Research

Mixed

High polygenic scores for obesity or type 2 diabetes significantly increase disease risk but are currently weak predictors of individual outcomes, necessitating the integration of lifestyle and environmental factors for accurate risk assessment.

Do not rely on direct-to-consumer genetic tests to predict your weight or diabetes risk. While you may have a higher genetic predisposition, these tests are currently poor predictors of individual outcomes. Focus on modifiable factors like diet, physical activity, and sleep, as these environmental factors interact with your genetics to determine your actual health status. Personalized care requires combining genetic insights with lifestyle data, not just genetics alone.

GoodQualifiesHIGH confidence
Even though the genetic associations observed in GWASs are robust, their ability to predict who will be at a high risk of obesity or type 2 diabetes is still low-to-moderate, and not ready for use in clinical settings... it is unlikely that a polygenic score on its own will ever be able to accurately predict obesity or type 2 diabetes. More comprehensive approaches that include a broad spectrum of genetic, demographic, environmental, clinical, and possibly also molecular markers are needed to accurately predict who is at risk of gaining weight and/or developing type 2 diabetes.
Nicolas J. Pillon et al. · Cell · 2021

Why this rating

Based on large-scale GWAS data (UK Biobank) and Mendelian Randomization studies cited in the review.

Source

Metabolic consequences of obesity and type 2 diabetes: Balancing genes and environment for personalized care

Nicolas J. Pillon et al. · Cell · 2021

DOI 10.1016/j.cell.2021.02.012

narrative_reviewCited 226×
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DOI resolved against Crossref · corpus check 2026-06-10

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