Exome Sequencing and Prediction of Long-Term Kidney Allograft Function

Abstract

Current strategies to improve graft outcome following kidney transplantation consider information at the human leukocyte antigen (HLA) loci. Cell surface antigens, in addition to HLA, may serve as the stimuli as well as the targets for the anti-allograft immune response and influence long-term graft outcomes. We therefore performed exome sequencing of DNA from kidney graft recipients and their living donors and estimated all possible cell surface antigens mismatches for a given donor/recipient pair by computing the number of amino acid mismatches in trans-membrane proteins. We designated this tally as the allogenomics mismatch score (AMS). We examined the association between the AMS and post-transplant estimated glomerular filtration rate (eGFR) using mixed models, considering transplants from three independent cohorts (a total of 53 donor-recipient pairs, 106 exomes, and 239 eGFR measurements). We found that the AMS has a significant effect on eGFR (mixed model, effect size across the entire range of the score: -19.4 [-37.7, -1.1], P = 0.0042, χ2 = 8.1919, d.f. = 1) that is independent of the HLA-A, B, DR matching, donor age, and time post-transplantation. The AMS effect is consistent across the three independent cohorts studied and similar to the strong effect size of donor age. Taken together, these results show that the AMS, a novel tool to quantify amino acid mismatches in trans-membrane proteins in individual donor/recipient pair, is a strong, robust predictor of long-term graft function in kidney transplant recipients.PLOS Computational Biology |

Reply to Hernandez et al. - GWAS of acute renal graft rejection

“…In the absence of significant results in their discovery cohort, Finally, the absence of donor-recipient SNP genotype interaction influencing acute rejection in this study echoes with a recent observation by Mesnard et al 3 By the calculation of a genetic score based on the sum of non-HLA donor-recipient mismatches among transmembrane proteins, these authors noticed that many genetic variants composing the score were actually rare alleles, which are not captured in SNP-array-based GWAS. Together, the works of Hernandez and Mesnard call for sequencing-based studies that can detect both common and rare variants for deciphering non-HLA donor-recipient interactions.…”

Sensitization in transplantation: Assessment of risk (STAR) 2019 Working Group Meeting Report

“…Despite a large body of published data, there is a lack of concordance across genetically varied transplant populations and with differences in disease phenotype definition such as serum creatinine or specific pathological diagnoses whose criteria change periodically 111,112 . Similarly, the effect of individual gene variants is generally relatively small, and it is likely that few are obligatory for the outcome to occur 113 .…”

Adaptive Somatic Mutations Calls with Deep Learning and Semi-Simulated Data

“…Exome and Trio reads were aligned to the 1000 Genome Project human reference sequence as previously described Mesnard et al [2016].…”