Lin JY, Fu JJ, Wen DG. Letter to the Editor: Hepatic multi-omics insights into Jiangtang tiaozhi formula for glycolipid metabolic disorders. World J Diabetes 2026; 17(8): 118206 [DOI: 10.4239/wjd.118206]
Corresponding Author of This Article
Di-Guang Wen, School of Medical Imaging, Hangzhou Medical College, No. 8 Yikang Street, Lin’an District, Hangzhou 310059, Zhejiang Province, China. 2018110626@stu.cqmu.edu.cn
Research Domain of This Article
Cell Biology
Article-Type of This Article
letter
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Share the Article
Lin JY, Fu JJ, Wen DG. Letter to the Editor: Hepatic multi-omics insights into Jiangtang tiaozhi formula for glycolipid metabolic disorders. World J Diabetes 2026; 17(8): 118206 [DOI: 10.4239/wjd.118206]
World J Diabetes. Aug 15, 2026; 17(8): 118206 Published online Aug 15, 2026. doi: 10.4239/wjd.118206
Letter to the Editor: Hepatic multi-omics insights into Jiangtang tiaozhi formula for glycolipid metabolic disorders
Jia-Yu Lin, Jia-Jie Fu, Di-Guang Wen
Jia-Yu Lin, Di-Guang Wen, School of Medical Imaging, Hangzhou Medical College, Hangzhou 310059, Zhejiang Province, China
Jia-Jie Fu, Department of Radiology, Longhua Hospital Shanghai University of Traditional Chinese Medicine, Shanghai 200032, China
Author contributions: Lin JY and Fu JJ drafted the manuscript; Wen DG designed the study, supervised the project, and critically revised the manuscript; all authors read and approved the final version of the manuscript.
Conflict-of-interest statement: The authors declare that they have no competing interests.
Corresponding author: Di-Guang Wen, School of Medical Imaging, Hangzhou Medical College, No. 8 Yikang Street, Lin’an District, Hangzhou 310059, Zhejiang Province, China. 2018110626@stu.cqmu.edu.cn
Received: December 28, 2025 Revised: January 12, 2026 Accepted: January 21, 2026 Published online: August 15, 2026 Processing time: 221 Days and 8.5 Hours
Abstract
Diabetic kidney disease (DKD) remains a major cause of chronic kidney failure despite advances in standard-of-care therapies. Emerging real-world evidence suggests that combination therapy with sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists may provide additive renal and metabolic benefits beyond single-agent approaches. However, DKD is a biologically heterogeneous condition, and treatment responses may vary substantially across disease stages and patient subphenotypes. In this commentary, we discuss the implications of recent clinical findings from a precision-oriented perspective, highlighting the importance of patient stratification, stage-specific evaluation, and mechanism-informed decision-making. We further emphasize the need to move beyond uniform treatment paradigms toward a layered, decision-driven therapeutic framework that integrates clinical phenotypes with emerging biological insights to optimize outcomes in DKD. The study by Miao et al published in the recent issue of the World Journal of Diabetes, aimed to clarify addressing the multifactorial pathophysiology of DKD.
Core Tip: Diabetic kidney disease (DKD) is a biologically heterogeneous condition, and uniform treatment strategies may not yield equivalent benefits across patients. Recent real-world evidence supports the use of combined sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists as part of a layered therapeutic approach. This commentary highlights the importance of precision patient selection, stage-specific evaluation, and mechanism-informed decision-making to optimize combination therapy. Integrating clinical phenotypes with emerging biological insights may facilitate more individualized and effective management of DKD.