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Journal Club

Journal Club. Meier JJ, Menge BA, Breuer TG, Müller CA, Tannapfel A, Uhl W, Schmidt WE, Schrader H. Functional assessment of pancreatic beta-cell area in humans. Diabetes. 2009 Jul;58(7):1595-603

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Journal Club

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  1. Journal Club Meier JJ, Menge BA, Breuer TG, Müller CA, Tannapfel A, Uhl W, Schmidt WE, Schrader H. Functional assessment of pancreatic beta-cell area in humans. Diabetes. 2009 Jul;58(7):1595-603 Müssig K, Staiger H, Machicao F, Kirchhoff K, Guthoff M, Schäfer SA, Kantartzis K, Silbernagel G, Stefan N, Holst JJ, Gallwitz B, Häring HU, Fritsche A. Association of type 2 diabetes candidate polymorphisms in KCNQ1 with incretin and insulin secretion. Diabetes. 2009 Jul;58(7):1715-20. 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 2009年７月30日　8:30-8:55 ８階　医局

  2. Beta cell depletion in type 1 and 2 diabetes mellitus

  3. 2型糖尿病歴と膵β細胞機能低下 糖尿病患者の膵b細胞機能自然歴 膵b細胞を守る治療を考慮した場合の膵b細胞機能 100 75 50 膵b細胞機能（%） IGT 食　後 高血糖 糖尿病 第1期 25 糖尿病 第2期 糖尿病第3期 0 -12 -10 -6 -2 0 2 6 10 14 （年数） 糖尿病の診断 Lebovitz HE.: Diabetes Reviews,7,139,1999.より改変

  4. 80 60 40 20 膵β細胞機能障害と2型糖尿病の自然史 （%,HOMA-β） 100 膵β細胞機能 SU薬 メトホルミン 食事療法 n=4,209 0 （年） -10 -8 -6 -4 -2 0 2 4 6 診断からの年数 加来浩平（川崎医科大）：第11回軽症糖尿病研究会（2008.2 香川）

  5. IGTの段階から膵β細胞機能は低下している 40 β細胞機能 非肥満 30 肥満 80％ 低下 （∆ I / ∆ GLU ÷ IR） 20 10 0 2時間血糖値（mg/dL） <320 <120 <140 >400 <100 <240 <400 <200 <280 <360 NGT （138例） IGT （259例） 2型糖尿病 （201例） <160 <180 DeFronzo.R.A.:Diabetologia 47,31, 2004.

  6. We examined pancreatic tissue from 124 autopsies: 91 obese cases (BMI >27 kg/m2; 41 with type 2 diabetes, 15 with impaired fasting glucose [IFG], and 35 nondiabetic subjects) and 33 lean cases (BMI <25 kg/m2; 16 type 2 diabetic and 17 nondiabetic subjects). Butler AE, Janson J, Bonner-Weir S, Ritzel R, Rizza RA, Butler PC. Beta-cell deficit and increased beta-cell apoptosis in humans with type 2 diabetes. Diabetes. 2003 Jan;52(1):102-10.

  7. Previous Imaging Attempts Fluorine-18 4-fluorobenzyltrozamicol [11C]acetate chemical shift gradient–echo magnetic resonance imaging β cell–specific anti-IC2 mAb, modified with a radioisotope chelator, in vivo uptake of 6-deoxy-6-[125I]iodo-d-glucose uptake of [2-(14)C]alloxan, targeting the GLUT2 transporter Dithizone and sulfonylurea receptor ligands (e.g., 3H-glibenclamide) [11C]DTBZ (dihydrotetrabenazine) to image the beta cells in vivo

  8. CTI Molecular Imaging / Siemens

  9. Compound Name: (+)-alpha-Dihydrotetrabenazine • NIMH Code: T-802 • Alternative Name: (+)-(2R,3R,11bR)-alpha-Dihydrotetrabenazine • Abbreviation: • Indications: Active metabolite of tetrabenazine with high affinity for the vesicular monamine transporter (VMAT2) • Package Sizes: • References: 1) M. R. Kilbourne, L. C. Lee, M. J. Heeg and D. M. Jewett, Absolute configuration of (+)-alpha-dihydrotetrabenazine, an active metabolite of tetrabenazine, Chirality, 9(1), 59-62 (1997). 2) M. Kilbourne, L. Lee, T. Vander Borght, D. Jewett and K. Frey, Binding of alpha-dihydrotetrabenazine to the vasicular monoamine transporter is stereospecific, Eur. J. Pharmacol., 278(3), 249-252 (1995).

