Journal Article Review Ppublish
PubMed: 39848232 DOI: 10.1159/000543640
Personalized Care in CKD: Moving Beyond Traditional Biomarkers.
Nephron 149(6):339-357
Authors: Thomas McDonnell, Rosamonde E Banks, Maarten W Taal, Nicolas Vuilleumier, Philip A Kalra
Affiliations
- Donal O'Donoghue Renal Research Centre, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Salford, UK.
- Division of Cardiovascular Sciences, Faculty of Biology Medicine and Health, University of Manchester, Manchester, UK.
- Leeds Institute of Medical Research, St James's University Hospital, School of Medicine, Leeds, UK.
- Centre for Kidney Research and Innovation, Academic Unit for Translational Medical Sciences, School of Medicine, University of Nottingham, Nottingham, UK.
- Department of Renal Medicine, Royal Derby Hospital, University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK.
- Laboratory Medicine Division, Diagnostics Department, Geneva University Hospitals and Faculty of Medicine, Geneva, Switzerland.
Abstract
BACKGROUND
Traditional biomarkers, such as estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (uACR), have long been central to chronic kidney disease (CKD) diagnosis and management, leading to a standardized CKD classification system. However, these biomarkers are non-specific and fail to capture the heterogeneity within CKD and the nuances of an individual's disease mechanism, limiting personalized treatment approaches. There is an increasing need for novel biomarkers that reflect the diverse pathophysiological processes underlying CKD progression, enabling more precise risk prediction and treatment strategies.
SUMMARY
This review examines the limitations of current CKD biomarkers and classification systems, highlighting the need for a precision medicine approach. While traditional markers like eGFR and uACR are foundational, they inadequately capture CKD's complexity. Emerging biomarkers offer insights into specific disease processes, such as inflammation, oxidative stress, fibrosis, and tubular injury, which are crucial for personalized care. The article discusses the potential benefits of integrating these novel biomarkers into clinical practice, including more accurate risk prediction, tailored treatments, and personalized clinical trial designs, as well as the barriers to their implementation. Furthermore, advancements in multi-omics and high-throughput techniques offer opportunities to identify novel causative proteins with druggable targets, pushing CKD care towards greater precision.
KEY MESSAGES
Current CKD classification systems, based on non-specific biomarkers, fail to capture CKD's heterogeneity. Incorporating biomarkers reflecting diverse pathophysiological mechanisms can enhance risk prediction, customized treatments, and personalized clinical trials. High-throughput multi-omic techniques present a promising path towards precision medicine in nephrology.
MeSH
Kidney Diseases, Multiple Chronic Conditions, Classification, Biomarkers, Precision Medicine, Therapeutics