• 1.

    Adenwalla HS, Bhattacharya S. Dr. Joseph E. Murray. Indian J Plast Surg 2012; 45:596597. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3580381/

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    O’Brien RP, et al. A genome‐wide association study of recipient genotype and medium‐term kidney allograft function. Clin Transplant 2013; 27:379387. doi: 10.1111/ctr.12093

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Hernandez-Fuentes MP, et al. Long- and short-term outcomes in renal allografts with deceased donors: A large recipient and donor genome-wide association study. Am J Transplant 2018; 18:13701379. doi: 10.1111/ajt.14594

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Pihlstrøm H, et al. Single nucleotide polymorphisms and long‐term clinical outcome in renal transplant patients: A validation study. Am J Transplant 2017; 17:528533. doi: 10.1111/ajt.13995

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Oetting WS, et al. Genome-wide association study identifies the common variants in CYP3A4 and CYP-3A5 responsible for variation in tacrolimus trough concentration in Caucasian kidney transplant recipients. Pharmacogenomics J 2018; 18:501505. doi: 10.1038/tpj.2017.49

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Caudle KE, et al. Standardizing terms for clinical pharmacogenetic test results: Consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Genet Med 2017; 19:215223. doi: 10.1038/gim.2016.87

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Doshi MD, et al. APOL1 genotype and renal function of black living donors. J Am Soc Nephrol 2018; 29:13091316. doi: 10.1681/ASN.2017060658

  • 8.

    Steers NJ, et al. Genomic mismatch at LIMS1 locus and kidney allograft rejection. N Engl J Med 2019; 380:19181928. doi: 10.1056/NEJMoa1803731

  • 9.

    Reindl-Schwaighofer R, et al. Contribution of non-HLA incompatibility between donor and recipient to kidney allograft survival: Genome-wide analysis in a prospective cohort. Lancet 2019; 393:910917. doi: 10.1016/S0140-6736(18)32473-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    McCaughan JA, et al. Genetics of new-onset diabetes after transplantation. J Am Soc Nephrol 2014; 25:10371049. doi: 10.1681/ASN.2013040383

  • 11.

    Ghisdal L, et al. Genome-wide association study of acute renal graft rejection. Am J Transplant 2017; 17:201209. doi: 10.1111/ajt.13912

  • 12.

    Israni AK, et al. Genome-wide association meta-analysis for acute rejection of kidney transplants. Transplantation 2018; 102:S27S28. https://research.rug.nl/en/publications/genome-wide-association-meta-analysis-for-acute-rejection-of-kidn

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Stapleton CP, et al. The impact of donor and recipient common clinical and genetic variation on estimated glomerular filtration rate in a European renal transplant population. Am J Transplant 2019; 19:22622273. doi: 10.1111/ajt.15326

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Markkinen S, et al. Mismatches in gene deletions and kidney-related proteins are novel histocompatibility factors in kidney transplantation. medRxiv February 19, 2022. https://www.medrxiv.org/content/10.1101/2022.02.16.22270977v1

    • Search Google Scholar
    • Export Citation

Genomics in Kidney Transplantation

Elhussein A. E. ElhassanElhussein A. E. Elhassan, MBBS, and Peter J. Conlon, MB, Bch, BAO, are with the Department of Nephrology and Transplantation, Beaumont Hospital and Royal College of Surgeons, Dublin, Ireland. Kane Collins, PhD, and Edmund Gilbert, PhD, are with the School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons, Dublin, Ireland.

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Kane CollinsElhussein A. E. Elhassan, MBBS, and Peter J. Conlon, MB, Bch, BAO, are with the Department of Nephrology and Transplantation, Beaumont Hospital and Royal College of Surgeons, Dublin, Ireland. Kane Collins, PhD, and Edmund Gilbert, PhD, are with the School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons, Dublin, Ireland.

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Edmund GilbertElhussein A. E. Elhassan, MBBS, and Peter J. Conlon, MB, Bch, BAO, are with the Department of Nephrology and Transplantation, Beaumont Hospital and Royal College of Surgeons, Dublin, Ireland. Kane Collins, PhD, and Edmund Gilbert, PhD, are with the School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons, Dublin, Ireland.

