Diagnosis of Sport-related Concussion Using Urine Metabolites

September 28, 2021 updated by: University of Calgary

Diagnosing Sport-related Concussion Using Urine Metabolomics: A 1H NMR-Based Analysis

Millions of sport related concussions (SRC) occur yearly in the United States, and current diagnosis of concussion is based upon largely subjective clinical evaluations. The objective of this study is to determine whether urinary metabolites are significantly altered post SRC. Urine of 26 athletes will be analyzed pre-injury and after SRC by 1H NMR spectroscopy. Data will be analyzed using multivariate statistics, pairwise t-test, and metabolic pathway analysis. Variable Importance Analysis based on random Variable Combination (VIAVC) was used to select what features are present out of 224 features. Partial least squares discriminant analysis was performed leading to separation between pre-season and post-SRC groups. A Receiver Operator Curve (ROC) curve will be constructed to classify the features. Pathway topology analysis will also be completed to determine biological pathways are potentially affected following SRC.

Study Overview



Intervention / Treatment

Detailed Description


Sport concussion or sport-related mild traumatic brain injury (mTBI) affects patients across the spectrum of age, race and gender. It is a medical problem that if not treated appropriately can have devastating outcomes to patients and families. MTBI or concussion (terminology used interchangeably in this proposal) more recently has been a hot topic in the media with high profile politicians and athletes having career altering outcomes following a concussion. According to the Canadian Institute for Health Information, sports and recreational activities were the third leading cause of TBI admissions in Canadian hospitals in 2003-2004. In the United States, the Center for Disease Control and Prevention estimates that 1.6 to 3.8 million concussions occur in sports and recreational activities annually. In Calgary, approximately 10,000 patients were seen in the emergency departments with a head injury in 2013, 80% of which were diagnosed as mTBI and a vast majority of these were sport related (unpublished data).

Currently, there is no single "gold standard" assessment or diagnostic marker to objectively determine if a patient has suffered a sport concussion and if so, how long it will take to recover. As such, concussion remains a clinical diagnosis based on post-traumatic symptoms, physical signs, and impairment in cognitive function, which at best is done by a trained and experienced medical professional. But, this is primarily a qualitative, individualized approach to diagnosing and is typically clouded by a lack of objective clinical findings. Other assessment tools can aid a clinician in diagnosing a concussion such as the Sport Concussion Assessment Tool 3 (SCAT3) (Appendix 1), but unfortunately this has not been validated and was developed based on expert consensus. As well, computerized neuropsychological testing may help with the assessment of concussion recovery; however it is expensive, time consuming and has recently been criticized as lacking specificity and sensitivity for head injury.

Over the past 20 years researchers have studied biomarkers such as S100B and neuron-specific enolase in hopes of finding a quantitative approach to diagnosing and prognosticating concussion. This unfortunately, has met with much disappointment as none of these markers, in and of themselves, has adequate specificity or sensitivity to be used as a single biomarker in clinical practice.

Metabolomics is defined as "the quantitative measurement of the metabolic response of living systems to pathophysiological stimuli or genetic modification" and is based on analytical platforms such as proton nuclear magnetic resonance spectroscopy (1H NMR) and/or mass spectrometry. Metabolomic studies of clinically accessible bio-fluids, such as blood and urine, provides an intricate and relatively non-invasive snapshot into this response. To date, metabolomics has been shown to be a useful biomarker tool in amyotrophic lateral sclerosis, Alzheimer's disease, Parkinson's disease, neonatal hypoxic ischemic encephalopathy, brain cancer, multiple sclerosis, aging and neurodegenerative disease, epilepsy, stroke, severe traumatic brain injury and pediatric septic shock. To the best of our knowledge, no study has assessed quantitative metabolomic profiling as a diagnostic and prognosticating tool in sport concussion.

This pilot study would aid in the following:

  1. To determine the feasibility of testing metabolomics in the sport concussion population.
  2. The first study of its kind to use quantitative metabolic profiling to assist with the diagnosis of acute sport concussion.
  3. The first study of its kind to develop a metabolic "fingerprint" that may help prognosticate recovery in acute sport concussion.

Subjects will be asked to provide an mid-stream urine sample between 7-9 am at pre-injury and post-concussion. Urine aliquots will be obtained immediately by centrifuge and then stored at -80C until required for analysis. Once all samples are collected they will be batched and transported to the University of Lethbridge for analysis.

