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1. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Vasiliki Lagou, Reedik Mägi, Jouke- Jan Hottenga, Harald Grallert, John R. B. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, Rick Jansen, Josine L. Min, Antigone S. Dimas, Anna Ulrich, Liudmila Zudina, Jesper R. Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G. Stathopoulou, Aaron Isaacs, Sara M. Willems, Pau Navarro, Toshiko Tanaka, Anne U. Jackson, May E. Montasser, Jeff R. O’Connell, Lawrence F. Bielak, Rebecca J. Webster, Richa Saxena, Jeanette M. Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, So-Youn Shin, Najaf Amin, Albert V. Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C. D. Johnson, Toby Johnson, Karen Kapur, Gudmar Thorleifsson, Rona J. Strawbridge, Laura J. Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, Tove Fall, Ross M. Fraser, Anubha Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, Marcus E. Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, Jian’an Luan, Momoko Horikoshi, Ping An, Serena Sanna, Yvonne Boettcher, N. William Rayner, Ilja M. Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D. Hastie, Sarah H. Wild, Stela McLachlan, Susan Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, Gonneke Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, Andrew A. Hicks, Rainer Rauramaa, Stefania Bandinelli, Barbara Thorand, Yongmei Liu, Iva Miljkovic, Lars Lind, Alex Doney, Markus Perola, Aroon Hingorani, Mika Kivimaki, Meena Kumari, Amanda J. Bennett, Christopher J. Groves, Christian Herder, Heikki A. Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J. L. Bakker, Matti Uusitupa, Colin N. A. Palmer, J. Wouter Jukema, Naveed Sattar, Anneli Pouta, Harold Snieder, Eric Boerwinkle, James S. Pankow, Patrik K. Magnusson, Ulrika Krus, Chiara Scapoli, Eco J. C. N. de Geus, Matthias Blüher, Bruce H. R. Wolffenbuttel, Michael A. Province, Goncalo R. Abecasis, James B. Meigs, G. Kees Hovingh, Jaana Lindström, James F. Wilson, Alan F. Wright, George V. Dedoussis, Stefan R. Bornstein, Peter E. H. Schwarz, Anke Tönjes, Bernhard R. Winkelmann, Bernhard O. Boehm, Winfried März, Andres Metspalu, Jackie F. Price, Panos Deloukas, Antje Körner, Timo A. Lakka, Sirkka M. Keinanen-Kiukaanniemi, Timo E. Saaristo, Richard N. Bergman, Jaakko Tuomilehto, Nicholas J. Wareham, Claudia Langenberg, Satu Männistö, Paul W. Franks, Caroline Hayward, Veronique Vitart, Jaakko Kaprio, Sophie Visvikis-Siest, Beverley Balkau, David Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia M. van Duijn, Christian Gieger, Thomas Illig, Luigi Ferrucci, Nancy L. Pedersen, Peter P. Pramstaller, Michael Boehnke, Timothy M. Frayling, Alan R. Shuldiner, Patricia A. Peyser, Sharon L. R. Kardia, Lyle J. Palmer, Brenda W. Penninx, Pierre Meneton, Tamara B. Harris, Gerjan Navis, Pim van der Harst, George Davey Smith, Nita G. Forouhi, Ruth J. F. Loos, Veikko Salomaa, Nicole Soranzo, Dorret I. Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, Vilmundur Gudnason, David S. Siscovick, Hugh Watkins, Cecile Lecoeur, Peter Vollenweider, Anders Franco-Cereceda, Per Eriksson, Marjo-Riitta Jarvelin, Kari Stefansson, Anders Hamsten, George Nicholson, Fredrik Karpe, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Mark I. McCarthy, Philippe Froguel, Marika A. Kaakinen, Valeriya Lyssenko, Richard M. Watanabe, Erik Ingelsson, Jose C. Florez, Josée Dupuis, Inês Barroso, Andrew P. Morris, Inga Prokopenko, and Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC)

Subjects
Science
Abstract

Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

Published
2021
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3. Insulin Action, Glucose Homeostasis and Free Fatty Acid Metabolism: Insights From a Novel Model

Author

Darko Stefanovski, Naresh M. Punjabi, Raymond C. Boston, and Richard M. Watanabe

Subjects
free fatty acids (FFA), insulin action, FFA metabolism, glucose, lipolysis, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

Glucose and free fatty acids (FFA) are essential nutrients that are both partly regulated by insulin. Impaired insulin secretion and insulin resistance are hallmarks of aberrant glucose disposal, and type 2 diabetes (T2DM). In the current study, a novel model of FFA kinetics is proposed to estimate the role insulin action on FFA lipolysis and oxidation allowing estimation of adipose tissue insulin sensitivity (SIFFA). Twenty-five normal volunteers were recruited for the current study. To participate, volunteers had to be less than 40 years of age and have a body mass index (BMI) < 30 kg/m2, and be free of medical comorbidity. The proposed model of FFA kinetics was used to analyze the data derived from the insulin-modified FSIGT. Mean fractional standard deviations of the parameter estimates were all less than 20%. Standardized residuals of the fit of the model to the FFA temporal data were randomly distributed, with only one estimated point lying outside the 2-standard deviation range, suggesting an acceptable fit of the model to the FFA data. The current study describes a novel one-compartment non-linear model of FFA kinetics during an FSIGT that provides an FFA metabolism insulin sensitivity parameter (SIFFA). Furthermore, the models suggest a new role of glucose as the modulator of FFA disposal. Estimates of SIFFA confirmed previous findings that FFA metabolism is more sensitive to changes in insulin than glucose metabolism. Novel derived indices of insulin sensitivity of FFA (SIFFA) were correlated with minimal model indices. These associations suggest a cooperative rather than competitive interplay between the two primary nutrients (glucose and FFA) and allude to the FFA acting as the buffer, such that glucose homeostasis is maintained.

Published
2021
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4. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Vasiliki Lagou, Reedik Mägi, Jouke- Jan Hottenga, Harald Grallert, John R. B. Perry, Nabila Bouatia-Naji, Letizia Marullo, Denis Rybin, Rick Jansen, Josine L. Min, Antigone S. Dimas, Anna Ulrich, Liudmila Zudina, Jesper R. Gådin, Longda Jiang, Alessia Faggian, Amélie Bonnefond, Joao Fadista, Maria G. Stathopoulou, Aaron Isaacs, Sara M. Willems, Pau Navarro, Toshiko Tanaka, Anne U. Jackson, May E. Montasser, Jeff R. O’Connell, Lawrence F. Bielak, Rebecca J. Webster, Richa Saxena, Jeanette M. Stafford, Beate St Pourcain, Nicholas J. Timpson, Perttu Salo, So-Youn Shin, Najaf Amin, Albert V. Smith, Guo Li, Niek Verweij, Anuj Goel, Ian Ford, Paul C. D. Johnson, Toby Johnson, Karen Kapur, Gudmar Thorleifsson, Rona J. Strawbridge, Laura J. Rasmussen-Torvik, Tõnu Esko, Evelin Mihailov, Tove Fall, Ross M. Fraser, Anubha Mahajan, Stavroula Kanoni, Vilmantas Giedraitis, Marcus E. Kleber, Günther Silbernagel, Julia Meyer, Martina Müller-Nurasyid, Andrea Ganna, Antti-Pekka Sarin, Loic Yengo, Dmitry Shungin, Jian’an Luan, Momoko Horikoshi, Ping An, Serena Sanna, Yvonne Boettcher, N. William Rayner, Ilja M. Nolte, Tatijana Zemunik, Erik van Iperen, Peter Kovacs, Nicholas D. Hastie, Sarah H. Wild, Stela McLachlan, Susan Campbell, Ozren Polasek, Olga Carlson, Josephine Egan, Wieland Kiess, Gonneke Willemsen, Johanna Kuusisto, Markku Laakso, Maria Dimitriou, Andrew A. Hicks, Rainer Rauramaa, Stefania Bandinelli, Barbara Thorand, Yongmei Liu, Iva Miljkovic, Lars Lind, Alex Doney, Markus Perola, Aroon Hingorani, Mika Kivimaki, Meena Kumari, Amanda J. Bennett, Christopher J. Groves, Christian Herder, Heikki A. Koistinen, Leena Kinnunen, Ulf de Faire, Stephan J. L. Bakker, Matti Uusitupa, Colin N. A. Palmer, J. Wouter Jukema, Naveed Sattar, Anneli Pouta, Harold Snieder, Eric Boerwinkle, James S. Pankow, Patrik K. Magnusson, Ulrika Krus, Chiara Scapoli, Eco J. C. N. de Geus, Matthias Blüher, Bruce H. R. Wolffenbuttel, Michael A. Province, Goncalo R. Abecasis, James B. Meigs, G. Kees Hovingh, Jaana Lindström, James F. Wilson, Alan F. Wright, George V. Dedoussis, Stefan R. Bornstein, Peter E. H. Schwarz, Anke Tönjes, Bernhard R. Winkelmann, Bernhard O. Boehm, Winfried März, Andres Metspalu, Jackie F. Price, Panos Deloukas, Antje Körner, Timo A. Lakka, Sirkka M. Keinanen-Kiukaanniemi, Timo E. Saaristo, Richard N. Bergman, Jaakko Tuomilehto, Nicholas J. Wareham, Claudia Langenberg, Satu Männistö, Paul W. Franks, Caroline Hayward, Veronique Vitart, Jaakko Kaprio, Sophie Visvikis-Siest, Beverley Balkau, David Altshuler, Igor Rudan, Michael Stumvoll, Harry Campbell, Cornelia M. van Duijn, Christian Gieger, Thomas Illig, Luigi Ferrucci, Nancy L. Pedersen, Peter P. Pramstaller, Michael Boehnke, Timothy M. Frayling, Alan R. Shuldiner, Patricia A. Peyser, Sharon L. R. Kardia, Lyle J. Palmer, Brenda W. Penninx, Pierre Meneton, Tamara B. Harris, Gerjan Navis, Pim van der Harst, George Davey Smith, Nita G. Forouhi, Ruth J. F. Loos, Veikko Salomaa, Nicole Soranzo, Dorret I. Boomsma, Leif Groop, Tiinamaija Tuomi, Albert Hofman, Patricia B. Munroe, Vilmundur Gudnason, David S. Siscovick, Hugh Watkins, Cecile Lecoeur, Peter Vollenweider, Anders Franco-Cereceda, Per Eriksson, Marjo-Riitta Jarvelin, Kari Stefansson, Anders Hamsten, George Nicholson, Fredrik Karpe, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Mark I. McCarthy, Philippe Froguel, Marika A. Kaakinen, Valeriya Lyssenko, Richard M. Watanabe, Erik Ingelsson, Jose C. Florez, Josée Dupuis, Inês Barroso, Andrew P. Morris, Inga Prokopenko, and Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC)

Subjects
Science
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21276-3

Published
2021
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5. The genetic regulatory signature of type 2 diabetes in human skeletal muscle

Author

Laura J. Scott, Michael R. Erdos, Jeroen R. Huyghe, Ryan P. Welch, Andrew T. Beck, Brooke N. Wolford, Peter S. Chines, John P. Didion, Narisu Narisu, Heather M. Stringham, D. Leland Taylor, Anne U. Jackson, Swarooparani Vadlamudi, Lori L. Bonnycastle, Leena Kinnunen, Jouko Saramies, Jouko Sundvall, Ricardo D'Oliveira Albanus, Anna Kiseleva, John Hensley, Gregory E. Crawford, Hui Jiang, Xiaoquan Wen, Richard M. Watanabe, Timo A. Lakka, Karen L. Mohlke, Markku Laakso, Jaakko Tuomilehto, Heikki A. Koistinen, Michael Boehnke, Francis S. Collins, and Stephen C. J. Parker

Subjects
Science
Abstract

More than 90% of genetic variants associated with type 2 diabetes occur in non-coding regions. Scott et al. report genomes, epigenomes and transcriptomes of skeletal muscle from 271 participants with a range of glucose tolerances, revealing a genetic regulatory architecture enriched in muscle stretch/super enhancers.

Published
2016
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6. Pharmacogenetics of Anti-Diabetes Drugs

Author

Johanna K. DiStefano and Richard M. Watanabe

Subjects
pharmacogenetics, biguanides, sufonylureas, thiazolidinediones, type 2 diabetes mellitus, drug response, association analysis, candidate gene, Medicine, Pharmacy and materia medica, RS1-441
Abstract

A variety of treatment modalities exist for individuals with type 2 diabetes mellitus (T2D). In addition to dietary and physical activity interventions, T2D is also treated pharmacologically with nine major classes of approved drugs. These medications include insulin and its analogues, sulfonylureas, biguanides, thiazolidinediones (TZDs), meglitinides, α-glucosidase inhibitors, amylin analogues, incretin hormone mimetics, and dipeptidyl peptidase 4 (DPP4) inhibitors. Pharmacological treatment strategies for T2D are typically based on efficacy, yet favorable responses to such therapeutics are oftentimes variable and difficult to predict. Characterization of drug response is expected to substantially enhance our ability to provide patients with the most effective treatment strategy given their individual backgrounds, yet pharmacogenetic study of diabetes medications is still in its infancy. To date, major pharmacogenetic studies have focused on response to sulfonylureas, biguanides, and TZDs. Here, we provide a comprehensive review of pharmacogenetics investigations of these specific anti-diabetes medications. We focus not only on the results of these studies, but also on how experimental design, study sample issues, and definition of ‘response’ can significantly impact our interpretation of findings. Understanding the pharmacogenetics of anti-diabetes medications will provide critical baseline information for the development and implementation of genetic screening into therapeutic decision making, and lay the foundation for “individualized medicine” for patients with T2D.

Published
2010
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9. 140-OR: Machine Learning for Metabolite Estimation to Examine Contributors to Glucose Homeostasis and Adiposity: The GUARDIAN Consortium

Author

NICHOLETTE ALLRED, HANNAH C. AINSWORTH, XIUQING GUO, ADRIENNE W. MACKAY, FESTUS NYASIMI, OWEN MELIA, YANYU LIANG, DONALD W. BOWDEN, KENT TAYLOR, LESLIE J. RAFFEL, THOMAS A. BUCHANAN, RICHARD M. WATANABE, JEROME I. ROTTER, LYNNE E. WAGENKNECHT, CARL D. LANGEFELD, and HAE K. IM

Subjects
Endocrinology, Diabetes and Metabolism, Internal Medicine
Abstract

Diabetes is characterized by metabolic dysregulation. Metabolomics captures interactions of cellular processes and environmental exposures to promote disease and can improve mechanistic understanding to identify clinically relevant targets. However, use is limited by cost and sample availability. To facilitate investigation, machine learning approaches were used in the Insulin Resistance Atherosclerosis Family Study (n=943 Mexican Americans) with empiric metabolites (Metabolon HD4) and GWAS data to generate genetically regulated metabolite estimation models for broad application. 950 metabolites were heritable. Ridge and LASSO regression had cross validated correlation >0.1 for 448 metabolites. In an independent set, LASSO (enforcing sparsity) outperformed Ridge (full polygenic architecture) regression. Estimation was extended to the GUARDIAN Consortium (n∼4377) to assess the association of genetically predicted metabolites with glucose homeostasis and adiposity. Multiple associations (FDR P In conclusion, we have developed algorithms for estimating 448 metabolites using genetic data that had good performance in an independent dataset. Estimation models were used to assess association with glucose homeostasis and adiposity highlighting known and novel associations and demonstrating utility. Future work will expand genetic coverage to include rare variants and phenotypic associations to further characterize metabolic dysregulation. Disclosure N.Allred: None. L.J.Raffel: None. T.A.Buchanan: None. R.M.Watanabe: None. J.I.Rotter: None. L.E.Wagenknecht: None. C.D.Langefeld: None. H.K.Im: None. H.C.Ainsworth: None. X.Guo: None. A.W.Mackay: None. F.Nyasimi: None. O.Melia: None. Y.Liang: None. D.W.Bowden: None. K.Taylor: None. Funding R01DK118062

