Structural Myelin Mapping in Repetitive Head Injury
Poster No:
1739
Submission Type:
Abstract Submission
Authors:
Erica Howard1, Jessica Cloud1, Ann Lee1, Nicole Saltiel1, Scott Hayes1, Jasmeet Hayes1
Institutions:
1The Ohio State University, Columbus, OH
First Author:
Co-Author(s):
Introduction:
Head injury is a significant environmental risk factor for dementia (Baumgart, 2015), highlighting a critical need to understand the neurobiological mechanisms underlying post-injury neurodegeneration. Axonal injury, including demyelination, is classically associated with head injuries (Fehily, 2017) and may accelerate normative age-related demyelinating processes to promote disease-related neuropathology (Bartzokis, 2004; Depp, 2023). Diffusion tensor imaging (DTI) has been widely used to explore subcortical white matter changes following head injury. However, myelinated axons may also extend to the cortical mantle (Timmler, 2019), and these surface regions are not well-captured by existing DTI methodology. Additionally, the extent to which cortical myelin is impacted by differential injury mechanisms, specifically concussive traumatic brain injuries (TBI) versus repetitive sub-concussive head impacts (RHI), remains unclear. To address these gaps, the present study used a structural magnetic resonance imaging (MRI) method (T1-weighted [T1w]/T2-weighted [T2w] ratio; T1w/T2w) that, unlike DTI, can measure cortical myelin content following remote TBI or RHI history in a sample of older adults.
Methods:
We selected 73 non-demented older adults (aged ≥ 50 years; M = 64.8 years; 42% male) from the Fitness, Aging, Stress, and TBI Exposure Repository (Hayes & Hayes) at The Ohio State University based on available MRI and clinical assessment data. The Boston Assessment of TBI – Lifetime was used to assess self-reported lifetime history of head injuries, including number of TBIs and RHIs. Participants were categorized into binarized RHI (n=23) or TBI (n=31) exposed and non-exposed groups. T1w and T2w images were collected on a 3T Siemens Prisma scanner and processed to obtain participant-level T1w/T2w ratios (Figure 1), a proxy measure for surface-based myelin content, as previously outlined (Glasser, 2011; Glasser, 2013). Groupwise whole-brain T1w/T2w ratios were obtained via multiple resampling steps (Coalson, 2016) and dual-hemisphere summation of sulcal-gyral parcellation values (Destrieux, 2010). Analyses of covariance compared T1w/T2w values between groups, and partial Spearman's correlations related whole-brain T1w/T2w values to continuous numbers of RHIs and TBIs across the entire cohort. Linear regression models explored interaction effects between age and TBI or RHI exposure on whole-brain T1w/T2w values. Covariates in all analyses included sex and an imaging quality assurance metric for residual intensity bias.
Results:
When categorizing the sample based on RHI status, the RHI exposed group had significantly reduced T1w/T2w ratios (i.e. cortical myelin content) relative to the non-exposed group (F=6.45, p=.013). When categorizing the sample based on TBI status, T1w/T2w values did not significantly differ between TBI exposed and non-exposed groups. Across the entire sample, lifetime number of RHIs (ρ= -0.27, p=.001), but not TBIs (p>.05), were significantly and negatively correlated with T1w/T2w ratios. Linear models also revealed a significant interaction between RHI exposure and age (β=.03, p=.021), such that age was negatively associated with T1w/T2w ratios in non-exposed individuals (ρ= -0.38, p<.001) but not exposed individuals (p>.05). There was no such interaction effect between TBI exposure and age on T1w/T2w ratio.
Conclusions:
Results suggest that RHI, but not TBI, exposure is associated with lower myelination at the cortical surface in older adults. Cortical myelin may be more vulnerable to RHI-induced secondary injury mechanisms (e.g. inflammation, excitotoxity; Mierzwa, 2014) than TBI-induced axonal shearing. RHI may disrupt age-related demyelination patterns by reducing myelin at younger ages or disrupting normative repair processes. Assessment of cortical myelination may help inform interventions to mitigate risk of injury-related neurodegeneration.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s)
Lifespan Development:
Aging
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Cortical Cyto- and Myeloarchitecture 1
White Matter Anatomy, Fiber Pathways and Connectivity
Novel Imaging Acquisition Methods:
Anatomical MRI 2
Keywords:
Aging
Cortex
Myelin
STRUCTURAL MRI
White Matter
Other - Head Injury
1|2Indicates the priority used for review
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