Early disease biomarkers can be found using animal models urine proteomics

Exploring the Effects of Metformin on the Body via the Urine Proteome

Metformin is the first-line medication for treating type 2 diabetes mellitus, with more than 200 million patients taking it daily. Its effects are extensive and play a positive role in multiple areas. Can its effects and potential mechanisms be explored through the urine proteome? In this study, 166 differential proteins were identified following the administration of 150 mg/(kg·d) of metformin to rats for five consecutive days. These included complement component C6, pyruvate kinase, coagulation factor X, growth differentiation factor 15, carboxypeptidase A4, chymotrypsin-like elastase family member 1, and L-lactate dehydrogenase C chain. Several of these proteins have been reported to be directly affected by metformin or associated with its effects. Multiple biological pathways enriched by these differential proteins, or proteins containing differentially modified peptides, have been reported to be associated with metformin, such as the glutathione metabolic process, negative regulation of gluconeogenesis, and the renin-angiotensin system. Additionally, some significantly changed proteins and enriched biological pathways, not yet reported to be associated with metformin's effects, may provide clues for exploring its potential mechanisms. In conclusion, the application of the urine proteome offers a comprehensive and systematic approach to exploring the effects of drugs, providing a new perspective on the study of metformin's mechanisms.

Proteomics of neuropsychiatric disorders

The pathogenesis of neuropsychiatric disorders (NDs) remains largely unclear, hence there is a lack of objective and reliable biomarkers. Proteomics, as a powerful tool for disease biomarkers research, has been largely ignored in the field of NDs. This review summarizes recent research on the application of mass spectrometry-based proteomics in NDs. Proteins associated with NDs have been identified in various sample sources, including blood, urine, saliva, tear, cerebrospinal fluid, and brain tissue. These studies have preliminarily demonstrated the potential of proteomics in NDs and require comprehensive validation in multi-center, large-scale clinical cohorts. We also discuss the challenges and prospects of proteomics in the research of early diagnostic biomarkers for NDs. These findings may provide a foundation for developing proteomic-based diagnostics and advancing precision medicine in NDs.

Urinary Proteome and Exosome Analysis Protocol for the Discovery of Respiratory Diseases Biomarkers

This study aims to develop a protocol for respiratory disease-associated biomarker discovery by combining urine proteome studies with urinary exosome components analysis (i.e., miRNAs). To achieve this, urine was DTT treated to decrease uromodulin, then concentrated and ultracentrifuged. Proteomic analyses of exosome-free urine were performed using LC-MS/MS. Simultaneously, miRNA expression from urine exosomes was measured using either RTqPCR (pre-amplification) or nCounter Nanostring (non-amplication) analyses. We detected 548 different proteins in exosome-free urine samples (N = 5) with high confidence (FDR < 1%), many of them being expressed in different non-renal tissues. Specifically, lung-related proteins were overrepresented (Fold enrichment = 1.31; FDR = 0.0335) compared to whole human proteome, and 10-15% were already described as protein biomarkers for several pulmonary diseases. Urine proteins identified belong to several functional categories important in respiratory pathology. We could confirm the expression of miRNAs previously connected to respiratory diseases (i.e., miR-16-5p, miR-21-5p, miR-146a-5p, and miR-215-5p) in urine exosomes by RTqPCR. Finally, we detected 333 miRNAs using Nanostring, 15 of them up-regulated in T2high asthma (N = 4) compared to T2low asthma (N = 4) and healthy subjects (N = 4). Therefore, this protocol combining the urinary proteome (exosome free) with the study of urinary exosome components (i.e., miRNAs) holds great potential for molecular biomarker discovery of non-renal and particularly respiratory pathologies.

Association Between the Copper-to-Zinc Ratio and Cardiovascular Disease Among Chinese Adults: A China Multi-ethnic Cohort (CMEC) Study

