Plasma biomarkers in chronic single moderate–severe traumatic brain injury
Bibliographic record
Abstract
Blood biomarkers are an emerging diagnostic and prognostic tool that reflect a range of neuropathological processes following traumatic brain injury (TBI). Their effectiveness in identifying long-term neuropathological processes after TBI is unclear. Studying biomarkers in the chronic phase is vital because elevated levels in TBI might result from distinct neuropathological mechanisms during acute and chronic phases. Here, we examine plasma biomarkers in the chronic period following TBI and their association with amyloid and tau PET, white matter microarchitecture, brain age and cognition. We recruited participants ≥40 years of age who had suffered a single moderate-severe TBI ≥10 years previously between January 2018 and March 2021. We measured plasma biomarkers using single molecule array technology [ubiquitin C-terminal hydrolase L1 (UCH-L1), neurofilament light (NfL), tau, glial fibrillary acidic protein (GFAP) and phosphorylated tau (P-tau181)]; PET tracers to measure amyloid-β (18F-NAV4694) and tau neurofibrillary tangles (18F-MK6240); MRI to assess white matter microstructure and brain age; and the Rey Auditory Verbal Learning Test to measure verbal-episodic memory. A total of 90 post-TBI participants (73% male; mean = 58.2 years) were recruited on average 22 years (range = 10-33 years) post-injury, and 32 non-TBI control participants (66% male; mean = 57.9 years) were recruited. Plasma UCH-L1 levels were 67% higher {exp(b) = 1.67, P = 0.018, adjusted P = 0.044, 95% confidence interval (CI) [10% to 155%], area under the curve = 0.616} and P-tau181 were 27% higher {exp(b) = 1.24, P = 0.011, adjusted P = 0.044, 95% CI [5% to 46%], area under the curve = 0.632} in TBI participants compared with controls. Amyloid and tau PET were not elevated in TBI participants. Higher concentrations of plasma P-tau181, UCH-L1, GFAP and NfL were significantly associated with worse white matter microstructure but not brain age in TBI participants. For TBI participants, poorer verbal-episodic memory was associated with higher concentration of P-tau181 {short delay: b = -2.17, SE = 1.06, P = 0.043, 95% CI [-4.28, -0.07]; long delay: bP-tau = -2.56, SE = 1.08, P = 0.020, 95% CI [-4.71, -0.41]}, tau {immediate memory: bTau = -6.22, SE = 2.47, P = 0.014, 95% CI [-11.14, -1.30]} and UCH-L1 {immediate memory: bUCH-L1 = -2.14, SE = 1.07, P = 0.048, 95% CI [-4.26, -0.01]}, but was not associated with functional outcome. Elevated plasma markers related to neuronal damage and accumulation of phosphorylated tau suggest the presence of ongoing neuropathology in the chronic phase following a single moderate-severe TBI. Plasma biomarkers were associated with measures of microstructural brain disruption on MRI and disordered cognition, further highlighting their utility as potential objective tools to monitor evolving neuropathology post-TBI.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".