Poster Presentation ANZOS-Breakthrough Discoveries Joint Annual Scientific Meeting 2018

Lower prevalence of performance genes are linked with increased severity of obesity in youth (#242)

Christoph CS Saner 1 2 , Brooke BH Harcourt 1 2 3 , Markus MJ Juonala 2 4 , Kung-Ting KTK Kao 1 2 3 , Peter PH Houweling 2 3 , Kathryn KN North 2 3 , Matthew MS Sabin 1 2 3
  1. Department of Endocrinology, Royal Children`s Hospital, Parkville, Victoria, Australia
  2. Murdoch Children's Research Institute, Parkville, Victoria, Australia
  3. Department of Paediatrics, The University of Melbourne, Parkville, Victoria, Australia
  4. Department of Medicine, University of Turku and Division of Medicine, Turku, Finland

Introduction
Obesity mainly arises from an imbalance between activity and energy intake, although some children appear to carry a genetic predisposition for weight gain. The ability to sustain physical activity and effectively induce a favorable metabolic outcome is genetically predetermined. Candidate genes for fitness and muscle strength have been shown to influence muscle function and mass in response to exercise. We aimed to determine whether there is a genetic predisposition limiting effectiveness of training and substrate’s utilization.

Methods
Children from the Childhood Overweight BioRepository of Australia (COBRA), presenting at The RCH Weight management Service, were clinically assessed, PBMCs were collected for DNA analysis (N=238) and Actical-accelerometer was worn for 7-days. SNP analysis on a unique performance gene panel included; ACTN3-rs1815739, CNDP1-rs2887, HIF1A-rs11549465, GALNT13-rs10196189, PPARGC1A-rs8192678, RPLP1_GEMIN8P1-rs4776471, CRHBP-rs1715747. Correlation analyses were calculated between allele prevalence of fitness genes and BMI z-scores, body and truncal fat percentage, waist circumference, blood pressure and accelerometer data.

Results
Genotypes associated with fitness were less prevalent in the COBRA cohort than in reference population studies. A more pro-fitness genotype was associated with lower body weight (p<0.05 for ACTN3,ZFYVE26 and CNDP1), decreased waist circumference (p<0.01 for RPLP1_GEMIN8P1) and decreased body fat (p<0.05 for IL15RA) in females and lower body fat (p<0.05 for SHBG_GENE) for males. Increased daily physical activity was associated with pro-fitness genotypes (p<0.05 for ZFYVE26,CNDP1,HIF1A,CRHBP and SHBG_GENE). Sex dependent variation was observed in blood pressure measurements between genotypes (p<0.05 for UGT2B4 in females; for GALNT13 and PPARGC1A in males).

Conclusion
In an obese cohort, those with higher BMI are less likely to exhibit a favorable ‘fitness genotype’ and are less physically active which places them at greater risk of cardiometabolic complications. Knowledge about susceptibility for weight gain may identifies individuals at risk for increasing severity of obesity and complications.