Diagnostics
Genetic Predictors of Curve Progression and Brace Treatment Response in Adolescent Idiopathic Scoliosis: Toward Personalized Management
By Alexandru Ulici, Alexandru Ionuț Ciobanu and Alexandru Herdea.
Abstract
Adolescent idiopathic scoliosis (AIS) is characterized by substantial variability in curve progression and response to conservative treatment, making accurate prognostic assessment a major clinical challenge. Although established clinical and radiographic factors contribute to risk stratification, they do not fully explain individual differences in disease evolution or brace treatment outcome. This review critically examines current evidence on genetic determinants of curve progression and brace treatment response in AIS, with particular emphasis on their potential contribution to individualized risk prediction. Candidate-gene studies have reported associations involving hormonal, metabolic, developmental, and skeletal pathways, while studies of brace response have identified potential predictive associations involving ERα, TPH1, VDR, VDBP, and BNC2. Multigene approaches, including ScoliScore, have further explored the potential of polygenic information for prognostic assessment. However, reported genetic effects are generally modest, replication across populations remains limited, and substantial heterogeneity exists in study design, outcome definitions, and characterization of brace treatment. Importantly, current evidence remains insufficient to demonstrate clinically meaningful predictive value of genetic information beyond established clinical factors. Future research should prioritize large prospective multicenter cohorts, standardized definitions of progression and treatment outcome, objective assessment of brace adherence and correction, progression-specific polygenic approaches, and external validation across diverse populations. Ultimately, integrating genetic information with clinical, radiographic, developmental, biomechanical, and treatment-related variables may provide a more comprehensive framework for individualized prediction and precision management of AIS.




