| Předmět: |
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| Zdroj: |
Heart Disease Weekly; 10/7/2024, p1264-1264, 1p |
| Abstrakt: |
A study conducted by researchers at Osaka University Graduate School of Medicine explores the relationship between polygenic risk scores (PRSs) and the individual risk of cardiometabolic diseases associated with certain environmental factors. Using machine learning techniques, the study found that the association between obesity and type 2 diabetes and between smoking and coronary artery disease varied across different PRS values. The researchers concluded that individual-level prediction of disease risks associated with specific exposures is important in precision medicine. The study highlights the complexity of these associations and suggests that high-PRS groups may not necessarily benefit the most from preventive interventions. [Extracted from the article] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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