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Metabolites
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Interactions between Exercise Physiology and Metabolism
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Interactions between Exercise Physiology and Metabolism

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Endocrinology and Clinical Metabolic Research".

Deadline for manuscript submissions: 20 June 2025 | Viewed by 5862

Special Issue Editors

Dr. Lijing Gong

E-Mail Website
Guest Editor
China Institute of Sport and Health Science, Beijing Sport University, Beijing 100084, China
Interests: exercise and health promotion
Dr. Enming Zhang

E-Mail Website
Guest Editor
Department of Clinical Sciences Malmö, Lund University, 21428 Malmö, Sweden
Interests: the regulation of insulin secretion in diabetes

Special Issue Information

Dear Colleagues,

Due to factors such as insufficient physical activity, excessive food consumption, and inhospitable environments, worldwide, the incidence of chronic diseases such as metabolic and non-communicable diseases is high; such incidence results in unhealthy consumption, accumulation of fat, and metabolic disorders. Exercise, as a non-pharmacological and economic therapy, can upregulate a large number of substances in the body, such as exerkines; these substances may then participate in the regulation of signaling pathways, improve physical health, prevent and treat chronic diseases, and promote the recovery of health.

This Special Issue is dedicated to the intersection of metabolism and physical activity, and the topics covered will include (but are not limited to) studies on the impact of exercise on metabolic health, the role of physical activity in preventing and managing chronic diseases, the molecular mechanisms underlying exercise-induced metabolic changes, the development of non-pharmacological interventions for enhancing metabolic functions and overall health, and the role of nutrient metabolism in improving performance.

Dr. Lijing Gong
Dr. Enming Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • exercise
  • metabolism
  • physical activity
  • chronic disease prevention
  • exerkines

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Published Papers (5 papers)

