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. 2023 Nov;53(11):2039-2053.
doi: 10.1007/s40279-023-01866-5. Epub 2023 Jun 21.

Blood-Based Biomarkers for Managing Workload in Athletes: Perspectives for Research on Emerging Biomarkers

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Blood-Based Biomarkers for Managing Workload in Athletes: Perspectives for Research on Emerging Biomarkers

Nils Haller et al. Sports Med. 2023 Nov.

Abstract

At present, various blood-based biomarkers have found their applications in the field of sports medicine. This current opinion addresses biomarkers that warrant consideration in future research for monitoring the athlete training load. In this regard, we identified a variety of emerging load-sensitive biomarkers, e.g., cytokines (such as IL-6), chaperones (such as heat shock proteins) or enzymes (such as myeloperoxidase) that could improve future athlete load monitoring as they have shown meaningful increases in acute and chronic exercise settings. In some cases, they have even been linked to training status or performance characteristics. However, many of these markers have not been extensively studied and the cost and effort of measuring these parameters are still high, making them inconvenient for practitioners so far. We therefore outline strategies to improve knowledge of acute and chronic biomarker responses, including ideas for standardized study settings. In addition, we emphasize the need for methodological advances such as the development of minimally invasive point-of-care devices as well as statistical aspects related to the evaluation of these monitoring tools to make biomarkers suitable for regular load monitoring.

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Conflict of interest statement

Nils Haller, Michael Behringer, Thomas Reichel, Patrick Wahl, Perikles Simon, Karsten Krüger, Philipp Zimmer, and Thomas Stöggl declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
Phases of biomarker development. Ideally, the identification phase (through omics approaches or transferred from clinical settings) is followed by an assessment using standardized exercise settings. Finally, the biomarker is then applied in longitudinal study designs

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