  10. Sections stained with guinea pig anti-bovine insulin antibodies were analyzed by Image J software.

  11. the 1Department of Medicine I, St. Josef-Hospital, Ruhr-University Bochum, Germany; the 2Department of Surgery, St. Josef-Hospital, Ruhr- University Bochum, Germany; and the 3Department of Pathology, Ruhr- University Bochum, Germany. Diabetes 58:1595–1603, 2009

  12. OBJECTIVE b-Cell mass declines progressively during the course of diabetes, and various antidiabetic treatment regimens have been suggested to modulate b-cell mass. However, imaging methods allowing the monitoring of changes in b-cell mass in vivo have not yet become available. We address whether pancreatic b-cell area can be assessed by functional test of insulin secretion in humans.

  13. RESEARCH DESIGN AND METHODS A total of 33 patients with chronic pancreatitis (n = 17), benign pancreatic adenomas (n = 13), and tumors of the ampulla of Vater (n = 3) at various stages of glucose tolerance were examined with an oral glucose load before undergoing pancreatic surgery. Indexes of insulin secretion were calculated and compared with the fractional b-cell area of the pancreas.

  14. FIG. 1. Concentrations of glucose (A), insulin (B), and C-peptide (C) in eight individuals with NGT (□), 14 individuals with IFG and/or IGT (◇), and 11 patients with diabetes (△) after oral ingestion of 75 g glucose. Data are the means _ SE. Statistics were carried out using repeated-measures ANOVA and denote differences between the experiments (A), differences over time (B), and differences due to the interaction of experiment and time (AB). *Significant (P <0.05) differences vs. control subjects at individual time points (one-way ANOVA and Duncan’s post hoc test). -5,0,15,30,60,90,120,150,180,210,240 min

  15. RESULTS b-Cell area was related to fasting glucose concentrations in an inverse linear fashion (r =-0.53, P = 0.0014) and to 120-min postchallenge glycemia in an inverse exponential fashion (r =- 0.89). b-Cell area was best predicted by a C-peptide–to– glucose ratio determined 15 min after the glucose drink (r = 0.72, P < 0.0001). However, a fasting C-peptide–to– glucose ratio already yielded a reasonably close correlation (r = 0.63, P <1). Homeostasis model assessment (HOMA) b-cell function was unrelated to b-cell area.

  16. Discussion 1 Insulin secretion can be confounded by a number of factors: Obesity, GLP-1, concomitant antidiabetic treatment Collectivel, these findings further emphasize the importance of beta-cell mass for the development of diabetes. BMI ~23.4kg/m2 (~37 kg/m2 in Butler et al.)

  17. Discussion 2 Indexes to estimate beta-cell function in vivo Insulin response to iv glucagon or arginine (with or without glucose potentiation) Oral glucose tolerance test Pancreatic weight: cannot readily measured at surgery in humans. Pancreatic volume is not affected by the presence of type 2 diabetes and remains rather constant. A close inverse relationship between postchallenge glycemia and beta-cell area in humans in vivo.

  18. CONCLUSIONS Glucose control is closely related to pancreatic b-cell area in humans. A C-peptide–to–glucose ratio after oral glucose ingestion appears to better predict b-cell area than fasting measures, such as the HOMA index.

