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Metabolic Signatures of Performance in Elite World Tour Professional Male Cyclists

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Travis Nemkov
Travis Nemkov
Travis Nemkov
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Francesca Isabelle Cendali at University of Colorado Anschutz
Francesca Isabelle Cendali
  • University of Colorado Anschutz
Davide Stefanoni at San Raffaele Scientific Institute
Davide Stefanoni
Janel L. Martinez
Janel L. Martinez
Janel L. Martinez
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Abstract and Figures

Background and Objective Metabolomics studies of recreational and elite athletes have been so far limited to venipuncture-dependent blood sample collection in the setting of controlled training and medical facilities. However, limited to no information is currently available to determine if findings in laboratory settings are translatable to a real-world scenario in elite competitions. The goal of this study was to define molecular signatures of exertion under controlled exercise conditions and use these signatures as a framework for assessing cycling performance in a World Tour competition. Methods To characterize molecular profiles of exertion in elite athletes during cycling, we performed metabolomics analyses on blood isolated from 28 international-level, elite, World Tour professional male athletes from a Union Cycliste Internationale World Team taken before and after a graded exercise test to volitional exhaustion and before and after a long aerobic training session. Moreover, established signatures were then used to characterize the metabolic physiology of five of these cyclists who were selected to represent the same Union Cycliste Internationale World Team during a seven-stage elite World Tour race. Results Using dried blood spot collection to circumvent logistical hurdles associated with field sampling, these studies defined metabolite signatures and fold change ranges of anaerobic or aerobic exertion in elite cyclists, respectively. Blood profiles of lactate, carboxylic acids, fatty acids, and acylcarnitines differed between exercise modes. The graded exercise test elicited significant two- to three-fold accumulations in lactate and succinate, in addition to significant elevations in free fatty acids and acylcarnitines. Conversely, the long aerobic training session elicited a larger magnitude of increase in fatty acids and acylcarnitines without appreciable increases in lactate or succinate. Comparable signatures were revealed after sprinting and climbing stages, respectively, in a World Tour race. In addition, signatures of elevated fatty acid oxidation capacity correlated with competitive performance. Conclusions Collectively, these studies provide a unique view of alterations in the blood metabolome of elite athletes during competition and at the peak of their performance capabilities. Furthermore, they demonstrate the utility of dried blood sampling for omics analysis, thereby enabling molecular monitoring of athletic performance in the field during training and competition.
Metabolic signatures of short/high-intensity and long/low-intensity training regimens. A During the training camp, whole blood from 28 Elite World Tour cyclists was sampled before and after a 1 h graded exercise test on an ergometer. B Whole blood lactate measurements (millimolar) as a function of normalized power output (W·kg⁻¹) during the test. C During the same training camp, whole blood was sampled from 27 of the cyclists before and after a 180 km field test maintained in an aerobic regimen beneath the lactate threshold. Multivariate analyses including a principal component analysis (PCA) and a variable importance in projection (VIP) of partial least squares-discriminant analysis were performed on metabolomics data generated from the graded exercise test (D) and (E), or aerobic field test (F) and (G), respectively. Individual cyclist fold changes (post/pre) for metabolites involved in glycolysis and the tricarboxylic acid (TCA) cycle are shown as violin plots for the (H) graded exercise test and (I) aerobic field test. Individual cyclist fold changes (post/pre) for free fatty acids are shown as violin plots for the (J) graded exercise test and (K) aerobic field test. Individual cyclist fold changes (post/pre) for acylcarnitines are shown as violin plots for the (L) graded exercise test and (M) aerobic field test. P values (two-tailed paired T-test) for the post/pre-comparison are indicated as * < 0.05, ** < 0.01, *** < 0.001, and **** < 0.0001
