Intervertebral disc (IVD) degeneration is a significant contributor to lower back pain, a leading cause of disability in individuals over 45. IVD is marked by the degradation of collagen and the extracellular matrix, which triggers inflammatory responses, recruits macrophages and accelerates degeneration. Monitoring the progression of IVD degeneration and assessing the effectiveness of regenerative treatments have challenges.
Traditional methods such as histology and immunohistochemistry are time-consuming and lack the capability to distinguish between damaged and intact collagen—a critical metric for accurate IVD diagnosis and treatment. Collagen Hybridising Peptides (CHPs) selectively bind to damaged collagen, allowing precise visualisation and quantification of IVD in tissue samples. In this ex vivo disc degeneration model, fluorescently labeled CHPs rapidly and specifically tagged damaged collagen, significantly reducing hands-on time from 240-360 minutes to 20-30 minutes compared to traditional methods. In addition, CHPs provide the unique ability to visualise damaged collagen of all types, unlike conventional methods that only detect total collagen.
CHP-FITC staining detects age and inflammation-induced collagen breakdown in mouse intervertebral discs,
This enhanced visualisation of extracellular matrix remodelling in IVD offers a quantitative measure of disease progression and allows for better prediction of future disc degeneration. This group is currently developing an in vivo probe for early diagnosis of disc degeneration, which will empower clinicians with accurate diagnoses and more informed treatment decisions.
Xiao, Li et al. “Molecular Detection and Assessment of Intervertebral Disc Degeneration via a Collagen Hybridizing Peptide.” ACS biomaterials science & engineering vol. 5,4 (2019): 1661-1667. doi:10.1021/acsbiomaterials.9b00070
Information originally posted on: https://www.3helix.com/blogs/news/advancing-intervertebral-disc-degeneration-assessment-with-collagen-hybridizing-peptides-a-fast-accurate-approach-for-research-and-clinical-applications
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