Abstract
Acute tubulointerstitial nephritis (ATIN) is a leading cause of acute kidney injury (AKI) and acute kidney disease. It is characterized by interstitial inflammation and tubular injury, often triggered by medications, infections, or autoimmune disorders. Prompt diagnosis and treatment are crucial to prevent irreversible kidney damage; however, nonspecific clinical and laboratory findings pose diagnostic challenges. Although kidney biopsy remains the gold standard, its invasive nature and potential complications necessitate the exploration of alternative noninvasive strategies. Emerging biomarkers offer promising noninvasive tools for diagnosing ATIN and differentiating it from other causes of AKI and acute kidney disease. Biomarker applications, as an alternative, are viewed through the lens of distinct immune reaction subtypes, including variations in type IV hypersensitivity mechanisms. Biomarkers such as urinary CXC chemokine ligand (CXCL)9 and cytokines such as tumor necrosis factor (TNF)-α and interleukin (IL)-9 reflect T-cell polarization and specific inflammatory pathways, shedding light on T helper (Th)1- and Th2-mediated immune responses. Among these, the urinary CXCL9-to-creatinine ratio demonstrates high sensitivity and specificity, with well-defined thresholds guiding clinical decisions. Urinary retinol-binding protein and serum C-reactive protein (CRP) have also been explored, particularly in immune checkpoint inhibitor (ICPI)-associated AKI. However, their nonspecificity and overlap with other AKI etiologies limit their utility in isolating ATIN-specific pathways. This review highlights the need for integrating biomarker-based approaches with a broader understanding of immune heterogeneity and histologic correlation to improve diagnostic precision. Future studies should focus on validating biomarker panels that capture diverse inflammatory endotypes, enabling early diagnosis and personalized management. By acknowledging the complexity of immune reactions underlying ATIN, this approach aims to enhance clinical decision-making while minimizing the need for invasive diagnostics, ultimately improving patient outcomes.