Metabolic signatures of short/high-intensity and long/low-intensity training regimens. A During the training camp, whole blood from 28 Elite World Tour cyclists was sampled before and after a 1 h graded exercise test on an ergometer. B Whole blood lactate measurements (millimolar) as a function of normalized power output (W·kg⁻¹) during the test. C During the same training camp, whole blood was sampled from 27 of the cyclists before and after a 180 km field test maintained in an aerobic regimen beneath the lactate threshold. Multivariate analyses including a principal component analysis (PCA) and a variable importance in projection (VIP) of partial least squares-discriminant analysis were performed on metabolomics data generated from the graded exercise test (D) and (E), or aerobic field test (F) and (G), respectively. Individual cyclist fold changes (post/pre) for metabolites involved in glycolysis and the tricarboxylic acid (TCA) cycle are shown as violin plots for the (H) graded exercise test and (I) aerobic field test. Individual cyclist fold changes (post/pre) for free fatty acids are shown as violin plots for the (J) graded exercise test and (K) aerobic field test. Individual cyclist fold changes (post/pre) for acylcarnitines are shown as violin plots for the (L) graded exercise test and (M) aerobic field test. P values (two-tailed paired T-test) for the post/pre-comparison are indicated as * < 0.05, ** < 0.01, *** < 0.001, and **** < 0.0001
… 
Metabolomics of a multi-stage World Tour cycling race. A Whole-blood samples were isolated from cyclists before and after Stage 1, 4, and 6 of a consecutive seven-stage race and analyzed by mass spectrometry. B Volcano plots for Stage 1, 4, and 6 from top to bottom, respectively, with the number of significantly changed metabolites (fold change > 2, p < 0.05) indicated in the plot. C Hierarchical clustering analysis of features identified by metabolomics and lipidomics. D Partial least squares-discriminant analysis of identified metabolites and lipids before and after each stage (left) along with the top 15 compounds by variable importance in projection (right). Partial least squares-discriminant analysis of identified metabolites and lipids (E) before and (F) after each stage (left) along with the top 15 compounds by variable importance in projection (right). G Four distinct longitudinal signatures were determined by fuzzy c-means clustering. Compounds with patterns matching the top four clusters were analyzed to determine significantly enriched pathways in each cluster. Pathways for each cluster are organized by − log10(γp value), with the number of pathway hits (pink) plotted as a fraction of pathway total (turquoise)
Metabolomics of a multi-stage World Tour cycling race. A Whole-blood samples were isolated from cyclists before and after Stage 1, 4, and 6 of a consecutive seven-stage race and analyzed by mass spectrometry. B Volcano plots for Stage 1, 4, and 6 from top to bottom, respectively, with the number of significantly changed metabolites (fold change > 2, p < 0.05) indicated in the plot. C Hierarchical clustering analysis of features identified by metabolomics and lipidomics. D Partial least squares-discriminant analysis of identified metabolites and lipids before and after each stage (left) along with the top 15 compounds by variable importance in projection (right). Partial least squares-discriminant analysis of identified metabolites and lipids (E) before and (F) after each stage (left) along with the top 15 compounds by variable importance in projection (right). G Four distinct longitudinal signatures were determined by fuzzy c-means clustering. Compounds with patterns matching the top four clusters were analyzed to determine significantly enriched pathways in each cluster. Pathways for each cluster are organized by − log10(γp value), with the number of pathway hits (pink) plotted as a fraction of pathway total (turquoise)
… 
Energy metabolism. A A pathway overview of energy metabolism is shown, along with stage comparisons of individual metabolite levels in B the pentose phosphate pathway (oxidative phase in red, non-oxidative phase in blue), C glycolysis, and the D tricarboxylic acid (TCA) cycle and the E amino acid transamination products. P values are depicted as * < 0.05, ** < 0.01, and *** < 0.001. F A heat map for group averages of the summed total for lipid classes is shown. G Relative levels at each stage/timepoint of acylcarnitines (top) and fatty acids (bottom) for each cyclist are shown. P values for Stage 1 Pre/Post comparison (* < 0.05, ** < 0.01, *** < 0.001), Stage 4 Pre/Post comparison (+) and Stage 6 Pre/Post comparison (#) are shown. H The peak areas at each stage/timepoint for coenzyme A precursor pantothenate and carnitine are shown
