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High-dimensional proteomic analysis for pathophysiological classification of traumatic brain injury.
- Source :
-
Brain : a journal of neurology [Brain] 2024 Sep 26. Date of Electronic Publication: 2024 Sep 26. - Publication Year :
- 2024
- Publisher :
- Ahead of Print
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Abstract
- Pathophysiology and outcomes after Traumatic Brain Injury (TBI) are complex and heterogenous. Current classifications are uninformative about pathophysiology. Proteomic approaches with fluid-based biomarkers are ideal for exploring complex disease mechanisms, as they enable sensitive assessment of an expansive range of processes potentially relevant to TBI pathophysiology. We used novel high-dimensional, multiplex proteomic assays to assess altered plasma protein expression in acute TBI. We analysed samples from 88 participants from the BIO-AX-TBI cohort (n=38 moderate-severe TBI [Mayo Criteria], n=22 non-TBI trauma, n=28 non-injured controls) on two platforms: Alamar NULISA™ CNS Diseases and OLINK® Target 96 Inflammation. Patient participants were enrolled after hospital admission, and samples taken at a single timepoint up to 10 days post-injury. Participants also had neurofilament light, GFAP, total tau, UCH-L1 (all Simoa®) and S100B (Millipore) data. The Alamar panel assesses 120 proteins, most of which were previously unexplored in TBI, plus proteins with known TBI-specificity, such as GFAP. A subset (n=29 TBI, n=24 non-injured controls) also had subacute (10 days to 6 weeks post-injury) 3T MRI measures of lesion volume and white matter injury (fractional anisotropy). Differential Expression analysis identified 16 proteins with TBI-specific significantly different plasma expression. These were neuronal markers (calbindin2, UCH-L1, visinin-like protein1), astroglial markers (S100B, GFAP), neurodegenerative disease proteins (total tau, pTau231, PSEN1, amyloid-beta-42, 14-3-3γ), inflammatory cytokines (IL16, CCL2, ficolin2), cell signalling (SFRP1), cell metabolism (MDH1) and autophagy related (sequestome1) proteins. Acute plasma levels of UCH-L1, PSEN1, total tau and pTau231 correlated with subacute lesion volume. Sequestome1 was positively correlated, whilst CLL2 was inversely correlated, with white matter fractional anisotropy. Neuronal, astroglial, tau and neurodegenerative proteins correlated with each other, IL16, MDH1 and sequestome1. Exploratory clustering (k means) by acute protein expression identified 3 TBI subgroups that differed in injury patterns, but not age or outcome. One TBI cluster had significantly lower white matter fractional anisotropy than control-predominant clusters, but had significantly lower lesion subacute lesions volumes than another TBI cluster. Proteins that overlapped on two platforms had excellent (r>0.8) correlations between values. We identified TBI-specific changes in acute plasma levels of proteins involved in neurodegenerative disease, inflammatory and cellular processes. These changes were related to patterns of injury, thus demonstrating that processes previously only studied in animal models are also relevant in human TBI pathophysiology. Our study highlights how proteomic approaches might improve classification and understanding of TBI pathophysiology, with implications for prognostication and treatment development.<br /> (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)
Details
- Language :
- English
- ISSN :
- 1460-2156
- Database :
- MEDLINE
- Journal :
- Brain : a journal of neurology
- Publication Type :
- Academic Journal
- Accession number :
- 39323289
- Full Text :
- https://doi.org/10.1093/brain/awae305