Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Aug 1;54(8):283-295.
doi: 10.1152/physiolgenomics.00184.2021. Epub 2022 Jun 13.

Neuroendocrine, inflammatory, and extracellular vesicle responses during the Navy Special Warfare Screener Selection Course

Affiliations

Neuroendocrine, inflammatory, and extracellular vesicle responses during the Navy Special Warfare Screener Selection Course

Meaghan E Beckner et al. Physiol Genomics. .

Abstract

Military operational stress is known to increase adrenal hormones and inflammatory cytokines, while decreasing hormones associated with the anabolic milieu and neuroendocrine system. Less is known about the role of extracellular vesicles (EVs), a form of cell-to-cell communication, in military operational stress and their relationship to circulating hormones. The purpose of this study was to characterize the neuroendocrine, cytokine, and EV response to an intense. 24-h selection course known as the Naval Special Warfare (NSW) Screener and identify associations between EVs and cytokines. Blood samples were collected the morning of and following the NSW Screener in 29 men (18-26 yr). Samples were analyzed for concentrations of cortisol, insulin-like growth factor I (IGF-I), neuropeptide-Y (NPY), brain-derived neurotrophic factor (BDNF), α-klotho, tumor necrosis factor-α (TNFα), and interleukins (IL) -1β, -6, and -10. EVs stained with markers associated with exosomes (CD63), microvesicles (VAMP3), and apoptotic bodies (THSD1) were characterized using imaging flow cytometry and vesicle flow cytometry. The selection event induced significant changes in circulating BDNF (-43.2%), IGF-I (-24.6%), TNFα (+17.7%), and IL-6 (+13.6%) accompanied by increases in intensities of THSD1+ and VAMP3+ EVs (all P < 0.05). Higher concentrations of IL-1β and IL-10 were positively associated with THSD1+ EVs (P < 0.05). Military operational stress altered the EV profile. Surface markers associated with apoptotic bodies were positively correlated with an inflammatory response. Future studies should consider a multiomics assessment of EV cargo to discern canonical pathways that may be mediated by EVs during military stress.

Keywords: apoptotic bodies; biomarkers; exosomes; microvesicles; stress.

PubMed Disclaimer

Conflict of interest statement

No conflicts of interest, financial or otherwise, are declared by the authors.

