Performance of GFAP and UCH-L1 compared to S100B in detecting intracranial injury: influence of age, hemolysis, neurodegenerative diseases, and extracranial fractures in a prospective cohort of over 1,000 patients
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Antoine Puravet
, Jean-Baptiste Bouillon-Minois
Abstract
Objectives
To compare the diagnostic performances of GFAP and UCH-L1 with S100B in detecting intracranial injury, while investigating the impact of confounding factors.
Methods
In a large prospective cohort of 1,010 patients with mild traumatic brain injury, we first evaluated the clinical performances of S100B and the GFAP/UCH-L1 combination. To explore the impact of pre-analytical interferences on GFAP and UCH-L1 levels, HIL indices (hemolysis, icterus, lipemia) were measured using the Atellica® analyzer, and spiking experiments were performed with increasing concentrations of hemolysate, bilirubin, and Intralipid®. We then assessed the influence of four confounders on biomarker specificity: age over 80 years, hemolysis, neurodegenerative diseases, and extracranial fractures. Finally, we evaluated the ability of the biomarkers to predict clinical outcomes at one month.
Results
S100B and the GFAP/UCH-L1 combination showed sensitivities of 96 and 100 %, and specificities of 25 and 27 %, respectively. False positives were significantly associated with age >80 and extracranial fractures for S100B; with age >80 and neurodegenerative diseases for GFAP; and with age >80, hemolysis, and extracranial fractures for UCH-L1. UCH-L1 levels were markedly increased by hemolysis, starting at 400 mg/L of hemoglobin. Age was the only confounding factor to significantly affect specificity. Using age-adjusted thresholds in patients over 80 increased specificity to 30 % for S100B and 33 % for GFAP/UCH-L1. Overall, the biomarkers exhibited limited predictive value and performed poorly for one-month clinical outcomes.
Conclusions
S100B and the GFAP/UCH-L1 combination demonstrated very high sensitivities, close to 100 %, with specificities of approximately 30 % for the diagnosis of intracranial lesions. Age-adjusted thresholds improve specificity in older patients, supporting their clinical implementation. This study also provides the first evidence that hemolysis significantly elevates UCH-L1 concentrations from 400 mg/L of hemoglobin.
Acknowledgments
The authors would like to thank the technicians in the Department of Biochemistry and Molecular Genetics at Clermont-Ferrand University Hospital for their help with the biomarker assays.
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Research ethics: This study received approval from the Ile-de-France Ethics Committee for the Protection of Persons, in accordance with French regulations on research involving human participants (Reference 52-2019).
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Informed consent: Patients were informed of their right to express disagreement regarding the use of their clinical information for research purposes.
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Author contributions: AP, CO and DB analyzed and interpreted the data. AP wrote the initial version of the manuscript. DB, VS, JB, JS, FM and CO designed the study and assisted with interpretation of the data and writing of the manuscript. AP, BB and JD carried out assays. AP and BP provided statistical advice for the study design and analyzed the data. All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: The raw data can be obtained on request from the corresponding author.
