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Diabetic kidney disease (DKD) is a major microvascular complication of type 2 diabetes mellitus (T2DM). Monitoring the early diagnostic period and disease progression plays a crucial role in treating DKD. In this study, to comprehensively elucidate the molecular characteristics of urinary proteins and urinary exosome proteins in type 2 DKD, we performed large-scale urinary proteomics ( n =144) and urinary exosome proteomics ( n =44) analyses on T2DM patients with albuminuria in varying degrees. The dynamics analysis of the urinary and exosome proteomes in our study provides a valuable resource for discovering potential urinary biomarkers in patients with DKD. A series of potential biomarkers, such as SERPINA1 and transferrin (TF), were detected and validated to be used for DKD diagnosis or disease monitoring. The results of our study comprehensively elucidated the changes in the urinary proteome and revealed several potential biomarkers reflecting the progression of DKD, which provide a reference for DKD biomarker screening.

The prevalence of Parkinson's disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive, and non‐invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)‐based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non‐carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone were sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP, and other PD‐associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD. Synopsis This study presents a scalable, sensitive and reproducible mass spectrometry‐based proteomics workflow for urinary proteome profiling, and demonstrates it as a promising strategy for urine biomarker discovery for Parkinson’s disease (PD). The presented workflow allows quantification of more than 2,000 proteins in urine. Lysosomal dysregulation is reflected in the urinary proteomes of individuals with the pathogenic LRRK2 G2019S mutation. Machine learning on the urinary proteome classifies LRRK2 mutation and PD disease states with sensitivities of 78% and 74% and specificities of 73% and 84%, respectively. The neurotrophic factor VGF was identified as the most important feature to discriminate manifesting from non‐manifesting LRRK2 G2019S carriers. Graphical Abstract This study presents a scalable, sensitive and reproducible mass spectrometry‐based proteomics workflow for urinary proteome profiling, and demonstrates it as a promising strategy for urine biomarker discovery for Parkinson’s disease (PD).

It is widely accepted that circadian rhythm disruption caused short- or long-term adverse effects on health. Although many previous studies have focused on exploration of the molecular mechanisms, there is no rapid, convenient, and non-invasive method to reveal the influence on health after circadian rhythm disruption. Here, we performed a high-resolution mass spectrometry-based data-independent acquisition (DIA) quantitative urinary proteomic approach in order to explore whether urine could reveal stress changes to those brought about by circadian rhythm disruption after sleep deprivation. After sleep deprivation, the subjects showed a significant increase in both systolic and diastolic blood pressure compared with routine sleep. More than 2000 proteins were quantified and they contained specific proteins for various organs throughout the body. And a total of 177 significantly up-regulated proteins and 68 significantly down-regulated proteins were obtained after sleep deprivation. These differentially expressed proteins (DEPs) were associated with multiple organs and pathways, which reflected widespread influences of sleep deprivation. Besides, machine learning identified a panel of five DEPs (CD300A, SCAMP3, TXN2, EFEMP1, and MYH11) that can effectively discriminate circadian rhythm disruption. Taken together, our results validate the value of urinary proteome in predicting and diagnosing the changes by circadian rhythm disruption.

PurposeT1 bladder cancer is known for its high progression and recurrence rates. Identifying aggressive tumours at the non-muscle-invasive stage is crucial to allow early interventions and subsequently increase patient survival. This study aimed to investigate the potential of the cubilin/myeloperoxidase (CUBN/MPO) ratio as a high-grade T1 bladder cancer biomarker.MethodsUrine samples were collected from 30 patients who underwent transurethral resection of the tumour with high-grade T1 bladder cancer (June 2015 to December 2019) before surgery. The urinary proteome was analysed using high-resolution mass spectrometry and the CUBN/MPO ratio was calculated. The primary outcome was the recurrence during the follow-up (around 31.5 months after resection). Univariate Cox regression and Kaplan–Meier curves were used for data analysis.ResultsPatients with a low CUBN/MPO ratio exhibited upregulated MPO and/or downregulated CUBN. This group of patients had a higher incidence of disease recurrence and progression. Low CUBN/MPO ratio was significantly associated with a higher likelihood of recurrence, progression, and death. It is worth noting that this study was exploratory and conducted on a small sample size, so further research is needed to validate these findings in larger cohorts.ConclusionThis study highlights the potential of the CUBN/MPO ratio as a prognostic biomarker for high-grade T1 bladder cancer.

