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. Graphical

Background: Cardiovascular disease is the leading cause of death in chronic kidney disease populations. The risk of major adverse cardiovascular events (MACE) is greater than that of progression to end-stage kidney disease. An exponential increase in mortality risk is associated with declining kidney function. This study aimed to review the current landscape of traditional and novel blood biomarkers in predicting MACE in ESKD patients. Methods: The systematic review was registered on PROSPERO (CRD42024497403). Standard and extensive Cochrane search methods were used. The latest search date was July 2023. Participants were aged ≥18 years with end-stage kidney disease. Descriptive analysis was performed and data was presented in tabular form. The hazard ratio or odds ratio was presented for potential biomarkers discovered. Results: Overall, 14 studies (4965 participants) were included for analysis; 12 focused on participants requiring haemodialysis and 2 on haemodialysis and peritoneal dialysis. The biomarkers analysed were Troponin I (n = 3), Troponin T (n = 3), B-type natriuretic peptide (n = 2), N-Terminal Pro-Brain-Natriuretic Peptide (n = 7), soluble receptors for advanced glycation end products (n = 2), Galectin 3 (n = 4), and the serum-soluble suppression of tumorigenicity-2 (n = 2). Reported study outcomes included all-cause mortality (n = 11), MACE (n = 5), cardiac specific mortality (n = 6), sudden cardiac death (n = 2), and first cardiovascular event (n = 3). Conclusions: This review outlines the potential role of traditional and novel biomarkers in predicting MACE in end-stage kidney disease. Further larger-scale research is required to establish the validity of the study outcomes to develop new methods of cardiovascular risk prediction in this high-risk population.

Background: Despite its many advantages, haemodialysis (HD) has been shown to be associated with significant cardiovascular events, especially in patients commencing HD. Currently, there is no specific method to risk-stratify incident HD patients. Blood-based biomarkers provide insight into myocardial injury and stress. We aimed to evaluate the association of increased circulating biomarker concentration in incident HD with incident major adverse cardiac events (MACE). Methods: This was a retrospective cohort study of incident haemodialysis cases within 3 months of treatment initiation (≥18 years) from the TriNetX database. Cohorts were grouped by biomarker thresholds: Troponin I: ≥50 ng/L, BNP ≥ 100 pg/mL and 1:1 propensity-score matched for demographic characteristics, baseline cardiovascular risk, laboratory values, and cardiovascular medication. Primary outcome: Incidence of major adverse cardiac events (MACE) censored prior to index event of HD. Secondary outcome: Risk of each individual component of the composite outcome. Cox regression reported hazard ratios (95% CI) for the outcomes. Results: In total, 62,206 and 10,476 patients were included in the troponin I and BNP cohorts, respectively. In the troponin I cohort, 5878 developed MACE (HR 1.33 (95% CI 1.26–1.41, p < 0.0001)). In the BNP cohort, 1050 developed MACE (HR 1.28 (95% CI 1.13–1.44, p < 0.0001)). Conclusions: In incident HD, routine clinical laboratory biomarkers can predict incident MACE. The results suggest the clinical need for CV mortality and morbidity risk profiling in incident HD using a combination of clinical and laboratory variables.

