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Metabolomics profiling of concussion in adolescent male hockey players: a novel diagnostic method

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Abstract

Introduction

Concussions are a major health concern as they cause significant acute symptoms and in some athletes, long-term neurologic dysfunction. Diagnosis of concussion can be difficult, as are the decisions to stop play.

Objective

To determine if concussions in adolescent male hockey players could be diagnosed using plasma metabolomics profiling.

Methods

Plasma was obtained from 12 concussed and 17 non-concussed athletes, and assayed for 174 metabolites with proton nuclear magnetic resonance and direct injection liquid chromatography tandem mass spectrometry. Data were analysed with multivariate statistical analysis and machine learning.

Results

The estimated time from concussion occurrence to blood draw at the first clinic visit was 2.3 ± 0.7 days. Using principal component analysis, the leading 10 components, each containing 9 metabolites, were shown to account for 82 % of the variance between cohorts, and relied heavily on changes in glycerophospholipids. Cross-validation of the classifier using a leave-one out approach demonstrated a 92 % accuracy rate in diagnosing a concussion (P < 0.0001). The number of metabolites required to achieve the 92 % diagnostic accuracy was minimized from 174 to as few as 17 metabolites. Receiver operating characteristic analyses generated an area under the curve of 0.91, indicating excellent concussion diagnostic potential.

Conclusion

Metabolomics profiling, together with multivariate statistical analysis and machine learning, identified concussed athletes with >90 % certainty. Metabolomics profiling represents a novel diagnostic method for concussion, and may be amenable to point-of-care testing.

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References

  • Braverman, N. E., & Moser, A. B. (2012). Functions of plasmalogen lipids in health and disease. Biochimica et Biophysica Acta, 1822(9), 1442–1452. doi:10.1016/j.bbadis.2012.05.008.

    Article  CAS  PubMed  Google Scholar 

  • Brisson, A. R., Matsui, D., Rieder, M. J., & Fraser, D. D. (2012). Translational research in pediatrics: Tissue sampling and biobanking. Pediatrics, 129(1), 153–162. doi:10.1542/peds.2011-0134.

    Article  PubMed  Google Scholar 

  • Bujak, R., Struck-Lewicka, W., Markuszewski, M. J., & Kaliszan, R. (2014). Metabolomics for laboratory diagnostics. Journal of Pharmaceutical and Biomedical Analysis. doi:10.1016/j.jpba.2014.12.017.

    Google Scholar 

  • Di Battista, A. P., Rhind, S. G., & Baker, A. J. (2013). Application of blood-based biomarkers in human mild traumatic brain injury. Frontiers in Neurology, 4, 44. doi:10.3389/fneur.2013.00044.

    Article  PubMed  PubMed Central  Google Scholar 

  • Farooqui, A. A., Horrocks, L. A., & Farooqui, T. (2000). Glycerophospholipids in brain: their metabolism, incorporation into membranes, functions, and involvement in neurological disorders. Chemistry and Physics of Lipids, 106(1), 1–29.

    Article  CAS  PubMed  Google Scholar 

  • Gillio-Meina, C., Cepinskas, G., Cecchini, E. L., & Fraser, D. D. (2013). Translational research in pediatrics II: blood collection, processing, shipping, and storage. Pediatrics, 131(4), 754–766. doi:10.1542/peds.2012-1181.

    Article  PubMed  Google Scholar 

  • Glaviano, N. R., Benson, S., Goodkin, H. P., Broshek, D. K., & Saliba, S. (2015). Baseline SCAT2 assessment of healthy youth student-athletes: Preliminary evidence for the use of the child-SCAT3 in children younger than 13 years. Clinical Journal of Sport Medicine, 25(4), 373–379. doi:10.1097/JSM.0000000000000154.

    Article  PubMed  Google Scholar 

  • Guskiewicz, K. M., Register-Mihalik, J., McCrory, P., McCrea, M., Johnston, K., Makdissi, M., et al. (2013). Evidence-based approach to revising the SCAT2: Introducing the SCAT3. British Journal of Sports Medicine, 47(5), 289–293. doi:10.1136/bjsports-2013-092225.

    Article  PubMed  Google Scholar 

  • Hajian-Tilaki, K. (2013). Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian Journal of Internal Medicine, 4(2), 627–635.

