Novel Biomarkers in the Early Detection of Chronic Kidney Disease: Current Evidence and Future Directions

Chronic kidney disease (CKD) affects over 850 million individuals worldwide, with conventional markers failing to detect early renal damage until significant nephron loss occurs. This review synthesizes current evidence on emerging biomarkers—including proteomic signatures (e.g., CKD273 panel), metabolomics profiles, circulating microRNAs, APOL1 genetic variants, cell-free DNA methylation patterns, and urinary exospores that enable earlier detection of CKD. We examine multi-marker panels integrated with machine-learning algorithms, achieving high sensitivity and specificity in prospective cohorts, and assess point-of-care technologies facilitating decentralized screening. Regulatory and ethical challenges, cost-effectiveness analyses, and standardization hurdles across diverse healthcare settings are also discussed. Finally, we identify research gaps in longitudinal, multi-center validation studies and propose future directions toward precision nephrology, integrating multi-omics data with imaging and wearable sensors to shift CKD management from treatment to prevention. This comprehensive overview informs clinicians and researchers on the translational potential of novel diagnostics in combating the growing CKD burden.

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Publication Details

Journal
Indus journal of bioscience research.
Published
2025-05-25
DOI
https://doi.org/10.70749/ijbr.v3i5.1480
Citations
3
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
8.81
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article

Novel Biomarkers in the Early Detection of Chronic Kidney Disease: Current Evidence and Future Directions

Muhammad Uzair, Zafar Ahmad Khan, Ahmad Khan Iftikhar, Qasim Ishtiaq et al.
3 citations
Indus journal of bioscience research.
Artificial Intelligence in Healthcare
8.81
article

Novel Biomarkers in the Early Detection of Chronic Kidney Disease: Current Evidence and Future Directions

Muhammad Uzair, Zafar Ahmad Khan, Ahmad Khan Iftikhar, Qasim Ishtiaq, Quratul Ain Nazir, Akif Saeed
article en
3 citations

Abstract

Chronic kidney disease (CKD) affects over 850 million individuals worldwide, with conventional markers failing to detect early renal damage until significant nephron loss occurs. This review synthesizes current evidence on emerging biomarkers—including proteomic signatures (e.g., CKD273 panel), metabolomics profiles, circulating microRNAs, APOL1 genetic variants, cell-free DNA methylation patterns, and urinary exospores that enable earlier detection of CKD. We examine multi-marker panels integrated with machine-learning algorithms, achieving high sensitivity and specificity in prospective cohorts, and assess point-of-care technologies facilitating decentralized screening. Regulatory and ethical challenges, cost-effectiveness analyses, and standardization hurdles across diverse healthcare settings are also discussed. Finally, we identify research gaps in longitudinal, multi-center validation studies and propose future directions toward precision nephrology, integrating multi-omics data with imaging and wearable sensors to shift CKD management from treatment to prevention. This comprehensive overview informs clinicians and researchers on the translational potential of novel diagnostics in combating the growing CKD burden.

Indus journal of bioscience research.Vol. 3(5)
Khyber Medical College (PK), University of Balochistan (PK), Punjab Medical College (PK), Bolan University of Medical and Health Sciences (PK), Superior University (PK), University of Veterinary and Animal Sciences (PK)
Openalex Percentile: Top 3%
Artificial Intelligence in Healthcare
8.81
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Novel Biomarkers in the Early Detection of Chronic Kidney Disease: Current Evidence and Future Directions — Muhammad Uzair, Zafar Ahmad Khan, et al. · Indus journal of bioscience research. (2025) | TGRS Research Map | TGRS