Biofluid-based predictors of post-concussion symptoms: a narrative review of mild traumatic brain injury biomarkers
Year: 2025
Type: review
Abstract: Mild traumatic brain injury can disrupt brain function and is associated with high morbidity and healthcare utilization. While many individuals recover from mild traumatic brain injury, a significant proportion experience long-term sequelae, collectively known as post-concussion syndrome. Symptoms of post-concussion syndrome include headache, dizziness, insomnia, cognitive processing difficulties and mental health disturbances. The disease burden is augmented by the current lack of objective measures to accurately predict long-term symptoms and deficits, providing an opportunity to utilize biomarkers in biofluids. A large proportion of available diagnostic clinical tools are subjective symptom scores. This review aims to explore current fluid biomarkers, grouped by clinical symptoms. With the available literature, we have discovered a wide range of fluid biomarkers that have been investigated for predicting post-traumatic headache, including neuropeptides; sleep disturbances, such as cortisol and melatonin; vestibular disturbances, including interleukin-6 and neurone-specific enolase; and vomiting, such as S100B. Along with physical symptoms, biomarkers investigated for predicting cognitive disturbances include inflammatory markers, S100B, neurofilament light chain, tau, microRNA and hormones. Biomarkers to predict mental health disturbances may include brain-derived neurotrophic factor, tau and cortisol. By utilizing such biomarkers, there is capacity to adopt a personalized medicine approach to facilitate early interventions for those most in need while also identifying individuals with a favourable prognosis who can safely return to their normal activities.
Source: Brain Communications
Authors: Hannah S Lyons, Jessica C Hubbard, Chloe N Thomas, James A Roberts, Caroline W Mugo, Gabriel Bellamy Plaice, Olivia Grech, Sophie Prosser, Asha Strom, Samuel J E Lucas, Laura E Downie, Jessica M Gill, James L Mitchell, Alexandra J Sinclair, Lisa J Hill, Adam Hampshire, Agata Czarnecka, Ahmed Fouad Abdel-Hay, Aimee R Smith, Alex Bryant, Alexandra J Sinclair, Ali Mazaheri, Alice J Sitch, Aliyah Mannan, Altus Chan, Andreas Yiangou, Andrew P Bagshaw, Andrew Palmer, Angus M Hunter, Animesh Ghose, Asha Strom, Caroline W Mugo, Carl R Krynicki, Caroline Witton, Cherie Nicholls, Chloe N Thomas, Claire H Brown, Clare Anderson, Dan Ford, Danny Smullen, David J Smith, David Jimenez-Grande, Davinia Fernandez-Espejo, Eleanor G Rowan-MacIndoe, Emma C Lardner, Hamid Dehghani, Hannah Fisher, Hannah S Lyons, Hyojin Park, Ian Varley, Jacob H Tennant, James L Mitchell, Jan Novak, Jennie Gavin, Jessica C Hubbard, John T Read, Jonthan J Deeks, Julita Sulkowska, Karen J Mullinger, Karen Tester, Katherine L Cox, Katie Morris, Linda Martina Coughlan, Lisa J Hill, Maria Balaet, Mark Thaller, Matt Hill, Mia Mann, Nasreen Akhtar, Ned J Jenkinson, Neil Winkles, Pete J Hellyer, Raymond F Reynolds, Richard J Blanch, Ryan S Ottridge, Sabrina Qureshi, Samuel J E Lucas, Sarah Berhane, Syama Mohan, Thomas Meredith, Tom Inns, Yousef F Hyder
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,024
Awards: G1590412184, G2350218693
OpenAlex ID: W4417535932
