Journal Club
Carlsson LM, Peltonen M, Ahlin S, Anveden Å, Bouchard C, Carlsson B,
Jacobson P, Lönroth H, Maglio C, Näslund I, Pirazzi C, Romeo S, Sjöholm K,
Sjöström E, Wedel H, Svensson PA, Sjöström L.
Bariatric surgery and prevention of type 2 diabetes in Swedish obese subjects.
N Engl J Med. 2012 Aug 23;367(8):695-704.
DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
Large-scale association analysis provides insights into the genetic architecture
and pathophysiology of type 2 diabetes.
Nat Genet. 2012 Aug 12;44(9):981-990. doi: 10.1038/ng.2383. Epub 2012 Aug 12.
2012年9月6日 8:30-8:55
８階 医局
埼玉医科大学 総合医療センター 内分泌・糖尿病内科
Department of Endocrinology and Diabetes,
Saitama Medical Center, Saitama Medical University
松田 昌文
Matsuda, Masafumi
Bariatric Surgery versus
Conventional Medical Therapy for
Type 2 Diabetes.
2012年4月5日
n=20
n=20
n=20
Italy
N Engl J Med. 2012 Apr 26;366(17):1577-85.
2012年2月2日
Bariatric surgery and long-term cardiovascular events
University of Michigan
JAMA. 2012;307(1):56-65
2010年8月19日 Hospital complication rates with bariatric surgery in Michigan.
University of Michigan
JAMA. 2010;304(4):435-442
2009年８月６日
Perioperative safety in the longitudinal
assessment of bariatric surgery.
University of Washington
N Engl J Med. 2009 Jul 30;361(5):445-54.
the Institutes of Medicine (L.M.S.C., M.P., S.A., A.A., B.C., P.J., C.M., C.P., S.R., K.S.,
E.S., P.-A.S., L.S.) and Surgery (H.L.), Sahlgrenska Academy at the University of
Gothenburg, and the Nordic School of Public Health (H.W.), Gothenburg, and the
Department of Surgery, University Hospital, Orebro (I.N.) — all in Sweden; the
Department of Chronic Disease Prevention, National Institute for Health and Welfare,
Helsinki (M.P.); and Pennington Biomedical Research Center, Louisiana State University
System, Baton Rouge (C.B.).
N Engl J Med 2012;367:695-704.
Adjustable gastric banding
Biliopancreatic diversion
Roux-en-Y gastric bypass
Sleeve gastrectomy
Vertical banded gastroplasty
with duodenal switch
A meta-analysis from University of California, Los Angeles reports the
following weight loss at 36 months
Biliopancreatic diversion - 53 kg
Roux-en-Y gastric bypass (RYGB) - 41 kg
Open - 42 kg
Laparoscopic - 38 kg
Adjustable gastric banding - 35 kg
Vertical banded gastroplasty - 32 kg
Sleeve gastrectomy ?
BACKGROUND
Weight loss protects against type 2
diabetes but is hard to maintain with
behavioral modification alone. In an
analysis of data from a nonrandomized,
prospective, controlled study, we
examined the effects of bariatric
surgery on the prevention of type 2
diabetes.
METHODS
In this analysis, we included 1658 patients who underwent bariatric
surgery and 1771 obese matched controls (with matching performed on
a group, rather than individual, level). None of the participants had
diabetes at baseline. Patients in the bariatric-surgery cohort underwent
banding (19%), vertical banded gastroplasty (69%), or gastric bypass
(12%); nonrandomized, matched, prospective controls received usual
care. Participants were 37 to 60 years of age, and the body-mass index
(BMI; the weight in kilograms divided by the square of the height in
meters) was 34 or more in men and 38 or more in women. This analysis
focused on the rate of incident type 2 diabetes, which was a
prespecified secondary end point in the main study. At the time of this
analysis (January 1, 2012), participants had been followed for up to 15
years. Despite matching, some baseline characteristics differed
significantly between the groups; the baseline body weight was higher
and risk factors were more pronounced in the bariatric-surgery group
than in the control group. At 15 years, 36.2% of the original participants
had dropped out of the study, and 30.9% had not yet reached the time
for their 15-year follow-up examination.
Figure 1. Cumulative Incidence of Type 2 Diabetes.
Panel A shows the Kaplan–Meier unadjusted estimates of the cumulative incidence of
type 2 diabetes in the bariatric-surgery group and the control group. The light shading
represents the 95% confidence interval. The adjusted hazard ratio with bariatric surgery
was 0.17 (95% confidence interval, 0.13 to 0.21).
Figure 1. Cumulative Incidence of Type 2 Diabetes.
Panel B shows the Kaplan–Meier unadjusted estimates of the incidence of type 2
diabetes in subgroups defined in the control group according to receipt or no receipt of
professional guidance to lose weight and in the surgery group according to the method
of bariatric surgery: gastric banding, vertical banded gastroplasty (VBG), or gastric
bypass (GBP).