Background Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory airway disease caused by inhalation of cigarette smoke (CS) and other harmful gases and particles. Methods This study aimed to explore potential urinary biomarkers for CS-induced COPD based on LC–MS/MS analysis. Results A total of 340 urinary proteins were identified, of which 79 were significantly changed (30, 31, and 37 at week 2, 4 and 8, respectively). GO annotation of the differential urinary proteins revealed that acute-phase response, response to organic cyclic compounds, complement activation classical pathway, and response to lead ion were significantly enriched at week 2 and 4. Another four processes were only enriched at week 8, namely response to oxidative stress, positive regulation of cell proliferation, thyroid hormone generation, and positive regulation of apoptotic process. The PPI network indicated that these differential proteins were biologically connected in CS-exposed rats. Of the 79 differential proteins in CS-exposed rats, 56 had human orthologs. Seven proteins that had changed at week 2 and 4 when there were no changes of pulmonary function and pathological morphology were verified as potential biomarkers for early screening of CS-induced COPD by proteomic analysis. Another six proteins that changed at week 8 when obvious airflow obstruction was detected were verified as potential biomarkers for prognostic assessment of CS-induced COPD. Conclusions These results reveal that the urinary proteome could sensitively reflect pathological changes in CS-exposed rats, and provide valuable clues for exploring COPD biomarkers.

Introduction and hypothesisPrevious studies have indicated a hereditary component of stress urinary incontinence; however, evidence on candidate genes or single-nucleotide polymorphisms (SNPs) is scarce. We hypothesize a genetic association of female stress urinary incontinence based on significant differences of the urinary and serum proteomic pattern in the identical study population.MethodsCase-control study of 19 patients and 19 controls. We searched for known SNPs of SUI candidate genes (COL1A1, MMP1, SERPINA5, UMOD) in the database of short genetic variations and PubMed. Genomic DNA was isolated using QIAamp DNA Blood Midi Kit (Qiagen). We performed Sanger sequencing of selected exons and introns.ResultsThe rs885786 SNP of the SERPINA5 gene was identified in 15 cases and 10 controls (p = 0.09). The rs6113 SNP of the SERPINA5 gene was present in 4 controls compared to 0 cases (p = 0.105). The rs4293393, rs13333226 and rs13335818 SNPs of the UMOD gene were identified in five cases and two controls (p = 0.20), the rs1800012 SNP of the COL1A1 gene in five cases versus four controls (p = 0.24) and the homozygous rs1799750 SNP of the MMP1 gene in eight cases versus five controls (p = 0.18). The combination of the rs885786 SNP of the SERPINA5 gene and rs179970 SNP of the MMP1 gene was detected in ten cases versus five controls (p = 0.072).ConclusionsWe found nonsignificant trends toward associations of SNPs on the SERPINA5, UMOD and MMP1 gene and SUI.

Pregnancy involves a significant number of physiological changes. A normal pregnancy is essential to ensure healthy maternal and fetal development. We sought to explore whether the urinary proteome could reflect the pregnancy process. Urine samples were collected from pregnant and control rats on various gestational days. The urinary proteome was profiled by liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS), and differential proteins were obtained by comparing to the gestational day 1 of the same group at each time point. Many pathways related to embryo implantation and trophoblast differentiation were enriched in the early days in urine. Liver, kidney, and bone development started early to be enriched in the pregnant group, but not in the control group. Interestingly, the developmental processes of the fetal heart such as heart looping and endocardial cushion formation could be seen in urine of pregnant rats. Moreover, the timings were consistent with those of embryological studies. The timing of the surfactant appearance in urine was right before birth. The differential proteins related to pancreas development appeared in urine at the time during reported time of pancreatic cell proliferation and differentiation. These processes were enriched only in the pregnant group and not in the control group. Furthermore, coagulation-associated pathways were found to be increasingly prominent before labor. Our results indicated that the urine proteome of pregnant rats can reflect the process of pregnancy, even fetal embryonic development. Maternal urinary proteome detection was earlier than the developmental time point of tissue sections observed by microscopy.

