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Chu J, Wang K, Lu L, Zhao H, Hu J, Xiao W, Wu Q. Advances of Iron and Ferroptosis in Diabetic Kidney Disease. Kidney Int Rep 2024; 9:1972-1985. [PMID: 39081773 PMCID: PMC11284386 DOI: 10.1016/j.ekir.2024.04.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/29/2024] [Accepted: 04/01/2024] [Indexed: 08/02/2024] Open
Abstract
Diabetes mellitus presents a significant threat to human health because it disrupts energy metabolism and gives rise to various complications, including diabetic kidney disease (DKD). Metabolic adaptations occurring in the kidney in response to diabetes contribute to the pathogenesis of DKD. Iron metabolism and ferroptosis, a recently defined form of cell death resulting from iron-dependent excessive accumulation of lipid peroxides, have emerged as crucial players in the progression of DKD. In this comprehensive review, we highlight the profound impact of adaptive and maladaptive responses regulating iron metabolism on the progression of kidney damage in diabetes. We summarize the current understanding of iron homeostasis and ferroptosis in DKD. Finally, we propose that precise manipulation of iron metabolism and ferroptosis may serve as potential strategies for kidney management in diabetes.
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Affiliation(s)
- Jiayi Chu
- Department of Radiology, Center of Regenerative and Aging Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Zhejiang, China
| | - Kewu Wang
- Department of Radiology, Center of Regenerative and Aging Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Zhejiang, China
| | - Lulu Lu
- Department of Nutrition and Toxicology, Key Laboratory of Elemene Class Anti-Cancer Chinese Medicines of Zhejiang Province, School of Public Health, Hangzhou Normal University, Hangzhou, China
| | - Hui Zhao
- Department of Radiology, Center of Regenerative and Aging Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Zhejiang, China
| | - Jibo Hu
- Department of Radiology, Center of Regenerative and Aging Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Zhejiang, China
| | - Wenbo Xiao
- Department of Radiology, the First Affiliated Hospital, College of Medicine, Zhejiang University, Zhejiang, China
| | - Qian Wu
- Department of Radiology, Center of Regenerative and Aging Medicine, the Fourth Affiliated Hospital of School of Medicine, and International School of Medicine, International Institutes of Medicine, Zhejiang University, Zhejiang, China
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Xie H, Zhuang H, Guo Y, Sharma RD, Zhang Q, Li J, Lu S, Xu L, Chan Q, Yoneda T, Spincemaille P, Zhang H, Guo H, Prince MR, Yu C, Wang Y. The appearance of magnetic susceptibility objects in SWI phase depends on object size: Comparison with QSM and CT. Clin Imaging 2021; 82:67-72. [PMID: 34798560 DOI: 10.1016/j.clinimag.2021.11.005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 10/14/2021] [Accepted: 11/07/2021] [Indexed: 11/03/2022]
Abstract
PURPOSE Tissue magnetic susceptibility sign can potentially be detected on susceptibility weighted imaging (SWI) phase (SW-P). This study aims to investigate its performance for depicting brain susceptibility structures. METHODS A simulation was performed to depict magnetic susceptibility structures of various geometries on SW-P and quantitative susceptibility mapping (QSM). Brain MRI was performed on 25 subjects using SWI on a 3 T MRI system. QSM was generated from the same data. SW-P and QSM were analyzed according to radiological assessment for depicting globus pallidus nuclei, optic radiation white matter tracts, and lateral ventricular choroid plexus calcifications. In 11 of these subjects, CT was available and correlated with SW-P and QSM to assess their performance in quantifying calcifications in the choroid plexus. RESULTS In simulation, the appearance of a sphere on SW-P ranged from centric nodule to mixed positive and negative values as the diameter increased. Large cylinders also appeared as mixed positive and negative values. In comparison, QSM correctly depicted the susceptibility distribution of all magnetic structures. On human brain images, SW-P depicted the globus pallidus and optic radiation with mixed positive and negative values, consistent with simulation, and small choroid plexus calcifications as either mixed positive and negative values or as centric nodules; QSM depicted all structures as solid structures with the expected signs. For measuring calcification in the choroid plexus, QSM vs CT linear regression had a higher coefficient of determination compared to SW-P vs CT and SW-P vs QSM. CONCLUSION Appearance of susceptibility sources on SW-P changes with object size. This problem can be overcome using QSM.
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Affiliation(s)
- Hong Xie
- Department of Radiology, The First College of Clinical Medical Science, Three Gorges University, Yichang, Hubei Province, China
| | - Hangwei Zhuang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Yihao Guo
- Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Ria D Sharma
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA
| | - Qihao Zhang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Jiahao Li
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Shimin Lu
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Liang Xu
- Department of Radiology, The First College of Clinical Medical Science, Three Gorges University, Yichang, Hubei Province, China
| | | | - Tetsuya Yoneda
- Department of Medical Imaging Sciences, Kumamoto University, Kumamoto, Japan
| | - Pascal Spincemaille
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Honglei Zhang
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Hua Guo
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China
| | - Martin R Prince
- Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA
| | - Chengxin Yu
- Department of Radiology, The First College of Clinical Medical Science, Three Gorges University, Yichang, Hubei Province, China
| | - Yi Wang
- Department of Biomedical Engineering, Cornell University, Ithaca, NY, USA; Department of Radiology, Weill Medical College of Cornell University, New York, NY, USA.
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