Assessing biomarkers for predicting Alzheimer's disease in TBI patients: A subanalysis of the double‐blinded, phase III randomized clinical trial with biperiden
Bibliographic record
Abstract
BACKGROUND: Traumatic Brain Injury (TBI) is a significant risk factor for Alzheimer's Disease (AD). However, the mechanisms connecting TBI to AD pathology remain unclear. Identifying blood-based biomarkers of neuronal and astrocytic injury is crucial for advancing precision diagnostics and intervention by predicting neurodegeneration. This study evaluates serum biomarkers using the ultra-sensitive Single Molecule Array (SIMOA) platform to explore their association with TBI severity, sex-specific responses and potential relevance to AD. METHODS: We conducted a subanalysis of 123 patients enrolled in the phase III NCT01048138 clinical trial at HCFMUSP. Participants with acute TBI were randomized to receive either biperiden or placebo. Serum samples were collected and analyzed at multiple time points for biomarkers including Tau, NfL, GFAP, and UCHL1 using SIMOA. Biomarker profiles were compared across treatment groups, TBI severity, sex, age and time post-injury. Additional analyses explored their relevance to AD-related neurodegenerative process. RESULTS: GFAP and NfL emerged as the most reliable biomarkers, strongly correlating with age, sex, TBI severity and temporal progression post-injury. Intriguingly, elevated levels of these biomarkers in the acute phase post-TBI were associated with astrocytic and axonal injury, which are critical in AD pathology. UCHL1 levels are also associated with trauma severity, sex, and time post-injury, but less significantly than NfL and GFAP. Women exhibited higher levels of levels Tau, GFAP and UCHL1 but lower NfL levels compared to men, suggesting a potential sex-specific response. Age-stratified analyses revealed increased NfL and GFAP levels in older patients, emphasizing the impact of age on astrocytic activation. While biperiden treatment did not significantly alter biomarker levels across the overall cohort, exploratory analyses also revealed possible sex-specific trends in treatment response. CONCLUSIONS: Our findings underscore the feasibility of serum biomarkers such as GFAP and NfL to bridge the understanding of the molecular link between TBI and AD. The SIMOA technology enables precise quantification of biomarkers, providing valuable knowledge into the time window from the moment of TBI to the development of AD, allowing for the analysis of long-term neurodegeneration. These results reinforces the importance of personalized approaches to diagnosis and therapeutic monitoring.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".