Letter to the Editor: Hepatic transcriptome and metabolome analysis of Jiangtang Tiaozhi formula

doi:10.4239/wjd.117759

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World Journal of Diabetes

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1948-9358

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Diabetes. Jun 15, 2026; 17(6): 117759
Published online Jun 15, 2026. doi: 10.4239/wjd.117759

Letter to the Editor: Hepatic transcriptome and metabolome analysis of Jiangtang Tiaozhi formula

Shu-Meng Huang, Di-Guang Wen

Shu-Meng Huang, Di-Guang Wen, Department of Endocrinology, Yuyao People's Hospital, Yuyao 315400, Zhejiang Province, China

Author contributions: Huang SM drafted the manuscript; Wen DG designed the study, supervised the project, and critically revised the manuscript; both authors read and approved the final version of the manuscript.

Conflict-of-interest statement: There is no conflict of interest associated with any of the senior author or other coauthors contributed their efforts in this manuscript.

Corresponding author: Di-Guang Wen, PhD, Academic Fellow, Professor, Department of Endocrinology, Yuyao People's Hospital, No. 800 Chengdong Road, Yuyao 315400, Zhejiang Province, China. 2018110626@stu.cqmu.edu.cn

Received: December 15, 2025
Revised: January 15, 2026
Accepted: January 26, 2026
Published online: June 15, 2026
Processing time: 178 Days and 16.6 Hours

Core Tip

Core Tip: This commentary discusses a recent hepatic transcriptomic and metabolomic study that elucidates the regulatory effects of Jiangtang Tiaozhi formula on glycolipid metabolism. We emphasize key strengths of the multi-omics strategy and highlight critical issues that warrant further investigation, including dose-response relationships, cellular resolution, mechanistic causality, active constituent identification, and long-term safety evaluation. By integrating systems biology and translational perspectives, this work underscores the potential of traditional Chinese medicine-based therapies to advance precision medicine approaches for metabolic disorders.