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Paul Franks

Paul Franks

Principal investigator

Paul Franks

Gene×dietary pattern interactions in obesity: analysis of up to 68,317 adults of European ancestry.

Author

  • Jennifer A Nettleton
  • Jack L Follis
  • Julius S Ngwa
  • Caren E Smith
  • Shafqat Ahmad
  • Toshiko Tanaka
  • Mary K Wojczynski
  • Trudy Voortman
  • Rozenn N Lemaitre
  • Kati Kristiansson
  • Marja-Liisa Nuotio
  • Denise K Houston
  • Mia-Maria Perälä
  • Qibin Qi
  • Emily Sonestedt
  • Ani Manichaikul
  • Stavroula Kanoni
  • Andrea Ganna
  • Vera Mikkilä
  • Kari E North
  • David S Siscovick
  • Kennet Harald
  • Nicola M McKeown
  • Ingegerd Johansson
  • Harri Rissanen
  • Yongmei Liu
  • Jari Lahti
  • Frank B Hu
  • Stefania Bandinelli
  • Gull Rukh
  • Stephen Rich
  • Lisanne Booij
  • Maria Dmitriou
  • Erika Ax
  • Olli Raitakari
  • Kenneth Mukamal
  • Satu Männistö
  • Göran Hallmans
  • Antti Jula
  • Ulrika Ericson
  • David R Jacobs
  • Frank J A van Rooij
  • Panos Deloukas
  • Per Sjögren
  • Mika Kähönen
  • Luc Djousse
  • Markus Perola
  • Inês Barroso
  • Albert Hofman
  • Kathleen Stirrups
  • Jorma Viikari
  • André G Uitterlinden
  • Ioanna P Kalafati
  • Oscar H Franco
  • Dariush Mozaffarian
  • Veikko Salomaa
  • Ingrid B Borecki
  • Paul Knekt
  • Stephen B Kritchevsky
  • Johan G Eriksson
  • George V Dedoussis
  • Lu Qi
  • Luigi Ferrucci
  • Marju Orho-Melander
  • M Carola Zillikens
  • Erik Ingelsson
  • Terho Lehtimäki
  • Frida Renström
  • L Adrienne Cupples
  • Ruth Loos
  • Paul Franks

Summary, in English

Obesity is highly heritable. Genetic variants showing robust associations with obesity traits have been identified through genome-wide association studies. We investigated whether a composite score representing healthy diet modifies associations of these variants with obesity traits. 32 BMI- and 14 waist-hip ratio (WHR)-associated SNPs were genotyped and genetic risk scores (GRS) calculated in 18 cohorts of European ancestry (n=68,317). Diet score was calculated based on self-reported intakes of whole grains, fish, fruits, vegetables, nuts/seeds (favorable) and red/processed meats, sweets, sugar-sweetened beverages, fried potatoes (unfavorable). Multi-variable adjusted, linear regression within each cohort, followed by inverse variance-weighted fixed-effects meta-analysis was used to characterize: a) associations of each GRS with BMI and BMI-adjusted WHR; b) diet score modification of genetic associations with BMI and BMI-adjusted WHR. Nominally significant interactions (P=0.006-0.04) were observed between the diet score and WHR-GRS (but not BMI-GRS), two WHR loci (GRB14 rs10195252; LYPLAL1 rs4846567), and two BMI loci (LRRN6C rs10968576; MTIF3 rs4771122), for the respective BMI-adjusted WHR or BMI outcomes. Although the magnitudes of these select interactions were small, our data indicated that associations between genetic predisposition and obesity traits were stronger with a healthier diet. Our findings generate interesting hypotheses; however, experimental and functional studies are needed to determine their clinical relevance.

Department/s

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

Publishing year

2015

Language

English

Pages

4728-4738

Publication/Series

Human Molecular Genetics

Volume

24

Issue

16

Document type

Journal article

Publisher

Oxford University Press

Topic

  • Medical Genetics

Status

Published

Research group

  • Genetic and Molecular Epidemiology
  • Genomics, Diabetes and Endocrinology
  • Diabetes - Cardiovascular Disease

ISBN/ISSN/Other

  • ISSN: 0964-6906