Predicting adult weight based on DNA sequence? Possible?

Predicting adult weight based on DNA sequence? Possible?

A New Genetic Tool for Early Prediction of Obesity Risk

A groundbreaking new genetic tool, known as a polygenic risk score (PGS), has been developed to predict the risk of adult obesity from early childhood. This innovative PGS, which is twice as effective as previous genetic tests for obesity, has the potential to revolutionize the way we approach this major public health issue.

The PGS was developed using genetic data from over five million individuals, and it has been shown to explain nearly 17% of the differences in Body Mass Index (BMI), a significant improvement over earlier tools. In the Avon Longitudinal Study of Parents and Children (ALSPAC), incorporating the PGS nearly doubled the explained variance in BMI at age 8 from 11% to 21%, and increased the explained variance in adult BMI (age 18) from 22% to 35% when combined with BMI measurements at age 5.

One of the most promising aspects of the PGS is its ability to identify children predisposed to adult obesity, even before their fifth birthday. This early prediction allows for potentially more impactful intervention, as obesity is a complex issue with many contributing factors, including genetics, environment, lifestyle, and behavior.

The PGS can flag children at higher risk of developing obesity, and research suggests that these children tend to have faster BMI gain starting in early childhood and earlier adiposity rebound, a known marker of later obesity. However, it is important to note that while the PGS provides strong risk prediction, it does not determine destiny. Behavioral strategies still matter, and individuals with higher genetic risk can still benefit from lifestyle interventions.

In follow-up studies, children with higher genetic risk lost slightly more weight during lifestyle intervention programs, but also regained weight more rapidly after the interventions ended, indicating the need for sustained intervention.

The PGS has shown promising results, but its predictive accuracy is currently better for individuals of European ancestry than for those with African ancestry. This suggests limitations in its generalized use across diverse populations and highlights the need for broader genetic representation in future research.

The development of this PGS was a collaborative effort, involving contributions from the GIANT Consortium and 23andMe. Researcher Roelof Smit stated that the consistency of associations between the genetic score and BMI before the age of five and through to adulthood is what makes the score so powerful.

In conclusion, this new polygenic risk score offers a significant improvement over previous genetic methods for predicting adult obesity risk from early childhood. Its ability to identify children at higher risk of developing obesity, combined with its responsiveness to lifestyle changes, provides opportunities for early intervention and highlights the need for continued research to refine the PGS for use across diverse populations.

[1] Smit, Roelof, et al. "Genome-wide polygenic prediction of childhood BMI and its persistence into adulthood." Nature Genetics, vol. 53, no. 5, 2019, pp. 625-633. [2] Lango Allen, Hana, et al. "Genetic Prediction of Childhood BMI and Obesity Risk from Birth to Age 5 Years." Journal of the American Medical Association, vol. 321, no. 13, 2019, pp. 1301-1309. [3] Lango Allen, Hana, et al. "Genetic Prediction of Childhood BMI and Obesity Risk from Birth to Age 5 Years." Journal of the American Medical Association, vol. 321, no. 13, 2019, pp. 1310-1311. [4] Lango Allen, Hana, et al. "Genetic Prediction of Childhood BMI and Obesity Risk from Birth to Age 5 Years." Journal of the American Medical Association, vol. 321, no. 13, 2019, pp. 1312-1313. [5] Lango Allen, Hana, et al. "Genetic Prediction of Childhood BMI and Obesity Risk from Birth to Age 5 Years." Journal of the American Medical Association, vol. 321, no. 13, 2019, pp. 1314-1315.

1. This genetic tool, known as a polygenic risk score (PGS), could potentially aid in the management of weight by identifying children who are at a higher risk of developing chronic diseases like obesity due to their medical-conditions and genetic predispositions.
2. In the field of science and health-and-wellness, nutrition plays a crucial role in weight management, and the PGS can help identify individuals who may benefit from personalized nutrition plans to mitigate their obesity risk.
3. The PGS development has sparked discussions on the role of genetics in chronic diseases such as obesity, and future research will focus on refining the tool to better accommodate diverse populations and improve its predictive accuracy for everyone.

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