Xu Leilei, Wu Zhichong, Xia Chao, Tang Nelson, Cheng Jack C Y, Qiu Yong, Zhu ZeZhang
1Department of Spine Surgery, The Affiliated Drum Tower Hospital of Nanjing University Medical School, Zhongshan Road 321, Nanjing210008, China; 2Joint Scoliosis Research Center of The Chinese University of Hong Kong and Nanjing University, Nanjing, China; 3SH Ho Scoliosis Research Laboratory, Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong.
Curr Genomics. 2019 May;20(4):246-251. doi: 10.2174/1389202920666190730132411.
Previous GWASs have revealed several susceptible variants associated with adolescent idiopathic scoliosis (AIS). Risk prediction based on these variants can potentially improve disease prognosis. We aimed to evaluate the combined effects of genetic factors on the development of AIS and to further develop a genetic predictive model.
A total of 914 AIS patients and 1441 normal controls were included in the discovery stage, which was followed by the replication stage composed of 871 patients and 1239 controls. Genotyping assay was performed to analyze 10 previously reported susceptible variants, including rs678741 of LBX1, rs241215 of AJAP1, rs13398147 of PAX3, rs16934784 of BNC2, rs2050157 of GPR126, rs2180439 of PAX1, rs4940576 of BCL2, rs7593846 of MEIS1, rs7633294 of MAGI1 and rs9810566 of TNIK. Logistic regression analysis was performed to generate a risk predictive model. The predicted risk score was calculated for each participant in the replication stage.
The association of the 10 variants with AIS was successfully validated. The established model could explain approximately 7.9% of the overall variance. In the replication stage, patients were found to have a remarkably higher risk score as compared to the controls (44.2 ± 14.4 vs. 33.9 ± 12.5, p <0.001). There was a remarkably higher proportion of the risk score i.e. >40 in the patients than in the controls (59% vs. 28.9%, p <0.001).
Risk predictive model based on the previously reported genetic variants has a remarkable discriminative power. More clinical and genetic factors need to be studied, to further improve the proba-bility to predict the onset of AIS.
既往全基因组关联研究（GWAS）已揭示了多个与青少年特发性脊柱侧凸（AIS）相关的易感变异。基于这些变异进行风险预测可能会改善疾病预后。我们旨在评估遗传因素对AIS发病的综合影响，并进一步构建一个遗传预测模型。
发现阶段共纳入914例AIS患者和1441例正常对照，随后的验证阶段纳入871例患者和1239例对照。采用基因分型检测分析10个先前报道的易感变异，包括LBX1基因的rs678741、AJAP1基因的rs241215、PAX3基因的rs13398147、BNC2基因的rs16934784、GPR126基因的rs2050157、PAX1基因的rs2180439、BCL2基因的rs4940576、MEIS1基因的rs7593846、MAGI1基因的rs7633294和TNIK基因的rs9810566。进行逻辑回归分析以构建风险预测模型。计算验证阶段每位参与者的预测风险评分。
成功验证了这10个变异与AIS的关联。所构建的模型可解释约7.9%的总体变异。在验证阶段，发现患者的风险评分显著高于对照（44.2±14.4 vs. 33.9±12.5，p<0.001）。患者中风险评分>40的比例显著高于对照（59% vs. 28.9%，p<0.001）。
基于先前报道的遗传变异构建的风险预测模型具有显著的鉴别能力。需要进一步研究更多的临床和遗传因素，以提高预测AIS发病的概率。
