The interaction between energy intake, physical activity and UCP2 -866G/A gene variation on weight gain and changes in adiposity: an Indonesian Nutrigenetic Cohort (INDOGENIC)

Abstract

This study aimed to investigate an interaction between energy intake, physical activity, and UCP2 gene variation on weight gain and adiposity changes in Indonesian adults. This is a prospective cohort study conducted in 323 healthy adults living in the city of Yogyakarta, Indonesia. Energy intake, physical activity, body weight, body mass index (BMI), percent body fat, waist to hip ratio (WHR) were measured at baseline and after two years while and UCP2 -866G/A gene variation was determined at baseline. We reported that after two years subjects had a significant increment in body weight, BMI, body fat and reduction in WHR (all p<0.05). In all subjects, total energy intake was significantly correlated with changes in body weight (B=0.128, p=0.023) and body fat (B=0.123, p=0.030). Among subjects with GG genotype, changes in energy intake was positively correlated with changes in body weight (B=0.232, p=0.016) and body fat (B=0.201, p=0.034). These correlations were insignificant among those with AA+GA genotypes (all p>0.05). In summary, we show that UCP2 gene variation might influence the adiposity response towards changes in energy intake. Subjects with GG genotype of UCP2 -866G/A gene were more responsive to energy intake thus more prone to weight gain due to overeating.

Gene–Diet Interactions on Metabolic Disease-Related Outcomes in Southeast Asian Populations: A Systematic Review

“…There were no significant interactions observed between UCP2 gene variations and any of the dietary factors on the obesity-related parameters; however, significant interaction depicting a positive correlation between UCP2 SNP rs659366 (−866G/A) GG genotype and total energy intake on body weight change (P interaction = 0.016) and BFP (P interaction = 0.034) was observed. The same study also showed significant interaction (P interaction = 0.040) between UCP2 SNP rs659366 (−866G/A) GG genotype and physical activity on WHR indicating that participants with increased physical activity and the UCP2 gene variant had lower WHR [29]. Further studies on larger populations are required to validate these results and elucidate the mechanisms.…”

“…Seven studies analyzed gene-diet interactions on obesity-related parameters in the Indonesian population: four cross-sectional [12,21,31,32], two prospective cohort studies [29,33] and one case-control study [30].…”

Gene-environment interactions and the effect on obesity risk in low and middle-income countries: a scoping review

“…Four candidate gene studies showed that interactions between 4 different gene variants and low levels of PA were significantly associated with obesity-related anthropometrics ( 33 , 37 , 39 , 42 ). The study by Moore et al.…”

“…While results from nutrigenetic studies and studies investigating gene-physical activity interactions on obesity suggest there could be some consistent associations between eating patterns or low levels of PA and their genetic interactions on an increased risk of obesity, associations with specific gene variants were not replicated across studies. Across all included studies, statistically significant findings were reported for 12 individual SNPs, including FLJ33544 rs140133294 ( 43 ), FTO rs1421085 ( 29 , 37 ), rs9939609 ( 31 , 45 ), rs10163409 ( 33 ), rs3751812 ( 39 ), CARTPT rs2239670 ( 35 ), UCP2 rs659366 ( 42 ), CLOCK rs1801260 ( 36 ), MC4R rs17782313 ( 37 , 45 , 46 ), rs12970134 ( 40 , 46 ), TMEM18 rs7561317 and NEGR1 rs2815752 ( 37 ). However, these associations were either only significant in single trials or were not replicated in response to the same environmental exposure.…”

“…However, even with replication, many of the study designs shown in this review are susceptible to reverse causation, highlighting the need for more well-controlled long-term prospective longitudinal research looking at GxE on obesity. Using P -values without effect sizes or confidence intervals to report associations was also prevalent across studies ( 32 – 35 , 42 ), alongside small sample sizes and erroneous underpowered statistical analyses, resulting in concerns for selective reporting and publication bias.…”