References
1. Maas, AIR, Menon, DK, Manley, GT, Abrams, M, Åkerlund, C, Andelic, N, et al.. Traumatic brain injury: progress and challenges in prevention, clinical care, and research. Lancet Neurol 2022;21:1004–60.10.1016/S1474-4422(22)00307-6Search in Google Scholar PubMed
2. Dewan, MC, Rattani, A, Gupta, S, Baticulon, RE, Hung, YC, Punchak, M, et al.. Estimating the global incidence of traumatic brain injury. J Neurosurg 2019;130:1080–97. https://doi.org/10.3171/2017.10.jns17352.Search in Google Scholar PubMed
3. Oris, C, Kahouadji, S, Durif, J, Bouvier, D, Sapin, V. S100B, actor and biomarker of mild traumatic brain injury. Int J Mol Sci 2023;24:6602. https://doi.org/10.3390/ijms24076602.Search in Google Scholar PubMed PubMed Central
4. Jagoda, AS, Bazarian, JJ, Bruns, JJ, Cantrill, SV, Gean, AD, Howard, PK, et al.. Clinical policy: neuroimaging and decisionmaking in adult mild traumatic brain injury in the acute setting. Ann Emerg Med 2008;52:714–48. https://doi.org/10.1016/j.annemergmed.2008.08.021.Search in Google Scholar PubMed
5. Yuh, EL, Jain, S, Sun, X, Pisica, D, Harris, MH, Taylor, SR, et al.. Pathological computed tomography features associated with adverse outcomes after mild traumatic brain injury: a TRACK-TBI study with external validation in CENTER-TBI. JAMA Neurol 2021;78:1137–48. https://doi.org/10.1001/jamaneurol.2021.2120.Search in Google Scholar PubMed PubMed Central
6. Hageman, G, Nihom, J. An abnormal CT scan following a mild traumatic brain injury; what then? Ned Tijdschr Geneeskd 2019;163:D3578.Search in Google Scholar
7. Mathews, JD, Forsythe, AV, Brady, Z, Butler, MW, Goergen, SK, Byrnes, GB, et al.. Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians. BMJ 2013;346:f2360. https://doi.org/10.1136/bmj.f2360.Search in Google Scholar PubMed PubMed Central
8. Pearce, MS, Salotti, JA, Little, MP, McHugh, K, Lee, C, Kim, KP, et al.. Radiation exposure from CT scans in childhood and subsequent risk of leukaemia and brain tumours: a retrospective cohort study. Lancet 2012;380:499–505.10.1016/S0140-6736(12)60815-0Search in Google Scholar PubMed PubMed Central
9. Welch, RD, Papa, L, Bazarian, J, Howard, R, Chen, JY, Weber, A, et al.. Serum biomarker panel outperforms the Canadian computed tomography head rule for diagnosing traumatic intracranial injury. Acad Emerg Med 2019;26:S11.Search in Google Scholar
10. Stiell, IG, Wells, GA, Vandemheen, K, Clement, C, Lesiuk, H, Laupacis, A, et al.. The Canadian CT head rule for patients with minor head injury. Lancet 2001;357:1391–6.10.1016/S0140-6736(00)04561-XSearch in Google Scholar
11. Stiell, IG, Clement, CM, Rowe, BH, Schull, MJ, Brison, R, Cass, D, et al.. Comparison of the Canadian CT head rule and the New Orleans criteria in patients with minor head injury. JAMA 2005;294:1511–8. https://doi.org/10.1001/jama.294.12.1511.Search in Google Scholar PubMed
12. Bouvier, D, Duret, T, Rouzaire, P, Jabaudon, M, Rouzaire, M, Nourrisson, C, et al.. Preanalytical, analytical, gestational and pediatric aspects of the S100B immuno-assays. Clin Chem Lab Med 2016;54:833–42. https://doi.org/10.1515/cclm-2015-0771.Search in Google Scholar PubMed
13. Allouchery, G, Moustafa, F, Roubin, J, Pereira, B, Schmidt, J, Raconnat, J, et al.. Clinical validation of S100B in the management of a mild traumatic brain injury: issues from an interventional cohort of 1449 adult patients. Clin Chem Lab Med 2018;56:1897–904. https://doi.org/10.1515/cclm-2018-0471.Search in Google Scholar PubMed
14. Beaudeux, JL, Laribi, S. La protéine S100B, marqueur biologique de tri pour le diagnostic du traumatisme crânien léger. Ann Biol Clin 2013;71:71–8. https://doi.org/10.1684/abc.2013.0901.Search in Google Scholar PubMed
