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Abstract: PO1835

T Lymphocytes in Human Hypertension

Session Information

Category: Hypertension and CVD

  • 1403 Hypertension and CVD: Mechanisms

Authors

  • Quinn, Ghazal Z., University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Sheng, Xin, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Abedini, Amin, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Vuong, Lynda, Memorial Sloan Kettering Cancer Center, New York, New York, United States
  • Nixon, Briana G., Memorial Sloan Kettering Cancer Center, New York, New York, United States
  • Hill, Jonathan, Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Pullen, Steven S., Boehringer Ingelheim Pharmaceuticals, Inc., Ridgefield, Connecticut, United States
  • Shin, Myung, Merck & Co Inc, Kenilworth, New Jersey, United States
  • Li, Ming, Memorial Sloan Kettering Cancer Center, New York, New York, United States
  • Hakimi, A. Ari, Memorial Sloan Kettering Cancer Center, New York, New York, United States
  • Susztak, Katalin, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
Background

Mouse models have shown that T lymphocytes are required for hypertension (HTN) development and accumulate in the vasculature and kidneys. The role of immune cells, including T lymphocytes, remains poorly understood in patients with HTN. Here, we analyzed immune cells in human kidney tissue samples in patients with HTN.

Methods

Human kidney tissue was obtained from the unaffected portions of 631 tumor nephrectomies and included clinical, histological and follow up data. Tissue was microdissected into glomerular and tubular compartments for RNA-sequencing. In silico deconvolution of each kidney sample was performed using the CIBERSORTx method to enumerate relative cell type fractions. Flow cytometry was used for validation analyses using cell type specific antibodies in another set of 58 human kidney tissue samples. Regression analyses were used to determine the associations of renal immune cells and clinical parameters. Linear mixed modeling was used to assess longitudinal data.

Results

CD4 and CD8 T-cells were increased in patients with HTN (p<0.05) while T regulatory cells (Tregs) were decreased (0.4% vs. 0.6%, p=0.022). In adjusted models, HTN was associated with older age, Black race, diabetes, decreasing eGFR, dendritic cells (DCs) and Tregs and with increasing CD4 T-cells (p<0.001). In samples with CKD stages 1-2, older age, lower Tregs and natural killer T-cells and higher CD4 T-cells were associated with HTN, independent of baseline eGFR or the degree of renal fibrosis (p<0.001). In our flow cytometry cohort, HTN was also significantly associated with higher CD4 T-cells, lower Tregs and DCs, but also lower CD8 T-cells, independent of eGFR (p=0.009). Longitudinal data were available for 149 subjects for an average of three years and showed that older age, lower baseline eGFR and higher Th17 cells were associated with lower eGFR over time (p<0.001).

Conclusion

In silico deconvolution resolved a variety of renal immune cells and provided complementary information to flow cytometric analyses in kidney tissue. While multiple T-cell populations were increased in the setting of HTN, Tregs were decreased. These findings were independent of eGFR at CKD stages 1-2. Th17 cell expansion predicted faster eGFR decline. Our results highlight an important association between T-cell populations, HTN, kidney disease and kidney function decline.

Funding

  • NIDDK Support