Proteomic signature of tubulointerstitial tissue predicts prognosis in IgAN

The current use of proteomics and metabolomics in glomerulonephritis: a systematic literature review

BACKGROUND

Glomerulonephritis inherently leads to the development of chronic kidney disease. It is the second most common diagnosis in patients requiring renal replacement therapy in the United Kingdom. Metabolomics and proteomics can characterise, identify and quantify an individual's protein and metabolite make-up. These techniques have been optimised and can be performed on samples including kidney tissue, blood and urine. Utilising omic techniques in nephrology can uncover disease pathophysiology and transform the diagnostics and treatment options for glomerulonephritis.

OBJECTIVES

To evaluate the utility of metabolomics and proteomics using mass spectrometry and nuclear magnetic resonance in glomerulonephritis.

METHODS

The systematic review was registered on PROSPERO (CRD42023442092). Standard and extensive Cochrane search methods were used. The latest search date was March 2023. Participants were of any age with a histological diagnosis of glomerulonephritis. Descriptive analysis was performed, and data presented in tabular form. An area under the curve or p-value was presented for potential biomarkers discovered.

RESULTS

Twenty-seven studies were included (metabolomics (n = 9)), and (proteomics (n = 18)) with 1818 participants. The samples analysed were urine (n = 19) blood (n = 4) and biopsy (n = 6). The typical outcome themes were potential biomarkers, disease phenotype, risk of progression and treatment response.

CONCLUSION

This review shows the potential of metabolomic and proteomic analysis to discover new disease biomarkers that may influence diagnostics and disease management. Further larger-scale research is required to establish the validity of the study outcomes, including the several proposed biomarkers.

Kidney Disease and Proteomics: A Recent Overview of a Useful Tool for Improving Early Diagnosis

Kidney disease is a critical and potentially life-threatening degenerative condition that poses a significant global public health challenge due to its elevated rates of morbidity and mortality. It manifests primarily in two distinct clinical forms: acute kidney injury (AKI) and chronic kidney disease (CKD). The development of these conditions hinges on a multitude of factors, including the etiological agents and the presence of coexisting medical conditions. Despite disparities in their underlying pathogenic mechanisms, both AKI and CKD can progress to end-stage kidney disease (ESKD). This advanced stage is characterized by organ failure and its associated complications, greatly increasing the risk of mortality. There is an urgent need to delve into the pathogenic mechanisms underlying these diseases and to identify novel biomarkers that can facilitate earlier diagnosis. Such early detection is crucial for enhancing the efficacy of therapy and impeding disease progression. In this context, proteomic approaches have emerged as invaluable tools for uncovering potential new markers of different pathological conditions, including kidney diseases. In this chapter, we overview the recent discoveries achieved through diverse proteomic techniques aimed at identifying novel molecules that may play a pivotal role in kidney diseases such as diabetic kidney disease (DKD), IgA nephropathy (IgAN), CKD of unknown origin (CKDu), autosomal dominant polycystic kidney disease (ADPKD), lupus nephritis (LN), hypertensive nephropathy (HN), and COVID-19-associated acute kidney injury (COVID-AKI).

Identification and validation of glomerulotubular crosstalk genes mediating IgA nephropathy by integrated bioinformatics

Background

IgA nephropathy (IgAN), which has been reported as the most prevalent glomerulonephritis globally, is the major contributor to end-stage renal diseases. This bioinformatics study aimed to explore glomerulotubular crosstalk genes and dysregulated pathways relating to the pathogenesis of IgAN.

Methods

The microarray datasets from the Gene Expression Omnibus (GEO) database were searched. Weighted gene co-expression network analysis (WGCNA) and differentially expressed genes (DEGs) of both glomeruli and tubulointerstitium were conducted individually. The co-expression gene modules of glomeruli and tubulointerstitium were compared via gene function enrichment analysis. Subsequently, the crosstalk co-expression network was constructed via the STRING database and key genes were mined from the crosstalk network. Finally, key genes were validated using another GEO dataset (GSE99340) containing RNA-seq data of IgAN and lupus nephritis, and their potential diagnostic values were shown using receiver operating characteristic (ROC) analysis.

Results

Five hundred eighty-three DEGs and eight modules were identified in glomerular samples, while 272 DEGs and four modules were in tubulointerstitial samples. There were 119 overlapping DEGs between the two groups. Among the distinctive modules, four modules in glomeruli and one module in tubulointerstitium were positively associated with IgAN. While four modules in glomeruli and two modules in tubulointerstitium were negatively associated with IgAN. The top ten key genes screened by CytoHubba were ITGAM, ALB, TYROBP, ITGB2, CYBB, HCK, CSF1R, LAPTM5, FN1, and CTSS. Compared with lupus nephritis, there were significant differences in the expression levels of CYBB, CTSS and TYROBP (P < 0.05), while other key genes showed no significant difference. Meanwhile, CYBB, CTSS, and TYROBP demonstrated possible diagnostic significance.

Conclusions

The crosstalk genes confirmed in this study may provide novel insight into the pathogenesis of IgAN. Immune-related pathways are associated with both glomerular and tubulointerstitial injuries in IgAN. The glomerulotubular crosstalk might perform a role in the pathogenesis of IgAN.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-022-02779-7.