15. Bouvier, D, Fournier, M, Dauphin, JB, Amat, F, Ughetto, S, Labbé, A, et al.. Serum S100B determination in the management of pediatric mild traumatic brain injury. Clin Chem 2012;58:1116–22. https://doi.org/10.1373/clinchem.2011.180828.Search in Google Scholar PubMed
16. Calcagnile, O, Holmén, A, Chew, M, Undén, J. S100B levels are affected by older age but not by alcohol intoxication following mild traumatic brain injury. Scand J Trauma Resusc Emerg Med 2013;21:52. https://doi.org/10.1186/1757-7241-21-52.Search in Google Scholar PubMed PubMed Central
17. Karamian, A, Farzaneh, H, Khoshnoodi, M, Maleki, N, Karamian, A, Stufflebeam, S, et al.. Diagnostic accuracy of S100B in predicting intracranial abnormalities on CT imaging following mild traumatic brain injury: a systematic review and meta-analysis. Neurocrit Care 2025;42:1025–42. https://doi.org/10.1007/s12028-024-02189-7.Search in Google Scholar PubMed
18. Unden, J, Romner, B. Can low serum levels of S100B predict normal CT findings after minor head injury in adults? an evidence-based review and meta-analysis. J Head Trauma Rehabil 2010;25:228–40.10.1097/HTR.0b013e3181e57e22Search in Google Scholar PubMed
19. Puravet, A, Oris, C, Pereira, B, Kahouadji, S, Gonzalo, P, Masson, D, et al.. Serum GFAP and UCH-L1 for the identification of clinically important traumatic brain injury in children in France: a diagnostic accuracy substudy. Lancet Child Adolesc Health 2024;9:47–56.10.1016/S2352-4642(24)00295-5Search in Google Scholar PubMed
20. Bazarian, JJ, Biberthaler, P, Welch, RD, Lewis, LM, Barzo, P, Bogner-Flatz, V, et al.. Serum GFAP and UCH-L1 for prediction of absence of intracranial injuries on head CT (ALERT-TBI): a multicentre observational study. Lancet Neurol 2018;17:782–9.10.1016/S1474-4422(18)30231-XSearch in Google Scholar PubMed
21. Puravet, A, Oris, C, Pereira, B, Kahouadji, S, Dwamena, BA, Sapin, V, et al.. Can the association of the biomarkers GFAP and UCH-L1 predict intracranial injury after mild traumatic brain injury in adults? A systematic review and meta-analysis. Ann Emerg Med 2025;23:S0196-0644(25)00146-5.10.1016/j.annemergmed.2025.03.018Search in Google Scholar PubMed
22. Papa, L, Brophy, GM, Welch, RD, Lewis, LM, Braga, CF, Tan, CN, et al.. Time course and diagnostic accuracy of glial and neuronal blood biomarkers GFAP and UCH-L1 in a large cohort of trauma patients with and without mild traumatic brain injury. JAMA Neurol 2016;73:551–60. https://doi.org/10.1001/jamaneurol.2016.0039.Search in Google Scholar PubMed PubMed Central
23. Pereira, JB, Janelidze, S, Smith, R, Mattsson-Carlgren, N, Palmqvist, S, Teunissen, CE, et al.. Plasma GFAP is an early marker of amyloid-β but not tau pathology in Alzheimer’s disease. Brain 2021;144:3505–16. https://doi.org/10.1093/brain/awab223.Search in Google Scholar PubMed PubMed Central
24. Kim, KY, Shin, KY, Chang, KA. GFAP as a potential biomarker for Alzheimer’s disease: a systematic review and meta-analysis. Cells 2023;12:1309. https://doi.org/10.3390/cells12091309.Search in Google Scholar PubMed PubMed Central
25. Feng, Z, Tao, S, Huang, Z, Zheng, B, Kong, X, Xiang, Y, et al.. The deubiquitinase UCHL1 negatively controls osteoclastogenesis by regulating TAZ/NFATC1 signalling. Int J Biol Sci 2023;19:2319–32. https://doi.org/10.7150/ijbs.82152.Search in Google Scholar PubMed PubMed Central
26. Oris, C, Bouillon-Minois, JB, Pinguet, J, Kahouadji, S, Durif, J, Meslé, V, et al.. Predictive performance of blood S100B in the management of patients over 65 years old with mild traumatic brain injury. J. Gerontol., Ser. A 2021;76:1471–9. https://doi.org/10.1093/gerona/glab055.Search in Google Scholar PubMed
27. Ladang, A, Vavoulis, G, Trifonidi, I, Calluy, E, Karagianni, K, Mitropoulos, A, et al.. Increased specificity of the “GFAP/UCH-L1” mTBI rule-out test by age dependent cut-offs. Clin Chem Lab Med 2024;63:995–1003.10.1515/cclm-2024-1034Search in Google Scholar PubMed