Energy metabolism. A A pathway overview of energy metabolism is shown, along with stage comparisons of individual metabolite levels in B the pentose phosphate pathway (oxidative phase in red, non-oxidative phase in blue), C glycolysis, and the D tricarboxylic acid (TCA) cycle and the E amino acid transamination products. P values are depicted as * < 0.05, ** < 0.01, and *** < 0.001. F A heat map for group averages of the summed total for lipid classes is shown. G Relative levels at each stage/timepoint of acylcarnitines (top) and fatty acids (bottom) for each cyclist are shown. P values for Stage 1 Pre/Post comparison (* < 0.05, ** < 0.01, *** < 0.001), Stage 4 Pre/Post comparison (+) and Stage 6 Pre/Post comparison (#) are shown. H The peak areas at each stage/timepoint for coenzyme A precursor pantothenate and carnitine are shown
… 
Individual cyclist analysis. A Metabolite, lipid, and training peaks functional cycling data for the entirety of Stage 6, along with training peaks during the final 7.5 km climb were analyzed. B Average speed and output for Stage 6, as well as the average speed and output of the final 7.5 km are plotted by individual cyclist. C Pearson correlation coefficients (R²) for the top 20 Post-Stage 6 metabolite correlates with average speed during Stage 6 are shown, with positive correlates indicated in the red background and negative correlates indicated in the blue background. D Abundances (y-axis values are peak area top, given in arbitrary units) for each cyclist of the top three positive (top) and negative (bottom) correlates with average speed are shown. E A sparse partial least squares-discriminant analysis (sPLS-DA) is shown, with samples color coded according to cyclist and timepoint indicated as 1–6, where 1 = Stage 1-Pre consecutively up to 6 = Stage 6-Post. F The top ten loadings for principal component 2 are plotted. Longitudinal profiles during the course of the race for G acylcarnitines, H free fatty acids, I glycolysis, J tricarboxylic acid cycle, and K NAD + /NADH in each cyclist are shown as line graphs, with timepoints indicated on the bottom x-axis and abundance indicated on the y-axis as peak area (arbitrary units) except for glucose and lactate, for which the absolute concentrations are reported (millimolar)
Individual cyclist analysis. A Metabolite, lipid, and training peaks functional cycling data for the entirety of Stage 6, along with training peaks during the final 7.5 km climb were analyzed. B Average speed and output for Stage 6, as well as the average speed and output of the final 7.5 km are plotted by individual cyclist. C Pearson correlation coefficients (R²) for the top 20 Post-Stage 6 metabolite correlates with average speed during Stage 6 are shown, with positive correlates indicated in the red background and negative correlates indicated in the blue background. D Abundances (y-axis values are peak area top, given in arbitrary units) for each cyclist of the top three positive (top) and negative (bottom) correlates with average speed are shown. E A sparse partial least squares-discriminant analysis (sPLS-DA) is shown, with samples color coded according to cyclist and timepoint indicated as 1–6, where 1 = Stage 1-Pre consecutively up to 6 = Stage 6-Post. F The top ten loadings for principal component 2 are plotted. Longitudinal profiles during the course of the race for G acylcarnitines, H free fatty acids, I glycolysis, J tricarboxylic acid cycle, and K NAD + /NADH in each cyclist are shown as line graphs, with timepoints indicated on the bottom x-axis and abundance indicated on the y-axis as peak area (arbitrary units) except for glucose and lactate, for which the absolute concentrations are reported (millimolar)
… 
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Vol.:(0123456789)
Sports Medicine (2023) 53:1651–1665
https://doi.org/10.1007/s40279-023-01846-9
ORIGINAL RESEARCH ARTICLE
Metabolic Signatures ofPerformance inElite World Tour Professional
Male Cyclists
TravisNemkov1 · FrancescaCendali1 · DavideStefanoni1 · JanelL.Martinez2· KirkC.Hansen1 ·
IñigoSan‑Millán2,3 · AngeloD’Alessandro1,4
Accepted: 19 March 2023 / Published online: 6 May 2023
© The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023
Abstract
Background and Objective Metabolomics studies of recreational and elite athletes have been so far limited to venipuncture-
dependent blood sample collection in the setting of controlled training and medical facilities. However, limited to no infor-
mation is currently available to determineif findings in laboratory settings are translatable to a real-world scenario in elite
competitions.The goal of this study was to define molecular signatures of exertion under controlled exercise conditions and
use these signatures as a framework for assessing cycling performance in a World Tour competition.
