eavey, Jessie H. Conta, Christine E. Seidman, Steven A. McCarroll, Alexandre C. Pereira, Stacey Gabriel, David A. Hafler, Jennifer C Lin, Nancy A. Shadick, Samuel J Israel, David Altshuler, and Emel Ergul
Subjects: JAG1, congenital, hereditary, and neonatal diseases and abnormalities, endocrine system diseases, Heart malformation, Heart Ventricles, Gene Dosage, Locus (genetics), Biology, Gene dosage, Article, Genetic variation, mental disorders, Genetics, medicine, Humans, Copy-number variation, Tetralogy of Fallot, Chromosome, Genetic Variation, medicine.disease, Phenotype, Gene Expression Regulation, Chromosomes, Human, Pair 1, Child, Preschool, Chromosomes, Human, Pair 3
Abstract: Tetralogy of Fallot (TOF), the most common severe congenital heart malformation, occurs sporadically, without other anomaly, and from unknown cause in 70% of cases. Through a genome-wide survey of 114 subjects with TOF and their unaffected parents, we identified 11 de novo copy number variants (CNVs) that were absent or extremely rare (
Published: 2009

29. Deletion polymorphism upstream of IRGM associated with altered IRGM expression and Crohn's disease

Author: Philippe Goyette, Alan Huett, Steven R. Brant, Mark J. Daly, Steven A. McCarroll, Petric Kuballa, Aimee Landry, Kent D. Taylor, Judy H. Cho, Richard H. Duerr, Michael C. Zody, John D. Rioux, David Altshuler, Mark S. Silverberg, Ramnik J. Xavier, Jennifer L. Hall, and Shannon D Chilewski
Subjects: Genetics, Regulation of gene expression, Linkage disequilibrium, education.field_of_study, Haplotype, Population, Genome-wide association study, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, Cell Line, Crohn Disease, Gene Expression Regulation, GTP-Binding Proteins, Immunology, IRGM, Autophagy, Humans, Genetic Predisposition to Disease, education, Genetic association, Genome-Wide Association Study, Sequence Deletion
Abstract: Following recent success in genome-wide association studies, a critical focus of human genetics is to understand how genetic variation at implicated loci influences cellular and disease processes. Crohn’s disease (CD) is associated with SNPs around IRGM1,2, but coding-sequence variation has been excluded as a source of this association2. We identified a common, 20-kb deletion polymorphism, immediately upstream of IRGM and in perfect linkage disequilibrium (r2 = 1.0) with the most strongly CD-associated SNP, that causes IRGM to segregate in the population with two distinct upstream sequences. The deletion (CD risk) and reference (CD protective) haplotypes of IRGM showed distinct expression patterns. Manipulation of IRGM expression levels modulated cellular autophagy of internalized bacteria, a process implicated in CD. These results suggest that the CD association at IRGM arises from an alteration in IRGM regulation that affects the efficacy of autophagy and identify a common deletion polymorphism as a likely causal variant.
Published: 2009

