» Articles » PMID: 37410385

Mediation and Moderation of Genetic Risk of Obesity Through Eating Behaviours in Two UK Cohorts

Overview
Journal Int J Epidemiol
Specialty Public Health
Date 2023 Jul 6
PMID 37410385
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The mechanisms underlying genetic predisposition to higher body mass index (BMI) remain unclear.

Methods: We hypothesized that the relationship between BMI-genetic risk score (BMI-GRS) and BMI was mediated via disinhibition, emotional eating and hunger, and moderated by flexible (but not rigid) restraint within two UK cohorts: the Genetics of Appetite Study (GATE) (n = 2101, 2010-16) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 1679, 2014-18). Eating behaviour was measured by the Adult Eating Behaviour Questionnaire and Three-Factor Eating Questionaire-51.

Results: The association between BMI-GRS and BMI were partially mediated by habitual, emotional and situational disinhibition in the GATE/ALSPAC meta-mediation [standardized betaindirect 0.04, 95% confidence interval (CI) 0.02-0.06; 0.03, 0.01-0.04; 0.03, 0.01-0.04, respectively] external hunger and internal hunger in the GATE study (0.02, 0.01-0.03; 0.01, 0.001-0.02, respectively). There was evidence of mediation by emotional over/undereating and hunger in the ALSPAC study (0.02, 0.01-0.03; 0.01, 0.001-0.02; 0.01, 0.002-0.01, respectively). Rigid or flexible restraint did not moderate the direct association between BMI-GRS and BMI, but high flexible restraint moderated the effect of disinhibition subscales on BMI (reduction of the indirect mediation by -5% to -11% in GATE/ALSPAC) and external hunger (-5%) in GATE. High rigid restraint reduced the mediation via disinhibition subscales in GATE/ALSPAC (-4% to -11%) and external hunger (-3%) in GATE.

Conclusions: Genetic predisposition to a higher BMI was partly explained by disinhibition and hunger in two large cohorts. Flexible/rigid restraint may play an important role in moderating the impact of predisposition to higher BMI.

Citing Articles

Deciphering the Interplay between Genetic Risk Scores and Lifestyle Factors on Individual Obesity Predisposition.

Chermon D, Birk R Nutrients. 2024; 16(9).

PMID: 38732542 PMC: 11085817. DOI: 10.3390/nu16091296.


Exploring a novel therapeutic strategy: the interplay between gut microbiota and high-fat diet in the pathogenesis of metabolic disorders.

Jia X, Chen Q, Wu H, Liu H, Jing C, Gong A Front Nutr. 2024; 10:1291853.

PMID: 38192650 PMC: 10773723. DOI: 10.3389/fnut.2023.1291853.

References
1.
Paternoster L, Standl M, Waage J, Baurecht H, Hotze M, Strachan D . Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. Nat Genet. 2015; 47(12):1449-1456. PMC: 4753676. DOI: 10.1038/ng.3424. View

2.
Yengo L, Sidorenko J, Kemper K, Zheng Z, Wood A, Weedon M . Meta-analysis of genome-wide association studies for height and body mass index in ∼700000 individuals of European ancestry. Hum Mol Genet. 2018; 27(20):3641-3649. PMC: 6488973. DOI: 10.1093/hmg/ddy271. View

3.
Westenhoefer J, Stunkard A, Pudel V . Validation of the flexible and rigid control dimensions of dietary restraint. Int J Eat Disord. 1999; 26(1):53-64. DOI: 10.1002/(sici)1098-108x(199907)26:1<53::aid-eat7>3.0.co;2-n. View

4.
Brunner E, Maruyama K, Shipley M, Cable N, Iso H, Hiyoshi A . Correction: Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory. Int J Obes (Lond). 2021; 45(3):711. PMC: 7906901. DOI: 10.1038/s41366-021-00770-0. View

5.
Boyd A, Golding J, Macleod J, Lawlor D, Fraser A, Henderson J . Cohort Profile: the 'children of the 90s'--the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol. 2012; 42(1):111-27. PMC: 3600618. DOI: 10.1093/ije/dys064. View