Published
2022

10. Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Tove Fall, Anubha Mahajan, Dmitry Shungin, B. Balkau, Gerjan Navis, A. Metspalu, Anneli Pouta, Andrew A. Hicks, Ilja M. Nolte, Ian Ford, Aroon D. Hingorani, Stefan R Bornstein, Anuj Goel, Rona J. Strawbridge, Niek Verweij, Sarah H. Wild, Patricia B. Munroe, T.B. Harris, Jaana Lindström, Johnson Pcd., Nita G. Forouhi, Pierre Meneton, Patricia A. Peyser, Sarin A-P., Andrea Ganna, Timothy M. Frayling, Patrik K. E. Magnusson, Joanne M. Meyer, Yongmei Liu, Jeanette M. Stafford, Christian Herder, L Zudina, Maria G. Stathopoulou, May E. Montasser, Nicholas D. Hastie, Inês Barroso, Schwarz Peh., James B. Meigs, Perttu Salo, George Davey Smith, Gonneke Willemsen, Christopher J. Groves, Erik P A Van Iperen, M. A. Province, Veikko Salomaa, Naveed Sattar, Serena Sanna, Maria Dimitriou, Joop Jukema, Ulrika Krus, Albert V. Smith, Markku Laakso, James F. Wilson, George Nicholson, Loic Yengo, Tatijana Zemunik, Per Eriksson, Harold Snieder, Peter P. Pramstaller, Claudia Langenberg, R. Rauramaa, Alan R. Shuldiner, Pau Navarro, Veronique Vitart, Ross M. Fraser, Aaron Isaacs, C. Lecoeur, Jesper R. Gådin, Jackie F. Price, Letizia Marullo, L.F. Bielak, Sirkka Keinänen-Kiukaanniemi, Amélie Bonnefond, Michael Stumvoll, Alessia Faggian, Anke Tönjes, Tomohiro Tanaka, Wieland Kiess, Harry Campbell, Josée Dupuis, David Altshuler, João Fadista, Winfried März, G K Hovingh, Thomas Illig, Toby Johnson, H Grallert, Kari Stefansson, Reedik Mägi, Palmer Cna., de Geus Ejcn., Martina Müller-Nurasyid, Karen Kapur, Philippe Froguel, Dorret I. Boomsma, Anders Franco-Cereceda, Marcus E. Kleber, Boehnke M, Olga D. Carlson, Ozren Polasek, Andrew P. Morris, Alex S. F. Doney, Najaf Amin, Sara M. Willems, Vilmundur Gudnason, Jose C. Florez, Jeffery R. O'Connell, Nancy L. Pedersen, T. Saaristo, Wolffenbuttel Bhr., M. I. J. Uusitupa, Longda Jiang, Iva Miljkovic, James S. Pankow, Caroline Hayward, Hugh Watkins, Vasiliki Lagou, Johanna Kuusisto, Jaakko Tuomilehto, Alan F. Wright, Josephine M. Egan, Perry Jrb., C M van Duijn, Valeriya Lyssenko, Leif Groop, Stefania Bandinelli, Nigel W. Rayner, Tõnu Esko, Stela McLachlan, Momoko Horikoshi, Eric Boerwinkle, Rick Jansen, Richard N. Bergman, Gudmar Thorleifsson, Lyle J. Palmer, Vilmantas Giedraitis, Peter Kovacs, Nicholas J. Wareham, Luigi Ferrucci, N J Timpson, D Rybin, Anne U. Jackson, Tiinamaija Tuomi, Gonçalo R. Abecasis, Harst Pvd., Meena Kumari, Albert Hofman, Chiara Scapoli, Evelin Mihailov, Josine L. Min, Anders Hamsten, Hottenga J-J., Loos Rjf., Lars Lind, Ulf de Faire, Jaakko Kaprio, Guo Li, Beate St Pourcain, C Gieger, Amanda J. Bennett, Anna Ulrich, Nabila Bouatia-Naji, Satu Männistö, Antigone S. Dimas, Jarvelin M-R., Günther Silbernagel, F Karpe, A. Körner, David S. Siscovick, M Blüher, Rebecca J. Webster, Erik Ingelsson, Susan Campbell, Mika Kivimäki, Laura J. Rasmussen-Torvik, Heikki A. Koistinen, Sophie Visvikis-Siest, Bernhard O. Boehm, Inga Prokopenko, Ping An, Emmanouil T. Dermitzakis, Cecilia M. Lindgren, Kardia Slr., Richa Saxena, Igor Rudan, Richard M. Watanabe, Jian'an Luan, Marika Kaakinen, Shin S-Y., George Dedoussis, Panagiotis Deloukas, Mark I. McCarthy, Barbara Thorand, B.W.J.H. Penninx, Peter Vollenweider, Paul W. Franks, Leena Kinnunen, Markus Perola, Yvonne Boettcher, Timo A. Lakka, Nicole Soranzo, Stavroula Kanoni, Bakker Sjl., Winkelmann Br, The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Institute of Genomics [Tartu, Estonia], University of Tartu, Vrije Universiteit Amsterdam [Amsterdam] (VU), Vrije Universiteit Medical Centre (VUMC), Helmholtz-Zentrum München (HZM), University of Cambridge [UK] (CAM), Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP), Università degli Studi di Ferrara (UniFE), Boston University [Boston] (BU), VU University Medical Center [Amsterdam], University of Bristol [Bristol], Biomedical Sciences Research Centre Alexander Fleming [Vari, Greece] (BSRC), Imperial College London, Karolinska Institutet [Stockholm], Institute for Molecular Bioscience, University of Queensland [Brisbane], Statens Serum Institut [Copenhagen], Interactions Gène-Environnement en Physiopathologie Cardio-Vasculaire (IGE-PCV), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Erasmus University Medical Center [Rotterdam] (Erasmus MC), Cardiovascular Research Institute Maastricht (CARIM), Maastricht University [Maastricht], MRC Institute of Genetics and Molecular Medicine [Edinburgh] (IGMM), University of Edinburgh-Medical Research Council, National Institute on Aging [Baltimore, MD, USA] (NIH), University of Michigan [Ann Arbor], University of Michigan System, University of Maryland School of Medicine, University of Maryland System, The University of Western Australia (UWA), Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Massachusetts General Hospital [Boston], Harvard Medical School [Boston] (HMS), Wake Forest University, National Institute for Health and Welfare [Helsinki], The Wellcome Trust Sanger Institute [Cambridge], University of Iceland [Reykjavik], University of Washington [Seattle], University of Groningen [Groningen], University of Glasgow, William Harvey Research Institute, Barts and the London Medical School, Université de Lausanne (UNIL), deCODE genetics [Reykjavik], Northwestern University Feinberg School of Medicine, Uppsala Universitet [Uppsala], University of Edinburgh, Medical Faculty [Mannheim], University of Graz, Ludwig-Maximilians-Universität München (LMU), Johannes Gutenberg - Universität Mainz (JGU), Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki-University of Helsinki, Umeå University, Skane University Hospital [Malmo], Lund University [Lund], RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Washington University School of Medicine in St. Louis, Washington University in Saint Louis (WUSTL), Istituto di Ricerca Genetica e Biomedica (IRGB), Consiglio Nazionale delle Ricerche [Roma] (CNR), University Medical Center Groningen [Groningen] (UMCG), Universität Leipzig [Leipzig], Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Split, Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA), University of Eastern Finland, Harokopio University of Athens, European Academy Bozen/Bolzano (EURAC), University of Kuopio, German Center for Diabetes Research - Deutsches Zentrum für Diabetesforschung [Neuherberg] (DZD), University of Pittsburgh (PITT), Pennsylvania Commonwealth System of Higher Education (PCSHE), Ninewells Hospital and Medical School [Dundee], University College of London [London] (UCL), University of Essex, Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], University of Helsinki, Leiden University Medical Center (LUMC), Institute of Cardiovascular and Medical Sciences [Glasgow], University of Oulu, The University of Texas Health Science Center at Houston (UTHealth), University of Minnesota Medical School, University of Minnesota System, Keck School of Medicine [Los Angeles], University of Southern California (USC), Amsterdam UMC, University Hospital Carl Gustav Carus [Dresden, Germany], Technische Universität Dresden = Dresden University of Technology (TU Dresden), Lee Kong Chian School of Medicine, Nanyang Technological University (NTU), Universität Heidelberg [Heidelberg], King Abdulaziz University, Pirkanmaa Hospital District, Tampere University Hospital, Cedars-Sinai Medical Center, Danube University Krems, Harvard School of Public Health, Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Institute of Epidemiology [Neuherberg] (EPI), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Hannover Medical School [Hannover] (MHH), Universität zu Lübeck [Lübeck], University of Exeter, Regeneron Pharmaceuticals [Tarrytown], University of Adelaide, Centre de Recherche des Cordeliers (CRC (UMR_S 872)), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), National Institute on Aging [Bethesda, USA] (NIA), National Institutes of Health [Bethesda] (NIH), Icahn School of Medicine at Mount Sinai [New York] (MSSM), Harvard T.H. Chan School of Public Health, John Radcliffe Hospital [Oxford University Hospital], Centre Hospitalier Universitaire Vaudois [Lausanne] (CHUV), Université de Genève (UNIGE), Big Data Institute, University of Surrey (UNIS), University of Bergen (UiB), Stanford School of Medicine [Stanford], Stanford Medicine, Stanford University-Stanford University, Stanford Cardiovascular Institute, University of Liverpool, University of Manchester [Manchester], Institute of Biochemistry and Genetics of Ufa Scientific Centre, Russian Academy of Sciences [Moscow] (RAS), Experimental Vascular Medicine, Vascular Medicine, ACS - Atherosclerosis & ischemic syndromes, SIEST, Sofia, PreciDIAB Institute, the holistic approach of personal diabets care - - PreciDIAB2018 - ANR-18-IBHU-0001 - IBHU - VALID, Understanding the dynamic determinants of glucose homeostasis and social capability to promote Healthy and active aging - DYNAHEALTH - - H20202015-04-01 - 2019-03-31 - 633595 - VALID, Beyond the Genetics of Addiction - ADDICTION - - EC:FP7:ERC2011-12-01 - 2017-05-31 - 284167 - VALID, Rise of scientific excellence and collaboration for implementing personalised medicine in Estonia - ePerMed - - H20202016-01-01 - 2018-12-31 - 692145 - VALID, University of Oxford, Helmholtz Zentrum München = German Research Center for Environmental Health, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (EGENODIA (GI3M)), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Università degli Studi di Ferrara = University of Ferrara (UniFE), Université de Lausanne = University of Lausanne (UNIL), Karl-Franzens-Universität Graz, Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Amsterdam UMC - Amsterdam University Medical Center, Nanyang Technological University [Singapour], Universität zu Lübeck = University of Lübeck [Lübeck], Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Sorbonne Paris Nord, Université de Genève = University of Geneva (UNIGE), ANR-18-IBHU-0001,PreciDIAB,PreciDIAB Institute, the holistic approach of personal diabets care(2018), European Project: 633595,H2020,H2020-PHC-2014-two-stage,DYNAHEALTH(2015), European Project: 284167,EC:FP7:ERC,ERC-2011-StG_20101124,ADDICTION(2011), European Project: 692145,H2020,H2020-TWINN-2015,ePerMed(2016), Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Functional Genomics, APH - Mental Health, Sociology and Social Gerontology, APH - Methodology, Hottenga, Jouke- Jan [0000-0002-5668-2368], Bouatia-Naji, Nabila [0000-0001-5424-2134], Jansen, Rick [0000-0002-3333-6737], Min, Josine L. [0000-0003-4456-9824], Faggian, Alessia [0000-0002-3799-9722], Bonnefond, Amélie [0000-0001-9976-3005], Isaacs, Aaron [0000-0001-5037-4834], Willems, Sara M. [0000-0002-6803-3007], Navarro, Pau [0000-0001-5576-8584], Jackson, Anne U. [0000-0002-9672-2547], Bielak, Lawrence F. [0000-0002-3443-8030], Saxena, Richa [0000-0003-2233-1065], Smith, Albert V. [0000-0003-1942-5845], Verweij, Niek [0000-0002-4303-7685], Goel, Anuj [0000-0003-2307-4021], Johnson, Paul C. D. [0000-0001-6663-7520], Strawbridge, Rona J. [0000-0001-8506-3585], Fall, Tove [0000-0003-2071-5866], Fraser, Ross M. [0000-0003-0488-2592], Kanoni, Stavroula [0000-0002-1691-9615], Giedraitis, Vilmantas [0000-0003-3423-2021], Kleber, Marcus E. [0000-0003-0663-7275], Müller-Nurasyid, Martina [0000-0003-3793-5910], Luan, Jian’an [0000-0003-3137-6337], Sanna, Serena [0000-0002-3768-1749], Nolte, Ilja M. [0000-0001-5047-4077], Zemunik, Tatijana [0000-0001-8120-2891], Kovacs, Peter [0000-0002-0290-5423], Wild, Sarah H. [0000-0001-7824-2569], McLachlan, Stela [0000-0003-0480-6143], Egan, Josephine [0000-0002-8945-0053], Hicks, Andrew A. [0000-0001-6320-0411], Thorand, Barbara [0000-0002-8416-6440], Hingorani, Aroon [0000-0001-8365-0081], Kivimaki, Mika [0000-0002-4699-5627], Koistinen, Heikki A. [0000-0001-7870-070X], Bakker, Stephan J. L. [0000-0003-3356-6791], Palmer, Colin N. A. [0000-0002-6415-6560], Jukema, J. Wouter [0000-0002-3246-8359], Sattar, Naveed [0000-0002-1604-2593], Snieder, Harold [0000-0003-1949-2298], Magnusson, Patrik K. [0000-0002-7315-7899], Blüher, Matthias [0000-0003-0208-2065], Wolffenbuttel, Bruce H. R. [0000-0001-9262-6921], Abecasis, Goncalo R. [0000-0003-1509-1825], Meigs, James B. [0000-0002-2439-2657], Wilson, James F. [0000-0001-5751-9178], Schwarz, Peter E. H. [0000-0001-6317-7880], Boehm, Bernhard O. [0000-0002-2706-7710], Metspalu, Andres [0000-0002-3718-796X], Deloukas, Panos [0000-0001-9251-070X], Körner, Antje [0000-0001-6001-0356], Wareham, Nicholas J. [0000-0003-1422-2993], Langenberg, Claudia [0000-0002-5017-7344], Männistö, Satu [0000-0002-8668-3046], Franks, Paul W. [0000-0002-0520-7604], Hayward, Caroline [0000-0002-9405-9550], Vitart, Veronique [0000-0002-4991-3797], Kaprio, Jaakko [0000-0002-3716-2455], Visvikis-Siest, Sophie [0000-0001-8104-8425], Altshuler, David [0000-0002-7250-4107], Rudan, Igor [0000-0001-6993-6884], van Duijn, Cornelia M. [0000-0002-2374-9204], Pramstaller, Peter P. [0000-0002-9831-8302], Boehnke, Michael [0000-0002-6442-7754], Frayling, Timothy M. [0000-0001-8362-2603], Peyser, Patricia A. [0000-0002-9717-8459], Harst, Pim van der [0000-0002-2713-686X], Smith, George Davey [0000-0002-1407-8314], Forouhi, Nita G. [0000-0002-5041-248X], Loos, Ruth J. F. [0000-0002-8532-5087], Salomaa, Veikko [0000-0001-7563-5324], Soranzo, Nicole [0000-0003-1095-3852], Boomsma, Dorret I. [0000-0002-7099-7972], Groop, Leif [0000-0002-0187-3263], Tuomi, Tiinamaija [0000-0002-8306-6202], Munroe, Patricia B. [0000-0002-4176-2947], Gudnason, Vilmundur [0000-0001-5696-0084], Lecoeur, Cecile [0000-0003-0075-6417], Jarvelin, Marjo-Riitta [0000-0002-2149-0630], Stefansson, Kari [0000-0003-1676-864X], Dermitzakis, Emmanouil T. [0000-0002-9302-6490], Lindgren, Cecilia M. [0000-0002-4903-9374], Froguel, Philippe [0000-0003-2972-0784], Kaakinen, Marika A. [0000-0002-9228-0462], Watanabe, Richard M. [0000-0003-1015-0531], Ingelsson, Erik [0000-0003-2256-6972], Dupuis, Josée [0000-0003-2871-3603], Barroso, Inês [0000-0001-5800-4520], Apollo - University of Cambridge Repository, Epidemiology, University Hospital Mannheim | Universitätsmedizin Mannheim, National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Universität Leipzig, Universiteit Leiden, Universität Heidelberg [Heidelberg] = Heidelberg University, Karl-Franzens-Universität [Graz, Autriche], Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, General practice, APH - Digital Health, Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Life Course Epidemiology (LCE), Lifestyle Medicine (LM), Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Center for Liver, Digestive and Metabolic Diseases (CLDM), Value, Affordability and Sustainability (VALUE), Cardiovascular Centre (CVC), Hottenga, Jouke-Jan [0000-0002-5668-2368], Min, Josine L [0000-0003-4456-9824], Willems, Sara M [0000-0002-6803-3007], Jackson, Anne U [0000-0002-9672-2547], Bielak, Lawrence F [0000-0002-3443-8030], Smith, Albert V [0000-0003-1942-5845], Johnson, Paul CD [0000-0001-6663-7520], Strawbridge, Rona J [0000-0001-8506-3585], Fraser, Ross M [0000-0003-0488-2592], Kleber, Marcus E [0000-0003-0663-7275], Luan, Jian'an [0000-0003-3137-6337], Nolte, Ilja M [0000-0001-5047-4077], Wild, Sarah H [0000-0001-7824-2569], Hicks, Andrew A [0000-0001-6320-0411], Koistinen, Heikki A [0000-0001-7870-070X], Bakker, Stephan JL [0000-0003-3356-6791], Palmer, Colin NA [0000-0002-6415-6560], Jukema, J Wouter [0000-0002-3246-8359], Magnusson, Patrik K [0000-0002-7315-7899], Wolffenbuttel, Bruce HR [0000-0001-9262-6921], Abecasis, Goncalo R [0000-0003-1509-1825], Meigs, James B [0000-0002-2439-2657], Wilson, James F [0000-0001-5751-9178], Schwarz, Peter EH [0000-0001-6317-7880], Boehm, Bernhard O [0000-0002-2706-7710], Wareham, Nicholas J [0000-0003-1422-2993], Franks, Paul W [0000-0002-0520-7604], van Duijn, Cornelia M [0000-0002-2374-9204], Pramstaller, Peter P [0000-0002-9831-8302], Frayling, Timothy M [0000-0001-8362-2603], Peyser, Patricia A [0000-0002-9717-8459], Forouhi, Nita G [0000-0002-5041-248X], Loos, Ruth JF [0000-0002-8532-5087], Boomsma, Dorret I [0000-0002-7099-7972], Munroe, Patricia B [0000-0002-4176-2947], Dermitzakis, Emmanouil T [0000-0002-9302-6490], Lindgren, Cecilia M [0000-0002-4903-9374], Kaakinen, Marika A [0000-0002-9228-0462], Watanabe, Richard M [0000-0003-1015-0531], Tampere University, Tays Research Services, Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), Fysiologie, RS: FHML MaCSBio, and RS: Carim - B01 Blood proteins & engineering

Subjects
Male, Anorexia Nervosa, medicine.medical_treatment, 45/43, Insulin Resistance/genetics, SUSCEPTIBILITY, Quantitative trait, Impaired glucose tolerance, 0302 clinical medicine, Architecture, LS2_1, IMPUTATION, Insulin, ComputingMilieux_MISCELLANEOUS, Fasting, Publisher Correction, 3. Good health, [SDV] Life Sciences [q-bio], Kruppel-Like Transcription Factors/blood, Endokrinologi och diabetes, Science & Technology - Other Topics, Adult, Blood Glucose, European Continental Ancestry Group, Female, Gene Expression, Genetic Loci, Genome-Wide Association Study, Glucose Intolerance, Humans, Insulin Receptor Substrate Proteins, Insulin Resistance, Kruppel-Like Transcription Factors, Middle Aged, Phenotype, Sex Characteristics, Sex Factors, Waist-Hip Ratio, Sex characteristics, medicine.medical_specialty, Science, 631/208/205/2138, Endocrinology and Diabetes, General Biochemistry, Genetics and Molecular Biology, White People, Gender-differences, 03 medical and health sciences, SDG 3 - Good Health and Well-being, 692/53/2421, GLYCEMIC TRAITS, GENOME-WIDE ASSOCIATION, Glycemic, GENDER-DIFFERENCES, Science & Technology, IDENTIFICATION, 692/699/2743/2815, Blood Glucose/metabolism, Diagnostic markers, medicine.disease, Anorexia Nervosa/blood, 030104 developmental biology, Endocrinology, Glucose, Insulin/blood, Anorexia Nervosa/ethnology, Anorexia Nervosa/genetics, Anorexia Nervosa/physiopathology, Fasting/blood, Glucose Intolerance/blood, Glucose Intolerance/ethnology, Glucose Intolerance/genetics, Glucose Intolerance/physiopathology, Insulin Receptor Substrate Proteins/blood, Insulin Receptor Substrate Proteins/genetics, Kruppel-Like Transcription Factors/genetics, 0301 basic medicine, Identification, [SDV]Life Sciences [q-bio], General Physics and Astronomy, Genome-wide association studies, Waist–hip ratio, LS4_5, RISK, ARCHITECTURE, Multidisciplinary, article, Type 2 diabetes, Multidisciplinary Sciences, MENDELIAN RANDOMIZATION, Pre-diabetes, Medical Genetics, Risk, PATHOPHYSIOLOGY, 030209 endocrinology & metabolism, 3121 Internal medicine, 692/163/2743/137/773, NO, Insulin resistance, Internal medicine, Diabetes mellitus, medicine, Mendelian randomization, 631/208/480, Medicinsk genetik, business.industry, General Chemistry, Impaired fasting glucose, business
Abstract

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes., Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

Published
2021

11. Genome‐Wide Association Study Identifies Loci for Liver Enzyme Concentrations in Mexican Americans: The GUARDIAN Consortium

Author

Lynne E. Wagenknecht, Tasha E. Fingerlin, Carl D. Langefeld, Richard M. Watanabe, Mark O. Goodarzi, Jill M. Norris, Kendra A. Young, Xiuqing Guo, Leslie J. Raffel, Jerome I. Rotter, Kent D. Taylor, Anny H. Xiang, Adrienne H. Williams, Yii-Der Ida Chen, Nicholette D. Palmer, and Nan Wang

Subjects
Adult, Male, alanine aminotransferase, Endocrinology, Diabetes and Metabolism, Medicine (miscellaneous), 030209 endocrinology & metabolism, Single-nucleotide polymorphism, Genome-wide association study, Locus (genetics), Biology, digestive system, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, aspartate aminotransferase, Non-alcoholic Fatty Liver Disease, Mexican Americans, Genetic model, Nonalcoholic fatty liver disease, medicine, Humans, SNP, Aspartate Aminotransferases, 030212 general & internal medicine, Genetics, Nutrition and Dietetics, Mexican-American ancestry, Fatty liver, Membrane Proteins, Alanine Transaminase, Lipase, gamma-Glutamyltransferase, Middle Aged, medicine.disease, digestive system diseases, Liver, Genetic Loci, Linear Models, Female, gamma-glutamyl transferase, genetic variance, Liver function, Genome-Wide Association Study
Abstract

Author(s): Young, Kendra A; Palmer, Nicholette D; Fingerlin, Tasha E; Langefeld, Carl D; Norris, Jill M; Wang, Nan; Xiang, Anny H; Guo, Xiuqing; Williams, Adrienne H; Chen, Yii-Der I; Taylor, Kent D; Rotter, Jerome I; Raffel, Leslie J; Goodarzi, Mark O; Watanabe, Richard M; Wagenknecht, Lynne E | Abstract: ObjectivePopulations of Mexican American ancestry are at an increased risk for nonalcoholic fatty liver disease. The objective of this study was to determine whether loci in known and novel genes were associated with variation in aspartate aminotransferase (AST) (n = 3,644), alanine aminotransferase (ALT) (n = 3,595), and gamma-glutamyl transferase (GGT) (n = 1,577) levels by conducting the first genome-wide association study (GWAS) of liver enzymes, which commonly measure liver function, in individuals of Mexican American ancestry.MethodsLevels of AST, ALT, and GGT were determined by enzymatic colorimetric assays. A multi-cohort GWAS of individuals of Mexican American ancestry was performed. Single-nucleotide polymorphisms (SNP) were tested for association with liver outcomes by multivariable linear regression using an additive genetic model. Association analyses were conducted separately in each cohort, followed by a nonparametric meta-analysis.ResultsIn the PNPLA3 gene, rs4823173 (P = 3.44 × 10-10 ), rs2896019 (P = 7.29 × 10-9 ), and rs2281135 (P = 8.73 × 10-9 ) were significantly associated with AST levels. Although not genome-wide significant, these same SNPs were the top hits for ALT (P = 7.12 × 10-8 , P = 1.98 × 10-7 , and P = 1.81 × 10-7 , respectively). The strong correlation (r2 = 1.0) for these SNPs indicated a single hit in the PNPLA3 gene. No genome-wide significant associations were found for GGT.ConclusionsPNPLA3, a locus previously identified with ALT, AST, and nonalcoholic fatty liver disease in European and Japanese GWAS, is also associated with liver enzymes in populations of Mexican American ancestry.

