基于超高效液相色谱-串联质谱的组织代谢组学分析在股骨头坏死中的应用

Metabolomics study on osteonecrosis of femoral head based on UPLC-MS/MS

目的应用代谢组学分析方法探索股骨头坏死的组织代谢特征并寻找其潜在的生物标志物。方法分别收集23例（25髋）股骨头坏死和18例股骨颈骨折患者的股骨头组织标本，行病理学检查明确诊断。萃取骨组织标本代谢物，采用超高效液相色谱一质谱／质谱串联仪检测，对检测结果进行预处理，建立主成分分析（principalcomponentanalysis，PCA）、偏最小二乘法判别分析（partialleast．squaresdiscriminantanalysis，PLS．DA）及正交偏最小二乘法判别分析（orthogo．halpartialleastsquaresdiscriminantanalysis，OPLS．DA）模型。根据PLS．DA模型和多个独立样本的Kruskal．Wallis日检验筛选差异变量，依据一级和二级质谱推定其对应的代谢物。筛选两组峰强度变化最明显的代谢物作为潜在的生物标志物，通过二元Logistic回归进行受试者工作曲线receiveroperatingcharacteristicCHIVe，ROC）分析，评价其诊断意义。结果股骨头坏死和股骨颈骨折患者的股骨头骨组织代谢物表达模式在PCA、PLS—DA、OPLS．DA模型中均能明显区分。股骨头坏死组表达高于股骨颈骨折组的代谢物有D．精氨酸、L-脯氨酸、L一谷氨酰胺、肌苷、尿嘧啶、尿苷、LysoPC（20：4（5Z，8Z，11Z，14Z））、LysoPC（16：0）、PC（20：1（11z）／18：3（6z，9Z，12Z））、PE（P．16：0e／0：0）；低于股骨颈骨折组的有柑橘叶黄素、B--隐黄质。根据峰强度改变倍数、变量权重型投影值筛选出改变最为明显的三种物质是D-精氨酸、L-脯氨酸、L．谷氨酰胺，ROC曲线下面积分别是0．873、0．712、0．862，三种代谢物联合ROC曲线下面积为0．946。结论通过股骨头坏死和股骨颈骨折的骨组织代谢物PCA、PLS—DA、OPLS．DA模型可筛选出12种代谢物，其中D-精氨酸、L-脯氨酸、L．谷氨酰胺为潜在的股骨头坏死生物标志，其联合诊断的价值较高。

Objective To investigate the metabolism characteristics and the potetial biomarker candidates of osteonecrosis of the femoral head （ONFH） using metabolomic technology. Methods The femoral head specimens from 23 ONFH patients （25 necrotic femoral heads） and 18 normal femoral heads from femoral neck fracture patients were collected for histopathological examination to confirm the diagnosis of all samples. All the metabolites of bone trabecula were extracted for ultra-high performance liquid chromatography-MS/MS analyzed. The measured variables was pretreat, and PCA （principal component analysis）, PLS-DA （partial least squares-discriminant analysis） and OPLS-DA （orthogonal-partial least squares-diseriminant analysis） models were employed to confirm the difference between these two groups after UPLC-MS/MS （ultra-high performance liquid chromatogra- phy-mass spectrometry/mass spectrometry） analysis. At last, the differential variables were screened out by PLS-DA and variate analysis （Kruskal-Wallis H test）. The changed metabolites were confirmed by MS and MS/MS aligned in HMDB （human metabolomic database） and Massbank. The changed metabolites with the most obviously changed peak abundance, D-arginine, L-proline and L-glutamine, were picked out as the potential diagnostic biomarkers. After binary logistic regression analysis, the combined biomarkers candidates were further analyzed by receiver operating characteristic （ROC） curve to evaluate the significance of the combined biomarkers. Results Significant distinction of metabolites expression mode can be seen in PCA, PLS-DA and OPLS- DA models scoring plots between ONFH and control groups. Twelve changed metabolites in ONFH bone trabeculas were confirmed by multi-variate statistical analysis and variate statistical analysis. Compared with the femoral neck fracture patients, the increased metabolites included D-arginine, L-proline, L-glutamine, creatine, uracil, uridine, LysoPC（20： 4（5Z, 8Z, 11Z, 14Z））, LysoPC（16： 0）, PC（20： 1 （11Z）/18 ： 3（6Z, 9Z, 12Z）） and PE（P- 16 ： 0e/0 ： 0）. The decreased metabolites were reticulataxanthin and β- cryptoxanthin. According to the change fold of peak abundance and variable weight projection in PLS-DA, the most obviously dif-ferential metabolites were picked out as the biomarker candidates of ONFH. The potential biomarkers candidates were identified as D-arginine, L-proline and L-glutamine. The area under the curve of D-arginine, L-proline and L-glutamine ROC were 0.873, 0.712 and 0.862. The area under the curve of ROC was 0.946 after combining D-arginine, L-proline, L-glutamine using binary lo- gistic regression analysis. Conclusion PCA, PLS-DA and OPLS-DA models were used to find out the differential variables in the metabolites of bone trabeculas in ONFH and femoral neck fracture patients. Twelve metabolites were identified by MS/MS, and 3 obviously changed metabolites, D-arginine, L-proline, L-glutamine, were indicated as biomarker candidates. These 3 obviously changed metabolites showed a good diagnostic significance.