The aim of the present study was to investigate the effects of exercise during canicross competition on urinary biochemical parameters and urinary proteins. Our results showed that, among the parameters analysed in routine urinalysis, pH was affected by exercise and albuminuria also showed changes immediately after physical exercise with a return to baseline within 2 h after the physical activity. In particular, SDS-PAGE electrophoresis allowed the separation of the urinary proteins on the basis of their molecular mass allowing a qualitative evaluation of the urinary proteome and a quantitative analysis of urine albumin and uromodulin, with a significant increase in urinary albumin and a decrease in uromodulin after exercise. In this study, urine was collected by spontaneous voiding and the use of this non-invasive sampling method proved useful in obtaining information on the health of the animals in the immediate moments before and after the competition without increasing the stress of the animals involved in the competition by any visits or invasive manipulations by veterinarians.

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) may increase the mortality and incidence rates of chronic kidney disease in critically ill patients. This study aimed to investigate the underlying correlations between urinary proteomic changes and CSA-AKI. Methods: Nontargeted proteomics was performed using nano liquid chromatography coupled with Orbitrap Exploris mass spectrometry (MS) on urinary samples preoperatively and postoperatively collected from patients with CSA-AKI. Gemini C18 silica microspheres were used to separate and enrich trypsin-hydrolysed peptides under basic mobile phase conditions. Differential analysis was conducted to screen out urinary differential expressed proteins (DEPs) among patients with CSA-AKI for bioinformatics. Kyoto Encyclopedia of Genes and Genomes (KEGG) database analysis was adopted to identify the altered signal pathways associated with CSA-AKI. Results: Approximately 2000 urinary proteins were identified and quantified through data-independent acquisition MS, and 324 DEPs associated with AKI were screened by univariate statistics. According to KEGG enrichment analysis, the signal pathway of protein processing in the endoplasmic reticulum was enriched as the most up-regulated DEPs, and cell adhesion molecules were enriched as the most down-regulated DEPs. In protein–protein interaction analysis, the three hub targets in the up-regulated DEPs were α-1-antitrypsin, β-2-microglobulin and angiotensinogen, and the three key down-regulated DEPs were growth arrest-specific protein 6, matrix metalloproteinase-9 and urokinase-type plasminogen activator. Conclusion: Urinary protein disorder was observed in CSA-AKI due to ischaemia and reperfusion. The application of Gemini C18 silica microspheres can improve the protein identification rate to obtain highly valuable resources for the urinary DEPs of AKI. This work provides valuable knowledge about urinary proteome biomarkers and essential resources for further research on AKI.

BackgroundPosterior urethral valves (PUVs) account for 17% of pediatric renal failure. The management of pregnancies involving fetuses with PUV is hampered by the fact that current clinical parameters obtained from fetal ultrasound and/or fetal urine biochemistry are insufficient to predict postnatal renal function. We previously have developed a fetal urine peptide signature (12PUV) that predicted with high precision postnatal renal failure at 2 years of age in fetuses with PUV. Here, we evaluated the accuracy of this signature to predict postnatal renal outcome in fetuses with PUV in an independent single-center study.MethodsThirty-three women carrying fetuses with suspected PUV were included. Twenty-five fetuses received vesicoamniotic shunts during pregnancy. PUV was confirmed postnatally in 23 patients. Of those 23 fetuses, 2 were lost in follow-up. Four and 3 patients died in the pre- and perinatal periods, respectively. Follow-up renal function at 6 months of age was obtained for the remaining 14 patients. The primary outcome was early renal failure, defined by an eGFR < 60 mL/min/1.73 m2 before 6 months of age or pre- or perinatal death.ResultsThe peptide signature predicted postnatal renal outcome in postnatally confirmed PUV fetuses with an AUC of 0.94 (95%CI 0.74–1.0) and an accuracy of 90% (95%CI 78–100). The signature predicted postnatal renal outcome for the suspected PUV cases with an AUC of 0.89 (95%CI 0.72–0.97) and an accuracy of 84% (95%CI 71–97).ConclusionsThis single-center study confirms the predictive power of the previously identified 12PUV fetal urinary peptide signature.