Exploring the non-targeted metabolomic landscape in endurance-trained runners following 10 weeks of different dietary patterns and concomitant training

Abstract

Introduction: Established guidelines recommend carbohydrate-rich diets to optimize performance in endurance sports. However, alternative dietary strategies, such as the low-arbohydrate and high-fat (LCHF) diet, have gained increasing attention due to their potential to influence metabolic flexibility and endurance performance outcomes. In this study, we aim to investigate the combined effects of a LCHF diet, along with low glycemic index (LOW-GI) and high glycemic index (HIGH-GI) diets, in conjunction with regular endurance exercise, on the metabolomic profiles of recreational runners. The classification into LOW-GI and HIGH-GI groups is based on the premise that metabolic regulation, particularly insulin response and glucose metabolism, differs significantly between the consumption of high-glycemic and low-glycemic foods.

Methods: The participants (n = 49, 28 ± 4 years, BMI: 24.2 ± 2.8 kg/m2, VO2 peak: 56 ± 8 ml/min/kg) were randomly allocated to a LOW-GI (n = 16), a HIGH-GI (n = 16) or a LCHF (n = 17) diet for 10 weeks and the same endurance training intervention. Fasting plasma samples were collected both pre- and post-intervention and were prepared for non-targeted metabolomic analysis using liquid chromatography coupled to high-resolution mass spectrometry.

Results: The LCHF diet had a considerable impact on plasma lipids, whereas the respective effects in the LOW-GI and HIGH-GI groups were less pronounced. Specifically, 179 up- or down-regulated metabolites were identified in the LCHF group, 111 in the LOW-GI group, and 139 in the HIGH-GI group. Phospholipids and sphingolipids were found to be the most prominent metabolites in the samples. Furthermore, the regulation of glycerolipids, carnitine, amino acids, and carbon acids exhibited differential patterns across the groups.

Discussion: There is evidence to suggest that the LCHF diet enhances fat metabolism, as indicated by increased levels of carnitine and ketone bodies, as well as a downregulation of amino acids. Conversely, the presence of specific carbon acids might diminish carbohydrate metabolism and impair endurance performance. In contrast, the LOW-GI group may have demonstrated augmented metabolic flexibility due to the upregulations of both carnitines and carbon acids in the samples. The elevated glycerolipids content in the HIGH-GI group suggests a potential reduction in fatty acid oxidation due to hyperinsulinemia.

Keywords: Metabolism; carbohydrate intake; glycemic index; non-targeted metabolomics; phospholipids.

Figure 1.

Schematic overview of the study design. (a) Fifty-seven recreational active male runners were recruited. (b) Subjects were randomly assigned to one of the three nutritional regimes. Training intervention was the same for all test subjects. (c) Sample treatment and preparation were performed according to previous described methods. Data treatment and statistical analysis were performed using MetaboAnalyst 5.0.

Figure 2.

Study flow chart.

Figure 3.

Training minutes in total and divided into in basic and interval sessions over the study period for the three groups.

Figure 4.

Principal component analysis (PCA) scores plot demonstrating the distribution of samples across PC3 and PC4. PC3 accounts for 5.5% of the total variance, while PC2 explains 4.9%. The clustering of data points indicates that there are no significant differences between the groups at baseline, confirming their similarity prior to the intervention.

Figure 5.

Principal component analysis (PCA) scores plot demonstrating the distribution of samples across the first two principal components (PC1 and PC2). PC1 accounts for 15% of the total variance, while PC2 explains 10%.

Figure 6.

K-means clustering after the intervention.