Published
2019

12. The trans-ancestral genomic architecture of glycemic traits

Author

Albertine J. Oldehinkel, Wieland Kiess, Xueling Sim, Norihiro Kato, Philippe Froguel, Astrid van Hylckama Vlieg, Josée Dupuis, Nanette R. Lee, Symen Ligthart, Harry Campbell, Marta E. Alarcón-Riquelme, P. Eline Slagboom, Massimo Mangino, Tian Xie, Niek Verweij, James B. Meigs, Chaolong Wang, Michael Y. Tsai, Erik Ingelsson, Colin N. A. Palmer, Erik B. van den Akker, Fumihiko Matsuda, Rainer Rauramaa, Yi-Cheng Chang, Lars Lind, Stefan R. Bornstein, Mandy Vogel, Sven Bergmann, Ya X. Wang, Ching-Ti Liu, Annette Schürmann, Michael Boehnke, David J. Porteous, Kazuya Setoh, Qibin Qi, Ayse Demirkan, Francesco Cucca, Allan Linneberg, Claire J. Steves, Jun Liu, Leslie A. Lange, Noël P. Burtt, Diana Kuh, Cassandra N. Spracklen, Ken K. Ong, Charumathi Sabanayagam, Jost B. Jonas, Ele Ferrannini, Lawrence J. Beilin, Qing Duan, Blair H. Smith, Isobel D. Stewart, Alexander P. Reiner, Simon P. Mooijaart, Tim D. Spector, Paul W. Franks, E. Shyong Tai, Mark I. McCarthy, Anna L. Gloyn, D.I. Boomsma, Dennis Raven, Nicholas J. Timpson, Rona J. Strawbridge, George Dedoussis, Susan Redline, Jaeyoung Hong, Harald Grallert, Jagadish Vangipurapu, Rico Rueedi, Diane M. Becker, Marian Beekman, Claudia P. Cabrera, Johannes Waage, Jin Fang Chai, Yii-Der Ida Chen, Graciela E. Delgado, Thibaud S. Boutin, Yang Hai, Yoriko Heianza, Wei Zhao, Andres Metspalu, Tien Yin Wong, Mila Desi Anasanti, Inger Njølstad, Hans Bisgaard, Valeriya Lyssenko, Denis Rybin, Wanqing Wen, Torben Hansen, James F. Wilson, Sameline Grimsgaard, Annette Peters, Michele K. Evans, Damia Noce, Sarah C. Nelson, May E. Montasser, Nan Wang, Geltrude Mingrone, Gudny Eiriksdottir, Nicholas J. Wareham, Fouad Kandeel, Linda S. Adair, Kelvin Lam, Jaana Lindström, Eco J. C. de Geus, Debbie A Lawlor, Sara M. Willems, Xu Lin, Harold Snieder, Matt J. Neville, Naveed Sattar, Chelsea K. Raulerson, Paul M. Ridker, Jer-Yuarn Wu, Weihua Zhang, H. Janaka de Silva, Jana V. van Vliet-Ostaptchouk, Elena Tremoli, Toru Nabika, Jing Hua Zhao, Vilmundur Gudnason, Tao Huang, Robert C. Kaplan, Sohee Han, Mohammad Hadi Zafarmand, Aaron Leong, Yen-Feng Chiu, Kumaraswamy Naidu Chitrala, Ivana Kolcic, Franco Giulianini, Tao Wang, Lu Qi, Stephan J. L. Bakker, Laura J Corbin, Zoltán Kutalik, Bruna Gigante, Willa A. Hsueh, Peter J. van der Most, Tin Louie, Yujie Wang, Stella Trompet, Fernando Rivideneira, Yasumasa Ohyagi, Lynne E. Wagenknecht, Jerry L. Nadler, Michael Stumvoll, Mark O. Goodarzi, Sahoko Ichihara, Jeffrey R. O'Connell, Tomohiro Katsuya, Giorgio Pistis, Alice Stanton, Sirkka Keinänen-Kiukaanniemi, Momoko Horikoshi, Honglan Li, Tanja G. M. Vrijkotte, Caroline Hayward, Karen L. Mohlke, Carola Marzi, Girish N. Nadkarni, Laura J. Rasmussen-Torvik, Alain G. Bertoni, Andrew R. Wood, Annique Claringbould, Mi Yeong Hwang, Hugh Watkins, Heikki A. Koistinen, Mattias Frånberg, Jani Heikkinen, Elizabeth Selvin, Donald W. Bowden, Abbas Dehghan, Christian Fuchsberger, Audrey Y. Chu, Kent D. Taylor, Katherine A. Kentistou, Johanna Kuusisto, Jingyi Tan, Huaixing Li, Eric Boerwinkle, Catharina A. Hartman, Archie Campbell, Kari E. North, Oluf Pedersen, Sölve Elmståhl, Emil V. R. Appel, Chang-Hsun Hsieh, Dennis O. Mook-Kanamori, Rob M. van Dam, Pontiano Kaleebu, Corri Black, Jennifer A. Brody, Bengt Sennblad, Shaofeng Huo, M. Larissa Avilés-Santa, Ruth J. F. Loos, Patricia B. Munroe, Chien-Hsiun Chen, Liang Sun, Zorayr Arzumanyan, Rebecca Rohde, Yasuharu Tabara, Albert V. Smith, Betina H. Thuesen, Niels Grarup, Jorgen Engmann, Tatijana Zemunik, M. Arfan Ikram, Marit E. Jørgensen, Christian Herder, Ching-Yu Cheng, Serena Sanna, Damiano Baldassarre, Tarunveer S. Ahluwalia, Mark J. Caulfield, Anne Ndungu, Carl D. Langefeld, Lisa R. Yanek, Luigi Ferrucci, Ananda R. Wickremasinghe, Raymond Noordam, Trevor A. Mori, Tom Wilsgaard, Mika Kivimäki, Rita R. Kalyani, Alan B. Zonderman, Veronique Vitart, Patricia A. Peyser, Shuiqing Lai, Richa Saxena, Li-Ching Chang, Karin Leander, Wei Huang, Peter Vollenweider, Tanya M. Teslovich, Ying Wu, Shufa Du, Brian E. Cade, Patrik K. E. Magnusson, John C. Chambers, Stephen C. J. Parker, Tamar Sofer, Winfried März, Sharon L.R. Kardia, Peter K. Joshi, Neil R. Robertson, Anny H. Xiang, Fumihiko Takeuchi, N. Amin, Jouke-Jan Hottenga, Carol A. Wang, Stefan Gustafsson, Jung Ho Gong, Penny Gordon-Larsen, Yu-Tang Gao, Abhishek Nag, Gonneke Willemsen, Michael A. Province, Aliki-Eleni Farmaki, Segun Fatumo, Antje Körner, Pim van der Harst, Marie Loh, Kei Hang Katie Chan, Gonçalo R. Abecasis, Nicholette D. Palmer, Simin Liu, Ishminder K. Kooner, Javier Gayán, Arne Astrup, Laura J. Scott, Erwin P. Bottinger, Andrew Wong, Inga Prokopenko, Ping An, Markku Laakso, Matthias Blüher, Susan R. Heckbert, Thomas A. Buchanan, Tatsuaki Matsubara, Andrew P. Morris, Brian H. Chen, Kristi Läll, Teresa Tusie, Timo A. Lakka, Jie Yao, Michael Preuss, Teemu Kuulasmaa, Carlos Lorenzo, Stephen S. Rich, Marie Lauzon, Laura M. Raffield, Pankow S. James, Takahisa Kawaguchi, Kathleen A. Ryan, Wei Zheng, Igor Rudan, Thomas Sparsø, Hugoline G. de Haan, Sandosh Padmanabhan, Richard M. Watanabe, Alicia Huerta-Chagoya, Anette P. Gjesing, Andrew A. Hicks, Richard N. Bergman, Mitsuhiro Yokota, Heather M. Stringham, Bruce M. Psaty, Jian'an Luan, Anuj Goel, Eleanor Wheeler, Masahiro Nakatochi, Young-Jin Kim, Xiao-Ou Shu, Mickaël Canouil, Robert A. Scott, Marika Kaakinen, Mari Nelis, Adolfo Correa, Jaspal S. Kooner, Michiya Igase, Anubha Mahajan, Peter E. H. Schwarz, Craig E. Pennell, Claudia Schurmann, Xiaoran Chai, Ji Chen, Lori L. Bonnycastle, Peter S. Sever, Thorkild I. A. Sørensen, André G. Uitterlinden, Ilja M. Nolte, Gaëlle Marenne, Timothy M. Frayling, Bong-Jo Kim, Kerrin S. Small, Cecilia M. Lindgren, Bernhard O. Böhm, Shih-Yi Lin, Katharina E. Schraut, Cornelia M. van Duijn, Sanghoon Moon, Mark Walker, Chiea Chuen Khor, Ruifang Li-Gao, Qiuyin Cai, Neil Schneiderman, Ko Willems van Dijk, Ozren Polasek, W. Craig Johnson, Dermot F. Reilly, Inês Barroso, Anke Tönjes, Manjinder S. Sandhu, Wen B. Wei, Jose C. Florez, Lorraine Southam, Leif Groop, Lawrence F. Bielak, Peter Kovacs, Jianjun Liu, Jouko Saramies, Helen R. Warren, Man Li, Daniel I. Chasman, Eleftheria Zeggini, Xiaoshuai Zhang, Loic Yengo, Shi Jinxiu, Jirong Long, Xiuqing Guo, Meena Kumari, Leslie J. Raffel, Jill M. Norris, Henrik Vestergaard, Jing He, Peter P. Pramstaller, Diana van Heemst, Kevin Sandow, Marjo-Ritta Jarvelin, Carlos A. Aguilar-Salinas, Peitao Wu, Hortensia Moreno-Macías, Jerome I. Rotter, Kathryn Roll, Frits R. Rosendaal, Bernardo L. Horta, Heming Wang, Fernando Pires Hartwig, Richard A. Jensen, Matti Uusitupa, Rozenn N. Lemaitre, Paul R. H. J. Timmers, Timo Saaristo, Jaakko Tuomilehto, Reedik Mägi, Debashree Ray, J. Wouter Jukema, Claudia Langenberg, Marcus E. Kleber, Francis S. Collins, Klaus Bønnelykke, Lenore J. Launer, Arushi Varshney, Anders Hamsten, European Commission, Génétique, génomique fonctionnelle et biotechnologies (UMR 1078) (GGB), Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-EFS-Institut National de la Santé et de la Recherche Médicale (INSERM), Sanger Institute, Wellcome Trust, Marenne, Gaëlle [0000-0002-4363-7170], Varshney, Arushi [0000-0001-9177-9707], Corbin, Laura J [0000-0002-4032-9500], Parker, Stephen CJ [0000-0001-8122-0117], Langenberg, Claudia [0000-0002-5017-7344], Wheeler, Eleanor [0000-0002-8616-6444], Morris, Andrew P [0000-0002-6805-6014], Barroso, Inês [0000-0001-5800-4520], Apollo - University of Cambridge Repository, Lifelines Cohort Study, Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC), de Haan, H.G., van den Akker, E., van der Most, P.J., de Geus, EJC, van Dam, R.M., van Heemst, D., van Hylckama Vlieg, A., van Willems van Dijk, K., de Silva, H.J., van der Harst, P., van Duijn, C., Centre of Excellence in Complex Disease Genetics, HUS Abdominal Center, Institute for Molecular Medicine Finland, Leif Groop Research Group, HUS Internal Medicine and Rehabilitation, Department of Medicine, Department of Biochemistry and Developmental Biology, Helsinki University Hospital Area, University of Helsinki, Clinicum, Department of Public Health, Biological Psychology, APH - Health Behaviors & Chronic Diseases, APH - Personalized Medicine, Physiology, AMS - Musculoskeletal Health, AMS - Tissue Function & Regeneration, APH - Mental Health, Nutrition and Health, APH - Methodology, Epidemiology and Data Science, ACS - Atherosclerosis & ischemic syndromes, APH - Aging & Later Life, ARD - Amsterdam Reproduction and Development, Public and occupational health, Epidemiology, Internal Medicine, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Institute for Organ Transplantation (GIOT), Groningen Kidney Center (GKC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Center for Liver, Digestive and Metabolic Diseases (CLDM), and Cardiovascular Centre (CVC)

Subjects
Blood Glucose, Disease risk, Multifactorial Inheritance, Glycated Hemoglobin A, [SDV]Life Sciences [q-bio], Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC), LOCI, Genome-wide association study, Type 2 diabetes, VARIANTS, GLUCOSE, Epigenesis, Genetic, chemistry.chemical_compound, 0302 clinical medicine, Mechanisms, WIDE ASSOCIATION, genetics, Gene-expression, HEMOGLOBIN, ComputingMilieux_MISCELLANEOUS, 11 Medical and Health Sciences, GENE-EXPRESSION, Genetics, Genetics & Heredity, 0303 health sciences, INSULIN-RESISTANCE, Genome, Loci, 1184 Genetics, developmental biology, physiology, Variants, ALSPAC, Physical Chromosome Mapping, Life Sciences & Biomedicine, Human, Quantitative Trait Loci, Wide association study, Biology, Quantitative trait locus, Article, White People, diseases, MECHANISMS, Quantitative Trait, 03 medical and health sciences, Insulin resistance, Quantitative Trait, Heritable, SDG 3 - Good Health and Well-being, Genetic, Lifelines Cohort Study, Diabetes mellitus, medicine, Humans, Hemoglobin, Heritable, METAANALYSIS, Alleles, 030304 developmental biology, Genetic association, Glycemic, Glycated Hemoglobin, Science & Technology, Genome, Human, Whites, Gene Expression Profiling, DISEASE RISK, Settore MED/13 - ENDOCRINOLOGIA, Insulin-resistance, 06 Biological Sciences, medicine.disease, Glucose, chemistry, Blood Glucose/genetics, European Continental Ancestry Group/genetics, Genome-Wide Association Study, Glycated Hemoglobin A/metabolism, Multifactorial Inheritance/genetics, Quantitative Trait Loci/genetics, Glycated hemoglobin, 030217 neurology & neurosurgery, Meta analysis, Epigenesis, Developmental Biology
Abstract

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

Published
2021

13. Publisher Correction: Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability

Author

Stavroula Kanoni, Bakker Sjl., Winkelmann Br, Wieland Kiess, Josée Dupuis, Palmer Cna., James F. Wilson, Schwarz Peh., Maria Dimitriou, Joop Jukema, Sara M. Willems, J L Min, R. Rauramaa, Perry Jrb., Momoko Horikoshi, Timo A. Lakka, Nicole Soranzo, J Kaprio, Niek Verweij, Martina Müller-Nurasyid, Jaana Lindström, Toby Johnson, Olga D. Carlson, Nita G. Forouhi, George Dedoussis, Johnson Pcd., Patrick K.E. Magnusson, Gonçalo R. Abecasis, Ozren Polasek, Wolffenbuttel Bhr., M. I. J. Uusitupa, Longda Jiang, Nancy L. Pedersen, Beate St Pourcain, Erik P A Van Iperen, Iva Miljkovic, Stefania Bandinelli, M. A. Province, Veikko Salomaa, Andrew A. Hicks, Evelin Mihailov, Rick Jansen, James B. Meigs, D Rybin, Peter Kovacs, George Davey Smith, Rona J. Strawbridge, Gudmar Thorleifsson, Meena Kumari, Chiara Scapoli, Christopher J. Groves, Barbara Thorand, T.B. Harris, Ulf de Faire, Inga Prokopenko, Stela McLachlan, Ping An, Anubha Mahajan, L.F. Bielak, Rebecca J. Webster, David Altshuler, Susan Campbell, Bernhard O. Boehm, A. Metspalu, Perttu Salo, D.I. Boomsma, Ilja M. Nolte, Andrea Ganna, Timothy M. Frayling, Pau Navarro, N J Timpson, Kardia Slr., Jeanette M. Stafford, Tõnu Esko, Ulrika Krus, Richa Saxena, Per Eriksson, Peter P. Pramstaller, Anne U. Jackson, V Lagou, Anders Franco-Cereceda, David S. Siscovick, Josephine M. Egan, Loos Rjf., C Gieger, Amanda J. Bennett, Anna Ulrich, Satu Männistö, Mika Kivimäki, Loic Yengo, Caroline Hayward, George Nicholson, C M van Duijn, Anke Tönjes, Nigel W. Rayner, Jose C. Florez, Leif Groop, Valeri Lyssenko, Lyle J. Palmer, Vilmantas Giedraitis, Maria G. Stathopoulou, B. Balkau, Anneli Pouta, Anuj Goel, Pierre Meneton, Serena Sanna, Jesper R. Gådin, Claudia Langenberg, Alessia Faggian, H Grallert, Karen Kapur, Marcus E. Kleber, Philippe Froguel, Boehnke M, Harry Campbell, Anders Hamsten, T. Saaristo, Antigone S. Dimas, Jarvelin M-R., F Karpe, A. Körner, Leena Kinnunen, Markus Perola, Joanne M. Meyer, May E. Montasser, Erik Ingelsson, Naveed Sattar, Yvonne Boettcher, Sirkka Keinänen-Kiukaanniemi, Aaron Isaacs, Gerjan Navis, Ian Ford, Amélie Bonnefond, Reedik Mägi, Tove Fall, Dmitry Shungin, Jenna Price, Igor Rudan, Richard M. Watanabe, Luigi Ferrucci, Jian'an Luan, Harst Pvd., Marika Kaakinen, Tatijana Zemunik, Christian Herder, Shin S-Y., Veronique Vitart, Ross M. Fraser, Alan R. Shuldiner, Panagiotis Deloukas, C. Lecoeur, Letizia Marullo, Kari Stefansson, Lars Lind, Winfried März, L Zudina, Aroon D. Hingorani, Gonneke Willemsen, de Geus Ejcn., Albert V. Smith, Jeffery R. O'Connell, Yongmei Liu, James S. Pankow, Sarah H. Wild, Patricia B. Munroe, Patricia A. Peyser, Nicholas J. Wareham, Tiinamaija Tuomi, Nicholas D. Hastie, Markku Laakso, Albert Hofman, J. Tuomilehto, Emmanouil T. Dermitzakis, Thomas Illig, Tomohiro Tanaka, Cecilia M. Lindgren, Sarin A-P., Alex S. F. Doney, Najaf Amin, Hugh Watkins, Johanna Kuusisto, Andrew P. Morris, Richard N. Bergman, Mark I. McCarthy, Nabila Bouatia-Naji, Günther Silbernagel, João Fadista, Harold Snieder, Ins Barroso, Michael Stumvoll, B.W.J.H. Penninx, M Blüher, Stefan R Bornstein, Laura J. Rasmussen-Torvik, Alan F. Wright, Peter Vollenweider, G K Hovingh, Heikki A. Koistinen, Sophie Visvikis-Siest, Vilmundur Gudnason, Eric Boerwinkle, Hottenga J-J., Guo Li, Paul W. Franks, Université de Lille, Centre de recherche en épidémiologie et santé des populations (CESP), and Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay

Subjects
Genetics, Multidisciplinary, Science, Insulin, medicine.medical_treatment, General Physics and Astronomy, Diagnostic marker, Genome-wide association study, General Chemistry, Type 2 diabetes, Quantitative trait locus, Biology, medicine.disease, GeneralLiterature_MISCELLANEOUS, General Biochemistry, Genetics and Molecular Biology, Fasting glucose, Sexual dimorphism, Pre diabetes, [SDU]Sciences of the Universe [physics], ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, medicine
Abstract

The original version of this Article contained an error in Fig. 2, in which panels a and b were inadvertently swapped. This has now been corrected in the PDF and HTML versions of the Article.

Published
2021

14. Insulin Action, Glucose Homeostasis and Free Fatty Acid Metabolism: Insights From a Novel Model

Author

Darko Stefanovski, Raymond C. Boston, Richard M. Watanabe, and Naresh M. Punjabi

Subjects
0301 basic medicine, Adult, Blood Glucose, 030213 general clinical medicine, medicine.medical_specialty, free fatty acids (FFA), Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Lipolysis, Adipose tissue, Type 2 diabetes, Carbohydrate metabolism, Fatty Acids, Nonesterified, Diseases of the endocrine glands. Clinical endocrinology, Body Mass Index, 03 medical and health sciences, chemistry.chemical_compound, Young Adult, 0302 clinical medicine, Insulin resistance, Endocrinology, Internal medicine, Insulin Secretion, medicine, Glucose homeostasis, Homeostasis, Humans, Insulin, insulin action, Original Research, Fatty acid metabolism, Correction, Models, Theoretical, RC648-665, medicine.disease, 030104 developmental biology, Glucose, chemistry, Adipose Tissue, lipids (amino acids, peptides, and proteins), Insulin Resistance, FFA metabolism
Abstract

Glucose and free fatty acids (FFA) are essential nutrients that are both partly regulated by insulin. Impaired insulin secretion and insulin resistance are hallmarks of aberrant glucose disposal, and type 2 diabetes (T2DM). In the current study, a novel model of FFA kinetics is proposed to estimate the role insulin action on FFA lipolysis and oxidation allowing estimation of adipose tissue insulin sensitivity (SIFFA). Twenty-five normal volunteers were recruited for the current study. To participate, volunteers had to be less than 40 years of age and have a body mass index (BMI) < 30 kg/m2, and be free of medical comorbidity. The proposed model of FFA kinetics was used to analyze the data derived from the insulin-modified FSIGT. Mean fractional standard deviations of the parameter estimates were all less than 20%. Standardized residuals of the fit of the model to the FFA temporal data were randomly distributed, with only one estimated point lying outside the 2-standard deviation range, suggesting an acceptable fit of the model to the FFA data. The current study describes a novel one-compartment non-linear model of FFA kinetics during an FSIGT that provides an FFA metabolism insulin sensitivity parameter (SIFFA). Furthermore, the models suggest a new role of glucose as the modulator of FFA disposal. Estimates of SIFFA confirmed previous findings that FFA metabolism is more sensitive to changes in insulin than glucose metabolism. Novel derived indices of insulin sensitivity of FFA (SIFFA) were correlated with minimal model indices. These associations suggest a cooperative rather than competitive interplay between the two primary nutrients (glucose and FFA) and allude to the FFA acting as the buffer, such that glucose homeostasis is maintained.

Published
2020

15. The Trans-Ancestral Genomic Architecture of Glycaemic Traits

Author

Hugoline G. de Haan, Andrew A. Hicks, Achilleas Pitsilides, Fernando Pires Hartwig, Richard A. Jensen, Matti Uusitupa, Anders Hamsten, Dennis O. Mook-Kanamori, Zorayr Arzumanyan, Betina H. Thuesen, Karin Leander, Fernando Rivideneira, Lynne E. Wagenknecht, Andrew R. Wood, Annique Claringbould, Ele Ferranni, Sölve Elmståhl, Eleanor Wheeler, Sharon L.R. Kardia, Richa Saxena, Tatijana Zemunik, Cassandra N. Spracklen, Ken K. Ong, Xiao-Ou Shu, Johannes Waage, Blair H. Smith, Rozenn N. Lemaitre, Torben Hansen, Peter K. Joshi, Lisa R. Yanek, Neil R. Robertson, Sven Bergmann, Mila Desi Anasanti, Inger Njølstad, Ananda R. Wickremasinghe, Xu Lin, Harold Snieder, Wanqing Wen, Veronique Vitart, Paul R. H. J. Timmers, Timo Saaristo, James F. Wilson, Tian Xie, Tao Huang, Rainer Rauramaa, Kei Hang, Rebecca Rohde, Li-Ching Chang, Jing Hua Zhao, Kazuya Setoh, Yasuharu Tabara, Michael Stumvoll, Mark O. Goodarzi, Igor Rudan, James B. Meigs, Jaakko Tuomilehto, Richard M. Watanabe, Ruth J. F. Loos, Reedik Mägi, Jouke-Jan Hottenga, Ozren Polasek, Michael Y. Tsai, Donald W. Bowden, Diana Kuh, Erik B. van den Akker, Yii-Der Ida Chen, Daniel I. Chasman, Weihua Zhang, Nicholette D. Palmer, Marcus E. Kleber, Anny H. Xiang, Chang-Hsun Hsieh, Alan B. Zonderman, Stefan Gustafsson, Timo A. Lakka, Brian H. Chen, Dermot F. Reilly, Francis S. Collins, Oluf Pedersen, Corri Black, Yang Hai, Zoltán Kutalik, Yoriko Heianza, Willa A. Hsueh, Vilmundur Gudnason, Robert C. Kaplan, Jun Liu, Michael A. Province, Aliki-Eleni Farmaki, Stephen S. Rich, Jian'an Luan, Erik Ingelsson, Marie Loh, Michael Preuss, Lars Lind, Stefan R. Bornstein, Mandy Vogel, Colin N. A. Palmer, Fumihiko Matsuda, Takahisa Kawaguchi, Sohee Han, Ching-Ti Liu, Young-Jin Kim, L. Southam, Sara M. Willems, Mickaël Canouil, Robert A. Scott, Marika Kaakinen, Stephan J. L. Bakker, Momoko Horikoshi, Tarunveer S. Ahluwalia, Annette Schürmann, Graciela E. Delgado, Thibaud S. Boutin, Thomas Sparsø, Sandosh Padmanabhan, Fouad Kandeel, Eco J. C. de Geus, Anubha Mahajan, Claudia Schurmann, Klaus Bønnelykke, Leslie A. Lange, Qing Duan, Rona J. Strawbridge, Dennis Raven, Gonçalo R. Abecasis, Mitsuhiro Yokota, Jani Heikkinen, Elizabeth Selvin, Audrey Y. Chu, Anke Tönjes, Marta E. Alarcón-Riquelme, Hans Bisgaard, P. Eline Slagboom, Eric Boerwinkle, Massimo Mangino, Catharina A. Hartman, Geltrude Mingrone, Lenore J. Launer, Michael Boehnke, Emil V. R. Appel, Niels Grarup, Arushi Varshney, Archie Campbell, Kari E. North, W. Craig Johnson, Inês Barroso, Ya X. Wang, Carola Marzi, Anuj Goel, Eleftheria Zeggini, Lu Qi, Yasumasa Ohyagi, Tien Yin Wong, Tanja G. M. Vrijkotte, Gudny Eiriksdottir, Harald Grallert, Ishminder K. Kooner, Trevor A. Mori, Jagadish Vangipurapu, Laura J Corbin, Tomohiro Katsuya, Wen B. Wei, Segun Fatumo, Debashree Ray, Annette Peters, Lori L. Bonnycastle, Ilja M. Nolte, M. Arfan Ikram, Manjinder S. Sandhu, Marit E. Jørgensen, Christian Herder, Damia Noce, Sarah C. Nelson, Chien-Hsiun Chen, Heather M. Stringham, Yong-Bing Xiang, Bruce M. Psaty, Alain G. Bertoni, Gaëlle Marenne, Timothy M. Frayling, Jose C. Florez, Penny Gordon-Larsen, Yu-Tang Gao, Abhishek Nag, Damiano Baldassarre, J. Wouter Jukema, Wei Huang, Yi-Cheng Chang, Albertine J. Oldehinkel, Xiaoshuai Zhang, Yujie Wang, Shaofeng Huo, Xueling Sim, Norihiro Kato, Bernhard O. Böhm, Lorraine Southam, Mari Nelis, Gonneke Willemsen, Laura J. Rasmussen-Torvik, Philippe Froguel, Charumathi Sabanayagam, Leif Groop, Loic Yengo, Shi Jinxiu, Adolfo Correa, Serena Sanna, Arne Astrup, Teemu Kuulasmaa, Symen Ligthart, Shih-Yi Lin, David J. Porteous, Harry Campbell, Peter Vollenweider, Mark J. Caulfield, Kristi Läll, Anne Ndungu, Carl D. Langefeld, Tanya M. Teslovich, Heikki A. Koistinen, Ying Wu, Mattias Frånberg, D.I. Boomsma, Lawrence F. Bielak, Diana van Heemst, Peter Kovacs, Markku Laakso, Leslie J. Raffel, Katharina E. Schraut, Noël P. Burtt, Michiya Igase, Craig E. Pennell, Claudia Langenberg, Huaixing Li, Teresa Tusie, Laura M. Raffield, Jorgen Engmann, Stephen C. J. Parker, Michele K. Evans, Chaolong Wang, Rico Rueedi, Jianjun Liu, Pankow S. James, Hortensia Moreno-Macías, Fumihiko Takeuchi, Cornelia M. van Duijn, Sanghoon Moon, Susan R. Heckbert, Thomas A. Buchanan, Ko Willems van Dijk, Toru Nabika, May E. Montasser, Caroline Hayward, Jie Yao, Aaron Leong, Antje Körner, Jouko Saramies, Jost B. Jonas, Pim van der Harst, Naveed Sattar, Helen R. Warren, Alice Stanton, Yen-Feng Chiu, Kumaraswamy Naidu Chitrala, Mi Yeong Hwang, Jin Fang Chai, Alicia Huerta-Chagoya, Anette P. Gjesing, Ching-Yu Cheng, Debbie A Lawlor, Simin Liu, Man Li, Ivana Kolcic, Erwin P. Bottinger, Andrew Wong, Stella Trompet, Heming Wang, Jirong Long, Xiuqing Guo, Jeffrey R. O'Connell, Meena Kumari, Sirkka Keinänen-Kiukaanniemi, Rita R. Kalyani, Bengt Sennblad, Mohammad Hadi Zafarmand, Kent D. Taylor, Katherine A. Kentistou, Carol A. Wang, Shuiqing Lai, Patricia B. Munroe, Patricia A. Peyser, Lawrence J. Beilin, Niek Verweij, Inga Prokopenko, Brian E. Cade, Patrik K. E. Magnusson, John C. Chambers, Tamar Sofer, Ping An, Matthias Blüher, Isobel D. Stewart, Alexander P. Reiner, Anna L. Gloyn, Simon P. Mooijaart, Tim D. Spector, Paul W. Franks, Wei Zhao, Andres Metspalu, Wieland Kiess, Kathleen A. Ryan, Astrid van Hylckama Vlieg, Jaana Lindström, Wei Zheng, E. Shyong Tai, Josée Dupuis, Nanette R. Lee, Laura J. Scott, Nicholas J. Timpson, George Dedoussis, Mark I. McCarthy, Tatsuaki Matsubara, Carlos Lorenzo, Denis Rybin, Luigi Ferruci, Chelsea K. Raulerson, Mika Kivimäki, Paul M. Ridker, Jer-Yuarn Wu, Shufa Du, Jaeyoung Hong, Linda S. Adair, Tin Louie, Valeriya Lyssenko, Susan Redline, Kelvin Lam, Qibin Qi, H. Janaka de Silva, Jana V. van Vliet-Ostaptchouk, Peter J. van der Most, Sahoko Ichihara, Nicholas J. Wareham, Ayse Demirkan, Francesco Cucca, Allan Linneberg, Rob M. van Dam, Claire J. Steves, Liang Sun, Albert V. Smith, Raymond Noordam, Tom Wilsgaard, Winfried März, Jung Ho Gong, Matt J. Neville, Jerry L. Nadler, Giorgio Pistis, Karen L. Mohlke, Bruna Gigante, Jennifer A. Brody, Andrew P. Morris, Marie Lauzon, Peter E. H. Schwarz, Bernardo L. Horta, Xiaoran Chai, Ji Chen, Peter S. Sever, Thorkild I. A. Sørensen, André G. Uitterlinden, Javier Gayán, Elena Tremoli, Girish N. Nadkarni, Najaf Amin, Hugh Watkins, Johanna Kuusisto, Jingyi Tan, Sameline Grimsgaard, Bong-Jo Kim, Kerrin S. Small, Jill M. Norris, Cecilia M. Lindgren, Richard N. Bergman, Mark Walker, Henrik Vestergaard, Larissa Aviles-Santa, Jing He, Masahiro Nakatochi, Peter P. Pramstaller, Chiea Chuen Khor, Ruifang Li-Gao, Qiuyin Cai, Neil Schneiderman, Kevin Sandow, Jaspal S. Kooner, Carlos A. Aguilar-Salinas, Peitao Wu, Jerome I. Rotter, Kathryn Roll, Frits R. Rosendaal, Diane M. Becker, Marian Beekman, Claudia P. Cabrera, Nan Wang, Franco Giulianini, Tao Wang, Honglan Li, Abbas Dehghan, Christian Fuchsberger, and Pontiano Kaleebu

