title: Fried food consumption, genetic risk, and body mass index: gene-diet interaction analysis in three US cohort studies.
abstract: OBJECTIVE
  To examine the interactions between genetic predisposition and consumption of fried food in relation to body mass index (BMI) and obesity.
  
  
  METHODS
  Prospective cohort study.
  
  
  METHODS
  Health professionals in the United States.
  
  
  METHODS
  9623 women from the Nurses' Health Study, 6379 men from the Health Professionals Follow-up Study, and a replication cohort of 21,421 women from the Women's Genome Health Study.
  
  
  METHODS
  Repeated measurement of BMI over follow-up.
  
  
  RESULTS
  There was an interaction between fried food consumption and a genetic risk score based on 32 BMI-associated variants on BMI in both the Nurses' Health Study and Health Professionals Follow-up Study (P ≤ 0.001 for interaction). Among participants in the highest third of the genetic risk score, the differences in BMI between individuals who consumed fried foods four or more times a week and those who consumed fried foods less than once a week amounted to 1.0 (SE 0.2) in women and 0.7 (SE 0.2) in men, whereas the corresponding differences were 0.5 (SE 0.2) and 0.4 (SE 0.2) in the lowest third of the genetic risk score. The gene-diet interaction was replicated in the Women's Genome Health Study (P<0.001 for interaction). Viewed differently, the genetic association with adiposity was strengthened with higher consumption of fried foods. In the combined three cohorts, the differences in BMI per 10 risk alleles were 1.1 (SE 0.2), 1.6 (SE 0.3), and 2.2 (SE 0.6) for fried food consumption less than once, one to three times, and four or more times a week (P<0.001 for interaction); and the odds ratios (95% confidence intervals) for obesity per 10 risk alleles were 1.61 (1.40 to 1.87), 2.12 (1.73 to 2.59), and 2.72 (2.12 to 3.48) across the three categories of consumption (P=0.002 for interaction). In addition, the variants in or near genes highly expressed or known to act in the central nervous system showed significant interactions with fried food consumption, with the FTO (fat mass and obesity associated) variant showing the strongest result (P<0.001 for interaction).
  
  
  CONCLUSIONS
  Our findings suggest that consumption of fried food could interact with genetic background in relation to obesity, highlighting the particular importance of reducing fried food consumption in individuals genetically predisposed to obesity.
authors.affiliation: Department of Nutrition, Harvard School of Public Health, Boston, MA, USA.
authors.forename: Qibin
authors.initials: Q
authors.lastname: Qi
authors.forename: Audrey Y
authors.initials: AY
authors.lastname: Chu
authors.forename: Jae H
authors.initials: JH
authors.lastname: Kang
authors.forename: Jinyan
authors.initials: J
authors.lastname: Huang
authors.forename: Lynda M
authors.initials: LM
authors.lastname: Rose
authors.forename: Majken K
authors.initials: MK
authors.lastname: Jensen
authors.forename: Liming
authors.initials: L
authors.lastname: Liang
authors.forename: Gary C
authors.initials: GC
authors.lastname: Curhan
authors.forename: Louis R
authors.initials: LR
authors.lastname: Pasquale
authors.forename: Janey L
authors.initials: JL
authors.lastname: Wiggs
authors.forename: Immaculata
authors.initials: I
authors.lastname: De Vivo
authors.forename: Andrew T
authors.initials: AT
authors.lastname: Chan
authors.forename: Hyon K
authors.initials: HK
authors.lastname: Choi
authors.forename: Rulla M
authors.initials: RM
authors.lastname: Tamimi
authors.forename: Paul M
authors.initials: PM
authors.lastname: Ridker
authors.forename: David J
authors.initials: DJ
authors.lastname: Hunter
authors.forename: Walter C
authors.initials: WC
authors.lastname: Willett
authors.forename: Eric B
authors.initials: EB
authors.lastname: Rimm
authors.forename: Daniel I
authors.initials: DI
authors.lastname: Chasman
authors.forename: Frank B
authors.initials: FB
authors.lastname: Hu
authors.forename: Lu
authors.initials: L
authors.lastname: Qi
mesh_terms: D000328:Adult; D000368:Aged; D000483:Alleles; D015992:Body Mass Index; D015331:Cohort Studies; D003296:Cooking; D004032:Diet / Q000009:adverse effects* / Q000706:statistics & numerical data; D005260:Female; D059647:Gene-Environment Interaction; D020022:Genetic Predisposition to Disease / Q000209:etiology / Q000235:genetics*; D060005:Genotyping Techniques; D006801:Humans; D008297:Male; D008875:Middle Aged; D009765:Obesity / Q000209:etiology* / Q000235:genetics; D011446:Prospective Studies; D012307:Risk Factors; D014481:United States / Q000453:epidemiology