Multi-Omics in Kidney Disease Research: Technological Advances, Biomarker Discovery and Clinical Translation

Abstract

Abstract Background Multi-omics research is reshaping precision nephrology by linking genetic susceptibility, epigenetic regulation, transcriptional state, protein abundance, metabolic activity and spatial tissue context within integrated analytical frameworks. Methods We critically reviewed recent technological advances and applications of multi-omics in kidney diseases, with particular attention to biomarker discovery and clinical translation, and discussed the challenges and future directions of multi-omics integration and its application in precision medicine. Results Emerging approaches, including single-cell and spatial omics, artificial intelligence-assisted analytics and integrative computational frameworks, have substantially improved the resolution of renal pathophysiology and molecular heterogeneity. These advancements not only reveal novel molecular pathways underlying chronic kidney disease, diabetic kidney disease, acute kidney injury and immune-mediated nephropathies, but also significantly facilitate biomarker discovery and therapeutic target prioritization. However, major challenges remain, including limited cohort diversity, high analytical complexity, lack of standardized pipelines, insufficient external validation and barriers to clinical implementation, such as cost, scalability and regulatory integration. Conclusions Collectively, multi-omics strategies are reshaping kidney disease research and hold considerable promise for advancing precision diagnosis, risk stratification and personalized therapeutics. Future efforts should prioritize harmonized multicentre datasets, longitudinal validation, explainable artificial intelligence models and clinically actionable frameworks to bridge the gap between omics discovery and routine nephrology practice.