# Metabolomics Approach for Sweat Mapping the Performance of Soccer Players in Pretoria, South Africa
## 4 Discussion  
As the field of biomarker discovery expands to include new bio-sources, sweat metabolomics analysis has become an attractive approach since it is considered a non-invasive real-time media for performance monitoring [20]. Recent advancements in metabolic methodologies have facilitated their application in exercise research to investigate the adaptive and responsive mechanisms of tissues, organs, and cells in various sports contexts [14]. Monitoring sweat metabolites during intense physical activity such as soccer, is essential for understanding functional variations in response to exercise [20]. Unfortunately, there are limited scientific research studies on the discovery of sweat metabolomics of soccer players. Prior to metabolomics analysis, RPE values of soccer players were considered to determine the reached post-exercise-induced exhaustion [14]. An average RPE value of 18.25 was reached by the soccer players. Moreover, their running speed, heart rate, and temperature post 400 m track exercises were 19.78 km/h, 179 bpm, and 30.46 \({}^{\circ}\)C, respectively. In this study, metabolomics analysis was carried out to evaluate the functional status of soccer players with the aid of GCXGC/TOF-MS. Moreover, untargeted analysis was completed to discover possible significant metabolites from the sweat samples of soccer players pre- and post-exercise. Total ion chromatogram peaks of 407 metabolites were discovered from sweat samples of soccer players pre- and post-exercise. Cross-validation did not support the robustness of the model PLS-DA, due to the model being trained on a dependent and small dataset, leading to overfitting [21]. According to [PERSON] and [PERSON] [22], PLS-DA is prone to overfitting. Nonetheless, two distinct clusters were observed in the OPLS-DA score plot with permutation tests supporting the robustness of the model. Leading to a total of 57 signature metabolites being detected from the participants' sweat samples. Among the top 15 signature metabolites with the lowest \(p\)-value ranking and greater VIP are derivatives of niacin, Analyte 817 UM103, 2-[(Trimethylsilyl)oxy]propan-1-ol, L-Serine, pyroglutamic acid, L-Valine, L-Aspartic acid, meso-Erythritol, d-Galactose, 2,3,4,5,6-pentakis-O-(trimethylsilyl)-, o-methyloxyme, (1E), L-Isoleucine, L-Glutamic acid, bis(trimethylsilyl) ester, L-Alanine and 2-Octanol were mostly abundant pre-exercise, while silanamine, N,N\({}^{\prime}\)-methanetetraylbis[1,1,1-trimethyl and Benzimidazole[2,1-a]isoquinoline metabolites were mostly abundant post-exercise. The identified signature metabolites belonging to carboxylic acids, ketone, alcohols, aldehydes, aromatics, alkenes, hexoses, hydroxy fatty acids, tetracyclic N-heterocycles, allopentose, benzenes, alkanes, phenols and heterocyclic. Niacin (nicotinic acid or vitamin B3) which is the most downregulated and abundant pre-exercise, can employ its effects through energy metabolism as a precursor for nicotinamide adenine dinucleotide (NAD) and nicotinamide adenine dinucleotide phosphate (NADP), which are crucial for redox reactions in energy production [23; 24]. Moreover, nicotinate and nicotinamide metabolism were found in this study to be the sweat metabolomic pathway in soccer players pre- and post-exercise. Niacin is a coenzyme in the metabolism of amino acids, fats, and carbohydrates and it is involved in tissue formation. Researchers have established that urine is the most sensitive and reliable measure of niacin status due to its key methylated metabolites, N1-methyl-2-pyridone-5-carboxamide and N1-methyl-nicotinamide [25; 26]. However, in this study, sweat samples were used and the niacin status was also revealed. Moreover, blending niacin with a Hubbard regimen can develop diaphoresis and elimination of lipid-stored xenobiotics via the sebum or skin [27]. Moreover, the study of [PERSON] et al. [28] demonstrated that sweat is an efficient way to remove excess nicotinamide from the body.