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Abstract: PO1456

Defining Cell Type Specificity of TNF Targets in Nephrotic Syndrome

Session Information

Category: Glomerular Diseases

  • 1202 Glomerular Diseases: Immunology and Inflammation

Authors

  • McCown, Phillip J., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • Eddy, Sean, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • Alakwaa, Fadhl, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • Harder, Jennifer L., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • El Saghir, Jamal, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • Ju, Wenjun, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • Kretzler, Matthias, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
  • Mariani, Laura H., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States

Group or Team Name

  • Nephrotic Syndrome Study Network (NEPTUNE)
Background

Mechanistic, targeted therapies are needed for patients with FSGS and MCD, as diverse biological processes produce similar histologic injury patterns. Bulk transcriptomic data from kidney biopsy tissue can be used to find subgroups with shared molecular features, but cellular signaling networks need to be defined.

Methods

Consensus clustering was applied to bulk RNA sequencing data from the tubulointerstitial (TI) compartment of 220 participants from the NEPTUNE cohort, a study of children and adults with nephrotic syndrome enrolled at the time of kidney biopsy. Clusters were assessed for association with clinical outcome. Differential gene expression analysis was analyzed for enrichment of canonical pathways and functional groups between patient clusters. Nuclei were extracted from renal biopsies, processed, and quality control analyzed to remove low quality nuclei. Nuclei identity were assigned by comparisons of enriched genes in a cluster to previously identified cell type-specific gene profiles.

Results

One cluster of 59 patients was associated with a higher risk of loss of kidney function over time and observed TNF activation. To test the cellular source of the TNF pathway biomarker candidates, we performed snRNA-seq on 10 NEPTUNE biopsies, 5 with high TNF activity scores and 5 with moderate to low TNF activity scores in TI gene expression profiles. We pooled 45,175 nuclei into 15 clusters, which included all major kidney cell types. TNF expression was found in nuclei from immune clusters and in a proximal tubule and loop of Henle cluster. TNFRSF1A was universally expressed across cell clusters, while TNFRSF1B showed more restrictive expression. TNF targets CCL2 and TIMP1 had higher levels in all patients with activated TNF scores with maximal increase in epithelial cells (proximal and podocytes). Kidney organoids confirmed MCP1 (encoded by CCL2) and TIMP1 upregulation by TNF treatment.

Conclusion

TNF, TNF receptors, and TNF-responsive biomarkers reflect alterations in inflammatory and intrinsic kidney cell populations in patients with a TNF-associated signaling profile and are currently assessed as TNF target engagement biomarkers in a clinical trial of FSGS patients (NCT04009668).

Funding

  • NIDDK Support