30. Genetic variants near TNFAIP3 on 6q23 are associated with systemic lupus erythematosus

Author: Noël P. Burtt, Timothy W. Behrens, Patrick M. Gaffney, Rachel Hackett, Leela Davies, David Altshuler, Melissa Parkin, Deborah S. Cunninghame Graham, Andrew Wong, Robert M. Plenge, Chris Cotsapas, Joan E. Wither, Paul R. Fortin, Casey Gates, Timothy J. Vyse, Candace Guiducci, Mark J. Daly, John D. Rioux, Kathy L. Moser, Robert R. Graham, Christopher J. Lessard, and Joanlise M. Leon
Subjects: Systemic disease, Arthritis, Genome-wide association study, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Article, Arthritis, Rheumatoid, immune system diseases, Immunopathology, Genetics, medicine, Humans, Lupus Erythematosus, Systemic, Genetic Predisposition to Disease, skin and connective tissue diseases, Tumor Necrosis Factor alpha-Induced Protein 3, Autoimmune disease, Lupus erythematosus, Intracellular Signaling Peptides and Proteins, Nuclear Proteins, medicine.disease, Connective tissue disease, DNA-Binding Proteins, Rheumatoid arthritis, Immunology, Chromosomes, Human, Pair 6, Genome-Wide Association Study
Abstract: Systemic lupus erythematosus (SLE) is an autoimmune disease influenced by genetic and environmental factors. We carried out a genome-wide association scan and replication study and found an association between SLE and a variant in TNFAIP3 (rs5029939, meta-analysis P = 2.89 x 10(-12), OR = 2.29). We also found evidence of two independent signals near TNFAIP3 associated with SLE, including one previously associated with rheumatoid arthritis (RA). These results establish that variants near TNFAIP3 contribute to differential risk of SLE and RA.
Published: 2009

31. Multiple regions within 8q24 independently affect risk for prostate cancer

Author: Arti Tandon, Sue A. Ingles, Nick Patterson, Brian E. Henderson, Matthew L. Freedman, Alicja Waliszewska, David Altshuler, Laurence N. Kolonel, David Reich, Gavin J. McDonald, Julie Neubauer, Melissa A. Frasco, Loreall Pooler, Kristin G. Ardlie, Steven C. Greenway, Ingrid Oakley-Girvan, Loic Le Marchand, Simon Myers, Christine Schirmer, Malcolm C. Pike, Daniel O. Stram, Esther M. John, Alice S. Whittemore, Kathleen A. Cooney, Christopher A. Haiman, and David T.W. Wong
Subjects: Male, Genotype, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, White People, Prostate cancer, Polymorphism (computer science), Risk Factors, Genetic variation, Genetics, medicine, Ethnicity, Odds Ratio, Humans, MSMB, Genetic Predisposition to Disease, Haplotype, Cancer, Genetic Variation, Prostatic Neoplasms, Genomics, medicine.disease, United States, Black or African American, Haplotypes, Chromosomes, Human, Pair 8
Abstract: After the recent discovery that common genetic variation in 8q24 influences inherited risk of prostate cancer, we genotyped 2,973 SNPs in up to 7,518 men with and without prostate cancer from five populations. We identified seven risk variants, five of them previously undescribed, spanning 430 kb and each independently predicting risk for prostate cancer (P = 7.9 x 10(-19) for the strongest association, and P < 1.5 x 10(-4) for five of the variants, after controlling for each of the others). The variants define common genotypes that span a more than fivefold range of susceptibility to cancer in some populations. None of the prostate cancer risk variants aligns to a known gene or alters the coding sequence of an encoded protein.
Published: 2006

32. Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration

Author: David Altshuler, Sarah George, Jes Fagerness, Johanna M. Seddon, Julian Maller, Shaun Purcell, and Mark J. Daly
Subjects: Population, Locus (genetics), Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, White People, Macular Degeneration, Risk Factors, Genotype, Genetics, Humans, Allele, education, Alleles, Aged, education.field_of_study, Chi-Square Distribution, Siblings, Genetic Variation, eye diseases, United States, Ophthalmology, Logistic Models, Factor H, Case-Control Studies, Complement Factor H, Epistasis, Population study
Abstract: Age-related macular degeneration (AMD) is a common, late-onset disease with seemingly typical complexity: recurrence ratios for siblings of an affected individual are three- to sixfold higher than in the general population, and family-based analysis has resulted in only modestly significant evidence for linkage. In a case-control study drawn from a US-based population of European descent, we have identified a previously unrecognized common, noncoding variant in CFH, the gene encoding complement factor H, that substantially increases the influence of this locus on AMD, and we have strongly replicated the associations of four other previously reported common alleles in three genes (P values ranging from 10(-6) to 10(-70)). Despite excellent power to detect epistasis, we observed purely additive accumulation of risk from alleles at these genes. We found no differences in association of these loci with major phenotypic categories of advanced AMD. Genotypes at these five common SNPs define a broad spectrum of interindividual disease risk and explain about half of the classical sibling risk of AMD in our study population.
Published: 2006

