Summary: Researchers report different types of brain injuries caused by concussions in children may lead to similar symptoms.
Source: McGill University
Different types of brain damage caused by a concussion may lead to similar symptoms in children, according to research led by McGill University. A new way of studying concussions could help develop future treatments.
While most children fully recover after a concussion, some will have lasting symptoms.
The findings published in eLife help explain the complex relationships that exist between symptoms and the damage caused by the injury.
The researchers found that certain combinations of brain damage were associated with specific symptoms such as attention difficulties. Other symptoms, such as sleep problems, occurred in children with multiple types of injuries. For example, damage to areas of the brain that are essential for controlling sleep and wakefulness could cause challenges with sleeping, as could damage to brain regions that control mood.
The brain’s white matter holds clues
To do this, they examined how damage to the brain resulting from concussion affected its structural connection network, known as white matter. They then used statistical modeling techniques to see how these changes related to 19 different symptoms reported by the children or their caregivers.
Analyzing symptoms may advance treatment
“Despite decades of research, no new treatment targets and therapies for concussions have been identified in recent years,” says lead author Guido Guberman, a Vanier Scholar and MDCM Candidate at McGill University.
“This is likely because damage to the brain caused by concussions, and the symptoms that result from it, can vary widely across individuals. In our study, we wanted to explore the relationships that exist between the symptoms of concussion and the nature of the injury in more detail.”
Guberman and his colleagues analyzed data collected from 306 children, aged 9 to 10 years old, who had previously had a concussion. The children were all participants in the Adolescent Brain Cognitive Development (ABCD) Study.
“The methods used in our study provide a novel way of conceptualizing and studying concussions,” says senior author Maxime Descoteaux, a Professor of Computer Science at Université de Sherbrooke.
“Once our results are validated and better understood, they could be used to explore potential new treatment targets for individual patients. More broadly, it would be interesting to see if our methods could also be used to gather new insights on neurological diseases that likewise cause varied symptoms among patients.”
Multi-tract multi-symptom relationships in pediatric concussion
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).