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Proteomics Applications in Renal Diseases

Renal diseases, commonly referred to as kidney diseases, encompass a diverse range of medical conditions affecting the structure and function of the kidneys. The kidneys, vital organs in the human body, play a crucial role in maintaining fluid balance, electrolyte concentrations, and the elimination of waste products. Renal diseases can arise from various factors, including genetic predisposition, infections, autoimmune disorders, and chronic conditions.

Types of Renal Diseases

  • Chronic Kidney Disease (CKD): CKD is a progressive and irreversible condition characterized by the gradual loss of kidney function over time. It often develops silently and can result from hypertension, diabetes, or other underlying health issues.
  • Glomerulonephritis: This inflammatory condition affects the glomeruli, the filtering units of the kidneys. Glomerulonephritis can be acute or chronic, leading to impaired filtration and potential kidney damage.
  • Renal Fibrosis: Excessive scarring of renal tissue, known as fibrosis, can occur in response to prolonged inflammation or injury. Renal fibrosis can contribute to a decline in kidney function and is a common feature in various renal diseases.
  • Polycystic Kidney Disease (PKD): PKD is a genetic disorder characterized by the formation of fluid-filled cysts within the kidneys. These cysts can gradually enlarge, impacting kidney function and structure.

Proteomics, the scientific study of protein interactions and functions, utilizes analyses of protein-level changes within the body to extract a plethora of biological information. Whether in disease prediction or treatment, this biological information plays a crucial role. Consequently, an increasing number of scholars are integrating proteomics with medicine to explore the onset and progression of diseases and to discover new biomarkers.

Blood undergoes filtration, reabsorption, and secretion in the kidneys, culminating in the formation of the ultimate metabolic byproduct – urine. Both blood and urine contain abundant biological information that can reflect the body's metabolic status. Kidney diseases are intricately linked to metabolic disorders.

Overview of the main strategies employed in proteomic studiesOverview of the main strategies employed in proteomic studies (Smith et al., 2009)

Proteomics in Renal Research

Comprehensive Analysis of Renal Proteome

Proteomics, utilizing advanced mass spectrometry techniques, enables a comprehensive analysis of the protein composition within renal tissues. This approach provides researchers with the ability to identify and characterize specific proteins associated with normal kidney function and various renal diseases.

Discovery and Validation of Biomarkers

A significant breakthrough facilitated by proteomics in renal research is the discovery of potential biomarkers. Analyzing the protein composition in biological samples such as urine and blood allows researchers to discover biomarkers associated with renal dysfunction. These biomarkers aid in early diagnosis and offer insights into disease progression and treatment response.

Study of Protein Modifications and Interaction Networks

Proteomics not only identifies the basic composition of proteins but also reveals post-translational modifications and interaction networks. This is crucial for understanding the molecular mechanisms of renal diseases. For example, analyzing modifications like phosphorylation and methylation helps identify key proteins involved in the development of renal diseases.

Drug Discovery and Target Identification

Proteomics contributes to drug discovery for renal diseases by unraveling intricate molecular pathways. Understanding the protein networks involved in renal pathologies allows researchers to identify novel therapeutic targets. This precision approach holds promise for developing more effective and personalized treatments for renal diseases.

Application of Proteomics in Chronic Kidney Disease CKD

Proteomics, the scientific study of protein interactions and functions, utilizes analyses of protein-level changes within the body to extract a plethora of biological information. Whether in disease prediction or treatment, this biological information plays a crucial role. Consequently, an increasing number of scholars are integrating proteomics with medicine to explore the onset and progression of diseases and to discover new biomarkers.

Blood undergoes filtration, reabsorption, and secretion in the kidneys, culminating in the formation of the ultimate metabolic byproduct – urine. Both blood and urine contain abundant biological information that can reflect the body's metabolic status. Kidney diseases are intricately linked to metabolic disorders.

