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©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Sep 15, 2025; 16(9): 107663
Published online Sep 15, 2025. doi: 10.4239/wjd.v16.i9.107663
Published online Sep 15, 2025. doi: 10.4239/wjd.v16.i9.107663
Spatial transcriptomics meets diabetic kidney disease: Illuminating the path to precision medicine
Dan-Dan Liu, Han-Yue Hu, Fei-Fei Li, Qiu-Yue Hu, You-Jin Hao, Bo Li, College of Life Sciences, Chongqing Normal University, Chongqing 401331, China
Ming-Wei Liu, College of Laboratory Medicine, Chongqing Medical University, Chongqing 400016, China
Author contributions: Liu DD drafted the original manuscript; Liu DD and Liu MW handled resources and visualization; Liu DD, Hao YJ, and Li B were responsible for conceptualization and data curation; Hu HY, Li FF, and Hu QY provided the critical review and editorial input; Hao YJ and Li B supervised this project and secured funding; all authors reviewed and approved the final version of this manuscript.
Supported by Science and Technology Research Program of Chongqing Municipal Education Commission, No. KJQN202100538; and Talent Innovation Project in Life Sciences of Chongqing Normal University, No. CSSK2023-04.
Conflict-of-interest statement: All the Authors have no conflict of interest related to this manuscript.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Bo Li, PhD, Associate Professor, College of Life Sciences, Chongqing Normal University, No. 37 University City Middle Road, Shapingba District, Chongqing 401331, China. libcell@cqnu.edu.cn
Received: March 28, 2025
Revised: May 23, 2025
Accepted: August 15, 2025
Published online: September 15, 2025
Processing time: 167 Days and 9.5 Hours
Revised: May 23, 2025
Accepted: August 15, 2025
Published online: September 15, 2025
Processing time: 167 Days and 9.5 Hours
Core Tip
Core Tip: This mini-review highlights the emerging role of spatial transcriptomics (ST) in diabetic kidney disease (DKD) research. ST enables high-resolution mapping of gene expression within intact tissues, offering novel insights into cellular interactions, lesion-specific transcriptional changes, and immune infiltration. The mini-review further discusses the integration of ST with computational tools such as machine learning and network analysis, and its potential in precision diagnostics and therapy. Despite challenges in spatial resolution and data complexity, ST is poised to transform DKD research by bridging molecular discovery with clinical application.