Pretransplant kidney transcriptome captures intrinsic donor organ quality and predicts 24‐month outcomes. Issue 11 (4th July 2022)

• Record Type: Journal Article
• Authors: Archer, Kellie J.; Bardhi, Elissa; Maluf, Daniel G.; McDaniels, Jennifer; Rousselle, Thomas; King, Anne; Eason, James D.; Gallon, Lorenzo; Akalin, Enver; Mueller, Thomas F.; Mas, Valeria R.
• Is Part Of: American journal of transplantation. Volume 22:Issue 11(2022)
• Page Start: 2515
• Page End: 2528
• Publication Date: 2022-07-04
• Subjects: biomarker -- clinical decision‐making -- donors and donation: deceased -- kidney transplantation/nephrology -- genomics -- glomerular filtration rate (GFR) -- translational research/science; Transplantation of organs, tissues, etc -- Periodicals; 617.95
• DOI: 10.1111/ajt.17127
• Languages: English
• ISSNs: 1600-6135

Abstract

Abstract : With the development of novel prognostic tools derived from omics technologies, transplant medicine is entering the era of precision medicine. Currently, there are no established predictive biomarkers for posttransplant kidney function. A total of 270 deceased donor pretransplant kidney biopsies were collected and posttransplant function was prospectively monitored. This study first assessed the utility of pretransplant gene expression profiles in predicting 24‐month outcomes in a training set ( n = 174). Nearly 600 differentially expressed genes were associated with 24‐month graft function. Grafts that progressed to low function at 24 months exhibited upregulated immune responses and downregulated metabolic processes at pretransplantation. Using penalized logistic regression modeling, a 55 gene model area under the receiver operating curve (AUROC) for 24‐month graft function was 0.994. Gene expression for a subset of candidate genes was then measured in an independent set of pretransplant biopsies ( n = 96) using quantitative polymerase chain reaction. The AUROC when using 13 genes with three donor characteristics (age, race, body mass index) was 0.821. Subsequently, a risk score was calculated using this combination for each patient in the validation cohort, demonstrating the translational feasibility of using gene markers as prognostic tools. These findings support the potential of pretransplant transcriptomic biomarkers as novel instruments for improving posttransplant outcome predictions and associated management. Abstract : This genome‐wide large‐cohort study shows that the donor kidney transcriptome prior to implantation captures intrinsic organ quality and carries significant predictive weight for 24‐month graft function. See Helanterä and Divard comment on page 2497 .