More than genetic factors, lifestyle, diet & nutrition play significant role in predicting obesity risk among Indians

Hyderabad: A genetic study conducted on Indians by researchers at the Hyderabad-based Centre for Cellular and Molecular Biology (CCMB) has contributed to groundbreaking international research that developed a genetic test called a polygenic risk score (PRS) for predicting adulthood obesity in early childhood.

This discovery could revolutionize early intervention strategies by identifying children and adolescents who are genetically predisposed to developing obesity. These at-risk individuals could then benefit from targeted preventative measures, including lifestyle interventions implemented at a younger age.

The research represents a massive collaborative effort involving an international team of 600 researchers across 500 institutions. They utilized the largest and most diverse genetic dataset ever assembled, drawing from the GIANT consortium and consumer DNA testing company 23andMe.

This comprehensive approach provided access to genetic information from over five million people across different countries, including India. Using this extensive genetic data, the research team developed the PRS, marking a significant advancement in predictive medicine and childhood obesity prevention.

Obesity poses a particularly grave problem in India and other parts of South Asia, given the high incidence of associated diseases such as diabetes, hypertension, and cardiovascular conditions. The pattern of obesity in India differs notably from that observed in Europe, with Indians tending to develop more central (abdominal) obesity. Earlier studies by Dr Giriraj Ratan Chandak at CCMB had demonstrated that the genetic basis of non-communicable diseases varies significantly between Indians and Europeans.

In this study, researchers at CCMB, led by Dr Chandak, characterised the genomes of the Indian population. Their research included individuals with diabetes as well as those with normal blood glucose levels, who have been monitored for nearly twenty years. This long-term follow-up provided a unique opportunity to investigate the genetic basis of obesity in Indians.

The team identified several obesity-associated genetic variants and used them to develop a PRS specifically tailored for Indians, effectively creating a "virtual individual" to model obesity risk. Data from Indian samples served as representative for the broader South Asian population in the international study, making the findings more relevant for Indian and South Asian populations.

The scientists also examined the relationship between genetic risk of obesity and the effectiveness of lifestyle interventions such as diet and exercise. They discovered that individuals with higher genetic risk of obesity responded better to interventions initially but also regained weight more quickly once the interventions ended.

The study also highlights the significant influence of population ancestry on obesity risk prediction accuracy. Despite utilizing genomes from a wider, more globally representative population, the PRS predicted obesity more accurately in people with European-like ancestry than in those with other ancestries, including Indians with South Asian heritage.

Many genetic variants previously associated with obesity in Europeans do not affect Indians similarly, reflecting the different pattern of obesity observed in Indian populations. “The observations made from this study are similar to the earlier results on height, where genetic variants identified in Europeans, predicted lower risk in Indians and environment related modifications of genes play a larger role. It looks like lifestyle, diet and nutrition might be playing an equal or more important role in predicting obesity in Indians. So, for Indians, lifestyle solutions or specific nutrient supplementation in the background of genetic risk might yield better results,” said Dr Chandak.

The findings suggest that lifestyle, diet, and nutrition may play equally important or even more significant roles in predicting obesity risk among Indians compared to genetic factors alone.