Publikation
Genetic and clinic predictors of new onset diabetes mellitus after transplantation
Wissenschaftlicher Artikel/Review - 27.12.2017
Saigi-Morgui Núria, Eap Chin B, Pascual Manuel, Soccal Paola M, Dufour Jean-François, Mohacsi Paul, Steiger Jürg, Van Delden Christian, Binet Françoise-Isabelle, Mueller Nicolas J, Kutalik Zoltán, Crettol Severine, Bochud Pierre-Yves, Quteineh Lina, Swiss Transplant Cohort Study
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New Onset Diabetes after Transplantation (NODAT) is a frequent complication after solid organ transplantation, with higher incidence during the first year. Several clinical and genetic factors have been described as risk factors of Type 2 Diabetes (T2DM). Additionally, T2DM shares some genetic factors with NODAT. We investigated if three genetic risk scores (w-GRS) and clinical factors were associated with NODAT and how they predicted NODAT development 1 year after transplantation. In both main (n = 725) and replication (n = 156) samples the clinical risk score was significantly associated with NODAT (OR: 1.60 [1.36-1.90], p = 3.72*10and OR: 2.14 [1.39-3.41], p = 0.0008, respectively). Two w-GRS were significantly associated with NODAT in the main sample (OR:1.09 [1.04-1.15], p = 0.001 and OR:1.14 [1.01-1.29], p = 0.03) and a similar ORwas found in the replication sample, although it did not reach significance probably due to a power issue. Despite the low OR of w-GRS on NODAT compared to clinical covariates, when integrating w-GRS 2 and w-GRS 3 in the clinical model, the Area under the Receiver Operating Characteristics curve (AUROC), specificity, sensitivity and accuracy were 0.69, 0.71, 0.58 and 0.68, respectively, with significant Likelihood Ratio test discrimination index (p-value 0.0004), performing better in NODAT discrimination than the clinical model alone. Twenty-five patients needed to be genotyped in order to detect one misclassified case that would have developed NODAT 1 year after transplantation if using only clinical covariates. To our knowledge, this is the first study extensively examining genetic risk scores contributing to NODAT development.