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Biomarkers as Temporal Signals: A Decision-Linked Multi-Layer Framework for Exercise Recovery, Overload, and

Dan Cristian Mănescu1, Camelia Daniela Plăstoi2, Ancuța Pîrvan3

  • 1Department of Physical Education and Sport, Bucharest University of Economic Studies, 010374 Bucharest, Romania.

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Summary

Understanding exercise adaptation requires monitoring biomarkers within a decision-linked framework. This approach considers the molecule-matrix-time-decision relationship for accurate interpretation of training overload and recovery.

Keywords:
biomarkerscell-free DNAcirculating RNAexercise adaptationextracellular vesiclesmetabolomicsmulti-omicsoverloadoverreachingrecovery monitoring

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Area of Science:

  • Exercise physiology
  • Biomarker science
  • Sports medicine

Background:

  • Exercise adaptation and maladaptation involve complex physiological processes.
  • Current biomarker interpretation often lacks context regarding timing and decision-making.

Purpose of the Study:

  • To develop a decision-linked framework for minimally invasive biomarkers across the recovery-overload continuum.
  • To establish a molecule-matrix-time-decision relationship for biomarker interpretation.

Main Methods:

  • Narrative review of existing literature.
  • Development of a five-layered framework for biomarker analysis.
  • Evaluation of current evidence for various biomarker types.

Main Results:

  • No single biomarker reliably distinguishes productive remodeling from maladaptation.
  • Classical chemistry is useful for stress reactivity; cfDNA shows promise for load sensitivity; metabolite panels aid recovery phenotyping.
  • Circulating RNAs and extracellular vesicles offer mechanistic insights but face pre-analytical challenges.

Conclusions:

  • Overload should be viewed as a progressive loss of signal resolution, not a threshold event.
  • Sparse, temporally staggered biomarker panels are more effective for monitoring than isolated markers.
  • Future progress requires purpose-specific panels, standardized analytics, and validation across diverse contexts.