The impact of metal exposure on cardiovascular diseases has become an increasingly concerning topic. To date, few studies have investigated the relationship between the copper-to-zinc ratio and CVD (Cardiovascular disease). This China multi-ethnic cohort study explored the association between the copper-to-zinc ratio and CVD in Chinese adults. The study included a sample size of 9878 people. Logistic regression analysis was used to examine the correlation between urinary copper, urinary zinc, and the copper-to-zinc ratio and CVD prevalence. Restricted cubic spline (RCS) analysis was used to investigate the potential dose-response relationships among copper-to-zinc ratio, urinary copper, urinary zinc, and CVD prevalence. In addition, the least absolute shrinkage and selection operator (LASSO) regression method was used to identify significant risk factors associated with CVD, leading to the development of a nomogram. The predictive performance of the nomogram model for CVD was assessed using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). Compared with the copper-to-zinc ratio in Q1, the copper-to-zinc ratio in Q4 was associated with CVD after adjusting for all potential confounders (Model 3) (Q4, odds ratio [OR] 0.608, 95% confidence interval [CI] 0.416-0.889, P = 0.010). After adjusting for all potential confounders (Model 3), urinary copper levels in Q4 were associated with CVD (Q4, odds ratio [OR] 0.627, 95% confidence interval [CI] 0.436-0.902, P = 0.012). No significant difference was found between urinary zinc levels and CVD. The RCS showed a linear dose-response relationship between the copper-to-zinc ratio and CVD (P for overall = 0.01). The nomogram based on the influencing factors examined with LASSO showed good predictive power, and the AUC was 76.3% (95% CI 73.7-78.9%). Our results suggest that there is a significant linear negative correlation between the copper-to-zinc ratio and CVD in Chinese adults and that it has good predictive value for CVD.

Proteomics approach reveals urinary markers for early pregnancy diagnosis in buffaloes

This study aimed to compare urine proteomics from non- and pregnant buffaloes in order to identify potential biomarkers of early pregnancy. Forty-four females underwent hormonal ovulation synchronization and were randomly divided into two experimental groups: inseminated (n = 30) and non-inseminated (n = 14). The pregnant females were further divided into two groups: pregnant at Day 12 (P12; n = 8) and at Day 18 (P18; n = 8) post-ovulation. The non-pregnant group was also subdivided into two groups: non-pregnant at Day 12 (NP12; n = 7) and at Day 18 (NP18; n = 7). Urine was collected from all females on Days 12 or 18. The samples were processed for proteomics. A total of 798 proteins were reported in the urine considering all groups. The differential proteins play essential roles during pregnancy, acting in cellular transport and metabolism, endometrial remodeling, embryonic protection, and degradation of defective proteins. We suggest that some proteins from our study can be considered biomarkers for early pregnancy diagnosis, since they were increased in pregnant buffaloes. SIGNIFICANCE: Macromolecules have been studied for early pregnancy diagnosis, aiming to increase reproductive efficiency in cattle and buffaloes. Direct methods such as rectal palpation and ultrasonography have been considered late. Thus, this study aimed to compare urine proteomics from non- and pregnant buffaloes to identify potential biomarkers of early pregnancy. The differential proteins found in our study play essential roles during pregnancy, acting in cellular transport and metabolism, endometrial remodeling, embryonic protection, and degradation of defective proteins. We suggest that these proteins can be considered possible biomarkers for early pregnancy diagnosis since they were increased in the pregnant buffaloes.

Proteomic advance of ischemic stroke: preclinical, clinical, and intervention

Ischemic stroke (IS) is the most common type of stroke and is characterized by high rates of mortality and long-term injury. The prediction and early diagnosis of IS are therefore crucial for optimal clinical intervention. Proteomics has provided important techniques for exploring protein markers associated with IS, but there has been no systematic evaluation and review of research that has used these techniques. Here, we review the differential proteins that have been found in cell- and animal- based studies and clinical trials of IS in the past 10 years; determine the key pathological proteins that have been identified in clinical trials; summarize the target proteins affected by interventions aimed at treating IS, with a focus on traditional Chinese medicine treatments. Overall, we clarify findings and problems that have been identified in recent proteomics research on IS and provide suggestions for improvements in this area. We also suggest areas that could be explored for determining the pathogenesis and developing interventions for IS.

Progress in the Diagnostic and Predictive Evaluation of Crush Syndrome

Crush syndrome (CS), also known as traumatic rhabdomyolysis, is a syndrome with a wide clinical spectrum; it is caused by external compression, which often occurs in earthquakes, wars, and traffic accidents, especially in large-scale disasters. Crush syndrome is the second leading cause of death after direct trauma in earthquakes. A series of clinical complications caused by crush syndrome, including hyperkalemia, myoglobinuria, and, in particular, acute kidney injury (AKI), is the main cause of death in crush syndrome. The early diagnosis of crush syndrome, the correct evaluation of its severity, and accurate predictions of a poor prognosis can provide personalized suggestions for rescuers to carry out early treatments and reduce mortality. This review summarizes various methods for the diagnostic and predictive evaluation of crush syndrome, including urine dipstick tests for a large number of victims, traditional and emerging biomarkers, imaging-assisted diagnostic methods, and developed evaluation models, with the aim of providing materials for scholars in this research field.

