Multi-tract multi-symptom relationships in pediatric concussion

  1. Guido I Guberman  Is a corresponding author
  2. Sonja Stojanovski
  3. Eman Nishat
  4. Alain Ptito
  5. Danilo Bzdok
  6. Anne L Wheeler
  7. Maxime Descoteaux
  1. McGill University, Canada
  2. University of Toronto, Canada
  3. Université de Sherbrooke, Canada

Abstract

Background: The heterogeneity of white matter damage and symptoms in concussion has been identified as a major obstacle to therapeutic innovation. In contrast, most diffusion MRI (dMRI) studies on concussion have traditionally relied on group-comparison approaches that average out heterogeneity. To leverage, rather than average out, concussion heterogeneity, we combined dMRI and multivariate statistics to characterize multi-tract multi-symptom relationships.

Methods: Using cross-sectional data from 306 previously-concussed children aged 9-10 from the Adolescent Brain Cognitive Development Study, we built connectomes weighted by classical and emerging diffusion measures. These measures were combined into two informative indices, the first representing microstructural complexity, the second representing axonal density. We deployed pattern-learning algorithms to jointly decompose these connectivity features and 19 symptom measures.

Results: Early multi-tract multi-symptom pairs explained the most covariance and represented broad symptom categories, such as a general problems pair, or a pair representing all cognitive symptoms, and implicated more distributed networks of white matter tracts. Further pairs represented more specific symptom combinations, such as a pair representing attention problems exclusively, and were associated with more localized white matter abnormalities. Symptom representation was not systematically related to tract representation across pairs. Sleep problems were implicated across most pairs, but were related to different connections across these pairs. Expression of multi-tract features was not driven by sociodemographic and injury-related variables, as well as by clinical subgroups defined by the presence of ADHD. Analyses performed on a replication dataset showed consistent results.

Conclusions: Using a double-multivariate approach, we identified clinically-informative, cross-demographic multi-tract multi-symptom relationships. These results suggest that rather than clear one-to-one symptom-connectivity disturbances, concussions may be characterized by subtypes of symptom/connectivity relationships. The symptom/connectivity relationships identified in multi-tract multi-symptom pairs were not apparent in single-tract/single-symptom analyses. Future studies aiming to better understand connectivity/symptom relationships should take into account multi-tract multi-symptom heterogeneity.

Funding: financial support for this work from a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (GIG), an Ontario Graduate Scholarship (SS), a Restracomp Research Fellowship provided by the Hospital for Sick Children (SS), an Institutional Research Chair in Neuroinformatics (MD), as well as a Natural Sciences and Engineering Research Council CREATE grant (MD).

Data availability

All data used in this project were obtained from the Adolescent Brain Cognitive Development Study. This dataset is administered by the National Institutes of Mental Health Data Archive and is freely available to all qualified researchers upon submission of an access request. All relevant instructions to obtain the data can be found in https://nda.nih.gov/abcd/request-access. The Institutional Review Board of the McGill University Faculty of Medicine and Health Sciences reviewed the application and confirmed that no further ethics approvals were required.

The following previously published data sets were used

Article and author information

Author details

  1. Guido I Guberman

    Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
    For correspondence
    guido.guberman@mail.mcgill.ca
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4422-2225
  2. Sonja Stojanovski

    Department of Physiology, University of Toronto, Toronto, Canada
    Competing interests
    No competing interests declared.
  3. Eman Nishat

    Department of Physiology, University of Toronto, Toronto, Canada
    Competing interests
    No competing interests declared.
  4. Alain Ptito

    Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
  5. Danilo Bzdok

    Montreal Neurological Institute (MNI), McGill University, Montreal, Canada
    Competing interests
    No competing interests declared.
  6. Anne L Wheeler

    Department of Physiology, University of Toronto, Toronto, Canada
    Competing interests
    No competing interests declared.
  7. Maxime Descoteaux

    Department of Computer Science, Université de Sherbrooke, Sherbrooke, Canada
    Competing interests
    Maxime Descoteaux, works as Chief Scientific Officer for IMEKA. He holds the following patents: DETERMINATION OF WHITE-MATTER NEURODEGENERATIVE DISEASE BIOMARKERS (Patent Application No.: 63/222,914), PROCESSING OF TRACTOGRAPHY RESULTS USING AN AUTOENCODER (Patent Application No.: 17/337,413). No other authors have any financial or other conflicts of interest..

Funding

Canadian Institutes of Health Research (Vanier Canada Graduate Scholarship)

  • Guido I Guberman

Government of Ontario (Ontario Graduate Scholarship)

  • Sonja Stojanovski

Hospital for Sick Children (Restracomp Research Fellowship)

  • Sonja Stojanovski

Université de Sherbrooke (Institutional Research Chair)

  • Maxime Descoteaux

Natural Sciences and Engineering Research Council of Canada (CREATE Grant)

  • Maxime Descoteaux

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The data used in this study were obtained from the Adolescent Brain Cognitive Development Study. All aspects related to ethical standards were managed by the ABCD Study team. The Institutional Review Board of the McGill University Faculty of Medicine and Health Sciences reviewed the application and confirmed that no further ethics approvals were required.

Reviewing Editor

  1. Alexander Shackman, University of Maryland, United States

Publication history

  1. Preprint posted: April 7, 2021 (view preprint)
  2. Received: May 17, 2021
  3. Accepted: April 26, 2022
  4. Accepted Manuscript published: May 17, 2022 (version 1)
  5. Version of Record published: May 25, 2022 (version 2)

Copyright

© 2022, Guberman et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Guido I Guberman
  2. Sonja Stojanovski
  3. Eman Nishat
  4. Alain Ptito
  5. Danilo Bzdok
  6. Anne L Wheeler
  7. Maxime Descoteaux
(2022)
Multi-tract multi-symptom relationships in pediatric concussion
eLife 11:e70450.
https://doi.org/10.7554/eLife.70450

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