Subjects
0303 health sciences, medicine.medical_specialty, business.industry, Type 2 diabetes, medicine.disease, Fasting insulin, Fasting glucose, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Internal medicine, Diabetes mellitus, medicine, Genomic architecture, business, Glycated haemoglobin, 030217 neurology & neurosurgery, 030304 developmental biology, Genetic association
Abstract

Glycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.

Published
2020

16. A diet high in sugar-sweetened beverage and low in fruits and vegetables is associated with adiposity and a pro-inflammatory adipokine profile

Author

Richard M. Watanabe, Thomas A. Buchanan, Yu-Hsiang Shu, Jun Wu, Adrienne W. MacKay, Mary Helen Black, Corinna Koebnick, and Anny H. Xiang

Subjects
Adult, Male, medicine.medical_specialty, Dietary Sugars, Medicine (miscellaneous), Adipokine, 030209 endocrinology & metabolism, 030204 cardiovascular system & hematology, Article, Beverages, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Adipokines, Diabetes mellitus, Internal medicine, Mexican Americans, Vegetables, medicine, Humans, Obesity, Adiposity, Inflammation, Nutrition and Dietetics, biology, Adiponectin, business.industry, Leptin, C-reactive protein, medicine.disease, Diet, Apelin, Endocrinology, Adipose Tissue, Fruit, biology.protein, Female, Resistin, Energy Intake, business, Nutritive Sweeteners
Abstract

Diet, obesity and adipokines play important roles in diabetes and CVD; yet, limited studies have assessed the relationship between diet and multiple adipokines. This cross-sectional study assessed associations between diet, adiposity and adipokines in Mexican Americans. The cohort included 1128 participants (age 34·7±8·2 years, BMI 29·5±5·9 kg/m2, 73·2 % female). Dietary intake was assessed by 12-month food frequency questionnaire. Adiposity was measured by BMI, total percentage body fat and percentage trunk fat using dual-energy X-ray absorptiometry. Adiponectin, apelin, C-reactive protein (CRP), dipeptidyl peptidase-4 (DPP-IV), IL-1β, IL-1ra, IL-6, IL-18, leptin, lipocalin, monocyte chemo-attractant protein-1 (MCP-1), resistin, secreted frizzled protein 4 (SFRP-4), SFRP-5, TNF-α and visfatin were assayed with multiplex kits or ELISA. Joint multivariate associations between diet, adiposity and adipokines were analysed using canonical correlations adjusted for age, sex, energy intake and kinship. The median (interquartile range) energy intake was 9514 (7314, 11912) kJ/d. Overall, 55 % of total intake was accounted for by carbohydrates (24 % from sugar). A total of 66 % of the shared variation between diet and adiposity, and 34 % of diet and adipokines were explained by the top canonical correlation. The diet component was most represented by sugar-sweetened beverages (SSB), fruit and vegetables. Participants consuming a diet high in SSB and low in fruits and vegetables had higher adiposity, CRP, leptin, and MCP-1, but lower SFRP-5 than participants with high fruit and vegetable and low SSB intake. In Mexican Americans, diets high in SSB but low in fruits and vegetables contribute to adiposity and a pro-inflammatory adipokine profile.

Published
2018

17. rs641738C>T near MBOAT7 is positively associated with liver fat, ALT, and histological severity of NAFLD: a meta-analysis

Author

Jesus M. Banales, Jerome I. Rotter, Connor A. Emdin, Leon A. Adams, Sreekumar G. Pillai, Stephan Buch, Yu Ri Im, Thomas Berg, Claudia Langenberg, Kendra A. Young, Felix Stickel, Elizabeth K. Speliotes, Julia Kozlitina, Sonia Caprio, Madison Fairey, Kevin Teo, Hanieh Yaghootkar, Abhijit Chowdhury, Eu-Pnafld Investigators, Yii-Der Ida Chen, Harriet Hunter, Faiza Qayyum, Pavel Strnad, Matthias C. Reichert, Elmar Aigner, Marcin Krawczyk, Dana de Gracia Hahn, Lin Li, Matthew Hickman, Nicholette D. Palmer, Panu K. Luukkonen, Jiawen Dong, Christian Datz, Ali Canbay, Kent D. Taylor, Joel E. Lavine, Philip E. Melton, Nicola Santoro, Richard M. Watanabe, Xiuqing Guo, Giuseppina Rosaria Umano, Lynne E. Wagenknecht, Amedine Duret, Pallav Bhatnagar, Trevor A. Mori, Johanna K. DiStefano, Anne Tybjærg-Hansen, Stefano Romeo, Julia Wattacheril, Jake P. Mann, Luca Valenti, Ankita Chatterjee, Stefan Stender, Jochen Hampe, Rajarshi Banerjee, Glenn S. Gerhard, Frank Lammert, Rohit Loomba, Christian A. Hudert, Kushala W M Abeysekera, L Heintz, Constantinos A. Parisinos, Hong Kai Lim, Christopher D. Still, Matt Kelly, Mrudula Utukuri, Priyadarshi Basu, Nicholas J. Wareham, Hannele Yki-Järvinen, and Clemens Schafmayer

Subjects
0303 health sciences, medicine.medical_specialty, business.industry, Insulin, medicine.medical_treatment, Fatty liver, Genome-wide association study, medicine.disease, Gastroenterology, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Fibrosis, 030220 oncology & carcinogenesis, Hepatocellular carcinoma, Internal medicine, Genetic model, medicine, Steatosis, Risk factor, business, 030304 developmental biology
Abstract

Background & AimsA common genetic variant near MBOAT7 (rs641738C>T) has been previously associated with hepatic fat and advanced histology in non-alcoholic fatty liver disease (NAFLD), however, these findings have not been consistently replicated in the literature. We aimed to establish whether rs641738C>T is a risk factor across the spectrum of NAFLD and characterize its role in the regulation of related metabolic phenotypes through meta-analysis.MethodsWe performed meta-analysis of studies with data on the association between rs641738C>T genotype and: liver fat, NAFLD histology, and serum ALT, lipids, or insulin. These included directly genotyped studies and population-level data from genome-wide association studies (GWAS). We performed random effects meta-analysis using recessive, additive, and dominant genetic models.ResultsData from 1,047,265 participants (8,303 with liver biopsies) across 42 studies was included in the meta-analysis. rs641738C>T was associated with higher liver fat on CT/MRI (+0.03 standard deviations [95% CI: 0.02 - 0.05]) and diagnosis of NAFLD (OR 1.22 [95% CI 1.08 - 1.39]) in Caucasian adults. The variant was also positively associated with presence of severe steatosis, NASH, and advanced fibrosis (OR: 1.32 [95% CI: 1.06 - 1.63]) in Caucasian adults using a recessive model of inheritance (CC+CT vs. TT). Meta-analysis of data from previous GWAS found the variant to be associated with higher ALT (Pz=0.002) and lower serum triglycerides (Pz=1.5×10−4). rs641738C>T was not associated with fasting insulin and no effect was observed in children with NAFLD.ConclusionOur study validates rs641738C>T near MBOAT7 as a risk factor for the presence and severity of NAFLD in individuals of European descent.

Published
2019

18. Longitudinal Increases in Adiposity Contribute to Worsening Adipokine Profile over Time in Mexican Americans

Author

Anny H. Xiang, Yu-Hsiang Shu, Mary Helen Black, Corinna Koebnick, Jun Wu, Thomas A. Buchanan, Adrienne W. MacKay, and Richard M. Watanabe

Subjects
Adult, Leptin, Male, 0301 basic medicine, obesity, medicine.medical_specialty, longitudinal, Endocrinology, Diabetes and Metabolism, Medicine (miscellaneous), Adipokine, 030209 endocrinology & metabolism, Type 2 diabetes, Article, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Adipokines, Internal medicine, Diabetes mellitus, Mexican Americans, medicine, Humans, adiposity, Nutrition and Dietetics, Adiponectin, biology, Interleukin-6, business.industry, C-reactive protein, medicine.disease, Obesity, C-Reactive Protein, 030104 developmental biology, Diabetes Mellitus, Type 2, biology.protein, Female, business, Body mass index
Abstract

OBJECTIVE Limited studies have assessed the relationship between longitudinal changes in adiposity and changes in multiple adipokines over time. This study examined changes in BMI, total body fat, and trunk fat associated with changes in 16 circulating adipokines in Mexican Americans at risk for type 2 diabetes. METHODS Participants included 1,213 individuals with cross-sectional data and a subset of 368 individuals with follow-up measures (mean 4.6 ± 1.5 years from baseline). Joint multivariate associations between 3 adiposity measures and 16 adipokines were assessed by canonical correlation analysis. RESULTS Longitudinal increases in adiposity were most strongly associated with increasing leptin, C-reactive protein (CRP), and interleukin 1 receptor antagonist (IL-1Ra) and decreasing adiponectin and secreted frizzled protein 5 (SFRP5) over time. Participants with BMI ≥ 30 kg/m2 at baseline had greater increases in leptin, CRP, IL-1Ra, and interleukin 6 (IL-6) and greater decreases in adiponectin and SFRP5, associated with increasing adiposity over follow-up, than those with BMI

Published
2018

19. Plasminogen Activator Inhibitor-1 Predicts Negative Alterations in Whole-Body Insulin Sensitivity in Chronic HIV Infection

Author

Kamonkiat Wirunsawanya, Bruce Shiramizu, Cecilia M. Shikuma, Philip J. Norris, Sheila M. Keating, Dominic C. Chow, Brooks I. Mitchell, Lindsay B Kohorn, Lishomwa C. Ndhlovu, Loni Belyea, Richard M. Watanabe, and Scott A. Souza

Subjects
Male, medicine.medical_specialty, medicine.medical_treatment, Immunology, Human immunodeficiency virus (HIV), HIV Infections, 030209 endocrinology & metabolism, Pathogenesis, medicine.disease_cause, Proinflammatory cytokine, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Insulin resistance, Virology, Diabetes mellitus, Internal medicine, Plasminogen Activator Inhibitor 1, Fibrinolysis, medicine, Humans, Longitudinal Studies, 030212 general & internal medicine, business.industry, Insulin sensitivity, Metabolism, Middle Aged, medicine.disease, Infectious Diseases, Endocrinology, chemistry, Plasminogen activator inhibitor-1, Female, Insulin Resistance, business
Abstract

Plasminogen activator inhibitor type 1 (PAI-1), a key negative regulator of fibrinolysis, has been investigated to be one of the potential mechanisms of the development of impaired insulin sensitivity, insulin resistance, and diabetes mellitus. Because chronically stable HIV-infected individuals frequently develop abnormal glucose metabolism, including insulin resistance and diabetes mellitus, we postulated that PAI-1 could be one of the multifactorial pathogenic roles in the development of impaired insulin sensitivity and insulin resistance among chronic HIV-infected individuals. From our longitudinal cohort study, we selectively recruited chronically stable HIV-infected individuals without diagnosis of diabetes mellitus at baseline (N = 62) to analyze the correlation of baseline inflammatory cytokines, including PAI-1 and whole-body insulin sensitivity, with 2-year follow-up, as measured by Matsuda Index. We found a negative correlation between baseline PAI-1 and Matsuda Index (r = −0.435, p = .001) and a negative correlation between baseline PAI-1 and Matsuda Index at 2 years (r = −0.377, p = .005). In a linear regression model that included age, total body fat mass percentage, serum amyloid A, and family history of diabetes mellitus, PAI-1 still remained significantly associated with Matsuda Index at 2-year follow-up (β = −.397, p = .002). Our longitudinal study suggests that PAI-1 is an independent predictor of impaired insulin sensitivity among chronic HIV-infected individuals.

Published
2017

20. Contributors

Author

E. Abou Diwan, Jesper B. Andersen, Saeed Aslani, Nieves Baenas, Wanda Baer-Dubowska, Moinak Banerjee, Bernhard T. Baune, Ahlem Belhadj, Vincent L. Biron, Chad Bousman, Ramón Cacabelos, Pablo Cacabelos, Juan C. Carril, P. Castro-Santos, Si Chen, Yuanyuan Cheng, Anusha Chidambaram, Ramesh Kumar Chidambaram, Teresa Cunha-Oliveira, Richard Daifuku, Christos Damaskos, R. Díaz-Peña, Dimitrios Dimitroulis, Yıldız Dincer, Johanna K. DiStefano, Nathan J. Dupper, Dibyendu Dutta, Aseel Eid, Harris A. Eyre, Qian Feng, Luciana L. Ferreira, Gabriel R. Fries, Anna Garmpi, Nikolaos Garmpis, Jérôme Govin, Joaquín Guerra, Lei Guo, Soumeyya Halayem, Meriem Hamza, Antja-Voy Hartley, Rong-Rong He, Christian Michael Hedrich, Zhiying Huang, Qiuju Huang, Eun Seong Hwang, Jiamin Jin, Morris Kostiuk, Olga Kovalchuk, Igor Kovalchuk, Dongying Li, Seah H. Lim, Cameron Lindsay, Bo Liu, Hong-Min Liu, Zhongqiu Liu, Linlin Lu, Tao Lu, Mahdi Mahmoudi, Aleksandra Majchrzak-Celińska, Matthew Martin, Charles E. McKenna, Kunio Miyake, Ridha Mrad, Patricia Munoz-Garrido, R. Nasr, Baitang Ning, Tomomi Noguchi-Yachide, Colm J. O’Rourke, Douglas V.N.P. Oliveira, Paulo J. Oliveira, Binithamol K. Polakkattil, Joao Quevedo, Ramazan Rezaei, Jason R. Richardson, Kathleen Saavedra, Luis A. Salazar, Ana Sanmartín, Letizia Satriano, Corinne Sidler, Tao Su, Babu Swathy, Oscar Teijido, Iván Tellado, William H. Tolleson, Weida Tong, Ravikumar Vilwanathan, Nguyen Quoc Vuong Tran, Serena Valsami, Anika E. Wagner, Richard M. Watanabe, Wenming Xiao, Dianke Yu, Bin Yu, Tomás Zambrano, R. Zeitoun, N.K. Zgheib, and Yingsheng Zhou

Published
2019

21. Pharmacoepigenetics in Type 2 Diabetes Mellitus

Author

Johanna K. DiStefano and Richard M. Watanabe

Subjects
Drug, medicine.medical_specialty, endocrine system diseases, business.industry, media_common.quotation_subject, Type 2 Diabetes Mellitus, Disease, medicine.disease, Bioinformatics, Comorbidity, Insulin resistance, Pharmacogenomics, Diabetes mellitus, Epidemiology, medicine, business, media_common
Abstract

Type 2 diabetes (T2D) is a common disease resulting from multiorgan insulin resistance and inadequate pancreatic insulin production. Lifestyle modifications can often reduce glycemia in individuals with recent T2D onset; however, for patients who are significantly insulinopenic, pharmacological intervention is necessary to treat the disease. The repertoire of oral and injected antidiabetic agents has expanded greatly during the past decade; however, the effects of oral antihyperglycemic agents are highly variable, and factors such as age, sex, disease, drug and food interactions, comorbidity, and genetic factors contribute to interindividual differences in drug response. Emerging evidence also suggests that epigenetic factors modulate pharmacological response to antidiabetes drugs. In this chapter we provide an overview of the epidemiology, pathogenesis, and clinical management of T2D and review the current state of pharmacoepigenetics research of antidiabetes medications. Combined with pharmacogenomics, pharmacoepigenetics may lead to the development of individualized approaches in the treatment of T2D.

