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Long Non-coding RNA Expression Profiling in Biopsy to Identify Renal Allograft at Risk of Chronic Damage and Future Graft Loss.

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机构: [1]Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha 410008, People’s Republic of China [2]Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, 110 Xiangya Road, Changsha 410078, People’s Republic of China [3]Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, 110 Xiangya Road, Changsha 410078, People’s Republic of China [4]National Clinical Research Center for Geriatric Disorders, 87 Xiangya Road, Changsha 410008 Hunan, People’s Republic of China [5]Collaborative Innovation Center of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China [6]Department of Orthopaedics, The Third Xiangya Hospital, Central South University, 138 Tongzipo Road, Changsha, Hunan, People’s Republic of China
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关键词: Chronic allograft damage Graft loss Kidney transplantation GEO datasets Long non-coding RNAs Biomarkers

摘要:
The loss of allograft from chronic damage is still the major risk that renal transplant recipients face today. Biomarkers for early detection of chronic damage are needed to improve the long-term graft survival. This study aimed to identify long non-coding RNA (lncRNA) biomarkers associated with chronic damage and graft loss after renal transplantation. Gene Expression Omnibus (GEO) datasets including GSE57387 (n = 101), GSE21374 (n = 282), and GSE25902 (n = 24) from three high-quality studies were analyzed. By repurposing the publicly available array-based data coupled with Affymetrix Human Exon 1.0 ST and Human U133 Plus 2.0 arrays, we obtained expression profiles of 11323 and 3383 lncRNAs in biopsies after renal transplantation, respectively. The logistic regression model and Cox regression model were applied to identify lncRNAs associated with chronic damage and graft survival. High AC093673.5 expression was identified as significantly associated with the three endpoints including chronic damage, progressive chronic histological damage, and graft failure across these three datasets. A six-lncRNA signature was created to predict renal allograft at risk of chronic damage with a high predictive ability (AUC = 0.94). Gene set enrichment analysis (GSEA) indicated that our lncRNA signature was related with allograft rejection and immunity. Our study highlights the importance of lncRNAs in chronic graft damage and allograft loss, supporting their potential role as prognosis biomarkers.

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出版当年[2020]版:
大类 | 4 区 工程技术
小类 | 4 区 生化与分子生物学 4 区 生物工程与应用微生物
最新[2023]版:
大类 | 4 区 生物学
小类 | 4 区 生化与分子生物学 4 区 生物工程与应用微生物
第一作者:
第一作者机构: [1]Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha 410008, People’s Republic of China [2]Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, 110 Xiangya Road, Changsha 410078, People’s Republic of China [3]Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, 110 Xiangya Road, Changsha 410078, People’s Republic of China [4]National Clinical Research Center for Geriatric Disorders, 87 Xiangya Road, Changsha 410008 Hunan, People’s Republic of China
通讯作者:
通讯机构: [1]Department of Clinical Pharmacology, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha 410008, People’s Republic of China [2]Institute of Clinical Pharmacology, Hunan Key Laboratory of Pharmacogenetics, Central South University, 110 Xiangya Road, Changsha 410078, People’s Republic of China [3]Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, 110 Xiangya Road, Changsha 410078, People’s Republic of China [4]National Clinical Research Center for Geriatric Disorders, 87 Xiangya Road, Changsha 410008 Hunan, People’s Republic of China
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