Background Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the ‘gold standard’ for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress. Methods In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic samples, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs. Results We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent dataset. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patients have progressed to DKD3. Conclusions Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.
Background Type 2 diabetic kidney disease is the most common cause of chronic kidney diseases (CKD) and end-stage renal diseases (ESRD). Although kidney biopsy is considered as the ‘gold standard’ for diabetic kidney disease (DKD) diagnosis, it is an invasive procedure, and the diagnosis can be influenced by sampling bias and personal judgement. It is desirable to establish a non-invasive procedure that can complement kidney biopsy in diagnosis and tracking the DKD progress. Methods In this cross-sectional study, we collected 252 urine samples, including 134 uncomplicated diabetes, 65 DKD, 40 CKD without diabetes and 13 follow-up diabetic sample, and analyzed the urine proteomes with liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We built logistic regression models to distinguish uncomplicated diabetes, DKD and other CKDs. Results We quantified 559 ± 202 gene products (GPs) (Mean ± SD) on a single sample and 2,946 GPs in total. Based on logistic regression models, DKD patients could be differentiated from the uncomplicated diabetic patients with 2 urinary proteins (AUC = 0.928), and the stage 3 (DKD3) and stage 4 (DKD4) DKD patients with 3 urinary proteins (AUC = 0.949). These results were validated in an independent data set. Finally, a 4-protein classifier identified putative pre-DKD3 patients, who showed DKD3 proteomic features but were not diagnosed by clinical standards. Follow-up studies on 11 patients indicated that 2 putative pre-DKD patient have progressed to DKD3. Conclusions Our study demonstrated the potential for urinary proteomics as a noninvasive method for DKD diagnosis and identifying high-risk patients for progression monitoring.
Background: Dilong (earthworm), a traditional Chinese medicine obtained from the dried body of Pheretima aspergillum (E. Perrier), has proven cardioprotective effects in cardiovascular disorders. We aimed to investigate the potential therapeutic application of Dilong in preventing cardiomyocyte fibrosis and inflammation during cardiac hypertrophy (CH) after pressure overload (PO).Methods: We used the active protein compounds of Dilong (DAPC) to treat CH in vivo and in vitro. Hypertrophic rats were generated by abdominal aortic constriction (AAC)-surgery in male Wistar rats. DAPC (low-dose, 400 mg/kg per day; high-dose, 800 mg/kg per day, intraperitoneal injection [i.p.]) or captopril (50 mg/kg per day, i.p.) were given to rats for 3 weeks post AAC-surgery. Primary neonatal rat ventricular myocytes (NRVMs) isolated from 1-to 2-day-old SD rats were CH induced by phenylephrine (PE, 50 μ M) with or without DAPC (low-dose, 4 mg/mL; high-dose, 8 mg/mL) or captopril (10 μ M). Myocardial hypertrophy was identified by the heart weight index. Left ventricle remodeling and fibrosis of hypertrophic rats were evaluated by hematoxylin and eosin (H&E) staining, Mason staining, and Wheat germ agglutinin (WGA) staining. Using quantitative real-time PCR to examine the expressions of hypertrophic markers and inflammatory cytokines at mRNA levels. Additionally, protein expression of the Akt/mTOR and NF-κB signaling pathways were evaluated by western blot assay. Results: DAPC markedly decreased heart weight index and improved pathological morphology of the myocardium in AAC-induced rats. Of note, DAPC inhibits hypertrophic biomarkers ANP and BNP in vivo and in vitro. Meanwhile, the levels of IL-1β, IL-6, and TNF-α were decreased. Interestingly, DAPC inhibited the activation of Akt/mTOR and NF-κB proteins, which were in line with the in vitro findings.Conclusion: DAPC treatment in rats with PO-induced CH prevented cardiac fibrosis and had anti-inflammatory effects via regulation of the Akt/mTOR and NF-κB pathways.
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