Published
2019

22. The genetic architecture of type 2 diabetes

Author

Clement Ma, Liisa Hakaste, Claes Ladenvall, Massimo Mangino, Lars Lind, Aaron G. Day-Williams, Ryan Poplin, Thomas Schwarzmayr, Annette Peters, Thomas Meitinger, Satish Kumar, Kyong Soo Park, Ching-Yu Cheng, Farook Thameem, Kyle J. Gaulton, Olov Rolandsson, Yossi Farjoun, Neil Robertson, Mauricio O. Carneiro, Mark A. DePristo, Pierre Fontanillas, Ruth J. F. Loos, Heather M. Highland, Vilmantas Giedraitis, Gemma Buck, Fredrik Karpe, Mohammad Kamran Ikram, Alex S. F. Doney, Hae Kyung Im, Eric S. Lander, Johanna Kuusisto, Dorothée Thuillier, Denis Rybin, Jacquelyn Murphy, Benjamin M. Neale, Martina Müller-Nurasyid, Eric R. Gamazon, Johanne Marie Justesen, Tin Aung, Vincent K. L. Lam, John Danesh, Donna M. Lehman, Goo Jun, Marit E. Jørgensen, Christian Herder, Edmund Chan, Pamela J. Hicks, Todd Green, Claudia Langenberg, Yoon Shin Cho, James G. Wilson, Daniel E. Hale, Rector Arya, Giriraj R. Chandak, Juan Fernandez Tajes, Jaakko Tuomilehto, Christopher P. Jenkinson, Anders Rosengren, Torsten Lauritzen, Michael Griswold, Karen L. Mohlke, Amy J. Swift, Alena Stančáková, Christian Fuchsberger, Iksoo Huh, Nikhil Tandon, João Fadista, Christa Meisinger, Gonçalo R. Abecasis, Pål R. Njølstad, Dwaipayan Bharadwaj, Richard M. Watanabe, Shaun Purcell, Veikko Salomaa, Tim D. Spector, Paul W. Franks, Adam E. Locke, Sharon P. Fowler, Panos Deloukas, Reedik Mägi, Solomon K. Musani, Kee Seng Chia, Barbara Thorand, Soo Heon Kwak, Annemari Käräjämäki, Evelin Mihailov, John Blangero, Thomas Wieland, Christian Gieger, E. Shyong Tai, Jianjun Liu, James B. Meigs, Teemu Kuulasmaa, Martin Hrabé de Angelis, Francis S. Collins, Tim M. Strom, Tibor V. Varga, Juyoung Lee, Mark I. McCarthy, Domenico Palli, Jong-Young Lee, Benjamin Glaser, Tasha E. Fingerlin, Stephen O'Rahilly, Andrew T. Hattersley, Gil Atzmon, Manuel A. Rivas, Noël P. Burtt, Ivan Brandslund, Young-Jin Kim, Dorairaj Prabhakaran, Xu Wang, Taylor J. Maxwell, Valeriya Lyssenko, Frank B. Hu, Adolfo Correa, Khalid Shakir, Kathleen A. Jablonski, Yingchang Lu, Wei-Yen Lim, Min Jin Go, William R. Scott, Hanna E. Abboud, Leena Kinnunen, Inês Barroso, Gabriela L. Surdulescu, Peng Chen, Robert Sladek, Marju Orho-Melander, Xueling Sim, Robert A. Scott, Joanna M. M. Howson, Markku Laakso, David Altshuler, Vidya S. Farook, Harald Grallert, Janina S. Ried, Vineeta Agarwala, Philippe Froguel, Nicholas J. Wareham, Tiinamaija Tuomi, Joon Yoon, Heikki A. Koistinen, Toni I. Pollin, Heiner Boeing, Marie Loh, Nicola L. Beer, Joanne E. Curran, Lars Lannfelt, Dorota Pasko, Taesung Park, David Buck, Nir Barzilai, Stephen C. J. Parker, Michael Roden, Bok-Ghee Han, David Aguilar, Timothy Fennell, Sian-Tsung Tan, Gregory P. Wilson, Momoko Horikoshi, Cramer Christensen, Craig L. Hanis, Gilean McVean, Benjamin F. Voight, Wolfgang Rathmann, Jared Maguire, Ashok Kumar, Donald W. Bowden, Michael L. Stitzel, Yongkang Kim, Christine Blancher, Jason Carey, Min-Seok Kwon, Nicholette D. Palmer, Oluf Pedersen, Niels Grarup, Peter S. Chines, Cornelia Huth, James Scott, Torben Hansen, Konstantin Strauch, Erwin P. Bottinger, Andrew D. Morris, Anette P. Gjesing, Erik Ingelsson, Colin N. A. Palmer, Claudia H. T. Tam, Stacey Gabriel, Pablo Cingolani, Beverley Balkau, Michael Boehnke, Peter M. Nilsson, Wing-Yee So, Andrew R. Wood, Lili Milani, Ravindranath Duggirala, Qibin Qi, Mark Walker, Weiping Jia, Mark Seielstad, Narisu Narisu, Tien Yin Wong, Martijn van de Bunt, Anubha Mahajan, Davis J. McCarthy, Ann-Christine Syvänen, Jennifer Kriebel, N. William Rayner, Han Chen, Jinyan Huang, Chiea Chuen Khor, Richard N. Bergman, Shah Ebrahim, Dylan Hodgkiss, Weihua Zhang, Manjinder S. Sandhu, Richard D. Pearson, Juliana C.N. Chan, Rainer Rauramaa, Ralph A. DeFronzo, Andrew Farmer, Yoshihiko Nagai, Allan Linneberg, Herman A. Taylor, Jose C. Florez, Jaspal S. Kooner, Lori L. Bonnycastle, Jeroen R. Huyghe, Leif Groop, Joseph Trakalo, Sobha Puppala, Bong-Jo Kim, Kathleen Stirrups, Kerrin S. Small, Cecilia M. Lindgren, Jennifer E. Below, Heung Man Lee, Inga Prokopenko, Liming Liang, Timothy M. Frayling, Uzma Afzal, Mark J. Daly, Yik Ying Teo, Andrew P. Morris, Phoenix Kwan, Yvonne T. van der Schouw, Cheng Hu, Katharine R. Owen, Alisa K. Manning, Christopher J. Groves, Josée Dupuis, Ryan P. Welch, Loukas Moutsianas, Joshua D. Smith, Tanya M. Teslovich, Robert C. Onofrio, Maggie C.Y. Ng, Peter Donnelly, Tõnu Esko, Matt Neville, Bo Isomaa, Anne U. Jackson, Jette Bork-Jensen, Barry I. Freedman, Yi Chen, Danish Saleheen, Lu Qi, Laura J. Scott, Jasmina Kravic, Paul Elliott, Mette Hollensted, Carmen Navarro, Selyeong Lee, Benjamin Lehne, Thomas Illig, Nancy J. Cox, Jonathan C. Levy, George B. Grant, John C. Chambers, Adam S. Butterworth, Ronald C.W. Ma, Teresa Ferreira, John R. B. Perry, Eleftheria Zeggini, Hyun Min Kang, Loic Yengo, Eric Banks, Jae-Hoon Lee, Anna L. Gloyn, Christopher Hartl, Wei Zhao, Andres Metspalu, Keng-Han Lin, Graeme I. Bell, Jason Flannick, Torben Jørgensen, Thomas W. Blackwell, Heather M. Stringham, Olle Melander, Omri Gottesman, Other departments, British Heart Foundation, Wellcome Trust, Medical Research Council (MRC), Massachusetts Institute of Technology. Department of Biology, Altshuler, David M, Internal Medicine, Perry, John [0000-0001-6483-3771], Butterworth, Adam [0000-0002-6915-9015], Howson, Joanna [0000-0001-7618-0050], Danesh, John [0000-0003-1158-6791], Johnson, Kathleen [0000-0002-6823-3252], O'Rahilly, Stephen [0000-0003-2199-4449], Langenberg, Claudia [0000-0002-5017-7344], Sandhu, Manjinder [0000-0002-2725-142X], Barroso, Ines [0000-0001-5800-4520], Wareham, Nicholas [0000-0003-1422-2993], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, PROTEIN INTERACTION NETWORKS, SUSCEPTIBILITY LOCI, Genotyping Techniques, General Science & Technology, DNA Mutational Analysis, SEQUENCING ASSOCIATION, 030209 endocrinology & metabolism, Genome-wide association study, Biology, Research Support, N.I.H, 03 medical and health sciences, 0302 clinical medicine, Research Support, N.I.H., Extramural, SDG 3 - Good Health and Well-being, MD Multidisciplinary, Genetic predisposition, Journal Article, Humans, Exome, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, Non-U.S. Gov't, Exome sequencing, Alleles, Genetic association, Genetics, RISK, Multidisciplinary, HERITABILITY, Research Support, Non-U.S. Gov't, COMPLEX TRAITS, Extramural, Genetic Variation, Genetic architecture, HUMAN-DISEASE, Europe, 030104 developmental biology, Diabetes Mellitus, Type 2, RARE VARIANTS, Sample Size, LOW-FREQUENCY, Imputation (genetics), Common disease-common variant, Genome-Wide Association Study
Abstract

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of the heritability of this disease. Here, to test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole-genome sequencing in 2,657 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

Published
2016

23. Improved Performance of Dynamic Measures of Insulin Response Over Surrogate Indices to Identify Genetic Contributors of Type 2 Diabetes: The GUARDIAN Consortium

Author

Hooman Allayee, Nan Wang, Richard N. Bergman, Talin Haritunians, Jerome I. Rotter, Leslie J. Raffel, Kent D. Taylor, Thomas A. Buchanan, Richard M. Watanabe, Tasha E. Fingerlin, Mark O. Goodarzi, Donald W. Bowden, Anny H. Xiang, Nicholette D. Palmer, Yii-Der Ida Chen, Lynne E. Wagenknecht, and Carl D. Langefeld

Subjects
Adult, Blood Glucose, Male, 0301 basic medicine, medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Population, Type 2 diabetes, Biology, Medical and Health Sciences, Endocrinology & Metabolism, 03 medical and health sciences, Insulin resistance, Internal medicine, Diabetes Mellitus, Genetics, Internal Medicine, medicine, Homeostasis, Humans, Insulin, Glucose homeostasis, education, Metabolic and endocrine, Aged, education.field_of_study, Glucose tolerance test, medicine.diagnostic_test, Diabetes, Genetics/Genomes/Proteomics/Metabolomics, Glucose Tolerance Test, Middle Aged, medicine.disease, 030104 developmental biology, Endocrinology, Diabetes Mellitus, Type 2, Basal (medicine), Female, Insulin Resistance, TCF7L2, Type 2
Abstract

Type 2 diabetes (T2D) is a heterogeneous disorder with contributions from peripheral insulin resistance and β-cell dysfunction. For minimization of phenotypic heterogeneity, quantitative intermediate phenotypes characterizing basal glucose homeostasis (insulin resistance and HOMA of insulin resistance [HOMAIR] and of β-cell function [HOMAB]) have shown promise in relatively large samples. We investigated the utility of dynamic measures of glucose homeostasis (insulin sensitivity [SI] and acute insulin response [AIRg]) evaluating T2D-susceptibility variants (n = 57) in Hispanic Americans from the GUARDIAN Consortium (n = 2,560). Basal and dynamic measures were genetically correlated (HOMAB-AIRg: ρG = 0.28–0.73; HOMAIR-SI: ρG = −0.73 to −0.83) with increased heritability for the dynamic measure AIRg. Significant association of variants with dynamic measures (P < 8.77 × 10−4) was observed. A pattern of superior performance of AIRg was observed for well-established loci including MTNR1B (P = 9.46 × 10−12), KCNQ1 (P = 1.35 × 10−4), and TCF7L2 (P = 5.10 × 10−4) with study-wise statistical significance. Notably, significant association of MTNR1B with AIRg (P < 1.38 × 10−9) was observed in a population one-fourteenth the size of the initial discovery cohort. These observations suggest that basal and dynamic measures provide different views and levels of sensitivity to discrete elements of glucose homeostasis. Although more costly to obtain, dynamic measures yield significant results that could be considered physiologically “closer” to causal pathways and provide insight into the discrete mechanisms of action.

Published
2016

24. Ambient Air Pollutants Have Adverse Effects on Insulin and Glucose Homeostasis in Mexican Americans

Author

Claudia M. Toledo-Corral, Zhanghua Chen, Rima Habre, Frank D. Gilliland, John Wilson, Anny H. Xiang, Muhammad T. Salam, Theresa M. Bastain, Richard M. Watanabe, Thomas A. Buchanan, Enrique Trigo, and Fred Lurmann

Subjects
Adult, Blood Glucose, Male, medicine.medical_specialty, Adolescent, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Blood lipids, Type 2 diabetes, 010501 environmental sciences, 01 natural sciences, Body Mass Index, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Insulin resistance, Internal medicine, Diabetes mellitus, Mexican Americans, Internal Medicine, medicine, Homeostasis, Humans, Insulin, Glucose homeostasis, Obesity, 030212 general & internal medicine, Epidemiology/Health Services Research, Air quality index, Aged, 0105 earth and related environmental sciences, Advanced and Specialized Nursing, Pollutant, Air Pollutants, business.industry, Incidence, Cholesterol, HDL, Cholesterol, LDL, Middle Aged, medicine.disease, Cross-Sectional Studies, Endocrinology, Diabetes Mellitus, Type 2, Female, Particulate Matter, Insulin Resistance, business
Abstract

OBJECTIVE Recent studies suggest that air pollution plays a role in type 2 diabetes (T2D) incidence and mortality. The underlying physiological mechanisms have yet to be established. We hypothesized that air pollution adversely affects insulin sensitivity and secretion and serum lipid levels. RESEARCH DESIGN AND METHODS Participants were selected from BetaGene (n = 1,023), a study of insulin resistance and pancreatic β-cell function in Mexican Americans. All participants underwent DXA and oral and intravenous glucose tolerance tests and completed dietary and physical activity questionnaires. Ambient air pollutant concentrations (NO2, O3, and PM2.5) for short- and long-term periods were assigned by spatial interpolation (maximum interpolation radius of 50 km) of data from air quality monitors. Traffic-related air pollution from freeways (TRAP) was estimated using the dispersion model as NOx. Variance component models were used to analyze individual and multiple air pollutant associations with metabolic traits. RESULTS Short-term (up to 58 days cumulative lagged averages) exposure to PM2.5 was associated with lower insulin sensitivity and HDL-to-LDL cholesterol ratio and higher fasting glucose and insulin, HOMA-IR, total cholesterol, and LDL cholesterol (LDL-C) (all P ≤ 0.036). Annual average PM2.5 was associated with higher fasting glucose, HOMA-IR, and LDL-C (P ≤ 0.043). The effects of short-term PM2.5 exposure on insulin sensitivity were largest among obese participants. No statistically significant associations were found between TRAP and metabolic outcomes. CONCLUSIONS Exposure to ambient air pollutants adversely affects glucose tolerance, insulin sensitivity, and blood lipid concentrations. Our findings suggest that ambient air pollutants may contribute to the pathophysiology in the development of T2D and related sequelae.

Published
2016

25. Assessment of soluble epoxide hydrolase activity in vivo: A metabolomic approach

Author

Jang H. Youn, Darko Stefanovski, Pei-an Betty Shih, Richard M. Watanabe, and Bruce D. Hammock

Subjects
Male, 0301 basic medicine, Epoxide hydrolase 2, Anorexia Nervosa, Soluble epoxide hydrolase activity, Physiology, Diol, 030204 cardiovascular system & hematology, Biochemistry, Article, Mice, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Metabolomics, In vivo, polycyclic compounds, Animals, Humans, Oxylipins, Rats, Wistar, Epoxide Hydrolases, Pharmacology, Cell Biology, Disease Models, Animal, 030104 developmental biology, chemistry, Case-Control Studies, Metabolome, cardiovascular system, Epoxy Compounds, hormones, hormone substitutes, and hormone antagonists
Abstract

Soluble epoxide hydrolase (sEH) converts several FFA epoxides to corresponding diols. As many as 15 FFA epoxide-diol ratios are measured to infer sEH activity from their ratios. Using previous data, we assessed if individual epoxide-diol ratios all behave similarly to reflect changes in sEH activity, and whether analyzing these ratios together increases the power to detect changes in in-vivo sEH activity. We demonstrated that epoxide-diol ratios correlated strongly with each other (P < 0.05), suggesting these ratios all reflect changes in sEH activity. Furthermore, we developed a modeling approach to analyze all epoxide-diol ratios simultaneously to infer global sEH activity, named SAMI (Simultaneous Analysis of Multiple Indices). SAMI improved power in detecting changes in sEH activity in animals and humans when compared to individual ratio estimates. Thus, we introduce a new powerful method to infer sEH activity by combining metabolomic determination and simultaneous analysis of all measurable epoxide-diol pairs.

Published
2020

26. Exome Sequencing Identifies Genetic Variants Associated with Circulating Lipid Levels in Mexican Americans: The Insulin Resistance Atherosclerosis Family Study (IRASFS)

Author

John Blangero, Jerome I. Rotter, Richard M. Watanabe, Jirong Long, Xiuqing Guo, Chuan Gao, Keri L. Tabb, Nicholette D. Palmer, Donald W. Bowden, Kent D. Taylor, Nan Wang, Latchezar Dimitrov, Joanne E. Curran, and Carl D. Langefeld

Subjects
Adult, 0301 basic medicine, Genetic Linkage, lcsh:Medicine, Single-nucleotide polymorphism, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Insulin resistance, Genetic linkage, Polymorphism (computer science), Mexican Americans, Exome Sequencing, Genetic variation, medicine, Humans, lcsh:Science, Triglycerides, Exome sequencing, Genetic association, Genetics, Multidisciplinary, lcsh:R, Genetic Variation, Middle Aged, Atherosclerosis, medicine.disease, Lipids, 030104 developmental biology, Apolipoprotein A-V, Female, lcsh:Q, Insulin Resistance, Carrier Proteins, Lipoproteins, HDL, Genome-Wide Association Study
Abstract

Genome-wide association studies have identified numerous variants associated with lipid levels; yet, the majority are located in non-coding regions with unclear mechanisms. In the Insulin Resistance Atherosclerosis Family Study (IRASFS), heritability estimates suggest a strong genetic basis: low-density lipoprotein (LDL, h2 = 0.50), high-density lipoprotein (HDL, h2 = 0.57), total cholesterol (TC, h2 = 0.53), and triglyceride (TG, h2 = 0.42) levels. Exome sequencing of 1,205 Mexican Americans (90 pedigrees) from the IRASFS identified 548,889 variants and association and linkage analyses with lipid levels were performed. One genome-wide significant signal was detected in APOA5 with TG (rs651821, PTG = 3.67 × 10−10, LODTG = 2.36, MAF = 14.2%). In addition, two correlated SNPs (r2 = 1.0) rs189547099 (PTG = 6.31 × 10−08, LODTG = 3.13, MAF = 0.50%) and chr4:157997598 (PTG = 6.31 × 10−08, LODTG = 3.13, MAF = 0.50%) reached exome-wide significance (P −08). rs189547099 is an intronic SNP in FNIP2 and SNP chr4:157997598 is intronic in GLRB. Linkage analysis revealed 46 SNPs with a LOD > 3 with the strongest signal at rs1141070 (LODLDL = 4.30, PLDL = 0.33, MAF = 21.6%) in DFFB. A total of 53 nominally associated variants (P −05, MAF ≥ 1.0%) were selected for replication in six Mexican-American cohorts (N = 3,280). The strongest signal observed was a synonymous variant (rs1160983, PLDL = 4.44 × 10−17, MAF = 2.7%) in TOMM40. Beyond primary findings, previously reported lipid loci were fine-mapped using exome sequencing in IRASFS. These results support that exome sequencing complements and extends insights into the genetics of lipid levels.

Published
2018

27. Physiologic Interpretation of GWAS Signals for Type 2 Diabetes

Author

Richard M, Watanabe

Subjects
Phenotype, Diabetes Mellitus, Type 2, Quantitative Trait Loci, Animals, Humans, Genome-Wide Association Study
Abstract

This chapter reviews both statistical and physiologic issues related to the pathophysiologic effects of genetic variation in the context of type 2 diabetes. The goal is to review current methodologies used to analyze disease-related quantitative traits for those who do not have extensive quantitative and physiologic background, as an attempt to bridge that gap. We leverage mathematical modeling to illustrate the strengths and weaknesses of different approaches and attempt to reinforce with real data analysis. Topics reviewed include phenotype selection, phenotype specificity, multiple variant analysis via the genetic risk score, and consideration of multiple disease-related phenotypes. Type 2 diabetes is used as the example, not only because of the extensive existing knowledge at the genetic, physiologic, clinical, and epidemiologic levels, but also because type 2 diabetes has been at the forefront of complex disease genetics, with many examples to draw from.

Published
2018

28. Physiologic Interpretation of GWAS Signals for Type 2 Diabetes

Author

Richard M. Watanabe

Subjects
0301 basic medicine, Complex disease, Genome-wide association study, Type 2 diabetes, Computational biology, Quantitative trait locus, medicine.disease, 03 medical and health sciences, 030104 developmental biology, medicine, Leverage (statistics), Genetic risk, Psychology, Strengths and weaknesses
Abstract

This chapter reviews both statistical and physiologic issues related to the pathophysiologic effects of genetic variation in the context of type 2 diabetes. The goal is to review current methodologies used to analyze disease-related quantitative traits for those who do not have extensive quantitative and physiologic background, as an attempt to bridge that gap. We leverage mathematical modeling to illustrate the strengths and weaknesses of different approaches and attempt to reinforce with real data analysis. Topics reviewed include phenotype selection, phenotype specificity, multiple variant analysis via the genetic risk score, and consideration of multiple disease-related phenotypes. Type 2 diabetes is used as the example, not only because of the extensive existing knowledge at the genetic, physiologic, clinical, and epidemiologic levels, but also because type 2 diabetes has been at the forefront of complex disease genetics, with many examples to draw from.

Published
2018

29. An Islet-Targeted Genome-Wide Association Scan Identifies Novel Genes Implicated in Cytokine-Mediated Islet Stress in Type 2 Diabetes

Author

Lynne E. Wagenknecht, Richard M. Watanabe, Aaron J. Mackey, Poonam Sharma, Kent D. Taylor, Nicholette D. Palmer, Eden A. Dejene, Carl D. Langefeld, James W. Ramadan, Craig S. Nunemaker, and Stephen S. Rich

Subjects
Male, endocrine system, medicine.medical_specialty, Candidate gene, endocrine system diseases, medicine.medical_treatment, Interleukin-1beta, Population, Single-nucleotide polymorphism, Type 2 diabetes, Biology, Diabetes Mellitus, Experimental, Islets of Langerhans, Mice, Endocrinology, Receptor-Interacting Protein Serine-Threonine Kinase 2, Stress, Physiological, Internal medicine, medicine, Animals, Humans, education, Original Research, Oligonucleotide Array Sequence Analysis, Inflammation, education.field_of_study, geography, geography.geographical_feature_category, Factor XIII, Interleukin-6, Microarray analysis techniques, Gene Expression Profiling, Serine Endopeptidases, Membrane Proteins, Islet, medicine.disease, Cytokine, Diabetes Mellitus, Type 2, Lipotoxicity, Receptor-Interacting Protein Serine-Threonine Kinases, Serine Proteases, Carrier Proteins, Genome-Wide Association Study
Abstract

Genome-wide association studies in human type 2 diabetes (T2D) have renewed interest in the pancreatic islet as a contributor to T2D risk. Chronic low-grade inflammation resulting from obesity is a risk factor for T2D and a possible trigger of β-cell failure. In this study, microarray data were collected from mouse islets after overnight treatment with cytokines at concentrations consistent with the chronic low-grade inflammation in T2D. Genes with a cytokine-induced change of >2-fold were then examined for associations between single nucleotide polymorphisms and the acute insulin response to glucose (AIRg) using data from the Genetics Underlying Diabetes in Hispanics (GUARDIAN) Consortium. Significant evidence of association was found between AIRg and single nucleotide polymorphisms in Arap3 (5q31.3), F13a1 (6p25.3), Klhl6 (3q27.1), Nid1 (1q42.3), Pamr1 (11p13), Ripk2 (8q21.3), and Steap4 (7q21.12). To assess the potential relevance to islet function, mouse islets were exposed to conditions modeling low-grade inflammation, mitochondrial stress, endoplasmic reticulum (ER) stress, glucotoxicity, and lipotoxicity. RT-PCR revealed that one or more forms of stress significantly altered expression levels of all genes except Arap3. Thapsigargin-induced ER stress up-regulated both Pamr1 and Klhl6. Three genes confirmed microarray predictions of significant cytokine sensitivity: F13a1 was down-regulated 3.3-fold by cytokines, Ripk2 was up-regulated 1.5- to 3-fold by all stressors, and Steap4 was profoundly cytokine sensitive (167-fold up-regulation). Three genes were thus closely associated with low-grade inflammation in murine islets and also with a marker for islet function (AIRg) in a diabetes-prone human population. This islet-targeted genome-wide association scan identified several previously unrecognized candidate genes related to islet dysfunction during the development of T2D.