Blood- and Urine-Based Liquid Biopsy for Early-Stage Cancer Investigation: Taken Clear Renal Cell Carcinoma as a Model

Liquid biopsy is a noninvasive technique that can provide valuable information for disease characterization by using biofluids as a source of biomarkers. Proteins found in biofluids can offer a wealth of information for understanding pathological processes. In this study, we used early-stage clear cell renal cell carcinoma (ccRCC) as a model to explore the proteomic relationships among tissue, plasma, and urine. We analyzed samples of tumor tissue, plasma, and urine from a cohort of 27 ccRCC patients with T1-2 stage and 27 matched healthy controls, using liquid chromatography-mass spectrometry (LC-MS) for proteomic analysis. We integrated the differential proteins found in the three types of samples to explore ccRCC-associated molecular changes. Our results showed that both plasma and urine proteomes could reflect functional changes in tumor tissue. In plasma, cytoskeletal proteins and metabolic enzymes were differentially expressed, while in urine, adhesion molecules and defense proteins showed differential levels. The differential proteins found in plasma and urine both reflect the binding and catalytic activity of tumor tissue. Additionally, proteins only changed in biofluids could reflect body immune response changes, with plasma proteins involved in actin cytoskeleton and oxidative stress, and urine proteins involved in granulocyte adhesion and leukocyte extravasation signaling. Plasma and urine proteins could effectively distinguish RCC from control, with good performances (plasma/urine: 92.6%/92.6% specificity, 96.3%/92.6% sensitivity, and an area under the curve of 0.981/0.97). In conclusion, biofluids could not only reflect functional changes in tumor tissue but also reflect changes in the body's immune response. These findings will benefit the understanding of body biomarkers in tumors and the discovery of potential disease biomarkers.

Comparison of urine proteomes from tumor-bearing mice with those from tumor-resected mice

Objective

This study aimed to address on the most important concern of surgeons-whether to completely resect tumor. Urine can indicate early changes associated with physiological or pathophysiological processes. Based on these ideas, we conducted experiments to explore changes in the urine proteome between tumor-bearing mice and tumor-resected mice.

Method

The tumor-bearing mouse model was established with MC38 mouse colon cancer cells, and the mice were divided into the control group, tumor-resected group, and tumor-bearing group. Urine was collected 7 and 30 days after tumor resection. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was used to identify the urine proteome, which was analyzed for differentially expressed proteins and functional annotation.

Results

(1) Seven days after tumor resection, 20 differentially expressed proteins distinguished the tumor-resected group and the tumor-bearing group. The identified biological processes included circadian rhythm, Notch signaling pathway, leukocyte cell-cell adhesion, and heterophilic cell-cell adhesion via plasma membrane cell adhesion molecules. (2) Thirty days after tumor resection, 33 differentially expressed proteins distinguished the tumor-resected group and the tumor-bearing group. The identified biological processes included cell adhesion; complement activation, the alternative pathway; the immune system process; and angiogenesis. (3) The difference in the urine proteome between the tumor-resected group and the healthy control group was smaller 30 days after tumor resection.

Conclusion

Changes in the urinary proteome can reflect the complete resection of MC38 tumors.

Mass Spectrometry-Based Proteomics for Biomarker Discovery

Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.

Complexity of skeletal muscle degeneration: multi-systems pathophysiology and organ crosstalk in dystrophinopathy

Duchenne muscular dystrophy is a highly progressive muscle wasting disorder due to primary abnormalities in one of the largest genes in the human genome, the DMD gene, which encodes various tissue-specific isoforms of the protein dystrophin. Although dystrophinopathies are classified as primary neuromuscular disorders, the body-wide abnormalities that are associated with this disorder and the occurrence of organ crosstalk suggest that a multi-systems pathophysiological view should be taken for a better overall understanding of the complex aetiology of X-linked muscular dystrophy. This article reviews the molecular and cellular effects of deficiency in dystrophin isoforms in relation to voluntary striated muscles, the cardio-respiratory system, the kidney, the liver, the gastrointestinal tract, the nervous system and the immune system. Based on the establishment of comprehensive biomarker signatures of X-linked muscular dystrophy using large-scale screening of both patient specimens and genetic animal models, this article also discusses the potential usefulness of novel disease markers for more inclusive approaches to differential diagnosis, prognosis and therapy monitoring that also take into account multi-systems aspects of dystrophinopathy. Current therapeutic approaches to combat muscular dystrophy are summarised.