Circulating microRNA signatures for diagnosis and prediction of curve progression in pediatric patients with idiopathic scoliosis.

Abstract

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. In our prospective monocentric study, a Czech cohort comprising 114 pediatric IS patients at the time of diagnosis and 89 age‑matched healthy controls was studied. Risk groups were defined based on the final Cobb angle at the end of follow-up at skeletal maturity. Plasma miRNA profiles were obtained by small RNA sequencing 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 48 miRNAs with significantly different expression in the blood plasma of IS patients and controls (adj. p < 0.05), and plasma miR-4451 to have decreased levels in high-risk compared to low- and medium-risk IS patients (adj. p < 0.01). A 28‑miRNA diagnostic signature distinguished IS patients from controls with AUC = 0.95 (sensitivity 88%, specificity 92%) and LOOCV accuracy = 0.85. For prognosis, comparison of high‑risk versus low/medium‑risk patients revealed a 7‑miRNA prognostic signature, achieving AUC = 0.83, sensitivity 82%, specificity 74% and LOOCV accuracy = 0.81. Notably, the incorporation of clinical variables such as age or sex did not improve significantly model performance. Our study highlights the clinical utility of miRNA‑based models for precise diagnosis and individualized patient management and supports further validation in larger, independent cohorts.