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Usage Information

RTN1A mediates diabetes-induced AKI-to-CKD transition
Lulin Min, Ya Chen, Yixin Chen, Fang Zhong, Zhaohui Ni, Leyi Gu, Kyung Lee, John Cijiang He
Lulin Min, Ya Chen, Yixin Chen, Fang Zhong, Zhaohui Ni, Leyi Gu, Kyung Lee, John Cijiang He
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Research Article Nephrology

RTN1A mediates diabetes-induced AKI-to-CKD transition

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Abstract

Diabetic patients have increased susceptibility to acute kidney injury (AKI), and AKI could progress to chronic tubulointerstitial injury and fibrosis, referred to as AKI-to–chronic kidney disease (AKI-to-CKD) transition. However, whether diabetes directly promotes AKI-to-CKD transition is not known. We previously showed that reticulon-1A (RTN1A), a gene highly upregulated in injured renal tubular epithelial cells (RTECs), promotes AKI-to-CKD transition in nondiabetic settings. Therefore, we also examined whether reducing RTN1A expression could attenuate diabetes-induced AKI-to-CKD transition. Diabetes was induced by a high-fat diet and streptozotocin injections, and unilateral ischemic reperfusion injury was created as an AKI model in control, diabetic, and RTEC-specific Rtn1a-knockdown diabetic mice. AKI induced greater renal function decline, tubulointerstitial injury, and fibrosis in diabetic mice than in nondiabetic mice. Reduction of RTN1A markedly reduced the CKD development following AKI in diabetic mice, which was associated with reduced ER stress and mitochondrial dysfunction in RTECs. These findings indicate that diabetes markedly accelerates AKI-to-CKD transition and that RTN1A is a crucial mediator of diabetes-induced AKI-to-CKD transition. The development of RTN1A inhibitors could potentially attenuate AKI-to-CKD transition in diabetic patients.

Authors

Lulin Min, Ya Chen, Yixin Chen, Fang Zhong, Zhaohui Ni, Leyi Gu, Kyung Lee, John Cijiang He

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Usage data is cumulative from June 2025 through June 2026.

Usage JCI PMC
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PDF 284 109
Figure 829 4
Supplemental data 335 30
Citation downloads 208 0
Totals 3,776 657
Total Views 4,433

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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