RESULTS
During the follow-up period, type 2 diabetes developed
in 392 participants in the control group and in 110 in the
bariatric-surgery group, corresponding to incidence rates
of 28.4 cases per 1000 person-years and 6.8 cases per
1000 person-years, respectively (adjusted hazard ratio
with bariatric surgery, 0.17; 95% confidence interval,
0.13 to 0.21; P<0.001). The effect of bariatric surgery
was influenced by the presence or absence of impaired
fasting glucose (P = 0.002 for the interaction) but not by
BMI (P = 0.54). Sensitivity analyses, including end-point
imputations, did not change the overall conclusions. The
postoperative mortality was 0.2%, and 2.8% of patients
who underwent bariatric surgery required reoperation
within 90 days owing to complications.
CONCLUSIONS
Bariatric surgery appears to be
markedly more efficient than usual care
in the prevention of type 2 diabetes in
obese persons.
(Funded by the Swedish Research Council and others;
ClinicalTrials.gov number, NCT01479452.)
Bariatric Surgery — From Treatment of Disease to Prevention?
Danny O. Jacobs, M.D., M.P.H.
n engl j med 367;8 nejm.764 org august 23, 2012
The current study should provide an impetus
to develop a more complete understanding
of the mechanisms by which the various
bariatric procedures exert their beneficial
effects. Such understanding will be important
because it will enable the identification of the
persons who are the most appropriate
candidates for surgery.
Message
体格指数（BMI）が男性34以上、女性38以上の肥
満患者3429人を対象に、胃バンディング術、胃
バイパス術など肥満手術の2型糖尿病予防効果を
非無作為化前向き対照試験で評価。15年の追跡
調査の結果、糖尿病発症率は手術群で1000人年
当たり6.8人、通常ケアを受けた対照群で28.4人
だった（調整ハザード比0.17）。
Laparoscopic Roux en Y Gastric Bypass: LRYGB
Dr. Kasama
減量手術
245件
（内訳）
腹腔鏡下胃バイパス手
術
143件
腹腔鏡下袖状胃切除術
58件
ラップバンド手術
17件
腹腔鏡下BPD/DS
27件
Laparoscopic Gastric Banding
Before
After
その他
胃内バルーン挿入術
BIB
7件
Message
１．肥満度の指標であるBMI（＝体重kg÷身長mの２
乗）が32以上で、糖尿病またはそれ以外の2つ合
併症をもつ方（身長160cmで82kg以上）
２．BMIが37以上の方（身長160cmで95kg以上）
※ 上記の適応を満たす方で、内科的治療が効果がな
かった方
楽をしてやせるための手術ではなく、患者様の命を守
るための手術であることを十分に理解することです
■四谷メディカルキューブ
減量外科 笠間和典先生
http://wwwmcube.jp/
〒102-0084 東京都千代田区二番町7番7
T2DM Candidate Polymorphisms
• IGF2BP2 インスリンの作用を調整していると考えられているイン
スリン様成長因子2に関係する
• CDKAL1 β細胞に作用するタンパク質
• CDKN2AとCDKN2B β 細胞の成長に関与するタンパク質、ガンの
成長でも研究されていた遺伝子
• TCF7L2 β細胞の機能障害 インクレチンシグナル障害
• SCL30A8 β細胞だけで発現する亜鉛輸送体遺伝子
• KCNJ11 新生児糖尿病に関与
• HHEX
• PPARα 脂肪酸化障害
• PPARγ
• FTO 肥満
• GCKR 中性脂肪を調節
• WFS1 インクレチンシグナル障害
• SLC30A8
• KCNQ1
• KCNJ15
• UBE2E2
• C2CD4A-C2CD4B
2010年9月9日
Nat Genet. 2010
Oct;42(10):864-8.
2010年9月9日
SNP Single Nucleotide Polymorphism
Chr., chromosome
RAF, risk allele frequency
OR, odds ratio
Nat Genet. 2010
Oct;42(10):864-8.
2010年12月16日
McCarthy MI.: Genomics,
type 2 diabetes, and obesity.
N Engl J Med. 2010 Dec
9;363(24):2339-50.
2010年12月16日
McCarthy MI.: Genomics, type 2 diabetes, and obesity. N Engl J Med.
2010 Dec 9;363(24):2339-50.
血糖レベルに関する形質と2型糖尿病に関連する遺伝的多様体
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
Broad Institute of Harvard and Massachusetts Institute of Technology (MIT),
Cambridge, Massachusetts, USA.
Nat Genet. 2012 Aug 12;44(9):981-990.
