# Establishment and research progress of animal models for intervertebral disc degeneration

## TL;DR

This review summarizes current animal models for studying intervertebral disc degeneration and highlights challenges and future directions to improve research and treatment development.

## Contribution

The paper provides a systematic synthesis of existing IDD animal models and outlines future research directions to enhance translational outcomes.

## Key findings

- Current IDD animal models include injury, spontaneous, mechanical, and chemical models with distinct advantages and limitations.
- Existing models struggle to replicate the progressive and heterogeneous nature of human IDD.
- Advances in bioengineering and molecular imaging offer new opportunities for improved model development and evaluation.

## Abstract

Low back pain associated with intervertebral disc degeneration (IDD) is a prevalent condition in clinical practice, significantly impacting patients’ work and quality of life. Animal models are indispensable for IDD research, offering crucial tools to investigate the molecular mechanisms of disease onset and progression, as well as to evaluate potential therapeutic interventions. Current animal models for IDD include intervertebral disc injury, spontaneous degeneration, mechanically induced, and chemically induced models, each exhibiting unique strengths and limitations in mimicking the pathological features of human IDD. Despite these advancements, existing models continue to struggle with replicating the long-term, progressive nature of degeneration and the heterogeneity observed in human patients. With the emergence of bioengineering techniques and molecular imaging, novel approaches to model construction and evaluation have opened new avenues for IDD research. This review systematically synthesizes current strategies for constructing IDD animal models, their application characteristics, and associated challenges, while also projecting future research directions. The aim is to provide guidance for optimizing model selection and accelerating translational research in the field of IDD.