Abstract
Adolescent Idiopathic Scoliosis (AIS) is the most common orthopedic condition requiring surgery, affecting 4% of adolescents. There is currently no proven method or prognostic test to identify symptomatic patients at risk of developing severe scoliosis who could benefit from growth-guided devices or minimally invasive non-fusion instrumentation surgeries. These innovative treatments must be performed at an early disease stage in younger patients to benefit from their growth potential. In this prospective cross-sectional study, we investigated the clinical utility of circulating microRNAs (miRNAs), an important class of small non-coding RNA, as biomarkers to predict the risk of developing severe scoliosis in AIS. Blood samples and clinical data were collected from 116 AIS patients who were followed until skeletal maturity and stratified according to their clinical outcome. Genome-wide expression profiling of miRNAs was performed with plasma obtained at the time of diagnosis of AIS (mean age of 13.3 ± 1.7 years with a mean Cobb angle of 24.4° ± 12.4°). This approach led to the identification of 15 circulating miRNAs that are upregulated in AIS patients who developed a severe scoliosis (Cobb angle ≥ 45°) at skeletal maturity compared to moderate and mild scoliosis groups (Cobb angle between 25°-44° and < 25° respectively). After optimization and the application of Random Forest Models a panel of six miRNAs (miR-1-3p, miR-19a-3p, miR-19b-3p, miR-133b, miR-143-3p, and miR-148b-3p) out of 15 led us to develop an algorithm predicting the risk of developing a severe scoliosis with great accuracy (100%), sensitivity (100%) and specificity (100%). Having a scoliosis predictive bioassay and decision-making tools to predict curve progression in order to find the best treatment plan will undoubtedly transform the orthopedic care system in the field of pediatric scoliosis by integrating innovative precision medicine approaches. In addition, investigation of genes targeted by these miRNAs could fill our gaps in our understanding of AIS pathogenesis and reveal new actionable targets.