33. A common haplotype of interferon regulatory factor 5 (IRF5) regulates splicing and expression and is associated with increased risk of systemic lupus erythematosus

Author: Marta E. Alarcón-Riquelme, Timothy W. Behrens, Ward A. Ortmann, Sergey V. Kozyrev, Robert M. Plenge, M.V. Prasad Linga Reddy, Javier Martin, David Altshuler, Thearith Koeuth, Robert R. Graham, Jason W. Bauer, Peter K. Gregersen, Mark J. Daly, Michelle Petri, Ma Francisca González Escribano, Emily C. Baechler, and Bernardo A. Pons-Estel
Subjects: Genetics, Lupus erythematosus, Polymorphism, Genetic, Genotype, RNA Splicing, Haplotype, Molecular Sequence Data, Transmission disequilibrium test, Biology, medicine.disease, medicine.disease_cause, Autoimmunity, Cohort Studies, Exon, Haplotypes, Case-Control Studies, Immunology, Interferon Regulatory Factors, medicine, Humans, Lupus Erythematosus, Systemic, Allele, IRF5, Interferon regulatory factors
Abstract: Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by activation of the type I interferon (IFN) pathway. Here we convincingly replicate association of the IFN regulatory factor 5 (IRF5) rs2004640 T allele with SLE in four independent case-control cohorts (P = 4.4 x 10(-16)) and by family-based transmission disequilibrium test analysis (P = 0.0006). The rs2004640 T allele creates a 5' donor splice site in an alternate exon 1 of IRF5, allowing expression of several unique IRF5 isoforms. We also identify an independent cis-acting variant associated with elevated expression of IRF5 and linked to the exon 1B splice site. Haplotypes carrying the variant associated with elevated expression and lacking the exon 1B donor site do not confer risk of SLE. Thus, a common IRF5 haplotype driving elevated expression of multiple unique isoforms of IRF5 is an important genetic risk factor for SLE, establishing a causal role for type I IFN pathway genes in human autoimmunity.
Published: 2005

