According to a new study that was published in the journal Cell Metabolism, lifestyle factors that can be changed can reduce an individual’s hereditary risk of obesity.
A non-infectious pandemic of obesity is being caused by sedentary lifestyles and increased consumption of foods high in calories. Obesity is polygenic and heritable. Weight growth is a result of multiple metabolic pathways, and obesity is linked to over a thousand genetic variations. It has long been accepted that there is no way to change an individual’s genetic propensity to fat.
Studies on the interactions between genes and environment, however, have revealed that some lifestyle choices may lessen the impact of particular genes linked to obesity. However, these investigations were restricted to a small number of obesogenic genes and lifestyle variables. Furthermore, it is unclear how genetic propensity to obesity interacts with modifiable lifestyle factors to lessen its burden.
Researchers looked at whether lifestyle factors that can be changed could reduce an individual’s genetic risk of obesity in the current study. After removing over 1,000 patients without data on body mass index (BMI) or obesity-related morbidities (ORMs) and identifying over 338,600 white British people from the United Kingdom Biobank who passed the genetic quality control, 337,554 people were left for inclusion.
Based on a genome-wide association analysis for BMI in individuals with European ancestry, a polygenic score (PGS) was calculated. Five obesogenic lifestyle factors—alcohol intake, sleep length, sedentary habits, nutrition, and physical activity—were combined to create a healthy lifestyle score. After examining the Biobank health data, incident obesity was found to be the main effect. The secondary outcome was prevalent obesity, which was defined as having a baseline BMI of 30 kg/m2.
By calculating the odds (ORs) and hazard ratios (HRs) of prevalent and incident obesity by PGS percentile and lifestyle, absolute hazards were estimated. Cox proportional hazard regression models were used to estimate HRs, while logistic regression models were used to evaluate ORs. Additionally, the likelihood of obesity by the age of 75 was estimated. Using hospital data, self-reports, or death registry records, incident ORM was determined.
Using additive and multiplicative interaction analysis, the relationship between lifestyle and genetic susceptibility to obesity was assessed. The correlations between genetic risk and lifestyle factors and incidence obesity and ORMs were investigated using Cox proportional hazard regression models. Multivariable logistic regression was used to investigate the relationship between genetic risk categories, lifestyle categories, or both, and the prevalence of obesity.
People who were obese had lower levels of healthy lifestyle characteristics and a higher PGS. Obesity was found to be both independently and together related with an unhealthy lifestyle and a high genetic risk. The researchers looked at the independent effects of lifestyle on obesity and genetic risk on obesity after controlling for lifestyle categories.
Regardless of lifestyle categories, a high genetic risk was linked to a higher incidence of incident and widespread obesity. In a similar vein, poor lifestyle choices were linked, independently of genetic risk, to a higher chance of incident and widespread obesity. When comparing people with a healthy lifestyle and low genetic risk to those with a poor lifestyle and high genetic risk, the HR of obesity was 3.54.
The healthy lifestyle group had a 1.7% chance of obesity by age 75, while the bad lifestyle group had a 2.8% chance based on incident obesity. According to the prevalence of obesity, the comparable estimations were 30.7% and 13.9%, respectively. Different additive interactions were found when analyzing the relative excess risk caused by the interaction between genetic risk and lifestyle; multiplicative interaction analysis also yielded reliable results.
Regardless of genetic risk, the lowest risks of obesity were linked to avoiding sedentary behavior. The dangers of ORMs were similar for people with high PGS and healthy lifestyles compared to those with low PGS. On the other hand, ORM risks were higher among those with a bad lifestyle and a high PGS. After controlling for BMI, there was no longer any correlation between PGS and ORM risks.