Sex-Specific Relationship between the Cardiorespiratory Fitness and Plasma Metabolite Patterns in Healthy Humans—Results of the KarMeN Study

Abstract

Cardiorespiratory fitness (CRF) represents a strong predictor of all-cause mortality and is strongly influenced by regular physical activity (PA). However, the biological mechanisms involved in the body’s adaptation to PA remain to be fully elucidated. The aim of this study was to systematically examine the relationship between CRF and plasma metabolite patterns in 252 healthy adults from the cross-sectional Karlsruhe Metabolomics and Nutrition (KarMeN) study. CRF was determined by measuring the peak oxygen uptake during incremental exercise. Fasting plasma samples were analyzed by nuclear magnetic resonance spectroscopy and mass spectrometry coupled to one- or two-dimensional gas chromatography or liquid chromatography. Based on this multi-platform metabolomics approach, 427 plasma analytes were detected. Bi- and multivariate association analyses, adjusted for age and menopausal status, showed that CRF was linked to specific sets of metabolites primarily indicative of lipid metabolism. However, CRF-related metabolite patterns largely differed between sexes. While several phosphatidylcholines were linked to CRF in females, single lyso-phosphatidylcholines and sphingomyelins were associated with CRF in males. When controlling for further assessed clinical and phenotypical parameters, sex-specific CRF tended to be correlated with a smaller number of metabolites linked to lipid, amino acid, or xenobiotics-related metabolism. Interestingly, sex-specific CRF explanation models could be improved when including selected plasma analytes in addition to clinical and phenotypical variables. In summary, this study revealed sex-related differences in CRF-associated plasma metabolite patterns and proved known associations between CRF and risk factors for cardiometabolic diseases such as fat mass, visceral adipose tissue mass, or blood triglycerides in metabolically healthy individuals. Our findings indicate that covariates like sex and, especially, body composition have to be considered when studying blood metabolic markers related to CRF.

Sustained Endurance Training Leads to Metabolomic Adaptation

“…A metabolic stimulus is probably missing here, as these patients are usually very inactive [ 22 ]. An association of PC aa C42:0 with cardiopulmonary fitness has already been shown for women in the KarMeN Study [ 23 ], which strengthens the assumption that it is a cross-gender marker of cardiopulmonary fitness.…”

Single and Joined Behaviour of Circulating Biomarkers and Metabolic Parameters in High-Fit and Low-Fit Healthy Females

“…Since leptin levels have been positively correlated to body fat percentage [ 28 , 29 ], the difference in leptin presumably results from a significant difference in body fat percentage between high-fit and low-fit females, further underpinning the validity of our data. Our observation that all other biomarkers and metabolic parameters were similar between the two groups, while previous studies in high and low aerobically fit individuals found significant differences in e.g., lipid and protein metabolites [ 30 , 31 , 32 , 33 , 34 , 35 ], is likely related to our standardised experimental set-up, as compared to other studies. We studied healthy, young-adult females of similar age and BMI in a highly controlled setting, while previous studies were performed with metabolically impaired individuals [ 26 ], and individuals with substantially different BMIs [ 30 , 31 , 32 , 35 ], or wider age ranges [ 30 , 35 ] in experimental conditions that were less standardised [ 30 , 31 , 32 , 33 , 35 ], and these factors especially impact circulating metabolite levels [ 26 , 30 , 31 ].…”

“…Our observation that all other biomarkers and metabolic parameters were similar between the two groups, while previous studies in high and low aerobically fit individuals found significant differences in e.g., lipid and protein metabolites [ 30 , 31 , 32 , 33 , 34 , 35 ], is likely related to our standardised experimental set-up, as compared to other studies. We studied healthy, young-adult females of similar age and BMI in a highly controlled setting, while previous studies were performed with metabolically impaired individuals [ 26 ], and individuals with substantially different BMIs [ 30 , 31 , 32 , 35 ], or wider age ranges [ 30 , 35 ] in experimental conditions that were less standardised [ 30 , 31 , 32 , 33 , 35 ], and these factors especially impact circulating metabolite levels [ 26 , 30 , 31 ]. Given that the levels of the analysed biomarkers and metabolic parameters were similar among the healthy females in our study, and multiple of these biomarkers and metabolic parameters showed dysregulation during disease, our findings imply that this biomarker and metabolic parameters set could be used to monitor progress from a healthy to an unhealthier state and may be used in health improvement interventions.…”

“…An understanding of biomarkers in healthy individuals is a prerequisite for their use in preventive health, for example, biomarkers and metabolic parameters guided dietary advice for health improvement. Another strength of our study is the focus on female individuals, since sex can affect metabolic responses [ 20 , 30 ], and females are often underrepresented in biomarker studies [ 15 ]. One limitation of our study is the relatively small sample size with mixed Caucasian and non-Caucasian healthy females.…”

“…Here, we provided insight into which biomarkers and metabolic parameters were still not back to baseline after 22 h after exercise. Fourth, our study focused on a total of 102 biomarkers and metabolic parameters related to hormone signaling, inflammation and oxidative stress, and metabolism, while fitness level and single exercise stimulation have been associated with alterations in markers that were not included in our study, such as vitamins [ 32 , 33 ], ceramides [ 26 ], individual lysophosphatidylcholines [ 26 , 30 ] and bile acids, which could possibly have provided additional insights in these biomarkers and metabolic parameters in view of the homogeneity of our study subjects characteristics and high level of study standardisation.…”