Novel Biomarkers for Acute Kidney Injury: Diagnostic Profiles, Etiology-Specific Applications, Prognostic Impacts, and the Path to Precision Medicine: Bridging the Clinical Action Gap—Review
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2025
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Abstract
Acute kidney injury (AKI) remains a substantial clinical challenge, affecting approximately half of all critically ill patients and is associated with a high risk of mortality, need for dialysis, and progression to chronic kidney disease (CKD). Traditional diagnostic methods, which rely on urine output and serum creatinine (sCr), are non-specific and delayed, thus missing the crucial window for early intervention. New urine and plasma biomarkers, such as neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), liver-type fatty acid-binding protein (L-FABP), interleukin-18 (IL-18), tissue inhibitor of metalloproteinase-2, insulin-like growth factor-binding protein 7 ([TIMP-2] × [IGFBP7]), and C-C motif chemokine ligand 14 (CCL14), have become effective tools for risk assessment and early detection over the past decade. With diagnostic accuracy superior to creatinine, these biomarkers allow for the identification of AKI within 2 to 12 hours, as they represent tubular stress, damage, and healing processes. Multi-marker panels further enhance diagnostic performance, particularly in complex clinical scenarios such as sepsis and heart surgery. Etiology-specific biomarker patterns are now well-delineated: minimal elevations in prerenal conditions may guide safe fluid management, whereas sustained increases in intrinsic AKI suggest poor recovery and may necessitate renal replacement therapy (RRT). Biomarker-guided interventions have been shown to reduce the incidence of severe AKI by 15% to 30% in high-risk populations. Emerging biomarker types that have the potential to improve early detection and prognosis accuracy include filtration surrogates, oxidative stress indicators, microRNAs (e.g., miR-21, exosomal panels), and inflammation/repair biomarkers. Despite these advancements, difficulties remain, including inconsistencies in testing, high costs, limited data on juvenile and postrenal AKI, and a “clinical action gap” where biomarker findings have not been reliably linked to evidence-based therapies. The integration of artificial intelligence with point-of-care diagnostics has significant potential for future clinical applications. This review consolidates current data to illustrate how emerging biomarkers are transforming thetreatment of AKI from a reactive diagnosis to a proactive, precision-oriented strategy.
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| Authors | Elmukhtar Habas, Aml Habas, Amnna Rayani, Ala Habas, Khaled Alarbi, Eshrak Habas, Mohamed Baghi, Mohammad Babikir, Abdelrahaman Hamad, Almehdi Errayes |
| Journal | Yemen Journal of Medicine |
| Year | 2025 |
| DOI |
10.63475/yjm.v4i3.0226
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| URL | |
| Keywords | Keywords not found |
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