34. Evaluating potential for whole-genome studies in Kosrae, an isolated population in Micronesia

Author: Itsik Pe'er, Robert M. Plenge, David Altshuler, Markus Stoffel, Richard P. Lifton, Mark J. Daly, Jennifer K. Lowe, Jackie Salit, Jan L. Breslow, Michael H. Shapero, David Reich, Penelope E. Bonnen, Keith W. Jones, and Jeffrey M. Friedman
Subjects: Genetics, Linkage disequilibrium, education.field_of_study, Genome, Human, Genetics, Medical, Haplotype, Population, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, Gene Frequency, Haplotypes, Humans, Human genome, Genetic Predisposition to Disease, International HapMap Project, Haplotype estimation, education, Alleles, Genetic association, Micronesia
Abstract: Whole-genome association studies are predicted to be especially powerful in isolated populations owing to increased linkage disequilibrium (LD) and decreased allelic diversity, but this possibility has not been empirically tested 1–3 .W e compared genome-wide data on 113,240 SNPs typed on 30 trios from the Pacific island of Kosrae to the same markers typed in the 270 samples from the International HapMap Project 4,5 . The extent of LD is longer and haplotype diversity is lower in Kosrae than in the HapMap populations. More than 98% of Kosraen haplotypes are present in HapMap populations, indicating that HapMap will be useful for genetic studies on Kosrae. The long-range LD around common alleles and limited diversity result in improved efficiency in genetic studies in this population and augments the power to detect association of ‘hidden SNPs’. The use of LD-based mapping strategies makes it practical to perform whole-genome association studies without typing every common variant in the human genome 6,7 . It has been suggested that the power of such studies is increased in isolated populations, and this has been demonstrated for rare alleles 8 . However, it remains unclear whether LD among common alleles in isolated populations extends significantly farther than in other populations—far enough to have impact for studies that seek to identify alleles contributing to common complex traits 9‐11 . Thus, although LD has been observed around rare alleles (such as disease genes) in isolated populations, facilitating disease gene mapping and cloning, this finding has not been extended to the common alleles and haplotypes that are the focus of the HapMap project. Even among isolated populations, variation in demographic history has powerful consequences for LD structure around rare alleles 3,12,13 , necessitating an evaluation of each population to assess the power of an LD-based mapping strategy. Thus, with the intense worldwide effort to generate a haplotype map for the general population, it is important to establish the utility of marker sets developed using samples from the HapMap project for use in other populations. We addressed these issues using samples from the island of Kosrae, Federated States of Micronesia 14 , which was settled by a small number of Micronesian founders B2,000 years ago 15 . In the current study, we generated a genome-wide high-density dataset of B110,000 SNPs to assess the effects of Kosraen population history on genomic variation in 30 Kosraen (KOS) trios. These same SNPs have been typed in the samples used in the HapMap project (see Methods). The 30 Kosraen trios were chosen such that all trios would be five or more generations separated from each other, which represents the most distant branches of the Kosrae pedigree. Thus, the individuals in these trios allow a fuller sampling of the range of diversity on Kosrae than if we had analyzed a random set of individuals. Comparing data on the same set of markers typed in samples included in the HapMap project permits examination of the relative extent of LD and haplotype diversity in Kosrae compared with these other populations.
Published: 2005

35. Efficiency and power in genetic association studies

Author: Roman Yelensky, Paul I.W. de Bakker, Itsik Pe'er, Mark J. Daly, David Altshuler, and Stacey Gabriel
Subjects: Genetics, Genetic Markers, Models, Genetic, Haplotype, Chromosome Mapping, Computational biology, Tag SNP, Biology, Reference Standards, Polymorphism, Single Nucleotide, Statistical power, Linkage Disequilibrium, Haplotypes, Case-Control Studies, Multiple comparisons problem, Humans, Computer Simulation, Genetic Predisposition to Disease, International HapMap Project, Genotyping, Selection (genetic algorithm), Algorithms, Genetic association
Abstract: We investigated selection and analysis of tag SNPs for genome-wide association studies by specifically examining the relationship between investment in genotyping and statistical power. Do pairwise or multimarker methods maximize efficiency and power? To what extent is power compromised when tags are selected from an incomplete resource such as HapMap? We addressed these questions using genotype data from the HapMap ENCODE project, association studies simulated under a realistic disease model, and empirical correction for multiple hypothesis testing. We demonstrate a haplotype-based tagging method that uniformly outperforms single-marker tests and methods for prioritization that markedly increase tagging efficiency. Examining all observed haplotypes for association, rather than just those that are proxies for known SNPs, increases power to detect rare causal alleles, at the cost of reduced power to detect common causal alleles. Power is robust to the completeness of the reference panel from which tags are selected. These findings have implications for prioritizing tag SNPs and interpreting association studies.
Published: 2005

