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Abstract: SA-PO0742

Combined Transcriptomics and Proteomics Approach to Identify Immune Signatures in ANCA-Associated Glomerulonephritis

Session Information

Category: Glomerular Diseases

  • 1401 Glomerular Diseases: Mechanisms, including Podocyte Biology

Authors

  • Stojkic, Ivana, Nationwide Children's Hospital, Columbus, Ohio, United States
  • Arazi, Arnon, Northwell Health Feinstein Institutes for Medical Research, Manhasset, New York, United States
  • Song, Huijuan, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States
  • Yan, Pearlly, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States
  • Fussner, Lynn A., The Ohio State University Wexner Medical Center, Columbus, Ohio, United States
  • Rovin, Brad, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States
  • Parikh, Samir V., The Ohio State University Wexner Medical Center, Columbus, Ohio, United States
  • Ardoin, Stacy, Nationwide Children's Hospital, Columbus, Ohio, United States
  • Almaani, Salem, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States
Background

ANCA-associated vasculitis frequently involves the kidneys causing glomerulonephritis (AAGN). Despite advances in treatment, many patients develop end-stage kidney disease. An improved understanding of the immune drivers of AAGN has the potential to improve treatment outcomes. To achieve that goal, we utilized a combined transcriptomics/compartmental proteomics approach to identify the major immune pathways driving AAGN.

Methods

Formalin-fixed paraffin embedded kidney biopsies of 23 patients with AAGN and 5 healthy controls (pre-implantation kidney donor biopsy) were used. For transcriptomics, RNA was extracted and bulk RNAseq was performed on all 23 AAGN biopsies and controls. Differential expression analysis was performed using the DESeq framework. For proteomics, laser capture microdissection was utilized to collect the glomerular and tubulointerstitial compartments separately using 10 AAGN biopsies and all controls. Peptides were extracted and submitted for mass-spectrometric analysis. After normalization, differential expression analysis was done using T-tests. The Benjamini-Hochberg method was used for multiple hypothesis testing correction in all experiments. Differentially abundant mRNA and peptide spectral counts were used to identify enriched immune pathways using Ingenuity pathway analysis.

Results

Patient and disease characteristics of the full (transcriptomic) and proteomics cohort are described in table 1. The top enriched pathways in each of the 3 experiments (whole tissue transcriptomics, glomerular proteomics, tubulointerstitial proteomics) are depicted in Figure 1a-c. Comparison analysis using data from the 3 experiments demonstrated many shared enriched and upregulated pathways including complement, neutrophil degranulation, and FC gamma receptor signaling. PD-1/PDL1 and IL-10 signaling were downregulated across the 3 tissues studied. Upstream analysis demonstrated upregulation of TNF, INF-gamma, INF-alpha, and IL-6.

Conclusion

Analysis of biopsies from patients with AAGN demonstrated largely similar upregulated/downregulated immune pathways and upstream regulators when comparing transcriptomic and compartmental proteomics approaches. These may help inform patient stratification and therapy development.

Funding

  • Private Foundation Support

Digital Object Identifier (DOI)