Wellcome Trust Centre for Human Genetics, Univ. of Oxford, Oxford, UK. Andrew P Morris, Teresa Ferreira, Anubha Mahajan, Inga Prokopenko, Ashish Kumar, Vasiliki Lagou, Cecilia M Lindgren, N William Rayner, Steven Wiltshire, Antigone S
Dimas, John R B Perry, Neil Robertson, Ghazala Mirza, Joseph Trakalo, Peter J Donnelly & Mark I McCarthy Broad Institute of Harvard and Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA. Benjamin F Voight, Ayellet V
Segrè, Elizabeth J Rossin, Soumya Raychaudhuri, Pierre Fontanillas, Noël Burtt, Jason Carey, Andrew T Crenshaw, George B Grant, Candace Guiducci, Melissa Parkin, Wendy Winckler, Sekar Kathiresan & David Altshuler Department of
Pharmacology, Univ. of Pennsylvania–Perelman School of Medicine, Philadelphia, Pennsylvania, USA. Benjamin F Voight Department of Biostatistics, Univ. of Michigan, Ann Arbor, Michigan, USA. Tanya M Teslovich, Hyun Min Kang, Laura J Scott,
Heather M Stringham, Anne U Jackson, Goncalo R Abecasis & Michael Boehnke Center for Human Genetic Research, Massachusetts General Hosp., Boston, Massachusetts, USA. Ayellet V Segrè, Elizabeth J Rossin, Jose C Florez, Sekar
Kathiresan & David Altshuler Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA. Ayellet V Segrè, Jose C Florez, James B Meigs & David Altshuler deCODE Genetics, Reykjavik, Iceland. Valgerdur Steinthorsdottir,
Augustine Kong, Gudmar Thorleifsson, Unnur Thorsteinsdottir & Kari Stefansson Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden. Rona J Strawbridge, Karl Gertow, Bengt Sennblad, Angela
Silveira & Anders Hamsten Center for Molecular Medicine, Karolinska Univ. Hosp. Solna, Stockholm, Sweden. Rona J Strawbridge, Karl Gertow, Bengt Sennblad, Angela Silveira & Anders Hamsten Department of Public Health and Primary Care,
Univ. of Cambridge, Cambridge, UK. Hassan Khan, Kay-Tee Khaw, Danish Saleheen & John Danesh Research Unit of Molecular Epidemiology, Helmholtz Zentrum Muenchen, Neuherberg, Germany. Harald Grallert, Norman Klopp & Thomas Illig
Oxford Centre for Diabetes, Endocrinology and Metabolism, Univ. of Oxford, Oxford, UK. Inga Prokopenko, N William Rayner, Neil Robertson, Christopher J Groves, Katharine R Owen & Mark I McCarthy Institut National de la Santé et de la
Recherche Médicale (INSERM) Unité Mixte de Recherche (UMR) 1087, Nantes, France. Christian Dina Centre National de la Recherche Scientifique (CNRS) UMR 6291, Nantes, France. Christian Dina Department of Biology, Medicine and Health,
Nantes Univ., Nantes, France. Christian Dina Estonian Genome Center, Univ. of Tartu, Tartu, Estonia. Tonu Esko, Krista Fischer, Kaarel Krjutškov & Andres Metspalu Institute of Molecular and Cell Biology, Univ. of Tartu, Tartu, Estonia. Tonu Esko &
Andres Metspalu Centre for Population Health Sciences, Univ. of Edinburgh, Edinburgh, UK. Ross M Fraser, Harry Campbell, Jackie F Price & James F Wilson Wellcome Trust Sanger Institute, Hinxton, Cambridge, UK. Stavroula Kanoni, Sarah E
Hunt, Simon Potter, Kathleen Stirrups, Sarah Edkins, Cordelia Langford, Eleftheria Zeggini, Ines Barroso, Samuli Ripatti & Panos Deloukas Medical Research Council (MRC) Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hosp.,
Cambridge, UK. Claudia Langenberg, Jian'an Luan, Ruth J F Loos, Nita G Forouhi & Nicholas J Wareham Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany. Martina Müller-Nurasyid
Institute of Genetic Epidemiology, Helmholtz Zentrum Muenchen, Neuherberg, Germany. Martina Müller-Nurasyid, Julia Meyer & Christian Gieger Department of Medicine I, Univ. Hosp. Grosshadern, Ludwig-Maximilians-Universität, Munich,
Germany. Martina Müller-Nurasyid Institute for Medical Informatics, Biometry and Epidemiology, Univ. Hosp. of Essen, Univ. Duisburg-Essen, Essen, Germany. Sonali Pechlivanis, Karl-Heinz Jöckel & Susanne Moebus CNRS UMR 8199, Institute of
Biology and Lille 2 Univ., Pasteur Institute, Lille, France. Loic Yengo, Elodie Eury, Stéphane Lobbens, Stephane Cauchi & Philippe Froguel Laboratory of Mathematics, CNRS UMR 8524, Univ. Lille 1, Model for Data Analysis and Learning (MODAL)
Team, Institut National de Recherche en Informatique et en Automatique (INRIA) Lille Nord-Europe, Lille, France. Loic Yengo Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland. Leena Kinnunen & Jaakko Tuomilehto
Health Science and Technology MD Program, Harvard Univ. and Massachusetts Institute of Technology, Boston, Massachusetts, USA. Elizabeth J Rossin Harvard Biological and Biomedical Sciences Program, Harvard Univ., Boston, Massachusetts,
USA. Elizabeth J Rossin Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hosp., Harvard Medical School, Boston, Massachusetts, USA. Soumya Raychaudhuri Partners Center for Personalized Genomic Medicine, Boston,
