Exome sequencing and prediction of long-term kidney allograft function
- Published
- Accepted
- Subject Areas
- Genomics, Immunology, Nephrology
- Keywords
- kidney transplantation, Genomics, Human Leukocyte Antigen, organ transplantation, long-term graft function, Immunology
- Copyright
- © 2015 Mesnard et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2015. Exome sequencing and prediction of long-term kidney allograft function. PeerJ PrePrints 3:e854v2 https://doi.org/10.7287/peerj.preprints.854v2
Abstract
Current strategies to improve graft outcome following kidney transplantation consider information at the HLA loci. Here, we used exome sequencing of DNA from ABO compatible kidney graft recipients and their living donors to determine recipient and donor mismatches at the amino acid level over entire exomes. We estimated the number of amino acid mismatches in transmembrane proteins, more likely to be seen as foreign by the recipient’s immune system, and designated this tally as the allogenomics mismatch score (AMS). The AMS can be measured prior to transplantation with DNA for potential donor and recipient pairs. We examined the degree of relationship between the AMS and post-transplantation kidney allograft function by linear regression. In a discovery cohort, we found a significant inverse correlation between the AMS and kidney graft function at 36 months post-transplantation (n=10 recipient/donor pairs; 20 exomes) (r2>=0.57, P<0.05). The predictive ability of the AMS persists when the score is restricted to regions outside of the HLA loci. This relationship was validated using an independent cohort of 24 recipient donor pairs (n=48 exomes) (r2>=0.39, P<0.005). In an additional cohort of living and mostly intra-familial recipient/donor pairs (n=19, 38 exomes), we validated the association after controlling for donor age at time of transplantation. Finally, a model that controls for donor age, HLA mismatches and time post-transplantation yields a consistent AMS effect across these three independent cohorts (P<0.05). Taken together, these results show that the AMS is a strong predictor of long-term graft function in kidney transplant recipients.
Author Comment
This new version presents results obtained on a third independent cohort (adding 19 pairs for a total of 53, or 106 exomes). A new approach to analysis is also described which considers time post-transplantation as a covariate in a mixed linear model.