28. Ramont, L, Thoannes, H, Volondat, A, Chastang, F, Millet, MC, Maquart, FX. Effects of hemolysis and storage condition on neuron-specific enolase (NSE) in cerebrospinal fluid and serum: implications in clinical practice. Clin Chem Lab Med 2005;43:1215–7. https://doi.org/10.1515/CCLM.2005.210.Search in Google Scholar PubMed
29. Babkina, AS, Lyubomudrov, MA, Golubev, MA, Pisarev, MV, Golubev, AM. Neuron-specific enolase—What are we measuring? Int J Mol Sci 2024;25:5040. https://doi.org/10.3390/ijms25095040.Search in Google Scholar PubMed PubMed Central
30. Beaudeux, JL, Léger, P, Dequen, L, Gandjbakhch, I, Coriat, P, Foglietti, MJ. Influence of hemolysis on the measurement of S-100beta protein and neuron-specific enolase plasma concentrations during coronary artery bypass grafting. Clin Chem 2000;46:989–90. https://doi.org/10.1093/clinchem/46.7.989.Search in Google Scholar
31. Biberthaler, P, Linsenmeier, U, Pfeifer, KJ, Kroetz, M, Mussack, T, Kanz, KG, et al.. Serum S-100B concentration provides additional information fot the indication of computed tomography in patients after minor head injury: a prospective multicenter study. Shock 2006;25:446–53. https://doi.org/10.1097/01.shk.0000209534.61058.35.Search in Google Scholar PubMed
32. Gil-Jardiné, C, Payen, JF, Bernard, R, Bobbia, X, Bouzat, P, Catoire, P, et al.. Management of patients suffering from mild traumatic brain injury 2023. Anaesth Crit Care Pain Med 2023;42:101260.10.1016/j.accpm.2023.101260Search in Google Scholar PubMed
33. Bouvier, D, Cantais, A, Laspougeas, A, Lorton, F, Plenier, Y, Cottier, M, et al.. Serum S100B level in the management of pediatric minor head trauma: a randomized clinical trial. JAMA Network Open 2024;7:e242366. https://doi.org/10.1001/jamanetworkopen.2024.2366.Search in Google Scholar PubMed PubMed Central
34. Oris, C, Khatib-Chahidi, C, Pereira, B, Bailly Defrance, V, Bouvier, D, Sapin, V. Comparison of GFAP and UCH-L1 measurements using two automated immunoassays (i-STAT(®) and alinity(®)) for the management of patients with mild traumatic brain injury: preliminary results from a French single-center approach. Int J Mol Sci 2024;25:4539. https://doi.org/10.3390/ijms25084539.Search in Google Scholar PubMed PubMed Central
35. Bouvier, D, Duret, T, Abbot, M, Stiernon, T, Pereira, B, Coste, A, et al.. Utility of S100B serum level for the determination of concussion in Male rugby players. Sports Med 2017;47:781–9. https://doi.org/10.1007/s40279-016-0579-9.Search in Google Scholar PubMed
36. Oris, C, Durif, J, Rouzaire, M, Pereira, B, Bouvier, D, Kahouadji, S, et al.. Blood biomarkers for return to play after concussion in professional rugby players. J Neurotrauma 2023;40:283–95. https://doi.org/10.1089/neu.2022.0148.Search in Google Scholar PubMed
37. McIntosh, SJ, Vergeer, MH, Galarneau, JM, Eliason, PH, Debert, CT. Factors associated with persisting symptoms after concussion in adults with mild TBI: a systematic review and meta-analysis. JAMA Network Open 2025;8:e2516619. https://doi.org/10.1001/jamanetworkopen.2025.16619.Search in Google Scholar PubMed PubMed Central
38. Wang, H, Zhao, T, Zeng, J, Zhang, R, Pu, L, Qian, S, et al.. Methods and clinical biomarker discovery for targeted proteomics using olink technology. Proteonomics Clin Appl 2024;18:e2300233. https://doi.org/10.1002/prca.202300233.Search in Google Scholar PubMed
39. Feng, W, Beer, JC, Hao, Q, Ariyapala, IS, Sahajan, A, Komarov, A, et al.. NULISA: a proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing. Nat Commun 2023;14:7238. https://doi.org/10.1038/s41467-023-42834-x.Search in Google Scholar PubMed PubMed Central
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