Application of Proteomics in Renal Cell Carcinoma

Renal cell carcinoma (RCC), commonly known as kidney cancer, is a malignant tumor originating from the renal tubular epithelial system. As of now, specific biomarkers for RCC have not been identified. High-throughput proteomics techniques in the tumor domain primarily involve uncovering the mechanisms of tumor initiation and progression, identifying biomarkers, and discovering new therapeutic targets.

Research utilizing protein chip technology screened differentially expressed proteins in the peripheral blood serum of RCC patients. It revealed significantly lower levels of Rich-2 protein in RCC patients compared to non-RCC patients. This protein is inhibited by molecules associated with RCC but shows an increase in expression levels after tumor load reduction following surgical treatment. The subsequent rise, however, becomes statistically insignificant three months post-operation, indicating a correlation rather than certainty with postoperative RCC patients. Using iTRAQ and LC-MS/MS technologies, a study identified the overexpression of heat shock protein 70 family member HISC71 in serum proteins, with 16 upregulated and 14 downregulated proteins in RCC.

Moreover, tumor cell cycle-related protein (CREPT) in RCC tissues localizes to the cell nucleus. Immunohistochemistry and clinical pathology data analysis demonstrated that CREPT is associated with RCC TNM staging (T for primary tumor, N for regional lymph nodes, M for distant metastasis) and Fuhrman grading (degree of cancer cell differentiation, including well-differentiated, moderately differentiated, poorly differentiated, and undifferentiated). Higher expression levels of CREPT in RCC tissues indicate later clinical staging and higher Fuhrman grading in patients.

Application of Proteomics in Kidney Injury

Renal injury refers to damage to the kidneys, with complications including uncontrollable bleeding, extrusion of urine, abscess formation, and high blood pressure. Acute kidney injury (AKI) is a common clinical condition with a high risk of mortality. In women of childbearing age, pregnancy is a major cause of AKI and can lead to secondary chronic kidney disease.

Contrast-induced acute kidney injury (CIAKI) results from the direct toxic effects of contrast agents on renal tubular cells and their damaging impact on the generation of oxygen free radicals. Proteomic changes in the serum protein profile, induced by contrast agent administration, have significant implications for screening biomarkers of contrast-induced AKI. Various methods can be employed to collect patient proteins, with urine collection being the most common. Urinary components can reflect the function of the urinary system, and specific proteins rapidly enter the urine after blood circulation through the kidneys. Compared to blood proteomics, urinary proteomics offers advantages such as simplicity, non-invasiveness, and the ability to obtain a large, continuous volume.

The quantity and composition of excreted proteins in urine are essential indicators reflecting kidney function and disease status. Patients with renal injury diseases exhibit differences in urine composition compared to normal individuals, including increased urinary protein when renal injury occurs. Additionally, changes in protein components in urine may carry information related to renal injury. Four classes of urinary biomarkers (urinary N-acetyl-beta-D-glucosaminidase, hepatic-type urinary fatty acid-binding protein, urinary fructoseamine 61, urinary fetuin A) improve the diagnosis of AKI. Proteomic techniques such as SELDI-TOF-MS and two-dimensional gel electrophoresis have identified upregulation of Apolipoprotein E protein in patients with more than threefold persistent expression after contrast agent use, making it a potential new diagnostic marker for CIAKI. SGLT-2 inhibitors can inhibit glucose reabsorption in the kidneys, increasing glucose excretion in urine, thereby achieving hypoglycemic effects. SGIT-2 inhibitors can also inhibit Na+ reabsorption, leading to increased Na+ concentration at the macula densa, promoting ATP metabolism and breakdown into adenosine. Adenosine binding to receptors at the afferent arteriole causes constriction, reducing renal blood flow and lowering glomerular pressure, thus protecting renal function.

Reference

  1. Smith, Matthew P. Welberry, et al. "Application of proteomic analysis to the study of renal diseases." Nature Reviews Nephrology 5.12 (2009): 701-712.
* For Research Use Only. Not for use in diagnostic procedures.
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