Massachusetts, USA. Soumya Raychaudhuri National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts, USA. Andrew D Johnson, Caroline Fox & Josée Dupuis Department of Genetic Medicine and
Development, Univ. of Geneva Medical School, Geneva, Switzerland. Antigone S Dimas Biomedical Sciences Research Center Al Fleming, Vari, Greece. Antigone S Dimas Charles R Bronfman Institute for Personalized Medicine, Mount Sinai School
of Medicine, New York, New York, USA. Ruth J F Loos Child Health and Development Institute, Mount Sinai School of Medicine, New York, New York, USA. Ruth J F Loos Department of Preventive Medicine, Mount Sinai School of Medicine, New York,
New York, USA. Ruth J F Loos Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, USA. Sailaja Vedantam & Jose C Florez Division of Genetics and Endocrinology, Children's Hosp., Boston,
Massachusetts, USA. Sailaja Vedantam Department of Biostatistics, Boston Univ. School of Public Health, Boston, Massachusetts, USA. Han Chen, Ching-Ti Liu & Josée Dupuis Diabetes Research Center, Diabetes Unit, Massachusetts General
Hosp., Boston, Massachusetts, USA. Jose C Florez Division of Endocrinology and Metabolism, Brigham and Women's Hosp. and Harvard Medical School, Boston, Massachusetts, USA. Caroline Fox Boston Univ. Data Coordinating Center, Boston,
Massachusetts, USA. Denis Rybin Collaborative Studies Coordinating Center, Department of Biostatistics, Univ. of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. David J Couper Department of Epidemiology, Johns Hopkins
Bloomberg School of Public Health, Baltimore, Maryland, USA. Wen Hong L Kao & Man Li Department of Nutrition and Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. Marilyn C Cornelis, Peter Kraft, Qi Sun, Rob M van
Dam, David J Hunter, Lu Qi & Frank Hu Program in Molecular and Genetic Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA. Peter Kraft & David J Hunter Channing Laboratory, Department of Medicine, Brigham and
Women's Hosp. and Harvard Medical School, Boston, Massachusetts, USA. Qi Sun, David J Hunter, Lu Qi & Frank Hu Saw Swee Hock School of Public Health, National Univ. of Singapore, Singapore. Rob M van Dam National Human Genome
Research Institute, US National Institutes of Health, Bethesda, Maryland, USA. Peter S Chines, Lori L Bonnycastle & Francis S Collins Nord-Trondelag Health Study (HUNT) Research Centre, Department of Public Health and General Practice,
Norwegian Univ. of Science and Technology, Levanger, Norway. Oddgeir L Holmen, Carl G P Platou & Kristian Hveem Centre for Genetic Epidemiology and Biostatistics, The Univ. of Western Australia, Nedlands, Western Australia, Australia. Robert
Lawrence Genetics of Complex Traits, Institute of Biomedical and Clinical Science, Peninsula Medical School, Univ. of Exeter, Exeter, UK. John R B Perry, Andrew R Wood & Timothy M Frayling Department of Internal Medicine, Levanger Hosp.,
Nord-Trøndelag Health Trust, Levanger, Norway. Carl G P Platou Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Emil Rehnberg, Nancy L Pedersen & Erik Ingelsson Department of Vascular
Medicine, Academic Medical Center, Univ. of Amsterdam, Amsterdam, The Netherlands. Suthesh Sivapalaratnam, Mieke D Trip & Kees Hovingh Department of Medicine, Univ. of Eastern Finland and Kuopio Univ. Hosp., Kuopio, Finland. Alena
Stančáková, Markku Laakso & Johanna Kuusisto Institute for Molecular Medicine Finland (FIMM), Helsinki, Finland. Emmi Tikkanen & Samuli Ripatti Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki,
Finland. Emmi Tikkanen, Satu Männistö, Johan G Eriksson, Samuli Ripatti & Veikko Salomaa Department of Clinical Science Malmö, Lund Univ. Diabetes Centre, Scania Univ. Hosp., Lund Univ., Malmö, Sweden. Peter Almgren, Mozhgan Dorkhan,
Anna Jonsson, Jasmina Kravic, Eero Lindholm, Valeriya Lyssenko, Olle Melander, Peter M Nilsson & Leif C Groop Institute of Biomedicine, Physiology, Univ. of Eastern Finland, Kuopio, Finland. Mustafa Atalay & Timo A Lakka Faculty of Medicine,
Univ. of Iceland, Reykjavík, Iceland. Rafn Benediktsson, Unnur Thorsteinsdottir & Kari Stefansson Department of Endocrinology and Metabolism, Landspitali Univ. Hosp., Reykjavík, Iceland. Rafn Benediktsson, Astradur B Hreidarsson & Gunnar
Sigurðsson Endocrinology-Diabetology Unit, Corbeil-Essonnes Hosp., Corbeil-Essonnes, France. Guillaume Charpentier Diabetes Research Centre, Biomedical Research Institute, Univ. of Dundee, Ninewells Hosp., Dundee, UK. Alex S F Doney,
Colin N A Palmer & Andrew D Morris Pharmacogenomics Centre, Biomedical Research Institute, Univ. of Dundee, Ninewells Hosp., Dundee, UK. Alex S F Doney, Colin N A Palmer & Andrew D Morris Icelandic Heart Association, Kopavogur, Iceland.
