Shriners Hospital for Children, USA.
Curr Opin Pediatr. 2010 Feb;22(1):67-70. doi: 10.1097/MOP.0b013e32833419ac.
Adolescent idiopathic scoliosis (AIS) is the most common spinal deformity affecting 2% of the population. Initial diagnosis is straightforward. Determining which curves will progress and warrant intervention is still problematic. Recent genetics research has discovered markers that are associated with progression to a severe curve, providing new information that can lead to more effective care with lower cost and fewer unnecessary radiographs and brace applications.
Current family studies indicate that AIS is a polygenic disorder with multiple patterns of inheritance. Genetic markers have been identified that are related to AIS curve progression to a severity in which surgery is often performed (under review 2009). These genetic markers have been validated in white girls and boys but are not yet confirmed in Asians or African-Americans. These markers provide a basis for calculating the risk of progression in a score-based model, thus enabling personalized medical decisions. Further research following these discoveries may lead to an understanding of the underlying molecular biology of AIS.
Genetic markers have been identified that are associated with progression to a severe curve in AIS patients. A risk of progression score can be calculated using these saliva-based DNA markers that risk stratifies patients on a scale of 1-200. This AIS progression test enables personalized medical decisions for treatment algorithms and improves the quality of care by allowing evidence-based management decisions.
青少年特发性脊柱侧凸（AIS）是最常见的脊柱畸形，影响人群的 2%。初始诊断很简单。确定哪些曲线会进展并需要干预仍然是个问题。最近的遗传学研究发现了与进展为严重曲线相关的标志物，提供了新的信息，可以通过降低成本和减少不必要的射线检查和支具应用来实现更有效的治疗。
目前的家族研究表明，AIS 是一种多基因疾病，具有多种遗传模式。已经确定了与 AIS 曲线进展到通常需要手术的严重程度相关的遗传标记（正在审查 2009 年）。这些遗传标记已经在白人女孩和男孩中得到验证，但尚未在亚洲人或非裔美国人中得到证实。这些标志物为基于评分的模型计算进展风险提供了基础，从而实现了个体化的医疗决策。对这些发现的进一步研究可能会导致对 AIS 潜在分子生物学的理解。
已经确定了与 AIS 患者严重曲线进展相关的遗传标记。可以使用这些基于唾液的 DNA 标记计算进展风险评分，该评分将患者的风险分层在 1-200 的范围内。这种 AIS 进展测试可用于治疗算法的个体化医疗决策，并通过允许基于证据的管理决策来提高护理质量。
