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Changes in Cytokines Concentration Following Long-Distance Running: A Systematic Review and Meta-Analysis
Abstract
Long-distance running is an exhausting effort for the whole organism. Prolonged aerobic exercise induces changes in inflammatory markers. However, predicting muscle damage in response has limitations in terms of selecting biomarkers used to measure inflammatory status. The present study conducts a systematic review and meta-analysis of articles focusing in ultra-marathon, marathon, and half-marathon and levels of cytokines. The search was conducted in PubMed, Web of Science, and Scopus databases, resulting in the inclusion of 76 articles. IL-6 was highlighted, evaluated in 62 studies and show increase in the standard mean difference (SMD): half-marathon (SMD −1.36; IC 95%: −1.82, −0.89, Ch 2:0.58; tau 2:0.00;p< 0.0001), marathon (SMD −6.81; IC 95%: −9.26, −4.37; Ch 2:481.37 tau 2:11.88;p< 0.0001) and ultra-marathon (SMD −8.00 IC 95%: −10.47, −5.53; Ch 2:328.40; tau 2:14.19;p< 0.0001). In contrast meta-regression analysis did not show relationship to the running distance (p = 0.864). The meta-analysis evidenced increase in the concentration of IL-1ra (p< 0.0001), IL-1B (p< 0.0001), IL-8 (p< 0.0001), IL-10 (p< 0.0001) and TNF-α (p< 0.0001). Reduction in IL-2 (p< 0.0001) and INF-y (p< 0.03) and no change in the IL-4 (p< 0.56). The number of studies evaluating the effect of adipokines was limited, however Leptin and Resistin were recurrent. The effects of an acute bout of prolonged aerobic exercise will protect against chronic systemic inflammation. The time to return to baseline values showed a substantial and dose-dependent relationship with run volume. The concentration of IL-6 was robustly studied and the marathon running was the most explored. Network of endocrine interactions in which circulating factors, released in extreme exercises, interplay through inter-organ crosstalk and physiologic changes were expressed. The running volume variability was able to modulate compounds that play a fundamental role in the maintenance of homeostasis and cell signaling.
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“Inflammation can occur even after a single session of intense or prolonged physical activity and is characterized by, among other features, increased macrophage infiltration and higher secretion of both pro-inflammatory cytokines (e.g., interleukin-1β (IL-1β), interleukin-6 (IL-6), interleukin-8 (IL-8)) and anti-inflammatory cytokines (e.g., interleukin-10 (IL-10))3,4.”
From Impact of a single swimming session on inflammatory response and iron homeostasis in adolescent female athletes during the luteal phase (2025) · cites this paper as [3]
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BackgroundMuscle as an Endocrine Organ: Focus on Muscle-Derived Interleukin-6
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Cited by
Mydłowska, M., Kasperska, A., Cichoń-Woźniak, J., Dziewiecka, H., Ostapiuk-Karolczuk, J., & Skarpańska-Stejnborn, A. (2025) · Scientific Reports · doi:10.1038/s41598-025-29551-9 · Cited by 2
Metadata
- Authors
- Alves, M. D. D. J., Silva, D. D. S., Pereira, E. V. M., Pereira, D. D., de Sousa Fernandes, M. S., Santos, D. F. C., Oliveira, D. P. M., Vieira-Souza, L. M., Aidar, F. J., & de Souza, R. F.
- Venue
- Frontiers in Physiology
- Publisher
- Frontiers Media SA
- Published
- 2022-02-17
- Volume
- 13
- ISSN
- 1664-042X
- Cited by
- 41
- References
- 14
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.