Utility of extracellular vesicles as a potential biological indicator of physiological resilience during military operational stress

Abstract

Extracellular vesicles (EVs) transport biological content between cells to mediate physiological processes. The association between EVs and resilience, the ability to cope with stress, is unknown. Using unbiased machine learning approaches, we aimed to identify a biological profile of resilience. Twenty servicemen (27.8 ± 5.9 years) completed the Connor Davidson Resilience (CD‐RISC) questionnaire and were exposed to daily physical and cognitive exertion with 48‐hr sleep and caloric restriction. Blood samples from baseline and the second day of stress were analyzed for neuroendocrine biomarkers impacted by military stress. EVs were isolated from plasma and stained with antibodies associated with exosomes (CD63), microvesicles (VAMP3), and apoptotic bodies (THSD1). Individuals were separated into high (n = 10, CD‐RISC > 90) and low (n = 10, CD‐RISC p = 0.002, Hedges’ g = 1.59). Among medium‐sized EVs, high resilience exhibited a greater decrease in side scatter intensity (p = 0.014, Hedges’ g = 1.17). Both features demonstrated high to moderate diagnostic accuracy for high resilience (AUC = 0.90 and 0.79). In contrast, neuroendocrine biomarker concentrations were similar between groups. The increase in variability among THSD1 + EVs in high, but not low, resilient individuals following stress may suggest high resilience is accompanied by stress‐triggered apoptotic adaptations to the environment that are not detected in neuroendocrine biomarkers.

Document Details

Document Type
Pub Defense Publication
Publication Date
Apr 01, 2022
Source ID
10.14814/phy2.15219

Entities

People

  • Amrita Sahu
  • Bradley C. Nindl
  • Brian J. Martin
  • Fabio Ferrarelli
  • Fabrisia Ambrosio
  • Meaghan E. Beckner
  • Qi Mi
  • Shawn D Flanagan
  • William R. Conkright
  • Zachary Clemens

Organizations

  • United States Department of Defense
  • University of Pittsburgh

Tags

Readers

  • Materials Science and Engineering.
  • Oncology and Biomarker-Based Cancer Detection.
  • Psychological Intervention/Treatment for Stress, Anxiety, PTSD, and Related Emotional and Cognitive Health Symptoms.

Technology Areas

  • AI & ML