Diabetic kidney disease (DKD) is the main cause of uremia,but western medical treatment of DKD has its limitations.“Syndrome Differentiation and Treatment” of Chinese medicine (CM) has certain advantages for DKD treatment.However,their objectivity and reproducibility of disease assessment and efficacy judgment were questioned.Traditional Chinese Medicine (TCM) syndromes are inevitably related to the intrinsic nature of the disease,the holistic characteristics of metabolomics are helpful to find the metabolic markers corresponding to TCM syndromes of DKD.Therefore,it is of great scientific significance and clinical application value to carry out the study of DKD diagnostic metabolic markers based on metabonomic techniques.In this study,we discussed the bottleneck problem of TCM syndrome normalized and objective study of DKD,and expounded the necessity and feasibility of TCM Syndrome markers of DKD based on high-sensitivity and high-resolution UPLC-Q-Orbitrap mass spectrometry analysis method and “big data and deep learning” technique.In order to provide a quantifiable and repeatable objective basis for DKD syndrome differentiation, and improve the scientific nature of DKD syndrome differentiation.