    PubMed  PubMed Central  Google Scholar 

  • Halstead, M. E., & Walter, K. D. (2010). Sport-related concussion in children and adolescents. Pediatrics, 126(3), 597–615. doi:10.1542/peds.2010-2005.

    Article  PubMed  Google Scholar 

  • Harmon, K. G., Drezner, J. A., Gammons, M., Guskiewicz, K. M., Halstead, M., Herring, S. A., et al. (2013). American Medical Society for sports medicine position statement: Concussion in sport. British Journal of Sports Medicine, 47(1), 15–26. doi:10.1136/bjsports-2012-091941.

    Article  PubMed  Google Scholar 

  • Jeter, C. B., Hergenroeder, G. W., Hylin, M. J., Redell, J. B., Moore, A. N., & Dash, P. K. (2013). Biomarkers for the diagnosis and prognosis of mild traumatic brain injury/concussion. Journal of Neurotrauma, 30(8), 657–670. doi:10.1089/neu.2012.2439.

    Article  PubMed  Google Scholar 

  • Karlin, A. M. (2011). Concussion in the pediatric and adolescent population: “Different population, different concerns”. PM&R, 3(10 Suppl 2), S369–S379. doi:10.1016/j.pmrj.2011.07.015.

    Article  Google Scholar 

  • Lehmann, R., Zhao, X., Weigert, C., Simon, P., Fehrenbach, E., Fritsche, J., et al. (2010). Medium chain acylcarnitines dominate the metabolite pattern in humans under moderate intensity exercise and support lipid oxidation. PLoS One, 5(7), e11519. doi:10.1371/journal.pone.0011519.

    Article  PubMed  PubMed Central  Google Scholar 

  • Lovell, M. R., Collins, M. W., Iverson, G. L., Johnston, K. M., & Bradley, J. P. (2004). Grade 1 or “ding” concussions in high school athletes. American Journal of Sports Medicine, 32(1), 47–54.

    Article  PubMed  Google Scholar 

  • Lovell, M. R., & Solomon, G. S. (2013). Neurocognitive test performance and symptom reporting in cheerleaders with concussions. Journal of Pediatrics, 163(4), 1192–1195. doi:10.1016/j.jpeds.2013.05.061.

    Article  PubMed  Google Scholar 

  • Lutjohann, D., Breuer, O., Ahlborg, G., Nennesmo, I., Siden, A., Diczfalusy, U., et al. (1996). Cholesterol homeostasis in human brain: Evidence for an age-dependent flux of 24S-hydroxycholesterol from the brain into the circulation. Proceedings of the National Academy of Sciences, 93(18), 9799–9804.

    Article  CAS  Google Scholar 

  • McCrory, P., Meeuwisse, W., Aubry, M., Cantu, B., Dvorak, J., Echemendia, R. J., et al. (2013). Consensus statement on concussion in sport—the 4th International conference on concussion in sport held in Zurich, November 2012. Clinical Journal of Sport Medicine, 23(2), 89–117. doi:10.1097/JSM.0b013e31828b67cf.

    Article  PubMed  Google Scholar 

  • Meier, T. B., Brummel, B. J., Singh, R., Nerio, C. J., Polanski, D. W., & Bellgowan, P. S. (2015). The underreporting of self-reported symptoms following sports-related concussion. Journal of Science and Medicine in Sport, 18(5), 507–511. doi:10.1016/j.jsams.2014.07.008.

    Article  PubMed  Google Scholar 

  • Morrison, G., Fraser, D. D., & Cepinskas, G. (2013). Mechanisms and consequences of acquired brain injury during development. Pathophysiology, 20(1), 49–57. doi:10.1016/j.pathophys.2012.02.006.

    Article  CAS  PubMed  Google Scholar 

  • O’Brien, J. S., & Sampson, E. L. (1965). Lipid composition of the normal human brain: Gray matter, white matter, and myelin. Journal of Lipid Research, 6(4), 537–544.

    PubMed  Google Scholar 

  • Papa, L., Ramia, M. M., Edwards, D., Johnson, B. D., & Slobounov, S. M. (2015). Systematic review of clinical studies examining biomarkers of brain injury in athletes after sports-related concussion. Journal of Neurotrauma, 32(10), 661–673. doi:10.1089/neu.2014.3655.

