Untargeted metabolomics reveal signatures of a healthy lifestyle

Abstract

This cross-sectional study investigated differences in the plasma metabolome in two groups of adults that were of similar age but varied markedly in body composition and dietary and physical activity patterns. Study participants included 52 adults in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females). The results using an extensive untargeted ultra high-performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS) metabolomics analysis with 10,535 metabolite peaks identified 486 important metabolites (variable influence on projections scores of VIP ≥ 1) and 16 significantly enriched metabolic pathways that differentiated LIFE and CON groups. A novel metabolite signature of positive lifestyle habits emerged from this analysis highlighted by lower plasma levels of numerous bile acids, an amino acid profile characterized by higher histidine and lower glutamic acid, glutamine, β-alanine, phenylalanine, tyrosine, and proline, an elevated vitamin D status, higher levels of beneficial fatty acids and gut microbiome catabolism metabolites from plant substrates, and reduced levels of N-glycan degradation metabolites and environmental contaminants. This study established that the plasma metabolome is strongly associated with body composition and lifestyle habits. The robust lifestyle metabolite signature identified in this study is consistent with an improved life expectancy and a reduced risk for chronic disease.

Keywords: Diet; Lifestyle; Mass spectrometry; Metabolomics; Obesity; Physical activity.

Figure 1

Scores plots of OPLS-DA of the metabolomics data obtained by UHPLC-HRMS analysis of plasma samples showing the differentiation of Lifestyle (LIFE) (blue, right-hand side) from Controls (CON) (green, left-hand side), R2X = 0.175; R2Y = 0.959); Q2 = 0.523, sevenfold cross validation).

Figure 2

Receiver-operator-characteristic (ROC) curves for LIFE and CON group discriminators trained on the entire metabolomics dataset. The blue curve is derived from category scores obtained from a single model optimized on all 104 samples, while the red curve depicts category scores obtained for each of 104 samples using 104 separate models optimized on 103 samples (leave-one-out cross-validation, LOO-CV). The area under the curves (AUC) for the single model and LOO models were 1.0 and 0.96, respectively, with p values of 7.7e−19 and 5.6e−16.

Figure 3

Leave-one-out cross validation (LOOCV) predictions using all metabolomics data for selected traits. Older age was strongly related to the metabolomics data with no differences between the LIFE and CON groups (r = 0.80, p = value = 5e−24). LIFE and CON group membership was strongly predicted using the plasma metabolomics data for three different body composition outcomes including BMI (r = 0.84, p-value = 3e−29), percent body fat (r = 0.80, p-value = 7e−24), and the sagittal abdominal diameter (SAD) (r = 0.82, p-value = 6e−27), and moderately predicted for the average number of daily servings of fruits and vegetables combined (r = 0.66, p-value = 3e−14), and the days per week for moderate-to-vigorous physical activity (MVPA) (r = 0.68, p-value = 4e−15).

Figure 4

The enriched metabolic pathways for differentiating LIFE and CON groups using the Functional Analysis module in MetaboAnalyst. Top pathways significant (p < 0.05) in the analysis are annotated. A full list of enriched pathways is available in Supplementary Information Table S7. P1. Bile acid biosynthesis; P2. Histidine metabolism; P3. Lysine metabolism; P4. Heparan sulfate degradation; P5. Phytanic acid peroxisomal oxidation; P6. Glycosphingolipid metabolism; P7. Pyrimidine metabolism; P8. Chondroitin sulfate degradation; P9. N-Glycan degradation; P10. Aminosugars metabolism; P11. Beta-alanine metabolism; P12. Vitamin D3 (cholecalciferol) metabolism; P13. Glycosphingolipid biosynthesis—ganglioseries; P14. Glycosphingolipid biosynthesis—globoseries; P15. Butanoate metabolism; P16. Tyrosine metabolism. P4, P10, and P13 are not visible due to overlap.