Urine proteomic analysis in cystinuric children with renal stones

Effect of urine alkalization on urinary inflammatory markers in cystinuric patients

Background

Cystinuria is associated with a high prevalence of chronic kidney disease (CKD). We previously described a urinary inflammatory-protein signature (UIS), including 38 upregulated proteins, in cystinuric patients (Cys-patients), compared with healthy controls (HC). This UIS was higher in Cys-patients with CKD. In the present observational study, we aimed to investigate the UIS in Cys-patients without CKD and patients with calcium nephrolithiasis (Lith-patients), versus HC and the effect of urine alkalization on the UIS of Cys-patients.

Methods

UIS was evaluated by nano-liquid chromatography coupled to high-resolution mass spectrometry in adult HC, Lith-patients and non-treated Cys-patients with an estimated glomerular filtration rate >60 mL/min/1.73 m2, and after a 3-month conventional alkalizing treatment in Cys-patients.

Results

Twenty-one Cys-patients [12 men, median age (interquartile range) 30.0 (25.0-44.0) years], 12 Lith-patients [8 men, 46.2 (39.5-54.2) years] and 7 HC [2 men, 43.1 (31.0-53.9) years] were included. Among the 38 proteins upregulated in our previous work, 11 proteins were also upregulated in Cys-patients compared with HC in this study (5 circulating inflammatory proteins and 6 neutrophil-derived proteins). This UIS was also found in some Lith-patients. Using this UIS, we identified two subclusters of Cys-patients (5 with a very high/high UIS and 16 with a moderate/low UIS). In the Cys-patients with very high/high UIS, urine alkalization induced a significant decrease in urinary neutrophil-derived proteins.

Conclusion

A high UIS is present in some Cys-patients without CKD and decreases under alkalizing treatment. This UIS could be a prognostic marker to predict the evolution towards CKD in cystinuria.

Protein network analysis and functional enrichment via computational biotechnology unravel molecular and pathogenic mechanisms of kidney stone disease

Mass spectrometry-based proteomics has been extensively applied to current biomedical research. From such large-scale identification of proteins, several computational tools have been developed for determining protein-protein interactions (PPI) network and functional significance of the identified proteins and their complex. Analyses of PPI network and functional enrichment have been widely applied to various fields of biomedical research. Herein, we summarize commonly used tools for PPI network analysis and functional enrichment in kidney stone research and discuss their applications to kidney stone disease (KSD). Such computational approach has been used mainly to investigate PPI networks and functional significance of the proteins derived from urine of patients with kidney stone (stone formers), stone matrix, Randall's plaque, renal papilla, renal tubular cells, mitochondria and immune cells. The data obtained from computational biotechnology leads to experimental validation and investigations that offer new knowledge on kidney stone formation processes. Moreover, the computational approach may also lead to defining new therapeutic targets and preventive strategies for better outcome in KSD management.

Proteomics in Inherited Metabolic Disorders

Inherited metabolic disorders (IMD) are rare medical conditions caused by genetic defects that interfere with the body's metabolism. The clinical phenotype is highly variable and can present at any age, although it more often manifests in childhood. The number of treatable IMDs has increased in recent years, making early diagnosis and a better understanding of the natural history of the disease more important than ever. In this review, we discuss the main challenges faced in applying proteomics to the study of IMDs, and the key advances achieved in this field using tandem mass spectrometry (MS/MS). This technology enables the analysis of large numbers of proteins in different body fluids (serum, plasma, urine, saliva, tears) with a single analysis of each sample, and can even be applied to dried samples. MS/MS has thus emerged as the tool of choice for proteome characterization and has provided new insights into many diseases and biological systems. In the last 10 years, sequential window acquisition of all theoretical fragmentation spectra mass spectrometry (SWATH-MS) has emerged as an accurate, high-resolution technique for the identification and quantification of proteins differentially expressed between healthy controls and IMD patients. Proteomics is a particularly promising approach to help obtain more information on rare genetic diseases, including identification of biomarkers to aid early diagnosis and better understanding of the underlying pathophysiology to guide the development of new therapies. Here, we summarize new and emerging proteomic technologies and discuss current uses and limitations of this approach to identify and quantify proteins. Moreover, we describe the use of proteomics to identify the mechanisms regulating complex IMD phenotypes; an area of research essential to better understand these rare disorders and many other human diseases.

