The genetic architecture of the association between eating behaviors and obesity : combining genetic twin modeling and polygenic risk scores

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Masip-Manuel , G , Silventoinen , K , Keski-Rahkonen , A , Palviainen , T , Sipilä , P N , Kaprio , J & Bogl , L H 2020 , ' The genetic architecture of the association between eating behaviors and obesity : combining genetic twin modeling and polygenic risk scores ' , American Journal of Clinical Nutrition , vol. 112 , no. 4 , pp. 956-966 . https://doi.org/10.1093/ajcn/nqaa181

Title: The genetic architecture of the association between eating behaviors and obesity : combining genetic twin modeling and polygenic risk scores
Author: Masip-Manuel, Guiomar; Silventoinen, Karri; Keski-Rahkonen, Anna; Palviainen, Teemu; Sipilä, Pyry N.; Kaprio, Jaakko; Bogl, Leonie H.
Contributor: University of Helsinki, Department of Public Health
University of Helsinki, Helsinki Inequality Initiative (INEQ)
University of Helsinki, Department of Public Health
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Department of Public Health
University of Helsinki, Institute for Molecular Medicine Finland
University of Helsinki, Institute for Molecular Medicine Finland
Date: 2020-10
Language: eng
Number of pages: 11
Belongs to series: American Journal of Clinical Nutrition
ISSN: 0002-9165
URI: http://hdl.handle.net/10138/320450
Abstract: Background Obesity susceptibility genes are highly expressed in the brain suggesting that they might exert their influence on body weight through eating-related behaviors. Objectives To examine whether the genetic susceptibility to obesity is mediated by eating behavior patterns. Methods Participants were 3977 twins (33% monozygotic, 56% females), aged 31–37 y, from wave 5 of the FinnTwin16 study. They self-reported their height and weight, eating behaviors (15 items), diet quality, and self-measured their waist circumference (WC). For 1055 twins with genome-wide data, we constructed a polygenic risk score for BMI (PRSBMI) using almost 1 million single nucleotide polymorphisms. We used principal component analyses to identify eating behavior patterns, twin modeling to decompose correlations into genetic and environmental components, and structural equation modeling to test mediation models between the PRSBMI, eating behavior patterns, and obesity measures. Results We identified 4 moderately heritable (h2 = 36–48%) eating behavior patterns labeled “snacking,” “infrequent and unhealthy eating,” “avoidant eating,” and “emotional and external eating.” The highest phenotypic correlation with obesity measures was found for the snacking behavior pattern (r = 0.35 for BMI and r = 0.32 for WC; P < 0.001 for both), largely due to genetic factors in common (bivariate h2 > 70%). The snacking behavior pattern partially mediated the association between the PRSBMI and obesity measures (βindirect = 0.06; 95% CI: 0.02, 0.09; P = 0.002 for BMI; and βindirect = 0.05; 95% CI: 0.02, 0.08; P = 0.003 for WC). Conclusions Eating behavior patterns share a common genetic liability with obesity measures and are moderately heritable. Genetic susceptibility to obesity can be partly mediated by an eating pattern characterized by frequent snacking. Obesity prevention efforts might therefore benefit from focusing on eating behavior change, particularly in genetically susceptible individuals.
Subject: 3142 Public health care science, environmental and occupational health
3143 Nutrition
eating behavior patterns
diet quality score
polygenic risk score
obesity measures
susceptibility to obesity
heritability
twins
genetics
BMI
snacking
BODY-MASS INDEX
ENVIRONMENTAL-INFLUENCES
ABDOMINAL OBESITY
POOLED ANALYSIS
DIET QUALITY
WEIGHT-GAIN
ADULTHOOD
YOUNG
FOOD
QUESTIONNAIRE
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