  19. Message ２型糖尿病患者のインスリン分泌は次第に落ちます。必用な薬物介入は発症後の年数に応じて行うこと。 そのためには 外来診療では電子カルテに必ず糖尿病の診断年（月日）を入力すること！ カロリー計算に必用な 身長の入力も忘れずに！

  20. T2DMCandidate 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 • CDKAL1β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 • TCF7L2β細胞の機能障害 • 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 • PPARg脂肪酸化障害 • PPARa • FTO肥満 • GCKR中性脂肪を調節 • WFS1 • SLC30A8 • KCNQ1

  21. NATURE GENETICS40(9):1092-1097 Received 3 March; accepted 6 June; published online 17 August 2008; doi:10.1038/ng.207 1Department of Metabolic Disorder, Research Institute, International Medical Center of Japan, Tokyo 162-8655, Japan. 2Division of Diabetes, Metabolism, and Endocrinology, Department of Internal Medicine, Kobe University Graduate School of Medicine, Kobe 650-0017, Japan. 3Department of Diabetes and Endocrinology, Division of Molecule and Structure, Gifu University School of Medicine, Gifu 501-1194, Japan. 4Department of Metabolic Diseases, Graduate School of Medicine, University of Tokyo, Tokyo 113-8655, Japan. 5Department of Molecular and Genetic Medicine, Ehime University Graduate School of Medicine, Ehime 791-0295, Japan. 6First Department of Medicine, Wakayama Medical University, Wakayama 641-8509, Japan. 7Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital Malmo¨ , Lund University, S-205 02 Malmo¨ , Sweden. 8Department of Metabolic Medicine, Graduate School of Medicine, Osaka University, Osaka 565-0871, Japan. 9Division of Molecular Metabolism and Diabetes, Tohoku University Graduate School of Medicine, Sendai 980-8574, Japan. 10Division of Genetic Information, Institute for Genome Research, University of Tokushima, Tokushima 770-8503, Japan. 11Department of Endocrinology and Metabolism, Kyoto Prefectural University of Medicine, Graduate School of Medical Sciences, Kyoto 602-8566, Japan. 12Department of Medicine, Diabetes Center, Tokyo Women’s Medical University, Tokyo 162-8666, Japan. 13Department of Diabetes and Clinical Nutrition, Kyoto University School of Medicine, Kyoto 606-8501, Japan. 14Division of Endocrinology and Metabolism, Department of Medicine, Shiga University of Medical Science, Shiga 520-2192, Japan. 15Clinical Genome Informatics Center, Kobe University Graduate School of Medicine, Kobe 650-0017, Japan. 16Department of Genetic Epidemiology, SNP Genetics Inc., Seoul 110-834, Korea. 17Department of Internal Medicine, Seoul National University College of Medicine, Seoul 110-744, Korea. 18Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong. 19Department of Medicine, Helsinki University Hospital, FIN-00300 Helsinki, Finland. 20Folkhaelsan Research Center, FIN-00014 Helsinki, Finland. 21Department of Clinical Sciences, Medicine Research Unit, University Hospital Malmo¨ , Lund University, S-205 02 Malmo¨ , Sweden. 22Division of Genomic Medicine, Department of Advanced Biomedical Engineering and Science, Tokyo Women’s Medical University, Tokyo 162-8666, Japan. 23SNP Research Center, Institute of Physical and Chemical Research (RIKEN), Yokohama 230-0045, Japan. 24Department of Molecular Genetics, Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan. 25Genetics Division, National Cancer Center Research Institute, Tokyo 104-0045, Japan. 26Department of Human Genetics, Graduate School of Medicine, University of Tokyo, Tokyo 113-0033, Japan. 27Present addresses: Department of Medical Biochemistry, Faculty of Medical and Pharmaceutical Sciences, Kumamoto University, Kumamoto 860-8556, Japan (K. Yamagata), Shanghai Institute of Materia Medica, Chinese Academy of Science, Shanghai 200031, China (H.-Y.W.), Department of Internal Medicine, Akita University School of Medicine, Akita 010-8543, Japan (Y.Y.), Kansai Electric Power Hospital, Osaka 553-0003, Japan (Y. Seino) and Genome Informatics, Center for Genomic Medicine, Graduate School of Medicine and Faculty of Medicine, Kyoto University, Kyoto 606-8501, Japan (A.S.). Correspondence should be addressed to M.K. (kasuga@med.kobe-u.ac.jp).

