The diagnosis and treatment decisions in glomerular disease are principally based on renal pathology and nonspecific clinical laboratory measurements such as serum creatinine and urine protein. Using these classification approaches, patients have marked variability in rate of progression and response to therapy, exposing a significant number of patients to toxicity without benefit. Additionally, clinical trials are at risk of not being able to detect an efficacious therapy in relevant subgroups as patients with shared clinical-pathologic diagnoses have heterogeneous underlying pathobiology. To change this treatment paradigm, biomarkers that reflect the molecular mechanisms underlying the clinical-pathologic diagnoses are needed. Recent progress to identify such biomarkers has been aided by advances in molecular profiling, large-scale data generation and multi-scalar data integration, including prospectively collected clinical data.
The discovery and validation of useful biomarkers in glomerular disease are critical not only for research purposes and stratification for clinical trials, but also ultimately for the ability to practice precision medicine for patients with this disease. Glomerular disease patients have dramatically heterogeneous disease trajectories and response to therapies, despite their overlapping pathologic diagnosis and clinical presentation. To be able to develop a panel of biomarkers across the genotype-phenotype continuum will allow for mechanistically targeted therapies. Successful biomarkers already exist in this field, from the cross-disease utility of urine protein to disease-specific markers such as anti-glomerular basement membrane antibody. Several exploratory studies are already transitioning into clinical validation, including anti-PLA2R, and monogenetic mutations . As a result, biomarker-based diagnosis, prognosis and therapeutic decisions will be possible in glomerular diseases.