Valur Emilsson & Gunnar Sigurðsson Department of General Practice and Primary Health Care, Univ. of Helsinki, Helsinki, Finland. Tom Forsen & Johan G Eriksson Vaasa Health Care Centre, Vaasa, Finland. Tom Forsen Division of Cardiovascular
Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden. Bruna Gigante, Karin Leander & Ulf de Faire Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich
Heine Univ. Düsseldorf, Düsseldorf, Germany. Christian Herder & Michael Roden Busselton Population Medical Research Institute, Sir Charles Gairdner Hosp., Nedlands, Western Australia, Australia. Jennie Hui, Alan James, Bill Musk & John Beilby
PathWest Laboratory Medicine of Western Australia, Queen Elizabeth II Medical Centre, Nedlands, Western Australia, Australia. Jennie Hui & John Beilby School of Pathology and Laboratory Medicine, The Univ. of Western Australia, Nedlands,
Western Australia, Australia. Jennie Hui & John Beilby School of Population Health, The Univ. of Western Australia, Nedlands, Western Australia, Australia. Jennie Hui & Bill Musk Department of Pulmonary Physiology and Sleep Medicine, West
Australian Sleep Disorders Research Institute, Queen Elizabeth II Medical Centre, Nedlands, Western Australia, Australia. Alan James School of Medicine and Pharmacology, Univ. of Western Australia, Nedlands, Western Australia, Australia. Alan
James & Bill Musk Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine Univ. Düsseldorf, Düsseldorf, Germany. Wolfgang Rathmann Institute of Human Genetics, Univ. of Bonn,
Bonn, Germany. Thomas W Mühleisen & Markus M Nöthen Department of Genomics, Life & Brain Center, Univ. of Bonn, Bonn, Germany. Thomas W Mühleisen & Markus M Nöthen Respiratory Medicine, Sir Charles Gairdner Hosp., Nedlands,
Western Australia, Australia. Bill Musk Department of Cardiology, Univ. General Hosp. Attikon, Athens, Greece. Loukianos Rallidis South Karelia Central Hosp., Lappeenranta, Finland. Jouko Saramies Department of Genetics, Evolution and
Environment, Univ. College London (UCL) Genetics Institute, Univ. College London, London, UK. Sonia Shah & Delilah Zabaneh Department of Clinical Chemistry and Central Laboratory, Univ. of Ulm, Ulm, Germany. Gerald Steinbach & Roman
Wennauer Institute of Epidemiology II, Helmholtz Zentrum Muenchen, Neuherberg, Germany. Barbara Thorand & Annette Peters Centro Cardiologico Monzino, IRCCS, Milan, Italy. Fabrizio Veglia, Damiano Baldassarre & Elena Tremoli MRC Institute
of Genetics and Molecular Medicine at the Univ. of Edinburgh, Western General Hosp., Edinburgh, UK. Harry Campbell & James F Wilson Department of Epidemiology, Erasmus Univ. Medical Center, Rotterdam, The Netherlands. Cornelia van Duijn,
Andre G Uitterlinden & Albert Hofman Netherland Genomics Initiative, Netherlands Consortium for Healthy Ageing and Centre for Medical Systems Biology, Rotterdam, The Netherlands. Cornelia van Duijn & Andre G Uitterlinden Department of
Internal Medicine, Erasmus Univ. Medical Center, Rotterdam, The Netherlands. Andre G Uitterlinden & Eric Sijbrands Oxford National Institute for Health Research Biomedical Research Centre, Churchill Hosp., Oxford, UK. Katharine R Owen & Mark
I McCarthy Molecular Medicine, Department of Medical Sciences, Uppsala Univ., Uppsala, Sweden. Ann-Christine Syvänen Unit of General Practice, Helsinki Univ. General Hosp., Helsinki, Finland. Johan G Eriksson Folkhälsan Research Center,
Helsinki, Finland. Johan G Eriksson, Tiinamaija Tuomi & Bo Isomaa INSERM CESP U1018, Villejuif, France. Beverley Balkau Univ. Paris Sud 11, UMRS 1018, Villejuif, France. Beverley Balkau Department of Medicine, Helsinki Univ. Hosp., Univ. of
Helsinki, Helsinki, Finland. Tiinamaija Tuomi Department of Social Services and Health Care, Jakobstad, Finland. Bo Isomaa Division of Endocrinology, Diabetes and Nutrition, Univ. of Maryland School of Medicine, Baltimore, Maryland, USA. Alan R
Shuldiner Geriatric Research Education and Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore, Maryland, USA. Alan R Shuldiner Program in Personalized and Genomic Medicine, Univ. of Maryland School of Medicine,
Baltimore, Maryland, USA. Alan R Shuldiner Department of Medicine/Metabolic Diseases, Heinrich Heine Univ. Düsseldorf, Düsseldorf, Germany. Michael Roden Univ. of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science,
Addenbrooke's Hosp., Cambridge, UK. Ines Barroso National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre, Institute of Metabolic Science, Addenbrooke's Hosp., Cambridge, UK. Ines Barroso Department of
Community Medicine, Faculty of Health Sciences, Univ. of Tromsø, Tromsø, Norway. Tom Wilsgaard & Inger Njølstad Kuopio Research Institute of Exercise Medicine, Kuopio, Finland. Rainer Rauramaa & Timo A Lakka Department of Clinical
Physiology and Nuclear Medicine, Kuopio Univ. Hosp., Kuopio, Finland. Rainer Rauramaa Department of Medical Sciences, Uppsala Univ., Akademiska Sjukhuset, Uppsala, Sweden. Lars Lind Department of Dietetics-Nutrition, Harokopio Univ.,
Athens, Greece. George Dedoussis Faculty of Medicine, Institute of Health Sciences, Univ. of Oulu, Oulu, Finland. Sirkka M Keinanen-Kiukaanniemi Unit of General Practice, Oulu Univ. Hosp., Oulu, Finland. Sirkka M Keinanen-Kiukaanniemi Finnish
Diabetes Association, Tampere, Finland. Timo E Saaristo Pirkanmaa Hosp. District, Tampere, Finland. Timo E Saaristo Department of Internal Medicine, South Ostrobothnia Central Hosp., Seinäjoki, Finland. Eeva Korpi-Hyövälti & Jaakko Tuomilehto
Department of Medicine, Central Finland Central Hosp., Jyväskylä, Finland. Juha Saltevo Department of Genetics, Univ. of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. Karen L Mohlke Diabetes and Obesity Research Institute,
Cedars-Sinai Medical Center, Los Angeles, California, USA. Richard N Bergman Red RECAVA Grupo RD06/0014/0015, Hosp. Universitario La Paz, Madrid, Spain. Jaakko Tuomilehto Centre for Vascular Prevention, Danube-Univ. Krems, Krems,
Austria. Jaakko Tuomilehto Division of Endocrinology and Diabetes, Department of Internal Medicine, Univ. Medical Centre Ulm, Ulm, Germany. Bernhard O Boehm Genomic Medicine, Imperial College London, Hammersmith Hosp., London, UK.
