Title
Meta-Analysis of the INSIG2 Association with Obesity Including 74,345 Individuals: Does Heterogeneity of Estimates Relate to Study Design?
Authors
Iris M. Heid, German Research Center for Environmental Health, Neuherberg, Germany
Cornelia Huth, German Research Center for Environmental Health, Neuherberg, Germany
Ruth J. F. Loos, Medical Research Council, Cambridge, United Kingdom
Florian Kronenberg, Innsbruck Medical University, Innsbruck, Austria
Vera Adamkova, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
Sonia S. Anand, McMaster University
Kristin Ardlie, Harvard University
Heike Biebermann, Institut für Experimentelle Pädiatrische Endokrinologie, Berlin, Germany
Peter Bjerregaard, University of Southern Denmark, Copenhagen, Denmark
Heiner Boeing, German Institute of Human Nutrition Potsdam–Rehbrücke, Nuthetal, Germany
Claude Bouchard, Pennington Biomedical Research Center, Baton Rouge, LA
Marina Ciullo, Institute of Genetics and Biophysics, Naples, Italy
Jackie A. Cooper, Royal Free and University College Medical School, London, United Kingdom
Dolores Corella, University of Valencia, Valencia, Spain
Christian Dina, Pasteur Institute, Lille, France
James C. Engert, McGill University
Eva Fisher, German Institute of Human Nutrition Potsdam–Rehbrücke, Nuthetal, Germany
Francesc Francès, University of Valencia, Valencia, Spain
Philippe Froguel, Pasteur Institute, Lille, France
Johannes Hebebrand, University of Duisburg–Essen, Essen, Germany
Robert A. Hegele, Robarts Research Institute
Anke Hinney, University of Duisburg–Essen, Essen, Germany
Margret R. Hoehe, Max Planck Institut for Molecular Genetics, Berlin, Germany
Frank B. Hu, Harvard University
Jaroslav A. Hubacek, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
Steve E. Humphries, Royal Free and University College Medical School, London, United Kingdom
Steven C. Hunt, University of Utah
Thomas Illig, German Research Center for Environmental Health, Neuherberg, Germany
Marjo-Riita Järvelin, Imperial College, London, United Kingdom
Marika Kaakinen, University of Oulu, Oulu, Finland
Barbara Kollerits, Innsbruck Medical University, Innsbruck, Austria
Heiko Krude, Institut für Experimentelle Pädiatrische Endokrinologie, Berlin, Germany
Jitender Kumar, Institute of Genomics and Integrative Biology, Delhi, India
Leslie A. Lange, University of North Carolina, Chapel Hill
Birgit Langer, German Research Center for Environmental Health, Neuherberg, Germany
Shengxu Li, Medical Research Council, Cambridge, United Kingdom
Andreas Luchner, University Medical Center Regensburg, Regensburg, Germany
Helen N. Lyon, Harvard University
David Meyre, Pasteur Institute, Lille, France
Karen L. Mohlke, University of North Carolina, Chapel Hill
Vincent Mooser, GlaxoSmithKline, King of Prussia, PA
Almut Nebel, Christian-Albrechts-University of Kiel, Kiel, Germany
Thuy Trang Nguyen, Philipps-Universitaet Marburg, Marburg, Germany
Bernhard Paulweber, Paracelsus Private Medical University Salzburg, Salzburg, Austria
Louis Perusse, Université Laval
Lu Qi, Max Planck Institut for Molecular Genetics, Berlin, Germany
Tuomo Rankinen, Pennington Biomedical Research Center, Baton Rouge, LA
Dieter Rosskopf, Ernst Moritz Arndt University Greifswald, Greifswald, Germany
Stefan Schreiber, Christian-Albrechts-University of Kiel, Kiel, Germany
Shantanu Sengupta, Institute of Genomics and Integrative Biology, Delhi, India
Rossella Sorice, Institute of Genetics and Biophysics, Naples, Italy
Anita Suk, Max Planck Institut for Molecular Genetics, Berlin, Germany
Gudmar Thorleifsson, deCODE genetics, Reykjavik, Iceland
Unnur Thorsteinsdottir, deCODE genetics, Reykjavik, Iceland
Henry Völzke, Ernst Moritz Arndt University Greifswald, Greifswald, Germany
Karani S. Vimaleswaran, Institute of Metabolic Science, Cambridge, United Kingdom
Nicholas J. Wareham, Institute of Metabolic Science, Cambridge, United Kingdom
Dawn Waterworth, GlaxoSmithKline, King of Prussia, PA
Salim Yusuf, McMaster University
Cecilia Lindgren, University of Oxford
Mark I. McCarthy, University of Oxford
Christoph Lange, Harvard University
Joel N. Hirschhorn, Harvard University
Nan Laird, Harvard University
H-Erich Wichmann, German Research Center for Environmental Health, Neuherberg, Germany
Publication Date
10-23-2009
URL with Digital Object Identifier
10.1371/journal.pgen.1000694
Abstract
The INSIG2 rs7566605 polymorphism was identified for obesity (BMI> or =30 kg/m(2)) in one of the first genome-wide association studies, but replications were inconsistent. We collected statistics from 34 studies (n = 74,345), including general population (GP) studies, population-based studies with subjects selected for conditions related to a better health status ('healthy population', HP), and obesity studies (OB). We tested five hypotheses to explore potential sources of heterogeneity. The meta-analysis of 27 studies on Caucasian adults (n = 66,213) combining the different study designs did not support overall association of the CC-genotype with obesity, yielding an odds ratio (OR) of 1.05 (p-value = 0.27). The I(2) measure of 41% (p-value = 0.015) indicated between-study heterogeneity. Restricting to GP studies resulted in a declined I(2) measure of 11% (p-value = 0.33) and an OR of 1.10 (p-value = 0.015). Regarding the five hypotheses, our data showed (a) some difference between GP and HP studies (p-value = 0.012) and (b) an association in extreme comparisons (BMI> or =32.5, 35.0, 37.5, 40.0 kg/m(2) versus BMI<25 kg>/m(2)) yielding ORs of 1.16, 1.18, 1.22, or 1.27 (p-values 0.001 to 0.003), which was also underscored by significantly increased CC-genotype frequencies across BMI categories (10.4% to 12.5%, p-value for trend = 0.0002). We did not find evidence for differential ORs (c) among studies with higher than average obesity prevalence compared to lower, (d) among studies with BMI assessment after the year 2000 compared to those before, or (e) among studies from older populations compared to younger. Analysis of non-Caucasian adults (n = 4889) or children (n = 3243) yielded ORs of 1.01 (p-value = 0.94) or 1.15 (p-value = 0.22), respectively. There was no evidence for overall association of the rs7566605 polymorphism with obesity. Our data suggested an association with extreme degrees of obesity, and consequently heterogeneous effects from different study designs may mask an underlying association when unaccounted for. The importance of study design might be under-recognized in gene discovery and association replication so far.
