Serum integrative omics reveals the landscape of human diabetic kidney disease

Objective Diabetic kidney disease (DKD) is the most common microvascular complication of type 2 diabetes mellitus (2-DM). Currently, urine and kidney biopsy specimens are the major clinical resources for DKD diagnosis. Our study proposes to evaluate the diagnostic value of blood in monitoring the onset of DKD and distinguishing its status in the clinic. Methods This study recruited 1,513 participants including healthy adults and patients diagnosed with 2-DM, early-stage DKD (DKD-E), and advanced-stage DKD (DKD-A) from 4 independent medical centers. One discovery and four testing cohorts were established. Sera were collected and subjected to training proteomics and large-scale metabolomics. Results Deep profiling of serum proteomes and metabolomes revealed several insights. First, the training proteomics revealed that the combination of α2-macroglobulin, cathepsin D, and CD324 could serve as a surrogate protein biomarker for monitoring DKD progression. Second, metabolomics demonstrated that galactose metabolism and glycerolipid metabolism are the major disturbed metabolic pathways in DKD, and serum metabolite glycerol-3-galactoside could be used as an independent marker to predict DKD. Third, integrating proteomics and metabolomics increased the diagnostic and predictive stability and accuracy for distinguishing DKD status. Conclusions Serum integrative omics provide stable and accurate biomarkers for early warning and diagnosis of DKD. Our study provides a rich and open-access data resource for optimizing DKD management.
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Highlight • Serum proteomics and metabolomics are novel, noninvasive approaches to detect DKD. • Integrated serum omics enhances the diagnostic stability and accuracy of DKD diagnoses. • Galactose/glycerolipid metabolism is the major disturbed metabolic pathway in DKD. • Serum metabolite glycerol-3-galactoside is an independent predictive marker of DKD.