Health Technology/clinical-trials

Italian Study Launches Deep Phenotyping Approach to Predict Post-Transplant Diabetes Complications — Genomic Insights for Transplant Teams

247 Health News Editorial

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8 Apr 2026

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4 min read

·clinical-trials

Italian researchers launch genomic study to predict diabetic complications in kidney transplant recipients. The study uses whole genome sequencing and deep phenotyping to identify high-risk patients with new-onset diabetes after transplantation.

Originally reported by ClinicalTrials.gov

References

  1. 1.Fondazione Policlinico Universitario Agostino Gemelli IRCCS. (2024). Post-Transplant Diabetes Outcomes Prediction Through Machine Learning and Deep Phenotyping. ClinicalTrials.gov. NCT07512804. https://clinicaltrials.gov/study/NCT07512804
  2. 2.Shivaswamy, V., Boerner, B., & Larsen, J. (2016). Post-transplant diabetes mellitus: causes, treatment, and impact on outcomes. Endocrine Reviews, 37(3), 249-295. https://doi.org/10.1210/er.2015-1084
  3. 3.Cosio, F. G., Pesavento, T. E., Kim, S., Osei, K., Henry, M., & Ferguson, R. M. (2002). Patient survival after renal transplantation: IV. Impact of post-transplant diabetes. Kidney International, 62(4), 1440-1446. https://doi.org/10.1046/j.1523-1755.2002.00334.x
  4. 4.Pham, P. T., Pham, P. M., Pham, S. V., Pham, P. A., & Pham, P. C. (2011). New onset diabetes after transplantation (NODAT): an overview. Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy, 4, 175-186. https://doi.org/10.2147/DMSO.S19027
  5. 5.Rodrigo, E., Fernández-Fresnedo, G., Valero, R., Ruiz, J. C., Piñera, C., Palomar, R., González-Cotorruelo, J., Gómez-Alamillo, C., & Arias, M. (2006). New-onset diabetes after kidney transplantation: risk factors. Journal of the American Society of Nephrology, 17(12), 3441-3447. https://doi.org/10.1681/ASN.2006040386
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