Philippe Froguel Department of Pharmacological Sciences, Univ. of Milan, Milan, Italy. Damiano Baldassarre & Elena Tremoli Institute of Cardiovascular Science, Univ. College London, London, UK. Steve E Humphries Center for Non-Communicable
Diseases Pakistan, Karachi, Pakistan. Danish Saleheen Clinic of Cardiology, West German Heart Centre, Univ. Hosp. of Essen, Univ. Duisburg-Essen, Essen, Germany. Raimund Erbel Hannover Unified Biobank, Hannover Medical School, Hannover,
Germany. Thomas Illig Department of Statistics, Univ. of Oxford, Oxford, UK. Peter J Donnelly Diabetes Genetics, Institute of Biomedical and Clinical Science, Peninsula Medical School, Univ. of Exeter, Exeter, UK. Andrew T Hattersley Human
Genetics Center, Univ. of Texas Health Science Center at Houston, Houston, Texas, USA. Eric Boerwinkle Human Genome Sequencing Center at Baylor College of Medicine, Houston, Texas, USA. Eric Boerwinkle Cardiovascular Research Center,
Massachusetts General Hosp., Boston, Massachusetts, USA. Sekar Kathiresan Division of Epidemiology and Community Health, Univ. of Minnesota, Minneapolis, Minnesota, USA. James S Pankow General Medicine Division, Massachusetts
General Hosp., Boston, Massachusetts, USA. James B Meigs Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA. David Altshuler Department of Molecular Biology, Harvard Medical School, Boston, Massachusetts, USA.
David Altshuler Diabetes Unit, Massachusetts General Hosp., Boston, Massachusetts, USA. David Altshuler
AIM
To extend understanding of the genetic
architecture and molecular basis of type 2
diabetes (T2D)
Methods
we conducted a meta-analysis of genetic
variants on the Metabochip, including
34,840 cases and 114,981 controls,
overwhelmingly of European descent.
This custom array of 196,725 variants was designed to
facilitate cost-effective follow-up of nominal associations for T2D
and other metabolic and cardiovascular traits and to enhance fine
mapping of established loci. The T2D component of Metabochip
comprises 21,774 variants, including 5,057 ‘replication’ SNPs that
capture the strongest independent (r2 < 0.2 in 1000 Genomes
Project Utah residents of Northern and Western European
ancestry (CEU) data) autosomal association signals from the
GWAS meta-analysis conducted by the DIAbetes Genetics
Replication and Meta-analysis (DIAGRAM) Consortium.
This genome-wide meta-analysis (DIAGRAMv3) includes
data from 12,171 T2D cases and 56,862 controls of European
descent imputed at up to 2.5 million autosomal SNPs and
augments the previously published DIAGRAMv2 meta-analysis4
with 4 additional GWAS (Supplementary Table 1). The T2D
content of Metabochip includes an additional 16,717 variants,
most chosen from 1000 Genomes Project pilot data, to fine map
27 established susceptibility loci.
