Abstract: TH-PO940
Diabetes Weighted Genetic Risk Scores and Prediction of New Onset Diabetes after Kidney Transplantation
Session Information
- Transplantation: AKI, Cardiovascular, and Metabolic Complications
November 02, 2017 | Location: Hall H, Morial Convention Center
Abstract Time: 10:00 AM - 10:00 AM
Category: Transplantation
- 1702 Transplantation: Clinical and Translational
Authors
- Birdwell, Kelly A., Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Sanders, M. Lee, University of Iowa Hospitals and Clinics, Iowa City, Iowa, United States
- Velez edwards, Digna R, Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Ikizler, Talat Alp, Vanderbilt University Medical Center, Nashville, Tennessee, United States
- Giri, Ayush, Vanderbilt University Medical Center, Nashville, Tennessee, United States
Background
New onset diabetes after transplantation (NODAT) is associated with increased cardiovascular events and mortality, but the underlying pathogenesis is not well understood. We examined the genetics of NODAT in kidney transplant recipients using genetic risk scores constructed from previously identified single nucleotide polymorphisms (SNPs) for type 1 and type 2 diabetes in the general population to observe if NODAT overlaps with these disorders genetically.
Methods
Our study cohort included 54 cases and 248 controls, all European American, identified through our prior genome-wide association study completed using Illumina OMNI1 or OMNI5 platforms. Genetic risk scores (GRS) for type 1 and type 2 diabetes were created using SNPs published in the literature. GRS are used as a tool to summarize risk-associated SNPs across the genome to improve prediction of polygenic diseases. For type 1 diabetes, 3 GRS were created: 1) Full, with 25 type 1 SNPs and 3 HLA SNPs 2) Non-HLA, with 25 type 1 SNPs 3) HLA-only, with 3 HLA SNPs. For type 2 diabetes, 65 SNPs were used. All SNPs were from independent loci. Both non-weighted and weighted GRS were created. Logistic regression models were run using NODAT as the dependent variable and GRS as independent variables, with and without adjustment for covariates (sex, BMI, steroid use, and CMV infection).
Results
The cohort mean age was 42.4 years and 59.9% female. Weighted type 1 GRS, both Full and HLA-only, were significantly associated with NODAT in unadjusted and adjusted analyses. The odds of having NODAT was 1.25 times higher (OR 1.25, 95% CI 1.03-1.53, p = 0.03) in the weighted adjusted Full model, and similarly was 1.25 times higher (OR 1.25, 95% CI 1.01-1.534 p = 0.04) in the weighted adjusted HLA-only model, for each unit increase in weighted GRS score. Noteworthy associations were not observed using the type 1 Non-HLA GRS or the type 2 GRS.
Conclusion
Kidney transplant recipients with NODAT have genetic variants that are associated with those SNPs that predict type 1 diabetes but not type 2. This suggests the underlying pathogenesis might reflect more of a type 1 mechanism.
Funding
- Other NIH Support