No samples for metabolomic analysis will undergo a previous freeze/thaw cycle. An aliquot of 450 μl will be removed from each of the urine samples and added to 250 μl of buffer solution. The buffer solution will be prepared using a potassium phosphate solution at 0.5M and pH 7.4 ± 0.04. This buffer solution also contains 10 mL of sodium azide which acts as an antimicrobial agent. The solvent for the buffer will 1 part D2O to 4 parts normal water and the D2O contains 0.05 weight percent of 3-(trimethylsilyl)propionic-2,2,3,3-d4 acid (TSP). The final concentration of TSP will be used as an internal chemical shift and quantification standard. The buffer/urine solution is then centrifuged at 10 000 rpm for five minutes to remove any particulate matter, large fats, or large proteins and 500 μl is pipetted into 5mm NMR tubes.

All NMR spectra will be obtained on a Bruker AVANCE III HD 700 MHz spectrometer (Bruker BioSpin Ltd., Milton, ON, Canada) equipped with a high-throughput sample changer platform, a triple resonance (TBO) 5mm probe and TopSpin 3.2 software. Each sample will be acquired using the standard Bruker 1D pre-saturation pulse sequence (noesygppr1d) with a mixing time of 10 ms, an acquisition time of 5 seconds, a recycle delay of 4 seconds and a total of 512 scans. Each sample will then be processed with a line broadening of 0.3 Hz.

After initial processing in TopSpin 3.2, all spectra will be loaded into matNMR (24), correctly referenced by setting the TSP shift to 0 ppm, and exported into the Matlab ® workspace for further processing. The spectra will then be binned using a dynamic adaptive binning (DAB) method that has been coded for the Matlab environment. This DAB method deals with any movement in spectral lines from spectra to spectra, which can be caused by slight variation in pH from sample to sample (pH = 7.4 ± 0.04), and ensures that peaks from the same metabolite are not broken apart into different bins. After spectral binning, the spectra will be normalized, with water and urea excluded from the normalization, and Pareto scaled (26). The normalized and scaled spectra will then be analyzed using principal component analysis (PCA) and Partial Least Squared Discriminant Analysis (PLS-DA). The loadings plot of these two methods will be used for identifying the outlying bins. The chemical shift range associated with these outlying bins will then be compared to an established metabolite library in order to determine which metabolites have variation across comparison groups (concussion and pre-injury). Eretic tool in the TopSpin 3.2 software will be used to determine the quantitative changes in the concentration of these metabolites. This quantification of the concentration is based on the known internal concentration of TSP in our NMR samples. A Mann Whitney U test for metabolic analysis and a Fisher exact test for the categorical data will be performed.

Study Type


Enrollment (Actual)



  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Canada
    • Alberta
      • Calgary, Alberta, Canada, T2N2T9
        • Chantel T Debert

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

14 years and older (Child, Adult, Older Adult)

Accepts Healthy Volunteers


Genders Eligible for Study



Inclusion Criteria:

  • age greater than 18 years
  • diagnosis of concussion determined by the specialists (sports medicine physician or physiatrist)
  • concussion sustained within 72 hours of being seen.

Exclusion Criteria:

  • multiple injuries sustained coinciding with the concussive head injury
  • past medical history of neurological pathology such as seizures, CNS tumors or neurodegenerative disorders.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Other: Pre-injury
Each participant will act as their own control. Pre-injury samples were collected.
We aim to determine of a specific urine metabolomic biomarkers can diagnose concussion.
Active Comparator: Post-injury
Post-injury samples were collected at the same time and within 72 hours of injury.
We aim to determine of a specific urine metabolomic biomarkers can diagnose concussion.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Urine metabolite profile
Time Frame: Samples were taken within 72 hours of injury
224 urine metabolites were analyzed pre- and post sport related concussion to determine which metabolites were altered post injury.
Samples were taken within 72 hours of injury

Collaborators and Investigators

This is where you will find people and organizations involved with this study.



  • Principal Investigator: Chantel T Debert, MD MSc, University of Calgary

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

August 1, 2010

Primary Completion (Actual)

November 1, 2019

Study Completion (Actual)

November 1, 2019

Study Registration Dates

First Submitted

August 28, 2018

First Submitted That Met QC Criteria

August 29, 2018

First Posted (Actual)

August 31, 2018

Study Record Updates

Last Update Posted (Actual)

September 30, 2021

Last Update Submitted That Met QC Criteria

September 28, 2021

Last Verified

May 1, 2020

More Information

Terms related to this study

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?


IPD Plan Description

If other researchers request the data we will share.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product


Studies a U.S. FDA-regulated device product


This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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