Cosio, Fernando

Background. Recent studies identified underlying genetic causes in a proportion of patients with various forms of kidney disease. In particular, genetic testing reclassified some focal segmental glomerulosclerosis (FSGS) cases into collagen type 4 (COL4)-related nephropathy. This knowledge has major implications for counseling prospective transplant recipients about recurrence risk and screening biologically related donors. We describe our experience incorporating genetic testing in our kidney transplant multidisciplinary practice. Methods. Patients’ DNA was analyzed using whole exome sequencing for a comprehensive kidney gene panel encompassing 344 genes associated with kidney diseases and candidate genes highly expressed in the kidney. Results were correlated with phenotype by a multidisciplinary committee of nephrologists, renal pathologists, geneticists, and genetic counselors. Between October 2018 and July 2020, 30 recipient and 5 donor candidates completed testing. Results. Among recipient candidates, 24 (80%) carried the diagnosis of FSGS, 2 (6.7%) tubulointerstitial nephritis, and 1 (3.3%) nephrolithiasis, and 3 (10%) had an unknown cause of kidney disease. The yield for pathogenic/likely pathogenic variants was 43.3%, with majority being COL4 variants (53.8%). Among those with FSGS diagnosis, the yield was 10 of 24 (41.6%), with 29% reclassified into a COL4-related nephropathy. Family history of kidney disease was the only clinical characteristic difference between recipients with positive and negative results (76.9 versus 29.4%; P = 0.025). One of 5 donors tested positive for a pathogenic/likely pathogenic variant and was excluded from donation. Conclusions. We conclude that thoughtful use of genetic testing can be valuable for kidney donor selection and transplant recipient management.

Background. Delayed graft function (DGF) of a kidney transplant results in increased cost and complexity of management. For clinical care or a DGF trial, it would be ideal to accurately predict individual DGF risk and provide preemptive treatment. A calculator developed by Irish et al has been useful for predicting population but not individual risk. Methods. We analyzed the Irish calculator (IC) in the DeKAF prospective cohort (incidence of DGF = 20.4%) and investigated potential improvements. Results. We found that the predictive performance of the calculator in those meeting Irish inclusion criteria was comparable with that reported by Irish et al. For cohorts excluded by Irish: (a) in pump-perfused kidneys, the IC overestimated DGF risk; (b) in simultaneous pancreas kidney transplants, the DGF risk was exceptionally low. For all 3 cohorts, there was considerable overlap in IC scores between those with and those without DGF. Using a modified definition of DGF—excluding those with single dialysis in the first 24 h posttransplant—we found that the calculator had similar performance as with the traditional DGF definition. Studying whether DGF prediction could be improved, we found that recipient cardiovascular disease was strongly associated with DGF even after accounting for IC-predicted risk. Conclusions. The IC can be a useful population guide for predicting DGF in the population for which it was intended but has limited scope in expanded populations (SPK, pump) and for individual risk prediction. DGF risk prediction can be improved by inclusion of recipient cardiovascular disease.