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논문 기본 정보

자료유형
학술저널
저자정보
Sun Woo Lim (Convergent Research Consortium for Immunologic Disease, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea) Shin Yoo Jin (Convergent Research Consortium for Immunologic Disease, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea) Cui Sheng (가톨릭대학교) Ko Eun Jeong (Division of Nephrology, Department of Internal Medicine, Seoul St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, Seoul, KoreaTransplant Research Center, Convergent) 정병하 (가톨릭대학교) 양철우 (가톨릭대학교)
저널정보
대한신장학회 Kidney Research and Clinical Practice Kidney Research and Clinical Practice Vol.43 No.2
발행연도
2024.3
수록면
236 - 249 (14page)
DOI
10.23876/j.krcp.22.251

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Background: Multiple risk factors are involved in new-onset diabetes mellitus (DM) after organ transplantation; however, their ability to predict clinical prognosis remains unclear. Therefore, we investigated whether patient-specific induced pluripotent stem cells (iPSCs) could help predict DM development before performing kidney transplantation (KT). Methods: We first performed whole transcriptome and functional enrichment analyses of KT patient-derived iPSCs. Our results revealed that insulin resistance, type 2 DM, and transforming growth factor beta signaling pathways are associated between the groups of DM and non-DM. We next determined whether the genetic background was associated with development of iPSCs into pancreatic progenitor (PP) cells. Results: The levels of differentiation-related key markers of PP cells were significantly lower in the DM group than in the non-DM group. Moreover, the results of tacrolimus toxicity screening showed a significant decrease in the number of PP cells of the DM group compared with the non-DM group, suggesting that these cells are more susceptible to tacrolimus toxicity. Conclusion: Taken together, these results indicate that PP cells of the DM group showed low developmental potency accompanied by a significantly different genetic background compared with the non-DM group. Thus, genetic analysis can be used to predict the risk of DM before KT.

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