基于LC-MS代谢组学技术的肾病综合征潜在分型及进展生物标志物的研究

Investigation on potential subtyping and progression biomarkers of nephrotic syndrome based on LC-MS metabolomics technology

肾病综合征(nephrotic syndrome,NS)具有多种分型且发病机制和病理类型多样,临床上主要依赖血清生化进行诊断,而具体分型的鉴定必须通过肾穿刺进行活检,患者依从性较差。因此,寻找一种可无创、快速反映肾病综合征分型及疾病进展的方法对于临床诊断具有重要意义。本研究运用LC-MS代谢组学技术结合受试者工作特征曲线(receiver operating characteristic,ROC)和多元线性回归分析筛选鉴定可反映肾病综合征分型及疾病进展的潜在生物标志物。结果显示,依据正交偏最小二乘判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA)模型中的变量VIP>1、P<0.05和AUC>0.5筛选出区分膜性肾病(membranous nephropathy,MN)与IgA肾病(IgA nephropathy,IgAN)的5个潜在分型标志物包括吲哚乙酸、异亮氨酸脯氨酸、DL-吲哚-3-乳酸、D-苯丙氨酸和L-色氨酸。进一步以肾小球滤过率(estimated glomerular filtration rate,eGFR)为因变量,采用多元线性回归分析明确了可反映膜性肾病进展为尿毒症(uremia)的潜在进展标志物,包括丙氨酰亮氨酸、9-癸酰肉碱、葡萄糖酸、辛基甘氨酸和癸二酸,而IgA肾病进展为尿毒症的潜在进展标志物为丙氨酰亮氨酸、9-癸酰肉碱、辛基甘氨酸和癸二酸。该研究为肾病综合征潜在分型及进展生物标志物的发现提供理论依据,也为其他进展性疾病潜在生物标志物的发现提供方法参考。该方案经山西省人民医院伦理委员会同意[(2020)省医科伦审字第30号]。

Nephrotic syndrome(NS)has a variety of classifications,pathogenesis and pathological types.Clinical diagnosis primarily relies on serum biochemistry,while the specific classification necessitates renal puncture for biopsy,which is hindered by poor patient compliance.Therefore,it is of great significance for clinical diagnosis to find a non-invasive and rapid method to reflect the classification and progression of nephrotic syndrome.In this study,LC-MS metabolomics combined with receiver operating characteristic(ROC)and multiple linear regression analysis was used to screen and identify potential biomarkers capable of reflecting the typing and progression of nephrotic syndrome.According to the statistical parameters VIP>1,P<0.05 and AUC>0.5 obtained from the orthogonal partial least squares discriminant analysis(OPLS-DA)model,five potential classification markers were screened to distinguish membranous nephropathy(MN)from IgA nephropathy(IgAN),including indoleacetic acid,isoleucine proline,DL-indole-3-lactic acid,D-phenylalanine and L-tryptophan.Furthermore,using estimated glomerular filtration rate(eGFR)as the dependent variable,a multiple linear regression analysis was conducted to identify the potential progression markers capable of reflecting the progression of MN to uremia.These metabolites included alanylleucine,9-capryloylcarnitine,gluconic acid,caprylyl glycine and sebacic acid.Potential markers of progression of IgA nephropathy to uremia comprised alanylleucine,9-capryloylcarnitine,caprylyl glycine,and sebacic acid.This study provides a theoretical basis for the discovery of potential classification and progression biomarkers of kidney disease,and also offers a methodological reference for future research in this area.The protocol was approved by the Ethics Committee of Shanxi Provincial People's Hospital[(2020)Provincial Medical Ke Lun Shen Zi No.30].