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Peter J. ConlonElhussein A. E. Elhassan, MBBS, and Peter J. Conlon, MB, Bch, BAO, are with the Department of Nephrology and Transplantation, Beaumont Hospital and Royal College of Surgeons, Dublin, Ireland. Kane Collins, PhD, and Edmund Gilbert, PhD, are with the School of Pharmacy and Biomolecular Sciences, Royal College of Surgeons, Dublin, Ireland.

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The importance of genomic mismatch between donor and recipient in organ transplantation has been appreciated since Dr. Joseph E. Murray undertook the first successful kidney transplantation in 1954 (1). This seminal event confirmed the critical role that genetics plays in transplant outcome. Subsequent studies demonstrated the importance of genetically inherited human leukocyte antigen (HLA) mismatch between donor and recipient. To guide decision-making in living donors, genomics functions as an additional toolkit to determine susceptibility of a specific inherited disease aggregating among families or specific ancestries, such as apolipoprotein L1 (APOL1) nephropathy.

In the 1990s and early 2000s, several groups studied the impact of individual single nucleotide polymorphisms (SNPs) on graft outcome and kidney transplantation complications. Many studies were undertaken in which an investigator's specific SNP of interest was chosen and examined for transplant-related outcomes, such as acute rejection or graft function. However, these studies were substantially underpowered statistically, and their findings were rarely replicated.

In 2007, the genome-wide association study (GWAS) was introduced. With this approach, hundreds of thousands of SNPs were investigated for association with transplant-related outcomes. These studies brought several methodological improvements; they involved many patients to achieve statistical power, they adjusted for multiple comparisons, and they typically required a p value of 108 to be considered significant. Furthermore, and critically, these studies often replicated results in a separate independent sample.

Several GWASs were used to assess candidate genes or loci with transplant outcomes (Table 1). Our group undertook some of the earliest transplant GWASs, initially in a cohort based in Dublin, Ireland (2), and subsequently in a larger group of approximately 2500 kidney donor recipient pairs across the United Kingdom and Ireland (United Kingdom and Ireland Renal Transplant Consortium) (3). In the first large transplant GWAS, we confirmed the critical role that HLA plays in graft outcome but also failed to replicate any of the previously published SNPs in a data set that was approximately 10 times larger than previously published studies (4).

Table 1

Genome-wide association studies in kidney transplantation

Table 1

Subsequently, we undertook GWASs, incorporating a trans-national consortium, called the International Genetics & Translational Research in Transplantation Network (iGeneTRAiN), to identify genetic signals associated with kidney function at 5 years post-transplantation (3) and the development of skin cancer post-transplantation. We were able to identify a strong genetic predisposition to skin cancer between patients at the highest and lowest polygenic risk score. Other investigators have used the GWAS approach to identify genetic signals for the development of other complications post-transplantation, such as allograft rejection and diabetes.

Advancement in immunosuppressant medications is one of various factors that has contributed to the enormous improvement of long-term allograft survival to its current state. The genetic determinants influencing immunosuppressant metabolism have been apparent for many years, initially with involvement of the thiopurine methyltransferase enzyme on azathioprine metabolism and more recently, the cytochrome P450 genetic variation having a considerable impact on the pharmacokinetics of calcineurin inhibitors (5). As a result, although not widely adopted, guidelines have been proposed to integrate the knowledge of pharmacogenetic studies to improve immunosuppressant-dosing optimization (6).

Following the discovery of the HLA, knowledge about other genetic factors of donors and recipients, such as incompatibilities and APOL1 risk loci, has pushed the boundaries of precision medicine. Accumulating evidence indicates that mismatches and antibodies against non-HLA mediators can trigger transplant injury and rejection and elicit underlying etiology of graft failure, as one-third of all transplants that fail for immunological reasons cannot be explained by HLA mismatch. Some of this failure is proposed to be due to so-called minor histocompatibility antigens. Also, in live kidney donors, the APOL1 genotype informs the donor-assessment and stratification process, as reports suggest that donors with greater than typical risk (i.e., high-risk genotype) are associated with an increased rate of kidney failure after donation (7). It is critical that the role of regions outside of the HLA is further explored.

