A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality

doi:10.1016/j.isci.2021.103483

. 2021 Dec 15;25(1):103483.

doi: 10.1016/j.isci.2021.103483. eCollection 2022 Jan 21.

A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality

Nicole L Vike¹, Sumra Bari¹, Khrystyna Stetsiv¹, Alexa Walter², Sharlene Newman³, Keisuke Kawata^{4

5}, Jeffrey J Bazarian⁶, Zoran Martinovich¹, Eric A Nauman^{7

8

9}, Thomas M Talavage^{7

10

11}, Linda Papa¹², Semyon M Slobounov², Hans C Breiter^{1

13}

Affiliations

¹ Warren Wright Adolescent Center Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
² Department of Kinesiology, Pennsylvania State University, University Park, PA 16801, USA.
³ Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA.
⁴ Department of Kinesiology, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA.
⁵ Program in Neuroscience, College of Arts and Sciences, Indiana University, Bloomington, IN 47405, USA.
⁶ Department of Emergency Medicine, University of Rochester, Rochester, NY 14627, USA.
⁷ Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA.
⁸ School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
⁹ Department of Basic Medical Sciences, Purdue University, West Lafayette, IN 47907, USA.
¹⁰ School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
¹¹ Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45221, USA.
¹² Department of Emergency Medicine, Orlando Regional Medical Center, Orlando, FL 32806, USA.
¹³ Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard School of Medicine, Boston, MA 02114, USA.

PMID: 35106455
PMCID: PMC8786649
DOI: 10.1016/j.isci.2021.103483

A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality

Nicole L Vike et al. iScience. 2021.

. 2021 Dec 15;25(1):103483.

doi: 10.1016/j.isci.2021.103483. eCollection 2022 Jan 21.

Authors

Affiliations

¹ Warren Wright Adolescent Center Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
² Department of Kinesiology, Pennsylvania State University, University Park, PA 16801, USA.
³ Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA.
⁴ Department of Kinesiology, School of Public Health-Bloomington, Indiana University, Bloomington, IN 47405, USA.
⁵ Program in Neuroscience, College of Arts and Sciences, Indiana University, Bloomington, IN 47405, USA.
⁶ Department of Emergency Medicine, University of Rochester, Rochester, NY 14627, USA.
⁷ Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA.
⁸ School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.
⁹ Department of Basic Medical Sciences, Purdue University, West Lafayette, IN 47907, USA.
¹⁰ School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN 47907, USA.
¹¹ Department of Biomedical Engineering, University of Cincinnati, Cincinnati, OH 45221, USA.
¹² Department of Emergency Medicine, Orlando Regional Medical Center, Orlando, FL 32806, USA.
¹³ Laboratory of Neuroimaging and Genetics, Department of Psychiatry, Massachusetts General Hospital and Harvard School of Medicine, Boston, MA 02114, USA.

PMID: 35106455
PMCID: PMC8786649
DOI: 10.1016/j.isci.2021.103483

Abstract

Research suggests contact sports affect neurological health. This study used permutation-based mediation statistics to integrate measures of metabolomics, neuroinflammatory miRNAs, and virtual reality (VR)-based motor control to investigate multi-scale relationships across a season of collegiate American football. Fourteen significant mediations (six pre-season, eight across-season) were observed where metabolites always mediated the statistical relationship between miRNAs and VR-based motor control ( $p_{S o b e l}^{p e r m}$ $\leq$ 0.05; total effect $>$ 50%), suggesting a hypothesis that metabolites sit in the statistical pathway between transcriptome and behavior. Three results further supported a model of chronic neuroinflammation, consistent with mitochondrial dysfunction: (1) Mediating metabolites were consistently medium-to-long chain fatty acids, (2) tricarboxylic acid cycle metabolites decreased across-season, and (3) accumulated head acceleration events statistically moderated pre-season metabolite levels to directionally model post-season metabolite levels. These preliminary findings implicate potential mitochondrial dysfunction and highlight probable peripheral blood biomarkers underlying repetitive head impacts in otherwise healthy collegiate football athletes.

Keywords: Computer graphics; Metabolomics; Transcriptomics; Trauma.

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Conflict of interest statement

Dr. Papa is an inventor of a US patent application filed by Uniformed Services University of the Health Sciences (USUHS) regarding the potential utilities of selected miRNAs as diagnostic biomarkers for TBI. The other authors declare they have no financial or other conflicts of interest with regard to the data and analyses presented herein. The opinions expressed herein are those of the authors and are not necessarily representative of those from their respective institutions.

