Abstract
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. This article reviews the evolving success stories in glomerular disease biomarkers across the genotype-phenotype continuum and highlights opportunities to transition to precision medicine in glomerular disease.