ORIGINAL RESEARCH article
Front. Nutr.
Sec. Nutritional Epidemiology
Volume 12 - 2025 | doi: 10.3389/fnut.2025.1693151
This article is part of the Research TopicThe role of Lipids in Relation to Preventing Inflammation and Chronic DiseasesView all 4 articles
The NMR-Measured Omega-6/Omega-3 Fatty Acid Ratio Improves Cardiovascular Risk Prediction in 183,230 UK adults
Provisionally accepted- University of South China Hengyang Medical School, Hengyang, China
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Background: Improving 10-year cardiovascular risk prediction beyond the established SCORE2 algorithm is a clinical need. The plasma omega-6/omega-3 (O6:O3) polyunsaturated fatty acid (PUFA) ratio, a marker of inflammatory balance, is a promising biomarker for enhancing risk stratification. We aimed to evaluate if adding the O6:O3 ratio to the SCORE2 model improves the prediction of major adverse cardiovascular events (MACE). Methods: We conducted a prospective cohort study of 183,230 UK Biobank participants (aged 50-69 years, free of baseline cardiovascular disease or diabetes). The plasma O6:O3 ratio was measured by nuclear magnetic resonance (NMR) spectroscopy. We compared the predictive performance of the SCORE2 model with and without the O6:O3 ratio in an independent validation cohort (N=54,940) using Harrell's C-index, Net Reclassification Improvement (NRI), and Integrated Discrimination Improvement (IDI). Results: In the validation set, adding the O6:O3 ratio to SCORE2 significantly increased the C-index from 0.742 (95% CI: 0.738-0.746) to 0.747 (95% CI: 0.743-0.751) (P<0.001). The extended model also significantly improved risk reclassification (NRI 8.4%, 95% CI: 3.6-12.2%; IDI 0.021, 95% CI: 0.010-0.032). This improvement was more pronounced in men than in women, and both models remained well-calibrated. Conclusions: Incorporating the plasma O6:O3 PUFA ratio provides a modest but statistically significant improvement in 10-year MACE risk prediction with the SCORE2 algorithm. As a modifiable biomarker, the O6:O3 ratio holds potential to refine risk stratification and guide personalized nutritional interventions.
Keywords: Fatty Acids, cvd, Metabolomics, Prediction model, Score2
Received: 26 Aug 2025; Accepted: 13 Oct 2025.
Copyright: © 2025 Huang, Lu, Shen, Liu, Zeng, Liu, Bin and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Wenkai Bin, 771779024@qq.com
Meili Li, usc_tzt@163.com
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