Figures

**Figure 1**
Significant *Pre*-season mediation results In all analyses, miRNA was X, metabolite was M, and VR score was Y. VR terms were reported as standardized values and adjusted R² ( $R_{adj .}^{2}$ ), p-values (significance level = 0.05), and $β$ terms were reported from linear regression analyses (i.e., *without* common outlier removal that preceded the mediation analyses presented in Table 2). T_eff and $p_{S obel}^{p erm}$ were reported from each permutation-based mediation analysis. (A) There was a negative relation between miR-20a and 2-hydroxyglutarate (2-HG), a positive relation between 2-HG and VR composite score (Comp), and a negative relation between miR-20a and Comp. When 2-HG was added to the regression model, the relationship between miR-20a and Comp no longer existed (p-value > 0.05); therefore, 2-HG statistically mediated the relationship ( $p_{S obel}^{p erm}$ = 0.002, T_eff = 52%). The graph depicts the change in slope between model 1 (X → Y), which plots the slope term for the interaction between miR-20a and Comp, and model 2 (X + M → Y), which plots the slope term for the relationship between miR-20a and Comp when 2-HG was included in the regression model. (B–F) mimic what has been described in (A).

**Figure 2**
Significant across-season mediation results In all analyses, $Δ$ miRNA was X, $Δ$ metabolite was M, and $Δ$ VR score was Y. $Δ$ VR terms were reported as standardized values and adjusted R² ( $R_{adj .}^{2}$ ), p-values (significance level = 0.05), and $β$ terms were reported from linear regression analyses (i.e., *without* common outlier removal that preceded the mediation analyses presented in Table 3). T_eff and $p_{S obel}^{p erm}$ were reported from each permutation-based mediation analysis. (A) There was a negative relation between $Δ$ miR-505 and $Δ$ sebacate, a positive interaction between $Δ$ sebacate and $Δ$ Comp, and a negative relation between $Δ$ miR-505 and $Δ$ Comp. When $Δ$ sebacate was added to the regression model, the relationship between $Δ$ miR-505 and $Δ$ Comp no longer existed; therefore, sebacate statistically mediated the relationship ( $p_{S obel}^{p erm}$ = 0.008, T_eff = 50%). The graph depicts the change in slope between model 1 (X → Y), which plots the slope term for the interaction between $Δ$ miR-505 and $Δ$ Comp, and model 2 (X + M → Y), which plots the slope term for the relationship between $Δ$ miR-505 and $Δ$ Comp when $Δ$ sebacate was included in the regression model. (B–H) mimic what has been described in (A).

**Figure 3**
Summary of the observed metabolic disturbances There were significant increases in medium-chain monohydroxy and dicarboxylic fatty acids (FAs) (suberate, sebacate, UND, and 8-HOA) from *Pre* to *Post*. Increases in these FAs are associated with genetic disorders related to impaired $β$ -oxidation, which can result in an accumulation of medium-chain FAs that cannot be further oxidized into smaller, functional, metabolites, such as acetyl-CoA. Acetyl-CoA is a critical input for the TCA cycle – a major source of energy-rich molecules that are fed into further energy-producing processes (e.g., electron chain transport system). Here, TCA-related metabolites (citrate, aconitate, $α$ -KG, fumarate, and malate) all decreased, suggesting a problem with the initial step of the cycle (i.e., lack of acetyl-CoA). Additionally, there were alterations in energy-rich molecules such as adenine, adenosine, nicotinamide, and phosphate, suggesting a state of energy imbalance. Lastly, 2-HG increased. Regardless of its role as a known oncometabolite, its increase suggests a state of oxidative stress. Together, it is suggested that there are dysfunctional $β$ -oxidative mitochondrial processes in this cohort of collegiate football athletes leading to subsequent issues with energy production.

