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Paul Franks

Paul Franks

Principal investigator

Paul Franks

No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels


  • Robert A. Scott
  • Audrey Y. Chu
  • Niels Grarup
  • Alisa K. Manning
  • Marie-France Hivert
  • Dmitry Shungin
  • Anke Toenjes
  • Ajay Yesupriya
  • Daniel Barnes
  • Nabila Bouatia-Naji
  • Nicole L. Glazer
  • Anne U. Jackson
  • Zoltan Kutalik
  • Vasiliki Lagou
  • Diana Marek
  • Laura J. Rasmussen-Torvik
  • Heather M. Stringham
  • Toshiko Tanaka
  • Mette Aadahl
  • Dan E. Arking
  • Sven Bergmann
  • Eric Boerwinkle
  • Lori L. Bonnycastle
  • Stefan R. Bornstein
  • Eric Brunner
  • Suzannah J. Bumpstead
  • Soren Brage
  • Olga D. Carlson
  • Han Chen
  • Yii-Der Ida Chen
  • Peter S. Chines
  • Francis S. Collins
  • David J. Couper
  • Elaine M. Dennison
  • Nicole F. Dowling
  • Josephine S. Egan
  • Ulf Ekelund
  • Michael R. Erdos
  • Nita G. Forouhi
  • Caroline S. Fox
  • Mark O. Goodarzi
  • Juergen Graessler
  • Stefan Gustafsson
  • Goeran Hallmans
  • Torben Hansen
  • Aroon Hingorani
  • John W. Holloway
  • Frank B. Hu
  • Bo Isomaa
  • Karen A. Jameson
  • Ingegerd Johansson
  • Anna Jonsson
  • Torben Jorgensen
  • Mika Kivimaki
  • Peter Kovacs
  • Meena Kumari
  • Johanna Kuusisto
  • Markku Laakso
  • Cecile Lecoeur
  • Claire Levy-Marchal
  • Guo Li
  • Ruth J. F. Loos
  • Valeriya Lyssenko
  • Michael Marmot
  • Pedro Marques-Vidal
  • Mario A. Morken
  • Gabriele Mueller
  • Kari E. North
  • James S. Pankow
  • Felicity Payne
  • Inga Prokopenko
  • Bruce M. Psaty
  • Frida Renström
  • Ken Rice
  • Jerome I. Rotter
  • Denis Rybin
  • Camilla H. Sandholt
  • Avan A. Sayer
  • Peter Shrader
  • Peter E. H. Schwarz
  • David S. Siscovick
  • Alena Stancakova
  • Michael Stumvoll
  • Tanya M. Teslovich
  • Gerard Waeber
  • Gordon H. Williams
  • Daniel R. Witte
  • Andrew R. Wood
  • Weijia Xie
  • Michael Boehnke
  • Cyrus Cooper
  • Luigi Ferrucci
  • Philippe Froguel
  • Leif Groop
  • W. H. Linda Kao
  • Peter Vollenweider
  • Mark Walker
  • Richard M. Watanabe
  • Oluf Pedersen
  • James B. Meigs
  • Erik Ingelsson
  • Ines Barroso
  • Jose C. Florez
  • Paul Franks
  • Josee Dupuis
  • Nicholas J. Wareham
  • Claudia Langenberg

Summary, in English

Gene-lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) X BMI and SNP x physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (beta = 0.22 mmol/L [95% CI 0.13-0.31], P = 1.63 X 10(-6)). All SNPs were associated with 2-h glucose (beta = 0.06-0.12 mmol/allele, P <= 1.53 X 10(-7)), but no significant interactions were found with PA (P > 0.18) or BMI (P >= 0.04). In this large study of gene-lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions. Diabetes 61:1291-1296, 2012


  • Genomics, Diabetes and Endocrinology
  • Genetic and Molecular Epidemiology
  • EXODIAB: Excellence in Diabetes Research in Sweden
  • EpiHealth: Epidemiology for Health

Publishing year












Document type

Journal article


American Diabetes Association Inc.


  • Endocrinology and Diabetes



Research group

  • Genomics, Diabetes and Endocrinology
  • Genetic and Molecular Epidemiology


  • ISSN: 1939-327X