  22. NATURE GENETICS40(9):1092-1097 Received 3 March; accepted 10 June; published online 17 August 2008; doi:10.1038/ng.208 1Laboratory for Endocrinology and Metabolism, 2Laboratory for Statistical Analysis and 3Laboratory for Medical Informatics, Center for Genomic Medicine, RIKEN, Yokohama, Kanagawa 230-0045, Japan. 4Department of Metabolic Diseases, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8655, Japan. 5Steno Diabetes Center, Niels Steensens Vej 2, DK-2820 Gentofte, Copenhagen, Denmark. 6Department of Community, Occupational and Family Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore. 7Research Centre for Prevention and Health, Glostrup University Hospital, 2600 Glostrup, Denmark. 8Faculty of Health Science and 9Department of General Practice, University of Aarhus, 8000 Aarhus, Denmark. 10Laboratory for Genotyping Development, Center for Genomic Medicine, RIKEN, Yokohama, Kanagawa 230-0045, Japan. 11Diabetes Center, Tokyo Women’s Medical University, Tokyo 162-8666, Japan. 12Health Center and 13Department of Internal Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan. 14Department of Medicine, Shiga University of Medical Science, Otsu, Shiga 520-2192, Japan. 15Division of Endocrinology and Metabolism, Department of Internal Medicine, Kawasaki Medical School, Kurashiki, Okayama 701-0192, Japan. 16Department of Medicine, Metabolism and Endocrinology, School of Medicine, Juntendo University, Tokyo 113-8421, Japan. 17Department of Endocrinology, Singapore General Hospital, Singapore 169608, Singapore. 18Laboratory of Molecular Medicine, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo 108-8639, Japan. Correspondence should be addressed to S.M. (smaeda@src.riken.jp).

  23. the 1Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, University Hospital of Tu¨ bingen, Tu¨ bingen, Germany; and the 2Department of Biomedical Sciences, The Panum Institute, University of Copenhagen, Copenhagen, Denmark. Diabetes 57:1715–1720, 2009

  24. OBJECTIVE KCNQ1 gene polymorphisms are associated with type 2 diabetes. This linkage appears to be mediated by altered b-cell function. In an attempt to study underlying mechanisms, we examined the effect of four KCNQ1 single nucleotide polymorphisms (SNPs) on insulin secretion upon different stimuli.

  25. RESEARCH DESIGN AND METHODS We genotyped 1,578 nondiabetic subjects at increased risk of type 2 diabetes for rs151290, rs2237892, rs2237895, and rs2237897. All participants underwent an oral glucose tolerance test (OGTT); glucagon-like peptide (GLP)-1 and gastric inhibitory peptide secretion was measured in 170 participants. In 519 participants, a hyperinsulinemic- euglycemic clamp was performed, in 314 participants an intravenous glucose tolerance test (IVGTT), and in 102 subjects a hyperglycemic clamp combined with GLP-1 and arginine stimuli.

  26. Figure 1 Dense mapping analysis of KCNQ1. The top panel shows the association –log10 (P value) in panel 2+3 for 64 SNPs of KCNQ1. The three blue circles represent the positive SNPs in the third screening. The red circle (rs2237892) indicates the SNP showing the most significant association with type 2 diabetes. The upper middle panel shows the physical position of KCNQ1 and neighboring genes on chromosome 11 (UCSC Genome Browser). The lower middle panel shows the positions and rs numbers of the 52 previously identified SNPs. Blue rectangles indicate the positive SNPs in the third screening. The bottom panel shows a Haploview representation of LD (D’) based on genotyping data from control subjects in panel 2+3 (n = 1,424). Yasuda K, et al: Nat Genet. 40:1092-7, 2008.