Kiryluk and co-workers (8) have recently proposed the idea of “genomic collision” in which kidney donor cells expressing proteins on their surface that were not present in the recipient demonstrate a robust adverse response on graft outcome and can have measurable donor-specific antibodies. A team in Austria has demonstrated the impact of a summation cell surface-expressed protein-coding variation between donors and recipients on long-term graft outcome (9).

The innovative abilities of genomic sequencing have undergone a revolution in the last 30 years and undoubtedly promise to reveal even more fascinating insights in the future.

References

  • 1.

    Adenwalla HS, Bhattacharya S. Dr. Joseph E. Murray. Indian J Plast Surg 2012; 45:596597. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3580381/

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    O’Brien RP, et al. A genome‐wide association study of recipient genotype and medium‐term kidney allograft function. Clin Transplant 2013; 27:379387. doi: 10.1111/ctr.12093

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Hernandez-Fuentes MP, et al. Long- and short-term outcomes in renal allografts with deceased donors: A large recipient and donor genome-wide association study. Am J Transplant 2018; 18:13701379. doi: 10.1111/ajt.14594

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 4.

    Pihlstrøm H, et al. Single nucleotide polymorphisms and long‐term clinical outcome in renal transplant patients: A validation study. Am J Transplant 2017; 17:528533. doi: 10.1111/ajt.13995

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Oetting WS, et al. Genome-wide association study identifies the common variants in CYP3A4 and CYP-3A5 responsible for variation in tacrolimus trough concentration in Caucasian kidney transplant recipients. Pharmacogenomics J 2018; 18:501505. doi: 10.1038/tpj.2017.49

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 6.

    Caudle KE, et al. Standardizing terms for clinical pharmacogenetic test results: Consensus terms from the Clinical Pharmacogenetics Implementation Consortium (CPIC). Genet Med 2017; 19:215223. doi: 10.1038/gim.2016.87

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 7.

    Doshi MD, et al. APOL1 genotype and renal function of black living donors. J Am Soc Nephrol 2018; 29:13091316. doi: 10.1681/ASN.2017060658

  • 8.

    Steers NJ, et al. Genomic mismatch at LIMS1 locus and kidney allograft rejection. N Engl J Med 2019; 380:19181928. doi: 10.1056/NEJMoa1803731

  • 9.

    Reindl-Schwaighofer R, et al. Contribution of non-HLA incompatibility between donor and recipient to kidney allograft survival: Genome-wide analysis in a prospective cohort. Lancet 2019; 393:910917. doi: 10.1016/S0140-6736(18)32473-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    McCaughan JA, et al. Genetics of new-onset diabetes after transplantation. J Am Soc Nephrol 2014; 25:10371049. doi: 10.1681/ASN.2013040383

  • 11.

    Ghisdal L, et al. Genome-wide association study of acute renal graft rejection. Am J Transplant 2017; 17:201209. doi: 10.1111/ajt.13912

  • 12.

    Israni AK, et al. Genome-wide association meta-analysis for acute rejection of kidney transplants. Transplantation 2018; 102:S27S28. https://research.rug.nl/en/publications/genome-wide-association-meta-analysis-for-acute-rejection-of-kidn

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Stapleton CP, et al. The impact of donor and recipient common clinical and genetic variation on estimated glomerular filtration rate in a European renal transplant population. Am J Transplant 2019; 19:22622273. doi: 10.1111/ajt.15326

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Markkinen S, et al. Mismatches in gene deletions and kidney-related proteins are novel histocompatibility factors in kidney transplantation. medRxiv February 19, 2022. https://www.medrxiv.org/content/10.1101/2022.02.16.22270977v1

    • Search Google Scholar
    • Export Citation
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