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Research

15 pages, 2603 KiB  
Article
Metabolomic Profiling of the Striatum in Shank3 Knockout ASD Rats: Effects of Early Swimming Regulation
by Yunchen Meng, Yiling Hu, Yaqi Xue and Zhiping Zhen
Metabolites 2025, 15(2), 134; https://doi.org/10.3390/metabo15020134 - 16 Feb 2025
Viewed by 494
Abstract
Objectives: This study aimed to investigate the regulatory impact of early swimming intervention on striatal metabolism in Shank3 gene knockout ASD model rats. Methods: Shank3 gene knockout exon 11–21 male 8-day-old SD rats were used as experimental subjects and randomly divided into [...] Read more.
Objectives: This study aimed to investigate the regulatory impact of early swimming intervention on striatal metabolism in Shank3 gene knockout ASD model rats. Methods: Shank3 gene knockout exon 11–21 male 8-day-old SD rats were used as experimental subjects and randomly divided into the following three groups: a Shank3 knockout control group (KC), a wild-type control group (WC) from the same litter, and a Shank3 knockout swimming group (KS). The rats in the exercise group received early swimming intervention for 8 weeks starting at 8 days old. LC-MS metabolism was employed to detect the changes in metabolites in the striatum. Results: There were 17 differential metabolites (14 down-regulated) between the KC and WC groups, 19 differential metabolites (18 up-regulated) between the KS and KC groups, and 22 differential metabolites (18 up-regulated) between the KS and WC groups. Conclusions: The metabolism of striatum in Shank3 knockout ASD model rats is disrupted, involving metabolites related to synaptic morphology, and the Glu and GABAergic synapses are abnormal. Early swimming intervention regulated the striatal metabolome group of the ASD model rats, with differential metabolites primarily related to nerve development, synaptic membrane structure, and synaptic signal transduction. Full article
(This article belongs to the Special Issue Interactions between Exercise Physiology and Metabolism)
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15 pages, 3822 KiB  
Article
The Metabolome Characteristics of Aerobic Endurance Development in Adolescent Male Rowers Using Polarized and Threshold Model: An Original Research
by Fanming Kong, Miaomiao Zhu, Xinliang Pan, Li Zhao, Sanjun Yang, Jinyuan Zhuo, Cheng Peng, Dongkai Li and Jing Mi
Metabolites 2025, 15(1), 17; https://doi.org/10.3390/metabo15010017 - 4 Jan 2025
Viewed by 656
Abstract
Objective: This study aimed to explore the molecular response mechanisms of differential blood metabolites before and after 8 weeks of threshold and polarized training models using metabolomics technology combined with changes in athletic performance. Methods: Twenty-four male rowers aged 14–16 were randomly divided [...] Read more.
Objective: This study aimed to explore the molecular response mechanisms of differential blood metabolites before and after 8 weeks of threshold and polarized training models using metabolomics technology combined with changes in athletic performance. Methods: Twenty-four male rowers aged 14–16 were randomly divided into a THR group and a POL group (12 participants each). The THR group followed a threshold training model (72%, 24%, and 4% of training time in low-, moderate-, and high-intensity zones, respectively), while the POL group followed a polarized training model (78%, 8%, and 14% training-intensity distribution). Both groups underwent an 8-week training program. Aerobic endurance changes were assessed using a 2 km maximal rowing performance test, and untargeted metabolome analysis was conducted to examine blood metabolomic changes before and after the different training interventions. Aerobic endurance changes were assessed through a 2 km maximal rowing test. Non-targeted metabolomics analysis was employed to evaluate changes in blood metabolome profiles before and after the different training interventions. Results: After 8 weeks of training, both the THR and POL groups exhibited significant improvements in 2 km maximal rowing performance (p < 0.05), with no significant differences between the groups. The THR and POL groups had 46 shared differential metabolites before and after the intervention, primarily enriched in sphingolipid metabolism, glutathione metabolism, and glycine, serine, and threonine metabolism pathways. Nine unique differential metabolites were identified in the THR group, mainly enriched in pyruvate metabolism, glycine, serine, and threonine metabolism, glutathione metabolism, and sphingolipid metabolism. A total of 14 unique differential metabolites were identified in the POL group, predominantly enriched in sphingolipid metabolism, glycine, serine, and threonine metabolism, aminoacyl-tRNA biosynthesis, and glutathione metabolism. Conclusions: The 8-week THR and POL training models demonstrated similar effects on enhancing aerobic performance in adolescent male rowers, indicating that both training modalities share similar blood metabolic mechanisms for improving aerobic endurance. Furthermore, both the THR group and the POL group exhibited numerous shared metabolites and some differential metabolites, suggesting that the two endurance training models share common pathways but also have distinct aspects in enhancing aerobic endurance. Full article
(This article belongs to the Special Issue Interactions between Exercise Physiology and Metabolism)
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14 pages, 2368 KiB  
Article
Mediating Effects of Serum Lipids and Physical Activity on Hypertension Management of Urban Elderly Residents in China
by Yang Zhao, Yike Zhang and Fei Wang
Metabolites 2024, 14(12), 707; https://doi.org/10.3390/metabo14120707 - 15 Dec 2024
Viewed by 1178
Abstract
Background/Objectives: Investigating the importance and potential causal effects of serum lipid biomarkers in the management of hypertension is vital, as these factors positively impact the prevention and control of cardiovascular disease (CVD). Methods: We surveyed 3373 urban residents using longitudinal data [...] Read more.
Background/Objectives: Investigating the importance and potential causal effects of serum lipid biomarkers in the management of hypertension is vital, as these factors positively impact the prevention and control of cardiovascular disease (CVD). Methods: We surveyed 3373 urban residents using longitudinal data from the CHARLS database, collected between 2015 and 2020. Pearson correlation methods were employed to explore the relationships among the numerical variables. A logistic regression model was utilized to identify the risk factors for hypertension. The dose–effect relationship between serum lipids and BP was assessed using restricted cubic splines (RCS). Additionally, piecewise structural equation modeling (PiecewiseSEM) was conducted to further elucidate the direct and indirect pathways involving individual body indices, serum lipids, and PA on BP responses at different levels of physical activity (PA). Results: The four serum lipids showed significant differences between hypertensive and non-hypertensive residents (p < 0.05). All lipids, except for HDL cholesterol, demonstrated extremely significant positive correlations with both systolic blood pressure (SBP) and diastolic blood