Methods To characterize molecular profiles of exertion in elite athletes during cycling, we performed metabolomics analyses
on blood isolated from 28 international-level, elite, World Tour professional male athletes from a Union Cycliste Interna-
tionale World Team taken before and after a graded exercise test to volitional exhaustion and before and after a long aerobic
training session. Moreover, established signatures were then used to characterize the metabolic physiology of five of these
cyclists who were selected to represent the same Union Cycliste Internationale World Team during a seven-stage elite World
Tour race.
Results Using dried blood spot collection to circumvent logistical hurdles associated with field sampling, these studies
defined metabolite signatures and fold change ranges of anaerobic or aerobic exertion in elite cyclists, respectively. Blood
profiles of lactate, carboxylic acids, fatty acids, and acylcarnitines differed between exercise modes. The graded exercise
test elicited significant two- to three-fold accumulations in lactate and succinate, in addition to significant elevations in free
fatty acids and acylcarnitines. Conversely, the long aerobic training session elicited a larger magnitude of increase in fatty
acids and acylcarnitines without appreciable increases in lactate or succinate. Comparable signatures were revealed after
sprinting and climbing stages, respectively, in a World Tour race. In addition, signatures of elevated fatty acid oxidation
capacity correlated with competitive performance.
Conclusions Collectively, these studies provide a unique view of alterations in the blood metabolome of elite athletes dur-
ing competition and at the peak of their performance capabilities. Furthermore, they demonstrate the utility of dried blood
sampling for omics analysis, thereby enabling molecular monitoring of athletic performance in the field during training and
competition.
* Travis Nemkov
travis.nemkov@cuanschutz.edu
* Angelo D’Alessandro
angelo.dalessandro@cuanschutz.edu
1 Department ofBiochemistry andMolecular Genetics,
Anschutz Medical Campus, University ofColorado, 12801
East 17th Ave L18-9122, Aurora, CO80045, USA
2 Department ofMedicine, Division ofEndocrinology,
Metabolism andDiabetes, University ofColorado, Anschutz
Medical Campus, Aurora, CO, USA
3 Department ofHuman Physiology andNutrition, University
ofColorado, ColoradoSprings, CO, USA
4 Department ofBiochemistry andMolecular Genetics,
University ofColorado, Anschutz Medical Campus, 12801
East 17Th Ave L18-9118, Aurora, CO80045, USA
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... It allows for the screening of differential metabolites between individuals and populations while also elucidating the biological mechanisms underlying these differences. With these advantages, metabolomics has emerged as a research hot spot for explaining metabolic changes induced by endurance training [6,7]. ...
... These pathways converge to produce acetyl-CoA, which enters the TCA cycle, generating reduced equivalents (NADH+, FADH+) and GTP, which are converted to ATP through the electron transport chain [27]. As the initial compound in the TCA cycle, citric acid converts carbohydrates, fats, and proteins into carbon dioxide, releasing energy [7]. Increased resting levels of citric acid in athletes indicate enhanced aerobic energy contribution and improved mitochondrial TCA cycle function, suggesting enhanced aerobic metabolic activity [28,29]. ...
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... Blood clotting at room temperature (30 min); Centrifugation at 1000× g for 15 min; Storage at −80 • C - [80] To analyze the changes in plasma metabolome in response to cycling exercise Plasma Lithium heparin tubes 10 h-fast; Sampling 30 min before training, 10 min while cycling, and 20 min after training Centrifugation at 1800× g for 10 min; Storage at −80 • C - [44] To analyze the metabolomic pathways and exercise in myocardial ischemia cases Plasma -Sampling before, after, and 4 h after stress testing Blood plasma preparation within 60 min; Storage at −80 • C - [81] To assess the effect of physical exercise on the composition of metabolites in the blood - [85] To analyze the effects of respiratory muscle training at different exercise intensities on the metabolome profile Serum Serum separator tubes 12 h-fast Blood clotting at room temperature (30 min); Centrifugation at 1450× g for 10 min; Storage at −80 • C Blood samples were collected in the morning between 7:00 and 10:00. Participants were advised to avoid high-intensity exercise, stimulating foods and drinks, alcoholic beverages, and supplements on the day before blood collection. ...