HNF1B
FTO
MAEA
AP3S2
SLC30A8
ANKRD55
(TCF2)
HNF4A
KLHDC5
BCL11A
SPRY2
HNF1A
GLIS3
IGF2BP2
SRR
JAZF1
ZBED3
(TCF1)
HMG20A
WFS1
TCF7L2
BCAR1
HMGA2
RBMS1
TLE1
GIPR
CDC123/C
ADAMTS9
VPS26A
ST64GAL1
KCNQ1
C2CD4A
AMK1D
DGKB
PPARG
CDKAL1
THADA
PTPRD
IRS1
ZMIZ1
GRB14
HHEX/IDE
CDKN2A/B PSMD6
KCNK16
TSPAN8/L
GCK
ZFAND6
PROX1
PRC1
CCND2
GR5
PEPD
TLE4
MC4R
MTNR1B
ANK1
ZFAND3
DUSP8
KLF14
CILP2
KCNJ11
NOTCH2
ARAP1
GCKR
UBE2E2
GCC1
ADCY5
(CENTD2)
TP53INP1
Figure 2 Regional plots of T2D susceptibility loci with evidence of multiple association signals. Each circle
represents a Metabochip SNP passing quality control in our combined meta-analysis plotted with its association P
value (on a −log10 scale) as a function of genomic position (NCBI Build 36). For each locus, the lead SNP is
represented by a purple diamond. The color of all other SNPs indicates LD with the lead SNP (estimated by CEU
r2 from 1000 Genomes Project data, June 2010 release). Recombination rates are estimated from International
HapMap Project data, and gene annotations are taken from the UCSC Genome Browser.
Supplementary Figure 9. Plot of FG and T2D risk at novel and established T2D
susceptibility loci obtained from the present meta-analysis and up to 133,010 nondiabetic individuals from the MAGIC Investigators.
Each point represents a lead T2D SNP, aligned to the risk allele, coloured according to
the significance of association with FG: red p<5x10-8; orange 5x10-8≤p<10-4; yellow
10-4≤p<0.01; green 0.01≤p<0.05; blue p≥0.05.
Biological hypotheses related to disease pathogenesis tested with GSEA (gene-set enrichment analysis)
Adipocytokine signalling. Adipocytokines have been implicated in the development of insulin resistance. Leptin
and adiponectin are potential insulin sensitizers and TNF-alpha is a potential insulin antagonist19.
Amyloid metabolism. The islet amyloid polypeptide inhibits insulin and glucagon secretion from pancreatic betaislet cells. Islet amyloid deposits have been associated with T2D and pancreatic beta-cell loss20,21.
Branched-chain amino acid metabolism. Elevated branched-chain amino acid plasma levels are associated with
high insulin resistance and/or low circulating levels of insulin in T2D cases. The branched-chain amino acids,
isoleucine, leucine and valine, are strong predictors of future diabetes. Leucine acutely stimulates insulin secretion
in pancreatic beta cells22-24.
Cell cycle. Several cell cycle regulators lie in previously established T2D loci, including CDKN2B/A, CDKN1C,
and CCNE2. The majority of these genes regulate CDK4 or CDK6, shown to play a role in beta-islet pancreatic
cell proliferation, which in turn may affect insulin secretion. These regulators may also have an effect on peripheral
tissues relevant to T2D25-27.
Circadian rhythm. Several studies showed that people with an altered circadian rhythm have an increased risk of
developing T2D. MTNR1B regulates circardian rhythm and contains common variants associated with T2D,
fasting glucose, and pancreatic beta-cell function, suggesting a causal role for circadian rhythm in T2D. The
melatonin system was shown to regulate glucose homeostasis28-32.
Endoplasmic reticulum (ER) stress response (unfolded protein response). WFS1, a component of the
unfolded protein response, lies near common variants associated with T2D and harbours rare mutations
associated with Wolfram syndrome, a rare syndrome that causes diabetes mellitus, amongst other disorders.
WFS1 is up-regulated during insulin secretion. Inactivation of WFS1 in beta-cells causes ER stress and
dysfunction. Furthermore, EIF2AK3, a key component of the ER stress response pathway, contains rare mutations
that cause neonatal diabetes33-35.
Fatty acid metabolism. Elevated plasma free fatty acid (FFA) concentrations are linked with the onset of skeletal
muscle and hepatic insulin resistance and are associated with T2D. Elevated blood fatty-acid concentrations
reduce muscle glucose uptake, and increase liver glucose production, contributing to elevated blood glucose
levels. FFA also affects insulin secretion from the pancreas. However, in pre-diabetic patients, FFA stimulation of
insulin secretion is not sufficient to fully compensate for the FFA-induced insulin resistance, leading to
hyperglycaemia36,37.
Glycolysis and gluconeogenesis. Glucokinase, GCK, the first glycolytic enzyme, and GCKR, a regulator of GCK,
contain or lie near common SNPs associated with T2D. Studies have shown that hepatic gluconeogenesis is
increased in people with T2D compared with controls following overnight fasting38,39.
Inflammation. Elevated levels of the inflammatory cytokines, TNF-alpha and IL-6, and the Creactive protein that
rises in response to inflammation, predict the development of T2D. However, whether inflammation is a primary
cause of T2D or secondary to hyperglycaemia (or other T2D features) is not yet clear. A potential mechanism of
causality is through macrophages that release cytokines, causing neighbouring liver, muscle or fat cells to become
insulin resistant. Inflammation in pancreatic islets could also lead to a decrease in beta-cell mass affecting insulin
secretion levels40-43.
Insulin signalling. Alterations in insulin signalling may lead to insulin resistance in peripheral tissues such as fat,
liver and muscle, a major risk factor for T2D27,44.
