Enhancing intervertebral disc repair and regeneration through biology: platelet-rich plasma as an alternative strategy

Shan-Zheng Wang, Yun-Feng Rui, Qi Tan, Chen Wang, Shan-Zheng Wang, Yun-Feng Rui, Qi Tan, Chen Wang

Abstract

Intervertebral disc degeneration (IDD) is a common orthopedic disease associated with mechanical changes that may result in significant pain. Current treatments for IDD mainly depend on conservative therapies and spinal surgeries that are only able to relieve the symptoms but do not address the cause of the degeneration and even accelerate the degeneration of adjacent segments. This has prompted research to improve our understanding of the biology of intervertebral disc healing and into methods to enhance the regenerative process. Recently, biological therapies, including active substances, gene therapy and tissue engineering based on certain cells, have been attracting more attention in the field of intervertebral disc repair and regeneration. Early selection of suitable biological treatment is an ideal way to prevent or even reverse the progressive trend of IDD. Growth factors have been enjoying more popularity in the field of regeneration of IDD and many have been proved to be effective in reversing the degenerative trend of the intervertebral disc. Identification of these growth factors has led to strategies to deliver platelet-derived factors to the intervertebral disc for regeneration. Platelet-rich plasma (PRP) is the latest technique to be evaluated for promoting intervertebral disc healing. Activation of the PRP leads to the release of growth factors from the α-granules in the platelet cytoplasm. These growth factors have been associated with the initiation of a healing cascade that leads to cellular chemotaxis, angiogenesis, synthesis of collagen matrix, and cell proliferation. This review describes the current understanding of IDD and related biological therapeutic strategies, especially the promising prospects of PRP treatment. Future limitations and perspectives of PRP therapy for IDD are also discussed.

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Source: PubMed

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