    Article  PubMed  PubMed Central  Google Scholar 

  • Pellman, E. J., Lovell, M. R., Viano, D. C., & Casson, I. R. (2006). Concussion in professional football: Recovery of NFL and high school athletes assessed by computerized neuropsychological testing–Part 12. Neurosurgery, 58(2), 263–274. doi:10.1227/01.NEU.0000200272.56192.62.

    Article  PubMed  Google Scholar 

  • Psychogios, N., Hau, D. D., Peng, J., Guo, A. C., Mandal, R., Bouatra, S., et al. (2011). The human serum metabolome. PLoS One, 6(2), e16957. doi:10.1371/journal.pone.0016957.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  • Saude, E. J., Slupksy, C. M., & Sykes, B. D. (2006). Optimization of NMR analysis of biological fluids for quantitative accuracy. Metabolomics, 2(3), 113–123.

    Article  CAS  Google Scholar 

  • Shouval, R., Bondi, O., Mishan, H., Shimoni, A., Unger, R., & Nagler, A. (2014). Application of machine learning algorithms for clinical predictive modeling: A data-mining approach in SCT. Bone Marrow Transplantation, 49(3), 332–337. doi:10.1038/bmt.2013.146.

    Article  CAS  PubMed  Google Scholar 

  • Stewart, T. C., Gilliland, J., & Fraser, D. D. (2014). An epidemiologic profile of pediatric concussions: Identifying urban and rural differences. Journal of Trauma and Acute Care Surgery, 76(3), 736–742. doi:10.1097/TA.0b013e3182aafdf5.

    Article  PubMed  Google Scholar 

  • Toledo, E., Lebel, A., Becerra, L., Minster, A., Linnman, C., Maleki, N., et al. (2012). The young brain and concussion: Imaging as a biomarker for diagnosis and prognosis. Neuroscience and Biobehavioral Reviews, 36(6), 1510–1531. doi:10.1016/j.neubiorev.2012.03.007.

    Article  PubMed  PubMed Central  Google Scholar 

  • van der Maaten, L., & Hinton, G. (2008). Visualizing data using t-SNE. Journal of Machine Learning Research, 9(11), 2579–2605.

    Google Scholar 

  • Vitali, C., Wellington, C. L., & Calabresi, L. (2014). HDL and cholesterol handling in the brain. Cardiovascular Research, 103(3), 405–413. doi:10.1093/cvr/cvu148.

    Article  CAS  PubMed  Google Scholar 

  • Yudkoff, M. (1997). Brain metabolism of branched-chain amino acids. Glia, 21(1), 92–98.

    Article  CAS  PubMed  Google Scholar 

  • Zhu, W., Zeng, N., Wang, N. (2010). Sensitivity, specificity, accuracy, associated confidence interval and ROC analysis with practical SAS® implementations. In Northeast SAS Users Group Proceedings. Retrived from http://www.lexjansen.com/nesug/nesug10/hl/hl07.pdf

Download references

Acknowledgments

We thank Ms. Christy Barreira and Ms. Sandra Shaw for excellent technical support, and Ms. Kathryn Manning and Mr. Kevin Blackney for assistance with data. We graciously acknowledge analytic support from The Metabolomics Innovation Centre at the University of Alberta, Edmonton, AB (Ms. Rupasri Mandal, Ms. Jennifer D. Reid and Dr. David Wishart). This study was supported by the Children’s Health Foundation (http://childhealth.ca/) grant to DDF.

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Correspondence to Douglas D. Fraser.

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Conflict of interest

The authors have filed a patent application for metabolomics profiling of central nervous system injury (US Trade and Patent Office No. 62/135886).

Ethical approval

This study was approved by the Human Research Ethics Board at Western University (#103365).

Informed consent

Written informed consent was obtained from the legal guardians and assent was obtained from adolescent subjects.

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Daley, M., Dekaban, G., Bartha, R. et al. Metabolomics profiling of concussion in adolescent male hockey players: a novel diagnostic method. Metabolomics 12, 185 (2016). https://doi.org/10.1007/s11306-016-1131-5

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