Abstract: SA-PO0021
Cross-Species Molecular Mapping Reveals Early Innate Immune Activation Driving CKD Progression in Mice
Session Information
- Intelligent Imaging and Omics: Phenotyping and Risk Stratification
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Artificial Intelligence, Digital Health, and Data Science
- 300 Artificial Intelligence, Digital Health, and Data Science
Authors
- Majumdar, Arindam, Eli Lilly and Company, Indianapolis, Indiana, United States
- Alakwaa, Fadhl, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Eichinger, Felix H., University of Michigan Medical School, Ann Arbor, Michigan, United States
- Alaba, Mathew Olakunle, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Eddy, Sean, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Duffin, Kevin L., Eli Lilly and Company, Indianapolis, Indiana, United States
- Karihaloo, Anil K., Novo Nordisk A/S, Bagsværd, Capital Region of Denmark, Denmark
- Williams, Julie, AstraZeneca R&D Cambridge, Cambridge, England, United Kingdom
- Dey, Asim, Eli Lilly and Company, Indianapolis, Indiana, United States
- Fermin, Damian, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Hodgin, Jeffrey B., University of Michigan Medical School, Ann Arbor, Michigan, United States
- Hartman, John R., University of Michigan Medical School, Ann Arbor, Michigan, United States
- Qi, Na, Roche Innovation Center Basel, F Hoffmann-La Roche AG Research and Development Division, Basel, Switzerland
- Menzies, Robert I., AstraZeneca R&D Cambridge, Cambridge, England, United Kingdom
- Moisan, Annie, Roche Innovation Center Basel, F Hoffmann-La Roche AG Research and Development Division, Basel, Switzerland
- Østergaard, Mette Viberg, Novo Nordisk A/S, Bagsværd, Capital Region of Denmark, Denmark
- Chen, Yu, Eli Lilly and Company, Indianapolis, Indiana, United States
- Nair, Viji, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Breyer, Matthew Douglas, University of Michigan Medical School, Ann Arbor, Michigan, United States
- Kretzler, Matthias, University of Michigan Medical School, Ann Arbor, Michigan, United States
Group or Team Name
- Renal Pre-Competitive Consortium (RPC2).
Background
Preclinical models of chronic kidney disease (CKD) vary in how well they reflect human disease severity. We applied a molecular classification tool [1], originally used to stratify CKD patients into four transcriptomic classes of increasing severity (blue → olive → plum → gold), across species to identify mouse models that mimic human-like progression and uncover associated pathways.
Methods
We mapped each transcriptomic profile from 378 mice across 17 CKD models (Figure 1A) to human molecular classes using a Self-Organizing Map based framework [2]. Pathway activity was quantified using ssGSEA against Reactome pathways. We grouped mice from mild to severe and identified pathways with progressively increasing slope.
Results
We mapped all mouse samples to the four human CKD molecular classes: 10% to Gold, 17% to Olive, 36% to Plum, and 37% to Blue. Sham and control mice clustered in the Blue class, while severe models mapped to Gold. All UUO mice mapped to Gold, compared to 13% of ReninAAV mice. Pathway analysis in mice revealed that complement, innate immune, and vascular injury pathways increased with class severity.
Conclusion
Cross-species molecular mapping and pathway analysis showed some mouse models reflect human CKD severity at the transcriptomic level. Progressive activation of innate immune and vascular injury pathways tracked with advancing disease. Our findings highlight key disease-driving pathways and support molecular mapping for model selection and drug evaluation.
[1] http://kidneyclass.org:3838
[2] Reznichenko A et al.Kidney Int. 2024;105(6):1263–1278.
Funding
- Commercial Support – Eli Lilly, AstraZeneca, Novo Nordisk, Roche