36. Detection of regulatory variation in mouse genes

Author: Christopher R Cowles, David Altshuler, Eric S. Lander, and Joel N. Hirschhorn
Subjects: Genetic Markers, DNA, Complementary, Biology, DNA sequencing, Mice, Genetics, Animals, Tissue Distribution, RNA, Messenger, Allele, Gene, Transcription factor, Alleles, Crosses, Genetic, Regulation of gene expression, Binding Sites, Polymorphism, Genetic, Reverse Transcriptase Polymerase Chain Reaction, Brain, Phenotype, Mice, Inbred C57BL, Gene Expression Regulation, Genetic Techniques, Genetic marker, Function (biology), Transcription Factors
Abstract: Functional polymorphism in genes can be classified as coding variation, altering the amino-acid sequence of the encoded protein, or regulatory variation, affecting the level or pattern of expression of the gene. Coding variation can be recognized directly from DNA sequence, and consequently its frequency and characteristics have been extensively described. By contrast, virtually nothing is known about the extent to which gene regulation varies in populations. Yet it is likely that regulatory variants are important in modulating gene function: alterations in gene regulation have been proposed to influence disease susceptibility and to have been the primary substrate for the evolution of species. Here, we report a systematic study to assess the extent of cis-acting regulatory variation in 69 genes across four inbred mouse strains. We find that at least four of these genes show allelic differences in expression level of 1.5-fold or greater, and that some of these differences are tissue specific. The results show that the impact of regulatory variants can be detected at a significant frequency in a genomic survey and suggest that such variation may have important consequences for organismal phenotype and evolution. The results indicate that larger-scale surveys in both mouse and human could identify a substantial number of genes with common regulatory variation.
Published: 2002

37. Quality and completeness of SNP databases

Author: Stacey Gabriel, David Altshuler, and David Reich
Subjects: Genetics, Heterozygote, Database, Sequence analysis, Genome, Human, Haplotype, Chromosome Mapping, Genetic Variation, Single-nucleotide polymorphism, Sequence Analysis, DNA, Biology, computer.software_genre, Polymorphism, Single Nucleotide, Loss of heterozygosity, Databases as Topic, Haplotypes, Polymorphism (computer science), Genetic variation, SNP, Humans, Allele, computer, Alleles
Abstract: To address the quality and completeness of single-nucleotide polymorphism (SNP) databases, we resequenced 173 kb (spanning 17 loci) in 150 chromosomes of west African and European ancestry. Over 88% of SNPs in the public (TSC and BAC overlap) and Celera databases were confirmed in independent resequencing. Approximately 45% of all human heterozygosity is attributable to SNPs already available from the two databases, and of SNPs with minor-allele frequencies >10%, more than half are represented.
Published: 2002

38. The common PPARgamma Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes

Author: Daniel Gaudet, Thomas J. Hudson, James Nemesh, Charles R. Lane, Carl G. Brewer, Tiinamaija Tuomi, Marie-Claude Vohl, Mia Klannemark, David Altshuler, Stephen F. Schaffner, Mark J. Daly, Stacey Bolk, Leif Groop, Joel N. Hirschhorn, Cecilia M. Lindgren, and Eric S. Lander
Subjects: Oncology, Adult, Blood Glucose, Male, medicine.medical_specialty, Diabetes risk, Genotype, Proline, Population, Mothers, Receptors, Cytoplasmic and Nuclear, Blood Pressure, Type 2 diabetes, Population stratification, Linkage Disequilibrium, Body Mass Index, Fathers, Risk Factors, Internal medicine, Genetics, medicine, Humans, Age of Onset, education, CDKAL1, Alleles, Aged, Family Health, education.field_of_study, Alanine, Polymorphism, Genetic, SLC30A8, biology, Models, Genetic, Odds ratio, Middle Aged, medicine.disease, Endocrinology, Cholesterol, Phenotype, Diabetes Mellitus, Type 2, biology.protein, Female, Lipoproteins, HDL, TCF7L2, Transcription Factors
Abstract: Genetic association studies are viewed as problematic and plagued by irreproducibility. Many associations have been reported for type 2 diabetes, but none have been confirmed in multiple samples and with comprehensive controls. We evaluated 16 published genetic associations to type 2 diabetes and related sub-phenotypes using a family-based design to control for population stratification, and replication samples to increase power. We were able to confirm only one association, that of the common Pro12Ala polymorphism in peroxisome proliferator-activated receptor-gamma(PPARgamma) with type 2 diabetes. By analysing over 3,000 individuals, we found a modest (1.25-fold) but significant (P=0.002) increase in diabetes risk associated with the more common proline allele (85% frequency). Moreover, our results resolve a controversy about common variation in PPARgamma. An initial study found a threefold effect, but four of five subsequent publications failed to confirm the association. All six studies are consistent with the odds ratio we describe. The data implicate inherited variation in PPARgamma in the pathogenesis of type 2 diabetes. Because the risk allele occurs at such high frequency, its modest effect translates into a large population attributable risk-influencing as much as 25% of type 2 diabetes in the general population.
Published: 2000

