Mitochondrial Biomarker-enhanced Diagnostic Framework for Assessing Chronic Kidney Disease Prevalence in Hypertensive Populations: A Cross-sectional Study Integrating Urinary Mitochondrial DNA and Oxidative Stress Indices

Background: Hypertension is a leading risk factor for chronic kidney disease (CKD), yet early-stage CKD often remains undetected by conventional glomerular-centric diagnostics such as estimated glomerular filtration rate (eGFR) and albuminuria. These markers are insufficiently sensitive to detect subclinical tubular injury, which precedes overt renal dysfunction. There is a critical need for novel biomarkers that capture early, subtle renal damage, particularly in hypertensive populations. Methods: We propose a diagnostic framework that incorporates urinary mitochondrial DNA (mtDNA) copy number and oxidative stress marker 8-hydroxy-2′-deoxyguanosine (8-oxo-dG) alongside eGFR and albuminuria. Urinary mtDNA is quantified using droplet digital polymerase chain reaction (PCR) targeting the MT-ND1 gene, while 8-oxo-dG is measured via competitive enzyme-linked immunosorbent assay. These variables are combined into a composite risk score using multivariate logistic regression. A Transformer-based machine learning model with attention mechanisms processes the integrated data, emphasising mitochondrial biomarkers in early-stage cases where glomerular markers are less sensitive. Results: The framework outperforms conventional and quantitative PCR-based methods in precision and early-stage detection. It effectively mitigates confounding from age-related mitochondrial decline by modelling tubular injury pathways directly. Cross-sectional validation using bootstrap resampling confirms the robustness and stability of biomarker thresholds. The model replaces binary classification with a dynamic, continuum-based risk stratification. Conclusion: This approach redefines CKD diagnostics by incorporating a tubular-mitochondrial axis, enabling earlier detection and risk stratification in hypertensive patients. Early identification of high-risk individuals facilitates timely clinical intervention to prevent irreversible renal damage.