Pretransplant transcriptomic signature in peripheral blood predicts early acute rejection

JCI Insight. 2019 Jun 6;4(11):e127543. doi: 10.1172/jci.insight.127543.

Abstract

Commonly available clinical parameters fail to predict early acute cellular rejection (EAR, occurring within 6 months after transplant), a major risk factor for graft loss after kidney transplantation. We performed whole-blood RNA sequencing at the time of transplant in 235 kidney transplant recipients enrolled in a prospective cohort study (Genomics of Chronic Allograft Rejection [GoCAR]) and evaluated the relationship of pretransplant transcriptomic profiles with EAR. EAR was associated with downregulation of NK and CD8+ T cell gene signatures in pretransplant blood. We identified a 23-gene set that predicted EAR in the discovery (n = 81, and AUC = 0.80) and validation (n = 74, and AUC = 0.74) sets. Exclusion of recipients with 5 or 6 HLA donor mismatches increased the AUC to 0.89. The risk score derived from the gene set was also significantly associated with acute cellular rejection after 6 months, antibody-mediated rejection and/or de novo donor-specific antibodies, and graft loss in a cohort of 154 patients, combining the validation set and additional GoCAR patients with surveillance biopsies between 6 and 24 months (n = 80) posttransplant. This 23-gene set is a potentially important new tool for determination of the recipient's immunological risk before kidney transplantation, and facilitation of an individualized approach to immunosuppressive therapy.

Keywords: Expression profiling; NK cells; Nephrology; Organ transplantation; Transplantation.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Biomarkers / blood
  • Biomarkers / metabolism
  • Female
  • Graft Rejection* / diagnosis
  • Graft Rejection* / epidemiology
  • Graft Rejection* / genetics
  • Graft Rejection* / metabolism
  • Humans
  • Kidney Transplantation / adverse effects*
  • Male
  • Middle Aged
  • Predictive Value of Tests
  • Prospective Studies
  • Risk Assessment
  • Transcriptome / genetics*

Substances

  • Biomarkers