... Isotopically labeled internal standards [85] To study the effects of respiratory muscle training at different exercise intensities on the metabolome profile NRM Serum -Isotopically labeled internal standards [86] BSTFA-bis(trimethylsilyl)-trifluoroacetamide; GC-MS-gas chromatography-mass spectrometry; LC-MS-liquid chromatography-mass spectrometry; MS-mass spectrometry; NMR-Nuclear Magnetic Resonance Spectroscopy; TMCS-trimethylchlorosilane; UHPLC MS-ultra-high-performance liquid chromatography-mass spectrometry. ...
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Full-text available
  • Feb 2023
Metabolomics and lipidomics techniques are capable of comprehensively measuring hundreds to thousands of small molecules in single analytical runs and have been used to characterize responses to exercise traditionally using venipuncture‐produced liquid samples. Advanced microsampling devices offer an alternative by circumventing the requirement to maintain frozen samples. This approach combines a microneedle puncture for blood draw with microfluidic sample collection onto a dried carrier and has thus far been employed for targeted measurements of a few analytes. To demonstrate the utility of advanced dried microsampling to characterize metabolomic and lipidomic changes during exercise, we obtained samples before and after a 2‐mile run from twelve (8 male, 4 female) healthy volunteers with various ranges in activity levels. Results highlighted significant changes in whole blood levels of several metabolites associated with energy (glycolysis and Tricarboxylic Acid cycle) and redox (Pentose Phosphate Pathway) metabolism. Lipid changes during this same period were individualized and less uniform. Sex‐based differences in response to running highlighted reliance on carbohydrate or fat substrate utilization in males or females, respectively. The results presented herein illustrate the ability of this approach to monitor circulating metabolome and lipidome profiles from field sampled blood in response to exercise.
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Signatures of Mitochondrial Dysfunction and Impaired Fatty Acid Metabolism in Plasma of Patients with Post-Acute Sequelae of COVID-19 (PASC)
Article
Full-text available
  • Oct 2022
Exercise intolerance is a major manifestation of post-acute sequelae of severe acute respiratory syndrome coronavirus infection (PASC, or “long-COVID”). Exercise intolerance in PASC is associated with higher arterial blood lactate accumulation and lower fatty acid oxidation rates during graded exercise tests to volitional exertion, suggesting altered metabolism and mitochondrial dysfunction. It remains unclear whether the profound disturbances in metabolism that have been identified in plasma from patients suffering from acute coronavirus disease 2019 (COVID-19) are also present in PASC. To bridge this gap, individuals with a history of previous acute COVID-19 infection that did not require hospitalization were enrolled at National Jewish Health (Denver, CO, USA) and were grouped into those that developed PASC (n = 29) and those that fully recovered (n = 16). Plasma samples from the two groups were analyzed via mass spectrometry-based untargeted metabolomics and compared against plasma metabolic profiles of healthy control individuals (n = 30). Observational demographic and clinical data were retrospectively abstracted from the medical record. Compared to plasma of healthy controls or individuals who recovered from COVID-19, PASC plasma exhibited significantly higher free- and carnitine-conjugated mono-, poly-, and highly unsaturated fatty acids, accompanied by markedly lower levels of mono-, di- and tricarboxylates (pyruvate, lactate, citrate, succinate, and malate), polyamines (spermine) and taurine. Plasma from individuals who fully recovered from COVID-19 exhibited an intermediary metabolic phenotype, with milder disturbances in fatty acid metabolism and higher levels of spermine and taurine. Of note, depletion of tryptophan—a hallmark of disease severity in COVID-19—is not normalized in PASC patients, despite normalization of kynurenine levels—a tryptophan metabolite that predicts mortality in hospitalized COVID-19 patients. In conclusion, PASC plasma metabolites are indicative of altered fatty acid metabolism and dysfunctional mitochondria-dependent lipid catabolism. These metabolic profiles obtained at rest are consistent with previously reported mitochondrial dysfunction during exercise, and may pave the way for therapeutic intervention focused on restoring mitochondrial fat-burning capacity.