Figures

Figure 1.
Figure 1.
Overview of extracellular vesicle (EV) analysis. A: EVs were isolated from plasma samples using size exclusion chromatography (SEC). B: EV concentrations and size were measured using vesicle flow cytometry (vFC). C: EV samples were stained with immunofluorescence markers associated with exosomes (CD63), microvesicles (VAMP3), and apoptotic bodies (THSD1) and then assed using imaging flow cytometry to collect multispectral images of each EV that passed through the system. D: gating strategies were applied to EV image files to identify populations of CD63+, VAMP3+, and THSD1+ EVs. (Figure created with BioRender.com.)
Figure 2.
Figure 2.
Neuroendocrine biomarker concentrations before and after 24-h Screener (N = 20). Significant declines (*P < 0.05) in response to the stress of the 24-h Screener were observed in brain-derived neurotrophic factor (BDNF) (A) and insulin-like growth factor I (IGF-I) (B), whereas no significant difference was observed in cortisol (C), neuropeptide-Y (NPY) (D), or α-klotho (E). Bars indicate mean and standard deviation. Gray lines connect raw data points corresponding to each individual’s response. Statistical significance was analyzed by paired samples t test.
Figure 3.
Figure 3.
Inflammatory cytokine concentrations before and after 24-h Screener (N = 20). A significant increase (*P < 0.05) in response to the stress of the 24-h Screener was observed in tumor necrosis factor-α (TNF-α) (A), whereas no significant differences were observed in interleukin 6 (IL-6) (B), interleukin 1β (IL-1β) (C), or interleukin 10 (IL-10) (D). Bars indicate mean and standard deviation. Gray lines connect raw data points corresponding to each individual’s response. Statistical significance was analyzed by paired samples t test.
Figure 4.
Figure 4.
Extracellular vesicle (EV) characterization pre- and post-Screener using vesicle flow cytometry (vFC). A: representative plot of estimated diameter of all particles. Extracellular vesicles (EVs) were stained with a lipid membrane marker (vFRed) and analyzed by vFC. Data from each sample were collected for 120 s. B: there was no significant difference in EV concentration from pre- to post-Screener (N = 20). C: EV size was determined based on EV membrane fluorescence calibrated to synthetic vesicle size standards (Lipo100). EV diameter significantly (*P < 0.05) increased in response to the stress. Bars indicate mean and standard deviation. Gray lines connect raw data points corresponding to each individual’s response. Statistical significance was analyzed by paired samples t test.
Figure 5.
Figure 5.
Changes in THSD1+ (apoptotic bodies), VAMP3+ (microvesicles), and CD63+ (exosomes) extracellular vesicles (EVs) relative to total EVs in response to 24-h Screener (N = 20). A significant difference (*P < 0.05) in response to the stress of the 24-h Screener was not observed in the proportion of THSD1+ EVs relative to the total number of EVs (A); however, the average intensity of THSD1 among all THSD1+ EVs (B) and average intensity of THSD1+ EVs normalized to total EVs (C) significantly increased. No significant changes were observed in the proportion of VAMP3+ EVs relative to the total number of EVs (D), whereas the average intensity of VAMP3 among all VAMP3+ EVs (E) and the average intensity of VAMP3+ EVs normalized to total EVs (F) significantly increased. No significant differences were observed in the proportion of CD63+ EVs relative to the total number of EVs (G), the average intensity of CD63+ among all CD63+ EVs (H), or CD63+ EVs normalized to total EVs (I). Note that in H, all CD63 intensities were increased by 50 to be above 0 for figure interpretation. Note that in I, all CD63 intensities were increased by 0.001 to be above 0 for figure interpretation. Bars indicate mean and standard deviation in all figures. Statistical significance was analyzed by paired samples t test.
Figure 6.
Figure 6.
Changes in THSD1+ (apoptotic bodies), VAMP3+ (microvesicles), and CD63+ (exosomes) extracellular vesicles (EVs) based on size stratification pre- to post-Screener (N = 20). Among large-sized EVs, a significant difference (*P < 0.05) in response to the stress of the 24-h Screener was observed in the average intensity of THSD1+ (A), but not the average intensity of VAMP3+ (B). No changes were observed among medium-sized EVs in average intensity of THSD1+ (C) or the average intensity of VAMP3+ (D). There was no difference in the average intensity of CD63+ among small-sized EVs (E). Note that intensity data for D and E were increased by 50 arbitrary units (AU) to be above zero for figure interpretation. Bars indicate mean and standard deviation in all figures. Statistical significance was analyzed by paired samples t test.
Figure 7.
Figure 7.
Changes in tetraspanin (TS) cocktail+ (CD63, CD81, and CD9) extracellular vesicles (EVs) pre- to post-Screener (N = 20). A and B: the concentration of TS cocktail+ EVs was similar pre- to post-Screener (A), whereas the median fluorescence intensity (MFI) of TS cocktail+ EVs significantly (*P < 0.05) increased in response to the stress (B). Bars indicate mean and standard deviation in all figures. AU, arbitrary units. Statistical significance was analyzed by paired samples t test.

References

    1. Henning PC, Scofield DE, Spiering BA, Staab JS, Matheny RW Jr, Smith MA, Bhasin S, Nindl BC. Recovery of endocrine and inflammatory mediators following an extended energy deficit. J Clin Endocrinol Metab 99: 956–964, 2014. doi:10.1210/jc.2013-3046. - DOI - PubMed
    1. Friedl KE, Moore RJ, Hoyt RW, Marchitelli LJ, Martinez-Lopez LE, Askew EW. Endocrine markers of semistarvation in healthy lean men in a multistressor environment. J Appl Physiol (1985) 88: 1820–1830, 2000. doi:10.1152/jappl.2000.88.5.1820. - DOI - PubMed
    1. Morgan CA 3rd, Wang S, Mason J, Southwick SM, Fox P, Hazlett G, Charney DS, Greenfield G. Hormone profiles in humans experiencing military survival training. Biol Psychiatry 47: 891–901, 2000. doi:10.1016/s0006-3223(99)00307-8. - DOI - PubMed
    1. Beckner ME, Main L, Tait JL, Martin BJ, Conkright WR, Nindl BC. Circulating biomarkers associated with performance and resilience during military operational stress. Eur J Sport Sci 22: 72–86, 2022. doi:10.1080/17461391.2021.1962983. - DOI - PubMed
    1. Beckner ME, Conkright WR, Eagle SR, Martin BJ, Sinnott AM, LaGoy AD, Proessl F, Lovalekar M, Jabloner LR, Roma PG, Basner M, Ferrarelli F, Germain A, Flanagan SD, Connaboy C, Nindl BC. Impact of simulated military operational stress on executive function relative to trait resilience, aerobic fitness, and neuroendocrine biomarkers. Physiol Behav 236: 113413, 2021. doi:10.1016/j.physbeh.2021.113413. - DOI - PubMed

Publication types

LinkOut - more resources