# Current insights into circulating biomarkers and their potential for predicting adolescent idiopathic scoliosis progression

## TL;DR

This review discusses potential blood-based biomarkers for predicting the progression of adolescent idiopathic scoliosis, a spine deformity that worsens during puberty.

## Contribution

The paper highlights recent advances in non-coding RNA biomarkers and emphasizes the need for longitudinal studies to improve prediction accuracy.

## Key findings

- Circulating biomarkers like growth hormones, bone metabolism proteins, and microRNAs are being explored for AIS progression prediction.
- Current studies suffer from methodological flaws, such as single-time-point sampling, limiting their reliability.
- Longitudinal studies with repeated measurements are essential to capture dynamic biological changes in AIS.

## Abstract

Adolescent Idiopathic Scoliosis (AIS) is a three-dimensional deformation of the spine with a frontal plane curvature of 10° or more, measured using Cobb method. It typically gets more severe during pre-puberty and puberty, currently exhibiting unpredictable progression. Severe disease is more prevalent in females, and progression is associated with respiratory and neuromuscular dysfunction, pain, and psychological complications. Management strategies are guided by curve severity and include observation, therapeutic exercises, bracing, and surgery. Despite advances, the cellular and molecular mechanisms driving AIS remain poorly understood. Early detection and reliable progression biomarkers are increasingly recognized as critical to prevent clinical mismanagement. This mini-review summarizes current evidence on circulating biomarkers investigated in AIS, including growth-related hormones, bone metabolism proteins, and more recently non-coding RNAs (ncRNAs) such as microRNAs. In addition, we highlight key methodological limitations and risk-of-bias concerns across existing studies, especially the reliance on single-time-point sampling, underscoring the need for longitudinal prospective cohorts with repeated biomarker measurements. Such designs are critical for capturing dynamic biological changes, distinguishing stable from progressive cases, and validating biomarker trajectories for integration into clinically meaningful prediction models for AIS progression.