Published
2015

30. Variation inPPARGIs Associated With Longitudinal Change in Insulin Resistance in Mexican Americans at Risk for Type 2 Diabetes

Author

Enrique Trigo, Thomas A. Buchanan, Talin Haritunians, Jean M. Lawrence, Nan Wang, Anny H. Xiang, Kent D. Taylor, Richard M. Watanabe, Mary Helen Black, Miwa Takayanagi, and Jun Wu

Subjects
Adult, Male, Peroxisome proliferator-activated receptor gamma, medicine.medical_specialty, Proline, Cross-sectional study, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Clinical Biochemistry, Context (language use), Type 2 diabetes, Polymorphism, Single Nucleotide, Biochemistry, Young Adult, Endocrinology, Insulin resistance, Internal medicine, Mexican Americans, medicine, Humans, Genetic Predisposition to Disease, Longitudinal Studies, Alanine, business.industry, Insulin, Biochemistry (medical), Type 2 Diabetes Mellitus, Original Articles, medicine.disease, Obesity, PPAR gamma, Cross-Sectional Studies, Amino Acid Substitution, Diabetes Mellitus, Type 2, Female, Insulin Resistance, business
Abstract

Peroxisome proliferator-activated receptor gamma (PPARG) is a susceptibility locus for type 2 diabetes mellitus (T2DM). Although cross-sectional associations have been reported, primarily for Pro12Ala, few longitudinal studies in nondiabetic populations have been conducted.This study aimed to examine whether and to what extent variation in PPARG is associated with longitudinal changes in anthropometric and metabolic traits in Mexican Americans at risk for T2DM.Subjects were participants of BetaGene, a family-based study of obesity, insulin resistance, and β-cell function, who completed a baseline and follow-up study visit (n = 378; mean followup, 4.6 ± 1.5 y). Phenotypes included body fat assessed by dual-energy x-ray absorptiometry; insulin sensitivity (SI), acute insulin response, and β-cell function (disposition index; DI) were estimated from iv glucose tolerance tests with Minimal Model analysis. Eighteen tag single nucleotide polymorphisms (SNPs) capturing variation in a 156-kb region surrounding PPARG were tested for association with changes in longitudinal traits. P-values were Bonferroni-corrected for multiple testing.Six SNPs (rs2972164, rs11128598, rs17793951, rs1151996, rs1175541, rs3856806) were significantly associated with rate of change in SI after adjustment for age, sex, and body fat percentage, but not with changes in adiposity. rs17793951 also had a significant effect on change in DI over time. Association between rs1175541 and change in SI varied by changes in adiposity such that only carriers of the minor allele who reduced body fat over followup improved SI. rs1306470 (captured Pro12Ala, r(2) = 0.9) was not associated with rates of change in any traits and its effects were not modified by changes in adiposity.Variation in PPARG, but not Pro12Ala, contributes to declining SI and concomitant deterioration in β-cell function in Mexican Americans at risk for T2DM.

Published
2015

31. Living near a freeway is associated with lower bone mineral density among Mexican Americans

Author

Frank D. Gilliland, Richard M. Watanabe, Thomas A. Buchanan, Claudia M. Toledo-Corral, Maryam Taher, John Wilson, Roksana Karim, Zhanghua Chen, Rima Habre, Enrique Trigo, Fred Lurmann, Muhammad T. Salam, Theresa M. Bastain, and Anny H. Xiang

Subjects
Adult, Male, musculoskeletal diseases, medicine.medical_specialty, Bone density, Endocrinology, Diabetes and Metabolism, Osteoporosis, Overweight, California, Article, Absorptiometry, Photon, Bone Density, Residence Characteristics, Air Pollution, Mexican Americans, medicine, Humans, Pelvic Bones, Vehicle Emissions, Bone mineral, Anthropometry, business.industry, Environmental Exposure, Environmental exposure, medicine.disease, Obesity, Surgery, Osteopenia, Motor Vehicles, Socioeconomic Factors, Female, medicine.symptom, business, Environmental Monitoring, Demography
Abstract

We hypothesized that chronic exposures to traffic combustion products may lower bone mineral density (BMD). We found that proximity to freeways was associated with reduced BMD. Our findings suggest that traffic-related pollution may contribute to the occurrence of osteopenia and osteoporosis.Adults residing in rural areas have been linked with higher BMD. We aimed to determine if this difference is due in part to air pollution by examining the relationships between traffic metrics and ambient air pollution with total body and pelvic BMD.Mexican American adults (n = 1,175; mean 34 years; 72 % female) who had participated in the BetaGene study of air pollution, obesity, and insulin resistance were included in this analysis. Total body and pelvic BMD were estimated using dual-energy X-ray absorptiometry. Traffic and ambient air pollutant exposures were estimated at residences using location and ambient monitoring data. Variance component models were used to analyze the associations between residential distance to the nearest freeway and ambient air pollutants with BMD.Residential proximity to a freeway was associated with lower total body BMD (p-trend = 0.01) and pelvic BMD (p-trend = 0.03) after adjustment for age, sex, weight, and height. The adjusted mean total body and pelvic BMD in participants living within 500 m of a freeway were 0.02 and 0.03 g/cm(2) lower than participants living greater than 1,500 m from a freeway. These associations did not differ significantly by age, sex, or obesity status. Results were similar after further adjustment for body fat and weekly physical activity minutes. Ambient air pollutants (NO2, O3, and PM2.5) were not significantly associated with BMD.Traffic-related exposures in overweight and obese Mexican Americans may adversely affect BMD. Our findings indicate that long-term exposures to traffic may contribute to the occurrence of osteoporosis and its consequences.

Published
2015

32. Adults with long-duration type 2 diabetes have blunted glycemic and β -Cell function improvements after bariatric surgery

Author

Sangeeta R. Kashyap, Richard M. Watanabe, John P. Kirwan, Philip R. Schauer, Deepak L. Bhatt, Steven K. Malin, Beth Abood, Steven E. Nissen, James Bena, Stacy A. Brethauer, Vishesh Khanna, and Claire E. Pothier

Subjects
medicine.medical_specialty, Nutrition and Dietetics, business.industry, Endocrinology, Diabetes and Metabolism, Insulin, medicine.medical_treatment, Medicine (miscellaneous), Incretin, Blood sugar, Type 2 diabetes, medicine.disease, Obesity, 3. Good health, Surgery, Endocrinology, Weight loss, Diabetes mellitus, Internal medicine, medicine, medicine.symptom, business, Glycemic
Abstract

Objective: This study investigated the effect of type 2 diabetes duration on glucose regulation 24 months post-bariatric surgery. Methods: Twenty-seven adults with short- (

Published
2015

33. Genetic Variants Associated With Quantitative Glucose Homeostasis Traits Translate to Type 2 Diabetes in Mexican Americans: The GUARDIAN (Genetics Underlying Diabetes in Hispanics) Consortium

Author

Talin Haritunians, Craig L. Hanis, Nancy J. Cox, Yii-Der Ida Chen, Amy L. Williams, Laura J. Rasmussen-Torvik, Stephen S. Rich, Xiuqing Guo, Carlos A. Aguilar-Salinas, Rohit Varma, Noël P. Burtt, Clicerio Gonzalez-Villalpando, Carl D. Langefeld, W. Craig Johnson, Simin Liu, Nan Wang, Jerome I. Rotter, Jerry L. Nadler, Fouad Kandeel, Leslie J. Raffel, Xiaoyi Gao, Michael Y. Tsai, Darko Stefanovski, Thomas A. Buchanan, Jie Yao, Julie T. Ziegler, Lorena Orozco, Adrienne H. Williams, James S. Pankow, Jennifer E. Below, Rebecca D. Jackson, James Gauderman, Richard N. Bergman, Christopher A. Haiman, Tasha E. Fingerlin, Jill M. Norris, Mark O. Goodarzi, Heather M. Highland, Donald W. Bowden, Leora Henkin, Adrienne W. MacKay, Nicholette D. Palmer, Alicia Huerta-Chagoya, Richard M. Watanabe, Lynne E. Wagenknecht, Beverly M. Snively, Kent D. Taylor, Anny H. Xiang, and Jinrui Cui

Subjects
Blood Glucose, endocrine system diseases, Databases, Factual, Genotype, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Genome-wide association study, Type 2 diabetes, Quantitative trait locus, Medical and Health Sciences, Databases, Endocrinology & Metabolism, Clinical Research, Diabetes mellitus, Internal Medicine, Diabetes Mellitus, Genetics, Medicine, Glucose homeostasis, Homeostasis, Humans, Obesity, CDKAL1, Factual, Metabolic and endocrine, 2. Zero hunger, Genome, business.industry, Insulin, Diabetes, Human Genome, nutritional and metabolic diseases, Genetic Variation, Genetics/Genomes/Proteomics/Metabolomics, Hispanic or Latino, medicine.disease, Genetic architecture, Diabetes Mellitus, Type 2, Gene Expression Regulation, Hispanic Americans, business, human activities, Type 2, Genome-Wide Association Study
Abstract

© 2015 by the American Diabetes Association. Insulin sensitivity, insulin secretion, insulin clearance, and glucose effectiveness exhibit strong genetic components, although few studies have examined their genetic architecture or influence on type 2 diabetes (T2D) risk. We hypothesized that loci affecting variation in these quantitative traits influence T2D. We completed a multicohort genome-wide association study to search for loci influencing T2D-related quantitative traits in 4,176 Mexican Americans. Quantitative traits were measured by the frequently sampled intravenous glucose tolerance test (four cohorts) or euglycemic clamp (three cohorts), and random-effects models were used to test the association between loci and quantitative traits, adjusting for age, sex, and admixture proportions (Discovery). Analysis revealed a significant (P < 5.00 3 1028) association at 11q14.3 (MTNR1B) with acute insulin response. Loci with P < 0.0001 among the quantitative traits were examined for translation to T2D risk in 6,463 T2D case and 9,232 control subjects of Mexican ancestry (Translation). Nonparametric meta- Analysis of the Discovery and Translation cohorts identified significant associations at 6p24 (SLC35B3/TFAP2A) with glucose effectiveness/T2D, 11p15 (KCNQ1) with disposition index/T2D, and 6p22 (CDKAL1) and 11q14 (MTNR1B) with acute insulin response/T2D. These results suggest that T2D and insulin secretion and sensitivity have both shared and distinct genetic factors, potentially delineating genomic components of these quantitative traits that drive the risk for T2D.

Published
2014

34. Postprandial effect to decrease soluble epoxide hydrolase activity: roles of insulin and gut microbiota

Author

Richard M. Watanabe, Debin Wan, Jun Yang, Jang H. Youn, Young Taek Oh, and Bruce D. Hammock

Subjects
0301 basic medicine, Male, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Clinical Biochemistry, Wistar, 030204 cardiovascular system & hematology, medicine.disease_cause, FFA epoxides, Biochemistry, 0302 clinical medicine, Models, Insulin Secretion, Glucose homeostasis, Insulin, Meals, Epoxide Hydrolases, Nutrition and Dietetics, Chemistry, Diabetes, Glucose clamp technique, Postprandial Period, Cardiovascular disease, Anti-Bacterial Agents, Dietary potassium, Postprandial, Cardiovascular Diseases, 5.1 Pharmaceuticals, cardiovascular system, Oxylipin analysis, Development of treatments and therapeutic interventions, Algorithms, Epoxide hydrolase 2, medicine.medical_specialty, Dietary, Models, Biological, Article, 03 medical and health sciences, Food Sciences, Internal medicine, Complementary and Integrative Health, medicine, Animals, Oxylipins, Rats, Wistar, Molecular Biology, Metabolic and endocrine, Nutrition, Nutrition & Dietetics, Potassium, Dietary, Reproducibility of Results, Lipid signaling, Oxylipin, Biological, Rats, Gastrointestinal Microbiome, Oxidative Stress, 030104 developmental biology, Endocrinology, Solubility, Potassium, Glucose Clamp Technique, Eicosanoids, Biochemistry and Cell Biology, Oxidative stress, Biomarkers
Abstract

Epoxides of free fatty acids (FFAs), especially epoxyeicosatrienoic acids (EETs), are lipid mediators with beneficial effects in metabolic and cardiovascular (CV) health. FFA epoxides are quickly metabolized to biologically less active diols by soluble epoxide hydrolase (sEH). Inhibition of sEH, which increases EET levels, improves glucose homeostasis and CV health and is proposed as an effective strategy for the treatment of diabetes and CV diseases. Here, we show evidence that sEH activity is profoundly reduced in postprandial states in rats; plasma levels of 17 sEH products (i.e., FFA diols), detected by targeted oxylipin analysis, all decreased after a meal. In addition, the ratios of sEH product to substrate (sEH P/S ratios), which may reflect sEH activity, decreased ~70% on average 2.5 h after a meal in rats (P < 0.01). To examine whether this effect was mediated by insulin action, a hyperinsulinemic euglycemic clamp was performed for 2.5 h, and sEH P/S ratios were assessed before and after the clamp. The clamp resulted in small increases rather than decreases in sEH P/S ratios (P < 0.05), indicating that insulin cannot account for the postprandial decrease in sEH P/S ratios. Interestingly, in rats treated with antibiotics to deplete gut bacteria, the postprandial effect to decrease sEH P/S ratios was completely abolished, suggesting that a gut bacteria-derived factor(s) may be responsible for the effect. Further studies are warranted to identify such a factor(s) and elucidate the mechanism by which sEH activity (or sEH P/S ratio) is reduced in postprandial states.

Published
2017

35. A genome-wide association study of IVGTT-based measures of first-phase insulin secretion refines the underlying physiology of type 2 diabetes variants

Author

Jaakko Tuomilehto, Lorena Boquete-Vilarino, Andrea Natali, Robert L. Hanson, Anny H. Xiang, Markku Laakso, Nicholette D. Palmer, Donald W. Bowden, Ewan R. Pearson, Oluf Pedersen, Leen M 't Hart, Jussi Paananen, Francis S. Collins, Anne U. Jackson, Mark I. McCarthy, Dorret I. Boomsma, Richard M. Watanabe, Karina Banasik, Nienke van Leewen, Anette P. Gjesing, Christopher J. Groves, Andreas Fritsche, Timon W. van Haeften, Karen L. Mohlke, Michael Boehnke, Anubha Mahajan, Nan Wang, Lynne E. Wagenknecht, Mark H. H. Kramer, Jill M. Norris, Timothy M. Frayling, Andrew R. Wood, Alena Stančáková, Annemarie M. C. Simonis-Bik, Giel Nijpels, Eco J. C. de Geus, Leslie J. Baier, Andrea Mari, Kent D. Taylor, Torben Hansen, Niels Grarup, Thomas A. Buchanan, Anna Jonsson, Elisabeth M. W. Eekhoff, Hans Eiberg, Richard N. Bergman, Mark Walker, Sayuko Kobes, Joris Deelen, Yii-Derr Chen, Ulf Smith, Internal medicine, ACS - Diabetes & metabolism, AGEM - Endocrinology, metabolism and nutrition, AMS - Musculoskeletal Health, AMS - Physical Functioning in Major Disease, General practice, APH - Health Behaviors & Chronic Diseases, Biological Psychology, APH - Mental Health, APH - Methodology, and Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Blood Glucose, Genotyping Techniques, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Type 2 diabetes, chemistry.chemical_compound, Endocrinology, Insulin-Secreting Cells, Insulin Secretion, Insulin, Alleles, C-Peptide, Diabetes Mellitus, Type 2, Genetic Variation, Genome-Wide Association Study, Genotype, Glucose Tolerance Test, Humans, Linear Models, Liver, Transcription Factor 7-Like 2 Protein, Internal Medicine, Glucose tolerance test, medicine.diagnostic_test, C-peptide, Genetics/Genomes/Proteomics/Metabolomics, Diabetes and Metabolism, Type 2, Insulin processing, medicine.medical_specialty, Diabetes risk, Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Diabetes mellitus, Internal medicine, medicine, Journal Article, Diabetes Mellitus, medicine.disease, 030104 developmental biology, chemistry, TCF7L2
Abstract

Understanding the physiological mechanisms by which common variants predispose to type 2 diabetes requires large studies with detailed measures of insulin secretion and sensitivity. Here we performed the largest genome-wide association study of first-phase insulin secretion, as measured by intravenous glucose tolerance tests, using up to 5,567 individuals without diabetes from 10 studies. We aimed to refine the mechanisms of 178 known associations between common variants and glycemic traits and identify new loci. Thirty type 2 diabetes or fasting glucose–raising alleles were associated with a measure of first-phase insulin secretion at P < 0.05 and provided new evidence, or the strongest evidence yet, that insulin secretion, intrinsic to the islet cells, is a key mechanism underlying the associations at the HNF1A, IGF2BP2, KCNQ1, HNF1B, VPS13C/C2CD4A, FAF1, PTPRD, AP3S2, KCNK16, MAEA, LPP, WFS1, and TMPRSS6 loci. The fasting glucose–raising allele near PDX1, a known key insulin transcription factor, was strongly associated with lower first-phase insulin secretion but has no evidence for an effect on type 2 diabetes risk. The diabetes risk allele at TCF7L2 was associated with a stronger effect on peak insulin response than on C-peptide–based insulin secretion rate, suggesting a possible additional role in hepatic insulin clearance or insulin processing. In summary, our study provides further insight into the mechanisms by which common genetic variation influences type 2 diabetes risk and glycemic traits.

Published
2017

36. Antiretroviral therapy modifies the genetic effect of known type 2 diabetes-associated risk variants in HIV-infected women

Author

Richard M. Watanabe, Chenglong Liu, Celeste Leigh Pearce, Melissa A. Frasco, Kathryn Anastos, David Van Den Berg, Phyllis C. Tien, Roksana Karim, Stephen J. Gange, Mardge H. Cohen, Wendy J. Mack, and Deborah Gustafson

Subjects
Adult, Cart, medicine.medical_specialty, Adolescent, Immunology, Population, HIV Infections, Context (language use), Type 2 diabetes, Risk Assessment, Article, Cohort Studies, Young Adult, immune system diseases, Antiretroviral Therapy, Highly Active, Diabetes mellitus, Internal medicine, Ethnicity, medicine, Humans, Immunology and Allergy, Genetic Predisposition to Disease, Prospective Studies, education, Aged, Aged, 80 and over, education.field_of_study, Reverse-transcriptase inhibitor, business.industry, Hazard ratio, virus diseases, Type 2 Diabetes Mellitus, Middle Aged, medicine.disease, Infectious Diseases, Anti-Retroviral Agents, Diabetes Mellitus, Type 2, Female, business, medicine.drug
Abstract

OBJECTIVE Type 2 diabetes mellitus incidence is increased in HIV-infected persons. We examined the associations of diabetes mellitus with known diabetes mellitus-risk alleles from the general population in the context of HIV infection, and explored effect modification by combination antiretroviral therapy (cART). METHODS The Women's Interagency HIV Study is a prospective cohort of HIV-infected women. Seventeen European-derived diabetes mellitus-risk polymorphisms were genotyped in the eligible participants of the Women's Interagency HIV Study. Analyses were run separately for non-African Americans (Whites, Hispanics, Asians, and other; n = 378, 49 with incident diabetes mellitus) and African Americans (n = 591, 49 with incident diabetes mellitus). Cox proportional-hazards models were fit to estimate hazard ratios for diabetes mellitus overall and within strata of cART. RESULTS In non-African Americans, heterogeneity across cART regimen was observed for nine of the 14 polymorphisms (phet

Published
2014

37. Impact of Type 2 Diabetes Susceptibility Variants on Quantitative Glycemic Traits Reveals Mechanistic Heterogeneity

Author

J. Graessler, Ulf Smith, Marie-France Hivert, Antigone S. Dimas, Joshua W. Knowles, Stéphane Cauchi, Karen L. Mohlke, Michael Boehnke, David Meyre, Nicholas J. Wareham, Ci Song, Denis Rybin, Erik Ingelsson, Mario A. Morken, Anne U. Jackson, Michael R. Erdos, Peter Kovacs, Fahim Abbasi, Claudia Langenberg, Ke Hao, Andreas Pfeiffer, Thomas Quertemous, Lars Lind, Stefan R. Bornstein, Suzannah Bumpstead, Alena Stančáková, Lori L. Bonnycastle, Michael Stumvoll, Oluf Pedersen, Themistocles L. Assimes, Inês Barroso, Andrea Benazzo, Richard M. Watanabe, Magic Investigators, Josée Dupuis, Inga Prokopenko, Heather M. Stringham, Felicity Payne, Markku Laakso, Antje Fischer-Rosinsky, Francis S. Collins, Mark Walker, James B. Meigs, Torben Hansen, Peter Schwarz, Xia Yang, Yvonne Böttcher, Hans-Ulrich Häring, Anke Tönjes, Narisu Narisu, Cécile Lecoeur, Jaakko Tuomilehto, Reedik Mägi, Joachim Spranger, Amy J. Swift, Johanna Kuusisto, Jose C. Florez, Niels Grarup, Philippe Froguel, Vasiliki Lagou, Peter S. Chines, Mark I. McCarthy, Adam Barker, Trine Welløv Boesgaard, and Richard N. Bergman

Subjects
Male, Endocrinology, Diabetes and Metabolism, Insulin Resistance/genetics, Type 2 diabetes, Medical and Health Sciences, Endocrinology, 0302 clinical medicine, Gene Frequency, Risk Factors, Insulin-Secreting Cells, Insulin Secretion, 2.1 Biological and endogenous factors, Cluster Analysis, Insulin, Aetiology, 2. Zero hunger, Genetics, 0303 health sciences, SLC30A8, Medicine (all), Diabetes, Single Nucleotide, Diabetes and Metabolism, Diabetes Mellitus, Type 2/genetics, Female, Type 2, Insulin processing, medicine.medical_specialty, Insulin/metabolism, Quantitative Trait Loci, Socio-culturale, 030209 endocrinology & metabolism, Biology, Autoimmune Disease, Polymorphism, Single Nucleotide, MAGIC Investigators, Endocrinology & Metabolism, 03 medical and health sciences, Insulin-Secreting Cells/metabolism, Insulin resistance, Clinical Research, Alleles, Diabetes Mellitus, Type 2, Genetic Variation, Genome-Wide Association Study, Humans, Insulin Resistance, Transcription Factors, Genetic Predisposition to Disease, Internal Medicine, Diabetes mellitus, Internal medicine, Genetic model, Diabetes Mellitus, medicine, Transcription Factors/metabolism, Polymorphism, Metabolic and endocrine, 030304 developmental biology, Glycemic, Prevention, medicine.disease, biology.protein, Quantitative Trait Loci/genetics, TCF7L2
Abstract

Patients with established type 2 diabetes display both beta-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF712, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition. Patients with established type 2 diabetes display both b-cell dysfunction and insulin resistance. To define fundamental processes leading to the diabetic state, we examined the relationship between type 2 diabetes risk variants at 37 established susceptibility loci, and indices of proinsulin processing, insulin secretion, and insulin sensitivity. We included data from up to 58,614 nondiabetic subjects with basal measures and 17,327 with dynamic measures. We used additive genetic models with adjustment for sex, age, and BMI, followed by fixed-effects, inverse-variance meta-analyses. Cluster analyses grouped risk loci into five major categories based on their relationship to these continuous glycemic phenotypes. The first cluster (PPARG, KLF14, IRS1, GCKR) was characterized by primary effects on insulin sensitivity. The second cluster (MTNR1B, GCK) featured risk alleles associated with reduced insulin secretion and fasting hyperglycemia. ARAP1 constituted a third cluster characterized by defects in insulin processing. A fourth cluster (TCF7L2, SLC30A8, HHEX/IDE, CDKAL1, CDKN2A/2B) was defined by loci influencing insulin processing and secretion without a detectable change in fasting glucose levels. The final group contained 20 risk loci with no clear-cut associations to continuous glycemic traits. By assembling extensive data on continuous glycemic traits, we have exposed the diverse mechanisms whereby type 2 diabetes risk variants impact disease predisposition.

