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Joint testing of donor and recipient genetic matching scores and recipient genotype has robust power for finding genes associated with transplant outcomes.

ABSTRACT: Genetic matching between transplant donor and recipient pairs has traditionally focused on the human leukocyte antigen (HLA) regions of the genome, but recent studies suggest that matching for non-HLA regions may be important as well. We assess four genetic matching scores for use in association analyses of transplant outcomes. These scores describe genetic ancestry distance using identity-by-state, or genetic incompatibility or mismatch of the two genomes and therefore may reflect different underlying biological mechanisms for donor and recipient genes to influence transplant outcomes. Our simulation studies show that jointly testing these scores with the recipient genotype is a powerful method for preliminary screening and discovery of transplant outcome related single nucleotide polymorphisms (SNPs) and gene regions. Following these joint tests with marginal testing of the recipient genotype and matching score separately can lead to further understanding of the biological mechanisms behind transplant outcomes. In addition, we present results of a liver transplant data analysis that shows joint testing can detect SNPs significantly associated with acute rejection in liver transplant.

SUBMITTER: Arthur VL

PROVIDER: S-EPMC7658035 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Joint testing of donor and recipient genetic matching scores and recipient genotype has robust power for finding genes associated with transplant outcomes.

Arthur Victoria L VL Guan Weihua W Loza Bao-Li BL Keating Brendan B Chen Jinbo J

Genetic epidemiology 20200811 8

Genetic matching between transplant donor and recipient pairs has traditionally focused on the human leukocyte antigen (HLA) regions of the genome, but recent studies suggest that matching for non-HLA regions may be important as well. We assess four genetic matching scores for use in association analyses of transplant outcomes. These scores describe genetic ancestry distance using identity-by-state, or genetic incompatibility or mismatch of the two genomes and therefore may reflect different und ...[more]

PMID: 32783273

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Project description:BackgroundNephron endowment in renal transplantation is infrequently considered, but may have important implications for post kidney transplantation outcomes. In this population-cohort study, we analyzed the deceased-donor kidney transplant outcomes stratified by donor-to-recipient size ratios.MethodsData for all deceased-donor adult kidney transplantation recipients between 2003 and 2015 were extracted from the UK Transplant Registry. We used weight as a surrogate marker for kidney size and defined the following mismatch categories (donor weight/recipient weight × 100): less than 75% (small donor kidney), 75% to 125% (weight matched kidney), and greater than 125% (large donor kidney). Univariable and multivariable analyses were undertaken to assess the relationship between this marker and patient outcomes.ResultsOutcomes for 11 720 transplants were analyzed with weight mismatch stratified as follows; small donor kidney (n = 1608, 13.7%), weight matched kidney (n = 7247, 61.8%) and large donor kidney (n = 2865, 24.4%). On multivariable analysis, no significant differences were detected in overall (P = 0.876) or death-censored (P = 0.173) graft survival, or in rates of delayed graft function (P = 0.396) between these 3 groups. However, 12-month creatinine levels were found to decline progressively across the groups (P < 0.001), with adjusted averages of 144.2 μmol/L for recipients of small donor kidneys, 134.7 μmol/L in weight matched kidneys, and 124.9 μmol/L in recipients of large donor kidneys. In addition, patient survival was found to be significantly shorter in recipients of larger kidneys than those with weight matched kidneys (hazard ratio, 1.21; 95% confidence interval, 1.05-1.40; P = 0.009), which is inconsistent with the existing literature.ConclusionsOur data demonstrate that 12-month creatinine is influenced by donor-to-recipient difference in body weight, but that no such difference is observed for either delayed graft function or death-censored graft survival. However, we observed increased mortality in recipients receiving larger kidneys; an observation which conflicts with the existing literature and warrants further investigation.

Project description:ObjectiveOne of the main problems of lung transplantation is the shortage of organs as well as reduced survival rates. In the absence of an international standardized model for lung donor-recipient allocation, we set out to develop such a model based on the characteristics of past experiences with lung donors and recipients with the aim of improving the outcomes of the entire transplantation process.MethodsThis was a retrospective analysis of 404 lung transplants carried out at the Reina Sofía University Hospital (Córdoba, Spain) over 23 years. We analyzed various clinical variables obtained via our experience of clinical practice in the donation and transplantation process. These were used to create various classification models, including classical statistical methods and also incorporating newer machine-learning approaches.ResultsThe proposed model represents a powerful tool for donor-recipient matching, which in this current work, exceeded the capacity of classical statistical methods. The variables that predicted an increase in the probability of survival were: higher pre-transplant and post-transplant functional vital capacity (FVC), lower pre-transplant carbon dioxide (PCO2) pressure, lower donor mechanical ventilation, and shorter ischemia time. The variables that negatively influenced transplant survival were low forced expiratory volume in the first second (FEV1) pre-transplant, lower arterial oxygen pressure (PaO2)/fraction of inspired oxygen (FiO2) ratio, bilobar transplant, elderly recipient and donor, donor-recipient graft disproportion requiring a surgical reduction (Tailor), type of combined transplant, need for cardiopulmonary bypass during the surgery, death of the donor due to head trauma, hospitalization status before surgery, and female and male recipient donor sex.ConclusionsThese results show the difficulty of the problem which required the introduction of other variables into the analysis. The combination of classical statistical methods and machine learning can support decision-making about the compatibility between donors and recipients. This helps to facilitate reliable prediction and to optimize the grafts for transplantation, thereby improving the transplanted patient survival rate.

Dataset Information

Joint testing of donor and recipient genetic matching scores and recipient genotype has robust power for finding genes associated with transplant outcomes.

Publications

Joint testing of donor and recipient genetic matching scores and recipient genotype has robust power for finding genes associated with transplant outcomes.

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