Biomarker Research in CKD Space Can Support Therapeutic Advancements and Approaches

In chronic kidney disease (CKD) research, biomarkers are paving the way for diagnoses, monitoring, and predicting outcomes of the disease. However, data to guide biomarker therapies are scarce. In a piece published in Nature Reviews Nephrology, researchers wrote of an urgent need for more targeted studies, especially given the availability of several effective new therapies for attenuating CKD progression and improving patient outcomes.¹

Albuminuria and estimated glomerular filtration rate (eGFR) remain the main diagnostic and monitoring metrics used in people with CKD, according to the study authors. Although these are both useful markers, they represent the consequence of CKD and not the cause, and therefore can neither detect disease at its earliest stages nor determine its etiology. For these reasons, these markers are often suboptimal in helping health care professionals guide therapeutic intervention.

Conversely, nucleotide, protein, peptide, and metabolite findings from urine may provide a wealth of information about kidney-tissue biology and pathological processes, representing a source of potential biomarkers for early disease detection, prognostication, and therapeutic guidance. According to the authors, urinary biomarker research is currently dominated by studies of protein biomarkers that reflect tissue injury and repair, inflammation, and fibrosis. These can be combined for use in multimarker panels, with data specifically on biomarkers for guiding therapy less common, emphasizing an urgent need for more targeted studies. Consequently, although several—and mainly protein-based—biomarkers with evidenced potential to improve disease management are currently available, their clinical implementation is limited by the lack of both clinical and health-economic impact data for people with CKD.¹

The authors wrote that urine analysis is equivalent to a liquid biopsy that can provide insights into kidney pathophysiology. The components gathered from these insights, when analyzed using contemporary techniques, provide substantial biological and clinical information. Additionally, biologically relevant changes in urinary mitochondrial and nuclear DNA, and various RNA variants have been linked to CKD, said the authors; however, follow-up studies are needed to further define their values as biomarkers.

Metabolomic studies have highlighted uremic toxins and metabolites of potential biomarker value, including amino acids and lipids; however, the vast complexity of the metabolome and confounding factors impede biomarker validation. Finally, the authors noted that the clinical and health-economic impact of applying promising biomarkers in combination with the latest interventional approaches must be assessed to facilitate their implementation.¹

Another recent study predicting kidney failure determined that a model combining 3 biomarkers (soluble TNF receptor 1, soluble cluster of differentiation 40, and urinary collagen type 1 α1 chain) demonstrated good discrimination (C-index: 0.86 [95% CI 0.83–0.89]) but was outperformed by a model using established risk factors, including age, sex, ethnicity, eGFR, and urinary albumin creatinine ratio (C-index: 0.90 [95% CI 0.88–0.92]). When assessing all-cause mortality, a different model using 3 biomarkers (high-sensitivity cardiac troponin T, N-terminal pro-brain natriuretic peptide, and soluble urokinase plasminogen activator receptor) demonstrated equivalent discrimination (C-index: 0.80 [95% CI, 0.75–0.84]) to a previously established risk factor model (C-index 0.80 [95% CI, 0.76–0.84]). Additionally, for the composite outcome, the biomarker model discrimination (C-index: 0.78 [95% CI, 0.76–0.81]) was numerically higher than for established risk factors (C-index: 0.77 [95% CI, 0.74–0.80]). These study authors wrote that the addition of biomarkers to the established risk factors led to a small—but statistically significant—improvement in discrimination (C-index: 0.80 [95% CI, 0.77–0.82]; P < .01).²

Another study published in American Journal of Physiology – Renal Physiology indicated that a blood biomarker, symmetric dimethylarginine (SDMA), demonstrated a stronger connection to vascular health in patients with CKD, especially when compared with asymmetric dimethylarginine (ADMA). In this study, it was determined that SDMA significantly elevated in patients with CKD (163 ± 37 ng/mL) than in those without (100 ± 15 ng/mL; P < .0001), whereas ADMA did not differ significantly between these groups (111 ± 22 vs 103 ± 12 ng/mL; P = .083). Patients with CKD were also observed to have lower flow-mediated dilation (FMD; 3.66 ± 2.45 vs 4.47 ± 2.45%; P = 0.048) and peak blood velocity (47.43 ± 16.67 vs 60.18 ± 16.88 cm/s; P = 0.009), but higher carotid-femoral pulse wave velocity (cfPWV; 8.82 ± 1.53 vs 7.69 ± 1.35 m/s; P = 0.004) compared with the controls who did not have CKD. A pooled analysis demonstrated that SDMA correlated inversely with eGFR (r = −0.86; P < .0001), FMD (r_s = −0.28; P = .039), and peak blood velocity (r_s = −0.40; P = .001); however, this was not the case for cfPWV (r = 0.14; P = .338). ADMA was also observed to correlate inversely with peak blood velocity (r_s = −0.28; P = .042), but the opposite was true for eGFR (r = −0.25; P = .063), FMD (r_s = −0.06; P = .664), or cfPWV (r = 0.21; P = .146).³

Taken together, these emerging data emphasize the potential of biomarkers to transform the diagnosis, monitoring, and treatment of CKD. Although traditional measures such as eGFR and albuminuria remain central to care, they primarily reflect disease consequences rather than underlying mechanisms; therefore, advances in urinary, blood, and molecular biomarkers offer new opportunities to detect disease earlier, individualize therapy, and refine prognostic models. As novel therapies and technologies continue to evolve, biomarker-driven approaches may soon allow for more precise, proactive, and personalized care for patients with CKD.

REFERENCES

1. Vlahou, A., Vanholder, R. Urine as a source of biomarkers and biological knowledge in chronic kidney disease. Nat Rev Nephrol (2025). doi:10.1038/s41581-025-01008-2

2. McGovern G. Study Finds Biomarkers That May Help Predict, Manage Chronic Kidney Disease. Pharmacy Times. August 12, 2025. Accessed October 10, 2025. https://www.pharmacytimes.com/view/study-finds-biomarkers-that-may-help-predict-manage-chronic-kidney-disease

3. McGovern G. Blood Biomarker Shows Strong Connection to Vascular Health in Patients With CKD. Pharmacy Times. October 2, 2025. Accessed October 10, 2025. https://www.pharmacytimes.com/view/blood-biomarker-shows-strong-connection-to-vascular-health-in-patients-with-ckd