2型糖尿病肾病患者血清代谢组学分析构建预后预测模型研究  

Analysis of Serum Metabolomics Model in Type 2 Diabetic Nephropathy

作　　者：陈筱涛[1] 刘韵[1] 龙碧莹 郭皖北[1] CHEN Xiao-tao;LIU Yun;LONG Bi-ying;GUO Wan-bei(Department of Endocrinology,Affiliated Hospital of Xiangnan University,Hunan Chenzhou 423000,China)

机构地区：[1]湘南学院附属医院内分泌科,湖南郴州423000

出　　处：《现代检验医学杂志》2023年第3期97-102,164,共7页Journal of Modern Laboratory Medicine

基　　金：湖南省教育厅科学研究项目(项目编号:20A466):糖尿病肾病发病的相关危险因素及代谢组学分析研究。

摘　　要：目的探讨代谢组学分析构建风险预测模型对预测2型糖尿病肾病(type 2 diabetic nephropathy,T2DN)患者预后的应用价值。方法选取2014年9月~2017年9月于湘南学院附属医院接受治疗的282例T2DN患者,按照预后情况将患者分为预后良好组(n=199)和预后不良组(n=83)。采用超高效液相色谱系统分析测试样品,并运用Markieview软件进行判别分析,寻找出特征差异性代谢物。采用向前逐步法明确最终纳入预测模型的变量,根据各变量对应的偏回归系数(β)构建方程,建立T2DN患者预后预测模型。利用Hosmer-Lemeshow检验和受试者工作特征曲线(receiver operating characteristic curve,ROC)评价预测模型的拟合优度以及预测能力。结果与预后良好组比较,预后不良组患者血清空腹血糖(fasting blood sugar,FBG)(7.96±1.67mmol/L vs 5.03±0.69 mmol/L)、糖化血红蛋白(glycosylated hemoglobin,HbAlc)(8.01%±2.66%vs 5.96%±2.57%)、血尿素氮(blood urea nitrogen,BUN)(6.31±0.88 mol/L vs4.51±0.91 mol/L)、血尿酸(uric acid,UA)(411.25±79.61μmol/L vs 331.21±91.36μmol/L)、三酰甘油(triacylglycerol,TG)(2.18±0.33 mmol/L vs 1.75±0.63 mmol/L)水平升高,低密度脂蛋白-胆固醇(low density lipoprotein-cholesterol,LDL-C)(2.53±0.19 mmol/L vs 2.60±0.21 mmol/L)、高密度脂蛋白-胆固醇(high density lipoprotein-cholesterol,HDLC)(0.95±0.11 mmol/L vs 1.14±0.12 mmol/L)水平降低,差异均有统计学意义(t=10.998,6.042,9.644,4.796,4.101,1.676,7.916,均P<0.01)。代谢组学检验结果显示,预后良好组和预后不良组的代谢状态可明显区分,与预后良好组比较,预后不良组上调的代谢产物有溶血磷脂酰胆碱(t=1.362,P<0.01)、谷氨酰胺-精氨酸(t=2.302,P<0.01)、半乳糖羟赖氨酸(t=1.036,P<0.01)、鹅去氧胆酸(t=5.261,P<0.01);下调的代谢产物有溶血磷脂酰乙醇胺(t=2.321,P<0.01)、磷脂酰乙醇胺(t=5.261,P=0.001)、磷脂酰胆碱(t=2.528,P=0.001)、磷脂酰甘油(t=3.624,P<0.01)、鞘磷脂(t=2.591,P<0.Objective To explore the application value of metabolomics analysis and constructing a risk prediction model in predicting the prognosis of patients with type 2 diabetic nephropathy(T2DN).Methods The 282 patients with type 2 diabetic nephropathy who were treated in the Affiliated Hospital of Xiangnan University from September 2014 to September 2017 were divided into good prognosis group(n=199)and poor prognosis group(n=83)according to their prognosis.Test samples were analyzed by uHPLC system and analyzed by Markieview software to find the characteristic differential metabolites.The forward stepwise method was used to clarify the variables finally included in the prediction model,and the equation was constructed according to the corresponding partial regression coefficient(β)of each variable to establish the prognosis prediction model of patients with type 2 diabetic nephropathy.The goodness-of-fit and prediction ability of the prediction model were evaluated by Hosmer-Lemeshow test and subject operating characteristic curve.Results Compared with the good-prognosis group,patients in the poor prognosis group had serum fasting blood glucose(FBG)(7.96±1.67mmol/L vs 5.03±0.69 mmol/L),glycosylated hemoglobin(HbAlc)(8.01%±2.66%vs 5.96%±2.57%),blood urea nitrogen(BUN)(6.31±0.88 mol/L vs 4.51±0.91 mol/L),Blood uric acid(UA)(411.25±79.61μmol/L vs 331.21±91.36μmol/L),Triacylglycerol(2.18±0.33 mmol/L vs 1.75±0.63 mmol/L)increased,low density lipoprotein-cholesterol(LDL-C)(2.53±0.19 mmol/L vs 2.60±0.21 mmol/L),high density lipoprotein-cholesterol(HDL-C)(0.95±0.11 mmol/L vs 1.14±0.12 mmol/L)decreased,and the differences were statistically significant(t=10.998,6.042,9.644,4.796,4.101,1.676,7.916,all P<0.01).The results of the metabolomics test showed that the metabolic status was clearly distinguished between the good and poor prognosis groups.In comparison with the well-prognosis group,the upregulated metabolites in the poor prognosis group were lysophosphatidylcholine(t=1.362,P=0.000),glutamine-arginine(t=2.

关 键 词：代谢组学 2型糖尿病肾病 预测模型 

分 类 号：R587.2[医药卫生—内分泌] R446.11[医药卫生—内科学]