Rationale & objective: Glomerulonephritis (GN) is a leading cause of chronic kidney disease (CKD). Major adverse cardiovascular events (MACE) are prolific in CKD. The risk of MACE in GN cohorts is multifactorial. We investigated the prognostic significance of routine cardiac biomarkers, Troponin I and N-terminal pro-BNP (NT-proBNP) in predicting MACE within 5 years of GN diagnosis. Study Design: Retrospective cohort study. Setting & participants: Data were obtained from TriNetX, a global federated health research network of electronic health records (EHR). Exposure or predictor: Biomarker thresholds: Troponin I: 18 ng/L, NT-proBNP: 400 pg/mL. Outcomes: Primary outcome: Incidence of major adverse cardiovascular events (MACE). Secondary outcome: was the risk for each individual component of the composite outcome. Analytical Approach: 1:1 propensity score matching using logistic regression. Cox proportional hazard models were used to assess the association of cardiac biomarkers with the primary and secondary outcomes, reported as Hazard Ratio (HR) and 95% confidence intervals (CI). Survival analysis was performed which estimates the probability of an outcome over a 5-year follow-up from the index event. Results: Following PSM, 34,974 and 18,218 patients were analysed in the Troponin I and NTproBNP cohorts, respectively. In the Troponin I all cause GN cohort, 3,222 (9%) developed composite MACE outcome HR 1.79; (95% CI, 1.70, 1.88, p < 0.0001). In the NTproBNP GN cohort, 1,686 (9%) developed composite MACE outcome HR 1.99; (95% CI, 1.86, 2.14, p < 0.0001). Limitations: The data are derived from EHR for administrative purposes; therefore, there is the potential for data errors or missing data. Conclusions: In GN, routinely available cardiac biomarkers can predict incident MACE. The results suggest the clinical need for cardiovascular and mortality risk profiling in glomerular disease using a combination of clinical and laboratory variables.

Rationale & Objective: Several trials have shown the nephroprotective and cardiovascular benefits of sodium-glucose cotransporter-2 inhibitors (SGLT2i) among patients with native kidney disease. However, little is known about the safety and efficacy of SGLT2i in kidney transplant. The study aimed to investigate the benefits of SGLT2i in kidney transplant recipients. Methods: Retrospective cohort study utilising data from adult kidney transplant recipients (≥ 18 years) was obtained from TriNetX, a global federated health research network. Cohorts were grouped by receipt of SGLT2i and 1:1 propensity-score matched for demographic characteristics, baseline cardiovascular comorbidities, laboratory data and immunosuppression. Cox regression produced hazard ratios with 95% CI for the outcomes. Outcomes: Primary outcome: incident 5-year death-censored graft failure, rejection, major adverse cardiac events and mortality. Secondary outcomes: known complications of SGLT2i. Results: 4,872 patients (mean age 59.2 years SD 12.2; 63% male). Patients in the SGLT2i cohort had statistically significantly reduced death censored graft failure (HR 0.43, 95% CI 0.37-0.51, p <0.0001), rejection (HR 0.44, 95% CI 0.39-0.50, p <0.0001, major adverse cardiovascular events (HR 0.80, 95% CI 0.70, 0.92, p 0.001) and mortality (HR 0.63 95% CI 0.55-0.72, p <0.017). The cohort identified no significant side effects associated with SGLT2i use. Conclusion: Kidney transplant recipients treated with SGLT2i demonstrated a significant reduction in clinically relevant outcomes. The data suggests that they may have a strong beneficial role in the kidney transplant population.

Equitable access to large sample cohorts for robust, high-throughput proteomics for biomarker discovery is a major barrier to widescale clinical implementation. Dried blood spots (DBS) offer a minimally invasive alternative to venous blood draws, enabling at-home microsampling (<50 µL) for centralised analysis, thus enhancing research participation. This approach is particularly relevant for under-represented groups, including children, the elderly, minority backgrounds and those with long-term health conditions such as chronic kidney disease (CKD), where disease fluctuations may occur outside the clinic, and vein preservation is critical. Proteomic analysis has demonstrated great utility in monitoring disease progression, and for biomarker/therapeutic target discovery. However, liquid chromatography–tandem mass spectrometry (LC–MS/MS) of whole blood is hindered by the wide dynamic range and the relatively high abundance of proteins such as haemoglobin, compromising biomarker discovery. Here, we establish an optimised workflow for protein extraction and haemoglobin depletion from microsamples obtained using DBS, enabling sensitive and high-throughput proteomic analysis. We demonstrate that haemoglobin depletion increases protein identifications by ∼50%, mitigating ion suppression and dynamic range effects, enabling the identification of putative biomarkers from patients with stage 5 CKD on dialysis. We also evaluated a commercial cell-free DBS device which yielded a sample more representative of plasma compared to traditional DBS and enabled greater depletion of haemoglobin compared to traditional DBS with haemoglobin depletion methods. Our findings offer a scalable approach for biomarker discovery, facilitating remote, longitudinal clinical studies.