AI and Molecular Biomarkers Drive Precision Diagnosis in Lupus Nephritis
This review examines how novel molecular biomarkers, artificial intelligence, and machine learning are transforming lupus nephritis diagnosis and treatment prediction. AI-driven tools can delineate disease subtypes and forecast treatment responses, while targeted biologics offer more precise therapeutic options. The convergence of biomarker discovery, computational pathology, and targeted therapy positions lupus nephritis as a model for precision diagnostics in autoimmune kidney disease.
The original study
Advances in precision medicine for lupus nephritis: biomarker- and AI-driven diagnosis and treatment response prediction and targeted therapies.
- Authors
- Shang S, Xia J, He G, Zheng Y, Zhang J, Lu H, et al.
- Journal
- EBioMedicine
- Type
- Journal Article, Review
- PMID
- 40466435
Original abstract
With the rapid evolution of precision medicine, diagnostic, and therapeutic strategies for lupus nephritis (LN) are progressively shifting towards greater personalisation and accuracy. On the diagnostic front, the discovery and deployment of novel molecular biomarkers, together with the integration of artificial intelligence (AI) and machine learning (ML) technologies, have opened new avenues for delineating disease subtypes and forecasting treatment responses, thereby optimising clinical decision-support systems. In the therapeutic domain, innovations in targeted biologics and the precise application of diverse targeted modalities have shown promise in enhancing efficacy while reducing adverse effects. The triadic synergy of molecular biomarker breakthroughs, iterative advances in intelligent computational tools and pioneering targeted therapies is poised to usher LN in a new era of customised diagnosis and intervention.