**Figure 4**
Shift in metabolism and its relationship to neuroinflammatory miRNAs and complex behavior We observed changes indicative of mitochondrial distress as evidenced from both the accumulation of medium-chain FAs and decreases in TCA-related metabolites. Mitochondrial dysfunction can lead to numerous physiological disturbances, some of which were observed in the present study: 1) oxidative stress (i.e., increased levels of 2-HG), 2) impairment in beta-oxidative processes (i.e., increased levels of medium-chain FAs), and 3) increased metabolic demands (i.e., decreased TCA and energy-related metabolites). Together, these processes may be related to the observed elevation in neuroinflammatory-related miRNA molecules (specifically miR-20a, miR-505, miR-151-5p, miR-30d, miR-92a, and miR-195). In fact, these miRNAs were significantly correlated with the metabolites shown in Figure 3. In addition, the metabolites were shown to mediate the relationship between elevated miRNA levels and VR-based motor control. This complex relationship may explain why obvious behavioral changes in subconcussed athletes are not routinely observed, but how repetitive, long-term exposure to HAEs, chronic elevation of neuroinflammatory miRNAs, and acute, but deleterious changes in energy metabolites could result in behavioral disturbances later in life.

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References

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[1] Abdul-Muneer P.M., Chandra N., Haorah J. Interactions of oxidative stress and neurovascular inflammation in the pathogenesis of traumatic brain injury. Mol. Neurobiol. 2015;51:966–979. doi: 10.1007/s12035-014-8752-3. - DOI - PMC - PubMed

[2] Abdul-Muneer P.M., Chandra N., Haorah J. Interactions of oxidative stress and neurovascular inflammation in the pathogenesis of traumatic brain injury. Mol. Neurobiol. 2015;51:966–979. doi: 10.1007/s12035-014-8752-3. - DOI - PMC - PubMed

[3] Al-Khelaifi F., Diboun I., Donati F., Botrè F., Alsayrafi M., Georgakopoulos C., Suhre K., Yousri N.A., Elrayess M.A. A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines. Sport Med. Open. 2018;4:2. doi: 10.1186/s40798-017-0114-z. - DOI - PMC - PubMed

[4] Al-Khelaifi F., Diboun I., Donati F., Botrè F., Alsayrafi M., Georgakopoulos C., Suhre K., Yousri N.A., Elrayess M.A. A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines. Sport Med. Open. 2018;4:2. doi: 10.1186/s40798-017-0114-z. - DOI - PMC - PubMed

[5] Alosco M.L., Jarnagin J., Tripodis Y., Martin B., Chaisson C., Baugh C.M., Torres A., Nowinski C.J., Cantu R.C., Stern R.A. Utility of providing a concussion definition in the assessment of concussion history in former NFL players. Brain Inj. 2017;31:1116–1123. doi: 10.1080/02699052.2017.1294709. - DOI - PMC - PubMed

[6] Alosco M.L., Jarnagin J., Tripodis Y., Martin B., Chaisson C., Baugh C.M., Torres A., Nowinski C.J., Cantu R.C., Stern R.A. Utility of providing a concussion definition in the assessment of concussion history in former NFL players. Brain Inj. 2017;31:1116–1123. doi: 10.1080/02699052.2017.1294709. - DOI - PMC - PubMed

[7] Alosco M.L., Tripodis Y., Rowland B., Chua A.S., Liao H., Martin B., Jarnagin J., Chaisson C.E., Pasternak O., Karmacharya S., et al. A magnetic resonance spectroscopy investigation in symptomatic former NFL players. Brain Imaging Behav. 2020;14:1419–1429. doi: 10.1007/s11682-019-00060-4. - DOI - PMC - PubMed

[8] Alosco M.L., Tripodis Y., Rowland B., Chua A.S., Liao H., Martin B., Jarnagin J., Chaisson C.E., Pasternak O., Karmacharya S., et al. A magnetic resonance spectroscopy investigation in symptomatic former NFL players. Brain Imaging Behav. 2020;14:1419–1429. doi: 10.1007/s11682-019-00060-4. - DOI - PMC - PubMed

[9] Alston C.L., Rocha M.C., Lax N.Z., Turnbull D.M., Taylor R.W. The genetics and pathology of mitochondrial disease. J. Pathol. 2017;241:236–250. doi: 10.1002/PATH.4809. - DOI - PMC - PubMed

[10] Alston C.L., Rocha M.C., Lax N.Z., Turnbull D.M., Taylor R.W. The genetics and pathology of mitochondrial disease. J. Pathol. 2017;241:236–250. doi: 10.1002/PATH.4809. - DOI - PMC - PubMed

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A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality

Affiliations

A preliminary model of football-related neural stress that integrates metabolomics with transcriptomics and virtual reality

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

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References

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Abstract

Conflict of interest statement

Figures

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