pressure (DBP) (p < 0.001). All serum lipid variables were significantly associated with the incidence of hypertension. Specifically, triglycerides (bl_tg), HDL (bl_hdl), and low-density lipoprotein LDL cholesterol were identified as significant risk factors, with odds ratios (ORs) of 1.56 (95% CI: 1.33–1.85, p < 0.001), 1.16 (95% CI: 1.02–1.33, p < 0.05), and 1.62 (95% CI: 1.23–2.15, p < 0.001), respectively. Conversely, cholesterol (bl_cho) was a protective factor for hypertension, with an OR of 0.60 (95% CI: 0.42–0.82, p < 0.01). PA showed weak relationships with blood pressure (BP); however, PA levels had significant effects, particularly at low PA levels. The four serum lipids had the most mediating effect on BP, especially under low PA level conditions, while PA exhibited a partly weak mediating effect on BP, particularly under high PA level conditions. Conclusions: Serum lipids have significant nonlinear relationships with BP and PA levels exert different influences on BP. The significant mediating effects of serum lipids and the weak mediating effects of PA on individual body indices related to SBP and DBP demonstrate significant differences across varying levels of PA, highlighting the importance of low PA levels in hypertension management. This study could provide valuable recommendations and guidance in these areas. Full article
(This article belongs to the Special Issue Interactions between Exercise Physiology and Metabolism)
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15 pages, 3638 KiB  
Article
Based on Sportomics: Comparison of Physiological Status of Collegiate Sprinters in Different Pre-Competition Preparation Periods
by Pengyu Fu, Xiaomin Duan, Yuting Zhang, Xiangya Dou and Lijing Gong
Metabolites 2024, 14(10), 527; https://doi.org/10.3390/metabo14100527 - 29 Sep 2024
Cited by 1 | Viewed by 1509
Abstract
This study aimed to assess the impact of pre-competition training by comparing the differences of collegiate sprinters in physiological state between strengthening and tapering training period by sportomics and combining their sport performance. Fifteen collegiate sprinters were investigated or tested on their body [...] Read more.
This study aimed to assess the impact of pre-competition training by comparing the differences of collegiate sprinters in physiological state between strengthening and tapering training period by sportomics and combining their sport performance. Fifteen collegiate sprinters were investigated or tested on their body composition, dietary habits, energy expenditure, sleep efficiency, heart rate and respiratory rate during training, blood (blood cells, biochemical and immune markers) and urine (urinalysis), gut microbiome distribution, microbiome and blood metabolites, and their functions during the strengthening (Group A) and tapering training period (Group B) prior to competing in the national competitions. We found that 26.67% of sprinters achieved personal bests (PB) after the competition. The limb skeletal muscle mass and lymphocyte ratio of male sprinters in Group B were lower than those in Group A, and the serum creatine kinase (CK) level was higher than Group A (p < 0.05). The levels of serum CK, interleukin-6 (IL-6), interleukin-1β (IL-1β), and urine-specific gravity (SG) of the two groups were higher than the upper limit of the reference value. The detection rates of urine white blood cell (WBC) and protein in Group B were higher than those in Group A. The gut microbiome health index (GMHI) of Group A was higher than that of Group B, and the microbial dysbiosis index was lower than that of Group B. The ratio of Firmicutes/Bacteroidota (F/B) in Group A was higher than that in Group B. There were 65 differential metabolites in the A/B group, and the enriched pathway was mainly the NF-kappa B signaling pathway (up); B/T cell receptor signaling pathway (up); Th1 and Th2 cell differentiation (up); phenylalanine metabolism (up); and growth hormone synthesis, secretion, and action (up). There were significant differences in blood metabolites between the A and B groups, with a total of 89 differential metabolites, and the enriched pathway was mainly the NF-kappa B signaling pathway (up), T cell receptor signaling pathway (up), Th1 and Th2 cell differentiation (up), and glycerophospholipid metabolism (down). In conclusion, the imbalance of the gut microbiome and inflammation and immune-related metabolites of collegiate sprinters during the pre-competition tapering training period may be the cause of their limited sports performance. Full article
(This article belongs to the Special Issue Interactions between Exercise Physiology and Metabolism)
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20 pages, 4420 KiB  
Article
Plasma Metabolomics Study on the Impact of Different CRF Levels on MetS Risk Factors
by Xiaoxiao Fei, Qiqi Huang and Jiashi Lin
Metabolites 2024, 14(8), 415; https://doi.org/10.3390/metabo14080415 - 27 Jul 2024
Viewed by 1359
Abstract
To investigate the metabolomic mechanisms by which changes in cardiorespiratory fitness (CRF) levels affect metabolic syndrome (MetS) risk factors and to provide a theoretical basis for the improvement of body metabolism via CRF in people with MetS risk factors, a comparative blood metabolomics [...] Read more.
To investigate the metabolomic mechanisms by which changes in cardiorespiratory fitness (CRF) levels affect metabolic syndrome (MetS) risk factors and to provide a theoretical basis for the improvement of body metabolism via CRF in people with MetS risk factors, a comparative blood metabolomics study of individuals with varying levels of CRF and varying degrees of risk factors for MetS was conducted. Methods: Ninety subjects between the ages of 40 and 45 were enrolled, and they were categorized into low-MetS (LM ≤ two items) and high MetS (HM > three items) groups, as well as low- and high-CRF (LC, HC) and LCLM, LCLM, LCHM, and HCHM groups. Plasma was taken from the early morning abdominal venous blood. LC-MS was conducted using untargeted metabolomics technology, and the data were statistically and graphically evaluated using SPSS26.0 and R language. Results: (1) There were eight common differential metabolites in the HC vs. LC group as follows: methionine (↓), γ-aminobutyric acid (↑), 2-oxoglutatic acid (↑), arginine (↑), serine (↑), cis-aconitic acid (↑), glutamine (↓), and valine (↓); the HM vs. LM group are contrast. (2) In the HCHM vs. LCLM group, trends were observed in 2-oxoglutatic acid (↑), arginine (↑), serine (↑), cis-aconitic acid (↑), glutamine (↓), and valine (↓). (3) CRF and MetS risk factors jointly affect biological metabolic pathways such as arginine biosynthesis, TCA cycle, cysteine and methionine metabolism, glycine, serine, and threonine metabolism, arginine and proline metabolism, and alanine, aspartate, and glutamate metabolism. Conclusion: The eight common differential metabolites can serve as potential biomarkers for distinguishing individuals with different CRF levels and varying degrees of MetS risk factors. Increasing CRF levels may potentially mitigate MetS risk factors, as higher CRF levels are associated with reduced MetS risk. Full article
(This article belongs to the Special Issue Interactions between Exercise Physiology and Metabolism)
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