Published
2014

38. Genetic variation in MTNR1B is associated with gestational diabetes mellitus and contributes only to the absolute level of beta cell compensation in Mexican Americans

Author

Richard M. Watanabe, Miwa Takayanagi, Jie Ren, Jaana Hartiala, Jean M. Lawrence, Hooman Allayee, Elizabeth Beale, Enrique Trigo, Thomas A. Buchanan, Joyce M. Richey, and Anny H. Xiang

Subjects
Adult, Blood Glucose, Male, medicine.medical_specialty, Cross-sectional study, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Polymorphism, Single Nucleotide, Article, Young Adult, Insulin resistance, Pregnancy, Insulin-Secreting Cells, Internal medicine, Diabetes mellitus, Mexican Americans, Genetic variation, Internal Medicine, medicine, Humans, Insulin, Genetic Predisposition to Disease, Genetic Association Studies, Glucose tolerance test, medicine.diagnostic_test, Receptor, Melatonin, MT2, business.industry, Glucose Tolerance Test, Middle Aged, medicine.disease, Gestational diabetes, Diabetes, Gestational, Cross-Sectional Studies, Endocrinology, Trait, Female, Insulin Resistance, business
Abstract

MTNR1B is a type 2 diabetes susceptibility locus associated with cross-sectional measures of insulin secretion. We hypothesised that variation in MTNR1B contributes to the absolute level of a diabetes-related trait, temporal rate of change in that trait, or both.We tested rs10830963 for association with cross-sectional diabetes-related traits in up to 1,383 individuals or with rate of change in the same phenotypes over a 3-5 year follow-up in up to 374 individuals from the family-based BetaGene study of Mexican Americans.rs10830963 was associated cross-sectionally with fasting glucose (p = 0.0069), acute insulin response (AIR; p = 0.0013), disposition index (p = 0.00078), glucose effectiveness (p = 0.018) and gestational diabetes mellitus (OR 1.48; p = 0.012), but not with OGTT 30 min Δinsulin (the difference between the 30 min and fasting plasma insulin concentration) or 30 min insulin-based disposition index. rs10830963 was also associated with rate of change in fasting glucose (p = 0.043), OGTT 30 min Δinsulin (p = 0.01) and AIR (p = 0.037). There was no evidence for an association with the rate of change in beta cell compensation for insulin resistance.We conclude that variation in MTNR1B contributes to the absolute level of insulin secretion but not to differences in the temporal rate of change in insulin secretion. The observed association with the rate of change in insulin secretion reflects the natural physiological response to changes in underlying insulin sensitivity and is not a direct effect of the variant.

Published
2014

39. Insulin Sensitivity and Insulin Clearance Are Heritable and Have Strong Genetic Correlation in Mexican Americans

Author

Anny H. Xiang, Carl D. Langefeld, Yii-Der Ida Chen, Richard M. Watanabe, Lynne E. Wagenknecht, Jerome I. Rotter, Steven M. Haffner, Xiuqing Guo, Carlos Lorenzo, Jerry L. Nadler, Leslie J. Raffel, Stephen S. Rich, Thomas A. Buchanan, Mark O. Goodarzi, Donald W. Bowden, Anthony J. Hanley, Jill M. Norris, Marian Rewers, Tasha E. Fingerlin, Richard N. Bergman, and Fouad Kandeel

Subjects
Genetics, Glucose tolerance test, medicine.medical_specialty, Nutrition and Dietetics, medicine.diagnostic_test, business.industry, Endocrinology, Diabetes and Metabolism, Insulin, medicine.medical_treatment, Medicine (miscellaneous), Genome-wide association study, Heritability, Glucose clamp technique, medicine.disease, Genetic correlation, Endocrinology, Insulin resistance, Diabetes mellitus, Internal medicine, Medicine, business
Abstract

Objective We describe the GUARDIAN (Genetics UndeRlying DIAbetes in HispaNics) consortium, along with heritability estimates and genetic and environmental correlations of insulin sensitivity and metabolic clearance rate of insulin (MCRI).

Published
2014

40. HOMA and Matsuda indices of insulin sensitivity: poor correlation with minimal model-based estimates of insulin sensitivity in longitudinal settings

Author

Richard M. Watanabe, Thomas A. Buchanan, and Anny H. Xiang

Subjects
Adult, Blood Glucose, Male, medicine.medical_specialty, endocrine system diseases, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, Article, Body Mass Index, Minimal model, Insulin resistance, Internal medicine, Internal Medicine, medicine, Humans, Hypoglycemic Agents, Insulin, Longitudinal Studies, Poor correlation, Glucose tolerance test, Pioglitazone, medicine.diagnostic_test, business.industry, Reproducibility of Results, nutritional and metabolic diseases, Insulin sensitivity, Fasting, Glucose Tolerance Test, medicine.disease, Cross-Sectional Studies, Endocrinology, Female, Thiazolidinediones, Insulin Resistance, business, Body mass index, Biomarkers, medicine.drug
Abstract

Little is known about the performance of surrogates in assessing changes in insulin sensitivity over time. This report compared updated HOMA of insulin sensitivity (HOMA2-%S) and the Matsuda index from OGTTs with minimal model-based estimates of insulin sensitivity (SI) from frequently sampled IVGTTs (FSIGTs) in longitudinal settings and cross-sectional settings.Two longitudinal studies were used: one a natural observational study in which 338 individuals were followed for a median of 4 years; one a clinical treatment study in which 97 individuals received pioglitazone treatment and were followed for 1 year. Pairs of OGTTs and FSIGTs were performed at baseline and follow-up. Correlations were computed. Impact of measurement uncertainty was investigated through simulation studies.Correlations between HOMA2-%S and SI from baseline or follow-up data were in the range reported previously (0.61-0.69). By contrast, correlations for changes over time were only 0.35-0.39. The corresponding correlations between the Matsuda index and SI were 0.66-0.72 for cross-sectional data and 0.40-0.48 for longitudinal change. Correlations for changes were significantly lower than the cross-sectional correlations in both studies (p 0.03). Simulation results demonstrated that the reduced correlations for change were not explained by error propagation, supporting a real limitation of surrogates to fully capture longitudinal changes in insulin sensitivity.HOMA and Matsuda indices derived from cross-sectional data should be used cautiously in assessing longitudinal changes in insulin sensitivity.

Published
2013

41. Metabolic Effects of Bariatric Surgery in Patients With Moderate Obesity and Type 2 Diabetes

Author

Philip R. Schauer, Manjula K. Gupta, Beth Abood, Kathy Wolski, John P. Kirwan, Claire E. Pothier, Steven E. Nissen, Sangeeta R. Kashyap, Richard M. Watanabe, Deepak L. Bhatt, Stacy A. Brethauer, and Muhammad A. Abdul-Ghani

Subjects
medicine.medical_specialty, Sleeve gastrectomy, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, 030209 endocrinology & metabolism, Type 2 diabetes, 030204 cardiovascular system & hematology, law.invention, 03 medical and health sciences, 0302 clinical medicine, Insulin resistance, Randomized controlled trial, law, Weight loss, Diabetes mellitus, Internal Medicine, medicine, Glycemic, Advanced and Specialized Nursing, business.industry, medicine.disease, 3. Good health, Surgery, Gastrectomy, medicine.symptom, business
Abstract

OBJECTIVE To evaluate the effects of two bariatric procedures versus intensive medical therapy (IMT) on β-cell function and body composition. RESEARCH DESIGN AND METHODS This was a prospective, randomized, controlled trial of 60 subjects with uncontrolled type 2 diabetes (HbA1c 9.7 ± 1%) and moderate obesity (BMI 36 ± 2 kg/m2) randomized to IMT alone, IMT plus Roux-en-Y gastric bypass, or IMT plus sleeve gastrectomy. Assessment of β-cell function (mixed-meal tolerance testing) and body composition was performed at baseline and 12 and 24 months. RESULTS Glycemic control improved in all three groups at 24 months (N = 54), with a mean HbA1c of 6.7 ± 1.2% for gastric bypass, 7.1 ± 0.8% for sleeve gastrectomy, and 8.4 ± 2.3% for IMT (P < 0.05 for each surgical group versus IMT). Reduction in body fat was similar for both surgery groups, with greater absolute reduction in truncal fat in gastric bypass versus sleeve gastrectomy (−16 vs. −10%; P = 0.04). Insulin sensitivity increased significantly from baseline in gastric bypass (2.7-fold; P = 0.004) and did not change in sleeve gastrectomy or IMT. β-Cell function (oral disposition index) increased 5.8-fold in gastric bypass from baseline, was markedly greater than IMT (P = 0.001), and was not different between sleeve gastrectomy versus IMT (P = 0.30). At 24 months, β-cell function inversely correlated with truncal fat and prandial free fatty acid levels. CONCLUSIONS Bariatric surgery provides durable glycemic control compared with intensive medical therapy at 2 years. Despite similar weight loss as sleeve gastrectomy, gastric bypass uniquely restores pancreatic β-cell function and reduces truncal fat, thus reversing the core defects in diabetes.

Published
2013

42. Compensatory responses to insulin resistance in obese African-American and Latina girls

Author

Michael I. Goran, Rebecca E. Hasson, Jaimie N. Davis, Tanja C. Adam, and Richard M. Watanabe

Subjects
African american, medicine.medical_specialty, Nutrition and Dietetics, business.industry, Health Policy, Insulin, medicine.medical_treatment, Public Health, Environmental and Occupational Health, medicine.disease, Glucagon-like peptide-1, Insulin resistance, Endocrinology, Intravenous glucose, Internal medicine, Pediatrics, Perinatology and Child Health, medicine, Oral glucose tolerance, business, Body mass index, ACUTE INSULIN RESPONSE
Abstract

Summary Purpose: Insulin responses to oral and intravenous glucose markedly differ by ethnicity. This study examined whether ethnic differences in pancreatic insulin secretion, hepatic insulin extraction and clearance explain these disparate findings in 35 obese African–American and 41 Latina girls (Tanner Stages: IV–V; ages: 14–18; body mass index percentile: 85.9–99.8%). Methods: Pancreatic insulin secretion, hepatic insulin extraction and clearance were estimated by C-peptide and insulin modeling during an oral glucose tolerance test. Insulin sensitivity (SI), acute insulin response to glucose (AIRG) and disposition index were derived from a frequently sampled intravenous glucose tolerance test. Results: Compared to Latinas, obese African–American adolescents had lower pancreatic insulin secretion (21.3%; P 0.05). Conclusions: Compensatory mechanisms to insulin resistance do not appear to explain the ethnic differences in insulin responses to oral and intravenous glucose in obese African–American and Latina girls.

Published
2013

43. High-Fat Diet Is Associated with Obesity-Mediated Insulin Resistance and β-Cell Dysfunction in Mexican Americans

Author

Miwa Takayanagi, Mary Helen Black, Jean M. Lawrence, Enrique Trigo, Anny H. Xiang, Thomas A. Buchanan, and Richard M. Watanabe

Subjects
Adult, Male, medicine.medical_specialty, Adolescent, medicine.medical_treatment, Medicine (miscellaneous), Biology, Diet, High-Fat, Body fat percentage, Body Mass Index, Insulin resistance, Pregnancy, Classification of obesity, Insulin-Secreting Cells, Internal medicine, Diabetes mellitus, Mexican Americans, Dietary Carbohydrates, medicine, Humans, Nutritional Epidemiology, Obesity, Adiposity, Aged, Glucose tolerance test, Nutrition and Dietetics, Anthropometry, medicine.diagnostic_test, Insulin, Glucose Tolerance Test, Middle Aged, medicine.disease, Diet, Diabetes, Gestational, Endocrinology, Body Composition, Female, Dietary Proteins, Insulin Resistance, Energy Intake, Body mass index
Abstract

Consumption of energy-dense, nutrient-poor foods has contributed to the rising incidence of obesity and may underlie insulin resistance and β-cell dysfunction. Macronutrient intake patterns were examined in relation to anthropometric and metabolic traits in participants of BetaGene, a family-based study of obesity, insulin resistance, and β-cell dysfunction in Mexican Americans. Dietary intake, body composition, insulin sensitivity (SI), and β-cell function [Disposition Index (DI)] were assessed by food-frequency questionnaires, dual-energy X-ray absorptiometry, and intravenous glucose-tolerance tests, respectively. Patterns of macronutrient intake were identified by using a K-means model based on the proportion of total energy intake per day attributable to carbohydrate, fat, and protein and were tested for association with anthropometric and metabolic traits. Among 1150 subjects aged 18–65 y (73% female), tertiles of fat intake were associated with greater adiposity and lower SI, after adjustment for age, sex, and daily energy intake. Moreover, 3 distinct dietary patterns were identified: “high fat” (35% fat, 44% carbohydrate, 21% protein; n = 238), “moderate fat” (28% fat, 54% carbohydrate, 18% protein; n = 520), and “low fat” (20% fat, 65% carbohydrate, 15% protein; n = 392). Compared with the low-fat group, the high-fat group had higher age- and sex-adjusted mean body mass index, body fat percentage, and trunk fat and lower SI and DI. Further adjustment for daily energy intake by matching individuals across dietary pattern groups yielded similar results. None of the observed associations were altered after adjustment for physical activity; however, associations with SI and DI were attenuated after adjustment for adiposity. These findings suggest that high-fat diets may contribute to increased adiposity and concomitant insulin resistance and β-cell dysfunction in Mexican Americans.

Published
2013

44. Self-Reported Physical Activity Is Associated With β-Cell Function in Mexican American Adults

Author

Jean M. Lawrence, Miwa Takayanagi, Zhanghua Chen, Thomas A. Buchanan, Enrique Trigo, Richard M. Watanabe, Anny H. Xiang, and Mary Helen Black

Subjects
Adult, Blood Glucose, Male, Research design, medicine.medical_specialty, Adolescent, Endocrinology, Diabetes and Metabolism, medicine.medical_treatment, 030209 endocrinology & metabolism, Motor Activity, 030204 cardiovascular system & hematology, Body Mass Index, Young Adult, 03 medical and health sciences, Absorptiometry, Photon, 0302 clinical medicine, Insulin-Secreting Cells, Diabetes mellitus, Internal medicine, Mexican Americans, Internal Medicine, medicine, Humans, Insulin, Epidemiology/Health Services Research, Young adult, Original Research, Aged, 2. Zero hunger, Advanced and Specialized Nursing, business.industry, Middle Aged, medicine.disease, Obesity, Endocrinology, Cohort, Female, Blood sugar regulation, business, Body mass index
Abstract

OBJECTIVE To examine the association between self-reported physical activity (PA) and diabetes-related quantitative traits. RESEARCH DESIGN AND METHODS The observational cohort was 1,152 Mexican American adults with dual-energy X-ray absorptiometry, oral and intravenous glucose tolerance tests, and self-reported dietary and PA questionnaires. PA was categorized into three mutually exclusive groups according to the U.S. Department of Health and Human Services PA guidelines for Americans: low (vigorous RESULTS The participants’ mean age was 35 years (range, 18–66 years), mean BMI was 29.6 kg/m2, and 73% were female. Among them, 501 (43%), 448 (39%), and 203 (18%) were classified as having low, moderate, and high PA, respectively. After adjustment for age, a higher PA was significantly associated with lower 2-h glucose, fasting insulin, and 2-h insulin and greater β-cell function (P = 0.001, 0.0003, 0.0001, and 0.004, respectively). The association did not differ significantly by sex. Results were similar after further adjustment for age, sex, BMI, or percent body fat. CONCLUSIONS An increasing level of PA is associated with a better glucose and insulin profile and enhanced β-cell function that is not explained by differences in BMI or percent body fat. Our results suggest that PA can be beneficial to β-cell function and glucose regulation independent of obesity.

Published
2013

45. Exome array analysis identifies new loci and low-frequency variants influencing insulin processing and secretion

Author

Anne U. Jackson, Jeroen R. Huyghe, Jane Romm, Johanna Kuusisto, Laura J. Scott, Lingyao Yang, Kimberly F. Doheny, Gonçalo R. Abecasis, Tanya M. Teslovich, Hyun Min Kang, Francis S. Collins, Mark J. Daly, Richard M. Watanabe, Michael Boehnke, Benjamin M. Neale, Marie P. Fogarty, Elizabeth W. Pugh, Hua Ling, Heather M. Stringham, Peter S. Chines, Markku Laakso, Alena Stančáková, Henna Cederberg, Martin L. Buchkovich, Karen L. Mohlke, Christian Fuchsberger, Roxann G. Ingersoll, Xueling Sim, and Ivy McMullen

Subjects
Genetics, education.field_of_study, Insulin, medicine.medical_treatment, Population, Biology, medicine.disease, medicine, Metabolic syndrome, education, Exome, Allele frequency, Glycemic, Insulin processing, Proinsulin
Abstract

Karen Mohlke, Markku Laakso, Michael Boehnke and colleagues report the first application of the Illumina HumanExome Beadchip array, examining association with insulin and glycemic traits in 8,229 nondiabetic Finnish males from the population-based Metabolic Syndrome in Men (METSIM) study. They identify low-frequency coding variants at both known and newly associated loci with insulin processing and secretion.

Published
2012

46. Six new loci associated with body mass index highlight a neuronal influence on body weight regulation

Author

Angelo Scuteri, Chris Wallace, Rachel Hackett, Sonja I. Berndt, Richard B. Hayes, Peter Vollenweider, Susan M. Ring, Lauren Gianniny, Alistair S. Hall, Christopher J. Gillson, Karani Santhanakrishnan Vimaleswaran, Karol Estrada, Thomas Meitinger, Kay-Tee Khaw, Nicholas J. Timpson, Willem H. Ouwehand, Cristen J. Willer, Andy R Ness, Peter S. Chines, Wendy L. McArdle, I. Sadaf Farooqi, Eleftheria Zeggini, Jouko Saramies, Amanda J. Bennett, Matthew A. Sims, Richard M. Watanabe, David M. Evans, Patricia B. Munroe, Toshiko Tanaka, Francis S. Collins, Peter Kraft, Morris Brown, Inês Barroso, Sheila Bingham, John M. C. Connell, Jian'an Luan, Pekka Jousilahti, Amanda F. Elliott, Lachlan J. M. Coin, Parimal Deodhar, Kijoung Song, Ruth J. F. Loos, Eleanor Wheeler, George Davey Smith, Kate Northstone, Joshua C. Randall, Claudia Lamina, André G. Uitterlinden, Dawn M. Waterworth, Tim D. Spector, Robert Luben, Veikko Salomaa, Vincent Mooser, Candace Guiducci, Andrew T. Hattersley, Guillaume Lettre, Guangju Zhai, Gonçalo R. Abecasis, Jaana Laitinen, Cyrus Cooper, David J. Hunter, Noël P. Burtt, Timo T. Valle, Carolin Purmann, Narisu Narisu, Lori L. Bonnycastle, Steven A. McCarroll, Christian Gieger, Albert Hofman, Laura J. Scott, Iris M. Heid, Lu Qi, Kevin B. Jacobs, Toby Johnson, Cornelia M. van Duijn, David Altshuler, David Hadley, Marjo-Riitta Järvelin, Johannes Hebebrand, Stephen J. Chanock, Stephen O'Rahilly, Jaakko Tuomilehto, Cecilia M. Lindgren, Y. C. Loraine Tung, Panagiotis Deloukas, Manjinder S. Sandhu, H-Erich Wichmann, Antonella Mulas, Matthew G. Rees, Jack M. Guralnik, Elaine M. Dennison, Timothy M. Frayling, David P. Strachan, Jonathan Stephens, Inga Prokopenko, Mikko Kuokkanen, Shengxu Li, Leif Groop, Jing Hua Zhao, Paul Elliott, David Schlessinger, Ken K. Ong, Peter Almgren, Massimo Mangino, Manuela Uda, Zorica Jovanovic, Karen L. Mohlke, Leena Peltonen, Michael N. Weedon, Elizabeth K. Speliotes, Markku Laakso, Bo Isomaa, Serena Sanna, Mark J. Caulfield, Gérard Waeber, Martin Ridderstråle, Luigi Ferrucci, Anne U. Jackson, Suzanne Stevens, Aimo Ruokonen, Jacqueline C. M. Witteman, Nicole Soranzo, Kaisa Silander, Mark I. McCarthy, Joel N. Hirschhorn, Nilesh J. Samani, Frank B. Hu, Michael R. Erdos, Paul Scheet, Leonie C. Jacobs, Rosa Maria Roccasecca, Heather M. Stringham, Helen N. Lyon, Konstantinos A. Papadakis, Aki S. Havulinna, Michael Boehnke, Richard N. Bergman, Nicholas J. Wareham, M. Carola Zillikens, Nicholas A. Watkins, Tiinamaija Tuomi, Fernando Rivadeneira, Noha Lim, Edward G. Lakatta, and Johanna Kuusisto

Subjects
Central Nervous System, medicine.medical_specialty, Quantitative Trait Loci, Medizin, Gene Dosage, 030209 endocrinology & metabolism, Genome-wide association study, Locus (genetics), Biology, FTO gene, Polymorphism, Single Nucleotide, Article, Body Mass Index, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Quantitative Trait, Heritable, SH2B1, Meta-Analysis as Topic, Internal medicine, Genetics, medicine, Humans, Genetic Predisposition to Disease, Obesity, Alleles, 030304 developmental biology, 2. Zero hunger, 0303 health sciences, Neuronal growth regulator 1, Anthropometry, Genetics of obesity, Body Weight, 3. Good health, Endocrinology, Alpha-Ketoglutarate-Dependent Dioxygenase FTO, Genome-Wide Association Study, Colaus Study, Body mass index
Abstract

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 × 10⁻⁸): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity. © 2009 Nature America, Inc. All rights reserved.