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Cancer-related fatigue mediates the relationships between physical fitness and attendance and quality of life after participation in a clinical exercise program for survivors of cancer
Article
Full-text available
  • Jul 2022
  • QUAL LIFE RES
Purpose Cancer-related fatigue (CRF) is a common and limiting symptom reported by survivors of cancer, negatively impacting health-related quality of life (HRQoL). Exercise improves CRF, HRQoL, and physical fitness in survivors. Prospective research trials have shown that exercise-associated fitness improvements effects on HRQoL are mediated by CRF; however, this has not been investigated in a pragmatic real-world setting. This study utilizes data from a large heterogenous population of survivors participating in a clinical exercise program to investigate this mediation effect, as well as effects of program attendance. Methods Data were collected from 194 survivors completing the BfitBwell Cancer Exercise Program (July 2016–February 2020). Changes in HRQoL, CRF, and fitness were calculated and program attendance collected. Basic correlation analyses were performed. Linear regression analyses were performed to assess mediation by CRF. Results All measures of CRF, HRQoL, and physical fitness significantly improved following the exercise program. Improvements in physical fitness were significantly correlated with improvements in HRQoL (r = 0.15–0.18), as was program attendance (r = 0.26) and CRF (r = 0.59). The effects of physical fitness and program attendance on HRQoL were at least partially mediated by the effects of CRF. Conclusion This study extends research findings on how exercise programs improve HRQoL in survivors of cancer to a real-world setting. Results indicate that clinical exercise programs should target reductions in CRF in survivors (during or after treatment) through improvements in physical fitness to improve HRQoL and that high attendance should be encouraged regardless of fitness changes.
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Chronic Lactate Exposure Decreases Mitochondrial Function by Inhibition of Fatty Acid Uptake and Cardiolipin Alterations in Neonatal Rat Cardiomyocytes
Article
Full-text available
  • Mar 2022
Introduction Lactate is an important signaling molecule with autocrine, paracrine and endocrine properties involved in multiple biological processes including regulation of gene expression and metabolism. Levels of lactate are increased chronically in diseases associated with cardiometabolic disease such as heart failure, type 2 diabetes, and cancer. Using neonatal ventricular myocytes, we tested the hypothesis that chronic lactate exposure could decrease the activity of cardiac mitochondria that could lead to metabolic inflexibility in the heart and other tissues. Methods Neonatal rat ventricular myocytes (NRVMs) were treated for 48 h with 5, 10, or 20 mM lactate and CPT I and II activities were tested using radiolabelled assays. The molecular species profile of the major mitochondrial phospholipid, cardiolipin, was determined using electrospray ionization mass spectrometry along with reactive oxygen species (ROS) levels measured by Amplex Red and mitochondrial oxygen consumption using the Seahorse analyzer. Results CPT I activity trended downward (p = 0.07) and CPT II activity significantly decreased with lactate exposure (p < 0.001). Cardiolipin molecular species containing four 18 carbon chains (72 carbons total) increased with lactate exposure, but species of other sizes decreased significantly. Furthermore, ROS production was strongly enhanced with lactate (p < 0.001) and mitochondrial ATP production and maximal respiration were both significantly down regulated with lactate exposure (p < 0.05 and p < 0.01 respectively). Conclusions Chronic lactate exposure in cardiomyocytes leads to a decrease in fatty acid transport, alterations of cardiolipin remodeling, increases in ROS production and decreases in mitochondrial oxygen consumption that could have implications for both metabolic health and flexibility. The possibility that both intra-, or extracellular lactate levels play roles in cardiometabolic disease, heart failure, and other forms of metabolic inflexibility needs to be assessed in vivo.
