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Paul Franks

Paul Franks

Principal investigator

Paul Franks

Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study


  • Lina Cai
  • Eleanor Wheeler
  • Nicola D. Kerrison
  • Jian’an Luan
  • Panos Deloukas
  • Paul W. Franks
  • Pilar Amiano
  • Eva Ardanaz
  • Catalina Bonet
  • Guy Fagherazzi
  • Leif C. Groop
  • Rudolf Kaaks
  • José María Huerta
  • Giovanna Masala
  • Peter M. Nilsson
  • Kim Overvad
  • Valeria Pala
  • Salvatore Panico
  • Miguel Rodriguez-Barranco
  • Olov Rolandsson
  • Carlotta Sacerdote
  • Matthias B. Schulze
  • Annemieke M.W. Spijkerman
  • Anne Tjonneland
  • Rosario Tumino
  • Yvonne T. van der Schouw
  • Stephen J. Sharp
  • Nita G. Forouhi
  • Elio Riboli
  • Mark I. McCarthy
  • Inês Barroso
  • Claudia Langenberg
  • Nicholas J. Wareham

Summary, in English

Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D.


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

Publishing year





Scientific Data





Document type

Journal article


Nature Publishing Group


  • Endocrinology and Diabetes



Research group

  • Genetic and Molecular Epidemiology
  • Genomics, Diabetes and Endocrinology
  • Internal Medicine - Epidemiology


  • ISSN: 2052-4463