Kidney Week

Abstract: SA-OR01

Understanding Pathophysiology of Acute Interstitial Nephritis through Spatial Characterization of Cell-Cell Interactions Using Imaging Mass Cytometry in a Human Biopsy Cohort

Session Information

• AKI: An Inflamed State of the Union
  October 26, 2024 | Location: Room 5, Convention Center
  Abstract Time: 04:30 PM - 04:40 PM

Category: Acute Kidney Injury

• 103 AKI: Mechanisms

Authors

• Baker, Megan Leila, Yale University School of Medicine, New Haven, Connecticut, United States

Megan Leila Baker, MD

• Kakade, Vijayakumar R., Yale University School of Medicine, New Haven, Connecticut, United States

Vijayakumar R. Kakade, PhD

• Budiman, Tifanny, Yale University School of Medicine, New Haven, Connecticut, United States

Tifanny Budiman

• Weiss, Marlene, Yale University School of Medicine, New Haven, Connecticut, United States

Marlene Weiss, DrMed

• Shelar, Ashish, Yale University, New Haven, Connecticut, United States

Ashish Shelar, PhD

• Moledina, Dennis G., Yale University School of Medicine, New Haven, Connecticut, United States

Dennis G. Moledina, MD, PhD, FASN

• Cantley, Lloyd G., Yale University School of Medicine, New Haven, Connecticut, United States

Lloyd G. Cantley, MD, FASN

Background

Kidney damage in AIN is believed to result from immune-mediated tubular injury, with ongoing inflammation leading to fibrosis and progression to CKD. Delineation of the immune cell signature and corresponding tubular and vascular cell responses in AIN should lead to more targeted therapies.

Methods

Adjudicated human kidney biopsy tissues with AIN(13), ATI(13), DKD(7), and healthy reference tissue(13) underwent imaging mass cytometry using 34 customized metal conjugated antibodies (Fig1). Cell identities and activation states were defined in spatial context. A customized deep-learning-based algorithm (Mesmer) was used for segmentation. Downstream data analyses used open-source analytic pipelines steinbock and imcRtools.

Results

Across samples 786,580 cells were analyzed. Preliminary findings show 37 cell clusters with 17 primary cell types (Fig2). Immune populations are increased in AIN and ATI compared to reference. AIN showed the largest increase in CD4+ T cells (8.6%, 2.5% ATI, 1.6% ref, p<0.0001). Lymphatics were expanded in AIN and ATI (both 1.1%) above reference tissues(0.5%) and colocalized with lymphocyte enrichment. Mast cells also show enrichment with injury (2.4% AIN, 1.3% ATI, 0.2% ref, p<0.0001).

Conclusion

Our initial analysis is supportive of the role of CD4+ T cells, and perhaps mast cells and lymphatics, in the pathophysiology of AIN. Subsequent analyses, including subclustering for improved phenotyping, cell quantification by tissue area, neighborhood and interaction analyses, and integration with clinical data, are underway and expected to result in the identification of specific cell-cell interactions which will advance our understanding of AIN.

Raw IMC output from 1 AIN section pseudocolored by resident cell markers(L) and immune cell markers(R).

Initial UMAP and initial cell phenotypes across tissue types.

Funding

• NIDDK Support