Oral Presentation ANZOS-Breakthrough Discoveries Joint Annual Scientific Meeting 2018

Longitudinal association of a body mass index (BMI) genetic risk score with growth and BMI changes across the lifecourse (#44)

Marie-Jeanne Buscot 1 , Markus Juonala 2 3 , Terho Lehtimäki 4 5 6 , Niina Pitkänen 3 4 , Olli Raitakari 2 4 , Jorma Viikari 2 4 , Costan Magnussen 1 2
  1. Menzies Institute for Medical Research - University of Tasmania, Hobart, TASMANIA, Australia
  2. Department of Medicine, Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
  3. Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, Turku, Finland
  4. Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
  5. Department of Clinical Chemistry, Fimlab Ltd , Tampere, Finland
  6. Department of Pediatrics, Tampere University Hospital, , University of Tampere Faculty of Medicine and Life Sciences, Tampere, Finland

BACKGROUND: 

Genome-wide associations studies have identified genetic variants associated with obesity. However, the effect of genetic variants on body mass index (BMI) at different periods in life remains poorly understood. We examined the association between validated BMI-associated single nucleotide polymorphisms (SNPs) and BMI growth trajectories from childhood to mid-adulthood.

 

METHODS: 

Data were from 2631 participants aged 6-18 years at baseline in the Cardiovascular Risk in Young Finns Study who had up to 8 BMI measures collected over 31 years follow-up. A genetic risk score (GRS) was generated from 98 BMI-associated SNPs. Mixed effect and Latent Class Growth Mixture modelling were used to model individual growth parameters, and identity 6 distinct long-term BMI trajectory groups. Associations between the GRS, growth parameters, BMI trajectory groups was examined using hierarchical linear and multinomial logit regression.

 

RESULTS: 

The GRS associated with higher BMI at 9 years (females= 0.017 kg/m2 per allele, males= 0.013 kg/m2 per allele) and faster BMI growth in childhood in both sexes (age*GRS interactions p<0.01), resulting in separation of BMI trajectories between participants with high and low GRS throughout childhood. The GRS was also associated with higher weight gain after age 25 years (age*GRS interaction p<0.01, with each unit increase in GRS associated with a 0.12 kg/m2 increase in BMI/year). The relative risk for belonging to the progressively overweight, incident obese, and increasing obese categories vs. stable normal BMI trajectory ranged between 0.3 and 0.9 per unit increase in GRS.

 

CONCLUSIONS: 

Genetic determinants of BMI effect early childhood growth and weight gain in adulthood. These data shed light on biological pathways of genetic predisposition for obesity and provide insight into the timing of BMI changes that lead to the development of adult obesity.