Akbaraly et al. Association of circulating metabolites with healthy diet and risk of cardiovascular disease: analysis of two cohort studies. Scientific Reports 2018;8:8620 DOI:10.1038/s41598-018-26441-1
Circulating metabolite levels reflect the effects of dietary intake, making metabolic profiling a highly relevant method for exploring the relationship between diet and chronic disease risk. Understanding how dietary habits impact on metabolite levels may help us to identify pathways that mediate or increase protection for chronic diseases. For example, diet may modify metabolic profiles towards a higher or lower risk of cardiovascular diseases (CVD). Dietary interventions could potentially be used to modify an individual’s disease risk and therefore represent a crucial element in the development of personalized medicine treatments.(1)
In this study, Akbaraly and colleagues aimed to identify associations between circulating metabolites and a high adherence to dietary recommendations, using the Alternative Healthy Eating Index (AHEI) – a dietary index linked to reduced risk of CVD morbidity and mortality. A discovery analysis of 80 circulating metabolites identified 41 metabolites significantly associated with AHEI score, which were measured using Nightingale’s NMR-based blood biomarker analysis in 4824 British middle-aged men and women from the Whitehall II study. Positive adherence to healthy diet was associated with lower blood levels of branched-chain amino acids, isoleucine and leucine, phenylalanine (previously linked to cardiovascular risk) and GlycA (a well-reported metabolite marker of inflammation).
A higher AHEI score was found to result in a broadly cardioprotective anti-atherogenic lipid profile. Lower blood concentrations of intermediate-density lipoprotein (IDL), low-density lipoprotein (LDL) and very low-density lipoprotein (VLDL) particles were observed, along with smaller average size of VLDL particles and a larger average size of high-density lipoprotein (HDL) particles. AHEI score was also inversely associated with VLDL cholesterol, remnant cholesterol and free cholesterol concentrations. The strongest associations observed were between AHEI score and fatty acids. Higher AHEI scores were associated with lower concentrations of saturated and monounsaturated fatty acids, and increased blood concentrations of polyunsaturated fatty acids (including omega-3 and omega-6 levels).
The 41 metabolite associations identified with AHEI scoring were further replicated in an analysis of 1716 participants in an independent cohort – the Cardiovascular Risk in Young Finns Study. Consistent results were primarily found between AHEI score and fatty acid ratios. Following these analyses, Akbaraly’s team further assessed the extent to which each of the 41 metabolites associated with AHEI score predicted CVD events over 15-year follow-up in the Whitehall II study. Higher AHEI scores were found to associate with metabolites related to lower CVD risk, with a higher ratio of polyunsaturated fatty acids and omega-3 linked to decreased CVD risk. Increased levels of branched chain amino acids, GlycA, lipoprotein particle size, monosaturated fatty acids and total VLDL cholesterol were found to significantly predict CVD risk. These metabolite biomarker associations with incident CVD risk were highly consistent with those reported earlier in a Finnish general population study.(2)
In conclusion, these finding provide evidence that further supports our understanding of the alterations in circulating metabolite levels associated with dietary intake. It is possible that specific fatty acids act as molecular mediators between unhealthy diet and increased CVD risk. Based on these observational results, additional studies directly testing the risk mediation via the metabolic biomarkers highlighted would be helpful to clarify the molecular link between diet and CVD risk development. Adherence to a healthy diet may result in cardioprotective fatty acid profiles that can reduce CVD risk.
In this study, Nightingale’s blood biomarker analysis service was used to quantify 80 lipid and metabolite measures for 4,824 participants in the Whitehall II study and 41 metabolite measures for 1,716 participants in the Cardiovascular Risk in Young Finns Study. Nightingale’s NMR-based metabolomics platform has been successfully used in a wide range of research applications and has featured in over 150 peer-reviewed studies.
1. Lehtovirta et al. Effect of Dietary Counseling on a Comprehensive Metabolic Profile from Childhood to Adulthood. Journal of Paediatrics 2018;195:190
2. Würtz et al. Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts. Circulation 2015;131:774
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