39. Partners in crime

Author: Mark J Daly and David Altshuler
Subjects: Genetics
Published: 2005

40. Genome-wide meta-analyses identify multiple loci associated with smoking behavior

Author: Laura M. Thornton, Cornelia M. van Duijn, Danyu Lin, Eco J. C. de Geus, Albert Hofman, Helena Furberg, Thomas Quertermous, Jed E. Rose, Henning Tiemeier, Fangyi Gu, Karen L. Mohlke, Yuri Milaneschi, Dana Mates, Brenda W.J.H. Penninx, Neonilia Szeszenia-Dabrowska, Toshiko Tanaka, Nora Franceschini, Janet Audrain-McGovern, Daniel Levy, Stephen J. Chanock, Patrick F. Sullivan, Devin Absher, Danielle Posthuma, Vladimir Bencko, Diego Ardissino, Paul M. Ridker, Joshua W. Knowles, Kristina Kjærheim, Tatiana V. Macfarlane, Jubao Duan, Peter Kraft, James McKay, Eric Boerwinkle, Heather M. Stringham, Bruce M. Psaty, David J. Hunter, Talin Haritunians, Themistocles L. Assimes, Piera Angelica Merlini, John P. A. Ioannidis, Alan R. Sanders, Anne U. Jackson, Stephen P. Fortmann, David Altshuler, Claire M. Healy, André G. Uitterlinden, Michael Boehnke, Pagona Lagiou, Susan E. Hankinson, Peter Rudnai, Antonio Agudo, Stefan Walter, Barbara McKnight, Douglas F. Levinson, Jack M. Guralnik, Claes Ladenvall, Cristina Canova, Caryn Lerman, Olle Melander, Guillaume Paré, Ray Lowry, Lorenzo Richiardi, Pablo V. Gejman, Nicole Vogelzangs, Jaakko Kaprio, Veikko Salomaa, Evan L. Thacker, Peter Almgren, Xavier Castellsagué, Jacqueline M. Vink, Timothy M. Frayling, Ramachandran S. Vasan, Lenka Foretova, Sarah R. Preis, Emelia J. Benjamin, Ariana Znaor, Francesco Mauri, Hermine H. Maes, Jaakko Tuomilehto, John R. B. Perry, David Zaridze, Dorret I. Boomsma, S. Kathiresan, Joshua C. Bis, Vladimir Janout, Curt D. Furberg, Stephen M. Schwartz, Roberto Elosua, Luisa Bernardinelli, Gavin Lucas, Jianxin Shi, Simone Benhamou, Daniel I. Chasman, Jolanta Lissowska, Johannes H. Smit, Paul Brennan, Gonneke Willemsen, Esther H. Lips, Ivana Holcatova, Shih-Jen Hwang, Yunjung Kim, Leif Groop, Luigi Ferrucci, David I. Conway, Mark Lathrop, Jennifer Dackor, Eleonora Fabianova, Christopher J. O'Donnell, Carlos Iribarren, Pier Mannuccio Mannucci, Brendan M. Everett, Luigi Barzan, Benjamin F. Voight, Stefania Bandinelli, Kent D. Taylor, Ming D. Li, Hematology, Epidemiology, Child and Adolescent Psychiatry / Psychology, Internal Medicine, Biological Psychology, Functional Genomics, Neuroscience Campus Amsterdam - Addictive Behavior, EMGO+ - Mental Health, Neuroscience Campus Amsterdam - integrative Analysis & Modeling, Psychiatry, EMGO - Mental health, NCA - Addictive Behavior, and NCA - Integrative Analysis & Modeling
Subjects: Netherlands Twin Register (NTR), Nicotine, medicine.medical_treatment, Health Behavior, Chromosome 9, Genome-wide association study, Single-nucleotide polymorphism, Biology, Receptors, Nicotinic, Article, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, Genotype, Genetics, medicine, SNP, Humans, Allele, 030304 developmental biology, Family Health, 0303 health sciences, Models, Genetic, Smoking, Chromosome Mapping, Odds ratio, Sequence Analysis, DNA, Tobacco Use Disorder, 3. Good health, Pharmacogenetics, Smoking cessation, Twin Studies as Topic, Smoking Cessation, 030217 neurology & neurosurgery
Abstract: Consistent but indirect evidence has implicated genetic factors in smoking behavior. We report meta-analyses of several smoking phenotypes within cohorts of the Tobacco and Genetics Consortium (n = 74,053). We also partnered with the European Network of Genetic and Genomic Epidemiology (ENGAGE) and Oxford-GlaxoSmithKline (Ox-GSK) consortia to follow up the 15 most significant regions (n 140,000). We identified three loci associated with number of cigarettes smoked per day. The strongest association was a synonymous 15q25 SNP in the nicotinic receptor gene CHRNA3 (rs1051730[A], Β = 1.03, standard error (s.e.) = 0.053, P = 2.8 × 10 73). Two 10q25 SNPs (rs1329650[G], Β = 0.367, s.e. = 0.059, P = 5.7 × 10 10; and rs1028936[A], Β = 0.446, s.e. = 0.074, P = 1.3 × 10 9) and one 9q13 SNP in EGLN2 (rs3733829[G], Β = 0.333, s.e. = 0.058, P = 1.0 × 10 8) also exceeded genome-wide significance for cigarettes per day. For smoking initiation, eight SNPs exceeded genome-wide significance, with the strongest association at a nonsynonymous SNP in BDNF on chromosome 11 (rs6265[C], odds ratio (OR) = 1.06, 95% confidence interval (Cl) 1.04-1.08, P = 1.8 × 10 8). One SNP located near DBH on chromosome 9 (rs3025343[G], OR = 1.12, 95% Cl 1.08-1.18, P = 3.6 × 10 8) was significantly associated with smoking cessation. © 2010 Nature America, Inc. All rights reserved.
Published: 2010