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Metabolomics in Exercise and Sports: A Systematic Review
Article
Full-text available
  • Mar 2022
  • SPORTS MED
Background Metabolomics is a field of omics science that involves the comprehensive measurement of small metabolites in biological samples. It is increasingly being used to study exercise physiology and exercise-associated metabolism. However, the field of exercise metabolomics has not been extensively reviewed or assessed.Objective This review on exercise metabolomics has three aims: (1) to provide an introduction to the general workflow and the different metabolomics technologies used to conduct exercise metabolomics studies; (2) to provide a systematic overview of published exercise metabolomics studies and their findings; and (3) to discuss future perspectives in the field of exercise metabolomics.Methods We searched electronic databases including Google Scholar, Science Direct, PubMed, Scopus, Web of Science, and the SpringerLink academic journal database between January 1st 2000 and September 30th 2020.ResultsBased on our detailed analysis of the field, exercise metabolomics studies fall into five major categories: (1) exercise nutrition metabolism; (2) exercise metabolism; (3) sport metabolism; (4) clinical exercise metabolism; and (5) metabolome comparisons. Exercise metabolism is the most popular category. The most common biological samples used in exercise metabolomics studies are blood and urine. Only a small minority of exercise metabolomics studies employ targeted or quantitative techniques, while most studies used untargeted metabolomics techniques. In addition, mass spectrometry was the most commonly used platform in exercise metabolomics studies, identified in approximately 54% of all published studies. Our data indicate that biomarkers or biomarker panels were identified in 34% of published exercise metabolomics studies.Conclusion Overall, there is an increasing trend towards better designed, more clinical, mass spectrometry-based metabolomics studies involving larger numbers of participants/patients and larger numbers of metabolites being identified.
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Daily energy expenditure through the human life course
Article
Full-text available
  • Aug 2021
A lifetime of change Measurements of total and basal energy in a large cohort of subjects at ages spanning from before birth to old age document distinct changes that occur during a human lifetime. Pontzer et al . report that energy expenditure (adjusted for weight) in neonates was like that of adults but increased substantially in the first year of life (see the Perspective by Rhoads and Anderson). It then gradually declined until young individuals reached adult characteristics, which were maintained from age 20 to 60 years. Older individuals showed reduced energy expenditure. Tissue metabolism thus appears not to be constant but rather to undergo transitions at critical junctures. —LBR
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Physiological extremes of the human blood metabolome: A metabolomics analysis of highly glycolytic, oxidative, and anabolic athletes
Article
Full-text available
  • Jun 2021
Human metabolism is highly variable. At one end of the spectrum, defects of enzymes, transporters, and metabolic regulation result in metabolic diseases such as diabetes mellitus or inborn errors of metabolism. At the other end of the spectrum, favorable genetics and years of training combine to result in physiologically extreme forms of metabolism in athletes. Here, we investigated how the highly glycolytic metabolism of sprinters, highly oxidative metabolism of endurance athletes, and highly anabolic metabolism of natural bodybuilders affect their serum metabolome at rest and after a bout of exercise to exhaustion. We used targeted mass spectrometry‐based metabolomics to measure the serum concentrations of 151 metabolites and 43 metabolite ratios or sums in 15 competitive male athletes (6 endurance athletes, 5 sprinters, and 4 natural bodybuilders) and 4 untrained control subjects at fasted rest and 5 minutes after a maximum graded bicycle test to exhaustion. The analysis of all 194 metabolite concentrations, ratios and sums revealed that natural bodybuilders and endurance athletes had overall different metabolite profiles, whereas sprinters and untrained controls were more similar. Specifically, natural bodybuilders had 1.5 to 1.8‐fold higher concentrations of specific phosphatidylcholines and lower levels of branched chain amino acids than all other subjects. Endurance athletes had 1.4‐fold higher levels of a metabolite ratio showing the activity of carnitine‐palmitoyl‐transferase I and 1.4‐fold lower levels of various alkyl‐acyl‐phosphatidylcholines. When we compared the effect of exercise between groups, endurance athletes showed 1.3‐fold higher increases of hexose and of tetradecenoylcarnitine (C14:1). In summary, physiologically extreme metabolic capacities of endurance athletes and natural bodybuilders are associated with unique blood metabolite concentrations, ratios, and sums at rest and after exercise. Our results suggest that long‐term specific training, along with genetics and other athlete‐specific factors systematically change metabolite concentrations at rest and after exercise. Years of training and favorable genetics combine to physiologically extrem forms of metabolism in competitive athletes. We compared the serum metabolomes of sprinters, natural bodybuilders, endurance athletes and untrained subjects. Natural bodybuilders and endurance athletes have unique metabolomes after an overnight fast and after fasted maximum exercise whereas sprinters are more similar to untrained controls.
