Circulating microRNA signatures for diagnosis and prediction of progression in pediatric idiopathic scoliosis
Introduction: Idiopathic scoliosis (IS) is the most common pediatric spinal deformity, yet no biomarker currently enables early diagnosis or reliable prediction of progression to guide individualized treatment. Circulating microRNAs (miRNAs) are promising non-invasive biomarkers reflecting multifactorial disease mechanisms. Methods: We conducted a prospective study in a Czech cohort comprising 114 pediatric IS patients at the time of diagnosis (82 females, 32 males; median age 13 years, range 7–17) and 89 age-matched healthy controls (60 females, 29 males; median age 13 years, range 7–18). Plasma miRNA profiles were obtained by next-generation sequencing, corrected for batch effect, and analyzed for differential expression. Logistic regression models were used to construct miRNA diagnostic and prognostic signatures, validated by leave-one-out cross-validation (LOOCV). Differential expression analysis identified multiple miRNAs with significant diagnostic potential. A 28-miRNA diagnostic signature distinguished IS patients from controls with AUC = 0.95 and LOOCV accuracy = 0.85, with high PPV and NPV. For prognosis, comparison of high-risk versus low/medium-risk patients revealed a 7-miRNA prognostic signature, achieving AUC = 0.83 and LOOCV accuracy = 0.81. Notably, the incorporation of clinical variables such as age or sex did not improve model performance. Our study demonstrates that circulating miRNA signatures have potential as diagnostic markers and, importantly, as predictors of disease progression in pediatric idiopathic scoliosis. These findings highlight the clinical utility of miRNA-based models for individualized patient management and support further validation in larger, independent cohorts. Overall design: All patients included in our study were both females or males diagnosed with juvenile or adolescent idiopathic scoliosis.. The blood plasma samples of 114 IS patients and 89 healthy controls were analysed. IS patients were divided into three subgroups according to the risk of progression.