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Abstract: TH-OR52

Harnessing Kidney Transcriptome Profiles to Predict Rapid Progression of Diabetic Kidney Disease

Session Information

Category: Diabetic Kidney Disease

  • 702 Diabetic Kidney Disease: Clinical

Authors

  • Acoba, Dianne, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
  • Levin, Anna, Department of Clinical Science, Intervention and Technology, Division of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
  • Witasp, Anna, Department of Clinical Science, Intervention and Technology, Division of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
  • Mölne, Johan C., Department of Laboratory Medicine, Institute of Biomedicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
  • Greasley, Peter J., Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
  • Nystrom, Jenny C., Department of Physiology, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
  • Wernerson, Annika, Department of Clinical Science, Intervention and Technology, Division of Renal Medicine, Karolinska Institutet, Stockholm, Sweden
  • Reznichenko, Anna, Research and Early Development, Cardiovascular, Renal and Metabolism, BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
Background

Kidney gene expression has been shown to be associated with kidney function in diabetic kidney disease (DKD) patients by cross-sectional transcriptomics studies. However, how the renal transcriptome correlates to disease progression has not been established due to the paucity of longitudinal studies. We hypothesized that certain intra-kidney transcriptomic patterns associated with progressive DKD may elucidate disease drivers and predictive factors.

Methods

RNA-seq data from micro-dissected kidney biopsies and post-biopsy clinical data were available for 19 DKD patients. Patients were stratified into rapid and non-rapid progressors based on the following: eGFR decline more than ≤ -5 ml/min/year, CKD stage advancement, ≥30% UACR increase, nephrotic range albuminuria, and a composite outcome of kidney failure/≥40% eGFR loss. Gene signatures associated with rapid DKD progression were identified by differential expression (DEA), weighted gene co-expression network (WGCNA) and pathway enrichment analyses.

Results

We identified 265 statistically significant (Padj < 0.05) rapid progression-associated genes in the glomerular and tubulointerstitial compartments across all disease progression definitions through DEA. With WGCNA, 1 module in the glomeruli and 7 in the tubulointerstitium were found to be significantly correlated to eGFR slope (P < 0.05). The rapid progression-associated genes in the glomeruli were enriched for pathways linked to cell adhesion by integrins and syndecans, and signaling by NOTCH, MET and PTK2. Pathways involved in cellular response to starvation mediated by GCN2 and mTORC, SLIT signaling through ROBO receptors, and cytoskeletal reorganization were enriched in the tubulointerstitium. These pathways are less studied in the context of DKD progression and could elucidate novel disease understanding.

Conclusion

To the best of our knowledge, this study is the first to link baseline kidney compartment-specific gene expression to prospective DKD progression. We have identified transcriptomic profiles prognostic of rapid DKD progression that were distinct from those previously reported as associated with cross-sectional kidney function. Potentially, our findings can advance the understanding of DKD biology and steer towards discovery of prognostic biomarkers and therapeutic targets.

Funding

  • Government Support – Non-U.S.