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Analysis of major fatty acids from matched plasma and serum samples reveals highly comparable absolute and relative levels
Article
Full-text available
  • Mar 2021
  • PROSTAG LEUKOTR ESS
Measuring fatty acid (FA) levels in blood as a risk factor for chronic disease has been studied extensively. Previous research has used either plasma or serum samples to examine these associations. However, whether results from plasma and serum samples can be compared remains unclear, as differences in methodology related to the separation of plasma and serum from whole blood may impact FA levels. This study analyzed the individual FA content of matched plasma and serum samples in both absolute (μg/mL) and relative percent (%) composition. Analyses were performed using archived fasted morning samples from the Florey Adelaide Male Ageing Study (FAMAS). Matched plasma and serum samples were available from 98 male subjects aged 40-85. Total FA were analyzed by gas-liquid chromatography equipped with a flame ionization detector (GLC-FID). Analyses comprised of over 60 FA including major FA such as Palmitic Acid (PA), Palmitoleic acid (POA), Stearic Acid (SA), Oleic Acid (OA), Linoleic Acid (LNA), alpha-linolenic acid (ALA), Eicosapentaenoic acid (EPA), Arachidonic Acid (ARA), and Docosahexaenoic acid (DHA). Differences between groups was determined by t-test. Correlation and Bland-Altman analyses were also performed to examine the relationship between plasma and serum samples. There were no significant differences between major plasma and serum fatty acids expressed in μg/mL and relative % composition. Correlation analysis determined a strong and significantly positive association (r ≥ 0.65, p < 0.05) between major plasma and serum FA in absolute and relative terms. Bland-Altman analysis further supported the strong agreement between plasma and serum values in both absolute and relative terms. These findings demonstrate that studies reporting plasma or serum fatty acid analyzed by GLC-FID can be compared with one another.
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Warburg-like metabolic transformation underlies neuronal degeneration in sporadic Alzheimer’s disease
Article
  • Aug 2022
  • CELL METAB
The drivers of sporadic Alzheimer’s disease (AD) remain incompletely understood. Utilizing directly converted induced neurons (iNs) from AD-patient-derived fibroblasts, we identified a metabolic switch to aerobic glycolysis in AD iNs. Pathological isoform switching of the glycolytic enzyme pyruvate kinase M (PKM) toward the cancer-associated PKM2 isoform conferred metabolic and transcriptional changes in AD iNs. These alterations occurred via PKM2’s lack of metabolic activity and via nuclear translocation and association with STAT3 and HIF1α to promote neuronal fate loss and vulnerability. Chemical modulation of PKM2 prevented nuclear translocation, restored a mature neuronal metabolism, reversed AD-specific gene expression changes, and re-activated neuronal resilience against cell death.
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Hallmarks of Cancer: New Dimensions
Article
  • Jan 2022
The hallmarks of cancer conceptualization is a heuristic tool for distilling the vast complexity of cancer phenotypes and genotypes into a provisional set of underlying principles. As knowledge of cancer mechanisms has progressed, other facets of the disease have emerged as potential refinements. Herein, the prospect is raised that phenotypic plasticity and disrupted differentiation is a discrete hallmark capability, and that nonmutational epigenetic reprogramming and polymorphic microbiomes both constitute distinctive enabling characteristics that facilitate the acquisition of hallmark capabilities. Additionally, senescent cells, of varying origins, may be added to the roster of functionally important cell types in the tumor microenvironment. Significance Cancer is daunting in the breadth and scope of its diversity, spanning genetics, cell and tissue biology, pathology, and response to therapy. Ever more powerful experimental and computational tools and technologies are providing an avalanche of “big data” about the myriad manifestations of the diseases that cancer encompasses. The integrative concept embodied in the hallmarks of cancer is helping to distill this complexity into an increasingly logical science, and the provisional new dimensions presented in this perspective may add value to that endeavor, to more fully understand mechanisms of cancer development and malignant progression, and apply that knowledge to cancer medicine.
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