ArticleScientific reports2023
Interaction between genetic susceptibility to obesity and food intake on BMI in Finnish school-aged children.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 11 citations in OpenAlex.
- Trends in Ultraprocessed Food Consumption Among Korean Children and Adolescents, 2007 to 2024.JAMA network open · 2026Article
- Interaction between polygenic scores and dietary intake in relation to BMI in Canadian children.Journal of nutritional science · 2026Article
- Genetics of Common Obesity in Children and Adolescents.Annals of the New York Academy of Sciences · 2025Review
- Identification of SEC16B as a novel regulator of glucose homeostasis.Diabetologia · 2025Article
- Mediterranean diet and obesity polygenic risk interaction on adiposity in European children: The IDEFICS/I.Family Study.Pediatric obesity · 2025Article
- Young-onset type 2 diabetes-Epidemiology, pathophysiology, and management.Journal of diabetes investigation · 2025Review
- Variability of polygenic prediction for body mass index in Africa.Genome medicine · 2024Article
- Effects of marketing claims on toddler food products on parents' product preferences, perceptions and purchasing intentions: an online experiment.The international journal of behavioral nutrition and physical activity · 2024Article
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diet modulates the genetic risk of obesity, but the modulation has been rarely studied using genetic risk scores (GRSs) in children. Our objectives were to identify single nucleotide polymorphisms (SNPs) that drive the interaction of specific foods with obesity and combine these into GRSs. Genetic and food frequency data from Finnish Health in Teens study was utilized. In total, 1142 11-year-old subjects were genotyped on the Metabochip array. BMI-GRS with 30 well-known SNPs was computed and the interaction of individual SNPs with food items and their summary dietary scores were examined in relation to age- and sex-specific BMI z-score (BMIz). The whole BMI-GRS interacted with several foods on BMIz. We identified 7-11 SNPs responsible for each interaction and these were combined into food-specific GRS. The most predominant interaction was witnessed for pizza (p < 0.001): the effect on BMIz was b - 0.130 (95% CI - 0.23; - 0.031) in those with low-risk, and 0.153 (95% CI 0.072; 0.234) in high-risk. Corresponding, but weaker interactions were verified for sweets and chocolate, sugary juice drink, and hamburger and hotdog. In total 5 SNPs close to genes NEGR1, SEC16B, TMEM18, GNPDA2, and FTO were shared between these interactions. Our results suggested that children genetically prone to obesity showed a stronger association of unhealthy foods with BMIz than those with lower genetic susceptibility. Shared SNPs of the interactions suggest common differences in metabolic gene-diet interactions, which warrants further investigation.
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