Published
2016

47. Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes

Author

Bo Isomaa, Anne U. Jackson, Richard N. Bergman, A Sandbaek, Yun Li, Oluf Pedersen, Thomas Edward Hughes, Mike Erdos, Christine Meisinger, Kari Kubalanza, Felicity Payne, Mark Walker, E Pettersen, William L. Duren, Kristin Ardlie, Palmer Cna., Michael Boehnke, Peter M. Nilsson, Graham A. Hitman, Rachel M. Freathy, Matthew G. Rees, Johanna Kuusisto, Finny G Kuruvilla, Kari Stefansson, P Deodhar, Knut Borch-Johnsen, Perry Jrb., Inês Barroso, Hana Lango, Richa Saxena, Augustine Kong, Gonçalo R. Abecasis, Katherine S. Elliott, Jonathan Marchini, Richard M. Watanabe, Christopher J. Groves, Niels Grarup, Unnur Thorsteinsdottir, Doney Asf., Kristina Bengtsson Boström, Peter Almgren, Cristen J. Willer, Torben Jørgensen, Lauren Gianniny, Beverley M. Shields, Christian Herder, Mario A. Morken, Lu Qi, Valgerdur Steinthorsdottir, Cecilia M. Lindgren, Nigel W. Rayner, Benjamin F. Voight, H Chen, J J Roix, Karen L. Mohlke, Heather M. Stringham, Andrew D. Morris, Mark I. McCarthy, Gudmar Thorleifsson, Frank B. Hu, Narisu Narisu, Mark J. Daly, Amanda F. Marvelle, Markku Laakso, Leif Groop, Laura J. Scott, Ding C-J., L Qin, Lori L. Bonnycastle, Thomas Illig, Noël P. Burtt, Michael N. Weedon, Valeriya Lyssenko, Amy J. Swift, Timothy M. Frayling, Nicholas J. Wareham, de Bakker Piw., Tiinamaija Tuomi, Kristian Hveem, Candace Guiducci, T Hu, Andrew T. Hattersley, David Altshuler, Harald Grallert, Peter S. Chines, Inga Prokopenko, Torsten Lauritzen, Katharine R. Owen, Eleftheria Zeggini, Carl Platou, Marketa Sjögren, Jaakko Tuomilehto, Nicholas J. Timpson, Francis S. Collins, Kristian Midthjell, Gregers S. Andersen, Claudia Langenberg, and Torben Hansen

Subjects
Genetics, 0303 health sciences, endocrine system, SLC30A8, Genome, Human, 030209 endocrinology & metabolism, Locus (genetics), Single-nucleotide polymorphism, Genome-wide association study, Heritability, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, 0302 clinical medicine, Diabetes Mellitus, Type 2, Meta-analysis, biology.protein, Humans, Genetic Predisposition to Disease, Human genome, CDKAL1, 030304 developmental biology
Abstract

Udgivelsesdato: 2008-May Genome-wide association (GWA) studies have identified multiple loci at which common variants modestly but reproducibly influence risk of type 2 diabetes (T2D). Established associations to common and rare variants explain only a small proportion of the heritability of T2D. As previously published analyses had limited power to identify variants with modest effects, we carried out meta-analysis of three T2D GWA scans comprising 10,128 individuals of European descent and approximately 2.2 million SNPs (directly genotyped and imputed), followed by replication testing in an independent sample with an effective sample size of up to 53,975. We detected at least six previously unknown loci with robust evidence for association, including the JAZF1 (P = 5.0 x 10(-14)), CDC123-CAMK1D (P = 1.2 x 10(-10)), TSPAN8-LGR5 (P = 1.1 x 10(-9)), THADA (P = 1.1 x 10(-9)), ADAMTS9 (P = 1.2 x 10(-8)) and NOTCH2 (P = 4.1 x 10(-8)) gene regions. Our results illustrate the value of large discovery and follow-up samples for gaining further insights into the inherited basis of T2D.

Published
2016

48. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance

Author

John R. B. Perry, James B. Meigs, José Dupuis, Luigi Ferrucci, Johan G. Eriksson, Vilmundur Gudnason, Eric J.G. Sijbrands, Jeanette S. Andrews, Jonna L. Grimsby, Lawrence F. Bielak, Peter Kovacs, Panos Deloukas, Marijana Peričić, Johannes H. Smit, Ruth J. F. Loos, Gonneke Willemsen, Eric Boerwinkle, Ben A. Oostra, Manuel Serrano-Ríos, Alena Stančáková, Meena Kumari, Antti Jula, Michael Marmot, Caroline S. Fox, Simon Heath, Guo Li, Ola Hansson, Gerard Waeber, Anne U. Jackson, Nicholas L. Smith, Markku Laakso, George Dedoussis, Aarno Palotie, Sara M. Willems, John F. Peden, Elisabeth Widen, Caroline Hayward, Alan F. Wright, Claes Ladenvall, May E. Montasser, María Teresa Martínez-Larrad, Peter Vollenweider, Louis Pérusse, Tamara B. Harris, Wen Hong L. Kao, Danijela Budimir, Denis Rybin, David B. Savage, Michael A. Province, Alisa K. Manning, Bruna Gigante, Najaf Amin, Lenore J. Launer, Naveed Sattar, Lori L. Bonnycastle, Göran Hallmans, Jeffrey R. O'Connell, Stéphane Lobbens, Jacques S. Beckmann, Gemma Cadby, J. Wouter Jukema, Maria Dimitriou, Michael Stumvoll, Max Vikström, Rona J. Strawbridge, Hugh Watkins, Lyle J. Palmer, Johanna Kuusisto, Aimo Ruokonen, Hanieh Yaghootkar, Yan V. Sun, Inês Barroso, Amy J. Swift, Nancy L. Pedersen, Lars Lind, Mladen Boban, Nita G. Forouhi, Ken K. Ong, Ivana Kolcic, Anke Tönjes, Timothy M. Frayling, Paul W. Franks, Narisu Narisu, Karin Leander, Serge Hercberg, Diana Zelenika, Sharon L.R. Kardia, Min A. Jhun, Marjo-Riitta Järvelin, Stella Trompet, Jaakko Kaprio, Toshiko Tanaka, David S. Siscovick, Toby Johnson, Cornelia M. van Duijn, Veikko Salomaa, Jose C. Florez, James F. Wilson, Leena Peltonen, Pilar Galan, Robert Clarke, Andrew A. Hicks, Claudia Langenberg, Anders Hamsten, David Couper, Albert Hofman, Dawn M. Waterworth, John Blangero, James S. Pankow, Nabila Bouatia-Naji, Sirkka Keinänen-Kiukaanniemi, Mark I. McCarthy, Valeriya Lyssenko, Leif Groop, Brenda W.J.H. Penninx, Ching-Ti Liu, Anuj Goel, Marina Pehlić, Michael Boehnke, Mika Kivimäki, Maria Sabater-Lleal, Emil Rehnberg, Ingrid B. Borecki, Ozren Polasek, Eco J. C. de Geus, Peter P. Pramstaller, Igor Rudan, Richard M. Watanabe, Pierre Meneton, Iva Miljkovic, Vincent Mooser, G. Mark Lathrop, John Beilby, Laura J. Rasmussen-Torvik, Arturo Corbató-Anchuelo, Yvonne Böttcher, Richard N. Bergman, Daniel R. Barnes, Paul C. D. Johnson, Mustafa Atalay, Aroon D. Hingorani, Olga D. Carlson, Perttu Salo, Jacqueline C.M. Witteman, Udo Seedorf, Timo Saaristo, Jian'an Luan, Nicholas J. Wareham, Gudny Eiriksdottir, Matti Uusitupa, Yongmei Liu, Jaakko Tuomilehto, Yurii S. Aulchenko, Peter Schwarz, Robert A. Scott, Lina Zgaga, Joseph Hung, Reedik Mägi, Maria Grazia Franzosi, Eric J. Brunner, Claude Bouchard, Ian Ford, Francis S. Collins, Ulf de Faire, Benjamin F. Voight, Erik Ingelsson, Mario A. Morken, Stefania Bandinelli, Nicole L. Glazer, Dmitry Shungin, Lars Lannfelt, André G. Uitterlinden, Tatijana Zemunik, Markus Perola, Kenneth Rice, Veronique Vitart, Kerrin S. Small, Jouke-Jan Hottenga, Han Chen, Jerome I. Rotter, Philippe Froguel, Karen L. Mohlke, Marie-Claude Vohl, Dorret I. Boomsma, Harry Campbell, Peter S. Chines, Pau Navarro, Vasiliki Lagou, Albert V. Smith, Kathleen Stirrups, Josephine M. Egan, Alan R. Shuldiner, Katri Räikkönen, Inga Prokopenko, Ping An, Rainer Rauramaa, Beverley Balkau, Thor Aspelund, Eleanor Wheeler, Mariza de Andrade, Richa Saxena, Jari Lahti, Cécile Lecoeur, Timo A. Lakka, Jennie Hui, Michael R. Erdos, Stavroula Kanoni, Kirsten Ohm Kyvik, Bengt Sennblad, Sarah H. Wild, Patricia A. Peyser, Patrik K. E. Magnusson, Claire Bellis, Elodie Eury, Jaana Lindström, Boston University [Boston] (BU), Broad Institute of Harvard and MIT, Partenaires INRAE, Massachusetts General Hospital, Massachusetts General Hospital [Boston], Department of Genetics [Boston], Harvard Medical School [Boston] (HMS), Department of Medicine, Université de Sherbrooke (UdeS), Addenbrooke's Hospital, Harvard Medical School [Boston] (HMS)-Beth Israel Deaconess Medical Center [Boston] (BIDMC), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP), Université Lille Nord de France (COMUE), Department of Epidemiology, University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System-Center for Social Epidemiology and Population Health, Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford [Oxford], The Wellcome Trust Centre for Human Genetics [Oxford], The Netherlands Cancer Institute, Ontario Institute for Cancer Research, Mount Sinai Hospital [Toronto, Canada] (MSH), VU University Amsterdam, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], University of Michigan System, Queen Mary University of London (QMUL), The Wellcome Trust Sanger Institute [Cambridge], Lund University [Lund], Diabetes Centre, Lund University, University of Helsinki, Wake Forest School of Medicine, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, University of Maryland School of Medicine, University of Maryland System, University of Edinburgh, University of Exeter, Department of Twin Research and Genetic Epidemiology, King's College London, London, Northwestern University [Evanston], National Institute of Health and Welfare, Institute of Cardiovascular and Medical Sciences, University of Glasgow, Lund University Diabetes Centre, Umeå University, National Institutes of Health, Centre for Medical Systems Biology, Netherlands Genomics Initiative, Washington University in Saint Louis (WUSTL), Department of Health Sciences Research, Mayo Clinic, Wake Forest University, Icelandic Heart Association, Heart Preventive Clinic and Research Institute, University of Iceland, Institute of Biomedicine, Physiology, University of Eastern Finland, Institut National de la Santé et de la Recherche Médicale (INSERM), UMR S 1018, Université Paris-Sud - Paris 11 (UP11), Azienda Sanitaria Firenze, Department of Medical Genetics, Université de Lausanne (UNIL), Centre Hospitalier Universitaire Vaudois (CHUV), Queen Elizabeth II Medical Centre, Research Institute, University of Southern California (USC), University of Split, The University of Texas Health Science Center at Houston (UTHealth), Leipzig University, Pennington Biomedical Research Center, Department of Epidemiology & Public Health, University College of London [London] (UCL), San Carlos Clinical Hospital, University of North Carolina, Harokopio University, National Institute on Aging, Folkhälsan Research Centre, Vaasa Central Hospital, Unité de Recherche en Epidémiologie Nutritionnelle (UREN), Université Paris 13 (UP13)-Institut National de la Recherche Agronomique (INRA)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Psychiatry, EMGO - Lifestyle, overweight and diabetes, Epidemiology, Immunology, Erasmus School of Social and Behavioural Sciences, Clinical Genetics, Ophthalmology, Internal Medicine, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Multiple Tissue Human Expression Resource (MUTHER) Consortium, Ahmadi, K.R., Ainali, C., Barrett, A., Bataille, V., Bell, J.T., Buil, A., Deloukas, P., Dermitzakis, E.T., Dimas, A.S., Durbin, R., Glass, D., Grundberg, E., Hassanali, N., Hedman, Å.K., Ingle, C., Knowles, D., Krestyaninova, M., Lindgren, C.M., Lowe, C.E., McCarthy, M.I., Meduri, E., di Meglio, P., Min, J.L., Montgomery, S.B., Nestle, F.O., Nica, A.C., Nisbet, J., O'Rahilly, S., Parts, L., Potter, S., Sekowska, M., Shin, S.Y., Small, K.S., Soranzo, N., Spector, T.D., Surdulescu, G., Travers, M.E., Tsaprouni, L., Tsoka, S., Wilk, A., Yang, T.P., Zondervan, K.T., Voight, B.F., Scott, L.J., Steinthorsdottir, V., Morris, A.P., Dina, C., Welch, R.P., Zeggini, E., Huth, C., Aulchenko, Y.S., Thorleifsson, G., McCulloch, L.J., Ferreira, T., Grallert, H., Amin, N., Wu, G., Willer, C.J., Raychaudhuri, S., McCarroll, S.A., Langenberg, C., Hofmann, O.M., Dupuis, J., Qi, L., Segrè, A.V., van Hoek, M., Navarro, P., Ardlie, K., Balkau, B., Benediktsson, R., Bennett, A.J., Blagieva, R., Boerwinkle, E., Bonnycastle, L.L., Boström, K.B., Bravenboer, B., Bumpstead, S., Burtt, N.P., Charpentier, G., Chines, P.S., Cornelis, M., Couper, D.J., Crawford, G., Doney, A.S., Elliott, K.S., Elliott, A.L., Erdos, M.R., Fox, C.S., Franklin, C.S., Ganser, M., Gieger, C., Grarup, N., Green, T., Griffin, S., Groves, C.J., Guiducci, C., Hadjadj, S., Herder, C., Isomaa, B., Jackson, A.U., Johnson, P.R., Jørgensen, T., Kao, W.H., Klopp, N., Kong, A., Kraft, P., Kuusisto, J., Lauritzen, T., Li, M., Lieverse, A., Lyssenko, V., Marre, M., Meitinger, T., Midthjell, K., Morken, M.A., Narisu, N., Nilsson, P., Owen, K.R., Payne, F., Perry, J.R., Petersen, A.K., Platou, C., Proença, C., Prokopenko, I., Rathmann, W., Rayner, N.W., Robertson, N.R., Rocheleau, G., Roden, M., Sampson, M.J., Saxena, R., Shields, B.M., Shrader, P., Sigurdsson, G., Sparsø, T., Strassburger, K., Stringham, H.M., Sun, Q., Swift, A.J., Thorand, B., Tichet, J., Tuomi, T., van Dam, R.M., van Haeften, T.W., van Herpt, T., van Vliet-Ostaptchouk, J.V., Walters, G.B., Weedon, M.N., Wijmenga, C., Witteman, J., Bergman, R.N., Cauchi, S., Collins, F.S., Gloyn, A.L., Gyllensten, U., Hansen, T., Hide, W.A., Hitman, G.A., Hofman, A., Hunter, D.J., Hveem, K., Laakso, M., Mohlke, K.L., Morris, A.D., Palmer, C.N., Pramstaller, P.P., Rudan, I., Sijbrands, E., Stein, L.D., Tuomilehto, J., Uitterlinden, A., Walker, M., Wareham, N.J., Watanabe, R.M., Abecasis, G.R., Boehm, B.O., Campbell, H., Daly, M.J., Hattersley, A.T., Hu, F.B., Meigs, J.B., Pankow, J.S., Pedersen, O., Wichmann, H.E., Barroso, I., Florez, J.C., Frayling, T.M., Groop, L., Sladek, R., Thorsteinsdottir, U., Wilson, J.F., Illig, T., Froguel, P., van Duijn, C.M., Stefansson, K., Altshuler, D., Boehnke, M., Biological Psychology, EMGO+ - Lifestyle, Overweight and Diabetes, Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Sorbonne Paris Cité (USPC)-Université Paris 13 (UP13)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Institut National de la Recherche Agronomique (INRA)

Subjects
Blood Glucose, Netherlands Twin Register (NTR), medicine.medical_treatment, [SDV]Life Sciences [q-bio], LOCI, Genome-wide association study, Type 2 diabetes, SUSCEPTIBILITY, Body Mass Index, GLUCOSE, Blood Glucose/metabolism, Cholesterol, HDL/metabolism, Diabetes Mellitus, Type 2/genetics, Genome-Wide Association Study, Humans, Insulin/metabolism, Insulin Resistance/genetics, Polymorphism, Single Nucleotide, 0302 clinical medicine, Insulin, 2. Zero hunger, Genetics, 0303 health sciences, COMMON VARIANTS, 3. Good health, ENVIRONMENT INTERACTION, OBESITY, CORONARY-ARTERY-DISEASE, medicine.medical_specialty, 030209 endocrinology & metabolism, Accounting, Biology, Article, 03 medical and health sciences, Insulin resistance, SDG 3 - Good Health and Well-being, Internal medicine, Diabetes mellitus, medicine, 030304 developmental biology, Genetic association, Glycemic, loci, SNP, insulin, business.industry, Cholesterol, HDL, medicine.disease, Obesity, POLYMORPHISM, ASSOCIATION ANALYSIS, Endocrinology, Diabetes Mellitus, Type 2, TYPE-2 DIABETES RISK, Insulin Resistance, business
Abstract

Group Authors : DIAGRAM Consortium MUTHER Consortium variants influencing fasting glycemic traits and insulin resistance Seuls les 100 premiers auteurs ont été conservés dans la publication. La liste complète des auteurs et des des affiliations est disponible sur la publication https://www.nature.com/articles/ng.2274.pdf p. 667-669.; International audience; Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and beta-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 x 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.

Published
2012

49. Estimating Hepatic Glucokinase Activity Using a Simple Model of Lactate Kinetics

Author

Anne U. Jackson, Richard M. Watanabe, Viorica Ionut, Darko Stefanovski, Richard N. Bergman, Matthew G. Rees, Jang H. Youn, Marilyn Ader, Francis S. Collins, and Michael Boehnke

Subjects
medicine.medical_specialty, Endocrinology, Diabetes and Metabolism, 030209 endocrinology & metabolism, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, In vivo, Diabetes mellitus, Internal medicine, Glucokinase, Internal Medicine, medicine, Animals, Humans, Glucose homeostasis, Glycolysis, Lactic Acid, Original Research, 030304 developmental biology, Advanced and Specialized Nursing, 0303 health sciences, Glucose tolerance test, medicine.diagnostic_test, business.industry, Clinical Care/Education/Nutrition/Psychosocial Research, Metabolism, Models, Theoretical, medicine.disease, Lactic acid, Endocrinology, Liver, chemistry, business
Abstract

OBJECTIVE Glucokinase (GCK) acts as a component of the “glucose sensor” in pancreatic β-cells and possibly in other tissues, including the brain. However, >99% of GCK in the body is located in the liver, where it serves as a “gatekeeper”, determining the rate of hepatic glucose phosphorylation. Mutations in GCK are a cause of maturity-onset diabetes of the young (MODY), and GCKR, the regulator of GCK in the liver, is a diabetes susceptibility locus. In addition, several GCK activators are being studied as potential regulators of blood glucose. The ability to estimate liver GCK activity in vivo for genetic and pharmacologic studies may provide important physiologic insights into the regulation of hepatic glucose metabolism. RESEARCH DESIGN AND METHODS Here we introduce a simple, linear, two-compartment kinetic model that exploits lactate and glucose kinetics observed during the frequently sampled intravenous glucose tolerance test (FSIGT) to estimate liver GCK activity (KGK), glycolysis (K12), and whole body fractional lactate clearance (K01). RESULTS To test our working model of lactate, we used cross-sectional FSIGT data on 142 nondiabetic individuals chosen at random from the Finland–United States Investigation of NIDDM Genetics study cohort. Parameters KGK, K12, and K01 were precisely estimated. Median model parameter estimates were consistent with previously published values. CONCLUSIONS This novel model of lactate kinetics extends the utility of the FSIGT protocol beyond whole-body glucose homeostasis by providing estimates for indices pertaining to hepatic glucose metabolism, including hepatic GCK activity and glycolysis rate.

Published
2012

50. Metabolic Syndrome is linked to Chromosome 7q21 and associated with genetic variants in CD36 and GNAT3 in Mexican Americans

Author

Ravindranath Duggirala, Jennifer L. Schneider, Mary Helen Black, Christopher P. Jenkinson, Rector Arya, Hooman Allayee, Laura Almasy, Sharon P. Fowler, Vidya S. Farook, Richard M. Watanabe, Sobha Puppala, Donna M. Lehman, Joanne E. Curran, John Blangero, Thomas A. Buchanan, Geetha Chittoor, Shelley A. Cole, and Thomas D. Dyer

Subjects
Adult, CD36 Antigens, Male, Genetic Linkage, Endocrinology, Diabetes and Metabolism, Population, Medicine (miscellaneous), linkage/genome scan, Context (language use), Type 2 diabetes, GNAT3, Polymorphism, Single Nucleotide, Article, variance components linkage analysis, NCEP/ATPIII, single nucleotide polymorphisms, Endocrinology, Genetic linkage, Genetic variation, Mexican Americans, Medicine, Humans, Genetic Predisposition to Disease, Obesity, Transducin, education, National Cholesterol Education Program, Genetic association, Genetics, Metabolic Syndrome, education.field_of_study, Nutrition and Dietetics, business.industry, Genetic Variation, CD36/FAT, medicine.disease, Heterotrimeric GTP-Binding Proteins, association analysis, United States, Phenotype, Female, Metabolic syndrome, Lod Score, business, Chromosomes, Human, Pair 7, Demography
Abstract

Metabolic abnormalities such as obesity, insulin resistance and hyperinsulinemia, impaired glucose tolerance, dyslipidemia, and hypertension often cluster to constitute the Metabolic Syndrome [MS]. The MS is a predictor of both type 2 diabetes (T2DM) and Coronary Heart Disease (CHD), and its prevalence has been rising alarmingly worldwide. In the United States (US), more than 47 million people are affected with MS. Specifically, its prevalence is high in minority populations such as Mexican Americans, who had the highest age-adjusted prevalence of MS [∼32%] when compared to the non-Hispanic whites, African Americans and other ethnic groups (1). Added to this burden, over the past 20 years, the prevalence of MS among children and adolescents has also been increasing at epidemic rates in several populations including Mexican Americans and African Americans (2-4). The MS and its components are complex disease conditions that are influenced by genetic and environmental factors and their interactions MS can be defined as a single, composite phenotype for genetic analysis using criteria such as the National Cholesterol Education Program [NCEP]/Adult Treatment Panel III [ATPIII] (NCEP/ATPIII) recommendations, the most widely used definition in the US (5,6). In addition to the NCEP/ATPIII criteria, several organizations have proposed different definitions for MS. While the various definitions use similar core components of MS, primarily including the measurements of obesity, glucose, lipids, and blood pressure, they differ in the number of traits and the cut-off points required for the diagnosis. Despite certain caveats, several studies have used the NCEP/ATPIII definition for its simplicity, in the context of clinical practice and epidemiological investigations (7); most importantly, as noted by Grundy et al. (6), it avoids emphasis on a single cause. Several genome-wide linkage and association studies have been performed to understand the genetic basis of the components of MS by using a number of analytical tools such as multivariate genetic analysis and factor analysis (8-12). Such studies have identified several genetic regions linked to MS related traits, but showing limited concordance in their results (11). In contrast to the above approaches, a single, composite MS phenotype using the NCEP/ATPIII or other criteria can be used to identify genetic regions with potential common genetic influences on MS; however, there have been a few such studies (13, 14). Therefore, the aim of our study was to identify the susceptibility loci for MS using the NCEP/ATPIII definition in a Mexican American population who are at high risk for the development of MS. Here, we report the results of our genome-wide linkage screen for MS performed by using the multipoint variance components linkage analysis and the phenotypic and genotypic (∼10 cM map) data collected from the Mexican American individuals who participated in our San Antonio Family Diabetes/Gallbladder Study (SAFDGS). In addition, we report the results of our preliminary MS association study performed by examining the genetic variants in two of the positional candidate genes, which are physically close to each other, located within the 1-LOD support interval region of our MS linkage signal on chromosome 7q.

Published
2012

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