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Donor and recipient polygenic risk scores influence the risk of post-transplant diabetes

Abstract

Post-transplant diabetes mellitus (PTDM) reduces allograft and recipient life span. Polygenic risk scores (PRSs) show robust association with greater risk of developing type 2 diabetes (T2D). We examined the association of PTDM with T2D PRS in liver recipients (n = 1,581) and their donors (n = 1,555), and kidney recipients (n = 2,062) and their donors (n = 533). Recipient T2D PRS was associated with pre-transplant T2D and the development of PTDM. T2D PRS in liver donors, but not in kidney donors, was an independent risk factor for PTDM development. The inclusion of a combined liver donor and recipient T2D PRS significantly improved PTDM prediction compared with a model that included only clinical characteristics: the area under the curve (AUC) was 67.6% (95% confidence interval (CI) 64.1–71.1%) for the combined T2D PRS versus 62.3% (95% CI 58.8–65.8%) for the clinical characteristics model (P = 0.0001). Liver recipients in the highest quintile of combined donor and recipient T2D PRS had the greatest risk of PTDM, with an odds ratio of 3.22 (95% CI 2.07–5.00) (P = 1.92 × 10−7) compared with those in the lowest quintile. In conclusion, T2D PRS identifies transplant candidates with high risk of PTDM for which pre-emptive diabetes management and donor selection may be warranted.

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Fig. 1: Association of PTDM risk with combined donor and recipient T2D PRS.

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Data availability

Upon request, the authors can provide the deidentified genetic and clinical datasets that were used for the T2D PRS analysis. GWAS summary statistics are available in the GWAS Catalog (https://www.ebi.ac.uk/gwas) under GCST90091503 and GCST90091504. Organ donor-specific GWG datasets were generated using Human Subjects Exemption, and data use agreements would not allow the transfer of donor-level genetic datasets. The authors will collaborate with interested investigators and run scripts against relevant donor-level and recipient-level data. The collaborative projects will be initiated within 1 month of request being made by e-mail to baoli@pennmedicine.upenn.edu. Source data are provided with this paper.

Code availability

Publicly available analysis tools were employed as described in the Methods, and no custom code was used for the analysis of data.

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Acknowledgements

Funding for this study was received from the Fred and Suzanne Biesecker Pediatric Liver Center at Children’s Hospital of Philadelphia (A.S.), Gift-of-Life Organ Procurement Organization (A.S.), and National Institutes of Health (NIH) National Institute of Allergy and Infectious Diseases (NIAID) grant no. U01AI152960-01 (A.S. and B.J.K.).

Author information

Authors and Affiliations

Authors

Contributions

A.S., B.-L.L. and B.J.K. contributed to the design, analysis and writing of this study. A.Z., C.E.F., H.G., A.K.I., P.A.J., W.S.O., M.N., E.V.L. and S.K.A. contributed to data collection and literature review. A.S., B.-L.L., B.J.K., K.M.O., G.T., G.K., S.K.A., A.K.I., P.A.J., W.S.O., J.T., M.N. and E.V.L. contributed samples and phenotypes. A.S., B.-L.L., W.G., B.J.K., M.N. and E.V.L. contributed to, advised on and supervised statistical analysis. A.S., B.-L.L., K.M.O., S.K.A. and B.J.K. composed and revised the manuscript drafts. All co-authors read and approved the final manuscript for submission.

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Correspondence to Abraham Shaked.

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Nature Medicine thanks Trond Jenssen, Adnan Sharif and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Anna Maria Ranzoni, in collaboration with the Nature Medicine team.

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Extended data

Extended Data Fig. 1 ROC curve for the model to predict T2D for the Penn and Baylor combined liver transplant cohorts.

The probability of the PRS model to predict the development of T2D in the post-transplant population is similar to what was shown for T2D genetic predictors in the general population. AUROC curve for the multivariate logistic regression model to predict PTDM in recipients for the Penn and Baylor combined liver transplant cohorts (cases n=321, controls n=835) was depicted. The test statistics for each terms included in the multivariate logistic regression model were listed in Table 3. This multivariate model had AUC of 67.6% (95%CI: 64.1%–71.1%) at a threshold of 0.514. The negative and positive predictive values were 81.3 and 42.5 respectively, assuming 28% prevalence.

Source data

Extended Data Table 1 T2D-PRS association with pre-transplant DM for individual cohorts (multivariate analysis)
Extended Data Table 2 Under the scenario of treating liver transplant recipients in higher risk categories Q4/Q5

Supplementary information

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

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Shaked, A., Loza, BL., Van Loon, E. et al. Donor and recipient polygenic risk scores influence the risk of post-transplant diabetes. Nat Med 28, 999–1005 (2022). https://doi.org/10.1038/s41591-022-01758-7

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