Abstract: SA-PO0656
MOSAIC-IgAN: Multi-Omics- and Artificial Intelligence (AI)-Based Subphenotyping of IgAN Among Diverse Populations
Session Information
- Glomerular Diseases: Clinical, Outcomes, and Therapeutics Research - Other
October 24, 2026 | Location: Exhibit Hall A, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Glomerular Diseases
- 1402 Glomerular Diseases: Clinical, Outcomes, and Therapeutics
Authors
- Vasquez-Rios, George, Glomerular and Genetic Diseases Center, Renal Medical Associates, Albuquerque, New Mexico, United States
- Rajasekaran, Arun, Glomerular and Genetic Diseases Center, Renal Medical Associates, Albuquerque, New Mexico, United States
- Kumar, Jayant, Glomerular and Genetic Diseases Center, Renal Medical Associates, Albuquerque, New Mexico, United States
- Madan, Arvind, Glomerular Institute, Central Florida Kidney Specialists, Orlando, Florida, United States
- Oh, Wonsuk, Division of Data-Driven and Digital Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Mosoyan, Gohar, Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Cravedi, Paolo, Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Campbell, Kirk N., University of Pennsylvania Division of Renal Electrolyte and Hypertension, Philadelphia, Pennsylvania, United States
- Coca, Steven G., Division of Nephrology, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, United States
- Sanchez Russo, Luis F., Glomerular Institute, Central Florida Kidney Specialists, Orlando, Florida, United States
Background
IgA nephropathy (IgAN) is a heterogeneous glomerular disease characterized by variable trajectories of proteinuria, kidney function decline, and progression to kidney failure. Conventional markers incompletely capture the immune-mediated mechanisms underlying disease progression and therapeutic response. MOSAIC-IgAN is a prospective translational precision-nephrology cohort integrating longitudinal biomarker profiling, genomics, and AI-based analytics to characterize response patterns in IgAN.
Methods
MOSAIC-IgAN will prospectively enroll 60 adults with biopsy-proven IgAN across four glomerular centers enriched for Latino/Hispanic, Native American, Asian, and other ethnic minorities. Participants will undergo standardized longitudinal collection of clinical, histopathologic, genomic, and biospecimen data before and after APRIL/BAFF pathway inhibition with sibeprenlimab, enabling therapy-linked mechanistic profiling and evaluation of disease-state modification over time. Clinical variables include eGFR and proteinuria, treatment exposure, and kidney outcomes. Histopathologic characterization incorporates Oxford MEST-C scoring and chronicity features. Blood and urine biospecimens will evaluate podocyte injury, inflammation, complement activation, tubular injury/fibrosis, galactose-deficient IgA1, and urinary CD163. Genomic analyses include APOL1, COL4A3/A4, NPHS1/2 variants. Longitudinal biomarkers will be evaluated using mixed-effects modeling and exploratory AI-driven learning approaches to identify early clinical-pathologic-molecular subphenotypes associated with differential kidney outcomes and therapeutic response.
Results
Standardized biospecimen workflows, centralized biobanking infrastructure, dedicated MOPs, and assay pipelines for serum, plasma, urine, and molecular profiling were operationalized in collaboration with Mount Sinai. Major milestones achieved include umbrella protocol approval through Advarra IRB, expansion of DUAs, and clinical site agreements with Mount Sinai, University of Pennsylvania, and Central Florida Kidney Specialists. Initial Phase I funding (2026–2028) was secured and first three patients were enrolled in May 2026.
Conclusion
MOSAIC-IgAN establishes a prospective precision-nephrology platform focused on therapy-linked mechanistic phenotyping in IgAN to identify disease subphenotypes and advance future biomarker-guided therapies in IgAN.
Funding
- Commercial Support – Otsuka