  27. Yasuda K, et al: Nat Genet. 40:1092-7, 2008.

  28. Unoki H, et al: Nat Genet. 40(9):1098-102、2008

  29. 膵臓 筋肉 肝臓 グルコースクランプSteady state (Direct) • Hyperglycemic clamp 膵臓のインスリン分泌を評価する。 • Euglycemic hyperinsulinemic clamp 末梢組織（主に筋肉）のインスリン感受性を評価する。 (インスリンクランプ) ●Pancreatic clamp 肝臓のインスリン感受性を評価する

  30. 高血糖クランプ法 膵臓 グルコースクランプ法の一つ 基本的にはインスリン分泌を見る方法。インスリン感受性は計算可能だが，人為的な要因の影響を受けやすい。 血糖 (動脈) インスリン (動脈） 糖注入率 (mg/kg per min) (mg/dl) 凸 U/ml) ( m 25 250 100 200 20 80 150 60 15 10 100 40 ２相性インスリン分泌が観察できる 20 5 50 0 0 0 0 40 80 120 0 120 40 80 分 分

  31. インスリン注入 アルゴリズム 筋肉 内因性インスリン分泌は無視できるレベルとなる インスリンクランプ法 グルコースクランプ法の一つ 糖注入量 糖注入量 インスリン (動脈側） 　　　　　　 （一定にするように注入) 血糖 (動脈側) (mg/kg per min) (mg/kg per min) (mg/dl) ( U/ml) 凸 ( U/ml) m 凸 m 100 100 250 250 80 80 200 10.0 200 10.0 60 150 60 150 7.5 7.5 40 40 100 100 5.0 5.0 20 20 50 2.5 50 2.5 0 0 0 0 0 0 0 40 80 120 0 40 80 120 0 40 80 120 0 40 80 120 分 分

  32. Matsuda Index IVGTT derived indexes of insulin secretion: all P>0.4 OGTT derived insulin secretion: significant! The goal of the International HapMap Project is to develop a haplotype map of the human genome, the HapMap, which will describe the common patterns of human DNA sequence variation. The HapMap is expected to be a key resource for researchers to use to find genes affecting health, disease, and responses to drugs and environmental factors. The information produced by the Project will be made freely available.

  33. Ｍｏｄｉｆｉｅｄ　Ｈｙｐｅｒｇｌｙｃｅｍｉｃ　CｌａｍｐＭｏｄｉｆｉｅｄ　Ｈｙｐｅｒｇｌｙｃｅｍｉｃ　Cｌａｍｐ

  34. FIG. 1. A: Associations of KCNQ1 SNPs rs151290, rs2237892, rs2237895, and rs2237897 with insulin secretion. Insulin secretion was assessed by C-peptide levels at 30 min during an OGTT. Unadjusted data from 1,578 subjects are presented. B: Association of KCNQ1 SNPs rs151290, rs2237892, rs2237895, and rs2237897 with increase of GLP-1 levels during an OGTT. C: Association of KCNQ1 SNPs rs151290, rs2237892, rs2237895, and rs2237897 with increase of GIP levels during OGTT. Incretin increase was assessed by the ratio of levels at 30 min during OGTT to fasting levels. Unadjusted data from 170 subjects are presented. Before multivariate linear regression analysis in the dominant model, non–normally distributed data were log–transformed. C-peptide levels were adjusted for sex, age, BMI, and insulin sensitivity. Incretin increase was adjusted for sex, age, and BMI. P values are given above the columns. Sample sizes are given at the bottom of the columns.

  35. RESULTS rs151290 was nominally associated with 30-min C-peptide levels during OGTT, first-phase insulin secretion, and insulinogenic index after adjustment in the dominant model (all P < 0.01). rs2237892, rs2237895, and rs2237897 were nominally associated with OGTT-derived insulin secretion indexes (all P < 0.05). No SNPs were associated with b-cell function during intravenous glucose or GLP-1 administration. However, rs151290 was associated with glucose-stimulated gastric inhibitory polypeptide and GLP-1 increase after adjustment in the dominant model (P = 0.0042 and P = 0.0198, respectively). No associations were detected between the other SNPs and basal or stimulated incretin levels (all P < 0.05).

  36. CONCLUSIONS Common genetic variation in KCNQ1 is associated with insulin secretion upon oral glucose load in a German population at increased risk of type 2 diabetes. The discrepancy between orally and intravenously administered glucose seems to be explained not by altered incretin signaling but most likely by changes in incretin secretion.

  37. http://mmatsuda.diabetes-smc.jp/newpage115.html Message Matsuda Indexは世の中に役立っています

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