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Citation
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Daley M, Dekaban G, Bartha R, Brown A, Stewart TC, Doherty T, Fischer L, Holmes J, Menon RS, Rupar CA, Shoemaker JK, Fraser DD. Metabolomics 2016; 12(12): e185. |
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Abstract
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IntroductionConcussions 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.
OBJECTIVETo determine if concussions in adolescent male hockey players could be diagnosed using plasma metabolomics profiling.
METHODSPlasma 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.
RESULTSThe 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.
CONCLUSIONMetabolomics 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.
Language: en |