Comprehensive proteomic quantification of bladder stone progression in a cystinuric mouse model using data-independent acquisitions

Cystinuria is one of various disorders that cause biomineralization in the urinary system, including bladder stone formation in humans. It is most prevalent in children and adolescents and more aggressive in males. There is no cure, and only limited disease management techniques help to solubilize the stones. Recurrence, even after treatment, occurs frequently. Other than a buildup of cystine, little is known about factors involved in the formation, expansion, and recurrence of these stones. This study sought to define the growth of bladder stones, guided by micro-computed tomography imaging, and to profile dynamic stone proteome changes in a cystinuria mouse model. After bladder stones developed in vivo, they were harvested and separated into four developmental stages (sand, small, medium and large stone), based on their size. Data-dependent and data-independent acquisitions allowed deep profiling of stone proteomics. The proteomic signatures and pathways illustrated major changes as the stones grew. Stones initiate from a small nidus, grow outward, and show major enrichment in ribosomal proteins and factors related to coagulation and platelet degranulation, suggesting a major dysregulation in specific pathways that can be targeted for new therapeutic options.

A polymorphism in the 3'-untranslated region of the matrix metallopeptidase 9 gene is associated with susceptibility to idiopathic calcium nephrolithiasis in the Chinese population

Objective

To investigate whether single nucleotide polymorphisms (SNPs) in the 3′ untranslated region (UTR) of the matrix metallopeptidase 9 gene (MMP9) are associated with susceptibility to calcium oxalate stones.

Methods

A total of 428 patients with kidney stone disease (KSD) and 450 control individuals were enrolled. Three MMP9 SNPs (rs20544, rs9509, and rs1056628) were genotyped, and MMP9 mRNA and protein expression was determined in patients and controls. The dual luciferase reporter gene assay was conducted by transfecting HEK293 cells with miR-491-5p mimics and plasmids containing MMP9 with rs1056628 AA/CC genotypes.

Results

The rs1056628 CC genotype was significantly increased in KSD patients compared with controls (CC vs AA: odds ratio [OR] = 2.279, 95% confidence interval [CI] = 1.048–4.956). The rs1056628 C allele frequency was higher in KSD patients than controls. The increased KSD risks associated with rs1056628 were more evident in individuals aged <30 years (OR = 3.504, 95% CI = 1.102–11.139) and men (OR = 2.522, 95% CI = 1.004–6.334). mRNA and protein levels of MMP9 were significantly higher in KSD patients with the CC genotype than in those with the AA genotype.

Conclusion

This study demonstrates that MMP9 SNP rs1056628 is associated with a significant KSD risk in Chinese Han individuals.

Mini-encyclopaedia of the wound healing - Opportunities for integrating multi-omic approaches into medical practice

Wound healing is a highly complex life-important repair process triggered by plenty of local and/or systemic organ and tissue damaging events, such as an acute surgical invasion, accidental organ and tissue damages, acute and chronic diseases, aggressive local and systemic therapeutic approaches (e.g. irradiation and systemic chemotherapy). Individual health condition determines over the quality of wound healing. Impaired wound healing, in turn, may lead, for example, to post-surgical complications frequently observed in elderly, chronic ulcers in diabetic patients, hindered and ineffective pain management, etc. However, these well-acknowledged examples are just the tip of the iceberg. The entire spectrum of potential consequences is much broader. Therefore, all the aspects of wound healing need to receive a dedicated attention of many specialised medical fields and healthcare as a whole. In contrast, there is still strongly limited knowledge collected regarding the molecular and cellular mechanisms underlying the physiological versus impaired wound healing. The contents of this article might be of great importance for multi-professional considerations as well as for the experts working in specific fields such as clinical proteomics, general practice, laboratory medicine, surgery including plastic surgery and aesthetic medicine, gerontology, psychology, diabetology, endocrinology, oncology, cardiovascular disease, radiology, and healthcare economy.

SIGNIFICANCE

The contents of this article are strongly motivated by the particular value of wound healing quality for medical care and might be of great importance for multi-professional considerations and experts working in specialised fields: predictive and preventive medicine, general practitioners, laboratory medicine, surgery including plastic surgery and aesthetic medicine, gerontology, psychology, diabetology, endocrinology, oncology, cardiovascular disease, radiology, and healthcare economy. The article is aiming at both educational and scientific purposes: on one side it summarises comprehensive information available regarding wound healing mechanisms and molecular pathways involved. On the other side the article provides highly innovative hypotheses for multi-professional considerations relevant for several research fields which may potentially advance medical services in the close future such as clinical proteomics and multi-omics.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.