Insulin synthesis and secretion. Insufficient insulin secretion is one of the major causes of T2D. Many of the
established T2D common SNP associations lie near genes implicated in beta-cell function, such as KCNJ11 and
ABCC8. These ATP sensitive potassium channel subunits, proximal to each other on the chromosome, are targets
of anti-diabetes drugs (sulfonylurea and/or meglitinides) that lead to an increase in insulin secretion. Mutations in
these genes are also associated with different forms of neonatal diabetes27,44.
Mitochondrial dysfunction. Mitochondrial dysfunction has been implicated in both rare and common forms of
diabetes. T2D cases have less mitochondria in their skeletal muscle, and oxidative phosphorylation genes are
collectively down-regulated in muscle, compared with healthy individuals. However, pronounced genetic evidence
for a causal effect of decreased mitochondrial activity on T2D has not yet been shown45-47.
NOTCH signalling. NOTCH2 contains a common variant associated with T2D. NOTCH signalling plays a role in
pancreas development35,48.
PPARG signalling. PPARG contains a common variant associated with T2D, and is the target of thiazolidinedione
(TZD) drugs, used clinically to reduce insulin resistance in T2D patients. PPARG plays a role in fat, liver and
muscle49,50.
Vitamin D metabolism. Vitamin D deficiency has been suggested to be associated with T2D and insulin
resistance. Vitamin D may also play a role in insulin secretion by promoting calcium absorption in the pancreas5153. WNT signalling. A strong common variant association signal lies in an intron of TCF7L2, a transcription factor
that regulates WNT targets. The WNT signalling pathway may play a role in both the insulin secretion and insulin
sensitivity features of T2D. For example, WNT signalling activation in the pancreas leads to pancreatic beta cell
proliferation, and improved insulin sensitivity in skeletal muscle54-57.
a nuclear protein that binds to
cAMP-response elementbinding protein (CREB),
We saw no evidence of enrichment for other processes
implicated in T2D pathogenesis, including amyloid
formation, endoplasmic reticulum stress and insulin
signaling.
Figure 3 Functional analyses. (a,b) PPI
subnetwork for CREBBP (a) and
adipocytokine (b) interactions. All direct
interactions and common interactors
between direct connections were extracted
from the larger network of 314 proteins
defined in DAPPLE network analysis.
Genes in the network are represented as
circles (nodes), colored according to the
statistical relationship with T2D: gray,
common interactors between GWASidentified or monogenic loci; blue,
monogenic loci only; red, GWAS-identified
loci only; green, loci with GWAS association
and implicated by monogenic forms of
diabetes. Each interaction defined in the in
WEB network is depicted by a line (edge)
between nodes. (c) GRAIL circle plot of
locus connectivity. Each locus is plotted in
a circle, where significant connections (P <
0.05) based on PubMed abstracts are
drawn spanning the circle. Conservatively,
we treated all monogenic loci (region 142)
as a single locus by which connectivity was
assessed. The strongest connections (P <
0.001) are colored in bright red. (d) GSEA
of associations in the adipocytokine
signaling pathway. Black bars represent
the stage 1 meta-analysis P values of 63
autosomal genes in the adipocytokine
signaling pathways (KEGG). Top, density
plot of the black bars (red line). The
replicating genes in the leading edge of the
GSEA are listed. Stage 2 modified GSEA P
= 1.6 × 10−4 was calculated on the basis of
both the primary and secondary transcripts
using the LD locus definition.
Supplementary Figure 11. Plot of T2D and T1D risk at 37 established T1D susceptibility loci
obtained from the present meta-analysis and up to 7,514 T1D cases and 9,045 population
controls from the Type 1 Diabetes Genetics Consortium.
Each point represents a lead T1D SNP, aligned to the risk allele, coloured according to the
significance of association with T2D: red p<0.05; blue p≥0.05.
Findings
We identified ten previously unreported T2D
susceptibility loci, including two showing sexdifferentiated association. Genome-wide
analyses of these data are consistent with a
long tail of additional common variant loci
explaining much of the variation in
susceptibility to T2D. Exploration of the
enlarged set of susceptibility loci implicates
several processes, including CREBBP-related
transcription, adipocytokine signaling and cell
cycle regulation, in diabetes pathogenesis.
Message
オックスフォード大学、米ハーバード・マサチューセッツ工科大
学（MIT）ブロード研究所および米ミシガン大学の研究者らによ
る今回の研究では、2型糖尿病に関連する可能性のあるDNAに共通
する遺伝的多様性（バリエーション）について検討。2型糖尿病
患者約3万5,000人と、同疾患のない約11万5,000人のDNAを調べ、
DNAの変化と糖尿病リスクとの関連のみられる新たな遺伝子領域
を突き止めた。このうち2つは性別によって異なる作用がみられ、
1つは男性の疾患リスク増大に関連しており、もう1つは女性のリ
スク増大に関連していた。
この研究から、2型糖尿病に関連する遺伝子タイプのパターン
も浮上した。「60強の遺伝子全体を併せ見ることにより、疾患リ
スクに影響を及ぼす遺伝子の種類の特徴を探ることができる」と、
McCarthy氏は述べている。細胞の成長、分裂および老化のプロセ
スに関与する遺伝子、脂肪細胞が他の身体部位での生物学的プロ
セスに影響を及ぼす経路に関与する遺伝子、他の遺伝子を制御す
る転写因子遺伝子などが認められているという。