Abstract: SA-PO0070
Paired Transcriptomic-Proteomic Pseudotime Analysis Reveals a Shift from Mitochondrial Metabolism to Immune Activation During Aging-Accelerated Kidney Function Decline
Session Information
- Artificial Intelligence: Kidney Imaging, Pathology, and Precision Phenotyping
October 24, 2026 | Location: Exhibit Hall A, 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
- Zhu, Minyan, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Hirohama, Daigoro, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Li, Chenyu, University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Karihaloo, Anil K., Novo Nordisk A/S, Bagsværd, Capital Region of Denmark, Denmark
- Susztak, Katalin, University of Pennsylvania, Philadelphia, Pennsylvania, United States
Background
Age-accelerated eGFR decline affects a substantial proportion of the population, yet its progression is highly heterogeneous and its molecular drivers remain poorly understood. Integrating transcriptomic and proteomic dynamics along disease trajectories offers a powerful approach to uncover the mechanisms underlying progressive kidney dysfunction.
Methods
Longitudinal eGFR records from All of Us (AoU) participants (with whole-genome sequencing, Fitbit data, and ≥2 eGFR measurements) were used to characterize age-related kidney function decline. Separately, paired RNA sequencing and SomaScan V4.1 proteomics were performed on human kidney biopsy samples from 328 participants in the Susztak biobank. Protein velocity, a method adapted from single-cell approaches that uses protein/mRNA ratios to infer biological state, here applied at the individual sample level, was combined with pseudotime analysis to model molecular transitions along the eGFR trajectory.
Results
In the AoU cohort, participants with CKD showed a 2.5-fold steeper eGFR decline slope compared with controls. In the paired kidney molecular dataset, protein velocity exhibited directional changes along an eGFR-associated pseudotime trajectory toward severe interstitial fibrosis. Pathway analysis revealed a shift from mitochondrial metabolic pathways toward immune activation and extracellular matrix remodeling. Age-stratified analysis showed that older individuals (≥60 years) exhibited additional enrichment of immune and inflammatory pathways, whereas younger individuals showed predominant cytoskeletal organization and RNA processing signatures; extracellular matrix–related processes were shared across age groups. LTF and PIGR emerged as unique age-specific drivers of GFR deterioration in the older group, with concordant signals in both transcriptomic and proteomic data, suggesting roles in epithelial immune defense and immunoglobulin transport.
Conclusion
Paired transcriptomic and proteomic analysis reveals that aging-accelerated kidney function decline is characterized by a shift from mitochondrial metabolic activity toward immune activation and extracellular matrix remodeling. The age-specific drivers identified here, particularly LTF and PIGR, nominate candidate targets for mechanistic investigation and potential biomarker development in CKD progression.
Acknowledgment
This work was supported by National Institutes of Health (NIH), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) grants 1U24AT013504-01, R01 DK076077, R01 DK087635 and R01 DK105821 (to K.S.).
Funding
- NIDDK Support