41. Erratum: Corrigendum: Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans

Author: Marju Orho-Melander, Olle Melander, Marja-Riitta Taskinen, Pekka Jousilahti, Veikko Salomaa, Christopher Newton-Cheh, Noël P. Burtt, Thomas Hedner, Dolores Corella, Leena Peltonen, David Altshuler, Leif Groop, Benjamin F. Voight, Bo Hedblad, Göran Berglund, Charlotta Roos, Björn Wahlstrand, Aarti Surti, Gregory M. Cooper, Aki S. Havulinna, Candace Guiducci, Erkki Vartiainen, Mark J. Rieder, E. Shyong Tai, Jose M. Ordovas, and Sekar Kathiresan
Subjects: chemistry.chemical_compound, medicine.medical_specialty, Very low-density lipoprotein, Endocrinology, Low-density lipoprotein receptor-related protein 8, High-density lipoprotein, chemistry, Cholesterol, Internal medicine, Genetics, medicine, Low density lipoprotein cholesterol, Biology
Published: 2008

42. Reply to 'Statistical concerns about the GSEA procedure'

Author: Leif Groop, Nick Patterson, David Altshuler, Mark J. Daly, Vamsi K. Mootha, and Joel N. Hirschhorn
Subjects: Genetics, Biology, Data science
Published: 2004

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