Aim: There is a critical need to validate biofluid-based biomarkers as diagnostic and drug development tools for traumatic brain injury (TBI). As part of the TBI Endpoints Development Initiative, we identified four potentially predictive and pharmacodynamic biomarkers for TBI: astroglial markers GFAP and S100B and the neuronal markers UCH-L1 and Tau. Materials & methods: Several commonly used platforms for these four biomarkers were identified and compared on analytic performance and ability to detect gold standard recombinant protein antigens and to pool control versus TBI cerebrospinal fluid (CSF). Results: For each marker, only some assay formats could differentiate TBI CSF from the control CSF. Also, different assays for the same biomarker reported divergent biomarker values for the same biosamples. Conclusion: Due to the variability of TBI marker assay in performance and reported values, standardization strategies are recommended when comparing reported biomarker levels across assay platforms.
Keywords: GFAP; S100B; Tau; UCH-L1; biomarker qualification; neurodegeneration; protein biomarkers; traumatic brain injury.
Lay abstract Traumatic brain injury (TBI) is a leading cause of mortality and morbidity around the world. There is a critical need to validate biofluid-based biomarker tests as diagnostic and drug development tools. For this study, we focused on four brain-derived proteins called GFAP, S100B, UCH-L1 and Tau. To measure these biomarker proteins in human biofluid, one relies on either commercial or home-brew assays. Here, we attempted to compare the performance of 2–4 assay formats for each biomarker. We compared their assay sensitivity, ability to detect ‘gold standard’ protein analyte we procured, as well as the ability to differentiated pooled TBI cerebrospinal fluid from healthy control cerebrospinal fluid. We found that there are high variabilities among TBI marker assays in assay performance, reported biomarker values and ability to differentiate TBI versus control biofluid. Thus, a standardization strategy is needed when comparing reported biomarker levels across assay platforms.